Kshivets O. Cancer, Synergetics, Computer Sciences and Alive Supersystems
•Download as PPT, PDF•
289 likes•968 views
1. The document studied phase transitions in the system of malignancy and the human organism, discovering three phases: normal to pre-cancer, pre-cancer to early malignancy, and early malignancy to invasive cancer. 2. It found the most important factor was the cancer cell population in the organism, with a critical threshold of 4.189e+9 cells. Below this threshold, there was equilibrium between cancer and organism homeostasis. 3. The transition from early to invasive cancer depended on blood cell levels, the ratio of cancer to blood cells, cancer characteristics, biochemical factors, and anthropometric data.
Report
Share
Report
Share
![Abstract: ,[object Object],[object Object],[object Object],[object Object],[object Object]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
Recommended
Kshivets O. Expert Systems for Diagnosis and Prognosis of Malignant Neoplasms
Expert Systems for Diagnosis and Prognosis of Malignant Neoplasms
Kshivets O. Synergetics and Survival of Lung Cancer Patients
Phase Transitions and Cell Ratio
Factors in Prediction of Lung Cancer
Patients Survival
Kshivets O. Esophageal and Cardioesophageal Cancer Surgery
5-YEAR SURVIVAL OF ESOPHAGEAL AND CARDIOESOPHAGEAL CANCER PATIENTS AFTER RADICAL SURGERY SIGNIFICANTLY DEPENDED ON PHASE TRANSITION “EARLY-INVASIVE CANCER”, LYMPH NODE METASTASES AND CELL RATIO FACTORS
Kshivets O. Lung Cancer Surgery: Synergetics and Prediction
SIGNIFICANT IMPACT OF PHASE TRANSITIONS AND CELL RATIO FACTORS FOR 5-YEAR SURVIVAL OF NON SMALL CELL LUNG CANCER PATIENTS AFTER SURGERY
Kshivets eso10 y2021
10-Year survival after radical procedures significantly depended on: 1) PT “early-invasive cancer”; 2) PT N0--N12; 3) Cell Ratio Factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) EC characteristics; 9) tumor localization; 10) anthropometric data; 11) surgery type. Optimal diagnosis and treatment strategies for EC are: 1) screening and early detection of EC; 2) availability of experienced thoracoabdominal surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for ECP with unfavorable prognosis.
Recommended
Kshivets O. Expert Systems for Diagnosis and Prognosis of Malignant Neoplasms
Expert Systems for Diagnosis and Prognosis of Malignant Neoplasms
Kshivets O. Synergetics and Survival of Lung Cancer Patients
Phase Transitions and Cell Ratio
Factors in Prediction of Lung Cancer
Patients Survival
Kshivets O. Esophageal and Cardioesophageal Cancer Surgery
5-YEAR SURVIVAL OF ESOPHAGEAL AND CARDIOESOPHAGEAL CANCER PATIENTS AFTER RADICAL SURGERY SIGNIFICANTLY DEPENDED ON PHASE TRANSITION “EARLY-INVASIVE CANCER”, LYMPH NODE METASTASES AND CELL RATIO FACTORS
Kshivets O. Lung Cancer Surgery: Synergetics and Prediction
SIGNIFICANT IMPACT OF PHASE TRANSITIONS AND CELL RATIO FACTORS FOR 5-YEAR SURVIVAL OF NON SMALL CELL LUNG CANCER PATIENTS AFTER SURGERY
Kshivets eso10 y2021
10-Year survival after radical procedures significantly depended on: 1) PT “early-invasive cancer”; 2) PT N0--N12; 3) Cell Ratio Factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) EC characteristics; 9) tumor localization; 10) anthropometric data; 11) surgery type. Optimal diagnosis and treatment strategies for EC are: 1) screening and early detection of EC; 2) availability of experienced thoracoabdominal surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for ECP with unfavorable prognosis.
Kshivets O. Cancer, Computer Sciences and Alive Supersystems
EXPERT SYSTEM TECHNOLOGIES FOR DIAGNOSIS AND PROGNOSIS OF MALIGNANCIES
Kshivets barcelona2017
Esophageal cancer patients’ survival after surgery significantly depended on cell ratio factors, blood cell circuit, biochemical factors, hemostasis system, adjuvant chemoimmunoradiotherapy, cancer characteristics, localization, anthropometric data
Kshivets ny2021aats
CONCLUSIONS: 10-Year survival after radical procedures significantly depended on: 1) PT “early-invasive cancer”; 2) PT N0--N12; 3) Cell Ratio Factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) EC characteristics; 9) tumor localization; 10) anthropometric data; 11) surgery type. Optimal diagnosis and treatment strategies for EC are: 1) screening and early detection of EC; 2) availability of experienced thoracoabdominal surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for ECP with unfavorable prognosis.
Kshivets esophageal cancer_management
Optimization of Management for Esophageal Cancer Patients with Stage T1-4N0-2M0
Kshivets barcelona2020
Combined Gastrectomies: Survival Outcomes in Patients with Local Advanced Gastric Cancer
Kshivets O. Lung Cancer Surgery
Immunity Netwoks in Prediction of Five-Year Survival of Lung Cancer Patients after Radical Procedures
Kshivets lc10 ys_wjarr
Conclusions: 10-Year survival of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) anthropometric data; 10) surgery type. Optimal diagnosis and treatment strategies for LC are: 1) screening and early detection of LC; 2) availability of experienced thoracic surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for LCP with unfavorable prognosis.
Kshivets O. Esophageal Cancer Surgery
ESOPHAGEAL CANCER: THE ROLE OF CHEMOIMMUNORADIOTHERAPY AFTER SURGERY
Kshivets Oleg Local Advanced Gastric Cancer: Optimization of Management
Local Advanced Gastric Cancer: Optimization of Management
Kshivets O. Lung Cancer Surgery: Prognosis
HOMEOSTASIS NETWORKS IN PROGNOSIS OF LUNG CANCER PATIENTS SURVIVAL
Kshivets elcc2022
It was revealed that separation of LCP with early LC (n=215) from invasive LCP (n=555) significantly depended on: Hb, leucocytes (abs, total), thrombocytes (abs, tot), erythrocytes (abs, tot), segmented neutrophils (%, abs, total), stick neutrophils (%, abs, total), lymphocytes (%), monocytes (abs, tot), ESS, coagulation time, fibrinogen, cell ratio factors (CRF) (ratio between cancer cells- CC and blood cells subpopulations), tumor size, age, tumor growth, T1-4, G1-3, PT N0---N12 (P=0.046-0.000). Neural networks computing, genetic algorithm selection and bootstrap simulation revealed relationships of PT early—invasive cancer and CRF: healthy cells/CC (rank=1), erythrocytes/CC (2), stick neutrophils/CC (3), thrombocytes/CC (4), eosinophils/CC (5), segmented neutrophils/CC (6), lymphocytes/CC (7), monocytes/CC (8), leucocytes/CC (9). Correct classification PT early—invasive cancer was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSION: Blood cell circuit significantly influenced the phase transition early—invasive lung cancer.
Kshivets O. Lung Cancer Stage III Surgery
PREDICTION OF 5-YEAR SURVIVAL OF NON-SMALL CELL LUNG CANCER PATIENTS WITH STAGE III AFTER COMPLETE RESECTIONS
Kshivets gc 10_ys_wjarr-2021-0659
10-Year survival of GCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) GC characteristics; 9) anthropometric data; 10) surgery type. Optimal diagnosis and treatment strategies for GC are: 1) screening and early detection of GC; 2) availability of experienced abdominal surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunotherapy for GCP with unfavorable prognosis.
Kshivets O. Local Advanced Lung Cancer Surgery
LOCAL ADVANCED LUNG CANCER: OPTIMAL SURGERY STRATEGIES
Kshivets O. Lung Cancer: Early Detection and Diagnosis
Lung Cancer: Early Detection and Diagnosis and Immune System
Kshivets O. Lung Cancer Surgery
5-Year Survival of Non-Small Cell Lung Cancer Patients after Adjuvant Chemoimmunoradiotherapy
Kshivets chicago2016
Artificial Intelligence, System Analysis and Simulation Modeling in Optimization of Management for Lung Cancer Patients
Kshivets IASLC_Vienna2016
5-Year Survival of Lung Cancer Patients after Radical Surgery was Significantly Depended on Tumor Characteristics, Blood Cell Circuit, Cell Ratio Factors, Hemostasis System, Biochemic Homeostasis, Surgery Type, Adjuvant Treatment and Anthropometric Data
More Related Content
What's hot
Kshivets O. Cancer, Computer Sciences and Alive Supersystems
EXPERT SYSTEM TECHNOLOGIES FOR DIAGNOSIS AND PROGNOSIS OF MALIGNANCIES
Kshivets barcelona2017
Esophageal cancer patients’ survival after surgery significantly depended on cell ratio factors, blood cell circuit, biochemical factors, hemostasis system, adjuvant chemoimmunoradiotherapy, cancer characteristics, localization, anthropometric data
Kshivets ny2021aats
CONCLUSIONS: 10-Year survival after radical procedures significantly depended on: 1) PT “early-invasive cancer”; 2) PT N0--N12; 3) Cell Ratio Factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) EC characteristics; 9) tumor localization; 10) anthropometric data; 11) surgery type. Optimal diagnosis and treatment strategies for EC are: 1) screening and early detection of EC; 2) availability of experienced thoracoabdominal surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for ECP with unfavorable prognosis.
Kshivets esophageal cancer_management
Optimization of Management for Esophageal Cancer Patients with Stage T1-4N0-2M0
Kshivets barcelona2020
Combined Gastrectomies: Survival Outcomes in Patients with Local Advanced Gastric Cancer
Kshivets O. Lung Cancer Surgery
Immunity Netwoks in Prediction of Five-Year Survival of Lung Cancer Patients after Radical Procedures
Kshivets lc10 ys_wjarr
Conclusions: 10-Year survival of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) anthropometric data; 10) surgery type. Optimal diagnosis and treatment strategies for LC are: 1) screening and early detection of LC; 2) availability of experienced thoracic surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for LCP with unfavorable prognosis.
Kshivets O. Esophageal Cancer Surgery
ESOPHAGEAL CANCER: THE ROLE OF CHEMOIMMUNORADIOTHERAPY AFTER SURGERY
Kshivets Oleg Local Advanced Gastric Cancer: Optimization of Management
Local Advanced Gastric Cancer: Optimization of Management
Kshivets O. Lung Cancer Surgery: Prognosis
HOMEOSTASIS NETWORKS IN PROGNOSIS OF LUNG CANCER PATIENTS SURVIVAL
Kshivets elcc2022
It was revealed that separation of LCP with early LC (n=215) from invasive LCP (n=555) significantly depended on: Hb, leucocytes (abs, total), thrombocytes (abs, tot), erythrocytes (abs, tot), segmented neutrophils (%, abs, total), stick neutrophils (%, abs, total), lymphocytes (%), monocytes (abs, tot), ESS, coagulation time, fibrinogen, cell ratio factors (CRF) (ratio between cancer cells- CC and blood cells subpopulations), tumor size, age, tumor growth, T1-4, G1-3, PT N0---N12 (P=0.046-0.000). Neural networks computing, genetic algorithm selection and bootstrap simulation revealed relationships of PT early—invasive cancer and CRF: healthy cells/CC (rank=1), erythrocytes/CC (2), stick neutrophils/CC (3), thrombocytes/CC (4), eosinophils/CC (5), segmented neutrophils/CC (6), lymphocytes/CC (7), monocytes/CC (8), leucocytes/CC (9). Correct classification PT early—invasive cancer was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSION: Blood cell circuit significantly influenced the phase transition early—invasive lung cancer.
Kshivets O. Lung Cancer Stage III Surgery
PREDICTION OF 5-YEAR SURVIVAL OF NON-SMALL CELL LUNG CANCER PATIENTS WITH STAGE III AFTER COMPLETE RESECTIONS
Kshivets gc 10_ys_wjarr-2021-0659
10-Year survival of GCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) GC characteristics; 9) anthropometric data; 10) surgery type. Optimal diagnosis and treatment strategies for GC are: 1) screening and early detection of GC; 2) availability of experienced abdominal surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunotherapy for GCP with unfavorable prognosis.
Kshivets O. Local Advanced Lung Cancer Surgery
LOCAL ADVANCED LUNG CANCER: OPTIMAL SURGERY STRATEGIES
Kshivets O. Lung Cancer: Early Detection and Diagnosis
Lung Cancer: Early Detection and Diagnosis and Immune System
Kshivets O. Lung Cancer Surgery
5-Year Survival of Non-Small Cell Lung Cancer Patients after Adjuvant Chemoimmunoradiotherapy
What's hot (20)
Kshivets O. Cancer, Computer Sciences and Alive Supersystems
Kshivets O. Cancer, Computer Sciences and Alive Supersystems
Kshivets Oleg Local Advanced Gastric Cancer: Optimization of Management
Kshivets Oleg Local Advanced Gastric Cancer: Optimization of Management
Kshivets O. Lung Cancer: Early Detection and Diagnosis
Kshivets O. Lung Cancer: Early Detection and Diagnosis
Viewers also liked
Kshivets chicago2016
Artificial Intelligence, System Analysis and Simulation Modeling in Optimization of Management for Lung Cancer Patients
Kshivets IASLC_Vienna2016
5-Year Survival of Lung Cancer Patients after Radical Surgery was Significantly Depended on Tumor Characteristics, Blood Cell Circuit, Cell Ratio Factors, Hemostasis System, Biochemic Homeostasis, Surgery Type, Adjuvant Treatment and Anthropometric Data
SADI for GMOD: Semantic Web Services for Model Organism Databases
SADI for GMOD is a collection of ready-made SADI services for accessing sequence feature data in RDF form. The services were developed as an add-on for the GMOD (Generic Model Organism Database) project, which is a popular toolkit for building model organism databases and their associated websites (e.g. FlyBase).
Viewers also liked (6)
SADI for GMOD: Semantic Web Services for Model Organism Databases
SADI for GMOD: Semantic Web Services for Model Organism Databases
Similar to Kshivets O. Cancer, Synergetics, Computer Sciences and Alive Supersystems
Liquid Biopsy Cancer Prevention and Monitoring
Molecular characterization of a patient’s tumor to guide treatment decisions is increasingly being
applied in clinical care and can have a significant impact on disease outcome. These molecular analyses,
including mutation characterization, are typically performed on tissue acquired through a biopsy at diagnosis.
However, tumors are highly heterogeneous and sampling in its entirety is challenging. Furthermore, tumors
evolve over time and can alter their molecular genotype, making clinical decisions based on historical biopsy
data suboptimal. Personalized medicine for cancer patients aims to tailor the best treatment options for the
individual at diagnosis and during treatment. To fully enable personalized medicine it is desirable to have an
easily accessible, minimally invasive way to determine and follow the molecular makeup of a patient’s tumor
longitudinally. One such approach is through a liquid biopsy, where the genetic makeup of the tumor can be
assessed through a bio fluid sample. Liquid biopsies have the potential to help clinicians screen for disease,
stratify patients to the best treatment and monitor treatment response and resistance mechanisms in the tumor. A liquid biopsy can be used for molecular characterization of the tumor and its non-invasive nature
allows repeat sampling to monitor genetic changes over time without the need for a tissue biopsy. This review will summarize three approaches in the liquid biopsy field: circulating tumor cells (CTCs), cell free DNA (cfDNA) and exosomes. We also outline some of the analytical challenges encountered using liquid biopsy techniques to detect rare mutations in a background of wild-type sequences.
Development and Validation of a Nomogram for Predicting Response to Neoadjuva...
Retrospective analysis of clinical data on female patients with breast cancer was performed. Model 1 was developed by entering variables from the univariate analysis (P < 0.1) into a multivariate logistic regression analysis. Model 2 was developed via the stepwise forward-backward variable selection technique in partial least squares regression. For model 3, the least absolute shrinkage and selection operator (LASSO) method was used to choose suitable variables, followed by the multivariate logistic regression analysis.
Development and Validation of a Nomogram for Predicting Response to Neoadjuva...
Retrospective analysis of clinical data on female
patients with breast cancer was performed. Model 1 was developed by entering variables from the univariate analysis (P < 0.1)
into a multivariate logistic regression analysis. Model 2 was developed via the stepwise forward-backward variable selection technique in partial least squares regression. For model 3, the least
absolute shrinkage and selection operator (LASSO) method was
used to choose suitable variables, followed by the multivariate
logistic regression analysis. Harrell’s C-index, calibration curves,
and decision curve analyses (DCA) were used to compare the
performance of the models. In the validation cohort, these results
were validated
Precision Medicine in Oncology Informatics
Precision Medicine Initiative in Oncology Informatics. For the Cancer Informatics for Cancer Centers (CI4CC) meeting in October 2015.
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Pancreatic cancer remains as one of the most aggressive and deadliest of cancers largely due to formidable challenges in diagnosis and therapy. Consensus standard treatment for patients with nonmetastatic Pancreatic Cancer (PC) incorporates possible neoadjuvant chemotherapy with timely surgical resection and adjuvant chemotherapy. However, despite all the sophistication of modern radiological and endoscopic techniques, the decision regarding operability is often only made intra-operatively, therefore subjecting a patient to unnecessary surgical intervention, and postponing the possibility of starting early chemotherapy.
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Pancreatic cancer remains as one of the most aggressive and deadliest of cancers largely due to formidable challenges in diagnosis and therapy. Consensus standard treatment for patients with nonmetastatic Pancreatic Cancer (PC) incorporates possible neoadjuvant chemotherapy with timely surgical resection and adjuvant chemotherapy. However, despite all the sophistication of modern radiological and endoscopic techniques, the decision regarding operability is often only made intra-operatively, therefore subjecting a patient to unnecessary surgical intervention, and postponing the possibility of starting early chemotherapy.
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Pancreatic cancer remains as one of the most aggressive and deadliest of cancers largely due to formidable challenges in diagnosis and therapy. Consensus standard treatment for patients with nonmetastatic Pancreatic Cancer (PC) incorporates possible neoadjuvant chemotherapy with timely surgical resection and adjuvant chemotherapy. However, despite all the sophistication of modern radiological and endoscopic techniques, the decision regarding operability is often only made intra-operatively, therefore subjecting a patient to unnecessary surgical intervention, and postponing the possibility of starting early chemotherapy.
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Pancreatic cancer remains as one of the most
aggressive and deadliest of cancers largely due to formidable challenges in diagnosis and therapy. Consensus standard treatment for
patients with nonmetastatic Pancreatic Cancer (PC) incorporates
possible neoadjuvant chemotherapy with timely surgical resection
and adjuvant chemotherapy. However, despite all the sophistication of modern radiological and endoscopic techniques, the decision regarding operability is often only made intra-operatively,
therefore subjecting a patient to unnecessary surgical intervention,
and postponing the possibility of starting early chemotherapy.
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Pancreatic cancer remains as one of the most aggressive and deadliest of cancers largely due to formidable challenges in diagnosis and therapy. Consensus standard treatment for patients with nonmetastatic Pancreatic Cancer (PC) incorporates possible neoadjuvant chemotherapy with timely surgical resection and adjuvant chemotherapy. However, despite all the sophistication of modern radiological and endoscopic techniques, the decision regarding operability is often only made intra-operatively, therefore subjecting a patient to unnecessary surgical intervention, and postponing the possibility of starting early chemotherapy.
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Pancreatic cancer remains as one of the most aggressive and deadliest of cancers largely due to formidable challenges in diagnosis and therapy. Consensus standard treatment for patients with nonmetastatic Pancreatic Cancer (PC) incorporates possible neoadjuvant chemotherapy with timely surgical resection and adjuvant chemotherapy. However, despite all the sophistication of modern radiological and endoscopic techniques, the decision regarding operability is often only made intra-operatively, therefore subjecting a patient to unnecessary surgical intervention, and postponing the possibility of starting early chemotherapy.
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Pancreatic cancer remains as one of the most
aggressive and deadliest of cancers largely due to formidable challenges in diagnosis and therapy. Consensus standard treatment for
patients with nonmetastatic Pancreatic Cancer (PC) incorporates
possible neoadjuvant chemotherapy with timely surgical resection
and adjuvant chemotherapy
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Pancreatic cancer remains as one of the most aggressive and deadliest of cancers largely due to formidable challenges in diagnosis and therapy. Consensus standard treatment for patients with nonmetastatic Pancreatic Cancer (PC) incorporates possible neoadjuvant chemotherapy with timely surgical resection and adjuvant chemotherapy. However, despite all the sophistication of modern radiological and endoscopic techniques, the decision regarding operability is often only made intra-operatively, therefore subjecting a patient to unnecessary surgical intervention, and postponing the possibility of starting early chemotherapy.
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Pancreatic cancer remains as one of the most aggressive and deadliest of cancers largely due to formidable challenges in diagnosis and therapy. Consensus standard treatment for patients with nonmetastatic Pancreatic Cancer (PC) incorporates possible neoadjuvant chemotherapy with timely surgical resection and adjuvant chemotherapy. However, despite all the sophistication of modern radiological and endoscopic techniques, the decision regarding operability is often only made intra-operatively, therefore subjecting a patient to unnecessary surgical intervention, and postponing the possibility of starting early chemotherapy.
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Pancreatic cancer remains as one of the most
aggressive and deadliest of cancers largely due to formidable challenges in diagnosis and therapy. Consensus standard treatment for
patients with nonmetastatic Pancreatic Cancer (PC) incorporates
possible neoadjuvant chemotherapy with timely surgical resection
and adjuvant chemotherapy
Usefulness of Serum Carcinoembryonic Antigen (CEA) in evaluating response to ...
Usefulness of Serum Carcinoembryonic Antigen (CEA) in evaluating response to ...Enrique Moreno Gonzalez
High serum carcinoembryonic antigen (CEA) levels are an independent prognostic factor for recurrence and survival in patients with non-small cell lung cancer (NSCLC). Its role as a predictive marker of treatment response has not been widely characterized. Similar to Kshivets O. Cancer, Synergetics, Computer Sciences and Alive Supersystems (20)
Development and Validation of a Nomogram for Predicting Response to Neoadjuva...
Development and Validation of a Nomogram for Predicting Response to Neoadjuva...
Development and Validation of a Nomogram for Predicting Response to Neoadjuva...
Development and Validation of a Nomogram for Predicting Response to Neoadjuva...
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Circulating Tumor Cells and Cell-Free Nucleic Acids as Predictor Factors for ...
Usefulness of Serum Carcinoembryonic Antigen (CEA) in evaluating response to ...
Usefulness of Serum Carcinoembryonic Antigen (CEA) in evaluating response to ...
More from Oleg Kshivets
Local Advanced Lung Cancer: Artificial Intelligence, Synergetics, Complex Sys...
Overall life span (LS) was 1671.7±1721.6 days and cumulative 5YS reached 62.4%, 10 years – 50.4%, 20 years – 44.6%. 94 LCP lived more than 5 years without cancer (LS=2958.6±1723.6 days), 22 – more than 10 years (LS=5571±1841.8 days). 67 LCP died because of LC (LS=471.9±344 days). AT significantly improved 5YS (68% vs. 53.7%) (P=0.028 by log-rank test). Cox modeling displayed that 5YS of LCP significantly depended on: N0-N12, T3-4, blood cell circuit, cell ratio factors (ratio between cancer cells-CC and blood cells subpopulations), LC cell dynamics, recalcification time, heparin tolerance, prothrombin index, protein, AT, procedure type (P=0.000-0.031). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and N0-12 (rank=1), thrombocytes/CC (rank=2), segmented neutrophils/CC (3), eosinophils/CC (4), erythrocytes/CC (5), healthy cells/CC (6), lymphocytes/CC (7), stick neutrophils/CC (8), leucocytes/CC (9), monocytes/CC (10). Correct prediction of 5YS was 100% by neural networks computing (error=0.000; area under ROC curve=1.0).
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...
RESULTS: Overall life span (LS) was 2252.1±1742.5 days and cumulative 5-year survival (5YS) reached 73.2%, 10 years – 64.8%, 20 years – 42.5%. 513 LCP lived more than 5 years (LS=3124.6±1525.6 days), 148 LCP – more than 10 years (LS=5054.4±1504.1 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (78.1% vs.63.7%, P=0.00001 by log-rank test). AT significantly improved 5YS (66.3% vs. 34.8%) (P=0.00000 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.038). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), erythrocytes/CC (4), eosinophils/CC (5), healthy cells/CC (6), lymphocytes/CC (7), segmented neutrophils/CC (8), stick neutrophils/CC (9), monocytes/CC (10); leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5YS of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) LC cell dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data. Optimal diagnosis and treatment strategies for LC are: 1) screening and early detection of LC; 2) availability of experienced thoracic surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for LCP with unfavorable prognosis.
Gastric Cancer: Сlinical Implementation of Artificial Intelligence, Synergeti...
5-year survival of GCP after radical procedures significantly depended on: 1) PT “early-invasive cancer”; 2) PT N0--N12; 3) Cell Ratio Factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) GC cell dynamics; 9) GC characteristics; 10) tumor localization; 11) anthropometric data; 12) surgery type. Optimal diagnosis and treatment strategies for GC are: 1) screening and early detection of GC; 2) availability of sufficient quantity of experienced abdominal surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunotherapy for GCP with unfavorable prognosis.
Local Advanced Esophageal Cancer (T3-4N0-2M0): Artificial Intelligence, Syner...
5YS of local advanced ECP after combined radical procedures significantly depended on: tumor characteristics, blood cell circuit, cell ratio factors, biochemical factors, hemostasis system, anthropometric data and adjuvant treatment. Optimal strategies for local advanced ECP are: 1) availability of very experienced thoracoabdominal surgeons because of complexity radical procedures; 2) aggressive en block surgery and adequate lymph node dissection for completeness; 3) precise prediction; 4) AT for ECP with unfavorable prognosis.
Esophageal Cancer: Artificial Intelligence, Synergetics, Complex System Analy...
5-year survival of ECP after radical procedures significantly depended on: 1) PT “early-invasive cancer”; 2) PT N0--N12; 3) Cell Ratio Factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) EC cell dynamics; 9) EC characteristics; 10) tumor localization; 11) anthropometric data; 12) surgery type. Optimal diagnosis and treatment strategies for EC are: 1) screening and early detection of EC; 2) availability of experienced thoracoabdominal surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for ECP with unfavorable prognosis.
Kshivets Oleg Optimization of Management for Esophageal Cancer Patients (T1-...
Optimization of Management for Esophageal Cancer Patients (T1-4N0-2M0).
Kshivets Oleg Surgery Department, Bagrationovsk Hospital, Bagrationovsk, Kaliningrad, Russia
ABSTRACT
OBJECTIVE: 5-survival (5YS) and life span after radical surgery for esophageal cancer (EC) pa¬tients (ECP)(T1-4N0-2M0) - alive supersysems was analyzed. The importance must be stressed of using complex system analysis, artificial intelligence (neural networks computing), simulation modeling and statistical methods in combination, because the different approaches yield complementary pieces of prognostic information.
METHODS: We analyzed data of 563 consecutive ECP (age=56.6±8.9 years; tumor size=6±3.5 cm) radically operated (R0) and monitored in 1975-2024 (m=419, f=144; esophagogastrectomies (EG) Garlock=289, EG Lewis=274, combined EG with resection of pancreas, liver, diaphragm, aorta, VCS, colon transversum, lung, trachea, pericardium, splenectomy=170; adenocarcinoma=323, squamous=230, mix=10; T1=131, T2=119, T3=185, T4=128; N0=285, N1=71, N2=207; G1=161, G2=143, G3=259; early EC=112, invasive=451; only surgery=428, adjuvant chemoimmunoradiotherapy-AT=135: 5-FU+thymalin/taktivin+radiotherapy 45-50Gy). Multivariate Cox modeling, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine any significant dependence.
RESULTS: Overall life span (LS) was 1915.4±2284.8 days and cumulative 5-year survival (5YS) reached 52.6%, 10 years – 46.3%, 20 years – 33.3%, 30 years – 27.5%. 193 ECP lived more than 5 years (LS=4309.1±2507.4 days), 105 ECP – more than 10 years (LS=5860.8±2469.2 days). 228 ECP died because of EC (LS=629.8±324.1 days). AT significantly improved 5YS (69% vs. 49.1%) (P=0.0007 by log-rank test). 5YS of ECP of upper/3 was significantly better than others (65.3% vs.50.3%) (P=0.003). Cox modeling displayed that 5YS of ECP significantly depended on: phase transition (PT) N0—N12 in terms of synergetics, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), T, G, histology, age, AT, localization, prothrombin index, hemorrhage time, residual nitrogen, protein (P=0.000-0.019). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and healthy cells/CC (rank=1), PT N0—N12 (2), PT early-invasive EC (3), erythrocytes/CC (4), thrombocytes/CC (5); segmented neutrophils/CC (6), stick neutrophils/CC (7), lymphocytes/CC (8), eosinophils/CC (9), monocytes/CC (10), leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5-year survival of ECP after radical procedures significantly depended on: 1) PT “early-invasive cancer”; 2) PT N0--N12; 3) Cell Ratio Factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) EC cell dynamics; 9) EC characteristics; 10) tumor localization; 11) anthropometric data; 12) surgery type. Optimal diagnosis and trea
Kshivets_IASLC_Singapore2023.pdf
5YS of LCP after radical procedures significantly depended on: PT early-invasive cancer; PT N0--N12; cell ratio factors; blood cell circuit; biochemical factors; hemostasis system; AT; LC characteristics; LC cell dynamics; surgery type; anthropometric data.
KshivetsWSCTS2023_Brazil.pdf
5-year survival of ECP after radical procedures significantly depended on: 1) PT “early-invasive cancer”; 2) PT N0--N12; 3) Cell Ratio Factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) EC characteristics; 9) EC cell dynamics; 10) tumor localization; 11) anthropometric data; 12) surgery type. Optimal diagnosis and treatment strategies for EC are: 1) screening and early detection of EC; 2) availability of experienced thoracoabdominal surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for ECP with unfavorable prognosis.
KshivetsWSCTS2023_Brazil.pdf
OBJECTIVE: 5-survival (5YS) and life span after radical surgery for esophageal cancer (EC) pa¬tients (ECP) (T1-4N0-2M0) was analyzed. The importance must be stressed of using complex system analysis, artificial intelligence (neural networks computing), simulation modeling and statistical methods in combination, because the different approaches yield complementary pieces of prognostic information.
METHODS: We analyzed data of 557 consecutive ECP (age=56.6±8.9 years; tumor size=6±3.5 cm) radically operated (R0) and monitored in 1975-2023 (m=415, f=142; esophagogastrectomies (EG) Garlock=288, EG Lewis=269, combined EG with resection of pancreas, liver, diaphragm, aorta, VCS, colon transversum, lung, trachea, pericardium, splenectomy=168; adenocarcinoma=319, squamous=228, mix=10; T1=130, T2=115, T3=184, T4=128; N0=282, N1=70, N2=205; G1=157, G2=142, G3=258; early EC=111, invasive=446; only surgery=425, adjuvant chemoimmunoradiotherapy-AT=132: 5-FU+thymalin/taktivin+radiotherapy 45-50Gy). Multivariate Cox modeling, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine any significant dependence.
RESULTS: Overall life span (LS) was 1876.9±2219.8 days and cumulative 5-year survival (5YS) reached 52%, 10 years – 45.5%, 20 years – 33.4%, 30 years – 26.9%. 187 ECP lived more than 5 years (LS=4271±2411.9 days), 99 ECP – more than 10 years (LS=5883±2296.6 days). 228 ECP died because of EC (LS=629.8±324.1 days). AT significantly improved 5YS (67.8% vs. 48.7%) (P=0.00084 by log-rank test). Cox modeling displayed that 5YS of ECP significantly depended on: phase transition (PT) N0—N12 in terms of synergetics, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), T, G, histology, age, AT, localization, prothrombin index, hemorrhage time, residual nitrogen, protein (P=0.000-0.019). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and
healthy cells/CC (rank=1), PT early-invasive EC (2); PT N0—N12 (3), erythrocytes/CC (4), thrombocytes/CC (5); stick neutrophils/CC (6), lymphocytes/CC (7), segmented neutrophils/CC (8), eosinophils/CC (9), leucocytes/CC (10); monocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5-year survival of ECP after radical procedures significantly depended on: 1) PT “early-invasive cancer”; 2) PT N0--N12; 3) Cell Ratio Factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) EC characteristics; 9) EC cell dynamics; 10) tumor localization; 11) anthropometric data; 12) surgery type. Optimal diagnosis and treatment strategies for EC are: 1) screening and early detection of EC; 2) availability of experienced thoracoabdominal surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5)AT
KshivetsWSCTS2023_Brazil.pdf
OBJECTIVE: 5-survival (5YS) and life span after radical surgery for esophageal cancer (EC) pa¬tients (ECP) (T1-4N0-2M0) was analyzed. The importance must be stressed of using complex system analysis, artificial intelligence (neural networks computing), simulation modeling and statistical methods in combination, because the different approaches yield complementary pieces of prognostic information.
METHODS: We analyzed data of 557 consecutive ECP (age=56.6±8.9 years; tumor size=6±3.5 cm) radically operated (R0) and monitored in 1975-2023 (m=415, f=142; esophagogastrectomies (EG) Garlock=288, EG Lewis=269, combined EG with resection of pancreas, liver, diaphragm, aorta, VCS, colon transversum, lung, trachea, pericardium, splenectomy=168; adenocarcinoma=319, squamous=228, mix=10; T1=130, T2=115, T3=184, T4=128; N0=282, N1=70, N2=205; G1=157, G2=142, G3=258; early EC=111, invasive=446; only surgery=425, adjuvant chemoimmunoradiotherapy-AT=132: 5-FU+thymalin/taktivin+radiotherapy 45-50Gy). Multivariate Cox modeling, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine any significant dependence.
RESULTS: Overall life span (LS) was 1876.9±2219.8 days and cumulative 5-year survival (5YS) reached 52%, 10 years – 45.5%, 20 years – 33.4%, 30 years – 26.9%. 187 ECP lived more than 5 years (LS=4271±2411.9 days), 99 ECP – more than 10 years (LS=5883±2296.6 days). 228 ECP died because of EC (LS=629.8±324.1 days). AT significantly improved 5YS (67.8% vs. 48.7%) (P=0.00084 by log-rank test). Cox modeling displayed that 5YS of ECP significantly depended on: phase transition (PT) N0—N12 in terms of synergetics, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), T, G, histology, age, AT, localization, prothrombin index, hemorrhage time, residual nitrogen, protein (P=0.000-0.019). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and
healthy cells/CC (rank=1), PT early-invasive EC (2); PT N0—N12 (3), erythrocytes/CC (4), thrombocytes/CC (5); stick neutrophils/CC (6), lymphocytes/CC (7), segmented neutrophils/CC (8), eosinophils/CC (9), leucocytes/CC (10); monocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5-year survival of ECP after radical procedures significantly depended on: 1) PT “early-invasive cancer”; 2) PT N0--N12; 3) Cell Ratio Factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) EC characteristics; 9) EC cell dynamics; 10) tumor localization; 11) anthropometric data; 12) surgery type. Optimal diagnosis and treatment strategies for EC are: 1) screening and early detection of EC; 2) availability of experienced thoracoabdominal surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant ch
Kshivets_WCGIC2023.pdf
5-year survival of GCP after radical procedures
significantly depended on: 1) PT “early-invasive
cancer”; 2) PT N0--N12; 3) Cell Ratio Factors; 4) blood
cell circuit; 5) biochemical factors; 6) hemostasis
system; 7) AT; 8) GC characteristics; 9) GC cell
dynamics; 10) tumor localization; 11) anthropometric
data; 12) surgery type. Best diagnosis and treatment
strategies for GC are: 1) screening and early detection
of GC; 2) availability of experienced abdominal
surgeons because of complexity of radical procedures;
3) aggressive en block surgery and adequate lymph
node dissection for completeness; 4) precise
prediction; 5) adjuvant chemoimmunotherapy for GCP
with unfavorable prognosis.
Kshivets_ELCC2023.pdf
OBJECTIVE: 5-survival (5YS) and life span after radical surgery for non-small cell lung cancer (LC) pa¬tients (LCP) (T1-4N0-2M0) was analyzed.
METHODS: We analyzed data of 771 consecutive LCP (age=57.6±8.3 years; tumor size=4.1±2.4 cm) radically operated and monitored in 1985-2022 (m=662, f=109; upper lobectomies=278, lower lobectomies=178, middle lobectomies=18, bilobectomies=42, pneumonectomies=255, mediastinal lymph node dissection=771; combined procedures with resection of trachea, carina, atrium, aorta, VCS, vena azygos, pericardium, liver, diaphragm, ribs, esophagus=194; only surgery-S=620, adjuvant chemoimmunoradiotherapy-AT=151: CAV/gemzar + cisplatin + thymalin/taktivin + radiotherapy 45-50Gy; T1=322, T2=255, T3=133, T4=61; N0=518, N1=131, N2=122, M0=771; G1=195, G2=243, G3=333; squamous=418, adenocarcinoma=303, large cell=50; early LC=215, invasive LC=556; right LC=413, left LC=358; central=291; peripheral=480. Variables selected for study were input levels of 45 blood parameters, sex, age, TNMG, cell type, tumor size. Regression modeling, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine significant dependence.
RESULTS: Overall life span (LS) was 2240.9±1748.8 days and cumulative 5-year survival (5YS) reached 73%, 10 years – 64.2%, 20 years – 43%. 503 LCP lived more than 5 years (LS=3126.6±1536 days), 145 LCP – more than 10 years (LS=5068.5±1513.2 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (77.7% vs.63.4%, P=0.00001 by log-rank test). AT significantly improved 5YS (64.4% vs. 34.8%) (P=0.00003 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.035). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), eosinophils/CC (4), erythrocytes/CC (5),healthy cells/CC (6), segmented neutrophils/CC (7), lymphocytes/CC (8), stick neutrophils/CC (9), monocytes/CC (10); leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5YS of LCP after radical procedures significantly depended on: PT early-invasive cancer; PT N0--N12; cell ratio factors; blood cell circuit; biochemical factors; hemostasis system; AT; LC characteristics; surgery type; anthropometric data.
Kshivets_ELCC2023.pdf
OBJECTIVE: 5-survival (5YS) and life span after radical surgery for non-small cell lung cancer (LC) pa¬tients (LCP) (T1-4N0-2M0) was analyzed.
METHODS: We analyzed data of 771 consecutive LCP (age=57.6±8.3 years; tumor size=4.1±2.4 cm) radically operated and monitored in 1985-2022 (m=662, f=109; upper lobectomies=278, lower lobectomies=178, middle lobectomies=18, bilobectomies=42, pneumonectomies=255, mediastinal lymph node dissection=771; combined procedures with resection of trachea, carina, atrium, aorta, VCS, vena azygos, pericardium, liver, diaphragm, ribs, esophagus=194; only surgery-S=620, adjuvant chemoimmunoradiotherapy-AT=151: CAV/gemzar + cisplatin + thymalin/taktivin + radiotherapy 45-50Gy; T1=322, T2=255, T3=133, T4=61; N0=518, N1=131, N2=122, M0=771; G1=195, G2=243, G3=333; squamous=418, adenocarcinoma=303, large cell=50; early LC=215, invasive LC=556; right LC=413, left LC=358; central=291; peripheral=480. Variables selected for study were input levels of 45 blood parameters, sex, age, TNMG, cell type, tumor size. Regression modeling, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine significant dependence.
RESULTS: Overall life span (LS) was 2240.9±1748.8 days and cumulative 5-year survival (5YS) reached 73%, 10 years – 64.2%, 20 years – 43%. 503 LCP lived more than 5 years (LS=3126.6±1536 days), 145 LCP – more than 10 years (LS=5068.5±1513.2 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (77.7% vs.63.4%, P=0.00001 by log-rank test). AT significantly improved 5YS (64.4% vs. 34.8%) (P=0.00003 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.035). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), eosinophils/CC (4), erythrocytes/CC (5),healthy cells/CC (6), segmented neutrophils/CC (7), lymphocytes/CC (8), stick neutrophils/CC (9), monocytes/CC (10); leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5YS of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) LC dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data.
Lung Cancer: Precise Prediction
OBJECTIVE: 5-survival (5YS) and life span after radical surgery for non-small cell lung cancer (LC) pa¬tients (LCP) (T1-4N0-2M0) was analyzed.
METHODS: We analyzed data of 771 consecutive LCP (age=57.6±8.3 years; tumor size=4.1±2.4 cm) radically operated and monitored in 1985-2022 (m=662, f=109; upper lobectomies=278, lower lobectomies=178, middle lobectomies=18, bilobectomies=42, pneumonectomies=255, mediastinal lymph node dissection=771; combined procedures with resection of trachea, carina, atrium, aorta, VCS, vena azygos, pericardium, liver, diaphragm, ribs, esophagus=194; only surgery-S=620, adjuvant chemoimmunoradiotherapy-AT=151: CAV/gemzar + cisplatin + thymalin/taktivin + radiotherapy 45-50Gy; T1=322, T2=255, T3=133, T4=61; N0=518, N1=131, N2=122, M0=771; G1=195, G2=243, G3=333; squamous=418, adenocarcinoma=303, large cell=50; early LC=215, invasive LC=556; right LC=413, left LC=358; central=291; peripheral=480. Variables selected for study were input levels of 45 blood parameters, sex, age, TNMG, cell type, tumor size. Regression modeling, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine significant dependence.
RESULTS: Overall life span (LS) was 2240.9±1748.8 days and cumulative 5-year survival (5YS) reached 73%, 10 years – 64.2%, 20 years – 43%. 503 LCP lived more than 5 years (LS=3126.6±1536 days), 145 LCP – more than 10 years (LS=5068.5±1513.2 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (77.7% vs.63.4%, P=0.00001 by log-rank test). AT significantly improved 5YS (64.4% vs. 34.8%) (P=0.00003 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.035). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), eosinophils/CC (4), erythrocytes/CC (5),healthy cells/CC (6), segmented neutrophils/CC (7), lymphocytes/CC (8), stick neutrophils/CC (9), monocytes/CC (10); leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5YS of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) LC dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data.
Kshivets_SPB_WSCTS2022Lung.pdf
Survival of Lung Cancer Patients after Lobectomies was Significantly Superior in Comparison with Lung Cancer Patients after Pneumonectomies
Lung cancer cell dynamics significantly depended on blood cell circuit, bioch...
OBJECTIVE: We examined factors significantly affecting lung cancer (LC) cell dynamics.
METHODS: We analyzed data of 768 consecutive non-small cell LC patients (LCP) (age=57.6±8.3 years; tumor size=4.1±2.4 cm) radically operated and monitored in 1985-2022 (m=660, f=108; upper lobectomies=277, lower lobectomies=177, middle lobectomies=18, bilobectomies=42, pneumonectomies=254, mediastinal lymph node dissection=768; combined procedures with resection of trachea, carina, atrium, aorta, VCS, vena azygos, pericardium, liver, diaphragm, ribs, esophagus=193; only surgery-S=618, adjuvant chemoimmunoradiotherapy-AT=150: CAV/gemzar + cisplatin + thymalin/taktivin + radiotherapy 45-50Gy; T1=320, T2=255, T3=133, T4=60; N0=516, N1=131, N2=121, M0=768; G1=194, G2=243, G3=331; squamous=417, adenocarcinoma=301, large cell=50; early LC=214, invasive LC=554; right LC=412, left LC=356; central=290; peripheral=478. Variables selected for study were input levels of 45 blood parameters, sex, age, TNMG, cell type, tumor size. Regression modeling, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine significant dependence.
RESULTS: Overall life span (LS) was 2244.9±1750.3 days and cumulative 5-year survival (5YS) reached 72.9%, 10 years – 64.3%, 20 years – 43.1%. 502 LCP lived more than 5 years (LS=3128.7±1536.8 days), 145 LCP – more than 10 years (LS=5068.5±1513.2 days).199 LCP died because of LC (LS=562.7±374.5 days). Regression modeling displayed LC cell dynamics significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, histology, T, G, LC growth, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), ESS, glucose, bilirubin (P=0.000-0.033). Neural networks simulation revealed relationships between LC cell dynamics and segmented neutrophils (rank=1), lymphocytes (2), PT N0—N12 (3), PT early-invasive LC (4), leucocytes (5), stick neutrophils (6), eosinophils (7), erythrocytes (8), monocytes (9), thrombocytes (10), Hb (11), ESS (12). Prediction was 92-95% by neural networks computing.
CONCLUSIONS: Lung cancer cell dynamics significantly depended on blood cell circuit, biochemical factors, hemostasis system, cancer characteristics, anthropometric data.
Esophageal Cancer: Precise Prediction
OBJECTIVE: 5-survival (5YS) and life span after radical surgery for esophageal cancer (EC) pa¬tients (ECP) (T1-4N0-2M0) was analyzed.
METHODS: We analyzed data of 556 consecutive ECP (age=56.5±8.9 years; tumor size=6±3.5 cm) radically operated (R0) and monitored in 1975-2022 (m=415, f=141; esophagogastrectomies (EG) Garlock=287, EG Lewis=269, combined EG with resection of pancreas, liver, diaphragm, aorta, VCS, colon transversum, lung, trachea, pericardium, splenectomy=167; adenocarcinoma=318, squamous=228, mix=10; T1=129, T2=115, T3=184, T4=128; N0=281, N1=70, N2=205; G1=157, G2=141, G3=258; early EC=110, invasive=446; only surgery=424, adjuvant chemoimmunoradiotherapy-AT=132: 5-FU+thymalin/taktivin+radiotherapy 45-50Gy). Multivariate Cox modeling, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine any significant dependence.
RESULTS: Overall life span (LS) was 1877±2221.6 days and cumulative 5-year survival (5YS) reached 52%, 10 years – 45%, 20 years – 33.4%, 30 years – 27%. 186 ECP lived more than 5 years (LS=4283.3±2412.6 days), 99 ECP – more than 10 years (LS=5883±2296.6 days). 227 ECP died because of EC (LS=631.8±323.4 days). AT significantly improved 5YS (60.3% vs. 42%) (P=0.0029 by log-rank test). Cox modeling displayed that 5YS of ECP significantly depended on: phase transition (PT) N0—N12 in terms of synergetics, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), T, G, histology, age, AT, localization, prothrombin index, hemorrhage time, residual nitrogen, protein (P=0.000-0.021). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and P PT early-invasive EC (rank=1); healthy cells/CC (2), erythrocytes/CC (3), PT N0—N12 (4) thrombocytes/CC (5); segmented neutrophils/CC (6), stick neutrophils/CC (7), lymphocytes/CC (8), monocytes/CC (9); leucocytes/CC (10); eosinophils/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5-year survival of ECP after radical procedures significantly depended on: 1) PT “early-invasive cancer”; 2) PT N0--N12; 3) Cell Ratio Factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) EC characteristics; 9) tumor localization; 10) anthropometric data; 11) surgery type. Optimal diagnosis and treatment strategies for EC are: 1) screening and early detection of EC; 2) availability of experienced thoracoabdominal surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for ECP with unfavorable prognosis.
Survival of Lung Cancer Patients after Lobectomies was Significantly Superior...
OBJECTIVE: This study aimed to determine surgery type influence for 5-year survival (5YS) of non-small cell lung cancer (LC) patients (LCP) after complete en block (R0) lobectomies and pneumonectomies.
METHODS: We analyzed data of 765 consecutive patients (age=57.6±8.3 years; tumor size=4.1±2.4 cm) radically operated (R0) and monitored in 1985-2022 (m=659, f=106; bi/lobectomies=512, pneumonectomies=253, mediastinal lymph node dissection=765; combined procedures with resection of trachea, carina, atrium, aorta, VCS, vena azygos, pericardium, liver, diaphragm, ribs, esophagus=192; only surgery-S=616, adjuvant chemoimmunoradiotherapy-AT=149: CAV/gemzar + cisplatin + thymalin/taktivin + radiotherapy 45-50Gy; T1=318, T2=255, T3=133, T4=59; N0=514, N1=131, N2=120, M0=765; G1=194, G2=241, G3=330; squamous=417, adenocarcinoma=298, large cell=50; early LC=212, invasive LC=553. Multivariate Cox modeling, discriminant analysis, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine any significant dependence.
RESULTS: Overall life span (LS) was 2240.1±1751.6 days and cumulative 5-year survival (5YS) reached 72.8%, 10 years – 64.2%, 20 years – 42.9%. 499 LCP lived more than 5 years (LS=3126.8±1540 days), 143 LCP – more than 10 years (LS=5083.3±1518.6 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (77.6% vs.63.1%, P=0.00001 by log-rank test). AT significantly improved 5YS (64.4% vs. 34.8%) (P=0.00003 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.038). 5YS of LCP after Lobectomies (77.6%) was significantly superior in comparison with LCP after pneumonectomies (63%) (P=0.00001 by log-rank test). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12(rank=2), thrombocytes/CC (3), erythrocytes/CC (4), eosinophils/CC (5), healthy cells/CC (6), segmented neutrophils/CC (7), lymphocytes/CC (8), monocytes/CC (9); stick neutrophils/CC (10), leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5YS of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) surgery type: lobectomy/pneumonectomy; 10) anthropometric data.
• Gastric cancer prognosis and cell ratio factors
OBJECTIVE: We examined cell ratio factors (CRF) significantly affecting gastric cancer (EC) patients GCP) survival. CRF - ratio between cancer cells (CC) and blood cells subpopulations.
METHODS: We analyzed data of 799 consecutive GCP (T1-4N0-2M0) (age=57.1±9.4 years; tumor size=5.4±3.1 cm) radically operated (R0) and monitored in 1975-2022 (m=558, f=241; total gastrectomies=173, distal gastrectomies=461; proximal gastrectomies=165; combined gastrectomies=247 with resection of esophagus, pancreas, liver, duodenum, diaphragm, colon transversum, splenectomy, etc; only surgery-S=624, adjuvant chemoimmunotherapy-AT=175 (5-FU + thymalin/taktivin); T1=238, T2=220, T3=184, T4=157; N0=437, N1=109, N2=253, M0=799; G1=222, G2=164, G3=413. Variables selected for prognosis study were input levels of 45 blood parameters, sex, age, TNMG, cell type, tumor size. Survival curves were estimated by the Kaplan-Meier method. Differences in curves between groups of GCP were evaluated using a log-rank test. Multivariate Cox modeling, discriminant analysis, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine any significant dependence.
RESULTS: Overall life span (LS) was 2128.9±2300.3 days and cumulative 5-year survival (5YS) reached 58.4%, 10 years – 51.9%, 20 years – 39%, 30 years – 27.2%. 318 GCP lived more than 5 years (LS=4304.5±2290.6 days), 169 GCP – more than 10 years (LS=5919.5±2020 days). 290 GCP died because of GC (LS=651±347.2 days). Cox modeling displayed that G CP survival significantly depended on CRF: healthy cells/CC, erythrocytes/CC, monocytes/CC, phase transition (PT) in terms of synergetics early—invasive cancer; PT N0--N12, age, G1-3, hemorrhage time, ESS, sex, AT, prothrombin index, residual nitrogen. Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early—invasive cancer (rank=1); PT N0--N12 (2); healthy cells/CC (3), erythrocytes/CC (4), thrombocytes/CC (5), monocytes/CC (6), segmented neutrophils/CC (7), leucocytes/CC (8), lymphocytes/CC (9), stick neutrophils/CC (10), eosinophils/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: GCP survival after radical procedures significantly depended on CRF.
More from Oleg Kshivets (20)
Local Advanced Lung Cancer: Artificial Intelligence, Synergetics, Complex Sys...
Local Advanced Lung Cancer: Artificial Intelligence, Synergetics, Complex Sys...
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...
Gastric Cancer: Сlinical Implementation of Artificial Intelligence, Synergeti...
Gastric Cancer: Сlinical Implementation of Artificial Intelligence, Synergeti...
Local Advanced Esophageal Cancer (T3-4N0-2M0): Artificial Intelligence, Syner...
Local Advanced Esophageal Cancer (T3-4N0-2M0): Artificial Intelligence, Syner...
Esophageal Cancer: Artificial Intelligence, Synergetics, Complex System Analy...
Esophageal Cancer: Artificial Intelligence, Synergetics, Complex System Analy...
Kshivets Oleg Optimization of Management for Esophageal Cancer Patients (T1-...
Kshivets Oleg Optimization of Management for Esophageal Cancer Patients (T1-...
Lung cancer cell dynamics significantly depended on blood cell circuit, bioch...
Lung cancer cell dynamics significantly depended on blood cell circuit, bioch...
Survival of Lung Cancer Patients after Lobectomies was Significantly Superior...
Survival of Lung Cancer Patients after Lobectomies was Significantly Superior...
Recently uploaded
Integrating Ayurveda into Parkinson’s Management: A Holistic Approach
Explore the benefits of combining Ayurveda with conventional Parkinson's treatments. Learn how a holistic approach can manage symptoms, enhance well-being, and balance body energies. Discover the steps to safely integrate Ayurvedic practices into your Parkinson’s care plan, including expert guidance on diet, herbal remedies, and lifestyle modifications.
Basavarajeeyam - Ayurvedic heritage book of Andhra pradesh
Basavarajeeyam is an important text for ayurvedic physician belonging to andhra pradehs. It is a popular compendium in various parts of our country as well as in andhra pradesh. The content of the text was presented in sanskrit and telugu language (Bilingual). One of the most famous book in ayurvedic pharmaceutics and therapeutics. This book contains 25 chapters called as prakaranas. Many rasaoushadis were explained, pioneer of dhatu druti, nadi pareeksha, mutra pareeksha etc. Belongs to the period of 15-16 century. New diseases like upadamsha, phiranga rogas are explained.
KDIGO 2024 guidelines for diabetologists
KDIGO guidelines 2024 for evaluation and management of CKD, related to diabetes and management of diabetic kidney disease
263778731218 Abortion Clinic /Pills In Harare ,
263778731218 Abortion Clinic /Pills In Harare ,ABORTION WOMEN’S CLINIC +27730423979 IN women clinic we believe that every woman should be able to make choices in her pregnancy. Our job is to provide compassionate care, safety,affordable and confidential services. That’s why we have won the trust from all generations of women all over the world. we use non surgical method(Abortion pills) to terminate…Dr.LISA +27730423979women Clinic is committed to providing the highest quality of obstetrical and gynecological care to women of all ages. Our dedicated staff aim to treat each patient and her health concerns with compassion and respect.Our dedicated group ABORTION WOMEN’S CLINIC +27730423979 IN women clinic we believe that every woman should be able to make choices in her pregnancy. Our job is to provide compassionate care, safety,affordable and confidential services. That’s why we have won the trust from all generations of women all over the world. we use non surgical method(Abortion pills) to terminate…Dr.LISA +27730423979women Clinic is committed to providing the highest quality of obstetrical and gynecological care to women of all ages. Our dedicated staff aim to treat each patient and her health concerns with compassion and respect.Our dedicated group of receptionists, nurses, and physicians have worked together as a teamof receptionists, nurses, and physicians have worked together as a team wwww.lisywomensclinic.co.za/
ABDOMINAL TRAUMA in pediatrics part one.
Abdominal trauma in pediatrics refers to injuries or damage to the abdominal organs in children. It can occur due to various causes such as falls, motor vehicle accidents, sports-related injuries, and physical abuse. Children are more vulnerable to abdominal trauma due to their unique anatomical and physiological characteristics. Signs and symptoms include abdominal pain, tenderness, distension, vomiting, and signs of shock. Diagnosis involves physical examination, imaging studies, and laboratory tests. Management depends on the severity and may involve conservative treatment or surgical intervention. Prevention is crucial in reducing the incidence of abdominal trauma in children.
Dehradun #ℂall #gIRLS Oyo Hotel 8107221448 #ℂall #gIRL in Dehradun
Dehradun #ℂall #gIRLS Oyo Hotel 8107221448 #ℂall #gIRL in Dehradun
Light House Retreats: Plant Medicine Retreat Europe
Our aim is to organise conscious gatherings and retreats for open and inquisitive minds and souls, with and without the assistance of sacred plants.
Physiology of Special Chemical Sensation of Taste
Title: Sense of Taste
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the structure and function of taste buds.
Describe the relationship between the taste threshold and taste index of common substances.
Explain the chemical basis and signal transduction of taste perception for each type of primary taste sensation.
Recognize different abnormalities of taste perception and their causes.
Key Topics:
Significance of Taste Sensation:
Differentiation between pleasant and harmful food
Influence on behavior
Selection of food based on metabolic needs
Receptors of Taste:
Taste buds on the tongue
Influence of sense of smell, texture of food, and pain stimulation (e.g., by pepper)
Primary and Secondary Taste Sensations:
Primary taste sensations: Sweet, Sour, Salty, Bitter, Umami
Chemical basis and signal transduction mechanisms for each taste
Taste Threshold and Index:
Taste threshold values for Sweet (sucrose), Salty (NaCl), Sour (HCl), and Bitter (Quinine)
Taste index relationship: Inversely proportional to taste threshold
Taste Blindness:
Inability to taste certain substances, particularly thiourea compounds
Example: Phenylthiocarbamide
Structure and Function of Taste Buds:
Composition: Epithelial cells, Sustentacular/Supporting cells, Taste cells, Basal cells
Features: Taste pores, Taste hairs/microvilli, and Taste nerve fibers
Location of Taste Buds:
Found in papillae of the tongue (Fungiform, Circumvallate, Foliate)
Also present on the palate, tonsillar pillars, epiglottis, and proximal esophagus
Mechanism of Taste Stimulation:
Interaction of taste substances with receptors on microvilli
Signal transduction pathways for Umami, Sweet, Bitter, Sour, and Salty tastes
Taste Sensitivity and Adaptation:
Decrease in sensitivity with age
Rapid adaptation of taste sensation
Role of Saliva in Taste:
Dissolution of tastants to reach receptors
Washing away the stimulus
Taste Preferences and Aversions:
Mechanisms behind taste preference and aversion
Influence of receptors and neural pathways
Impact of Sensory Nerve Damage:
Degeneration of taste buds if the sensory nerve fiber is cut
Abnormalities of Taste Detection:
Conditions: Ageusia, Hypogeusia, Dysgeusia (parageusia)
Causes: Nerve damage, neurological disorders, infections, poor oral hygiene, adverse drug effects, deficiencies, aging, tobacco use, altered neurotransmitter levels
Neurotransmitters and Taste Threshold:
Effects of serotonin (5-HT) and norepinephrine (NE) on taste sensitivity
Supertasters:
25% of the population with heightened sensitivity to taste, especially bitterness
Increased number of fungiform papillae
Novas diretrizes da OMS para os cuidados perinatais de mais qualidade
Novas diretrizes da OMS para os cuidados perinatais de mais qualidadeProf. Marcus Renato de Carvalho
Recomendações da OMS sobre cuidados maternos e neonatais para uma experiência pós-natal positiva.
Em consonância com os ODS – Objetivos do Desenvolvimento Sustentável e a Estratégia Global para a Saúde das Mulheres, Crianças e Adolescentes, e aplicando uma abordagem baseada nos direitos humanos, os esforços de cuidados pós-natais devem expandir-se para além da cobertura e da simples sobrevivência, de modo a incluir cuidados de qualidade.
Estas diretrizes visam melhorar a qualidade dos cuidados pós-natais essenciais e de rotina prestados às mulheres e aos recém-nascidos, com o objetivo final de melhorar a saúde e o bem-estar materno e neonatal.
Uma “experiência pós-natal positiva” é um resultado importante para todas as mulheres que dão à luz e para os seus recém-nascidos, estabelecendo as bases para a melhoria da saúde e do bem-estar a curto e longo prazo. Uma experiência pós-natal positiva é definida como aquela em que as mulheres, pessoas que gestam, os recém-nascidos, os casais, os pais, os cuidadores e as famílias recebem informação consistente, garantia e apoio de profissionais de saúde motivados; e onde um sistema de saúde flexível e com recursos reconheça as necessidades das mulheres e dos bebês e respeite o seu contexto cultural.
Estas diretrizes consolidadas apresentam algumas recomendações novas e já bem fundamentadas sobre cuidados pós-natais de rotina para mulheres e neonatos que recebem cuidados no pós-parto em unidades de saúde ou na comunidade, independentemente dos recursos disponíveis.
É fornecido um conjunto abrangente de recomendações para cuidados durante o período puerperal, com ênfase nos cuidados essenciais que todas as mulheres e recém-nascidos devem receber, e com a devida atenção à qualidade dos cuidados; isto é, a entrega e a experiência do cuidado recebido. Estas diretrizes atualizam e ampliam as recomendações da OMS de 2014 sobre cuidados pós-natais da mãe e do recém-nascido e complementam as atuais diretrizes da OMS sobre a gestão de complicações pós-natais.
O estabelecimento da amamentação e o manejo das principais intercorrências é contemplada.
Recomendamos muito.
Vamos discutir essas recomendações no nosso curso de pós-graduação em Aleitamento no Instituto Ciclos.
Esta publicação só está disponível em inglês até o momento.
Prof. Marcus Renato de Carvalho
www.agostodourado.com
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists
Preoperative Management of Patients on GLP-1 Receptor Agonists like Ozempic and Semiglutide
ASA GUIDELINE
NYSORA Guideline
2 Case Reports of Gastric Ultrasound
Physiology of Chemical Sensation of smell.pdf
Title: Sense of Smell
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the primary categories of smells and the concept of odor blindness.
Explain the structure and location of the olfactory membrane and mucosa, including the types and roles of cells involved in olfaction.
Describe the pathway and mechanisms of olfactory signal transmission from the olfactory receptors to the brain.
Illustrate the biochemical cascade triggered by odorant binding to olfactory receptors, including the role of G-proteins and second messengers in generating an action potential.
Identify different types of olfactory disorders such as anosmia, hyposmia, hyperosmia, and dysosmia, including their potential causes.
Key Topics:
Olfactory Genes:
3% of the human genome accounts for olfactory genes.
400 genes for odorant receptors.
Olfactory Membrane:
Located in the superior part of the nasal cavity.
Medially: Folds downward along the superior septum.
Laterally: Folds over the superior turbinate and upper surface of the middle turbinate.
Total surface area: 5-10 square centimeters.
Olfactory Mucosa:
Olfactory Cells: Bipolar nerve cells derived from the CNS (100 million), with 4-25 olfactory cilia per cell.
Sustentacular Cells: Produce mucus and maintain ionic and molecular environment.
Basal Cells: Replace worn-out olfactory cells with an average lifespan of 1-2 months.
Bowman’s Gland: Secretes mucus.
Stimulation of Olfactory Cells:
Odorant dissolves in mucus and attaches to receptors on olfactory cilia.
Involves a cascade effect through G-proteins and second messengers, leading to depolarization and action potential generation in the olfactory nerve.
Quality of a Good Odorant:
Small (3-20 Carbon atoms), volatile, water-soluble, and lipid-soluble.
Facilitated by odorant-binding proteins in mucus.
Membrane Potential and Action Potential:
Resting membrane potential: -55mV.
Action potential frequency in the olfactory nerve increases with odorant strength.
Adaptation Towards the Sense of Smell:
Rapid adaptation within the first second, with further slow adaptation.
Psychological adaptation greater than receptor adaptation, involving feedback inhibition from the central nervous system.
Primary Sensations of Smell:
Camphoraceous, Musky, Floral, Pepperminty, Ethereal, Pungent, Putrid.
Odor Detection Threshold:
Examples: Hydrogen sulfide (0.0005 ppm), Methyl-mercaptan (0.002 ppm).
Some toxic substances are odorless at lethal concentrations.
Characteristics of Smell:
Odor blindness for single substances due to lack of appropriate receptor protein.
Behavioral and emotional influences of smell.
Transmission of Olfactory Signals:
From olfactory cells to glomeruli in the olfactory bulb, involving lateral inhibition.
Primitive, less old, and new olfactory systems with different path
The Electrocardiogram - Physiologic Principles
These lecture slides, by Dr Sidra Arshad, offer a quick overview of the physiological basis of a normal electrocardiogram.
Learning objectives:
1. Define an electrocardiogram (ECG) and electrocardiography
2. Describe how dipoles generated by the heart produce the waveforms of the ECG
3. Describe the components of a normal electrocardiogram of a typical bipolar lead (limb II)
4. Differentiate between intervals and segments
5. Enlist some common indications for obtaining an ECG
6. Describe the flow of current around the heart during the cardiac cycle
7. Discuss the placement and polarity of the leads of electrocardiograph
8. Describe the normal electrocardiograms recorded from the limb leads and explain the physiological basis of the different records that are obtained
9. Define mean electrical vector (axis) of the heart and give the normal range
10. Define the mean QRS vector
11. Describe the axes of leads (hexagonal reference system)
12. Comprehend the vectorial analysis of the normal ECG
13. Determine the mean electrical axis of the ventricular QRS and appreciate the mean axis deviation
14. Explain the concepts of current of injury, J point, and their significance
Study Resources:
1. Chapter 11, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 9, Human Physiology - From Cells to Systems, Lauralee Sherwood, 9th edition
3. Chapter 29, Ganong’s Review of Medical Physiology, 26th edition
4. Electrocardiogram, StatPearls - https://www.ncbi.nlm.nih.gov/books/NBK549803/
5. ECG in Medical Practice by ABM Abdullah, 4th edition
6. Chapter 3, Cardiology Explained, https://www.ncbi.nlm.nih.gov/books/NBK2214/
7. ECG Basics, http://www.nataliescasebook.com/tag/e-c-g-basics
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journey
Tom Selleck, an enduring figure in Hollywood. has captivated audiences for decades with his rugged charm, iconic moustache. and memorable roles in television and film. From his breakout role as Thomas Magnum in Magnum P.I. to his current portrayal of Frank Reagan in Blue Bloods. Selleck's career has spanned over 50 years. But beyond his professional achievements. fans have often been curious about Tom Selleck Health. especially as he has aged in the public eye.
Follow us on: Pinterest
Introduction
Many have been interested in Tom Selleck health. not only because of his enduring presence on screen but also because of the challenges. and lifestyle choices he has faced and made over the years. This article delves into the various aspects of Tom Selleck health. exploring his fitness regimen, diet, mental health. and the challenges he has encountered as he ages. We'll look at how he maintains his well-being. the health issues he has faced, and his approach to ageing .
Early Life and Career
Childhood and Athletic Beginnings
Tom Selleck was born on January 29, 1945, in Detroit, Michigan, and grew up in Sherman Oaks, California. From an early age, he was involved in sports, particularly basketball. which played a significant role in his physical development. His athletic pursuits continued into college. where he attended the University of Southern California (USC) on a basketball scholarship. This early involvement in sports laid a strong foundation for his physical health and disciplined lifestyle.
Transition to Acting
Selleck's transition from an athlete to an actor came with its physical demands. His first significant role in "Magnum P.I." required him to perform various stunts and maintain a fit appearance. This role, which he played from 1980 to 1988. necessitated a rigorous fitness routine to meet the show's demands. setting the stage for his long-term commitment to health and wellness.
Fitness Regimen
Workout Routine
Tom Selleck health and fitness regimen has evolved. adapting to his changing roles and age. During his "Magnum, P.I." days. Selleck's workouts were intense and focused on building and maintaining muscle mass. His routine included weightlifting, cardiovascular exercises. and specific training for the stunts he performed on the show.
Selleck adjusted his fitness routine as he aged to suit his body's needs. Today, his workouts focus on maintaining flexibility, strength, and cardiovascular health. He incorporates low-impact exercises such as swimming, walking, and light weightlifting. This balanced approach helps him stay fit without putting undue strain on his joints and muscles.
Importance of Flexibility and Mobility
In recent years, Selleck has emphasized the importance of flexibility and mobility in his fitness regimen. Understanding the natural decline in muscle mass and joint flexibility with age. he includes stretching and yoga in his routine. These practices help prevent injuries, improve posture, and maintain mobilit
Recently uploaded (20)
Integrating Ayurveda into Parkinson’s Management: A Holistic Approach
Integrating Ayurveda into Parkinson’s Management: A Holistic Approach
Basavarajeeyam - Ayurvedic heritage book of Andhra pradesh
Basavarajeeyam - Ayurvedic heritage book of Andhra pradesh
Triangles of Neck and Clinical Correlation by Dr. RIG.pptx
Triangles of Neck and Clinical Correlation by Dr. RIG.pptx
Dehradun #ℂall #gIRLS Oyo Hotel 8107221448 #ℂall #gIRL in Dehradun
Dehradun #ℂall #gIRLS Oyo Hotel 8107221448 #ℂall #gIRL in Dehradun
Light House Retreats: Plant Medicine Retreat Europe
Light House Retreats: Plant Medicine Retreat Europe
Novas diretrizes da OMS para os cuidados perinatais de mais qualidade
Novas diretrizes da OMS para os cuidados perinatais de mais qualidade
Temporomandibular Joint By RABIA INAM GANDAPORE.pptx
Temporomandibular Joint By RABIA INAM GANDAPORE.pptx
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journey
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journey
Kshivets O. Cancer, Synergetics, Computer Sciences and Alive Supersystems
- 1. Early Detection and Phase Transitions in System “Malignancy-Human Organism” Oleg Kshivets, M.D., Ph.D. Siauliai Cancer Center , Lithuania AACR Special Conference: The Biology and Genetics of Early Detection & Chemoprevention of Cancer Miami, Florida, The USA, 1999
- 4. Prognostic Role of Cancer Diameter
- 8. Regularities between Dynamics Cancer Cell Population and Patient's Survival Rate
- 9. Phase Transitions in System «Homeostasis-Malignancy»
- 10. The Three Phase Transitions in the System «Malignancy-Human’s Organism»
- 11. Phase Transition Early Malignancy into Invasive Cancer
- 12. Role of Cell Ratio Factors in Phaze Transition Erly Cancer into Invasive Cancer
- 13. Regression Models (Lym/CC--Life Span of GCP, n=224; BCP, n=120 and LCP, n=162; 18th Degree Polynomial Fit): y=a+bx+cx 2 +dx 3 +...
- 14. Cell Ratio Factors in Prognosis 5-Year Survival Cancer Patients
- 15. Results of Monte Carlo Simulation
- 16. Results of Structural Equotion Modeling
- 17. Early and Differential Diagnosis of Malignancies
- 18. The Results of Multiple Correspondence and Claster Analysis of Blood Indexes in Oncoscreening
- 19. Interdependencies between Blood Parameters, Indexes and Cancer Cell Population
- 20. Interdependencies between Blood Indexes and Immune System of Cancer Patients
- 21. Networks Between Phase Transition “Early Cancer-Invasive Cancer”, Life Span and Homeostasis Data