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Analysis of High-Order Residual-Based Dissipation for Unsteady Compressible F...kgrimich
A comprehensive study of the numerical properties of high-order residual-based dissipation terms for unsteady compressible flows leads to the design of well-behaved, low dissipative schemes of third-, fifth- and seventh-order accuracy. The dissipation and dispersion properties of the schemes are then evaluated theoreticaly, through Fourier space analysis, and numerically, through selected test cases including the inviscid Taylor-Green Vortex flow.
Analysis of High-Order Residual-Based Dissipation for Unsteady Compressible F...kgrimich
A comprehensive study of the numerical properties of high-order residual-based dissipation terms for unsteady compressible flows leads to the design of well-behaved, low dissipative schemes of third-, fifth- and seventh-order accuracy. The dissipation and dispersion properties of the schemes are then evaluated theoreticaly, through Fourier space analysis, and numerically, through selected test cases including the inviscid Taylor-Green Vortex flow.
ElogPoct: A Tool for Lipophilicity Determination in Drug DiscoveryBrian Bissett
ElogPoct: A Tool for Lipophilicity Determination in Drug Discovery
Franco Lombardo,Marina Y. Shalaeva, Karl A. Tupper,Feng Gao, and Michael H. Abraham
Molecular Properties Group and Mathematical and Statistical Sciences Group, Central Research Division,
Pfizer Inc., Groton, Connecticut 06340, and Department of Chemistry, University College London, 20 Gordon Street,
London, United Kingdom WC1H OAJ
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I received a nice acknowledgement in this paper.
ElogDoct: A Tool for Lipophilicity Determination in Drug Discovery. 2. Basic and Neutral Compounds
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Molecular Properties Group and Mathematical and Statistical Sciences Group, Pfizer Global Research and Development
Hyphenated Techniques - coupling of a separation technique and an on-line spectroscopic detection technology.
Advantages of hyphenated techniques;
1. Fast and accurate analysis.
2. Higher degree of automation.
3. Higher sample throughput.
4. Better reproducibility.
5. Reduction of contamination due to its closed system.
6. Separation and quantification achieved at same time.
Quantitative Analysis of Oligonucleotides in Human Muscle Tissue Using Liquid...Covance
APA 2019 -- Duchenne muscular dystrophy (DMD) is a rare X-linked recessive neuromuscular disease characterized by progressive severe muscle wasting and weakness. DMD is ultimately fatal, with patients typically dying from respiratory or cardiac complications in their mid- to late-20s. Exon skipping by phosphorodiamidate morpholino oligomer (PMO) is considered a promising, disease-modifying approach to treat the underlying cause of DMD. PMO was conjugated to a proprietary peptide to enhance tissue uptake, providing a PPMO. This poster describes the development and validation of a sensitive, selective and high-throughput liquid chromatography-tandem high resolution-accurate mass (LC/HR-AM) method for the quantitation of the PPMO in human muscle tissue using an analogue as the internal standard (ISTD). A key modification to the PMO is the addition of a proprietary peptide that provides specificity to binding and due to the metabolism of the peptide several entities of the PMO will be present in the muscle tissue, in order to quantitate the total amount of the PPMO in the muscle. The extraction undergoes a peptide digestion step to form an end product of PMO-A prior to the analysis.
This presentation describes the operation and application of the Waters APGC (Atmospheric Pressure Gas Chromatography) ion source which provides a highly sensitive GC-MS, MS/MS capability for tandem quadrupole and time of flight MS systems. It is very easy to swap between APGC, Electrospray (for UPLC) and other ion sources without instrument venting in minutes.
APGC provides significant performance advantages over traditional GC/MS ionisation methods, giving high sensitivity and less fragmented spectra.
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Peptides as a therapeutic method attract much attention due to the synthetic accessibility, high degree of specific binding, and the ability to target protein surfaces traditionally considered "undruggable". Macrocyclic peptides possess a lot of pharmacological characteristics distinct from other well-established therapeutic
molecular classes, resulting in a versatile drug modality with a unique profile of advantages. https://www.medicilon.com/services/biology-services/
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http://www.ihtsdo.org/show13/abstract14.pdf
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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 leads (limb II)
4. Differentiate between intervals and segments
5. Enlist some common indications for obtaining an ECG
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. ECG Basics, http://www.nataliescasebook.com/tag/e-c-g-basics
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is the oldest recreational drug and likely contributes to more morbidity,
mortality, and public health costs than all illicit drugs combined. The
5th edition of the Diagnostic and Statistical Manual of Mental Disorders
(DSM-5) integrates alcohol abuse and alcohol dependence into a single
disorder called alcohol use disorder (AUD), with mild, moderate,
and severe subclassifications (American Psychiatric Association, 2013).
In the DSM-5, all types of substance abuse and dependence have been
combined into a single substance use disorder (SUD) on a continuum
from mild to severe. A diagnosis of AUD requires that at least two of
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AUD: 2–3 criteria; moderate AUD: 4–5 criteria; severe AUD: 6–11 criteria).
The four main behavioral effects of AUD are impaired control over
drinking, negative social consequences, risky use, and altered physiological
effects (tolerance, withdrawal). This chapter presents an overview
of the prevalence and harmful consequences of AUD in the U.S.,
the systemic nature of the disease, neurocircuitry and stages of AUD,
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pharmacotherapies for AUD.
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EATING DISORDERS (Psychiatry-7)by dr Shivam sharma.pptxShivam Sharma
For any queries ,contact shvmshrm@outlook.com
---
## Introduction to Eating Disorders
Welcome to this comprehensive presentation on Eating Disorders, a critical and often misunderstood area of mental health. This presentation is designed to provide in-depth knowledge and insights into the various aspects of eating disorders, making it valuable for both postgraduate medical aspirants preparing for the INI-CET and the general public seeking to understand these complex conditions.
### Objectives:
1. **Understanding Eating Disorders**: Gain a clear understanding of what eating disorders are, their types, and their distinguishing characteristics.
2. **Etiology and Risk Factors**: Explore the underlying causes and risk factors that contribute to the development of eating disorders.
3. **Clinical Features and Diagnosis**: Learn about the clinical features, diagnostic criteria, and the importance of early detection.
4. **Management and Treatment**: Review the current approaches to managing and treating eating disorders, including medical, psychological, and nutritional interventions.
5. **Prevention and Awareness**: Discuss strategies for prevention, early intervention, and increasing awareness about eating disorders.
This presentation aims to bridge the gap between academic knowledge and practical understanding, providing you with the tools to recognize, diagnose, and effectively manage eating disorders. Whether you are preparing for a medical exam or seeking to educate yourself or others about these serious conditions, this presentation will equip you with essential information and practical insights.
Let's begin our journey into understanding eating disorders and the significant impact they have on individuals and society.
---
For any queries ,contact shvmshrm@outlook.com
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Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...Oleg Kshivets
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.
Quality Assurance in LOINC® using Description Logic
1. Quality Assurance in LOINC®
using Description Logic
Tomasz Adamusiak MD PhD
Postdoc at NIH NLM LHC CgSB
10/11 – 03/12
2. Objective
Identify areas for improvement in LOINC by
changing its representation to OWL DL and
comparing its classification to that of
SNOMED CT
2
3. Why do it the hard way?
Rector, A. L., & Brandt, S. Why do it the hard
way? (2008) The case for an expressive
description logic for SNOMED.
More flexibility in a more expressive language
A uniform, clear, and understandable schema
Modularisation
Access to standard tooling developed by the
wider Semantic Web and OWL communities
Protégé, OWL API
3
6. Web Ontology Language (OWL)
Manchester Syntax
Class: VegetarianPizza
EquivalentTo:
Pizza and
not (hasTopping some FishTopping) and
not (hasTopping some MeatTopping)
DisjointWith:
NonVegetarianPizza
6
7. A number of papers explored LOINC
SNOMED CT integration and DL
Dolin, R. H., Huff, S. M., Rocha, R. A., Spackman, K. A.,
& Campbell, K. E. (1998). Evaluation of a “lexically
assign, logically refine” strategy for semi-automated
integration of overlapping terminologies.
Spackman, K. A. (1998). Integrating sources for a
clinical reference terminology: experience linking
SNOMED to LOINC and drug vocabularies.
Srinivasan A. et al. (2006). Semantic web
representation of LOINC: an ontological perspective.
Bodenreider, O. (2008). Issues in mapping LOINC
laboratory tests to SNOMED CT.
7
8. Quality Assurance in literature
Geller et al. (2009). Special issue on auditing of terminologies.
Journal of biomedical informatics
Bodenreider, O., & Peters, L. B. (2009). A graph-based approach to
auditing RxNorm.
Wei, D., & Bodenreider, O. (2010). Using the abstraction network in
complement to description logics for quality assurance in
biomedical terminologies - a case study in SNOMED CT.
Rector, A., & Iannone, L. (2011). Lexically suggest, logically define:
Quality assurance of the use of qualifiers and expected results of
post-coordination in SNOMED CT.
Lin, M. C., Vreeman, D. J., McDonald, C. J., & Huff, S. M. (2012).
Auditing consistency and usefulness of LOINC use among three
large institutions - Using version spaces for grouping LOINC codes.
8
9. A universal code system for identifying
laboratory and clinical observations
9
10. LOINC codes consist of parts
Code:
2160-0 Creatinine [Mass/volume] in Serum or Plasma
Parts:
Part Type Part No. Part Name
Component LP14355-9 Creatinine
Property LP6827-2 MCnc [Mass Concentration]
Time LP6960-1 Pt [Point in time (spot)]
System LP7576-4 Ser/Plas [Serum or Plasma]
Scale LP7753-9 Qn
10
12. We used part links to create logical
definitions for codes
Code:
2160-0 Creatinine [Mass/volume] in Serum or Plasma
Parts:
Part Type Part Name DL definition:
Component Creatinine (has_component some Creatinine) and
Property MCnc (has_property some MCnc) and
Time Pt (has_time_aspect some Pt ) and
System Ser/Plas (has_system some Ser/Plas) and
Scale Qn (has_scale some Qn)
12
13. Component 2nd subpart: challenge
Code:
1558-6 Fasting glucose [Mass/volume] in Serum or Plasma
Parts:
Part Type Part No. Part Name
Component LP14635-4 Glucose
Challenge LP20355-1 post CFst
Property LP6827-2 MCnc [Mass Concentration]
Time LP6960-1 Pt [Point in time (spot)]
System LP7576-4 Ser/Plas [Serum or Plasma]
Scale LP7753-9 Qn
13
14. Component 3rd subpart: adjustment
Code:
23811-3 Alpha-1-Fetoprotein [Multiple of the median]
adjusted in Serum or Plasma
Parts:
Part Type Part No. Part Name
Component LP14331-0 Alpha-1-Fetoprotein
Adjustment LP20174-6 adjusted
Property LP71590-1 MoM [Multiple of the median]
Time LP6960-1 Pt [Point in time (spot)]
System LP7576-4 Ser/Plas [Serum or Plasma]
Scale LP7753-9 Qn
14
15. LOINC parts are not available in the
public release (2.36)
Part
Codes Parts
Links
Multiaxial
hierarchy
15
17. Multiaxial hierarchy in LOINC could be
vastly improved with DL
Type
Screenshot from the Regenstrief LOINC Mapping Assistant (RELMA)
17
18. Type
Multiaxial hierarchy in LOINC could be
vastly improved with DL
18
19. Separated codes and parts and defined
corresponding observations
OBS
Glucose
Glucose
Glucose |
OBS Glucose|
Urine
Urine
Urine
Glucose in 10
hour Urine
Glucose in Protein & Glucose
Urine by Test panel in Urine by
Test strip
strip
Multiaxial
19
20. Separated codes and parts and defined
corresponding observations
Glucose
OBS ≡
Glucose
Glucose |
Urine
OBS Glucose| ≡
Urine Urine
Glucose in 10 ≡
hour Urine
Glucose in ≡
Urine by Test
Protein & Glucose
panel in Urine by
≡
Test strip
strip
Multiaxial Inferred
20
21. SNOMED CT compensates for missing
parts relations in LOINC
Body fluid owl:EquivalentTo Body fluid
LP30504-2 32457005
Body Fluids C0005889
ISA
Urine owl:EquivalentTo Urine
LP7681-2 78014005
Urine C0042036
21
22. SNOMED CT compensates for missing
parts relations in LOINC
Body fluid
LP30504-2
32457005
Body Fluids C0005889
ISA
Urine
LP7681-2
78014005
Urine C0042036
22
23. We can identify semantically
equivalent LOINC parts via UMLS
Erythrocyte Erythrocytes
LP16699-8 LP14304-7
RBC
LP7536-8
Erythrocytes C0014792
23
24. We can identify semantically
equivalent LOINC parts via UMLS
Erythrocytes
RBC
Erythrocyte
LP14304-7
LP7536-8
LP16699-8
Erythrocytes C0014792
24
25. Reasoner infers logical consequences
from a set of asserted facts or axioms
≡
OBS Glucose has_component some Glucose and
| Urine has_system some Urine
DL definition
Inferred
≡
Glucose in 10
has_component some Glucose and
has_property some Arbitrary Concentration and
has_time_aspect some Point in time (spot) and
hour Urine has_system some Urine and
has_scale some Ord and
has_method some Test strip
DL definition
25
29. a) LOINC codes
CD3-CD56+
cells/100 cells in
Cerebral spinal b) Linked parts
fluid (56897-2) LP19037-8:Cells.CD3+CD56+
CD3+CD56+ LP35646-6:Cells.CD3-CD56+
cells/100 cells in
Cerebral spinal
fluid (51279-8) LOINC
c) DL definition
…
and (has_component some Cells.CD3+CD56+)
and (has_component some Cells.CD3-CD56+)
29
30. Also visible in LOINC browser/RELMA
http://s.details.loinc.org/LOINC/56897-2.html?sections=Comprehensive
30
31. Inconsistencies in part hierarchy result
in incorrect inference
Monocytes+Macrophages
LP14312-0
Monocytes+Macrophages Macrophages
/100 leukocytes in Peritoneal /100 leukocytes in Peritoneal
fluid by Manual count
ISA fluid by Manual count
(32029-1) (40517-5)
Macrophages
LP14314-6
31
32. Pop quiz: removing which has_component
relation changes equivalence to subsumption?
Monocytes+Macrophages
LP14312-0
Monocytes+Macrophages Macrophages
/100 leukocytes in Peritoneal /100 leukocytes in Peritoneal
fluid by Manual count
ISA fluid by Manual count
(32029-1) (40517-5)
Macrophages
LP14314-6
32
33. Issues with referential integrity
*
LP28805-7
Type of Enema device Type of Enema device
(8950-8) (8932-6)
Enema device
LP7209-2
33
35. a) LOINC codes b) Linked parts
Helmet cells [Presence] LP14570-3:Helmet cells
in Blood by Light LP14738-6:Cells
microscopy (10374-7)
Schistocytes [Presence]
in Blood by Light LP29945-0:Schistocytes
microscopy (800-3)
LOINC
c) DL definitions
(has_component some 'Helmet cells') (has_component some Schistocytes)
and (has_component some Cells)
d) Mappings
SCT_70310009: Helmet cell
is_a SCT_362837007:Entire cell SNOMED CT
35
37. Inferred nodes are better connected
locally
1000
LOINC
Inferred
Logarithm of average connectivity
100
10
1
1 10 100 1000 10000
Logarithm of number of neighbours
37
39. ¡¿Find all carbohydrate observations?!
Everything
else
Gene tests
Here Be Dragons
HPA tests
HLA tests Patient
information
Skin tests
Evaluation and
management
40. It is not easy
Here Be
Everything
Dragons
else
Gene tests
Here Be Dragons
HPA tests
HLA tests Patient
information
Skin tests
Evaluation and
management
45. No direct path between Carbohydrates
| Urine and Glucose | Urine originally
45
46. 239 LOINC codes were found to be
inconsistenly asserted in the hierarchy
183 concepts of scale type Document
28626-0:History and physical
note:Find:Pt:Setting:Doc:Physician
Asserted History and physical note
Inferred Note
Mostly insufficient modelling
46
48. LOINC curators are doing a splendid
job and the terminology is consistent
Significance of DL
1. Error detection
a) Duplicates
b) Missing hierarchical relations
c) Inconsistencies in hierarchy
2. Enhanced navigation
3. Enhanced subsumption
4. Maintenance
48
49. Recommendations
1. Create logical definitions for codes
2. Have an inferred hierarchy
3. Parts vs. codes
4. Alignment with SNOMED CT
49
50. What does it mean to have several
parts in LOINC map to SNOMED CT?
SCT_3711007:Structure of great blood vessel
(organ)
SYSTEM LP7303-3:Heart.great vessels
SYSTEM LP33690-6:Great vessel
SYSTEM LP30622-2:Great vessels
SCT_66019005:Limb structure
COMPONENT LP121777-9:Extremity
SYSTEM LP7216-7:Extremities
SYSTEM LP7395-9:Limbs
SYSTEM LP29945-0:Extremity
50
51. Limitations
Relying on UMLS to provide mappings
Imposing a specific ontological commitment
Modelling with conjunctions likely suboptimal
for more complex observations
51
53. Acknowledgments
Olivier Bodenreider MD PhD (mentor)
Bastien Rance PhD
Rainer Winnenburg PhD
Clement McDonald MD
Daniel J. Vreeman PT DPT MSc
(Regenstrief Institute)
This work was supported by the Intramural Research Program of the National Institutes of Health
(NIH), National Library of Medicine (NLM) and the Oak Ridge Institute for Science and Education (ORISE)
Training Program in Clinical Informatics managed for the U.S. Department of Energy (DOE) by Oak Ridge
Associated Universities (ORAU).
53