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1.
Ann Biol Clin (Paris). 2019 Aug 1;77(4):422-428. doi: 10.1684/abc.2019.1462.

Can the 72-hour rule based on "Blast/Abn Lymph" flag on Sysmex XN-10 optimize the workflow in hematology laboratory?

Author information

1
Department of laboratory medicine-hematology, Cliniques universitaires Saint-Luc and Université catholique de Louvain, Brussels, Belgium.
2
Department of laboratory medicine-hematology, Assistance publique-Hôpitaux de Paris, Paris, France.
3
Laboratory of hematology, Centre hospitalier universitaire, Caen, France.

Abstract

Despite the continuing improvement of automated blood cell counters, confirmation by blood smear examination remains the gold standard in case of anomalies. With a constant goal of standardisation, different experts committees (e.g. the French-speaking cellular hematology group (Groupe francophone d'hématologie cellulaire, GFHC and the ISLH International society for laboratory hematology) recently published criteria for microscopic analysis of blood smears. Cornet et al. evaluated the application of those criteria and propose to suppress any review for 72 hours when a "Blast/Abn lymph" flag is triggered for a sample with no abnormal cell on the microscopic review. The aims of our study were to retrospectively evaluate whether this 72-hour rule adequately operates and whether it is possible to extend the arbitrary 72-hour timeframe to 96h and 144h. To achieve this goal, 40,688 blood samples were collected from three French-speaking hospitals. 1,548 samples presented an isolated "Blast/Abn lymph" flag. Only 221 samples presented the application of the 72-hour rule at least once for our study period. We were able to extend this rule to 144 hours for 10 samples of them. All blood smears for which the rule was applied were verified and there was no abnormal cell on smears at 72 and 144 hours. In conclusion, the 72-hour rule derived from the GFHC's criteria is secure and reduces the slide review rate and thus the production costs and the turnaround time of hemogram results. Further investigations could confirm that its extension to 144 hours is also adequate.

KEYWORDS:

72-hour rule; Blast/Abn lymph; XN-10; blood smear; flag

2.
Comput Methods Programs Biomed. 2019 Sep;178:145-153. doi: 10.1016/j.cmpb.2019.06.020. Epub 2019 Jun 18.

Pediatric population health analysis of southern and central Illinois region: A cross sectional retrospective study using association rule mining and multiple logistic regression.

Author information

1
University of Illinois at Springfield, Department of Computer Science, United States. Electronic address: esahe2@uis.edu.
2
Office of Population Science and Policy, Southern Illinois University School of Medicine, United States. Electronic address: svohra97@siumed.edu.
3
University of Illinois at Springfield, Department of Computer Science, United States. Electronic address: yguo56@uis.edu.
4
Office of Population Science and Policy, Southern Illinois University School of Medicine, United States. Electronic address: afogleman@siumed.edu.
5
Office of Population Science and Policy, Southern Illinois University School of Medicine, United States. Electronic address: rpate307@uis.edu.

Abstract

BACKGROUND:

Southern Illinois University School of Medicine (SIUSOM) collects large amounts of data every day. SIUSOM and other similar healthcare systems are always looking for better ways to use the data to understand and address population level problems. The purpose of this study is to analyze the administrative dataset for pediatric patients served by Southern Illinois University School of Medicine (SIUSOM) to uncover patterns that correlate specific demographic information to diagnoses of pediatric diseases. The study uses a cross-sectional database of medical billing information for all pediatric patients served by SIUSOM between June 2013 and December 2016. The dataset consists of about 980.9K clinical visits for 65.4K unique patients and includes patient demographic identifiers such as their sex, date of birth, race, anonymous zipcode and primary and secondary insurance plan as well as the related pediatric diagnosis codes. The goal is to find unknown correlations in this database.

METHOD:

We proposed a two step methodology to derive unknown correlations in SIUSOM administrative database. First, Class association rule mining was used as a well-established data mining method to generate hypothesis and derive associations of the form D → M, where D is diagnosis code of a pediatric disease and M is a patient demographic identifier (age,sex, anonymous zipcode, insurance plan, or race). The resulting associations were pruned and filtered using measures such as lift, odds ratio, relative risk, and confidence. The final associations were selected by a pediatric doctor based on their clinical significance. Second,each association rule in the final set was further validated and adjusted odds ratios were obtained using multiple logistic regression.

RESULTS:

Several associations were found correlating specific patients' residential zip codes with the diagnosis codes for viral hepatitis carrier, exposure to communicable diseases, screening for mental and developmental disorder in childhood, history allergy to medications, disturbance of emotions specific to childhood, and acute sinusitis. In addition, the results show that African American patients are more likely to be screened for mental and developmental disorders compared to White patients for SIUSOM pediatric population (Odds Ratio (OR):3.56, 95% Confidence Interval (CI):[3.29,3.85]).

CONCLUSION:

Class association rule mining is an effective method for detecting signals in a large patient administrative database and generating hypotheses which correlate patients' demographics with diagnosis of pediatric diseases. A post processing of the hypotheses generated by this method is necessary to prune spurious associations and select a set of clinically relevant hypotheses.

KEYWORDS:

Data mining; Medical billing database; Pediatric diseases risk factors; Population health analysis

3.
Nature. 2019 Aug;572(7769):312. doi: 10.1038/d41586-019-02429-3.

Rule out conflicts of interest in psychology awards.

KEYWORDS:

Ethics; Psychology

Publication type

Publication type

4.
Neuroimage. 2019 Aug 10:116088. doi: 10.1016/j.neuroimage.2019.116088. [Epub ahead of print]

The effect of rule retrieval on activity in the default mode network.

Author information

1
Medical Research Council Cognition and Brain Sciences Unit, United Kingdom; University of Cambridge, United Kingdom. Electronic address: Verity.Smith@mrc-cbu.cam.ac.uk.
2
Medical Research Council Cognition and Brain Sciences Unit, United Kingdom; University of Cambridge, United Kingdom.
3
Medical Research Council Cognition and Brain Sciences Unit, United Kingdom; University of Cambridge, United Kingdom; University of Oxford, United Kingdom.

Abstract

The default mode network (DMN) is often associated with internally-directed cognition, distinct from the constraints of the external environment. However, a recent finding is that the DMN shows strong activation after large task switches during a demanding externally-directed task (Crittenden et al., 2015; Smith et al., 2018). Following other proposals, we have suggested that the DMN encodes cognitive or environmental context, and that context representations are momentarily strengthened during large cognitive switches, perhaps so that new activity can be checked against current environmental constraints. An alternative account, consistent with the role of the DMN in episodic memory, might be that switches to a substantially new task increase demands on rule retrieval. To test this alternative, we directly manipulated rule retrieval demands. Contrary to the retrieval account, increased retrieval demand led to reduced DMN activity, accompanied by increased activation in prefrontal and lateral parietal cognitive control areas. Unlike episodic retrieval, with its rich contextual representations, rule retrieval does not drive DMN activity. Accordingly, it cannot explain increased DMN activity during large cognitive switches.

KEYWORDS:

Cognitive control; DMN; fMRI

5.
J Cell Biochem. 2019 Aug 12. doi: 10.1002/jcb.29326. [Epub ahead of print]

N-end rule pathway inhibitor sensitizes cancer cells to antineoplastic agents by regulating XIAP and RAD21 protein expression.

Author information

1
Department of Applied Biology, CSIR-Indian Institute of Chemical Technology, Hyderabad, India.
2
Life Science Division, Institute of Advanced Study in Science and Technology, Guwahati, Assam, India.
3
Department of Pharmaceutical Sciences, Wayne State University, Detroit, Michigan.
4
Department of Chemical Engineering, Arizona State University, Tempe, Arizona.
5
Department of Integrative Medical Sciences, Northeast Ohio Medical University (NEOMED), Rootstown, Ohio.

Abstract

Anticancer drugs exert their effects on cancer cells by deregulating many pathways linked to cell cycle, apoptosis, etc. but cancer cells gradually become resistive against anticancer drugs, thereby necessitating the development of newer generation anticancer molecules. N-end rule pathway has been shown to be involved in the degradation of many cell cycle and apoptosis-related proteins. However, the involvements of this pathway in cancer are not well established. Recently, we developed a non-peptide-based N-end rule pathway inhibitor, RF-C11 for type 1 and 2 recognition domains of E3 ubiquitin ligases. The inhibitor significantly increased the half-life of potential N-degrons leading to significant physiological changes in vivo. We hypothesized RF-C11 may be used to decipher the N-end rule pathway's role in cancer towards the development of anticancer therapeutics. In this study, we showed that RF-C11, barring noncancer cells, significantly sensitizes cancer cells towards different anticancer agents tested. We further find that the profound cellular sensitization to anticancer drugs was affected by (a) downregulation of X-linked inhibitor of apoptosis protein, an antiapoptotic protein and (b) by stabilization of RAD21, and thereby inhibiting metaphase to anaphase promotion. The study shows that RF-C11 or its analogs may be used as a novel additive in combination therapy against cancer.

KEYWORDS:

N-end rule; RAD21; UBR1; XIAP; cancer; drug sensitivity

PMID:
31407360
DOI:
10.1002/jcb.29326
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6.
J Emerg Med. 2019 Aug 9. pii: S0736-4679(19)30467-6. doi: 10.1016/j.jemermed.2019.06.010. [Epub ahead of print]

Thoracolumbar Evaluation in the Low-Risk Trauma Patient: A Pilot Study Towards Development of a Clinical Decision Rule to Avoid Unnecessary Imaging in the Emergency Department.

Author information

1
Department of Emergency Medicine, Jackson Memorial Hospital, Miami, Florida.
2
University of Miami Miller School of Medicine, Miami, Florida.

Abstract

BACKGROUND:

Thoracolumbar (TL) injury is a common finding in the severely injured multi-trauma patient. However, the incidence and pattern of TL injury in patients with milder trauma is unclear.

OBJECTIVE:

The aim of this study was to collect and analyze evidence for the development of a clinical decision rule (CDR) to evaluate the TL spine in patients with non-severe blunt trauma and avoid dedicated imaging in low-risk cases.

METHODS:

Adult patients with blunt trauma who presented to a major academic center (May 2016 to October 2017) and received dedicated imaging of the TL spine were included. Exclusion criteria consisted of any coexisting condition preventing the acquisition of history or examination. The primary endpoint is TL spine injury requiring orthopedic evaluation, bracing/orthosis, or surgery. Preliminary CDR derivation was performed with recursive partitioning.

RESULTS:

Of 4612 patients screened, 1049 (22.7%) met inclusion criteria. Thirty-six (3.4%) patients were found to have TL spine injury, of which 88.9% received spinal bracing, orthosis, or surgery. Absence of midline tenderness conveyed the highest negative predictive value, followed by a non-severe mechanism of injury, lack of neurologic examination findings, and age < 65 years. No patients in this cohort with these four findings had a TL spine injury.

CONCLUSIONS:

In certain lower-risk blunt trauma patients < 65 years of age, focused examination combined with mechanism of injury may be highly sensitive (100%) to rule out TL injury without the need for dedicated imaging. However, validation is necessary, given multiple study limitations. Potential instrument to screen for TL injury in minor trauma: TL injury is unlikely if all four of the following are present: 1) no midline back tenderness or deformity, 2) no focal neurologic signs or symptoms or altered mentation, 3) age < 65 years; and 4) lack of severe mechanism of injury, for example, fall greater than standing, motor-vehicle collision with rollover/ejection/pedestrian or unenclosed vehicle, and assault with a weapon.

KEYWORDS:

blunt; imaging; rule; spine; thoracolumbar; trauma

7.
J Hypertens. 2019 Aug 7. doi: 10.1097/HJH.0000000000002192. [Epub ahead of print]

Is the rule of halves still relevant today? A cross-sectional analysis of hypertension detection, treatment and control in an urban community.

Author information

1
King's College, London, UK.

Abstract

AIMS:

To estimate percentages of patients with undiagnosed hypertension, diagnosed untreated hypertension and diagnosed, treated and uncontrolled hypertension and to identify sociodemographic factors for diagnosed, uncontrolled hypertension and not having a blood pressure (BP) reading recorded.

METHODS:

Data from 320 094 patients aged 18 to less than 80 years from general practices in inner London was analysed using both last recorded BP (blood pressure) and mean BP. Logistic regression models identified factors associated with uncontrolled hypertension and no recorded BP.

RESULTS:

Twenty-nine thousand, seven hundred and nineteen (9.3%) patients had a recorded diagnosis of hypertension. On the basis of analysis of the last BP value, 14.2% (n = 4207) were untreated and 46.3% (n = 13 749) had uncontrolled hypertension; 10.0% (n = 28 274) without a prior hypertension diagnosis had undiagnosed hypertension. Corresponding values based on mean BP analysis were 8.9% (n = 2367) untreated, 51.5% (n = 13 734) uncontrolled; 4.1% (n = 11 446) undiagnosed. 17.5% (n = 55 960) had no recorded BP value.Black ethnicity was a predictor of uncontrolled hypertension: compared with the White British population, the adjusted odds ratio (AOR) for the Black African population was 1.39 (95% CI: 1.25-1.53) and for the Black Caribbean was 1.31 (95% CI: 1.19-1.45). The White Other group were most likely to have no record of BP measurement (AOR: 1.52; 95% CI: 1.47-1.57); conversely, unrecorded BP was less likely in the Black African (AOR: 0.79; CI: 0.74-0.83) and Black Caribbean (AOR: 0.71; CI: 0.66-0.76) groups, relative to the White British population.

CONCLUSION:

In an inner-city, multiethnic population, the 'rule of halves' still broadly applies to the diagnosis and control of hypertension, although only a small proportion were untreated.

8.
Front Psychol. 2019 Jul 24;10:1705. doi: 10.3389/fpsyg.2019.01705. eCollection 2019.

From Experience to Memory: On the Robustness of the Peak-and-End-Rule for Complex, Heterogeneous Experiences.

Author information

1
Academy for Leisure, Breda University of Applied Sciences, Breda, Netherlands.
2
Academy for Tourism, Breda University of Applied Sciences, Breda, Netherlands.
3
Academy for Digital Entertainment, Breda University of Applied Sciences, Breda, Netherlands.
4
Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, Netherlands.

Abstract

Memory forms the input for future behavior. Therefore, how individuals remember a certain experience may be just as important as the experience itself. The peak-and-end-rule (PE-rule) postulates that remembered experiences are best predicted by the peak emotional valence and the emotional valence at the end of an experience in the here and now. The PE-rule, however, has mostly been assessed in experimental paradigms that induce relatively simple, one-dimensional experiences (e.g., experienced pain in a clinical setting). This hampers generalizations of the PE-rule to the experiences in everyday life. This paper evaluates the generalizability of the PE-rule to more complex and heterogeneous experiences by examining the PE-rule in a virtual reality (VR) experience, as VR combines improved ecological validity with rigorous experimental control. Findings indicate that for more complex and heterogeneous experiences, peak and end emotional valence are inferior to other measures (such as averaged valence and arousal ratings over the entire experiential episode) in predicting remembered experience. These findings suggest that the PE-rule cannot be generalized to ecologically more valid experiential episodes.

KEYWORDS:

experience; experiencing self; memory; peak-and-end-rule; remembering self

9.
10.
Ann Biomed Eng. 2019 Aug 6. doi: 10.1007/s10439-019-02335-9. [Epub ahead of print]

Repetitive Head Impact Exposure in College Football Following an NCAA Rule Change to Eliminate Two-A-Day Preseason Practices: A Study from the NCAA-DoD CARE Consortium.

Author information

1
Joint Department of Biomedical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, USA. bstemper@mcw.edu.
2
Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA. bstemper@mcw.edu.
3
Neuroscience Research, Clement J. Zablocki Veterans Affairs Medical Center, Milwaukee, WI, USA. bstemper@mcw.edu.
4
Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA.
5
Neuroscience Research, Clement J. Zablocki Veterans Affairs Medical Center, Milwaukee, WI, USA.
6
Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA.
7
Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA, USA.
8
Matthew Gfeller Sport-Related Traumatic Brain Injury Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
9
Department of Orthopedics, School of Medicine and Public Health, University of Wisconsin, Madision, WI, USA.
10
John A. Feagin Jr. Sports Medicine Fellowship, Keller Army Hospital, United States Military Academy, West Point, NY, USA.
11
Departments of Neurosurgery and Pediatrics, UCLA Steve Tisch BrainSPORT Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
12
Department of Sports Medicine, United States Air Force Academy, Colorado Springs, CO, USA.
13
Hospital for Special Surgery, New York, NY, USA.
14
Michigan Concussion Center, University of Michigan, Ann Arbor, MI, USA.
15
Department of Psychiatry, Indiana School of Medicine, Indianapolis, IN, USA.

Abstract

Repetitive head impact exposure sustained by athletes of contact sports has been hypothesized to be a mechanism for concussion and a possible explanation for the high degree of variability in sport-related concussion biomechanics. In an attempt to limit repetitive head impact exposure during the football preseason, the NCAA eliminated two-a-day practices in 2017, while maintaining the total number of team practice sessions. The objective of this study was to quantify head impact exposure during the preseason and regular season in Division I college football athletes to determine whether the 2017 NCAA ruling decreased head impact exposure. 342 unique athletes from five NCAA Division I Football Bowl Subdivision (FBS) programs were consented and enrolled. Head impacts were recorded using the Head Impact Telemetry (HIT) System during the entire fall preseasons and regular seasons in 2016 and 2017. Despite the elimination of two-a-day practices, the number of preseason contact days increased in 2017, with an increase in average hourly impact exposure (i.e., contact intensity), resulting in a significant increase in total head impact burden (+ 26%) for the 2017 preseason. This finding would indicate that the 2017 NCAA ruling was not effective at reducing the head impact burden during the football preseason. Additionally, athletes sustained a significantly higher number of recorded head impacts per week (+ 40%) during the preseason than the regular season, implicating the preseason as a time of elevated repetitive head impact burden. With increased recognition of a possible association between repetitive head impact exposure and concussion, increased preseason exposure may predispose certain athletes to a higher risk of concussion during the preseason and regular season. Accordingly, efforts at reducing concussion incidence in contact sports should include a reduction in overall head impact exposure.

KEYWORDS:

Acceleration; Injury biomechanics; Sport-related concussion; Traumatic brain injury

11.
Eur J Trauma Emerg Surg. 2019 Aug 6. doi: 10.1007/s00068-019-01201-6. [Epub ahead of print]

Features of urine S100B and its ability to rule out intracranial hemorrhage in patients with head trauma: a prospective trial.

Author information

1
Department of Clinical Sciences, Lund University, Svartbrödragränden 3-5, 251 87, Helsingborg, Sweden. tvedin@gmail.com.
2
Department of Clinical Chemistry and Center for Clinical Research, Centralsjukhuset, Karlstad, Sweden.
3
Department of Clinical Sciences, Lund University, Svartbrödragränden 3-5, 251 87, Helsingborg, Sweden.
4
Karlstad Central Hospital, Rosenborgsgatan 9, 652 30, Karlstad, Sweden.

Abstract

PURPOSE:

Traumatic brain injury causes morbidity and mortality worldwide. S100B is the most documented emergency brain biomarker and its urine-assay might be advantageous because of easier sampling. The primary aim was to evaluate urine S100B's ability to rule out intracranial hemorrhage. Secondary aims included S100B temporal pattern for 48 h post-trauma and chemical properties of urine that affect urine S100B.

METHODS:

Patients with head trauma were sampled for serum and urine S100B. Patients who were admitted for intracranial hemorrhage were sampled for 48 h to assess S100B-level, renal function, urine-pH, etc. RESULTS: The negative predictive value of serum S100B was 97.0% [95% confidence interval (CI) 89.5-99.2%] and that of urine S100B was 89.1% (95% CI 85.5-91.9%). The specificity of serum S100B was 34.4% (95% CI 27.7-41.6%) and that of urine was 67.1% (95% CI 59.4-74.1%). Urine-pH correlated strongly with urine S100B during the first 6-h post-trauma. Trend-analysis of receiver operator characteristics of S100B in serum, urine the arithmetic difference between serum and urine S100B showed the largest area under the curve for arithmetic difference, which had a negative predictive value of 93.1% (95% CI 89.1-95.8%) and a specificity of 71.8% (95% CI 64.4-78.4%).

CONCLUSION:

This study cannot support ruling out intracranial hemorrhage with urine S100B. Urine-pH might affect urine S100B and merits further studies. Serum and urine S100B have poor concordance and interchangeability. The arithmetic difference had a slightly better area under the curve and can be worth exploring in certain subgroups.

KEYWORDS:

Blood specimen collection; S100 calcium-binding protein beta subunit; Traumatic brain injuries; Urine specimen collection

12.
Neural Netw. 2019 Jul 26;119:10-30. doi: 10.1016/j.neunet.2019.07.017. [Epub ahead of print]

A programmable neural virtual machine based on a fast store-erase learning rule.

Author information

1
Department of Elec. Engr. and Comp. Sci., Syracuse University, Syracuse, NY, USA. Electronic address: gkatz01@syr.edu.
2
Department of Computer Science, University of Maryland, College Park, MD, USA. Electronic address: gpdavis@cs.umd.edu.
3
Department of Kinesiology, University of Maryland, College Park, MD, USA. Electronic address: rodolphe@umd.edu.
4
Department of Computer Science, University of Maryland, College Park, MD, USA. Electronic address: reggia@cs.umd.edu.

Abstract

We present a neural architecture that uses a novel local learning rule to represent and execute arbitrary, symbolic programs written in a conventional assembly-like language. This Neural Virtual Machine (NVM) is purely neurocomputational but supports all of the key functionality of a traditional computer architecture. Unlike other programmable neural networks, the NVM uses principles such as fast non-iterative local learning, distributed representation of information, program-independent circuitry, itinerant attractor dynamics, and multiplicative gating for both activity and plasticity. We present the NVM in detail, theoretically analyze its properties, and conduct empirical computer experiments that quantify its performance and demonstrate that it works effectively.

KEYWORDS:

Itinerant attractor dynamics; Local learning; Multiplicative gating; Programmable neural networks; Symbolic processing

13.
Int J Pediatr Otorhinolaryngol. 2019 Jul 27;126:109610. doi: 10.1016/j.ijporl.2019.109610. [Epub ahead of print]

Is there a role for computed tomography scanning in microtia with complete aural atresia to rule out cholesteatoma?

Author information

1
University of Saskatchewan, Saskatoon, Canada.
2
University of British Columbia, Vancouver, Canada; Division of Pediatric Otolaryngology-Head & Neck Surgery, BC Children's Hospital, Vancouver, Canada. Electronic address: nchadha@cw.bc.ca.
3
University of British Columbia, Vancouver, Canada; Division of Pediatric Plastic and Reconstructive Surgery, BC Children's Hospital, Canada.

Abstract

OBJECTIVE:

To determine if radiologic imaging is necessary to rule out cholesteatoma in patients with congenital aural atresia.

METHODS:

A retrospective chart review of patients attending the BC Children's Hospital Microtia Clinic from January 1, 1990 through April 17, 2017 was undertaken. Patients with complete atresia of the external canal were included in the study. Available radiologic imaging and clinical records were examined for the presence or absence of cholesteatoma.

RESULTS:

Of the 125 charts reviewed, 102 met criteria for inclusion in the study and 79 had three-dimensional imaging completed. None of these 102 patients had radiologic or clinical evidence of cholesteatoma.

CONCLUSION:

Computed tomography and/or magnetic resonance imaging remains an essential modality in the work-up of selected patients with microtia/atresia. It may be unnecessary in the follow-up of certain patients to rule out a congenital cholesteatoma. This imaging avoidance may reduce exposure to radiation, the potential need for general anaesthesia, and unnecessary financial cost.

KEYWORDS:

Cholesteatoma; Computed tomography (CT); Congenital aural atresia; Microtia

14.
Pharmacol Ther. 2019 Jul 30:107395. doi: 10.1016/j.pharmthera.2019.107395. [Epub ahead of print]

Machine learning and data mining frameworks for predicting drug response in cancer: An overview and a novel in silico screening process based on association rule mining.

Author information

1
Biomedical Research Foundation of the Academy of Athens, 4 Soranou Ephessiou Str., Athens GR-11527, Greece; Molecular Carcinogenesis Group, Department of Histology and Embryology, School of Medicine, National and Kapodistrian University of Athens, 75 Mikras Asias Str, Athens GR-11527, Greece.
2
Department of Pathology, NYU School of Medicine, New York, NY 10016, USA; Laura and Isaac Perlmutter Cancer Center, NYU School of Medicine, New York, NY 10016, USA.
3
Molecular Carcinogenesis Group, Department of Histology and Embryology, School of Medicine, National and Kapodistrian University of Athens, 75 Mikras Asias Str, Athens GR-11527, Greece.
4
Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY 10021, USA.
5
Molecular Carcinogenesis Group, Department of Histology and Embryology, School of Medicine, National and Kapodistrian University of Athens, 75 Mikras Asias Str, Athens GR-11527, Greece; Division of Pharmaceutical Chemistry, School of Pharmacy, National and Kapodistrian University of Athens, Athens, Greece.
6
Applied Bioinformatics Laboratories, NYU School of Medicine, New York, NY 10016, USA.
7
Laboratory of Tumour Cell Biology, School of Medicine, University of Crete, Heraklion, Crete, Greece.
8
School of Mechanical Engineering, National Technical University of Athens, Zografou 15780, Greece.
9
Division of Cancer Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, Manchester Cancer Research Centre, NIHR Manchester Biomedical Research Centre, University of Manchester, Manchester M20 4GJ, UK.
10
1st Department of Propaedeutic Internal Medicine, Medical School, Laikon Hospital, National and Kapodistrian University of Athens, 75 Mikras Asias Str, Athens GR-11527, Greece; Center for New Biotechnologies and Precision Medicine, Medical School, National and Kapodistrian University of Athens, 75 Mikras Asias Str, Athens GR-11527, Greece.
11
Medical Research Council Cancer Unit, Hutchison/Medical Research Council Research Centre, University of Cambridge, Cambridge, UK.
12
Biomedical Research Foundation of the Academy of Athens, 4 Soranou Ephessiou Str., Athens GR-11527, Greece.
13
Genome Integrity Unit, Danish Cancer Society Research Centre, Strandboulevarden 49, Copenhagen DK-2100, Denmark; Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University, Hněvotínská, Olomouc 1333/5 779 00, Czech Republic; Science for Life Laboratory, Division of Translational Medicine and Chemical Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institute, Stockholm SE-171 77, Sweden.
14
Division of Molecular and Clinical Medicine, Ninewells Hospital and School of Medicine, University of Dundee, Dundee DD1 9SY, Scotland.
15
Department of Pathology, NYU School of Medicine, New York, NY 10016, USA; Laura and Isaac Perlmutter Cancer Center, NYU School of Medicine, New York, NY 10016, USA; Applied Bioinformatics Laboratories, NYU School of Medicine, New York, NY 10016, USA. Electronic address: aristotelis.tsirigos@nyulangone.org.
16
Biomedical Research Foundation of the Academy of Athens, 4 Soranou Ephessiou Str., Athens GR-11527, Greece; Molecular Carcinogenesis Group, Department of Histology and Embryology, School of Medicine, National and Kapodistrian University of Athens, 75 Mikras Asias Str, Athens GR-11527, Greece; Division of Cancer Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, Manchester Cancer Research Centre, NIHR Manchester Biomedical Research Centre, University of Manchester, Manchester M20 4GJ, UK; Center for New Biotechnologies and Precision Medicine, Medical School, National and Kapodistrian University of Athens, 75 Mikras Asias Str, Athens GR-11527, Greece. Electronic address: vgorg@med.uoa.gr.

Abstract

A major challenge in cancer treatment is predicting the clinical response to anti-cancer drugs on a personalized basis. The success of such a task largely depends on the ability to develop computational resources that integrate big "omic" data into effective drug-response models. Machine learning is both an expanding and an evolving computational field that holds promise to cover such needs. Here we provide a focused overview of: 1) the various supervised and unsupervised algorithms used specifically in drug response prediction applications, 2) the strategies employed to develop these algorithms into applicable models, 3) data resources that are fed into these frameworks and 4) pitfalls and challenges to maximize model performance. In this context we also describe a novel in silico screening process, based on Association Rule Mining, for identifying genes as candidate drivers of drug response and compare it with relevant data mining frameworks, for which we generated a web application freely available at: https://compbio.nyumc.org/drugs/. This pipeline explores with high efficiency large sample-spaces, while is able to detect low frequency events and evaluate statistical significance even in the multidimensional space, presenting the results in the form of easily interpretable rules. We conclude with future prospects and challenges of applying machine learning based drug response prediction in precision medicine.

KEYWORDS:

Association Rule Mining; Data mining; Drug Response Prediction; Machine Learning; Precision Medicine

Publication type

Publication type

15.
CMAJ. 2019 Jul 29;191(30):E844. doi: 10.1503/cmaj.72273.

One EHR should not rule them all.

Author information

1
Assistant professor; physician informatician, General Internal Medicine, McMaster University, Hamilton, Ont.
2
Project manager ICAT Redevelopment, West Park Healthcare, University of Toronto, Toronto, Ont.

Conflict of interest statement

Competing interests: None declared.

Publication type

Publication type

16.
Molecules. 2019 Jul 26;24(15). pii: E2716. doi: 10.3390/molecules24152716.

Applicability Domain of Active Learning in Chemical Probe Identification: Convergence in Learning from Non-Specific Compounds and Decision Rule Clarification.

Author information

1
Kyoto University Graduate School of Medicine, Department of Molecular Biosciences, Life Science Informatics Research Unit, Kyoto, Sakyo, Yoshida, Konoemachi, Kyoto 606-8501, Japan.
2
Kyoto University Graduate School of Medicine, Department of Radiation Genetics; Kyoto, Sakyo, Yoshida, Konoemachi, Kyoto 606-8501, Japan.
3
Kyoto University Graduate School of Medicine, Department of Molecular Biosciences, Life Science Informatics Research Unit, Kyoto, Sakyo, Yoshida, Konoemachi, Kyoto 606-8501, Japan. jbbrown@kuhp.kyoto-u.ac.jp.

Abstract

Efficient identification of chemical probes for the manipulation and understanding of biological systems demands specificity for target proteins. Computational means to optimize candidate compound selection for experimental selectivity evaluation are being sought. The active learning virtual screening method has demonstrated the ability to efficiently converge on predictive models with reduced datasets, though its applicability domain to probe identification has yet to be determined. In this article, we challenge active learning's ability to predict inhibitory bioactivity profiles of selective compounds when learning from chemogenomic features found in non-selective ligand-target pairs. Comparison of controls versus multiple molecule representations de-convolutes factors contributing to predictive capability. Experiments using the matrix metalloproteinase family demonstrate maximum probe bioactivity prediction achieved from only approximately 20% of non-probe bioactivity; this data volume is consistent with prior chemogenomic active learning studies despite the increased difficulty from chemical biology experimental settings used here. Feature weight analyses are combined with a custom visualization to unambiguously detail how active learning arrives at classification decisions, yielding clarified expectations for chemogenomic modeling. The results influence tactical decisions for computational probe design and discovery.

KEYWORDS:

active learning; active projection; chemical probes; chemogenomics; compound specificity; decision tree; ligand-target interactions; molecular representation

PMID:
31357419
DOI:
10.3390/molecules24152716
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17.
Am J Nurs. 2019 Aug;119(8):16. doi: 10.1097/01.NAJ.0000577392.14576.54.

NewsCAP: U.S. Department of Health and Human Services (HHS) issues final 'conscience rule'.

[No authors listed]
18.
Phys Rev Lett. 2019 Jun 28;122(25):250603. doi: 10.1103/PhysRevLett.122.250603.

Operator Entanglement in Interacting Integrable Quantum Systems: The Case of the Rule 54 Chain.

Author information

1
Institute for Theoretical Physics, Universiteit van Amsterdam, Science Park 904, Postbus 94485, 1098 XH Amsterdam, Netherlands.
2
Laboratoire de Physique et Chimie Théoriques, CNRS, UMR 7019, Université de Lorraine, 54506 Vandoeuvre-les-Nancy, France.
3
Institut de Physique Théorique Philippe Meyer, École Normale Supérieure, PSL University, Sorbonne Universités, CNRS, 75005 Paris, France.

Abstract

In a many-body quantum system, local operators in the Heisenberg picture O(t)=e^{iHt}Oe^{-iHt} spread as time increases. Recent studies have attempted to find features of that spreading which could distinguish between chaotic and integrable dynamics. The operator entanglement-the entanglement entropy in operator space-is a natural candidate to provide such a distinction. Indeed, while it is believed that the operator entanglement grows linearly with time t in chaotic systems, we present evidence that it grows only logarithmically in generic interacting integrable systems. Although this logarithmic growth has been previously established for noninteracting fermions, there has been no progress on interacting integrable systems to date. In this Letter we provide an analytical upper bound on operator entanglement for all local operators in the "Rule 54" qubit chain, a cellular automaton model introduced in the 1990s [Bobenko et al., CMP 158, 127 (1993)CMPHAY0010-361610.1007/BF02097234], and recently advertised as the simplest representative of interacting integrable systems. Physically, the logarithmic bound originates from the fact that the dynamics of the models is mapped onto the one of stable quasiparticles that scatter elastically. The possibility of generalizing this scenario to other interacting integrable systems is briefly discussed.

19.
Pediatr Rheumatol Online J. 2019 Jul 25;17(1):50. doi: 10.1186/s12969-019-0355-0.

A prediction rule for lack of achievement of inactive disease with methotrexate as the sole disease-modifying antirheumatic therapy in juvenile idiopathic arthritis.

Author information

1
Università degli Studi di Genova, Dipartimento di Neuroscienze, Riabilitazione, Oftalmologia, Genetica e Scienze Materno-Infantili (DiNOGMI), Genova, Italy. ceciliabava4@gmail.com.
2
Clinica Pediatrica e Reumatologia, IRCCS Istituto Giannina Gaslini, Largo G. Gaslini 5, 16147, Genova, Italy. ceciliabava4@gmail.com.
3
Università degli Studi di Genova, Dipartimento di Neuroscienze, Riabilitazione, Oftalmologia, Genetica e Scienze Materno-Infantili (DiNOGMI), Genova, Italy.
4
IRCCS Istituto Giannina Gaslini, Genova, Italy.
5
Azienda Ospedaliera Nazionale SS. Antonio e Biagio e Cesare Arrigo, Alessandria, Italy.
6
Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milano, Italy.
7
IRCCS Fondazione Policlinico San Matteo, Pavia, Italy.
8
Ospedale Regina Montis Regalis, Mondovì, Italy.
9
Sechenov First Moscow State Medical University, Moscow, Russian Federation.

Abstract

BACKGROUND:

To investigate the frequency of achievement of inactive disease (ID) in children with juvenile idiopathic arthritis (JIA) treated with methotrexate (MTX) as the sole disease-modifyng antirheumatic (DMARD) therapy and to develop a prediction model for lack of attainment of ID.

METHODS:

The clinical charts of consecutive patients started with MTX as the sole DMARD between 2000 and 2013 were reviewed. Patient follow-up was censored at first episode of ID or, in case ID was not reached, at last follow-up visit or when a biologic DMARD was prescribed. The characteristic at MTX start of patients who achieved or did not achieve ID were compared with univariate and multivariable analyses. Regression coefficients (β) of variables that entered the best-fitting logistic regression model were converted and summed to obtain a "prediction score" for lack of achievement of ID.

RESULTS:

A total of 375 patients were included in the study. During MTX administration, 8.8% were given systemic corticosteroids and 44.1% intra-articular corticosteroids. After MTX start, 229 (61%) patients achieved ID after a median of 1.7 years, whereas 146 patients (39%) did not reach ID after a median of 1.2 years. On multivariable analysis, independent correlations with lack of achievement of ID were identified for the disease categories of systemic arthritis, enthesitis-related arthritis (ERA) and polyarthritis and C-reactive protein (CRP) >  1.4 mg/dl. The prediction score ranged from 0 to 3 and its cutoff that discriminated best between patients who achieved or did not achieve ID was > 0.5. The categories of systemic arthritis or ERA, both of which had a score greater than 0.5, were sufficient alone to predict a lower likelihood to reach ID. Polyarthritis and increased CRP, whose score was 0.5, assumed a predictive value only when present in association.

CONCLUSION:

A conventional treatment regimen based on MTX as the sole DMARD led to achievement of ID in a sizeable proportion of children with JIA. Our findings help to outline the characteristics of patients who may deserve a synthetic DMARD other than MTX or the introduction of a biologic DMARD from disease outset.

KEYWORDS:

Biologic therapies; Juvenile idiopathic arthritis; Methotrexate; Pediatric rheumatology; Prediction rule; Predictors

20.
BMJ Open. 2019 Jul 23;9(7):e028311. doi: 10.1136/bmjopen-2018-028311.

Multicentre cross-sectional observational registry to monitor the safety of early discharge after rule-out of acute myocardial infarction by copeptin and troponin: the Pro-Core registry.

Author information

1
Cardiology, University of Heidelberg, Heidelberg, Germany.
2
Buckinghamshire Healthcare NHS Trust, Amersham, UK.
3
Department of Emergency Medicine CVK, CCM and Department of Cardiology CVK, Charité Universitiy Medicine, Berlin, Germany.
4
College of Public Health Medical and Veterinary Sciences, Centre for Chronic Disease Prevention, Australian Institute of Tropical Health and Medicine, James Cook University, Cairns, Queensland, Australia.
5
Cardiology, St. Elisabeth Krankenhaus, Mayen, Germany.
6
Department of Cardiology, Kerckhoff Heart and Thorax Centre, Bad Nauheim, Germany.
7
Partner Site, German Center for Cardiovascular Research (DZHK), Frankfurt am Main, Germany.
8
Hôpital du Bocage, CHU Dijon, Dijon, France.
9
3rd Department of Internal Medicine, Cardiology and Intensive Care Medicine, Wilhelminenhospital, Vienna, Austria.
10
Medical School, Sigmund Freud University, Vienna, Austria.
11
Cardiovascular Biomarkers, Thermo Fisher Scientific, Hennigsdorf, Germany.
12
Cardiology, Krankenhaus Hedwigshohe Berlin, Berlin, Germany.
13
Internal Medicine and Cardiology, Unfallkrankenhaus Berlin, Berlin, Germany.

Abstract

OBJECTIVES:

There is sparse information on the safety of early primary discharge from the emergency department (ED) after rule-out of myocardial infarction in suspected acute coronary syndrome (ACS). This prospective registry aimed to confirm randomised study results in patients at low-to-intermediate risk, with a broader spectrum of symptoms, across different institutional standards and with a range of local troponin assays including high-sensitivity cTn (hs-cTn), cardiac troponin (cTn) and point-of-care troponin (POC Tn).

DESIGN:

Prospective, multicentre European registry.

SETTING:

18 emergency departments in nine European countries (Germany, Austria, Switzerland, France, Spain, UK, Turkey, Lithuania and Hungary) PARTICIPANTS: The final study cohort consisted of 2294 patients (57.2% males, median age 57 years) with suspected ACS.

INTERVENTIONS:

Using the new dual markers strategy, 1477 patients were eligible for direct discharge, which was realised in 974 (42.5%) of patients.

MAIN OUTCOME MEASURES:

The primary endpoint was all-cause mortality at 30 days.

RESULTS:

Compared with conventional workup after dual marker measurement, the median length of ED stay was 60 min shorter (228 min, 95% CI: 219 to 239 min vs 288 min, 95% CI: 279 to 300 min) in the primary dual marker strategy (DMS) discharge group. All-cause mortality was 0.1% (95% CI: 0% to 0.6%) in the primary DMS discharge group versus 1.1% (95% CI: 0.6% to 1.8%) in the conventional workup group after dual marker measurement. Conventional workup instead of discharge despite negative DMS biomarkers was observed in 503 patients (21.9%) and associated with higher prevalence of ACS (17.1% vs 0.9%, p<0.001), cardiac diagnoses (55.2% vs 23.5%, p<0.001) and risk factors (p<0.01), but with a similar all-cause mortality of 0.2% (95% CI: 0% to 1.1%) versus primary DMS discharge (p=0.64).

CONCLUSIONS:

Copeptin on top of cardiac troponin supports safe discharge in patients with chest pain or other symptoms suggestive of ACS under routine conditions with the use of a broad spectrum of local standard POC, conventional and high-sensitivity troponin assays.

TRIAL REGISTRATION NUMBER:

NCT02490969.

KEYWORDS:

acute coronary syndrome; copeptin; mortality; myocardial infarction; registry; troponin

Conflict of interest statement

Competing interests: EG received honoraria for lectures from Roche Diagnostics, AstraZeneca, Bayer, Daiichi-Sankyo, Lilly Eli Deutschland. He serves as a consultant for Roche Diagnostics, BRAHMS Thermo Fisher Scientific, Boehringer Ingelheim and has received research funding from BRAHMS Thermo Fisher Scientific, Roche Diagnostics, Bayer Vital and Daiichi Sankyo; AS has received research funding from Roche Diagnostics, BRAHMS Thermofisher Scientific and the German Research Council (DFG); MM received honoraria for lectures from Roche Diagnostics, AstraZeneca, Bayer Vital, Daiichi-Sankyo, Boehringer Ingelheim and BRAHMS Thermo Fisher Scientific. He serves as a consultant for BRAHMS Thermo Fisher Scientific and Bayer, and has received research funding from BRAHMS Thermo Fisher Scientific, Roche Diagnostics and Radiometer. CS, JOV, JCW are employees of BRAHMS Thermo Fisher Scientific. MM-H report research grants from Roche Diagnostics, BRAHMS Thermo Fisher Scientific and the University of Heidelberg. Speaker honoraria from RocheDiagnostics KK reports fees from BRAHMS Thermo Fisher Scientific for monitoring activities related to the study. DH reports speakers fees from BRAHMS Thermo Fisher Scientific. KH received honoraria for lectures from AstraZeneca, Bayer, Boehringer Ingelheim, BRAHMS Thermo Fisher Scientific, Daiichi Sankyo, Pfizer, Sanofi and The Medicines Company and has received research funding form AstraZeneca and BRAHMS Thermo Fisher, respectively. ChH and CPC report speakers fees and honoraria for consultancy from BRAHMS Thermo Fisher Scientific.

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