HIPSD&R-seq enables scalable genomic copy number and transcriptome profiling.

Single-cell DNA sequencing (scDNA-seq) enables decoding somatic cancer variation. Existing methods are hampered by low throughput or cannot be combined with transcriptome sequencing in the same cell. We propose HIPSD&R-seq (HIgh-throughPut Single-cell Dna and Rna-seq), a scalable yet simple and accessible assay to profile low-coverage DNA and RNA in thousands of cells in parallel.

Drugst.One - a plug-and-play solution for online systems medicine and network-based drug repurposing.

In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In response, computational systems and network medicine tools have emerged to identify potential drug repurposing candidates. However, these tools often require complex installation and lack intuitive visual network mining capabilities.

TF-Prioritizer: a Java pipeline to prioritize condition-specific transcription factors.

Background: Eukaryotic gene expression is controlled by cis-regulatory elements (CREs), including promoters and enhancers, which are bound by transcription factors (TFs). Differential expression of TFs and their binding affinity at putative CREs determine tissue- and developmental-specific transcriptional activity. Consolidating genomic datasets can offer further insights into the accessibility of CREs, TF activity, and, thus, gene regulation.

Lipid network and moiety analysis for revealing enzymatic dysregulation and mechanistic alterations from lipidomics data.

Lipidomics is of growing importance for clinical and biomedical research due to many associations between lipid metabolism and diseases. The discovery of these associations is facilitated by improved lipid identification and quantification. Sophisticated computational methods are advantageous for interpreting such large-scale data for understanding metabolic processes and their underlying (patho)mechanisms.

Thinking about order: a review of common processing of magnitude and learned orders in animals.

Rich behavioral and neurobiological evidence suggests cognitive and neural overlap in how quantitatively comparable dimensions such as quantity, time, and space are processed in humans and animals. While magnitude domains such as physical magnitude, time, and space represent information that can be quantitatively compared (4 "is half of" 8), they also represent information that can be organized ordinally (1→2→3→4). Recent evidence suggests that the common representations seen across physical magnitude, time, and space domains in humans may be due to their common ordinal features rather than their common quantitative features, as these common representations appear to extend beyond magnitude domains to include learned orders.

Mass cytometry of platelet-rich plasma: a new approach to analyze platelet surface expression and reactivity.

Mass cytometry (CyTOF) is a new technology that allows the investigation of protein expression at single cell level with high resolution. While several protocols are available to investigate leukocyte expression, platelet staining and analysis with CyTOF have been described only from whole blood. Moreover, available protocols do not allow sample storage but require fresh samples to be obtained, processed, and measured immediately.

A systematic comparison of novel and existing differential analysis methods for CyTOF data.

Cytometry techniques are widely used to discover cellular characteristics at single-cell resolution. Many data analysis methods for cytometry data focus solely on identifying subpopulations via clustering and testing for differential cell abundance. For differential expression analysis of markers between conditions, only few tools exist.

Network medicine for disease module identification and drug repurposing with the NeDRex platform.

Traditional drug discovery faces a severe efficacy crisis. Repurposing of registered drugs provides an alternative with lower costs and faster drug development timelines. However, the data necessary for the identification of disease modules, i.

Efficacy of distal haemostasis during caesarean delivery in women with placenta accreta spectrum disorders.

Unlabelled: Pregnancies complicated by the placenta praevia are associated with an increased risk of massive obstetric bleeding and high rates of hysterectomy which are often caused by the placenta accreta. was to identify the risk factors for placenta praevia associated with PAS disorders and the efficacy of distal haemostasis during Cesarean delivery.

Methods: This was a cohort study carried out between 2014 and 2020 in 532 women with abnormal placental localization and attachment.

Does cognition differ across species, and how do we know? Lessons from research in transitive inference.

Comparative psychologists study cognition by characterizing the behavior of individual species and explicitly comparing behavior across species. We use the extensive comparative literature on transitive inference (TI) as a case study to evaluate four central methodological questions that continue to be debated in the field of comparative psychology: 1) Are contextual variables sufficient to explain species differences in cognition? 2) Can cognitive performance be accounted for by associative processes alone? 3) Can we determine the cognitive mechanisms by which animals solve tasks? and 4) What is the role of ecologically driven hypotheses in comparative psychology? Although contextual variables and associative processes undeniably influence choice behavior in TI tasks, neither is sufficient to explain all performance. Instead, multiple distinct cognitive mechanisms, including associative processes, logical inference, and spatial representations, can and do result in successful TI performance.

Platelet Surface Protein Expression and Reactivity upon TRAP Stimulation after BNT162b2 Vaccination.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection induces a coagulopathy characterized by platelet activation and a hypercoagulable state with an increased incidence of cardiovascular events. The viral spike protein S has been reported to enhance thrombosis formation, stimulate platelets to release procoagulant factors, and promote the formation of platelet-leukocyte aggregates even in absence of the virus. Although SARS-CoV-2 vaccines induce spike protein overexpression to trigger SARS-CoV-2-specific immune protection, thrombocyte activity has not been investigated in this context.

On the limits of active module identification.

In network and systems medicine, active module identification methods (AMIMs) are widely used for discovering candidate molecular disease mechanisms. To this end, AMIMs combine network analysis algorithms with molecular profiling data, most commonly, by projecting gene expression data onto generic protein-protein interaction (PPI) networks. Although active module identification has led to various novel insights into complex diseases, there is increasing awareness in the field that the combination of gene expression data and PPI network is problematic because up-to-date PPI networks have a very small diameter and are subject to both technical and literature bias.

Machine learning for deciphering cell heterogeneity and gene regulation.

Epigenetics studies inheritable and reversible modifications of DNA that allow cells to control gene expression throughout their development and in response to environmental conditions. In computational epigenomics, machine learning is applied to study various epigenetic mechanisms genome wide. Its aim is to expand our understanding of cell differentiation, that is their specialization, in health and disease.

[The attitude and awareness of students of medical university concerning issues of reproductive health and pregravid training from positions of "4P Medicine"].

The young generation aged 16-24 years is the main demographic national reserve for coming decades. Hence, the purpose of the study is to investigate attitude of modern youth exemplified by students of medical university to establishing family, marriage and birth of children, and also their awareness about issues of reproductive health and training of couple to birth of healthy progeny considering modern approaches of personalized "4P Medicine". The survey of medical students was carried out on the basis of sampling of 193 students in November 2019 to February 2020.

SARS-CoV-2 infection is associated with a pro-thrombotic platelet phenotype.

Novel coronavirus disease 2019 (COVID-19) is associated with a hypercoagulable state, characterized by abnormal coagulation parameters and by increased incidence of cardiovascular complications. With this study, we aimed to investigate the activation state and the expression of transmembrane proteins in platelets of hospitalized COVID-19 patients. We investigated transmembrane proteins expression with a customized mass cytometry panel of 21 antibodies.

BiCoN: network-constrained biclustering of patients and omics data.

Motivation: Unsupervised learning approaches are frequently used to stratify patients into clinically relevant subgroups and to identify biomarkers such as disease-associated genes. However, clustering and biclustering techniques are oblivious to the functional relationship of genes and are thus not ideally suited to pinpoint molecular mechanisms along with patient subgroups.

Results: We developed the network-constrained biclustering approach Biclustering Constrained by Networks (BiCoN) which (i) restricts biclusters to functionally related genes connected in molecular interaction networks and (ii) maximizes the difference in gene expression between two subgroups of patients.

Pregnancy and delivery in women with a high risk of infection in pregnancy.

Background: Pregnant women with chronic genital and non-genital infections are at a high risk of infections complication during pregnancy and the postpartum period. Preterm birth is one of the leading causes of obstetric and neonatal complications and occurs in one in nine women. Forty per cent of preterm births are considered to be caused by the abnormal vaginal microbiome, and there is currently no consensus on the contribution of combined bacterial and viral infections.

[Hypoglycemia in neonates: a review of the literature and a case report].

Hypoglycemia in the neonatal period is one of the urgent problems of pediatric endocrinology. The main factors that lead to disruption of carbohydrate homeostasis are generally known, but the issues of neonatal hypoglycemia continue to be actively studied. In the last few years, the effect of low blood glucose on brain neurons has been studied, the issues of glycemia monitoring in the first days of life have been outlined, and strategies for managing newborns with hypoglycemic syndrome are being discussed.

Analysis of the Mortality of Russian Patients With Chronic Myeloid Leukemia in the Multicenter EUTOS ELN Population-based Study (EUTOS-PBS).

Introduction: Russia took part in the multicenter population-based study (Europe) and included 6.8% adult patients with newly diagnosed chronic myeloid leukemia (CML). The objective of this study was to analyze the mortality in the Russian cohort of patients with newly diagnosed CML in the EUTOS PBS observational study.

Associative models fail to characterize transitive inference performance in rhesus monkeys (Macaca mulatta).

It has been suggested that non-verbal transitive inference (if A > B and B > C, then A > C) can be accounted for by associative models. However, little is known about the applicability of such models to primate data. In Experiment 1, we tested the fit of two associative models to primate data from both sequential training, in which the training pairs were presented in a backward order, and simultaneous training, in which all training pairs are presented intermixed from the beginning.

The effect of labor market shocks on health: The case of the Russian transition.

During the first years of the transition to the market economy in Russia, many people experienced the whole range of stressful labor market events, including job loss, wage cuts and nonpayments; some people had to change occupations or take on additional work. These events were caused externally by the unprecedented structural shifts in the economy. This natural experiment provides an opportunity to estimate the causal effect of various labor market shocks on individual health and health-related behaviors.