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In recent years, analyzing genome-wide expression profiles to find genetic markers has received much attention as a challenging field of research aiming at unveiling biological mechanisms behind complex disorders. The identification of reliable and reproducible markers has lately been achieved by integrating genome-scale functional relationships and transcriptome datasets, and a number of algorithms have been developed to support this strategy. In this paper, we present a promising and easily applicable tool to accomplish this goal, namely CytoGTA, which is a Cytoscape plug-in that relies on an optimistic game theoretic approach (GTA) for identifying subnetwork markers. Given transcriptomic data of two phenotype classes and interactome data, this plug-in offers discriminative markers for the two classes. The high performance of CytoGTA would not have been achieved if the strategy of GTA was not implemented in Cytoscape. This plug-in provides a simple-to-use platform, convenient for biological researchers to interactively work with and visualize the structure of subnetwork markers. CytoGTA is one of the few available Cytoscape plug-ins for marker identification, which shows superior performance to existing methods. [ABSTRACT FROM AUTHOR]

Differential, transmitted reference (TR) and energy detection (ED) based ultra-wideband impulse radios (UWBIR) can collect the rich multipath energy offered by UWB channels with a low-complexity receiver. However, they perform satisfactorily only when the channel induced inter-pulse interference (IPI) is negligible. This can be achieved by appending a guard interval with duration greater than or equal to the channel's delay spread to each frame an operation limiting the maximum achievable data rate. As a remedy, this Letter advocates block transmissions in conjunction with orthogonal spreading sequences to remove the introduced IPI. The resultant scheme requires no channel knowledge besides timing offset and incurs slightly more complexity than non-block alternatives, while it increases the data rate at no cost in error performance. Given a fixed data rate of 25 Mbps, the novel block scheme exhibits about 1.8 dB gain relative to its non-block counterpart in single-user simulated tests. [ABSTRACT FROM PUBLISHER]

Objectives: This study aimed to formulate a novel herbal mixture of Hypericum perforatum (H) and Melissa officinalis (M) and evaluate its toxicity, microbial load, and phytochemical content., Materials and Methods: Total flavonoids were measured using the AlCl 3 /NaNO 2 complex formation method and colorimetric assay. The quercetin content of the herbal mixture was determined by reverse-phase high-performance liquid chromatography. The in vitro and in vivo safety of the herbal formulations were analyzed using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and acute oral toxicity analysis in the rat model, respectively., Results: The formulated extract (HM), compared with the standard rutin extract, had a total flavonoid content of 15.29 ± 0.64 mg rutin per mL sample. Reverse-phase high-performance liquid chromatography revealed a quercetin content of 0.187 mg/mL. Microbial tests for Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus , and Salmonella spp. were negative. Colony counts for total aerobic microbial and yeast and mold counts were 10 in each case. The MTT assay (with up to about 5% v/v HM extract) using the NIH/3T3 cell line revealed no cell toxicity in the range of concentrations tested. Acute oral toxicity was tested in the Wistar rat model, and the LD 50 was 695.2 ± 7.5 mg/kg. The dry weight of the HM extract was 38.1 mg/mL., Conclusion: Preliminary results proved the safety of the HM herbal mixture, with its toxicity and microbial load within the limits of accepted guidelines allowable for use in clinical trials., Competing Interests: Conflict of Interest: No conflict of interest was declared by the authors., (Copyright© 2024 The Author. Published by Galenos Publishing House on behalf of Turkish Pharmacists’ Association.)

Diabetes mellitus represents a persistent metabolic condition marked by heightened levels of blood glucose, presenting a considerable worldwide health concern, and finding targeted treatment for it is a crucial priority for global health. Gram-positive aerobic bacteria, predominantly inhabiting water and soil, are known carriers of various enzyme-encoding genetic material, which includes the malic enzyme gene that plays a role in insulin secretion. Corynebacterium glutamicum bacteria (ATCC 21799) were acquired from the Pasteur Institute and confirmed using microbiological and molecular tests, including DNA extraction. After identification, gene purification and cloning of the maeB gene were performed using the TA Cloning method. Additionally, the enhancement of enzyme expression was assessed using the expression vector pET-28a, and validation of simulation results was monitored through a real-time PCR analysis. Based on previous studies, the malic enzyme plays a pivotal role in maintaining glucose homeostasis, and increased expression of this enzyme has been associated with enhanced insulin sensitivity. However, the production of malic enzyme has encountered numerous challenges and difficulties. This study successfully isolated the malic enzyme genes via Corynebacterium glutamicum and introduced them into Escherichia coli for high-yield production. According to the results, the optimum temperature for the activity of enzymes has been identified as 39 °C., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Urinary tract infections are one of the most common infections worldwide. Given the increasing antibiotic resistance, monitoring antibiotic sensitivity patterns is crucial. Furthermore, silver nanoparticles synthesized from Stachys schtschegleevii can exhibit potent antibacterial, antibiotic, and antifungal properties. The plant S. schtschegleevii was collected from its natural habitat, dried, and its extract was then exposed to silver nitrate. Under specific conditions, silver nanoparticles were synthesized from it. Subsequently, the production and validation of silver nanoparticles were confirmed through techniques such as FTIR analysis, UV-Vis analysis, TEM, SEM, EDX analysis, and zeta potential analysis. In the in vitro section of the research, the impact of the extracted silver nanoparticles on bacteria isolated from patients' urine and standard bacterial culture (control) was assessed using the disc diffusion and MIC test methods. The results of the analyses are FTIR (high protein content; proteins and phenols serve as stabilizing agents), UV-Vis (peak of 460 nm), TEM (spherical to occasionally elliptical shapes), SEM (sizes: 26 to 72 nm), EDX (peak at 3 keV), and zeta potential (- 15.76 ± 0.05 mV). The effect of silver nanoparticles by disc diffusion method (mm) is Enterococcus faecalis = 18.31 ± 0.35, Escherichia coli = 21.51 ± 0.61, and Staphylococcus aureus = 19.02 ± 1.28, and by MIC test (μg/ml), E. faecalis = 19, E. coli = 18, and Staphylococcus aureus = 16. Antibacterial activity of the silver nanoparticles synthesized from S. schtschegleevii means that these herbal nanoparticles treat urinary tract infections caused by some of the test isolates., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Consumer exposure to cosmetic ingredients is estimated in a tiered manner. Simple Tier1 deterministic aggregate exposure modelling generates a worst case estimate of exposure. Tier1 assumes that a consumer uses all cosmetic products concomitantly daily, at maximum frequency, and products always contain the ingredient at the maximum allowed % w/w concentration. Refining exposure assessment from worst case to more realistic estimates uses evidence from surveys of actual use levels of ingredients and Tier2 probabilistic models, where distributions of consumer use data can be applied. In Tier2+ modelling, occurrence data provides evidence of products on the market actually containing the ingredient. Three case studies are presented using this tiered approach to illustrate progressive refinement. The scale of refinements from Tier1 to Tier2+ modelling for the ingredients, propyl paraben, benzoic acid and DMDM hydantoin were: 0.492 to 0.026; 1.93 to 0.042 and 1.61 to 0.027 mg/kg/day exposure dose. For propyl paraben, moving from Tier1 to Tier2+ represents a refinement from 49-fold to 3-fold overestimate of exposure when compared to a maximum estimate of 0.01 mg/kg/day exposure seen in human studies. Such refinements from worst case to realistic levels of exposure estimation can be critical in the demonstration of consumer safety., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: All authors are employed by the Cosmetics Industry. C Alexander-White is an independent consultant in chemicals safety assessment who was commissioned by Cosmetics Europe specifically for this project as a specialist in cosmetics safety evaluation and scientific writer., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

In Acidithiobacillus ferrooxidans, proteins such as CcO are present in the electron transport pathway. They cause ferrous iron oxidation to ferric leading to the electron release. CcO has two copper atoms (CuA, CuB). CuA plays an important role in electron transfer. According to previous studies, the conversion of histidine to methionine in a similar protein increased the redox potential and was directly related to the number of electrons received. Also, the binding of methionine 233 to CuA and CuB in the wild protein structure is the reason for the selection of the H230 M mutation in the CuA site. Then, wild-type and H230 M mutant were simulated in the presence of a bilayer membrane POPC using the gromacs version 5.1.4. The changes performed in the H230 M mutant were evaluated by MD simulations analyzes. CcO and CoxA proteins are the last two proteins in the chain and were docked by the PatchDock server. By H230 M mutation, the connection between CuA and M230 weakens. The M230 moves further away from CuA, resulting become more flexible. Therefore, the Methionine gets closer to E149 of the CoxA leading to the higher stability of the CcO/CoxA complex. The results of RMSF analysis at the mutation point showed a significant increase. This indicates more flexibility in the active site. And leads to an increase in E 0 in the mutation point, an increase in the rate of electron reception, and an improved bioleaching process., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background: A new domain of "personal and professional development" was introduced as a core competency of health-care providers. This study aimed to explore the experiences of learners and faculty members about what competencies or skills were essential for the professional development and success of health-care providers., Materials and Methods: This is a qualitative study using an inductive content analysis approach in 2019-2020. In the present study, 58 academic faculty members participated by purposeful sampling including ten associate professors (17.24%) and 24 assistance professors (41.37%), in addition to 23-year medical residents (20.65%) and 4 th -year nursing students (20.65%). Individual and group interviews were conducted. Data were analyzed by the inductive content analysis approach introduced by Graneheim and Lundman., Results: The qualitative data were classified in 953 open codes and eight categories, which were further divided into four main categories: "socio-emotional skills," "life-long learning skills," "coping skills," and "well-being strategies.", Conclusions: The present results showed socioemotional and coping skills affect interpersonal and professional interactions that contributed to their improved health-care providers' capabilities. Participants also considered lifelong learning as influential in developing professional capabilities and keeping their knowledge and skills up-to-date for accountability to duties. Moreover, using well-being strategies protects the mental and physical health of health-care providers. These skills are synergistic, and their combination can have a significant role in improving the personal and professional capabilities., Competing Interests: There are no conflicts of interest., (Copyright: © 2022 Journal of Education and Health Promotion.)

Cyc 1 (Cytochrome c 552 ) is a protein in the electron transport chain of the Acidithiobacillus ferrooxidans (Af) bacteria which obtain their energy from oxidation Fe 2+ to Fe 3+ . The electrons are directed through Cyc 2 , RCY (rusticyanin), Cyc 1 and Cox aa 3 proteins to O 2 . Cyc 1 protein consists of two chains, A and B. In the present study, a novel mutation (E121D) in the A chain of Cyc 1 protein was selected due to electron receiving from Histidine 143 of RCY. Then, the changes performed in the E121D mutant were evaluated by MD simulations analyzes. Cyc 1 and RCY proteins were docked by a Patchdock server. By E121D mutation, the connection between Zn 1388 of chain B and aspartate 121 of chain A weaken. Asp 121 gets farther from Zn 1388. Therefore, the aspartate gets closer to Cu 1156 of the RCY leading to the higher stability of the RCY/Cyc 1 complex. Further, an acidic residue (Glu121) becomes a more acidic residue (Asp121) and improves the electron transfer to Cyc 1 protein. The results of RMSF analysis showed further ligand flexibility in mutation. This leads to fluctuation of the active site and increases redox potential at the mutation point and the speed of electron transfer. This study also predicts that in all respiratory chain proteins, electrons probably enter the first active site via glutamate and exit histidine in the second active site of each respiratory chain protein., (© 2022. The Microbiological Society of Korea.)

The current standard of care for many patients with HER2-positive breast cancer is neoadjuvant chemotherapy in combination with anti-HER2 agents, based on HER2 amplification as detected by in situ hybridization (ISH) or protein immunohistochemistry (IHC). However, hematoxylin & eosin (H&E) tumor stains are more commonly available, and accurate prediction of HER2 status and anti-HER2 treatment response from H&E would reduce costs and increase the speed of treatment selection. Computational algorithms for H&E have been effective in predicting a variety of cancer features and clinical outcomes, including moderate success in predicting HER2 status. In this work, we present a novel convolutional neural network (CNN) approach able to predict HER2 status with increased accuracy over prior methods. We trained a CNN classifier on 188 H&E whole slide images (WSIs) manually annotated for tumor Regions of interest (ROIs) by our pathology team. Our classifier achieved an area under the curve (AUC) of 0.90 in cross-validation of slide-level HER2 status and 0.81 on an independent TCGA test set. Within slides, we observed strong agreement between pathologist annotated ROIs and blinded computational predictions of tumor regions / HER2 status. Moreover, we trained our classifier on pre-treatment samples from 187 HER2+ patients that subsequently received trastuzumab therapy. Our classifier achieved an AUC of 0.80 in a five-fold cross validation. Our work provides an H&E-based algorithm that can predict HER2 status and trastuzumab response in breast cancer at an accuracy that may benefit clinical evaluations., (© 2021. The Author(s), under exclusive licence to United States & Canadian Academy of Pathology.)

Acidithiobacillus ferrooxidans (Af) is an acidophilic bacterium that grows in rigid surroundings and gets its own energy from the oxidation of Fe 2+ to Fe 3+ . These bacteria are involved in the bioleaching process. Cyc 1 is a periplasmic protein with a crucial role in electron transportation in the respiratory chain. His53 of the Cyc 1 protein, involved in electron transfer to CoxB, was selected for mutation and bioinformatics studies. His53 was substituted by Ile using PyMol software. Molecular dynamics simulations were performed for wild and mutant types of Cyc 1 protein. The conformational changes of mutated protein were studied by analyzing RMSD, RMSF, SASA, Rg, H Bond, and DSSP. The results of the RMSF analysis indicated an increase in the flexibility of the ligand in the mutant. Finally, active site instability leads to an increase in the value of E 0 at the mutation point and improving electron transfer. On the other, His53 in Cyc 1 is interconnected to Glu126 in CoxB through the water molecule (W76) and hydrogen bonding. In the H53I mutation, there was a decrease in the distance between H2O 2030, 2033, and isoleucine 53, and subsequently, the distance to the water molecule 76 between the two proteins was reduced and strengthens the hydrogen bond between Cyc 1 and CoxB, finally improves electron transfer and the bioleaching process., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Histopathological images are a rich but incompletely explored data type for studying cancer. Manual inspection is time consuming, making it challenging to use for image data mining. Here we show that convolutional neural networks (CNNs) can be systematically applied across cancer types, enabling comparisons to reveal shared spatial behaviors. We develop CNN architectures to analyze 27,815 hematoxylin and eosin scanned images from The Cancer Genome Atlas for tumor/normal, cancer subtype, and mutation classification. Our CNNs are able to classify TCGA pathologist-annotated tumor/normal status of whole slide images (WSIs) in 19 cancer types with consistently high AUCs (0.995 ± 0.008), as well as subtypes with lower but significant accuracy (AUC 0.87 ± 0.1). Remarkably, tumor/normal CNNs trained on one tissue are effective in others (AUC 0.88 ± 0.11), with classifier relationships also recapitulating known adenocarcinoma, carcinoma, and developmental biology. Moreover, classifier comparisons reveal intra-slide spatial similarities, with an average tile-level correlation of 0.45 ± 0.16 between classifier pairs. Breast cancers, bladder cancers, and uterine cancers have spatial patterns that are particularly easy to detect, suggesting these cancers can be canonical types for image analysis. Patterns for TP53 mutations can also be detected, with WSI self- and cross-tissue AUCs ranging from 0.65-0.80. Finally, we comparatively evaluate CNNs on 170 breast and colon cancer images with pathologist-annotated nuclei, finding that both cellular and intercellular regions contribute to CNN accuracy. These results demonstrate the power of CNNs not only for histopathological classification, but also for cross-comparisons to reveal conserved spatial behaviors across tumors.

Background: Adverse drug reactions (ADRs) are one of the leading causes of morbidity and mortality in health care. Understanding which drug targets are linked to ADRs can lead to the development of safer medicines., Methods: Here, we analyse in vitro secondary pharmacology of common (off) targets for 2134 marketed drugs. To associate these drugs with human ADRs, we utilized FDA Adverse Event Reports and developed random forest models that predict ADR occurrences from in vitro pharmacological profiles., Findings: By evaluating Gini importance scores of model features, we identify 221 target-ADR associations, which co-occur in PubMed abstracts to a greater extent than expected by chance. Amongst these are established relations, such as the association of in vitro hERG binding with cardiac arrhythmias, which further validate our machine learning approach. Evidence on bile acid metabolism supports our identification of associations between the Bile Salt Export Pump and renal, thyroid, lipid metabolism, respiratory tract and central nervous system disorders. Unexpectedly, our model suggests PDE3 is associated with 40 ADRs., Interpretation: These associations provide a comprehensive resource to support drug development and human biology studies., Funding: This study was not supported by any formal funding bodies., Competing Interests: Declaration of Competing Interest None., (Copyright © 2020 The Author(s). Published by Elsevier B.V. All rights reserved.)

This study aimed to compare the diagnostic accuracy of heart, lung and inferior vena cava (IVC) ultrasonography modalities, alone and combined, for possible added accuracy in diagnosing acute decompensated heart failure (ADHF), in a group of patients with the final diagnosis of ADHF based on plasma level of B-type natriuretic peptide (BNP) as the standard. The present study is a diagnostic accuracy study, which was carried out in the emergency department of Imam Khomeini hospital, affiliated to Tehran University of Medical Sciences, in 2014-2015. All patients over 18 years old, who were referred to emergency department with complaint of acute dyspnea were regarded as eligible and no exclusion criteria were considered. All ultrasounds were performed by a trained emergency medicine resident and then saved and classified for each patient, separately, and reviewed by the attending emergency medicine physician. In this study, patients with BNP levels higher than 500 pg/ml were considered positive for dyspnea caused by heart failure. A total of 120 patients with an average age of 60.83 ± 16.528 years were studied, 64 (53%) of which were male. In total, 47.5% of patients had a BNP level over 500 pg/ml. Among patients with positive ultrasound, 94.7% were true positive and among those with a negative ultrasound, 61.4% were true negative. Based on the findings, B-line ≥ 10 has the highest specificity and left ventricular ejection fraction (LVEF) < 45% has the highest sensitivity. The combination of LVEF and IVC collapsibility index (IVC-CI), LVEF and BLC, IVC-CI and BLC, and IVC-CI and BBPC had a higher specificity rate and combination of LVEF and BBPC and BLC and BBPC had the highest sensitivity. Sensitivity, specificity, positive predictive value and negative predictive value of all three ultrasounds combined were 31.6%, 98.4%, 94.7% and 61.4%, respectively. In this study, the diagnostic accuracy of double and triple ultrasonography of heart, lung and IVC in the diagnosis of ADHF was very high, among which triple ultrasonography was more preferable.

Background: Transcription factors (TFs) are proteins that are fundamental to transcription and regulation of gene expression. Each TF may regulate multiple genes and each gene may be regulated by multiple TFs. TFs can act as either activator or repressor of gene expression. This complex network of interactions between TFs and genes underlies many developmental and biological processes and is implicated in several human diseases such as cancer. Hence deciphering the network of TF-gene interactions with information on mode of regulation (activation vs. repression) is an important step toward understanding the regulatory pathways that underlie complex traits. There are many experimental, computational, and manually curated databases of TF-gene interactions. In particular, high-throughput ChIP-Seq datasets provide a large-scale map or transcriptional regulatory interactions. However, these interactions are not annotated with information on context and mode of regulation. Such information is crucial to gain a global picture of gene regulatory mechanisms and can aid in developing machine learning models for applications such as biomarker discovery, prediction of response to therapy, and precision medicine., Methods: In this work, we introduce a text-mining system to annotate ChIP-Seq derived interaction with such meta data through mining PubMed articles. We evaluate the performance of our system using gold standard small scale manually curated databases., Results: Our results show that the method is able to accurately extract mode of regulation with F-score 0.77 on TRRUST curated interaction and F-score 0.96 on intersection of TRUSST and ChIP-network. We provide a HTTP REST API for our code to facilitate usage. Availibility: Source code and datasets are available for download on GitHub: https://github.com/samanfrm/modex., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Introduction: This study aimed to explore the challenges of professional identity formation at clinical education environments from the faculty members' viewpoints., Methods: This is a qualitative study. The population consisted of clinical faculty members of Tehran University of Medical Sciences. In this study, 39 faculty members participated in an in-depth semi-structured interview. To analyze the data, conventional content analysis approach was used. Open coding was extracted from the participants' statements that represented their experiences. Then, based on their similarities, the codes were classified. Subcategories were emerged and after arranging, they were classified into categories based on their relationships., Results: Instability of professional commitment, patient-centeredness as the missing loop care and treatment, and inappropriate conductive context were explored as the challenges of professional identity in clinical educational environment., Conclusion: According to the results of the study, the formation of professional identity among the providers is not an easy task because many factors affect the formation of professional identity. Therefore, a comprehensive shift towards forming the professional identity at individual and organizational level should be planned., Competing Interests: Conflict of Interest: None Declared., (Copyright: © Shiraz University of Medical Sciences.)

Inference of active regulatory mechanisms underlying specific molecular and environmental perturbations is essential for understanding cellular response. The success of inference algorithms relies on the quality and coverage of the underlying network of regulator-gene interactions. Several commercial platforms provide large and manually curated regulatory networks and functionality to perform inference on these networks. Adaptation of such platforms for open-source academic applications has been hindered by the lack of availability of accurate, high-coverage networks of regulatory interactions and integration of efficient causal inference algorithms. In this work, we present CIE, an integrated platform for causal inference of active regulatory mechanisms form differential gene expression data. Using a regularized Gaussian Graphical Model, we construct a transcriptional regulatory network by integrating publicly available ChIP-seq experiments with gene-expression data from tissue-specific RNA-seq experiments. Our GGM approach identifies high confidence transcription factor (TF)-gene interactions and annotates the interactions with information on mode of regulation (activation vs. repression). Benchmarks against manually curated databases of TF-gene interactions show that our method can accurately detect mode of regulation. We demonstrate the ability of our platform to identify active transcriptional regulators by using controlled in vitro overexpression and stem-cell differentiation studies and utilize our method to investigate transcriptional mechanisms of fibroblast phenotypic plasticity., (© The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Nonsyndromic oral clefting (NSOC) is although one of the most common congenital disorders worldwide, its underlying molecular basis remains elusive. This process has been hindered by the overwhelmingly high level of heterogeneity observed. Given that hitherto multiple loci and genes have been associated with NSOC, and that complex diseases are usually polygenic and show a considerable level of missing heritability, we used a systems genetics approach to reconstruct the NSOC network by integrating human-based physical and regulatory interactome with whole-transcriptome microarray data. We show that the network component contains 53% (23/43) of the curated NSOC-implicated gene set and displays a highly significant propinquity (P < 0.0001) between genes implicated at the genomic level and those differentially expressed at the transcriptome level. In addition, we identified bona fide candidate genes based on topological features and dysregulation (e.g. ANGPTL4), and similarly prioritised genes at GWA loci (e.g. MYC and CREBBP), thus providing further insight into the underlying heterogeneity of NSOC. Gene ontology analysis results were consistent with the NSOC network being associated with embryonic organ morphogenesis and also hinted at an aetiological overlap between NSOC and cancer. We therefore recommend this approach to be applied to other heterogeneous complex diseases to not only provide a molecular framework to unify genes which may seem as disparate entities linked to the same disease, but to also predict and prioritise candidate genes for further validation, thus addressing the missing heritability.