bluuebunny/crossref_metadata_2025_split huggingface dataset:
Three-Step Excision: An Easy Way for Composite Labia Minora and Lateral Clitoral Hood Reduction
Authors: Xia Zenan , Liu Chang-Yi , Yu Nanze , Liu Zhifei , Zeng Ang , Zhang Yuwei , Si Loubin , Long Fei , Zhu Lin , Wang Xiaojun 
Published: October 2021

Background:
Hypertrophy of the labia minora with lateral clitoral hood redundancy is common, but the excess clitoral hood is often overlooked during labiaplasty, which may result in imbalanced and unsatisfactory outcomes. The purpose of this study was to present an easy method of three-step excision for composite labia minora and lateral clitoral hood reduction.

Methods:
The procedure was performed in three steps: the prominent clitoral hood skin parallel to the labia majora and the clitoral hood sulcus was removed first; then, the protuberant portion of the labia minora was removed by wedge resection; and finally, a triangle at the junction between the labia minora and the clitoral hood was trimmed. Patients were required to return for examination on the first day and within 14 days after surgery. Follow-ups were arranged on the Internet or at the outpatient clinic. Satisfaction questionnaires were completed during follow-up.

Results:
Between January of 2016 and January of 2020, 136 patients underwent composite labia minora and lateral clitoral hood reduction. Ages ranged from 9 to 55 years. Six patients experienced complications (4.4 percent) and five underwent revision surgery (3.7 percent). The overall satisfaction rate within 14 days and after 3 months following surgery was 91.0 percent and 95.5 percent, respectively. Preoperative discomfort was resolved in 43.0 percent and significantly relieved in 54.2 percent, and sex life was improved in 70.9 percent.

Conclusions:
Three-step excision is effective and safe for composite labia minora and lateral clitoral hood reduction with very high satisfaction. Considering the advantages of easy preoperative design and controllable tissue removal, this method could be a better alternative to the present procedures.

CLINICAL QUESTION/LEVEL OF EVIDENCE:
Therapeutic, IV.
Cell-type specific cis-eQTLs in eight brain cell-types identifies novel risk genes for human brain disorders
Authors: Bryois Julien , Calini Daniela , Macnair Will , Foo Lynette , Urich Eduard , Ortmann Ward , Iglesias Victor Alejandro , Selvaraj Suresh , Nutma Erik , Marzin Manuel , Amor Sandra , Williams Anna , Castelo-Branco Gonçalo , Menon Vilas , De Jager Philip , Malhotra Dheeraj 
Published: October 2021

AbstractMost expression quantitative trait loci (eQTL) studies to date have been performed in heterogeneous brain tissues as opposed to specific cell types. To investigate the genetics of gene expression in adult human cell types from the central nervous system (CNS), we performed an eQTL analysis using single nuclei RNA-seq from 196 individuals in eight CNS cell types. We identified 6108 eGenes, a substantial fraction (43%, 2620 out of 6108) of which show cell-type specific effects, with strongest effects in microglia. Integration of CNS cell-type eQTLs with GWAS revealed novel relationships between expression and disease risk for neuropsychiatric and neurodegenerative diseases. For most GWAS loci, a single gene colocalized in a single cell type providing new clues into disease etiology. Our findings demonstrate substantial contrast in genetic regulation of gene expression among CNS cell types and reveal genetic mechanisms by which disease risk genes influence neurological disorders.
Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slides
Authors: Xu Feng , Zhu Chuang , Tang Wenqi , Wang Ying , Zhang Yu , Li Jie , Jiang Hongchuan , Shi Zhongyue , Liu Jun , Jin Mulan 
Published: October 2021

AbstractObjectivesTo develop and validate a deep learning (DL) based primary tumor biopsy signature for predicting axillary lymph node (ALN) metastasis preoperatively in early breast cancer (EBC) patients with clinically negative ALN.MethodsA total of 1058 EBC patients with pathologically confirmed ALN status were enrolled from May 2010 to August 2020. A deep learning core-needle biopsy (DL-CNB) model was built on the attention based multiple instance learning (AMIL) framework to predict ALN status utilizing the deep learning features, which were extracted from the cancer areas of digitized whole-slide images (WSIs) of breast CNB specimens annotated by two pathologists. Accuracy, sensitivity, specificity, receiver operating characteristic (ROC) curves, and areas under the receiver operating characteristic curve (AUCs) were analyzed to evaluate our model.ResultsThe best performing DL-CNB model with VGG16_BN as the feature extractor achieved an AUC of 0.816 (95% confidence interval (CI): 0.758, 0.865) in predicting positive ALN metastasis in the independent test cohort. Furthermore, our model incorporating the clinical data, which was called DL-CNB+C, yielded the best accuracy of 0.831 (95%CI: 0.775, 0.878), especially for patients younger than 50 years (AUC: 0.918, 95%CI: 0.825, 0.971). The interpretation of DL-CNB model showed that the top signatures most predictive of ALN metastasis were characterized by the nuclei features including density (p=0.015), circumference (p=0.009), circularity (p=0.010), and orientation (p=0.012).ConclusionOur study provides a novel deep learning-based biomarker on primary tumor CNB slides to predict the metastatic status of ALN preoperatively for patients with early breast cancer.
Artificial Intelligence for the Diagnosis and Treatment of Diabetes Kidney Disease: a systematic review
Authors: Abrar Shams Mohammad 
Published: October 2021

AbstractBackgroundDiabetic nephropathy (DN) is a serious microvascular complication that affects 40% of diabetes patients. In the last decade, artificial intelligence (AI) has been widely used in both structured and unstructured clinical data to improve the treatment of patients/potential patients with DN.MethodsThis systematic review aims to cover all applications of AI in the clinical use of DN or related topics. Studies were searched in four open-access databases (Pubmed, IEEE Xplore, DBLP Computer Science Bibliography, and ACM digital library). Finally, the author manually searched the reference list of included studies in the study for additional relevant articles.ResultsFinally, a total of 24 original peers reviewed articles were included in this study. Through a manual data extraction, the summary of key information such as applied AI algorithm, main outcomes, performance evaluation etc. was taken. Then the included studies underwent a quality assessment criterion, assessing the reproducibility, generalizability etc. Most of the included studies revealed that the AI frameworks outperformed conventional statistical methods. A summary of the limitations, such as lack of data availability or external validation of the framework, in the included studies, was also included.ConclusionThe rapid advancement of the AI framework and the exponential data generation in healthcare can be utilized and applied in clinical practices. The aid of AI can be instrumental in the treatment of DN.
PAGEANT: Personal Access to Genome and Analysis of Natural Traits
Authors: Huang Jie , Liang Zhi-Sheng , Pallotti Stefano , Ranson Janice M. , Llewellyn David J. , Zheng Zhi-Jie , King Dan A. , Zhou Qiang , Zheng Houfeng , Napolioni Valerio 
Published: October 2021

AbstractGWASs have identified numerous genetic variants associated with a wide variety of diseases, yet despite the wide availability of genetic testing the insights that would enhance the interpretability of these results are not widely available to members of the public. As a proof of concept and demonstration of technological feasibility, we developed PAGEANT (Personal Access to Genome & Analysis of Natural Traits), usable through Graphical User Interface or command line-based version, aiming to serve as a protocol and prototype that guides the overarching design of genetic reporting tools. PAGEANT is structured across five core modules, summarized by five Qs: (1) Quality assurance of the genetic data; (2) Qualitative assessment of genetic characteristics; (3) Quantitative assessment of health risk susceptibility based on polygenic risk scores and population reference; (4) Query of third-party variant databases (e.g., ClinVAR and PharmGKB); and (5) Quick Response code of genetic variants of interest. Literature review was conducted to compare PAGEANT with academic and industry tools. For 2,504 genomes made publicly available through the 1,000 Genomes Project, we derived their genomic characteristics for a suite of qualitative and quantitative traits. One exemplary trait is susceptibility to COVID-19, based on the most up-to-date scientific findings reported.
Access to social protection by people living with, at risk of, or affected by HIV in Eswatini, Malawi, Tanzania and Zambia - results from Population-Based HIV Impact Assessments
Authors: Chipanta David , Pettifor Audrey , Edwards Jessie , Giovenco Danielle , Topazian Hillary Mariko , Bray Rachel M. , Millington Monique C. , Estill Janne , Keiser Olivia , Justman Jessica E 
Published: October 2021

AbstractWe aimed to measure social protection (SP) coverage among the general population and women and men living with HIV (WLHIV, MLHV), female and male sex workers (FSW, MSW), men who have sex with men (MSM), adolescent girls young women (AGYW), and orphans vulnerable children (OVC). We used Population-Based HIV Impact Assessments data from Eswatini, Malawi, Tanzania and Zambia. We generated survey-weighted proportions for each population group receiving any SP benefits, along with 95% confidence intervals (CI) using jackknife variance estimation. The proportion reported receiving SP benefits among the general population ranged from 7.7% (95% CI: 6.7%–8.8%) in Zambia to 39.6% (95% CI: 36.8%– 42.5%) in Eswatini. SP benefits by WLHIV, MLHIV, AGYW, OVC, SW and MSM – were lower than the 2017-19 global average of 45%. Data on access to SP benefits by people living with or affected by HIV from other regions is needed to estimate their SP coverage better.
Impact of Variability in Cell Cycle Periodicity on Cell Population Dynamics
Authors: Nowak Chance M. , Quarton Tyler , Bleris Leonidas 
Published: October 2021

AbstractThe cell cycle consists of a series of orchestrated events controlled by molecular sensing and feedback networks that ultimately drive the duplication of total DNA and the subsequent division of a single parent cell into two daughter cells. The ability to block the cell cycle and synchronize cells within the same phase has helped understand factors that control cell cycle and the properties of each individual phase. Intriguingly, when cells are released from a synchronized state, they do not maintain synchronized cell division and rapidly become asynchronous. The rate and factors that control cellular desynchronization remain largely unknown. In this study, using a combination of experiments and simulations, we investigate the desynchronization properties in cervical cancer cells (HeLa) starting from the G1/S boundary following double-thymidine block. Propidium iodide (PI) DNA staining was used to perform flow cytometry cell cycle analysis at regular intervals of 8 hours, and a custom auto-similarity function to assess the desynchronization and quantify the convergence to asynchronous state. In parallel, we developed a single-cell phenomenological model the returns the DNA concentration across the cell cycle stages and fitted the parameters using experimental data. Simulations of population of cells reveal that the cell cycle desynchronization rate is primarily sensitive to the variability of cell cycle duration within a population. To validate the model prediction, we introduced lipopolysaccharide (LPS) to increase cell cycle noise. Indeed, we observed an increase in cell cycle variability under LPS stimulation in HeLa cells, accompanied with an enhanced rate of cell cycle desynchronization. Our results show that the desynchronization rate of artificially synchronized in-phase cell populations can be used a proxy of the degree of variance in cell cycle periodicity, an underexplored axis in cell cycle research.
Transcriptomic analysis revealed reactive oxygen species scavenging mechanisms associated with ferrous iron toxicity in aromatic Keteki Joha rice
Authors: Regon Preetom , Dey Sangita , Rehman Mehzabin , Pradhan Amit Kumar , Tanti Bhaben , Das Talukdar Anupam , Panda Sanjib Kumar 
Published: October 2021

AbstractLowland acidic soils with water-logged regions are often affected by ferrous iron (Fe2+) toxicity, a major yield-limiting factor of rice production. The Reactive Oxygen Species (ROS) was hypothesized to be crucial under severe Fe2+ toxicity conditions. However, molecular mechanisms and associated ROS homeostasis genes are still not well-explored. In this study, a comparative RNA-Seq based transcriptome analysis was conducted to understand the Fe2+ toxicity tolerance mechanism in aromatic Keteki Joha. About 69 Fe homeostasis related genes and their homologs were identified, where most of the genes were downregulated. Differentially expressed genes (DEGs) are associated with biological processes-response to stress, stimulus and abiotic stimulus. DEGs involved in the Biosynthesis of amino acids, RNA degradation, Glutathione metabolism etc. were induced, whereas, Phenylpropanoid biosynthesis, Photosynthesis, and Fatty acid elongation were inhibited. The Mitochondrial iron transporter (OsMIT), Vacuolar Iron Transporter 2 (OsVIT2), Ferritin (OsFER), Vacuolar Mugineic Acid Transporter (OsVMT), Phenolic Efflux Zero1 (OsPEZ1), Root Meander Curling (OsRMC), Nicotianamine synthase (OsNAS3), etc. were upregulated in different tissues suggesting the importance of Fe retention and sequestration for detoxification. However, several antioxidants, ROS scavenging genes and abiotic stress-responsive transcription factors indicate ROS homeostasis as one of the most important defense mechanisms under severe Fe2+ toxicity. The CAT, GSH, APX, MDHAR, DHAR, GR were upregulated. Moreover, abiotic stress-responsive transcription factors NAC, MYB, ARF, bZIP, WRKY, C2H2-ZFP were also upregulated. Accordingly, ROS homeostasis has been proposed to be an important defense mechanism under such conditions. Thus, our results will enrich the knowledge of understanding Fe-homeostasis in rice.
ONTdeCIPHER: An amplicon-based nanopore sequencing pipeline for tracking pathogen variants
Authors: Cherif Emira , Thiam Fatou Seck , Salma Mohammad , Rivera-Ingraham Georgina , Justy Fabienne , Deremarque Theo , Breugnot Damien , Doudou Jean-Claude , Gozlan Rodolphe Elie , Combe Marine 
Published: October 2021

AbstractMotivationAmplicon-based nanopore sequencing is increasingly used for molecular surveillance during epidemics (e.g. ZIKA, EBOLA) or pandemics (e.g. SARS-CoV-2). However, there is still a lack of versatile and easy-to-use tools that allow users with minimal bioinformatics skills to perform the main steps of downstream analysis, from quality testing to SNPs effect to phylogenetic analysis.ResultsHere, we present ONTdeCIPHER, an amplicon-based Oxford Nanopore Technology (ONT) sequencing pipeline to analyze the genetic diversity of SARS-CoV-2 and other pathogenes. Our pipeline integrates 13 bioinformatics tools. With a single command line and a simple configuration file, users can pre-process their data and obtain the sequencing statistics, reconstruct the consensus genome, identify variants and their effects for each viral isolate, infer lineage and, finally perform multi-sequence alignments and phylogenetic analyses.Availability and implementation:ONTdeCIPHER is available at https://github.com/emiracherif/ONTdeCIPHERContactemira.cherif@ird.frSupplementary informationSupplementary data are available at …
SunCatcher: Clonal Barcoding with qPCR-Based Detection Enables Functional Analysis of Live Cells and Generation of Custom Combinations of Cells for Research and Discovery
Authors: Guo Qiuchen , Spasic Milos , Maynard Adam , Goreczny Gregory J. , Olive Jessica F. , Bizuayehu Amanuel , McAllister Sandra S. 
Published: October 2021

AbstractOver recent decades, cell lineage tracing, clonal analyses, molecular barcoding, and single cell “omic” analysis methods have proven to be valuable tools for research and discovery. Here, we report a clonal molecular barcoding method, which we term SunCatcher, that enables longitudinal tracking and retrieval of live barcoded cells for further analysis. Briefly, single cell-derived clonal populations are generated from any complex cell population and each is infected with a unique, heritable molecular barcode. One can combine the barcoded clones to recreate the original parental cell population or generate custom pools of select clones, while also retaining stocks of each individual barcoded clone. We developed two different barcode deconvolution methods: a Next-Generation Sequencing method and a highly sensitive, accurate, rapid, and inexpensive quantitative PCR-based method for identifying and quantifying barcoded cellsin vitroandin vivo. Because stocks of each individual clone are retained, one can analyze not only the positively selected clones but also the negatively selected clones result from any given experiment. We used SunCatcher to barcode individual clones from mouse and human breast cancer cell lines. Heterogeneous pools of barcoded cells reliably reproduced the original proliferation rates, tumor-forming capacity, and disease progression as the original parental cell lines. The SunCatcher PCR-based approach also proved highly effective for detecting and quantifying early spontaneous metastases from orthotopic sites that would otherwise have not been detected by conventional methods. We envision that SunCatcher can be applied to any cell-based studies and hope it proves a useful tool for the research community.
A High-Resolution Method for the Systematic Detection of EMS-Induced Mutations in a Sequenced Population
Authors: Simons Jared M. , Herbert Tim C. , Kauffman Coleby , Batete Marc Y. , Simpson Andrew T. , Katsuki Yuka , Le Dong , Amundson Danielle , Buescher Elizabeth M. , Weil Clifford , Tuinstra Mitch , Addo-Quaye Charles 
Published: October 2021

AbstractThe precise detection of causal DNA mutations is very crucial for forward genetic studies. Several sources of errors contribute to false-positive detections by current variant-calling algorithms, and these impact associating phenotypes with genotypes. To improve the accuracy of mutation detection we propose and implemented a high-resolution binning method for the accurate detection of likely EMS-induced mutations in a sequenced mutant population. The approach also incorporates a novel clustering algorithm for detecting likely false negatives with high accuracy. Sorghum bicolor is a very valuable crop species with tremendous potential for uncovering novel gene functions associated with highly desirable agronomical traits. We demonstrate the precision of the proposed method in the detection of likely EMS-induced mutations in the publicly available low-cost sequencing of the M3 generation from 600 sorghum BTx623 mutants. The method detected 3,274,606 single nucleotide polymorphisms (SNPs) of which 96% (3,141,908) were G/C to A/T DNA substitutions, as expected by EMS-mutagenesis action. We demonstrated the general applicability of the method, and showed a high concordance, 94% (3,074,759) SNPs overlap between SAMtools-based and GATK-based variant-calling algorithms. We also implemented a novel clustering algorithm which uncovered evidence for an additional 223,048 likely false-negative shared EMS-induced mutations. The final 3,497,654 SNPs represents an 87% increase in SNPs detected in the previous analysis of the sorghum mutant population. Annotation of the final SNPs revealed 10,263 high impact and 136,639 moderate impact SNPs, including 7,217 stop-gained mutations, and an average of 12 stop-gained mutations per mutant. We have implemented a public search database for this new genetic resource of 30,285 distinct sorghum genes containing medium or high impact EMS-induced mutations. Seedstock for a select 486 of the 600 described mutants are publicly available in the Germplasm Resources Information Network (GRIN) database.
The Endocytic Recycling Compartment Serves as a Viral Factory for Hepatitis E Virus
Authors: Bentaleb Cyrine , Hervouet Kévin , Montpellier Claire , Camuzet Charline , Ferrié Martin , Burlaud-Gaillard Julien , Bressanelli Stéphane , Metzger Karoline , Werkmeister Elisabeth , Ankavay Maliki , Janampa Nancy Leon , Marlet Julien , Roux Julien , Deffaud Clarence , Goffard Anne , Rouillé Yves , Dubuisson Jean , Roingeard Philippe , Aliouat-Denis Cécile-Marie , Cocquerel Laurence 
Published: October 2021

AbstractBackground & AimsAlthough Hepatitis E virus (HEV) is the major leading cause of enterically transmitted viral hepatitis worldwide, many gaps remain in the understanding of the HEV lifecycle. Notably, viral factories induced by HEV have not been documented yet and it is currently unknown whether HEV infection leads to cellular membrane modelling as many positive-strand RNA viruses. HEV genome encodes three proteins, the ORF1 replicase, the ORF2 capsid protein and the ORF3 protein involved in virion egress. Previously, we demonstrated that HEV produces different ORF2 isoforms including the virion-associated ORF2i form. Here, we aimed to probe infectious particles and viral factories in HEV-producing cells, using antibodies directed against the different ORF2 isoforms.MethodsWe generated monoclonal antibodies that specifically recognize the particle-associated ORF2i form, and antibodies that recognize the different ORF2 isoforms. We used them in confocal and electron microscopy approaches to probe viral factories in HEV-producing cells. We performed an extensive colocalization study of viral proteins with subcellular markers. We analyzed the impact of silencing Rab11, a central player of the endocytic recycling compartment (ERC).ResultsOne of the antibodies, named P1H1 and targeting the N-terminus of ORF2i, recognized delipidated HEV particles. Confocal and ultrastructural microscopy analyses of HEV-producing cells revealed an unprecedented HEV-induced membrane network containing tubular and vesicular structures. These subcellular structures were enriched in ORF2 and ORF3 proteins, and were dependent on the ORF3 expression and ORF2i capsid protein assembly. Colocalization and silencing analyses revealed that these structures are derived from the ERC.ConclusionsOur study reveals that HEV hijacks the ERC and forms a membrane network of vesicular and tubular structures that might be the hallmark of HEV infection.Lay summaryHepatitis E virus (HEV) is the leading cause of acute hepatitis worldwide but many steps of its lifecycle are still elusive. Thanks to the development of new antibodies that recognize the different forms of the HEV capsid protein, we were able to visualize vesicular and tubular structures that were established by the virus in the host cell. In addition, extensive efforts to identify these structures led us to conclude that HEV hijacks the endocytic recycling compartment of the cell to form this network of vesicles and tubules, which might be the hallmark of HEV infection.