bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Slingshot phosphatase 2 is required for acrosome biogenesis during spermatogenesis in mice
Authors: Xu Ke , Su Xianwei , Fang Kailun , Lv Yue , Lu Gang , Chan Waiyee , Chen Zi-Jiang , Ma Jinlong , Liu Hongbin 
Published: September 2022

AbstractThe acrosome is a membranous organelle positioned in the anterior portion of sperm head and is essential for male fertility. Acrosome biogenesis requires the dynamic cytoskeletal shuttling of vesicles towards nascent acrosome which is regulated by a series of accessory proteins. However, much remains unknown about the molecular basis underlying this process. Here, we generatedSsh2knock-out (KO) mice and show that Slingshot phosphatase 2 (SSH2), a regulator of actin remodeling, is essential for acrosome biogenesis and male fertility. InSsh2KO males, spermatogenesis was arrested at the early spermatid stage with enhanced germ cell apoptosis and the impaired acrosome biogenesis was characterized by defective transport/fusion of proacrosomal vesicles. Moreover, disorganized F-actin structures accompanied by excessive phosphorylation of COFILIN were observed in testes ofSsh2KO mice. Collectively, our data reveal a modulatory role for SSH2 in acrosome biogenesis through COFILIN-mediated actin remodeling and the indispensability of this phosphatase in male fertility in mice.
Dehydration alters transcript levels in the mosquito midgut, likely facilitating rapid rehydration
Authors: Holmes Christopher J. , Brown Elliott S. , Sharma Dhriti , Warden Matthew , Pathak Atit , Payton Blaine , Nguyen Quynh , Spangler Austin , Sivakumar Jaishna , Hendershot Jacob M. , Benoit Joshua B. 
Published: September 2022

AbstractThe mosquito midgut is an important site for bloodmeal regulation while also acting as a primary site for pathogen exposure within the mosquito. Recent studies show that exposure to dehydrating conditions alters mosquito bloodfeeding behaviors as well as post-feeding regulation, likely altering how pathogens interact with the mosquito. Unfortunately, few studies have explored the underlying dynamics between dehydration and bloodmeal utilization, and the overall impact on disease transmission dynamics remains veiled. In this study, we find that dehydration-based feeding in the yellow fever mosquito,Aedes aegypti, prompts alterations to midgut gene expression, as well as subsequent physiological factors involving water control and post-bloodfeeding (pbf) regulation. Altered expression of ion transporter genes in the midgut of dehydrated mosquitoes and rapid reequilibration of hemolymph osmolality after a bloodmeal indicate an ability to expedite fluid and ion processing. These alterations ultimately indicate that femaleA. aegyptiemploy mechanisms to ameliorate the detriments of dehydration by imbibing a bloodmeal, providing an effective avenue for rehydration. Continued research into bloodmeal utilization and the resulting effects on arthropod-borne transmission dynamics becomes increasingly important as drought prevalence is increased by climate change.
Chronic Gq activation of ventral hippocampal neurons and astrocytes differentially affects memory and behavior
Authors: Suthard Rebecca L. , Jellinger Alexandra L. , Surets Michelle , Shpokayte Monika , Pyo Angela Y. , Buzharsky Michelle D. , Senne Ryan A. , Dorst Kaitlyn , Leblanc Heloise , Ramirez Steve 
Published: September 2022

AbstractNetwork dysfunction is implicated in numerous diseases and psychiatric disorders, and the hippocampus serves as a common origin for these abnormalities. To test the hypothesis that chronic modulation of neurons and astrocytes induces impairments in cognition, we activated the hM3D(Gq) pathway in CaMKII+ neurons or GFAP+ astrocytes within the ventral hippocampus across 3, 6 and 9 months. CaMKII-hM3Dq activation impaired fear extinction at 3 months and acquisition at 9 months. Both CaMKII-hM3Dq manipulation and aging had differential effects on anxiety and social interaction. GFAP-hM3Dq activation impacted fear memory at 6 and 9 months. GFAP-hM3Dq activation impacted anxiety in the open field only at the earliest time point. CaMKII-hM3Dq activation modified the number of microglia, while GFAP-hM3Dq activation impacted microglial morphological characteristics, but neither affected these measures in astrocytes. Overall, our study elucidates how distinct cell types can modify behavior through network dysfunction, while adding a more direct role for glia in modulating behavior.HighlightsCaMKII- and GFAP-Gq activation impacted memory, anxiety, and social behaviors.Novel environment exploration was affected by CaMKII- and GFAP-Gq activation.CaMKII-Gq modified microglial number, while GFAP-Gq affected microglial morphology.Neither cell manipulation affected astrocytic number or morphology.
Illuminating histidine phosphorylation in the pancreatic tumor microenvironment
Authors: Luhtala Natalie , Lytle Nikki , DelGiorno Kathleen E. , Shi Yu , Naeem Razia , Hollingsworth Michael A. , Kaech Susan M. , Wahl Geoffrey M. , Hunter Tony 
Published: September 2022

AbstractDevelopment of phosphohistidine (pHis) antibodies has significantly advanced our understanding of pHis contributions to tumor biology, including a tumor suppressive role for a pHis phosphatase, a metastasis suppressive role for His kinases, and pHis regulation of T cell receptor signaling. Using these antibodies, we investigated pHis pathway regulation in the mouse pancreatic tumor microenvironment. We identified deregulated expression of pHis and pHis phosphatases that correlated with mouse pancreatic tumor progression. We developed a protocol to circumvent the acid and heat-sensitivity of pHis signals, enabling their co-staining with other proteins in FFPE tissue, identifying a significant enrichment of 1-pHis and a subtype of 3-pHis signals (Gly-3-pHis) in the stroma. We discovered increased Gly-3-pHis levels in tumor-associated myeloid cells mainly resulting from elevated ATP citrate lyase 3-pHis levels and predicted the existence of pHis in cell-cell adhesion proteins. We provide evidence that mitochondrial delocalization of PGAM5, a pHis phosphatase with increased expression during pancreatic tumorigenesis, occurs in tumor cells as compared to stromal cells, enabling access to PGAM5’s known cytoplasmic substrate, pHis-NME (Non-MEtastatic), and two potential Gly-3-pHis substrates, SCSα (Succinyl CoA Synthetase) and β-catenin. Overall, we introduce a new method and possible targets for future studies of pHis pathway deregulation during tumorigenesis.
CTCF and R-loops are boundaries of cohesin-mediated DNA looping
Authors: Zhang Hongshan , Shi Zhubing , Banigan Edward J. , Kim Yoori , Yu Hongtao , Bai Xiao-chen , Finkelstein Ilya J. 
Published: September 2022

AbstractCohesin and CCCTC-binding factor (CTCF) are key regulatory proteins of three-dimensional (3D) genome organization. Cohesin extrudes DNA loops that are anchored by CTCF in a polar orientation. Here, we present direct evidence that CTCF binding polarity controls cohesin-mediated DNA looping. Using single-molecule imaging of CTCF-cohesin collisions, we demonstrate that a critical N-terminal motif of CTCF blocks cohesin translocation and DNA looping. The cryo-electron microscopy structure of the intact cohesin-CTCF complex reveals that this CTCF motif ahead of zinc-fingers can only reach its binding site on the STAG1 cohesin subunit when the N-terminus of CTCF faces cohesin. Remarkably, a C-terminally oriented CTCF accelerates DNA compaction by cohesin. DNA-bound Cas9 and Cas12a ribonucleoproteins are also polar cohesin barriers, indicating that stalling is intrinsic to cohesin itself, and other proteins can substitute for CTCF in fruit flies and other eukaryotes. Finally, we show that RNA-DNA hybrids (R-loops) block cohesin-mediated DNA compaction in vitro and are enriched with cohesin subunits in vivo, likely forming TAD boundaries. Our results provide direct evidence that CTCF orientation and R-loops shape the 3D genome by directly regulating cohesin.
ReproTox-KG: Toxicology Knowledge Graph for Structural Birth Defects
Authors: Evangelista John Erol , Clarke Daniel J. B. , Xie Zhuorui , Marino Giacomo B. , Utti Vivian , Ahooyi Taha M. , Jenkins Sherry L. , Taylor Deanne , Bologa Cristian G. , Yang Jeremy J. , Binder Jessica L. , Kumar Praveen , Lambert Christophe G. , Grethe Jeffrey S. , Wenger Eric , Oprea Tudor I. , de Bono Bernard , Ma’ayan Avi 
Published: September 2022

AbstractBirth defects are functional and structural abnormalities that impact 1 in 33 births in the United States. Birth defects have been attributed to genetic as well as other factors, but for most birth defects there are no known causes. Small molecule drugs, cosmetics, foods, and environmental pollutants may cause birth defects when the mother is exposed to them during pregnancy. These molecules may interfere with the process of normal fetal development. To characterize associations between small molecule compounds and their potential to induce specific birth abnormalities, we gathered knowledge from multiple sources to construct a reproductive toxicity Knowledge Graph (ReproTox-KG) with an initial focus on associations between birth defects, drugs, and genes. Specifically, to construct ReproTox-KG we gathered data from drug/birth-defect associations from co-mentions in published abstracts, gene/birth-defect associations from genetic studies, drug- and preclinical-compound-induced gene expression data, known drug targets, genetic burden scores for all human genes, and placental crossing scores for all small molecules in ReproTox-KG. Using the data stored within ReproTox-KG, we scored 30,000 preclinical small molecules for their potential to induce birth defects. Querying the ReproTox-KG, we identified over 500 birth-defect/gene/drug cliques that can be used to explain molecular mechanisms for drug-induced birth defects. The ReproTox-KG is provided as curated tables and via a web-based user interface that can enable users to explore the associations between birth defects, approved and preclinical drugs, and human genes.
Using Generalized Structured Additive Regression Models to determine factors associated with and clusters for COVID-19 hospital deaths in South Africa
Authors: Maposa Innocent , Welch Richard , Ozougwu Lovelyn , Arendse Tracy , Mudara Caroline , Blumberg Lucille , Jassat Waasila 
Published: September 2022

AbstractBackgroundThe first case of COVID-19 in South Africa was reported in March 2020 and the country has since recorded over 3.6 million laboratory-confirmed cases and 100 000 deaths as of March 2022. Transmission and infection of SARS-CoV-2 virus and deaths in general due to COVID-19 have been shown to be spatially associated but spatial patterns in in-hospital deaths have not fully been investigated in South Africa. This study uses national COVID-19 hospitalization data to investigate the spatial effects on hospital deaths after adjusting for known mortality risk factors.MethodsCOVID-19 hospitalization data and deaths were obtained from the National Institute for Communicable Diseases (NICD). Generalized structured additive logistic regression model was used to assess spatial effects on COVID-19 in-hospital deaths adjusting for demographic and clinical covariates. Continuous covariates were modelled by assuming second-order random walk priors, while spatial autocorrelation was specified with Markov random field prior and fixed effects with vague priors respectively. The inference was fully Bayesian.ResultsThe risk of COVID-19 in-hospital mortality increased with patient age, with admission to intensive care unit (ICU) (aOR=4.16; 95% Credible Interval: 4.05-4.27), being on oxygen (aOR=1.49; 95% Credible Interval: 1.46-1.51) and on invasive mechanical ventilation (aOR=3.74; 95% Credible Interval: 3.61-3.87). Being admitted in a public hospital (aOR= 3.16; 95% Credible Interval: 3.10-3.21) was also significantly associated with mortality. Risk of in-hospital deaths increased in months following a surge in infections and dropped after months of successive low infections highlighting crest and troughs lagging the epidemic curve. After controlling for these factors, districts such as Vhembe, Capricorn and Mopani in Limpopo province, and Buffalo City, O.R. Tambo, Joe Gqabi and Chris Hani in Eastern Cape province remained with significantly higher odds of COVID-19 hospital deaths suggesting possible health systems challenges in those districts.ConclusionThe results show substantial COVID-19 in-hospital mortality variation across the 52 districts. Our analysis provides information that can be important for strengthening health policies and the public health system for the benefit of the whole South African population. Understanding differences in in-hospital COVID-19 mortality across space could guide interventions to achieve better health outcomes in affected districts.
Observational assessments of the relationship of dietary and pharmacological treatment on continuous measures of dysglycemia over 24 hours in women with gestational diabetes
Authors: Dingena Cassy F. , Holmes Melvin J. , Campbell Matthew D. , Cade Janet E. , Scott Eleanor M. , Zulyniak Michael A. 
Published: September 2022

AbstractObjectivesStudies that use continuous glucose monitoring (CGM) to monitor women with gestational diabetes (GDM) highlight the importance of managing dysglycemia over a 24-hour period. However, the effect of current treatment methods on dysglycemia over 24-hrs are currently unknown. This study aimed to characterise CGM metrics over 24-hrs in women with GDM and the moderating effect of treatment strategy.MethodsRetrospective analysis of CGM data from 128 women with GDM in antenatal diabetes clinics. CGM was measured for 7-days between 30-32 weeks gestation. Non-parametric tests were used to evaluate differences of CGM between periods of day (morning, afternoon, evening, and overnight) and between treatment methods (i.e., diet alone or diet+metformin). Exploratory analysis in a subgroup of 34 of participants was performed to investigate the association between self-reported macronutrient intake and glycaemic control.ResultsGlucose levels significantly differed during the day (i.e., morning to evening; P<0.001) and were significantly higher (i.e., mean blood glucose and AUC) and more variable (i.e., SD and CV) than overnight glucose levels. Morning showed the highest amount of variability (CV; 8.4% vs 6.5%, P<0.001 and SD; 0.49 mmol/L vs 0.38 mmol/L, P<0.001). When comparing treatment methods, mean glucose (6.09 vs 5.65 mmol/L; P<0.001) and AUC (8760.8 vs 8115.1 mmol/L.hr; P<0.001) were significantly higher in diet+metformin compared to diet alone. Finally, the exploratory analysis revealed a favourable association between higher protein intake (+1SD or +92 kcal/day) and lower mean glucose (-0.91 mmol/L p, P=0.02) and total AUC (1209.6 mmol/L.h, P=0.021).ConclusionsGlycemia varies considerably across a day, with morning glycemia demonstrating greatest variability. Additionally, our work confirms that individuals assigned to diet+metformin have greater difficulty managing glycemia and results suggest that increased dietary protein may assist with management of dysglycemia. Future work is needed to investigate the benefit of increased protein intake on management of dysglycemia.
Real World Effectiveness of Tixagevimab/cilgavimab (Evusheld) in the Omicron Era
Authors: Chen Benjamin , Haste Nina , Binkin Nancy , Law Nancy , Horton Lucy E. , Yam Nancy , Chen Victor , Abeles Shira 
Published: September 2022

AbstractBackgroundPre-exposure prophylaxis for COVID-19 with tixagevimab/cilgavimab (T/C) received Emergency Use Authorization (EUA) based off of results from a clinical trial conducted prior to the Omicron variant. Its clinical effectiveness has not been well described in the Omicron era. We examined the incidence of symptomatic illness and hospitalizations among T/C recipients when Omicron accounted for virtually all cases.MethodsWe used the electronic medical record to identify patients who received T/C at our institution. Among these patients, we assessed for cases of symptomatic COVID-19 and associated hospitalizations before and after receiving T/C. We used chi square tests and Fishers exact p-values to examine differences between characteristics of those who got COVID before and after T/C prophylaxis.ResultsOf 1295 T/C recipients, 121 (9.3%) developed symptomatic COVID-19 before receiving T/C, and 102 (7.9%) developed symptomatic disease after receiving it. Among those with infection prior to T/C, 36/121 (29.8%) were hospitalized, including 8 (6.6%) admitted to the ICU. Among those with COVID-19 after receiving T/C, 6/102 (5.9%) were hospitalized but none required ICU admission. No COVID-related deaths occurred in either group. The majority of COVID-19 cases among those infected prior to T/C treatment occurred during Omicron BA.1 surge, while the majority of cases among post-T/C recipients occurred when BA.5 was predominant. Patients infected with COVID-19 prior to receiving T/C had received fewer vaccine doses and were less likely to receive COVID-19 therapeutics compared to those with COVID-19 after having received T/C.ConclusionWe identified COVID-19 infections after T/C prophylaxis. Among persons eligible for T/C, COVID-19 illnesses occurring after T/C were less likely to require hospitalization compared to those with COVID-19 prior to T/C. In the presence of changing vaccine coverage, multiple therapies, and changing variants, the effectiveness of T/C in the Omicron era remains difficult to assess.
New primer sets to detect recent human adenovirus F41 variants in wastewater: Is it linked to the new acute hepatitis?
Authors: Perez-Zabaleta Mariel , Williams Cecilia , Cetecioglu Zeynep 
Published: September 2022

AbstractHuman adenovirus type F-41 has been pursued as one of the potential reasons for the new acute hepatitis cases of unknown cause in young children. Tracking the spread of this virus in the population using wastewater-based epidemiology tools can help clinical investigations to determine its relation to this new hepatitis outbreak.In this study, methods to detect human adenovirus type F (40 and 41) and specifically type F41 were designed and implemented to quantify the amount of these pathogens in wastewater samples from Stockholm, Sweden. An assay based on reverse transcriptase quantitative polymerase chain reaction using TaqMan technology and primers targeting the three main capsid genes of adenoviruses: hexon, penton and fiber, was designed. The hexon primers were specific to adenovirus F41, while fiber primers could quantify both adenoviruses, F40 and F41. Wastewater samples from Stockholm were used to validate the designed assay and, in addition, pepper mild mottle virus (PMMoV) levels were quantified to study the data normalization.Our results can help link the occurrence of the virus variant with new cases of acute hepatitis and contribute to a better understanding of the possible causes. It can also provide valuable information that can be used in future investigations on the monitoring of human adenovirus type F in wastewater.
A Novel Machine Learning Systematic Framework and Web Tool for Breast Cancer Survival Rate Assessment
Authors: Ji Jonathan M. , Shen Wen H. 
Published: September 2022

AbstractCancer research, including that of breast cancer, has increasingly relied on molecular profiling based on advances in genomic technology. Although these techniques have permitted scientists to unravel the process by which cancer develops, scientists still struggle to effectively translate the vast amounts of patient data into clinically meaningful results. As a result, tasks such as predicting the human response to differing treatments remains a major challenge in cancer treatment.There have been many studies attempting to determine the survival indicators of breast cancer patients. However, most of these analyses were predominantly performed using traditional statistical methods, which are imperfect and inadequate in tackling vast amounts of data or unstructured data on human breast cancer. With the exponential progress in computing power and artificial intelligence approaches, we believe that there is an opportunity for machine learning to supersede our current capabilities in fully understanding the correlations between geneset alterations, drug responses, and the prognosis of breast cancer patients. This information would greatly benefit scientists and physicians in developing clinical therapeutic strategies, such as performing personalized treatment.This machine learning project employs multiple machine learning approaches, including a novel deep learning algorithm, in building models for the detection and visualization of significant prognostic indicators of breast cancer patient survival rate. The clinical and genomic data of 1,980 primary breast cancer samples used in this project were obtained from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database of cBioPortal. The data was preprocessed and then split to train eight classical machine learning models and the aforementioned deep learning Convolutional Neural Network (CNN) model.These models were evaluated using the recall scores, the accuracy scores, the receiver operating characteristic (ROC) curve, and the area under the ROC curve (AUC) on the training dataset and confirmed using the rest of the data of the dataset. Both the deep learning and machine learning methods produced desirable prediction accuracies. However, the deep learning model noticeably outperformed all other classifiers and achieved the highest accuracy (AUC = 0.900). This project was constructed in the Google Colab environment based on python and its programming libraries with data visualization, Tensorflow, and Keras.The CNN model demonstrates a powerful ability to be used as a systematic framework for real time prediction by end users. A web application for the breast cancer survival rate prediction was designed and developed using streamlit, Tensorflow, Keras and python libraries to allow end-users to interact with the model with ease and obtain quick and accurate prediction.
Epidermal maintenance of Langerhans cells relies on autophagy-regulated lipid metabolism
Authors: Arbogast Florent , Sal-Carro Raquel , Boufenghour Wacym , Frenger Quentin , Bouis Delphine , De La Palavesa Louise Filippi , Fauny Jean-Daniel , Griso Olivier , Puccio Hélène , Fima Rebecca , Huby Thierry , Gautier Emmanuel L. , Molitor Anne , Carapito Raphaël , Bahram Seiamak , Romani Nikolaus , Clausen Björn E. , Voisin Benjamin , Mueller Christopher G. , Gros Frédéric , Flacher Vincent 
Published: September 2022

ABSTRACTMacroautophagy (often-named autophagy), a catabolic process involving autophagy-related (Atg) genes, prevents accumulation of harmful cytoplasmic components and mobilizes energy reserves in long-lived and self-renewing cells. Autophagy deficiency affects antigen presentation in conventional dendritic cells (DCs) without impacting their survival. However, previous studies did not address epidermal Langerhans cells (LCs). Here, we demonstrate that deletion of eitherAtg5orAtg7in LCs leads to their gradual depletion. ATG5-deficient LCs showed metabolic dysregulation and accumulated neutral lipids. Despite increased mitochondrial respiratory capacity, they were unable to process lipids, eventually leading them to ferroptosis. Finally, metabolically impaired LCs upregulated proinflammatory transcripts and showed decreased expression of neuronal interaction receptors. Altogether, autophagy represents a critical regulator of lipid storage and metabolism in LCs, allowing their maintenance in the epidermis.