bluuebunny/crossref_metadata_2025_split huggingface dataset:
SARS-CoV-2 alters neural synchronies in the brain with more severe effects in younger individuals
Authors: Valsamis Helen , Baki Samah Abdul , Leung Jason , Ghosn Samer , Lapin Brittany , Chari Geetha , Rasheed Izad-Yar , Park Jaehan , Punia Vineet , Masri Ghinwa , Nair Dileep , Kaniecki Ann Marie , Edhi Muhammad , Saab Carl Y. 
Published: February 2023

AbstractCoronavirus disease secondary to infection by SARS-CoV-2 (COVID19 or C19) causes respiratory illness, as well as severe neurological symptoms that have not been fully characterized. In a previous study, we developed a computational pipeline for the automated, rapid, high-throughput and objective analysis of electroencephalography (EEG) rhythms. In this retrospective study, we used this pipeline to define the quantitative EEG changes in patients with a PCR-positive diagnosis of C19 (n = 31) in the intensive care unit (ICU) of Cleveland Clinic, compared to a group of age-matched PCR-negative (n = 38) control patients in the same ICU setting. Qualitative assessment of EEG by two independent teams of electroencephalographers confirmed prior reports with regards to the high prevalence of diffuse encephalopathy in C19 patients, although the diagnosis of encephalopathy was inconsistent between teams. Quantitative analysis of EEG showed distinct slowing of brain rhythms in C19 patients compared to control (enhanced delta power and attenuated alpha–beta power). Surprisingly, these C19-related changes in EEG power were more prominent in patients below age 70. Moreover, machine learning algorithms showed consistently higher accuracy in the binary classification of patients as C19 versus control using EEG power for subjects below age 70 compared to older ones, providing further evidence for the more severe impact of SARS-CoV-2 on brain rhythms in younger individuals irrespective of PCR diagnosis or symptomatology, and raising concerns over potential long-term effects of C19 on brain physiology in the adult population and the utility of EEG monitoring in C19 patients.
Taxonomic and enzymatic basis of the cellulolytic microbial consortium KKU-MC1 and its application in enhancing biomethane production
Authors: Wongfaed Nantharat , O-Thong Sompong , Sittijunda Sureewan , Reungsang Alissara 
Published: February 2023

AbstractLignocellulosic biomass is a promising substrate for biogas production. However, its recalcitrant structure limits conversion efficiency. This study aims to design a microbial consortium (MC) capable of producing the cellulolytic enzyme and exploring the taxonomic and genetic aspects of lignocellulose degradation. A diverse range of lignocellulolytic bacteria and degrading enzymes from various habitats were enriched for a known KKU-MC1. The KKU-MC1 was found to be abundant in Bacteroidetes (51%), Proteobacteria (29%), Firmicutes (10%), and other phyla (8% unknown, 0.4% unclassified, 0.6% archaea, and the remaining 1% other bacteria with low predominance). Carbohydrate-active enzyme (CAZyme) annotation revealed that the genera Bacteroides,Ruminiclostridium,Enterococcus, and Parabacteroides encoded a diverse set of cellulose and hemicellulose degradation enzymes. Furthermore, the gene families associated with lignin deconstruction were more abundant in the Pseudomonas genera. Subsequently, the effects of MC on methane production from various biomasses were studied in two ways: bioaugmentation and pre-hydrolysis. Methane yield (MY) of pre-hydrolysis cassava bagasse (CB), Napier grass (NG), and sugarcane bagasse (SB) with KKU-MC1 for 5 days improved by 38–56% compared to non-prehydrolysis substrates, while MY of prehydrolysed filter cake (FC) for 15 days improved by 56% compared to raw FC. The MY of CB, NG, and SB (at 4% initial volatile solid concentration (IVC)) with KKU-MC1 augmentation improved by 29–42% compared to the non-augmentation treatment. FC (1% IVC) had 17% higher MY than the non-augmentation treatment. These findings demonstrated that KKU-MC1 released the cellulolytic enzyme capable of decomposing various lignocellulosic biomasses, resulting in increased biogas production.
Self-administration of a Salmonella vaccine by domestic pigs
Authors: Robbins Rebecca C. , Archer Courtney , Giménez-Lirola Luis G. , Mora-Díaz Juan Carlos , McGlone John J. 
Published: February 2023

AbstractHand vaccinating is time consuming and inefficient. Oral vaccines delivered by drenching are less likely to be used due to a lack of labor on farms. Current environmental enrichment (EE) technologies do not allow pigs to express certain natural behaviors such as rooting and getting a reward. We developed a sprayer so that domestic pigs can self-apply any liquid. By adding an attractant (pig maternal pheromone), the use of EE devices by individual pigs can be increased. In this study, we used a Salmonella oral vaccine to evaluate efficacy of three delivery methods: (1) Control, no vaccine, (2) hand drenching as labeled, and (3) self-administration by this EE rooting device. All pigs sprayed themselves within 80 min of exposure to the EE device. While control pigs had little or no Salmonella serum and oral fluid IgG or IgA, hand-drenched and self-vaccinated pigs built similar levels of both serum and oral fluid IgA and IgG. We conclude we were able to significantly reduce human labor needed and achieved 100% efficacy in eliciting a serologic response when pigs self-administered a Salmonella vaccine. This technology could benefit commercial pig production while providing an enriched behavioral environment. Self-vaccination could also assist in control or immunization of feral swine and improve domestic pig health and food safety.
Mathematical modelling of the dynamics of image-informed tumor habitats in a murine model of glioma
Authors: Slavkova Kalina P. , Patel Sahil H. , Cacini Zachary , Kazerouni Anum S. , Gardner Andrea L. , Yankeelov Thomas E. , Hormuth David A. 
Published: February 2023

AbstractTumors exhibit high molecular, phenotypic, and physiological heterogeneity. In this effort, we employ quantitative magnetic resonance imaging (MRI) data to capture this heterogeneity through imaging-based subregions or “habitats” in a murine model of glioma. We then demonstrate the ability to model and predict the growth of the habitats using coupled ordinary differential equations (ODEs) in the presence and absence of radiotherapy. Female Wistar rats (N = 21) were inoculated intracranially with 106 C6 glioma cells, a subset of which received 20 Gy (N = 5) or 40 Gy (N = 8) of radiation. All rats underwent diffusion-weighted and dynamic contrast-enhanced MRI at up to seven time points. All MRI data at each visit were subsequently clustered using k-means to identify physiological tumor habitats. A family of four models consisting of three coupled ODEs were developed and calibrated to the habitat time series of control and treated rats and evaluated for predictive capability. The Akaike Information Criterion was used for model selection, and the normalized sum-of-square-error (SSE) was used to evaluate goodness-of-fit in model calibration and prediction. Three tumor habitats with significantly different imaging data characteristics (p < 0.05) were identified: high-vascularity high-cellularity, low-vascularity high-cellularity, and low-vascularity low-cellularity. Model selection resulted in a five-parameter model whose predictions of habitat dynamics yielded SSEs that were similar to the SSEs from the calibrated model. It is thus feasible to mathematically describe habitat dynamics in a preclinical model of glioma using biology-based ODEs, showing promise for forecasting heterogeneous tumor behavior.
Rumen-protected glucose stimulates the secretion of reproductive hormones and the mTOR/AKT signaling pathway in the ovaries of early postpartum
Authors: Wang Yan , Jin Chenzhong , Yi Yuzhen , Hu Yihong , Han Xuefeng , Tan Zhiliang , Wang Zheng , Kang Jinhe 
Published: February 2023

AbstractThis study was conducted to determine the response of the reproductive hormones and the mTOR/AKT/PI3K pathway in the ovaries of postpartum dairy cows with dietary rumen-protected glucose (RPG). Twelve Holstein cows were randomly assigned to two groups (n = 6/group): the control group (CT) and the RPG group. Blood samples were collected on d 1, 7, and 14 after calving for the gonadal hormone assay. The expression of the gonadal hormones receptors and PI3K/mTOR/AKT pathways were detected using RT-PCR and Western blot. The RPG addition increased the plasma LH, E2, and P4 concentrations on d 14 after calving and upregulated the mRNA and protein expressions of the ERα, ERβ, 17β-HSD, FSHR, LHR, and CYP17A1 but downregulated StAR expression. Immunohistochemical analysis identified higher expressions of the FSHR and LHR in the ovaries of RPG-fed cows compared to CT cows. Furthermore, the protein expressions of p-AKT/AKT and p-mTOR/mTOR were significantly increased in the ovaries of RPG-fed cows compared to the CT group, but the addition of RPG did not alter the protein expression of p-PI3K/PI3K. In conclusion, the current results indicated that dietary RPG supplementation regulated gonadotropin secretion and stimulated expression of hormone receptors and the mTOR/AKT pathway in the ovaries of early postpartum dairy cows. RPG may be beneficial for the recovery of ovarian activity in post-calving dairy cows.
Risk factors and geographic disparities in premature cardiovascular mortality in US counties: a machine learning approach
Authors: Dong Weichuan , Motairek Issam , Nasir Khurram , Chen Zhuo , Kim Uriel , Khalifa Yassin , Freedman Darcy , Griggs Stephanie , Rajagopalan Sanjay , Al-Kindi Sadeer G. 
Published: February 2023

AbstractDisparities in premature cardiovascular mortality (PCVM) have been associated with socioeconomic, behavioral, and environmental risk factors. Understanding the “phenotypes”, or combinations of characteristics associated with the highest risk of PCVM, and the geographic distributions of these phenotypes is critical to targeting PCVM interventions. This study applied the classification and regression tree (CART) to identify county phenotypes of PCVM and geographic information systems to examine the distributions of identified phenotypes. Random forest analysis was applied to evaluate the relative importance of risk factors associated with PCVM. The CART analysis identified seven county phenotypes of PCVM, where high-risk phenotypes were characterized by having greater percentages of people with lower income, higher physical inactivity, and higher food insecurity. These high-risk phenotypes were mostly concentrated in the Black Belt of the American South and the Appalachian region. The random forest analysis identified additional important risk factors associated with PCVM, including broadband access, smoking, receipt of Supplemental Nutrition Assistance Program benefits, and educational attainment. Our study demonstrates the use of machine learning approaches in characterizing community-level phenotypes of PCVM. Interventions to reduce PCVM should be tailored according to these phenotypes in corresponding geographic areas.
Bimodal CNN for cardiovascular disease classification by co-training ECG grayscale images and scalograms
Authors: Yoon Taeyoung , Kang Daesung 
Published: February 2023

AbstractThis study aimed to develop a bimodal convolutional neural network (CNN) by co-training grayscale images and scalograms of ECG for cardiovascular disease classification. The bimodal CNN model was developed using a 12-lead ECG database collected from Chapman University and Shaoxing People's Hospital. The preprocessed database contains 10,588 ECG data and 11 heart rhythms labeled by a specialist physician. The preprocessed one-dimensional ECG signals were converted into two-dimensional grayscale images and scalograms, which are fed simultaneously to the bimodal CNN model as dual input images. The proposed model aims to improve the performance of CVDs classification by making use of ECG grayscale images and scalograms. The bimodal CNN model consists of two identical Inception-v3 backbone models, which were pre-trained on the ImageNet database. The proposed model was fine-tuned with 6780 dual-input images, validated with 1694 dual-input images, and tested on 2114 dual-input images. The bimodal CNN model using two identical Inception-v3 backbones achieved best AUC (0.992), accuracy (95.08%), sensitivity (0.942), precision (0.946) and F1-score (0.944) in lead II. Ensemble model of all leads obtained AUC (0.994), accuracy (95.74%), sensitivity (0.950), precision (0.953), and F1-score (0.952). The bimodal CNN model showed better diagnostic performance than logistic regression, XGBoost, LSTM, single CNN model training with grayscale images alone or with scalograms alone. The proposed bimodal CNN model would be of great help in diagnosing cardiovascular diseases.
Environmental and pathological factors affecting the hatching success of the two northernmost loggerhead sea turtle (Caretta caretta) nests
Authors: Pietroluongo Giudo , Centelleghe Cinzia , Sciancalepore Giuseppe , Ceolotto Luca , Danesi Patrizia , Pedrotti Davide , Mazzariol Sandro 
Published: February 2023

AbstractIn recent years, the report of loggerhead sea turtle (Caretta caretta) Mediterranean nesting range has expanded together with new records of nests becoming northward on the Italian coastline of the Tyrrhenian and Adriatic seas. These areas are characterized by intensive human activities, such as tourism, fishery, and marine traffic, all possibly involved in the influence of the use of coastal habitat by marine species. These anthropic threats, in addition to the natural ones and the changing environmental characteristics of the beach, may influence the growth of microorganisms causing hatching failures. Among microorganisms, fungal infection by the genus Fusarium (Link, 1809) is considered one of the main causes of globally declining sea turtle populations. In summer 2021, the two northernmost worldwide loggerhead sea turtle nests were monitored along the Northern Adriatic coastline (Veneto, Italy). These first records may potentially candidate this area as suitable for a large part of the loggerhead turtle’s life cycle and it could represent a minor sea turtle nesting area that, according to Prato and colleagues, remained unnoticed due to the lack of specific monitoring. Sea Turtle Egg Fusariosis (STEF) was deemed to have deeply compromised the hatching success of the northmost one. Climate change and anthropogenic impacts have been scored as one of the highest hazards to sea turtle health and could have played a role in the STEF development. Environmental changes, human activities, and emerging pathogens deserve the highest attention in terms of health research, and conservation management.
Protective effect of Anoectochilus burmannicus extracts and its active compound, kinsenoside on adipocyte differentiation induced by benzyl butyl phthalate and bisphenol A
Authors: Buacheen Pensiri , Karinchai Jirarat , Kammasit Natchapon , Temviriyanukul Piya , Butkinaree Chutikarn , Watthana Santi , Wongnoppavich Ariyaphong , Imsumran Arisa , Pitchakarn Pornsiri 
Published: February 2023

AbstractBenzyl butyl phthalate (BBP) and bisphenol-A (BPA) are obesogens that have been reported to be associated with obesity. Inhibition of their adipogenic activity could decrease the risk of obesity-related metabolic disorders. This study hypothesized thatAnoectochilus burmannicusethanolic extract (ABE) which has been previously reported its anti-inflammation property and its known active compound, kinsenoside (Kin) abrogate BBP- and BPA-induced adipogenesis. ABE and Kin markedly suppress both BBP- and BPA-stimulated adipogenesis with different modulations on adipogenic-gene expression including C/EBPα, PPARγ, adiponectin, and leptin in 3T3-L1. BBP induced C/EBPα, adiponectin, and leptin mRNA expressions and slightly increased PPARγ mRNA level, whereas BPA markedly induced PPARγ and adiponectin mRNA levels. ABE significantly decreased the expression of C/EBPα and leptin, but not PPARγ and adiponectin in the BBP-treated cells. In the BPA-treated cells, ABE significantly decreased the mRNA expression of C/EBPα and PPARγ, but not adiponectin and leptin. Interestingly, Kin significantly overcame BBP- and BPA-induced C/EBPα, PPARγ, adiponectin, and leptin expressions. This study first provides evidence to support the health benefits of this plant, especially for people exposed to obesogens. Besides, this finding would encourage the conservation and culture of this orchid for development as an economic plant and healthy food.
Important role of stratosphere-troposphere coupling in the Arctic mid-to-upper tropospheric warming in response to sea-ice loss
Authors: Xu Mian , Tian Wenshou , Zhang Jiankai , Screen James A. , Zhang Chongyang , Wang Zhe 
Published: February 2023

AbstractRecent studies have suggested that deep Arctic warming, extending from the surface to the upper troposphere, could trigger mid-latitude atmospheric circulation changes, while shallow Arctic warming, confined in the lowermost troposphere, induces comparatively weak remote responses. The causes of Arctic mid-to-upper tropospheric warming are less clear compared with near-surface warming. Here, we demonstrate a new dynamical mechanism responsible for the polar mid-to-upper tropospheric warming associated with Arctic sea-ice loss, using both reanalysis and model simulations. The Barents-Kara sea-ice loss enhances the upward propagating waves, leading to the wave convergence anomalies in the sub-polar lower stratosphere and upper troposphere. The consequent eddy feedback leads to clockwise residual overturning anomalies in the sub-polar upper and middle troposphere, accompanied by anomalous descent and consequent adiabatic warming in the Arctic mid-to-upper troposphere. The essential role of stratosphere-troposphere coupling for deep Arctic warming induced by sea-ice loss is confirmed by model simulations with stratospheric variability suppressed, in which only the Arctic lower troposphere is warmed in response to sea-ice loss. Our results suggest that a considerable part of the observed Arctic mid-to-upper warming is caused by a dynamical response to sea-ice loss, in which stratosphere-troposphere coupling plays a major role.
Combined low-pass whole genome and targeted sequencing in liquid biopsies for pediatric solid tumors
Authors: Christodoulou Eirini , Yellapantula Venkata , O’Halloran Katrina , Xu Liya , Berry Jesse L. , Cotter Jennifer A. , Zdanowicz Anya , Mascarenhas Leo , Amatruda James F. , Ostrow Dejerianne , Bootwalla Moiz , Gai Xiaowu , Navid Fariba , Biegel Jaclyn A. 
Published: February 2023

AbstractWe designed a liquid biopsy (LB) platform employing low-pass whole genome sequencing (LP-WGS) and targeted sequencing of cell-free (cf) DNA from plasma to detect genome-wide copy number alterations (CNAs) and gene fusions in pediatric solid tumors. A total of 143 plasma samples were analyzed from 19 controls and 73 patients, including 44 bone or soft-tissue sarcomas and 12 renal, 10 germ cell, five hepatic, and two thyroid tumors. cfDNA was isolated from plasma collected at diagnosis, during and after therapy, and/or at relapse. Twenty-six of 37 (70%) patients enrolled at diagnosis without prior therapy (radiation, surgery, or chemotherapy) had circulating tumor DNA (ctDNA), based on the detection of CNAs from LP-WGS, including 18 of 27 (67%) patients with localized disease and eight of 10 (80%) patients with metastatic disease. None of the controls had detectable somatic CNAs. There was a high concordance of CNAs identified by LP-WGS to CNAs detected by chromosomal microarray analysis in the matching tumors. Mutations identified in tumor samples with our next-generation sequencing (NGS) panel, OncoKids®, were also detected by LP-WGS of ctDNA in 14 of 26 plasma samples. Finally, we developed a hybridization-based capture panel to target EWSR1 and FOXO1 fusions from patients with Ewing sarcoma or alveolar rhabdomyosarcoma (ARMS), respectively. Fusions were detected in the plasma from 10 of 12 patients with Ewing sarcoma and in two of two patients with ARMS. Combined, these data demonstrate the clinical applicability of our LB platform to evaluate pediatric patients with a variety of solid tumors.
Mass spectrometry uncovers intermediates and off-pathway complexes for SNARE complex assembly
Authors: Hesselbarth Julia , Schmidt Carla 
Published: February 2023

AbstractThe SNARE complex assembles from vesicular Synaptobrevin-2 as well as Syntaxin-1 and SNAP25 both anchored to the presynaptic membrane. It mediates fusion of synaptic vesicles with the presynaptic plasma membrane resulting in exocytosis of neurotransmitters. While the general sequence of SNARE complex formation is well-established, our knowledge on possible intermediates and stable off-pathway complexes is incomplete. We, therefore, follow the stepwise assembly of the SNARE complex and target individual SNAREs, binary sub-complexes, the ternary SNARE complex as well as interactions with Complexin-1. Using native mass spectrometry, we identify the stoichiometry of sub-complexes and monitor oligomerisation of various assemblies. Importantly, we find that interactions with Complexin-1 reduce multimerisation of the ternary SNARE complex. Chemical cross-linking provides detailed insights into these interactions suggesting a role for membrane fusion. In summary, we unravel the stoichiometry of intermediates and off-pathway complexes and compile a road map of SNARE complex assembly including regulation by Complexin-1.
Endogenous DAF-16 spatiotemporal activity quantitatively predicts lifespan extension induced by dietary restriction
Authors: Huayta Javier , Crapster Joseph P. , San-Miguel Adriana 
Published: February 2023

AbstractIn many organisms, dietary restriction (DR) leads to lifespan extension through the activation of cell protection and pro-longevity gene expression programs. In the nematode C. elegans, the DAF-16 transcription factor is a key aging regulator that governs the Insulin/IGF-1 signaling pathway and undergoes translocation from the cytoplasm to the nucleus of cells when animals are exposed to food limitation. However, how large is the influence of DR on DAF-16 activity, and its subsequent impact on lifespan has not been quantitatively determined. In this work, we assess the endogenous activity of DAF-16 under various DR regimes by coupling CRISPR/Cas9-enabled fluorescent tagging of DAF-16 with quantitative image analysis and machine learning. Our results indicate that DR regimes induce strong endogenous DAF-16 activity, although DAF-16 is less responsive in aged individuals. DAF-16 activity is in turn a robust predictor of mean lifespan in C. elegans, accounting for 78% of its variability under DR. Analysis of tissue-specific expression aided by a machine learning tissue classifier reveals that, under DR, the largest contribution to DAF-16 nuclear intensity originates from the intestine and neurons. DR also drives DAF-16 activity in unexpected locations such as the germline and intestinal nucleoli.