bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative analysis of the outcomes of COVID-19 between patients infected with SARS-CoV-2 Omicron and Delta variants: a retrospective cohort study
Authors: Gunadi  , Hakim Mohamad Saifudin , Wibawa Hendra , Vujira Khanza Adzkia , Puspitarani Dyah Ayu , Supriyati Endah , Trisnawati Ika , Iskandar Kristy , Khair Riat El , Afiahayati  , Siswanto  , Puspadewi Yunika , Irene  , Irianingsih Sri Handayani , Daniwijaya Edwin Widyanto , Agung Nugrahaningsih Dwi Aris , Gabriela Gita Christy , Geometri Esensi Tarian , Eryvinka Laudria Stella , Trie Utami Fadila Dyah , Devana Edita Mayda , Aditama Lanang , Putri Kinasih Nathania Christi , Amadeus Verrell Christopher , Hediningsih Yekti , Ananda Nur Rahmi , Arguni Eggi , Nuryastuti Titik , Wibawa Tri 
Published: May 2022

AbstractBackgroundThe SARS-CoV-2 Omicron variant has replaced the previously dominant Delta variant because of high transmissibility. It is responsible for the current increase in the COVID-19 infectivity rate worldwide. However, studies on the impact of the Omicron variant on the severity of COVID-19 are still limited in developing countries. Here, we compared the outcomes of patients infected with SARS-CoV-2 Omicron and Delta variants and associated with prognostic factors, including age, sex, comorbidities, and smoking.MethodsWe involved 352 patients, 139 with the Omicron variant and 213 with the Delta variant. The whole-genome sequences of SARS-CoV-2 were conducted using the Illumina MiSeq next-generation sequencer.ResultsCt value and mean age of COVID-19 patients were not significantly different between both groups (Delta: 20.35 ± 4.07 vs. Omicron: 20.62 ± 3.75; p=0.540; and Delta: 36.52 ± 21.24 vs. Omicron: 39.10 ± 21.24; p=0.266, respectively). Patients infected with Omicron and Delta variants showed similar hospitalization (p=0.433) and mortality rates (p=0.565). Multivariate analysis showed that older age (≥65 years) had higher risk for hospitalization (OR=3.67 [95% CI=1.22-10.94]; p=0.019) and fatalities (OR=3.93 [95% CI=1.35-11.42]; p=0.012). In addition, patients with cardiovascular disease had higher risk for hospitalization (OR=5.27 [95% CI=1.07-25.97]; p=0.041), whereas patients with diabetes revealed higher risk for fatalities (OR=9.39 [95% CI=3.30-26.72]; p=<0.001).ConclusionsOur study shows that patients infected with Omicron and Delta variants reveal similar clinical outcomes, including hospitalization and mortality. In addition, our findings further confirm that older age, cardiovascular disease, and diabetes are strong prognostic factors for the outcomes of COVID-19 patients.
BRCA1 Hypermethylation In Sporadic Breast Cancers: Discovering A Novel Pathway To Tumorigenesis Via Coordinate NBR2 Deregulation And TNBC Transformation
Authors: Patra Dipyaman , Varghese Geetu Rose , Jaikumar Vishnu Sunil , Rajan Arathi , Krishnan Neethu , Kuppuswamy Krithiga , Thankappan Rateeshkumar , Srinivas Priya 
Published: May 2022

ABSTRACTWomen with a family history of mutations in the Breast cancer susceptibility gene, BRCA1 will have an increased risk of developing breast neoplasms. However, majority of the breast cancers are sporadic where BRCA1 mutations are very rare. Instead, 5-65% of sporadic cases manifest BRCA1 promoter hypermethylation and 30-40% of such cases develop into Triple Negative Breast Cancers. Even then, the molecular mechanism of BRCA1 hypermethylation mediated breast tumorigenesis has remained an enigma till date. Here, we present a novel tumorigenesis pathway for breast cancers that engenders from BRCA1 hypermethylation by generating site-specific methylations in the BRCA1 promoter using a modified version of CRISPR technology.We report that induction of site-specific methylation on BRCA1 promoter α effectuates a downregulation in BRCA1 expression via alteration in the balance between its alternate transcripts β and α. Induced BRCA1 hypermethylation is also responsible for the attenuation of a long noncoding RNA, NBR2 (Neighbour of BRCA1 gene 2), which is transcribed through the bidirectional BRCA1 promoter α in the reverse direction. Downregulation of NBR2 activates a feedback loop by leading to further downregulation of BRCA1 which is more evident under glucose starvation conditions and is associated with impaired DNA damage repair. BRCA1 hypermethylation also results in significant overexpression of β-hCG (human chorionic gonadotrophin), which was found to be associated with highly aggressive and drug-resistant forms of BRCA1 mutated breast cancersinvitro&in vivoin our previous study. Further, we report a change in the hormone receptor levels as the tumor progresses which demonstrates how BRCA1 deficient cells modulate their expression of ER-α and ER-β to promote their proliferation in early stages of tumor development and at later stages, transform to a basal tumor subtype by shedding down the expression of ER-α & PR. Interestingly, we also discovered that modulation of ER-α expression upon BRCA1 hypermethylation is responsible for the alteration in BRCA1 transcript ratio. Finally, inin vivomouse studies, BRCA1 hypermethylated tumors were found to be much larger, aggressive and invasive as compared to wildtype, BRCA1 and NBR2 knockdown tumors with downregulation of ER-α and PR; which explains the most probable reason behind high relapse rates in BRCA1 hypermethylated tumors.GRAPHICAL ABSTRACT
Compressive stress drives adhesion-dependent unjamming transitions in breast cancer cell migration
Authors: Cai Grace , Nguyen Anh , Bashirzadeh Yashar , Lin Shan-Shan , Bi Dapeng , Liu Allen P. 
Published: May 2022

AbstractCellular unjamming is the collective fluidization of cell motion and has been linked to many biological processes, including development, wound repair, and tumor growth. In tumor growth, the uncontrolled proliferation of cancer cells in a confined space generates mechanical compressive stress. However, because multiple cellular and molecular mechanisms may be operating simultaneously, the role of compressive stress in unjamming transitions during cancer progression remains unknown. Here we investigate which mechanism dominates in a dense, mechanically stressed monolayer. We find that long-term mechanical compression triggers cell arrest in benign epithelial cells and enhances cancer cell migration in transitions correlated with cell shape, leading us to examine the contributions of cell-cell adhesion and substrate traction in shape-dependent unjamming transitions. We show that cadherin-mediated cell-cell adhesion regulates differential cellular responses to compressive stress and predominantly controls unjamming transitions in dense monolayers. Importantly, compressive stress does not induce the epithelial—mesenchymal transition in unjammed cells. Using traction force microscopy, traction forces are attenuated in compressed cells in the bulk of the monolayer regardless of cell type and motility. Intercellular adhesion thus is the dominant regulator of compression-induced unjamming transitions and may impact collective cell motion in tumor development and breast cancer progression.
Transcription-induced active forces suppress chromatin motion
Authors: Shin Sucheol , Shi Guang , Cho Hyun Woo , Thirumalai D. 
Published: May 2022

The organization of interphase chromosomes in a number of species is starting to emerge thanks to advances in a variety of experimental techniques. However, much less is known about the dynamics, especially in the functional states of chromatin. Some experiments have shown that the mobility of individual loci in human interphase chromosome decreases during transcription, and increases upon inhibiting transcription. This is a counter-intuitive finding because it is thought that the active mechanical force (F) on the order of ten pico-newtons, generated by RNA polymerase II (RNAPII) that is pre-sumably transmitted to the gene-rich region of the chromatin, would render it more open, thus enhancing the mobility. Inspired by these observations, we developed a minimal active copolymer model for interphase chromosomes to investigate howFaffects the dynamical properties of chromatin. The movements of the loci in the gene-rich region are suppressed in an intermediate range ofF, and are enhanced at smallFvalues, which has also been observed in experiments. In the intermediateF, the bond length between consecutive loci increases, becoming commensurate with the distance at the minimum of the attractive interaction between non-bonded loci. This results in a transient disorder-to-order transition, leading to the decreased mobility during transcription. Strikingly, theF-dependent change in the locus dynamics preserves the organization of the chromosome atF= 0. Transient ordering of the loci, which is not found in the polymers with random epigenetic profiles, in the gene-rich region might be a plausible mechanism for nucleating a dynamic network involving transcription factors, RNAPII, and chromatin.Significance StatementIn order to explain a physically counter-intuitive experimental finding that chromatin mobility is reduced during transcription, we introduced a polymer model for interphase chromosome that accounts for RNA polymerase (RNAP) induced active force. The simulations show that, over a range of active forces, the mobility of the gene-rich loci is suppressed. Outside this range, chromosomes are compact and exhibit glass-like dynamics. Our study, which accounts for the experimental observations, leads to a novel and testable mechanism of how transcription could shape the coexistence of fluid- and solid-like properties within chromosomes.
Elevator mechanism dynamics in a sodium-coupled dicarboxylate transporter
Authors: Kinz-Thompson Colin D. , Lopez-Redondo Maria Louisa , Mulligan Christopher , Sauer David B. , Marden Jennifer J. , Song Jinmei , Tajkhorshid Emad , Hunt John F. , Stokes David L. , Mindell Joseph A. , Wang Da-Neng , Gonzalez Ruben L. 
Published: May 2022

AbstractVcINDY, the sodium-dependent dicarboxylate transporter fromVibrio cholerae, is responsible for C4- and C5-carboxylate uptake into cells. The molecular mechanism of how VcINDY physically moves substrates across the membrane, and does so in an energetically efficient manner, is unclear. Here, we use single-molecule fluorescence resonance energy transfer experiments to directly observe the individual mechanistic steps that VcINDY takes to translocate substrates across a lipid bilayer, and then test key predictions of transport cycle mechanistic models. Our data provide the first direct evidence that VcINDY undergoes stochastic, elevator-type conformational motions that enable substrate translocation. Kinetic analysis suggests that the two protomers of the VcINDY homodimer undergo those motions in a non-cooperative manner, and thus catalyze two independent transport reactions. The relative substrate independence of those motions supports the notion that the VcINDY transport cycle maintains strict co-substrate coupling using a cooperative binding mechanism. Finally, thermodynamic modeling provides insight into how such a cooperative binding mechanism provides a generalized approach to optimizing transport for many secondary active transporters.Significance StatementTransporter proteins use energy to move molecular materials into and out of cells. To be efficient, the transporter motions responsible for moving the molecules must be tightly choreographed to avoid wasting energy without transporting anything. By measuring the motions and kinetics of a prototypical transporter (VcINDY) at the single-molecule level, this study finds the first evidence that transporters like VcINDY achieve efficient transport by coordinating constantly dynamic, “elevator-type” motions while sitting in the cellular membrane. The efficiency of these surprisingly dynamic transporters is then revealed by thermodynamic modeling, which explains the molecular basis behind how highly cooperative, substrate binding reactions may have evolved as the optimal strategy for maximizing transporter efficiency.
How to Best Represent Proteins in Machine Learning-based Prediction of Drug/Compound-Target Interactions
Authors: Atas Heval , Doğan Tunca 
Published: May 2022

AbstractThe identification of drug/compound-target interactions (DTIs) constitutes the basis of drug discovery, for which computational predictive approaches have been applied. As a relatively new data-driven paradigm, proteochemometric (PCM) modeling utilizes both protein and compound properties as a pair at the input level and processes them via statistical/machine learning. The representation of input samples (i.e., proteins and their ligands) in the form of quantitative feature vectors is crucial for the extraction of interaction-related properties during the artificial learning and subsequent prediction of DTIs. Lately, the representation learning approach, in which input samples are automatically featurized via training and applying a machine/deep learning model, has been utilized in biomedical sciences. In this study, we performed a comprehensive investigation of different computational approaches/techniques for data preparation and protein featurization, including both conventional approaches and the novel learned embeddings, with the aim of achieving better data representations and more successful learning in PCM-based DTI prediction. For this, we first constructed realistic and challenging benchmark datasets on small, medium, and large scales to be used as reliable gold standards for specific DTI modeling tasks. We developed and applied a network analysis-based splitting strategy to divide datasets into structurally different training and test folds. Using these datasets together with various featurization methods, we trained and tested DTI prediction models and evaluated their performance from different angles. Our main findings can be summarized under 3 items: (i) random splitting of the dataset into train and test folds leads to near-complete data memorization and produce highly over-optimistic results, as a result, it should be avoided; (ii) learned protein sequence embeddings works well in DTI prediction, even though no information related to protein structures, interactions or biochemical properties is utilized during the training of these models; and (iii) PCM models tends to learn from compound features and leave out protein features, mostly due to the natural bias in DTI data. We hope this study will aid researchers in designing robust and high-performing data-driven DTI prediction systems that have real-world translational value in drug discovery.
Microbial metabolite butyrate-prodrug polymeric micelles demonstrate therapeutic efficacy in pre-clinical models of food allergy and colitis
Authors: Wang Ruyi , Cao Shijie , Bashir Mohamed Elfatih H. , Hesser Lauren A. , Su Yanlin , Hong Sung Min Choi , Thompson Andrew , Culleen Elliot , Sabados Matthew , Dylla Nicholas P. , Campbell Evelyn , Bao Riyue , Nonnecke Eric B. , Bevins Charles L. , Wilson D. Scott , Hubbell Jeffrey A. , Nagler Cathryn R. 
Published: May 2022

AbstractThe microbiome modulates host immunity and aids in maintenance of tolerance in the gut, where microbial and food-derived antigens are abundant. Modern lifestyle practices, including diet and antibiotic use, have depleted beneficial taxa, specifically butyrate-producing Clostridia. This depletion is associated with the rising incidence of food allergy, inflammatory bowel diseases, and other noncommunicable chronic diseases. Although butyrate is known to play important roles in regulating gut immunity and maintaining epithelial barrier function, its clinical translation is challenging due to its offensive odor and quick absorption in the upper gut. Here, we have developed two polymeric micelle systems, one with a neutral charge (NtL-ButM) and one with a negative charge (Neg-ButM) that release butyrate from their polymeric core in different regions of the gastrointestinal tract when administered intragastrically to mice. We show that these butyrate-containing micelles, used in combination, restore a barrier-protective response in mice treated with either dextran sodium sulfate or antibiotics. Moreover, butyrate micelle treatment protects peanut-allergic dysbiotic mice from an anaphylactic reaction to peanut challenge and rescues their antibiotic-induced dysbiosis by increasing the abundance ofClostridiumCluster XIVa. Butyrate micelle treatment also reduces the severity of colitis in a murine model. By restoring microbial and mucosal homeostasis, these butyrate-prodrug polymeric micelles may function as a new, antigen-agnostic approach for the treatment of allergic and inflammatory disease.
Decoding natural gait cycle in Parkinson’s disease from cortico-subthalamic field potentials
Authors: Louie Kenneth H. , Gilron Ro’ee , Yaroshinsky Maria S. , Morrison Melanie A. , Choi Julia , de Hemptinne Coralie , Little Simon , Starr Philip A. , Wang Doris D. 
Published: May 2022

AbstractHuman bipedal walking is a complex motor behavior that requires precisely timed alternating activity across multiple nodes of the supraspinal network. However, understanding the neural dynamics that underlie walking is limited. We investigated the cortical-subthalamic circuit dynamics of overground walking from three patients with Parkinson’s disease without major gait impairments. All patients were implanted with chronic bilateral deep brain stimulation leads in the subthalamic nucleus (STN) and electrocorticography paddles overlying the primary motor (M1) and sensory (S1) cortices. Local field potentials were wirelessly streamed through implanted bidirectional pulse generators during overground walking and synchronized to external gait kinematics sensors. We found that the STN displays increased low frequency (4-12 Hz) spectral power between ipsilateral heel strike to contralateral leg swing. Furthermore, the STN shows increased theta frequency (4-8 Hz) coherence with M1 through the initiation and early phase of contralateral leg swing. Our findings support the hypothesis that oscillations from the basal ganglia and cortex direct out-of-phase, between brain hemispheres in accordance with the gait cycle. In addition, we identified patient-specific, gait-related biomarkers in both STN and cortical areas at discrete frequency bands. These field potentials support classification of left and right gait events. These putative biomarkers of the gait cycle may eventually be used as control signals to drive adaptive DBS to further improve gait dysfunction in patients with Parkinson’s disease.
An Early Return-to-Work Program for COVID-19 Close Contacts in Healthcare During the Omicron Wave in Japan
Authors: Naruse Hiroyuki , Doi Yohei , Iwata Mitsunaga , Ishikawa Kiyohito 
Published: May 2022

AbstractDuring the coronavirus disease 2019 (COVID-19) pandemic, maintaining adequate staffing in healthcare facilities is important to provide a safe work environment for healthcare workers (HCWs). Japan’s early return-to-work (RTW) program may be a rational strategy at a time when there is an increased demand for the services of HCWs. We assessed whether the early RTW program for HCWs who have been in close contact with a COVID-19 case in our hospital was justified. Close contacts were identified according to the guidance of the World Health Organization. Between January and March 2022, 256 HCWs were identified as close contacts (median age, 35 years; 192 female). Thirty-seven (14%) secondary attack cases of COVID-19 were detected. Among 141 HCWs who applied to the early RTW program, nurses and doctors comprised about three-quarters of participants, with a higher participation rate by doctors (78%) than nurses (59%). Eighteen HCWs tested positive for COVID-19 by the sixth day after starting the early RTW program. No COVID-19 infection clusters were reported during the observation period. These findings suggest that the early RTW program for COVID-19 close contacts was a reasonable strategy for HCWs during the Omicron wave.
Real-World Progression-Free Survival as an Endpoint in Advanced Non-Small-Cell Lung Cancer: Replicating Atezolizumab and Docetaxel Arms of the OAK Trial Using Data Derived From Electronic Health Records
Authors: Mhatre Shivani K. , Machado Robson J. M. , Ton Thanh G.N. , Trinh Huong , Mazieres Julien , Rittmeyer Achim , Bretscher Michael T. 
Published: May 2022

ABSTRACTBackgroundEvaluating cancer treatments in real-world data (RWD) requires informative endpoints. Due to non-standardized data collection in RWD, it is unclear if and when common oncology endpoints are approximately equivalent to their clinical trial analogues. This study used RWD to replicate both the atezolizumab and docetaxel arms of the OAK trial. Outcomes using progression-free survival (PFS) derived from abstracted physician’s notes in RWD (rwPFS) were then compared against PFS outcomes derived according to Response Evaluation Criteria in Solid Tumors (RECIST) from the clinical trial (ctPFS).MethodsAtezolizumab and docetaxel arms of the phase III OAK RCT (NCT02008227) were replicated in a US nationwide real-world database by applying selected OAK inclusion/exclusion criteria, followed by adjustment for baseline prognostic variables using propensity score-based methods. Multiple rwPFS definitions were characterized and a definition was chosen that was acceptable from both clinical and data analysis perspectives. Concordance of outcomes was assessed using Kaplan-Meier (KM) medians and hazard ratios (HRs).ResultsOverall, 133 patients receiving atezolizumab and 479 patients receiving docetaxel were selected for the RWD cohort. After adjustment, prognostic variables were balanced between RCT arms and corresponding RWD cohorts. Comparing rwPFS against ctPFS outcomes in terms of KM median and HR showed better concordance for docetaxel (2.99 vs 3.52 months; HR, 0.99, 95% CI, 0.85-1.15) than for atezolizumab (3.71 vs 2.76 months; HR, 0.8, 95% CI 0.61-1.02). The latter improved when events labelled “pseudo-progression” were excluded from the RWD (im-rwPFS) and immune-modified RECIST PFS (im-ctPFS) was used in the RCT Atezolizumab data (4.24 vs 4.14 months; HR, 0.95, 95% CI, 0.70-1.25). These findings were robust across several sensitivity analyses.ConclusionsWhile rwPFS and ctPFS were similar under docetaxel treatment, this was only the case for atezolizumab when immune-modified progression criteria were used, suggesting that similarity of RWD endpoints to their clinical trial analogues depends on drug category and possibly other factors. Replication of RCTs using RWD and comparison of outcomes can be used as a tool for characterizing RWD endpoints. Additional studies are needed to verify these findings and to better understand the conditions for approximate numerical equivalence of rwPFS and ctPFS endpoints.