bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pharmacological inhibition of tyrosine protein-kinase 2 reduces islet inflammation and delays type 1 diabetes onset in mice
Authors: Syed Farooq , Ballew Olivia , Lee Chih-Chun , Rana Jyoti , Krishnan Preethi , Castela Angela , Weaver Staci A. , Chalasani Namratha Shivani , Thomaidou Sofia F. , Demine Stephane , Chang Garrick , Coomans de Brachène Alexandra , Alvelos Maria Ines , Marselli Lorella , Orr Kara , Felton Jamie L. , Liu Jing , Marchetti Piero , Zaldumbide Arnaud , Scheuner Donalyn , Eizirik Decio L. , Evans-Molina Carmella 
Published: March 2024

SUMMARYTyrosine protein-kinase 2 (TYK2), a member of the Janus kinase family, mediates inflammatory signaling through multiple cytokines, including interferon-α (IFNα), interleukin (IL)-12, and IL-23. Missense mutations in TYK2 are associated with protection against type 1 diabetes (T1D), and inhibition of TYK2 shows promise in the management of other autoimmune conditions. Here, we evaluated the effects of specific TYK2 inhibitors (TYK2is) in pre-clinical models of T1D. First, human β cells, cadaveric donor islets, and iPSC-derived islets were treatedin vitrowith IFNα in combination with a small molecule TYK2i (BMS-986165 or a related molecule BMS-986202). TYK2 inhibition prevented IFNα-induced β cell HLA class I up-regulation, endoplasmic reticulum stress, and chemokine production. In co-culture studies, pre-treatment of β cells with a TYK2i prevented IFNα-induced activation of T cells targeting an epitope of insulin.In vivoadministration of BMS-986202 in two mouse models of T1D (RIP-LCMV-GPmice and NOD mice) reduced systemic and tissue-localized inflammation, prevented β cell death, and delayed T1D onset. Transcriptional phenotyping of pancreatic islets, pancreatic lymph nodes (PLN), and spleen during early disease pathogenesis highlighted a role for TYK2 inhibition in modulating signaling pathways associated with inflammation, translational control, stress signaling, secretory function, immunity, and diabetes. Additionally, TYK2i treatment changed the composition of innate and adaptive immune cell populations in the blood and disease target tissues, resulting in an immune phenotype with a diminished capacity for β cell destruction. Overall, these findings indicate that TYK2i has beneficial effects in both the immune and endocrine compartments in models of T1D, thus supporting a path forward for testing TYK2 inhibitors in human T1D.
The cage effect of electron beam irradiation damage in cryo-electron microscopy
Authors: Li Yi , Kang Dong-Dong , Dai Jia-Yu , Wang Lin-Wang 
Published: March 2024

AbstractElectron beam irradiation can cause damage to biological and organic samples, as determined via transmission electron microscopy (TEM). Cryo-electron microscopy (cryo-EM) significantly reduces such damage by quickly freezing the environmental water around organic molecules. However, there are multiple hypotheses about the mechanism of cryo-protection in cryo-EM. A lower temperature can cause less molecular dissociation in the first stage, or frozen water can have a “cage” effect by preventing the dissociated fragments from flying away. In this work, we used real-time time-dependent density functional theory (rt-TDDFT-MD) molecular dynamic simulations to study the related dynamics. We used our newly developed natural orbital branching (NOB) algorithm to describe the molecular dissociation process after the molecule is ionized. We found that despite the difference in surrounding water molecules at different temperatures, the initial dissociation process is similar. On the other hand, the dissociated fragments will fly away at room temperature, while they will remain in the same cage when frozen water is used. Our results provide direct support for the cage effect mechanism.
DrugDomain: the evolutionary context of drugs and small molecules bound to domains
Authors: Medvedev Kirill E. , Schaeffer R. Dustin , Grishin Nick V. 
Published: March 2024

AbstractInteractions between proteins and small organic compounds play a crucial role in regulating protein functions. These interactions can modulate various aspects of protein behavior, including enzymatic activity, signaling cascades, and structural stability. By binding to specific sites on proteins, small organic compounds can induce conformational changes, alter protein-protein interactions, or directly affect catalytic activity. Therefore, many drugs available on the market today are small molecules (72% of all approved drugs in the last five years). Proteins are composed of one or more domains: evolutionary units that convey function or fitness either singly or in concert with others. Understanding which domain(s) of the target protein binds to a drug can lead to additional opportunities for discovering novel targets. The Evolutionary Classification Of protein Domains (ECOD) classifies domains into an evolutionary hierarchy that focuses on distant homology. Previously, no structure-based protein domain classification existed that included information about both the interaction between small molecules or drugs and the structural domains of a target protein. This data is especially important for multidomain proteins and large complexes. Here, we present the DrugDomain database that reports the interaction between ECOD domains of human target proteins and DrugBank molecules and drugs. The pilot version of DrugDomain describes the interaction of 5,160 DrugBank molecules associated with 2,573 human proteins. It describes domains for all experimentally determined structures of these proteins and incorporates AlphaFold models when such structures are unavailable. The DrugDomain database is available online:http://prodata.swmed.edu/DrugDomain/
Effect of copper mill waste material on benthic invertebrates and zooplankton diversity and abundance in Lake Superior beaches
Authors: Larson James H , Lowe Michael R , Bailey Sean W , Bell Amanda H , Cleveland Danielle M 
Published: March 2024

AbstractFrom 1900 to 1932 a copper (Cu) mill operated near Gay, Michigan, along the eastern shore of the Keweenaw Peninsula (Lake Superior, Michigan) and discharged waste material (stamp sands [SS]) to a nearby beach. These SS escaped containment structures and have been redeposited by wave action along the beaches in northern Grand Traverse Bay and onto Buffalo Reef, an important spawning area for native fish. Newly hatched fish move into nearby beach habitats where they grow during their first summer. Juvenile fish initially consume zooplankton before switching to benthic invertebrates once they are large enough. SS contain metals (especially Cu) that are toxic to many invertebrate taxa, and studies have observed few benthic taxa in areas covered by SS. We sampled the invertebrate community from four Lake Whitefish nursery areas: one near Buffalo Reef with high SS, one south of the Traverse River with moderate SS, one in nearby Little Traverse Bay with little SS, and a beach ∼58 km away with no SS (Big Bay). We also resampled the benthos at sites that had been sampled as part of an earlier Grand Traverse Bay study. Buffalo Reef (high SS) had fewer benthic taxa, and less density of several taxa than Little Traverse Bay (little SS), especially benthic copepods. All beaches had comparable zooplankton diversity, but the abundance was ∼2 orders of magnitude lower at Buffalo Reef (high SS) than other beaches. Cu and several other metals were elevated at beaches with more SS. We found support for associations between benthic density and diversity with depth (positive effect) and Cu concentration (negative effect). Cu concentration was a better predictor of declines in benthic invertebrate abundance and diversity than SS. We also observed that the relationship between Cu concentration and SS was non-linear, and highly variable. For example, 149 mg Cu/kg dry weight sediment is a consensus toxicity threshold used in the literature, but the prediction interval around that concentration from our model is 26-851 mg Cu/kg dry weight. A better predictive model of this relationship would be beneficial to develop to understand what level of SS reduction would prevent Cu impacts on invertebrates.
High-throughput selection of glucose-binding proteins from massive datasets: Integrating molecular docking and molecular dynamics simulations
Authors: Makare Anurag , Chaudhary Amit , De Debankita , Deshpande Parijat , Panwar Ajay Singh 
Published: March 2024

ABSTRACTSelecting suitable glucose-binding proteins (GBPs) is vital for biosensor development for medical diagnostics and quality control in the food industry. Biosensors offer advantages such as high specificity, selectivity, fast response time, continuous measurement, and cost-effectiveness. The current work utilized a combination of molecular docking, molecular dynamics (MD) simulations, and free energy calculations to develop a high-throughput bioinformatics pipeline to select GBP candidates from an extensive protein database (37,325 proteins). Using molecular docking, GBPs with good binding affinity to glucose (1,447 candidates) were virtually screened from the Protein Data Bank. MD simulations ascertained the binding dynamics of a few selected candidates. Further, steered MD (Brownian dynamics fluctuation-dissipation-theorem) was used to estimate binding free energies of the ligand-protein complex. Correlations between ligand-binding parameters obtained from longer MD simulations and binding parameters interpreted from significantly faster docking simulations were investigated. The correlation plots suggested that a combination of threshold values of the following three docking parameters: docking binding energy, binding cavity depth, and the number of hydrogen bonds between the ligand and binding site residues can be used to predict candidate GBPs reliably. Thus, a high-throughput and accurate protein selection process based on relatively faster docking simulations was proposed to screen GBPs for glucose biosensing.
GLMsim: a GLM-based single cell RNA-seq simulator incorporating batch and biological effects
Authors: Wang Jianan , Chen Lizhong , Thijssen Rachel , Phipson Belinda , Speed Terence P. 
Published: March 2024

AbstractWith development of the single cell RNA-seq technologies, large numbers of cells can now be routinely sequenced by different platforms. This requires us to choose an efficient integration tool to merge those cells, and computational simulators to help benchmark and assess the performance of these tools. Although existing single cell RNA-seq simulators can simulate library size, biological and batch effects separately, they currently do not capture associations among these three factors. Here we present GLMsim, the first single cell RNA-seq simulator to simultaneously capture the library size, biology and unwanted variation and their associations via a generalized linear model, and to simulate data resembling the original experimental data in these respects. GLMsim is capable of quantitatively benchmarking different single cell integration methods, and assessing their abilities to retain biology and remove library size and batch effects.
Multi-omics of a rice population identifies genes and genomic regions in rice that bestow low glycemic index and high protein content
Authors: Badoni Saurabh , Pasion-Uy Erstelle , Kor Sakshi , Kim SungRyul , Misra Gopal , Tiozon Rhowell , Buenafe Reuben James Q. , Ramos-Castrosanto Ana Rose , Pratap Vipin , Slamet-Loedin Inez , Steimker Julia von , Alseekh Saleh , Fernie Alisdair R. , Kohli Ajay , Khush Gurudev S. , Sreenivasulu Nese 
Published: March 2024

AbstractTo address the growing incidences of increased diabetes and to meet the daily protein requirements, we developed low glycemic index (GI) rice varieties with protein yield exceeding 14%. In the development of recombinant inbred lines using Samba Mahsuri and IR36 amylose extender as parental lines, we identified quantitative trait loci (QTLs) and genes associated with low GI, high amylose content (AC), and high protein content (PC). By integrating genetic techniques with classification models, this comprehensive approach identified candidate genes on chromosome 2 (qGI2.1/qAC2.1 spanning the region from 18.62Mb to 19.95Mb), exerting influence on low GI and high amylose. Notably, the phenotypic variant with high value was associated with the recessive allele of the starch branching enzyme 2b (sbeIIb). The genome-edited sbeIIb line confirmed low GI phenotype in milled rice grains. Further, combinations of alleles from the highly significant SNPs from the targeted associations and epistatically interacting genes showed ultra-low GI phenotypes with high amylose and high protein. Metabolomics analysis of rice with varying AC, PC, and GI revealed that the superior lines of high AC and PC, and low GI were preferentially enriched in glycolytic and amino acid metabolism, whereas the inferior lines of low AC and PC and high GI were enriched with fatty acid metabolism. The high amylose high protein RIL (HAHP_101) was enriched in essential amino acids like lysine. Such lines may be highly relevant for food product development to address diabetes and malnutrition.Significance StatementThe increasing global incidence of diabetes calls for the development of diabetic friendly healthier rice. In this study, we developed recombinant inbred rice lines with milled rice exhibiting ultra-low to low glycemic index and high protein content from the cross between Samba Mahsuri and IR36 amylose extender. We performed comprehensive genomics and metabolomics complemented with modeling analyses emphasizing the importance ofOsSbeIIbalong with additional candidate genes whose variations allowed us to produce target rice lines with lower glycemic index and high protein content in a high-yielding background. These lines represent an important breeding resource to address food and nutritional security.
Aberrant neuronal hyperactivation causes an age- and diet-dependent decline in associative learning behavior
Authors: Aleogho Binta Maria , Mohri Mizuho , Jang Moon Sun , Tsukada Sachio , Al-Hebri Yana , Tsukada Yuki , Mori Ikue , Noma Kentaro 
Published: March 2024

AbstractThe impairment of memory, cognition, and behavior during aging is generally thought to arise from diminished neuronal activities. The nematodeCaenorhabditis elegansexhibits age-dependent declines in an associative learning behavior called thermotaxis. Genetic ablation of individual neurons revealed that an absence of either AWC sensory or AIA inter-neurons preserved the thermotaxis ability of aged animals. Calcium imaging showed age-dependent spontaneous hyperactivities in both neurons. The age-dependent neuronal hyperactivity and behavioral decline were ameliorated by changing diets. We further demonstrate that the enhanced activities of AWC and AIA were differentially dependent on the forms of neurotransmission mediated by neurotransmitters and neuropeptides. Together, our data provides evidence that aberrantly enhanced, not diminished, neuronal responses can impair behavior during aging.One-Sentence SummaryEnhanced neuronal activity during aging impairsC. eleganslearning behavior.
Consensus Clustering for Robust Bioinformatics Analysis
Authors: Yousefi Behnam , Schwikowski Benno 
Published: March 2024

AbstractClustering plays an important role in a multitude of bioinformatics applications, including protein function prediction, population genetics, and gene expression analysis. The results of most clustering algorithms are sensitive to variations of the input data, the clustering algorithm and its parameters, and individual datasets. Consensus clustering (CC) is an extension to clustering algorithms that aims to construct a robust result from those clustering features that are invariant under the above sources of variation. As part of CC, stability scores can provide an idea of the degree of reliability of the resulting clustering. This review structures the CC approaches in the literature into three principal types, introduces and illustrates the concept of stability scores, and illustrates the use of CC in applications to simulated and real-world gene expression datasets. Open-source R implementations for each of these CC algorithms are available in the GitHub repository:https://github.com/behnam-yousefi/ConsensusClustering
Assembly Arena: Benchmarking RNA isoform reconstruction algorithms for nanopore sequencing
Authors: Sagniez Mélanie , Budhraja Anshul , Paré Bastien , Simpson Shawn M. , Vinet-Ouellette Clément , Rozendaal Marieke , Smith Martin A. 
Published: March 2024

AbstractResolving the transcriptomes of higher eukaryotes is more tangible with the advent of long read sequencing, which greatly facilitates the identification of new transcripts and their splicing isoforms. However, the computational analysis of long read RNA sequencing data remains challenging as it is difficult to disentangle technical artifacts frombona fidebiological information. To address this, we evaluated the performance of multiple leading transcriptome assembly algorithms on their ability to accurately reconstruct RNA transcript isoforms. We specifically focused on deep nanopore sequencing of synthetic RNA spike-in controls (Sequins™ and SIRVs) across different chemistries, including cDNA and direct RNA protocols. Our systematic comparative benchmarking exposes the strengths and limitations of the different surveyed strategies. We also highlight conceptual and technical challenges with the annotation of transcriptomes and the formalization of assembly quality metrics. Our results complement similar recent endeavors, helping forge a path towards a gold standard analytical pipeline for long read transcriptome assembly.
Endogenous CD28 drives CAR T cell responses in multiple myeloma
Authors: Lieberman Mackenzie M. , Tong Jason H. , Odukwe Nkechi U. , Chavel Colin A. , Purdon Terence J. , Burchett Rebecca , Gillard Bryan M. , Brackett Craig M. , McGray A. J. Robert , Bramson Jonathan L. , Brentjens Renier J. , Lee Kelvin P. , Olejniczak Scott H. 
Published: March 2024

AbstractRecent FDA approvals of chimeric antigen receptor (CAR) T cell therapy for multiple myeloma (MM) have reshaped the therapeutic landscape for this incurable cancer. In pivotal clinical trials B cell maturation antigen (BCMA) targeted, 4-1BB co-stimulated (BBζ) CAR T cells dramatically outperformed standard-of-care chemotherapy, yet most patients experienced MM relapse within two years of therapy, underscoring the need to improve CAR T cell efficacy in MM. We set out to determine if inhibition of MM bone marrow microenvironment (BME) survival signaling could increase sensitivity to CAR T cells. In contrast to expectations, blocking the CD28 MM survival signal with abatacept (CTLA4-Ig) accelerated disease relapse following CAR T therapy in preclinical models, potentially due to blocking CD28 signaling in CAR T cells. Knockout studies confirmed that endogenous CD28 expressed on BBζ CAR T cells drovein vivoanti-MM activity. Mechanistically, CD28 reprogrammed mitochondrial metabolism to maintain redox balance and CAR T cell proliferation in the MM BME. Transient CD28 inhibition with abatacept restrained rapid BBζ CAR T cell expansion and limited inflammatory cytokines in the MM BME without significantly affecting long-term survival of treated mice. Overall, data directly demonstrate a need for CD28 signaling for sustainedin vivofunction of CAR T cells and indicate that transient CD28 blockade could reduce cytokine release and associated toxicities.
Hypothalamic Sex-Specific Metabolic Shift by Canagliflozin during Aging
Authors: Jayarathne H.S.M. , Sullivan R. , Stilgenbauer L. , Debarba L.K. , Kuchumov A. , Koshko L. , Scofield S. , Liu W. , Ginsburg B.C. , Miller R.A. , Sadagurski M. 
Published: March 2024

AbstractThe hypothalamus undergoes significant changes with aging and plays crucial roles in age-related metabolic alterations. Sodium-glucose co-transporter 2 inhibitors (SGLT2i) are anti-diabetic agents that promote glucose excretion, and promote metabolic homeostasis. Recent studies have shown that SGLT2i, Canagliflozin (Cana), can extend the median survival of genetically heterogeneous UM-HET3 male mice and improve central metabolic control via increases in hypothalamic insulin responsiveness in aged males, as well as reduced age-associated hypothalamic inflammation. We studied the long- and short-term effects of Cana on hypothalamic metabolic control in UM-HET3 mice. We show that Cana treatment reduced body weight and fat mass in male mice that was associated with enhanced glucose tolerance and insulin sensitivity observed by 12 months. Indirect calorimetry showed that short-term Cana treatment (5 months) increased energy expenditure in male, but not female mice, at 12 months of age. Long-term Cana treatment (18 months) increased metabolic rates in both sexes, and markedly increasing formation of both orexigenic and anorexigenic projections to the paraventricular nucleus of the hypothalamus (PVH) mostly in females by 25 months. Hypothalamic RNA-sequencing analysis revealed sex-specific genes and signaling pathways related to insulin signaling, glycogen catabolic pathway, neuropeptide signaling, and mitochondrial function upregulated by Cana, with males showing a more pronounced and sustained effect on metabolic pathways at both age groups. Overall, our data provide critical evidence for sex-specific mechanisms that are impacted by Cana during aging suggesting key targets of hypothalamic Cana-induced neuroprotection for metabolic control.
Snapshots ofPseudomonas aeruginosaSOS response activation complex reveal structural prerequisites for LexA engagement and cleavage
Authors: Vascon Filippo , Felice Sofia De , Gasparotto Matteo , Huber Stefan T. , Catalano Claudio , Chinellato Monica , Grinzato Alessandro , Filippini Francesco , Maso Lorenzo , Jakobi Arjen J. , Cendron Laura 
Published: March 2024

AbstractAntimicrobial resistance represents a major threat to human health andPseudomonas aeruginosastands out among the pathogens responsible for this emergency. The SOS response to DNA damage plays a pivotal role in bacterial evolution, driving the development of resistance mechanisms and influencing the adaptability of bacterial populations to challenging environments, particularly in the context of antibiotic exposure. Recombinase A (RecA) and the transcriptional repressor LexA are the key players that orchestrate this process, determining either the silencing or the active transcription of the genes under their control. By integrating state-of-the-art structural approaches with binding and functional assaysin vitro, we elucidated the molecular events governing the SOS response activation inP. aeruginosa, focusing on the RecA-LexA interaction. Our findings identify the conserved determinants and strength of the interactions that let RecA trigger the autocleavage and inactivation of the LexA repressor. These results provide the groundwork for designing novel antimicrobial strategies and for exploring the potential translation ofEscherichia coli-derived approaches, to address the health-threatening implications of bacterial infections.Graphical Abstract