bluuebunny/crossref_metadata_2025_split huggingface dataset:
Similarity metric learning on perturbational datasets improves functional identification of perturbations
Authors: Smith Ian , Smirnov Petr , Haibe-Kains Benjamin 
Published: June 2023

AbstractAnalysis of high-throughput perturbational datasets, including the Next Generation Connectivity Map (L1000) and the Cell Painting projects, uses similarity metrics to identify perturbations or disease states that induce similar changes in the biological feature space. Similarities among perturbations are then used to identify drug mechanisms of action, to nominate therapeutics for a particular disease, and to construct bio-logical networks among perturbations and genes. Standard similarity metrics include correlations, cosine distance and gene set enrichment methods, but these methods operate on the measured features without refinement by transforming the measurement space. We introduce Perturbational Metric Learning (PeML), a weakly supervised similarity metric learning method to learn a data-driven similarity function that maximizes discrimination of replicate signatures by transforming the biological measurements into an intrinsic, dataset-specific basis. The learned similarity functions show substantial improvement for recovering known biological relationships, like mechanism of action identification. In addition to capturing a more meaningful notion of similarity, data in the transformed basis can be used for other analysis tasks, such as classification and clustering. Similarity metric learning is a powerful tool for the analysis of large biological datasets.
A non-oscillatory, millisecond-scale embedding of brain state provides insight into behavior
Authors: Parks David F. , Schneider Aidan M. , Xu Yifan , Brunwasser Samuel J. , Funderburk Samuel , Thurber Danilo , Blanche Tim , Dyer Eva L. , Haussler David , Hengen Keith B. 
Published: June 2023

ABSTRACTSleep and wake are understood to be slow, long-lasting processes that span the entire brain. Brain states correlate with many neurophysiological changes, yet the most robust and reliable signature of state is enriched in rhythms between 0.1 and 20 Hz. The possibility that the fundamental unit of brain state could be a reliable structure at the scale of milliseconds and microns has not been addressed due to the physical limits associated with oscillation-based definitions. Here, by analyzing high resolution neural activity recorded in 10 anatomically and functionally diverse regions of the murine brain over 24 h, we reveal a mechanistically distinct embedding of state in the brain. Sleep and wake states can be accurately classified from on the order of 100to 101ms of neuronal activity sampled from 100 μm of brain tissue. In contrast to canonical rhythms, this embedding persists above 1,000 Hz. This high frequency embedding is robust to substates and rapid events such as sharp wave ripples and cortical ON/OFF states. To ascertain whether such fast and local structure is meaningful, we leveraged our observation that individual circuits intermittently switch states independently of the rest of the brain. Brief state discontinuities in subsets of circuits correspond with brief behavioral discontinuities during both sleep and wake. Our results suggest that the fundamental unit of state in the brain is consistent with the spatial and temporal scale of neuronal computation, and that this resolution can contribute to an understanding of cognition and behavior.
3D spheroid culturing ofAstyanax mexicanusliver-derived cell lines recapitulates distinct transcriptomic and metabolic states ofin vivotissue environment
Authors: Biswas Tathagata , Rajendran Naresh , Hassan Huzaifa , Zhao Chongbei , Rohner Nicolas 
Published: June 2023

AbstractIn vitroassays are crucial tools for gaining detailed insights into various biological processes, including metabolism. Cave morphs of the river-dwelling fish species,Astyanax mexicanus, have adapted their metabolism allowing them to thrive in the biodiversity-deprived and nutrient-limited environment of caves. Liver-derived cells from the cave and river morphs ofAstyanax mexicanushave proven to be excellentin vitroresources to better understand the unique metabolism of these fish. However, the current 2D cultures have not fully captured the complex metabolic profile of theAstyanaxliver. It is known that 3D culturing can modulate the transcriptomic state of cells when compared to its 2D monolayer culture. Therefore, in order to broaden the possibilities of thein vitrosystem by modeling a wider gamut of metabolic pathways, we cultured the liver-derivedAstyanaxcells of both surface and cavefish into 3D spheroids. We successfully established 3D cultures at various cell seeding densities for several weeks and characterized the resultant transcriptomic and metabolic variations. We found that the 3D culturedAstyanaxcells represent a wider range of metabolic pathways, including cell cycle changes and antioxidant activities, associated with liver functioning as compared to its monolayer culture. Additionally, the spheroids also exhibited surface and cave-specific metabolic signatures, making it a suitable system for evolutionary studies associated with cave adaptation. Taken together, the liver-derived spheroids prove to be a promisingin vitromodel for widening our understanding of metabolism inAstyanax mexicanusand of vertebrates in general.
Performance of Off-the-Shelf Machine Learning Architectures and Biases in Detection of Low Left Ventricular Ejection Fraction
Authors: Bergquist Jake A. , Zenger Brian , Brundage James , MacLeod Rob S. , Bunch T. Jared , Shah Rashmee , Ye Xiangyang , Lyons Ann , Ranjan Ravi , Tasdizen Tolga , Steinberg Benjamin A. 
Published: June 2023

1AbstractArtificial intelligence - machine learning (AI-ML) is a computational technique that has been demonstrated to be able to extract meaningful clinical information from diagnostic data that are not available using either human interpretation or more simple analysis methods. Recent developments have shown that AI-ML approaches applied to ECGs can accurately predict different patient characteristics and pathologies not detectable by expert physician readers. There is an extensive body of literature surrounding the use of AI-ML in other fields, which has given rise to an array of predefined open-source AI-ML architectures which can be translated to new problems in an “off-the-shelf” manner. Applying “off-the-shelf” AI-ML architectures to ECG-based datasets opens the door for rapid development and identification of previously unknown disease biomarkers. Despite the excellent opportunity, the ideal open-source AI-ML architecture for ECG related problems is not known. Furthermore, there has been limited investigation on how and when these AI-ML approaches fail and possible bias or disparities associated with particular network architectures. In this study, we aimed to: (1) determine if open-source, “off-the-shelf” AI-ML architectures could be trained to classify low LVEF from ECGs, (2) assess the accuracy of different AI-ML architectures compared to each other, and (3) to identify which, if any, patient characteristics are associated with poor AI-ML performance.
The Mechanism and Energetics of the Dynein Priming Stroke
Authors: Golcuk Mert , Yilmaz Sema Zeynep , Yildiz Ahmet , Gur Mert 
Published: June 2023

ABSTRACTDyneins is an AAA+ motor responsible for motility and force generation towards the minus end of microtubules. Dynein motility is powered by nucleotide-dependent transitions of its linker domain, which transitions between straight (post-powerstroke) and bent (pre-powerstroke) conformations. To understand the dynamics and energetics of the linker, we per-formed all-atom molecular dynamics (MD) simulations of human dynein-2 primed for its power stroke. Simulations re-vealed that the linker can adopt either a bent conformation or a semi-bent conformation, separated by a 5.7 kT energy bar-rier. The linker cannot switch back to its straight conformation in the pre-powerstroke state due to a steric clash with the AAA+ ring. Simulations also showed that an isolated linker has a free energy minimum near the semi-bent conformation in the absence of the AAA+ ring, indicating that the linker stores mechanical energy as it bends and releases this energy during the powerstroke.
Deep Learning for Transesophageal Echocardiography View Classification
Authors: Steffner Kirsten , Christensen Matthew , Gill George , Bowdish Michael , Rhee Justin , Kumaresan Abirami , He Bryan , Zou James , Ouyang David 
Published: June 2023

AbstractTransesophageal echocardiography (TEE) imaging is a vital monitoring and diagnostic tool used during all major cardiac surgeries, guiding perioperative diagnoses, surgical decision-making, and hemodynamic evaluation in real-time. A key limitation to the automated evaluation of TEE data is the complexity and unstructured nature of the images, which demonstrate significant heterogeneity across varied views in the evaluation of different cardiac structures. In this study, we describe the first machine learning model for TEE view classification. We trained a convolutional neural network (CNN) to predict standardized TEE views using labeled intraoperative and intraprocedural TEE videos from Cedars-Sinai Medical Center (CSMC). We externally validated our model on intraoperative TEE videos from Stanford University Medical Center (SUMC). Accuracy of our model was high across all labeled views. The highest performance was achieved for the Trans-Gastric Left Ventricular Short Axis View (area under the receiver operating curve [AUC] = 0.971 at CSMC, 0.957 at SUMC), the Mid-Esophageal Long Axis View (AUC = 0.954 at CSMC, 0.905 at SUMC), the Mid-Esophageal Aortic Valve Short Axis View (AUC = 0.946 at CSMC, 0.898 at SUMC), and the Mid-Esophageal 4-Chamber View (AUC = 0.939 at CSMC, 0.902 at SUMC). Ultimately, we demonstrate that our unique deep learning model can accurately classify standardized TEE views, which will facilitate further downstream analyses for intraoperative TEE imaging.
ChatGPT in Dermatology: A Comprehensive Systematic Review
Authors: Gabashvili Irene S. 
Published: June 2023

AbstractBackgroundIn recent years, the field of dermatology has adopted the latest technologies to enhance patient care and medical education. Mobile technology and social media platforms have revolutionized the delivery of services, and AI-based procedures are poised to become part of dermatologists’ daily routines. There are already numerous papers on the use of the latest conversational AI tool, ChatGPT, in dermatology, and a systematic analysis of these studies can yield valuable insights.ObjectiveTo comprehensively evaluate the literature on the various applications of ChatGPT in dermatology and related areas.MethodsWe searched PubMed, Cochrane Library, EuropePMC, medRxiv, arXiv, bioRxiv, Dimensions AI, Semantic Scholar, and Google Scholar, to obtain articles published up until May 15, 2023. The eligibility criteria focused on studies examining the use of ChatGPT in dermatology-related areas. To address the risks of bias, we employed a meticulous selection process, incorporating diverse information sources, including preprints, in multiple languages. In addition to full text articles, acknowledgments and supplemental material were also examined to ensure a thorough analysis. The synthesis of findings utilized network analysis and thematic synthesis methodologies.ResultsThere was a total of 87 manuscripts that fulfilled eligibility requirements. Over a third of them (36%) acknowledged the assistance of ChatGPT in writing, data analysis or software development. About a quarter (24%) were case reports describing dermatological manifestations and complications. ChatGPT demonstrated successful performance answering questions related to dermatology, ranging from excellent in cancer to barely passable in specialized and lesser-known dermatology areas, although its performance improved with GPT 4. There are advancements in interactive learning, integrations with image-based AI, and enhancing language models for dermatology applications.ConclusionsThere has been a remarkable surge in the adoption of ChatGPT in areas related to dermatology, especially in writing case reports. As researchers are aware of safety and uncertainty, a continued feedback loop for reporting errors is crucial for the ongoing improvement and training of AI models, ensuring their reliability and effectiveness in the field.
An Interleukin 9-Zbtb18 axis promotes germinal center development of memory B cells
Authors: Luo Xiaocui , Hou Xiaoxiao , Wang Yifeng , Li Ye , Yu Shangcheng , Qi Hai 
Published: June 2023

AbstractGerminal centers (GCs) generate humoral memory in the form of long-lived plasma cells and memory B cells (MBCs). MBC development in GCs entail profound changes in states of cell cycle, localization and survival. Whether and how these changes are extrinsically instructed and intrinsically programmed in GC B cells are not well understood. Here we demonstrate that Il-9 instructs MBC development from GCs during the primary response. Il-9 induces expression of Zbtb18, a transcription repressor that is repressed in the bulk of GC cells but highly expressed in GC memory precursor cells and MBCs. While Zbtb18 is dispensable for activation of naïve B cells and for GC formation, it is essential for normal development of GC-derived MBCs. Zbtb18 directly binds to and represses a suite of cyclin and CDK genes to promote quiescence, pro-apoptotic genesBidandCasp3to promote survival, and GC-retaining geneS1pr2to promote GC departure. In the absence of Zbtb18, GCMP cells do not efficiently quit cell cycle to achieve quiescence, do not efficiently downregulate S1pr2 to exit, and they become more prone to die. Our results support that an Il-9-Zbtb18 axis instructs development of functional B-cell memory from GCs.
Comparative Interactome Analysis of α-arrestin Families in Human andDrosophila
Authors: Lee Kyung-Tae , Pranoto Inez K.A. , Kim Soon-Young , Choi Hee-Joo , To Ngoc Bao , Chae Hansong , Lee Jeong-Yeon , Kim Jung-Eun , Kwon Young V. , Nam Jin-Wu 
Published: June 2023

AbstractThe α-arrestins form a large family of evolutionally conserved modulators that control diverse signaling pathways, including both G-protein-coupled receptor-(GPCR-) mediated and non-GPCR mediated pathways, across eukaryotes. However, unlike β-arrestins, only a few α-arrestin targets and functions have been characterized. Here, using affinity purification and mass spectrometry, we constructed interactomes for six human and twelveDrosophilaα-arrestins. The resulting high-confidence interactomes comprised 307 and 467 prey proteins in human andDrosophila, respectively. A comparative analysis of these interactomes predicted not only conserved binding partners, such as motor proteins, proteases, ubiquitin ligases, RNA splicing factors, and GTPase-activating proteins, but also those specific to mammals, such as histone modifiers and the subunits of V-type ATPase. Given the manifestation of the interaction between the human α-arrestin, TXNIP, and the histone-modifying enzymes, including HDAC2, we undertook a global analysis of transcription signals and chromatin structures that were affected by TXNIP knockdown. We found that TXNIP activated targets by blocking HDAC2 recruitment to targets, a result that was validated by chromatin immunoprecipitation assays. Additionally, the interactome for an uncharacterized human α-arrestin ARRDC5 uncovered multiple components in the V-type ATPase, which plays a key role in bone resorption by osteoclasts. Our study presents conserved and species-specific protein-protein interaction maps for α-arrestins, which provide a valuable resource for interrogating their cellular functions for both basic and clinical research.
Evolutionary History of Calcium-Sensing Receptors Unveils Hyper/Hypocalcemia-Causing Mutations
Authors: Bircan Aylin , Kuru Nurdan , Dereli Onur , Selçuk Berkay , Adebali Ogün 
Published: June 2023

AbstractCalcium-sensing receptor evolution highlights hyper/hypocalcemia-causing mutations The Calcium Sensing Receptor (CaSR) is a key player in regulating calcium levels and has been linked to disorders like hypercalcemia and hypocalcemia. Despite advancements in understanding CaSR’s structure and functions, there are still gaps in our understanding of its specific residues and their differences from receptors within the same class. In this study, we used phylogeny-based techniques to identify functionally equivalent orthologs of CaSR, predict residue significance, and compute specificity-determining position (SDP) scores to understand its evolutionary basis. The analysis revealed exceptional conservation of the CaSR subfamily, with high SDP scores being critical in receptor activation and pathogenicity. To further enhance the findings, gradient-boosting trees were applied to differentiate between gain- and loss-of-function mutations responsible for hypocalcemia and hypercalcemia. Lastly, we investigated the importance of these mutations in the context of receptor activation dynamics. In summary, through comprehensive exploration of the evolutionary history of the CaSR subfamily, coupled with innovative phylogenetic methodologies, we identified activating and inactivating residues, providing valuable insights into the regulation of calcium homeostasis and its connections to associated disorders.
An intranuclear bacterial parasite of deep-sea mussels expresses apoptosis inhibitors acquired from its host
Authors: González Porras Miguel Ángel , Assié Adrien , Tietjen Målin , Violette Marlene , Kleiner Manuel , Gruber-Vodicka Harald , Dubilier Nicole , Leisch Nikolaus 
Published: June 2023

AbstractEndozoicomonadaceae bacteria are widespread in many marine animals, and generally considered beneficial. Members of one clade, however, Candidatus Endonucleobacter, infect the nuclei of deep-sea mussels, where they replicate to ≥ 80,000 bacteria per nucleus and cause the nuclei to swell to 50 times their original size. How these parasites are able to persist in host nuclei without the cell undergoing apoptosis is not known. We show here that Ca. Endonucleobacter encodes and expresses 7-15 inhibitors of apoptosis (IAPs), proteins previously only known from animals and viruses. Dual RNA-seq transcriptomes of infected nuclei revealed parallel upregulation of Ca. Endonucleobacter IAPs and host caspases, suggesting an arms race between the parasite and host for control of apoptosis. Comparative phylogenetic analyses revealed that Ca. Endonucleobacter acquired IAPs repeatedly through horizontal gene transfer from their hosts in convergent acquisition, possibly mediated by herpes viruses that may infect both the parasite and the host.
Comparative evaluation of straight and curved extension dialysis catheters for continuous renal replacement therapy in dogs with acute kidney injury
Authors: Bhat Abid Ali , Chandrasekar M. , Nambi A. P. , Bhavani Sandhya , Kavitha S. , Khan Firdous A. 
Published: June 2023

AbstractA patent dual lumen dialysis catheter is one of the basic requirements for efficient extracorporeal (EC) therapy. The objective of this study was to measure resistance to blood flow offered by straight and curved extension dual lumen dialysis catheters used for continuous renal replacement therapy (CRRT). Twenty dogs suffering from acute kidney injury (AKI) were subjected to CRRT. The dogs were allocated randomly to Group-I (Curved extension catheter, n=12) or Group-II (Straight extension catheter, n=8), based on the type of dual-lumen catheter used in CRRT. The catheter outflow and inflow pressures were recorded at blood pump speeds of 50 mL/min and 99-100 mL/min. Data were tested for normality and differences in mean inflow and outflow catheter resistances were evaluated for statistical significance using independent samplesttests. Straight extension catheters offered lower inflow resistance than curved extension catheters at both 50 mL/min (41.50 ± 5.84 mm Hg and 63.75 ± 6.88 mm Hg, respectively;P=0.03) and 99-100 mL/min (63.00 ± 8.11 mm Hg and 86.92 ± 7.02 mm Hg, respectively;P=0.04) blood flow rates. Straight extension catheters also offered lower outflow resistance than curved catheters at 99-100 mL/min (−94.12 ± 7.91 mm Hg and -128.25 ± 7.56 mm Hg, respectively;P=0.01; the negative signs only indicate the direction of blood flow). These findings suggest that straight extension dual lumen dialysis catheters would likely perform better than the curved model in extracorporeal renal replacement therapy.
COVID-19-related disruption and resiliency in immunisation activities in LMICs: a rapid review
Authors: Hartner Anna-Maria , Li Xiang , Gaythorpe Katy 
Published: June 2023

AbstractObjectivesRapid review to determine the extent that immunisation services in LMICs were disrupted by the COVID-19 pandemic and what factors can be considered to build resilience in future.SettingWe searched PubMed on 28th Feb 2023 for studies published after 1st December 2019 in English that focused on LMICs.ParticipantsScreening and data extraction were conducted by two experienced reviewers with one reviewer vote minimum per study per stage. Of 3801 identified studies, 66 met the eligibility criteria.OutcomesRoutine vaccine coverage achieved; Supplementary immunisation activity timing; Vaccine doses given; Timing of vaccination; Supply chain changes; factors contributing to disruption or resilience.ResultsIncluded studies showed evidence of notable declines in immunisation activities across LMICs related to the COVID-19 pandemic. These have included reductions in achieved routine coverage, cancellation or postponement of campaigns, and underimmunised cohorts. Immunisation was most disrupted in the early months of the pandemic, particularly March to May 2020; however, the amount of recovery seen varied by country, age-group, and vaccine. Though many countries observed partial recovery beginning after lockdown policies were lifted in 2020, disruption in many countries has also continued into 2021. It has also been noted that clinician staff shortages and vaccine stock outs caused by supply chain disruptions contributed to immunisation delays but that concern over COVID transmission was a leading factor. Key resiliency factors included community outreach and healthcare worker support. Finally, whilst our search took place in February 2023, the latest dataset used across all studies was from November 2022 and many focused on 2020; as a result some of the study conclusions do not take recovery into account.ConclusionsThere is limited information on whether reductions in vaccination coverage or delays have persisted beyond 2021. Further research is needed to assess ongoing disruptions and identify missed vaccine cohorts.Strengths and limitations of this studyThe rapid synthesis of findings related to immunization disruption and recovery to-date allows for key insights to target missed cohorts and identify research gaps.We include a narrative analysis of disruption across LMICs; this review benefits from the inclusion of barriers, enablers, and resilience to/in service provision.The search strategy was limited to studies published on PubMed up to February 28th, 2023, meaning not all relevant research meeting inclusion criteria may have been captured.