bluuebunny/crossref_metadata_2025 huggingface dataset:
TET1 Functions as a Tumor Suppressor in Lung Adenocarcinoma Through Epigenetic Remodeling and Immune Modulation
Authors: Rahim Abdur , Ruis Brian , Rajczewski Andrew T. , Kruk Monica , Tretyakova Natalia Y.
Published: November 2024

Ten-Eleven Translocation (TET1-3) dioxygenases oxidize 5-methylcytosine (5mC) in DNA to generate 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC), and 5-carboxylcytosine (5caC), initiating DNA demethylation. The three proteins share significant sequence homology and catalyze the same chemical reaction utilizing alpha-ketoglutarate cofactor and non-heme iron to oxidize the methyl group of 5mC. Since their discovery in 2009, there have been contradictory reports regarding the roles of TET proteins in cancer.TETgenes have been characterized as tumor suppressor genes because their expression levels are reduced in many human cancers including lymphoma, prostate, and pancreas, andTET2gene mutations are common in hematological cancers. However,TET1was recently reported to be overexpressed in triple negative breast cancer and to act as a protooncogene in lung cancer. In the present study, we employed genetic approaches to directly address the function of TET1 protein in lung adenocarcinoma. We found that overexpression ofTET1in human lung adenocarcinoma (H441) cells decreased their proliferation and inhibited colony formation, cell migration, and 3D spheroid tumorigenesis. In contrast,TET1knockout in lung adenocarcinoma accelerated cell growth and promoted colony formation, cell migration, and 3D spheroid tumorigenesis. Transcriptomics and proteomics analyses revealed thatTET1overexpression was associated with overexpression of immune markers, primarily via activation of TNF and NF-kB signaling pathways.TET1knockout in lung adenocarcinoma cells induces the expression of genes involved in cellular metabolism and cell growth. Our results are consistent with a tumor suppressor role ofTET1gene in lung adenocarcinoma and reveal its role in activating antitumor immunity.
Tissue-specific responses of the central carbon metabolism in tomato fruit to low oxygen stress
Authors: Li Xindan , Terzoudis Konstantinos , Hertog Maarten L.A.T.M. , Nicolaï Bart M.
Published: November 2024

Tomato (Solanum lycopersicumL.) is an important model plant whose fleshy fruit consists of well-differentiated tissues. Recently it was shown that these tissues develop hypoxia during fruit development and ripening. Therefore, we employed a combination of metabolomics and isotopic labeling to investigate the central carbon metabolic response of tomato fruit tissues (columella, septa and mesocarp) to low O2stress. The concentration and13C-label enrichment of intermediates from the central carbon metabolism were analyzed using gas chromatography–mass spectrometry. The results showed an increase in glycolytic activity and the initiation of fermentation in response to low O2conditions. In addition, the up-regulation of the GABA shunt and accumulation of amino acids, alanine and glycine, were observed under low O2conditions. Notably, tissue specificity was observed at the metabolite level, with concentrations of most metabolites being highest in columella tissue. In addition, there were tissue-specific differences in the central carbon metabolism with the columella exhibiting the highest metabolic activity and sensitivity to the changes in O2concentration, followed by septa and mesocarp tissues. Our results are consistent with common plant responses and adaptive mechanisms to low O2stress, while unravelling some tissue-specific differences, increasing our understanding of the intact fruit response to low O2stress.
DiCARN-DNase: Enhancing Cell-to-Cell Hi-C Resolution Using Dilated Cascading ResNet with Self-Attention and DNase-seq Chromatin Accessibility Data
Authors: Olowofila Samuel , Oluwadare Oluwatosin
Published: November 2024

The spatial organization of chromatin is fundamental to gene regulation and essential for proper cellular function. The Hi-C technique remains the leading method for unraveling 3D genome structures, but the limited availability of high-resolution Hi-C data poses significant challenges for comprehensive analysis. Deep learning models have been developed to predict high-resolution Hi-C data from low-resolution counterparts. Early CNN-based models improved resolution but struggled with issues like blurring and capturing fine details. In contrast, GAN-based methods encountered difficulties in maintaining diversity and generalization. Additionally, most existing algorithms perform poorly in cross-cell line generalization, where a model trained on one cell type is used to enhance high-resolution data in another cell type. In this work, we propose DiCARN (Dilated Cascading Residual Network) to overcome these challenges and improve Hi-C data resolution. DiCARN leverages dilated convolutions and cascading residuals to capture a broader context while preserving fine-grained genomic interactions. Additionally, we incorporate DNase-seq data into our model, providing a robust framework that demonstrates superior generalizability across cell lines in high-resolution Hi-C data reconstruction. DiCARN is publicly available athttps://github.com/OluwadareLab/DiCARN
Transcutaneous Vagus Nerve Stimulation Reduces Pain and OA Progression in Mouse Models of Post-Traumatic Osteoarthritis
Authors: Yadav Shivmurat , Morris Lynsie , Conner Taylor , Lumry Jessica , South Sanique M , Prinz Emmaline , Izda Vladislav , Dyson Gabby , Barrett Montana , Stavrakis Stavros , Jeffries Matlock A , Griffin Timothy M , Humphrey Mary Beth
Published: November 2024

Currently, there are no disease-modifying osteoarthritis (OA) drugs (DMOAD) to prevent OA progression and there are limitations on pain relieving therapeutics. Vagus nerve stimulation (VNS) delivered by an implantable device is FDA-approved for refractory epilepsy and severe depression. Here, we investigated the efficacy of transcutaneous VNS (tVNS) for preventing OA progression and providing pain relief in two mouse models of post-traumatic OA (PTOA): the surgical destabilized medial meniscus (DMM) and the non-surgical forced tibial compression anterior cruciate ligament rupture (ACLR). Here, we show that 2 weeks of tVNS significantly reduced histological OA scores in male and female mice after ACLR compared to sham stimulation. In female, but not male, mice, tVNS reduced hyperalgesia and mechanical allodynia. In the slower DMM model, 8 weeks of tVNS improved weight bearing in male and female mice, but only female mice had improved hyperalgesia. Male mice had lower OA histological scores. Serum proinflammatory cytokines were significantly reduced by tVNS in both models but differed by gender and model. Overall, these results provide strong pre-clinical evidence that tVNS reduces OA progression, improves pain, and suppresses pro-inflammatory cytokines, making it a promising DMOAD.
Heterogeneity induced block co-polymer segregation in confinement
Authors: Mohanta Dibyajyoti , Dwivedi Manish , Giri Debaprasad
Published: November 2024

Motivated by the work on block copolymer models that provide insights into epigenetics driven chromosome organization, we investigate the segregation behavior of five distinct 2-block co-polymers (BCPs) system with varying block sizes, confined within both symmetric and lateral geometries. Using exact enumeration method and Langevin dynamics simulation, our simple self-avoiding polymer model reveals robust behaviors (across statics and dynamic studies) despite strong finite-size effects. We observe that as block length increases, polymer compaction intensifies relying on non-specific interaction, leading to longer segregation times. The dynamic study clearly demonstrates the formation of globular lamellar phases and condensed, stable complex structures in long-range block copolymer (BCP) systems, providing a simplified analogy to lamellar-mediated chromatin compaction, which involves structures that are difficult to segregate under physiological conditions. Dominance of specific interaction over non-specific interaction in long range BCP systems leads to phase separation driven self assemblies which provides a simplified analogy to heterochromatin—inactive or stable domains. In contrast, short-range block sequences remain in a coiled state, exhibiting minimal overlap or interaction due to strong short range attraction, which may corresponds to euchromatin regions where diverse epigenetic states coexist, resulting in active, non-condensed structures. We also observe that asymmetric or lateral confinement favors more segregation between the BCPs irrespective of their underlying sequence.
CytoSpatio: Learning cell type spatial relationships using multirange, multitype point process models
Authors: Chen Haoran , Murphy Robert F.
Published: November 2024

Recent advances in multiplexed fluorescence imaging have provided new opportunities for deciphering the complex spatial relationships among various cell types across diverse tissues. We introduce CytoSpatio, open-source software that constructs generative, multirange, and multitype point process models that capture interactions among multiple cell types at various distances simultaneously. On analyzing five cell types across five tissues, our software showed consistent spatial relationships within the same tissue type, with certain cell types like proliferating T cells consistently clustering across tissue types. It also revealed that the attraction-repulsion relationships between cell types like B cells and CD4-positive T cells vary with tissue type. CytoSpatio can also generate synthetic tissue structures that preserve the spatial relationships seen in training images, a capability not provided by previous descriptive, motif-based approaches. This potentially allows spatially realistic simulations of how cell relationships affect tissue biochemistry.
The effect of deferring feedback on rule-based and information-integration category learning
Authors: Edmunds C. E. R. , Carpenter Kathryn , Wills Andy J. , Milton Fraser
Published: November 2024

Previous work has shown that deferring feedback significantly impairs two-dimensional information-integration category learning, often thought to recruit an implicit learning system, but leaves intact unidimensional rule-based learning, commonly assumed to engage an explicit system (Smith et al., 2014). These results were taken to support the influential COmpetition between Verbal and Implicit Systems (COVIS) dual-process theory. This conclusion has subsequently been challenged by the finding that this dissociation disappears when the number of relevant dimensions is matched between tasks (Le Pelley et al., 2019). However, as well as replacing a unidimensional rule-based task with a two-dimensional conjunction task, Le Pelley et al. also changed the stimuli that were used in their study making it unclear which of these alterations was driving the difference in results. The current paper directly examined how both category structure and stimulus type influence the deferred feedback effect. We replicated both the original sets of results but found that deferred feedback also impaired information-integration learning to a greater extent than a conjunction task when Smith et al.’s original stimuli were used. This result suggests that the effect of deferred feedback on category learning is more complicated than has previously been documented and highlights the critical role the choice of stimuli has in determining whether the effect is obtained.
An Integrated Germline and Somatic Genomic Model Improves Risk Prediction for Coronary Artery Disease
Authors: Yang Xiong , Kim Min Seo , Zhu Xinyu , Uddin Md Mesbah , Nakao Tetsushi , Jemma Cho So Mi , Koyama Satoshi , Xu Tingfeng , Reeskamp Laurens F. , Zhang Rufan , Liu Zhaoqi , Yunga A , de Vries Paul S. , Vasan Ramachandran S. , Boerwinkle Eric , Morrison Alanna C. , Psaty Bruce M. , Tracy Russell P. , Heckbert Susan R. , Cho Michael H. , Yun Jeong H , Palmer Nicholette D. , Bowden Donald W. , Murabito Joanne M. , Levy Daniel , Heard-Costa Nancy L. , O’Connor George T. , Becker Lewis C. , Kral Brian G. , Yanek Lisa R. , Raffield Laura M. , Hidalgo Bertha , Rotter Jerome I. , Rich Stephen S. , Taylor Kent D. , Post Wendy S. , Kooperberg Charles , Reiner Alexander P. , Mitchell Braxton D. , Kardia Sharon L.R. , Smith Jennifer A. , Peyser Patricia A. , Bielak Lawrence F. , Yon Dong Keon , Won Hong-Hee , Arnett Donna K. , Smith Albert V. , Gabriel Stacey B. , Ellinor Patrick T. ,   NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Natarajan Pradeep , Wang Minxian , Fahed Akl C.
Published: November 2024

Multiple germline and somatic genomic factors are associated with risk of coronary artery disease (CAD), but there is no single measure of risk that integrates all information from a DNA sample, limiting clinical use of genomic information. To address this gap, we developed an integrated genomic model (IGM), analogous to a clinical risk calculator that combines various clinical risk factors into a unified risk estimate. The IGM includes six genetic drivers for CAD, including germline factors (familial hypercholesterolemia [FH] variants, CAD polygenic risk score [PRS], proteome PRS, metabolome PRS) and somatic factors (clonal hematopoiesis of indeterminate potential [CHIP], and leukocyte telomere length [LTL]). We evaluated the IGM on CAD risk prediction in the UK Biobank (N=391,536), and validated it in the Trans-Omics for Precision Medicine (TOPMed) program (N=34,177). The 10-year CAD risk based on the IGM profile ranged from 1.1% to 15.5% in the UK Biobank and from 3.8% to 33.0% in TOPMed, with a more pronounced gradient in males than females. IGM captured the cumulative effect of multiple genetic drivers, identifying individuals at high risk for CAD despite lacking obvious high risk genetic factors, or individuals at low risk for CAD despite having known genetic risk variants such as FH and CHIP. The IGM had the highest performance in younger individuals (C-statistic 0.805 [95% CI, 0.699-0.913] for age ≤ 45 years). In middle age, IGM augmented the performance of the Pooled Cohort Equations (PCE), a clinical risk calculator for CAD. Adding IGM to PCE resulted in a continuous net reclassification index of 33.45% (95% CI, 32.11%-34.76%). We present the first model that integrates all currently available information from a single “DNA biopsy” to translate complex genetic information into a single risk estimate.
Evaluation of T Cell Receptor Construction Methods from scRNA-Seq Data
Authors: Tian Ruonan , Yu Zhejian , Xue Ziwei , Wu Jiaxin , Wu Lize , Cai Shuo , Gao Bing , He Bing , Zhao Yu , Yao Jianhua , Lu Linrong , Liu Wanlu
Published: November 2024

T cell receptors (TCRs) serve pivotal roles in the adaptive immune system by enabling recognition and response to pathogens and irregular cells. Various methods exist for TCR construction from single-cell RNA sequencing (scRNA-seq) datasets, each with its unique characteristics regarding accuracy, sensitivity, adaptability, usability, time, and memory consumption. Yet, a comprehensive understanding of their relative strengths and weaknesses for different applications remains elusive. In our research, we implemented a benchmark analysis utilizing experimental single-cell immune profiling datasets encompassing paired scRNA-seq as input and scTCR-seq datasets as ground truth reference from human and mouse. Additionally, we introduced a novel simulator, YASIM-scTCR (Yet Another Simulator for single-cell TCR), capable of generating scTCR-seq reads containing a diverse array of TCR- derived sequences under different sequencing depths and read lengths. Our results consistently showed that TRUST4 outperformed others across multiple datasets, while MiXCR and DeRR also demonstrated considerable accuracy. We also discovered that the sequencing depth inherently imposes a critical constraint on successful TCR construction from scRNA-seq data. In summary, we present a benchmark study to aid researchers in choosing the most appropriate methods for reconstructing TCR from scRNA-seq data.
Density-based optimization for unbiased, reproducible clustering applied to single molecule localization microscopy
Authors: Hammer Joseph L. , Devanny Alexander J. , Kaufman Laura J.
Published: November 2024

Single molecule localization microscopy (SMLM) has provided insight into the spatial organization of molecules at length scales below the diffraction limit of visible light. In SMLM data, density-based clustering approaches have proven to be valuable tools for probing the nanoscale structure of biological molecules, although little guidance is available for evaluating the accuracy of these results, which are often strongly dependent on user-input parameters. Here, we develop an efficient implementation of density-based cluster validation (DBCV) that can quantitatively evaluate clustering performance in SMLM-sized datasets without ground truth knowledge. We demonstrate that maximizing DBCV scores accurately identifies ground truth clustering in noisy, simulated datasets. By coupling DBCV score maximization with Bayesian optimization, we outline an optimization method, DBOpt, that selects unbiased input parameters for density-based clustering algorithms. We demonstrate that optimal input parameters can be selected for popular algorithms (DBSCAN, HDBSCAN, OPTICS) with minimal user input. Lastly, we show that DBOpt reports accurate feature sizes in 2D and 3D experimental datasets. Taken together, we propose an analysis pipeline that can be applied to a diverse array of experimental data that will improve the integrity and quality of cluster analyses in the broader scientific community.
Targeted Alpha Therapy with [225Ac]Ac-Macropa-Isatuximab for CD38-positive Hematological Malignancies
Authors: Alvarez Natalia Herrero , Bauer David , Michel Alexa L. , Carter Lukas M. , Lewis Jason S.
Published: November 2024

Background

Hematological malignancies include diverse cancers related to immune system cells and blood-forming tissue. Treatment resistance and relapse are common despite the introduction of novel therapeutics. Following the development of the PET probe [89Zr]Zr-DFO-isatuximab, targeting the overexpressed CD38 receptor, we developed [225Ac]Ac-Macropa-isatuximab for targeted alpha therapy in murine models of human multiple myeloma (MM) and lymphoma.

Methods

In vitro studies were performed using the CD38 expressing MM1.S (human MM) and Daudi (human lymphoma). Radiopharmaceutical therapy studies were performed in female NSG mice, and the disseminated disease models were established by intravenous injection of luciferase-transfected cells. Mice were randomized (n = 10 mice per cohort) and received a high activity (5.5 kBq) or low activity (2.7 kBq) of [225Ac]Ac-Macropa-Isatuximab in single or multiple cycles. Controls receiving untargeted [225Ac]Ac-Macropa-IgG or saline were included. Tumor burden was measured by bioluminescence imaging (BLI). Weight loss greater than 20% or leg paralysis were used as endpoints.

Results

[225Ac]Ac-Macropa-Isatuximab was obtained with high radiochemical yield and purity (>95%). It displayed high immunoreactivity and excellent stability in human serum over 10 days. The therapeutic effect of [225Ac]Ac-mcp-Isatuximab was significant for all the treatment cohorts compared to the saline control after administration of the first cycle. Low activities were better tolerated in general, resulting in extended median survivals. The most successful regimen in the MM model was the dual cycle of low activity, with a median survival of 60 days (P < 0.001). In the lymphoma model, the single high activity of 5.5 kBq and four low activity of 2.7 kBq resulted in similar median survivals of 143 days (P < 0.0001) and 147 days (P < 0.0001). These regimens resulted in complete responses with no detectable cancer cells in some cases. Remarkably, no significant kidney damage was observed in any of the models.

Conclusion

[225Ac]Ac-Macropa-Isatuximab selectively targets CD38, reducing tumor growth and, in some cases, tumor eradication, especially when applied in multiple cycles. Importantly, it has not been associated with significant toxicities at levels of administered activity required for therapeutic benefit, indicating its promise as a therapeutic option.
Phase Separation to Resolve Growth-Related Circuit Failures
Authors: Zhang Rong , Yang Wangfei , Zhang Rixin , Rijal Sadikshya , Youssef Abdelrahaman , Zheng Wenwei , Tian Xiao-Jun
Published: November 2024

Fluctuations in host cell growth poses a significant challenge to synthetic gene circuits, often disrupting circuit function. Existing solutions typically rely on circuit redesign with alternative topologies or additional control elements, yet a broadly applicable approach remains elusive. Here, we introduce a new strategy based on liquid-liquid phase separation (LLPS) to stabilize circuit performance. By engineering a self-activating circuit with transcription factors (TF) fused to an intrinsically disordered region (IDR), we enable the formation of TF condensates at the promoter region, maintaining local TF concentration despite growth-mediated dilution. This condensate formation preserves bistable memory in the self-activating circuit, demonstrating that phase separation can robustly counteract growth fluctuations, offering a novel design principle for resilient synthetic circuits.
Identification and annotation of centromeric hypomethylated regions with Centromere Dip Region (CDR)-Finder
Authors: Mastrorosa F. Kumara , Oshima Keisuke K. , Rozanski Allison N. , Harvey William T. , Eichler Evan E. , Logsdon Glennis A.
Published: November 2024

Centromeres are chromosomal regions historically understudied with sequencing technologies due to their repetitive nature and short-read mapping limitations. However, recent improvements in long-read sequencing allowed for the investigation of complex regions of the genome at the sequence and epigenetic levels. Here, we present Centromere Dip Region (CDR)-Finder: a tool to identify regions of hypomethylation within the centromeres of high-quality, contiguous genome assemblies. These regions are typically associated with a unique type of chromatin containing the histone H3 variant CENP-A, which marks the location of the kinetochore. CDR-Finder identifies the CDRs in large and short centromeres and generates a BED file indicating the location of the CDRs within the centromere. It also outputs a plot for visualization, validation, and downstream analysis. CDR-Finder is available at https://github.com/EichlerLab/CDR-Finder.
Hypoxia exposure fine-tunes mitochondrial function in sea turtle cells
Authors: Arango B. Gabriela , Ensminger David C. , Xing Dianna , Godard-Codding Celine A. , Vázquez-Medina José Pablo
Published: November 2024

Sea turtles experience extreme fluctuations in oxygen availability derived from extended breath-hold diving, yet the cellular adjustments that underlie hypoxia tolerance in these animals remain poorly understood. Here, we used metabolite profiling, extracellular flux assays, and microscopic analyses of the mitochondrial reticulum to study how primary cells derived from sea turtles and lizards cope with extended hypoxia exposure. Cells from both species proliferate in primary culture, stain positive for fibroblast markers, are metabolically active, and stabilize HIF1-α when exposed to chemical or environmental hypoxia. In contrast to lizard cells, sea turtle cells exhibit a faster and more robust response to 1 or 24-hour hypoxia exposure (0.1% O2), upregulating antioxidant pathways and optimizing oxygen use rather than relying on glycolytic metabolism. Similarly, the mitochondrial reticulum is maintained without apparent fragmentation during hypoxia exposure in sea turtle cells. Consistent with these observations, mitochondrial function readily recovers in sea turtle but not lizard cells upon reoxygenation. These findings show that sea turtle cells undergo intrinsic metabolic adjustments to cope with extreme oxygen fluctuations, aligning with the remarkable hypoxic tolerance exhibited by these animals, which can endure up to 7 hours of breath-holding underwater.
Effects of ultrasound-guided high ankle block combined with general anesthesia on postoperative cognitive function in fragile elderly patients based on the analysis of scale and EEG monitor
Authors: Xia Ziwei , Ma Guangkuo , Xue Huanjia , Wang Fangjun , Wang Liwei , Wang Kai
Published: November 2024

Introduction

Ultrasound-guided high ankle block can provide prolonged analgesia for foot and ankle surgeries while preserving ankle motor function. Given that fragile elderly patients are prone to cognitive impairment after general anesthesia, this study intends to implement high ankle block for fragile elderly patients undergoing foot and ankle fracture surgery, and use intraoperative electroencephalogram (EEG) analysis combined with postoperative scales to investigate its effect on patients’ postoperative cognitive function.

Methods and analysis

This randomized controlled trial will be conducted in Xuzhou Central Hospital. A total of 126 elderly patients scheduled to undergo unilateral ankle fracture (uni/bi-/triple ankle) incision and reduction internal fixation (ORIF) surgery will be randomly assigned to either the HAB group or the GB group in a 1:1 ratio. Patients will receive ultrasound-guided high ankle block and general anesthesia (HAB group) or general anesthesia alone (GB group). Multimodal analgesia will include intraoperative flurbiprofen ester and postoperative patients will be given appropriate medications according to the postoperative pain management “three-step ladder”. The primary outcome indicator was the incidence of dNCR at 7th day postoperation. The secondary outcome indicators were the incidence of dNCR at 1st and 30th days postoperation; alpha relative power, alpha power, and burst inhibition ratio in each brain region at 30 min after induction of anesthesia; MoCA scores, patient stress response indexes: ACTH, NE, Ang-II, β-EP, Glu, and Cor levels; patients’ VAS pain scores; patients’ satisfaction scores; first time getting out of bed postoperatively; and time of discharge from the hospital. Safety outcomes were dizziness, headache, vomiting, urinary retention, bradycardia, tachycardia, hypotension, and hypertension.

Ethics and dissemination

Ethics approval was obtained from the Ethics Committee of the Xuzhou Central Hospital. All patients will provide written informed consent. The results of this study will be published in a peer-reviewed journal.

Trial registration number

Chinese Clinical Trial Registry (ChiCTR2400050927)
A Decade of Progress in Artificial Intelligence for Fundus Image-Based Diabetic Retinopathy Screening (2014–2024): A Bibliometric Analysis
Authors: Huang Yuting , Qi Yunfei , Liu Chi , Jing Fengshi , Li Changjin , Wang Minghao , Zhu Congcong , Gui Peng , Ge Zongyuan , Han Xiaotong
Published: November 2024

Background/Aims

Diabetic retinopathy (DR) screening using artificial intelligence (AI) has evolved significantly over the past decade. This study aimed to analyze research trends, developments, and patterns in AI-based fundus image DR screening from 2014 to 2024 through bibliometric analysis.

Methods

The study analyzed 1,172 publications from the Web of Science Core Collection database using CiteSpace and Microsoft Excel. The analysis included publication trends, citation patterns, institutional collaborations, and keyword emergence analysis.

Results

Publications showed consistent growth from 2014-2022, with a peak in 2021. India (26%), China (20.05%), and USA (9.98%) dominated research output. IEEE ACCESS was the leading publication venue with 44 articles. Research evolved from traditional image processing to deep learning approaches, with recent emphasis on multimodal AI models. The analysis identified three distinct phases: CNN-based systems (2014-2020), Vision Transformers and innovative learning paradigms (2020-2022), and large foundation models (2022-2024).

Conclusion

The field shows mature development in traditional AI approaches while transitioning toward multimodal learning technologies. Future directions indicate increased focus on telemedicine integration, innovative AI algorithms, and real-world implementation.

What is already known on this topic

AI-based DR screening has been developing since the 1960s, with significant acceleration after 2014 due to deep learning advances.

Traditional manual analysis of fundus images is time-consuming and error-prone.

What this study adds

Comprehensive mapping of research evolution in AI-based DR screening over the past decade.

Identification of research concentration in specific geographical areas and emerging trends in multimodal AI approaches.

How this study might affect research, practice or policy

Highlights the need for increased international collaboration and technology sharing.

Suggests focus areas for future research, including multimodal learning and real-world implementation.

Provides direction for healthcare organizations and researchers in adopting and developing AI-based DR screening technologies.
Methods used to Account for Concurrent Analgesic Use in Randomized Controlled Trials of Interventional Pain Treatments: A Meta-Epidemiologic Study
Authors: Sridhar Balaji V , Humbert Andrew , Babitts Adam , Staab Carina , Daniels Clinton J. , Dhillon Malka , Heagerty Patrick , Goldenberg Joshua , Jensen Mark , Suri Pradeep
Published: November 2024

Objective

The modest effect sizes of most pain treatments make it essential that randomized controlled trials (RCTs) use methods that clearly define treatment effects of interest and consider the role of concurrent treatments. This study aims to determine how frequently concurrent analgesic use is reported in interventional pain RCTs and how accounting for analgesic use can affect pain intensity outcomes.

Design

Meta-epidemiologic study.

Methods

We conducted a study of concurrent analgesic use among RCTs from a recent systematic review of non-surgical interventional pain treatments (n= 37). We calculated the prevalence of different methods used to report concurrent analgesic use. We performed meta-analyses to compare treatment effects on pain intensity with vs. without accounting for concurrent analgesic use via a novel quantitative composite outcome, the “QPAC1.5.”

Results

About half of interventional pain RCTs reported concurrent analgesic use, but only one RCT directly accounted for concurrent analgesic use in their pain intensity outcome. Analyses accounting for concurrent analgesic use using the QPAC1.5substantially increased the estimated treatment effect of interventions on pain intensity by an average of −0.45 numeric rating scale points (95% CI −0.76 to −0.14; p<0.001), as compared to analyses that did not adjust for analgesic use.

Conclusion

Concurrent analgesic use is sometimes reported in interventional pain RCTs, but rarely accounted for when examining treatment effects on pain intensity. Accounting for concurrent analgesic use changes the treatment effect of interest to remove differential analgesic rates and has the potential to significantly affect estimates of effect sizes on pain treatments.
Polygenic risk scores for precision psychiatry: a study on the effect heterogeneity of antidepressants
Authors: Goto Ryunosuke , Naito Tatsuhiko , Skokauskas Norbert , Inoue Kosuke
Published: November 2024

Depression continues to be a major contributor to the global burden of diseases. Antide-pressants are recommended as the initial choice of treatment for moderate and severe depression among adults, but the choice of antidepressant class can be challenging, as efficacies of commonly used antidepressants are generally comparable between classes. As such, to determine which medication to prescribe to each patient, clinicians often rely on the adverse effect profile of antidepressants. One of the most discussed adverse effects is the possibility of increased suicidality with antidepressant initiation, a rare but serious adverse event. Efforts to predict this have mostly relied on clinical and sociodemographic characteristics of patients, but we do not yet have a clear picture. A promising avenue is to use patients’ genetic data, but the evidence on its utility has so far been mixed, and few large scale databases have both clinical and genetic data that can evaluate its utility. Here, using genetic and clinical data on more than 7,000 patients, both children and adults, with major depressive disorder from the All of Us Research Program, we show that the genetic predisposition for psychiatric disorders may underlie the substantial heterogeneity in the risk of suicidal thoughts with antidepressant use. Specifically, using a target trial emulation framework, we show that patients with higher polygenic risk scores for psychiatric disorders, particularly for attention deficit-hyperactivity disorder, are more likely than those with lower scores to experience suicidal thoughts with the use of selective serotonin reuptake inhibitors, relative to bupropion. In the personalized medicine framework, PRSs for various psychiatric disorders may help tailor antidepressants to each patient to avoid serious adverse effects such as suicidal thoughts.
Transcriptome analysis ofatad3-null zebrafish embryos elucidates possible disease mechanisms
Authors: Ezer Shlomit , Ronin Nathan , Yanovsky-Dagan Shira , Rotem-Bamberger Shahar , Halstuk Orli , Wexler Yair , Ben-Moshe Zohar , Plaschkes Inbar , Benyamini Hadar , Saada Ann , Inbal Adi , Harel Tamar
Published: November 2024

ATAD3A, a nuclear gene encoding the ATAD3A protein, has diverse roles in mitochondrial processes, encompassing mitochondrial dynamics, mitochondrial DNA maintenance, metabolic pathways and inter-organellar interactions. Pathogenic variants in this gene cause neurological diseases in humans with recognizable genotype-phenotype correlations. To further investigate the gene function and its implication in health and disease, we utilized CRISPR/Cas9 genome editing to generate a knockout (KO) model of the zebrafish ortholog gene,atad3. Analysis ofatad3-null zebrafish embryos revealed microcephaly, small eyes, pericardial edema and musculature thinning, closely mirroring with the human rare disease phenotype. Larvae exhibited delayed hatching and embryonic lethality by 13 days post-fertilization (dpf). Locomotor activity, ATP content, mitochondrial content, and mitochondrial activity were all reduced in the mutant embryos. Transcriptome analysis at 3 dpf via RNA-sequencing indicated decline in most mitochondrial pathways, accompanied by a global upregulation of cytosolic tRNA synthetases, presumably secondary to mitochondrial stress and possibly endoplasmic reticulum (ER)-stress. Differential expression of select genes was corroborated in fibroblasts from an affected individual. Theatad3-null zebrafish model emerges as a reliable representation of humanATAD3A-associated disorders, with similarities in differentially expressed pathways and processes. Furthermore, our study underscores mitochondrial dysfunction as the primary underlying pathogenic mechanism inATAD3A-associated disorders and identifies potential readouts for therapeutic studies.
A Bidirectional Brain-Fat Body Axis for Pathogen Avoidance
Authors: Wang Yujie , Saito Kokoro , Tanimoto Hiromu , Grunwald Kadow Ilona C.
Published: November 2024

Ingesting pathogens through spoiled food can cause serious harm, including infections, tissue damage, and even death. To prevent these outcomes, many animals have evolved behaviors to avoid consuming harmful pathogens. While pathogen avoidance behavior is conserved across species, the mechanisms linking immune responses of the body with neuron-controlled behavior remain unclear. Building on our previous findings, we here present a new bidirectional body-brain communication between the fat body and the nervous system that drives immune receptor-induced avoidance behavior. We show that immune receptor signaling and a specific antimicrobial peptide (AMP) are essential in both octopaminergic neuromodulatory neurons and the fat body for rapidly reducing pathogen intake after initial ingestion. Mechanistically, the octopaminergic neurons innervate the fly’s fat body where they trigger a calcium response through a specific octopamine receptor. This octopaminergic signal prompts the fat body to release dopamine. In turn, Dop1R1 signaling in output neurons of the mushroom body, the insect higher brain center, drives pathogen avoidance. Together, our data suggest that ingested pathogens are detected by immune receptors in neurons, which, through synaptic connections, trigger the release of dopamine and AMPs from fat cells. While AMPs combat the pathogens, dopamine reduces further ingestion by inducing behavioral changes. This mechanism demonstrates efficient communication between the body and brain, coordinating survival behaviors through systemic dopamine signaling from the fat body to the brain.
Theperiodgene alters daily and seasonal timing inOstrinia nubilalis
Authors: Dayton Jacob N. , Dopman Erik B.
Published: November 2024

The timing of insects’ daily (feeding, movement) and seasonal (diapause, migration) rhythms affects their population dynamics and distribution. Yet, despite their implications for insect conservation and pest management, the genetic mechanisms underlying variation in timing are poorly understood. Prior research in the European corn borer moth (Ostrinia nubilalis) associated ecotype differences in seasonal diapause and daily activity with genetic variation at the circadian clock geneperiod(per). Here, we demonstrate that populations with divergent allele frequencies atperexhibit differences in daily behavior, seasonal development, and the expression of circadian clock genes. Specifically, later daily activity and shortened diapause were associated with a reduction and delay in the abundance of cyclingpermRNA. CRISPR/Cas9-mediated mutagenesis revealed thatperand/or an intact circadian clock network were essential for the appropriate timing of daily behavior and seasonal responsiveness. Furthermore, a reduction ofpergene dosage inperheterozygous mutants (per-/+) pleiotropically decreased the diapause incidence, shortened post-diapause development, and delayed the timing of daily behavior, in a manner phenotypically reminiscent of wild-type individuals. Altogether, this combination of observational and experimental research strongly suggests thatperis a master regulator of biological rhythms and may contribute to the observed life cycle differences between bivoltine (two generation) and univoltine (one generation)O. nubilalis.

Highlights

Natural ecotypes with divergentperiod(per) genotypes differ in their daily and seasonal responses to photoperiod

Later daily activity, reduced diapause incidence, and shorter post-diapause development is associated with reducedpermRNA abundance

peris essential for short-day recognition and daily timing

Reducedpergene dosage shortened post-diapause development and delayed locomotor activity
Strip cropping designed for maintaining productivity increases ground beetle biodiversity
Authors: Croijmans Luuk , Cuperus Fogelina , van Apeldoorn Dirk F. , Bianchi Felix J.J.A. , Rossing Walter A.H. , Poelman Erik H.
Published: November 2024

Global biodiversity is declining at an unprecedented rate, with agriculture as a major driver. There is mounting evidence that intercropping can increase insect biodiversity while maintaining or increasing yield. Yet, intercropping is often considered impractical for mechanized farming systems. Strip cropping is pioneered by Dutch farmers as it is compatible with standard farm machinery. Here, we use ground beetle data from four experimental locations across four years of measurements because these are good agrobiodiversity indicators and hold keystone positions in agroecosystem foodwebs. We show that strip cropping systems that are designed for retaining productivity can also enhance ground beetle biodiversity, without incurring major yield loss. Strip cropped fields had on average 15% more ground beetle species and 30% more individuals than monocultural fields. The increase in field-level beetle species richness in organic agriculture through strip cropping approached increases found for other readily deployed biodiversity conservation methods, like shifting from conventional to organic agriculture (+19% - +23%). This makes strip cropping a useful tool for bending the curve of biodiversity loss without compromising food production.
Reciprocal regulation of autophagy and exosome pathway is mediated by GABARAPL2 and Alix to facilitate cellular homeostasis
Authors: Soni Naveen , Chaudhary Megha , Bissa Bhawana
Published: November 2024

The continuous reliance of cancer cells to acquire energy and communicate their nutrient needs makes them resilient and vulnerable. It provides an opportunity to stifle cancer cells by restricting their energy generation and communication ability. Autophagy and exosome biogenesis are two such pathways that are essential in maintaining the robust growth and survival of cancer cells. In this study we observed that inhibition of one pathway altered the expression of genes in other pathway. Exosome biogenesis, when blocked, led to an increase in breast cancer cell proliferation, while inhibition of autophagy did not significantly affect cancer cell proliferation. Therefore, the two pathways, when independently inhibited, did not present any significant effect on restricting cancer cell growth. However, we observed a substantial reduction in cancer cell proliferation upon combined inhibition of two pathways. To evaluate the reciprocal regulation of two pathways, we blocked the autophagy pathway and observed increase in the secretion of exosomes from MDA-MB-231 cells, along with decreased expression of Alix and CD63. On contrary, inhibition of exosome biogenesis led to an increase in the expression of ATG5 and ATG16L1, which caused a significant decrease in expression of GABARAPL2. Interestingly, the knockdown of GABARAPL2 abrogated the decrease in Alix expression upon autophagy inhibition, thus highlighting the essential role of GABARAPL2 in Alix secretion. Thus, our study highlights for the first time the synergistic effects of autophagy and exosome pathway inhibition in restricting cancer cell growth as well as the involvement of GABARAPL2 in the regulation of exosome secretion via modulating Alix expression.
Mild focal cooling selectively impacts computations in dendritic trees
Authors: Matin Meisam Habibi , Xiao Shulan , Jayant Krishna
Published: November 2024

Focal cooling is a powerful technique to temporally scale neural dynamics. However, the underlying cellular mechanisms causing this scaling remain unresolved. Here, using targeted focal cooling (with a spatial resolution of 100 micrometers), dual somato-dendritic patch clamp recordings, two-photon calcium imaging, transmitter uncaging, and modeling we reveal that a 5°C drop can enhance synaptic transmission, plasticity, and input-output transformations in the distal apical tuft, but not in the basal dendrites of intrinsically bursting L5 pyramidal neurons. This enhancement depends on N-methyl-D-aspartate (NMDA) and Kv4.2, suggesting electrical structure modulation. Paradoxically, and despite the increase in tuft excitability, we observe a reduced rate of recovery from inactivation for apical Na+ channels, thereby regulating back-propagating action potential invasion, coincidence detection, and overall burst probability, resulting in an “apparent” slowing of somatic spike output. Our findings reveal a differential temperature sensitivity along the basal-tuft axis of L5 neurons analog modulates cortical output.
Quantifying the intricacies of biological pattern formation: A new perspective through complexity measures
Authors: Riedel Jurgen , Barnes Chris P.
Published: November 2024

In this study we examine the emergence of complex biological patterns through the lens of reaction-diffusion systems. We introduce two novel complexity metrics — Diversity of Number of States (DNOS) and Diversity of Pattern Complexity (DPC)— which aim to quantify structural intricacies in pattern formation, enhancing traditional linear stability analysis methods. We demonstrate this approach to different systems including the linear Turing, Gray-Scott and FitzHugh-Nagumo models. These measures reveal insights into nonlinear dynamics, multistability, and the conditions under which complex biological patterns stabilize. We then apply the approach to gene regulatory networks, including models of the toggle switch in developmental biology, demonstrating how diffusion and self-activation contribute to robust spatial patterning. Additionally, simulations of the Notch-Delta-EGF signaling pathway in Drosophila neurogenesis highlight the role of gene regulation and parameter variations in modulating pattern complexity and state diversity. Overall, this work establishes complexity-based approaches as valuable tools for exploring the conditions that drive diverse and stable biological pattern formation, offering a pathway for future applications in synthetic biology and tissue engineering.
Tachykinin1-expressing neurons in the parasubthalamic nucleus control active avoidance learning
Authors: Hu Ruining , Wu Nannan , Liu Tong , Zou Liuting , Lv Songjie , Huang Xiao , Hu Rongfeng K.
Published: November 2024

Active avoidance is a type of instrumental behavior that requires an organism actively to engage in specific actions to avoid or escape from a potentially aversive stimulus and is crucial for the survival and well-being of organisms. It requires a widely distributed, hard-wired neural circuits spanning multiple brain regions, including the amygdala and thalamus. However, less is known about whether and how the hypothalamus encodes and controls active avoidance learning. Here we identify a previously unknown role for the parasubthalamic nucleus (PSTN), located in the lateral subdivision of the posterior hypothalamus, in the encoding and control of active avoidance learning. Fiber photometry calcium imaging shows that the activity of tachykinin1-expressing PSTN (PSTNTac1) neurons progressively increases during this learning. Cell-type specific ablation and optogenetic inhibition of PSTNTac1neurons attenuates active avoidance learning, whereas optogenetic activation of these cells promotes this learning via a negative motivational drive. Moreover, the PSTN mediates this learning differentially through its downstream targets. Together, this study identifies the PSTN as a new member of the neural networks involved in active avoidance learning and offers us potential implications for therapeutic interventions targeting anxiety disorders and other conditions involving maladaptive avoidance learning.