bluuebunny/crossref_metadata_2025 huggingface dataset:
Tissue-based Gene Expression Diagnosis of Mild and Moderate T-cell-mediated Rejection to Guide Therapy in Kidney Transplants
Authors: Kumar Dhiren , Raju Nihar , Tanriover Bekir , Azzouz Louiza , Moinuddin Irfan , Philogene Mary , Kamal Layla , McDougan Felecia , Massey Hugh Davis , Muthusamy Selvaraj , Lee Inkoo , Halloran Philip , Gupta Gaurav
Published: December 2024

Background.

Mild histologic lesions of tubulo-interstitial inflammation could represent a “response-to-wounding” rather than allorecognition. Tissue gene expression may complement histopathology for T-cell-mediated rejection (TCMR) diagnostics.

Methods.

We report on the incorporation of tissue gene expression testing using a Molecular Microscope Diagnostic System into the management of kidney transplant biopsies with suspected TCMR. Patients (N = 209) were divided into 3 groups based upon diagnosis and TCMR therapy (with high-dose steroids and/or anti-thymocyte globulin): Group 1: Untreated histologic TCMR with molecular quiescence (H+M–); Group 2: Treated histologic and molecular TCMR (H+M+); and Group 3: Controls, with no histologic or molecular (H–M–) rejection.

Results.

At biopsy, estimated glomerular filtration rate was worse (P = 0.006) in H+M+ (N = 35; 33 ± 22 mL/min/1.73 m2) and H+M– (N = 30; 40 ± 18 mL/min/1.73 m2) groups; compared with H–M– (N = 144; 47 ± 24 mL/min/1.73 m2) group. In H+M– biopsies, mean molecular acute kidney injury scores (0.33 versus 0.10; P = 0.03) were higher than in H–M–; while molecular TCMR was lower compared with H+M+ (0.04 versus 0.54; P < 0.001). At 12 m postbiopsy estimated glomerular filtration rate remained low (P < 0.001) in H+M+ (38 ± 22 mL/min/1.73 m2) but improved in untreated H+M– (44 ± 22 mL/min/1.73 m2) and H–M– (50 ± 23 mL/min/1.73 m2) groups. At a mean follow-up of 2.1 ± 1.2 y post-index biopsy, death-censored graft survival was lower in H+M+ (74%) than in H+M– (90%) and H–M– (92%; P = 0.001). H+M+ cases had numerically higher rejection on follow-up biopsy (20%) than H+M– (7%) (P = 0.12) and de novo donor-specific antibody formation (H+M+ 24%; H+M– 10%; P = 0.13).

Conclusions.

In this large single-center study, biopsies with untreated histological TCMR and molecular quiescence had comparable clinical outcomes to cases with no rejection, whereas those with histologic and tissue gene expression confirmed TCMR had inferior outcomes.
Divergent effects of cytomegalovirus and rheumatoid arthritis on senescent CD4+T cells
Authors: Williams Lea , Saber Ali O. , Xu Ruozhang , Jung Hannah , Awad Silina , Shahane Anupama , Baker Joshua F. , Su Laura F.
Published: December 2024

CD4+T cell senescence has been linked to repeated antigen stimulation. However, how different types of chronic antigenic exposures impact T cell differentiation and function remains incompletely understood. Using rheumatoid arthritis (RA) and cytomegalovirus (CMV) as models for persistent stimulation in autoimmunity and chronic viral infection, we performed high-dimensional mass cytometry analyses to examine their effects on CD4+T cell differentiation. We found that CMV seropositive adults have a significant population of highly differentiated CD27-CD28-CD4+T cells that exhibited common features of senescence, including CD57 and cytotoxic granule expression. In contrast, CD27-CD28-CD4+T cells were rare in RA patients and Epstein-Barr virus (EBV) or Herpes simplex virus (HSV) seropositive individuals. The few that were present exhibited a predominantly non-cytotoxic profile, with higher expression of TCF1, CD127, and Ki67. Among CMV seropositive individuals, RA was associated with reduced degranulation of cytotoxic granules and lower cytokine production by senescent CD4+T cells. We did not find an association with age, sex, clinical characteristics, or medication usage by univariate linear regression analyses. However,in vitrotofacitinib treatment reduced T cell functional activity, suggesting contributions from both the disease and RA treatment. These data uncovered distinct influences from CMV and RA, and their combined impact on senescent CD4+T cell differentiation and function.
Harnessing Environmental DNA (eDNA) to Explore Frugivorous Interactions: A Case Study in Papaya (Carica papaya) and Pineapple (Ananas comosus)
Authors: Banerjee Pritam , Maity Jyoti Prakash , Chatterjee Nalonda , Weber Sven , Dey Gobinda , Sharma Raju Kumar , Chen Chien-Yen
Published: December 2024

Plant-animal interactions (PAIs) are critical in ecosystem function, mediating energy flow and species interactions. Traditional methods of tracking PAIs, such as morphological identification and camera trapping, are limited in speed and scalability, posing challenges for comprehensive biodiversity monitoring. Recently, environmental DNA (eDNA) metabarcoding has emerged as a promising technique for detecting species interactions non-destructively. This pilot study explores the application of eDNA metabarcoding to investigate interactions involving partially consumed and intact fruits ofCarica papayaandAnanas comosus. eDNA metabarcoding were performed from of 36 partially consumed and 6 intact fruit samples. Metabarcoding of mitochondrial COI gene fragments revealed a diverse range of taxa, with Arthropoda, particularly insects, being the most abundant. Results indicated significant differences in taxonomic composition between pineapple and papaya samples, where both the fruit hold some unique as well as shared taxa. Furthermore, the diversity also differed between consumed and intact fruits, suggesting that partially consumed fruits serve as rich eDNA sources, capturing interactions with various frugivores and decomposers. Signal from various organisms detected through eDNA metabarcoding from consumed and damaged fruits allowed us to capture a wide array of taxa, revealing insights into species composition and ecological relationships. The unique ASVs associated with each fruit type suggest that certain taxa may showing preferences based on fruit characteristics such as sugar content, texture, or chemical profile. Present work highlighted the importance of eDNA based methods in unraveling the taxonomic composition of fruit-associated plant-animal interactions. This method needs limited taxonomic expertise, less labors, fast and effective, which can be implemented in monitoring ecological and economical species interactions.
Extrachromosomal DNA-mediated glutamine synthetase 2 (GS2) amplification enables glufosinate resistance inAmaranthus palmeri
Authors: Noguera Matheus M , Albert Patrice S , Saski Christopher A , Birchler James A , Porri Aimone , Meiners Ingo , Lerchl Jens , Roma-Burgos Nilda
Published: December 2024

Background

Palmer amaranth achieves resistance to glufosinate by overproducing the chloroplastic glutamine synthetase (GS2) protein, a result of the amplification and overexpression of its nuclear coding gene. This study examined how amplifiedGS2copies are inherited, identified their physical location in the cell, and investigated the mechanism ofGS2amplification.

Results

Segregation analysis revealed that inheritance of amplifiedGS2copies deviates from classical Mendelian patterns, with poor correlation between plant level resistance andGS2amplification. Fluorescencein situhybridization revealed chromosomal insertions ofGS2and potential extrachromosomal circular DNA (eccDNA), and variability inGS2amplification both among individual plants and within cells (not all cells in plants with highGS2copy number showed GS2 amplification). The unpredictable inheritance patterns and distribution ofGS2copies across multiple chromosomes suggest a role for eccDNA inGS2amplification. This was confirmed through eccDNA sequencing, which also identified multiple isoforms ofGS2.

Conclusion

This is the second documented case of herbicide resistance conferred by eccDNA-mediated target-site gene amplification in Palmer amaranth.
Natural monoclonal autoantibodies against HERV-K102 Envelope-TM from SLE patients selectively eliminate autoreactive immune cells and cancer cells
Authors: Gong Qinyuan , Li Mengyuan , Zheng Shuwen , Wu Zhaoxing , Wang Ping , Zhang Xuzhao , Liang Yun , Qian Wenbin , Xu Rongzhen
Published: December 2024

In sharp contrast to immune dysfunction in cancer, autoimmune diseases such as systemic lupus erythematosus (SLE) exhibit excessive immune reactions characterized by high titers of autoantibodies to HERV-K102-envelope (HERV-K102-Env) neoantigens, which are frequently found in cancer patients but seldom elicit a strong immune response. Here we aim to address whether anti-HERV-K102-Env autoantibodies in SLE can effectively eliminate autoreactive immune cells and cancer cells expressing HERV-K102-Env neoantigens. We established world-first fully human autoantibody phage display library with 3.67x108cfu using peripheral blood mononuclear cells (PBMCs) from SLE patients. Through high-throughput screening, we identified nineteen monoclonal autoantibodies (mAbs) targeting the conserved HERV-K102 Env-TM subunit. The EC50 values of these autoantibodies binding to the HERV-K102 Env-TM subunit ranged from 0.002436 μg/ml to 1.798 μg/ml. Remarkably, eleven of these mAbs not only recognized the HERV-K102 Env-TM glycoprotein on the cell surface but also effectively eliminated autoreactive B, T, and natural killer (NK) cells in SLE, as well as cancer cells. Our findings provide a conceptually new immunotherapy target HERV-K102 Env-TM subunit and open the era of using natural human autoantibodies to treat autoimmune disease and cancers.

Several of these monoclonal autoantibodies show promise as potential diagnostic and therapeutic agents, paving the way for innovative approaches to treating SLE and various malignancies.
Enabling Hydrogel Coating on Silicone Breast Implants with Poly(Vinyl Acetate) Primer Layer
Authors: Stanger Katrin , Bajrami Dardan , Wahl Peter , Moriarty Fintan , Gautier Emanuel , Dommann Alex , Wei Kongchang
Published: December 2024

Implant-associated infection is a major cause for breast implant re-operation. A practical method to reduce this risk is yet to be established. Hydrogel coating represents one promising approach. However, the adhesion of the hydrogel layer onto the silicone implant surface presents a significant challenge due to the intrinsic hydrophobicity of silicone surfaces. In this study, we described a surface-priming strategy involving poly(vinyl acetate) (PVAc) polymers to facilitate hydrogel adhesion to silicone implant surfaces. Miniature silicone implants with identical surface properties to clinical implants were custom-made for this study. We demonstrated that a PVAc primer layer can easily be deposited on the implant surface via a dip-coating procedure. The wettability of the implant surface was increased by this primer layer, as confirmed by contact angle measurements. The improved wettability allowed the application of a model hydrogel precursor solution (alginate) on the primed implant surface. The effectiveness of such a priming strategy in facilitating hydrogel coating was validated by testing two commercially available hydrogels on the silicone implant surface. Specifically, DAC (Defensive Antibacterial Coating) and Coseal hydrogels, representing paintable and sprayable hydrogels respectively, were successfully coated on the primed surface, as confirmed by ATR-FTIR analysis. Our surface priming strategy, which avoids surface treatments like chemical reactions and plasma irradiation that are impractical for clinical use, opens up new opportunities for exploring intraoperative hydrogel applications on silicone implants.
AMPK acts to remove immune barriers to CD8+T cell-mediated immunity against hepatocellular carcinoma
Authors: Hu Hui-Hui , Wang Xuefeng , Lan Bin , Cheng Haili , Wen Hong , Chen Fangfang , Wu Jianfeng , Li Mengqi , Chen Jiazhou , Chen Dongxu , Lin Shiyu , Yang Mingyang , Wu Zhenhua , Zheng Zhong-Zheng , Chen Fuqing , Zhou Jianyin , Chen Gang , Chen Yu , Deng Xianming , Zhang Chen-Song , Liu Jingfeng , Lin Sheng-Cai
Published: December 2024

Dysregulated metabolism in tumor tissues, and para-tumor tissues alike, can lead to immunosuppression, which may underlie cancer development. However, metabolic intervention as a therapeutic strategy has been of no avail. In this study, we explored the anti-cancer therapeutic effect of aldometanib that specifically targets lysosome-associated aldolase to mimic glucose starvation and thereby activates the lysosomal AMP-activated protein kinase (AMPK), a master regulator of metabolic homeostasis. We show that aldometanib inhibits the growth of HCC in an AMPK-dependent manner, allowing hepatoma-bearing mice to survive to mature ages, although aldometanib does not possess cytotoxicity towards HCC or normal cells. Intriguingly, aldometanib exerts anti-cancer effects only in immune-competent host mice, but not in immune-defective mice. We have further found that the HCC tissues in aldometanib-treated mice are massively infiltrated with CD8+T cells, which is not seen in mice with liver-specific knockout ofAMPKα. Our findings thus suggest that the metabolic regulator AMPK rebalances the tumor microenvironment to allow the cytotoxic immune cells inside the body to eliminate cancer cells and effectively contain the tumor tissues. The finding that metabolic intervention can make cancer a life-long manageable disease, may potentially usher in a new era of cancer therapy.
Blood-borne immune cells carry low biomass DNA remnants of microbes in patients with colorectal cancer or inflammatory bowel disease
Authors: Morsy Y. , Walberg Å. , Wawrzyniak P. , Hubeli B. , Truscello L. , Mamie C. , Niechcial A. , Gueguen E. , Manzini R. , Gottier C. , Lang S. , Scharl S. , Blümel S. , Biedermann L. , Rogler G. , Turina M. , Ramser M. , Petrowsky H. , Arnold I. C. , Zeissig S. , Zamboni N. , Egli A. , Niess J. H. , Hruz P. , Knuth A. , Fritsch R. , Manz M. G. , Wawrzyniak M. , Scharl M.
Published: December 2024

The involvement of the human intestinal microbiome in the regulation of immune cell homeostasis, as well as in the pathogenesis of inflammatory bowel disease (IBD) and colorectal cancer (CRC), are well-established1–4. Bacteria interact with immune cells at the sites of intestinal inflammation, but also in the CRC tumor microenvironment1–6. Indeed, bacterial remnants have recently been detected in human intestinal tissue in patients with IBD, at primary tumor sites and in the metastases of patients with CRC, and in whole blood3,7,8. A defective intestinal epithelial barrier is thought to promote bacterial remnant translocation and disease progression6. However, it is unknown, how bacterial remnants translocate from the intestine to sites of metastasis or into the circulation. We hypothesized that bacterial remnants translocate within peripheral blood immune cells into the circulation. Here, we thus explored the composition of the detectable microbiome in peripheral blood mononuclear cells (PBMCs) of patients with CRC or IBD compared to healthy controls. The PBMC microbiome profiles partially align with the tumor- and metastasis-derived or intestinal tissue-derived microbiome signatures obtained from the same patients with CRC or IBD, respectively. Our metagenomics data, supported by 16S-rRNA-FISH-Flow, imaging flow cytometry and species-specific qPCR, reveal the presence of translocated bacterial genetic sequences in the patients with CRC and IBD, likely due to an intestinal barrier defect. Pathway and serum metabolomics analysis connected to the metabolic potential of the PBMC-derived microbiome sequences support the onset of microbial translocation in such patients. Thus, our data suggest that in patients with intestinal barrier leakage, such as those with CRC or IBD, there is the potential for the translocation of bacterial remnants into the circulation via peripheral immune cells.
Investigating BPDE-induced embryonic toxicity employing hiPSC-based models
Authors: Meira de Amorim Vanessa Cristina , Szepanowski Leon , Lofrano Alessia , Loerch Christiane , Wruck Wasco , Graffmann Nina , Adjaye James
Published: December 2024

Benzo[a]pyrene diol epoxide (BPDE) is a metabolite of the environmental contaminant Benzo[a]pyrene- a byproduct of incomplete combustion of organic matter. BPDE reacts with DNA to form BPDE-DNA bulky adducts which if not removed can lead to mutations due to DNA base-pair substitutions. While the effects of BPDE on somatic cells are fairly well described, its effects on early human development are currently unknown. In this study, we investigated for the first time the effect of BPDE on human induced pluripotent stem cells (hiPSCs) and their differentiated neuroprogenitor cells (NPCs) as a model for early embryonic development. Furthermore, we compared hiPSCs and NPCs derived from cells of patients suffering from Nijmegen Breakage Syndrome (NBS), which is a chromosomal instability disorder characterized by defective DNA repair and increased risk of malignancies. Transcriptome analysis, coupled with protein content analysis employing immunostaining and Western blots, revealed that hiPSCs are more sensitive to BPDE exposure when compared to NPCs with an enhanced expression of several genes associated with p53-mediated DNA damage response, including DNA repair by lesion bypass, cell cycle checkpoints and extrinsic apoptosis. We also identified that cells from NBS patients showed less apoptotic response and a distinct p53 response than their healthy counterparts. This iPSC-based study enhances our meagre knowledge of the effects of BPDE on early human development in both healthy individuals and NBS patients. Furthermore, our model conforms with the 3Rs principle.
Simulation-based inference for close-kin mark-recapture: implications for small populations and nonrandom mating
Authors: Conn Paul B.
Published: December 2024

Close-kin mark-recapture (CKMR) uses data on the frequency of kin pair relationships (e.g. parent-offspring, half siblings) in genetic samples from animal populations to estimate parameters such as abundance and adult survival probability. To date, most applications of CKMR have relied on a pseudo-likelihood approximation where pairwise comparisons of relatedness are assumed to be independent. This approximation works well when abundance is high and the sampled fraction of the population is low (as with many marine fisheries), but resultant estimators have inflated nominal confidence interval coverage when applied to small populations. Small populations and nonrandom mating structures also lead to problems with using second-order kin for estimation because one cannot typically differentiate half-siblings from other kin pair types like aunt-niece. In this paper, I assess the utility of approximate Bayesian computation (ABC) as a way of relaxing the pseudo-likelihood independence assumption. Under this approach, one only needs the ability to simulate population and sampling dynamics and to summarize resulting statistics in an informative way (e.g., number of kin pairs of different types). After exploring bias and interval coverage in several simulation studies, I illustrate these procedures on CKMR data from a Canadian caribou population. I show that ABC substantially improves interval coverage, and allows inference for difficult biologies where it would be difficult to calculate the analytical probabilities necessary for a binomial pseudo-likelihood. Simulation-based approaches to inference have great potential for expanding the application of CKMR to small populations and for breeding dynamics that are difficult to model.
Astrocytic Signatures in Neuronal Activity: A Machine Learning-Based Identification Approach
Authors: Pirola João Pedro , DeForest Paige , Protachevicz Paulo R , Fontenas Laura , Ferreira Ricardo F , Pena Rodrigo FO
Published: December 2024

This study investigates the expanding role of astrocytes, the predominant glial cells, in brain function, focusing on whether and how their presence influences neuronal network activity. We focus on particular network activities identified as synchronous and asynchronous. Using computational modeling to generate synthetic data, we examine these network states and find that astrocytes significantly affect synaptic communication, mainly in synchronous states. We use different methods of extracting data from a network and compare which is best for identifying glial cells, with mean firing rate emerging with higher accuracy. To reach the aforementioned conclusions, we applied various machine learning techniques, including Decision Trees, Random Forests, Bagging, Gradient Boosting, and Feedforward Neural Networks, the latter outperforming other models. Our findings reveal that glial cells play a crucial role in modulating synaptic activity, especially in synchronous networks, highlighting potential avenues for their detection with machine learning models through experimental accessible measures.
Classifying Domains, Benchmarking GPT-4, A Portuguese Dataset for Medical AI Q&A
Authors: Matsuoka Felipe Akio , Onaga Henrique Nunes
Published: December 2024

Artificial Intelligence (AI), particularly large language models (LLMs), has demonstrated remarkable capabilities in addressing complex tasks, including professional-level medical question answering. While standardized benchmarks like the USMLE have been widely used for evaluating LLM performance in English, there is a significant gap in evaluating these models in other languages, such as Portuguese. To address this, we present a curated dataset derived from the Teste de Progresso (TP), a widely adopted Brazilian progress test used to assess medical knowledge across six key domains: Basic Sciences, Internal Medicine, Surgery, Obstetrics and Gynecology, Public Health, and Pediatrics. The dataset consists of 720 multiple-choice questions spanning five years (2019–2023). We demonstrate two primary applications of this dataset. First, we benchmark the performance of GPT-4, which achieved an overall accuracy of 90% across the six medical domains, with the highest performance in Internal Medicine (10%) and the lowest in Public Health (80%). Second, we develop a classification model based on BERTimbau, achieving an overall accuracy of 94% in categorizing questions into their respective medical domains. Our results highlight the utility of the dataset for both benchmarking AI models and automating medical question classification. This work emphasizes the importance of creating domain-specific datasets in underrepresented languages, like Portuguese, to advance AI-driven medical applications, ensure equitable access to AI technologies, and address linguistic and cultural gaps in healthcare education.
Silent reservoirs are shaping disease emergence: the case of Usutu virus in the Netherlands
Authors: de Wit M.M. , Beaunée G. , Dellar M. , Münger E. , Krol L. , Atama N. , van Irsel J. , van der Jeugd H. , Koopmans M. , de Jong M.C.M. , Sikkema R. S. , ten Bosch Q.
Published: December 2024

Disentangling contributions of different hosts to disease emergence and spread is highly complex, but critical for improving predictions, surveillance, and response. This is particularly challenging in wildlife, with pathogens often infecting multiple species and data collection being difficult. Using the emergence of Usutu virus (USUV) in the Netherlands as a case study, we demonstrate the use of an Approximate Bayesian Computation framework on diverse data sources to uncover hidden drivers of spatio-temporal wildlife disease emergence. We calibrated single- and multi-host mechanistic transmission models to five types of wildlife surveillance and research data, describing molecular and serological evidence of USUV in wild birds. Although Eurasian blackbirds, the primary sentinel species, were the most severely affected species, our models indicated that USUV could not persist in blackbirds alone. Our data-model framework provided statistical support for additional bird species to have contributed to transmission. This population of bird species is characterised by limited infection mortality, a longer lifespan, and likely further dispersal than blackbirds. Immunity in this reservoir population appears to have protected blackbirds from further USUV-related population decline. Continued surveillance could help identify these reservoir species. Our results underscore the importance of considering multiple host populations to understand outbreak dynamics. Neglecting the multi-host context of disease transmission can impact the reliability of future predictions and the projected impact of intervention strategies.

Significance statement

Understanding which species contribute to disease transmission is critical for improving predictions, surveillance, and response. However, disentangling these contributions is difficult, especially for wildlife diseases where pathogens often infect multiple species and data collection is notoriously difficult. Using Usutu virus (USUV) in the Netherlands as an example, we show how a computational framework can integrate diverse wildlife data sources to uncover hidden contributors to transmission. Our findings show that blackbirds, the most severely affected species, cannot sustain USUV transmission alone. Additional bird species, characterised by lower infection mortality and longer lifespans, are important for transmission and may protect more vulnerable species. This work emphasizes that studying transmission in a multi-host context is crucial for accurate outbreak predictions and effective interventions.
A comprehensive benchmark for multiple highly efficient base editors with broad targeting scope
Authors: Wang Xiaofeng , Cheng Xiaolong , Li Zexu , Ma Shixin , Zhang Han , Chen Zhisong , Yao Yingjia , Li Zihan , Zhong Chunge , Li You , Zhang Yunhan , Menon Vipin , Chao Lumen , Li Wei , Fei Teng
Published: December 2024

As the toolbox of base editors (BEs) expands, selecting appropriate BE and guide RNA (gRNA) to achieve optimal editing efficiency and outcome for a given target becomes challenging. Here, we construct a set of 10 adenine and cytosine BEs with high activity and broad targeting scope, and comprehensively evaluate their editing profiles and properties head-to-head with 34,040 BE-gRNA-target combinations using genomically integrated long targets and tiling gRNA strategies. Interestingly, we observe widespread non-canonical protospacer adjacent motifs (PAMs) for these BEs. Using this large-scale benchmark data, we build a deep learning model, named BEEP (BaseEditingEfficiencyPredictor), for predicting the editing efficiency and outcome of these BEs. Guided by BEEP, we experimentally test and validate the installment of 3,558 disease-associated single nucleotide variants (SNVs) via BEs, including 20.1% of target sites that would be generally considered as “uneditable”, due to the lack of canonical PAMs. We further predict candidate BE-gRNA-target combinations for modeling 1,752,651 ClinVar SNVs. We also identify several cancer-associated SNVs that drive the resistance to BRAF inhibitors in melanoma. These efforts benchmark the performance and illuminate the capabilities of multiple highly useful BEs for interrogating functional SNVs. A practical webserver (http://beep.weililab.org/) is freely accessible to guide the selection of optimal BEs and gRNAs for a given target.
Sparse neural networks enable low-power, implantable neural interfaces
Authors: Costello Joseph T. , Temmar Hisham , Cubillos Luis , Mender Matthew J. , Wallace Dylan M. , Kelberman Madison , Benharush Omer , Simons Jeremy , Willsey Matthew S. , Kumar Nishant Ganesh , Kung Theodore A. , Patil Parag G. , Chestek Cynthia A.
Published: December 2024

Recent advances in brain-machine interfaces (BMIs) using neural network decoders and increased channel count have improved the restoration of speech and motor function, but at the cost of higher power consumption. For wireless, implantable BMIs to be clinically viable, power consumption must be limited to prevent thermal tissue damage and enable long use without frequent charging. Here, we show how neural network “pruning” creates sparse decoders that require fewer computations and active channels for reduced power consumption. Across multiple movement decoding tasks using brain and muscle signals, recurrent neural network decoders can be compressed by over 100x while maintaining strong performance, enabling decoding on the implant with <1% power increase compared to decoding externally. Pruning also allows for deactivating up to 89% of channels, reducing BMI power by up to 5x. Counterintuitively, our findings suggest that BMIs employing a subset of a larger number of channels may achieve lower power consumption than BMIs with fewer channels, for a given performance level. These results suggest a path toward power-efficient, implantable BMIs suitable for long-term clinical use.
Periaqueductal gray passes over disappointment and signals continuity of remaining reward expectancy
Authors: Lee Hyunchan , Hikosaka Okihide
Published: December 2024

Disappointment is a vital factor in the learning and adjustment of strategies in reward-seeking behaviors. It helps them conserve energy in environments where rewards are scarce, while also increasing their chances of maximizing rewards by prompting them to escape to environments where richer rewards are anticipated (e.g., migration). However, another key factor in obtaining the reward is the ability to monitor the remaining possibilities of obtaining the outcome and to tolerate the disappointment in order to continue with subsequent actions. The periaqueductal gray (PAG) has been reported as one of the key brain regions in regulating negative emotions and escape behaviors in animals. The present study suggests that the PAG could also play a critical role in inhibiting escape behaviors and facilitating ongoing motivated behaviors to overcome disappointing events. We found that PAG activity is tonically suppressed by reward expectancy as animals engage in a task to acquire a reward outcome. This tonic suppression of PAG activity was sustained during a series of sequential task procedures as long as the expectancy of reward outcomes persisted. Notably, the tonic suppression of PAG activity showed a significant correlation with the persistence of animals’ reward-seeking behavior while overcoming intermittent disappointing events. This finding highlights that the balance between distinct tonic signaling in the PAG, which signals remaining reward expectancy, and phasic signaling in the LHb, which signals disappointment, could play a crucial role in determining whether animals continue or discontinue reward-seeking behaviors when they encounter an unexpected negative event. This mechanism would be essential for animals to efficiently navigate complex environments with various reward volatilities and ultimately contributes to maximizing their reward acquisition.
Validation of the Baseline Recurrence Risk in Cellulitis (BRRISC) score and the added impact of acute clinical response
Authors: Cross Elizabeth LA , Hayward Gail N , Llewelyn Martin J , Walker A Sarah
Published: December 2024

Objectives

The BRRISC score predicts hospital-attended recurrence of cellulitis using baseline clinical data. In practice, clinicians assess treatment response when deciding antibiotic duration. We investigated whether markers of acute clinical response improved prognostic score performance within an external validation cohort.

Methods

We recruited adults with lower limb cellulitis attending hospital. Outcomes included ‘hospital-attended recurrence’ (primary outcome for validation) and ‘any recurrence’. We assessed clinical response from days 0-3 of treatment. Using multivariate logistic regression with backwards elimination, we identified response variables independently associated with either outcome for an extended score.

Results

Of 202 patients, 8% (n=17) experienced ‘hospital-attended recurrence’ and 23% (n=46) ‘any recurrence’. In this validation dataset, the BRRISC score had a C-index=0.75 (95%CI, 0.64-0.86) for predicting ‘hospital-attended recurrence’. There was weak evidence that an extended score, incorporating day-2/3 severity of skin blistering, improved the C-index to 0.83 (0.75-0.92). No acute clinical response variables were independently associated with ‘any recurrence’ after adjusting for BRRISC score.

Conclusion

Our measures of early clinical response did not add useful prognostic information to BRRISC score baseline risk. Further research should consider whether responses after day-3 add helpful information, whether risk stratification can personalise antibiotic duration, and explore non-antibiotic approaches to prevent recurrence.
25-Hydroxy Cholesterol Effectively Inhibits Japanese Encephalitis Virus infection in Vero Cells
Authors: Archana Km. , Bohra Babita , Tripathi Raj Kamal , Haldar Sourav
Published: December 2024

The Japanese encephalitis virus (JEV) is a mosquito-borne, enveloped flavivirus that causes acute encephalitis. Although JEV is increasingly recognized as a global threat, there is currently no FDA-approved treatment available for JEV. 25-hydroxycholesterol (25-HC) is an oxysterol produced through the oxidation of cholesterol, a process catalyzed by cholesterol 25-hydroxylase (CH25H), which is an interferon-stimulated gene that is upregulated during viral infections. In this study, we report for the first time that 25-HC effectively prevents JEV infection in cells. Our results show that 25-HC inhibits JEV infection in Vero cells with an IC50 of ∼ 3.7 μM, while displaying no cell toxicity (CC50 > 50 μM). Given the antiviral effects of 25HC against Zika and Dengue viruses, our findings suggest that 25-HC could be a promising candidate for the development of broad-spectrum anti-flaviviral therapeutics.
Structural and energetic analysis of stabilizing indel mutations
Authors: Gutierrez Yulia Maria , Rocklin Gabriel Jacob
Published: December 2024

Amino acid insertions and deletions (indels) are among the most common protein mutations and necessitate changes to a protein's backbone geometry. Examining how indels affect protein folding stability (and especially how indels can increase stability) can help reveal the role of backbone energetics on stability and introduce new protein engineering strategies. Tsuboyama et al. measured folding stability for 57,698 single amino acid insertion or deletion mutants in 405 small domains, and this analysis identified 103 stabilizing mutants (∆∆Gunfolding> 1 kcal/mol). Here, we use computational modeling to analyze structural and energetic changes for these stabilizing indel mutants. We find that stabilizing indel mutations tend to have local structural effects and that stabilizing deletions (but less so insertions) are often found in regions of high backbone strain. We also find that stabilizing indels are typically correctly classified as stabilizing by the Rosetta energy function (which explicitly models backbone energetics), but not by an inverse folding (ESM-IF)-based analysis (Cagiada et al. 2024) which predicts absolute stability (∆Gunfolding).
Scavenger receptor CD163 multimerises to allow uptake of diverse ligands
Authors: Zhou Richard X. , Higgins Matthew K.
Published: December 2024

Scavenger receptors mediate cellular uptake of diverse ligands. CD163 is an archetypal scavenger receptor with a primary role in haemoglobin detoxification. Haemoglobin released from lysed erythrocytes causes oxidative damage. This is countered by formation of haemoglobin-haptoglobin complexes and CD163-mediated uptake into macrophages for degradation. Different haptoglobin isoforms form stoichiometrically diverse haptoglobin-haemoglobin complexes which must all be recognised by CD163. We show that CD163 forms multimeric complexes, with calcium-mediated interactions forming a trimeric base. Arms emerge from this base, moulding around the ligand to form a single promiscuous ligand-binding site. The arms can also bind to arms of adjacent protomers, blocking the ligand-binding surfaces in an autoinhibited state. This results in a scavenger receptor that can recognise diverse haemoglobin-containing complexes, allowing physiologically important detoxification.
Spatio-temporal interaction of immune and renal cells determines glomerular crescent formation in autoimmune kidney disease
Authors: Sultana Zeba , Khatri Robin , Yousefi Behnam , Shaikh Nikhat , Jauch-Speer Saskia L. , Schaub Darius P. , Engesser Jonas , Hellmig Malte , Hube Arthur L. , Sivayoganathan Varshi , Borchers Alina , Peters Anett , Kaffke Anna , Paust Hans-Joachim , Goldbeck-Strieder Thiago , Wenzel Ulrich O. , Puelles Victor , Hoxha Elion , Wiech Thorsten , Huber Tobias B. , Panzer Ulf , Bonn Stefan , Krebs Christian F.
Published: December 2024

Rapidly progressive glomerulonephritis (RPGN) is the most aggressive group of autoimmune kidney disease with the worst prognosis. Anti-neutrophil cytoplasmic antibody (ANCA) associated vasculitis, anti-glomerular basement membrane (anti-GBM) and lupus nephritis are the most common causes of RPGN and are characterized by the formation of glomerular crescents and infiltration of leukocytes that eventually lead to glomerulosclerosis and kidney failure.

In this work, we used high-resolution spatial transcriptomics of 32 ANCA, 19 lupus nephritis, 6 anti-GBM, and 6 control patients to understand how intercellular signaling between immune and renal tissue cells leads to renal inflammation and glomerular injury. Using 3,218,210 immune and kidney cells, we observed that the biological pathways involved in the sequence of glomerular crescent formation are similar across the diseases. While innate immune cells infiltrated the glomerular compartment relatively early, later increases in adaptive immune cells were largely restricted to the periglomerular regions. These changes in immune cells temporally correlated with increases in glomerular parietal epithelial (PEC) and fibrotic mesangial cells, suggesting disease-relevant functional signaling between these immune and renal cells. Cell communication analysis revealed early disease PDGF signaling from epithelial and mesangial cells to PECs, causing their activation and proliferation. At later stages, TGF-β signaling from macrophages, T cells, epithelial cells, and mesangial cells to PECs triggered the expression of extracellular matrix components resulting in glomerulosclerosis.

Our results highlight a spatio-temporally conserved progression into glomerular crescents and sclerosis for ANCA, lupus nephritis, and anti-GBM disease, which is driven by consecutive PDGF and TGF-β signaling to PECs.
Evaluating the causal association between type 2 diabetes and Alzheimer's disease: a Two-Sample Mendelian Randomisation Study
Authors: Han Si , Lelieveldt Tom , Sturkenboom Miriam CJM , Biessels Geert Jan , Ahmadizar Fariba
Published: December 2024

Aims Type 2 diabetes mellitus (T2DM) and Alzheimer's disease (AD) are significant global health issues. Epidemiological studies suggest T2DM increases AD risk, though confounding factors and reverse causality complicate this association. This study aims to clarify the causal relationship between T2DM and AD through a systematic review and meta-analysis of Mendelian randomization (MR) studies and a new two-sample MR analysis. Materials and Methods A literature search across major databases was conducted through May 2024 to identify MR studies linking T2DM and AD. Fixed/random-effect models provided pooled odds ratios (OR) with 95% confidence intervals (CI), and heterogeneity was assessed with the I^2 statistic. For our MR analysis, we pooled genetic variants from selected studies and analyzed AD outcomes using IGAP, EADB, and UKB databases. Multiple MR methods, including inverse-variance weighted (IVW) and pleiotropy-robust approaches, were applied for validation. Results Of 271 articles, eight MR studies were included (sample sizes: 68,905 to 788,989), all from European ancestry. Our meta-analysis found no significant causal link between T2DM and AD (OR = 1.01, 95% CI: 0.99-1.03) with moderate heterogeneity (I^2 = 44.16%). Similarly, our MR analysis using 511 SNPs as instrumental variables showed no significant associations in IGAP, EADB, or UKB data, consistent across sensitivity analyses. Conclusions This meta-MR and MR analysis revealed no significant causal association between T2DM and AD, indicating that T2DM may not directly influence AD risk. Further research should explore other mechanisms linking these conditions.
BRAFV600and ErbB inhibitors directly activate GCN2 in an off-target manner to limit cancer cell proliferation
Authors: Ill C. Ryland , Marikar Nasreen C. , Nguyen Vu , Nangia Varuna , Darnell Alicia M. , Vander Heiden Matthew G. , Reigan Philip , Spencer Sabrina L.
Published: December 2024

Targeted kinase inhibitors are well known for their promiscuity and off-target effects. Herein, we define an off-target effect in which several clinical BRAFV600inhibitors, including the widely used dabrafenib and encorafenib, interact directly with GCN2 to activate the Integrated Stress Response and ATF4. Blocking this off-target effect by co-drugging with a GCN2 inhibitor in A375 melanoma cells causes enhancement rather than suppression of cancer cell outgrowth, suggesting that the off-target activation of GCN2 is detrimental to these cells. This result is mirrored in PC9 lung cancer cells treated with erlotinib, an EGFR inhibitor, that shares the same off-target activation of GCN2. Using anin silicokinase inhibitor screen, we identified dozens of FDA-approved drugs that appear to share this off-target activation of GCN2 and ATF4. Thus, GCN2 activation may modulate the therapeutic efficacy of some kinase inhibitors, depending on the cancer context.
EpiAgent: Foundation model for single-cell epigenomic data
Authors: Chen Xiaoyang , Li Keyi , Cui Xuejian , Wang Zian , Jiang Qun , Lin Jiacheng , Li Zhen , Gao Zijing , Jiang Rui
Published: December 2024

Large-scale foundation models have recently opened new avenues for artificial general intelligence. Such a research paradigm has recently shown considerable promise in the analysis of single-cell sequencing data, while to date, efforts have centered on transcriptome. In contrast to gene expression, chromatin accessibility provides more decisive insights into cell states, shaping the chromatin regulatory landscapes that control transcription in distinct cell types. Yet, challenges also persist due to the abundance of features, high data sparsity, and the quasi-binary nature of these data. Here, we introduce EpiAgent, the first foundation model for single-cell epigenomic data, pretrained on a large-scale Human-scATAC-Corpus comprising approximately 5 million cells and 35 billion tokens. EpiAgent encodes chromatin accessibility patterns of cells as concise “cell sentences,” and employs bidirectional attention to capture cellular heterogeneity behind regulatory networks. With comprehensive benchmarks, we demonstrate that EpiAgent excels in typical downstream tasks, including unsupervised feature extraction, supervised cell annotation, and data imputation. By incorporating external embeddings, EpiAgent facilitates the prediction of cellular responses to both out-of-sample stimulated and unseen genetic perturbations, as well as reference data integration and query data mapping. By simulating the knockout of keycis-regulatory elements, EpiAgent enables in-silico treatment for cancer analysis. We further extended zero-shot capabilities of EpiAgent, allowing direct cell type annotation on newly sequenced datasets without additional training.
Sex-specific mate choice and mate change based on MHC-IIB dissimilarity in a genetically monogamous seabird
Authors: Thel Lucie , Pineaux Maxime , Ribeiro Léa , Danchin Etienne , Hatch Scott A. , Blanchard Pierrick , Leclaire Sarah
Published: December 2024

Among species reproducing sexually, mating strategies represent a major component of individual fitness. The Major Histocompatibility Complex (MHC) is an extremely diverse set of genes responsible for immunological recognition and defense against pathogens. Although MHC-dissimilarity between mates has been proposed to drive mate choice through increased offspring pathogen resistance, evidence is mixed, and evidence for other MHC-based mating strategies remains rare. We investigated whether MHC-IIB dissimilarity is associated with mate choice and mate change in the genetically monogamous black-legged kittiwake (Rissa tridactyla). We found that first-time male breeders are paired with females more MHC-IIB dissimilar to them than expected by chance. After a successful reproduction, the more males are MHC-IIB dissimilar to their mate, the less likely they are to change mate. When males change their mate, they tend to be more MHC-IIB dissimilar to the new mate compared to the previous mate. However, males are not more MHC-IIB dissimilar to their new mate than expected by chance. We did not find evidence for an effect of MHC-IIB dissimilarity on mating strategies when considering the female’s perspective. Male mate choice should not be overlooked in species with bi-parental care in which the male performs a significant part of parental care.
Viro3D: a comprehensive database of virus protein structure predictions
Authors: Litvin Ulad , Lytras Spyros , Jack Alexander , Robertson David L , Grove Joe , Hughes Joseph
Published: December 2024

Viruses are intracellular parasites of organisms from all domains of life. They infect and cause disease in humans, animals and plants but also play crucial roles in the ecology of microbial communities. Tolerance to genetic change, high-mutation rates, adaptations to hosts and immune escape has driven high divergence of viral genes, hampering their functional annotation and phylogenetic inference. The protein structure is more conserved than sequence and can be used for searches of distant homologs and evolutionary analysis of divergent proteins. Structures of viral proteins are traditionally underrepresented in public databases, but recent advances in protein structure prediction allows us to address this issue. Combining two state-of-the-art approaches, AlphaFold2-ColabFold and ESMFold, we predicted models for 85,000 proteins from 4,400 human and animal viruses, expanding the structural coverage for viral proteins by 30 times compared to experimental structures. We also performed structural and network analyses of the models to demonstrate their utility for functional annotation and inference of distant phylogenetic relationships. Taking this approach, we examined the deep evolutionary history of viral class-I fusion glycoproteins, gaining insights on the origins of coronavirus spike protein. To enable further discoveries, we have createdViro3D(https://viro3d.cvr.gla.ac.uk/), a virus species-centred protein structure database. It allows users to search, browse and download protein models from a virus of interest and explore similar structures present in other virus species. This resource will facilitate fundamental molecular virology, investigation of virus evolution, and may enable structure-informed design of therapies and vaccines.