Antiviral Res. 2025 May 8:106172. doi: 10.1016/j.antiviral.2025.106172. Online ahead of print.

ABSTRACT

The burden of dengue on human health has dramatically increased in recent years, underscoring the urgent need for effective therapeutic interventions. Despite decades of research since the discovery of the dengue virus, no specific antiviral treatments are available and strategies to reliably prevent severe disease remain limited. Direct-acting antivirals against dengue are under active investigation but have shown limited efficacy to date. An underappreciated Achille's heal of the virus is its dependence on host factors for infection and pathogenesis, each of which presents a potential avenue for therapeutic intervention. We and others have demonstrated that dengue virus relies on multiple host kinases, some of which are already targeted by clinically approved inhibitors. These offer drug repurposing opportunities for host-directed dengue treatment. Here, we summarize findings on the role of kinases in dengue infection and disease and highlight potential kinase targets for the development of innovative host-directed therapeutics.

PMID:40348023 | DOI:10.1016/j.antiviral.2025.106172

Comput Biol Med. 2025 May 9;192(Pt B):110203. doi: 10.1016/j.compbiomed.2025.110203. Online ahead of print.

ABSTRACT

Pre-eclampsia (PE) is a severe vascular disorder during pregnancy, significantly affecting maternal and fetal health worldwide. However, the exact molecular mechanism of its pathophysiology remains unclear, highlighting the need for reliable early diagnostic methods. Our primary aim of this study was to identify key genes (KGs) that may affect the outcome of patients with PE via integrated bioinformatics analysis. We analysed a gene expression dataset from the national center for biotechnology information (NCBI) sequence read archive (SRA) database and performed standard preprocessing steps, including quality assessment, trimming, genome alignment, and feature counts. Following this, normalization and differentially expressed genes (DEGs) were performed using Deseq2, which identified 781 DEGs were identified comprising 457 upregulated and 324 downregulated genes. Identified DEGs were significantly enriched in the cytokine interaction pathway and cellular calcium ion homeostasis. PPI network analysis revealed eight KGs (CXCL8, GAPDH, MMP9, SPP1, PTGS2, LEP, FGF7, and FGF10). These KGs were further found to be regulated by ten transcription factors (TFs), among which NF-kB1 and RELA consistently interact with all the KGs, and four microRNAs (miRNAs) such as hsa-mir-335-5p, has-mir-16a-5p, has-let-7b-5p, and has-mir-204-5p. The least absolute shrinkage and selection operator (LASSO) regression with 10-fold cross-validation (CV) confirmed all eight KGs may act as potential biomarkers based on their coefficients. Among these, GAPDH, SPP1, FGF7, and FGF10 emerged as novel biomarkers. Additionally, receiver operating characteristic (ROC) curve analysis for these novel biomarkers showed an area under the curve (AUC) of 0.869, demonstrating strong discriminatory power between the healthy and EOPE groups. The drug-gene interaction was performed by DrugMap database revealed an important interaction of GAPDH and FGF7 with FDA-approved drugs, indicating their therapeutic significance in PE. This analysis also facilitates drug repurposing for PE treatment.

PMID:40347801 | DOI:10.1016/j.compbiomed.2025.110203

Orphanet J Rare Dis. 2025 May 10;20(1):222. doi: 10.1186/s13023-025-03751-y.

ABSTRACT

PURPOSE: Patients with rare diseases often undergo a long diagnostic odyssey. However, there is little empirical evidence on the cost incurred during the diagnostic pathway for patients with suspected rare diseases. This study provides a comprehensive analysis of healthcare costs and utilization during the diagnostic pathway for a heterogeneous sample of patients with suspected rare diseases but unclear diagnosis.

METHODS: Using claims data from five German statutory health insurance organizations for the years 2014-2019, we analyzed costs and healthcare utilization of 1,243 patients (aged 0 to 82 years) with suspected rare diseases referred to a rare disease center. A control cohort was assigned using 1:75 exact matching on age, sex and place of residence.

RESULTS: In the years prior to referral to an expert center, healthcare utilization of patients with suspected rare diseases was, on average, substantially and significantly higher compared to a matched control cohort during the same observation period - e.g. in terms of the number of hospitalizations (3.1 (95%CI: 2.9-3.4) vs. 0.5 (95%CI: 0.5-0.5)), different diagnoses (50.0 (95%CI: 48.1-51.9) vs. 26.4 (95%CI: 26.2-26.5)), different active substances prescribed (12.7 (95%CI: 12.2-13.3) vs. 8.2 (95%CI: 8.2-8.3)) and the number of genetic tests (14.7 (95%CI: 12.6-16.7) vs. 0.3 (95%CI: 0.3-0.3)). We found evidence of heterogeneity in utilization by age and sex. On average, direct costs (inpatient, outpatient and prescription drug costs) of patients with suspected rare diseases during the diagnostic pathway were 7.6-fold higher than the costs of matched controls (€26,999 (95%CI: €23,751 - 30,247) vs. €3,561 (95% CI: € 3,455-3,667)). Inpatient costs were the main cost component, accounting for 62.5% of total costs.

CONCLUSIONS: The diagnostic odyssey of patients with suspected rare diseases is associated with extensive healthcare utilization and high cost. Against this background, new ways to shorten the diagnostic journey have a high potential to decrease the financial burden related to rare diseases.

PMID:40349051 | DOI:10.1186/s13023-025-03751-y

Eur Urol Oncol. 2025 May 9:S2588-9311(25)00121-X. doi: 10.1016/j.euo.2025.04.024. Online ahead of print.

ABSTRACT

Several large analyses have revealed contradictory results regarding the association between prostate cancer (PC) survival and the use of statins prescribed for prevention of dyslipidaemia or atherosclerosis complications, or of metformin prescribed for type 2 diabetes (T2D). Using data collected between 2006 and 2018 in French national health databases for 521 052 men with PC and 1 827 345 men without PC, we evaluated current evidence regarding overall survival for men with PC according to statin and/or metformin use. The highest mortality was observed in PC patients exposed to both statins and metformin (hazard ratio [HR] 2.29, 95% confidence interval [CI] 2.25-2.33). However, for patients whose first PC treatment was androgen deprivation therapy, a protective effect was observed for statin alone exposure (HR 0.91, 95% CI 0.88-0.93) and combined statin and metformin exposure (HR 0.86, 95% CI 0.85-0.87), whereas men with metformin exposure alone had higher mortality (HR 1.07, 95% CI 1.03-1.11) in comparison to non-users. This protective effect of statins was not observed for PC patients treated with radical prostatectomy. The result was confirmed using causal analysis in a Bayesian network, followed by semantic elicitation using generative artificial intelligence that compiles web-based human knowledge and dedicated literature.

PMID:40348654 | DOI:10.1016/j.euo.2025.04.024

Ann Clin Microbiol Antimicrob. 2025 May 10;24(1):32. doi: 10.1186/s12941-025-00799-3.

ABSTRACT

BACKGROUND: This study examines colistin resistance in Gram-negative bacteria in Egypt, analyzing prevalence, trends, geographic variations, colistin-carbapenem resistance correlation, and mcr-mediated plasmid resistance.

METHODS: We conducted a systematic search of articles published between 2014 and 2024 that reported on colistin or mcr-mediated resistance in Gram-negative bacteria isolated from human infections in Egypt, with clearly defined susceptibility testing methods. A random-effects meta-analysis was conducted to estimate colistin resistance prevalence based on broth microdilution (BMD) findings, the gold standard method. To explore the influence of study-level factors-including alternative susceptibility testing methods-a multivariate meta-regression analysis was performed. The results of the meta-regression are reported as regression coefficients (β), representing the difference in colistin resistance, expressed in percentage points. All statistical analyses were conducted using R software.

RESULTS: This analysis included 55 studies. Based on BMD susceptibility testing, colistin resistance was observed in 9% of all recovered Gram-negative isolates (95% CI: 6-14%) and was significantly higher among carbapenem-resistant isolates (31%, 95% CI: 25-38%), with p < 0.001. Multivariate meta-regression analysis further confirmed that colistin resistance was significantly higher in carbapenem-resistant isolates compared to the total recovered isolates (β = 9.8% points, p = 0.001). Additionally, colistin resistance has significantly increased over time, with a β = 1.8% points per year (p = 0.001). The use of the VITEK 2 system was associated with lower detected colistin resistance compared to BMD (β = -7.0, p = 0.02). Geographically, resistance rates were higher in Upper Egypt (β = 9.3, p = 0.04). Regarding mcr plasmid-mediated resistance, mcr-1 was the most prevalent resistance gene, particularly in E. coli. In contrast, mcr-2 was rare, detected sporadically in K. pneumoniae and P. aeruginosa.

CONCLUSION: In Egypt, BMD testing identified colistin resistance in 9% of Gram-negative bacteria, increasing to 31% in carbapenem-resistant isolates. This higher resistance in carbapenem-resistant strains suggests stronger selective pressure from frequent colistin use. Additionally, colistin resistance has shown a rising trend over time, likely driven by increased usage and the spread of plasmid-mediated resistance. These findings underscore the urgent need for strict antimicrobial stewardship and alternative therapies to curb resistance evolution.

PMID:40349047 | DOI:10.1186/s12941-025-00799-3

Psychiatr Clin North Am. 2025 Jun;48(2):257-264. doi: 10.1016/j.psc.2025.01.004. Epub 2025 Mar 4.

ABSTRACT

Pharmacogenomic (PGx) testing is an evidence-based strategy to optimize the selection and dosing of certain psychotropic medications. An individual's genetics play a role in medication response through pharmacokinetic and pharmacodynamic mechanisms. The current evidence base of psychiatric PGx mainly focuses on the metabolism of psychotropics through the cytochrome P450 (CYP) system. PGx testing and decision support tools are not yet standardized, resulting in variations in interpretation and prescribing recommendations. Clinicians are encouraged to use PGx results as part of the clinical picture, in addition to the patient's overall clinical profile, in determining a personalized treatment plan for their patients.

PMID:40348416 | DOI:10.1016/j.psc.2025.01.004

EBioMedicine. 2025 May 9;116:105745. doi: 10.1016/j.ebiom.2025.105745. Online ahead of print.

ABSTRACT

BACKGROUND: People with schizophrenia differ in the type and severity of symptoms experienced, as well as their response to medication. A better understanding of the factors that influence this heterogeneity is necessary for the development of individualised patient care. Here, we sought to investigate the relationships between phenotypic severity and both medication and pharmacogenomic variables in a cross-sectional sample of people with schizophrenia or schizoaffective disorder depressed type.

METHODS: Confirmatory factor analysis derived five dimensions relating to current symptom severity (positive symptoms, negative symptoms of diminished expressivity, negative symptoms of reduced motivation and pleasure, depression and suicide) and cognitive ability in participants prescribed with antipsychotic medication. Linear models were fit to test for associations between medication and pharmacogenomic variables with dimension scores in the full sample (N = 585), and in a sub-sample of participants prescribed clozapine (N = 215).

FINDINGS: Lower cognitive ability was associated with higher chlorpromazine-equivalent daily antipsychotic dose (β = -0.12; 95% CI, -0.19 to -0.05; p = 0.001) and with the prescription of clozapine (β = -0.498; 95% CI, -0.65 to -0.35; p = 3 × 10-10) and anticholinergic medication (β = -0.345; 95% CI, -0.55 to -0.14; p = 8 × 10-4). We also found associations between pharmacogenomics-inferred cytochrome P450 (CYP) enzyme activity and symptom dimensions. Increased genotype-predicted CYP2C19 and CYP3A5 activity were associated with reduced severity of the positive (β = -0.108; 95% CI, -0.19 to -0.03; p = 0.009) and both negative symptom dimensions (β = -0.113; 95% CI, -0.19 to -0.03; p = 0.007; β = -0.106; 95% CI, -0.19 to -0.02; p = 0.012), respectively. Faster predicted CYP1A2 activity was associated with higher cognitive dimension scores in people taking clozapine (β = 0.17; 95% CI, 0.05-0.29; p = 0.005).

INTERPRETATION: Our results confirm the importance of taking account of medication history (and particularly antipsychotic type and dose) in assessing potential correlates of cognitive impairment or poor functioning in patients with schizophrenia. We also highlight the potential for pharmacogenomic variation to be a useful tool to help guide drug prescription, although these findings require further validation.

FUNDING: Medical Research Council (MR/Y004094/1) and The National Center for Mental Health, funded by the Welsh Government through Health and Care Research Wales. SKL was funded by a PhD studentship from Mental Health Research UK (MHRUK). DBK, JTRW, MCOD and AFP were supported by the European Union's Horizon 2020 research and innovation programme under grant agreement 964874.

PMID:40347835 | DOI:10.1016/j.ebiom.2025.105745

Clin Transl Sci. 2025 May;18(5):e70246. doi: 10.1111/cts.70246.

ABSTRACT

Pharmacogenomics remains underutilized in pediatric oncology, despite the existence of evidence-based guidelines. Implementation of pharmacogenomics-informed prescribing could improve medication safety and efficacy in pediatric oncology patients, who are at high risk of adverse drug reactions. This study examines the prevalence of high-risk pharmacogenomic phenotypes and the prescription of relevant medications in a diverse Australian pediatric oncology cohort, highlighting the potential impact of pharmacogenomic testing in this unique population. Whole genome sequencing data from 180 patients were analyzed to assess 14 genes with evidence-based pharmacogenomic guidelines relevant to pediatric oncology. Over 90% of patients had at least one high-risk phenotype, with 20% presenting four or more. Ondansetron, mercaptopurine, omeprazole, pantoprazole, and voriconazole were commonly prescribed medications that have pharmacogenomic prescribing recommendations, with the latter three showing the highest actionability rates. High-risk phenotypes were most frequently observed for CYP2C19 and CYP2D6, with 30% of patients having a high-risk phenotype for both genes. This study underscores the potential utility of pharmacogenomics in pediatric oncology patients across a range of pharmacogenes and commonly prescribed medications. The findings support advocacy for implementing broad, pre-emptive pharmacogenomic testing in oncology patients to improve treatment safety and efficacy.

PMID:40347484 | DOI:10.1111/cts.70246

Chest. 2025 May;167(5):1282-1284. doi: 10.1016/j.chest.2024.09.036.

NO ABSTRACT

PMID:40348513 | DOI:10.1016/j.chest.2024.09.036

Patient Educ Couns. 2025 May 5;137:108822. doi: 10.1016/j.pec.2025.108822. Online ahead of print.

ABSTRACT

OBJECTIVES: Cystic fibrosis (CF) causes progressive respiratory disease and premature death. Lung transplantation (LTx) is an important treatment consideration for people with CF (PwCF). Among PwCF, does preparedness for LTx and knowledge about LTx improve by reading personal narratives from CF LTx recipients ("CF Stories")?

METHODS: Adults with CF were recruited and presented with online CF Stories. Pre- and post-intervention questionnaires assessed LTx preparedness, knowledge, and decisional conflict. Deductive thematic analysis of study visits was conducted.

RESULTS: Twenty-five participants were included. Pre-intervention, 24 % (6/25) reported feeling "very prepared" to discuss LTx. Among the remaining 19, preparedness improved post-intervention for 74 % (n = 14, 95 % CI: 51-88 %), with 42 % (n = 8, 95 % CI: 23-64 %) transitioning to feeling "very prepared." Baseline transplant knowledge was high (100 % questions correct) among 48 % (12/25) of participants; among the remaining 13, 92 % (n = 12, 95 % CI: 67-99 %) scored 100 % post-intervention. Decisional conflict improved for 67 % of participants (16/24), with a mean individual Decisional Conflict Scale change of -9.4 (95 % CI: -2.8, -15.9; p = 0.01). Thematic analysis revealed that participants valued practical LTx insights and relatable stories, identifying key medical information for LTx discussions.

CONCLUSIONS: CF Stories improved knowledge and preparedness for LTx discussions.

PRACTICE IMPLICATIONS: Personal narratives could enhance preparedness for LTx discussions and decision-making for PwCF.

PMID:40347548 | DOI:10.1016/j.pec.2025.108822

Indian J Med Res. 2025 Mar;161(3):207-214. doi: 10.25259/IJMR_1754_2024.

ABSTRACT

Background & objectives Availability of sweat chloride analysis, the gold standard test for diagnosis of Cystic Fibrosis (CF) faces significant challenges in India. This study aimed to compare sweat conductivity using Sweat-Chek™ Sweat Analyzer against sweat chloride analysis using the 926 Sherwood chloride analyser and assess if sweat conductivity test can guide CF diagnosis in resource-poor settings. Methods In this retrospective study sweat chloride analysis and sweat conductivity were simultaneously performed on samples collected via Macroduct® system from patients referred for sweat testing. CF diagnosis was based on sweat chloride levels: ≥60 mmol/l confirmed CF, 30-59 mmol/l was borderline, and <30 mmol/l excluded CF. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), and area under curve (AUC) were calculated via ROC curve. Spearman's rho was employed to analyse the correlation between methods. Results Both tests were performed on 118 children of which 106 samples were adequately collected. CF was diagnosed in 11 children. Sweat conductivity ≥ 80 mmol/l diagnosed CF with 100 per cent sensitivity, specificity, PPV, and NPV. Likewise, a value ≤ 49 mmol/l predicted absence of CF with 100 per cent sensitivity, 91.36 per cent specificity, 78.13 per cent PPV, and 100 per cent NPV. Spearman's rho of 0.93 (P< 0.001) showed a strong correlation between the two methods. Intermediate conductivity values also correlated well (rs 0.62, P< 0.003) with intermediate sweat chloride levels. Interpretations & conclusions Sweat conductivity reliably identified CF in the study population including those children with borderline levels, suggesting the possibility of its use in resource-limited settings where sweat chloride analyzers are unavailable.

PMID:40347500 | DOI:10.25259/IJMR_1754_2024

Sci Rep. 2025 May 10;15(1):16290. doi: 10.1038/s41598-025-01367-7.

ABSTRACT

While continuous glucose monitoring (CGM) has revolutionized metabolic health management, widespread adoption remains limited by cost constraints and usage burden, often resulting in interrupted monitoring periods. We propose a deep learning framework for glucose level inference that operates independently of prior glucose measurements, utilizing comprehensive life-log data. The model employs a bidirectional Long Short-Term Memory (LSTM) network with an encoder-decoder architecture, incorporating dual attention mechanisms for temporal and feature importance. The system was trained on data from 171 healthy adults, encompassing detailed records of dietary intake, physical activity metrics, and glucose measurements. The encoder's hidden state as latent representations were analyzed for distributions of patterns of glucose and life-log sequences. The model showed a 19.49 ± 5.42 (mg/dL) in Root Mean Squared Error, 0.43 ± 0.2 in correlation coefficient, and 12.34 ± 3.11 (%) in Mean Absolute Percentage Eror for current glucose level predictions without any information of glucose at the inference step. The distribution of latent representations from the encoder showed the potential differentiation for glucose patterns. The model's ability to maintain predictive accuracy during periods of CGM unavailability has the potential to support intermittent monitoring scenarios for users.

PMID:40348812 | DOI:10.1038/s41598-025-01367-7

BMC Pulm Med. 2025 May 10;25(1):229. doi: 10.1186/s12890-025-03703-z.

ABSTRACT

BACKGROUND: The role of chronic inflammation in non-idiopathic pulmonary fibrosis fibrotic interstitial lung disease (non-IPF f-ILD) remains unclear, with varied responses to anti-inflammatory or immunosuppressive therapy. A reliable predictor for guiding treatment response may enhance clinical decision-making and minimize adverse treatment effects. We hypothesized that elevated C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) may be associated with improved treatment response.

METHODS: Our retrospective cohort study compared treatment response to anti-inflammatory therapy in patients with non-IPF f-ILD stratified by baseline CRP and ESR levels. Treatment response was defined as: (1) relative increase in percent predicted forced vital capacity (FVC%) ≥ 5% in 6 months or ≥ 10% in 12 months; or (2) no change or any increase in FVC% if FVC% decline was noted prior to treatment. Logistic regression was used to delineate outcome predictors with FVC% change over time assessed with linear mixed effects models.

RESULTS: Of 832 non-IPF f-ILD patients screened, 167 received anti-inflammatory therapy and baseline inflammatory marker testing stratified into high vs. low-to-normal groups (104 vs. 63, respectively). Median age was 64 years, and 57% were diagnosed with a systemic autoimmune rheumatic disease (SARD). Treatment response was greater in those with elevated inflammatory markers (56% vs. 35%; OR 2.45 [1.243-4.828] P = 0.010) even after adjustment for a priori covariables. SARD diagnosis was associated with treatment response (OR 2.90 [1.45-5.81] P = 0.003), independent of inflammatory marker level. A positive FVC% slope was observed in treated patients with initially elevated inflammatory markers (P = 0.003).

CONCLUSION: Patients with non-IPF f-ILD and elevated inflammatory markers appear to be more responsive to anti-inflammatory therapy with slower FVC decline over time. These findings suggest baseline serum ESR and CRP may be feasible and reliable predictors of treatment response in certain subgroups.

PMID:40348969 | DOI:10.1186/s12890-025-03703-z

Sci Rep. 2025 May 10;15(1):16310. doi: 10.1038/s41598-025-00763-3.

ABSTRACT

Medulloblastoma (MB) is the most common malignant pediatric brain tumor, accounting for approximately 20% of all childhood brain tumors. Despite recent advances, current treatments like surgery, radiation, and chemotherapy still lead to severe side effects and high morbidity. Limited knowledge exists regarding the regulatory mechanisms behind the MB transcriptional alterations in high-aggressive subgroups like Group 3 and Group 4, hindering the development of targeted therapies. Identifying key transcriptional regulators, known as master regulators (MRs), can elucidate the dysregulated pathways underlying MB progression and uncover potential treatment targets. In this study, we utilize primary MB gene expression samples to infer its regulatory network. Subsequently, we applied the Master Regulator Analysis identifying the transcription factors BHLHE41, RFX4, and NPAS3 as its main transcriptional regulators, showing tumor suppressor features. We also identified eight risk MRs highly associated with patient outcome: four regulators (MYC, REL, ZSCAN5 A, and ZFAT) with activities associated with poor prognosis, and four (PAX6, ARNT2, ZNF157, and HIVEP3) acting antagonistically, being associated with good outcome. Our results offer key insights into the molecular mechanisms driving these tumors and identify novel potential therapeutic targets, addressing the urgent need for more effective and less toxic treatments.

PMID:40348787 | DOI:10.1038/s41598-025-00763-3

BMC Plant Biol. 2025 May 10;25(1):620. doi: 10.1186/s12870-025-06622-7.

ABSTRACT

Trichomes in Prunus persica (L.) Batsch are crucial specialized structures that play a protective role against both biotic and abiotic stresses. The fruits with and without trichomes are respectively named as peach and nectarine. At the genetic level, the formation of trichome in peach is controlled by a single gene, PpMYB25, at the G locus. Peach (GG or Gg) is dominant to nectarine (gg), but such regulatory role was reported in a small-scale accession. In this study, we performed large-scale genotype and phenotype screening on 295 accessions. Almost all accessions supported the casual relationship between trichome formation and PpMYB25. However, a peach to nectarine mutant, named Maravilha Nectarine Mutant (MN), was discovered to possess a putative functional PpMYB25 gene sequence (Gg) but revealed nectarine phenotype. Comparative transcriptomic analyses revealed that PpMYB25 transcript was absent in MN. Correlation analyses also demonstrated that the PpMYB25-mediated regulatory network was abolished in MN. In summary, our results demonstrated an alternative mechanism beyond genetic regulation on trichome formation.

PMID:40348985 | DOI:10.1186/s12870-025-06622-7

NPJ Digit Med. 2025 May 10;8(1):267. doi: 10.1038/s41746-025-01681-4.

ABSTRACT

Large-language models (LLMs) show promise for clinical note information extraction, but deployment challenges include high computational costs and privacy concerns. We used synthetic data distillation to fine-tune smaller, open-source LLMs to achieve performance comparable to larger models while enabling local hardware deployment or reduced cloud costs. Using Llama-3.1-70B-Instruct, we generated synthetic question-answer training pairs to fine-tune smaller Llama models. We evaluated performance across three tasks: synthetic clinical trial criteria, the i2b2 2018 Clinical Trial Eligibility Challenge, and apixaban trial criteria questions. The 8B-parameter model achieved high accuracy across all tasks and sometimes outperformed the 70B-Instruct teacher model. Fine-tuning with only the most challenging questions still improved performance, demonstrating the value of targeted training. Results from 3B- and 1B-parameter models showed a clear size-performance tradeoff. This work demonstrates synthetic data distillation's potential for enabling scalable clinical information extraction.

PMID:40348936 | DOI:10.1038/s41746-025-01681-4

Sci Data. 2025 May 10;12(1):766. doi: 10.1038/s41597-025-05111-8.

ABSTRACT

Non-contact behavioral study through intelligent image analysis is becoming increasingly vital in animal neuroscience and ethology. The shift from traditional "black box" methods to more open and intelligent approaches is driven by advances in deep learning-based pose estimation and tracking. These technologies enable the extraction of key points and their temporal relationships from sequence images. Such approach is particularly crucial for investigating animal behaviors in outer space, with microgravity, high radiation, and hypomagnetic field. However, the limited image data of space animal and the lack of publicly accessible datasets with ground truth annotations have hindered the development of effective evaluation tools and methods. To address this challenge, we present the SpaceAnimal Dataset-the first multi-task, expert-validated dataset for multi-animal behavior analysis in complex scenarios, including model organisms such as Caenorhabditis elegans, Drosophila, and zebrafish. Additionally, this paper provides evaluation code for deep learning models, establishing benchmarks to guide future research. This dataset will advance AI technology innovation in this field, contributing to the discovery of new behavior patterns in space animals.

PMID:40348756 | DOI:10.1038/s41597-025-05111-8

NPJ Parkinsons Dis. 2025 May 10;11(1):122. doi: 10.1038/s41531-025-00966-5.

ABSTRACT

Amyloid aggregation is associated with neurodegenerative disease and its modulation is a focus of drug development. We developed a chemical proteomics pipeline to probe the mechanism of action of anti-amyloidogenic compounds. Our approach identifies putative interaction sites with high resolution, can probe compound interactions with specific target conformations and directly in cell and brain extracts, and identifies off-targets. We analysed interactions of six anti-amyloidogenic compounds and the amyloid binder Thioflavin T with different conformations of the Parkinson's disease protein α-Synuclein and tested specific compounds in cell or brain lysates. AC Immune compound 2 interacted with α-Synuclein in vitro, in intact neurons and in neuronal lysates, reduced neuronal α-Synuclein levels in a seeded model, and had protective effects. EGCG, Baicalein, ThT and doxycycline interacted with α-Synuclein in vitro but not substantially in cell lysates, with many additional putative targets, underscoring the importance of testing compounds in situ. Our pipeline will enable screening of compounds against any amyloidogenic proteins in cell and patient brain extracts and mechanistic studies of compound action.

PMID:40348747 | DOI:10.1038/s41531-025-00966-5

Neurosci Biobehav Rev. 2025 May 8:106204. doi: 10.1016/j.neubiorev.2025.106204. Online ahead of print.

ABSTRACT

Microdosing, the repeated use of psychedelic substances at low doses, is growing in popularity among recreational consumers. While this practice is associated with many benefits to mood, well-being and health, research in this area is in its early stages and predominantly centered on human applications. In this narrative review, we synthesize the findings from studies investigating the effects of microdosing on the behaviors of three animal species: rats, mice, and zebrafish. A total of 12 studies were identified that implemented a microdosing regimen of LSD, psilocybin, or DMT in these animal models. Overall, microdosing caused little changes in behaviors associated with anxiety- and depressive-like states. Moreover, while microdosing was well-tolerated across species, further research is needed to capture specific safety concerns. Finally, we critically appraise the studies included in this review based on their methodologies and discuss further avenues of research to advance the preclinical literature on psychedelic microdosing. Specifically, we recommend that future research prioritize the replication of existing findings to inform the development of robust study designs and dosing protocols, as well as establish standardized methodologies to enable effective comparisons across different animal models. Furthermore, future investigations should explore the therapeutic potential of mescaline microdosing, examine sex-dependent effects, and extend research to additional models of psychiatric conditions, including those related to obsessive-compulsive disorder and post-traumatic stress disorder.

PMID:40348309 | DOI:10.1016/j.neubiorev.2025.106204

Structure. 2025 Apr 28:S0969-2126(25)00147-9. doi: 10.1016/j.str.2025.04.013. Online ahead of print.

ABSTRACT

The interaction network of Sla2, a vital endocytic mid-coat adaptor protein, undergoes constant rearrangement. Sla2 serves as a scaffold linking the membrane to the actin cytoskeleton, with its role modulated by the clathrin light chain (CLC), which inhibits Sla2's function under certain conditions. We show that Sla2 has two independent binding sites for CLC: one previously described in homologs of fungi (Sla2) and metazoa (Hip1R), and a second found only in Fungi. We present the structural model of the Sla2 actin-binding domains in the context of regulatory structural domains by cryoelectron microscopy. We provide an interaction map of Sla2 and the regulatory proteins Sla1 and Pan1, predicted by AI modeling and confirmed by molecular biophysics techniques. Pan1 may compete with CLC for the conserved Sla2-binding site. These results enhance the mapping of crucial interactions at endocytic checkpoints and highlight the divergence between Metazoa and Fungi in this vital process.

PMID:40347949 | DOI:10.1016/j.str.2025.04.013