EBioMedicine. 2025 May 9;116:105729. doi: 10.1016/j.ebiom.2025.105729. Online ahead of print.

ABSTRACT

BACKGROUND: Congregate living provides an ideal setting for SARS-CoV-2 transmission in which many outbreaks and superspreading events occurred. To avoid large outbreaks, universities turned to remote operations during the initial COVID-19 pandemic waves in 2020 and 2021. In late-2021, the University of California San Diego (UC San Diego) facilitated the return of students to campus with comprehensive testing, vaccination, masking, wastewater surveillance, and isolation policies.

METHODS: We performed molecular epidemiological and phylogeographic analysis of 4418 SARS-CoV-2 genomes sampled from UC San Diego students during the Omicron waves between December 2021 and September 2022, representing 58% of students with confirmed SARS-CoV-2 infection. We overlaid these analyses across on-campus residential information to assess the spread and persistence of SARS-CoV-2 within university residences.

FINDINGS: Within campus residences, SARS-CoV-2 transmission was frequent among students residing in the same room or suite. However, a quarter of pairs of suitemates with concurrent infections had distantly related viruses, suggesting separate sources of infection during periods of high incidence in the surrounding community. Students with concurrent infections residing in the same building were not at substantial increased probability of being members of the same transmission cluster. Genetic network and phylogeographic inference indicated that only between 3.1 and 12.4% of infections among students could be associated with transmission within buildings outside of individual suites. The only super-spreading event we detected was related to a large event outside campus residences.

INTERPRETATION: We found little evidence for sustained SARS-CoV-2 transmission within individual buildings, aside from students who resided in the same suite. Even in the face of heightened community transmission during the 2021-2022 Omicron waves, congregate living did not result in a heightened risk for SARS-CoV-2 transmission in the context of the multi-pronged mitigation strategy.

FUNDING: SEARCH Alliance: Centers for Disease Control and Prevention (CDC) BAA (75D301-22-R-72097) and the Google Cloud Platform Research Credits Program. J.O.W.: NIH-NIAID (R01 AI135992). T.I.V.: Branco Weiss Fellowship and Newkirk Fellowship. L.L.: University of California San Diego.

PMID:40347833 | DOI:10.1016/j.ebiom.2025.105729

Plant Biotechnol J. 2025 May 10. doi: 10.1111/pbi.70122. Online ahead of print.

ABSTRACT

The limited cytosolic delivery of DNA and protein-based therapeutics due to endosomal entrapment reduces drug efficacy, increasing treatment costs and possible side effects in human and veterinary medicine as a consequence of higher administered dosages. Plant-derived triterpenoid saponins, specifically those with endosomal escape-enhancing (EEE) properties, have shown promise in overcoming this limitation by disrupting endosomal membranes. QS-21, a well-known EEE saponin, has been used as an adjuvant in vaccines, and recent studies have elucidated its biosynthetic pathway. However, EEE saponins are typically present as minor compounds in plants, posing challenges for their large-scale production and purification. Here we investigated the possibility of engineering SO1861 production, an EEE saponin from Saponaria officinalis, using heterologous gene expression in Gypsophila elegans hairy roots, a plant species known to synthesize structurally related saponins. Via S. officinalis transcriptomics, we identified jasmonate-responsive saponin biosynthetic genes, and three cytochrome P450s (CYP450s) involved in C23, C28 and C16 oxidations were characterised. Heterologous expression of these CYP450s in G. elegans hairy roots successfully altered the saponin profile, with notable increases in SO1861 precursors in lines expressing the C23-oxidases SoCYP72A984 and SoCYP72A1003. Interestingly, expression of only SoCYP72A1003, a non-canonical C23 oxidase, resulted in the accumulation of a compound matching the SO1861 standard, suggesting the activation of a potentially latent pathway and of silent enzymes in a novel combination. This work underscores the potential of engineering strategies in heterologous plant systems to steer triterpenoid saponin biosynthetic pathways and suggests new avenues for producing high-value EEE saponins.

PMID:40347514 | DOI:10.1111/pbi.70122

STAR Protoc. 2025 May 8;6(2):103769. doi: 10.1016/j.xpro.2025.103769. Online ahead of print.

ABSTRACT

Regulatory modules are molecules that interact functionally, driving disease processes. Here, we present a protocol for identifying regulatory modules in Parkinson's disease (PD) using cohort-specific microRNA (miRNA) data and Boolean modeling. We describe steps for omics data collection, biomolecule and miRNA target analysis, and Boolean model construction and simulation. We then detail procedures for validation of the model and results. The modules identified using this protocol explain how miRNA-driven mechanisms influence PD progression in disease cohorts. For complete details on the use and execution of this protocol, please refer to Hemedan et al.1.

PMID:40347476 | DOI:10.1016/j.xpro.2025.103769

Eur J Hosp Pharm. 2025 May 10:ejhpharm-2025-004597. doi: 10.1136/ejhpharm-2025-004597. Online ahead of print.

NO ABSTRACT

PMID:40348405 | DOI:10.1136/ejhpharm-2025-004597

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

Pharmacotherapy. 2025 May 10. doi: 10.1002/phar.70028. Online ahead of print.

ABSTRACT

BACKGROUND: Oxaliplatin-induced peripheral neuropathy (OIPN) is a major clinical challenge because it leads to discontinuation of chemotherapy. Omeprazole, a proton pump inhibitor (PPI), has been shown to prevent OIPN in a rat model. Therefore, we aimed to test whether the concomitant use of a PPI reduces oxaliplatin discontinuation due to OIPN.

METHODS: This retrospective study used data from 1015 patients who started treatment with oxaliplatin and evaluated two cohorts (PPI vs. non-PPI). The primary outcome measure was oxaliplatin discontinuation due to OIPN. A Kaplan-Meier curve was generated for cumulative doses and evaluated using the log-rank test and Cox proportional hazards analysis.

RESULTS: The log-rank test showed that the number of patients who discontinued oxaliplatin due to OIPN was significantly lower in the PPI group (p = 0.0264). Cox proportional hazards analysis incorporated and analyzed factors previously reported as potentially affecting neuropathy (sex, age, use of PPIs, calcium channel antagonists, opioids and adjuvant analgesics, and the CAPOX [capecitabine + oxaliplatin] regimen). The analysis suggested that the concomitant use of PPIs was a factor in reducing oxaliplatin discontinuation (adjusted hazard ratio [HR] = 0.568, 95% confidence interval [CI], 0.344-0.937, p = 0.0269). Since there were significant differences in some patient demographics between the two groups, propensity score matching was performed to align the patient demographics and then reanalyzed. After propensity score matching, the same analysis as above showed that oxaliplatin discontinuation due to OIPN was significantly less common in the PPI group (p = 0.0081); cox proportional hazards analysis showed that PPI use was a factor that significantly reduced oxaliplatin discontinuation due to OIPN (adjusted HR = 0.478, 95% CI, 0.273-0.836, p = 0.0096).

CONCLUSIONS: These results suggest that concomitant PPI use may reduce oxaliplatin discontinuation due to OIPN in patients receiving oxaliplatin.

PMID:40347077 | DOI:10.1002/phar.70028

Chem Biol Drug Des. 2025 May;105(5):e70122. doi: 10.1111/cbdd.70122.

ABSTRACT

Carprofen, a nonsteroidal anti-inflammatory drug (NSAID) derived from propanoic acid, is known for its analgesic and antipyretic properties. Although it has long been employed in veterinary medicine as an anti-inflammatory agent, its use in humans was discontinued shortly after its market launch due to costly raw materials, complex synthesis, and labor-intensive production processes-factors that made it less competitive compared with other NSAIDs. Despite this, the carprofen molecule remains a subject of significant scientific interest. Recent advancements in its synthesis have introduced simplified and more cost-effective methods, reigniting its potential for both novel applications and drug repurposing. Exciting new research is exploring carprofen's broader therapeutic possibilities, extending beyond its original anti-inflammatory role. Studies are investigating its efficacy in antimicrobial therapy-including antibiofilm, anticancer, antiviral, and anti-Alzheimer's applications-opening doors to a wealth of untapped possibilities. This review delves into these emerging areas, highlighting how carprofen's molecular structure and derivatives can be leveraged to expand its therapeutic reach. The literature review was conducted using four databases: Web of Science, ScienceDirect, Scopus, Embase, and Reaxys. The review focused on English-language original research and review articles, examining carprofen and its derivatives in terms of their synthesis methods as well as their use as small molecules in various therapeutic applications, both human and veterinary. With ongoing research pushing the boundaries of its potential, carprofen remains a promising candidate for innovation in drug development and treatment strategies.

PMID:40346933 | DOI:10.1111/cbdd.70122

Mol Pain. 2025 May 10:17448069251343417. doi: 10.1177/17448069251343417. Online ahead of print.

ABSTRACT

Calcium channels play an essential role in the molecular and physiological mechanisms underlying anesthesia by mediating intracellular calcium ion (Ca²⁺) flux, which regulates key processes such as neurotransmitter release, neuronal excitability, and immune responses. Voltage-gated calcium channels (VGCCs) and ligand-gated calcium channels (LGCCs) are integral to the anesthetic process, with subtypes such as T-type VGCCs and NMDA receptors influencing consciousness and pain perception. This review emphasizes current evidence to highlight how anesthetic agents interact with calcium channels via direct inhibition and modulation of intracellular signaling pathways, such as phosphatidylinositol metabolism.Additionally, calcium channelopathies-genetic or acquired dysfunctions affecting VGCCs and LGCCs-pose challenges in anesthetic management, including arrhythmias, malignant hyperthermia, and altered anesthetic sensitivity. These findings underscore the critical need for precision medicine approaches tailored to patients with these conditions. While significant progress has been made in understanding the roles of calcium channels in anesthesia, knowledge gaps remain regarding the long-term implications of anesthetic interactions on calcium signaling and clinical outcomes.This review bridges foundational science with clinical practice, emphasizing the translational potential of calcium channel research for optimizing anesthetic strategies. By integrating molecular insights with emerging pharmacogenomic approaches, it provides a pathway for developing safer and more effective anesthesia protocols that enhance patient outcomes.

PMID:40346957 | DOI:10.1177/17448069251343417

Fundam Clin Pharmacol. 2025 Jun;39(3):e70013. doi: 10.1111/fcp.70013.

ABSTRACT

BACKGROUND: Opioid use disorder (OUD) is an emerging and global public health concern, and its management remains inadequate, notably due to a lack of biomarkers, except for the CYP2B6 genetic polymorphisms.

OBJECTIVES: Hence, the aim of this study was to assess the influence of genetic polymorphisms of ABCB1, SLC22A1, COMT, and OPRM1 on biological parameters and clinical response in patients receiving methadone maintenance treatment (MMT).

METHODS: A subgroup of 72 patients treated by MMT was genotyped for ABCB1 (rs1045642; rs2032582), SLC22A1 (rs12208357; rs72552763; rs113569197), COMT (rs4680), and OPRM1 (rs1799971) from Opioid PhArmacoLogy (OPAL), a clinical survey of patients suffering from OUD. Associations of these polymorphisms and both clinical and pharmacological (plasma methadone levels) responses were investigated.

RESULTS: All polymorphisms tested were not associated with (R,S)-methadone concentrations/doses (concentrations relative to doses), (R)-methadone concentrations/doses nor (S)-methadone concentrations/doses in bivariate analyses with codominant and recessive models. Also, polymorphisms tested were not related to clinical response (opiate cessation) during MMT in treated patients. The main limitations of our study were the sample size and the absence of polygenic analyses.

CONCLUSION: This study found no evidence to support the use of genotyping for polymorphisms in the ABCB1, SLC22A1, COMT, and OPRM1 genes in a clinical setting for the management of MMT in OUD.

PMID:40346879 | DOI:10.1111/fcp.70013

Clin Transl Sci. 2025 May;18(5):e70245. doi: 10.1111/cts.70245.

ABSTRACT

Elexacaftor/tezacaftor/ivacaftor (ETI) significantly improves treatment outcomes for people with cystic fibrosis (pwCF) with at least one F508del allele. In 2023, the Food and Drug Administration approved ETI for children with CF aged 2-5 years. However, real-world pharmacokinetic-pharmacodynamic data for ETI in pediatric and adult populations are still limited. This study aimed to characterize the population PK of ETI in children with CF (chCF) and evaluate current dosing recommendations. Population PK modeling was conducted using Monolix software on 150 ETI concentrations obtained from therapeutic drug (TDM) monitoring in 96 children with CF aged 2-18 years, as part of the MODUL-CF study. Area under the curve was derived from individual Bayesian pharmacokinetic estimates. A one-compartment model with a lag time, first-order absorption, and elimination best described the PK of elexacaftor/ivacaftor, while the PK of tezacaftor followed a one-compartment model with first-order absorption and elimination. A large between-subject variability was observed. The effect of body weight was significant on apparent clearance and volume of distribution parameters using allometric scaling. Children weighing 30-40 kg who received the adult-recommended dose showed higher drug exposure compared to adults with cystic fibrosis. This is the first study to describe the population pharmacokinetics of ETI in chCF aged 2-18 years, revealing high between-subject variability for all three drugs. In this context, TDM is likely essential for managing ETI exposure levels and guiding dosing adjustments. The appropriateness of current dosing recommendations for children under 12 years old weighing 30-40 kg remains to be clarified.

PMID:40347054 | DOI:10.1111/cts.70245

Diabetes Technol Ther. 2025 May 9. doi: 10.1089/dia.2025.0075. Online ahead of print.

ABSTRACT

Background: Studies investigating the safety and efficacy of automated insulin delivery (AID) systems in people with cystic fibrosis-related diabetes are limited. There are no published studies investigating the tubeless Omnipod 5 (OP5) AID system. Methods: This dual-center retrospective cohort study compared 14 days of baseline continuous glucose monitoring (CGM) data with days 1-90 and 91-180 post-OP5 initiation. Multivariable mixed-effects linear regression models were used to assess changes in glycemic metrics. Results: Among the 26 individuals with sufficient data initiating OP5, 65% were female, with a median age of 27.3 years and median diabetes duration of 10.9 years. Six (23%) had a history of solid organ transplant, and 2 (8%) were receiving enteral tube feeds. Participants transitioned to OP5 from multiple daily injections (54%), prior Omnipod generation (31%), or another AID system (15%). CGM time in range (70-180 mg/dL) increased from 54% (95% confidence interval [CI]: 45.0, 63.0) to 64% (95% CI: 57, 71.8, P < 0.001) during the first 90 days and to 62.7% (95% CI: 54.9, 70.5, P < 0.001) during 91-180 days. Time above range (TAR) 181-250 mg/dL and TAR >250 mg/dL improved at 1-90 days and 91-180 days compared with baseline (P = 0.001 and P = 0.002, respectively). There were no significant changes in time below range (54-69 mg/dL, <54 mg/dL) or coefficient of variation. Two individuals discontinued OP5 within 14 days due to persistent hypoglycemia. One adult experienced a hypoglycemic seizure after 3 months of use. Conclusions: Use of the OP5 system in youth and adults with CFRD led to significant improvements in multiples measures of hyperglycemia without a change in CGM-measured hypoglycemia over a 6-month period, although patient experience with hypoglycemia may limit sustained use. Given the unique comorbidities and pathophysiology of CFRD, these results emphasize the need for future studies to investigate the safety and efficacy of AID devices in this patient population.

PMID:40346784 | DOI:10.1089/dia.2025.0075

Acta Otolaryngol. 2025 May 10:1-9. doi: 10.1080/00016489.2025.2492359. Online ahead of print.

ABSTRACT

BACKGROUND: There is a lack of correlation studies between subjective behavioral test threshold and neural response telemetry (NRT) thresholds in cochlear implant (CI) patients. At present, there is no predictive model that can predict the parameters of CI adjustment objectively and reliably.

OBJECTIVES: To explore the correlation between the subjective behavior test method threshold and the NRT thresholds in patients with CI with normal cochlear (NC) morphology and inner ear malformation (IEM). To explore the value of using deep learning technology to predict the parameters of machine adjustment and guide the postoperative machine adjustment.

METHODS: NRT and subjective behavior tests were conducted on 57 cases of CI patients with NC morphology and 20 cases of IEM using electrodes 1, 6, 11, 16, and 22, respectively. The correlation between the NRT thresholds and T and C values was analyzed. Using deep learning techniques, establish a prediction model based on convolutional neural networks to predict the parameters of machine adjustment of CI.

RESULTS: The average NRT thresholds values of the NC group and the IEM group were both greater than the T values, close to and slightly smaller than the C values. The average values of T values, C values, and NRT thresholds in the IEM group were slightly higher than those in the NC group. The NRT thresholds of the both groups is significantly correlated with the C values and T values. The constructed prediction model has high accuracy between the predicted values and the actual values of each electrode. Moreover, the linear regression equation between the predicted and actual values is highly similar.

CONCLUSIONS: The NRT thresholds is significantly related to the subjective behavior test threshold. The correlation between NRT thresholds and T or C values can be used to assist in CI tuning. Especially for patients with IEM, different machine adjustment strategies should be adopted compared to NC patients. Moreover, the constructed neural network prediction model can also guide the postoperative adjustment of patients with cochlear implants.

PMID:40347195 | DOI:10.1080/00016489.2025.2492359

Nucleic Acids Res. 2025 May 10;53(9):gkaf323. doi: 10.1093/nar/gkaf323.

ABSTRACT

Nanopore sequencing allows identification of base modifications, such as methylation, directly from raw current data. Prevailing approaches, including deep learning (DL) methods, require training data covering all possible sequence contexts. These data can be prohibitively expensive or impossible to obtain for some modifications. Hence, research into DNA modifications focuses on the most prevalent modification in human DNA: 5mC in a CpG context. Improved generalization is required to reach the technology's full potential: calling any modification from raw current values. We developed ReQuant, an algorithm to impute full, k-mer based, modification models from limited k-mer context training data. ReQuant is highly accurate for calling modifications (CpG/GpC methylation and CpG glucosylation) in Lambda Phage R9 data when fitting on ≤25% of all possible 6-mers with a modification and extends to human R10 data. The success of our approach shows that DNA modifications have a consistent and therefore predictable effect on Nanopore current levels, suggesting that interpretable rule-based imputation in unseen contexts is possible. Our approach circumvents the need for modification-specific DL tools and enables modification calling when not all sequence contexts can be obtained, opening a vast field of biological base modification research.

PMID:40347136 | DOI:10.1093/nar/gkaf323

Cancer Med. 2025 May;14(9):e70931. doi: 10.1002/cam4.70931.

ABSTRACT

OBJECTIVES: Previous deep learning studies have not explored the synergistic effects of ROI dimensions (2D/2.5D/3D), peritumoral expansion levels (0-8 mm), and segmentation scenarios (ROI only vs. ROI original). Our study aims to evaluate the performance of multidimensional deep transfer learning models in distinguishing molecular subtypes of breast cancer (luminal vs. nonluminal) using DCE-MRI. Under two segmentation scenarios, we systematically compare the effects of ROI dimensions and peritumoral expansion levels to optimize multidimensional deep learning models via transfer learning for distinguishing luminal from nonluminal breast cancers in DCE-MRI-based analysis.

MATERIALS AND METHODS: From October 2020 to October 2023, data from 426 patients with primary invasive breast cancer were retrospectively collected. Patients were divided into three cohorts: (1) training cohort, n = 108, from SYSU Hospital (Zhuhai, China); (2) validation cohort 1, n = 165, from HZ Hospital (Huizhou, China); and (3) validation cohort 2, n = 153, from LY Hospital (Linyi, China). ROIs were delineated, and expansions of 2, 4, 6, and 8 mm beyond the lesion boundary were performed. We assessed the performance of various deep transfer learning models, considering precise segmentation (ROI only and ROI original) and varying peritumoral regions, using ROC curves and decision curve analysis.

RESULTS: The 2.5D1-based deep learning model (ROI original, 4 mm expansion) demonstrated optimal performance, achieving an AUC of 0.808 (95% CI 0.715-0.901) in the training cohort, 0.766 (95% CI 0.682-0.850) in validation cohort 1, and 0.799 (95% CI 0.725-0.874) in validation cohort 2.

CONCLUSION: The study highlights that the 2.5D1-based deep learning model utilizing the three principal slices of the minimum bounding box (ROI original) with a 4 mm peritumoral region is effective in distinguishing between luminal and nonluminal breast cancer tumors, serving as a potential diagnostic tool.

PMID:40347080 | DOI:10.1002/cam4.70931

J Sleep Res. 2025 May 10:e70093. doi: 10.1111/jsr.70093. Online ahead of print.

ABSTRACT

Home sleep apnea tests (HSATs) have emerged as alternatives to in-laboratory polysomnography (PSG), but Type IV HSATs often show limited diagnostic performance. This study clinically validates SleepAI, a novel remote digital health system that applies AI algorithms to raw oximetry data for automated sleep staging and obstructive sleep apnea (OSA) diagnosis. SleepAI algorithms were trained on over 10,000 PSG recordings. The system consists of a wearable oximeter connected via Bluetooth to a mobile app transmitting raw data to a cloud-based platform for AI-driven analysis. Clinical validation was conducted in 53 subjects with suspected OSA, who used SleepAI for three nights at home and one night in a sleep centre alongside PSG. SleepAI's apnea-hypopnea index (AHI) estimates and three-class sleep staging (Wake, REM, NREM) were compared to PSG references. For OSA severity classification (non-OSA, mild, moderate, severe), SleepAI achieved an overall accuracy of 89%, with F1-scores of 1.0, 1.0, 0.9, and 0.88, respectively. The three-stage sleep classification achieved a Cohen's kappa of 0.75. Night-to-night AHI variability showed that 37.5% of participants experienced a one-level severity change across nights at home. No significant differences in sleep metrics were found between the first and subsequent nights at home, indicating no sleep disturbance by SleepAI. These findings support the SleepAI system as a promising and scalable alternative to existing Type IV HSATs, with the potential to address key clinical gaps by improving diagnostic accuracy and accessibility.

PMID:40346945 | DOI:10.1111/jsr.70093

New Phytol. 2025 May 10. doi: 10.1111/nph.70197. Online ahead of print.

ABSTRACT

Leaf angle distribution (LAD) impacts plant photosynthesis, water use efficiency, and ecosystem primary productivity, which are crucial for understanding surface energy balance and climate change responses. Traditional LAD measurement methods are time-consuming and often limited to individual sites, hindering effective data acquisition at the ecosystem scale and complicating the modeling of canopy LAD variations. We present a deep learning approach that is more affordable, efficient, automated, and less labor-intensive than traditional methods for estimating LAD. The method uses unmanned aerial vehicle images processed with structure-from-motion point cloud algorithms and the Mask Region-based convolutional neural network. Validation at the single-leaf scale using manual measurements across three plant species confirmed high accuracy of the proposed method (Pachira glabra: R2 = 0.87, RMSE = 7.61°; Ficus elastica: R2 = 0.91, RMSE = 6.72°; Schefflera macrostachya: R2 = 0.85, RMSE = 5.67°). Employing this method, we efficiently measured leaf angles for 57 032 leaves within a 30 m × 30 m plot, revealing distinct LAD among four representative tree species: Melodinus suaveolens (mean inclination angle 34.79°), Daphniphyllum calycinum (31.22°), Endospermum chinense (25.40°), and Tetracera sarmentosa (30.37°). The method can efficiently estimate LAD across scales, providing critical structural information of vegetation canopy for ecosystem modeling, including species-specific leaf strategies and their effects on light interception and photosynthesis in diverse forests.

PMID:40346911 | DOI:10.1111/nph.70197

Small Methods. 2025 May 9:e2402010. doi: 10.1002/smtd.202402010. Online ahead of print.

ABSTRACT

Correlated single-atom catalysts offer transformative potential in catalysis, particularly in the field of electrocatalysis, with a focus on oxygen evolution reactions. Advanced characterization is critical to understanding their atomic-scale properties when techniques usually used in molecular science (Nuclear Magnetic Resonance (NMR), X-ray Diffraction (XRD), Infrared spectroscopy (IR), or Mass Spectrometry (MS)) cannot be applied after dispersing them on a carrier material. Here, a methodology that combines machine learning and mathematical optimization techniques to detect and quantify metal-metal interactions within heterobinuclear Au(III)-Pd(II) macrocyclic complexes on atomically resolved high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) images is introduced. Both supervised and unsupervised machine learning methods are evaluated, with the U-net architecture demonstrating superior performance in distinguishing the two involved chemical species. Mathematical optimization models further enhance the reliability of metal pair identification by providing precise distance metrics for the pairs. This methodology allows for the study of both the dynamics and bond interaction of heterobinuclear Au(III)-Pd(II) complexes. Notably, the analysis of time series of images reveals that most metal pairs remained stable under the high-energy electron beam irradiation conditions. Likewise, the Au-Pd distance within the pairs remains unchanged, indicating a robust interaction of the two metals with the ligand even after being deposited on the amorphous carbon substrate.

PMID:40346778 | DOI:10.1002/smtd.202402010

J Mol Med (Berl). 2025 May 10. doi: 10.1007/s00109-025-02549-6. Online ahead of print.

ABSTRACT

The development of therapeutics that enhances the regeneration of myelin sheaths following demyelination is predicted to prevent neurodegeneration. A promising target to enhance remyelination is the immunomodulatory cytokine tumor necrosis factor alpha (TNFα) and its receptors TNFR1 and TNFR2. TNFR2 on oligodendrocyte lineage cells and microglia coordinates different protective functions, such as proliferation of oligodendrocyte progenitor cells, survival of mature oligodendrocytes, and release of anti-inflammatory cytokines, in animal models of inflammation and demyelination. Here, we find in the cuprizone model that following demyelination, fewer axons are unmyelinated in the corpus callosum at an early stage of remyelination after single TNFR2 agonist delivery in the lateral ventricle, while astrocyte and microglia number and coverage are unchanged. Towards later stages of remyelination, TNFR2 agonist treatment maintains the number of oligodendrocyte lineage cells, and large caliber axons have thinner myelin. Hence, even short-term stimulation of TNFR2 has a positive impact on the remyelination processes. This study informs further on the beneficial implications of TNFR2 signaling on oligodendrocyte lineage cells and remyelination, emphasizing its potential therapeutic value for demyelinating diseases, including multiple sclerosis. KEY MESSAGES: Single TNFR2 agonist treatment in the lateral ventricle following cuprizone-induced demyelination impacts remyelination by: Leading to a lower percentage of unmyelinated axons at early stages. Preserving the number of oligodendrocyte lineage cells in the corpus callosum at later stages. Covering large calibre axons with thinner myelin sheaths at later stages.

PMID:40347238 | DOI:10.1007/s00109-025-02549-6

ACS Synth Biol. 2025 May 10. doi: 10.1021/acssynbio.5c00163. Online ahead of print.

ABSTRACT

Bisphenols are widely used in manufacturing plastics and resins, but their environmental persistence raises concerns to human health and ecosystems. Accurate measurements for bisphenols are crucial for effective monitoring and regulation. Analytical methods detect only preselected bisphenols, while bioassays assessing estrogen receptor α activation suffer from poor sensitivity and strong background signals due to estrogenic contaminations. To develop a bioassay in Saccharomyces cerevisiae with increased sensitivity and specificity for bisphenols, we performed multi-site directed mutagenesis and directed evolution of more than 108 stably integrated estrogen receptor variants. By mutating the estrogen receptor α towards recognition of bisphenol A in yeast, we determined the preBASE variant (M421G_V422G_V533D_L536G_Y537S) with elevated bisphenol A sensitivity (EC50:329 nM) and lost estrogen responsiveness (EC50:0,17 mM). Further engineering yielded an off-target mutant, identified as the Bisphenol-Affinity and Specificity-Enhanced (BASE) variant (M421G_V422G_V533D_L536G_Y537S_L544I) that uses bisphenols as its primary agonist (EC50:32 mM) and impaired estrogen sensitivity (EC50:85M). The rewiring into a bisphenol receptor was confirmed in ligand binding assays to purified ligand binding domains. Taken together, the identified variants form stepping stones for further protein engineering to generate bisphenol specific high-throughput yeast-based bioassays.

PMID:40347189 | DOI:10.1021/acssynbio.5c00163

Cancer Med. 2025 May;14(9):e70957. doi: 10.1002/cam4.70957.

ABSTRACT

BACKGROUND: The aim of this study was to estimate the global burden of lip and oral cavity cancer (LOC) and its trends in different genders, age groups, regions, and countries globally.

METHODS: Data were sourced from the Global Burden of Disease 2021 study.

RESULTS: During the 32-year period, a 92.92% and 113.94% increase was estimated in the absolute counts of LOC deaths and disability-adjusted life years (DALYs), respectively. Throughout the 32-year period, males exhibited higher age-standardized rates (ASRs) of incidence (ASIRs), prevalence (ASPRs), mortality (ASMRs), and DALYs (ASDRs) related to LOC. The age group of 60-64 years consistently recorded the highest numbers of new and prevalent cases across the years 1990, 2019, and 2021. In 2019 and 2021, the highest ASMR and ASDR were observed in individuals aged 95 years and older. Regions with low-middle and low socio-demographic index (SDI) consistently showed higher ASMRs and ASDRs associated with LOC from 1990 to 2021. Eastern Europe, South, North, and Southeast Asia exhibited a concentration of countries with higher ASIRs, ASPRs, ASMRs, and ASDRs in 2021. South Asia maintained high levels of ASIRs, ASPRs, ASMRs, and ASDRs in 2021. In 2021, Palau recorded the highest ASIR, ASPR, ASMR, and ASDR, followed by Pakistan. Projections indicate that ASIR, ASPR, ASMR, and ASDR are expected to increase by 7.40%, 10.10%, 2.85%, and 4.60%, respectively, from 2021 to 2040.

CONCLUSION: LOC remains a critical public health concern that requires immediate attention, particularly among certain demographics such as males, aged 60-64 or 95 and older, as well as in low- and middle-SDI regions, particularly Eastern Europe, South Asia (notably Pakistan), North Asia, and Southeast Asia.

PMID:40347073 | DOI:10.1002/cam4.70957