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All-in-One photo-biocatalysis system for sustainable chemical transformations

Topography-driven movement of biomolecular condensates

Biomolecular condensates are assemblies of proteins or nucleic acids that exhibit liquid-like properties and organize intracellular biochemical reactions within many cells. Some condensates require membrane association, and we previously developed an assay to reconstitute biomolecular condensates in the presence of various membrane topographies. However, the effect of membrane topography on the displacement of biomolecular condensates remains incompletely understood. Here, we studied the movement of biomolecular condensates on lipid membrane-clad microstructures in a cell-free assay. We observed movements perpendicular to microstructured surfaces opposing gravitational force for untethered condensates. Increased membrane attachment reduced the number of such movements. These movements were observed for liquid-like condensates as well as for more viscous condensates, on surfaces with grooves and in cylindrical microstructures with varying diameter. A passivating PEG-coating of the microstructures also enabled movements of the condensates perpendicular to microstructured surfaces, further confirming the role topography of modulating passive condensate movement. An increased wetting of condensates on microgrooves led to the formation of elongated condensates which exhibit a coordinated sideward movement upon fusion. Our results indicate that membrane topographies, in combination with membrane attachment patterns, regulate passive biomolecular condensate movement.

Cardiac reprogramming via transient overexpression of P-glycoprotein alleviates doxorubicin-induced cardiotoxicity in mice and pigs

Low-toxic and organic solvent-free isolation of RNA

RNA is the central molecule that connects genetic makeup to the function of living cells and organisms. Since genes will also cease to be transcribed, RNA must decay so that the cellular RNA-pool can reflect the current transcriptional state. Undesired degradation is therefore a major challenge when RNA is isolated from living cells, tissues or organisms. Strongly protein-denaturing conditions, often involving toxic organic solvents, are usually employed to quickly inactivate RNases prior to separating nucleic acids from protein. We propose to combine high concentrations of urea, a compound used in fertilizers, with SDS as a non-volatile, low toxicity denaturant. The use of urea and SDS has previously been combined with organic solvent extraction, chaotropic salt-mediated column purification or selective precipitation of long RNA with LiCl. Here, we demonstrate that – akin to the classic alkaline lysis protocol for plasmid preparation – addition of potassium acetate forms insoluble potassium dodecyl sulfate, which can be removed along with denatured proteins and part of the genomic DNA by centrifugation. The RNA is then precipitated with isopropanol, recovering also small non-coding RNAs. We demonstrate that these somewhat crude RNA preparations are nonetheless sufficiently clean to be quantified via classic UV absorption measurements, stable over the time-course of a typical molecular biology reaction and do not harbor inhibitors of reverse transcriptase. While it seems unlikely that we are the first to conceive this simple strategy, we are not aware of any corresponding prior publication.

Spliceosome induction is a druggable dependency of RAS-driven senescence and cancer

Abstract RAS family proteins, including HRAS, NRAS, and KRAS, are frequently mutated in cancer. Although there has been recent success in designing inhibitors that target oncogenic RAS, they elicit resistance and treating RAS-driven cancer remains difficult. Here, employing a proteomic analysis, we find that multiple spliceosome components are upregulated in the nuclei of cells undergoing RAS-induced senescence. This upregulation depends on RAS signalling and occurs in both senescent preneoplastic and fully transformed cancer cells. Spliceosome components are also highly expressed in preneoplastic and cancerous lesions in human and murine lung, liver, colorectal, and pancreatic cancers. Using siRNA screens, we identify six spliceosome components, including SF3B1 and RBM39, that are essential in cells expressing oncogenic RAS. We find that SF3B1 is required in these cells for maintaining splicing fidelity. By combining transcriptome and splicing analyses with functional screens, we identify the RNA Pol II-associated factor SPT5 as a key mediator of the SF3B1 effects. Importantly, using mouse models of liver cancer, we show that RBM39 and SF3B1 inhibitors are effective in targeting both preneoplastic lesions and aggressive tumours expressing oncogenic RAS. In summary, our study highlights the spliceosome as a promising target for RAS-driven cancers capable of inhibiting both cancer initiation and progression.

Modest google trends associations with mental health patient and general population deaths by suicide: A time-series analysis using patient-provided search terms

Background Suicide-related internet use (SRIU), particularly online information seeking, seems to be highly prevalent among mental health patients. Most research using Google Trends to examine suicide-related search patterns relies on researcher-selected terms rather than those actually used by people at risk, limiting ecological validity. No studies have specifically examined associations between volume of suicide-related searches and number of suicides by mental health patients, despite this population’s elevated risk and prevalent SRIU. Methods This study analysed suicide-related search terms provided by 196 people who had used mental health services in the UK who had engaged in SRIU. From 520 search entries, 36 terms were identified across seven categories and analysed using Google Trends data (2011–2022) for England, Wales, and Scotland. Transfer function modelling with ARIMA/SARIMA models examined cross-correlations between monthly search volumes and the number of suicide deaths by both mental health patients and the general population. Results Of 448 tested lag correlations, 18 (2.0%) were statistically significant, showing small to medium effect sizes. Most significant associations involved non-specific suicide-related queries (33.3%), characteristics of suicide (22.2%), and help-seeking queries (22.2%). No pro-suicide queries showed significant associations. Concurrent positive correlations were found between search volumes for suicide ideation terms and suicide deaths by mental health patients, and between help-seeking terms and suicide deaths in the general population. Some search terms, including those related to self-poisoning methods and major suicide prevention charities, showed protective associations, with increased searches preceding decreased suicide deaths by 2–3 months. Discussion The study reveals modest associations between suicide-related search patterns and actual suicide deaths. The associations differed between mental health patients and the general population. The absence of pro-suicide query associations may reflect effective online prevention efforts in the UK. However, the small number of significant correlations indicates limited predictive utility for population-level suicide monitoring, supporting conclusions that Google Trends data alone is insufficient for predicting trends in suicide, though valuable for generating hypotheses about suicide-related internet behaviours.

A deep learning–based digital biopsy for predicting early recurrence in gastric cancer

CrackNet: A novel multi-scale architecture for crack segmentation

Crack detection is essential for structural safety inspection but remains challenging due to noise, illumination variations, and complex backgrounds. In this paper, we propose CrackNet, a segmentation network specifically designed for concrete crack detection. CrackNet integrates three key modules: a lightweight multi-scale convolution enhancement block (LightMSCBlock) in the encoder to capture both local details and global context, a SAF attention module embedded in skip connections for scale-aware feature fusion and edge refinement, and a multi-scale feature fusion (MSFF) module in the decoder to enhance feature integration while reducing information loss. Extensive experiments on three public datasets—CFD, Crack500, and DeepCrack—demonstrate that CrackNet consistently outperforms state-of-the-art methods. Specifically, on CFD, F1 and IoU improve by 6.37% and 7.1% over SegFormer; on Crack500, F1 increases by 3.86% compared with MobileNetV3-UNet; and on DeepCrack, F1 and IoU gains reach 5.7% and 2.5%, respectively. Ablation studies further confirm the complementary effectiveness of LightMSCBlock, SAF, and MSFF. Overall, CrackNet achieves superior accuracy and robustness, showing strong potential for real-world engineering applications. The code is available at the following link: https://github.com/xzz-ya/CrackNet.git

Single-nucleus brain transcriptomics reveals microglia dysfunction in multiple system atrophy

Psychology at the screen: Investigating the current VAR protocol

This study aimed to investigate the psychological process of the current Video Assistant Referee (VAR) protocol by calculating, i) the prevalence of overturn/maintain decisions by the referee at the pitch-side monitor, ii) the likelihood that the referee would overturn their decision based on external factors, iii) the likelihood that the VAR would intervene based on external factors. 1520 matches were reviewed across 2021/22–2024/25 seasons in the English Premier League where the referee was advised to consult the pitch-side monitor 250 times, overturning their original decision 95% of the time. Binary Logistic Regression found that external factors did not predict the referee’s decision or VAR intervention. The high prevalence of overturn decisions may be expected as referees are being advised to review potential errors and interestingly maintain decisions were more prevalent when related to the home team, potentially due to proximity bias of the home crowd.

Fractional crystallization of colloids by sequential tuning of depletion forces

Trends in overweight and obesity among reproductive-age women in Bangladesh: Analysis of nationally representative surveys over a decade

Background Overweight and obesity are emerging public health concerns in Bangladesh, contributing to the rising burden of non-communicable diseases. We aimed to examine trends in prevalence of overweight and obesity among reproductive-age women in Bangladesh over the past decade and assess socioeconomic inequalities in their distribution. Methods We analyzed nationally representative data from four rounds of the Bangladesh Demographic and Health Survey (BDHS) conducted in 2011, 2014, 2017–18, and 2022, including a total of 60,921 women aged 15–49 years. Body mass index (BMI) was classified using Asian-specific cut-offs. Prevalence estimates of overweight and obesity were calculated for each survey year and stratified by age, residence, educational attainment, and wealth quintile. Log-linear regression was used to estimate annual percentage changes (APC) in overweight and obesity. Socioeconomic inequality was quantified using concentration curves and Erreygers-corrected concentration indices (CIX). Results Overall prevalence of overweight and obesity increased from 13.1% in 2011 to 18.7% in 2022 (APC 3.1%), and 17.7% to 36.6% (APC 6.8%), respectively. Rural women experienced faster relative increases in both overweight (APCs 4.4% vs 1.1%).and obesity (APCs 9.2% vs 4.3%) compared with urban women. Women in the poorest and poorer wealth quintiles showed the largest APCs for obesity (14.2% and 14.1%, respectively). The CIX for overweight declined from 0.098 to 0.031, and for obesity from 0.200 to 0.141, indicating a modest reduction in inequality concentrated among wealthier groups over time. Conclusions Overweight and obesity are increasing rapidly among reproductive-age women of Bangladesh, with faster rises among rural and lower-income groups. Policies and interventions should address both overall prevalence and shifting socioeconomic patterns to reduce the future burden of non-communicable diseases.

Extending Asymmetric π-Conjugation of Vinylene-Linked Covalent Organic Frameworks with Remodeled Redox Active Sites for H ₂ O ₂ Photosynthesis and Aerobic Oxidations

Demethylation-primed tandem CD19/CD20 CAR T cells in relapsed/refractory B-cell lymphoma: a phase I/II trial

Development and validation of prediction models for predicting social care strengths and vulnerability in older people: Cohort study using routine data in Adult Social Care

In Adult Social Care, UK local authorities have statutory responsibilities for assessing needs and delivering services to ensure adults’ wellbeing. Administrative data collected during this process may help local authorities’ compliance with these duties. We developed and internally validated predictive models for older people (>- 60 years) receiving social care for whether they remained at home or were admitted to care homes, two years after index assessments, using administrative data from one English City authority. We enquired whether the right data, to predict older people’s vulnerability to adverse outcome (care home) or evidence their strengths (remaining at home), were present in local authority systems, and if accurate datasets for large numbers of older people could be constructed to allow robust modelling. Logistic regression models were created with binary outcome (remaining at home/entering care homes). Sample size calculations determined the maximum number of candidate predictors we could consider for model development. 20,218 older people in the data cohort indicated we could consider a maximum of 46 candidate predictor parameters. In our final analyses we considered 31 candidate predictor parameters, in the areas of: age, sex, ethnicity, deprivation, housing tenure, abilities in activities of daily living, access to carer, Primary Support Reason, diagnosis of dementia. We used all data for model development and internal validation using cross-validation. Models were robust as to assumptions, with no evidence of overfitting and good predictive accuracy. Circumstances predicting strongly that older people would not remain at home were that they were: from other (non-white) ethnic groups, privately rented tenants or other (unstable) tenancies, not able to eat or keep their home habitable without difficulty, with their Primary Support Reason for personal care, mental health, or support with cognition. With public involvement partners, we created a prototype index for local authority use to inform professional decisions and/or local planning.

Design of Unique Amorphous FeO _<i>x</i> Mesoporous Nanosheets for Structural–Electronic Synergy toward Highly Selective and Efficient CO ₂ Photoconversion into Multicarbon Fuels

Author Correction: A proteogenomic atlas of 1032 brain metastases identifies molecular subtypes, immune landscapes, and therapeutic vulnerabilities

Acute SARS-CoV-2 viral load and systemic inflammation are associated with neuropsychiatric and musculoskeletal symptoms in long COVID

Background Long after recovery from acute-COVID illness, many patients show persistent multi-organ dysfunction consistent with Long COVID. Biochemical profile and measurements of inflammatory markers in these individuals can help to understand the underlying pathophysiology. This study aims to evaluate biochemical markers and their association with symptoms of Long COVID. We, in a retrospective analysis, also examined whether the Long COVID symptom persistence is associated with the SARS-CoV-2 viral load documented during the acute infection. Methods A total of 300 participants with previously diagnosed mild COVID-19 were recruited at 10 months post-infection. Brief clinical history was taken based on persistent symptoms after COVID-19 and categorized as Long COVID (n = 177) and controls group (n = 123) based on WHO defined criteria. Biochemical parameters in blood like complete blood count (RBC and WBC indices) were compared between the groups. Other measurements including inflammatory markers such as IL-6, IL-10, ferritin and C-reactive protein along with electrolytes, vitamin D3 and B12, and lipid profile, were also compared. SARS-CoV-2 viral load was assessed retrospectively. Data was analyzed through SPSS v.26. Results The findings of our study revealed that 59% (177) of individuals had symptoms of Long COVID. The most frequently reported symptoms of Long COVID were related to neuropsychiatry (35%), followed by musculoskeletal system (32.2%). The Hemoglobin, RBC counts and MCHC were decreased in Long COVID as compared to control group (p &lt; 0.05). While Lymphocytes, IL-6 and ferritin levels were raised in Long COVID group (p &lt; 0.05). In multivariable logistic regression analyses adjusted for age and sex, neuropsychiatric symptoms were independently associated with higher lymphocyte counts (aOR 1.19, 95% CI 1.12–1.51), IL-6 (aOR 1.16, 95% CI 1.10–1.86), ferritin (aOR 1.42, 95% CI 1.10–1.53), and vitamin D deficiency (aOR 1.45, 95% CI 1.22–2.01). Musculoskeletal symptoms were strongly associated with vitamin D deficiency (aOR 2.30, 95% CI 1.20–4.50) and ferritin levels (aOR 0.98, 95% CI 0.97–0.99). Moreover, higher SARS-CoV-2 viral load (CT ≤ 20) during acute infection was also associated with neuropsychiatric and musculoskeletal symptoms of Long COVID. Conclusion We identified Long COVID in 59% of the participants, the highest reported percentage in studies in the middle-aged individuals. Compared to controls, we found differential biochemical markers in the Long COVID group indicating a different metabolic status in these individuals. Moreover, the association of raised inflammatory markers at ten months follow up and acute-phase SARS-CoV-2 viral load were also seen to be associated with musculoskeletal and neuropsychiatric symptoms of the Long COVID. These significant clinical and biochemical changes warrant thorough monitoring and follow-ups for extended time.

Programmable DNA Origami-Based Protease Device for Precise and Direct Proteins Degradation

Thyrotropin-releasing hormone neurons of different hypothalamic nuclei increase energy expenditure

Abstract Several neuronal populations in the hypothalamus and brainstem express thyrotropin-releasing hormone (TRH). While TRH neurons in the paraventricular nucleus (PVN) regulate the thyroid axis, the roles of other TRH-producing neurons remain largely unknown. Here we investigate the role of TRH neurons in the PVN, the dorsomedial hypothalamus (DMH), the medial preoptic area (MPA), and the rostral raphe pallidus (RPa) for metabolism in mice. Selective activation of these populations using chemogenetics in mice revealed that TRH neurons of the hypothalamus increase food intake and influence energy homeostasis in different ways. Specifically, TRH neurons in the PVN and DMH enhance brown adipose tissue activity via a polysynaptic circuit, while MPA-located neurons increase locomotor activity and maintain cold tolerance. These effects were independent of the thyroid axis, demonstrating that TRH neurons have distinct, subtype-specific ways to increase energy expenditure beyond regulating the thyroid axis in mice.