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Unprecedented Amazonian rainforests damage during the 2023–2024 droughts
Between 2023 and 2024, Amazonian rainforests experienced two consecutive, record-breaking droughts—each more intense than any previously observed—yet their impacts remain largely unquantified. Using newly developed monthly radar satellite observations (1992 to 2025) that track forest moisture and biomass dynamics, we analyzed the long-term responses of intact Amazonian rainforests to past major droughts—particularly the 2023–2024 event—and projected their post-drought recovery. We found a biome-wide sharp decline in radar signal during 2023–2024, marking the lowest level observed since 1992. Spatially, 26.8% of the forests reached their three-decade minima during this period, primarily in eastern Amazonia. This ratio is more than double that recorded during the 2005 drought, when 11.0% of the forests reached such minima. Moreover, projections based on both historical and future CMIP6 precipitation scenarios consistently indicated that, even 7 y after the 2023–2024 droughts, less than 50% of the affected areas are expected to recover to predrought conditions, and these forests are associated with lower soil cation concentrations, higher soil sand content, and lower canopy height—characteristics that lessen the risk of hydraulic failure. Given that severe droughts have occurred approximately every 7 y over the past three decades, Amazonian rainforests may face another drought before fully recovering from the 2023–2024 event. Our results therefore highlight the growing vulnerability of the Amazonian rainforests to intensifying climate extremes driven by El Niño events and ongoing anthropogenic climate change, providing evidence that these forests are approaching the limits of their preindustrial operating space.
Development of a triplex FMCA assay for genotyping three genes, ADH1B, ADH1C, and ALDH2, involved in alcohol metabolism
Abstract Three functional single nucleotide variants (SNVs)‒ ALDH2 rs671 (p.E504K), ADH1C rs698 (p.I350V), and ADH1B rs1229984 (p.R48H)‒are key genetic determinants of human alcohol metabolism. These variants significantly affect drinking behavior and are associated with liver disease and increased risks of several malignancies, including esophageal and gastric cancers. We developed a triplex fluorescent probe-based melting curve analysis (FMCA) assay for the simultaneous detection of these three SNVs. The assay was validated by comparing FMCA results with Sanger sequencing using genomic DNA from 94 Japanese individuals. The automated detection algorithm reliably identified genotypes of rs671 and rs698. Although the melting peaks of rs1229984 exhibited lower resolution and necessitated manual visual inspection for definitive genotype discrimination, all genotypes were nevertheless correctly identified. The assay demonstrated 100% accuracy. In conclusion, this triplex FMCA assay provides a rapid, cost-effective, and streamlined method for the simultaneous genotyping of ADH1B , ADH1C , and ALDH2 . Given its high accuracy and ease of implementation, this method serves as a practical alternative to conventional sequencing, positioning it as a valuable tool for both large-scale epidemiological research and routine clinical assessment of alcohol-related health risks.
Recurrent SARS-CoV-2 Omicron broadly neutralizing humanized antibodies in different single human V <sub>H</sub> 1-2-rearranging mouse models
During V(D)J recombination, antibody diversity is enhanced by nontemplated junctional modifications that generate immensely diverse heavy chain (HC) and light chain (LC) complementarity-determining 3 antigen-contact regions (CDR3s). We previously developed a mouse model that generates diverse antibody repertoires by rearranging a single human V H 1-2 and Vκ1-33, associated with highly diverse CDR3s generated by V(D)J recombination with mouse Ds and/or Js. Immunization of this model with SARS-CoV-2 D614G spike elicited an antibody that potently neutralized SARS-CoV-2 variants through Omicron BA.2.754. Here, we report a related mouse model in which a single V H 1-2 rearranges to human D3-3 and J H 6, generating diverse HC-CDR3s much longer on average than those of our prior model. Omicron BA.4/.5 spike-ferritin nanoparticle-immunization of the new model elicited four highly related humanized antibodies that potently neutralize downstream Omicron subvariants. All four antibodies had 12 AA HC-CDR3s with two aromatic amino acids that engage an epitope comprising a hydrophobic patch opened-up by early Omicron lineage mutations and conserved in subsequent variants. Immunization of our prior, shorter CDR3-based model, elicited slightly less potent neutralizing antibodies that bound the same Omicron epitope, and were similar in all other aspects to those from the long, fully human CDR3 model. One tested antibody from each set reduced lung viral titers in a mouse-adapted BQ1.1 challenge. The antibodies we describe are related in their epitope recognition to recently described antibodies from Omicron-infected humans. These studies validate the utility of single human V H - and Vκ-rearranging mice for discovering humanized antibodies that neutralize emerging pathogens.
Recognition of Brucella abortus drives M2 like polarization and impaired antigen presentation in monocyte derived macrophages
General and selective nickel-electrocatalyzed cross-electrophile C*( <i>sp</i> <sup>2</sup> )–C( <i>sp</i> <sup>2</sup> ) coupling
Transition metal-catalyzed cross-coupling of two similar electrophiles (XEC) to construct C( sp 2 )–C( sp 2 ) bonds is a powerful emerging synthetic methodology. However, efficient and selective XEC to create heterocoupled C*( sp 2 )–C( sp 2 ) linkages from equimolar reagents while suppressing competing homocoupling, presents a synthetic challenge. Here, we describe a promising approach to address this challenge via electrocatalytic synthesis. This approach utilizes renewable and readily available electricity to replace traditional redox reagents, minimizing chemical use and chemical waste generation, while controlling the reaction pathway by the applied potential. This highly selective and general electrocatalytic eXEC process to construct C*( sp 2 )–C( sp 2 ) bonds is enabled by sequential and controllable eXEC oxidative addition processes, and supported mechanistically by experiment and DFT computation. Generality and efficacy are demonstrated by more than 80 examples, including important biaryl, fluorophore, and pharmaceutical products. Notably, the stoichiometric precision of eXEC enables the first synthesis of solution-processable low polydispersity conjugated opto-electronic polymers. Therefore, this report provides a conceptually attractive method to selectively create diverse and useful C*( sp 2 )–C( sp 2 ) coupled molecules and macromolecules.
Validity and reliability of Indonesian version of the digital screen exposure questionnaire (DSEQ) for young children
Studies have shown that excessive screen time in early childhood can negatively affect development. Therefore, assessing screen exposure in young children is important for preventing these negative effects. However, only a limited number of validated and reliable tools have been adapted into the Indonesian language. This study aimed to translate, culturally adapt, and evaluate the validity and reliability of the Digital Screen Exposure Questionnaire (DSEQ) for Indonesian children aged 2–5 years. This cross-sectional study included 171 caregivers. The translation and adaptation processes followed internationally accepted guidelines for patient-reported outcomes measures, with content and face validity evaluated through expert reviews. Reliability was assessed based on the COSMIN guidelines and previous studies, with internal consistency measured using Cronbach’s alpha and test-retest reliability assessed in a subsample of 31 caregivers using the intraclass correlation coefficient (ICC). This study is the first cultural adaptation of the DSEQ in Indonesia and demonstrates good face and content validity, as confirmed by expert evaluations. Internal consistency (Cronbach’s alpha) was strong for screen-time exposure and home media environment (0.704), media-related behaviors (0.863), and physical activity (0.768), whereas test–retest reliability across the three domains was moderate to high (ICC values: 0.514–0.946), with lower ICC values observed for the item related to parental supervision while watching television, which may vary owing to differences in household routines and parental availability. These findings support the Indonesian DSEQ as a valid and reliable tool for evaluating exposure to digital screens among children.
Ecofriendly synthesis and characterization of copper chitosan nanoparticles (CuChNPs) and assessing combined effect of nanoparticles and bismerthiozol against bacterial leaf blight of rice
A high-coverage Neandertal genome from the Altai Mountains reveals population structure among Neandertals
We present a genome sequenced to ~37-fold genomic coverage from an approximately 110,000-y-old male Neandertal from Denisova Cave in the Altai Mountains and analyze it together with previously published Neandertal genomes of high quality. We show that he belonged to a population more closely related to a ~120,000-y-old Neandertal from Denisova Cave than to Neandertals in Europe or to a ~80,000-y-old Neandertal from Chagyrskaya Cave in the Altai Mountains. Both Neandertals from Denisova Cave show evidence of gene flow from Denisovans, a pattern not seen in later Neandertals from the Altai region or from Western Europe. The extent of chromosomal regions of homozygosity in Neandertals from the Altai region between 120,000 and 80,000 y ago indicates that they lived in smaller and more isolated groups than later Neandertals in Europe (54,000 to 40,000 y ago). We estimate the extent of allele frequency differentiation among Neandertal populations and find that the older Eastern Neandertals in the Altai region and younger Western Neandertals in Europe were as differentiated as the most differentiated present-day human populations worldwide.
Overexpression of miR-149 attenuates opioid-related perturbations in neural stem cell fates and serves as a translational biomarker for infants with prenatal opioid exposure
There is currently no biomarker to predict the maximum morphine dose (MMD) for newborns experiencing withdrawal from chronic prenatal opioid exposure (POE). This is due, in part, to a lack of understanding about how the developing brain is altered by chronic opioid exposure and withdrawal on a molecular level. We previously developed a human induced pluripotent stem cell-derived model of POE and withdrawal to examine the impact on neural progenitor cell fates. Here, we leveraged our model to investigate the role of two microRNAs implicated in both neural stem cell differentiation and opioid signaling: miR-149 and miR-23b. Further, we asked if these microRNAs were related to the need for morphine treatment and MMD in the saliva of infants with POE. Levels of miR-149 (One-way ANOVA, F = 34.18, p < 0.0001), but not miR-23b (One-way ANOVA, p = 0.14), were significantly decreased in human neural progenitors after chronic morphine exposure (Tukey’s, adj. p = 0.004), and decreased further in those that underwent withdrawal compared to vehicle exposed controls (Tukey’s, adj. p < 0.0001). The relevance of miR-149 to neonates experiencing withdrawal after POE was confirmed by decreased salivary levels of miR-149 compared to levels in healthy infants 24–96 hours after birth (n = 56, 28 unexposed and 28 infants with POE) (Mann-Whitney U, p < 0.0001). Stratifying infants with POE by need for pharmacotherapy revealed a further decrease in levels of miR-149 in infants that required treatment (One-way ANOVA, p < 0.0001). In a hierarchical linear regression model utilizing infant demographic factors, addition of miR-149 levels in neonatal saliva improved performance for predicting the MMD necessary for symptom control (R = 0.673, p = 0.002). These results indicate the potential relevance of miR-149 levels in infants with prenatal opioid exposure. Validation in larger cohorts is necessary.
Assessing regulatory institutions and building collapse in Lagos state, Nigeria
Archaeogenetic insights into the demographic history of Late Neanderthals
The demographic history of Neanderthals is only partially understood. In Europe, some degree of genetic continuity has been shown from 120 thousand years ago (ka) onward despite the occurrence of multiple subsequent diversification events. While it has been proposed that a population turnover preceded the emergence of Late Neanderthals in Europe, the extent, timing, and geographic location of this event are currently unknown. Here, we report ten mitochondrial DNA sequences (mtDNAs) of Neanderthal individuals from six archaeological sites in Belgium, France, Germany and Serbia, and analyze them alongside 49 published mtDNAs. The integration of phylogenetic and molecular dating analyses with an extensive archaeological dataset enabled us to reconstruct temporal and spatial patterns in Neanderthal distribution. Remarkably, nearly all Late Neanderthal individuals across Europe belong to a single mtDNA lineage that diversified recently, confirming a large-scale genetic replacement. Our analyses date this diversification event to approximately 65 ka and suggest that it likely originated from a population refugium in southwestern France from which Neanderthals appear to have undergone a major range dispersal across Europe. In addition, we detect a sharp decline in the Neanderthal mtDNA effective population size beginning ~45 ka and reaching a minimum ~42 ka, shortly before their extinction. This study demonstrates that integrating molecular and archaeological datasets provides a more detailed understanding of the Late Neanderthal population’s history, and highlights the critical role of climate-driven refugia and subsequent range expansions in shaping the genetic landscape of Neanderthals through time.
Effectiveness of virtual reality technology combined with conventional pelvic floor rehabilitation training in postpartum myofascial pelvic pain syndrome: A randomized controlled trial
Objective The aim of this study was to compare the therapeutic efficacy of integrating virtual reality technology with conventional pelvic floor rehabilitation therapy versus conventional therapy alone in postpartum women with myofascial pelvic pain syndrome. Methods Fifty-seven postpartum women diagnosed with myofascial pelvic pain syndrome were recruited for this study between March 1, 2023, and December 29, 2023. All participants were randomly assigned to two groups. The experimental group (n = 27) underwent virtual reality training combined with conventional pelvic floor rehabilitation therapy, while the control group (n = 30) received only conventional pelvic floor rehabilitation therapy. Both groups completed ten treatment sessions. Changes in pelvic floor muscle contraction function were assessed using pelvic floor surface electromyography. Musculoskeletal ultrasound was employed to measure muscle thickness and Young’s modulus of the pelvic floor muscles. The Visual Analog Scale was used to evaluate the degree of pain experienced during palpation of the pelvic floor muscles. Results The experimental group demonstrated a significant reduction in relaxation time during the fast muscle contraction stage of the pelvic floor muscle’s Glazer S-EMG ( P < 0.05). No statistically significant differences were observed in the Visual Analog Scale, pelvic floor muscle thickness, or Young’s modulus of the pelvic floor muscle during resting and maximum contraction states ( P > 0.05). Conclusion The integration of virtual reality technology with conventional pelvic floor rehabilitation therapy has the potential to improve the relaxation capacity of fast-twitch muscle fibers within the pelvic floor muscles. However, it does not seem to offer any benefits in increasing pelvic floor muscle thickness or in alleviating myofascial pelvic pain. Trial Registry The registry and the registration number: Chinese Clinical Trial Registry (number ChiCTR2300069517).
Longitudinal association of circulating inflammatory biomarkers with epigenetic ageing in the Young Finns Study
Abstract DNA methylation-based epigenetic clocks are reliable measures of biological age and aging rate. Chronic inflammation may contribute to aging and various diseases, but population-based studies on specific inflammatory biomarkers’ impact on epigenetic clocks are limited. The aim of this study was to investigate the associations between 38 circulating inflammatory biomarkers, as well as a combined systemic inflammation variable, and epigenetic clocks in a middle-aged population. The cohort included 1,327 Finnish participants (aged 30–45 years, 50–55% female) from the Young Finns Study. Biomarkers were measured in 2007, and epigenetic clocks were assessed in 2011 and 2018. DunedinPACE and PCGrimAgeDev clocks were calculated using blood methylation data. Multiple linear regression models adjusted for age, sex, BMI, smoking, socioeconomic status, alcohol consumption, and physical activity were used. Results showed 11 biomarkers positively associated with DunedinPACE across both follow-ups. Seven biomarkers were positively associated with PCGrimAgeDev in the 4-year follow-up, but not in the 11-year follow-up. The combined systemic inflammation marker was positively associated with both clocks in both follow-ups. Although previous cross-sectional studies have reported associations between pro-inflammatory cytokines and epigenetic ageing, longitudinal findings remain sparse. Our results extend this literature by showing that several cytokines predict accelerated epigenetic ageing across an 11-year follow-up.
How the 2025 NIH grant terminations varied by researchers’ demographic groups
In early 2025, the NIH unexpectedly terminated 2,291 active research grants, withdrawing $2.45 billion and disrupting thousands of projects. While the economic magnitude of these cuts is known, less is understood about how they differed across researchers’ demographic groups. Using an original dataset of publicly available records, we documented how cancelations varied by gender and career stage. Although cuts occurred across all regions and institution types, statistical patterns show that early-career investigators—assistant professors, postdoctoral scholars, trainees, and graduate students—were disproportionately affected, as were women. Women’s projects were smaller on average, had a larger share of unspent funds at cancelation, and were more concentrated in training and transition awards. Although available data cannot determine downstream causal effects, NIH economic multipliers suggest a potentially large unrealized loss to the US research enterprise. These patterns highlight the vulnerability of early-career researchers and women to abrupt funding instability and underscore the need for sustained investment to protect the future scientific workforce.
Network-constrained Random Lasso for biologically interpretable gene network inference across unequal sample sizes
Gene regulatory network inference is a key approach for elucidating molecular mechanisms underlying complex diseases, but accurately inferring them from high-dimensional data, especially when sample sizes are imbalanced, remains a significant challenge. Although the L 1 -type regularization methods have been used for gene network inference, the existing methods often fail under conditions involving high dimensionality, noise, and unequal sample sizes across phenotypes. To overcome these limitations, this study developed netRL, a novel computational framework that integrates the Random Lasso with prior network biological knowledge. The proposed method leveraged a bootstrap-based strategy to stabilize the selection of key regulatory genes and incorporates network-informed penalization using centrality measures (i.e., hubness and betweenness centrality). This study also introduced a statistical strategy using a hypergeometric test to assess the significance of the inferred edges, thereby enhancing the reliability of the network. Through extensive simulation studies, this study demonstrated that netRL outperforms conventional methods in both network estimation and gene selection. Applying netRL to whole-blood RNA-seq profiles from the Japan COVID-19 Task Force, this study successfully identified distinct phenotype-specific molecular interplays between asymptomatic and critical cases despite pronounced sample imbalance. The findings reveal that asymptomatic networks were dense and enriched for ribosomal proteins, whereas critical networks were sparse, centralized, and characterized by hub genes such as NFKBIA, B2M, CXCL8, and FOS. Pathway enrichment further revealed phenotype-specific biological processes, highlighting molecular signatures of disease progression. The results of this study suggest that enhancing the activity of asymptomatic condition-specific markers (e.g., ribosomal proteins) may provide important insights into the molecular mechanisms underlying COVID-19 severity. Collectively, these results demonstrate that netRL enables biologically interpretable and statistically robust network inference, offering new insights into the molecular basis of COVID-19 severity and broader applications in systems biology.
Pomolic acid alleviates CCl4‑induced liver fibrosis in mice by suppressing β-arrestin 2-mediated pro-fibrotic macrophage polarization
Cross-cultural evidence that shame is a defense against reputational damage
Because shame leads to evasions, aggression, and other behaviors that victims and third parties find undesirable, a prominent theory regards this emotion as maladaptive. By contrast, an alternative, adaptationist theory asks whether shame might benefit the actor. Indications that an individual now offers fewer benefits or imposes greater costs on others, if they reach others’ minds, lead the individual to be socially devalued: Others become less inclined to help and more inclined to harm her. Thus, an adaptationist theory views shame as a neurocognitive adaptation designed to minimize the leakage of reputation-damaging information and the cost of being devalued. Here, we report tests of two predictions derived from the adaptationist theory across six countries—the United States, the Netherlands, Portugal, Spain, Japan, and China—and two cultural regions within the United States—Southern states (honor) and Northern states (nonhonor). First, failures that indicate reductions in abilities more highly valued by others will elicit more intense shame. Second, failures will trigger greater shame when they occur in public rather than in private. The data supported both predictions in all six countries and in both US cultural regions. The improbable fit between the severity of the devaluative threat and the intensity of shame suggests that this emotion is an adaptation. Further, the replication of these findings across regions that vary widely along the individualism–collectivism and honor–nonhonor dimensions suggests that shame is part of human nature rather than a cultural construction.