bluuebunny/crossref_metadata_2025 huggingface dataset:
The relationships between resilience and child health behaviors in a national dataset
Authors: McMahon Ellen L. , Wallace Shelby , Samuels Lauren R. , Heerman William J.
Published: October 2024

Background

Resilience mechanisms at the individual, family, and environmental levels may improve health outcomes despite potentially harmful stress exposure partly through the practice of positive health behaviors.

Methods

We performed a secondary analysis of 2016–2021 National Survey of Children’s Health data to assess the relationships between three resilience domains – child, family, neighborhood – and six health behaviors using multiple regression models adjusted for the other resilience domain(s) and potential confounders.

Results

Analysis revealed significant associations between each resilience domain and multiple health behaviors in a total weighted analytic sample of 70,156,540 children. For each outcome, the odds of better health behaviors were highest with high resilience in all possible domains. For example, among children ages 0–5 years, the adjusted odds of having “good quality” vs. “poor quality” sleep for those with “high” resilience in all domains were 2.21 times higher (95% CI 1.78, 2.63) than for those with “low” resilience in all domains.

Conclusions

This line of research may help to inform the design of resilience and health behavior promotion interventions by targeting multiple socio-ecological domains of influence to improve health and development outcomes in children exposed to experiences or sources of potential stress.

Impact

This study assessed the associations between three socio-ecological resilience domains (child, family, and neighborhood) and six child and family health behaviors in a national dataset.

Resilience exists within multiple socio-ecological levels and supports healthy functioning despite experiencing stress. Studies in adults and limited pediatric sub-populations show associations between resilience and health behaviors, which in turn influence numerous health outcomes.

Resilience at three levels of socio-ecological levels was found to be associated with the performance of multiple child and family health behaviors in a nationally representative general pediatric population. These findings have important implications for child and family health promotion efforts.
Corynebacterium parakroppenstedtii secretes a novel glycolipid to promote the development of granulomatous lobular mastitis
Authors: Liu Ran , Luo Zixuan , Dai Chong , Wei Yuchen , Yan Shuqing , Kuang Xinwen , Qi Kuan , Fu Aisi , Li Yinxin , Fu Shuai , Ma Zhengning , Dai Wen , Xiao Xiao , Wu Qing , Zhou Haokui , Rao Yan , Yuan Jingping , Shi Ting , Deng Zixin , Chen Chuang , Liu Tiangang
Published: October 2024

Granulomatous lobular mastitis (GLM) is a chronic idiopathic granulomatous mastitis of the mammary gland characterized by significant pain and a high propensity for recurrence, the incidence rate has gradually increased, and has become a serious breast disease that should not be ignored. GLM is highly suspected relative to microbial infections, especially those of Corynebacterium species; however, the mechanisms involved are unclear, and prevention and treatment are difficult. In this study, we demonstrated the pathogenicity of Corynebacterium parakroppenstedtii in GLM using Koch’s postulates. Based on the drug sensitization results of C. parakroppenstedtii, and utilizing a retrospective study in conjunction with a comprehensive literature review, we suggested an efficacious, targeted antibiotic treatment strategy for GLM. Subsequently, we identified the pathogenic factor as a new type of glycolipid (named corynekropbactins) secreted by C. parakroppenstedtii. Corynekropbactins may chelate iron, cause the death of mammary cells and other mammary -gland-colonizing bacteria, and increase the levels of inflammatory cytokines. We further analyzed the prevalence of C. parakroppenstedtii infection in patients with GLM. Finally, we suggested that the lipophilicity of C. parakroppenstedtii may be associated with its infection route and proposed a possible model for the development of GLM. This research holds significant implications for the clinical diagnosis and therapeutic management of GLM, offering new insights into targeted treatment approaches.
Identification of KW-2449 as a dual inhibitor of ferroptosis and necroptosis reveals that autophagy is a targetable pathway for necroptosis inhibitors to prevent ferroptosis
Authors: Zhao Yaxing , Wang Qingsong , Zhu Jing , Cai Jin , Feng Xiaona , Song Qianqian , Jiang Hui , Ren Wenqing , He Yuan , Wang Ping , Feng Du , Yu Jianqiang , Liu Yue , Wu Qihui , Siriporn Jitkaew , Cai Zhenyu
Published: October 2024

Necroptosis and ferroptosis are two distinct forms of necrotic-like cell death in terms of their morphological features and regulatory mechanisms. These two types of cell death can coexist in disease and contribute to pathological processes. Inhibition of both necroptosis and ferroptosis has been shown to enhance therapeutic effects in treating complex necrosis-related diseases. However, targeting both necroptosis and ferroptosis by a single compound can be challenging, as these two forms of cell death involve distinct molecular pathways. In this study, we discovered that KW-2449, a previously described necroptosis inhibitor, also prevented ferroptosis both in vitro and in vivo. Mechanistically, KW-2449 inhibited ferroptosis by targeting the autophagy pathway. We further identified that KW-2449 functioned as a ULK1 (Unc-51-like kinase 1) inhibitor to block ULK1 kinase activity in autophagy. Remarkably, we found that Necrostatin-1, a classic necroptosis inhibitor that has been shown to prevent ferroptosis, also targets the autophagy pathway to suppress ferroptosis. This study provides the first understanding of how necroptosis inhibitors can prevent ferroptosis and suggests that autophagy is a targetable pathway for necroptosis inhibitors to prevent ferroptosis. Therefore, the identification and design of pharmaceutical molecules that target the autophagy pathway from necroptosis inhibitors is a promising strategy to develop dual inhibitors of necroptosis and ferroptosis in clinical application.
Kinetochore dynein is sufficient to biorient chromosomes and remodel the outer kinetochore
Authors: Prevo Bram , Cheerambathur Dhanya K. , Earnshaw William C. , Desai Arshad
Published: October 2024

Multiple microtubule-directed activities concentrate on mitotic chromosomes to ensure their faithful segregation. These include couplers and dynamics regulators localized at the kinetochore, the microtubule interface built on centromeric chromatin, as well as motor proteins recruited to kinetochores and chromatin. Here, we describe an in vivo approach in the C. elegans one-cell embryo in which removal of the major microtubule-directed activities on mitotic chromosomes is compared to the selective presence of individual activities. Our approach reveals that the kinetochore dynein module, comprised of cytoplasmic dynein and its kinetochore-specific adapters, is sufficient to biorient chromosomes; by contrast, this module is unable to support congression. In coordination with orientation, the dynein module directs removal of outermost kinetochore components, including dynein itself, independently of the other microtubule-directed activities and kinetochore-localized protein phosphatase 1. These observations indicate that the kinetochore dynein module is sufficient to biorient chromosomes and to direct remodeling of the outer kinetochore in a microtubule attachment state-sensitive manner.
Cancer treatment monitoring using cell-free DNA fragmentomes
Authors: van ’t Erve Iris , Alipanahi Bahar , Lumbard Keith , Skidmore Zachary L. , Rinaldi Lorenzo , Millberg Laurel K. , Carey Jacob , Chesnick Bryan , Cristiano Stephen , Portwood Carter , Wu Tony , Peters Erica , Bolhuis Karen , Punt Cornelis J. A. , Tom Jennifer , Bach Peter B. , Dracopoli Nicholas C. , Meijer Gerrit A. , Scharpf Robert B. , Velculescu Victor E. , Fijneman Remond J. A. , Leal Alessandro
Published: October 2024

Circulating cell-free DNA (cfDNA) assays for monitoring individuals with cancer typically rely on prior identification of tumor-specific mutations. Here, we develop a tumor-independent and mutation-independent approach (DELFI-tumor fraction, DELFI-TF) using low-coverage whole genome sequencing to determine the cfDNA tumor fraction and validate the method in two independent cohorts of patients with colorectal or lung cancer. DELFI-TF scores strongly correlate with circulating tumor DNA levels (ctDNA) (r = 0.90, p < 0.0001, Pearson correlation) even in cases where mutations are undetectable. DELFI-TF scores prior to therapy initiation are associated with clinical response and are independent predictors of overall survival (HR = 9.84, 95% CI = 1.72-56.10, p < 0.0001). Patients with lower DELFI-TF scores during treatment have longer overall survival (62.8 vs 29.1 months, HR = 3.12, 95% CI 1.62-6.00, p < 0.001) and the approach predicts clinical outcomes more accurately than imaging. These results demonstrate the potential of using cfDNA fragmentomes to estimate tumor burden in cfDNA for treatment response monitoring and clinical outcome prediction.
Multi-parametric thrombus profiling microfluidics detects intensified biomechanical thrombogenesis associated with hypertension and aging
Authors: Din Misbahud , Paul Souvik , Ullah Sana , Yang Haoyi , Xu Rong-Guang , Abidin Nurul Aisha Zainal , Sun Allan , Chen Yiyao Catherine , Gao Rui , Chowdhury Bari , Zhou Fangyuan , Rogers Stephenie , Miller Mariel , Biswas Atreyee , Hu Liang , Fan Zhichao , Zahner Christopher , Fan Jing , Chen Zi , Berman Megan , Xue Lingzhou , Ju Lining Arnold , Chen Yunfeng
Published: October 2024

Arterial thrombosis is a leading cause of death and disability worldwide with no effective bioassay for clinical prediction. As a symbolic feature of arterial thrombosis, severe stenosis in the blood vessel creates a high-shear, high-gradient flow environment that facilitates platelet aggregation towards vessel occlusion. Here, we present a thrombus profiling assay that monitors the multi-dimensional attributes of thrombi forming in such biomechanical conditions. Using this assay, we demonstrate that different receptor–ligand interactions contribute distinctively to the composition and activation status of the thrombus. Our investigation into hypertensive and older individuals reveals intensified biomechanical thrombogenesis and multi-dimensional thrombus profile abnormalities, endorsing the diagnostic potential of the assay. Furthermore, we identify the hyperactivity of GPIbα-integrin αIIbβ3 mechanosensing axis as a molecular mechanism that contributes to hypertension-associated arterial thrombosis. By studying drug-disease interactions and inter-individual variability, our work reveals a need for personalized anti-thrombotic drug selection that accommodates each patient’s pathological profile.
Developmental mouse brain common coordinate framework
Authors: Kronman Fae N. , Liwang Josephine K. , Betty Rebecca , Vanselow Daniel J. , Wu Yuan-Ting , Tustison Nicholas J. , Bhandiwad Ashwin , Manjila Steffy B. , Minteer Jennifer A. , Shin Donghui , Lee Choong Heon , Patil Rohan , Duda Jeffrey T. , Xue Jian , Lin Yingxi , Cheng Keith C. , Puelles Luis , Gee James C. , Zhang Jiangyang , Ng Lydia , Kim Yongsoo
Published: October 2024

3D brain atlases are key resources to understand the brain’s spatial organization and promote interoperability across different studies. However, unlike the adult mouse brain, the lack of developing mouse brain 3D reference atlases hinders advancements in understanding brain development. Here, we present a 3D developmental common coordinate framework (DevCCF) spanning embryonic day (E)11.5, E13.5, E15.5, E18.5, and postnatal day (P)4, P14, and P56, featuring undistorted morphologically averaged atlas templates created from magnetic resonance imaging and co-registered high-resolution light sheet fluorescence microscopy templates. The DevCCF with 3D anatomical segmentations can be downloaded or explored via an interactive 3D web-visualizer. As a use case, we utilize the DevCCF to unveil GABAergic neuron emergence in embryonic brains. Moreover, we map the Allen CCFv3 and spatial transcriptome cell-type data to our stereotaxic P56 atlas. In summary, the DevCCF is an openly accessible resource for multi-study data integration to advance our understanding of brain development.
Confidence control for efficient behaviour in dynamic environments
Authors: Balsdon Tarryn , Philiastides Marios G.
Published: October 2024

Signatures of confidence emerge during decision-making, implying confidence may be of functional importance to decision processes themselves. We formulate an extension of sequential sampling models of decision-making in which confidence is used online to actively moderate the quality and quantity of evidence accumulated for decisions. The benefit of this model is that it can respond to dynamic changes in sensory evidence quality. We highlight this feature by designing a dynamic sensory environment where evidence quality can be smoothly adapted within the timeframe of a single decision. Our model with confidence control offers a superior description of human behaviour in this environment, compared to sequential sampling models without confidence control. Using multivariate decoding of electroencephalography (EEG), we uncover EEG correlates of the model’s latent processes, and show stronger EEG-derived confidence control is associated with faster, more accurate decisions. These results support a neurobiologically plausible framework featuring confidence as an active control mechanism for improving behavioural efficiency.
Ethane-oxidising archaea couple CO2 generation to F420 reduction
Authors: Lemaire Olivier N. , Wegener Gunter , Wagner Tristan
Published: October 2024

The anaerobic oxidation of alkanes is a microbial process that mitigates the flux of hydrocarbon seeps into the oceans. In marine archaea, the process depends on sulphate-reducing bacterial partners to exhaust electrons, and it is generally assumed that the archaeal CO2-forming enzymes (CO dehydrogenase and formylmethanofuran dehydrogenase) are coupled to ferredoxin reduction. Here, we study the molecular basis of the CO2-generating steps of anaerobic ethane oxidation by characterising native enzymes of the thermophile Candidatus Ethanoperedens thermophilum obtained from microbial enrichment. We perform biochemical assays and solve crystal structures of the CO dehydrogenase and formylmethanofuran dehydrogenase complexes, showing that both enzymes deliver electrons to the F420 cofactor. Both multi-metalloenzyme harbour electronic bridges connecting CO and formylmethanofuran oxidation centres to a bound flavin-dependent F420 reductase. Accordingly, both systems exhibit robust coupled F420-reductase activities, which are not detected in the cell extract of related methanogens and anaerobic methane oxidisers. Based on the crystal structures, enzymatic activities, and metagenome mining, we propose a model in which the catabolic oxidising steps would wire electron delivery to F420 in this organism. Via this specific adaptation, the indirect electron transfer from reduced F420 to the sulphate-reducing partner would fuel energy conservation and represent the driving force of ethanotrophy.
Direct and lagged climate change effects intensified the 2022 European drought
Authors: Bevacqua Emanuele , Rakovec Oldrich , Schumacher Dominik L. , Kumar Rohini , Thober Stephan , Samaniego Luis , Seneviratne Sonia I. , Zscheischler Jakob
Published: October 2024

In 2022, Europe faced an extensive summer drought with severe socioeconomic consequences. Quantifying the influence of human-induced climate change on such an extreme event can help prepare for future droughts. Here, by combining observations and climate model outputs with hydrological and land-surface simulations, we show that Central and Southern Europe experienced the highest observed total water storage deficit since satellite observations began in 2002, probably representing the highest and most widespread soil moisture deficit in the past six decades. While precipitation deficits primarily drove the soil moisture drought, human-induced global warming contributed to over 30% of the drought intensity and its spatial extent via enhanced evaporation. We identify that 14–41% of the climate change contribution was mediated by the warming-driven drying of the soil that occurred before the hydrological year of 2022, indicating the importance of considering lagged climate change effects to avoid underestimating associated risks. Human-induced climate change had qualitatively similar effects on the extremely low observed river discharges. These results highlight that global warming effects on droughts are already underway, widespread and long lasting, and that drought risk may escalate with further human-induced warming in the future.
Fight or flight alternative mating tactics may explain the iconic male polymorphism of the European stag beetle
Authors: Giannetti Daniele , Schifani Enrico , Rolli Enrico , Fior Emanuele , Pasquali Benedetta , Campanaro Alessandro , Grasso Donato A.
Published: October 2024

The existence of different male morphologies within a single species is associated with alternative mating tactics across different animal groups, offering textbook examples of evolutionary biology. The European stag beetle Lucanus cervus is a flagship species which has long fascinated naturalists for its charismatic appearance and behavior, with males possessing large mandibles used in ritualized ground fights for females. Males are polymorphic, with larger males possessing disproportionately larger mandibles and being better fighters, while smaller males require less food to develop and may have better chances to escape predation. We discovered an alternative mating tactic that opens a new interpretation on the evolution of the smaller males, based on aggregations of flying males competing to catch flying females in mid-air. Flight aggregations occur earlier in the season and in sites with sparser canopy cover as compared to ground fight aggregations, but most importantly, smaller males tend to prevail due to their greater agility in flight. Competition between males is crucial for reproductive success in this species, and alternative mating tactics involving flight were unknown in beetles, advocating for further research on the ecology and evolution of the iconic male polymorphism of stag beetles.
Predictive machine learning models for anticipating loss to follow-up in tuberculosis patients throughout anti-TB treatment journey
Authors: Chen Jingfang , Jiang Youli , Li Zhihuan , Zhang Mingshu , Liu Linlin , Li Ao , Lu Hongzhou
Published: October 2024

Loss to follow-up (LTFU) in tuberculosis (TB) management increases morbidity and mortality, challenging effective control strategies. This study aims to develop and evaluate machine learning models to predict loss to follow-up in TB patients, improving treatment adherence and outcomes. Retrospective data encompassing tuberculosis patients who underwent treatment or registration at the National Center for Clinical Medical Research on Infectious Diseases from January 2017 to December 2021 were compiled. Employing machine learning techniques, namely SVM, RF, XGBoost, and logistic regression, the study aimed to prognosticate LTFU. A comprehensive cohort of 24,265 tuberculosis patients underwent scrutiny, revealing a LTFU prevalence of 12.51% (n = 3036). Education level, history of hospitalization, alcohol consumption, outpatient admission, and prior tuberculosis history emerged as precursors for pre-treatment LTFU. Employment status, outpatient admission, presence of chronic hepatitis/cirrhosis, drug adverse reactions, alternative contact availability, and health insurance coverage exerted substantial influence on treatment-phase LTFU. XGBoost consistently surpassed alternative models, boasting superior discriminative ability with an average AUC of 0.921 for pre-treatment LTFU and 0.825 for in-treatment LTFU. Our study demonstrates that the XGBoost model provides superior predictive performance in identifying LTFU risk among tuberculosis patients. The identification of key risk factors highlights the importance of targeted interventions, which could lead to significant improvements in treatment adherence and patient outcomes.
An open-access dashboard to interrogate the genetic diversity of Mycobacterium tuberculosis clinical isolates
Authors: Phelan Jody , Van den Heede Klaas , Masyn Serge , Verbeeck Rudi , Lamprecht Dirk A. , Koul Anil , Wall Richard J.
Published: October 2024

Tuberculosis (TB) remains one of the leading infectious disease killers in the world. The ongoing development of novel anti-TB medications has yielded potent compounds that often target single sites with well-defined mechanisms of action. However, despite the identification of resistance-associated mutations through target deconvolution studies, comparing these findings with the diverse Mycobacterium tuberculosis populations observed in clinical settings is often challenging. To address this gap, we constructed an open-access database encompassing genetic variations from > 50,000 clinical isolates, spanning the entirety of the M. tuberculosis protein-encoding genome. This resource offers a valuable tool for investigating the prevalence of target-based resistance mutations in any drug target within clinical contexts. To demonstrate the practical application of this dataset in drug discovery, we focused on drug targets currently undergoing phase II clinical trials. By juxtaposing genetic variations of these targets with resistance mutations derived from laboratory-adapted strains, we identified multiple positions across three targets harbouring resistance-associated mutations already present in clinical isolates. Furthermore, our analysis revealed a discernible correlation between genetic diversity within each protein and their predicted essentiality. This meta-analysis, openly accessible via a dedicated dashboard, enables comprehensive exploration of genetic diversity pertaining to any drug target or resistance determinant in M. tuberculosis.
A hybrid approach of vision transformers and CNNs for detection of ulcerative colitis
Authors: Shah Syed Abdullah , Taj Imran , Usman Syed Muhammad , Hassan Shah Syed Nehal , Imran Ali Shariq , Khalid Shehzad
Published: October 2024

Ulcerative Colitis is an Inflammatory Bowel disease caused by a variety of factors that lead to a serious impact on the quality of life of the patients if left untreated. Due to complexities in the identification procedures of this disease, the treatment timeline and quality can be severely affected, leading to further consequences for the sufferer. The difficulties in identification are due to high patients to healthcare professionals ratio. Researchers have proposed variety of machine/deep learning methods for automated detection of ulcerative colitis, however, several challenges exists including class imbalance problem, comprehensive feature extraction and accurate classification. We propose a novel method for accurate detection of ulcerative colitis with augmentation techniques to overcome class imbalance issue, a comprehensive feature vector extraction using custom architecture of Vision Transformer (ViT) and accurate classification using customized Convolutional Neural Network (CNN). We used the TMC-UCM and LIMUC datasets in this research for training and testing of proposed method and achieved accuracy of 90% with AUC-ROC scores of 0.91, 0.81, 0.94, and 0.94 for the endoscopic classes of Mayo 0, Mayo 1, Mayo 2, and Mayo 3 respectively. We have compared the proposed method with existing state of the art methods and conclude that the proposed method outperforms the existing methods.
Empowering consumers to purchase safe ready-to-eat chicken from street restaurants in Ouagadougou, Burkina Faso: impact of a multi-media behavior change campaign
Authors: Madjdian Donya S. , van Asseldonk Marcel , Talsma Elise F. , Dione Michel , Ilboudo Guy , Roesel Kristina , Grace Delia , Knight-Jones Theodore J.D. , de Vet Emely
Published: October 2024

Foodborne disease resulting from food sold at urban informal markets is a major public health challenge in Sub-Saharan Africa. This study assessed the impact of an innovative nine-months multi-media campaign engaging a key influencer, aimed at empowering consumers to choose safer ready-to-eat chicken meat at informal street restaurants in Ouagadougou, Burkina Faso. A two-wave panel study assessed associations between recall of TV, radio, billboard, and social media advertisements, and self-reported behavior regarding purchasing and consumption of ready-to-eat chicken at outlets, consumer intentions, knowledge, attitudes, norms, and agency. A panel of randomly selected adult consumers (n = 852) were interviewed pre- and post-campaign, 12 months apart. 60% recalled at least one of the campaign channels when prompted. Mixed-effects models showed associations between prompted recall and feeling better informed about food safety (aOR 1.449) and increased knowledge (0.132 unit increase on total score). Social media recall was associated with higher perceived access to information (aOR 1.449) and knowledge. Billboard recall increased odds of higher perceived health benefits of paying attention to food safety behaviors when purchasing chicken (aOR 2.046). TV ad recall was associated with a 0.159 unit decrease in the gap between consumers’ intentions and behavior. An engaging consumer food safety multimedia campaign that engages key influencers improved food safety awareness and knowledge, ultimately supporting consumers to choose safer chicken at markets.
Significant role of secondary electrons in the formation of a multi-body chemical species spur produced by water radiolysis
Authors: Kai Takeshi , Toigawa Tomohiro , Matsuya Yusuke , Hirata Yuho , Tezuka Tomoya , Tsuchida Hidetsugu , Yokoya Akinari
Published: October 2024

Scientific insights into water photolysis and radiolysis are essential for estimating the direct and indirect effects of deoxyribonucleic acid (DNA) damage. Secondary electrons from radiolysis intricately associated with both effects. In our previous paper, we simulated the femtosecond (1 × 10− 15 s) dynamics of secondary electrons ejected by energy depositions of 11−19 eV into water via high-energy electron transport using a time-dependent simulation code. The results contribute to the understanding of simple “intra-spur” chemical reactions of tree-body chemical species (hydrated electrons, hydronium ion and OH radical) in subsequent chemical processes. Herein, we simulate the dynamics of the electrons ejected by energy depositions of 20−30 eV. The present results contribute to the understanding of complex “inter-spur” chemical reactions of the multi-body chemical species as well as for the formation of complex DNA damage with redox site and strand break on DNA. The simulation results present the earliest formation mechanism of an unclear multi-body chemical species spur when secondary electrons induce further ionisations or electronic excitations. The formation involves electron–water collisions, i.e. ionisation, electronic excitation, molecular excitation and elastic scattering. Our simulation results indicate that (1) most secondary electrons delocalise to ~ 12 nm, and multiple collisions are sometimes induced in a water molecule at 22 eV deposition energy. (2) The secondary electrons begin to induce diffuse band excitation of water around a few nm from the initial energy deposition site and delocalise to ~ 8 nm at deposition energies ~ 25 eV. (3) The secondary electron can cause one additional ionisation or electronic excitation at deposition energies > 30 eV, forming a multi-body chemical species spur. Thus, we propose that the type and density of chemical species produced by water radiolysis strongly depend on the deposition energy. From our results, we discuss formation of complex DNA damage.
Measuring instability in chronic human intracortical neural recordings towards stable, long-term brain-computer interfaces
Authors: Pun Tsam Kiu , Khoshnevis Mona , Hosman Tommy , Wilson Guy H. , Kapitonava Anastasia , Kamdar Foram , Henderson Jaimie M. , Simeral John D. , Vargas-Irwin Carlos E. , Harrison Matthew T. , Hochberg Leigh R.
Published: October 2024

Intracortical brain-computer interfaces (iBCIs) enable people with tetraplegia to gain intuitive cursor control from movement intentions. To translate to practical use, iBCIs should provide reliable performance for extended periods of time. However, performance begins to degrade as the relationship between kinematic intention and recorded neural activity shifts compared to when the decoder was initially trained. In addition to developing decoders to better handle long-term instability, identifying when to recalibrate will also optimize performance. We propose a method, “MINDFUL”, to measure instabilities in neural data for useful long-term iBCI, without needing labels of user intentions. Longitudinal data were analyzed from two BrainGate2 participants with tetraplegia as they used fixed decoders to control a computer cursor spanning 142 days and 28 days, respectively. We demonstrate a measure of instability that correlates with changes in closed-loop cursor performance solely based on the recorded neural activity (Pearson r = 0.93 and 0.72, respectively). This result suggests a strategy to infer online iBCI performance from neural data alone and to determine when recalibration should take place for practical long-term use.
Forecasting trends in food security with real time data
Authors: Herteux Joschka , Raeth Christoph , Martini Giulia , Baha Amine , Koupparis Kyriacos , Lauzana Ilaria , Piovani Duccio
Published: October 2024

Early warning systems are an essential tool for effective humanitarian action. Advance warnings on impending disasters facilitate timely and targeted response which help save lives and livelihoods. In this work we present a quantitative methodology to forecast levels of food consumption for 60 consecutive days, at the sub-national level, in four countries: Mali, Nigeria, Syria, and Yemen. The methodology is built on publicly available data from the World Food Programme’s global hunger monitoring system which collects, processes, and displays daily updates on key food security metrics, conflict, weather events, and other drivers of food insecurity. In this study we assessed the performance of various models including Autoregressive Integrated Moving Average (ARIMA), Extreme Gradient Boosting (XGBoost), Long Short Term Memory (LSTM) Network, Convolutional Neural Network (CNN), and Reservoir Computing (RC), by comparing their Root Mean Squared Error (RMSE) metrics. Our findings highlight Reservoir Computing as a particularly well-suited model in the field of food security given both its notable resistance to over-fitting on limited data samples and its efficient training capabilities. The methodology we introduce establishes the groundwork for a global, data-driven early warning system designed to anticipate and detect food insecurity.
Osmotic signaling releases PP2C-mediated inhibition of Arabidopsis SnRK2s via the receptor-like cytoplasmic kinase BIK1
Authors: Li Guo-Jun , Chen Kong , Sun Shujing , Zhao Yang
Published: October 2024

Osmotic stress and abscisic acid (ABA) signaling are important for plant growth and abiotic stress resistance. Activation of osmotic and ABA signaling downstream of the PYL-type ABA receptors requires the release of SnRK2 protein kinases from the inhibition imposed by PP2Cs. PP2Cs are core negative regulators that constantly interact with and inhibit SnRK2s, but how osmotic signaling breaks the PP2C inhibition of SnRK2s remains unclear. Here, we report that an Arabidopsis receptor-like cytoplasmic kinase, BIK1, releases PP2C-mediated inhibition of SnRK2.6 via phosphorylation regulation. The dominant abi1-1 ABA-signaling mutation (G180D) disrupts PYL-PP2C interactions and disables PYL-initiated release of SnRK2s; in contrast, BIK1 releases abi1-1-mediated inhibition of SnRK2.6. BIK1 interacts with and phosphorylates SnRK2.6 at two tyrosine residues, which are critical for SnRK2.6 activation and function. Phosphorylation of the two tyrosine residues may affect the docking of the tryptophan “lock” of PP2C into SnRK2.6. Moreover, the bik1 mutant is defective in SnRK2 activation, stress-responsive gene expression, ABA accumulation, growth maintenance, and water loss under osmotic stress. Our findings uncover the critical role of BIK1 in releasing PP2C-mediated inhibition of SnRK2s under osmotic stress.
Reusable Co-catalysts for general and selective α-alkylation of nitriles with alcohols
Authors: Ma Zhuang , Wu Zechen , Kreyenschulte Carsten , Bartling Stephan , Lund Henrik , Beller Matthias , Jagadeesh Rajenahally V.
Published: October 2024

A general cobalt-catalyzed α-alkylation of nitriles with alcohols is reported.
Exploring a low-cost turbidimetric sensor for available potassium determination in soil
Authors: Pereira Cristian Kelling , Viana Ana Barbosa , Macedo Adrean Arruda , Pardinho Renan Buque , Vecchia Paula Dalla , Dressler Valderi Luiz
Published: October 2024

A low cost turbidimetric sensor was developed and applied for available potassium determination in soil.
Magnetically induced localized heating enabling rapid and efficient synthesis of metal–organic frameworks
Authors: Kapoor Mansi , Dussa Saikumar , Dahotre Narendra B. , Verma Gaurav , Ma Shengqian
Published: October 2024

A rapid, energy-efficient method is demonstrated for synthesizing metal–organic frameworks via magnetic induction heating with superparamagnetic iron oxide nanoparticles that produces three benchmark MOFs in good yields with high crystallinity.
Synthesis and Frizzled-receptor binding of a WNT5A hairpin-3 peptide
Authors: Hei Yuanyuan , Hu Qinli , Manisa Berti , Li Xiaochun , Wang Boyuan
Published: October 2024

We synthesized the three-disulfide crosslinked hairpin-3 from Wnt proteins as a peptide ligand for Frizzled.
Pivotal role of starch in restoring the photocatalytic performance of chitosan films for eliminating water pollutants
Authors: Chauhan Aman , Negi Archana , Kirti  , Chauhan Moondeep , Kaushik Ajeet , Chaudhary Ganga Ram
Published: October 2024

The enhanced adsorption properties of chitosan films after starch impregnation combined with the excellent charge-transfer traits of the CdS@CuS catalyst restore the reduced photocatalytic activity towards ciprofloxacin degradation.
Sulfonated hierarchical ZSM-5 zeolite monoliths as solid acid catalyst for esterification of oleic acid
Authors: Zhao Binhang , Yang Pan , Zhang Nan , Inns Donald R. , Kozhevnikova Elena F. , Katsoulidis Alexandros P. , Kozhevnikov Ivan V. , Steiner Alexander , Zhang Haifei
Published: October 2024

Sulfonated hierarchical H-ZSM-5 monoliths were synthesized via ice-templating as solid acid catalysts for biodiesel production.
Photoluminescent ruthenium(ii) bipyridyl complexes containing phosphonium ylide ligands
Authors: Fayafrou Oussama , Lognon Elise , Duhayon Carine , Sortais Jean-Baptiste , Monari Antonio , Baslé Olivier , Canac Yves
Published: October 2024

An unprecedented photoluminescent phosphonium ylide Ru(ii) bipyridyl complex was reported to be active in visible-light photocatalyzed single electron and energy transfer processes.
Ultrasmall RuO2/CoFe2O4 nanoparticles with robust interfacial interactions for the enhanced acidic oxygen evolution reaction
Authors: Wei Ming , Mu Liuhua , Liu Zhiwei , Gao Feng , Song Guangjian , Si Qiankang , Zhang Mao , Dai Fangfang , Zhang Min , Ding Rui , Yang Li , Gao Zhonggui , Song Sanzhao
Published: October 2024

Ultrasmall RuO2/CoFe2O4 nanoparticles with strong interfacial interactions exhibit enhanced oxygen evolution reaction (OER) performance, driven by efficient charge transfer between RuO2 and CoFe2O4.
An acidity-triggered aggregation nanoplatform based on degradable mesoporous organosilica nanoparticles for precise drug delivery and phototherapy of focal bacterial infection
Authors: Huang Yunhan , Guo Wei , Wang Xinyu , Chang Jingrui , Lu Bo
Published: October 2024

An acidity-triggered aggregation antibacterial nanoplatform based on biodegradable mesoporous organic silica nanoparticles, is reported. It enables precise drug release and spatial accuracy for photodynamic therapy and photothermal therapy.
Catalytic partial oxidation of methane over oxide-ion-conductive lanthanum silicate apatites
Authors: Pamungkas Afif , Goto Yuta , Murata Kazumasa , Hosokawa Saburo , Ogawa Satoshi , Ohishi Kosaku , Matsumoto Tomohiro , Saito Miwa , Motohashi Teruki
Published: October 2024

The oxide-ion-conductive lanthanum silicate La9.33Si6O26 with an apatite-type structure exhibits high activity for the catalytic partial oxidation of methane (CPOX).
Reactivity of Mg(AlMe4)2 towards neutral tris(pyrazolyl)alkanes
Authors: Kracht Felix , Stuhl Christoph , Maichle-Mössmer Cäcilia , Anwander Reiner
Published: October 2024

Depending on the substitution pattern of tris(pyrazoyl)alkanes, cationic complexes [(MeCTp3-R)Mg(AlMe4)][AlMe4] can be accessed that reversibly release AlMe3.
Emerging investigator series: open dumping and burning: an overlooked source of terrestrial microplastics in underserved communities
Authors: Hess Kendra Z. , Forsythe Kyle R. , Wang Xuewen , Arredondo-Navarro Andrea , Tipling Gwen , Jones Jesse , Mata Melissa , Hughes Victoria , Martin Christine , Doyle John , Scott Justin , Minghetti Matteo , Jilling Andrea , Cerrato José M. , El Hayek Eliane , Gonzalez-Estrella Jorge
Published: October 2024

Open dumping and burning of solid waste are widely practiced in underserved communities lacking access to solid waste management facilities. The generation of microplastics from these sites has been overlooked.
Weathering pathways differentially affect colloidal stability of nanoplastics
Authors: Cao Tianchi , Zhao Mengting , Zhang Tong , Chen Wei
Published: October 2024

This study demonstrates that environmental weathering processes differentially affect the aggregation behavior of nanoplastics, providing important insights into the risk assessment of nanoplastics contamination.
Effective separation of metal impurities from gypsum nanosludge: synergism of mechanical force and metal species regulation
Authors: Weng Changzhou , Zheng Zhengqiang , Tian Chen , Lin Zhang
Published: October 2024

A novel and sustainable method combining mechanical force and species regulation enables a two-step dehydration–rehydration process, achieving full extraction of impurities like P, or heavy metals like Cr, As, Sr, Cd, and Hg from gypsum waste.
Two-dimensional multifunctional metal–organic frameworks with large in-plane negative Poisson ratios and photocatalytic water splitting properties
Authors: Lin Wei , Wang Huimiao , Luo Yaling , Liu Xiaofeng , Li ZhongJun , Zhu Weiduo , Li Xingxing , Chen Zhao , Wang Haidi
Published: October 2024

Two-dimensional auxetic materials designed based on metal–organic frameworks.
Unveiling the catalytic potency of a novel hydrazone-linked covalent organic framework for the highly efficient one-pot synthesis of 1,2,4-triazolidine-3-thiones
Authors: Teli Pankaj , Soni Shivani , Teli Sunita , Agarwal Shikha
Published: October 2024

Synthesis of 1,2,4-triazolidine-3-thiones using a novel hydrazone-linked covalent organic framework (TRIPOD-DHTH COF) as a catalyst at room temperature.
Visible light-driven, persulfate-mediated dual C–H sulfenylation of imidazopyridines using thiocyanate salt
Authors: Saha Pallavi , Kumar Vijay , Sharma Deepak K
Published: October 2024

We present a visible light-mediated dual C–H sulfenylation of imidazopyridines using thiocyanate salt as a sulfur source.
Great wall structure inspired 2D@2D hetero-layered W-doped MoS2 for an enhanced hydrogen evolution reaction
Authors: Ma Sainan , Yan Qing , Gui Huiqin , Gao Ruiqin , Zhang Luohuan , Bai Xiaojing , Cheng Kui
Published: October 2024

Great Wall structure inspired 2D@2D hetero-layered W-doped MoS2 is synthesized and characterized as an efficient electrocatalyst for the hydrogen evolution reaction.
In situ three-dimensional observation of plasticity onset in a Pt nanoparticle
Authors: Yehya Sarah , Cornelius Thomas W. , Richard Marie-Ingrid , Berenguer Felisa , Levi Mor , Rabkin Eugen , Thomas Olivier , Labat Stéphane
Published: October 2024

Combining in situ nano indentation and Bragg Coherent X-ray Diffraction Imaging reveal prismatic dislocation loops nucleation in a Pt nanoparticle. This sets a new strength record for Pt with a shear stress of 6.4 GPa found at the onset of plasticity.
Characterization of neutral metal hydride–hydroxide hydrogen-bonded clusters HMOH(H2O)2 (M = Al and Ga)
Authors: Yan Wenhui , Zheng Huijun , Wang Tiantong , Jiang Shuai , Li Shangdong , Zhuang Jianxing , Xie Hua , Li Gang , Jiang Ling
Published: October 2024

Characterization of neutral metal hydride–hydroxide hydrogen-bonded clusters HMOH(H2O)2 (M = Al and Ga) using infrared-vacuum ultraviolet spectroscopy combined with quantum chemical calculations.
One-pot synthesis of heterostructured CsPbBr3/PdSe nanowires with excellent humidity stability
Authors: Ye Shuai , Huang Mingyi , Song Jun , Qu Junle
Published: October 2024

CsPbBr3@PdSe nanowires were prepared by a one-pot solution process and demonstrated excellent humidity stability. Approximately 95% of their PL intensity was retained after 30 days’ exposure to air.
The CF3TMS adduct of anthraquinone as a monomer for making polymers with potential as separation membranes
Authors: Wu Kim Jiayi , Tobin John M. , Ji Anli , Shi Yang , Ye Chunchun , Nichol Gary S. , Fuoco Alessio , Longo Mariagiulia , Jansen Johannes C. , McKeown Neil B.
Published: October 2024

The CF3TMS adduct of anthraquinone reacts with diphenyl ether via a superacid-catalysed step-growth polymerisation to give a polymer (BTFMA-DPE) with promise for making gas separation membranes.
Novel PPAR-γ agonists as potential neuroprotective agents against Alzheimer's disease: rational design, synthesis, in silico evaluation, PPAR-γ binding assay and transactivation and expression studies
Authors: D. Priya , Hani Umme , Haider Nazima , Talath Sirajunisa , Shanmugarajan Dhivya , P. Prabitha , P. Archana , Prashantha Kumar B. R.
Published: October 2024

The potential use of novel PPAR-γ agonists in the treatment of Alzheimer's disease.
Application of kartogenin for the treatment of cartilage defects: current practice and future directions
Authors: Liu Xuemiao , Liu Pengfei , Li Han , Cen Ying , Jiang Guichun , Zhang Weiguo , Tian Kang , Wang Xing
Published: October 2024

Synthesis and decomposition of KGN molecule.
Synthesis, characterization and application of silk sericin-based silver nanocomposites for antibacterial and food coating solutions
Authors: Shaw Shubhajit , Mondal Rittick , Dam Paulami , Mandal Avijit , Acharya Ritwik , Manna Sanjeet , Gangopadhyay Debnirmalya , Mandal Amit Kumar
Published: October 2024

The rising demand for fresh and safe food is driving advancements in preservation technologies, with nanoparticles offering a revolutionary solution.
Scalable electrocatalyzed formation of C–O bonds using flow reactor technology
Authors: Prieschl Michael , Cantillo David , Kappe C. Oliver , Laudadio Gabriele
Published: October 2024

A scalable C–O bond formation via continuous-flow Ni-electrocatalysis was developed, enabling the gram-scale preparation of a key delamanid intermediate, a pharmaceutical used to treat multidrug-resistant tuberculosis.
Exonuclease-assisted enrichment and base resolution analysis of pseudouridine in single-stranded RNA
Authors: Fang Xin , Lu Ziang , Wang Yafen , Zhao Ruiqi , Mo Jing , Yang Wei , Sun Mei , Zhou Xiang , Weng Xiaocheng
Published: October 2024

We developed RIPS for identification of Ψ sites with a higher signal-to-noise ratio by combining the CMC specific labeling and exonuclease digestion. What's more, we selectively identified Ψ sites in single-stranded RNA by applying RIPS.
A high entropy metallic–high entropy nonmetallic community as a high performance electrocatalyst for the oxygen evolution reaction and oxygen reduction reaction
Authors: Zhang Chunyan , Li Hang , Su Mengfei , Li Shengfa , Gao Feng , Lu Qingyi
Published: October 2024

A unique high entropy metallic–high entropy nonmetallic community (HEM–HENMC) in which five metals (Cr, Mn, Fe, Co and Ni) and five non-metals (C, N, O, P and S) co-exist is fabricated as efficient electrocatalyst by a high entropy precursor method.
Unlocking the potential of Ti3C2 electrodes: a data-driven capacitance prediction study
Authors: Krishna Sanjith , Mir Afkham
Published: October 2024

This study pioneers the use of machine learning to predict Ti3C2 supercapacitor capacitance, evaluating KNN, ANN, and BRR models and uncovering key factors like cation mobility and scan rate that influence performance, with robust accuracy.
Joint antenna selection and resource allocation for mm‐wave directional D2D communications using distributed deep reinforcement learning
Authors: Akhoundzadeh Pouya , Mirjalily Ghasem
Published: October 2024

In this paper, with the promising assumption of using adaptive directional microstrip antenna on user equipment, the problem of joint antenna selection, spectrum assignment, and transmit power allocation for mm‐wave device‐to‐device communications underlying cellular networks is tackled, with the goal of enhancing system throughput and energy efficiency. To address the complexity of this problem, a method based on multi‐agent distributed deep reinforcement learning in which an autonomous intelligent agent is deployed for each user equipment is proposed. The performance evaluation demonstrates its superiority over existing strategies, resulting in improved system performance, reduced outage probability, and enhanced energy efficiency.
Artificial intelligence‐driven insights: Precision tracking of power plant carbon emissions using satellite data
Authors: Zhang Zeqi , Leng Di , Li Yingjie , Gui Xuanang , Cheng Yuheng , Zhao Junhua , Zhang Zhengwen , Ghias Amer M. Y. M.
Published: October 2024

Human activities have been driving massive greenhouse gas emissions, causing global warming, and triggering increasingly frequent extreme weather events that severely threaten the environment. Power generation is the leading contributor to anthropogenic emissions, making precise, real‐time measurement and monitoring of power plant carbon emissions crucial in reducing climate change. This study uses a new sophisticated pipeline that combines tropospheric monitoring instrument satellite data, power plant attributes, and advanced artificial intelligence algorithms to build a predictive carbon emission model. The approach utilizes multimodal data processing, encoding, and model optimisation. Experimental results confirm that this pipeline can automatically extract and utilize vast amounts of relevant data, thereby enabling the artificial intelligence model to accurately predict power plant carbon emissions and providing a vital tool for reducing global warming.