Browse Articles

Hybrid-domain attention learning for lightweight underwater image enhancement and real-time vision deployment

Scalable networks of multimodal haptic arrays for plantar sensory substitution

Feet provide essential sensory input, supporting body awareness for safe movement. The impairment of plantar sensation, arising in conditions such as stroke and spinal cord injury, has a major impact on mobility, balance, and quality of life. Substituting the sensation of plantar pressure to another area on the body with intact somatosensory abilities requires capabilities for fast, programmable delivery of haptic feedback. Here, we introduce a wireless network of skin-conformable, multimodal haptic arrays that deliver high-density thermal and vibrotactile patterns anywhere on the body. Central to this approach is a hybrid motor unit that independently controls thermal and mechanical stimulation, enabling 128 degrees of freedom across 64 addressable nodes. Electromechanical characterization establishes precise, simultaneous, and safe modulation of both modalities. Psychophysical experiments demonstrate reliable spatial discrimination of colocated heat and vibration. These haptic arrays form the receivers in a sensory substitution system that delivers patterns of vibrotactile stimulation to mirror the distribution of pressure recorded from an insole-based array of pressure sensors. Exploratory case studies in individuals with spinal cord injury and stroke demonstrate feasibility and suggest improved performance during standing balance and walking tests. Altogether, this work highlights the potential of information-rich cutaneous interfaces to substitute plantar sensation, expanding the scope of somatosensory engagement for rehabilitation, entertainment, and education.

A H-MnO2 nanoplatform for tumor microenvironment remodeling and multimodal synergistic therapy in prostate cancer

Endothelial c-IAP2 loss amplifies P2X7 receptor-driven inflammation and worsens schistosomiasis-associated pulmonary hypertension

Schistosomiasis-associated pulmonary hypertension (Sch-PH) is the most common form of group I PH worldwide. Recently, data revealed that the preclinical Sch-PH animal model exhibited gut and lung microbiome dysbiosis, associated with significant lung endothelial cell (EC) dysfunction and microvascular apoptosis. However, the role of pro-/antiapoptosis sensors, such as the inhibitor of apoptosis protein 2 (c-IAP2) and the purinergic receptor P2X7 (P2X7R), remained unclear. Using Cdh5cre-ER T2 ;cIAP1 −/− ;cIAP2 fl/fl animal model, this study investigated the contribution of endothelial c-IAP2 in this process, revealing pulmonary P2X7R overexpression as a putative target in the onset of Sch-PH. Pharmacologically, inhibition of P2X7R function confirmed its role in promoting lung EC death and disease progression. Moreover, data suggest that microbiome-associated metabolic alterations in Sch-PH seem linked to microvascular EC apoptosis driven by ATP/P2X7R overactivation and suppressed c-IAP2 expression. Indeed, genetic ablation of endothelial c-IAP2 expression was sufficient to induce PH-like features in mice, with echocardiography indicating a higher pulmonary acceleration time (PAT), PAT/pulmonary ejection time, and right ventricular free wall thickness (RVFWTH) after IP/IV-Egg challenge compared to controls, an effect linked to the female prevalence of the disease. These findings suggest a significant contribution of lung EC-P2X7R activation and c-IAP2 suppression to sex-linked Sch-PH pathology, highlighting them as promising therapeutic targets for this life-threatening illness.

Role of new urbanization in tourism supply-demand evolution within the urban agglomeration via driving mechanisms and obstacle diagnosis

Correction for Zhang et al., Deep learning framework for quantifying self-organization in <i>Myxococcus xanthus</i>

SNAKE-71: wire-free direct aspiration thrombectomy using the Cereglide 71 catheter for acute large vessel occlusion stroke

A pico-calorimeter for cellular metabolism and antimicrobial susceptibility testing

While methods exist to indirectly quantify the metabolism of biological systems, directly measuring metabolic rates in living samples remains challenging. Here, we describe a calorimetric sensor with a sensitivity of ~100 pW at 23.1 mHz, suitable for measurements on living organisms, surpassing previously reported sensitivities. The sensor measures minute temperature differences between a capillary that contains the sample and two reference capillaries, directly relating this temperature difference to the heat produced by the sample. The sensor provides high responsivity (23 to 100 nV/nW), a fast thermal response time (~7.9 s), and supports real-time, long-term monitoring of biological processes, such as the proliferation and growth of small numbers of bacteria. These capabilities offer opportunities to advance our understanding of complex biological phenomena. We demonstrate the utility of the sensor by measuring the growth rate of Escherichia coli . The technique enables estimation of the oxygen consumption rate per cell, the heat production per cell, and the associated contributions from respiration and fermentation. We further show how the growth rate changes in response to different concentrations of chloramphenicol, rifampicin, and ampicillin, three antibiotics with distinct mechanisms of action. The sensor shows significant potential for determining the minimum inhibitory concentrations of antibiotics, performing antibiotic susceptibility testing of pathogens, and enabling fundamental studies of microorganism metabolism.

NOSIP promotes cell proliferation and motility by targeting SPTAN1 for ubiquitination and degradation in clear cell renal cell carcinoma

A vast temporal continuum for sensory processing arises from a nontopographic cellular multilevel gradient

Classification of neurons into discrete populations aids the comprehension of neuronal function. However, such simplifications do not fully reflect the complexity and gradual nature of sensory stimuli and internal representations. Therefore, heterogeneous neuronal populations might be more adequate to process and represent neuronal function compared to discrete populations. Using patch-seq recordings, we identify a heterogeneous cell population in the auditory brainstem that forms an extensive functional continuum through molecular, biophysical, and synaptic gradients. Through the interaction of this multilevel gradient, this population spans nearly the full range of known membrane time constants forming a temporal filter bank. This temporal filter bank matches the range of relevant frequencies of environmental sound transients. This arrangement processes early cross-frequency integration producing a holistic information of environmental sound transients known to be relevant during speech and pitch detection. Thus, the presence of a functionally continuous neuronal population relates to the complexity of stimulus information.

Gastrointestinal endoscopic image classification using a hybrid modified inception network and a customized vision transformer with tree growth feature selection

Abstract The Gastrointestinal (GI) tract plays a vital role in digestion by breaking down food into essential nutrients. Disorders such as bleeding lesions, ulcerative colitis, Inflammatory Bowel Disease (IBD), constipation, diarrhea, abdominal pain, nausea, and vomiting may indicate serious chronic conditions, including cancer. GI malignancies are among the leading causes of cancer-related mortality worldwide; however, early and accurate diagnosis can significantly reduce fatality rates. Existing endoscopic AI systems often struggle to generalize across datasets. They also face challenges in capturing both local lesion characteristics and long-range contextual information. To address this, the proposed study explores deep learning-based methods for automated classification of gastrointestinal diseases using endoscopic images. Two models were developed: a modified Inception architecture with four blocks and a customized Vision Transformer (ViT-3) consisting of three transformer encoder blocks. Deep features were extracted from both models, which were fused using a weighted fusion strategy. The redundant features were reduced using the Tree Growth Algorithm (TGA). The optimized feature set was then classified using machine learning classifiers to improve diagnostic performance. To evaluate its effectiveness, the framework was tested on two widely used benchmark datasets, Kvasir v1 and Kvasir v2, which include 4,000 and 8,000 images, respectively across eight GI disease categories. On the Kvasir v1 dataset, the proposed method achieved an accuracy of 98.9%, along with sensitivity, precision, and F1-score values of 98.87%, 98.86%, and 98.86%, respectively. Similar performance was observed on the Kvasir v2 dataset. These findings demonstrate that the proposed method provides a reliable and effective solution for early identification and classification of gastrointestinal diseases from endoscopic images.

Improved latitudinal carbon budgets from global airborne surveys

Robust information on the spatial distribution of global carbon fluxes is required to project the future trajectory of carbon-climate feedback effects and atmospheric CO 2 concentrations. Estimates of the latitudinal partitioning of carbon fluxes from top-down atmospheric CO 2 inverse models currently diverge widely, because of methodological limitations or systematic biases in models or observations. We use airborne CO 2 observations from the NASA Atmospheric Tomography Mission to evaluate and refine inverse model estimates from the Orbiting Carbon Observatory version 10 Model Intercomparison Project of total CO 2 exchange for the two-year period of June 2016–May 2018. Applying emergent concentration-flux relationships as constraints reduces zonal total flux uncertainties by 46 to 56% relative to the full v10 MIP ensemble and by 17 to 28% relative to the subset excluding satellite observations over ocean. Subtracting independent estimates of fossil-fuel emissions and air-sea gas exchange results in residual land fluxes with a large northern extratropical sink, a small southern extratropical sink, and a small tropical source. The airborne-derived tropical land source disagrees with a large tropical land sink from process-based terrestrial models combined with estimates of land use emissions and river fluxes, representing an important challenge for our understanding of the global carbon cycle. The large implied northern extratropical sink can be explained either by underestimated land uptake by process models or a combination of process model bias and overestimated fossil fuel emissions.

Green spectrofluorimetric determination of Ibrexafungerp using NBD-Cl derivatization

Uncovering thousands of endosymbiont DNA transfer events within single cockroach genomes

Horizontal gene transfer (HGT) between organisms can be a valuable source of genetic variation and innovation. Research on HGT in eukaryotes has hitherto focused on transfers of coding sequences; insertions of noncoding DNA remain poorly understood. Here, we investigated HGT in cockroaches, which have a long-standing evolutionary relationship with the transovarially transmitted endosymbiont Blattabacterium cuenoti , making them a valuable system for assessing the potential scale of HGT. We aligned 150-bp genomic fragments of B. cuenoti to 23 cockroach and termite genomes, including 8 genomes newly sequenced, and revealed pervasive endosymbiont DNA transfer events. Australian panesthiine and geoscapheine cockroaches were consistently found to harbor &gt;3000 HGT inserts, more than an order of magnitude higher than the previous maximum estimate in other eukaryotes, excluding rotifers. Some inserts appear to have persisted for ≥28.7 million years in this group, which may reflect functional roles. We identified numerous chimeric inserts comprising up to nine short segments from different locations in the B. cuenoti genome. Our findings indicate pervasive HGT in eukaryote genomes, with potentially far-reaching implications for adaptation and speciation.

Correction: Green synthesis and characterizations of zinc oxide nanoparticles using acorn fruit extract for antimicrobial, larvicidal and in silico activities

Multidecadal preindustrial methane variability can be explained by noise in the source–sink imbalance

Ice core records of preindustrial methane indicate variability of ± 30 ppb ( ± 5%) on multidecadal-to-centennial timescales. Previous work has attributed these excursions to low-frequency or episodic changes in methane sources due to large-scale climate variability (e.g., the Little Ice Age) or human activity. Here, we explore what source and sink dynamics are consistent with ice core variability and show that the preserved variability can arise solely from white noise fluctuations in the source–sink imbalance. A simple model driven by unforced random perturbations, when integrated by the methane lifetime and firn processes, produces synthetic ice core records that match the spectral features of observations. Thus, fast-varying sources or sinks previously assumed too transient to affect ice core variability, such as weather-driven fluctuations in methane oxidants and emissions (e.g., interannual wetland variability), can produce the observed variability. Given large structural uncertainty in methane budget dynamics, we expand our model to quantify how variability in atmospheric methane and its drivers changes with the assumed dominant timescale of source–sink imbalance variability. Our results show that any source–sink imbalance timescale shorter than a century is consistent with the ice core record. Shorter timescales imply greater atmospheric variability but require larger-amplitude source–sink imbalance fluctuations. A key consequence is that rapid preindustrial source–sink variability (timescales ≲ 1 y) could explain modern methane growth rate variability. Constraining methane source and sink dynamics with preindustrial ice core records could therefore provide more robust priors for evaluating modern methane trends.

Firecracker-induced air pollution and health burden during Diwali: ground and satellite assessment across 14 cities of The Indo-Gangetic Basin

Triggering three-step relay mechanism over Cu-based electrocatalysts for nitrate reduction

Electrocatalytic nitrate reduction reaction (NO 3 RR) is a promising approach for pollutant appreciation. Cu-based catalysts have attracted extensive attention due to their favorable adsorption with nitrate. At present, the continuous hydrogenation is considered as a single reaction mechanism for NO 3 RR over Cu, in which the high energy barrier of NO 3 − -to-NO 2 − conversion and insufficient active hydrogen (*H) supply lead to high onset potential and low faradaic efficiency. The three-step relay (TSR) mechanism can solve these issues, but it is retarded by the low driving force of spontaneous redox reaction between Cu and NO 3 − . Herein, we design P-doped Cu cluster catalyst to trigger and enhance TSR. The onset potential and faradaic efficiency of NH 3 are −0.15 V (vs. reversible hydrogen electrode) and 99.17% over P-doped Cu cluster, outperforming the reported Cu-based catalysts. The electrochemical in situ characterizations, isotope-labeling experiments and theoretical calculations prove that the low-coordinated Cu in cluster promotes the rate of spontaneous redox reaction as well as P doping provides sufficient *H, which can trigger and enhance TSR pathway for NO 3 RR, achieving excellent NO 3 RR performance.

Delayed intubation and 60-day mortality in severe COVID-19-associated acute respiratory failure in an emulated target trial using the OUTCOMEREA network

Structural and cellular insights into DCTPP1 antagonists and their synergistic action with DNMT inhibitors

DCTPP1 is a nucleotide pyrophosphatase that helps preserve genomic stability and epigenetic programming by hydrolyzing and preventing the misincorporation of methylated base-modified deoxycytosine triphosphates into DNA. Through this role, DCTPP1 can degrade the efficacy of nucleotide analog-based DNA methyltransferase inhibitors and thus represents a compelling therapeutic target in cancer treatment. To identify prospective antagonists of DCTPP1, we conducted a high-throughput chemical screen against the enzyme, identifying both existing and previously unreported inhibitor classes with potent submicromolar activity. Structural characterization using X-ray crystallography revealed that the inhibitors all occupy DCTPP1’s nucleotide-binding pocket, associating primarily with a pair of tryptophans and two critical histidine residues that mimic interactions observed with natural substrates. Biochemical assays using modified chemical scaffolds confirmed the relevancy of the observed DCTPP1–antagonist interactions, while cell-based experiments demonstrated significant synergy between the lead inhibitors and the nucleoside analog decitabine in blocking the growth of prostate cancer cells. The specificity and efficacy of the compounds were further validated through loss- and gain-of-function studies, confirming the dependence of their therapeutic synergy on DCTPP1 activity. These findings advance our understanding of DCTPP1 as a therapeutic target while uncovering chemical scaffolds that can potentiate the action of existing nucleotide-based cancer therapies.