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Transcription factor CEBPA suppresses sepsis induced lung injury by activating SIRT4 transcription

Correction: Carnosol Induces ROS-Mediated Beclin1-Independent Autophagy and Apoptosis in Triple Negative Breast Cancer

Laser-assisted microbial culturomics

Abstract Even though metagenomics have revolutionized the characterization of the human microbiome, detailed mechanistic studies are impracticable, as there is a dearth of robust culture collections. We now describe the development and use of a laser-assisted culturomics platform, incorporating the elements of a bioprinter, the culture conditions, the methods to characterize the microorganisms and a biobank. With laser-assisted bioprinting, the microorganisms can be rapidly and precisely transferred from clinical biofilms to highly organized arrays of microbial colonies, which are suitable for co-culturing and molecular analyses. The presented technique has propagated 99 of 100 microbial species and recovered 79% of abundant species from dental plaque in accordance with full 16S rRNA gene profiling of 691,199 sequences. Microscopy, spectroscopy and enzyme assays have been used to guide isolations. Processing of oral biofilms from four individuals has yielded 249 representative isolates, from 14 classes and 124 species in total. Functional profiling with bioprinting has indicated commensals which could potentially contribute to disease development. Isolates from peri-implantitis cover 85.4% of the transcriptionally active clinical biofilms at genus level. Taken together, this work provides the basis for generating on-demand culture collections and biofilms for research and clinical use.

Comparative seismic analysis of t-shaped and conventional deep cement mixing columns in highway embankments on soft soil

Sampling informational properties of codon usage through the tree of life

The genetic code, a unifying principle in biology, ensures that all organisms, stemming from a Last Universal Common Ancestor (LUCA), share fundamental rules for translating DNA into proteins. However, codon usage varies across the tree of life, influenced not only by GC-content and proteome composition but also by complex, often less understood rules dependent on each species’ evolutionary trajectory. To better understand these rules, we segregated codons into their functional parts and applied Shannon’s information-theoretic measures to 1,434 species from eight diverse taxonomic groups. We provide robust evidence that the first codon base plays a central role in amino acid determination, while the third base serves an accessory function. Using conditional entropy measures, we rigorously quantified this relationship, universally confirming the greater informational variability of the third base across all sampled species for the first time at this scale. Our analysis revealed significant heterogeneity in coding strategies across different taxonomic groups. Notably, the unique variability observed in Archaea, in contrast to the more constrained patterns in Eukaryotes and Bacteria, underscores the profound influence of evolutionary pressures and distinct life histories on genetic information processing. The identification of outlier species, exhibiting distinct informational profiles, highlights specific instances where unusual lifestyles or ecological niches may have driven unique adaptations in codon usage and underlying informational dependencies. These informational patterns offer a complementary perspective to traditional phylogenetic analyses, further revealing a hierarchical organization of informational dependencies among codon components that sheds light on the intricate grammar of genetic information. We also rigorously investigated the relationship between GC-content and our informational measures, concluding that these entropy measures provide valuable insights that cannot be obtained from GC-content alone. This work not only offers a novel framework for quantifying informational properties of codon usage but also reveals previously unappreciated aspects of how genetic information is encoded and processed across life’s domains.

A hierarchy of time constants and reliable signal propagation in the marmoset cerebral cortex

Abstract A hierarchy of timescales in the cerebral cortex is functionally desirable for rapid information processing in sensory areas and slow time integration in association areas. Here, through an analysis of electrocorticography (ECoG) data, we identified a timescale hierarchy in the neocortex of marmoset, a primate species commonly used in neuroscience. Constrained by the anatomical and electrophysiological data, we developed a multi-regional model of the marmoset neocortex that captures the observed timescale hierarchy phenomenon. Furthermore, we used the model to investigate how the neocortex reconciles information integration on distinct timescales in local areas with reliable signal propagation globally across regions. We found that a near-criticality state is optimal for both localized signal integration within areas and reliable signal propagation across areas in the multi-regional neocortex. Our model also mechanically explains recent experimental observations that the structural and functional connectivities are less correlated in association areas than in sensory areas.

An adaptive multi-scale kriging framework with committee-based infill for engineering design optimization

Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm for Mobile Edge Computing Networks (EHRL)

Mobile Edge Computing (MEC) is a computational paradigm that brings resources closer to the network edge to provide fast and efficient computing services for Mobile Devices (MDs). However, MDs are often constrained by limited energy and computational resources, which are insufficient to handle the high number of tasks. The problems of limited energy resources and the low computing capability of wireless nodes have led to the emergence of Wireless Power Transfer (WPT) and Energy Harvesting (EH) as a potential solution where electrical energy is transmitted wirelessly and then harvested by MDs and converted into power. This paper considers a wireless-powered MEC network employing a binary offloading policy, in which the computation tasks of MDs are either executed locally or fully offloaded to an edge server (ES). The objective is to optimize binary offloading decisions under dynamic wireless channel conditions and energy harvesting constraints. Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. Simultaneously, the DNN is trained using the Nadam optimizer (Nesterov-accelerated Adaptive Moment Estimation), which combines the benefits of Adam and Nesterov momentum, offering improved convergence speed and training stability. The proposed algorithm addresses the dual challenges of limited energy availability in MDs and the need for efficient task offloading to minimize latency and maximize computational performance. Numerical results validate the superiority of the proposed approach, demonstrating significant gains in computation performance and time efficiency compared to conventional techniques, making real-time and optimal offloading design truly viable even in a fast-fading environment.

DFT calculations do not explain enantiospecific NMR responses in cross polarization

A comparative assessment of the antidepressant efficacy of ketamine, psilocybin, and fluoxetine in a chronic stress model

Developing a novel evaluation model to assess the performance of base hospitals in China National Stroke Screening Surveys

Background The China National Stroke Screening Surveys (CNSSS), a decade-long national public health initiative, aims to reduce stroke morbidity and mortality through early detection and intervention. This study develops a novel evaluation model to systematically assess the performance of base hospitals (BHS) participating in the CNSSS program in Sichuan Province, China. Methods Sixteen BHS in Sichuan Province participated in the CNSSS program in 2024. We utilized eleven performance indicators to develop the evaluation model. Subjective weights were derived from scores assigned to indicators, while objective weights were calculated using the Entropy Weight Method (EWM). A Multiplicative Synthesis with Normalization (MSN) method was adopted to generate combined weights. Based on the subjective, objective, and combined weights, we generated weighted data matrices, determined the corresponding BHS rankings separately, and compared BHS performance in CNSSS implementation across these three ranking systems. Results Among the evaluation indicators, Task Completion Rate received the highest subjective weight (0.3125), whereas Intervention Rate dominated both objective (0.1594) and combined (0.2303) weights. Notable weight changes were observed: Task Completion Rate exhibited the largest reduction (−92.45%) from subjective to objective weights, followed by Age Deviation Degree (−76.11%), Follow-up Completion Rate (−73.31%), and Hypertension Awareness Rate (−3.31%). Conversely, Diabetes Detection Rate displayed the most significant increase (+313.65%), followed by Dyslipidemia Detection Rate (+249.44%), Hypertension Detection Rate (+227.79%), Stroke High-Risk Detection Rate (+119.52%), Stroke High-Risk Intervention Rate (+107.90%), Intervention Rate (+48.77%), and Risk Factor Control Rate (+42.52%). BHS A and B ranked top 3 across all weighting methodologies. BHS A ranked first under original, subjective and combined weights, while BHS D led in the objective ranking. Compared to the original methodology, the combined weighting methodology has the highest discrimination degree (0.1166). Conclusions Weighting methodologies significantly influence BHS performance evaluations. Subjective approaches emphasize expert expertise, whereas objective methods prioritize data variability. Compared to single weighting method, combined weighting effectively balances discrepancies between expert subjective priorities and data-driven objectivity, thereby addressing limitations of single-method designs. For the CNSSS program, our model underscores the need to shift quality focus from high-risk screening to targeted management, including timely post-screening interventions and effective risk factor control. These targeted interventions are expected to significantly reduce stroke incidence, recurrence, and mortality among screened populations, while enhancing the overall quality of the CNSSS program in the region.

A hyperconformal dual-modal metaskin for well-defined and high-precision contextual interactions

Abstract Proprioception and touch serve as complementary sensory modalities to coordinate hand kinematics and recognize users’ intent for precise interactions. However, current motion-tracking electronics remain bulky and insufficiently precise. Accurately decoding both is also challenging owing to the mechanical crosstalk of endogenous and exogenous deformations. Here, we report a hyperconformal dual-modal (HDM) metaskin for interactive hand motion interpretation. The metaskin integrates a strongly coupled hydrophilic interface with a two-step transfer strategy to minimize interfacial mechanical losses. The 10-μm-scale hyperconformal film is highly sensitive to intricate skin stretches while minimizing signal distortion. It accurately tracks skin stretches as well as touch locations and translates them into polar signals, which are individually salient. This approach enables a differentiable signaling topology within one single data channel without burdening structural complexity to the metaskin. When combined with temporal differential calculations and time-series machine learning network, the metaskin extracts interactive context and action cues from the low-dimensional data. This phenomenon is further exemplified through demonstrations in contextual navigation, typing and control integration, and multi-scenario object interaction. We demonstrate this fundamental approach in advanced skin-integrated electronics, highlighting its potential for instinctive interaction paradigms and paving the way for augmented somatosensation recognition.

Postural stability reveals cognitive load of holding an intention in mind

Abstract It is well known that walking while talking may be challenging, but does merely keeping a future intention in mind (i.e., prospective memory, PM), even without execution, impose cognitive costs on postural stability? Reaction times and accuracy in a primary cognitive activity used so far may not fully capture these hidden costs, whereas center of pressure (COP) fluctuations offer a promising task-external indicator of cognitive load due to shared cognitive-postural resources. Fifty-three younger (18–30 years) and 47 older adults (60–86 years) performed an arrow task while standing on a force platform. Cognitive load was manipulated across two task-load conditions (low vs. high) and three PM conditions: (1) no PM instruction, (2) an instructed but unexecuted PM task (intended-PM), and (3) an instructed and executed PM task (executed-PM). The Cognition-Balance-Cost-Index (CBCI), integrating reaction times and COP, quantified cognitive-postural resource allocation. Results showed that younger adults’ CBCI remained stable, with only a moderate increase in executed-PM under high load. In contrast, older adults exhibited significantly higher CBCI scores across all conditions, peaking in the executed-PM condition. Notably, intended-PM under high load reduced CBCI in older adults, suggesting compensatory resource allocation, and highlighting postural stability as a valuable, non-invasive indicator of cognitive load.

Investigating barriers to adherence to antimalarial prescribing guidelines in public healthcare facilities in Arba Minch, South Ethiopia: A qualitative study

Background Early diagnosis and prompt treatment of malaria cases are a crucial component of curative and preventive interventions. There have been reports of healthcare workers overprescribing antimalarial agents against guidelines, but the barriers they face in adhering to the guidelines are not well studied. This study aimed to investigate barriers to adherence to guidelines in prescribing antimalarial drugs in public healthcare facilities in Arba Minch, South Ethiopia. Method A cross-sectional descriptive exploratory qualitative method was employed. We included ten participants from public healthcare facilities, including health centres, a hospital, a city health office, and a zonal health bureau. A key informant interview technique was used to collect data. All interviews were audio-recorded, transcribed, and analyzed. Data analysis was performed using ATLAS.ti, version 7.5 software. The results were presented thematically and narrated to support the main themes. Results Public healthcare facilities primarily used blood smear microscopy to test all malaria-suspected patients. However, in cases of microscopy service interruptions or when confirming negative results, rapid diagnostic tests (RDTs) were employed in some facilities. Limited availability of microscopes and reagents, and electric power interruptions hindered reliable microscopy services. Drug stock-outs, patient expectations for antimalarial drugs, self-treatment, and delayed care-seeking are barriers to adherence to malaria treatment guidelines. The main reason for non-adherence to withholding antimalarial drugs after negative tests was greater trust in clinical findings over laboratory results. Confidence in experience contributed to trust in clinical judgment, while perceived inexperience and negligence, inconsistent RDT and microscopy results, and poor-quality control assessment results undermined trust in laboratories. Despite supporting the guidelines, study participants emphasized the need for flexibility to allow empirical treatment and highlighted the lack of training and mentoring for healthcare workers. Conclusion To improve adherence to malaria treatment guidelines, it is essential to ensure consistent lab operations, enhance quality assurance, maintain effective communication between lab personnel and prescribers, and provide healthcare and patient education. Implementing training and mentoring programs and promoting evidence-based practices are also crucial.

Cross-scale high-bandwidth atomic force microscopy with a stick-slip nanopositioner

6-Gingerol enhances the anti-tumor activity of temozolomide by inhibiting EGR1/GDF15 signaling in glioblastoma

Relative abundance and diversity of sharks and predatory fishes across Marine Protected Areas of the Tropical Eastern Pacific

Marine Protected Areas (MPAs) in the Tropical Eastern Pacific (TEP) support globally distinct reef fish populations, which exhibit differences between the remote oceanic islands and continental coast. While oceanic island MPAs typically support large abundances of sharks and large predatory teleost (bony) fishes, coastal MPAs show increasing signs of depletion. We deployed stereo-Baited Remote Underwater Video systems (stereo-BRUVs) to assess reef fish community structure across seven MPAs in the region. Oceanic island MPAs had considerably greater species richness and relative abundances than coastal MPAs across all trophic levels. Within the biogeographic subprovinces, fish assemblages were differentiated from each other corresponding to latitude, aligning with the established patterns and supporting finer scale bioregionalization within the TEP. Notably, oceanic MPAs supported some of the largest relative abundances (MaxN hr -1 ) of sharks on nearshore reefs reported globally. This is likely driven by the regional oceanographic processes enhancing productivity and trophic diversity and sustained by reduced anthropogenic disturbances associated with MPA remoteness and protection. Therefore, we highlight the critical role of MPAs in the TEP as refuges for sharks. However, we also found evidence of fishing pressure on predatory fishes within MPAs across the region. Coastal MPAs in Ecuador exhibit low fish abundances across all trophic levels, with large predators notably absent, indicative of ‘fishing down the food web’. Our results highlight the need for fishing impact assessments and improved conservation measures, such as strengthened enforcement, within MPAs to conserve globally significant marine biodiversity.

Pharmacologic inhibition of PCBP2 biomolecular condensates relieves Alzheimer’s disease

Abstract Biomolecular condensates, membrane-less assemblies formed by phase separation, are implicated in neurodegenerative disease, but their role in Alzheimer’s disease (AD) remains unclear. Here, we report that in the brain of AD patients and animal models, an elevation of poly(C)-binding protein 2 (PCBP2) correlates with biomolecular condensation that involves phase separation. These condensates sequester large numbers of mitochondrial and mRNA-binding proteins, leading to the outside impairment of mitochondrial morphology and function, and BACE1 mRNA decay relative to amyloid deposition. We then identify a small molecule CN-0928 that inhibits the condensates by reducing PCBP2 protein level and mitigates AD pathology and cognitive decline, in which CN-0928 binding to a target protein integrator complex subunit 1 (INTS1) allows to regulate PCBP2 expression. Our findings place PCBP2 condensates as a key player that cooperates the seemingly disparate but important pathways, and show pharmacological modulation of PCBP2 as an effective approach for treating AD.

AUPA: weakly supervised approach for streamlining breast cancer diagnostic workflow by WSI histological type classification for efficient IHC triage

Identity abuse against sexual and gender minority communities: The Being LGBTQI+ in Ireland study

Identity abuse targets people on the basis of immutable characteristics, and has the potential to cause greater emotional and psychological distress for this reason. People with multiple intersecting identities may be at greater risk. While the LGBTQI+ population experience higher rates of abuse than the general population, studies often focus on one type of abuse and rarely examine within LGBTQI+ group variation. A national cohort study involving over 2,800 LGBTQI+ participants aged 14 + examined the prevalence and predictors of LGBTQI+ identity abuse across six forms of abuse, as well as experiences of identity abuse more broadly via an open-ended question. Lifetime and past year prevalence of at least one form of abuse was 79% and 42% respectively. Polyvictimisation (two or more forms of abuse) was experienced by over half of the sample within their lifetime. Besides LGBTQI+ identity abuse, participants also experienced other forms of identity abuse, including ableism, racism, and sexism. LGBTQI+ people with disability were particularly at risk of abuse. Asexual and bisexual participants had lower odds of many forms of identity abuse. Risk, however, was constituted differently across the different forms of abuse, highlighting the importance of not siloing abuse in research by examining each type independently of one another. Interventions to tackle prejudice-based abuse are required, including those that address heteronormative and gender normative assumptions that seem to underpin prejudice, as well as tackling ageism and racism. Polices and measures to safeguard LGBTQI+ people against identity abuse also need to be enacted.