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Production of improved Ethiopian Tej using mixed lactic acid bacteria and yeast starter cultures
Cytoplasmic TRIM24 promotes colorectal cancer cell proliferation by activating Wnt/β-catenin signaling
Discovery of non-invasive biomarkers for accurate detection of membranous nephropathy
Oral cancer biosensor using ternary photonic crystal and parity time symmetry
In vivo CRISPR screening in head and neck cancer reveals Uchl5 as an immunotherapy target
Correction: Atopic dermatitis-alleviating effects of lactiplantibacillus plantarum LRCC5195 paraprobiotics through microbiome modulation and safety assessment via genomic characterization and in vitro analysis
Benchmarking the utility of dry-electrode electroencephalography for clinical trials
Abstract This study investigated if new dry-electrode technologies for electroencephalography (EEG) can substantially lower patient and site burden in clinical trials while maintaining adequate data quality. We benchmarked three dry-electrode EEG devices against a standard EEG using typical clinical trial procedures and EEG tasks that are often used for biomarker purposes. We found that dry-electrode EEG can perform on par with standard EEG for a range of different applications. However, both the participant and technician acceptance varied strongly across devices. Dry-electrode EEG was able to only match the comfort of standard EEG at best but was faster and easier to work with. Consequently, dry-electrode EEG was ranked among the most and least preferred options. The quantitative performance of dry-electrode EEG varied strongly across different applications. For example, quantitative resting state EEG and P300 evoked activity were adequately captured by dry-electrode EEG. However, certain signal aspects, such as low frequency activity (< 6 Hz) and induced gamma activity (40–80 Hz) presented notable challenges for dry-electrode EEG. Our findings suggest that dry-electrode EEG can substantially improve clinical trial applications of EEG, if the device and its context of use are carefully matched.
Direct circMAN1A2(2,3,4,5)-CENPB mRNA interaction regulates cell proliferation and cancer progression
Factors influencing post discharge activities of daily living in patients receiving rehabilitation in acute care hospital
Abstract Post-discharge functional outcomes in patients undergoing acute rehabilitation—especially regarding activities of daily living (ADL) and instrumental activities of daily living (IADL)—remain inadequately understood. The combined effects of demographic factors and in-hospital variables on ADL and IADL status at discharge has not been clearly defined. This study aimed to clarify these associations to support effective discharge planning and post-discharge care strategies. We retrospectively analyzed 309 adult patients who received rehabilitation in an acute care hospital in Japan between April and September 2016. Patients who underwent only assessments, were pediatric, deceased, or did not receive rehabilitation were excluded. Demographic data and Barthel Index scores at rehabilitation initiation and discharge were extracted. Post-discharge ADL and IADL status were assessed approximately 1.5–2 years later using a questionnaire based on the Frenchay Activities Index (FAI). Among the 309 patients, 57 were transferred, 249 discharged home, and 3 institutionalized. ADL and IADL scores were significantly higher in the home discharge group. Higher ADL scores at discharge and post-discharge were independently associated with higher FAI scores, underscoring the importance of ADL independence for post-discharge IADL recovery. Addressing ADL limitations and optimizing rehabilitation may enhance IADL outcomes and support independent living after discharge.
Multi-species eDNA as a screening tool to facilitate early detection and eradication of aquatic invasive species in large water bodies
Abstract Aquatic invasive species can devastate native biodiversity and human water infrastructure. Effective eradication relies on early detection. However, commonly used visual surveys are ineffective for detection of small populations of submerged invasive species in large water bodies. Here, we explored detection of invasive aquatic plants, animals (vertebrate and invertebrate), and pathogens using 10 environmental DNA (eDNA) water sampling events every two weeks between June and October, 2018, informing ideal sampling times for long-term early-detection monitoring. The highest number of species detections across taxa were found using 6 replicates in late August and early September. Detections varied by taxon, with the most detections for fishes, followed by invertebrates, amphibians, and submerged plants. All expected species were detected with eDNA except for three terrestrial and emergent riparian plants. Reservoirs had the most consistent presence of AIS, suggesting that those systems and aquatic communities may be susceptible to new invasions. AIS detections occurred across more sites and water bodies than had been previously documented which provided evidence of silent invasions by species such as crayfishes, mollusks, and plants. We offer a framework for interpreting management response to low-read counts from multispecies eDNA sampling that balances interpretation of results with the cost of management responses.
Looping metal-support interaction in heterogeneous catalysts during redox reactions
How the time and type of physical education lessons affect attention capacity and cortisol levels in primary school children
Sustainability in large language model supply chains-insights and recommendations using analysis of utility for affecting factors
Abstract The increasing adoption of Large Language Models (LLMs) has intensified concerns regarding the sustainability of their supply chains, particularly concerning energy consumption, resource utilization, and carbon emissions. To address these concerns, this study proposes a two-step approach. First, a Delphi method is employed to systematically identify the critical factors affecting the sustainability of LLM supply chains. Expert consensus through four rounds of feedback highlights key factors such as Environmental Impact, Computational Efficiency & Resource Optimization, Data Quality & Ethical Considerations, and Social Responsibility & Governance. In the second step, the identified factor’s relative importance was calculated using Conjoint Analysis, a statistical technique used to determine how respondents value different factors of a supply chain of LLMs. This prioritization helps formulate strategies to make LLM’s supply chain sustainable. The low score for environmental impact suggests a lack of awareness about the sustainability of LLMs’ supply chain. The study finds Data Quality and Ethical considerations to be the most important considerations for the respondents. Thus, it provides a framework for implementing sustainable practices in LLMs’ supply chains in resource-constrained settings. The results demonstrate the effectiveness of this combined Delphi-Conjoint Analysis approach, providing actionable insights for AI organizations aiming to enhance the sustainability of their LLM operations.
Critical fluctuations and noise spectra in two-dimensional Fe3GeTe2 magnets
Data-driven analysis of chemical graph of carbazole and diketopyrrolopyrrole
Multi-objective optimization for dynamic logistics scheduling based on hierarchical deep reinforcement learning
A loss-of-function human ADAR variant activates innate immune response and promotes bowel inflammation
Strengthening of structurally deficient and partially damaged short square columns using GFRECC retrofit technique
Disruption of ClC-3-mediated 2Cl−/H+ exchange leads to behavioural deficits and thalamic atrophy
Abstract CLCN3 encodes ClC-3, an endosomal 2Cl⁻/H⁺ exchanger, with pathogenic variants causing a neurodevelopmental condition marked by developmental delays, intellectual disability, seizures, hyperactivity, anxiety, and brain and retinal abnormalities. Clcn3 −/− mice show hippocampal and retinal degeneration, recapitulating key symptoms observed in humans. ClC-3 forms homodimers (ClC-3/ClC-3) and heterodimers with ClC-4 (ClC-3/ClC-4), with overlapping brain expression. This suggests distinct functional roles for homo- and heterodimeric assemblies and raises the question of which brain regions specifically depend on ClC-3/ClC-3 rather than ClC-3/ClC-4 complexes. Using ex vivo PET tracer analyses, Clcn3 −/− and Clcn3 td/td mice, we found neurodegeneration in the hippocampus and thalamus of Clcn3 −/− , while Clcn3 td/td mice showed thalamic degeneration and altered neuronal excitability, including changes in action potential threshold and after hyperpolarization. Clcn3 td/td mice carrying a transport-deficient p.E281Q ClC-3 variant that still associates with ClC-4, thereby allowing ClC-4 to be sorted to endosomes as ClC-4/ClC-3 heterodimers, unlike in the Clcn3 −/− model. Clcn3 td/td mice also exhibited reduced weight, hyperactivity, and motor deficits, reflecting clinical features. Lower ClC-4 levels in thalamus predict a predominant thalamic expression of ClC-3/ClC-3 homodimers. Overall, our findings indicate a region-specific function of ClC-3/ClC-3 homodimeric complexes and highlight the importance of ClC-3 transport activity in thalamic neuron survival, with electrophysiological dysfunction likely contributing to neurodegeneration.