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Association between serum anion gap and all-cause mortality in critically ill patients with Gastrointestinal bleeding: insights from MIMIC-IV database
Evaluating masked self-supervised learning frameworks for 3D dental model segmentation tasks
Abstract The application of deep learning using dental models is crucial for automated computer-aided treatment planning. However, developing highly accurate models requires a substantial amount of accurately labeled data. Obtaining this data is challenging, especially in the medical domain. Masked self-supervised learning has shown great promise in overcoming the challenge of data scarcity. However, its effectiveness has not been well explored in the 3D domain, particularly on dental models. In this work, we investigate the applicability of the four recently published masked self-supervised learning frameworks-Point-BERT, Point-MAE, Point-GPT, and Point-M2AE-for improving downstream tasks such as tooth and brace segmentation. These frameworks were pre-trained on a proprietary dataset of over 4000 unlabeled 3D dental models and fine-tuned using the publicly available Teeth3DS dataset for tooth segmentation and a self-constructed braces segmentation dataset. Through a set of experiments we demonstrate that pre-training can enhance the performance of downstream tasks, especially when training data is scarce or imbalanced—a critical factor for clinical usability. Our results show that the benefits are most noticeable when training data is limited but diminish as more labeled data becomes available, providing insights into when and how this technique should be applied to maximize its effectiveness.
Superior forward osmosis cellulosic membrane for water desalination and brine concentration
Abstract Brine is an inevitable product of desalination plants and various industrial sectors. The appropriate disposal of brines and their highly concentrated salts and other diverse contaminants is a critical environmental challenge to most plants. Recently, the FO process is gaining attention as a viable alternative to conventional brine concentration methods, primarily due to its reduced energy consumption. This study aimed to fabricate a high-performance nonwoven FO membrane from cellulose acetate (CA) blended with polysulfone (PS) via the phase inversion technique. The prepared membrane was investigated in both saline water desalination and brine concentration. The FO membrane performance was tested for saline water desalination at different NaCl concentrations and applied in brine concentration using two kinds of draw solutions: ammonium bicarbonate (NH4HCO3) and a mixture of ammonium hydroxide/ammonium bicarbonate (NH4 OH)/(NH4HCO3) at different concentrations. It was observed that a high flux of 150 LMH was attained by using 2 M NaCl as a draw solution against distillate water as a feed solution. For brine concentration, by application of (NH4 OH)/(NH4HCO3) draw solution mixture at a 1:1 ratio, the modified cellulosic FO membrane exhibited the highest water flux of 113 LMH.
Early detection of Alzheimer’s disease progression stages using hybrid of CNN and transformer encoder models
Single-cell RNA sequencing reveals immunological link between house dust mite allergy and childhood asthma
Unraveling the anti-tumor effects of midazolam in non-small cell lung cancer through the lncRNA XLOC_010706/miR-520d-5p/STAT3/autophagy pathway
Metagenomic biodiversity assessment within an offshore wind farm
Abstract Environmental DNA (eDNA) analysis can be a powerful tool for monitoring biodiversity and assessing human impacts on ecosystems. In this study, we employed a genome-wide metagenomic eDNA approach to assess the marine biodiversity within and around the Horns Rev 1 offshore wind farm in the Danish North Sea. Seawater samples were collected from both within the windfarm and surrounding control sites, sequenced, and analyzed using a combination of DNA k-mer matching and alignment-based classification methods. We identified a wide range of species across the tree of life—highlighting the species richness of this marine ecosystem. Our results revealed a high degree of species diversity congruence between the wind farm and control sites. While this could suggest minimal ecological disruption of the wind farm, we cannot rule out that the influence of ocean currents and water mixing the DNA from different regions dominate the species detection. We detected bioindicator species, such as Thalassiosira, Phaeocystis and Skeletonema, which can provide insights into water quality. Our metagenomic approach also enabled us to obtain population genomics insights for species, such as the European anchovy (Engraulis encrasicolus) and the diatom Rhizosolenia setigera, and genetically confirmed the origin of the invasive Sea walnut (Mnemiopsis leidyi) in the North Sea. This study highlights the potential of genome-wide eDNA metagenomics as a framework for assessing marine biodiversity and detecting population-level genetic signals, contributing to informed and scalable ecosystem monitoring strategies.
Relationship between atherosclerotic burden and sarcopenia in U.S. adults: A cross-sectional study based on the NHANES database
Hydraulic drive framework on habitat suitability enhances movement bias of brown trout in stream networks
Abstract Freshwater ecosystems face increasing threats from human activities and climate change, thus requiring efforts to reduce impacts and prevent further deterioration. Restoration projects for riverine environments often rely on hydraulic, habitat, and metapopulation models, which depend on their accuracy in capturing the interactions among the different elements. In this regard, a critical challenge is represented by the definition of reliable relationships between fish population dynamics among river reaches in a catchment and habitat characteristics. This study presents an efficient, eco-hydraulically based framework to model the movement bias of brown trout within a river network. The proposed framework integrates the effects of hydraulics and habitat characteristics in terms of the Habitat Suitability Index for various trout age classes. Novel relationships linking fish dynamics to habitat quality are employed to correct the movement bias of fish based on the upstream and downstream habitat conditions. The corrected bias is used to compute the population dynamics at the catchment scale and tested against different flow regimes. Accordingly, the impact of habitat condition changes on the population dynamics is highlighted. The framework simplicity makes it suitable for future integration into existing habitat and metapopulation models, thus offering a practical tool for enhancing riverine restoration planning.
Formulation optimization of furosemide floating-bioadhesive matrix tablets using waste-derived Citrus aurantifolia peel pectin as a polymer
Optimization process of coffee pulp wines combined with the artificial neural network and response surface methodology
Abstract Coffee pulp wine was made from coffee pulp. The level range of fermentation factors was determined by one-factor experiment. The significance factors affecting fermentation were screened by Plackett-Burman and steepest climbing experiments, which were material-liquid ratio, initial pH, initial sugar and yeast amount, respectively. The screened factors were then subjected to a central combination design, and the results were optimized using RSM and ANN-GA. The ANN-GA shows a more accurate optimization effect compared with RSM and a higher degree of model fitting. The coefficient of determination (R2) of the ANN-GA predicted value was 0.9140, while the RMSE was 0.0896. The best results of optimization process showed that the material-liquid ratio was 4.25 : 95.75, the initial pH value was 6.92, the initial sugar concentration was 22.248%, the yeast addition was 1.98%, and the final predicted value was 10.255 mg/L. The research results provided a technical reference for the production of coffee pulp wines.
Computational drug discovery of phytochemical alkaloids targeting the NACHT/PYD domain in the NLRP3 inflammasome
Macrophage-derived pro-inflammatory cytokines augment the cytotoxicity of cytokine-induced killer cells by strengthening the NKG2D pathway in multiple myeloma
Abstract Multiple myeloma (MM) is a clonal hematologic malignancy characterized by low rate of complete remissions. Cytokine-induced killer (CIK) cell therapy has shown promising benefits in MM treatment. In this study, we investigated whether the pro-inflammatory cytokines secreted by macrophages could upregulate MICA/B expression and thus the cytotoxicity of CIK cells. Flow cytometry was used for phenotypic measurement and the cytotoxicity assay of CIK cells. Soluble MICA/B and macrophage-derived cytokines were measured using ELISA assay. CCK-8 assay was applied to evaluate cell viabilities. Gene expression levels were investigated using RT-qPCR. The expression of MICA/B and PD-L1 in MM cells was upregulated by pro-inflammatory cytokines. Pro-inflammatory cytokines enhanced the cytotoxicity of CIK cells against MM cells, with TNF-α exhibiting a more potent effect than IL-1β and IL-6 as it strengthened both components of the NKG2D-MICA/B axis. PD-L1 blockade promoted the cytotoxic ability of CIK cells. Mechanistically, IL-1β, IL-6, and TNF-α enhanced the transcription of MICA/B and PD-L1 genes via the PI3K/AKT, JAK/STAT3, and MKK/p38 MAPK pathways. Pro-inflammatory cytokines upregulated the expression of MICA/B and PD-L1, thereby promoting the cytotoxicity of CIK cells against MM by strengthening the NKG2D pathway, while PD-L1 blockade enhanced the cytotoxicity of CIK cells.
Multi dynamic temporal representation graph convolutional network for traffic flow prediction
Recurring cycles of deprivation of serum and migration in confined spaces augments ganglioside SSEA-4 expression, boosting clonogenicity and cisplatin resistance in TNBC cell line
Abstract The remarkable biophysical properties of metastatic migrating cells, such as their exceptional motility and deformability, enable them to migrate through physical confinements created by neighboring cells or extracellular matrix. This study explores the adaptive responses of breast cancer (BC) cell sublines derived from the highly aggressive, metastatic triple-negative MDA-MB-231 and the non-metastatic MCF7 human BC cell lines, after undergoing three rounds of confined migration (CM) stress. Our findings demonstrate that CM elicits common and cell-type specific adaptive responses in BC cell sublines. In particular, both cell sublines exhibit a similar enhancement of clonogenicity and nanoparticle (NP) uptake activity, indicating tumorigenic potential. We have, for the first time, shown that stimulation with CM induces a hybrid epithelial-to-mesenchymal transition (EMT) phenotype of MDA-MB-231 cells. This transition is characterized by a significant rise in the expression of stage-specific embryonic antigen-4 (SSEA4), alongside a substantial decline in the population of CD133+ cells and a marked reduction in Ki67 expression in the MDA-MB-231-derived subline following Cis-Platin treatment. These changes are likely associated with heightened resistance of this subline to cisplatin. In contrast, CM induces far fewer such alterations in the MCF7-derived counterpart with a notable increase of CD133+ population, which seems to be insufficient to change cell susceptibility to cisplatin exposure. This study contributes to our understanding of the adaptive mechanisms underlying metastasis and drug resistance in breast cancer, emphasizing the need for personalized approaches in cancer treatment that consider the heterogeneous responses of different cancer subtypes to environmental stresses.