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Abstract Background Large variations in respiratory system compliance and resistance may cause the accuracy of tidal volume (VT) delivery beyond the declared range. This study aimed at evaluating the accuracy of VT delivery using a test lung model to simulate pulmonary mechanics under normal or disease conditions. Methods In vitro assessment of the VT delivery accuracy was carried out on two commercial ventilators. Measurements of the inspired and expired VT from the ventilator and FlowAnalyser were compared to evaluate the separated and combined influences of compliance and resistance on the delivered VT accuracy. To do this, the errors of five delivered volumes (30 ml, 50 ml, 100 ml, 300 ml, and 500 ml) were checked under 29 test conditions involving a total of 27 combinations of resistance and compliance. Results For the tested ventilator S1 with a flow sensor near the expiratory valve, the average of expired VT errors (ΔVTexp) in three measurements (4 test conditions for each measurement) correlated to test lung compliance (r=-0.96, p = 0.044), and the average of inspired VT errors (ΔVTins) correlated to compliance (r = 0.89, p = 0.106); for the tested ventilator S2 with a flow sensor located at the Y piece, no clear relationship between compliance and ΔVTexp or ΔVTins was found. Furthermore, on two ventilators tested, the current measurements revealed a poor correlation between test lung resistance and ΔVTins or ΔVTexp, and the maximum values of ΔVTexp and ΔVTins correspond to the maximum resistance of 200 cmH2O/(L/s), at which the phenomenon of the flap fluttering in the variable orifice flow senor was observed, and the recorded peak inspiratory pressure (Ppeak) was much higher than the Ppeak estimated by the classical equation of motion. In contrast, at the lower resistance values of 5, 20, 50 and 100 cmH2O/(L/s), the recorded Ppeak was very close to the estimated Ppeak. Overall, the delivered VT errors were in the range of ± 14% on two ventilators studied. Conclusions Depending on the placement site of the flow sensor in the ventilator circuit, the compliance and resistance of the test lung have different influences on the accuracy of VT delivery, which is further attributed to different fluid dynamics effects of the compliance and resistance. The main influence of compliance is to raise the peak inspiratory pressure Ppeak, thereby increasing the compression volume within the ventilator circuit; whereas a high resistance not only contributes to elevating Ppeak, but more importantly, it governs the gas flow conditions. Ppeak is a critical predictive indicator for the accuracy of the VT delivered by a ventilator.

Sepsis is a life-threatening syndrome resulting from a dysregulated host response to infection. It is the primary cause of death in the intensive care unit, posing a substantial challenge to human health and medical resource allocation. The pathogenesis and pathophysiology of sepsis are complex. During its onset, pro-inflammatory and anti-inflammatory mechanisms engage in intricate interactions, possibly leading to hyperinflammation, immunosuppression, and long-term immune disease. Of all critical outcomes, hyperinflammation is the main cause of early death among patients with sepsis. Therefore, early suppression of hyperinflammation may improve the prognosis of these patients. Nafamostat mesilate is a serine protease inhibitor, which can inhibit the activation of the complement system, coagulation system, and contact system. In this review, we discuss the pathophysiological changes occurring in these systems during sepsis, and describe the possible targets of the serine protease inhibitor nafamostat mesilate in the treatment of this condition.

Abstract Cytokine-induced apoptosis inhibitor 1 (CIAPIN1) is a protein that regulates apoptosis and programmed cell death. This research aims to evaluate its potential role in inhibiting breast cancer cell proliferation, migration, and glycolysis and uncover its underlying molecular mechanism. We collected breast cancer tissue samples from eight patients between January 2019 and June 2023 in our Hospital to analyse CIAPIN1 expression. We transfected human breast cancer cell lines (MCF7, MDA-MB-231, MDA-MB-453, and MDA-MB-468) with siRNA of CIAPIN1. Finally, we determined protein expression using RT-qPCR and Western blotting. CIAPIN1 expression was elevated in both breast cancer tissue and serum. Overexpression of CIAPIN1 detected in the breast cancer cell lines MCF7 and MDA-MB-468. In addition, CIAPIN1 overexpression increased cell proliferation and migration rate. CIAPIN1 downregulation suppressed cell proliferation while elevated cellular apoptosis, reactive oxygen species (ROS) production and oxidative stress in breast cancer cells. Moreover, CIAPIN1 inhibition remarkably suppressed pyruvate, lactate and adenosine triphosphate (ATP) production and reduced the pyruvate kinase M2 (PKM2) protein expression and phosphorylation of signal transducer and activator of transcription 3 (STAT3) in breast cancer cells. Downregulation of CIAPIN1 suppresses cell proliferation, migration and glycolysis capacity in breast cancer cells by inhibiting the STAT3/PKM2 pathway.

Objective The marine organic-rich shale of the Luzhai Formation of the northern Guizhong Depression is an important replacement field for shale gas exploration in the Dian-Qian-Gui Basin. At present, great breakthroughs have been made in the initial stage of exploration. So it is very important to evaluate the geological-engineering integration. Methods In this study, petrophysical data (e.g., core, thin section and scanning electron microscopy data) and logging data (e.g., conventional, imaging, nuclear magnetic resonance and array acoustic) are used to study the logging characteristics of geological and engineering "sweet spots" on the basis of core calibration logs and fine delineation of small layers, respectively. By superimposing the hydrocarbon source rock quality, reservoir quality and engineering quality, the coupling and optimization of geological and engineering "double sweet spots" are finally completed. Results The results show that the lithology of the shale in the first member of the Luzhai Formation is dominated by three types: siliceous shale, mixed shale and gray shale. The organic matter abundance and pore permeability are low, and the TOC content is between 1% and 2%. The biogenic silica content is low, and the source of silica is mainly the land source of debris supply. Shale gas is mainly stored in the pore spaces and microfractures associated with clay minerals, and adsorbed gas is the main source, while the free gas content accounts for a small proportion. The brittleness index ranges from 20% to 80% and is basically greater than 40%. The stress coefficient of variation ranges from 0.26 to 0.50, and the direction of the present maximum horizontal in situ stress is NNE-SSW. Conclusion The shale "sweet spot" section at the bottom of the third small layer was selected as the target window of the horizontal well, and the results of horizontal section drilling and gas measurement showed good results. The research results can provide theoretical guidance and methodological support for the evaluation of "sweet spot" logging and the selection of horizontal well target windows for shale gas wells.

Abstract Apparently, understanding airway management status may help to reduce risk and improve clinical practice. Given these facts, our team conducted a second survey on the current status of airway management for mainland China following our 2016 national airway survey. The national survey was conducted from November 7 to November 28, 2022. An electronic survey was sent to the New Youth Anesthesia Forum, where Chinese anesthesiologists completed the questionnaire via WeChat. A total of 3783 respondents completed the survey, with a response rate of 72.14%. So far, in 2022, 34.84% of anesthesiologists canceled or delayed surgery at least once due to difficult airway. For the anticipated difficult airway management, 66.11% of physicians would choose awake intubation under sedation and topical anesthesia, while the percentage seeking help has decreased compared to the 2016 survey. When encountering an emergency, 74.20% of respondents prefer to use the needle cricothyrotomy, albeit less than a quarter have actually performed it. Anesthesiologists with difficult airway training experience reached 72.96%, with a significant difference in participation between participants in Tier 3 hospitals and those in other levels of hospitals (P

Abstract Background End-expiratory lung volume (EELV) has been observed to decrease in acute respiratory distress syndrome (ARDS). Yet, research investigating EELV in patients with COVID-19 associated ARDS (CARDS) remains limited. It is unclear whether EELV could serve as a potential metric for monitoring disease progression and identifying patients with ARDS at increased risk of adverse outcomes. Study design and methods This retrospective study included mechanically ventilated patients diagnosed with CARDS during the initial phase of epidemic control in Shanghai. EELV was measured using the nitrogen washout-washin technique within 48 h post-intubation, followed by regular assessments every 3–4 days. Chest CT scans, performed within a 24-hour window around each EELV measurement, were analyzed using AI software. Differences in patient demographics, clinical data, respiratory mechanics, EELV, and chest CT findings were assessed using linear mixed models (LMM). Results Out of the 38 patients enrolled, 26.3% survived until discharge from the ICU. In the survivor group, EELV, EELV/predicted body weight (EELV/PBW) and EELV/predicted functional residual capacity (EELV/preFRC) were significantly higher than those in the non-survivor group (survivor group vs. non-survivor group: EELV: 1455 vs. 1162 ml, P = 0.049; EELV/PBW: 24.1 vs. 18.5 ml/kg, P = 0.011; EELV/preFRC: 0.45 vs. 0.34, P = 0.005). Follow-up assessments showed a sustained elevation of EELV/PBW and EELV/preFRC among the survivors. Additionally, EELV exhibited a positive correlation with total lung volume and residual lung volume, while demonstrating a negative correlation with lesion volume determined through chest CT scans analyzed using AI software. Conclusion EELV is a useful indicator for assessing disease severity and monitoring the prognosis of patients with CARDS.

Abstract Heart failure is the final stage of several cardiovascular diseases, and the key to effectively treating heart failure is to reverse or delay ventricular remodelling. Levosimendan is a novel inotropic and vasodilator agent used in heart failure, whereas the impact of levosimendan on ventricular remodelling is still unclear. This study aims to investigate the impact of levosimendan on ventricular remodelling in patients with left ventricular systolic dysfunction. Electronic databases were searched to identify eligible studies. A total of 66 randomized controlled trials involving 7968 patients were included. Meta‐analysis results showed that levosimendan increased left ventricular ejection fraction [mean difference (MD) = 3.62, 95% confidence interval (CI) (2.88, 4.35), P

Summary: Objectives: The exostosins (EXT), which are responsible for heparan sulfate backbone synthesis and play a vital role in tissue homeostasis, have been reported to be correlated with prognosis of various cancers. However, the expression, prognostic value, and immune infiltration of EXT1 and EXT2 in head and neck squamous cell carcinoma (HNSC) remain uncertain. Methods: GEPIA, UALCAN, and Xiantao bioinformatics tools were used to explore the EXT1 and EXT2 expression level in HNSC. GEPIA and Sangerbox were utilised to obtain the prognostic value of EXT1 and EXT2 in HNSC. Genetic alterations, immune cell infiltration, and single-cell analysis were conducted in cBioPortal, TIMER, and TISCH2. In addition, the expressions of EXT1 and EXT2 were validated by real-time polymerase chain reaction (PCR) in HNSC samples. Results: EXT1 and EXT2 were highly expressed in HNSC, especially in malignant cells. Only EXT2 was significantly negatively correlated to the prognosis of patients with HNSC. EXT1 and EXT2 were found to be associated with focal adhesin and cell adhesin molecule binding. EXT1 expression levels were considerably connected with CD8+ T cell infiltrating levels, whilst EXT2 expression levels were considerably negatively connected with infiltrating levels of CD4+ T cells, macrophages, neutrophils, and dendritic cells in HNSC. The gene mutation rates of EXT1 and EXT2 in HNSC were 7% and 2.8%, respectively. Moreover, EXT2 was validated to be highly expressed in HNSC samples by real-time PCR. Conclusion: EXT2 was highly expressed and presented negative correlation with the prognosis and immune infiltration of HNSC, which might be a potential biomarker for HNSC.

Recent advancements in facial expression synthesis using deep learning, particularly with Cycle-Consistent Adversarial Networks (CycleGAN), have led to impressive results. However, a critical challenge persists: the generated expressions often lack the sharpness and fine details of the original face, such as freckles, moles, or birthmarks. To address this issue, we introduce the Facial Expression Morphing (FEM) algorithm, a novel post-processing method designed to enhance the visual fidelity of CycleGAN-based outputs. The FEM method blends the input image with the generated expression, prioritizing the preservation of crucial facial details. We experimented with our method on the Radboud Faces Database (RafD) and evaluated employing the Fréchet Inception Distance (FID) standard benchmark for image-to-image translation and introducing a new metric, FSD (Facial Similarity Distance), to specifically measure the similarity between translated and real images. Our comprehensive analysis of CycleGAN, UNet Vision Transformer cycle-consistent GAN versions 1 (UVCGANv1) and 2 (UVCGANv2) reveals a substantial enhancement in image clarity and preservation of intricate details. The average FID score of 31.92 achieved by our models represents a remarkable 50% reduction compared to the previous state-of-the-art model’s score of 63.82, showcasing the significant advancements made in this domain. This substantial enhancement in image quality is further supported by our proposed FSD metric, which shows a closer resemblance between FEM-processed images and the original faces.

BackgroundNamed entity recognition (NER) models are essential for extracting structured information from unstructured medical texts by identifying entities such as diseases, treatments, and conditions, enhancing clinical decision-making and research. Innovations in machine learning, particularly those involving Bidirectional Encoder Representations From Transformers (BERT)–based deep learning and large language models, have significantly advanced NER capabilities. However, their performance varies across medical datasets due to the complexity and diversity of medical terminology. Previous studies have often focused on overall performance, neglecting specific challenges in medical contexts and the impact of macrofactors like lexical composition on prediction accuracy. These gaps hinder the development of optimized NER models for medical applications. ObjectiveThis study aims to meticulously evaluate the performance of various NER models in the context of medical text analysis, focusing on how complex medical terminology affects entity recognition accuracy. Additionally, we explored the influence of macrofactors on model performance, seeking to provide insights for refining NER models and enhancing their reliability for medical applications. MethodsThis study comprehensively evaluated 7 NER models—hidden Markov models, conditional random fields, BERT for Biomedical Text Mining, Big Transformer Models for Efficient Long-Sequence Attention, Decoding-enhanced BERT with Disentangled Attention, Robustly Optimized BERT Pretraining Approach, and Gemma—across 3 medical datasets: Revised Joint Workshop on Natural Language Processing in Biomedicine and its Applications (JNLPBA), BioCreative V CDR, and Anatomical Entity Mention (AnatEM). The evaluation focused on prediction accuracy, resource use (eg, central processing unit and graphics processing unit use), and the impact of fine-tuning hyperparameters. The macrofactors affecting model performance were also screened using the multilevel factor elimination algorithm. ResultsThe fine-tuned BERT for Biomedical Text Mining, with balanced resource use, generally achieved the highest prediction accuracy across the Revised JNLPBA and AnatEM datasets, with microaverage (AVG_MICRO) scores of 0.932 and 0.8494, respectively, highlighting its superior proficiency in identifying medical entities. Gemma, fine-tuned using the low-rank adaptation technique, achieved the highest accuracy on the BioCreative V CDR dataset with an AVG_MICRO score of 0.9962 but exhibited variability across the other datasets (AVG_MICRO scores of 0.9088 on the Revised JNLPBA and 0.8029 on AnatEM), indicating a need for further optimization. In addition, our analysis revealed that 2 macrofactors, entity phrase length and the number of entity words in each entity phrase, significantly influenced model performance. ConclusionsThis study highlights the essential role of NER models in medical informatics, emphasizing the imperative for model optimization via precise data targeting and fine-tuning. The insights from this study will notably improve clinical decision-making and facilitate the creation of more sophisticated and effective medical NER models.

Abstract Due to its decade‐long progression, colorectal cancer (CRC) is most suitable for population screening to achieve a significant reduction in its incidence and mortality. DNA methylation has emerged as a potential marker for the early detection of CRC. However, the current mainstream methylation detection method represented by bisulfite conversion has issues such as tedious operation, DNA damage, and unsatisfactory sensitivity. Herein, a new high‐performance CRC screening tool based on the promising specific terminal‐mediated polymerase chain reaction (STEM‐PCR) strategy is developed. CRC‐related methylation‐specific candidate CpG sites are first prescreened through The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases using self‐developed bioinformatics. Next, 9 homebrew colorectal cancer DNA methylated STEM‒PCR assays (ColoC‐mSTEM) with high sensitivity (0.1%) and high specificity are established to identify candidate sites. The clinical diagnostic performance of these selected methylation sites is confirmed and validated by a case‐control study. The optimized diagnostic model has an overall sensitivity of 94.8% and a specificity of 95.0% for detecting early‐stage CRC. Taken together, ColoC‐mSTEM, based on a single methylation‐specific site, is a promising diagnostic approach for the early detection of CRC which is perfectly suitable for the screening needs of CRC in primary healthcare institutions.

Cardiomyocyte loss and myocardial fibrosis are major determinants of myocardial infarction (MI) pathological changes. Mesenchymal stem cell (MSC)-derived exosomes (exos) and Danshen decoction (DSY) have been demonstrated to mediate cardiac repair following MI. BM-MSCs exos or BM-MSCsDSY exos were intramuscularly injected into post-MI rats. On the 7th, 14th and 28th days, serum CK, LDH, α-HBDH, ALT, and AST were measured and electrocardiogram changes were monitored to identify cardiac function; Triphenyltetrazolium chloride staining, Hematein&Eosin staining, Masson trichrome staining and Transmission Electron Microscope were adopted to analyze infarct area, cardiac morphology, histopathology, and fibrosis and cardiomyocyte ultrastructure; TUNEL assay, real-time PCR and western blot were performed to detect cardiomyocyte apoptosis and autophagy. As a result, BMMSCsDSY exos are superior to BM‐MSCs‐exos in improvement of cardiac function, morphology, histopathology and cardiomyocyte ultrastructure, as well as in reduction of infarction area and cardiac fibrosis by inhibiting apoptosis and promoting autophagy of cardiomyocytes.

BackgroundPulmonary arterial hypertension (PAH) is a serious condition characterized by elevated pulmonary artery pressure, leading to right heart failure and increased mortality. This study investigates the link between PAH and genes associated with hypoxia and cuproptosis.MethodsWe utilized expression profiles and single-cell RNA-seq data of PAH from the GEO database and genecad. Genes related to cuproptosis and hypoxia were identified. After normalizing the data, differential gene expression was analyzed between PAH and control groups. We performed clustering analyses on cuproptosis-related genes and constructed a weighted gene co-expression network (WGCNA) to identify key genes linked to cuproptosis subtype scores. KEGG, GO, and DO enrichment analyses were conducted for hypoxia-related genes, and a protein–protein interaction (PPI) network was created using STRING. Immune cell composition differences were examined between groups. SingleR and Seurat were used for scRNA-seq data analysis, with PCA and t-SNE for dimensionality reduction. We analyzed hub gene expression across single-cell clusters and built a diagnostic model using LASSO and random forest, optimizing parameters with 10-fold cross-validation. A total of 113 combinations of 12 machine learning algorithms were employed to evaluate model accuracy. GSEA was utilized for pathway enrichment analysis of AHR and FAS, and a Nomogram was created to assess risk impact. We also analyzed the correlation between key genes and immune cell types using Spearman correlation.ResultsWe identified several diagnostic genes for PAH linked to hypoxia and cuproptosis. PPI networks illustrated relationships among these hub genes, with immune infiltration analysis highlighting associations with monocytes, macrophages, and CD8 T cells. The genes AHR, FAS, and FGF2 emerged as key markers, forming a robust diagnostic model (NaiveBayes) with an AUC of 0.9.ConclusionAHR, FAS, and FGF2 were identified as potential biomarkers for PAH, influencing cell proliferation and inflammatory responses, thereby offering new insights for PAH prevention and treatment.

Background: Current research has demonstrated that Simvastatin (SIM) and Whole Body Vibration (WBV) actively contributes to the repair of osteoporotic bones. However, there is still limited knowledge regarding the impact of this combined therapy on osseointegration in elderly individuals. Objective: The objective of this study was to verify the influence of WBV and SIM combination treatment on Titanium implants' fixation strength in aged rats. Methods: Male Sprague-Dawley rats at 24 months old were utilized for this investigation. Titanium rods were surgically inserted into the distal femoral canal on their left side. Subsequently, all animals were randomly assigned to one of four groups: Control group; WBV group; SIM group; and WBV + SIM group. Each group received Saline, Whole Body Vibration, Simvastatin, or a combination of Whole Body Vibration plus Simvastatin treatment until they reached their natural death after 12 weeks. The bilateral femurs and serum samples from these rats were collected for evaluation purposes. Results: Both WBV and SIM treatments exhibited an increase in bone mass, osseointegration, and push-out force compared to the Control group (all, P

Abstract Use of a flexible thermoelectric source is a feasible approach to realizing self‐powered wearable electronics and the Internet of Things. Inorganic thin films are promising candidates for fabricating flexible power supply, but obtaining high‐thermoelectric‐performance thin films remains a big challenge. In the present work, a p‐type BixSb2−xTe3 thin film is designed with a high figure of merit of 1.11 at 393 K and exceptional flexibility (less than 5% increase in resistance after 1000 cycles of bending at a radius of ∼5 mm). The favorable comprehensive performance of the BixSb2−xTe3 flexible thin film is due to its excellent crystallinity, optimized carrier concentration, and low elastic modulus, which have been verified by experiments and theoretical calculations. Further, a flexible device is fabricated using the prepared p‐type BixSb2−xTe3 and n‐type Ag2Se thin films. Consequently, an outstanding power density of ∼1028 μW cm−2 is achieved at a temperature difference of 25 K. This work extends a novel concept to the fabrication of high‐performance flexible thin films and devices for wearable energy harvesting.

Abstract The colon is the largest compartment of the immune system, with innate immune cells exposed to antigens in the environment. However, the mechanisms by which the innate immune system is instigated are poorly defined in colorectal cancer (CRC). Here, a population of CD16+ neutrophils that specifically accumulate in CRC tumor tissues by imaging mass cytometry (IMC), immune fluorescence, and flow cytometry, which demonstrated pro‐tumor activity by disturbing natural killer (NK) cells are identified. It is found that these CD16+ neutrophils possess abnormal cholesterol accumulation due to activation of the CD16/TAK1/NF‐κB axis, which upregulates scavenger receptors for cholesterol intake including CD36 and LRP1. Consequently, these region‐specific CD16+ neutrophils not only competitively inhibit cholesterol intake of NK cells, which interrupts NK lipid raft formation and blocks their antitumor signaling but also release neutrophil extracellular traps (NETs) to induce the death of NK cells. Furthermore, CD16‐knockout reverses the pro‐tumor activity of neutrophils and restored NK cell cytotoxicity. Collectively, the findings suggest that CRC region‐specific CD16+ neutrophils can be a diagnostic marker and potential therapeutic target for CRC.

The investigation of oil and gas migration plays a vital role in the field of oil and gas exploration and development. Determining the direction and path of crude oil migration is challenging due to factors such as crude oil viscosity, complex chemical composition, and geological influences. Molecular geochemical parameters are a valuable tool for studying petroleum migration, although they can be affected by factors like compound formation, distribution, and maturation. One approach involves simulating these parameters under controlled laboratory conditions to isolate their individual effects. This study establishes a sandy-packed system to simulate oil-driven experiments and uses a C18 solid-phase extraction column to analyze carbazole compound fractions at different migration distances. The findings indicate that certain carbazole parameters, such as 1-/4-MCA, 1, 8-/1, 7-DMCA, 1, 8-/2, 4-DMCA, 1, 8-/2, 5-DMCA, and 1, 8-/2, 7-DMCA, increase significantly with transport distances. Notably, fully shielded and fully exposed isomers like 1, 8-/2, 4-DMCA and 1, 8-/2, 5-DMCA show enrichment levels of up to 63.97% and 35.50%, making them potential indicators of oil migration. However, parameters related to benzo [a]/[c] carbazole show inconsistencies with previous findings, likely due to intrinsic configurations and varying geological conditions that must be taken into account. The experimental results presented in this study offer insights for assessing specific reservoirs, with a recommendation to also consider molecular kinetics when selecting molecular parameters.

In recent years, there has been widespread attention on hypergraphs as a research hotspot in network science.The unique structure of hypergraphs, which differs from traditional graphs, is characterized by hyperedges that can connect multiple nodes simultaneously, resulting in more complex and higher-order relationships.Effectively identifying important nodes and hyperedges in such network structures poses a key challenge.Eigenvector centrality, a common metric, has limitations in its application due to its locality when dealing with hub nodes with extremely high degree values in the network.To address this issue, the hypergraphs were transformed into their corresponding line graphs, and non-backtracking matrix centrality was employed as a method to measure the importance of hyperedges.This approach demonstrated better uniformity and differentiation in assessing the importance of hyperedges.Furthermore, the application of both eigenvector centrality and non-backtracking matrix centrality in assessing the importance of nodes in hypergraphs was explored.Comparative analysis revealed that non-backtracking matrix centrality effectively distinguished the importance of nodes.This research encompassed theoretical analysis, model construction, and empirical studies on real-world data.To validate the proposed method and conclusion, six real-world hypergraphs were selected as experimental subjects.The application of these methods to these hypergraphs confirmed the effectiveness of non-backtracking matrix centrality in identifying important nodes and hyperedges.The findings of this research offer a fresh perspective and approach for identifying key elements in hypergraphs, holding significant theoretical and practical implications for understanding and analyzing complex network systems.

Abstract The rodent running‐wheel recording apparatus is a reliable approach for studying circadian rhythm. This study demonstrated how to construct a simple and intelligent running‐wheel recording system. The running wheel was attached to the cage's base, whereas the Hall sensor was attached to the cage's cover. Then, the RJ25 adaptor relayed the running signal to the main control board. Finally, the main control board was connected to the USB port of the computer with the USB connection. Data were collected using the online‐accessible, self‐created software Magturning. Through Magturning, generated data were saved and exported in real time. Afterward, the device was validated by collecting data on the locomotor activities of mice under different light conditions. In conclusion, this new device can record circadian activity of rodents. Our device is appropriate for interdisciplinary investigations related to biological clock research.

Abstract The Alectoris Chukar (chukar) is the most geographically widespread partridge species in the world, demonstrating exceptional adaptability to diverse ecological environments. However, the scarcity of genetic resources for chukar has hindered research into its adaptive evolution and molecular breeding. In this study, we have sequenced and assembled a high-quality, phased chukar genome that consists of 31 pairs of relatively complete diploid chromosomes. Our BUSCO analysis reported a high completeness score of 96.8% and 96.5%, with respect to universal single-copy orthologs and a low duplication rate (0.3% and 0.5%) for two assemblies. Through resequencing and population genomic analyses of six subspecies, we have curated invaluable genotype data that underscores the adaptive evolution of chukar in response to both arid and high-altitude environments. These data will significantly contribute to research on how chukars adaptively evolve to cope with desertification and alpine climates.

Abstract We are writing to you in response to the article published in BMC Nephrology titled “Dose of nafamostat mesylate during continuous kidney replacement therapy in critically ill patients: a two-centre observational study”. The study provided valuable information on the use of nafamostat mesylate (NM) during continuous renal replacement therapy (CRRT) in critically ill patients. We noticed in this study that a higher dose of NM resulted in a decrease in ICU and hospital mortality. However, the underlying mechanism behind this phenomenon remains unclear. We believe exploring this further is warranted.

ObjectivesThis study aimed to explore the synergistic interaction effect between hyperuricemia and hypertension towards chronic kidney disease in patients with type 2 diabetes.MethodsThis research originates from a cross-sectional study performed in Zhejiang Province, Eastern China, between March and November 2018. The correlation between serum uric acid levels and the risk of chronic kidney disease was assessed using a restricted cubic spline model. An unconditional multivariable logistic regression model, along with an interaction table, was utilized to explore the potential interaction effect of hyperuricemia and hypertension towards chronic kidney disease.Results1,756 patients with type 2 diabetes were included in this study, the prevalence of chronic kidney disease (CKD) was 27.62% in this population. A U-shaped non-linear pattern emerged correlating serum uric acid (SUA) levels and CKD risk, indicating that both low and high SUA levels were linked to an increased CKD risk. This risk achieved its lowest point (nadir) at SUA approximately equals to 285μmol/L (p for trend

Fiber reinforced polymer (FRP) bars have become increasingly popular, while the studies on durability of FRP bars are primarily on small-diameter FRP bars. This study investigated the tensile strength retention in glass FRP (GFRP) bars of different diameters (13 mm and 25 mm) after immersion in an alkaline solution (pH=12.6) at various temperatures (20 °C, 40 °C and 60 °C) for 1, 2, 3, and 6 months. The results reveal that the degradation of GFRP bars was slow at 20 °C, accelerated but not pronounced at 40 °C and considerable at 60 °C. Particularly, the 13 mm diameter GFRP bars exhibited a more significant reduction in tensile strength, with a decrease of 20.12 % after 6 months, while the 25 mm diameter bars only decreased by 13.23 %. Results reveal that, importantly, degradation of GFRP bars is primarily attributed to the diffusion of the moisture and alkalis, which disrupts the bond between the fibers and the matrix, causing interface damage. Finally, based on the Arrhenius theory, it is predicted that the tensile strength retention of 13 mm and 25 mm diameter GFRP bars will be 66.4 % and 79.8 %, respectively, after 50 years of exposure at an average annual temperature of 35 °C. The important finding that the small-diameter FRP bars are more vulnerable to the alkaline exposure than larger diameter bars suggests that the current studies on durability of FRP bars are conservative to be referred in practice.