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Abstract In the vascular system, angiotensin II (Ang II) mediated vasoconstriction by inducing the production of 20-hydroxyeicosatetraenoic acid (20-HETE). However, the role of 20-HETE in Ang II-induced cardiac dysfunction had yet to be fully elucidated. This study investigated the effects of Ang II on CYP4A expression and 20-HETE production in H9c2 cells using RT-qPCR, Western blot, and ELISA. The role of 20-HETE in Ang II-induced cardiac hypertrophy was examined using DHE, MitoSOX, and JC-1 staining to evaluate reactive oxygen species (ROS) generation and mitochondrial membrane potential changes. The ERK/Akt and CaN/NFAT3 signaling pathways were analyzed through Western blot. Ang II was found to promote CYP4A expression and 20-HETE production in H9c2 cells via an AT1 receptor-dependent mechanism. Additionally, the upregulation of AT1 receptor expression by 20-HETE further confirms its facilitatory effect on the Ang II signaling pathway. Inhibition of 20-HETE synthesis or blockade of its receptor, G-protein-coupled receptor 75 (GPR75), significantly reversed Ang II-induced cardiac hypertrophy. This reversal was closely associated with 20-HETE-induced ROS production, oxidative stress, and activation of the Ca2+/CaN/NFAT3 signaling pathway. This study demonstrated that 20-HETE mediated Ang II-induced cardiac hypertrophy and, for the first time, highlighted the significant role of the GPR75 receptor in this process. These findings suggested that targeting 20-HETE reduction or blocking its receptor action could offer a novel therapeutic approach for cardiovascular diseases associated with Ang II.

Abstract Background The refinement of risk stratification in lung adenocarcinoma (LUAD) plays a pivotal role in advancing precision medicine; however, the current staging classification falls short of comprehensiveness, particularly in the case of stage IA patients. We aimed to molecularly stratify LUAD patients especially for stage IA. Methods We analysed tumour heterogeneity and identified highly proliferating cancer cells (HPCs) in LUAD by performing single-cell RNA sequencing (scRNA-seq) analysis, immunohistochemical (IHC) staining using a tissue microarray, flow cytometry and biological experiments. Then, we quantified the content of HPCs in nine LUAD datasets by single-sample gene set enrichment analysis and evaluated the relationship between the percentage of HPCs and overall survival (OS). Next, we analysed the OS predictive effect of HPCs at different LUAD stages, especially for stage I risk stratification. Furthermore, we established a prognostic prediction model based on HPC-associated genes for clinical application. The above findings were validated in another five LUAD datasets. Finally, we explored the relationship between HPCs and the progressive pathological evolution of early-stage LUAD and the driving mutations by scRNA-seq, bulk RNA-seq and IHC staining. Results LUAD tissues carry a small proportion of HPCs, which show potential for malignant proliferation and intense interactions with the microenvironment. A high HPC content is an independent risk factor for OS in LUAD patients, even in stage IA patients. HPCs can be used to establish a cut-off point for the prognosis of stage IA disease, with patients with a higher risk showing a prognosis similar to that of patients with stage IB disease. We built an R package (HSurADs) based on HPC-associated genes, which exhibited good efficacy for the prognostic prediction of LUAD. HPCs gradually increase with the pathological evolution of early-stage LUAD, which may be affected by TP53 mutations. Conclusion The HPC content can be used as a novel prognostic factor for LUAD, especially for stage IA risk stratification.

Fluoropolymers play a crucial role as binders in polymer-bonded explosive (PBX) formulations. However, there is a lack of clear understanding of the effects of increased fluoropolymer crystallinity on the shock response of PBXs in the service environment. This study investigated the shock Hugoniots of two widely applied fluoropolymer binders: (1) F2314 from China—a copolymer with a molar ratio of vinylidene fluoride (VDF) to chlorotrifluoroethylene (CTFE) of 1:4 and (2) F2313 from the United States, also known as Kel F-800, with a VDF to CTFE molar ratio of 1:3. The Hugoniot curves of both fluoropolymers were calculated based on equilibrium molecular dynamics (MD) and a mixing rule. Furthermore, the corresponding P–V curves were obtained through fitting using the Tait equation of state (EOS). Their calculated parameters, including zero-pressure bulk modulus (κo) and sound velocity (co), agreed well with experimental data. The results reveal that the Hugoniots of amorphous F2314 and F2313 exhibited negligible differences. However, increasing crystallinity significantly impacted the Hugoniot curves of both fluoropolymers, especially for F2314 with high crystallinity. The obtained macroscopic characteristic parameters, namely κo and co, exhibited an exponential dependence on crystallinity. Physically, this phenomenon can be attributed to a reduction in the compressible free volume of the fluoropolymers due to a more orderly chain arrangement. Additionally, under the same compression ratio, the shock temperature of the fluoropolymers increased with the crystallinity, posing potential safety risks to explosives. These findings establish a correlation between the crystallinity of fluoropolymers and the shock properties of PBXs, providing a theoretical reference for the formulation design of fluoropolymer-based PBXs.

Abstract This study aimed to reveal the effect of traditional Chinese herbal medicine residues (TCHMR) on growth performance, hematology, ruminal microbiota, and economic benefits of Guizhou black male goats through the fermented total mixed ration (FTMR) diet technique. A total of 22 Guizhou black male goats with an initial weight of 21.77 ± 0.85 kg were randomly divided into 2 groups (n = 11), with 11 goats in each group. The control group (CON) was fed a traditional total mixed ration (TMR) diet without the TCHMR. The TCHMR group was fed an FTMR diet containing 40%TCHMR. Compared with the CON group, the results showed that the incorporation of TCHMR into goat diets reduced feeding costs and Feed conversion ratio (FCR). On the contrary, it improved (P

Introduction: Gibberellin (GA) is a vital phytohormone in regulating plant growth and development. During the “Green Revolution”, modification of GA-related genes created semi-dwarfing phenotype in cereal crops but adversely affected grain weight. Gibberellin 2-oxidases (GA2oxs) in barley act as key catabolic enzymes in deactivating GA, but their functions are still less known. Objectives: This study investigates the physiological function of two HvGA2ox genes in barley and identifies novel semi-dwarf alleles with minimum impacts on other agronomic traits. Methods: Virus-induced gene silencing and CRISPR/Cas9 technology were used to manipulate gene expression of HvGA2ox9 and HvGA2ox8a in barley and RNA-seq was conducted to compare the transcriptome between wild type and mutants. Also, field trials in multiple environments were performed to detect the functional haplotypes. Results: There were ten GA2oxs that distinctly expressed in shoot, tiller, inflorescence, grain, embryo and root. Knockdown of HvGA2ox9 did not affect plant height, while ga2ox8a mutants generated by CRISPR/Cas9 increased plant height and significantly altered seed width and weight due to the increased bioactive GA4 level. RNA-seq analysis revealed that genes involved in starch and sucrose metabolism were significantly decreased in the inflorescence of ga2ox8a mutants. Furthermore, haplotype analysis revealed one naturally occurring HvGA2ox8a haplotype was associated with decreased plant height, early flowering and wider and heavier seed. Conclusion: Our results demonstrate the potential of manipulating GA2ox genes to fine tune GA signalling and biofunctions in desired plant tissues and open a promising avenue for minimising the trade-off effects of Green Revolution semi-dwarfing genes on grain size and weight. The knowledge will promote the development of next generation barley cultivars with better adaptation to a changing climate.

Interactions between bone cells and neurocytes are crucial for endosseous nerve and ensuing bone regeneration. However, absence of neural stem cells in bone makes the innervation of implant osseointegration a major challenge. Herein, a nanorod-like array of sodium hydrogen titanate (ST) co-doped with Co2+ and Co3+, namely STCh that behaves as a reactive oxygen species (ROS)-scavenging enzyme, was hydrothermally formed on Ti substrate. We show that the doped Co2+ and Co3+ locate at TiO6 octahedral interlayers and within octahedra of STCh lattice, appearing releasable and un-releasable, respectively, leading to an increase in Co3+/Co2+ ratio and enzyme activity of the array with immersion. The nanoenzyme-released Co2+ triggers macrophages (MΦs) towards M1 phenotype, then the nanoenzyme scavenges extracellular ROS inducing M1-to-M2 transition. The neurogenic factors secreted by STCh-regulated MΦs, in combination with the released Co2+, promote mesenchymal stem cells to differentiate into neurons and Schwann cells compared to sole Co2+and ST. STCh array greatly enhances nerve reconstruction, type-H capillary formation and ensuing osseointegration in normal rat bone, and antibacteria via engulfing S. aureus by MΦs and osteogenesis in infective case. This nanoenzyme provides an alternative strategy to orchestrate endosseous nerve regeneration for osseointegration without loading exogenous neurotrophins in implants.

Abstract River ecosystems face challenges due to environmental degradation and alterations in flow and sediment transport resulting from climate change and other anthropogenic impacts. These changes may substantially affect river morphology, nutrient dynamics, wetland vegetation, aquatic habitats, and river ecological stability. This highlights the urgent need for systematic and quantitative studies on the interactions and feedback between changes in flow, sediment transport, and river ecology. In this study, we reviewed flow and sediment transport changes in major Chinese rivers, along with their resulting ecological impacts. We propose conducting eco‐fluvial dynamic studies, a potential solution that can guide the evaluation and restoration of ecological health impacted by physical processes. These studies can provide major benefits in balancing human and environmental needs in large river systems, which is crucial for the healthy and sustainable development of rivers.

Abstract Background The triglyceride–glucose (TyG) index has garnered recognition as a surrogate marker for insulin resistance, a pivotal factor in the pathogenesis of various metabolic disorders. Despite its emerging role, the empirical evidence delineating its association with prediabetes mellitus (Pre-DM) remains scant. This research aims to clarify the link between the TyG index and the likelihood of Pre-DM development within a Chinese demographic. Methods This investigation was structured as a retrospective cohort analysis, encompassing a sample of 179,177 Chinese adults. These individuals underwent medical examinations at the Rich Healthcare Group over a period spanning from 2010 to 2016. To ascertain the relationship between the TyG index and the incidence of Pre-DM, this study employed Cox regression analysis complemented by sensitivity and subgroup assessments. Furthermore, Cox proportional hazards regression with cubic spline functions and smooth curve fitting was incorporated to explore the existence of any non-linear connection within this association. Results Upon adjusting for a comprehensive array of confounding variables, a statistically significant positive correlation between the TyG index and the risk of Pre-DM was identified (HR: 1.60, 95%CI 1.56–1.65, P

Abstract Background: Relative fat mass (RFM) represents a newly developed sex-specific anthropometric formula to estimate total body fat percentage. Nonetheless, research examining the correlation between RFM and the risk of diabetes remains scarce. This research assessed the link between RFM and DM risk within the Japanese demographic. Methods: From 2004 to 2015, 15,462 Japanese individuals without diabetes underwent physical evaluations at Murakami Memorial Hospital. The relationship between RFM and the onset of diabetes was analyzed separately using Cox proportional-hazards regression models. This study employed Cox proportional hazards regression incorporating cubic spline functions and smooth curve fitting to detect non-linear associations between RFM and new cases of diabetes, categorized by sex. Sensitivity analyses were performed to confirm the robustness of the link between RFM and incident diabetes. Results: After controlling for confounding factors, a significant positive correlation between RFM and diabetes risk was found in women (HR: 1.13, 95%CI: 1.04–1.24, P = 0.0061), while the association in men was not statistically significant (HR: 1.05, 95%CI: 0.98–1.13, P = 0.1511). Additionally, a non-linear relationship between RFM and the incidence of diabetes was detected in both genders. The RFM threshold was identified at 39.23 for women and 23.08 for men. For women, HR was 1.11 (95%CI: 1.01–1.21) below the threshold and 1.39 (95%CI: 1.17–1.65) above it. In men, an RFM above 23.08 was positively related to diabetes risk (HR: 1.16, 95%CI: 1.06–1.28, P = 0.0012), whereas an RFM below this point did not show a significant association (HR: 0.98, 95%CI: 0.91–1.06, P = 0.5899). Conclusion: Our findings suggest a non-linear relationship and threshold effect between RFM and the risk of diabetes. These findings imply that maintaining RFM at lower levels may be beneficial in mitigating the onset of DM.

Abstract Recent progress in elucidating the role of specific antidiuretic hormones in Drosophila models has provided valuable insights into the mechanisms underlying tumor-induced renal dysfunction. Xu et al. identified the mammalian neurokinin 3 receptor (TACR3), a homolog of the G protein-coupled receptor TkR99D in fruit flies, as a potential therapeutic target for alleviating renal tubular dysfunction in mice with malignant neoplasms. Here, we commented on these findings by emphasizing the structural and evolutionary significance of TACR3 and provided an in-depth analysis of cell type specific expression of TACR3 in response to renal injury and expressional dynamics during renal carcinoma progression. The implications of these findings for transforming the therapeutic approaches to renal complications associated with oncological disorders were highlighted. We also acknowledged the limitations of current experimental models in this study and emphasized the necessary clinical validation in the future. These insights could contribute to the advancement of diagnostic and therapeutic strategies for treating tumor-related renal pathologies. Graphical Abstract

Understanding the response of solid combustibles under high radiant fluxes is critical in predicting the thermal damage from extreme scenarios. Unlike the more moderate radiant fluxes in conventional hydrocarbon fires, extreme events such as strong explosion, concentrated sunlight and directed energy can generate dynamic radiant fluxes at the MW/m2 level, creating a unique threat to materials. This study investigates the pyrolysis and spontaneous ignition behaviors of corrugated cardboard by using both experimental and numerical methods, under 10-cm dynamic high radiant fluxes ranging from 0.2 to 1.25 MW/m2 for 10 s. The spontaneous ignition process at dynamic high radiant fluxes was recorded and quantified. Two ignition modes were found at the critical radiant flux of 0.4 MW/m2, namely hot-gas spontaneous ignition and hot-residue piloted ignition. The latter is not the focus of this paper due to its extremely small probability of occurrence. The research reveals that the increase in flux intensity induces shorter delay times for both pyrolysis and ignition, lower ignition energy density, along with a corresponding rise in the critical mass flux and surface temperature at ignition moment. The simulation results are generally aligned with the experimental findings, despite some divergences may be attributed to model simplifications and parameter assumptions. The work contributes to a deeper insight into material behavior under extreme radiation, with valuable implications for fire safety and hazard assessment.

Abstract Thyroid cancer (TC) represents one of the most prevalent endocrine malignancies, with a rising incidence worldwide. Epigenetic alterations, which modify gene expression without altering the underlying DNA sequence, have garnered significant attention in recent years. Increasing evidence underscores the pivotal role of epigenetic modifications, including DNA methylation, RNA methylation, and histone methylation, in the pathogenesis of TC. This review provides a comprehensive overview of these reversible and environmentally influenced epigenetic modifications, highlighting their molecular mechanisms and functional roles in TC. Additionally, the clinical implications, challenges associated with studying these epigenetic modifications, and potential future research directions are explored. Graphical Abstract

Natural products have been a reliable source of drug compounds in medical research. Technological advances have led to the discovery and characterization of many compounds that were previously difficult to isolate. However, when searching for anticancer drugs, finding natural compounds that can bind to specific targets is a daunting task. Polycyclic tetramate macrolactams (PoTeMs), specifically, have been a source of antibiotics for a long time, though they possess certain cytotoxic properties that make them attractive candidates for anticancer drug discovery. This review covers the structural diversity and widespread availability of PoTeM compounds and the past research that demonstrates their effects on human cancer cell lines. Additionally, this review documents the known receptors and molecular mechanisms of these compounds in mammalian cells.

Abstract Background An increased incidence of brain abscesses was observed post-COVID-19 pandemic. However, it remains unclear how the COVID-19 pandemic influenced the epidemiology of brain abscesses. This study aimed to investigate changes in the epidemiology of brain abscesses pre- and post-COVID-19 pandemic. Methods A retrospective study of demographic, clinical, radiological, and laboratory characteristics of patients with brain abscesses in Children's Hospital of Soochow University from 2015–2023 was performed. Results A total of 34 patients were admitted to the hospital during the study. The post-COVID-19 cohort had an average of 5.5 cases/year, which is a 129.2% increase compared to the pre-COVID-19 cohort's average of 2.4 cases/year. Additionally, the rates of fever upon admission (86.36% vs 50%, p = 0.04) and experiencing high-grade fever within 6 weeks before admission (40.91% vs 8.33%, p = 0.044) were significantly increased. A potential rise in the rate of intensive care unit admission was observed (36.36% vs 8.33%, p = 0.113). The average value of globulin in the post-COVID cohort was significantly higher compared to the pre-COVID cohort (31.60 ± 5.97 vs 25.50 ± 5.08, p = 0.009). Streptococcal infections were the predominant cause of brain abscesses in both cohorts (40% vs 43.75%, p = 0.57). Conclusions There was a significant increase in the number of brain abscess patients after the COVID-19 pandemic. This underscores the importance of children receiving the streptococcal vaccine.

The COVID-19 pandemic is caused by a novel and rapidly mutating coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although several drugs are already in clinical use or under emergency authorization, there is still an urgent need to develop new drugs. Through the mining and analysis of 2776 genomes of the SARS-CoV-2 virus, we identified papain-like protease (PLpro), which is a critical enzyme required for coronavirus to generate a functional replicase complex and manipulate post-translational modifications on host proteins for evasion against host antiviral immune responses, as a conserved molecular target for the development of anti-SARS-CoV-2 therapy. We then made an infection model using the NCI-H1299 cell line stably expressing SARS-CoV-2 PLpro protein (NCI-H1299/PLpro). To investigate the effect of targeting and degrading PLpro mRNA, a compact CRISPR-Cas13 system targeting PLpro mRNA was developed and validated, which was then delivered to the aforementioned NCI-H1299/PLpro cells. The results showed that CRISPR-Cas13 mediated mRNA degradation successfully reduced the expression of viral PLpro protein. By combining the power of AAV and CRISPR-Cas13 technologies, we aim to explore the potential of attenuating viral infection by targeted degradation of important viral mRNAs via safe and efficient delivery of AAV carrying the CRISPR-Cas13 system. This study demonstrated a virus-against-virus gene therapy strategy for COVID-19 and provided evidence for the future development of therapies against SARS-CoV-2 and other RNA viral infections.

Abstract Autophagy is crucial for synaptic plasticity and the architecture of dendritic spines. However, the role of autophagy in schizophrenia (SCZ) and the mechanisms through which it affects synaptic function remain unclear. In this study, we identified 995 single nucleotide polymorphisms (SNPs) across 19 autophagy-related genes that are associated with SCZ. Gene Set Enrichment Analysis (GSEA) of data from the Gene Expression Omnibus public database revealed defective autophagy in patients with SCZ. Using a maternal immune activation (MIA) rat model, we observed that autophagy was downregulated during the weaning period, and early-life activation of autophagy with rapamycin restored abnormal behaviors and electrophysiological deficits in adult rats. Additionally, inhibition of autophagy with 3-Methyladenine (3-MA) during the weaning period resulted in aberrant behaviors, abnormal electrophysiology, increased spine density, and reduced microglia-mediated synaptic pruning. Furthermore, 3-MA treatment significantly decreased the expression and synaptosomal content of complement, impaired the recognition of C3b and CR3, indicating that autophagy deficiency disrupts complement-mediated synaptic pruning. Our findings provide evidence for a significant association between SCZ and defective autophagy, highlighting a previously underappreciated role of autophagy in regulating the synaptic and behavioral deficits induced by MIA.

Abstract Background Relative fat mass (RFM) is a newly developed, sex-specific anthropometric formula designed to estimate total body fat percentage. However, research investigating the correlation between RFM and the risk of non-alcoholic fatty liver disease (NAFLD) remains limited. This study evaluates the association between RFM and the risk of NAFLD within the Japanese population. Methods This study including 14,250 Japanese adults who underwent physical examinations at Murakami Memorial Hospital between 2004 and 2015. We employed binary logistic regression to elucidate the direct relationship between RFM levels and the incidence of NAFLD. Additionally, a generalized additive model (GAM) coupled with smooth curve fitting techniques was utilized to map the non-linear association. Results The cohort had an average age of 43.53 ± 8.89 years, with a male majority of 52.00%. NAFLD was identified in 17.59% of the participants. After adjusting for confounding factors, a significant positive correlation between RFM and NAFLD risk was observed (OR: 1.15, 95%CI: 1.10–1.21, P

Surface nano-modification has emerged as an effective strategy to enhance osseointegration of titanium (Ti) implants. Despite its promise, rational optimization of surface nanomorphology for ameliorated osseointegration remains a significant challenge. Our research pioneering developed a one-step alkali etching technique to produce a gradient nanowire coating with continuously varied dimensions on Ti surfaces, which was subsequently served as a versatile platform for high-throughput screening of optimal dimensions to enhance osseointegration. The results showed that macrophages (MФs) that mainly governed the initial inflammatory reaction exhibited a polarization tendency towards pro-healing M2 phenotype with decreased nanowire dimension due to nanomorphology-mediated focal adhesion formation and activation of its downstream signaling pathways (typically PI3K-Akt). Simultaneously, small-sized nanowires with diameter of 5.63–14.25 nm and inter-spacing of 29.42–57.97 nm were conductive to angiogenesis of endothelial cells (ECs) and osteogenesis of bone marrow mesenchymal stem cells (BMSCs), which may share similar mechanisms of MФs. The in vivo results well corroborated these in vitro observations. The knowledge gained from the present work not only advance our understanding of the interaction between surface morphology and cells, but also potentially pave the way for efficient and cost-effective design of advanced biomaterial surfaces for better osseointegration.

Objective: Segmenting and reconstructing 3D models of bone tumors from 2D image data is of great significance for assisting disease diagnosis and treatment. However, due to the low distinguishability of tumors and surrounding tissues in images, existing methods lack accuracy and stability. This study proposes a U-Net model based on double dimensionality reduction and channel attention gating mechanism, namely the DCU-Net model for oncological image segmentation. After realizing automatic segmentation and 3D reconstruction of osteosarcoma by optimizing feature extraction and improving target space clustering capabilities, we built a mixed reality (MR) infrastructure and explored the application prospects of the infrastructure combining deep learning-based medical image segmentation and mixed reality in the diagnosis and treatment of bone tumors. Methods: We conducted experiments using a hospital dataset for bone tumor segmentation, used the optimized DCU-Net and 3D reconstruction technology to generate bone tumor models, and used set similarity (DSC), recall (R), precision (P), and 3D vertex distance error (VDE) to evaluate segmentation performance and 3D reconstruction effects. Then, two surgeons conducted clinical examination experiments on patients using two different methods, viewing 2D images and virtual reality infrastructure, and used the Likert scale (LS) to compare the effectiveness of surgical plans of the two methods. Results: The DSC, R and P values of the model introduced in this paper all exceed 90%, which has significant advantages compared with methods such as U-Net and Attention-Uet. Furthermore, LS showed that clinicians in the DCU-Net-based MR group had better spatial awareness of tumor preoperative planning. Conclusion: The deep learning DCU-Net algorithm model can improve the performance of tumor CT image segmentation, and the reconstructed fine model can better reflect the actual situation of individual tumors; the MR system constructed based on this model enhances clinicians’ understanding of tumor morphology and spatial relationships. The MR system based on deep learning and three-dimensional visualization technology has great potential in the diagnosis and treatment of bone tumors, and is expected to promote clinical practice and improve efficacy.

BackgroundSelpercatinib, a selective RET kinase inhibitor, is approved for treating various cancers with RET gene mutations such as RET-rearranged thyroid cancer and non-small cell lung cancer. The presence of process-related and degradation impurities in its active pharmaceutical ingredient (API) can significantly affect its safety and effectiveness. However, research on detecting these impurities is limited.MethodsThis study developed and systematically validated a High-Performance Liquid Chromatography (HPLC) method for identifying selpercatinib and its related impurities. The method utilized a 4.6 mm × 250 mm chromatographic column with 5 μm particles, employing a flow rate of 1.0 mL/min, a detection wavelength of 235 nm, an injection volume of 10 μL, and a column temperature of 35°C. Mobile phase A was composed of a 9:1 ratio of water to acetonitrile, with the aqueous component adjusted to pH 2.5 and containing 2 mM potassium dihydrogen phosphate (KH2PO4) and 0.4% triethylamine. Mobile phase B was pure acetonitrile. The gradient elution program was as follows: 0–2 min, 5%B; 2–15 min, 5% to 15%B; 15–30 min, 15% to 35%B; 30–35 min, 35% to 45%B; 35–36 min, 45% to 5%B; 36–45 min, 5%B.ResultsThe chromatographic method established in this study was validated according to the ICH Q2 (R1) guidelines. The developed HPLC method demonstrated excellent specificity, sensitivity, stability, linearity, precision, accuracy, and robustness. It efficiently separated the impurities present in selpercatinib, thereby confirming the method’s efficacy in ensuring the purity and quality of the drug.ConclusionThe chromatographic method established in this study can be used for the detection of selpercatinib and its impurities, providing significant reference value for the quality research of selpercatinib bulk drug and its preparations, and ensuring the safety of medication for patients.

Against the backdrop of a warming climate, heat stress has become one of the most limiting factors to crop productivity and food security worldwide. The flowering stage is susceptible to high temperatures in cereal crops, leading to severe grain yield losses by decreasing fertility and seed-setting rate. Our objective was to (1) assess a global panel of 572 barley varieties with contrasting genetic backgrounds for various agronomic traits related to spikelet fertility and grain quality, (2) identify barley germplasm with superior spikelet fertility and seed set under extreme heat conditions, and (3) understand the relationship between spikelet fertility and grain quality traits under heat stress at flowering time. Delayed sowing in target field environments as well as combined birdcage and heat chamber experiments were conducted in Western Australia for two consecutive years. Twenty-one agronomic traits, including spikelet fertility, grain plumpness, thousand-kernel weight, and screenings, were assessed when heat stress occurred during the crucial flowering period. Our study showed that varieties that flowered during heat stress periods recorded an average of 5–20 ​% lower spikelet fertility than those flowered outside the stress windows. Varieties with high or reduced spikelet fertility under heat stress were identified in the barley panel and showed significant differences of more than 80 ​% in Australian varieties. Based on decreased spikelet fertility, several research lines, but only a few cultivars, maintain spikelet fertility after heat stress compared to control conditions, providing evidence of adaptation to high temperatures in some genotypes. Our study shows that spikelet fertility at high temperatures is a valuable screening tool for heat tolerance during the reproductive phase. Information on heat-tolerant and susceptible varieties can improve the spikelet fertility of the next generation of barley cultivars and enhance adaptation to a changing climate.

Background and objective: Magnetic resonance imaging (MRI) plays a vital role in diagnosing spinal diseases, including different types of spinal tumors. However, conventional segmentation techniques are often labor-intensive and susceptible to variability. This study aims to propose a full-automatic segmentation method for spine MRI images, utilizing a convolutional-deconvolution neural network and patch-based deep learning. The objective is to improve segmentation efficiency, meeting clinical needs for accurate diagnoses and treatment planning. Methods: The methodology involved the utilization of a convolutional neural network to automatically extract deep learning features from spine data. This allowed for the effective representation of anatomical structures. The network was trained to learn discriminative features necessary for accurate segmentation of the spine MRI data. Furthermore, a patch extraction (PE) based deep neural network was developed using a convolutional neural network to restore the feature maps to their original image size. To improve training efficiency, a combination of pre-training and an enhanced stochastic gradient descent method was utilized. Results: The experimental results highlight the effectiveness of the proposed method for spine image segmentation using Gadolinium-enhanced T1 MRI. This approach not only delivers high accuracy but also offers real-time performance. The innovative model attained impressive metrics, achieving 90.6% precision, 91.1% recall, 93.2% accuracy, 91.3% F1-score, 83.8% Intersection over Union (IoU), and 91.1% Dice Coefficient (DC). These results indicate that the proposed method can accurately segment spine tumors CT images, addressing the limitations of traditional segmentation algorithms. Conclusion: In conclusion, this study introduces a fully automated segmentation method for spine MRI images utilizing a convolutional neural network, enhanced by the application of the PE-module. By utilizing a patch extraction based neural network (PENN) deep learning techniques, the proposed method effectively addresses the deficiencies of traditional algorithms and achieves accurate and real-time spine MRI image segmentation.

BackgroundPosttraumatic stress disorder (PTSD) is associated with the development of dementia. However, the link between PTSD and preclinical Alzheimer’s disease pathology (amyloid β [Aβ]) remains controversial. Moreover, the correlation between the severity of PTSD with Aβ levels remains unknown.MethodsThis cross-sectional study sought to investigate the associations of PTSD symptoms with global and regional brain Aβ burden. To this end, data were obtained from participants in the Anti-Amyloid Treatment in Asymptomatic Alzheimer’s Disease (A4) Study. In addition, we explored the association between the severity of PTSD symptoms and Aβ levels.ResultsA total of 4,228 participants aged 65 to 85 years were included in the final analysis. The results showed that PTSD symptoms were significantly associated with higher global Aβ levels (1.15 ± 0.20 vs. 1.09 ± 0.19; β = 0.056; p

Silicate-modified polyurethane (PU/WG) is an effective organic–inorganic hybrid-grouting material that blocks water and reinforces weak formations. In deep high-temperature formations, owing to environmental impacts, PU/WG raw materials are heated before grouting. To elucidate the basic characteristics of PU/WG grouting materials in deep, high-temperature environments, we investigated the effects of raw material temperature on the curing time and strength of PU/WG by considering different mass ratios during the curing time test. Furthermore, the influence of raw material temperature on the micro-structure of PU/WG was analysed from a microscopic perspective using scanning electron microscopy. Energy-dispersive X-ray spectroscopy revealed the composition and curing mechanism of PU/WG. The results indicated that as the raw material temperature increased from 24 to 60°C, the peak strength decreased from 41.65 to 14.51 MPa, and the peak strain decreased from 27.03 % to 8.83 %. Based on the experimental results of the curing time testing and strength test, we established a PU/WG curing time-variation model considering the coupling of raw material temperature and mass ratio and provided an optimisation scheme for the PU/WG strength, which provides effective guidance for grouting time design in high-temperature environments.

Abstract Despite the clear association between remnant cholesterol (RC)and diabetes risk, no study to date has examined the relationship between RC and reversal of prediabetes to normoglycemia. This retrospective cohort study included a total of 15,023 patients with prediabetes who underwent a physical examination between 2010 and 2016. The link between initial RC levels and the reversion from prediabetes to normoglycemia was analyzed using the Cox proportional-hazards regression model. Additionally, the study explored the possible relationship between RC and the probability of returning normoglycemia by applying Cox proportional hazards regression models with cubic spline functions. To address competing risks, a multivariate Cox regression analysis was undertaken, treating the onset of diabetes as a competing risk event for reversing prediabetes to normoglycemia. Additionally, the study incorporated extensive subgroup analyses alongside multiple sensitivity analyses, enhancing the reliability and robustness of the results. After adjusting for covariates, the findings indicated that RC was inversely associated with the likelihood of reverting to normoglycemia (per 5 mg/dL increase, HR = 0.918, 95% CI 0.909–0.927). The analysis also revealed a nonlinear relationship between RC and normoglycemia reversion, with an inflection point at 51.08 mg/dL. For RC values below this inflection point (RC

Abstract Oxidative stress and neuroinflammation contribute to schizophrenia (SCZ) pathology and may influence treatment efficacy. Matrix metalloproteinase 9 (MMP9) is a critical molecular node mediating the interaction between oxidative stress and inflammation, and so may influence treatment efficacy. Here we examined the associations of plasma MMP9 concentration with antipsychotic drug responses, clinical symptoms, and brain structure. A total of 129 healthy controls and 124 patients with SCZ were included in this study. Patients were monitored clinically during 8 weeks of antipsychotic treatment and classified as poor responders (n = 49) or good responders (n = 75). We then compared plasma MMP9 concentrations in healthy controls at baseline and both SCZ responder groups at baseline and after the 8-week antipsychotic treatment regimen. Cognitive function was also examined using the MATRICS Consensus Cognitive Battery. In addition, we extracted regional white matter density from magnetic resonance images of patients. Compared to healthy controls, plasma MMP9 levels were significantly elevated in poor responders at baseline and negatively correlated with both white matter density in the right superior temporal gyrus and the change in cognitive symptoms after treatment. Conversely, there was no significant difference in plasma MMP9 between good responders and healthy controls, and no associations of plasma MMP9 with cognitive symptoms or regional white matter density among good responders. Elevated plasma MMP9 is associated with poor antipsychotic drug efficacy and white matter deficits in SCZ patients, and so may be a useful biomarker to guide personalized treatment.

Abstract Biophysical processes of forests affect climate through the regulation of surface water and heat fluxes, which leads to further effects through the adjustment of clouds and water cycles. These indirect biophysical effects of forests on clouds and their radiative forcing are poorly understood but highly relevant in the context of large-scale deforestation or afforestation, respectively. Here, we provide evidence for local decreases in global low-level clouds and tropical high-level clouds from deforestation through both idealized deforestation simulations with climate models and from observations-driven reanalysis using space-for-time substitution. The decreased cloud cover can be explained by alterations in surface turbulent heat flux, which diminishes uplift and moisture to varying extents. Deforestation-induced reduction in cloud cover warms the climate, partially counteracting the cooling effects of increased surface albedo. The findings from idealized deforestation experiments and space-for-time substitution exhibit disparities, with global average offsets of, respectively, approximately 44% and 26%, suggesting the necessity for further constraints.

Purpose: The current study aimed to assess the protective performance of helmets equipped with multi-directional impact protection system (MIPS) under various oblique impact loads. Methods: Initially, a finite element model of a bicycle helmet with MIPS was developed based on the scanned geometric parameters of an actual bicycle helmet. Subsequently, the validity of model was confirmed using the KASK WG11 oblique impact test method. Three different impact angles (30°, 45°, and 60°) and 2 varying impact speeds (5 m/s and 8 m/s) were employed in oblique tests to evaluate protective performance of MIPS in helmets, focusing on injury assessment parameters such as peak linear acceleration (PLA) and peak angular acceleration (PAA) of the head. Results: The results demonstrated that in all impact simulations, both assessment parameters were lower during impact for helmets equipped with MIPS compared to those without. The PAA was consistently lower in the MIPS helmet group, whereas the difference in PLA was not significant in the no-MIPS helmet group. For instance, at an impact velocity of 8 m/s and a 30° inclined anvil, the MIPS helmet group exhibited a PAA of 3225 rad/s2 and a PLA of 281 g. In contrast, the no-MIPS helmet group displayed a PAA of 8243 rad/s2 and a PLA of 292 g. Generally, both PAA and PLA parameters decreased with the increase of anvil angles. At a 60° anvil angles, PAA and PLA values were 664 rad/s2 and 20.7 g, respectively, reaching their minimum. Conclusion: The findings indicated that helmets incorporating MIPS offer enhanced protection against various oblique impact loads. When assessing helmets for oblique impacts, the utilization of larger angle anvils and rear impacts might not adequately evaluate protective performance during an impact event. These findings will guide advancements in helmet design and the refinement of oblique impact test protocols.

Abstract Dysregulated Epiregulin (EREG) can activate epidermal growth factor receptor (EGFR) and promote tumor progression in head and neck squamous cell carcinoma (HNSCC). However, the mechanisms underlying EREG dysregulation remain largely unknown. Here, we showed that dysregulated EREG was highly associated with enhanced PDL1 in HNSCC tissues. Treatment of HNSCC cells with EREG resulted in upregulated PDL1 via the c-myc pathway. Of note, we found that N-glycosylation of EREG was essential for its stability, membrane location, biological function, and upregulation of its downstream target PDL1 in HNSCC. EREG was glycosylated at N47 via STT3B glycosyltransferases, whereas mutations at N47 site abrogated N-glycosylation and destabilized EREG. Consistently, knockdown of STT3B suppressed glycosylated EREG and inhibited PDL1 in HNSCC cells. Moreover, treatment of HNSCC cells with NGI-1, an inhibitor of STT3B, blocked STT3B-mediated glycosylation of EREG, leading to its degradation and suppression of PDL1. Finally, combination of NGI-1 treatment with anti-PDLl therapy synergistically enhanced the efficacy of immunotherapy of HNSCC in vivo. Taken together, STT3B-mediated N-glycosylation is essential for stabilization of EREG, which mediates PDL1 upregulation and immune evasion in HNSCC.

Abstract Background The occurrence of type II endoleaks after endovascular repair of aortic aneurysm has gradually gained increasing attention. We present a case of a patient with an expanding aneurysm after thoracic endovascular aortic repair (TEVAR) for a type II endoleak, in which successful direct ligations of the intercostal artery were performed using a sac incision without cardiopulmonary bypass (CPB) or graft replacement. Case presentation A 62-year-old male patient, previously treated with TEVAR for a descending thoracic aortic aneurysm, presented with ongoing chest discomfort. Based on the diagnosis of a growing aneurysm and type II endoleak, the patient was prepared for CPB and aortic cross-clamping, as a precautions against the possibility of a type I endoleak. A longitudinal opening of the thoracic aortic aneurysm sac was performed following left thoracotomy. Visual confirmation identified the T5 level intercostal artery as the source of the endoleak, and after confirming the absence of a type I endoleak, multiple ligations were applied to the intercostal artery. Follow-up computed tomography confirmed the absence of endoleaks or sac growth. Conclusion In a case involving TEVAR for a thoracic aortic aneurysm, open suture ligations were used to treat type II endoleaks without having to resort to CPB, resulting in successful outcomes.

Abstract The available evidence on the connection between excessive alcohol consumption and diabetes is controversial. Therefore, the primary objective of this investigation was to examine the connection between excessive alcohol consumption and incident diabetes in a Japanese population through the utilization of propensity score matching (PSM) analysis. Our retrospective cohort study encompassed a sample of 15,464 Japanese individuals who were initially free of diabetes between the years 2004 and 2015. The study utilized comprehensive medical records of individuals who underwent a physical examination. Employing a one:one PSM analysis, the current research included 2298 individuals with and without excessive alcohol consumption. Furthermore, a doubly robust estimation method was employed to ascertain the connection between excessive alcohol consumption and diabetes. The findings revealed that individuals with excessive alcohol consumption exhibited a 73% higher likelihood of developing diabetes (HR = 1.73, 95% CI 1.08–2.77). Furthermore, upon adjusting for variables, the PSM cohort demonstrated that individuals with excessive alcohol consumption had a 78% increased risk of developing diabetes in comparison to those with non-excessive alcohol consumption (HR = 1.78, 95% CI 1.08–2.93). Individuals with excessive alcohol consumption were found to have a 73% higher risk of developing diabetes compared to those with non-excessive alcohol consumption, even after controlling for propensity score (HR = 1.73, 95% CI 1.08–2.78). Participants in the PSM cohort with excessive alcohol consumption had a 73% higher risk of developing diabetes than those with non-excessive alcohol consumption after controlling for confounding factors. These findings underscore the importance of alcohol consumption guidelines aimed at reducing excessive drinking. Clinicians should be vigilant in screening for alcohol use in patients, particularly those at risk for diabetes, and provide appropriate counseling and resources to support alcohol reduction.

Multiple primary lung cancer (MPLC), can be categorized as synchronous multiple primary lung cancer (sMPLC) and metachronous multiple primary lung cancer (mMPLC), which are becoming increasingly common in clinical practice. A precise differential diagnosis between MPLC and intrapulmonary metastases (IPM) is essential for determining the appropriate management strategy. MPLC is primarily diagnosed through histology, imaging, and molecular methods. Imaging serves as an essential foundation for preoperative diagnosis, while histology is a critical tool for establishing a definitive diagnosis. As molecular biology advances, the diagnosis of MPLC has stepped into the era of molecular precision. Surgery is the preferred treatment approach, with stereotactic radiotherapy and ablation being viable options for unresectable lesions. Targeted therapy and immunotherapy can be considered for specific patients. A multidisciplinary team approach to evaluation and the application of combination therapy can benefit more patients. Looking ahead, the development of more authoritative guidelines will be instrumental in streamlining the diagnosis and management of MPLC.

Abstract The passive sensing and active control of electromagnetic (EM) waves have always been attractive in electronic and information areas, especially during the intelligent era. Here a new method is presented to achieve the angle sensing of incident wave and adaptive control of backward scattering using the intelligent metasurface. The proposed unit cells have the ability to dynamically manipulate the receiving and reflection of the EM energy respectively. The angle sensing of incident waves can be actualized using the method of compressive sensing based on multiple receiving patterns, which are generated by randomly switching the receiving and reflection states of the unit cells. Afterward, the customized performances of backward scattering waves according to the cognitive incident angle can be realized by controlling the programmable reflective phases of unit cells correspondingly. One prototype composed of the metasurface and the module for sensing and adaptive feedback control is fabricated. The whole intelligent metasurface with customizing the function of retro‐reflection or low scattering is measured without human intervention and the good results acquired can verify the validity of the proposed concept and design.

BackgroundThe triglyceride-glucose (TyG) index, recognized for its cost-efficiency and simplicity, serves as an accessible indicator of insulin resistance. Yet, its correlation with the risk of prediabetes and diabetes (Pre-DM/DM) in the Chinese demographic remains uncertain. Consequently, our study explored the association between the TyG index and the development of Pre-DM/DM within the Chinese population.MethodsThe retrospective cohort study was carried out utilizing data from a health screening initiative. The study included 179541 adults over 20 who underwent medical examinations at the Rich Healthcare Group over a period spanning from 2010 to 2016. The correlation between the TyG index and Pre-DM/DM risk was investigated using Cox regression analysis. Furthermore, Cox proportional hazards regression with cubic spline functions and smooth curve fitting was incorporated to explore their non-linear connection.ResultsThe mean age of study participants was 41.18 ± 12.20 years old, and 95255 (53.05%) were male. During a median follow-up of 3.01 years, 21281 (11.85%) participants were diagnosed with Pre-DM/DM. After adjusting the potential confounding factors, the results showed that the TyG index was positively correlated with incident Pre-DM/DM (HR: 1.67, 95%CI: 1.62-1.71, P< 0.001). Additionally, a non-linear association was observed between the TyG index and the onset of Pre-DM/DM, with an inflection point identified at 8.73. Hazard ratios (HR) to the left and right of this inflection point were 1.95 (95%CI: 1.86-2.04) and 1.34 (95%CI: 1.27-1.42), respectively. Furthermore, sensitivity analyses confirmed the stability of these findings.ConclusionThe TyG index exhibited a non-linear positive relationship with the risk of Pre-DM/DM. These findings imply that maintaining the TyG index at a lower, specified threshold may be beneficial in mitigating the onset of Pre-DM/DM.

Abstract Objective Fibrinogen, essential in primary hemostasis, platelet aggregation, and leukocyte-endothelial interactions, is also associated with a heightened risk of acute ischemic stroke (AIS). However, its influence on AIS patient outcomes is unclear. This study examines the correlation between fibrinogen levels and the risk of unfavorable outcomes three months post-AIS. Methods This is a secondary analysis of a prospective cohort study conducted in Korea. The sample consisted of 1851 AIS patients who received treatment at a Korean hospital between January 2010 and December 2016. Statistical models were established to understand the relationship between fibrinogen levels(mg/dL) and unfavorable outcomes(mRs ≥ 3), including logistic regression models, Generalized Additive Models (GAM), and smooth curve fitting (penalized splines). The log-likelihood ratio test has been utilized to evaluate the best fit. To ensure the robustness of the results, sensitivity analyses were conducted by reanalyzing the relationship after excluding participants with TG > 200 mg/dl and BMI > 25 kg/m2. Subgroup analyses were also performed to assess whether influencing factors modify the association between fibrinogen levels and unfavorable outcomes. Results After adjusting for multiple covariates including age, BMI, sex, LDL-c, TG, HGB, HDL-c, BUN, FPG, ALB, PLT, AF, hypertension, smoking, DM, mRs score at admission, the binary logistic regression model demonstrated revealed a significant positive association between fibrinogen levels and the risk of unfavorable outcomes in AIS patients (OR = 1.215, 95% CI: 1.032–1.429, p = 0.019). Sensitivity analyses supported these findings, with similar ORs observed in subsets of patients with TG

Abstract Background Mucosal melanoma (MM) is a rare but devastating subtype of melanoma. Our previous studies have demonstrated robust anti-tumor effects of cyclin-dependent kinase 4/6 (CDK 4/6) inhibitors in head and neck MM (HNMM) patient-derived xenograft models with CDK4 amplification. Herein, we aimed to investigate the efficacy and safety of dalpiciclib (SHR6390), a CDK4/6 inhibitor, in HNMM patients harboring CDK4 amplification. Methods The anti-tumor efficacy of dalpiciclib was assessed by HNMM patient-derived xenograft (PDX) models and patient-derived tumor cells (PDC) in vivo and in vitro. Immunohistochemical analyses and western blot were then performed to assess the markers of cell proliferation and CDK4/6 signaling pathway. For the clinical trial, advanced recurrent and/or metastatic HNMM patients with CDK4 amplification were treated with dalpiciclib 125 mg once daily for 21 consecutive days in 28-day cycles. The primary endpoint was disease control rate (DCR). Secondary endpoints included safety, objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). Results Dalpiciclib profoundly suppressed growth of HNMM-PDX and PDC with CDK4 amplification, whereas it showed relatively weak suppression in those with CDK4 wild type compared with vehicle. And dalpiciclib resulted in a remarkable reduction in the expression levels of Ki-67 and phosphorylated Rb compared with control group. In the clinical trial, a total of 17 patients were enrolled, and 16 patients were evaluable. The ORR was 6.3%, and the DCR was 81.3%. The estimated median PFS was 9.9 months (95% CI, 4.8-NA), and the median OS was not reached. The rate of OS at 12 months and 24 months was 68.8% (95% CI, 0.494–0.957) and 51.6% (95% CI, 0.307–0.866), respectively. The most frequent adverse events were neutrophil count decrease, white blood cell count decrease, and fatigue. Conclusions Dalpiciclib was well-tolerated and displayed a durable benefit for HNMM patients with CDK4 amplification in this study. Further studies on CDK4 inhibitors and its combination strategy for MM are worth further exploration. Trial registration ChiCTR2000031608.

Abstract The association between the initial cardiac rhythm and short-term survival in patients with in-hospital cardiac arrest (IHCA) has not been extensively studied despite the fact that it is thought to be a prognostic factor in patients with out-of-hospital cardiac arrest. This study aimed to look at the relationship between initial shockable rhythm and survival to hospital discharge in individuals with IHCA. 1516 adults with IHCA who received chest compressions lasting at least two minutes at the National Taiwan University Hospital between 2006 and 2014 made up the study population. Propensity scores were estimated using a fitted multivariate logistic regression model. Various statistical methodologies were employed to investigate the association between shockable rhythm and the probability of survival to discharge in patients experiencing IHCA, including multivariate adjustment, propensity score adjustment, propensity score matching, and logistic regression based on propensity score weighting. In the original cohort, the multivariate-adjusted odds ratio (OR) was 2.312 (95% confidence interval [CI]: 1.515–3.531, P

Abstract Objective The connection between triglycerides to high-density lipoprotein cholesterol (TG/HDL-C) ratio and stroke risk is controversial. Our goal was to explore this relationship in individuals aged 45 and older enrolled in the China Health and Retirement Longitudinal Study (CHARLS). Methods Our analysis encompassed 10,164 participants from the CHARLS cohorts. We applied the Cox proportional-hazards regression model to evaluate the potential correlation between the TG/HDL-C ratio and stroke incidence. Using a cubic spline function and smooth curve fitting within the Cox model allowed us to unearth a possible non-linear pattern in this relationship. We also conducted thorough sensitivity and subgroup analyses to deepen our understanding of the TG/HDL-C ratio’s impact on stroke risk. Results Adjusting for various risk factors, we observed a significant link between the TG/HDL-C ratio and increased stroke risk in individuals aged 45 and above (HR: 1.03, 95% CI 1.00–1.05, P = 0.0426). The relationship appeared non-linear, with an inflection at a TG/HDL-C ratio of 1.85. Ratios below this threshold indicated a heightened stroke risk (HR: 1.28, 95% CI 1.06–1.54, P = 0.0089), while ratios above it did not show a significant risk increase (HR: 1.01, 95% CI 0.98–1.04, P = 0.6738). Sensitivity analysis confirmed the robustness of these findings. Notably, non-smokers exhibited a stronger correlation between the TG/HDL-C ratio and stroke risk compared to past and current smokers. Conclusion Our investigation revealed a significant, yet non-linear, association between the TG/HDL-C ratio and the incidence of stroke among individuals aged 45 and above. Specifically, we found that stroke risk increased in correlation with TG/HDL-C ratio below the threshold of 1.85. These insights may guide healthcare providers in advising and developing more effective strategies for stroke prevention in this demographic.

Venovenous (VV) extracorporeal membrane oxygenation (ECMO) is a lifesaving technique for patients experiencing respiratory failure. When VV ECMO fails to provide adequate support despite optimal settings, alternative strategies may be employed. One option is to add another venous cannula to increase venous drainage, while another is to insert an additional arterial return cannula to assist cardiac function. Alternatively, a separate ECMO circuit can be implemented to function in parallel with the existing circuit. We present a case in which the parallel ECMO method was used in a 63-year-old man with respiratory failure due to coronavirus disease 2019, combined with cardiac dysfunction. We installed an additional venoarterial ECMO circuit alongside the existing VV ECMO circuit and successfully weaned the patient from both types of ECMO. In this report, we share our experience and discuss this method.

Abstract Objective In patients experiencing acute ischemic stroke, there is ongoing debate surrounding the connection between chronic hyperglycemic status and their initial clinical outcomes. Our objective was to examine the connection between glycated hemoglobin (HbA1c) levels and adverse clinical outcomes at both 3-months adverse clinical outcomes in individuals with acute ischemic stroke (AIS) with and without diabetes. Methods The present prospective cohort study involved 896 AIS patients without diabetes and 628 with diabetes treated at a South Korean hospital from January 2010 to December 2016. The target independent variable is HbA1c. The outcome variable is a modified Rankin scale score ≥ 3. A binary logistic regression model was applied to assess the connection between HbA1c levels and 3-month poor clinical outcomes in AIS patients with and without diabetes. Additionally, a generalized additive model and smoothed curve fitting were utilized to explore potential nonlinear associations between HbA1c levels and 3-month adverse clinical outcomes in AIS patients with and without diabetes. Results The binary logistic regression model could not identify any statistically significant connection between HbA1c and 3-month adverse clinical outcomes in AIS patients, both those with and without diabetes, after correcting for various factors. However, a nonlinear relationship emerged between HbA1c and 3-month adverse clinical outcomes in AIS patients with diabetes. The inflection point for HbA1c was determined to be 6.1%. For HbA1c values ≤ 6.1%, an inverse association was observed between HbA1c and 3-month adverse clinical outcomes in diabetic AIS patients, and each 1% increase in HbA1c in AIS patients with DM was associated with an 87% reduction in 3-month adverse clinical outcomes (OR = 0.13, 95% CI: 0.02–0.81). Conversely, when HbA1c exceeded 6.1%, a positive association between HbA1c and 3-month adverse clinical outcomes became apparent in diabetic AIS patients, and each 1% increase in HbA1c in AIS patients with DM was associated with a 23% increase in 3-month adverse clinical outcomes (OR = 1.23, 95%CI: 1.03–1.47). However, it’s important to note that no significant linear or nonlinear relationships were observed between HbA1c levels and 3-month adverse clinical outcomes in AIS patients without diabetes. Conclusion Our findings suggest a nonlinear connection and threshold effect between HbA1c and 3-month adverse clinical outcomes in AIS patients with diabetes. AIS patients with diabetes had a lower risk of 3-month adverse clinical outcomes when their HbA1c control was close to 6.1%. Our findings may aid treatment decision-making and potentially guide interventions to optimize glycemic control in AIS patients.

Abstract Objective The connection between total cholesterol to high-density lipoprotein cholesterol (TC/HDL-C) ratio and stroke risk is controversial. This study aims to examine the connection between the TC/HDL-C ratio and stroke in middle-aged and older individuals who are part of the China Health and Retirement Longitudinal Study (CHARLS). Methods This study conducted a retrospective cohort analysis, enrolling a total of 10,184 participants who met the designated criteria from CHARLS between 2011 and 2012. We then used the Cox proportional-hazards regression model to analyze the relationship between the TC/HDL-C ratio and stroke risk. Using a Cox proportional hazards regression model with cubic spline functions and smooth curve fitting, we were able to identify the non-linear relationship between the TC/HDL-C ratio and stroke occurrence. The sensitivity and subgroup analyses were also performed to investigate the connection between TC/HDL-C ratio and stroke. Results This study revealed a statistically significant association between the TC/HDL-C ratio and stroke risk in subjects aged 45 years or older after adjusting for risk factors (HR: 1.05, 95%CI 1.00–1.10, P = 0.0410). Furthermore, a non-linear connection between the TC/HDL-C ratio and stroke risk was detected, with a TC/HDL-C ratio inflection point of 3.71. We identified a significant positive connection between the TC/HDL-C ratio and stroke risk, when the TC/HDL-C ratio was less than 3.71 (HR: 1.25, 95%CI 1.07–1.45, P = 0.0039). However, their connection was not significant when the TC/HDL-C ratio exceeded 3.71 (HR: 1.00, 95%CI 0.94–1.06, P = 0.9232). The sensitivity analysis and subgroup analyses revealed that our findings were well-robust. Conclusion Our study demonstrated a positive, non-linear connection between the TC/HDL-C ratio and stroke risk in middle-aged and older individuals. There was a significant positive connection between the TC/HDL-C ratio and stroke risk, when the TC/HDL-C ratio was less than 3.71. The current research can be used as a guideline to support clinician consultation and optimize stroke prevention measures for middle-aged and older adults.

Abstract There is limited research on the association between the alanine aminotransferase to high-density lipoprotein cholesterol ratio (ALT/HDL-C) ratio and nonalcoholic fatty liver disease (NAFLD). The purpose of the current research was to look into the connection between the ALT/HDL-C ratio and the risk of NAFLD in lean Chinese individuals. Between January 2010 and December 2014, 11,975 non-obese people participated in this prospective cohort research. The relationship between the ALT/HDL-C ratio and the risk of developing NAFLD was assessed using the Cox proportional-hazards regression model, Cox proportional hazards regression with cubic spline functions and smooth curve fitting, sensitivity analysis, and subgroup analyses. The ALT/HDL-C ratio’s potential value as a NAFLD prognostic marker was to be evaluated using the receiver operating characteristic curve analysis. A total of 5419 (45.253%) women comprised the research's participant population, and the research participants’ average age was 43.278 ± 14.941 years. The ALT/HDL-C ratio was 11.607 (7.973–17.422) at the median (interquartile ranges). 2087 (17.428%) patients had NAFLD diagnoses throughout a median follow-up of 24.967 months. The study's findings demonstrated a positive connection between the ALT/AHDL-C ratio and the incident NAFLD (HR = 1.037, 95% CI: 1.031–1.042) when adjusting for relevant factors. The ALT/HDL-C ratio and NAFLD risk had a nonlinear connection, with 12.963 as the ratio's inflection point. Effect sizes (HR) were 1.023 (95% CI: 1.017–1.029) and 1.204 (95% CI: 1.171–1.237), respectively, on the right and left sides of the inflection point. The sensitivity analysis also showed how reliable our findings were. According to subgroup analysis, those with BMI

With the escalating demand for automation in chemical laboratories, multi-robot systems are assuming an increasingly prominent role in chemical laboratories, particularly in the task of transporting reagents and experimental materials. In this paper, we propose a multi-robot path planning approach based on the combination of the A* algorithm and the dynamic window algorithm (DWA) for optimizing the efficiency of reagent transportation in chemical laboratories. In environments like chemical laboratories, dynamic obstacles (such as people and equipment) and transportation tasks that demand precise control render traditional path planning algorithms challenging. To address these issues, in this paper, we incorporate the cost information from the current point to the goal point into the evaluation function of the traditional A* algorithm to enhance the search efficiency and add the safety distance to extract the critical points of the paths, which are utilized as the temporary goal points of the DWA algorithm. In the DWA algorithm, a stop-and-wait mechanism and a replanning strategy are added, and a direction factor is included in the evaluation function to guarantee that the robots can adjust their paths promptly in the presence of dynamic obstacles or interference from other robots to evade potential conflicts or traps, thereby reaching the goal point smoothly. Additionally, regarding the multi-robot path conflict problem, this paper adopts a dynamic prioritization method, which dynamically adjusts the motion priority among robots in accordance with real-time environmental changes, reducing the occurrence of path conflicts. The experimental results highlight that this approach effectively tackles the path planning challenge in multi-robot collaborative transportation tasks within chemical laboratories, significantly enhancing transportation efficiency and ensuring the safe operation of the robots.

As a key strategy for achieving a circular economy, remanufacturing involves bringing end-of-use (EoU) products or cores back to a ‘like new’ condition, providing more affordable and sustainable alternatives to new products. Despite the potential for substantial resources and energy savings, the industry faces operational challenges. These challenges arise from uncertainties surrounding core quality and functionality, return times, process variation required to meet product specifications, and the end-of-use (EoU) product values, as well as their new life expectancy after extended use as a ‘market product’. While remanufacturing holds immense promise, its full potential can only be realized through concerted efforts towards resolving the inherent complexities and obstacles that impede its operations. Machine learning (ML) and data-driven models emerge as transformative tools to mitigate numerous challenges encountered by manufacturing industry. Recently, the integration of cutting-edge technologies, such as sensor-based product data acquisition and storage, data analytics, machine health management, artificial intelligence (AI)-driven scheduling, and human–robot collaboration (HRC), in remanufacturing procedures has received significant attention from remanufacturers and the circular economy community. These advanced computational technologies help remanufacturers to implement flexible operation scheduling, enhance quality control, and streamline workflows for EoU products. This study embarks on a comprehensive review and in-depth analysis of state-of-the-art algorithms across various facets of remanufacturing processes and operations. Additionally, it identifies key challenges to advancing remanufacturing practices through data-driven and ML methods and uncovers research opportunities in synergy with smart manufacturing techniques. The study aims to offer guidelines for stakeholders and to reinforce the industry’s pivotal role in circular economy initiatives.

ObjectiveGiven the limited evidence on the relationship between the triglyceride-glucose (TyG) index and the risk of prediabetes among young adults, our study aimed to investigate the potential impact of the TyG index on the future development of prediabetes in young individuals.MethodsThis retrospective cohort study included 125,327 healthy adults aged 20 to 45 years. We utilized Cox proportional hazards regression models, combined with cubic spline functions and smooth curve fitting, to assess the relationship between baseline TyG index and the risk of prediabetes among young adults, exploring its non-linear association. A series of sensitivity analyses and subgroup analyses were conducted to ensure the robustness of our findings.ResultsAfter adjusting for covariates, the study found a positive correlation between the TyG index and the risk of prediabetes (HR=1.81, 95%CI: 1.54–2.13, p

Objective: This study aimed to investigate TCF19′s role in lung cancer development, specifically its involvement in the RAF/MEK/ERK signaling pathway. Methods: Lung cancer tissue analysis revealed significant TCF19 overexpression. In vitro experiments using A549 and Hop62 cells with TCF19 overexpression demonstrated enhanced cell growth. Transgenic mouse models confirmed TCF19′s role in primary tumor development. Transcriptome sequencing identified altered gene expression profiles, linking TCF19 to RAF/MEK/ERK pathway activation. Functional assays elucidated underlying mechanisms, revealing increased phosphorylation of Raf1, MEK1/2, and ERK1/2. Inhibiting RAF1 or ERK through shRaf1 or ERK inhibitor reduced cell cycle-related proteins and inhibited TCF19-overexpressing cell growth. Results: TCF19 was identified as an oncogene in lung carcinoma, specifically impacting the RAF/MEK/ERK pathway. Elevated TCF19 levels in lung cancer suggest targeting TCF19 or its associated pathways as a promising strategy for disease management. Conclusion: This study unveils TCF19′s oncogenic role in lung cancer, emphasizing its modulation of the RAF/MEK/ERK pathway and presenting a potential therapeutic target for TCF19-overexpressing lung cancers.

Background and aimsPediatric dilated cardiomyopathy (DCM) is a primary cause of heart failure, highlighting the urgent need for effective prognostic markers.MethodsWe performed a single-center retrospective study involving 145 children diagnosed with DCM, with a median follow-up period of 4.0 months (interquartile range: 6.2–108.4 months). The relationship between serum uric acid (SUA) levels and all-cause mortality was assessed using Kaplan–Meier survival curves, multivariate Cox proportional hazard models, and restricted cubic spline (RCS) models.ResultsOf the 145 children with DCM (median age 5.7 years; 61.4% male), 45 (31%) died within 1 year, and 65 (44.8%) died during the maximum follow-up period. In adjusted multivariate Cox regression models, each log2 SUA increase was linked to a higher risk of 1-year mortality [hazard ratio (HR), 2.66; 95% confidence interval (CI), 1.41–5.01] and overall mortality (HR, 1.97; 95% CI, 1.15–3.37). The highest SUA tertile showed a greater risk of mortality at 1 year (HR, 4.26; 95% CI: 1.5–12.06) and during the maximum follow-up (HR, 2.56; 95% CI: 1.06–6.16) compared with the lowest tertile. RCS models indicated an inverted L-shaped association between baseline SUA levels and overall mortality risk, with age-stratified analyses revealing a linear and U-shaped relationship in children ≤10 and >10 years, respectively. Further age-stratified analyses highlighted the modifying effect of age on this association.ConclusionElevated SUA levels are a significant predictor of mortality in pediatric DCM, with a pronounced impact on children under 10 years of age. Therefore, SUA levels could serve as potential biomarkers for risk stratification in this population.

Abstract Digital PCR (dPCR) holds immense potential for precisely detecting nucleic acid markers essential for personalized medicine. However, its broader application is hindered by high consumable costs, complex procedures, and restricted multiplexing capabilities. To address these challenges, an all‐in‐one dPCR system is introduced that eliminates the need for microfabricated chips, offering fully automated operations and enhanced multiplexing capabilities. Using this innovative oscillation‐induced droplet generation technique, OsciDrop, this system supports a comprehensive dPCR workflow, including precise liquid handling, pipette‐based droplet printing, in situ thermocycling, multicolor fluorescence imaging, and machine learning‐driven analysis. The system's reliability is demonstrated by quantifying reference materials and evaluating HER2 copy number variation in breast cancer. Its multiplexing capability is showcased with a quadruplex dPCR assay that detects key EGFR mutations, including 19Del, L858R, and T790M in lung cancer. Moreover, the digital stepwise melting analysis (dSMA) technique is introduced, enabling high‐multiplex profiling of seven major EGFR variants spanning 35 subtypes. This innovative dPCR system presents a cost‐effective and versatile alternative, overcoming existing limitations and paving the way for transformative advances in precision diagnostics.