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Abstract Idiopathic pulmonary fibrosis (IPF) is a severe interstitial lung disease characterized by a grim prognosis, in which various forms of cell death are significant contributors to its development. The objective of this study is to explore diagnostic biomarkers and molecular subtypes associated with PANoptosis in IPF, and to develop reliable diagnostic models based on PANoptosis-related mechanisms. The peripheral blood transcriptomic data of IPF from the Gene Expression Omnibus (GEO) database and PANoptosis-related genes from the GeneCards database were utilized to conduct differential gene expression analysis and weighted gene co-expression network analysis (WGCNA), identifying PANoptosis-related differentially expressed genes (PDEGs). We yielded 9 PDEGs and employed machine learning algorithms to identify 3 key diagnostic biomarkers for PANoptosis in IPF: MMP9, FCMR, NIBAN3. Consensus clustering algorithm was applied to recognize two PANoptosis-related subtypes. Cluster 1 exhibited higher abundance of adaptive immune response cells and significant enrichment in DNA damage and repair-related pathways. Cluster 2 exhibited greater prevalence of innate immune response cells and predominant enhancement in pathways related to lipid cholesterol metabolism and vascular remodeling. Diagnostic models were developed with the aid of clinical decision-making and a novel approach to the diagnosis and treatment for IPF.

Abstract Alzheimer’s Disease (AD) is a neurodegenerative disorder, and various molecules associated with PANoptosis are involved in neuroinflammation and neurodegenerative diseases. This work aims to identify key genes, and characterize PANoptosis-related molecular subtypes in AD. Moreover, we establish a scoring system for distinguishing PANoptosis molecular subtypes and constructing diagnostic models for AD differentiation. A total of 5 hippocampal datasets were obtained from the Gene Expression Omnibus (GEO) database. In total, 1324 protein-encoding genes associated with PANoptosis (1313 apoptosis genes, 11 necroptosis genes, and 31 pyroptosis genes) were extracted from the GeneCards database. The Limma package was used to identify differentially expressed genes. Weighted Gene Co-Expression Network Analysis (WGCNA) was conducted to identify gene modules significantly associated with AD. The ConsensusClusterPlus algorithm was used to identify AD subtypes. Gene Set Variation Analysis (GSVA) was used to assess functional and pathway differences among the subtypes. The Boruta, Least Absolute Shrinkage and Selection Operator (LASSO), Random Forest (RF), and Support Vector Machine Recursive Feature Elimination (SVM-RFE) algorithms were used to select the three PANoptosis-related Key AD genes (PKADg). A scoring model was constructed based on the Boruta algorithm. PANoptosis diagnostic models were developed using the RF, SVM-RFE, and Logistic Regression (LR) algorithms. The ROC curves were used to assess the model performance. A total of 48 important genes were identified by intersecting 725 differentially expressed genes and 2127 highly correlated module genes from WGCNA with 1324 protein-encoding genes related to PANoptosis. Machine learning algorithms identified 3 key AD genes related to PANoptosis, including ANGPT1, STEAP3, and TNFRSF11B. These genes had strong discriminatory capacities among samples, with Receiver Operating Characteristic Curve (ROC) analysis indicating Area Under the Curve (AUC) values of 0.839, 0.8, and 0.868, respectively. Using the 48 important genes, the ConsensusClusterPlus algorithm identified 2 PANoptosis subtypes among AD patients, i.e., apoptosis subtype and mild subtype. Apoptosis subtype patients displayed evident cellular apoptosis and severe functionality damage in the hippocampal tissue. Meanwhile, mild subtype patients showed milder functionality damage. These two subtypes had significant differences in apoptosis and necroptosis; however, there was no apparent variation in pyroptosis functionality. The scoring model achieved an AUC of 100% for sample differentiation. The RF PANoptosis diagnostic model demonstrated an AUC of 100% in the training set and 85.85% in the validation set for distinguishing AD. This study identified two PANoptosis-related hippocampal molecular subtypes of AD, identified key genes, and established machine learning models for subtype differentiation and discrimination of AD. We found that in the context of AD, PANoptosis may influence disease progression through the modulation of apoptosis and necrotic apoptosis.

Two new species of the genus Triplophysa from southwestern Guizhou Province, China, are described. These are Triplophysa ziyunensis Wu, Luo, Xiao & Zhou, sp. nov. and Triplophysa yaluwang Lan, Liu, Zhou & Zhou, sp. nov. from Maoying Town, Ziyun County, Guizhou Province, China. Triplophysa ziyunensis Wu, Luo, Xiao & Zhou, sp. nov. is distinguished from other hypogean species of the genus Triplophysa by having a combination of the following characteristics: body naked, scaleless, pigmented markings on surface of body, except ventral; eyes reduced, diameter 2.4–4.9% of head length; pelvic-fin tip extending to anus; tip of pectoral fin not reaching pelvic fin origin; anterior and posterior nostrils closely set, with anterior nostril elongated to a barbel-like tip; tip of outrostral barbel extending backward, not reaching anterior margin of the eye; lateral line complete; posterior chamber of air bladder degenerated; and fin differences. Triplophysa yaluwang Lan, Liu, Zhou & Zhou, sp. nov. is distinguished from other hypogean species of the genus Triplophysa by having a combination of the following characteristics: body naked, scaleless, with irregular pale and dark brownish brown markings, except ventrally; eyes reduced, diameter 4.6–6.1% of head length; pelvic-fin tip reaching anus; tip of pectoral fin not reaching to pelvic fin origin; anterior and posterior nostrils closely set, with anterior nostril elongated to a barbel-like tip; tip of outrostral barbel extending backward, not reaching to anterior margin of the eye; lateral line complete; posterior chamber of air bladder degenerated; and fin differences. Mitochondrial Cyt b revealed relatively small genetic differences, 1.4–2.0%, between the two new species and close relatives. Nuclear gene RAG1 indicated that the two new species possessed unique haplotypes with multiple linking mutations. This study emphasizes the importance of utilizing nuclear genes to identify new species in rapidly speciation cave species, with small genetic differences due to mitochondrial introgression occurring interspecies.

This research documents a new record of Miniopterus magnater in the south-western region of China, a significant discovery given the limited diversity of the Miniopterus genus within the country. Only three species of Miniopterus occur in China: Miniopterus magnater, Miniopterus fuliginosus and Miniopterus pusillus. These species share a high degree of morphological similarity, particularly in their external characteristics. This underscores the necessity for the identification of additional distinguishing traits that can aid in the taxonomic differentiation of these closely-related species.During the 2023 field expedition to various nature reserves in Yunnan Province, China, we encountered specimens of the genus Miniopterus. Utilising a combination of morphological assessments and phylogenetic analyses, we identified six individuals as Miniopterus magnater. A review of the existing geographical distribution data revealed that this species is primarily found in central and southern regions of China, with no previous records from the south-western part of the country. Based on our findings, we present a novel record of Miniopterus magnater's distribution in the south-western region of China.

Abstract Non-coding RNAs (ncRNAs) are frequently documented RNA modification substrates. Nanopore Technologies enables the direct sequencing of RNAs and the detection of modified nucleobases. Ordinarily, direct RNA sequencing uses polyadenylation selection, studying primarily mRNA gene expression. Here, we present NERD-seq, which enables detection of multiple non-coding RNAs, excluded by the standard approach, alongside natively polyadenylated transcripts. Using neural tissues as a proof of principle, we show that NERD-seq expands representation of frequently modified non-coding RNAs, such as snoRNAs, snRNAs, scRNAs, srpRNAs, tRNAs, and rRFs. NERD-seq represents an RNA-seq approach to simultaneously study mRNA and ncRNA epitranscriptomes in brain tissues and beyond.

Abstract Background The occurrence of blastocyst collapse may become an indicator of preimplantation embryo quality assessment. It has been reported that collapsing blastocysts can lead to higher rates of aneuploidy and poorer clinical outcomes, but more large-scale studies are needed to explore this relationship. This study explored the characteristics of blastocyst collapse identified and quantified by artificial intelligence and explored the associations between blastocyst collapse and embryo ploidy, morphological quality, and clinical outcomes. Methods This observational study included data from 3288 biopsied blastocysts in 1071 time-lapse preimplantation genetic testing cycles performed between January 2019 and February 2023 at a single academic fertility center. All transferred blastocysts are euploid blastocysts. The artificial intelligence recognized blastocyst collapse in time-lapse microscopy videos and then registered the collapsing times, and the start time, the recovery duration, the shrinkage percentage of each collapse. The effects of blastocyst collapse and embryo ploidy, pregnancy, live birth, miscarriage, and embryo quality were studied using available data from 1196 euploid embryos and 1300 aneuploid embryos. Results 5.6% of blastocysts collapsed at least once only before the full blastocyst formation (tB), 19.4% collapsed at least once only after tB, and 3.1% collapsed both before and after tB. Multiple collapses of blastocysts after tB (times ≥ 2) are associated with higher aneuploid rates (54.6%, P > 0.05; 70.5%, P

Abstract Background Primary pulmonary myxoid sarcoma (PPMS) is a rare, low-grade malignant tumor, constituting approximately 0.2% of all lung tumors. Despite its rarity, PPMS possesses distinctive histological features and molecular alterations, notably the presence of EWSR1-CREB1 gene fusion. However, its precise tissue origin remains elusive, posing challenges in clinical diagnosis. Case demonstration A 20-year-old male patient underwent a routine physical examination 6 months prior, revealing a pulmonary mass. Following surgical excision, microscopic evaluation unveiled predominantly short spindle-shaped tumor cells organized in a fascicular, beam-like, or reticular pattern. The stromal matrix exhibited abundant mucin, accompanied by lymphocytic and plasma cell infiltration, with Russell bodies evident in focal areas. Immunophenotypic profiling revealed positive expression of vimentin and epithelial membrane antigen in tumor cells, whereas smooth muscle actin and S-100, among others, were negative. Ki-67 proliferation index was approximately 5%. Subsequent second-generation sequencing identified the characteristic EWSR1-CREB1 gene fusion. The definitive pathological diagnosis established PPMS. The patient underwent no adjuvant chemotherapy or radiotherapy and remained recurrence-free during a 30-month follow-up period. Conclusions We report a rare case of PPMS located within the left lung lobe interlobar fissure, featuring Russell body formation within the tumor stroma, a novel finding in PPMS. Furthermore, the histomorphological characteristics of this case highlight the diagnostic challenge it poses, as it may mimic inflammatory myofibroblastic tumor, extraskeletal myxoid chondrosarcoma, or hemangiopericytoma-like fibrous histiocytoma. Therefore, accurate diagnosis necessitates an integrated approach involving morphological, immunohistochemical, and molecular analyses.

The objective of this study is to assess the impact of utilizing a BW (Buttress wall) to control the deflection of a diaphragm wall in colluvial soil conditions in Vietnam. The physical and mechanical properties of the colluvial layers are evaluated using data closely monitored during a specific project, serving as validation for 3D numerical simulations utilizing the Hardening Soil Model. The analysis results closely match the field monitoring data, which has tested the accuracy of the simulation model. This forms the basis for further investigations into the dimensional parameters of BW walls, including length, thickness, and spacing between them. The results obtained from the parametric study demonstrate that altering the wall length and spacing between BWwalls significantly limits the deflection of the diaphragm wall, while changes in thickness have a negligible effect. Through the 3D numerical simulations, a linear relationship between the maximum wall deflection and parameters such as wall length and spacing between BW walls has been established.

Abstract Background Emerging evidence has indicated a link between the gut microbiota and acute lymphoblastic leukaemia (ALL). However, the acute changes in gut microbiota during chemotherapy and the predictive value of baseline gut microbiota in infectious complication remain largely unknown. Methods Faecal samples (n = 126) from children with ALL (n = 49) undergoing induction chemotherapy were collected at three timepoints, i.e., initiation of chemotherapy (baseline, T0), 7 days (T1) and 33 days (T2) after initiation of chemotherapy. Gut microbiome profile was performed via metagenomic shotgun sequencing. The bioBakery3 pipeline (Kneaddata, Metaphlan 3 and HUMAnN) was performed to assign taxonomy and functional annotations. Gut microbiome at T0 were used to predict infection during chemotherapy. Results The microbial diversities and composition changed significantly during chemotherapy, with Escherichia coli, Klebsiella pneumoniae and Bifidobacterium longum being the most prominent species. The microbial metabolic pathways were also significantly altered during chemotherapy, including the pathway of pyruvate fermentation to acetate and lactate, and assimilatory sulfate reduction pathway. The receiver operating characteristic (ROC) models based on Bifidobacterium longum at T0 could predict infectious complications during the first month of chemotherapy with the area under the curve (AUC) of 0.720. Conclusions Our study provides new insights into the acute changes in microbial and functional characteristics in children with ALL during chemotherapy. The baseline gut microbiota could be potential biomarkers for infections during chemotherapy. Trial registration The study was approved by the Ethics Committee of Zhujiang Hospital, Southern Medical University (2021-KY-171-01) and registered on http://www.chictr.org.cn (ChiCTR2200065406, Registration Date: November 4, 2022).

Objective: An alternative to conventional posterior lumbar interbody fusion (PLIF) is a PLIF with transpedicular oblique screw fixation system. An assessment of new fixation system's viability and efficacy is conducted through a comparison of its biomechanical properties with those of conventional PLIF. Method: A comprehensive finite element model (FEM) of the lumbar regions L1-L5 was developed and the surgical segment L3-L4 was chosen to comprise the surgical models of both traditional PLIF and new PLIF. In new PLIF model, an analysis was conducted on segmental range of motion (RoM), cage stress, inferior endplates stress, vertebral stress, and internal fixation stress. Three-dimensional printers are utilized to fabricate and assemble the fusion cage and vertebrae, and compression test machines are employed to execute physiological load and extreme load experiments on new PLIF, so as to verify the accuracy of the FEM analysis and the mode of fatigue exhibited by new PLIF. Results: In new PLIF, the maximum stress on the inferior endplates under physiological loads was reduced in comparison to conventional PLIF. While the maximum stress on the cage, vertebral body, and screw increased, it remained within an acceptable range. The experimental data indicates that new fixation system can endure a vertical load exceeding 2800 N and an ultimate bending moment of 77 Nm. Conclusion: The new PLIF exhibits a comparable RoM to its predecessor, simultaneously mitigating inferior endplate stress and accommodating physiological loads, which reduce the amount of surgical incision and fusion fixation instruments. Consequently, it emerges as a sanguine surgical approach to fuse the degenerative lumbar spine.

Tremella fuciformis (TF) stem accounts for about 10% of the whole mushroom, and most of them are dumped without utilization. To effectively utilize the waste, the effects of fine grinding and superfine grinding technology on the processing characteristics and physicochemical properties of Tremella fuciformis stem powder (TFSP) were investigated, and the effects of TFSP on the quality of steamed bun were analyzed. The findings indicate that the specific surface area of superfine Tremella fuciformis stem powder (STFSP) is 1.6 times larger than that of fine Tremella fuciformis stem powder (FTFSP). Despite this, the infrared spectra of STFSP and FTFSP are similar. The water solubility index and oil holding capacities of STFSP saw an increase of 18.81%, whereas its water holding capacity decreased by 11.34%. Superfine grinding not only enhanced the processing characteristics but also stabilized the powder form. Moreover, steamed buns incorporating 4% STFSP were judged to have the optimal taste. Superfine grinding significantly influences the physicochemical properties of TFSP, resulting in enhanced quality of steamed buns.

Summary: Building a simple and efficient in vitro differentiation system is crucial for studying the regulatory mechanisms during the development of innate lymphoid cells (ILCs). Here, we present a protocol for generating ILC subsets from α4β7+ lymphoid progenitors (αLPs). We describe steps for murine cell isolation from fetal liver and adult bone marrow, flow cytometry sorting for αLPs, and cell culture. We then detail procedures for flow cytometry analysis of ILCs. This protocol significantly simplifies the differentiation process through ILC differentiation in vitro.For complete details on the use and execution of this protocol, please refer to Wu et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

In this paper, a spiral motion computation method based on transformation optics for computing the microwave heating processes with irregular food is presented. Firstly, the theoretical derivations of the rotating, lifting, and overlapping regions caused by rotating and lifting are conducted. Secondly, the electric field distribution computed by the proposed method is verified, and the computation accuracy and time are compared with implicit function and level set methods (IFLSM). It was found that the root-mean-square-errors (RMSEs) of the port reflection coefficients for rotating motion, lifting motion, and spiral motion are 0.021, 0.164, and 0.151, respectively, demonstrating the effectiveness of the proposed method in computing the spiral motion of irregular food shapes. Finally, the computation of spiral microwave heating of irregular-shaped bears with different materials under different motion states is studied, and the industrial application of cookies in secondary processing is analyzed.

Abstract Background Papillary thyroid carcinoma (PTC) stands out as the most prevalent epithelial malignant thyroid tumor. Thyroid primary follicular lymphoma (PFL) represents a rare malignant tumor originating from mesenchymal tissues. The concurrent occurrence of PTC and PFL is exceptionally rare, particularly in the context of Hashimoto’s thyroiditis, presenting significant challenges in clinical diagnosis and treatment. Case demonstration A 44-year-old female patient presented with a neck mass persisting for over 1 month. The patient underwent surgery, and the incised tissues were subjected to pathology examinations, along with immunohistochemistry and next-generation sequencing tests suggestive of an EZH2 gene mutation in the tumor cells. The final pathological diagnosis confirmed the presence of PTC combined with PFL. Following a 27-month follow-up, the patient displayed no signs of recurrence or metastasis. Conclusions The concurrent occurrence of PTC and PFL poses notable challenges in clinical practice, requiring careful consideration in diagnosis and treatment. Herein, we present a rare case of PTC combined with PFL featuring an EZH2 gene mutation, which can be easily overlooked in the context of Hashimoto’s thyroiditis. The patient’s favorable response to surgical and radiotherapeutic interventions underscores the importance of accurate diagnosis and tailored treatment strategies in similar cases.

The goal of this study is to assess the application of the Hardening soil model in predicting the deformation of retaining walls of excavations in 2D and 3D finite element analysis at the Ho Chi Minh Metro project. Designed as the deepest underground station in the first metro line built in Ho Chi Minh City (HCMC), Opera House station is located in an area with a dense building zone and close to historical buildings. A summary of the input soil properties is provided using data from site investigations, in-situ tests, and laboratory tests. By numerical simulation using the Hardening soil model, the parameters of the soil stiffness modulus value are verified based on the Standard Penetration Test (SPT), and Pressuremeter test (PMT). The obtained results of the numerical analysis by 2D and 3D finite element methods, and field observations indicate that applying the Hardening soil model with soil stiffness modulus obtained in situ tests gives reasonable results on the displacement of the retaining wall at the final phase. The relationship between the SPT value and the stiffness modulus of HCMC sand is a function of depth. This correlation is obtained through the comparison of wall deformation between the simulation and monitoring at the construction site. The results of the difference between 2D and 3D finite element analysis also are discussed in this study.

Objectives Osteoporotic vertebral fractures (OVFs) are a critical public health concern requiring urgent attention, and severe OVFs impose substantial health and economic burdens on patients and society. Analysis of the risk factors for severe OVF is imperative to actively prevent the occurrence of this degenerative disorder. This study aimed to investigate the risk factors associated with the severity of OVF, with a specific focus on changes in the paraspinal muscles. Methods A total of 281 patients with a first‐time single‐level acute OVF between January 2016 and January 2023 were enrolled in the study. Clinical and radiological data were collected and analyzed. The cross‐sectional area (CSA) and degree of fatty infiltration (FI) of the paraspinal muscles, including the multifidus muscles (MFMs), erector spinae muscles (ESMs), and psoas major muscles (PSMs), were measured by magnetic resonance imaging (MRI) of the L4/5 intervertebral discs. According to the classification system of osteoporotic fractures (OF classification) and recommended treatment plan, OVFs were divided into a low‐grade OF group and a high‐grade OF group. Univariate and multivariate logistic regression analyse s were performed to identify risk factors associated with the severity of OVF. Results Ninety‐eight patients were included in the low‐grade OF group, and 183 patients were included in the high‐grade OF group. Univariate analysis revealed a significantly higher incidence of a high degree of FI of MFMs (OR = 1.71, p = 0.002) and ESMs (OR = 1.56, p = 0.021) in the high‐grade OF group. Further multivariate logistic regression analysis demonstrated that a high degree of FI of the MFMs (OR = 1.71, p = 0.002) is an independent risk factor for the severity of OVF. Conclusion A high degree of FI of the MFMs was identified as an independent risk factor for the severity of OVF. Decreasing the degree of FI in the MFMs might lower the incidence of the severity of OVF, potentially reducing the necessity for surgical intervention in OVF patients.

Abstract Background Premature ovarian failure (POF) has a profound impact on female reproductive and psychological health. In recent years, the transplantation of umbilical cord-derived mesenchymal stem cells (UC-MSCs) has demonstrated unprecedented potential in the treatment of POF. However, the heterogeneity of human UC-MSCs remains a challenge for their large-scale clinical application. Therefore, it is imperative to identify specific subpopulations within UC-MSCs that possess the capability to improve ovarian function, with the aim of reducing the uncertainty arising from the heterogeneity while achieving more effective treatment of POF. Methods 10 × Genomics was performed to investigate the heterogeneity of human UC-MSCs. We used LRP1 as a marker and distinguished the potential therapeutic subpopulation by flow cytometry, and determined its secretory functions. Unsorted UC-MSCs, LRP1high and LRP1low subpopulation was transplanted under the ovarian capsules of aged mice and CTX-induced POF mice, and therapeutic effects was evaluated by assessing hormone levels, estrous cycles, follicle counts, and embryo numbers. RNA sequencing on mouse oocytes and granulosa cells after transplantation was performed to explore the mechanism of LRP1high subpopulation on mouse oocytes and granulosa cells. Results We identified three distinct functional subtypes, including mesenchymal stem cells, multilymphoid progenitor cells and trophoblasts. Additionally, we identified the LRP1high subpopulation, which improved ovarian function in aged and POF mice. We elucidated the unique secretory functions of the LRP1high subpopulation, capable of secreting various chemokines, cytokines, and growth factors. Furthermore, LRP1 plays a crucial role in regulating the ovarian microenvironment, including tissue repair and extracellular matrix remodeling. Consistent with its functions, the transcriptomes of oocytes and granulosa cells after transplantation revealed that the LRP1high subpopulation improves ovarian function by modulating the extracellular matrix of oocytes, NAD metabolism, and mitochondrial function in granulosa cells. Conclusion Through exploration of the heterogeneity of UC-MSCs, we identified the LRP1high subpopulation capable of improving ovarian function in aged and POF mice by secreting various factors and remodeling the extracellular matrix. This study provides new insights into the targeted exploration of human UC-MSCs in the precise treatment of POF. Graphical abstract

Amid a growing global focus on ecological conservation and biodiversity monitoring, the efficient identification and tracking of wildlife are essential for environmental research, wildlife protection, and habitat management. Nevertheless, intricate landscapes, varied animal sizes, and obstructions obstruct wildlife detection and tracking. This study introduces the wilDT-YOLOv8n model, specifically engineered for the effective identification and tracking of animals. Initially, the Stable Diffusion model augments the dataset, establishing a basis for training data. Subsequently, enhancements to the Yolov8n model are implemented through the incorporation of the deformable convolutional network DCNv3 and the utilization of the C2f_DCNV3 layer to augment feature extraction efficacy, while addressing detection challenges associated with small targets and intricate backgrounds by integrating the EMGA attention mechanism and the ASPFC feature fusion module. Enhancing the Extended Kalman Filter algorithm guarantees reliable and precise tracking. The research findings reveal that the wilDT-YOLOv8n model attained an average detection accuracy (mAP50) of 88.54 % on the custom dataset, reflecting a 4.57 % enhancement over the original YOLOv8n model; the refined Extended Kalman Filter realizes a Multi-Object Tracking Accuracy (MOTA) of 40.35 %, representing a 3.923 % advancement over the original Kalman Filter. The results indicate the feasibility of accurately detecting and monitoring wildlife in intricate environments, offering significant insights for ecological research and biodiversity conservation, and aiding in the protection of endangered species.

The role of CD161+CD127+CD8+ T cells in non-small cell lung cancer (NSCLC) patients with diabetes remains unexplored. This study determined the prevalence, phenotype, and function of CD8+ T cell subsets in NSCLC with diabetes. We recruited NSCLC patients (n = 436) treated with anti-PD-1 immunotherapy as first-line treatment. The progression-free survival (PFS), overall survival (OS), T cells infiltration, and peripheral blood immunological characteristics were analyzed in NSCLC patients with or without diabetes. NSCLC patients with diabetes exhibited shorter PFS and OS (p = 0.0069 and p = 0.012, respectively) and significantly lower CD8+ T cells infiltration. Mass cytometry by time-of-flight (CyTOF) showed a higher percentage of CD161+CD127+CD8+ T cells among CD8+T cells in NSCLC with diabetes before anti-PD-1 treatment (p = 0.0071) than that in NSCLC without diabetes and this trend continued after anti-PD-1 treatment (p = 0.0393). Flow cytometry and multiple-immunofluorescence confirmed that NSCLC with diabetes had significantly higher CD161+CD127+CD8+ T cells to CD8+T cells ratios than NSCLC patients without diabetes. The RNA-sequencing analysis revealed immune-cytotoxic genes were reduced in the CD161+CD127+CD8+ T cell subset compared to CD161+CD127−CD8+ T cells in NSCLC with diabetes. CD161+CD127+CD8+ T cells exhibited more T cell-exhausted phenotypes in NSCLC with diabetes. NSCLC patients with diabetes with ≥ 6.3% CD161+CD127+CD8+ T cells to CD8+T cells ratios showed worse PFS. These findings indicate that diabetes is a risk factor for NSCLC patients who undergo anti-PD-1 immunotherapy.CD161+CD127+CD8+ T cells could be a key indicator of a poor prognosis in NSCLC with diabetes. Our findings would help in advancing anti-PD-1 therapy in NSCLC patients with diabetes.

BackgroundChimeric antigen receptor T-cell (CAR-T) therapy, a rapidly emerging treatment for cancer that has gained momentum since its approval by the FDA in 2017, involves the genetic engineering of patients’ T cells to target tumors. Although significant therapeutic benefits have been observed, life-threatening adverse pulmonary events have been reported.MethodsUsing SAS 9.4 with MedDRA 26.1, we retrospectively analyzed data from the Food and Drug Administration’s Adverse Event Reporting System (FAERS) database, covering the period from 2017 to 2023. The analysis included the Reporting Odds Ratio Proportional Reporting Ratio Information Component and Empirical Bayes Geometric Mean to assess the association between CAR-T cell therapy and adverse pulmonary events (PAEs).ResultsThe FAERS database recorded 9,400 adverse events (AEs) pertaining to CAR-T therapies, of which 940 (10%) were PAEs. Among these CAR-T cell-related AEs, hypoxia was the most frequently reported (344 cases), followed by respiratory failure (127 cases). Notably, different CAR-T cell treatments demonstrated varying degrees of association with PAEs. Specifically, Tisa-cel was associated with severe events including respiratory failure and hypoxia, whereas Axi-cel was strongly correlated with both hypoxia and tachypnea. Additionally, other CAR-T therapies, namely, Brexu-cel, Liso-cel, Ide-cel, and Cilta-cel, have also been linked to distinct PAEs. Notably, the majority of these PAEs occurred within the first 30 days post-treatment. The fatality rates varied among the different CAR-T therapies, with Tisa-cel exhibiting the highest fatality rate (43.6%), followed by Ide-cel (18.8%).ConclusionThis study comprehensively analyzed the PAEs reported in the FAERS database among recipients of CAR-T cell therapy, revealing conditions such as hypoxia, respiratory failure, pleural effusion, and atelectasis. These CAR-T cell therapy-associated events are clinically significant and merit the attention of clinicians and researchers.

IntroductionAnalyzing the correlation between planktonic eukaryotic communities (PECs) and aquatic physicochemical parameters (APPs) provides important references for predicting the impact of climate change and human activities on aquatic ecosystems.MethodsTo assess the influence of seasons and APPs on PEC structures in lakes and rivers, we utilized high-throughput sequencing of the 18S rRNA gene to analyze PEC structures in a lake and seven rivers in the Chaohu Lake Basin and analyzed their correlations with APPs.ResultsOur results revealed that PEC structure was significantly affected by season, with the highest α-diversity observed in summer. Furthermore, we identified several APPs, including water temperature, conductivity, dissolved oxygen, pH, phosphate, total phosphorus, trophic level index (TLI), nitrate, ammonia nitrogen, and total nitrogen, that significantly influenced PEC structures. Specifically, we found that Stephanodiscus hantzschii, Simocephalus serrulatus, Cryptomonas sp. CCAC_0109, Pedospumella encystans, Actinochloris sphaerica, Chlamydomonas angulosa, Gonyostomum semen, Skeletonema potamos, Chlamydomonas klinobasis, Pedospumella sp., and Neochlorosarcina negevensis were significantly correlated to TLI, while Limnoithona tetraspina, Theileria sp., and Pseudophyllomitus vesiculosus were significantly correlated to the water quality index (WQI). However, our random forest regression analysis using the top 100 species was unable to accurately predict the WQI and TLI.DiscussionThese results provide valuable data for evaluating the impact of APPs on PEC and for protecting water resource in the Chaohu Lake Basin.

BackgroundAccumulating evidence reveals mitochondrial dysfunction exacerbates intestinal barrier dysfunction and inflammation. Despite the growing knowledge of mitochondrial dysfunction and ulcerative colitis (UC), the mechanism of mitochondrial dysfunction in UC remains to be fully explored.MethodsWe integrated 1137 UC colon mucosal samples from 12 multicenter cohorts worldwide to create a normalized compendium. Differentially expressed mitochondria-related genes (DE-MiRGs) in individuals with UC were identified using the “Limma” R package. Unsupervised consensus clustering was utilized to determine the intrinsic subtypes of UC driven by DE-MiRGs. Weighted gene co-expression network analysis was employed to investigate module genes related to UC. Four machine learning algorithms were utilized for screening DE-MiRGs in UC and construct MiRGs diagnostic models. The models were developed utilizing the over-sampled training cohort, followed by validation in both the internal test cohort and the external validation cohort. Immune cell infiltration was assessed using the Xcell and CIBERSORT algorithms, while potential biological mechanisms were explored through GSVA and GSEA algorithms. Hub genes were selected using the PPI network.ResultsThe study identified 108 DE-MiRGs in the colonic mucosa of patients with UC compared to healthy controls, showing significant enrichment in pathways associated with mitochondrial metabolism and inflammation. The MiRGs diagnostic models for UC were constructed based on 17 signature genes identified through various machine learning algorithms, demonstrated excellent predictive capabilities. Utilizing the identified DE-MiRGs from the normalized compendium, 941 patients with UC were stratified into three subtypes characterized by distinct cellular and molecular profiles. Specifically, the metabolic subtype demonstrated enrichment in epithelial cells, the immune-inflamed subtype displayed high enrichment in antigen-presenting cells and pathways related to pro-inflammatory activation, and the transitional subtype exhibited moderate activation across all signaling pathways. Importantly, the immune-inflamed subtype exhibited a stronger correlation with superior response to four biologics: infliximab, ustekinumab, vedolizumab, and golimumab compared to the metabolic subtype.ConclusionThis analysis unveils the interplay between mitochondrial dysfunction and the immune microenvironment in UC, thereby offering novel perspectives on the potential pathogenesis of UC and precision treatment of UC patients, and identifying new therapeutic targets.

The recycled concrete fine powder (RFP) after calcination activation not only contains active powder with potential hydration characteristics, but also may cause the limestone contained in the fine powder to form calcium oxide. The effects of TRFP-750 and TRFP-850(RFP calcined at 750 ℃ and 850 ℃) replacing calcium oxide on the preparation and properties of autoclaved aerated concrete (AAC) were investigated in this study. The results showed that when 60% of calcium oxide in quicklime is replaced by TRFP-750 and TRFP-850, AAC with strength greater than 2.5 MPa and density less than 550 kg/m3 can be prepared. The dosage of TRFP will degrade the gas-foaming performance of AAC due to the decrease in temperature and alkalinity of the slurry. At the same content, AAC with TRFP-850 had higher gas-foaming rate due to more free calcium oxide. When the TRFP content is the same, TRFP-850 also leads to a higher compressive strength than the AAC containing TRFP-750. Tobermorite with better crystallinity and the increase of tobermorite content are the main reasons for the higher strength of AAC.

Gastric cancer is one of the most common cancers and is considered the 5th most frequent occurring cancer worldwide. It has gained great attention from the clinicians and researchers because of high mortality rate. It is generally treated with chemotherapy, radiotherapy, and surgery. Recently, additional treatment options including immunotherapy and targeted therapy and immunotherapy have been developed. However, poor prognosis, limited survival rate of patients, and drug resistance to treatment remain critical problems. To improve treatment options or to overcome the bottleneck of treatment, identification of diagnostic and prognostic markers, determining the most effective therapeutic options, and uncovering the molecular regulations associated with treatment strategies are required. In this regard n6-methyladenosine (m6A) regulation is considered important. This reversible modification plays a crucial role in progression, development and treatment of HER2-positive gastric cancer. Here, we discuss the role of m6A modification in HER2-positive gastric cancer progression through collecting related studies at present. We further discuss the association of m6A modification with therapeutic efficacy in HER2-positive gastric cancer and list some examples. We conclude that modification of m6A can be a new strategy for improving the prognosis and survival rate of HER2-positive gastric cancer patients.

Warthin-like mucoepidermoid carcinoma (WL-MEC) is a newly reported variant of mucoepidermoid carcinoma. Its histological feature is easy to confused with metaplastic Warthin Tumor, and its relationship with Warthin tumor in histogenesis is controversial. In this study, we presented two cases of WL-MEC, discussing their clinicopathological and molecular features. Notably, one case was initially misdiagnosed during the first onset of the tumor. Case 1 was a 60-year-old female with a mass in the right parotid gland. Case 2 featured a 29-year-old male who developed a lump at the original surgical site 6 months after a “Warthin tumor” resection from the submandibular gland. Histologically, both tumor exhibited a prominent lymphoid stroma and cystic pattern, accompanied by various amounts of epithelial nests composed of squamoid cells, intermediate cells and mucinous cells. The characteristic eosinophilic bilayer epithelium of Warthin tumor was not typically presented in either case. Both cases tested positive for MAML2 gene rearrangement. To contextualize our findings, we conducted a comprehensive review of forty-eight WL-MEC cases documented in the English literature, aiming to synthesizing a reliable differential diagnostic approach. WL-MEC is a rare yet clinically relevant variant, posing a diagnostic pitfall for pathologists. Our study underscores the importance of a meticulous evaluation of both clinical and histological features, coupled with the detection of MAML2 rearrangement, as a credible method for distinguishing WL-MEC from other benign and malignant lesions, particularly metaplastic Warthin tumor.

BackgroundAnalyzing the differences in caregiving models for disabled older adult individuals after stroke and the influencing factors, to provide a basis for addressing relevant social demographic issues.MethodsThe older adult diagnosed with stroke were screened from the Chinese Geriatric Health Survey (CLHLS), and were further divided into subgroups of disability, which was based on their ability of or whether they need help in performing activities such as dressing, bathing, eating, toileting or bowel and bladder control using the international common Katz scale. The care model was divided into formal care, informal care and home care. Multivariate logistic regression was used to screen the influencing factors of the choice of care model for the disabled older adult after stroke.ResultsThe results of univariate analysis showed that there were statistical differences in the choice of care mode among different ages, household registration types, number of children, years of education, degree of disability, community services, retirement pension, marital status and medical insurance. Multiple logistic regression showed that, The rural older adult with more children, shorter education years, living with spouse and no help from community tend to choose informal care. Older adult people with higher levels of education, urban household registration, and access to community services are more likely to choose formal care. Older adult women with multiple children are more likely to receive care from their children.ConclusionIn the future, vigorous support for the development of formal caregiving institutions and the improvement of the management system of formal caregiving will help enhance the subjective initiative of disabled older adult individuals in choosing caregiving models and alleviate the burden of family caregiving.

IntroductionOsteoporosis, characterized by low bone mineral density (BMD), is an increasingly serious public health issue. So far, several traditional regression models and machine learning (ML) algorithms have been proposed for predicting osteoporosis risk. However, these models have shown relatively low accuracy in clinical implementation. Recently proposed deep learning (DL) approaches, such as deep neural network (DNN), which can discover knowledge from complex hidden interactions, offer a new opportunity to improve predictive performance. In this study, we aimed to assess whether DNN can achieve a better performance in osteoporosis risk prediction.MethodsBy utilizing hip BMD and extensive demographic and routine clinical data of 8,134 subjects with age more than 40 from the Louisiana Osteoporosis Study (LOS), we developed and constructed a novel DNN framework for predicting osteoporosis risk and compared its performance in osteoporosis risk prediction with four conventional ML models, namely random forest (RF), artificial neural network (ANN), k-nearest neighbor (KNN), and support vector machine (SVM), as well as a traditional regression model termed osteoporosis self-assessment tool (OST). Model performance was assessed by area under ‘receiver operating curve’ (AUC) and accuracy.ResultsBy using 16 discriminative variables, we observed that the DNN approach achieved the best predictive performance (AUC = 0.848) in classifying osteoporosis (hip BMD T-score ≤ −1.0) and non-osteoporosis risk (hip BMD T-score > −1.0) subjects, compared to the other approaches. Feature importance analysis showed that the top 10 most important variables identified by the DNN model were weight, age, gender, grip strength, height, beer drinking, diastolic pressure, alcohol drinking, smoke years, and economic level. Furthermore, we performed subsampling analysis to assess the effects of varying number of sample size and variables on the predictive performance of these tested models. Notably, we observed that the DNN model performed equally well (AUC = 0.846) even by utilizing only the top 10 most important variables for osteoporosis risk prediction. Meanwhile, the DNN model can still achieve a high predictive performance (AUC = 0.826) when sample size was reduced to 50% of the original dataset.ConclusionIn conclusion, we developed a novel DNN model which was considered to be an effective algorithm for early diagnosis and intervention of osteoporosis in the aging population.

In the development of chronic liver disease, the hepatic stellate cell (HSC) plays a pivotal role in increasing intrahepatic vascular resistance (IHVR) and inducing portal hypertension (PH) in cirrhosis. Our research demonstrated that HSC contraction, prompted by angiotensin II (Ang II), significantly contributed to the elevation of type I collagen (COL1A1) expression. This increase was intimately associated with enhanced cell tension and YAP nuclear translocation, mediated through α-smooth muscle actin (α-SMA) expression, microfilaments (MF) polymerization, and stress fibers (SF) assembly. Further investigation revealed that the Rho/ROCK signaling pathway regulated MF polymerization and SF assembly by facilitating the phosphorylation of cofilin and MLC, while Ca2+ chiefly governed SF assembly via MLC. Inhibiting α-SMA-MF-SF assembly changed Ang II-induced cell contraction, YAP nuclear translocation, and COL1A1 expression, findings corroborated in cirrhotic mice models. Overall, our study offers insights into mitigating IHVR and PH through cell mechanics, heralding potential breakthroughs.

Abstract The wide spread of Perfluoroalkyl substances (e.g., PFOA and PFOS) in soil can alter native soil geochemical properties and microbial communities through various approaches. Nonetheless, it is unclear that how PFOA and PFOS in soil affect the mineralization of soil organic carbon (SOC). A laboratory-scale culture experiment (180 d) was performed to explore the contribution of PFOA and PFOS to SOC dynamics and soil geochemical processes. Results showed that positive priming effect (PE) occurred in the short term (i.e., 30 days after PFOA and PFOS addition) and subsequently shifted to a slightly negative PE (i.e., 90 days) and remained in a significant negative PE thereafter (i.e., > 180 days). The PEs caused by PFOA and PFOS both accelerated the consumption of dissolved organic carbon (DOC), resulting in a significant increase in SOC mineralization (10.45%–127.36%) under the short-term incubation (30 d). As for long-term exposure (> 90 d), the organic carbon mineralization rate was significantly reduced (58.30%–65.24%) due to the excessive DOC consumption in the initial stage. High throughput analysis indicated that both PFOA and PFOS changed soil bacterial and fungal community structures, altered the relevant metabolic pathways and resulted in the enrichment of specific taxa. Graphical Abstract

Abstract Backgrounds Breast cancer screening plays an important role in the early detection, diagnosis and treatment of breast cancer. The aim of this study was to evaluate the screening results and explore the influencing factors of breast cancer detection rate in Guangdong. Methods This cross-sectional study was conducted among 2,024,960 women aged 35–64 in Guangdong Province during 2017–2021. The data about breast cancer screening information were collected from the Guangdong maternal and child health information system. Descriptive statistical analysis was used to explain demographic characteristics and results of breast cancer screening. The generalized linear regression model was applied to analyze the related influencing factors of breast cancer detection rate. Results The estimated detection rate of breast cancer in Guangdong Province is 70.32/105, with an early diagnosis rate of 82.06%. After adjusting covariates, those women with older age (45–55 [OR (95% CI) 2.174 (1.872, 2.526)], 55–65 [OR (95% CI) 2.162 (1.760, 2.657)]), education for high school ([OR (95% CI) 1.491 (1.254, 1.773)]) and older age at first birth ([OR (95% CI) 1.632 (1.445, 1.844)]) were more likely to have higher detection rate of breast cancer. No history of surgery or biopsy ([OR (95% CI) 0.527 (0.387, 0.718)]), no history of breast cancer check ([OR (95% CI) 0.873 (0.774, 0.985)]) and no family history of breast cancer ([OR (95% CI) 0.255 (0.151, 0.432)]) women were more likely to screen negative for breast cancer (P

Nasal drug delivery efficiency is highly dependent on the position in which the drug is deposited in the nasal cavity. However, no reliable method is currently available to assess its impact on delivery performance. In this study, a biomimetic nasal model based on three-dimensional (3D) reconstruction and three-dimensional printing (3DP) technology was developed for visualizing the deposition of drug powders in the nasal cavity. The results showed significant differences in cavity area and volume and powder distribution in the anterior part of the biomimetic nasal model of Chinese males and females. The nasal cavity model was modified with dimethicone and validated to be suitable for the deposition test. The experimental device produced the most satisfactory results with five spray times. Furthermore, particle sizes and spray angles were found to significantly affect the experimental device's performance and alter drug distribution, respectively. Additionally, mometasone furoate (MF) nasal spray (NS) distribution patterns were investigated in a goat nasal cavity model and three male goat noses, confirming the in vitro and in vivo correlation. In conclusion, the developed human nasal structure biomimetic device has the potential to be a valuable tool for assessing nasal drug delivery system deposition and distribution.

Abstract Background PANoptosis represents a newly identified form of programmed cell death that plays a significant role in the autoimmune diseases. Rheumatoid arthritis (RA) is characterized by the presence of autoantibodies. Nevertheless, the specific biomarkers and molecular mechanisms responsible for the apoptotic characteristics of RA remain largely uninvestigated. Methods We utilized 8 synovial tissue RA datasets. We selected genes associated with PANoptosis from the GeneCard database. By employing the limma, WGCNA, and machine learning algorithms we identified core genes. We utilized consensus clustering analysis to identify distinct PANoptosis subtypes of RA. Boruta algorithm was employed to construct a PANoptosis signature score. The sensitivity of distinct subtypes to drug treatment was verified using an independent dataset. Results The SPP1 emerged as the significant gene, with its elevated expression in RA patients. We identified two PANoptosis RA subtypes. Cluster 1 showed high expression of Tregs, resting dendritic cells, and resting mast cells. Cluster 2 exhibited high expression of CD4 memory T cells and follicular helper T cells. Cluster 2 exhibited a higher degree of sensitivity towards immune checkpoint therapy. Employing the Boruta algorithm, a subtype score was devised for 37 PANoptosis genes, successfully discerning the subtypes (AUC = 0.794), wherein patients with elevated scores demonstrated enhanced responsiveness to Rituximab treatment. Conclusion Our analysis revealed that SPP1 holds potential biomarker for the diagnosis of RA. Cluster 2 exhibited enhanced sensitivity to immune checkpoint therapy, higher PANoptosis scores, and improved responsiveness to drug treatment. This study offers potential implications in the realm of diagnosis and treatment.

ABSTRACTNatural pigments derived from microorganisms have many advantages and are widely studied in the food industry. A filamentous fungus, DBFL05, was identified as Aspergillus ustus, which produces a bright and abundant brown pigment. This extracellular, water-soluble pigment is highly polar and slightly soluble in alcohol but insoluble in other organic solvents. The pigment is stable under sunlight, at pH 2–10, and below 100°C. However, it is sensitive to Zn2+, Fe3+, Fe2+, and Cu2+. The pigment is mainly composed of two chemical components, pyrropyrazine diketone and dianthrone, and is classified as a polyketone pigment. Both components of the pigment exhibit inhibitory effects on bacteria and scavenging abilities for •OH and DPPH. The pigment showed no significant toxicity to plants and low toxicity to brine shrimp larvae. These findings indicate that the easily obtainable A. ustus pigment is a polyketone with attractive colour, stability, safety, and bioactivity.

This paper studies the effect of schistosity on the dynamic mechanical properties and failure pattern of thin-layered schist. Wudang Group schist with thin layers is selected as the research object, and the influence of the dynamic mechanical properties and failure pattern of schist under different angles and spacing is studied by combining an SHPB test and numerical simulation. The results indicate that under dynamic loading, the stress–strain curve demonstrates elastic compression, plastic deformation, and strain softening stages. Moreover, it is observed that the dynamic critical failure strength of schist exhibits typical “U”-type strength anisotropy. Specimens with a schistosity angle of 0° or 90° exhibit higher dynamic compressive strength under dynamic loading, with axial splitting and schistosity splitting as predominant failure modes. Conversely, when the schistosity angles are 30°, 45° or 60°, there is a noticeable decrease in compressive strength accompanied predominantly by shear failure along with local compressive shear failure. We additionally noted that as the spacing between schists decreases from 22 mm to 7 mm, there is a gradual reduction in dynamic compressive strength by approximately 20.3%.

Meteorological prediction is crucial for various sectors, including agriculture, navigation, daily life, disaster prevention, and scientific research. However, traditional numerical weather prediction (NWP) models are constrained by their high computational resource requirements, while the accuracy of deep learning models remains suboptimal. In response to these challenges, we propose a novel deep learning-based model, the Spatiotemporal Fusion Model (STFM), designed to enhance the accuracy of meteorological predictions. Our model leverages Fifth-Generation ECMWF Reanalysis (ERA5) data and introduces two key components: a spatiotemporal encoder module and a spatiotemporal fusion module. The spatiotemporal encoder integrates the strengths of convolutional neural networks (CNNs) and recurrent neural networks (RNNs), effectively capturing both spatial and temporal dependencies. Meanwhile, the spatiotemporal fusion module employs a dual attention mechanism, decomposing spatial attention into global static attention and channel dynamic attention. This approach ensures comprehensive extraction of spatial features from meteorological data. The combination of these modules significantly improves prediction performance. Experimental results demonstrate that STFM excels in extracting spatiotemporal features from reanalysis data, yielding predictions that closely align with observed values. In comparative studies, STFM outperformed other models, achieving a 7% improvement in ground and high-altitude temperature predictions, a 5% enhancement in the prediction of the u/v components of 10 m wind speed, and an increase in the accuracy of potential height and relative humidity predictions by 3% and 1%, respectively. This enhanced performance highlights STFM’s potential to advance the accuracy and reliability of meteorological forecasting.

The selection of the finest possible embryo in in-vitro fertilization (IVF) was crucial and revolutionary, particularly when just one embryo is transplanted to lessen the possibility of multiple pregnancies. However, practical usefulness of currently used methodologies may be constrained. Here, we established a novel non-invasive embryo evaluation method that combines non-invasive chromosomal screening (NICS) and Timelapse system along with artificial intelligence algorithms. With an area under the curve (AUC) of 0.94 and an accuracy of 0.88, the NICS-Timelapse model was able to predict blastocyst euploidy. The performance of the model was further evaluated using 75 patients in various clinical settings. The clinical pregnancy and live birth rates of embryos predicted by the NICS-Timelapse model, showing that embryos with higher euploid probabilities were associated with higher clinical pregnancy and live birth rates. These results demonstrated the NICS-Timelapse model's significantly wider application in clinical IVF due to its excellent accuracy and noninvasiveness.

In general, carriers are designed to deliver pharmaceutical (featuring small drug‐molecules) and biopharmaceutical (featuring large‐molecule drugs, e.g., antibodies, proteins, etc.) active ingredients and platform that is capable of transporting nanoparticles is rare. Herein, the fabrication of a supramolecular carrier with a nano‐grid structure for the entrapment of liposomes and exosomes is reported. The nano‐grid particles (NGP) are made of cyclodextrins as elementary units which are widely used to load drugs through host–guest inclusion complexes, whilst its secondary structure further formed the NGP tertiary architectures, enabling the entrapment of nanoparticles. The NGP features stimuli responsiveness, tunable surface charge, and good biocompatibility. The entrapped liposomes in NGP present enhanced distribution in lungs and extended duration of action in mice. And elongated release profiles for over 14 days is obtained for exosomes—making one‐of‐its‐kind unique platform to load and deliver nanoparticles.

IntroductionPear Valsa canker, caused by Valsa pyri (V. pyri), poses a major threat to pear production. We aimed to assess the effectiveness of the cell-free supernatant (CFS) produced by Trichoderma virens (T. virens) to control the development of pear Valsa canker and reveal the inhibitory mechanism against the pathogenic fungi.ResultsUsing morphological characteristics and phylogenetic analysis, the pathogen G1H was identified as V. pyri, and the biocontrol fungus WJ561 was identified as Trichoderma virens. CFS derived from WJ561 exhibited strong inhibition of mycelial growth and was capable of reducing the pathogenicity of V. pyri on pear leaves and twigs. Scanning electron microscopy (SEM) observations revealed deformations and shrinkages in the fungal hyphae treated with CFS. The CFS also destroyed the hyphal membranes leading to the leakage of cellular contents and an increase in the malondialdehyde (MDA) content. Additionally, CFS significantly inhibited the activities of catalase (CAT) and superoxide dismutase (SOD), and downregulated the expression of antioxidant defense-related genes in V. pyri, causing the accumulation of reactive oxygen species (ROS). Artesunate, identified as the main component in CFS by liquid chromatograph-mass spectrometry (LC–MS), exhibited antifungal activity against V. pyri.ConclusionOur findings demonstrate the promising potential of T. virens and its CFS in controlling pear Valsa canker. The primary inhibitory mechanism of CFS involves multiple processes, including membrane damage and negatively affecting enzymatic detoxification pathways, consequently leading to hyphal oxidative damage of V. pyri. This study lays a theoretical foundation for the utilization of T. virens to control V. pyri in practical production.

Abstract Introduction Elevated urinary albumin‐to‐creatinine ratio (UACR) was associated with increased mortality in general population and diabetic patients. However, whether the association remains similar in the subjects with different status of glucose metabolism was unclear. The optimal level of UACR in predicting mortality also remained unknown. This study aims to investigate the relationship between UACR with all‐cause and cardiovascular mortality in population with different status of glucose metabolism and explore the predictive cutoff point of UACR. Methods Six thousand three hundred and eighty‐six community‐dwelling individuals aged ≥45 years were enrolled and followed for an average of 5.3 years. Cox proportional hazards model was performed to analysis the association of baseline UACR and all‐cause as well as cardiovascular mortality according to the status of glucose metabolism. Receiver operating characteristic curve was plotted to explore the optimal predictive cutoff point of UACR. Results With UACR increasing, both the prevalence of all‐cause and cardiovascular death increased. Cox analyses showed baseline UACR independently predicted the risk of all‐cause and cardiovascular mortality in the patients with prediabetes mellitus (pre‐DM) and diabetes mellitus (DM) but not in subjects with normal glucose tolerance (NGT). When divided by quartiles of UACR, the cumulative survival rate decreased acrossing the quartiles. Compared to the subjects with lowest quartile of UACR, participants with UACR ≥7.40 mg/gCr had a higher risk of all‐cause mortality, and participants with UACR ≥16.60 mg/gCr had an increased risk of cardiovascular mortality in all hyperglycemia subjects. The optimal predictive cutoff point of UACR was about 17 mg/gCr. Conclusion UACR was an independent predictor of all‐cause and cardiovascular mortality in population with pre‐DM and DM but not in the subjects with NGT. The optimal predictive cutoff point of UACR is about 17 mg/gCr, which was far below the diagnostic cutoff point of microalbuminuria. Earlier interventions of albuminuria should be initiated from very early stage of hyperglycemia to reduce the burden of death in all patients whose glucose metabolism are impaired.

Abstract Background Postoperative pain is one of the most common complications after surgery. In order to detect early and intervene in time for moderate to severe postoperative pain, it is necessary to identify risk factors and construct clinical prediction models. This study aimed to identify significant risk factors and establish a better-performing model to predict moderate to severe acute postoperative pain after orthopedic surgery under general anesthesia. Methods Patients who underwent orthopedic surgery under general anesthesia were divided into patients with moderate to severe pain group (group P) and patients without moderate to severe pain group (group N) based on VAS scores. The features selected by Lasso regression were processed by the random forest and multivariate logistic regression models to predict pain outcomes. The classification performance of the two models was evaluated through the testing set. The area under the curves (AUC), the accuracy of the classifiers, and the classification error rate for both classifiers were calculated, the better-performing model was used to predict moderate to severe acute postoperative pain after orthopedic surgery under general anesthesia. Results A total of 327 patients were enrolled in this study (228 in the training set and 99 in the testing set). The incidence of moderate to severe postoperative pain was 41.3%. The random forest model revealed a classification error rate of 25.2% and an AUC of 0.810 in the testing set. The multivariate logistic regression model revealed a classification error rate of 31.3% and an AUC of 0.764 in the testing set. The random forest model was chosen for predicting clinical outcomes in this study. The risk factors with the greatest and second contribution were immobilization and duration of surgery, respectively. Conclusions The random forest model can be used to predict moderate to severe acute postoperative pain after orthopedic surgery under general anesthesia, which is of potential clinical application value.

Abstract In essence, the β2 adrenergic receptor (β2AR) plays an antiproliferative role by increasing the intracellular cyclic 3’,5’-adenosine monophosphate (cAMP) concentration through Gαs coupling, but interestingly, β2AR antagonists are able to effectively inhibit fibroblast-like synoviocytes (FLSs) proliferation, thus ameliorating experimental RA, indicating that the β2AR signalling pathway is impaired in RA FLSs via unknown mechanisms. The local epinephrine (Epi) level was found to be much higher in inflammatory joints than in normal joints, and high-level stimulation with Epi or isoproterenol (ISO) directly promoted FLSs proliferation and migration due to impaired β2AR signalling and cAMP production. By applying inhibitor of receptor internalization, and small interfering RNA (siRNA) of Gαs and Gαi, and by using fluorescence resonance energy transfer and coimmunoprecipitation assays, a switch in Gαs-Gαi coupling to β2AR was observed in inflammatory FLSs as well as in FLSs with chronic ISO stimulation. This Gαi coupling was then revealed to be initiated by G protein coupled receptor kinase 2 (GRK2) but not β-arrestin2 or protein kinase A-mediated phosphorylation of β2AR. Inhibiting the activity of GRK2 with the novel GRK2 inhibitor paeoniflorin-6′-O-benzene sulfonate (CP-25), a derivative of paeoniflorin, or the accepted GRK2 inhibitor paroxetine effectively reversed the switch in Gαs-Gαi coupling to β2AR during inflammation and restored the intracellular cAMP level in ISO-stimulated FLSs. As expected, CP-25 significantly inhibited the hyperplasia of FLSs in a collagen-induced arthritis (CIA) model (CIA FLSs) and normal FLSs stimulated with ISO and finally ameliorated CIA in rats. Together, our findings revealed the pathological changes in β2AR signalling in CIA FLSs, determined the underlying mechanisms and identified the pharmacological target of the GRK2 inhibitor CP-25 in treating CIA. Video Abstract

Abstract Background Serum remnant cholesterol levels are being increasingly acknowledged as a causal risk factor for atherosclerotic disease, regardless of conventional lipid parameters. The positive association between remnant cholesterol and nonalcoholic fatty liver disease (NAFLD) has been revealed in previous studies. However, whether remnant cholesterol is associated with the severity of NAFLD remains unknown. This study aimed to explore the association between serum remnant cholesterol and the risk of NAFLD severity. Methods This cross-sectional study included a total of 6,053 participants who attended health checkups. The severity of hepatic steatosis was evaluated by liver ultrasound transient elastography. Univariable and multivariable logistic regression analyses were performed to calculate the odds ratio (OR) and 95% confidence interval (95% CI) for the association between remnant cholesterol and the severity of hepatic steatosis. To explore whether the association between remnant cholesterol and NAFLD severity was independent of conventional lipid parameters, we further investigated this association in individuals with normal values of low-density lipoprotein-cholesterol (LDL-C), high-density lipoprotein-cholesterol (HDL-C) and triglycerides. Results In total, 36.9% of individuals had mild steatosis, and 5.9% had moderate-to-severe steatosis. The serum level of remnant cholesterol in nonsteatosis, mild steatosis and moderate-to-severe steatosis gradually increased (0.71 ± 0.33, 0.97 ± 0.52 and 1.07 ± 0.63 mmol/L, respectively). In the multivariable mode, remnant cholesterol was positively associated with mild hepatic steatosis (OR: 1.730, 95% CI: 1.541 − 1.941, P

Abstract Background Premature ovarian insufficiency (POI) is an important cause of infertility characterized by the functional decline of the ovary. Granulosa cells (GCs) around oocytes are critical for folliculogenesis, and GC dysfunction is one of the important etiologies of POI. The aim of this study was to explore the potential biomarkers of POI by identifying hub genes and analyze the correlation of biomarkers with immune infiltration in POI using RNA profiling and bioinformatics analysis. Methods RNA sequencing was performed on GCs from biochemical POI (bPOI) patients and controls. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were used to explore the candidate genes. qRT‒PCR was performed to verify the expression of hub genes. Western blot, Cell Counting Kit-8, 5‐ethynyl‐2’‐deoxyuridine (EdU) assays, TUNEL (TdT-mediated dUTP Nick-End Labeling) and flow cytometry analysis were used to validate the possible role of ubiquitin-conjugating enzyme 2C (UBE2C) in POI. CIBERSORT was adopted to explore immune cell infiltration and the correlation between UBE2C and immune cells in bPOI. Results Through analysis of differentially expressed genes (DEGs) and WGCNA, we obtained 143 candidate genes. After construction of the protein‒protein interaction (PPI) network and analysis with Cytoscape, 10 hub genes, including UBE2C, PBK, BUB1, CDC20, NUSAP1, CENPA, CCNB2, TOP2A, AURKB, and FOXM1, were identified and verified by qRT‒PCR. Subsequently, UBE2C was chosen as a possible biomarker of POI because knockdown of UBE2C could inhibit the proliferation and promote the apoptosis of GCs. Immune infiltration analysis indicated that monocytes and M1 macrophages may be associated with the pathogenesis of POI. In addition, UBE2C was negatively correlated with monocytes and M1 macrophages in POI. Conclusions This study identified a hub gene in GCs that might be important in the pathogenesis of POI and revealed the key role of UBE2C in driving POI. Immune infiltration may be highly related with the onset and etiology of POI.

Abstract Sound vibration is one of natural stimuli trigging physiological changes in plants. Recent studies showed that sound waves stimulated production of a variety of plant secondary metabolites, including flavonoids, in order to enhance seed germination, flowering, growth or defense. In this review, we examine the potential role of sound stimulation on the biosynthesis of secondary metabolites and the followed cascade of physiological changes in plants, from the perspective of transcriptional regulation and epigenetic regulation for the first time. A systematic summary showed that a wide range of factors may regulate the production of secondary metabolites, including plant species, growth stage, sound types, sound frequency, sound intensity level and exposure time, etc. Biochemical and physiological changes due to sound stimulation were thoroughly summarized as well, for secondary metabolites can also act as a free radical scavenger, or a hormone signaling molecule. We also discussed the limits of previous studies, and the future application of sound waves in biosynthesis of plant secondary metabolites.

Abstract We aimed to design a novel three-dimensional (3D) printed surgical guide and evaluate its accuracy in assisting endodontic microsurgeries. A new 3D printed surgical guide was designed by computer-aided design and computer-aided manufacturing (CAD/CAM) technology and applied to 7 patients who underwent endodontic microsurgeries of upper anterior teeth from 2020.01 to 2020.12 as the experimental group. 7 patients who suffered from endodontic microsurgeries operated by the same surgeon without using the surgical guide from 2019.01 to 2019.12 were selected as the control group. Cone beam computed tomography (CBCT) was performed more than 12 months after operation, and the accuracy of apical resection was compared between the two groups. The accuracy of the microsurgery focused on the length and angle of the root apical resection. In the study, CBCT data and oral digital scanning data were used to reconstruct 3D models of periapical lesions with soft and hard tissue information, based on which we designed the new 3D printed surgical guides. The guides were successfully applied to the apectomy in endodontic microsurgeries. The deviation of the apical resection length of the experimental group (0.467 ± 0.146 mm) was better than that of the control group (1.743 ± 0.122 mm) (P

Ag–Cu alloys, as one type of typical eutectic solders, have been widely used in microelectronic packaging. The welding performance of Ag–Cu solders is closely associated with their microstructures. However, the microstructure evolution of Ag–Cu alloys during solidification is still poorly understood. In this work, a new melt fluxing technique was proposed to investigate the microstructure evolution of undercooled Ag-50at.%Cu hypereutectic alloy. The maximum undercooling of Ag-50at.%Cu alloy can reach up to 135 K. The obtained results show that the microstructures consist of primary dendrite and lamellar eutectic at low undercooling (ΔT – 10 K). With the increase of undercooling, dendrites undergo refining (ΔT 135 K. Theoretical calculation results indicate that the formation of irregular eutectic is associated with the dendritic fragmentation and eutectic coarsening under larger undercooling (ΔT = 135 K). These results not only elucidate the relationship between the solidification microstructure and undercooling of Ag-50at. %Cu hypereutectic alloys but also has positive significance for other hyper-eutectic systems.

Deep undercooling rapid solidification experiments of Cu–Ni–Co alloys were carried out using the molten glass purification cycle superheat method. 130 K, 177 K and 277 K undercooling degrees were obtained and analysed for Cu55Ni43Co2 alloy. The crystallographic information obtained by EBSD and the dynamics of the solidification front taken by high speed photography were analysed and it was concluded that both the formation of relatively rounded equiaxed grains during the first refinement and the subsequent formation of finer subcrystals were due to the release of a large amount of solidification energy during the solidification process. The re-glow stage releases a large amount of latent heat of solidification resulting in the remelting of the dendrites. TEM tests were carried out on Cu55Ni43Co2 alloy with a maximum undercooling of 277 K. It was found that part of the substructure showed a high density dislocation network. By analysing the effect of increasing undercooling on the microstructure evolution, combined with the EBSD and TEM characterisation data, it was found that the stress-induced recrystallization mechanism was the dominant factor in the grain refinement mechanism at large undercooling.

The role of Auricularia auricula polysaccharide (AP) in the regulation of glycolipid metabolism was investigated using a high-fat-diet-induced hyperlipidemic mouse model. In a further step, its potential mechanism of action was investigated using microbiome analysis and widely targeted lipidomics. Compared to high-fat mice, dietary AP supplementation reduced body weight by 13.44%, liver index by 21.30%, epididymal fat index by 50.68%, fasting blood glucose (FBG) by 14.27%, serum total cholesterol (TC) by 20.30%, serum total triglycerides (TGs) by 23.81%, liver non-esterified fatty acid (NEFA) by 20.83%, liver TGs by 20.00%, and liver malondialdehyde (MDA) by 21.05%, and increased liver glutathione oxidase (GSH-PX) activity by 52.24%, total fecal bile acid (TBA) by 46.21%, and fecal TG by 27.16%, which significantly regulated glucose and lipid metabolism. Microbiome analysis showed that AP significantly downregulated the abundance of the Desulfobacterota phylum, as well as the genii Desulfovibrio, Bilophila, and Oscillbacter in the cecum of hyperlipidemic mice, which are positively correlated with high lipid indexes, while it upregulated the abundance of the families Eubacterium_coprostanoligenes_group and Ruminococcaceae, as well as the genii Eubacterum_xylanophilum_group, Lachnospiraceae_NK4A136_group, Eubacterium_siraeum_group, and Parasutterella, which were negatively correlated with high lipid indexes. In addition, AP promoted the formation of SCFAs by 119.38%. Widely targeted lipidomics analysis showed that AP intervention regulated 44 biomarkers in metabolic pathways such as sphingolipid metabolism and the AGE-RAGE signaling pathway in the hyperlipidemic mice (of which 15 metabolites such as unsaturated fatty acids, phosphatidylserine, and phosphatidylethanolamine were upregulated, and 29 metabolites such as phosphatidylcholine, ceramide, carnitine, and phosphatidylinositol were downregulated), thereby correcting glucose and lipid metabolism disorders.