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Abstract A single-blind, randomized controlled trial comparing oxycodone and fentanyl for patient-controlled intravenous analgesia (PCIA) after laparoscopic hysteromyomectomy found comparable pain relief between the two groups. The study included 60 participants, with NRS scores for pain at rest and when moving showing no significant differences between oxycodone and fentanyl groups at various time points postoperatively. Self-rating depression scale scores were also similar between the groups at 48 h. However, patients’ satisfaction with PCIA was higher in the oxycodone group, with 73.3% reporting being very satisfied compared to 36.7% in the fentanyl group. Additionally, the oxycodone group had fewer incidences of headaches within 48 h postoperatively compared to the fentanyl group. These findings suggest that oxycodone may offer comparable pain relief, higher patient satisfaction, and fewer headaches for patients undergoing laparoscopic hysteromyomectomy compared to fentanyl, making it a suitable option for postoperative pain management in this population. Clinical trial registration number The study was registered with CHICTR.org, ChiCTR2100051924.

Dissimilar materials of TC4 titanium alloy and 316L stainless steel were joined by means of resistance spot welding with nickel interlayer in different thicknesses. A significant enhancement in terms of nugget morphology quality with less defects was achieved for the welded joints with nickel interlayer compared with that without interlayer. With increasing the nickel interlayer thickness from 50 μm to 300 μm, the effective nugget diameter increased gradually from ∼4.8 mm to ∼5.2 mm, which was lower than that of the interlayer-free welded joint being ∼5.9 mm. A thinner intermetallic compound layer with dual-layered structure features with thickness of ∼11 μm was formed at the nugget/titanium interface in the welded joint with nickel interlayer compared with that of the interlayer-free welded joint, meanwhile an intermetallic compound layer with thickness of ∼3 μm was formed at the nugget/stainless steel interface, which exhibited serrated structure features. The introduction of nickel interlayer in the welded joint could suppress the formation of the brittle Ti–Fe intermetallics such as Fe2Ti, and facilitate the formation of TiNi, Ti2Ni and TiNi3. A more homogeneous current density distribution and a lower peak temperature (1809 °C) during welding were achieved via employing nickel interlayer. With increasing nickel interlayer thickness from 0 μm to 300 μm, the tensile shear load of welded joints experienced an increased tendency first and then decreased, meanwhile the maximum tensile shear load of 3.7 kN was obtained with the interlayer thickness of 200 μm, which was 61% higher than that of the interlayer-free welded joint.

The dissimilar welding between aluminum alloys and ultra-high strength steels (UHSS) can realize the structural lightweighting in the manufacturing of vehicle bodies. However, brittle Al–Fe intermetallic compounds (IMCs) are easily formed during welding, limit the industrial application of Al/steel hybrid structure. In this paper, solid rivet resistance riveting welding (RRW) is adopted to join AA6061-T6 aluminum alloy to CR1180T UHSS. This method employs a solid steel rivet to pierce the aluminum alloy workpiece under a piercing current, then a welding current is conducted to weld the rivet to the steel sheet. The influence of rivet leg height, rivet diameter, taper of rivet leg and volume ratio of rivet cap to rivet leg on the joint performance of RRW Al/steel are investigated. The results show that a rivet with small dimension will make it difficult to form effective piercing and welding, and a rivet with too large dimension will increase the difficulty of piercing and welding. With suitable design of rivet dimensions and selection of piercing and welding parameters, the maximum average tensile-shear force of RRW joint reaches 10.8 kN.

Abstract Deterministic encryption (DET) allows for fast retrieval of encrypted information, but it would cause significant leakage of frequency information of the underlying data, which results in an array of inference attacks. Simply replacing DET with fully randomized encryption is often undesirable in the scenario of an encrypted database since it incurs a large overhead in query and storage. Frequency Smoothing Encryption (FSE) is a practical encryption scheme to protect frequency information. Current FSE constructions still fall short of efficiency and a reasonable security definition. We revisit FSE and propose two security definitions from both theoretical and practical perspectives. Furthermore, we adopt a novel partitioning strategy to construct a new FSE scheme to improve performance. Experimental results show that compared with others, our scheme achieves excellent query performance while attaining security against inference attacks.

Abstract Bio-inspired micro-air-vehicles (MAVs) usually operate in the atmospheric boundary layer at a low Reynolds number and complex wind conditions including large-scale turbulence, strong shear, and gusts. We develop an open jet facility (OJF) to meet the requirements of MAV flight experiments at very low speed and high turbulence intensity. Powered by a stage-driven fan, the OJF is capable of generating wind speeds covering 0.1 – 16.8 m/s, with a velocity ratio of 100:1. The contraction section of the OJF is designed using an adjoint-driven optimization method, resulting in a contraction ratio of 3:1 and a length-to-diameter ratio of 0.75. A modularized design of the jet nozzle can produce laminar or high-turbulence wind conditions. Flow field calibration results demonstrate that the OJF is capable of producing a high-quality baseline flow with steady airspeed as low as 0.1 m/s, uniform region around 80% of the cross-sectional test area, and turbulence intensity around 0.5%. Equipped with an optimized active grid (AG), the OJF can reproduce controllable, fully-developed turbulent wind conditions with the turbulence intensity up to 24%, energy spectrum satisfying the five-thirds power law, and the uniform region close to 70% of the cross-sectional area of the test section. The turbulence intensity, integral length scale, Kolmogorov length scale, and mean energy dissipation rate of the generated flow can be adjusted by varying the area of the triangular through-hole in the wings of the AG.

Abstract Background The limited regenerative capacity of damaged neurons in adult mammals severely restricts neural repair. Although stem cell transplantation is promising, its clinical application remains challenging. Direct reprogramming, which utilizes cell plasticity to regenerate neurons, is an emerging alternative approach. Methods We utilized primary postnatal cortical astrocytes for reprogramming induced neurons (iNs) through the viral-mediated overexpression of the transcription factors Ngn2 and Pax6 (NP). Fluorescence-activated cell sorting (FACS) was used to enrich successfully transfected cells, followed by single-cell RNA sequencing (scRNA-seq) using the 10 × Genomics platform for comprehensive transcriptomic analysis. Results The scRNA-seq revealed that NP overexpression led to the differentiation of astrocytes into iNs, with percentages of 36% and 39.3% on days 4 and 7 posttransduction, respectively. CytoTRACE predicted the developmental sequence, identifying astrocytes as the reprogramming starting point. Trajectory analysis depicted the dynamic changes in gene expression during the astrocyte-to-iN transition. Conclusions This study elucidates the molecular dynamics underlying astrocyte reprogramming into iNs, revealing key genes and pathways involved in this process. Our research contributes novel insights into the molecular mechanisms of NP-mediated reprogramming, suggesting avenues for optimizing the efficiency of the reprogramming process.

Abstract The retina, an anatomical extension of the brain, forms physiological connections with the visual cortex of the brain. Although retinal structures offer a unique opportunity to assess brain disorders, their relationship to brain structure and function is not well understood. In this study, we conducted a systematic cross-organ genetic architecture analysis of eye-brain connections using retinal and brain imaging endophenotypes. We identified novel phenotypic and genetic links between retinal imaging biomarkers and brain structure and function measures from multimodal magnetic resonance imaging (MRI), with many associations involving the primary visual cortex and visual pathways. Retinal imaging biomarkers shared genetic influences with brain diseases and complex traits in 65 genomic regions, with 18 showing genetic overlap with brain MRI traits. Mendelian randomization suggests bidirectional genetic causal links between retinal structures and neurological and neuropsychiatric disorders, such as Alzheimer’s disease. Overall, our findings reveal the genetic basis for eye-brain connections, suggesting that retinal images can help uncover genetic risk factors for brain disorders and disease-related changes in intracranial structure and function.

Abstract Extremely large magnetoresistance (XMR) is highly applicable in spintronic devices such as magnetic sensors, magnetic memory, and hard drives. Typically, XMR is found in Weyl semimetals characterized by perfect electron–hole symmetry or exceptionally high electric conductivity and mobility. Our study explores this phenomenon in a recently developed graphene moiré system, which demonstrates XMR owing to its topological structure and high-quality crystal formation. We investigate the electronic properties of three-dimensional intertwined twisted graphene spirals (TGS), manipulating the screw dislocation axis to achieve a rotation angle of 7.3°. Notably, at 14 T and 2 K, the magnetoresistance of these structures reaches 1.7 × 107%, accompanied by a metal–insulator transition as the temperature increases. This transition becomes noticeable when the magnetic field exceeds a minimal threshold of approximately 0.1 T. These observations suggest the possible existence of complex, correlated states within the partially filled three-dimensional Landau levels of the 3D TGS system. Our findings open up possibilities for achieving XMR by engineering the topological structure of 2D layered moiré systems.

Abstract Dysfunction of the ubiquitin-proteasome system (UPS) is involved in the pathogenesis of various malignancies including colorectal cancer (CRC). Ubiquitin domain containing 1 (UBTD1), a ubiquitin-like protein, regulates UPS-mediated protein degradation and tumor progression in some cancer types. However, the biological function and mechanism of UBTD1 are far from being well elucidated, and its role in CRC has not been explored yet. In our study, we analyzed CRC patients’ clinical information and UBTD1 expression data, and found that the expression of UBTD1 in cancer tissue was significantly higher than that in adjacent normal tissue. Higher UBTD1 expression was significantly associated with poorer survival and more lymph node metastasis. Overexpression of UBTD1 could facilitate, while knockdown could inhibit CRC cell proliferation and migration, respectively. RNA-seq and proteomics indicated that c-Myc is an important downstream target of UBTD1. Metabolomics showed the products of the glycolysis pathway were significantly increased in UBTD1 overexpression cells. In vitro, we verified UBTD1 upregulating c-Myc protein and promoting CRC cell proliferation and migration via regulating c-Myc. UBTD1 promoted CRC cells’ glycolysis, evidenced by the increased lactate production and glucose uptake following UBTD1 overexpression. Mechanistically, UBTD1 prolonged the half-life of the c-Myc protein by binding to E3 ligase β-transducin repeat-containing protein (β-TrCP), thereby upregulated the expression of glycolysis rate-limiting enzyme hexokinase II (HK2), and enhanced glycolysis and promoted CRC progression. In conclusion, our study revealed that UBTD1 promotes CRC progression by upregulating glycolysis via the β-TrCP/c-Myc/HK2 pathway, suggesting its potential as a prognostic biomarker and therapeutic target in CRC.

Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) are closely related to the treatment of human diseases. Traditional biological experiments often require time-consuming and labor-intensive in their search for mechanisms of disease. Computational methods are regarded as an effective way to predict unknown lncRNA-miRNA interactions (LMIs). However, most of them complete their tasks by mainly focusing on a single lncRNA-miRNA network without considering the complex mechanism between biomolecular in life activities, which are believed to be useful for improving the accuracy of LMI prediction. To address this, a heterogeneous information network (HIN) learning model with neighborhood-level structural representation, called HINLMI, to precisely identify LMIs. In particular, HINLMI first constructs a HIN by integrating nine interactions of five biomolecules. After that, different representation learning strategies are applied to learn the biological and network representations of lncRNAs and miRNAs in the HIN from different perspectives. Finally, HINLMI incorporates the XGBoost classifier to predict unknown LMIs using final embeddings of lncRNAs and miRNAs. Experimental results show that HINLMI yields a best performance on the real dataset when compared with state-of-the-art computational models. Moreover, several analysis experiments indicate that the simultaneous consideration of biological knowledge and network topology of lncRNAs and miRNAs allows HINLMI to accurately predict LMIs from a more comprehensive perspective. The promising performance of HINLMI also reveals that the utilization of rich heterogeneous information can provide an alternative insight for HINLMI to identify novel interactions between lncRNAs and miRNAs.

Nonlinear photonics has unveiled new avenues for applications in metrology, spectroscopy, and optical communications. Recently, there has been a surge of interest in integrated platforms, attributed to their fundamental benefits, including compatibility with complementary metal-oxide semiconductor (CMOS) processes, reduced power consumption, compactness, and cost-effectiveness. This paper provides a comprehensive review of the key nonlinear effects and material properties utilized in integrated platforms. It discusses the applications and significant achievements in supercontinuum generation, a key nonlinear phenomenon. Additionally, the evolution of chip-based optical frequency combs is reviewed, highlighting recent pivotal works across four main categories. The paper also examines the recent advances in on-chip switching, computing, signal processing, microwave generation, and quantum applications. Finally, it provides perspectives on the development and challenges of nonlinear photonics in integrated platforms, offering insights into future directions for this rapidly evolving field.

Abstract Background Breast cancer patients undergoing chemotherapy via peripherally inserted central catheter often experience serious behavioral and psychological challenges, with uncertainty and cancer-related fatigue being prevalent issues that profoundly impact prognosis. Therefore, this study aimed to investigate the relationship between uncertainty and cancer-related fatigue by employing a chain mediation model to examine the potential mediating roles of psychological resilience and self-care. Methods A cross-sectional study was conducted with 223 breast cancer patients receiving peripherally inserted central catheter chemotherapy at two tertiary affiliated hospitals of China Medical University in Liaoning, China, from February 2021 to December 2022. Participants completed self-reported questionnaires to assess uncertainty, psychological resilience, self-care, and cancer-related fatigue. The collected data were subsequently analyzed using Pearson’s correlation analysis, hierarchical regression analysis, and mediation analysis. Results Uncertainty exhibited a significant positive correlation with cancer-related fatigue (p

Abstract The discovery of novel two-dimensional (2D) multiferroic materials is attractive due to their potential for the realization of information storage and logic devices. Although many approaches have been explored to simultaneously introduce ferromagnetic (FM) and ferroelectric (FE) orders into a 2D material, the resulting systems are often plagued by weak magnetoelectric (ME) coupling or limited room-temperature stability. Here, we present a superlattice strategy to construct non-centrosymmetric AM2X4 multiferroic monolayers, i.e., intercalating transition metal ions (A) into the tetragonal-like vacancies of transition metal dichalcogenide bilayers (MX2). Starting from 960 intercalated AM2X4 compounds, our high-throughput calculations have identified 21 multiferroics with robust magnetic order, large FE polarization, low transition barrier, high FE/FM transition temperature, and strong ME coupling. According to the origin of magnetism, we have classified them into twelve type-a, seven type-b, and two type-c multiferroics, which exhibit different ME coupling behavior. During the switching of polarization, the reversal of skyrmions chirality, the transition of the magnetic ground state from FM to antiferromagnetic, and the changes in spin-polarized electron distribution were observed in type-a, type-b, and type-c 2D multiferroic materials, respectively. These results substantially expand the family of 2D ferroic materials and pave an avenue for designing and implementing nonvolatile logic and memory devices.

Abstract Neural circuits with specific structures and diverse neuronal firing features are the foundation for supporting intelligent tasks in biology and are regarded as the driver for catalyzing next-generation artificial intelligence. Emulating neural circuits in hardware underpins engineering highly efficient neuromorphic chips, however, implementing a firing features-driven functional neural circuit is still an open question. In this work, inspired by avoidance neural circuits of crickets, we construct a spiking feature-driven sensorimotor control neural circuit consisting of three memristive Hodgkin-Huxley neurons. The ascending neurons exhibit mixed tonic spiking and bursting features, which are used for encoding sensing input. Additionally, we innovatively introduce a selective communication scheme in biology to decode mixed firing features using two descending neurons. We proceed to integrate such a neural circuit with a robot for avoidance control and achieve lower latency than conventional platforms. These results provide a foundation for implementing real brain-like systems driven by firing features with memristive neurons and put constructing high-order intelligent machines on the agenda.

Abstract Background Phytophthora sojae, a soil-borne oomycete pathogen, has been a yield limiting factor for more than 60 years on soybean. The resurgence of P. sojae (Phytophthora sojae) is primarily ascribed to the durable oospores found in soil and remnants of the disease. P. sojae is capable of infesting at any growth periods of the soybean, and the succeed infestation of P. sojae is predominantly attributed to long-lived oospores present in soil. Comprehending the molecular mechanisms that drive oospores formation and their significance in infestation is the key for effective management of the disease. However, the existing challenges in isolating and extracting significant quantities of oospores pose limitations in investigating the sexual reproductive stages of P. sojae. Results The study focused on optimizing and refining the culture conditions and extraction process of P. sojae, resulting in establishment of an efficient and the dependable method for extraction. Novel optimized approach was yielded greater quantities of high-purity P. sojae oospores than traditional methods. The novel approach exceeds the traditional approaches with respect to viability, survival ability, germination rates of new oospores and the pathogenicity of oospores in potting experiments. Conclusion The proposed method for extracting P. sojae oospores efficiently yielded a substantial quantity of highly pure, viable, and pathogenic oospores. The enhancements in oospores extraction techniques will promote the research on the sexual reproductive mechanisms of P. sojae and lead to the creation of innovative and effective approaches for managing oomycete diseases.

Abstract Background Mounting evidences shows that the ubiquitin‒proteasome pathway plays a pivotal role in tumor progression. The expression of 26S proteasome non-ATPase regulatory subunit 9 (PSMD9) is correlated with recurrence and radiotherapy resistance in several tumor types. However, the role and mechanism of PSMD9 in hepatocellular carcinoma (HCC) progression remain largely unclear. Methods PSMD9 was identified as a prognosis-related biomarker for HCC based on analysis of clinical characteristics and RNA-seq data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and the JP Project of the International Cancer Genome Consortium (ICGC-LIRI-JP). PSMD9 expression was analyzed in cancer tissues and adjacent noncancerous tissues via immunohistochemistry and Western blotting. Multiple in vivo and in vitro experimental techniques (such as CCK-8, colony formation, EdU, and Transwell assays; flow cytometry; Western blotting; quantitative RT-PCR; Coimmunoprecipitation assay and immunofluorescence confocal imaging) were used to assess the functions of PSMD9 in the pathogenesis of HCC. Results We found that the expression of PSMD9 was upregulated and associated with a poor prognosis in HCC patients. PSMD9 promoted HCC cell proliferation, migration, invasion and metastasis. Knockdown of PSMD9 significantly inhibited HCC cell proliferation by inducing G1/S cell cycle arrest and apoptosis. Mechanistically, we demonstrated that PSMD9 promoted HCC cell proliferation and metastasis via direct interaction with the E3 ubiquitin ligase c-Cbl, suppresses EGFR ubiquitination, influenced EGFR endosomal trafficking and degradation and subsequently activated ERK1/2 and Akt signaling. In addition, we showed that PSMD9 knockdown sensitized HCC cells to the tyrosine kinase inhibitor erlotinib in vitro and in vivo. Conclusions Collectively, our results indicate that PSMD9 drives HCC progression and erlotinib resistance by suppressing c-Cbl mediated EGFR ubiquitination and therefore can be a potential therapeutic target for HCC.

Abstract Notable-HCC (NCT05185531) is a phase 1b trial, aiming to evaluate the safety and preliminary effectiveness of neoadjuvant PD-1 blockade plus stereotactic body radiotherapy (SBRT) in early-stage resectable hepatocellular carcinoma (HCC). Twenty patients with HCC of BCLC stage 0-A received 3 $$\times $$ × Gy SBRT and two cycles of tislelizumab, an anti-PD-1 monoclonal antibody before the curative HCC resection. Primary endpoints were the surgery delay, radiographic and pathological tumor response after the neoadjuvant therapy, safety and tolerability. During the neoadjuvant therapy, treatment-related adverse events (TRAEs) of grade 1-2 occurred in all 20 patients (100%), eight patients (40%) had grade 3 TRAEs, no grade 4 to 5 TRAE occurred, and all resolved without corticosteroids treatment. Per mRECIST, the objective response rate was 63.2% (12/19), with 3 complete response; the disease control rate was 100%. Two (10.5%) patients achieved complete pathological response. No surgery delay occurred. The neoadjuvant therapy did not increase the surgical difficulty or the incidence of complications. Secondary endpoints of disease-free survival and overall survival were not mature at the time of the analysis. Our pilot trial shows that neoadjuvant therapy with anti-PD-1 + SBRT is safe and promotes tumor responses in early-stage resectable HCC.

Abstract Firstly, the Canny operator combined with circle fitting is used to position the working surface. Secondly, the median filter and the Laplacian operator are selected for preprocessing. Due to uneven illumination, surface texture, or environmental dust, the extracted scratches exhibit fragmentation, and traditional morphological operations cannot handle scratches well, so an improved Canny operator combined with probabilistic Hough transform is proposed for scratch connection. A bidirectional connection is introduced to optimize the edge detection process of the Canny operator, and a parallel algorithm is introduced to shorten the detection time. Finally, the standard Hough transform needs to traverse the entire parameter space, and the calculation is complicated, and the probability Hough transform is selected. The experimental results show that compared with the traditional Canny algorithm, the precision, recall, and F1‐score of the improved Canny algorithm are increased by 3.2%, 13.2%, and 6.0%, respectively. After adding parallel processing, the average detection time was reduced by 45 ms. Finally, the accuracy of scratches extracted using this algorithm reached 97.96%, the leak rate, and mistake rate of this study are only 3.33% and 2.00%, which provides a more accurate and efficient theoretical support for the research on brake disc scratch detection.

Objective: Ischemic stroke (IS) is a significant health concern with high disability and fatality rates despite available treatments. Immune cells and cuproptosis are associated with the onset and progression of IS. Investigating the interaction between cuproptosis-related genes (CURGs) and immune cells in IS can provide a theoretical basis for IS treatment. Methods: We obtained IS datasets from the Gene Expression Omnibus (GEO) and employed machine learning to identify CURGs. The diagnostic efficiency of the CURGs was evaluated using receiver operating characteristic (ROC) curves. KEGG and gene set enrichment analysis (GSEA) were also conducted to identify biologically relevant pathways associated with CURGs in IS patients. Single-cell analysis was used to confirm the expression of 19 CURGs, and pathway activity calculations were performed using the AUCell package. Additionally, a risk prediction model for IS patients was developed, and core modules and hub genes related to IS were identified using weighted gene coexpression network analysis (WGCNA). We classified IS patients using a method of consensus clustering. Results: We established a precise diagnostic model for IS. Enrichment analysis revealed major pathways, including oxidative phosphorylation, the NF-kappa B signaling pathway, the apoptosis pathway, and the Wnt signaling pathway. At the single-cell level, compared to those in non-IS samples, 19 CURGs were primarily overexpressed in the immune cells of IS samples and exhibited high activity in natural killer cell-mediated cytotoxicity, steroid hormone biosynthesis, and oxidative phosphorylation. Two clusters were obtained through consensus clustering. Notably, immune cell types including B cells, plasma cells, and resting NK cells, varied between the two clusters. Furthermore, the red module and hub genes associated with IS were uncovered. The expression patterns of CURGs varied over time. Conclusion: This study developed a precise diagnostic model for IS by identifying CURGs and evaluating their interaction with immune cells. Enrichment analyses revealed key pathways involved in IS, and single-cell analysis confirmed CURG overexpression in immune cells. A risk prediction model and core modules associated with IS were also identified.

Identifying the stability and sensitivity of land ecosystems to climate change is vital for exploring nature-based solutions. However, the underlying mechanisms governing ecosystem stability and sensitivity, especially in regions with overlapping ecological projects, remain unclear. based on Mann-Kendall, stability analysis method, and multiple regression method, this study quantified the stability and sensitivity of gross primary productivity (GPP) to climate variables [temperature, vapor pressure deficit (VPD), soil moisture, and radiation] in China from 1982 to 2019. Our findings revealed the following: (1) GPP demonstrated an increased trend with lower stability in Eastern regions, whereas a decreasing trend with higher stability was observed in Western and Southwest China. Notably, the stability of GPP was highest (74.58%) in areas with five overlapping ecological projects: Grain to Green, Natural Forest Resource Protection Project, Three-River Ecological Conservation and Restoration Project, Return Grazing to Grassland Project, and Three-North Shelter Forestation Project. (2) In regions with minimal or no overlapping ecological projects, temperature and radiation jointly dominated GPP variations. In contrast, water-related factors (VPD and soil moisture) significantly affected GPP in areas with multiple overlapping ecological projects. (3) In the southwestern and northeastern regions, GPP exhibited the highest sensitivity to climate change, whereas, in the eastern coastal areas and Tibet, GPP showed low sensitivity to climate change. In the Loess Plateau, where five ecological projects overlap extensively, carbon sinks primarily demonstrate a monotonic increasing trend, high stability, and low sensitivity to climate change. This study aimed to assess the stability of the land ecosystems and delineate their sensitivity to climate changes, thereby laying the groundwork for understanding ecosystem resilience.

BackgroundThe systemic immune-inflammation index (SII) is a novel inflammatory marker used to assess the immune-inflammatory status of the human body. The systemic immune inflammation has an interplay and mutual relationship with neurological disorders. Serum neurofilament light chain (sNfL) is widely regarded as a potential biomarker for various neurological diseases. The study aimed to examine the association between SII and sNfL.MethodsThis cross-sectional investigation was conducted in a population with complete data on SII and sNfL from the 2013–2014 National Health and Nutrition Examination Survey (NHANES). The SII was calculated by dividing the product of platelet count and neutrophil count by the lymphocyte count. Multivariate linear regression models and smooth curves were used to explore the linear connection between SII and sNfL. Sensitivity analyses, interaction tests, and diabetes subgroup smoothing curve fitting were also performed.ResultsA total of 2,025 participants were included in our present research. SII showed a significant positive association with the natural logarithm-transformed sNfL (ln-sNfL) in crude model [0.17 (0.07, 0.28)], partially adjusted model [0.13 (0.03, 0.22)], and fully adjusted model [0.12 (0.02, 0.22)]. In all participants, the positive association between SII and ln-sNfL served as a linear relationship, as indicated by a smooth curve. Interaction tests showed that age, gender, BMI, hypertension, and diabetes did not have a significant impact on this positive association (p for interaction >0.05). The subgroup analysis of diabetes was conducted using smooth curve fitting. It was found that compared to the group without diabetes and the group in a pre-diabetic state, the effect was more pronounced in the group with diabetes.ConclusionOur findings suggest that there is a positive association between SII and sNfL. Furthermore, in comparison to individuals without diabetes and those in a pre-diabetic state, the positive association between SII and sNfL was more pronounced in individuals with diabetes. Further large-scale prospective studies are needed to confirm the association between SII and sNfL.

BackgroundCancer immunotherapy has made significant progress in recent years, with numerous studies worldwide. Immunotherapy has had a transformative impact on oncology and autoimmune diseases. In the biomedical arena, hydrogels with good properties are widely used in cancer immunotherapy. Our study used bibliometrics to analyze the changing trends in using hydrogels for cancer immunotherapy.MethodsFrom 2013 to 2023, a systematic search was conducted in the Web of Science Core Collection database to identify reviews and articles discussing the applications of hydrogels in cancer immunotherapy. The software CiteSpace was used to visually perform the bibliometric analysis in terms of research trends, countries, institutions, authors, journals, and keywords. Individual authors’ productivity was assessed with the Lotka’s law. The most relevant publication sources were identified by Bradford’s law.ResultsA total of 422 English-language publications related to hydrogels in cancer immunotherapy were collected. The number of annual publications increased rapidly after 2021 and remained constant for the past two years. China published the most articles in this field. The institution with the maximum number of published articles was the Chinese Academy of Sciences in China. Chen. Q was the most prolific author, and Liu. Z was the second most published author. In terms of journal contributions, the journal “Biomaterials” had the highest number of publications (n = 30). Biomaterials, Advanced Functional Materials and Journal of Controlled Release were the most influential journals. Keyword analysis revealed that cancer immunotherapy, drug delivery, immunogenic cell death, tumor microenvironment, injectable hydrogels, and immune checkpoint blockade were the primary research hotspots. In recent 3 years, adoptive T-cell therapy, black phosphorus, cell capture, adaptive cell therapy, tumor microenvironment, photodynamic therapy, and sustained release were the research hotspots in this field. Our study summarizes the objective of hydrogels in cancer immunotherapy in recent years, providing a reference for potential researchers in related field.ConclusionThis bibliometric analysis shows the progress and trend of research on hydrogels in cancer immunotherapy. This study provides a significant avenue for future investigation into current concerns and trends in research within this field.

BackgroundHyperthyroidism is an endocrine disorder with a relatively low global prevalence but significantly higher incidence among females compared to males. The onset age primarily ranges from 30 to 50, although it is not limited to this age group. Challenges in the treatment of hyperthyroidism include individualized treatment plan formulation, management of side effects, and prediction of disease progression, necessitating comprehensive consideration to achieve more effective therapy and management. Mendelian randomization studies can reveal more precise therapeutic targets between blood and urine biomarkers and hyperthyroidism, providing more decadent treatment options for the condition.MethodsThe study will build upon the omics Mendelian randomization (MR) framework by conducting MR analysis using 35 blood and urine biomarkers separately for two distinct databases of hyperthyroidism. Subsequently, the results will undergo meta-analysis and multiple corrections to ensure accuracy and reliability. Finally, positive findings will undergo reverse MR validation to verify causal relationships with hyperthyroidism.ResultsIn the British database, the MR analysis of Total bilirubin levels about hyperthyroidism yielded an odds ratio (OR) of 1.097 (95% CI: 0.951-1.265, P = 0.205). Conversely, in the Thyroid Omics Association database, the MR analysis revealed an OR of 1.283 (95% CI: 1.122-1.467, P = 0.0002) for the same relationship. Meta-analysis of the MR analysis results from both databases, following multiple corrections, resulted in an OR of 1.192 (95% CI: 1.081-1.314, P = 0.015). Additionally, the direction of beta values in the MR analysis results from both databases was consistent.ConclusionThe urine biomarker total bilirubin levels may contribute to an increased risk of hyperthyroidism and accelerate its progression, thus representing a risk factor for the condition.

BackgroundSex is a crucial factor in the development, progression, and treatment of cancer, making it vital to examine cancer incidence trends by sex for effective prevention strategies. ObjectiveThis study aimed to assess the incidence of cancer in China between 2007 and 2021, with a focus on sex-based trends. MethodsA population-based cancer registry comprising 14.14 million individuals was maintained between 2007 and 2021 by the Beijing Municipal Health Big Data and Policy Research Center. The age-standardized rates (ASRs) of cancers were calculated using the Segi population. The average annual percentage of change (AAPC) was evaluated using the joinpoint regression model, while the Bayesian age-period-cohort model was used to predict cancer incidence in the next 10 years. ResultsFrom 2007 to 2021, the study included 651,342 incident patients with cancer, of whom 51.2% (n=333,577) were women. The incidence indicated by the ASR for all cancers combined was 200.8 per 100,000 for women and 184.4 per 100,000 for men. The increase in incidence indicated by AAPC for all malignancies combined significantly increased in women between 2007 and 2021 (AAPC=3.1%; P

Acute liver injury (ALI) is an abnormal liver function caused by oxidative stress, inflammation and other mechanisms.The interaction between intestine and liver plays an important role in ALI, and natural polysaccharides can participate in the regulation of ALI by regulating the composition of intestinal flora. In this study, Ganoderma lucidum polysaccharide was used as the research object, and ICR mice were used to construct an acute liver injury model induced by carbon tetrachloride (CCl4). 16S rRNA sequencing technology was used to analyze the flora structure abundance and detect the changes of intestinal flora. The effective reading of 8 samples was obtained by 16S rRNA sequencing technology, and a total of 1233 samples were obtained. The results of alpha diversity analysis showed that the sequencing depth was sufficient, the abundance of species in the samples was high and the distribution was uniform, and the sequencing data of the samples was reasonable. Nine species with significant differences were screened out by abundence analysis of intestinal flora structure at genus level. Beta diversity analysis showed that species composition was different between the model group and the treatment group. Ganoderma lucidum polysaccharide can maintain the integrity of mucosal barrier by promoting the proliferation of intestinal epithelial cells and anti-oxidative stress injury, thereby improving the intestinal mucosal inflammation of mice, regulating intestinal flora, and effectively alleviating CCl4-induced acute liver injury.

Nylon 54 is a novel, biodegradable polyamide with excellent thermal resistance and water absorption properties. It can be polymerized using bio-based cadaverine and succinic acid as monomers. Traditional separation methods isolate individual monomers from the fermentation broth through acidification or alkalization, resulting in significant amounts of waste salts; however, synchronous separation of dibasic acids and diamines has not been reported. This study investigated an integrated process for the separation and extraction of nylon 54 salts from a co-fermentation broth without acidification or alkalization. We meticulously optimized the operational parameters of the integrated process to achieve maximum separation efficiency. Following microfiltration, ultrafiltration, and decolorization, the bacterial eliminating rate was ≥99.83%, and the protein concentration was ≤40 mg/L. The absorbance of the decolorized solution was ≤0.021 at 430 nm, and the recovery rate of nylon 54 salt reached 97%. Then, the pretreated solution was passed through sequential chromatographic columns, which effectively removed organic acid by-products (such as acetic acid and lactic acid), SO42−, and NH4+ from the fermentation broth, resulting in a cadaverine yield of 98.01% and a succinic acid yield of 89.35%. Finally, by concentrating and crystallizing the eluent, the simulated fermentation broth yielded nylon 54 salt with a purity of 99.16% and a recovery rate of 58%, and the real fermentation broth yielded nylon 54 salt with a purity of 98.10% and a recovery rate of 56.21%. This integrated process offers a sustainable and environmentally friendly pathway for the complete biosynthesis of nylon 54 salt and has the potential to be extended to the preparation of other nylon salts.

Introduction: Augmented reality (AR) has been increasingly studied in transportation, particularly for drivers and pedestrians interacting with automated vehicles (AVs). Previous research evaluated AR interfaces using online video-based questionnaires but lacked human-subject research in immersive environments. This study examined if prior online evaluations of nine AR interfaces could be replicated in an immersive virtual environment and if AR interface effectiveness depends on pedestrian attention allocation.Methods: Thirty participants completed 120 trials in a CAVE-based simulator with yielding and non-yielding AVs, rating the interface’s intuitiveness and crossing the road when they felt safe. To emulate visual distraction, participants had to look into an attention-attractor circle that disappeared 1 s after the interface appeared.Results: The results showed that intuitiveness ratings from the current CAVE-based study and the previous online study correlated strongly (r ≈ 0.90). Head-locked interfaces and familiar designs (augmented traffic lights, zebra crossing) yielded higher intuitiveness ratings and quicker crossing initiations than vehicle-locked interfaces. Vehicle-locked interfaces were less effective when the attention-attractor was on the environment’s opposite side, while head-locked interfaces were relatively unaffected by attention-attractor position.Discussion: In conclusion, this ‘AR in VR’ study shows strong congruence between intuitiveness ratings in a CAVE-based study and online research, and demonstrates the importance of interface placement in relation to user gaze direction.

Periodontitis, delineated by the destruction of structures that support teeth, is predominantly propelled by intricate immune responses. Immunomodulatory treatments offer considerable promise for the management of this ailment; however, the modulation of the periodontal immune microenvironment to facilitate tissue regeneration presents a substantial biomedical challenge. Herein, our study investigates the role of Wilms’ tumor 1-associating protein (WTAP), a critical m6A methyltransferase, in the immunomodulation of periodontitis and assesses its viability as a therapeutic target. We observed heightened expression of WTAP in macrophages extracted from gingival tissues impacted by periodontitis, with a strong association with M1 polarization. Via loss-of-function experiments, we demonstrated that diminishing WTAP expression precipitates a transition from M1 to M2 macrophage phenotypes amidst inflammatory conditions, thus improving the periodontal immune landscape. Further, RNA sequencing and indirect co-culture assays indicated that suppressing of WTAP expression modulates osteoimmune responses and enhances the osteogenic differentiation of bone marrow stromal cells. The local deployment of adeno-associated virus-shWTAP in murine models of periodontitis robustly validated the therapeutic promise of targeting WTAP in this disease. Collectively, our findings highlight the crucial role of WTAP in orchestrating macrophage-mediated osteoimmune responses and tissue regeneration in periodontitis, proposing novel avenues for immunotherapeutic interventions in its treatment.

BackgroundThe evidence supporting a connection between elevated serum uric acid (SUA) levels and diabetic peripheral neuropathy (DPN) is controversial. The present study performed a comprehensive evaluation of this correlation by conducting a systematic review and meta-analysis of relevant research.MethodPubMed, Web of Science (WOS), Embase, and the Cochrane Library were searched for published literature from the establishment of each database to January 8, 2024. In total, 5 cohort studies and 15 cross-sectional studies were included, and 2 researchers independently screened and extracted relevant data. R 4.3.0 was used to evaluate the included literature. The present meta-analysis evaluated the relationship between SUA levels and the risk of DPN in type 2 diabetes (T2DM) by calculating the ratio of means (RoM) and 95% confidence intervals (CIs) using the method reported by JO Friedrich, and it also analyzed continuous outcome measures using standardized mean differences (SMDs) and 95% CIs to compare SUA levels between DPN and non-DPN groups. Funnel plot and Egger’s test were used to assess publication bias. Sensitivity analysis was conducted by sequentially removing each study one-by-one.ResultsThe meta-analysis included 20 studies, with 12,952 T2DM patients with DPN and 16,246 T2DM patients without DPN. There was a significant correlation between SUA levels and the risk of developing DPN [odds ratio (OR) = 1.23; 95% CI: 1.07-1.41; p = 0.001]. Additionally, individuals with DPN had higher levels of SUA compared to those without DPN (SMD = 0.4; 95% CI: -0.11-0.91; p < 0.01).ConclusionT2DM patients with DPN have significantly elevated SUA levels, which correlate with a heightened risk of peripheral neuropathy. Hyperuricemia (HUA) may be a risk indicator for assessing the risk of developing DPN in T2DM patients.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO, identifier CRD42024500373.

The nations of Brazil, Russia, India, China, South Africa, and Turkey (BRICS-T) have yet to find a satisfactory answer to the problem of how to reduce environmental pollution in their environments significantly. Using panel data from 1990 to 2022, this study analyzes the dynamic relationship between energy financial globalization (FG), good governance (GG), renewable energy consumption (REC), urbanization (URB), economic growth (GDP), and environmental pollution. To estimate the long-run and short-run interaction among the variables, this research included the Cross-sectional- ARDL. This research shows that economic growth, energy use, urbanization, and environmental degradation correlate positively and significantly. In contrast, the BRICS-T economies have significantly reduced environmental pollution due to FG, GG and REC. These results also lend credence to the Environmental Kuznets Curve (EKC) concept for developing nations, which has been the focus of recent attention. Additionally, the results from fixed effects-difference in differences (FE-DK) and AMG robustness tests also validate the results from the CS-ARDL estimator. Finally, the findings found that the BRICS-T countries may benefit from this study.

The advent of general anesthesia (GA) has significant implications for clinical practice. However, the exact mechanisms underlying GA-induced transitions in consciousness remain elusive. Given some similarities between GA and sleep, the sleep-arousal neural nuclei and circuits involved in sleep-arousal, including the 5-HTergic system, could be implicated in GA. Herein, we utilized pharmacology, optogenetics, chemogenetics, fiber photometry, and retrograde tracing to demonstrate that both endogenous and exogenous activation of the 5-HTergic neural circuit between the dorsal raphe nucleus (DR) and basolateral amygdala (BLA) promotes arousal and facilitates recovery of consciousness from sevoflurane anesthesia. Notably, the 5-HT1A receptor within this pathway holds a pivotal role. Our findings will be conducive to substantially expanding our comprehension of the neural circuit mechanisms underlying sevoflurane anesthesia and provide a potential target for modulating consciousness, ultimately leading to a reduction in anesthetic dose requirements and side effects.

Single-molecule intramolecular dynamics were successfully measured for three variants of SARS-CoV-2 spike protein, alpha: B.1.1.7, delta: B.1.617, and omicron: B.1.1.529, with a time resolution of 100 μs using X-rays. The results were then compared with respect to the magnitude and directions of motions for the three variants. The largest 3-D intramolecular movement was observed for the omicron variant irrespective of ACE2 receptor binding. A more detailed analysis of the intramolecular motions revealed that the distribution state of intramolecular motion for the three variants was completely different with and without ACE2 receptor binding. The molecular dynamics for the trimeric spike protein of the omicron variant increased when ACE2 binding occurred. At that time, the diffusion constant increased from 71.0 [mrad2/ms] to 91.1 [mrad2/ms].

Background: Our previous studies have shown that lipoxin A4 (LXA4) can serve as a potential biomarker for assessing the efficacy of exercise therapy in knee osteoarthritis (KOA), and fibroblast-like synoviocytes (FLSs) may play a crucial role in KOA pain as well as in the progression of the pathology. Objective: By analyzing the GSE29746 dataset and collecting synovial samples from patients with different Kellgren–Lawrence (KL) grades for validation, we focused on exploring the potential effect of LXA4 on ferroptosis in FLSs through the ESR2/LPAR3/Nrf2 axis to alleviate pain and pathological advancement in KOA. Methods: The association between FLSs ferroptosis and chondrocyte matrix degradation was explored by cell co-culture. We overexpressed and knocked down LPAR3 in vitro to explore its potential mechanism in FLSs. A rat model of monosodium iodoacetate (MIA)-induced KOA was constructed and intervened with moderate-intensity treadmill exercise and intraperitoneal injection of PHTPP to investigate the effects of the LXA4 intracellular receptor ESR2 on exercise therapy. Results: ESR2, LPAR3, and GPX4 levels in the synovium decreased with increasing KL grade. After LXA4 intervention in the co-culture system, GPX4, LPAR3, and ESR2 were upregulated in FLSs, collagen II was upregulated in chondrocytes, and MMP3 and ADAM9 were downregulated. LPAR3 overexpression upregulated the expression of GPX4, Nrf2, and SOD1 in FLSs, while downregulating the expression of MMP13 and MMP3; LPAR3 knockdown reversed these changes. Moderate-intensity platform training improved the behavioral manifestations of pain in KOA rats, whereas PHTPP treatment partially reversed the improvement in synovial and cartilage pathologies induced by platform training. Conclusion: LXA4 inhibited FLSs ferroptosis by activating the ESR2/LPAR3/Nrf2 axis, thereby alleviating the pain and pathological progression of KOA. This study brings a new target for the treatment of KOA and also leads to a deeper understanding of the potential mechanisms of exercise therapy for KOA.

Bessel beams have multiple applications owing to their propagation-invariant properties, including particle trapping, optical coherence tomography, and material processing. However, traditional Bessel-beam shaping techniques require bulky components, which limits the development of miniaturized optical systems for integration with other devices. Here, we report a novel femtosecond laser direct writing strategy for fabricating mesoscale (from submicrometer to subcentimeter) binary optical elements with microscale resolution. This strategy utilizes femtosecond beams with a long focal depth to increase throughput while reducing the constraints on critical sample positioning. As a demonstration, we manufactured and characterized a 2.2 mm diameter binary axicon. The experimentally measured quasi-Bessel beam intensity distribution and the numerical results were remarkably consistent, demonstrating a suitable tradeoff between the overall size, efficiency, and structural fidelity. Furthermore, a compact Bessel lens containing binary axicons was constructed and successfully used for femtosecond laser mask-less ablation of periodic grating-type surface plasmon polariton excitation units. The demonstrated approach shows significant potential for fabricating customizable integrated optical components.

Vaccines have an essential role in preventing infectious diseases and reducing the burden of disease. The differences in vaccine lists and prices, and the National Immunization Program (NIP) and vaccine development between China and the United States (US) in conjunction with epidemiologic data on infectious diseases were systematically compared. The epidemiologic data of infectious diseases in 2019 were extracted from the China National Health Commission and the US Centers for Disease Control and Prevention (CDC). The vaccine list was identified from the China National Medical Products Administration and US Food and Drug Administration databases. Vaccine prices were obtained via the China government procurement platform and the US CDC. The NIP vaccines for China and the US were obtained from the China and US CDCs. Vaccine candidates investigated in 2015-2022 were identified from the China Clinical Trial Registry Platform and the US clinicaltrials.gov database. Differences in the incidence of infectious diseases between China and the US were detected with both countries facing a lack of available vaccines for prevention of many diseases. The number of listed vaccines and preventable diseases in China was 59 and 36, respectively, which was higher than the US (45 and 31, respectively). The median price of NIP vaccines in China was significantly lower than the price in the US (median: $3.8 vs. $20; P

Abstract As immovable stone cultural heritage is kept in the open air, they are more susceptible to damage, and damage detection is very important for the protection and restoration of cultural heritage. This is especially true for gold-overlaid stone cultural heritage, which is usually more complicated than ordinary stone carvings. However, the detection of cultural heritage damages is mainly based on expert visual inspection, which is often subjective, time-consuming, and laborious. This paper uses the Mask R-CNN algorithm to rapidly and accurately detect the gold foil shedding of stone cultural heritage through two-dimensional images. The research data are from the high-precision images of the Dazu Thousand-Hand Bodhisattva Statue (World Heritage, UNESCO) in Chongqing, China. After cleaning and augmentation, 1900 images are input into Mask R-CNN model for training. Finally, the average precision value (AP) for detecting gold foil shedding is found to be 0.967. In order to test the performance of the model, the new images that do not participate in the training period are used, and it is found that the model can still accurately detect the gold foil shedding even if there are interference factors. This is the first attempt to detect the damages of gold-overlaid stone cultural heritage based on a deep learning algorithm, and it has achieved good results.

Abstract With the exponential growth of various data interactions on network systems, network intrusions are also increasing. The emergence of edge computing technology brings a new solution to network security. However, due to the difficulty of processing massive and unbalanced data at the edge, higher accuracy requirements are necessary for deployed detection models. This paper proposes a multi-classification model for network intrusion detection based on reconstruction and feature matching. This model can be deployed on small-scale edge nodes, effectively identifying various attack behaviors through the utilization of reconstruction errors and adaptive scaling. Furthermore, we proposed a model transfer method based on feature matching to enhance the training and detection efficiency of multi-classification models under different data distribution conditions. The proposed model has been evaluated on the CICIDS2017 dataset in terms of accuracy, recall, precision and F1 score. The model demonstrates high accuracy for normal flows in the network, majority class attacks, and minority class attacks, achieving an overall multi-class accuracy of 99.81%, outperforming similar models. Furthermore, this model demonstrates faster convergence and training speed after feature matching, exhibiting better robustness and outstanding performance at the edge.

Target detection technology in the field of machine vision plays a vital role in industrial production and manufacturing. In industrial production, productivity can be improved by accurate target detection. To implement this technology, many enterprises must manually clean and label a huge dataset. Meanwhile, it is a huge challenge for enterprises to obtain the dataset because of enterprise data privacy and security constraints. This paper proposes a method for rapidly generating synthetic samples based on digital twins to address this challenge. First, the virtual environment is utilized to replicate the real detecting environment, generating a variety of sample photos. The three-dimensional coordinates of the target object are then extracted in the virtual scene. Subsequently, an annotation method is designed for synthetic samples obtained from the virtual scene, utilizing principles of three-dimensional coordinate transformation and perspective coordinate transformation. This method efficiently produces numerous labeled samples with diverse annotations. Ultimately, the model performs detection tasks in the actual world using the synthetic samples as training data. The experimental results show that the synthetic samples created by this method based on digital twins can substitute real samples and effectively identify target objects during actual detection tasks. This paper proposes a unique strategy for synthetic samples that reduces sample collection costs and privacy risks, thereby addressing the limitations of machine vision detection technology induced by sample limitations.

Abstract Melody harmonization, which involves generating a chord progression that complements a user-provided melody, continues to pose a significant challenge. A chord progression must not only be in harmony with the melody, but also interdependent on its rhythmic pattern. While previous neural network-based systems have been successful in producing chord progressions for given melodies, they have not adequately addressed controllable melody harmonization, nor have they focused on generating harmonic rhythms with flexibility in the rates or patterns of chord changes. This paper presents AutoHarmonizer, a novel system for harmonic density-controllable melody harmonization with such a flexible harmonic rhythm. AutoHarmonizer is equipped with an extensive vocabulary of 1462 chord types and can generate chord progressions that vary in harmonic density for a given melody. Experimental results indicate that the AutoHarmonizer-generated chord progressions exhibit a diverse range of harmonic rhythms and that the system’s controllable harmonic density is effective.

Abstract Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) infection has many neurological manifestations, and its effects on the nervous system are increasingly recognized. There has been no systematic analysis of electroencephalography (EEG) characteristics in children exhibiting neurological symptoms of Coronavirus disease 2019 (COVID-19). The primary aim of this study was to describe the EEG characteristics caused by COVID-19 infection in children who were showing neurological symptoms and to assess the relationship between COVID-19-related EEG changes and clinical features in these children. Method: This study included 125 pediatric patients infected with SARS-CoV2 and showing neurological symptoms, and their continuous EEG was recorded. In addition, the demographic and clinical characteristics of these patients were analyzed and the correlation between the two was investigated. Results: Abnormal EEG findings were detected in 31.20% (N = 39) of the patients. Abnormal discharges (43.59%) were the most common EEG abnormalities, followed by background abnormalities (41.03%). The proportion of patients diagnosed with febrile seizure was higher in the normal EEG group than in the abnormal EEG group (P = 0.002), while the opposite was true for epilepsy and encephalitis/encephalopathy (P = 0.016 and P = 0.003, respectively). The independent associated factors of abnormal EEG were age and total length of stay (P

Abstract Objective To assess the effects of finerenone and glucagon-like peptide 1 receptor agonists (GLP1-RA) on cardiovascular and renal outcomes in patients with type 2 diabetes mellitus (T2DM), and the relative cardiovascular benefits in patients with or without established atherosclerotic cardiovascular disease for different outcomes with these classes of drugs. Methods We searched PubMed, the Cochrane Library, and Embase from January 1, 2000, to December 30, 2022, to identify randomized controlled trials. The primary outcomes were the composite of nonfatal myocardial infarction, nonfatal stroke, and cardiovascular death (MACE); hospitalization for heart failure (HHF); and a composite of renal outcomes. The results were reported as hazard ratios (HRs) with 95% confidence intervals (CIs). Results In total, we identified 11 trials and 73,927 participants, 13,847 (18.7%) in finerenone trials and 60,080 (81.3%) in GLP1-RA trials. Finerenone reduced the risk of MACE by 13% (HR, 0.87; 95% CI, 0.79–0.95; P = 0.003), while GLP1-RA reduced the risk in a similar magnitude by 13% (HR, 0.87; 95% CI, 0.83–0.92; P

Background and objectives In clinical practice, some patients are diagnosed with diabetic nephropathy (DN) combined with acute tubulointerstitial nephritis (ATIN) through renal biopsy. There is relatively little research on the treatment and prognosis of such patients, and no consensus exists on the use of glucocorticoid for treatment. Therefore, our study explores the progression of DN combined with ATIN and the renal outcomes after treatment with glucocorticoid.Methods This study retrospectively analyzed patients diagnosed with DN combined with ATIN through renal biopsy at our center from January 1, 2015, to December 31, 2021. We collected general patient information, laboratory indicators, renal pathology indicators, and the glucocorticoid usage after kidney biopsy. Follow-up data were collected from medical records. Statistical analysis methods included t-tests, non-parametric tests, and chi-square tests. Univariate and multivariate Cox regression analyses were used to evaluate the risk factors for renal endpoint events in patients. Statistical significance was defined as p-values < 0.05.Results In this study, a total of 67 patients were included. The subjects were divided into two groups based on whether they received glucocorticoid treatment: 33 patients in the steroid group and 34 in the non-steroid group. In the steroid group, 19 patients reached the renal endpoint event, which was significantly higher than in the non-steroid group (57.58% vs. 29.41%, p = 0.038). Univariate Cox regression analysis showed that serum creatinine (HR = 1.008, p

Background This study aims to investigate the incidence and prognosis of malignancy in individuals with thrombospondin type-1 domain-containing 7A (THSD7A)-associated membranous nephropathy (MN).Methods First, we performed a systematic literature review of prevalence of malignancy in THSD7A-associated MN. Then, we conducted a retrospective analysis of 454 patients diagnosed with MN through renal biopsy at our hospital between January 2016 and December 2020. We assessed the presence of serum anti-THSD7A antibodies and performed immunohistochemical staining of renal tissue for THSD7A. Subsequently, we followed patients with THSD7A-associated MN for a minimum of 3–5 years, collecting their clinical, pathological characteristics, and prognosis. Additionally, we conducted a literature review on patients with THSD7A-associated MN in conjunction with malignancy.Results We identified a total of nine articles containing comprehensive data on THSD7A-associated MN and malignancy. Among 235 patients with THSD7A-positive MN, 36 individuals had concurrent malignancies, resulting in a malignancy prevalence of 13.3% (95% CI: 8.9–17.7%). In our center, we followed up with 15 patients diagnosed with THSD7A-associated MN and observed three cases of concomitant tumors: two cases of lung adenocarcinoma and one case of small cell lung cancer with multiple metastases. The prevalence of malignancy in our cohort was 20%. Notably, we detected positive THSD7A staining in both renal and lung cancer tissues in one patient with small cell lung cancer.Conclusions Patients with THSD7A-associated MN should undergo vigilant follow-up assessments, with a particular focus on actively seeking potential tumorigenic lesions to prevent misdiagnosis or oversight.

ABSTRACTGut microbiota plays an essential role in nonalcoholic fatty liver disease (NAFLD). However, the contribution of individual bacterial strains and their metabolites to childhood NAFLD pathogenesis remains poorly understood. Herein, the critical bacteria in children with obesity accompanied by NAFLD were identified by microbiome analysis. Bacteria abundant in the NAFLD group were systematically assessed for their lipogenic effects. The underlying mechanisms and microbial-derived metabolites in NAFLD pathogenesis were investigated using multi-omics and LC-MS/MS analysis. The roles of the crucial metabolite in NAFLD were validated in vitro and in vivo as well as in an additional cohort. The results showed that Enterococcus spp. was enriched in children with obesity and NAFLD. The patient-derived Enterococcus faecium B6 (E. faecium B6) significantly contributed to NAFLD symptoms in mice. E. faecium B6 produced a crucial bioactive metabolite, tyramine, which probably activated PPAR-γ, leading to lipid accumulation, inflammation, and fibrosis in the liver. Moreover, these findings were successfully validated in an additional cohort. This pioneering study elucidated the important functions of cultivated E. faecium B6 and its bioactive metabolite (tyramine) in exacerbating NAFLD. These findings advance the comprehensive understanding of NAFLD pathogenesis and provide new insights for the development of microbe/metabolite-based therapeutic strategies.

Background This retrospective study aims to investigate the prevalence and immunopathologic characteristics of seropositive and seronegative hepatitis B virus-associated membranous nephropathy (HBV-MN).Methods Clinicopathologic and serologic records of 420 patients with histologically confirmed HBV-MN between January 2014 and July 2021 were examined to determine the prevalence of seropositive and seronegative HBV-MN. Serum anti-PLA2R antibody testing was conducted on 280 patients with HBV-associated membranous nephropathy (HBV-MN) from August 2018 to July 2021. Immunopathologic characteristics of HBV-MN patients and anti-PLA2R antibody positivity were analyzed.Results Among 420 pathologically confirmed HBV-MN patients, 230 (54.8%) were seropositive for HBV. The seropositive group exhibited higher blood creatinine values and incidence of liver function abnormalities than the seronegative group (p

Introduction: The carbon storage service of ecosystems in ecologically fragile areas is highly sensitive to regional land use/land cover (LULC) changes. Predicting changes in regional carbon storage under different LULC scenarios is crucial for land use management decisions and exploring carbon sink potential. This study focuses on the Luan River Basin, a typical ecologically fragile area, to analyze the impact of LULC changes on carbon storage.Methods: The PLUS-InVEST model was employed to simulate LULC patterns for the year 2030 under three scenarios: natural development, cropland protection and urban development, and ecological protection. The model projected the future carbon sink potential of the basin under these scenarios.Results: From 2000 to 2020, carbon storage showed a trend of decrease followed by an increase. By 2030, compared to 2020, carbon storage is projected to increase by 16.97% under the ecological protection scenario and decrease by 22.14% under the cropland protection and urban development scenario. The increase in carbon storage was primarily due to the conversion of cropland and grassland to forestland, while the decrease was mainly associated with the conversion of forestland to grassland and cropland, and the transformation of grassland to cropland and construction land. In the potential LULC scenarios of 2030, certain regions within the basin exhibited unstable carbon sink potential, strongly influenced by LULC changes. These areas were predominantly characterized by artificially cultivated forests, shrubs, and agricultural land. Implementing appropriate forest management measures and optimizing agricultural land management practices are essential to enhance carbon sink potential in these regions. Population density, annual average temperature, and DEM (Digital Elevation Model) were the dominant factors driving the spatial variation of carbon sink potential in the Luan River Basin.Discussion: The research results provide a theoretical basis for rational planning of land use and the enhancement of carbon sink potential in ecologically fragile regions.

IntroductionStudies focusing on coopetition and dynamic capabilities have expanded significantly over the past several decades. Coopetition strategy and dynamic capabilities are increasingly recognised as sources of sustained competitive advantage. The purpose of this paper is to provide a better understanding of the factors driving growth performance in digital healthcare ventures by examining the role of coopetition, exploration and exploitation capabilities, and environmental uncertainty. While numerous studies have examined the competitive advantage of coopetition, its specific contribution to the growth of ventures in the digital realm remains less explored. Clarifying the strategic role of coopetition in driving growth performance is critical for delineating the intricate relationship between coopetition and growth performance, particularly in the context of digital healthcare ventures. To fill in this research gap, this study uses coopetition theory and dynamic capabilities theory to look at how exploration and exploitation capabilities, as well as environmental uncertainty, affect the relationship between coopetition and growth performance in digital healthcare ventures.MethodsWe collected a total of 338 questionnaires from Chinese digital healthcare ventures between March 2023 and August 2023. We conducted data analysis using SPSS 26.0 and its macro-program PROCESS.ResultsOur results confirm that coopetition has a positive effect on growth performance in digital healthcare ventures. Furthermore, exploration and exploitation capabilities fully mediate the relationship between coopetition and growth performance. Moreover, environmental uncertainty significantly and distinctively moderates the impact of exploration and exploitation capabilities on growth performance.DiscussionThis study contributes to the existing literature by providing deeper insight into the relationship between coopetition and growth performance in digital healthcare ventures. It also offers important practical implications for public health improvement and socio-economic development.

Accurately predicting landslide displacement is essential for reducing and managing associated risks. To address the challenges of both under-decomposition and over-decomposition in landslide displacement analysis, as well as the low predictive accuracy of individual models, this paper proposes a novel prediction model based on time series theory. This model integrates a Convolutional Neural Network (CNN) with a Bidirectional Long-Short Term Memory network (BiLSTM) and an attention mechanism to form a comprehensive CNN-BiLSTM-Attention model. It harnesses the feature extraction capabilities of CNN, the bidirectional data mining strength of BiLSTM, and the focus-enhancing properties of the attention mechanism to enhance landslide displacement predictions. Furthermore, this paper proposes utilizing the Variational Mode Decomposition (VMD) method to decompose both landslide displacement and its influencing factors. The VMD algorithm’s parameters are optimized through the Sparrow Search Algorithm (SSA), which effectively minimizes the influence of subjective bias while maintaining the integrity of the decomposition. A fusion of the Maximal Information Coefficient (MIC) and Grey Relational Analysis (GRA) is then employed to identify the critical influencing factors. The selected sequence of factors that conforms to the criteria is used as the input variable for displacement prediction via the CNN-BiLSTM-Attention model. The cumulative displacement prediction is derived by aggregating the results from each sequence. The study reveals that the SSA-VMD-CNN-BiLSTM-Attention model introduced herein achieves superior predictive accuracy for both periodic and random term displacements than individual models. This advancement provides a dependable benchmark for forecasting displacement in similar landslide scenarios.