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Abstract Background The solid pattern is a highly malignant subtype of lung adenocarcinoma. In the current era of transitioning from lobectomy to sublobar resection for the surgical treatment of small lung cancers, preoperative identification of this subtype is highly important for patient surgical approach selection and long‐term prognosis. Methods A total of 1489 patients with clinical stage IA1‐2 primary lung adenocarcinoma were enrolled. Based on patient clinical characteristics and lung imaging features obtained via deep learning, highly correlated diagnostic factors were identified through LASSO regression and decision tree analysis. Subsequently, a logistic model and nomogram were constructed. A restricted cubic spline (RCS) was used to calculate the optimal inflection point of quantitative data and the differences between the groups. Results The three‐dimensional proportion of solid component (PSC), sex, and smoking status was identified as being highly correlated diagnostic factors for solid predominant adenocarcinoma. The logistic model had good prediction efficiency, and the area under the ROC curve was 0.85. Decision curve analysis demonstrated that the application of diagnostic factors can improve patient outcomes. RCS analysis indicated that the proportion of solid adenocarcinomas increased by 4.6 times when the PSC was ≥72%. A PSC of 72% is a good cutoff point. Conclusion The preoperative diagnosis of solid‐pattern adenocarcinoma can be confirmed by typical imaging features and clinical characteristics, assisting the thoracic surgeon in developing a more precise surgical plan.

Orthopedic and dental implantations under bacterial infection microenvironment face significant challenges in achieving high-quality bone-implant integration. Designing implant coatings that incorporate both immune defense and anti-inflammation is difficult in conventional single-functional coatings. We introduce a multifunctional nanointerface using a zinc finger-inspired peptide-metal-phenolic nanocoating, designed to enhance implant osseointegration under such conditions. Abaloparatide (ABL), a second-generation anabolic drug for treating osteoporosis, can be integrated into the design of a zinc-phenolic network constructed on the implant surface (ABL@ZnTA). Importantly, the phenolic-coordinated Zn2+ ions in ABL@ZnTA can act as zinc finger motif to co-stabilize the configuration of ABL through multiple molecular interactions, enabling high bioactivity, high loading capacity (1.36 times), and long-term release (>7 days) of ABL. Our results showed that ABL@ZnTA can modulate macrophage polarization from the pro-inflammatory M1 towards the anti-inflammatory M2 phenotype, promoting immune osteogenesis with increased OCN, ALP, and SOD 1 expression. Furthermore, the ABL@ZnTA significantly reduces inflammatory fibrous tissue encapsulation and enhances the long-term stability of the implants, indicated by enhanced binding strength (6 times) and functional connectivity (1.5−3 times) in the rat bone defect model infected by S. aureus. Overall, our research offers a nano-enabled synergistic strategy that balances infection defense and osteogenesis promotion in orthopedic and dental implantations.

Abstract Background Although previous observational studies have shown an association between venous thromboembolism (VTE) and atrial fibrillation (AF), the underlying causal relationship between them remains uncertain. Methods and results This two-sample bidirectional Mendelian randomization (MR) analysis was performed to investigate the causal relationship between VTE and AF. The VTE dataset were obtained from FinnGen, including 9,176 cases and 209,616 controls. Meanwhile a genome-wide association study (GWAS) of 60,620 individuals with AF and 970,216 control subjects identified genetic variations associated with AF. The principal MR analytic approach used in this study is the inverse-variance weighting (IVW) method. Furthermore, we performed complementary MR analyses, including the MR-Egger, Weighted median (WM), and Weighted Mode. MR pleiotropy residual sum was applied to identify pleiotropy. The MR analysis showed suggestive causal associations between VTE and the risk of AF (p = 0.0245, OR [95%CI]: 1.027 [1.003, 1.051]). The reverse MR analysis found that genetic susceptibility to AF was not significantly associated with VTE, as determined by the IVW method (p = 0.7773). The robustness of these findings was corroborated through MR sensitivity analyses. Conclusions There is a unidirectional causal relationship between VTE and AF, meaning that VTE is a causal risk factor for AF, whereas no effect of AF on VTE was identified.

Gender disparities are evident across different types of digestive system cancers, which are typically characterized by a lower incidence and mortality rate in females compared to males. This finding suggests a potential protective role of female steroid hormones, particularly estrogen, in the development of these cancers. Estrogen is a well-known sex hormone that not only regulates the reproductive system but also exerts diverse effects on non-reproductive organs mediated through interactions with estrogen receptors (ERs), including the classic (ERα and ERβ) and non-traditional ERs [G protein-coupled estrogen receptor (GPER)]. Recent advances have contributed to our comprehension of the mechanisms underlying ERs in digestive system cancers. In this comprehensive review we summarize the current understanding of the intricate roles played by estrogen and ERs in the major types of digestive system cancers, including hepatocellular, pancreatic, esophageal, gastric, and colorectal carcinoma. Furthermore, we discuss the potential molecular mechanisms underlying ERα, ERβ, and GPER effects, and propose perspectives on innovative therapies and preventive measures targeting the pathways regulated by estrogen and ERs. The roles of estrogen and ERs in digestive system cancers are complicated and depend on the cell type and tissue involved. Additionally, deciphering the intricate roles of estrogen, ERs, and the associated signaling pathways may guide the discovery of novel and tailored therapeutic and preventive strategies for digestive system cancers, eventually improving the care and clinical outcomes for the substantial number of individuals worldwide affected by these malignancies.

Abstract The rising flexible and intelligent electronics greatly facilitate the noninvasive and timely tracking of physiological information in telemedicine healthcare. Meticulously building bionic-sensitive moieties is vital for designing efficient electronic skin with advanced cognitive functionalities to pluralistically capture external stimuli. However, realistic mimesis, both in the skin’s three-dimensional interlocked hierarchical structures and synchronous encoding multistimuli information capacities, remains a challenging yet vital need for simplifying the design of flexible logic circuits. Herein, we construct an artificial epidermal device by in situ growing Cu3(HHTP)2 particles onto the hollow spherical Ti3C2T x surface, aiming to concurrently emulate the spinous and granular layers of the skin’s epidermis. The bionic Ti3C2T x @Cu3(HHTP)2 exhibits independent NO2 and pressure response, as well as novel functionalities such as acoustic signature perception and Morse code-encrypted message communication. Ultimately, a wearable alarming system with a mobile application terminal is self-developed by integrating the bimodular senor into flexible printed circuits. This system can assess risk factors related with asthmatic, such as stimulation of external NO2 gas, abnormal expiratory behavior and exertion degrees of fingers, achieving a recognition accuracy of 97.6% as assisted by a machine learning algorithm. Our work provides a feasible routine to develop intelligent multifunctional healthcare equipment for burgeoning transformative telemedicine diagnosis.

Abstract Background The aim of this study was to explore the relationships between teaching competence, career development, industrial orientation, and specialty construction in the case of intelligent medicine specialties in universities of traditional Chinese medicine, as well as the influencing factors of specialty construction. Methods Two-stage sampling with unequal probability was conducted to distribute self-administered questionnaires in the fieldwork. A structural equation model was built to investigate the influencing factors of specialty construction. Forty-two teachers were recruited and completed the questionnaire. Results The study found that teaching competence, career development, and industrial orientation positively affect specialty construction at a significant level. Career development and industrial orientation play chain mediating roles in the effect of teaching competence on specialty construction. Conclusions In the construction of intelligent medicine specialties, a professional curriculum system should be built that caters to industrial demand and is combined with industrial development, the traditional mode of teaching should be transformed, and the transformation of theoretical knowledge into practical ability should be promoted. Innovations in teaching modes should be achieved by introducing information technology, and the teacher evaluation system should be optimized.

The access of wind power reduces the carbon emissions of the power system from the generation side, and the introduction of demand response to eliminate wind abandonment provides a new idea for carbon reduction from the load side. Considering wind power and demand response comprehensively, based on the theory of carbon emission flow of power system, a day-ahead and day-in two-stage low carbon optimal dispatching method for power grid is proposed. Firstly, the carbon emission flow theory of power system is analyzed, and the node carbon potential model of load side is established. Then, the flexible load is divided into two types, transferable load and reducible load. Based on the carbon potential model of load nodes, the response mechanism of calling these two types of loads to reduce carbon is designed. On this basis, the source load coordination day-ahead optimal scheduling model considering low-carbon and economic is established. Based on model predictive control, the day-ahead optimal scheduling model is solved, and the day-ahead scheduling results are changed through feedback correction. Finally, the simulation results of the improved PJM-5 node system and IEEE 300-node system show that the proposed optimal scheduling method can effectively promote the flexible load to absorb wind power, and reduce wind abandonment, and achieve the goal of load side carbon reduction.

Abstract Liver cancer is a global health challenge, causing a significant social-economic burden. Hepatocellular carcinoma (HCC) is the predominant type of primary liver cancer, which is highly heterogeneous in terms of molecular and cellular signatures. Early-stage or small tumors are typically treated with surgery or ablation. Currently, chemotherapies and immunotherapies are the best treatments for unresectable tumors or advanced HCC. However, drug response and acquired resistance are not predictable with the existing systematic guidelines regarding mutation patterns and molecular biomarkers, resulting in sub-optimal treatment outcomes for many patients with atypical molecular profiles. With advanced technological platforms, valuable information such as tumor genetic alterations, epigenetic data, and tumor microenvironments can be obtained from liquid biopsy. The inter- and intra-tumoral heterogeneity of HCC are illustrated, and these collective data provide solid evidence in the decision-making process of treatment regimens. This article reviews the current understanding of HCC detection methods and aims to update the development of HCC surveillance using liquid biopsy. Recent critical findings on the molecular basis, epigenetic profiles, circulating tumor cells, circulating DNAs, and omics studies are elaborated for HCC diagnosis. Besides, biomarkers related to the choice of therapeutic options are discussed. Some notable recent clinical trials working on targeted therapies are also highlighted. Insights are provided to translate the knowledge into potential biomarkers for detection and diagnosis, prognosis, treatment response, and drug resistance indicators in clinical practice.

Abstract Protein methylation is a functionally important post-translational modification that occurs on diverse amino acid residues. The current proteomics approaches are inefficient to discover the methylation on residues other than Arg and Lys, which hinders the deep understanding of the functional role of rare protein methylation. Herein, we present a methyl-specific metabolic labeling approach for global methylome mapping, which enable the acquisition of methylome dataset covering diverse methylation types. Interestingly, of the identified methylation events, His methylation is found to be preferably occurred in C3H1 zinc fingers (ZFs). These His methylation events are determined to be Nπ specific and catalyzed by CARNMT1. The His methylation is found to stabilize the structure of ZFs. U2AF1 is used as a proof-of-concept to highlight the functional importance of His methylation in ZFs in RNA binding and RNA metabolism. The results of this study enable novel understanding of how protein methylation regulates cellular processes.

In 60Co based computed tomography (CT) of carbon components，reducing the number of sampling angles can significantly shorten detection time and improve detection efficiency. However，for conventional analytical reconstruction algorithms，sparse angle reconstruction images contain a large amount of noise and artifacts，which interfere with the detection of defects in the images and affect the quality evaluation of the inspected components by the detection system under fast detection conditions. This article proposes a sparse angle CT image reconstruction method based on neuralnetwork，which uses an untrained encoding decoding neural network to optimize the projection error of the reconstructed image，and uses the ADAM algorithm to optimize the total variation prior of the image. Compared with traditional deep learning reconstruction algorithms，this method does not require training sample sets and has stronger generalization ability and robustness. The results of simulation and practical experiments show that compared to traditional analytical and reconstruction algorithms，this method significantly improves the quality of reconstructed images，while retaining the detailed information of the detected components，and significantly suppresses artifacts and noise in the reconstructed images retaining image details and texture. This work can effectively improve image quality，eliminate the interference of artifacts on the identification of defects in graphics，and improve the ability to recognize defects in carbon components for the detection system.

Abstract Background Rifampicin resistant tuberculosis (RR-TB) poses a growing threat to individuals and communities. This study utilized a seasonal autoregressive integrated moving average (SARIMA) model to quantitatively predict the monthly incidence of RR-TB in Yunnan Province which could guide government health administration departments and the centers for disease control and prevention (CDC) in preventing and controlling the RR-TB epidemic. Methods The study utilized routine surveillance reporting data from the infectious Disease Network Surveillance and Reporting System. Monthly incidence rates of RR-TB were collected from January 2019 to December 2022. A time series SARIMA model was used to predict the number of monthly RR-TB cases in Yunnan Province in 2023, and the model was validated using time series plots, seasonal and non-seasonal differencing, autocorrelation and partial autocorrelation analysis, and white noise tests. Results From 2019 to 2022, the incidence of RR-TB decreases as the incidence of all TB decreases (P 0.05). The time series decomposition shows that it presented obvious seasonality, periodicity and randomness after being decomposed. Time series analysis was performed on the original series after 1 non-seasonal difference and 1 seasonal difference, the ADF test showed P

Abstract Tumor spread through air spaces (STAS) is a distinctive metastatic pattern affecting prognosis in lung adenocarcinoma (LUAD) patients. Several challenges are associated with STAS detection, including misdetection, low interobserver agreement, and lack of quantitative analysis. In this research, a total of 489 digital whole slide images (WSIs) were collected. The deep learning-based STAS detection model, named STASNet, was constructed to calculate semi-quantitative parameters associated with STAS density and distance. STASNet demonstrated an accuracy of 0.93 for STAS detection at the tiles level and had an AUC of 0.72–0.78 for determining the STAS status at the WSI level. Among the semi-quantitative parameters, T10S, combined with the spatial location information, significantly stratified stage I LUAD patients on disease-free survival. Additionally, STASNet was deployed into a real-time pathological diagnostic environment, which boosted the STAS detection rate and led to the identification of three easily misidentified types of occult STAS.

Abstract Adenoid hypertrophy can lead to adenoidal mouth breathing, which can result in “adenoid face” and, in severe cases, can even lead to respiratory tract obstruction. The Fujioka ratio method, which calculates the ratio of adenoid (A) to nasopharyngeal (N) space in an adenoidal-cephalogram (A/N), is a well-recognized and effective technique for detecting adenoid hypertrophy. However, this process is time-consuming and relies on personal experience, so a fully automated and standardized method needs to be designed. Most of the current deep learning-based methods for automatic diagnosis of adenoids are CNN-based methods, which are more sensitive to features similar to adenoids in lateral views and can affect the final localization results. In this study, we designed a local attention-based method for automatic diagnosis of adenoids, which takes AdeBlock as the basic module, fuses the spatial and channel information of adenoids through two-branch local attention computation, and combines the downsampling method without losing spatial information. Our method achieved mean squared error (MSE) 0.0023, mean radial error (MRE) 1.91, and SD (standard deviation) 7.64 on the three hospital datasets, outperforming other comparative methods.

To investigate the mechanism of rosmarinic acid in alleviating food allergy, an integrated approach, involving network pharmacology, molecular docking and lipid-omics were employed to investigate the potential mechanism of rosmarinic acid (RA) in alleviating food allergy. To obtain potential therapeutic targets for RA, database analysis platform such as database and analysis platform (TCMSP), Swiss Target Prediction, Pharm Mapper, Super Pred and Gene Cards were employed. The ''active ingredient-target'' protein-protein (PPI) network was constructed using Cytoscape software and the String database. The validation of molecular docking was performed using AutoDockTools software. Furthermore, a food allergy mouse model using ovalbumin (OVA) and lipid metabolism studies on mouse serum based on high-resolution mass spectrometry were applied to investigate the antiallergic effect of RA and the underling mechanism. Results showed that, through the network pharmacology analysis, a total of 46 associated target proteins were identified. The geno ontology (GO) enrichment analysis of the target proteins indicated that RA primarily exerted its effects through modulation of protein phosphorylation and the binding between glycosphingolipids, phospholipids and steroids. The kyoto encyclopedia of genes and genomes (KEGG) analysis indicated that the associated targets were mainly enriched in the Th1/Th2 cell differentiation pathways, lipid metabolism and inflammatory bowel disease pathways. The results indicated that RA intervention could significantly suppress the elevation of allergic mediators in the serum of mice sensitizes with OVA. In addition, the RA intervention group showed a decrease in the levels of total cholesterol and triglycerides in the mouse serum. In lipidomics analysis, 25 and 36 differentially expressed lipid metabolites were screened in positive and negative ion modes, respectively. Enrichment analysis of the differentially expressed lipid metabolites indicated that the serum lipid metabolism in mice affected glycerophospholipid metabolism and sphingolipid metabolic pathways. Therefore, this study demonstrated that RA primarily exerted its alleviating effect on food allergies by regulating lipid metabolism and the body's inflammatory response.

Introduction: Adipogenesis, the process of white adipose tissue expansion, plays a critical role in the development of obesity. Osteoprotegerin (OPG), known for its role in bone metabolism regulation, emerges as a potential regulator in mediating adipogenesis during obesity onset. Objectives: This study aims to elucidate the involvement of OPG in adipogenesis during the early phases of diet-induced obesity and explore its therapeutic potential in obesity management. Methods: Using a diet-induced obesity model, we investigated OPG expression patterns in adipocytes and explored the mechanisms underlying its involvement in adipogenesis. We also assessed the effects of targeted silencing of OPG and recombinant OPG administration on obesity progression and insulin resistance. Additionally, the impact of electroacupuncture treatment on OPG levels and obesity management was evaluated in both animal models and human participants. Results: OPG expression was prominently activated in adipocytes of white adipose tissues during the early phase of diet-induced obesity. Hyperlipidemia induced Cbfa1-dependent OPG transcription, initiating and promoting adipogenesis, leading to cell-size expansion and lipid storage. Intracellular OPG physically bound to RAR and released the PPARɤ/RXR complex, activating adipogenesis-associated gene expression. Targeted silencing of OPG suppressed obesity development, while recombinant OPG administration promoted disease progression and insulin resistance in obese mice. Electroacupuncture treatment suppressed obesity development in an OPG-dependent manner and improved obesity parameters in obese human participants. Conclusion: OPG emerges as a key regulator in mediating adipogenesis during obesity development. Targeting OPG holds promise for the prevention and treatment of obesity, as evidenced by the efficacy of electroacupuncture treatment in modulating OPG levels and managing obesity-related outcomes.

ObjectiveTo analyze the changes in the time intervals between diagnosis and treatment and the influencing factors of diagnosis and treatment delay among rifampicin-resistant tuberculosis (RR-TB) patients from 2016 to 2021 in Yunnan province, to provide a reference for reducing the occurrence of diagnosis and treatment delay in patients. MethodsData of 2 189 RR-TB patients registered in Yunnan province from 2016 to 2021 were extracted from the Tuberculosis Management Information System (TMIS) – a subsystem of the China Disease Prevention and Control Information System – to analyze the time intervals between symptom onset and diagnosis and that between diagnosis and treatment for the patients with different demographic and other characteristics. The time intervals were described in median and percentile 25th/75th (M, P25/P75) days, and multivariate binary logistic regression was used to analyze factors influencing delays in diagnosis and treatment of RR-TB patients. ResultsFor all patients, the median number of days from symptom onset to confirmed diagnosis of RR-TB increased from 50 in 2016 to 109 in 2018, but then decreased annually to 42 in 2021, with a trend of first increasing and then decreasing. The RR-TB patients who underwent conventional drug susceptibility testing and received initial diagnosis at a prefectural or municipal-level medical institution were more likely to have delayed diagnosis, with the odd ratio (OR) and 95% confidence interval (95%CI) of 5.193 (3.750 – 7.193) and 1.449 (1.199 – 1.752), respectively. The median number of days from diagnosis to treatment for the 1 488 RR-TB patients being treated increased slightly from one day in 2016 to 11 days in 2021. The RR-TB patients with the following characteristics were more likely to have treatment delays: being male (OR = 1.309, 95%CI: 1.063 – 1.612), being a farmer (OR = 1.317, 95%CI: 1.022 – 1.698), and being a permanent resident (OR = 4.016, 95%CI: 3.220 – 5.008) ; whereas RR-TB patients of younger age were less likely to have treatment delay, with the OR (95%CI) of 0.676 (0.487 – 0.938), 0.687 (0.494 – 0.954), and 0.663 (0.489 – 0.901) for the patients aged 25 – 34, 35 – 44, and 45 – 55 years respectively, compared with those aged ≥ 65 years. ConclusionDuring 2016 – 2021, the time interval between symptom onset and diagnosis was significantly shortened and the interval between diagnosis and treatment was relatively short for RR-TB patients in Yunnan province but attention still needs to be paid to patients at high risk of delayed diagnosis and treatment.

Objective The formation of monsoon climates is attributed to the seasonal reversal of wind direction and precipitation caused by the difference in thermal capacity between land and ocean. Asia is recognized as the most prominent region globally, with monsoon climates, that affect the largest population. The heavy rainfall accompanying monsoons can result in various secondary disasters, substatially jeopardizing human safety and productivity in the region. Consequently, comprehending the formation process of the Asian monsoon holds paramount importance. Methods This study aim to employ geological concepts to establish a connection between the past and present, providing an overview of the components of Asian monsoons, identifying the primary factors influencing their formation and evolution, and summarizing research progress on the South Asian and East Asian monsoons based on sediment records from key Asian locations. Results The findings indicate that during the Cenozoic, the collision between the Indian Plate and the southern margin of the Asian continent altered the distribution of land and sea in Asia. Consequently, the Tibetan Plateau experienced initial uplift, contributing to the emergence of monsoon climates in South Asia and East Asia. However, at this stage, the East Asian region was still primarily influenced by the planetary wind system, and the East Asian monsoon was in its early stages, predominantly restricted to the southern margin of the South China Plate in a localized manner. In contrast, the South Asian Monsoon covered a relatively extensive area. This discrepancy may be attributed to the delayed opening of marginal seas in the East Asian region compared to the relatively earlier occurrence of land and sea distribution in South Asia. However, as the Tibetan Plateau continued to uplift and approach its current altitude during the middle to late Cenozoic, the Asian monsoon entered a strengthening phase, notably impacting regional geological evolution processes. Since the middle to late Cenozoic, the development of the North and South Polar ice caps and the upliftment of the Tibetan Plateau have controlled the Asian monsoon, leading it to undergo multiple stable periods of development. Conclusion The development and evolution of the East Asian and South Asian monsoons are mainly driven by the distribution of sea and land in the Asia, the upliftment of the Tibetan Plateau and the global climate change during the Cenozoic. Significance These findings provide valuable insights into the scientific and rational utilization of the Asian monsoon for conducting systematic Earth science research in Asia.

Abstract Previous studies revealed that MIR155HG possessed an oncogenic role in many types of tumors including lung adenocarcinoma (LUAD), along with higher expression in tumors. However, in our study, we observed a positive correlation between MIR155HG expression and overall survival across different cohorts. The transferred PBMC on the NCG mouse model abrogated the tumor intrinsic oncogenic role of MIR155HG in LUAD. Upregulation of MIR155HG positively correlated with CD8+ T cell infiltration both in vitro and in vivo, as well as LUAD tissues. Mechanistically, we revealed that MIR155HG increased the cytokine CCL5 expression at the transcriptional level, which depended on the interaction between MIR155HG and YBX1 protein, a novel transcription factor of CCL5, resulting in the more protein stability of YBX1 through dampening ubiquitination. Additionally, we also observed that MIR155 could increase PD-L1 expression to hamper the activity of recruited CD8+ T cells, which could be rescued through PD-L1 mAb addition. Finally, we uncovered that patients with high MIR155HG expression had a higher response rate to immunotherapy, and the combination of MIR155HG overexpression and PD-L1 mAb increased the efficacy of PD-L1 mAb. Together, our study provides a novel biomarker and potential combination treatment strategy for patients who received immunotherapy.

Abstract Background Although laparoscopic hepatectomy (LH) and radiofrequency ablation (RFA) are the 2 principal minimally invasive surgical approaches and the first line of treatments for patients with hepatocellular carcinoma (HCC). It is not clear which one has greater safety and efficacy. In this meta-analysis, we aim to compare the safety and effectiveness of LH versus RFA for patients with HCC, especially where perioperative and postoperative outcomes differrent. Methods In PROSPERO, a meta-analysis with registration number CRD42021257575 was registered. Using an established search strategy, we systematically searched Web of Science, PubMed, and Embase to identify eligible studies before June 2023. Data on operative times, blood loss, length of stay, overall complications, overall survival (OS) and recurrence-free survival (RFS) were subjected to meta-analysis. Results Overall, the present meta-analysis included 8 retrospective and 6 PSM studies comprising 1,848 patients (810 and 1,038 patients underwent LH and RFA). In this meta-analysis, neither LH nor RFA showed significant differences in 1-year and 3-year OS rate and 5-year RFS rate. Despite this, in comparison to the RFA group, LH resulted in significantly higher 1-year(p

Abstract Background Patients with lung adenocarcinoma (LUAD) have a low response rate to immune checkpoint blockade. It is highly important to explore the tumor immune escape mechanism of LUAD patients and expand the population of patients who may benefit from immunotherapy. Methods Based on 954 bulk RNA-seq data of LUAD patients and 15 single-cell RNA-seq data, the relationships between tumor immune dysfunction and exclusion (TIDE) scores and survival prognosis in each patient were calculated and evaluated, and the immune escape mechanism affecting the independent prognosis of LUAD patients was identified. Functional enrichment analysis explored the antitumour immune response and biological behavior of tumor cells among different LUAD groups. Single-cell annotation and pseudotemporal analysis were used to explore the target molecules and immune escape mechanisms of LUAD. Results Myeloid-derived suppressor cells (MDSCs) and IRF8 were identified as risk and protective factors for the independent prognosis of LUAD patients, respectively. In the tumor microenvironment of patients with high infiltration of MDSCs, the antitumor immune response is significantly suppressed, while tumor cell division, proliferation, and distant metastasis are significantly enhanced. Single-cell RNA-seq analysis revealed that IRF8 is an important regulator of MDSC differentiation in LUAD myeloid cells. In addition, IRF8 may regulate the differentiation of MDSCs through the IL6-JAK-STAT3 signalling pathway. Conclusions IRF8 deficiency impairs the normal development of LUAD myeloid cells and induces their differentiation into MDSCs, thereby accelerating the immune escape of LUAD cells. IRF8-targeted activation to inhibit the formation of MDSCs may be a new target for immunotherapy in LUAD.

Abstract Background Postoperative radiotherapy can significantly reduce keloid recurrence. However, consensus on the optimal radiotherapy dose and treatment schedule remains elusive. This study aims to evaluate the effectiveness of surgery followed by a short-course of radiotherapy administered every other day for keloid treatment. Materials/Methods We conducted a retrospective analysis of 498 patients with keloids treated at our institution between January 2010 and December 2017. All patients underwent electron beam irradiation at a dose of 16 Gy, delivered in four fractions every other day, starting within 24 h post-surgery. The primary endpoint of the study was the local control rate. Results A total of 130 (26.5%) keloids recurred after a median follow-up of 68.1months (42.6-129.9 months). The local control rates at 1 year, 3 years and 5 years for all patients were 89.5%, 82.5% and 81%, respectively. The highest recurrence rate was observed in keloids located in the chest region (50.8%), followed by the suprapubic (47.8%), head and neck (38.8%), limbs (33.3%) and ear (14%). Both multivariate and univariate analyses identified the presence of pain and or pruritus as an independently prognostic factor for keloid recurrence (p

Background: Deep convolutional neural networks have garnered considerable attention in numerous machine learning applications, particularly in visual recognition tasks such as image and video analyses. There is a growing interest in applying this technology to diverse applications in medical image analysis. Automated three-dimensional Breast Ultrasound is a vital tool for detecting breast cancer, and computer-assisted diagnosis software, developed based on deep learning, can effectively assist radiologists in diagnosis. However, the network model is prone to overfitting during training, owing to challenges such as insufficient training data. This study attempts to solve the problem caused by small datasets and improve model detection performance. Methods: We propose a breast cancer detection framework based on deep learning (a transfer learning method based on cross-organ cancer detection) and a contrastive learning method based on breast imaging reporting and data systems (BI-RADS). Results: When using cross organ transfer learning and BIRADS based contrastive learning, the average sensitivity of the model increased by a maximum of 16.05%. Conclusion: Our experiments have demonstrated that the parameters and experiences of cross-organ cancer detection can be mutually referenced, and contrastive learning method based on BI-RADS can improve the detection performance of the model.

Abstract Recent research in computational imaging largely focuses on developing machine learning (ML) techniques for image recognition in the medical field, which requires large-scale and high-quality training datasets consisting of raw images and annotated images. However, suitable experimental datasets for cervical spine X-ray are scarce. We fill the gap by providing an open-access Cervical Spine X-ray Atlas (CSXA), which includes 4963 raw PNG images and 4963 annotated images with JSON format (JavaScript Object Notation). Every image in the CSXA is enriched with gender, age, pixel equivalent, asymptomatic and symptomatic classifications, cervical curvature categorization and 118 quantitative parameters. Subsequently, an efficient algorithm has developed to transform 23 keypoints in images into 77 quantitative parameters for cervical spine disease diagnosis and treatment. The algorithm’s development is intended to assist future researchers in repurposing annotated images for the advancement of machine learning techniques across various image recognition tasks. The CSXA and algorithm are open-access with the intention of aiding the research communities in experiment replication and advancing the field of medical imaging in cervical spine.

Abstract Current clustering analysis of spatial transcriptomics data primarily relies on molecular information and fails to fully exploit the morphological features present in histology images, leading to compromised accuracy and interpretability. To overcome these limitations, we have developed a multi-stage statistical method called iIMPACT. It identifies and defines histology-based spatial domains based on AI-reconstructed histology images and spatial context of gene expression measurements, and detects domain-specific differentially expressed genes. Through multiple case studies, we demonstrate iIMPACT outperforms existing methods in accuracy and interpretability and provides insights into the cellular spatial organization and landscape of functional genes within spatial transcriptomics data.

BackgroundMinimally invasive techniques have significantly gained popularity for hepatocellular carcinoma (HCC) based on the Milan criteria. However, whether or not laparoscopic liver resection (LLR) or radiofrequency ablation (RFA) is a better treatment option remains debatable. We conducted a meta-analysis to review the published data comparing LLR and RFA for HCC through Milan criteria depending on tumor recurrence risk and survival.MethodsPubMed, OvidSP, Web of Science, and Cochrane Library databases were searched from inception to December 31, 2023. The studies comparing the outcomes and methods between LLR and RFA for HCC within the Milan criteria were included.ResultsWe recruited 19 cohort studies with 2532 patients. The postoperative complication rate was low, and hospital stays were shorter in the RFA group than in the LLR group. The total tumor recurrence, the local tumor recurrence rate, and the intrahepatic tumor recurrence rate were lower within the LLR group than in the RFA group. There was no significant difference in the extrahepatic recurrence rate between the two groups. Moreover, no significant differences were observed between the groups concerning 1-, 3-, and 5-year overall survival (OS) and 1-year recurrence-free survival (RFS). However, 3-year and 5-year RFS were better within the LLR group than among the RFA group.ConclusionsThe treatment of HCC within the Milan criteria is moving toward multidisciplinary and minimally invasive approaches. Our meta-analysis identified a lower postoperative complication rate and higher recurrence rate for RFA than LLR. RFA could be an alternative treatment due to its comparable long-term efficacy with LLR.

Colistin (CT) is the last-resort of antibiotic against multidrug-resistance (MDR) Acinetobacter baumannii (A. baumannii) infection. However, colistin resistance is increasingly reported in A. baumannii isolates partially due to the global emergence and dissemination of plasmid-borne mobile colistin resistance (mcr) gene and is a threat to human health. Thus, available treatment strategies urgently required in the fight against colistin-resistant A. baumannii. Here, we showed that mcr confers damaged outer membrane (OM) permeability in A. baumannii, which could compromise the viability of A. baumannii. Consistently, A. baumannii with colistin resistance exhibits increased susceptibility to macromolecular antibiotics such as rifampicin (RIF) and erythromycin (ERY). Moreover, the combination therapy of colistin and rifampicin demonstrates efficacy against colistin-resistant A. baumannii, regardless of the presence of mcr. Altogether, our data suggest that the synergy of colistin in combination with macromolecular hydrophobic antibiotics poses a promising therapeutic alternative for colistin-resistant A. baumannii.

ObjectiveBiomaterials loaded with ingredients derived from traditional Chinese medicine (TCM) are viewed as a promising strategy for treating spinal cord injury (SCI). However, a comprehensive analysis of the existing literature on this topic has not yet been conducted. Therefore, this paper systematically reviews researches related to this approach, aiming to identify gaps and shortcomings in the field.MethodsPubMed, EMBASE, Web of Science, Chinese Biomedical Literature, Wanfang, and China National Knowledge Infrastructure (CNKI) were searched for retrieving studies on biomaterials loaded with TCM ingredients published from their inception to October 2024. Two reviewers performed screening of search results, information extraction, and literature quality assessment independently.ResultsFor this systematic review, 41 publications were included. Six TCM ingredients-paclitaxel, curcumin, tetramethylpyrazine, resveratrol, berberine, and tanshinone IIA were combined with biomaterials for treatment of SCI. Biomaterials were categorized into hydrogels, biodegradable scaffolds, nanoparticles, and microspheres according to the type of scaffold. These drug delivery systems exhibit commendable biocompatibility, drug-loading capacity, and drug-release capabilities, and in combination with TCM ingredients, synergistically contribute to anti-oxidative stress, anti-inflammatory, neuroprotective, and anti-apoptotic effects.ConclusionThese studies demonstrated the efficacy of biomaterials loaded with TCM ingredients in facilitating motor function recovery and neuroprotection in SCI rats, providing evidence for future research. However, in the complex microenvironment of SCI, achieving the maximum drug loading capacity of TCM ingredients within biomaterials, along with sustained and controlled release to fully exert their pharmacological effects, remains a major challenge for future research.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/ identifier CRD42024505000.

BackgroundIndividuals with substance use disorder (SUD) are characterized by loss of control in drug use, such as increased impulsivity. Methamphetamine and methcathinone are psychostimulants, the use of which is accompanied by a high level of impulsivity. Whether individuals with methamphetamine use disorder (MUD) and methcathinone use disorder (MCUD) differ in different aspects of impulsivity is unclear.MethodsWe investigated impulsivity traits and behaviors in individuals with MUD and MCUD. The Barratt Impulsiveness Scale (BIS), Sensation Seeking Scale (SSS), and delay discounting task (DDT) were assessed in individuals with MUD and MCUD and in healthy controls (HCs); then, we performed network-based analysis and computational modeling to understand the potential differences among the three groups.ResultsMUD subjects scored higher than MCUD subjects in terms of motor impulsivity, nonplanning impulsivity, and total BIS scores. The network analysis revealed that there were no significant differences between MUD and MCUD subjects in any centrality indices. The discount rate of MUD and MCUD subjects was significantly greater than that of HCs, whereas there was no difference in the discount rate between the two addiction groups.ConclusionsThese findings suggest that MUD and MCUD participants differ in impulsivity traits but not in impulsive behaviors, implying that impulsive traits and behaviors represent different aspects of impulsivity.

Abstract Rational design and construction of oxygen reduction reaction (ORR) electrocatalysts with high activity, good stability, and low price are essential for the practical applications of renewable energy conversion devices, such as metal‐air batteries. Electronic modification through constructing metal/semiconductor Schottky heterointerface represents a powerful strategy to enhance the electrochemical performance. Herein, we demonstrate a concept of Schottky electrocatalyst composed of uniform Co nanoparticles in situ anchored on the carbon nanotubes aligned on the carbon nanosheets (denoted as Co@N‐CNTs/NSs hereafter) toward ORR. Both experimental findings and theoretical simulation testify that the rectifying contact could impel the voluntary electron flow from Co to N‐CNTs/NSs and create an internal electric field, thereby boosting the electron transfer rate and improving the intrinsic activity. As a consequence, the Co@N‐CNTs/NSs deliver outstanding ORR activity, impressive long‐term durability, excellent methanol tolerance, and good performance as the air‐cathode in the Zn‐air batteries. The design concept of Schottky contact may provide the innovational inspirations for the synthesis of advanced catalysts in sustainable energy conversion fields.

Abstract The trap states at both the upper and bottom interfaces of perovskite layers significantly impact non‐radiative carrier recombination. The widely used solvent‐based passivation methods result in the disordered distribution of surface components, posing challenges for the commercial application of large‐area perovskite solar cells (PSCs). To address this issue, a novel NH3 gas‐assisted all‐inorganic dual‐interfaces passivation strategy is proposed. Through the gas treatment of the perovskite surface, NH3 molecules significantly enhanced the iodine vacancy formation energy (1.54 eV) and bonded with uncoordinated Pb2+ to achieve non‐destructive passivation. Meanwhile, the reduction of the film defect states is accompanied by a decrease in the work function, which promotes carrier transport between the interface. Further, a stable passivation layer is constructed to manage the bottom interfacial defects using inorganic potassium tripolyphosphate (PT), whose ─P═O group effectively mitigated the charged defects and lowered the carrier transport barriers and nucleation barriers of PVK, while the gradient distribution of K+ improved the crystalline quality of PVK film. Based on the dual‐interface synergistic effect, the optimal MA‐contained PSCs with an effective area of 0.1 cm2 achieved an efficiency of 24.51% and can maintain 90% of the initial value after aging (10−20% RH and 20 °C) for 2000 h.

Novel biochar-based fertilizers, produced by combining biochar particles with chemical fertilizers, have strong potential to enrich soil with carbon (C) and nitrogen (N), and to increase plant productivity. Application of biochar-based fertilizers modifies soil microbial community compositions, thereby influencing greenhouse gas emissions, including methane (CH4) fluxes. Due to the improved aeration in soils amended with biochar particles, we hypothesized that biochar-based urea would decrease CH4 production and increase CH4 oxidation, leading to increase of total CH4 uptake by soil. A three-year field experiment was conducted in a subtropical Moso bamboo forest to compare the impacts of biochar-based urea and traditional urea on seasonal CH4 uptake by soil, as well as on soil physicochemical and microbial attributes. Urea application lowered the annual soil CH4 uptake by 6 % and 16 % at 100 and 300 kg N/ha, respectively, within the first year. Biochar-based urea application at 300 kg N/ha increased the annual CH4 uptake by 12 % in both the first and second years, whereas the effects weakened over time. Soil CH4 uptake was positively correlated with CH4 oxidation rate but negatively with CH4 production rate. The urea-induced decrease in CH4 uptake was attributed to the increased NH4+ and NO3− contents and mcrA gene abundance as well as decreased pmoA/mcrA ratio, thereby increasing CH4 production rate. The biochar-based urea increased CH4 uptake by enhanced soil aeration and labile C supply, which created favorable conditions for methanotrophs. This resulted in increased pmoA gene abundance and the pmoA/mcrA ratio, thereby accelerating CH4 oxidation. Overall, these findings underscore the potential of biochar-based fertilizers in augmenting CH4 uptake within subtropical forest soils. Notably, the transition from traditional urea to biochar-based urea in China Moso bamboo forests alone has the potential to lift annual soil CH4 uptake by an estimated 4450 t.

Performance evaluation is important for improving medical quality and services. But, there is a lack of research for medical quality in traditional Chinese medicine (TCM) hospitals. This study examines the medical quality and various indicators of tertiary public traditional Chinese medicine hospitals in Gansu Province, to establish a foundation for improving the medical and management standards of these hospitals. This study collected performance assessment data from 10 tertiary TCM hospitals in Gansu Province from 2019 to 2022. Thirteen indicators with TCM characteristics were selected and categorized into 3 aspects: control of medical costs, internal operational dimensions, and comprehensive management. The level of medical quality in different hospitals and in different years were determined using the TOPSIS method for ranking and the RSR method for grading. Firstly, in terms of TCM characteristic indicators, hospital H had the highest control of medical costs and comprehensive management among different hospitals, with 45.87% and 24.20% respectively. The highest values for control of medical costs and comprehensive management were observed in 2020, with 40.65% and 18.69% respectively among different years. When evaluating the medical quality of different hospitals using the TOPSIS method, it was found that hospital H had the highest ranking from 2020 to 2022, with C i values of 0.725, 0.778, and 0.667 respectively. Additionally, the RSR method indicated that hospital H had a high level of grading from 2020 to 2022, with P i values of 0.687, 0.690, and 0.723 respectively. These findings suggest that the medical quality of hospital H is at a high and stable level of development. Based on the TOPSIS method to evaluate the performance appraisal results and ranking of different hospitals from 2019 to 2022. The results showed that the highest ranking was hospital B(C i = 0.913) in 2019. The highest ranking was hospital C(C i = 0.809)in 2020. The highest ranking was hospital D(C i = 0.689) in 2021. The highest ranking was hospital J(C i = 0.865) in 2022. The RSR method indicated that high grading level were hospitals B(P i = 0.899),F(P i = 0.795) in 2019. The highest grading level was hospital C(P i = 0.809) in 2020. The highest grading level were hospitals A(P i = 0.868), D(P i = 0.813), E(P i = 0.689), G(P i = 0.873), J(P i = 0.813), K(P i = 0.842) in 2022. Based on the above results indicate that there is a large variation in the medical quality profile of different hospitals from 2019 to 2022. By comparing the results of TOPSIS and RSR method from 2019 to 2022, we found that the hospitals with identical ranking were D and J, and the hospitals with ≤2 difference in ranking was A,B,C,E in 2019, the hospitals with >2 ranking was A, F in 2020, the hospitals with >2 ranking were C, G in 2021, and the hospitals with identical ranking results were B,D,E,G,J in 2022. Comparing the ranking results of TOPSIS and RSR methods, showed that the hospitals with identical rankings were B, F from 2019 to 2022. The difference in ranking results ≤2 were A, C, D, E, G, H, J, K, indicating that high consistency between TOPSIS and RSR methods and credible results. The findings reveal significant fluctuations in medical quality across different years, while the overall level of medical quality remains relatively stable among the various hospitals. It is recommended that TCM hospitals focus on improving management efficiency, optimizing hospital operations, enhancing the utilization of medical resources, and fostering the efficient development of hospitals.

Background: Hepatocellular carcinoma (HCC) is among the most prevalent digestive system malignancies and is associated with a poor prognosis. Necroptosis, a form of regulated death mediated by death receptors, exhibits characteristics of both necrosis and apoptosis. Long non-coding RNAs (lncRNAs) have been identified as crucial regulators in tumor necroptosis. This study aims to identify the necroptosis-related lncRNAs (np-lncRNA) in HCC and investigate their relationships with prognosis. Method: The RNA-sequencing data, along with clinicopathological and survival information of HCC patients were sourced from The Cancer Genome Atlas (TCGA) database. The np-lncRNAs were analyzed to assess their potential in predicting HCC prognosis. Prognostic signatures related to necroptosis were constructed using stepwise multivariate Cox regression analysis. The prognosis of patients was compared using Kaplan-Meier (KM) analysis. The accuracy of the prognostic signature was evaluated using Receiver operating characteristic (ROC) analysis and decision curve analysis (DCA). Quantitative real-time polymerase chain reaction(qPCR) was employed to validate the lncRNAs expression levels of lncRNAs among samples from an independent cohort. Results: The np-lncRNAs ZFPM2-AS1, AC099850.3, BACE1-AS, KDM4A-AS1 and MKLN1-AS were identified as potential prognostic biomarkers. The prognostic signature constructed from these np-lncRNAs achieved an Area Under the Curve (AUC) of 0.773. Based on the risk score derived from the signature, patients were divided into two groups, with the high-risk group exhibiting poorer overall survival. Gene Set Enrichment Analysis (GSEA) revealed significantly different between the low risk and high risk groups in tumor-related pathways (such as mTOR, MAPK and p53 signaling pathways) and immune-related functions (like T cell receptor signaling pathway and natural killer cell mediated cytotoxicity). The increased expression of np-lncRNAs was confirmed in another independent HCC cohort. Conclusions: This signature offers a dependable method for forecasting the prognosis of HCC patients. Our findings indicate a subset of np-lncRNA biomarkers that could be utilized for prognosis prediction and personalized treatment strategies of HCC patients.

ObjectiveThis study used finite element analysis to simulate four commonly used fixation methods for metacarpal shaft oblique fractures during finger motion and evaluate their biomechanical performance. The aim was to provide evidence for clinically selecting the optimal fixation method, guiding early rehabilitation treatment, and reducing the risk of complications.MethodsFinite element analysis simulated dynamic proximal phalanx motion (60° flexion, 20° extension, 20° adduction, and 20° abduction). We analysed stress, displacement, and distributions for dorsal plates, intramedullary nails, Kirschner wire, and screw fixation methods.ResultsAt 60° of finger flexion and 20° of abduction, plate fixation demonstrated greater stability and minimal displacement, with a peak displacement of 0.19 mm; however, it showed higher stress levels in all motion states, increasing the risk of failure. The stability of the intramedullary nail was similar to that of the dorsal plate, with a maximum displacement difference of 0.04 mm, and it performed better than the dorsal plate during adduction of 20°. Kirschner wire showed the highest stress levels of 81.6 Mpa during finger flexion of 60°, indicating a greater risk of failure and unstable displacement. Screws had lower stress levels in all finger motion states, reducing the risk of failure, but had poorer stability. Stress and displacement distributions showed that the dorsal plate, intramedullary nail, and Kirschner wire mainly bore stress on the implants, concentrating near the fracture line and the proximal metacarpal. In contrast, the screws partially bore stress in the screw group. The anterior end of the metacarpal mainly hosted the maximum displacement.ConclusionThis study demonstrates that under simulated finger motion states, the dorsal plate fixation method provides the best stability in most cases, especially during finger flexion and abduction. However, high stress levels also indicate a higher risk of failure. The intramedullary nail is similar to the dorsal plate in stability and performs better in certain motion states. Kirschner wire exhibits the highest risk of failure during flexion. Although screws have poorer stability in some motion states, they offer a lower risk of failure. These findings provide important reference and surgical selection strategies for treating metacarpal fractures.

Emerging mycotoxins enniatins (ENNs) and beauvericin (BEA) pose potential health risks to humans through dietary exposure. However, research into their mechanisms of toxicity is limited, with a lack of comprehensive toxicological data. This study investigates from a hepatic lipid metabolism perspective, establishing a more precise and reliable 3D HepaRG hepatocyte spheroid model as an alternative for toxicity assessment. Utilizing physiological indices, histopathological analyses, lipidomics, and molecular docking techniques, it comprehensively elucidates the effects of ENNs and BEA on hepatic lipid homeostasis and their molecular toxicological mechanisms. Our findings indicate that ENNs and BEA impact cellular viability and biochemical functions, significantly altering lipid metabolism pathways, particularly those involving glycerophospholipids and sphingolipids. Molecular docking has demonstrated strong binding affinity of ENNs and BEA with key enzymes in lipid metabolism such as Peroxisome Proliferator-Activated Receptor α (PPARα) and Cytosolic Phospholipase A2 (cPLA2), revealing the mechanistic basis for their hepatotoxic effects and potential to impair liver function and human health. These insights enhance our understanding of the potential hepatotoxicity of such fungal toxins and lay a foundation for the assessment of their health risks.

Inflammation is the response of the human body to injury, infection, or other abnormal states, which is involved in the development of many diseases. As a member of the Krüppel-like transcription factors (KLFs) family, KLF4 plays a crucial regulatory role in physiological and pathological processes due to its unique dual domain of transcriptional activation and inhibition. A growing body of evidence has demonstrated that KLF4 plays a pivotal role in the pathogenesis of various inflammatory disorders, including inflammatory bowel disease, osteoarthritis, renal inflammation, pneumonia, neuroinflammation, and so on. Consequently, KLF4 has emerged as a promising new therapeutic target for inflammatory diseases. This review systematically generalizes the molecular regulatory network, specific functions, and mechanisms of KLF4 to elucidate its complex roles in inflammatory diseases. An in-depth study on the biological function of KLF4 is anticipated to offer a novel research perspective and potential intervention strategies for inflammatory diseases.

Solid-state electrolytes (SSEs) are regarded as crucial materials, thus determining the comprehensive properties of solid-state lithium batteries (SSLBs). However, the existing issues of ion transport and interface limit their further development and application. As the inorganic solid-state electrolytes (ISEs) and polymer solid-state electrolytes (PSEs) both present obvious advantages and defects, the strategy of preparing composite solid-state electrolytes (CSEs) by incorporating inorganic components in polymer matrix is considered an effective way to overcome the above-mentioned problems. Nanowires with high aspect ratios are widely used in CSEs. Moreover, nanowires can not only effectively enhance the mechanical properties and ion transport efficiency of SSEs, but also boost the contact between electrolyte and electrode interface, thereby improving the cycle stability and safety of SSLBs. This review systematically categorized nanowires according to their morphology, function, and Li+ conductivity, and discussed their structural properties and synthesis strategies in detail. Moreover, application examples and mechanisms of nanowires in different polymer matrices are also introduced. In the summary and prospect section, we anticipate the existing challenges and future objectives of nanowires in the future research of CSEs.

As an important component of transcellular pathway, Caveolae enables the transcellular transport of substances without disrupting cellular homeostasis. In kidney, albumin crosses glomerular filtration barrier (GFB) via Caveolae. Transcellular transport of albumin plays a crucial role in the pathology of proteinuria. Thus the importance of Caveolae cannot be overstated. However, the acting mechanism of Caveolae affecting transcellular albumin transport in kidney and their signaling pathways have remained largely elusive. This review summarized the latest studies on the regulation of Caveolae affecting transcellular albumin transport. Thus elucidating the relevant mechanisms of action and understanding the pathways of influence may provide potential therapeutic targets in the prevention and alleviation of proteinuria

Induction of beige fat for thermogenesis is a potential therapy to improve homeostasis against obesity. β3-adrenoceptor (β3-AR), a type of G protein-coupled receptor (GPCR), is believed to mediate the thermogenesis of brown fat in mice. However, β3-AR has low expression in human adipose tissue, precluding its activation as a standalone clinical modality. This study aimed at identifying a potential GPCR target to induce beige fat. We found that chemerin chemokine-like receptor 1 (CMKLR1), one of the novel GPCRs, mediated the development of beige fat via its two ligands, chemerin and resolvin E1 (RvE1). The RvE1 levels were decreased in the obese mice, and RvE1 treatment led to a substantial improvement in obese features and augmented beige fat markers. Inversely, despite sharing the same receptor as RvE1, the chemerin levels were increased in obesogenic conditions, and chemerin treatment led to an augmented obese phenotype and a decline of beige fat markers. Moreover, RvE1 and chemerin induced or restrained the development of beige fat, respectively, via the mechanistic target of rapamycin complex 1 (mTORC1) signaling pathway. We further showed that RvE1 and chemerin regulated mTORC1 signaling differentially by forming hydrogen bonds with different binding sites of CMKLR1. In conclusion, our study showed that RvE1 and chemerin affected metabolic homeostasis differentially, suggesting that selectively modulating CMKLR1 may be a potential therapeutic target for restoring metabolic homeostasis.

Abstract Background Taraxacum kok-saghyz Rodin (TKS) is a highly potential source of natural rubber (NR) due to its wide range of suitable planting areas, strong adaptability, and suitability for mechanized planting and harvesting. However, current methods for detecting NR content are relatively cumbersome, necessitating the development of a rapid detection model. This study used near-infrared spectroscopy technology to establish a rapid detection model for NR content in TKS root segments and powder samples. The K445 strain at different growth stages within a year and 129 TKS samples hybridized with dandelion were used to obtain their near-infrared spectral data. The rubber content in the root of the samples was detected using the alkaline boiling method. The Monte Carlo sampling method (MCS) was used to filter abnormal data from the root segments of TKS and powder samples, respectively. The SPXY algorithm was used to divide the training set and validation set in a 3:1 ratio. The original spectrum was preprocessed using moving window smoothing (MWS), standard normalized variate (SNV), multiplicative scatter correction (MSC), and first derivative (FD) algorithms. The competitive adaptive reweighted sampling (CARS) algorithm and the corresponding chemical characteristic bands of NR were used to screen the bands. Partial least squares (PLS), random forest (RF), Lightweight gradient augmentation machine (LightGBM), and convolutional neural network (CNN) algorithms were employed to establish a model using the optimal spectral processing method for three different bands: full band, CARS algorithm, and chemical characteristic bands corresponding to NR. The model with the best predictive performance for high rubber content intervals (rubber content > 15%) was identified. Result The results indicated that the optimal rubber content prediction models for TKS root segments and powder samples were MWS–FD CASR–RF and MWS–FD chemical characteristic band RF, respectively. Their respective $${\text{R}}_{{\text{P}}}^{2}$$ R P 2 , RMSEP, and RPDP values were 0.951, 0.979, 1.814, 1.133, 4.498, and 6.845. In the high rubber content range, the model based on the LightGBM algorithm had the best prediction performance, with the RMSEP of the root segments and powder samples being 0.752 and 0.918, respectively. Conclusions This research indicates that dried TKS root powder samples are more appropriate for constructing a rubber content prediction model than segmented samples, and the predictive capability of root powder samples is superior to that of root segmented samples. Especially in the elevated rubber content range, the model formulated using the LightGBM algorithm has superior predictive performance, which could offer a theoretical basis for the rapid detection technology of TKS content in the future.

Abstract Cancer cells exhibit distinct metabolic activities and nutritional dependencies compared to normal cells. Thus, characterization of nutrient demands by individual tumor types may identify specific vulnerabilities that can be manipulated to target the destruction of cancer cells. We find that MYC-driven liver tumors rely on augmented tryptophan (Trp) uptake, yet Trp utilization to generate metabolites in the kynurenine (Kyn) pathway is reduced. Depriving MYC-driven tumors of Trp through a No-Trp diet not only prevents tumor growth but also restores the transcriptional profile of normal liver cells. Despite Trp starvation, protein synthesis remains unhindered in liver cancer cells. We define a crucial role for the Trp-derived metabolite indole 3-pyruvate (I3P) in liver tumor growth. I3P supplementation effectively restores the growth of liver cancer cells starved of Trp. These findings suggest that I3P is a potential therapeutic target in MYC-driven cancers. Developing methods to target this metabolite represents a potential avenue for liver cancer treatment.

Abstract Background The real-world tuberculosis (TB) surveillance data was generally incomplete due to underreporting and underdiagnosis. The inventory study aimed to assess and quantify the incompletion of surveillance systems in southwestern China. Methods The inventory study was conducted at randomly selected health facilities (HF) by multi-stage stratified cluster sampling. The participants were included in the period between August of 2020 in province-level and prefecture-level HF, and in the period between June to December of 2020 in other categories of HF respectively. The clinical committee confirmed medical records were matched to the National Notifiable Disease Reporting System (NNDRS) and the Tuberculosis Information Management System (TBIMS) to define the report and register status. The underreporting and under-register rates were evaluated based on the matched data, and factors associated with underreport and under-register were assessed by the 2-level logistic multilevel model (MLM). Results We enrolled 7,749 confirmed TB cases in the analysis. The province representative overall underreport rate to NNDRS was 1.6% (95% confidence interval, 95% CI, 1.3 − 1.9), and the overall under-register rate to TBIMS was 9.6% (95% CI, 8.9–10.3). The various underreport and under-register rates were displayed in different stratifications of background TB disease burden, HF level, HF category, and data source of the medical record in HF among prefectures of the province. The intraclass correlation coefficient (ICC) was 0.57 for the underreporting null MLM, indicating the facility-level cluster effect contributes a great share of variation in total variance. The two-level logistic MLM showed the data source of medical records in HF, diagnostic category of TB, and type of TB were associated with underreporting by adjusting other factors (p

Abstract Plant cellulose synthase is one of the important glycosyltransferases, which catalyzes the synthesis of the paracrystalline of H-bonded-β-(1,4)-glucose chains. This study isolated the cellulose synthase 3 (Ces3) sequence from sugarcane (Saccharum officinarum L.) leaves. SoCes3 (GenBank accession No. MG324347) has a full-length cDNA sequence of 3625 bp. It contains an open reading frame (3225 bp), encoding 1074 amino acids with a molecular weight of about 120.89 kDa and isoelectric point of 6.26. SoCes3 protein showed high activity with other plant cellulose synthases. The recombinant protein contains plant cellulose synthase (Ces) protein conservative domains. In subcellular localization experiments, the fusion protein of SoCes3 with green fluorescent protein (GFP) was specifically localized in the cell membrane. The gene expression of SoCes3 was found in the leaf, leaf sheath, and internodes of the sugarcane stem. The highest expression level was found in the internode, especially with the highest expression level in the 5th internode and lowest in the leaves, and the gene expression level of SoCes3 was upregulated by PP333 and not in gibberellic acid-treated plants. It was conducted in tobacco plants to understand the biotechnological potential of SoCes3. The contents of cellulose and lignin were increased in SoCes3-overexpressing tobacco. Transcriptomic analysis showed that the transgenic tobacco induced different genes associated with different biological regulatory processes. Differentially expressed genes (DEGs) mediated plant hormone signal transduction, starch and sucrose metabolism signaling pathways were widely induced and mostly upregulated. The transcription levels in SoCes3-overexpressing transgenic lines were higher than wild-type. Graphical Abstract

Abstract Osimertinib (Osi) is a widely used epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI). However, the emergence of resistance is inevitable, partly due to the gradual evolution of adaptive resistant cells during initial treatment. Here, we find that Osi treatment rapidly triggers adaptive resistance in tumor cells. Metabolomics analysis reveals a significant enhancement of oxidative phosphorylation (OXPHOS) in Osi adaptive-resistant cells. Mechanically, Osi treatment induces an elevation of NCOA4, a key protein of ferritinophagy, which maintains the synthesis of iron-sulfur cluster (ISC) proteins of electron transport chain and OXPHOS. Additionally, active ISC protein synthesis in adaptive-resistant cells significantly increases the sensitivity to copper ions. Combining Osi with elesclomol, a copper ion ionophore, significantly increases the efficacy of Osi, with no additional toxicity. Altogether, this study reveals the mechanisms of NCOA4-mediated ferritinophagy in Osi adaptive resistance and introduces a promising new therapy of combining copper ionophores to improve its initial efficacy.

Abstract Coordination cages have been widely reported to bind a variety of guests, which are useful for chemical separation. Although the use of cages in the solid state benefits the recycling, the flexibility, dynamicity, and metal-ligand bond reversibility of solid-state cages are poor, preventing efficient guest encapsulation. Here we report a type of coordination cage-integrated solid materials that can be swelled into gel in water. The material is prepared through incorporation of an anionic FeII 4L6 cage as the counterion of a cationic poly(ionic liquid) (MOC@PIL). The immobilized cages within MOC@PILs have been found to greatly affect the swelling ability of MOC@PILs and thus the mechanical properties. Importantly, upon swelling, the uptake of water provides an ideal microenvironment within the gels for the immobilized cages to dynamically move and flex that leads to excellent solution-level guest binding performances. This concept has enabled the use of MOC@PILs as efficient adsorbents for the removal of pollutants from water and for the purification of toluene and cyclohexane. Importantly, MOC@PILs can be regenerated through a deswelling strategy along with the recycling of the extracted guests.

Abstract Background Postoperative cognitive dysfunction (POCD) is a common neurological complication of anesthesia and surgery in aging individuals. Neuroinflammation has been identified as a hallmark of POCD. However, safe and effective treatments of POCD are still lacking. Itaconate is an immunoregulatory metabolite derived from the tricarboxylic acid cycle that exerts anti-inflammatory effects by activating the nuclear factor erythroid 2-related factor 2 (Nrf2) pathway. In this study, we investigated the effects and underlying mechanism of 4-octyl itaconate (OI), a cell-permeable itaconate derivative, on POCD in aged mice. Methods A POCD animal model was established by performing aseptic laparotomy in 18-month-old male C57BL/6 mice under isoflurane anesthesia while maintaining spontaneous ventilation. OI was intraperitoneally injected into the mice after surgery. Primary microglia and neurons were isolated and treated to lipopolysaccharide (LPS), isoflurane, and OI. Cognitive function, neuroinflammatory responses, as well as levels of gut microbiota and their metabolites were evaluated. To determine the mechanisms underlying the therapeutic effects of OI in POCD, ML385, an antagonist of Nrf2, was administered intraperitoneally. Cognitive function, neuroinflammatory responses, endogenous neurogenesis, neuronal apoptosis, and Nrf2/extracellular signal-related kinases (ERK) signaling pathway were evaluated. Results Our findings revealed that OI treatment significantly alleviated anesthesia/surgery-induced cognitive impairment, concomitant with reduced levels of the neuroinflammatory cytokines IL-1β and IL-6, as well as suppressed activation of microglia and astrocytes in the hippocampus. Similarly, OI treatment inhibited the expression of IL-1β and IL-6 in LPS and isoflurane-induced primary microglia in vitro. Intraperitoneal administration of OI led to alterations in the gut microbiota and promoted the production of microbiota-derived metabolites associated with neurogenesis. We further confirmed that OI promoted endogenous neurogenesis and inhibited neuronal apoptosis in the hippocampal dentate gyrus of aged mice. Mechanistically, we observed a decrease in Nrf2 expression in hippocampal neurons both in vitro and in vivo, which was reversed by OI treatment. We found that Nrf2 was required for OI treatment to inhibit neuroinflammation in POCD. The enhanced POCD recovery and promotion of neurogenesis triggered by OI exposure were, at least partially, mediated by the activation of the Nrf2/ERK signaling pathway. Conclusions Our findings demonstrate that OI can attenuate anesthesia/surgery-induced cognitive impairment by stabilizing the gut microbiota and activating Nrf2 signaling to restrict neuroinflammation and promote neurogenesis. Boosting endogenous itaconate or supplementation with exogenous itaconate derivatives may represent novel strategies for the treatment of POCD.

Abstract Background and aims Sorafenib is a major nonsurgical option for patients with advanced hepatocellular carcinoma (HCC); however, its clinical efficacy is largely undermined by the acquisition of resistance. The aim of this study was to identify the key lncRNA involved in the regulation of the sorafenib response in HCC. Materials and methods A clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) single-guide RNA (sgRNA) synergistic activation mediator (SAM)-pooled lncRNA library was applied to screen for the key lncRNA regulated by sorafenib treatment. The role of the identified lncRNA in mediating the sorafenib response in HCC was examined in vitro and in vivo. The underlying mechanism was delineated by proteomic analysis. The clinical significance of the expression of the identified lncRNA was evaluated by multiplex immunostaining on a human HCC microtissue array. Results CRISPR/Cas9 lncRNA library screening revealed that Linc01056 was among the most downregulated lncRNAs in sorafenib-resistant HCC cells. Knockdown of Linc01056 reduced the sensitivity of HCC cells to sorafenib, suppressing apoptosis in vitro and promoting tumour growth in mice in vivo. Proteomic analysis revealed that Linc01056 knockdown in sorafenib-treated HCC cells induced genes related to fatty acid oxidation (FAO) while repressing glycolysis-associated genes, leading to a metabolic switch favouring higher intracellular energy production. FAO inhibition in HCC cells with Linc01056 knockdown significantly restored sensitivity to sorafenib. Mechanistically, we determined that PPARα is the critical molecule governing the metabolic switch upon Linc01056 knockdown in HCC cells and indeed, PPARα inhibition restored the sorafenib response in HCC cells in vitro and HCC tumours in vivo. Clinically, Linc01056 expression predicted optimal overall and progression-free survival outcomes in HCC patients and predicted a better sorafenib response. Linc01056 expression indicated a low FAO level in HCC. Conclusion Our study identified Linc01056 as a critical epigenetic regulator and potential therapeutic target in the regulation of the sorafenib response in HCC.

Abstract Bolt looseness may occur on wind turbine (WT) blades exposed to operational and environmental variability conditions, which sometimes can cause catastrophic consequences. Therefore, it is necessary to monitor the loosening state of WT blade root bolts. In order to solve this problem, this paper proposes a method to monitor the looseness of blade root bolts using the sensors installed on the WT blade. An experimental platform was first built by installing acceleration and strain sensors for monitoring bolt looseness. Through the physical experiment of blade root bolts' looseness, the response data of blade sensors is then obtained under different bolt looseness numbers and degrees. Afterwards, the sensor signal of the blade root bolts is analyzed in time domain, frequency domain, and time‐frequency domain, and the sensitivity features of various signals are extracted. So the eigenvalue category as the input of the state discrimination model was determined. The LightGBM (light gradient boosting machine) classification algorithm was applied to identify different bolt looseness states for the multi‐domain features. The impact of different combinations of sensor categories and quantities as the data source on the identification results is discussed, and a reference for the selection of sensors is provided. The proposed method can discriminate four bolt states at an accuracy of around 99.8% using 5‐fold cross‐validation.

Abstract In this study, the ecological impact of human activities and the space occupied by construction and arable land on the Tibetan Plateau were examined, focusing on changes in the net primary productivity (NPP) as a key indicator of ecological health. With the utilization of land use data and multiyear average NPP data from 2002 to 2020, we analyzed the effects of the conversion of zonal vegetation into construction and arable land on carbon sequestration and oxygen release in Chengguan District, Lhasa city. Our findings indicated a marked spatial difference in the NPP among different land types. Regarding the original zonal vegetation, the NPP ranged from 0.2 to 0.3 kg/m2. Construction land showed a decrease in the NPP, with values ranging from 0.16 to 0.26 kg/m2, suggesting a decrease in ecological productivity. Conversely, arable land exhibited an increase in the NPP, with average values exceeding 0.3 kg/m2. This increase suggested enhanced productivity, particularly in regions where the original zonal vegetation provided lower NPP values. However, this enhanced productivity may not necessarily indicate a positive ecological change. In fact, such increases could potentially disrupt the natural balance of ecosystems, leading to unforeseen ecological consequences. The original zonal vegetation, with NPP values ranging from 0.12 to 0.43 kg/m2, exhibited higher ecological stability and adaptability than the other land types. This wider NPP range emphasizes the inherent resilience of native vegetation, which could sustain diverse ecological functions under varying environmental conditions. These findings demonstrate the urgent need for sustainable land use management on the Tibetan Plateau. This study highlights the importance of considering the ecological impact of land use changes in regional development strategies, ensuring the preservation and enhancement in the unique and fragile plateau ecosystem.