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Abstract Human genetics analysis has identified many noncoding SNPs associated with diabetic traits, but whether and how these variants contribute to diabetes is largely unknown. Here, we focus on a noncoding variant, rs6048205, and report that the risk-G variant impairs the generation of PDX1+/NKX6-1+ pancreatic progenitor cells and further results in the abnormal decrease of functional β cells during pancreatic differentiation. Mechanistically, this risk-G variant greatly enhances RXRA binding and over-activates FOXA2 transcription, specifically in the pancreatic progenitor stage, which in turn represses NKX6-1 expression. Consistently, inducible FOXA2 overexpression could phenocopy the differentiation defect. More importantly, mice carrying risk-G exhibit abnormal pancreatic islet architecture and are more sensitive to streptozotocin or a high-fat diet to develop into diabetes eventually. This study not only identifies a causal noncoding variant in diabetes susceptibility but also dissects the underlying gain-of-function mechanism by recruiting stage-specific factors.

Abstract Gliomas are the most common primary malignant tumours of the central nervous system (CNS), which are highly aggressive, with increasing morbidity and mortality rates year after year, posing a serious threat to the quality and expected survival time of patients. The treatment of gliomas is a major challenge in the field of neuro-oncology, especially high-grade gliomas such as glioblastomas (GBMs). Despite considerable progress in recent years in the study of the molecular and cellular mechanisms of GBMs, their prognosis remains bleak. Tumour-associated macrophages (TAMs) account for up to 50% of GBMs, and they are a highly heterogeneous cell population whose role cannot be ignored. Here, we focus on reviewing the contribution of classically activated M1-phenotype TAMs and alternatively activated M2-phenotype TAMs to GBMs, and exploring the research progress in reprogramming M1 TAMs into M2 TAMs.

Abstract Background We aimed to pinpoint biomarkers, create a diagnostic model for ulcerative colitis (UC), and delve into its immune features to better understand this autoimmune condition. Methods The sequencing data for both the UC and the control groups were obtained from GEO, including both bulk and single-cell data. Using GSE87466 as training group, we applied differential analysis, WGCNA, PPI, LASSO, RF, and SVM-RFE for biomarker selection. A neural network shaped our diagnostic model, corroborated by GSE92415 as the validation cohort with ROC assessment. Immune cell profiling was conducted using CIBERSORT. Results 53 disease-associated genes were screened. Enrichment analysis highlighted roles in complement cascades and cell adhesion. Eight biomarkers were finally identified through multiple machine learning and PPI: B4GALNT2, PDZK1IP1, FAM195A, REG4, MTMR11, FLJ35024, CD55, and CD44. The diagnostic model had AUCs of 0.984 (training group) and 0.957 (validation group). UC tissues revealed heightened plasma cells, CD8 T cells, and other immune cells. Two unique UC immune patterns emerged, with certain T and NK cells central to immune modulation. Conclusion We identified eight biomarkers of UC by various methods, constructed a diagnostic model through neural networks, and explored the immune complexity of the disease, which contributes to the diagnosis and treatment of UC.

Abstract Chronic obstructive pulmonary disease (COPD), a progressive inflammatory condition of the airways, emerges from the complex interplay between genetic predisposition and environmental factors. Notably, its incidence is on the rise, particularly among the elderly demographic. Current research increasingly highlights cellular senescence as a key driver in chronic lung pathologies. Despite this, the detailed mechanisms linking COPD with senescent genomic alterations remain elusive. To address this gap, there is a pressing need for comprehensive bioinformatics methodologies that can elucidate the molecular intricacies of this link. This approach is crucial for advancing our understanding of COPD and its association with cellular aging processes. Utilizing a spectrum of advanced bioinformatics techniques, this research delved into the potential mechanisms linking COPD with aging-related genes, identifying four key genes (EP300, MTOR, NFE2L1, TXN) through machine learning and weighted gene co-expression network analysis (WGCNA) analyses. Subsequently, a precise diagnostic model leveraging an artificial neural network was developed. The study further employed single-cell analysis and molecular docking to investigate senescence-related cell types in COPD tissues, particularly focusing on the interactions between COPD and NFE2L1, thereby enhancing the understanding of COPD's molecular underpinnings. Leveraging artificial neural networks, we developed a robust classification model centered on four genes—EP300, MTOR, NFE2L1, TXN—exhibiting significant predictive capability for COPD and offering novel avenues for its early diagnosis. Furthermore, employing various single-cell analysis techniques, the study intricately unraveled the characteristics of senescence-related cell types in COPD tissues, enriching our understanding of the disease's cellular landscape. This research anticipates offering novel biomarkers and therapeutic targets for early COPD intervention, potentially alleviating the disease's impact on individuals and healthcare systems, and contributing to a reduction in global COPD-related mortality. These findings carry significant clinical and public health ramifications, bolstering the foundation for future research and clinical strategies in managing and understanding COPD.

Abstract To evaluate the efficacy of neuronavigation-assisted stereotactic drilling drainage compared with that of craniotomy in the treatment of massive intracerebral haemorrhage (ICH) in elderly patients. This was a randomized, controlled, blind endpoint clinical study. Elderly patients with massive ICH treated at our neurosurgery department, without the formation of brain herniation preoperatively, all underwent neurosurgical intervention. Patients were randomly assigned to two groups: the minimally invasive surgery (MIS) group, which received neuronavigation-assisted stereotactic drilling drainage, and the craniotomy haematoma removal surgery (CHRS) group. Patient characteristics, surgical anaesthesia methods, surgery duration, intraoperative bleeding volume, duration of ICU stay duration of hospital stay, complications, and modified Rankin scale (mRS) scores at 90 days posttreatment were compared between the two groups. Statistical analysis was performed on the collected data. A total of 67 patients were randomly assigned, with 33 (49.25%) in the MIS group and 34 (50.75%) in the CHRS group. Compared with the CHRS group, the MIS group had advantages, including the use of local anaesthesia, shorter surgery duration, less intraoperative bleeding, shorter ICU stay, and fewer complications (P 0.05). For elderly patients with massive ICH without brain herniation, stereotactic drilling drainage is a simple surgical procedure that can be performed under local anaesthesia. Patients treated with this approach seem to have better outcomes than those treated with craniotomy. In clinical practice, neuronavigation-assisted stereotactic drilling drainage is recommended for surgical treatment in elderly patients with massive ICH without brain herniation. Clinical trial registration number: NCT04686877

Abstract The early-life organ development and maturation shape the fundamental blueprint for later-life phenotype. However, a multi-organ proteome atlas from infancy to adulthood is currently not available. Herein, we present a comprehensive proteomic analysis of ten mouse organs (brain, heart, lung, liver, kidney, spleen, stomach, intestine, muscle and skin) at three crucial developmental stages (1-, 4- and 8-weeks after birth) acquired using data-independent acquisition mass spectrometry. We detect and quantify 11,533 protein groups across the ten organs and obtain 115 age-related differentially expressed protein groups that are co-expressed in all organs from infancy to adulthood. We find that spliceosome proteins prevalently play crucial regulatory roles in the early-life development of multiple organs, and detect organ-specific expression patterns and sexual dimorphism. This multi-organ proteome atlas provides a fundamental resource for understanding the molecular mechanisms underlying early-life organ development and maturation.

BackgroundAtherosclerosis, a complex chronic vascular disorder with multifactorial etiology, stands as the primary culprit behind consequential cardiovascular events, imposing a substantial societal and economic burden. Nevertheless, our current understanding of its pathogenesis remains imprecise. In this investigation, our objective is to establish computational models elucidating molecular-level markers associated with atherosclerosis. This endeavor involves the integration of advanced machine learning techniques and comprehensive bioinformatics analyses.Materials and methodsOur analysis incorporated data from three publicly available the Gene Expression Omnibus (GEO) datasets: GSE100927 (104 samples, 30,558 genes), which includes atherosclerotic lesions and control arteries from carotid, femoral, and infra-popliteal arteries of deceased organ donors; GSE43292 (64 samples, 23,307 genes), consisting of paired carotid endarterectomy samples from 32 hypertensive patients, comparing atheroma plaques and intact tissues; and GSE159677 (30,498 single cells, 33,538 genes), examining single-cell transcriptomes of calcified atherosclerotic core plaques and adjacent carotid artery tissues from patients undergoing carotid endarterectomy. Utilizing single-cell sequencing, highly variable atherosclerotic monocyte subpopulations were systematically identified. We analyzed cellular communication patterns with temporal dynamics. The bioinformatics approach Weighted Gene Co—expression Network Analysis (WGCNA) identified key modules, constructing a Protein-Protein Interaction (PPI) network from module-associated genes. Three machine-learning models derived marker genes, formulated through logistic regression and validated via convolutional neural network(CNN) modeling. Subtypes were clustered based on Gene Set Variation Analysis (GSVA) scores, validated through immunoassays.ResultsThree pivotal atherosclerosis-associated genes—CD36, S100A10, CSNK1A1—were unveiled, offering valuable clinical insights. Profiling based on these genes delineated two distinct isoforms: C2 demonstrated potent microbicidal activity, while C1 engaged in inflammation regulation, tissue repair, and immune homeostasis. Molecular docking analyses explored therapeutic potential for Estradiol, Zidovudine, Indinavir, and Dronabinol for clinical applications.ConclusionThis study introduces three signature genes for atherosclerosis, shaping a novel paradigm for investigating clinical immunological medications. It distinguishes the high biocidal C2 subtype from the inflammation-modulating C1 subtype, utilizing identified signature gene as crucial targets.

Pancreatic cancer (PC) is a very aggressive digestive system tumor, known for its high mortality rate, low cure rate, low survival rate and poor prognosis. In particular, pancreatic ductal adenocarcinoma (PADC), which accounts for more than 90% of PC cases, has an overall 5-year survival rate of only 5%, which is an extremely critical situation. Early detection and effective treatment of PC is extremely difficult, which leads many patients to despair. In the current medical context, targeted therapy, as an important strategy for cancer treatment, is expected. However, the problems of immune escape and drug resistance in PC have become two major obstacles that are difficult to be overcome by targeted therapy. How to break through these two difficulties has become a key issue to be solved in the field of PC therapy. In recent years, non-coding RNAs (ncRNAs) have continued to heat up in the field of cancer research. NcRNAs play a pivotal role in gene regulation, cell differentiation, development, and disease processes, and their important roles in the genesis, development, and therapeutic response of PC have been gradually revealed. More importantly, ncRNAs have many advantages as therapeutic targets, such as high specificity and low side effects, making them a new favorite in the field of PC therapy. Therefore, the aim of this paper is to provide new ideas and methods for the targeted therapy of PC by reviewing the mechanism of action of four major ncRNAs (circRNAs, lncRNAs, miRNAs, siRNAs) in both immune escape and drug resistance of PC. It is expected that an effective way to overcome immune escape and drug resistance can be found through in-depth study of ncRNA, bringing a ray of hope to PC patients.

Rational heterostructure design can bring interfacial polarization relaxation to significantly enhance the electromagnetic wave (EMW) absorption performance. However, intelligently building a homogeneous heterostructure with superior EMW absorption properties remains a great challenge. Herein, a typical conductive metal–organic framework Cu3(HHTP)2 (hexahydroxytriphenylene, HHTP) is delicately packed onto a polypyrrole (PPy) conductive polymer surface via a one‐step in situ polymerization approach. Results show that Cu3(HHTP)2 is well packed on the PPy surface to form an elegant Cu3(HHTP)2@PPy hybrids interfacial microstructure with a unique superiority regarding EMW absorption compared with single components of PPy and Cu3(HHTP)2. Interestingly, the interfacial microstructure of Cu3(HHTP)2@PPy hybrids can be tuned by adjusting the composition of the PPy and Cu3(HHTP)2, resulting in the improvement of impedance matching, conductive loss, and enhancement of interfacial polarization relaxation, endowing the optimization of the EM wave absorption properties of the Cu3(HHTP)2@PPy. The broad effective absorption bandwidth covers a range as broad as 6.68 GHz (11.00–17.68 GHz), which is higher than most reported metal‐organic frameworks (MOFs) and conductive polymer‐based EM absorbing materials. Herein, new insight for developing highly efficient EMW absorption materials through hybridized interfacial microstructure engineering is provided.

Abstract Alzheimer’s disease (AD) is a serious brain disorder characterized by the presence of beta-amyloid plaques, tau pathology, inflammation, neurodegeneration, and cerebrovascular dysfunction. The presence of chronic neuroinflammation, breaches in the blood-brain barrier (BBB), and increased levels of inflammatory mediators are central to the pathogenesis of AD. These factors promote the penetration of immune cells into the brain, potentially exacerbating clinical symptoms and neuronal death in AD patients. While microglia, the resident immune cells of the central nervous system (CNS), play a crucial role in AD, recent evidence suggests the infiltration of cerebral vessels and parenchyma by peripheral immune cells, including neutrophils, T lymphocytes, B lymphocytes, NK cells, and monocytes in AD. These cells participate in the regulation of immunity and inflammation, which is expected to play a huge role in future immunotherapy. Given the crucial role of peripheral immune cells in AD, this article seeks to offer a comprehensive overview of their contributions to neuroinflammation in the disease. Understanding the role of these cells in the neuroinflammatory response is vital for developing new diagnostic markers and therapeutic targets to enhance the diagnosis and treatment of AD patients.

BackgroundColorectal cancer (CRC) poses a global health threat, with the oral microbiome increasingly implicated in its pathogenesis. This study leverages Mendelian Randomization (MR) to explore causal links between oral microbiota and CRC using data from the China National GeneBank and Biobank Japan. By integrating multi-omics approaches, we aim to uncover mechanisms by which the microbiome influences cellular metabolism and cancer development.MethodsWe analyzed microbiome profiles from 2017 tongue and 1915 saliva samples, and GWAS data for 6692 CRC cases and 27178 controls. Significant bacterial taxa were identified via MR analysis. Single-cell RNA sequencing and enrichment analyses elucidated underlying pathways, and drug predictions identified potential therapeutics.ResultsMR identified 19 bacterial taxa significantly associated with CRC. Protective effects were observed in taxa like RUG343 and Streptococcus_umgs_2425, while HOT-345_umgs_976 and W5053_sp000467935_mgs_712 increased CRC risk. Single-cell RNA sequencing revealed key pathways, including JAK-STAT signaling and tyrosine metabolism. Drug prediction highlighted potential therapeutics like Menadione Sodium Bisulfite and Raloxifene.ConclusionThis study establishes the critical role of the oral microbiome in colorectal cancer development, identifying specific microbial taxa linked to CRC risk. Single-cell RNA sequencing and drug prediction analyses further elucidate key pathways and potential therapeutics, providing novel insights and personalized treatment strategies for CRC.

Backgroundpancreatic ductal adenocarcinoma (PDAC) is a malignant tumor with a very poor prognosis and a complex tumor microenvironment, which plays a key role in tumor progression and treatment resistance. Glycosylation plays an important role in processes such as cell signaling, immune response and protein stability.Materials and methodssingle-cell RNA sequencing data and spatial transcriptome data were obtained from GSE197177 and GSE224411, respectively, and RNA-seq data and survival information were obtained from UCSC Xena and TCGA. Multiple transcriptomic data were comprehensively analyzed to explore the role of glycosylation processes in tumor progression, and functional experiments were performed to assess the effects of MGAT1 overexpression on PDAC cell proliferation and migration.ResultsIn PDAC tumor samples, the glycosylation level of macrophages was significantly higher than that of normal samples. MGAT1 was identified as a key glycosylation-related gene, and its high expression was associated with better patient prognosis. Overexpression of MGAT1 significantly inhibited the proliferation and migration of PDAC cells and affected intercellular interactions in the tumor microenvironment.ConclusionMGAT1 plays an important role in PDAC by regulating glycosylation levels in macrophages, influencing tumor progression and improving prognosis.MGAT1 is a potential therapeutic target for PDAC and further studies are needed to develop targeted therapeutic strategies against MGAT1 to improve clinical outcomes.

Abstract Spatial proteomics elucidates cellular biochemical changes with unprecedented topological level. Imaging mass cytometry (IMC) is a high-dimensional single-cell resolution platform for targeted spatial proteomics. However, the precision of subsequent clinical analysis is constrained by imaging noise and resolution. Here, we propose SpiDe-Sr, a super-resolution network embedded with a denoising module for IMC spatial resolution enhancement. SpiDe-Sr effectively resists noise and improves resolution by 4 times. We demonstrate SpiDe-Sr respectively with cells, mouse and human tissues, resulting 18.95%/27.27%/21.16% increase in peak signal-to-noise ratio and 15.95%/31.63%/15.52% increase in cell extraction accuracy. We further apply SpiDe-Sr to study the tumor microenvironment of a 20-patient clinical breast cancer cohort with 269,556 single cells, and discover the invasion of Gram-negative bacteria is positively correlated with carcinogenesis markers and negatively correlated with immunological markers. Additionally, SpiDe-Sr is also compatible with fluorescence microscopy imaging, suggesting SpiDe-Sr an alternative tool for microscopy image super-resolution.

BackgroundClear Cell Renal Cell Carcinoma (ccRCC) is the most common type of kidney cancer, characterized by high heterogeneity and complexity. Recent studies have identified mitochondrial defects and autophagy as key players in the development of ccRCC. This study aims to delve into the changes in mitophagic activity within ccRCC and its impact on the tumor microenvironment, revealing its role in tumor cell metabolism, development, and survival strategies.MethodsComprehensive analysis of ccRCC tumor tissues using single cell sequencing and spatial transcriptomics to reveal the role of mitophagy in ccRCC. Mitophagy was determined to be altered among renal clear cells by gene set scoring. Key mitophagy cell populations and key prognostic genes were identified using NMF analysis and survival analysis approaches. The role of UBB in ccRCC was also demonstrated by in vitro experiments.ResultsCompared to normal kidney tissue, various cell types within ccRCC tumor tissues exhibited significantly increased levels of mitophagy, especially renal clear cells. Key genes associated with increased mitophagy levels, such as UBC, UBA52, TOMM7, UBB, MAP1LC3B, and CSNK2B, were identified, with their high expression closely linked to poor patient prognosis. Particularly, the ubiquitination process involving the UBB gene was found to be crucial for mitophagy and its quality control.ConclusionThis study highlights the central role of mitophagy and its regulatory factors in the development of ccRCC, revealing the significance of the UBB gene and its associated ubiquitination process in disease progression.

Abstract Single cell western blot (scWB) is one of the most important methods for cellular heterogeneity profiling. However, current scWB based on conventional photoactive polyacrylamide hydrogel material suffers from the tradeoff between in‐gel probing and separation resolution. Here, a highly sensitive temperature‐controlled single‐cell western blotting (tc‐scWB) method is introduced, which is based on a thermo/photo‐dualistic‐sensitive polyacrylamide hydrogel, namely acrylic acid‐functionalized graphene oxide (AFGO) assisted, N‐isopropylacrylamide modified polyacrylamide (ANP) hydrogel. The ANP hydrogel is contracted at high‐temperature to constrain protein band diffusion during microchip electrophoretic separation, while the gel aperture is expanded under low‐temperature for better antibody penetration into the hydrogel. The tc‐scWB method enables the separation and profiling of small‐molecule‐weight proteins with highly crosslinked gel (12% T) in SDS‐PAGE. The tc‐scWB is demonstrated on three metabolic and ER stress‐specific proteins (CHOP, MDH2 and FH) in four pancreatic cell subtypes, revealing the expression of key enzymes in the Krebs cycle is upregulated with enhanced ER stress. It is found that ER stress can regulate crucial enzyme (MDH2 and FH) activities of metabolic cascade in cancer cells, boosting aerobic respiration to attenuate the Warburg effect and promote cell apoptosis. The tc‐scWB is a general toolbox for the analysis of low‐abundance small‐molecular functional proteins at the single‐cell level.

PHD (plant homeodomain) finger proteins emerge as central epigenetic readers and modulators in cancer biology, orchestrating a broad spectrum of cellular processes pivotal to oncogenesis and tumor suppression. This review delineates the dualistic roles of PHD fingers in cancer, highlighting their involvement in chromatin remodeling, gene expression regulation, and interactions with cellular signaling networks. PHD fingers’ ability to interpret specific histone modifications underscores their influence on gene expression patterns, impacting crucial cancer-related processes such as cell proliferation, DNA repair, and apoptosis. The review delves into the oncogenic potential of certain PHD finger proteins, exemplified by PHF1 and PHF8, which promote tumor progression through epigenetic dysregulation and modulation of signaling pathways like Wnt and TGFβ. Conversely, it discusses the tumor-suppressive functions of PHD finger proteins, such as PHF2 and members of the ING family, which uphold genomic stability and inhibit tumor growth through their interactions with chromatin and transcriptional regulators. Additionally, the review explores the therapeutic potential of targeting PHD finger proteins in cancer treatment, considering their pivotal roles in regulating cancer stem cells and influencing the immune response to cancer therapy. Through a comprehensive synthesis of current insights, this review underscores the complex but promising landscape of PHD finger proteins in cancer biology, advocating for further research to unlock novel therapeutic avenues that leverage their unique cellular roles.

PurposeTraditional Chinese medicine (TCM) therapies, especially acupuncture, have received increasing attention in the field of pain management. This meta-analysis evaluated the effectiveness of acupuncture in the treatment of myofascial pain syndrome.MethodsA comprehensive search was conducted across a number of databases, including PubMed, Cochrane Library, WOS, CNKI, WANFANG, Sinomed, and VIP. Furthermore, articles of studies published from the inception of these databases until November 22, 2023, were examined. This systematic review and meta-analysis encompassed all randomized controlled trials (RCTs) on acupuncture for myofascial pain syndromes, without language or date restrictions. Based on the mean difference (MD) of symptom change, we critically assessed the outcomes reported in these trials. The quality of evidence was assessed using the Cochrane Risk of Bias Tool. The study is registered with PROSPERO under registration number CRD42023484933.ResultsOur analysis included 10 RCTs in which 852 patients were divided into two groups: an acupuncture group (427) and a control group (425). The results of the study showed that acupuncture was significantly more effective than the control group in treating myofascial pain syndromes, which was reflected in a greater decrease in VAS scores (MD = −1.29, 95% [−1.65, −0.94], p

PurposeIn recent years, traditional Chinese medicine has received widespread attention in the field of cancer pain treatment. This meta-analysis is the first to evaluate the effectiveness and safety of acupuncture point stimulation in the treatment of stomach cancer pain.MethodsFor this systematic review and meta-analysis, we searched PubMed, Web of Science, Cochrane Library, Embase, WANFANG, China National Knowledge Infrastructure (CNKI), and Chinese Journal of Science and Technology (VIP) databases as well as forward and backward citations to studies published between database creation to July 27, 2023. All randomized controlled trials (RCTs) on acupuncture point stimulation for the treatment of patients with stomach cancer pain were included without language restrictions. We assessed all outcome indicators of the included trials. The evidence from the randomized controlled trials was synthesized as the standardized mean difference (SMD) of symptom change. The quality of the evidence was assessed using the Cochrane Risk of Bias tool. This study is registered on PROSPERO under the number CRD42023457341.ResultsEleven RCTs were included. The study included 768 patients, split into 2 groups: acupuncture point stimulation treatment group (n = 406), medication control group (n = 372). The results showed that treatment was more effective in the acupuncture point stimulation treatment group than in the medication control group (efficacy rate, RR = 1.63, 95% CI 1.37 to 1.94, p

Aiming at the requirements of the marine work platform for real-time control, time-varying speed and the time-varying torque control of the motor-driven active heave compensation device, this paper introduces a composite control strategy based on the switched reluctance motor (SRM)-driven active heave compensation device. As for the compensation error caused by the time lag in the real-time system, the model prediction trajectory algorithm is used to predict the compensation displacement obtained using the dynamic model. The next time, the control parameters are then provided for the SRM control system in advance to reduce the compensation error. The SRM control strategy selects a double closed-loop compound control strategy of Back Propagation (BP) fuzzy neural network Proportion Integration Differentiation (PID) control. Its outer speed loop uses a fuzzy controller to quickly track a wide range of speed changes. The torque inner loop uses BP neural network adaptive PID control. This helps to reduce torque ripple and to ensure that the electromagnetic torque output of the SRM remains stable. Finally, the system feasibility is verified by setting different wave parameters. The simulation results show that the simulation conditions can reach 97.5% and 96.4% under the 3 and 4 wave levels, respectively. The simulation effect is satisfying, which verifies the feasibility of the proposed scheme.

The mechanical properties of woven jute fiber-reinforced PLA polymer laminates additively manufactured through Laminated Object Manufacturing (LOM) technology are simulated using the finite element method in this work. Woven jute fiber reinforcements are used to strengthen bio-thermoplastic PLA polymers in creating highly biodegradable composite structures that can serve as one of the environmentally friendly alternatives for synthetic composites. A LOM 3D printer prototype was designed and built by the authors. All woven jute/PLA biocomposite laminated specimens made using the built prototype in this study had their tensile and flexural properties measured using ASTM test standards. These laminated structures were modeled using the ANSYS Mechanical Composite PrepPost (ACP) module, and then both testing processes were simulated using the experimentally measured input values. The FEA simulation results indicated a close match with experimental results, with a maximum difference of 9.18%. This study served as an exemplary case study using the FEA method to predict the mechanical behaviors of biocomposite laminate materials made through a novel manufacturing process.

In order to comprehensively describe and evaluate Chinese olive seeds, this study examined 33 varieties (strains) of Chinese olive seeds to address the limitations of previous research on quantitative trait variation and grading among Chinese olive seed varieties (strains). The research specifically focused on evaluating the morphological characteristics, seed locule structure, embryo composition, and phenotypic quantitative traits of Chinese olive seeds. The results indicated that Chinese olive seeds consisted of a core, seed coat, and embryo. Typically, the core contained two to four locules, with each locule containing zero to one embryos. Eight distinct structural variations were identified, with the number of locules per seed ranging from two to four and the number of embryos ranging from one to four. The most common structural types were ‘3-locule 1-embryo’ and ‘3-locule 2-embryo’, each occurring in 100% of the varieties (strains) studied. These two structural types also had a high average proportion within each variety (line), accounting for 50.17% and 42.06%, respectively. The average dimensions of a seed were 31.20 mm in length and 10.89 mm in width, with a shape index of 2.89 and weighing 1.55 g. These quantitative traits displayed significant variation, with the coefficient of variation being highest for single seed weight (19.35%) and lowest for seed length (9.39%). Normality tests revealed that seed width, seed length, and single seed weight followed a normal distribution. These traits were categorized into five levels based on specific points, with probabilities of occurrence approximately 10%, 20%, 40%, 20%, and 10%, respectively. The findings of this study are crucial for understanding and utilizing Chinese olive seed traits and provide valuable insights for the establishment of seed trait standards and data normalization.

Background: Atelectasis is a commonly observed postoperative complication of general anesthesia in children. Pulmonary protective ventilation strategies have been reported to have a beneficial effect on postoperative atelectasis in children. Therefore, the present study aimed to evaluate the efficacy of the ultrasound-guided transversus abdominis plane (TAP) block technique in preventing the incidence of postoperative atelectasis in children. Materials and methods: This study enrolled 100 consecutive children undergoing elective laparoscopic bilateral hernia repair and randomly divided them into the control and TAP groups. Conventional lung-protective ventilation was initiated in both groups after the induction of general anesthesia. The children in the TAP group received an ultrasound-guided TAP block with 0.3 mL/kg of 0.5% ropivacaine after the induction of anesthesia. Results: Anesthesia-induced atelectasis was observed in 24% and 84% of patients in the TAP (n = 50) and control (n = 50) groups, respectively, before discharge from the post-anesthetic care unit (T3; PACU) (odds ratio [OR], 0.062; 95% confidence interval [CI], 0.019–0.179; P

PurposeIn the realm of pain management, traditional Chinese medicine, specifically acupuncture, has garnered increasing attention. This meta-analysis pioneers the evaluation of acupuncture’s effectiveness in treating insomnia among hypertensive patients.MethodsWe conducted a comprehensive search across several databases—PubMed, Web of Science, Cochrane Library, WANFANG, China National Knowledge Infrastructure (CNKI), Sinomed, and the Chinese Journal of Science and Technology (VIP). Additionally, forward and backward articles of studies published from the inception of these databases until 10 September 2023, were reviewed. This systematic review and meta-analysis included all randomized controlled trials (RCTs) focusing on acupuncture for insomnia in hypertensive patients, without imposing language or date restrictions. We rigorously assessed all outcome measures reported in these trials. The evidence was synthesized by calculating the difference between mean differences (MD) in symptom change. The quality of the evidence was determined using the Cochrane Risk of Bias tool. This study is registered with PROSPERO under number CRD42023461760.ResultsOur analysis included 16 RCTs, comprising 1,309 patients. The findings revealed that acupuncture was significantly more effective than the control group in reducing insomnia symptoms, as indicated by a greater decrease in the PSQI score (MD = −3.1, 95% CI [−3.77 to −2.62], p

This study was conducted to evaluate the effects of phytosterols (PS) and phytosterol esters (PSE) on C57BL/6 mice. Three groups of 34 six-week-old C57BL/6 mice of specific pathogen free (SPF) grade, with an average initial body weight (IBW) of 17.7g, were fed for 24 days either natural-ingredient diets without supplements or diets supplemented with 89 mg/kg PS or diets supplemented with 400 mg/kg PSE. Growth performance, blood biochemistry, liver and colon morphology as well as intestinal flora status were evaluated. Both PS and PSE exhibited growth promotion and feed digestibility in mice. In blood biochemistry, the addition of both PS and PSE to the diet resulted in a significant decrease in Total Cholesterol (TC) and Triglyceride (TG) levels and an increase in Superoxide Dismutase (SOD) activity. No significant changes in liver and intestinal morphology were observed. Both increased the level of Akkermansia in the intestinal tract of mice. There was no significant difference between the effects of PS and PSE. It was concluded that dietary PS and PSE supplementation could improve growth performance, immune performance and gut microbiome structure in mice, providing insights into its application as a potential feed additive in animals production.

A nanoparticle’s shape is a critical determinant of its biological interactions and therapeutic effectiveness. This study investigates the influence of shape on the performance of mesoporous silica nanoparticles (MSNs) in anticancer therapy. MSNs with spherical, rod-like, and hexagonal-plate-like shapes were synthesized, with particle sizes of around 240 nm, and their other surface properties were characterized. The drug loading capacities of the three shapes were controlled to be 47.46%, 49.41%, and 46.65%, respectively. The effects of shape on the release behaviors, cellular uptake mechanisms, and pharmacological behaviors of MSNs were systematically investigated. Through a series of in vitro studies using 4T1 cells and in vivo evaluations in 4T1 tumor-bearing mice, the release kinetics, cellular behaviors, pharmacological effects, circulation profiles, and therapeutic efficacy of MSNs were comprehensively assessed. Notably, hexagonal-plate-shaped MSNs loaded with PTX exhibited a prolonged circulation time (t1/2 = 13.59 ± 0.96 h), which was approximately 1.3 times that of spherical MSNs (t1/2 = 10.16 ± 0.38 h) and 1.5 times that of rod-shaped MSNs (t1/2 = 8.76 ± 1.37 h). This research underscores the significance of nanoparticles’ shapes in dictating their biological interactions and therapeutic outcomes, providing valuable insights for the rational design of targeted drug delivery systems in cancer therapy.

Partially impaired sensor arrays pose a significant challenge in accurately estimating signal parameters. The occurrence of bad data is highly probable, resulting in random loss of source information and substantial performance degradation in parameter estimation. In this paper, a tensor variational sparse Bayesian learning (TVSBL) method is proposed for the estimate of direction of arrival (DOA) and polarization parameters jointly based on a conformal polarization sensitive array (CPSA), taking into account scenarios with the partially impaired sensor array. First, a sparse tensor-based received data model is developed for CPSAs that incorporates bad data. Then, a column vector detection method is proposed to diagnose the positions of the impaired sensors. In scenarios involving partially impaired sensor arrays, a low-rank matrix completion method is employed to recover the random loss of signal information. Finally, variational sparse Bayesian learning (VSBL) and minimum eigenvector methods are utilized sequentially to obtain the DOA and polarization parameters estimation, successively. Furthermore, the Cramér-Rao bound is given for the proposed method. Simulation results validated the effectiveness of the proposed method.

BackgroundClear cell renal carcinoma (ccRCC) stands as the prevailing subtype among kidney cancers, making it one of the most prevalent malignancies characterized by significant mortality rates. Notably,mitochondrial permeability transition drives necrosis (MPT-Driven Necrosis) emerges as a form of cell death triggered by alterations in the intracellular microenvironment. MPT-Driven Necrosis, recognized as a distinctive type of programmed cell death. Despite the association of MPT-Driven Necrosis programmed-cell-death-related lncRNAs (MPTDNLs) with ccRCC, their precise functions within the tumor microenvironment and prognostic implications remain poorly understood. Therefore, this study aimed to develop a novel prognostic model that enhances prognostic predictions for ccRCC.MethodsEmploying both univariate Cox proportional hazards and Lasso regression methodologies, this investigation distinguished genes with differential expression that are intimately linked to prognosis.Furthermore, a comprehensive prognostic risk assessment model was established using multiple Cox proportional hazards regression. Additionally, a thorough evaluation was conducted to explore the associations between the characteristics of MPTDNLs and clinicopathological features, tumor microenvironment, and chemotherapy sensitivity, thereby providing insights into their interconnectedness.The model constructed based on the signatures of MPTDNLs was verified to exhibit excellent prediction performance by Cell Culture and Transient Transfection, Transwell and other experiments.ResultsBy analyzing relevant studies, we identified risk scores derived from MPTDNLs as an independent prognostic determinant for ccRCC, and subsequently we developed a Nomogram prediction model that combines clinical features and associated risk assessment. Finally, the application of experimental techniques such as qRT-PCR helped to compare the expression of MPTDNLs in healthy tissues and tumor samples, as well as their role in the proliferation and migration of renal clear cell carcinoma cells. It was found that there was a significant correlation between CDK6-AS1 and ccRCC results, and CDK6-AS1 plays a key role in the proliferation and migration of ccRCC cells. Impressive predictive results were generated using marker constructs based on these MPTDNLs.ConclusionsIn this research, we formulated a new prognostic framework for ccRCC, integrating mitochondrial permeability transition-induced necrosis. This model holds significant potential for enhancing prognostic predictions in ccRCC patients and establishing a foundation for optimizing therapeutic strategies.

HBV infection profoundly escalates hepatocellular carcinoma (HCC) susceptibility, responsible for a majority of HCC cases. HBV-driven immune-mediated hepatocyte impairment significantly fuels HCC progression. Regrettably, inconspicuous early HCC symptoms often culminate in belated diagnoses. Nevertheless, surgically treated early-stage HCC patients relish augmented five-year survival rates. In contrast, advanced HCC exhibits feeble responses to conventional interventions like radiotherapy, chemotherapy, and surgery, leading to diminished survival rates. This investigation endeavors to unearth diagnostic hallmark genes for HBV-HCC leveraging a bioinformatics framework, thus refining early HBV-HCC detection. Candidate genes were sieved via differential analysis and Weighted Gene Co-Expression Network Analysis (WGCNA). Employing three distinct machine learning algorithms unearthed three feature genes (HHIP, CXCL14, and CDHR2). Melding these genes yielded an innovative Artificial Neural Network (ANN) diagnostic blueprint, portending to alleviate patient encumbrance and elevate life quality. Immunoassay scrutiny unveiled accentuated immune damage in HBV-HCC patients relative to solitary HCC. Through consensus clustering, HBV-HCC was stratified into two subtypes (C1 and C2), the latter potentially indicating milder immune impairment. The diagnostic model grounded in these feature genes showcased robust and transferrable prognostic potentialities, introducing a novel outlook for early HBV-HCC diagnosis. This exhaustive immunological odyssey stands poised to expedite immunotherapeutic curatives' emergence for HBV-HCC.

Background: Colon cancer, a prevalent and deadly malignancy worldwide, ranks as the third leading cause of cancer-related mortality. Disulfidptosis stress triggers a unique form of programmed cell death known as disulfidoptosis, characterized by excessive intracellular cystine accumulation. This study aimed to establish reliable bioindicators based on long non-coding RNAs (LncRNAs) associated with disulfidptosis-induced cell death, providing novel insights into immunotherapeutic response and prognostic assessment in patients with colon adenocarcinoma (COAD).Methods: Univariate Cox proportional hazard analysis and Lasso regression analysis were performed to identify differentially expressed genes strongly associated with prognosis. Subsequently, a multifactorial model for prognostic risk assessment was developed using multiple Cox proportional hazard regression. Furthermore, we conducted comprehensive evaluations of the characteristics of disulfidptosis response-related LncRNAs, considering clinicopathological features, tumor microenvironment, and chemotherapy sensitivity. The expression levels of prognosis-related genes in COAD patients were validated using quantitative real-time fluorescence PCR (qRT-PCR). Additionally, the role of ZEB1-SA1 in colon cancer was investigated through CCK8 assays, wound healing experiment and transwell experiments.Results: disulfidptosis response-related LncRNAs were identified as robust predictors of COAD prognosis. Multifactorial analysis revealed that the risk score derived from these LncRNAs served as an independent prognostic factor for COAD. Patients in the low-risk group exhibited superior overall survival (OS) compared to those in the high-risk group. Accordingly, our developed Nomogram prediction model, integrating clinical characteristics and risk scores, demonstrated excellent prognostic efficacy. In vitro experiments demonstrated that ZEB1-SA1 promoted the proliferation and migration of COAD cells.Conclusion: Leveraging medical big data and artificial intelligence, we constructed a prediction model for disulfidptosis response-related LncRNAs based on the TCGA-COAD cohort, enabling accurate prognostic prediction in colon cancer patients. The implementation of this model in clinical practice can facilitate precise classification of COAD patients, identification of specific subgroups more likely to respond favorably to immunotherapy and chemotherapy, and inform the development of personalized treatment strategies for COAD patients based on scientific evidence.

ObjectiveTo realize the dynamic visualization of forensic odontology based on the bibliometrics methods, and capture the research hotspots and identify the future development trend.MethodsLiterature articles published from January 1995 to December 2020 were searched according to specific subject words in the core data set of Web of Science. The visualization analysis of publishing country, institution, discipline, author, co-cited journal and keywords was performed by CiteSpace 5.7.R5W software.ResultsThe annual analysis of publications showed an upward trend of forensic odontology research literature year by year, with the number of annual publications more than 110 in the last five years. Developed countries were the main source of contributions and the average centrality was greater than 0.2. The research of forensic odontology involved multiple disciplines, including stomatology, biology, computer science and medical imaging, with a distinct interdisciplinary feature. A total of 115 nodes were obtained by keyword cluster analysis. The principal line of forensic odontology mainly included individual identification and age estimation and the emergence of hotspots was closely related to new technologies. Population-based odontology investigation, improvement of traditional dental age estimation method and dental age estimation based on new technology were popular research in forensic odontology.ConclusionDeveloping countries urgently need to increase the focus on related research. It may be an important direction for the development of forensic odontology to establish and enrich the regional dental database, develop new odontology identification technology combined with frontier and high-end technology, and develop the identification program based on advanced information technology.

Lungs are structurally and functionally complex organs consisting of diverse cell types from the proximal to distal axis. They have direct contact with the external environment and are constantly at risk of various injuries. Capable to proliferate and differentiate, pulmonary endogenous progenitor stem cells contribute to the maintenance of lung structure and function both under homeostasis and following injuries. Discovering candidate pulmonary endogenous progenitor stem cell types and underlying regenerative mechanisms provide insights into therapeutic strategy development for lung diseases. In this review, we reveal their compositions, roles in lung disease pathogenesis and injury repair, and the underlying mechanisms. We further underline the advanced progress in research approach and potential therapy for lung regeneration. We also demonstrate the feasibility and prospects of pulmonary endogenous stem cell transplantation for lung disease treatment.

Abstract The conformal polarization sensitive array (CPSA) is formed by placing some vector sensors on the conformal array and it has a wide range of practical application in direction of arrival (DOA) and polarization parameters estimation. However, due to the diversity of each sensor’s direction, the performance of the conventional parameters estimation methods based on the CPSA would decrease greatly, especially under the low signal to noise ratio (SNR) and limited snapshots. In order to solve this problem, a unified framework and sparse reconstruction perspective for joint DOA and polarization estimation based on CPSA is proposed in this paper. Specifically, the array received signal model of the CPSA is formulated first and the two-dimensional spatial sparsity of the incident signals is then exploited. Subsequently, after employing the singular value decomposition method to reduce the dimension of array output matrix, the variational sparse Bayesian learning and orthogonal matching pursuit methods are utilized to solve the source DOA estimation, respectively. Finally, the polarization parameters are obtained by the minimum eigenvector method. Simulation results demonstrate that the novel approaches can provide improved estimation accuracy and resolution with low SNR and limited snapshots.

Abstract Extracellular vesicle (EV) surface proteins, expressed by primary tumours, are important biomarkers for early cancer diagnosis. However, the detection of these EV proteins is complicated by their low abundance and interference from non‐EV components in clinical samples. Herein, we present a MEmbrane‐Specific Separation and two‐step Cascade AmpLificatioN (MESS2CAN) strategy for direct detection of EV surface proteins within 4 h. MESS2CAN utilises novel lipid probes (long chains linked by PEG2K with biotin at one end, and DSPE at the other end) and streptavidin‐coated magnetic beads, permitting a 49.6% EV recovery rate within 1 h. A dual amplification strategy with a primer exchange reaction (PER) cascaded by the Cas12a system then allows sensitive detection of the target protein at 10 EV particles per microliter. Using 4 cell lines and 90 clinical test samples, we demonstrate MESS2CAN for analysing HER2, EpCAM and EGFR expression on EVs derived from cells and patient plasma. MESS2CAN reports the desired specificity and sensitivity of EGFR (AUC = 0.98) and of HER2 (AUC = 1) for discriminating between HER2‐positive breast cancer, triple‐negative breast cancer and healthy donors. MESS2CAN is a pioneering method for highly sensitive in vitro EV diagnostics, applicable to clinical samples with trace amounts of EVs.

Background: Hepatitis B-related liver cirrhosis (HBV-LC) is a common clinical disease that evolves from chronic hepatitis B (CHB). The development of cirrhosis can be suppressed by pharmacological treatment. When CHB progresses to HBV-LC, the patient’s quality of life decreases dramatically and drug therapy is ineffective. Liver transplantation is the most effective treatment, but the lack of donor required for transplantation, the high cost of the procedure and post-transplant rejection make this method unsuitable for most patients.Methods: The aim of this study was to find potential diagnostic biomarkers associated with HBV-LC by bioinformatics analysis and to classify HBV-LC into specific subtypes by consensus clustering. This will provide a new perspective for early diagnosis, clinical treatment and prevention of HCC in HBV-LC patients. Two study-relevant datasets, GSE114783 and GSE84044, were retrieved from the GEO database. We screened HBV-LC for feature genes using differential analysis, weighted gene co-expression network analysis (WGCNA), and three machine learning algorithms including least absolute shrinkage and selection operator (LASSO), support vector machine recursive feature elimination (SVM-RFE), and random forest (RF) for a total of five methods. After that, we constructed an artificial neural network (ANN) model. A cohort consisting of GSE123932, GSE121248 and GSE119322 was used for external validation. To better predict the risk of HBV-LC development, we also built a nomogram model. And multiple enrichment analyses of genes and samples were performed to understand the biological processes in which they were significantly enriched. And the different subtypes of HBV-LC were analyzed using the Immune infiltration approach.Results: Using the data downloaded from GEO, we developed an ANN model and nomogram based on six feature genes. And consensus clustering of HBV-LC classified them into two subtypes, C1 and C2, and it was hypothesized that patients with subtype C2 might have milder clinical symptoms by immune infiltration analysis.Conclusion: The ANN model and column line graphs constructed with six feature genes showed excellent predictive power, providing a new perspective for early diagnosis and possible treatment of HBV-LC. The delineation of HBV-LC subtypes will facilitate the development of future clinical treatment of HBV-LC.

BackgroundPancreatic cancer (PC) is a lethal malignancy that ranks seventh in terms of global cancer-related mortality. Despite advancements in treatment, the five-year survival rate remains low, emphasizing the urgent need for reliable early detection methods. MicroRNAs (miRNAs), a group of non-coding RNAs involved in critical gene regulatory mechanisms, have garnered significant attention as potential diagnostic and prognostic biomarkers for pancreatic cancer (PC). Their suitability stems from their accessibility and stability in blood, making them particularly appealing for clinical applications.MethodsIn this study, we analyzed serum miRNA expression profiles from three independent PC datasets obtained from the Gene Expression Omnibus (GEO) database. To identify serum miRNAs associated with PC incidence, we employed three machine learning algorithms: Support Vector Machine-Recursive Feature Elimination (SVM-RFE), Least Absolute Shrinkage and Selection Operator (LASSO), and Random Forest. We developed an artificial neural network model to assess the accuracy of the identified PC-related serum miRNAs (PCRSMs) and create a nomogram. These findings were further validated through qPCR experiments. Additionally, patient samples with PC were classified using the consensus clustering method.ResultsOur analysis revealed three PCRSMs, namely hsa-miR-4648, hsa-miR-125b-1-3p, and hsa-miR-3201, using the three machine learning algorithms. The artificial neural network model demonstrated high accuracy in distinguishing between normal and pancreatic cancer samples, with verification and training groups exhibiting AUC values of 0.935 and 0.926, respectively. We also utilized the consensus clustering method to classify PC samples into two optimal subtypes. Furthermore, our investigation into the expression of PCRSMs unveiled a significant negative correlation between the expression of hsa-miR-125b-1-3p and age.ConclusionOur study introduces a novel artificial neural network model for early diagnosis of pancreatic cancer, carrying significant clinical implications. Furthermore, our findings provide valuable insights into the pathogenesis of pancreatic cancer and offer potential avenues for drug screening, personalized treatment, and immunotherapy against this lethal disease.

ObjectiveThe aim of this study was to evaluate the effects of stereotactic minimally invasive puncture with different catheter placement positions when combined with urokinase thrombolysis for the treatment of small- and medium-volume basal ganglia hemorrhage. Our goal was to identify the best minimally invasive catheter placement position to enhance therapeutic efficacy for patients with cerebral hemorrhage.MethodsThe stereotactic minimally invasive thrombolysis at different catheter positions in the treatment of small- and medium-volume basal ganglia hemorrhage (SMITDCPI) was a randomized, controlled, and endpoint phase 1 trial. We recruited patients with spontaneous ganglia hemorrhage (medium-to-small and medium volume) who were treated in our hospital. All patients received stereotactic, minimally invasive punctures combined with an intracavitary thrombolytic injection of urokinase hematoma. A randomized number table method was used to divide the patients into two groups concerning the location of catheterization: a penetrating hematoma long-axis group and a hematoma center group. The general conditions of the two groups of patients were compared, and the data were analyzed, including the time of catheterization, the dosage of urokinase, the amount of residual hematoma, the hematoma clearance rate, complications, and the National Institute of Health stroke scale (NIHSS) score data at 1 month after surgery.ResultsBetween June 2019 and March 2022, 83 patients were randomly recruited and assigned to the two groups as follows: 42 cases (50.60%) to the penetrating hematoma long-axis group and 41 cases (49.40%) to the hematoma center group. Compared with the hematoma center group, the long-axis group was associated with a significantly shorter catheterization time, a lower urokinase dose, a lower residual hematoma volume, a higher hematoma clearance rate, and fewer complications (P < 0.05). However, there were no significant differences between the two groups in terms of the NIHSS scores when tested 1 month after surgery (P > 0.05).ConclusionStereotactic minimally invasive puncture combined with urokinase for the treatment of small- and medium-volume hemorrhage in the basal ganglia, including catheterization through the long axis of the hematoma, led to significantly better drainage effects and fewer complications. However, there was no significant difference in short-term NIHSS scores between the two types of catheterization.

The study of the suitability of prehistoric human settlements (SPHE) can help us reproduce the process and characteristics of prehistoric human settlements, and is an important entry point for exploring the relationship between prehistoric humans and land. In this study, we discuss the definition, compositional structure, evolutionary mechanism, and spatiotemporal representation of the suitability of prehistoric human settlements, and propose its main research lines and possible research contents. We believe that the suitability of prehistoric human settlement environments refers to the ability and process of natural and social environmental conditions to meet the needs of human survival within a certain spatial range centered on the settlement of prehistoric humans. Additionally, with the temporal and spatial evolution of humans, society, and nature, it shows local consistency and global gradual and continuous change characteristics, and the human settlement environment has a suitability hierarchy of natural original, livelihood, and living spaces nested step by step. We believe that we can adopt the main research line of prehistoric human settlement suitability system construction to conduct extensive experiments and demonstrations on the theoretical construction, the evolution of the environment and living process, the relationship and evaluation of prehistoric human needs, the transformation of the living environment, living adaptation theories and models, and value and limitation verification. Thus, a complete research system can be formed to explore the evolution of the prehistoric human–land relationship.

IntroductionCampylobacter jejuni (C. jejuni) is a common food-borne bacterial pathogen that can use the host’s innate immune response to induce the development of colitis. There has been some research on the role of normal intestinal flora in C. jejuni-induced colitis, but the mechanisms that play a central role in resistance to C. jejuni infection have not been explored.MethodsWe treated Campylobacter jejuni-infected mice with fecal microbiota transplantation (FMT), oral butyric acid and deoxycholic acid in a controlled trial and analyzed the possible mechanisms of treatment by a combination of chromatography, immunohistochemistry, fluorescence in situ hybridization, 16s rRNA gene, proteomics and western blot techniques.ResultsWe first investigated the therapeutic effect of FMT on C. jejuni infection. The results showed that FMT significantly reduced the inflammatory response and blocked the invasion of C.jejuni into the colonic tissue. We observed a significant increase in the abundance of Akkermansia in the colon of mice after FMT, as well as a significant increase in the levels of butyric acid and deoxycholic acid. We next demonstrated that oral administration of sodium butyrate or deoxycholic acid had a similar therapeutic effect. Further proteomic analysis showed that C.jejuni induced colitis mainly through activation of the PI3K-AKT signaling pathway and MAPK signaling pathway, whereas Akkermansia, the core flora of FMT, and the gut microbial metabolites butyric acid and deoxycholic acid both inhibited these signaling pathways to counteract the infection of C. jejuni and alleviate colitis. Finally, we verified the above idea by in vitro cellular assays. In conclusion, FMT is highly effective in the treatment of colitis caused by C. jejuni, with which Akkermansia and butyric and deoxycholic acids are closely associated.The present study demonstrates that Akkermansia and butyric and deoxycholic acids are effective in the treatment of colitis caused by C. jejuni.DiscussionThis is the first time that Akkermansia has been found to be effective in fighting pathogens, which provides new ideas and insights into the use of FMT to alleviate colitis caused by C. jejuni and Akkermansia as a treatment for intestinal sexually transmitted diseases caused by various pathogens.

Shifts in tree species and their mycorrhizal associations driven by global change play key roles in biogeochemical cycles. In this paper, we proposed a framework of the mycorrhizal-associated nutrient economy (MANE), and tested it using nutrient addition experiments conducted in two tropical rainforests. We selected two tropical rainforests dominated by arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) trees, and established eighteen 20 ​m ​× ​20 ​m plots in each rainforest. Six nitrogen (N) and phosphorus (P) addition treatments were randomly distributed in each rainforest with three replicates. We examined the differences in soil carbon (C) and nutrient cycling, plant and litter productivity between the two rainforests and their responses to 10-year inorganic N and P additions. We also quantified the P pools of plants, roots, litter, soil and microbes in the two rainforests. Overall, distinct MANE frameworks were applicable for tropical rainforests, in which soil C, N and P were cycled primarily in an inorganic form in the AM-dominated rainforest, whereas they were cycled in an organic form in the ECM-dominated rainforest. Notably, the effects of mycorrhizal types on soil P cycling were stronger than those on C and N cycling. The intensified N and P deposition benefited the growth of AM-dominated rainforests instead of ECM-dominated rainforests. Our findings underpin the key role of mycorrhizal types in regulating biogeochemical processes, and have important implications for predicting the ecological consequences of global changes.

Sepsis-associated encephalopathy (SAE), a major cerebral complication of sepsis, occurs in 70% of patients admitted to the intensive care unit (ICU). This condition can cause serious impairment of consciousness and is associated with a high mortality rate. Thus far, several experimental screenings and radiological techniques (e.g., electroencephalography) have been used for the non-invasive assessment of the structure and function of the brain in patients with SAE. Nevertheless, the pathogenesis of SAE is complicated and remains unclear. In the present article, we reviewed the currently available literature on the epidemiology, clinical manifestations, pathology, diagnosis, and management of SAE. However, currently, there is no ideal pharmacological treatment for SAE. Treatment targeting mitochondrial dysfunction may be useful in the management of SAE.

Genetic risk scores (GRS) and polygenic risk scores (PRS) are weighted sums of, respectively, several or many genetic variant indicator variables. Although they are being increasingly proposed for clinical use, the best ways to construct them are still actively debated. In this commentary, we present several case studies illustrating practical challenges associated with building or attempting to improve score performance when there is expected to be heterogeneity of disease risk between cohorts or between subgroups of individuals. Specifically, we contrast performance associated with several ways of selecting single nucleotide polymorphisms (SNPs) for inclusion in these scores. By considering GRS and PRS as predictors that are measured with error, insights into their strengths and weaknesses may be obtained, and SNP selection approaches play an important role in defining such errors.

ObjectiveWe aimed to construct and validate machine learning models for endotracheal tube (ETT) size prediction in pediatric patients.MethodsData of 990 pediatric patients underwent endotracheal intubation were retrospectively collected between November 2019 and October 2021, and separated into cuffed and uncuffed endotracheal tube subgroups. Six machine learning algorithms, including support vector regression (SVR), logistic regression (LR), random forest (RF), gradient boosting tree (GBR), decision tree (DTR) and extreme gradient boosting tree (XGBR), were selected to construct and validate models using ten-fold cross validation in training set. The optimal models were selected, and the performance were compared with traditional predictive formulas and clinicians. Furthermore, additional data of 71 pediatric patients were collected to perform external validation.ResultsThe optimal 7 uncuffed and 5 cuffed variables were screened out by feature selecting. The RF models had the best performance with minimizing prediction error for both uncuffed ETT size (MAE = 0.275 mm and RMSE = 0.349 mm) and cuffed ETT size (MAE = 0.243 mm and RMSE = 0.310 mm). The RF models were also superior in predicting power than formulas in both uncuffed and cuffed ETT size prediction. In addition, the RF models performed slightly better than senior clinicians, while they significantly outperformed junior clinicians. Based on SVR models, we proposed 3 novel linear formulas for uncuffed and cuffed ETT size respectively.ConclusionWe have developed machine learning models with excellent performance in predicting optimal ETT size in both cuffed and uncuffed endotracheal intubation in pediatric patients, which provides powerful decision support for clinicians to select proper ETT size. Novel formulas proposed based on machine learning models also have relatively better predictive performance. These models and formulas can serve as important clinical references for clinicians, especially for performers with rare experience or in remote areas.

Abstract Background Minimally invasive surgery has achieved good results in the treatment of cerebral haemorrhage.However, no large-scale clinical study has demonstrated that surgical treatment of cerebral haemorrhages less than 30 ml can improve the curative effect. Our study explored the efficacy and complication of stereotactic drainage based on the amount of cerebral hemorrhage (15-30 ml) in hypertensive basal ganglia. Method Sixty patients with hypertensive basal ganglia haemorrhages were divided into a control group and an experimental group with 30 patients in each group. Patients in the control group were treated conservatively. In contrast, those in the experimental group received stereotactic drainage, and urokinase was injected into the haematoma cavity after the operation. The haematoma volume at admission and 1, 3, 7 and 30 days after treatment and National Institute of Health stroke scale(NIHSS) score data were recorded. Complications after treatment in the two groups of data were compared and analysed. Result No significant differences in age, sex, time of treatment after onset, admission blood pressure, admission haematoma volume or admission NIHSS score were noted between these two groups (P > 0.05). After treatment, significant differences in haematoma volume were noted between the two groups on the 1st, 3rd, 7th and 30th days after treatment (P

BackgroundScalp nerve block (SNB) is widely used for postoperative pain control, intraoperative hemodynamic control, and opioid-sparing in adult craniotomies. However, there are few studies of SNB in pediatric patients undergoing craniotomy. In the present study, we aimed to investigate the effect of SNB on postoperative pain, intraoperative hemodynamic stability, and narcotic consumption in pediatric craniotomy under general anesthesia.MethodsThis trial is a single-center, prospective, randomized, and double-blind study. A total of 50 children aged between 2 and 12 years who are undergoing elective brain tumor surgery will be randomly allocated in a 1:1 ratio to receive either 0.2% ropivacaine for SNB (group SNB, intervention group, n = 25) or the same volume of saline (group Ctrl, control group, n = 25). The primary outcome was to assess the score of postoperative pain intensity at time 1, 4, 8, 12, 24, and 48 h postoperatively using the FLACC score method. Secondary outcomes were to record intraoperative hemodynamic variables (MAP and HR) during skull-pin fixation, skin incision and end of skin closure, intraoperative total consumption of remifentanil and propofol, postoperative opioid consumption, and the incidence of postoperative nausea and vomiting.ResultsFifty patients were analyzed (n = 25 in SNB group; n = 25 in control group). Compared to the control group, postoperative pain intensity was significantly relieved in the SNB group up to 8 h post-operatively. In addition, SNB provided good intraoperative hemodynamic stability, reduced intraoperative overall propofol and remifentanil consumption rate, and postoperative fentanyl consumption compared to the control group. However, the incidence of postoperative nausea and vomiting was not different between SNB and the control group.ConclusionsIn pediatric craniotomies, SNB with 0.2% ropivacaine provides adequate postoperative pain control and good intraoperative hemodynamic stability during noxious events compared to the control group.Clinical trial registrationChinese Clinical Trial Registry [No: ChiCTR2100050594], Prospective registration.

BackgroundRegional lymph node metastasis (LNM) is crucial for planning additional lymphadenectomy, and is directly correlated with poor prognosis in gastroenteropancreatic neuroendocrine tumors (GEP-NETs). However, the patterns of LNM for small (≤20 mm) GEP-NETs remain unclear. This population-based study aimed at evaluating LNM patterns and identifying optimal surgical strategies from the standpoint of lymph node dissemination.MethodsThis retrospective cohort study retrieved data from the Surveillance, Epidemiology, and End Results (SEER) 18 registries database for 17,308 patients diagnosed as having localized well-differentiated GEP-NETs ≤ 20 mm between January 1, 2004, and December 31, 2017. The patterns of LNM were characterized in 6,622 patients who underwent extended resection for adequate lymph node harvest.ResultsOf 6,622 patients with localized small GEP-NETs in the current study, 2,380 (36%) presented with LNM after regional lymphadenectomy. Nodal involvement was observed in approximately 7.4%, 49.1%, 13.6%, 53.7%, 13.8%, 7.8%, and 15.4% of gastric (g-), small intestinal (si-), appendiceal (a-), colonic (c-), rectal (r-), non-functional pancreatic (nfp-), and functional pancreatic (fp-) NETs ≤ 20 mm. Patients with younger age, larger tumor size, and muscularis invasion were more likely to present with LNM. Additional lymphadenectomy conferred a significant survival advantage in NETs (≤10 mm: HR, 0.47; 95% CI, 0.33–0.66; p < 0.001; 11–20 mm: HR, 0.54; 95% CI, 0.34–0.85; p = 0.008) and fp-NETs ≤ 20 mm (HR, 0.08; 95% CI, 0.02–0.36; p = 0.001), as well as g-NETs (HR, 0.39; 95% CI, 0.16–0.96; p = 0.041) and c-NETs of 11–20 mm (HR, 0.07; 95% CI, 0.01–0.48; p = 0.007). Survival benefits of additional lymphadenectomy were not found in a-NETs, r-NETs, and nfp-NETs with a small size.ConclusionsGiven the increased risk for nodal metastasis, primary tumor resection with regional lymphadenectomy is a potential optimal surgical strategy for si-NETs and fp-NETs ≤ 20 mm, as well as g-NETs and c-NETs of 11–20 mm. Local resection is an appropriate and reliable surgical approach for a-NETs, r-NETs, and nfp-NETs ≤ 20 mm.

Acute respiratory distress syndrome (ARDS), a devastating complication of numerous conditions, is often associated with high mortality. It is well known that endothelial cell (EC) damage and inflammation are vital processes in the pathogenesis of ARDS. Nevertheless, the mechanisms of EC damage are largely unknown. In the present study, we investigated the role of pyroptosis in the initiation of ARDS and demonstrated that endothelial pyroptosis might play a pivotal role in the pathophysiology of ARDS. Metformin, an antidiabetic drug, exhibited a protective effect in lipopolysaccharide (LPS)-induced lung injury, and we hypothesized that metformin alleviated LPS-induced lung injury via inhibiting ECs pyroptosis. In vivo, male ICR mice were intratracheally injected with LPS, and metformin was previously administered intraperitoneally. Morphological properties of lung tissues were detected. We showed that metformin inhibited NLRP3 inflammasome activation and NLRP3-stimulated pyroptosis induction, as shown by decreased levels of cleaved caspase-1, N-terminal fragment of GSDMD, and protein contents of IL-1β in lung tissues of mice exposed to LPS. LPS-induced expression of vascular adhesion molecules was also reduced after the treatment with metformin. In vitro, exposure of pulmonary ECs to LPS resulted in increased expression of NLRP3 and pyroptosis-associated indicators. By inhibiting the expression of NLRP3 with NLRP3 inhibitor MCC950, pyroptosis-related markers and vascular adhesion molecules were ameliorated. Moreover, metformin treatment significantly inhibited the NF-κB signaling pathway and increased the expression of sirtuin 1 (SIRT1) both in LPS-stimulated lung tissues and pulmonary ECs. Administration of the selective SIRT1 inhibitor nicotinamide significantly reversed the protective effect of metformin against endothelial pyroptosis and lung injury in LPS-treated ECs and LPS-induced acute lung injury (ALI). Thus, these findings demonstrated that metformin alleviated LPS-induced ALI by inhibiting NF-κB-NLRP3–mediated ECs pyroptosis, possibly by upregulating the expression of SIRT1.

Abstract Background Neuropsychiatric symptoms (NPS) are increasingly recognized as early non-cognitive manifestations in the Alzheimer’s disease (AD) continuum. However, the role of NPS as an early marker of pathophysiological progression in AD remains unclear. Dominantly inherited AD (DIAD) mutation carriers are young individuals who are destined to develop AD in future due to the full penetrance of the genetic mutation. Hence, the study of DIAD mutation carriers enables the evaluation of the associations between pure AD pathophysiology and metabolic correlates of NPS without the confounding effects of co-existing pathologies. In this longitudinal study, we aimed to identify regional brain metabolic dysfunctions associated with NPS in cognitively intact DIAD mutation carriers. Methods We stratified 221 cognitively intact participants from the Dominantly Inherited Alzheimer’s Network according to their mutation carrier status. The interactions of NPS measured by the Neuropsychiatric Inventory-Questionnaire (NPI-Q), age, and estimated years to symptom onset (EYO) as a function of metabolism measured by [18F]flurodeoxyglucose ([18F]FDG) positron emission tomography, were evaluated by the mixed-effects regression model with family-level random effects in DIAD mutation carriers and non-carriers. Exploratory factor analysis was performed to identify the neuropsychiatric subsyndromes in DIAD mutation carriers using the NPI-Q sub-components. Then the effects of interactions between specific neuropsychiatric subsyndromes and EYO on metabolism were evaluated with the mixed-effects regression model. Results A total of 119 mutation carriers and 102 non-carriers were studied. The interaction of higher NPI-Q and shorter EYO was associated with more rapid declines of global and regional [18F]FDG uptake in the posterior cingulate and ventromedial prefrontal cortices, the bilateral parietal lobes and the right insula in DIAD mutation carriers. The neuropsychiatric subsyndromes of agitation, disinhibition, irritability and depression interacted with the EYO to drive the [18F]FDG uptake decline in the DIAD mutation carriers. The interaction of NPI and EYO was not associated with [18F]FDG uptake in DIAD mutation non-carriers. Conclusions The NPS in cognitively intact DIAD mutation carriers may be a clinical indicator of subsequent metabolic decline in brain networks vulnerable to AD, which supports the emerging conceptual framework that NPS represent early manifestations of neuronal injury in AD. Further studies using different methodological approaches to identify NPS in preclinical AD are needed to validate our findings.