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Abstract Background Gallbladder cancer (GBC) is characterized by high mortality rate. Our study sought therapeutic candidates for GBC. Results Bioinformatics analysis identified significant upregulation of MST1R in GBC. In vitro experiments demonstrated that the MST1R inhibitor MGCD-265 effectively restrained GBC cell proliferation at lower concentrations. Additionally, it induced cycle arrest and apoptosis in GBC cells in a dose-dependent manner. Mouse models exhibited that MGCD-265 treatment significantly diminished the proliferative capacity of GBC-SD cells. Transcriptomics sequencing revealed significant transcriptome alterations, with 200 transcripts upregulated and 883 downregulated. KEGG and GO analyses highlighted enrichment in processes like cell adhesion and pathways such as protein digestion and absorption. Downstream genes analysis identified JMJD6 upregulation post-MGCD-265 treatment. In vivo experiments confirmed that combining MGCD-265 with the JMJD6 inhibitor SKLB325 enhanced the anticancer effect against GBC. Conclusion Overall, targeting MST1R and its downstream genes, particularly combining MGCD-265 with SKLB325, holds promise as a therapeutic strategy for GBC.

Abstract Background Disulfidptosis is a newly identified mechanism of cell death triggered by disulfide stress. Thus, gaining a comprehensive understanding of the disulfidptosis signature present in gastric cancer (GC) could greatly enhance the development of personalized treatment strategies for this disease. Methods We employed consensus clustering to identify various subtypes of disulfidptosis and examined the distinct tumor microenvironment (TME) associated with each subtype. The Disulfidptosis (Dis) score was used to quantify the subtype of disulfidptosis in each patient. Subsequently, we assessed the predictive value of Dis score in terms of GC prognosis and immune efficacy. Finally, we conducted in vitro experiments to explore the impact of Collagen X (COL10A1) on the progression of GC. Results Two disulfidptosis-associated molecular subtypes (Discluster A and B) were identified, each with distinct prognosis, tumor microenvironment (TME), immune cell infiltration, and biological pathways. Discluster A, characterized by high expression of disulfidptosis genes, exhibited a high immune score but poor prognosis. Furthermore, the Dis score proved useful in predicting the prognosis and immune response in GC patients. Those in the low Dis score group showed better prognosis and increased sensitivity to immunotherapy. Finally, our experimental findings validated that downregulation of COL10A1 expression attenuates the proliferation and migration capabilities of GC cells while promoting apoptosis. Conclusions This study demonstrates that the disulfidptosis signature can assist in risk stratification and personalized treatment for patients with GC. The results offer valuable theoretical support for anti-tumor strategies.

Objectives The safety and analgesic efficacy of perioperative glucocorticoids have been established for patients without rheumatoid arthritis. Therefore, our study aims to investigate whether similar benefits can be observed in patients with rheumatoid arthritis undergoing total joint arthroplasty. Specifically, we aim to explore the impact of perioperative glucocorticoid use on postoperative complications, opioid consumption, incidence of hypotension, hyperglycemia, 30‐day mortality, and 90‐day re‐admission in this patient population. Methods Approval for the study protocol was obtained from the Medical Research Ethics Committee at Sichuan University, aligning with the principles outlined in the Declaration of Helsinki. We retrospectively analyzed a consecutive series of patients with rheumatoid arthritis who underwent total joint arthroplasty at our medical center between November 2009 and April 2021 and who were not on chronic glucocorticoid therapy before surgery. Those who received glucocorticoids at any time during hospitalization were compared to those who did not in terms of acute complications within 90 days after surgery as well as postoperative rescue opioid consumption, hypotension, and hyperglycemia during hospitalization. The two groups were also compared in terms of overall duration of hospitalization, all‐cause mortality within 30 days, and readmission for any reason within 90 days. Continuous data were assessed for significance using the independent‐samples t test. Categorical data were assessed using the Pearson chi‐squared test. Results Of the 849 patients included in the analysis, 598 administered perioperative glucocorticoids and 251 did not. Prior to surgery, the two groups did not differ significantly in any clinicodemographic variable that we examined. The incidence of acute postoperative complications (2.3% vs. 4.0%, p = 0.187) and acute postoperative infection (2.0% vs. 2.8%, p = 0.482) was comparable between those who received perioperative glucocorticoids and those who did not, but the former group exhibited a significantly lower incidence of rescue opioid use (17.9% vs. 44.6%, p

Objective: To investigate the effectiveness of the original oblique conformal anastomosis presented in this research in reducing the incidence of cervical anastomotic leak after performing totally minimally invasive esophagectomy (TMIE). Methods: The esophagus and stomach of 27 fresh pigs, termed the esophagogastric model, were used to simulate human esophagogastric organs for this study's in vitro experimental objectives. Nine esophagogastric models of similar weight were divided into three groups. Esophagogastrostomy with circular-stapled end-to-side anastomosis was performed. A tension gauge was used to pull the anastomosis, and the tension at which anastomotic leakage occurred was recorded. Furthermore, a retrospective assessment of 539 patients who underwent TMIE was conducted to analyze the influencing factors of cervical anastomotic leakage. Results: Experiments on the esophagogastric models showed a higher fracture strength of oblique conformal anastomosis than that of conventional anastomosis (F2,18 = 40.86, P

Abstract Currently, in vitro cultured corneal epithelial transplantation is effective in treating limbal stem cell dysfunction (LSCD). Selecting carriers is crucial for constructing the corneal epithelium through tissue engineering. In this study, the traditional amniotic membrane (AM) was modified, and mesenchymal stem cells (MSCs) were inoculated into the ultra-thin amniotic membrane (UAM) stroma to construct a novel UAM-MSC tissue-engineered corneal epithelial carrier, that could effectively simulate the limbal stem cells (LSCs) microenvironment. The structure of different carriers cultured tissue-engineered corneal epithelium and the managed rabbit LSCD model corneas were observed through hematoxylin–eosin staining. Cell phenotypes were evaluated through fluorescence staining, Western blotting, and RT-qPCR. Additionally, cell junction genes and expression markers related to anti-neovascularization were evaluated using RT-qPCR. Corneal epithelium cell junctions were observed via an electron microscope. The tissue-engineered corneal epithelium culture medium was analyzed through mass spectrometry. Tissue-engineered corneal epithelial cells expanded by LSCs on UAM-MSCs had good transparency. Simultaneously, progenitor cell (K14, PNCA, p63) and corneal epithelial (PAX6) gene expression in tissue-engineered corneal epithelium constructed using UAM-MSCs was higher than that in corneal epithelial cells amplified by UAM and de-epithelialized amniotic membrane. Electron microscopy revealed that corneal epithelial cells grafted with UAM-MSCs were closely connected. In conclusion, the UAM-MSCs vector we constructed could better simulate the limbal microenvironment; the cultured tissue-engineered corneal epithelium had better transparency, anti-neovascularization properties, closer intercellular connections, and closer resemblance to the natural corneal epithelial tissue phenotype.

Abstract Background Identifying rheumatoid arthritis patients at higher risk of complications after total hip arthroplasty could make perioperative management more effective. Here we examined whether disease activity is associated with risk of such complications. Methods We retrospectively analyzed data for 337 rheumatoid arthritis patients at our medical center who underwent primary total hip arthroplasty. Rheumatoid arthritis patients were categorized according to the simplified disease activity index (SDAI), the values of which at admission and follow-up were averaged together. Logistic regression was used to examine associations of mean SDAI with rates of dislocation, infection, periprosthetic fracture and aseptic loosening. As controls, 337 osteoarthritis patients who did not have systemic inflammation and who underwent the same procedure were matched across numerous clinicodemographic variables. Results Among the 337 rheumatoid arthritis patients, 38 (11.3%) had postoperative complications, the rates of which varied significantly from 0 to 17.5% (p = 0.003) among the four subgroups whose disease activity based on mean SDAI was categorized as high, moderate, low or in remission. Each 1-unit increase in mean SDAI was associated with a significant increase in risk of postoperative complications (OR 1.015, 95% CI 1.001–1.029, p = 0.035). Across all rheumatoid arthritis patients, rate of complications did not differ significantly between patients who received disease-modifying anti-rheumatic drugs or other treatments. Rates of dislocation, of infection or of all postoperative complications combined were significantly lower among osteoarthritis controls than among rheumatoid arthritis patients. Conclusion Greater mean SDAI is associated with higher risk of dislocation, infection and composite postoperative complications after total hip arthroplasty in rheumatoid arthritis patients. These patients show a significantly higher rate of postoperative complications than osteoarthritis patients, likely reflecting the influence of systemic inflammation. Disease activity should be reduced as much as possible in rheumatoid arthritis patients before they undergo total hip arthroplasty.

Abstract Background Ferroptosis is associated with the pathological progression of hemorrhagic injury and ischemia–reperfusion injury. According to our previous study, exosomes formed through bone marrow mesenchymal stem cells modified with miR-340-3p (MB-exos) can restore damaged endometrium. However, the involvement of ferroptosis in endometrial injury and the effect of MB-exos on ferroptosis remain elusive. Methods The endometrial injury rat model was developed. Exosomes were obtained from the supernatants of bone marrow mesenchymal stromal cells (BMSCs) and miR-340/BMSCs through differential centrifugation. We conducted RNA-seq analysis on endometrial tissues obtained from the PBS and MB-exos groups. Ferroptosis was induced in endometrial stromal cells (ESCs) by treating them with erastin or RSL3, followed by treatment with B-exos or MB-exos. We assessed the endometrial total m6A modification level after injury and subsequent treatment with B-exos or MB-exos by methylation quantification assay. We performed meRIP-qPCR to analyze m6A modification-regulated endogenous mRNAs. Results We reveal that MB-exos facilitate the injured endometrium to recover by suppressing ferroptosis in endometrial stromal cells. The injured endometrium showed significantly upregulated N 6-methyladenosine (m6A) modification levels; these levels were attenuated by MB-exos through downregulation of the methylase METTL3. Intriguingly, METTL3 downregulation appears to repress ferroptosis by stabilizing HMOX1 mRNA, thereby potentially elucidating the mechanism through which MB-exos inhibit ferroptosis in ESCs. We identified YTHDF2 as a critical m6A reader protein that contributes to HMOX1 mRNA degradation. YTHDF2 facilitates HMOX1 mRNA degradation by identifying the m6A binding site in the 3′-untranslated regions of HMOX1. In a rat model, treatment with MB-exos ameliorated endometrial injury-induced fibrosis by inhibiting ferroptosis in ESCs. Moreover, METTL3 short hairpin RNA-mediated inhibition of m6A modification enhanced the inhibitory effect of MB-exos on ferroptosis in endometrial injury. Conclusions Thus, these observations provide new insights regarding the molecular mechanisms responsible for endometrial recovery promotion by MB-exos and highlight m6A modification-dependent ferroptosis inhibition as a prospective therapeutic target to attenuate endometrial injury.

Abstract Emodin (EMO) has the effect of anti-cholestasis induced by alpha-naphthylisothiocyanate (ANIT). But its mechanism is still unclear. The farnesoid X receptor (Fxr) is the master bile acid nuclear receptor. Recent studies have reported that Sirtuin 1 (Sirt1) can regulate the activities of Fxr. The purpose of the current study was to investigate the mechanism of EMO against ANIT-induced liver injury based on Sirt1/Fxr signaling pathway. The ANIT-induced cholestatic rats were used with or without EMO treatment. Serum biochemical indicators, as well as liver histopathological changes were examined. The genes expressions of Sirt1, Fxr, Shp, Bsep and Mrp2 were detected. The expressions of Sirt1, Fxr and their downstream related genes were investigated in vitro. The results showed that EMO significantly alleviated ANIT-induced liver injury in rats, and increased Sirt1, Fxr, Shp, Bsep and Mrp2 gene expression in liver, while decreased the expression of Cyp7a1. EMO significantly activated Fxr, while Sirt1 inhibitor and Sirt1 gene silencing significantly reduced Fxr activity in vitro. Collectively, EMO in the right dose has a protective effect on liver injury induced by ANIT, and the mechanism may be through activation of Fxr by Sirt1, thus regulating bile acid metabolism, and reducing bile acid load in hepatocytes.

Abstract Group 3 innate lymphoid cells (ILC3) are crucial for maintaining mucosal homeostasis and regulating inflammatory diseases, but the molecular mechanisms governing their phenotype and function are not fully understood. Here, we show that ILC3s highly express Fcer1g gene, which encodes the antibody Fc-receptor common gamma chain, FcεR1γ. Genetic perturbation of FcεR1γ leads to the absence of critical cell membrane receptors NKp46 and CD16 in ILC3s. Alanine scanning mutagenesis identifies two residues in FcεR1γ that stabilize its binding partners. FcεR1γ expression in ILC3s is essential for effective protective immunity against bacterial and fungal infections. Mechanistically, FcεR1γ influences the transcriptional state and proinflammatory cytokine production of ILC3s, relying on the CD16-FcεR1γ signaling pathway. In summary, our findings highlight the significance of FcεR1γ as an adapter protein that stabilizes cell membrane partners in ILC3s and promotes anti-infection immunity.

The effects of Polymethacrylate (PMA)-series polar compounds on the friction and wear characteristics and on tribofilm formation in fully formulated low-viscosity engine oil have been studied. Optical microscopy, AFM, and element analyses by EPMA, AES, and XPS were used to determine the coexisting effects. The results showed that common additives in fully formulated (FF) oil had blocking effects that reduced the formation of ZnDTP-based tribofilm. PMA0 showed a blocking effect in preventing uniform tribofilm formation in FF low-viscosity oil. PMA-N showed comprehensive effects by forming a lower-quality uniform tribofilm in FF low-viscosity oil. PMA-OH and PMA-COOH showed a concerted effect by forming a lower S/P ratio and a higher Ca/Zn ratio uniform tribofilm in FF

Abstract Background L-theanine is a unique non-protein amino acid in tea that is widely used as a safe food additive. We investigated the cardioprotective effects and mechanisms of L-theanine in myocardial ischemia-reperfusion injury (MIRI). Methods The cardioprotective effects and mechanisms of L-theanine and the role of Janus Kinase 2 (JAK2)/signal transducer and activator of transcription 3 (STAT3) signaling were investigated in MIRI mice using measures of cardiac function, oxidative stress, and apoptosis. Results Administration of L-theanine (10 mg/kg, once daily) suppressed the MIRI-induced increase in infarct size and serum creatine kinase and lactate dehydrogenase levels, as well as MIRI-induced cardiac apoptosis, as evidenced by an increase in Bcl-2 expression and a decrease in Bax/caspase-3 expression. Administration of L-theanine also decreased the levels of parameters reflecting oxidative stress, such as dihydroethidium, malondialdehyde, and nitric oxide, and increased the levels of parameters reflecting anti-oxidation, such as total antioxidant capacity (T-AOC), glutathione (GSH), and superoxide dismutase (SOD) in ischemic heart tissue. Further analysis showed that L-theanine administration suppressed the MIRI-induced decrease of phospho-JAK2 and phospho-STAT3 in ischemic heart tissue. Inhibition of JAK2 by AG490 (5 mg/kg, once daily) abolished the cardioprotective effect of L-theanine, suggesting that the JAK2/STAT3 signaling pathway may play an essential role in mediating the anti-I/R effect of L-theanine. Conclusions L-theanine administration suppresses cellular apoptosis and oxidative stress in part via the JAK2/STAT3 signaling pathway, thereby attenuating MIRI-induced cardiac injury. L-theanine could be developed as a potential drug to alleviate cardiac damage in MIRI.

Timely inspection of defects on the surfaces of wind turbine blades can effectively prevent unpredictable accidents. To this end, this study proposes a semi-supervised object-detection network based on You Only Looking Once version 4 (YOLOv4). A semi-supervised structure comprising a generative adversarial network (GAN) was designed to overcome the difficulty in obtaining sufficient samples and sample labeling. In a GAN, the generator is realized by an encoder- decoder network, where the backbone of the encoder is YOLOv4 and the decoder comprises inverse convolutional layers. Partial features from the generator are passed to the defect detection network. Deploying several unlabeled images can significantly improve the generalization and recognition capabilities of defect-detection models. The small-scale object detection capacity of the network can be improved by enhancing essential features in the feature map by adding the concurrent spatial and channel squeeze and excitation (scSE) attention module to the three parts of the YOLOv4 network. A balancing improvement was made to the loss function of YOLOv4 to overcome the imbalance problem of the defective species. The results for both the single- and multi-category defect datasets show that the improved model can make good use of the features of the unlabeled images. The accuracy of wind turbine blade defect detection also has a significant advantage over classical object detection algorithms, including faster R-CNN and DETR.

Abstract This study aimed to develop a pan-genotypic and multifunctional small interfering RNA (siRNA) against hepatitis B virus (HBV) with an efficient delivery system for treating chronic hepatitis B (CHB), and explore combined RNA interference (RNAi) and immune modulatory modalities for better viral control. Twenty synthetic siRNAs targeting consensus motifs distributed across the whole HBV genome were designed and evaluated. The lipid nanoparticle (LNP) formulation was optimized by adopting HO-PEG2000-DMG lipid and modifying the molar ratio of traditional polyethylene glycol (PEG) lipid in LNP prescriptions. The efficacy and safety of this formulation in delivering siHBV (tLNP/siHBV) along with the mouse IL-2 (mIL-2) mRNA (tLNP/siHBVIL2) were evaluated in the rAAV-HBV1.3 mouse model. A siRNA combination (terms “siHBV”) with a genotypic coverage of 98.55% was selected, chemically modified, and encapsulated within an optimized LNP (tLNP) of high efficacy and security to fabricate a therapeutic formulation for CHB. The results revealed that tLNP/siHBV significantly reduced the expression of viral antigens and DNA (up to 3log10 reduction; vs PBS) in dose- and time-dependent manners at single-dose or multi-dose frequencies, with satisfactory safety profiles. Further studies showed that tLNP/siHBVIL2 enables additive antigenic and immune control of the virus, via introducing potent HBsAg clearance through RNAi and triggering strong HBV-specific CD4+ and CD8+ T cell responses by expressed mIL-2 protein. By adopting tLNP as nucleic acid nanocarriers, the co-delivery of siHBV and mIL-2 mRNA enables synergistic antigenic and immune control of HBV, thus offering a promising translational therapeutic strategy for treating CHB.

This paper proposes an improved You Only Look Once (YOLOv3) algorithm for automatically detecting damaged apples to promote the automation of the fruit processing industry. In the proposed method, a clustering method based on Rao-1 algorithm is introduced to optimize anchor box sizes. The clustering method uses the intersection over the union to form the objective function and the most representative anchor boxes are generated for normal and damaged apple detection. To verify the feasibility and effectiveness of the proposed method, real apple images collected from the Internet are employed. Compared with the generic YOLOv3 and Fast Region-based Convolutional Neural Network (Fast R-CNN) algorithms, the proposed method yields the highest mean average precision value for the test dataset. Therefore, it is practical to apply the proposed method for intelligent apple detection and classification tasks.

Abstract Dynamin-related protein 1 (Drp1) is a crucial regulator of mitochondrial dynamics, the overactivation of which can lead to cardiovascular disease. Multiple distinct posttranscriptional modifications of Drp1 have been reported, among which S-nitrosylation was recently introduced. However, the detailed regulatory mechanism of S-nitrosylation of Drp1 (SNO-Drp1) in cardiac microvascular dysfunction in diabetes remains elusive. The present study revealed that mitogen-activated protein kinase kinase kinase kinase 4 (MAP4K4) was consistently upregulated in diabetic cardiomyopathy (DCM) and promoted SNO-Drp1 in cardiac microvascular endothelial cells (CMECs), which in turn led to mitochondrial dysfunction and cardiac microvascular disorder. Further studies confirmed that MAP4K4 promoted SNO-Drp1 at human C644 (mouse C650) by inhibiting glutathione peroxidase 4 (GPX4) expression, through which MAP4K4 stimulated endothelial ferroptosis in diabetes. In contrast, inhibition of MAP4K4 via DMX-5804 significantly reduced endothelial ferroptosis, alleviated cardiac microvascular dysfunction and improved cardiac dysfunction in db/db mice by reducing SNO-Drp1. In parallel, the C650A mutation in mice abolished SNO-Drp1 and the role of Drp1 in promoting cardiac microvascular disorder and cardiac dysfunction. In conclusion, our findings demonstrate that MAP4K4 plays an important role in endothelial dysfunction in DCM and reveal that SNO-Drp1 and ferroptosis activation may act as downstream targets, representing potential therapeutic targets for DCM.

Abstract Doxorubicin (DOX) is a broad-spectrum and highly efficient anticancer agent, but its clinical implication is limited by lethal cardiotoxicity. Growing evidences have shown that alterations in intestinal microbial composition and function, namely dysbiosis, are closely linked to the progression of DOX-induced cardiotoxicity (DIC) through regulating the gut-microbiota-heart (GMH) axis. The role of gut microbiota and its metabolites in DIC, however, is largely unelucidated. Our review will focus on the potential mechanism between gut microbiota dysbiosis and DIC, so as to provide novel insights into the pathophysiology of DIC. Furthermore, we summarize the underlying interventions of microbial-targeted therapeutics in DIC, encompassing dietary interventions, fecal microbiota transplantation (FMT), probiotics, antibiotics, and natural phytochemicals. Given the emergence of microbial investigation in DIC, finally we aim to point out a novel direction for future research and clinical intervention of DIC, which may be helpful for the DIC patients.

Electrochemical water splitting faces challenges related to cost and efficiency, prompting researchers to develop new materials for cost reduction and efficiency enhancement. MXene Ti3C2Tx, with its large surface area and excellent conductivity, shows promising prospects for catalytic applications. Electrochemists have successfully utilized MXene Ti3C2Tx in catalysis, leveraging its ability to form heterojunction structures that enhance charge transfer and separation. In contrast, inexpensive metal oxide semiconductors encounter limitations such as harsh reaction conditions, instability, and low activity in electrochemical water splitting. Recent studies indicate that delaminated ultra-thin MXene Ti3C2Tx materials exhibit improved conductivity and larger surface area compared to the original MXene Ti3C2Tx. Theoretically, incorporating these ultra-thin MXene Ti3C2Tx materials with inexpensive metal oxide materials could overcome performance limitations. In this study, we developed a method for growing ZnO nanorods on a foam nickel substrate through an in-situ hydrothermal process, followed by coating with ultra-thin MXene Ti3C2Tx. This approach resulted in dual-functional electrocatalytic performance for both the oxygen evolution reaction and hydrogen evolution reaction. Notably, the prepared ZTNF catalyst demonstrated exceptional stability, with overpotentials of 260.3 mV for HER and 343.4 mV for OER at a current density of 10 mA/cm2. The Tafel slopes measured were 123.5 mV/dec for HER and 41.7 mV/dec for OER, highlighting the superiority of ZTNF over other catalyst materials in this research field. Overall, this study demonstrates the significant potential of metal oxide semiconductors and MXene Ti3C2Tx composite materials in the field of electrocatalysis.

Chelidonii herba is a traditional Chinese medicinal herb with effects including antispasmodic, analgesic, antitussive, and bronchodilator properties. Alkaloids are the main bioactive ingredients in Chelidonii herba. In this study, a two-dimensional nuclear magnetic resonance (Heteronuclear Singular Quantum Correlation, HSQC-2D-NMR) technique was employed to quantitatively analyze the total alkaloid content and three major active alkaloid monomers in Chelidonii herba from eleven different sources. The quantification results of the three monomeric alkaloids were also verified using conventional quantitative control methods such as HPLC. Experimental findings indicate that the total alkaloid content is not directly correlated with the content of the three monomeric alkaloids. Furthermore, the content of any individual monomeric alkaloid does not accurately reflect the overall quality of Chelidonii herba. It was demonstrated that the 2D-Q-NMR NMR can be applied as an alternative method. While maintaining the same levels of accuracy and precision, the 2D-Q-NMR method is simpler to operate and provides more comprehensive results with higher reproducibility in some cases.

Myasthenia gravis (MG) and idiopathic inflammatory myopathy (IIM) are autoimmune diseases of the nervous system, and their main clinical manifestation is muscle weakness. The concurrent presence of both conditions in the same patient is clinically rare and easily missed. Here, we report the case of a 74-year-old woman who went to the doctor with fluctuating weakness of the limbs and muscle pain. By analyzing the patient’s history and the results of repeated frequency electrical stimulation, chest computed tomography, thigh muscle magnetic resonance imaging, serum antibody detection, lymph node biopsy, etc., she was finally diagnosed with MG-concomitant IIM with squamous cell carcinoma of the thymus. Acetylcholine receptor antibody, titin antibody, ryanodine receptor antibody, anti–JO-1 antibody, and Ro-52 antibody tests were positive. MG-concomitant IIM is often associated with thymoma. The immunopathology mechanism may be different from that of pure MG or IIM, which needs further research.

Objective: To explore the mechanisms of the TGF-β1/Smad and NF-κB pathways in the effect of berberine (BBR) on colon cancer epithelial–mesenchymal transition (EMT) and their regulatory relationships with microRNAs (miRNAs). Methods: TGF-β1 was used to induce EMT in normal colon epithelial HCoEpiC cells and colon cancer HT29 cells in vitro. After BBR intervention, the expression of EMT-related markers and the major molecules involved in the TGF-β1/Smad and NF-κB pathways were detected via western blotting. Cell migration was detected via wound healing assays. SMAD2 and NF-κB p65 were overexpressed and transfected into cells, and the inhibitors SB431542 and BAY 11–7082 were added to block the TGF-β1/Smad and NF-κB pathways, respectively. The mRNA expression levels of related microRNA genes were detected by using RT‒PCR. Results: Treatment with 10 ng/ml TGF-β1 for 72 h significantly induced EMT in HCoEpiC and HT29 cells, which was repressed by BBR. BBR significantly inhibited the TGF-β1-induced migration of HCoEpiC and HT29 cells and the TGF-β1-promoted expression of p-Smad2/3, NF-κB p65, and p-IκBα. Compared to those in the group treated with TGF-β1, the expression of NF-κB p65 and p-Smad2 in the group treated with NF-κB pathway inhibitor BAY 11–7082 was decreased (P

The carnitine cycle is responsible for the transport of cytoplasmic fatty acids to the mitochondria for subsequent β-oxidation to maintain intracellular energy homeostasis. Recent studies have identified abnormalities in the carnitine cycle in various types of tumors; these abnormalities include the altered expression levels of carnitine cycle-related metabolic enzymes and transport proteins. Dysfunction of the carnitine cycle has been shown to influence tumorigenesis and progression by altering intracellular oxidative and inflammatory status or regulating tumor metabolic flexibility. Many therapeutic strategies targeting the carnitine cycle are actively being explored to modify the dysfunction of the carnitine cycle in patients with malignant tumors; such approaches include carnitine cycle-related enzyme inhibitors and exogenous carnitine supplementation. Therefore, here, we review the studies of carnitine in tumors, aiming to scientifically illustrate the dysfunction of the carnitine cycle in tumor progression and provide new ideas for further research.

BackgroundThe main challenge in diagnosing and treating ulcerative colitis (UC) has prompted this study to discover useful biomarkers and understand the underlying molecular mechanisms.MethodsIn this study, transcriptomic data from intestinal mucosal biopsies underwent Robust Rank Aggregation (RRA) analysis to identify differential genes. These genes intersected with UC key genes from Weighted Gene Co-expression Network Analysis (WGCNA). Machine learning identified UC signature genes, aiding predictive model development. Validation involved external data for diagnostic, progression, and drug efficacy assessment, along with ELISA testing of clinical serum samples.ResultsRRA integrative analysis identified 251 up-regulated and 211 down-regulated DEGs intersecting with key UC genes in WGCNA, yielding 212 key DEGs. Subsequently, five UC signature biomarkers were identified by machine learning based on the key DEGs—THY1, SLC6A14, ECSCR, FAP, and GPR109B. A logistic regression model incorporating these five genes was constructed. The AUC values for the model set and internal validation data were 0.995 and 0.959, respectively. Mechanistically, activation of the IL-17 signaling pathway, TNF signaling pathway, PI3K-Akt signaling pathway in UC was indicated by KEGG and GSVA analyses, which were positively correlated with the signature biomarkers. Additionally, the expression of the signature biomarkers was strongly correlated with various UC types and drug efficacy in different datasets. Notably, ECSCR was found to be upregulated in UC serum and exhibited a positive correlation with neutrophil levels in UC patients.ConclusionsTHY1, SLC6A14, ECSCR, FAP, and GPR109B can serve as potential biomarkers of UC and are closely related to signaling pathways associated with UC progression. The discovery of these markers provides valuable information for understanding the molecular mechanisms of UC.

The allure of team scale and functional diversity has led to the promising adoption of heterogeneous multi-robot systems (HMRS) in complex, large-scale operations such as disaster search and rescue, site surveillance, and social security. These systems, which coordinate multiple robots of varying functions and quantities, face the significant challenge of accurately assembling robot teams that meet the dynamic needs of tasks with respect to size and functionality, all while maintaining minimal resource expenditure. This paper introduces a pioneering adaptive cooperation method named inner attention (innerATT), crafted to dynamically configure teams of heterogeneous robots in response to evolving task types and environmental conditions. The innerATT method is articulated through the integration of an innovative attention mechanism within a multi-agent actor–critic reinforcement learning framework, enabling the strategic analysis of robot capabilities to efficiently form teams that fulfill specific task demands. To demonstrate the efficacy of innerATT in facilitating cooperation, experimental scenarios encompassing variations in task type (“Single Task”, “Double Task”, and “Mixed Task”) and robot availability are constructed under the themes of “task variety” and “robot availability variety.” The findings affirm that innerATT significantly enhances flexible cooperation, diminishes resource usage, and bolsters robustness in task fulfillment.

Highlights The anti-adhesion effect of polylactic acid (PLA) membrane with diamond-like carbon (DLC) depositing is 44.72%, enhanced by 23.11% compared to PLA. DLC deposited on PLA membranes has been shown to effectively reduce the levels of reactive oxygen species, leading to a decrease in the expression of pro-inflammatory cytokines within peritendinous adhesion tissue. DLC decelerates PLA biodegradation and lactic production, which reduces the number of CD68+CD206+ macrophages within peritendinous adhesion tissue.

Abstract Purpose The Systemic Immune-inflammatory Index (SII) and Geriatric Nutritional Risk Index (GNRI) have undergone comprehensive examination and validation in forecasting the outcomes of diverse medical conditions. Nevertheless, the correlation between the combined use of GNRI and SII metrics and hip fractures has yet to be elucidated. This study aimed to determine whether the amalgamation of SII and GNRI scores constitutes an independent prognostic factor for elderly patients with hip fractures. Methods We conducted a retrospective analysis of elderly patients admitted to our facility with hip fractures, encompassing both femoral neck and intertrochanteric fractures. Demographic information, experimental parameters, and postoperative complications were systematically recorded. The Geriatric Nutritional Risk Index (GNRI) and Systemic Immunoinflammatory Index (SII) were meticulously computed. Receiver operating characteristic (ROC) curves were generated, and optimal cutoff values for each parameter were determined. Subsequently, a multivariate Cox regression analysis was employed to assess the predictive utility of the SII–GNRI score in relation to 1-year postoperative mortality among elderly patients with hip fractures. Results In a study involving 597 patients, 90 of whom experienced mortality within 1 year, it was observed that the SII-GNRI score in the group of patients who passed away was significantly higher compared to the group that survived. Following a multifactorial adjustment, it was established that a high SII–GNRI score served as an independent predictor of 1-year all-cause mortality in older patients with hip fractures. In addition to the SII–GNRI score, factors such as length of hospital stay, CCI > 2, and blood transfusion were also identified as independent risk factors for survival. Notably, the incidence of postoperative complications in patients with high SII–GNRI scores was significantly greater than in patients with low scores. Conclusion The SII–GNRI score proves valuable in predicting the 1-year survival rate for elderly patients with hip fractures who have undergone surgery.

Abstract Background LncRNA ATP2B1-AS1 (ATP2B1-AS1) is involved in the occurrence and development of various diseases, while the relationship between lung adenocarcinoma (LUAD) and ATP2B1-AS1 is unclear. This study was to investigate the expression of ATP2B1-AS1 in LUAD and its influence on survival and prognosis of patients. Methods LUAD tissue samples from patients participating in this study were collected, and the expression levels of ATP2B1-AS1 and miR-141-3p in LUAD sampleswere detected by real-time quantitative polymerase chain reaction (RT-qPCR). The effect of ATP2B1-AS1 on the growth of A549 cells was investigated through cell counting kit-8 (CCK-8) and transwell experiments. Besides, the prognostic value of ATP2B1-AS1 in LUAD was assessed via Kaplan-Meier curve and multivariate Cox regression. Results ATP2B1-AS1 was downregulated in LUAD tissues and cells, whereas miR-141-3p was upregulated. After pcDNA3.1-ATP2B1-AS1 was transfected into A549 cells, the proliferation ability of A549 cells was decreased, and the migration level and invasion of A549 cells were also inhibited. High expression of ATP2B1-AS1 sponge miR-141-3p exerted prognostic value. Conclusions ATP2B1-AS1 sponge miR-141-3p alleviated the progression of LUAD, and ATP2B1-AS1 may be deemed as a prognostic marker for LUAD.

Introduction: Probiotics have been recognized for their various biological activities, including antioxidant and anti-inflammatory properties. This study investigates the therapeutic effect of a novel probiotic formula, BLLL, consisting of Bifidobacterium breve, Lactobacillus plantarum, Lactobacillus paracasei, and Lactobacillus helveticus, on chronic stress-induced depression-like behaviors in mice.Methods: The BLLL formula or phosphate-buffered saline (PBS) was given orally at a dose of 2, 4, or 8 × 1010 CFU/kg once daily for 10 days in mice treated with chronic unpredictable stress (CUS) treated or vehicle. Depression-like behaviors were assessed using the sucrose preference test (SPT), the forced swimming test (FST), and the tail suspension test (TST). The mRNA and/or protein expression of interleukin-1β (IL-1β), IL-6, tumor necrosis factor-α (TNF-α), IL-4, IL-10, and chitinase-3-like protein 3 (CHI3L1, also known as Ym-1), as well as the concentration of nitrite, malondialdehyde (MDA), glutathione (GSH), and brain-derived neurotrophic factor (BDNF) in the hippocampus and medial prefrontal cortex were examined.Results: The BLLL formula treatment at a dose of 8 × 1010 CFU/kg, but not at a dose of 2 or 4 × 1010 CFU/kg, improved CUS-induced depression-like behaviors in mice, as shown by the decrease in immobility time in the TST and FST and the increase in sucrose intake in the SPT. Further analysis revealed that BLLL treatment suppressed the CUS-induced increase in IL-1β, IL-6, and TNF-α mRNA and protein levels, as well as the CUS-induced decrease in IL-4, IL-10, and Ym-1 mRNA and/or protein levels in the hippocampus and medial prefrontal cortex. In addition, treatment with the BLLL formula countered the CUS-induced increase in nitrite and MDA levels and the CUS-induced decrease in GSH content and BDNF concentration in the hippocampus and medial prefrontal cortex.Conclusion: These results demonstrate that the novel probiotic formula BLLL ameliorates chronic stress-induced depression-like behavior in mice by suppressing neuroinflammation and oxido-nitrosative stress in the brain.

Abstract Critical‐size bone defects pose a formidable challenge in clinical treatment, prompting extensive research efforts to address this problem. In this study, an inorganic–organic multifunctional composite hydrogel denoted as PLG‐g‐TA/VEGF/Sr‐BGNPs is developed, engineered for the synergistic management of bone defects. The composite hydrogel demonstrated the capacity for mineralization, hydroxyapatite formation, and gradual release of essential functional ions and vascular endothelial growth factor (VEGF) and also maintained an alkaline microenvironment. The composite hydrogel promoted the proliferation and osteogenic differentiation of rat bone marrow mesenchymal stem cells (rBMSCs), as indicated by increased expression of osteogenesis‐related genes and proteins in vitro. Moreover, the composite hydrogel significantly enhanced the tube‐forming capability of human umbilical vein endothelial cells (HUVECs) and effectively inhibited the process of osteoblastic differentiation of nuclear factor kappa‐B ligand (RANKL)‐induced Raw264.7 cells and osteoclast bone resorption. After the implantation of the composite hydrogel into rat cranial bone defects, the expression of osteogenic and angiogenic biomarkers increased, substantiating its efficacy in promoting bone defect repair in vivo. The commendable attributes of the multifunctional composite hydrogel underscore its pivotal role in expediting hydrogel‐associated bone growth and repairing critical bone defects, positioning it as a promising adjuvant therapy candidate for large‐segment bone defects.

BackgroundKnee Osteoarthritis (KOA) is a prevalent and debilitating condition affecting millions worldwide, yet its underlying etiology remains poorly understood. Recent advances in neuroimaging and genetic methodologies offer new avenues to explore the potential neuropsychological contributions to KOA. This study aims to investigate the causal relationships between brain-wide morphometric variations and KOA using a genetic epidemiology approach.MethodLeveraging data from 36,778 UK Biobank participants for human brain morphometry and 487,411 UK Biobank participants for KOA, this research employed a two-sample Mendelian Randomization (TSMR) approach to explore the causal effects of 83 brain-wide volumes on KOA. The primary method of analysis was the Inverse Variance Weighted (IVW) and Wald Ratio (WR) method, complemented by MR Egger and IVW methods for heterogeneity and pleiotropy assessments. A significance threshold of p < 0.05 was set to determine causality. The analysis results were assessed for heterogeneity using the MR Egger and IVW methods. Brain-wide volumes with Q_pval < 0.05 were considered indicative of heterogeneity. The MR Egger method was employed to evaluate the pleiotropy of the analysis results, with brain-wide volumes having a p-value < 0.05 considered suggestive of pleiotropy.ResultsOur findings revealed significant causal associations between KOA and eight brain-wide volumes: Left parahippocampal volume, Right posterior cingulate volume, Left transverse temporal volume, Left caudal anterior cingulate volume, Right paracentral volume, Left paracentral volume, Right lateral orbitofrontal volume, and Left superior temporal volume. These associations remained robust after tests for heterogeneity and pleiotropy, underscoring their potential role in the pathogenesis of KOA.ConclusionThis study provides novel evidence of the causal relationships between specific brain morphometries and KOA, suggesting that neuroanatomical variations might contribute to the risk and development of KOA. These findings pave the way for further research into the neurobiological mechanisms underlying KOA and may eventually lead to the development of new intervention strategies targeting these neuropsychological pathways.

Total nitrogen concentration (CTN) enrichment is the primary cause of natural water eutrophication. Accurately estimating CTN and its spatiotemporal dynamics is crucial for formulating monitoring and control measures to alleviate lake eutrophication. A hybrid model was proposed for estimating CTN in optically complex inland waters by incorporating the relationship between CTN and water optical active components for Zhuhai-1 Orbita hyperspectral (OHS) imagery. Compared with other semi-analytical algorithms, the re-adjusted reference wavelength QAA716 shows the best performance in aph(λ) retrieval. The hybrid model for CTN estimation achieves an root mean square deviation (RMSD) of 0.20 mg/L, a mean absolute percentage deviation (MAPD) of 6.96 %, and a unbiased mean absolute percentage deviation (UMAPD) of 6.96 %, with aph(569) accuracy exerting the greatest influence. Ground-satellite synchronous validation demonstrates robust performance, with an RMSD of 0.28 mg/L, a MAPD of 14.49 %, and a UMAPD of 14.92 %. The hybrid model was applied to OHS observations of Lake Dianchi from April 2019 to September 2021. The analysis revealed a generally decreasing trend in CTN during this timeframe. The above results demonstrate that the robustness and applicability of the proposed CTN hybrid model for inland waters with complex optical properties. Furthermore, satellite-based data products provide valuable information for formulating lake management strategies.

Abstract Chromatin accessibility plays important roles in revealing the regulatory networks of gene expression, while its application in bladder cancer is yet to be fully elucidated. Chloride intracellular channel 3 (CLIC3) protein has been reported to be associated with the progression of some tumors, whereas the specific mechanism of CLIC3 in tumor remains unclear. Here, we screened for key genes in bladder cancer through the identification of transcription factor binding site clustered region (TFCR) on the basis of chromatin accessibility and TF motif. CLIC3 was identified by joint profiling of chromatin accessibility data with TCGA database. Clinically, CLIC3 expression was significantly elevated in bladder cancer and was negatively correlated with patient survival. CLIC3 promoted the proliferation of bladder cancer cells by reducing p21 expression in vitro and in vivo. Mechanistically, CLIC3 interacted with NAT10 and inhibited the function of NAT10, resulting in the downregulation of ac4C modification and stability of p21 mRNA. Overall, these findings uncover an novel mechanism of mRNA ac4C modification and CLIC3 may act as a potential therapeutic target for bladder cancer.

Abstract Hydrogen embrittlement reduces the durability of the structural steels required for the hydrogen economy. Understanding how hydrogen interacts with the materials plays a crucial role in managing the embrittlement problems. Theoretical models have indicated that carbon vacancies in metal carbide precipitates are effective hydrogen traps in steels. Increasing the number of carbon vacancies in individual metal carbides is important since the overall hydrogen trapping capacity can be leveraged by introducing abundant metal carbides in steels. To verify this concept, we compare a reference steel containing titanium carbides (TiCs), which lack carbon vacancies, with an experimental steel added with molybdenum (Mo), which form Ti-Mo carbides comprising more carbon vacancies than TiCs. We employ theoretical and experimental techniques to examine the hydrogen trapping behavior of the carbides, demonstrating adding Mo alters the hydrogen trapping mechanism, enabling hydrogen to access carbon vacancy traps within the carbides, leading to an increase in trapping capacity.

Shenmu Gas Field in Ordos Basin shows the characteristics of low quality gas reservoir, and its deve-lopment effect is quite different from that of surrounding gas fields, which brings some problems to the exploration deployment and sustainable production of the gas field. In order to reveal the origin of low-quality gas reservoirs, the microscopic characteristics and formation mechanism of Taiyuan Formation reservoirs in Shenmu Gas Field were studied based on microscopic experiments at different scales. The results show that the reservoir of Taiyuan Formation in Shenmu Gas Field is characterized by "rich in quartz, poor in feldspar, and high content of rock detritus". The reservoir of Taiyuan Formation is a low porosity and ultra-low permeability tight sandstone reservoir with small pore-fine throat combination, poor pore throat connectivity, and weak reservoir permeability. The formation of low-quality reservoirs in Taiyuan Formation is affected by the matrix, the content of rock detritus in eruptive rocks and diagenesis. During the late Carboniferous to early Permian, the formation of the reservoir was significantly affected by the volcanic activity of the Inner Mongolia ancient uplift in the north of the Ordos Basin. The content of matrix and rock detritus of the eruptive rock in the sandstone was generally high. The rock detritus of the eruptive rock provided the main material basis for the development of secondary pores. While the matrix blocked the pores, it also produced a certain number of matrix dissolved pores, which had a dual impact on the reservoir. The dissolution during diagenesis is critical to the formation of Taiyuan Formation reservoir, and the increased porosity accounts for 64.3% of the current porosity. At the end of the Late Cretaceous, the late Yanshan movement led to the structural inversion of the Ordos Basin, the readjustment of gas and water, and the escape of natural gas along the fault in the eastern part of the basin. Finally, the low quality gas reservoir of Taiyuan Formation in Shenmu Gas Field is formed. The next exploration focus of Shenmu Gas Field should be based on the clear macro distribution law of diagenesis and favorable lithologic traps, and further search for the development area with high content of eruptive rock detritus and low content of matrix.

The rapid expansion of highway infrastructure in the mountainous regions of China has led to a significant increase in tunnel construction, generating substantial amounts of tunnel waste slag. Concurrently, the development of transportation infrastructure has created a critical shortage of natural aggregates, necessitating the exploration of alternative sustainable sources. This study aimed to conduct a comprehensive evaluation of the physical and mechanical properties of tunnel waste slag and explore its potential for utilization in cement-stabilized base courses for highway engineering applications. The uniaxial compressive strength of the parent rock (tunnel waste slag) ranged from 81 MPa to 89 MPa in the desiccated state, indicating its suitability for use as a construction material. This study also determined the maximum dry density (2.432 g/cm3) and optimal moisture content (5.4%) of cement-stabilized mixtures incorporating recycled aggregates derived from tunnel waste slag. The splitting tensile strength of these mixtures at 28 days varied from 0.48 MPa to 0.73 MPa, demonstrating robust mechanical performance. Moreover, the unconfined compressive strength of these mixtures escalated from 7.0 MPa at 7 days to 11.0 MPa at 90 days, signifying a substantial enhancement in strength over time. These results validate the viability of utilizing tunnel waste slag in highway engineering and furnish valuable insights for designers, concrete manufacturers, and construction firms engaged in the development of cement-stabilized aggregate base courses.

With increasing attention being paid to electric vehicles, hybrid braking systems combining regenerative braking and conventional friction braking have become a hot research topic. Although some important advancements have been achieved in the field of hybrid braking system control, these have not been fully summarized. In order to fill this gap and provide a comprehensive perspective for other researchers, this paper surveys a wide range of research works reported in the literature on hybrid braking system control. We identify the advantages and limitations of existing hybrid brake control strategies via comparative analysis. Through analysis, we find that the control strategy used for brake torque distribution and braking systems’ coordinated control in current hybrid braking systems are usually designed separately. In order to ensure braking stability, most of the current hybrid braking control strategies are designed relatively conservatively, and it is difficult to fully leverage the advantages of hybrid braking systems. Comprehensively considering the coordinated control of braking torque distribution and braking systems is a good research direction for hybrid braking control research. Overall, this survey summarizes the existing research relevant to hybrid brake control methods and also discusses the research challenges and new research directions.

Long-term rotary tillage limit water infiltration and crop productivity in North China Plain (NCP). The practice of subsoiling to fracture plow pans has made beneficial impacts on soil surface structure and water infiltration. Further, appropriate irrigation method coupled with irrigation regime can improve crop productivity in subsoiling condition. A three-year field trial (2020–2023) was carried out to assess the effects of the irrigation regime and the method on winter wheat evapotranspiration (ET), grain yield (GY), water productivity (WP), partial factor productivity from applied nitrogen (PPFN), and economic analysis. The three irrigation regimes were irrigated when soil moisture levels decreased to 70%, 60% and 50% of the field capacity (referred as H, M and L) and two irrigation methods were the surface drip irrigation (SDI) and the micro-sprinkler irrigation (MSI). The traditional flood irrigation with 70% of the field capacity in subsoiling filed was CK. The results showed optimizing irrigation method and irrigation regime significantly influenced ET, GY, WP, PPFN, and net incomes. As the irrigation amount increased, the ET first increased while GY, WP, PPFN, and net incomes increased and then slightly decreased. Based on the three-year average, the maximum GY of 9454 kg ha−1 and the net income of 11089 yuan ha−1 was achieved in SDI-M, which had WP of 2.3 kg m−3 and PPFN of 39.4 kg kg−1. At the same time, SDI-M did not result in much increase of ET (average of 405.1 mm in three seasons). Considering comprehensively ET, GY, WP, PPFN, and net incomes, to irrigate when soil moisture decreases to 60% of the field capacity by surface drip irrigation was the optimal strategy in all aspects. These results will provide a scientific reference for irrigation management in subsoiling wheat field in NCP, as well as in similar production areas worldwide.

Iron overload occurs due to excessive iron intake compared to the body’s demand, leading to iron deposition and impairment of multiple organ functions. Our previous study demonstrated that chronic oral administration of ferric citrate (FC) caused colonic inflammatory injury. However, the precise mechanism underlying this inflammatory response remains unclear. The current study aims to investigate the mechanism by which iron overload induced by FC exposure leads to colonic inflammation. To accomplish this, mice were orally exposed to three different concentrations of FC (71 mg/kg/bw (L), 143 mg/kg/bw (M) and 286 mg/kg/bw (H)) for continuous 16 weeks, with the control group receiving ultrapure water (C). Exposure to FC caused disturbances in the excretory system, altered colonic flora alpha diversity, and enriched pathogenic bacteria, such as Mucispirillum, Helicobacter, Desulfovibrio, and Shigella. These changes led to structural disorders of the colonic flora and an inflammatory response phenotype characterized by inflammatory cells infiltration, atrophy of intestinal glands, and irregular thickening of the intestinal wall. Mechanistic studies revealed that FC-exposure activated the NF-κB signaling pathway by up-regulating TLR4, MyD88, and NF-κB mRNA levels and protein expression. This activation resulted in increased production of pro-inflammatory cytokines, further contributing to the colonic inflammation. Additionally, in vitro experiments in SW480 cells confirmed the activation of NF-κB signaling pathway by FC exposure, consistent with the in vivo findings. The significance of this study lies in its elucidation of the mechanism by which iron overload caused by FC exposure leads to colonic inflammation. By identifying the role of pathogenic bacteria and the NF-κB signaling pathway, this study could potentially offer a crucial theoretical foundation for the research on iron overload, as well as provide valuable insights for clinical iron supplementation.

Abstract Understanding the geochemical behavior of the Mo isotopes in estuarine systems is essential for determining the isotopic composition of riverine inputs to the ocean and for assessing the historical oxidation state of Earth’s ancient oceans. However, the extent and mechanisms of Mo isotope fractionation during estuarine processes are not yet fully understood. This study systematically investigated the seasonal and spatial variations in aqueous and particulate δ98Mo values within the Pearl River Estuary (PRE). Our research found that aqueous δ98Moaque. values in both summer and winter deviated significantly from the theoretical mixing line for the PRE. Based on the geochemical characteristics of the water column, particulate matter, and pore water in the PRE, we first propose that diagenesis release from sediments is the predominant factor resulting in lower than anticipated aqueous δ98Moaque. values. Given the prevalence of suboxic and anoxic sediments in estuarine and coastal areas, such diagenetic release may substantially decrease the global riverine influx of aqueous Mo isotopes to the ocean. Additionally, particulate δ98MoSPM values exhibit an increasing trend (from 0.02 to 1.62‰) with increasing salinity in both seasons, suggesting that the terrestrial input particulate δ98MoSPM value would be heavier than the mean value for UCC. We hypothesize that the adsorption and desorption processes involving Fe (hydro) oxides predominantly influence this trend. This study advances our understanding of the mechanisms of aqueous and particulate Mo isotopic fractionation in estuarine systems and would be helpful in constraining Mo isotopic compositions of rivers and oceans.

BackgroundIncreasing evidence indicating that coronavirus disease 2019 (COVID-19) increased the incidence and related risks of pericarditis and whether COVID-19 vaccine is related to pericarditis has triggered research and discussion. However, mechanisms behind the link between COVID-19 and pericarditis are still unknown. The objective of this study was to further elucidate the molecular mechanisms of COVID-19 with pericarditis at the gene level using bioinformatics analysis.MethodsGenes associated with COVID-19 and pericarditis were collected from databases using limited screening criteria and intersected to identify the common genes of COVID-19 and pericarditis. Subsequently, gene ontology, pathway enrichment, protein–protein interaction, and immune infiltration analyses were conducted. Finally, TF–gene, gene–miRNA, gene–disease, protein–chemical, and protein–drug interaction networks were constructed based on hub gene identification.ResultsA total of 313 common genes were selected, and enrichment analyses were performed to determine their biological functions and signaling pathways. Eight hub genes (IL-1β, CD8A, IL-10, CD4, IL-6, TLR4, CCL2, and PTPRC) were identified using the protein–protein interaction network, and immune infiltration analysis was then carried out to examine the functional relationship between the eight hub genes and immune cells as well as changes in immune cells in disease. Transcription factors, miRNAs, diseases, chemicals, and drugs with high correlation with hub genes were predicted using bioinformatics analysis.ConclusionsThis study revealed a common gene interaction network between COVID-19 and pericarditis. The screened functional pathways, hub genes, potential compounds, and drugs provided new insights for further research on COVID-19 associated with pericarditis.

Background Numerous online videos are available on sound therapy as a treatment modality for tinnitus, but it is uncertain if these videos are adequate for patient education. This study aims to evaluate the quality and reliability of tinnitus sound therapy videos on YouTube for patient education. Methods YouTube videos were searched using keywords related to “tinnitus sound therapy”. The top 100 videos were analyzed after excluding those were repetitive, irrelevant, less than 3 min, or not in English. After categorising the videos based on their authorship and content, the video power index (VPI) was relied to determine their popularity. The DISCERN questionnaire (DISCERN), the Global Quality Score (GQS), the Journal of the American Medical Association benchmark criteria (JAMA), and the Patient Education Materials Assessment Tool (PEMAT) were utilized to evaluate the quality, transparency, and patient education. Results Over half (56%) of the videos were published by professional organizations. A total of 93% of them contained sound only. Only 17% followed the recommendations of the Clinical Management of Tinnitus Guidelines, and 3% provided literature referenced by the video. A variety types of sound were used, among which music accounting for 35%. The videos were highly popular with an average views of 7,335,003.28 ± 24,174,764.02 and an average VPI of 4,610.33 ± 11,531.10. However, their quality was poor (the median scores: 38/80 for DISCERN, 2/5 for GQS, 1/4 for JAMA, and 50%/100% for PEMAT). There was a negative correlation between the popularity of the videos and their quality, indicated by PEMAT: −0.207, DISCERN: −0.307, GQS: −0.302, and JAMA: −0.233. Several dimensions of the videos require improvement, especially actionability, treatment options, and transparency with lacks of 100%, 63%, and 75% respectively. Conclusion The tinnitus sound therapy videos available on YouTube exhibit low quality. Nevertheless, they also hold potential for health education if refined and utilized suitably.

BackgroundPrevious studies mainly focused on risk factors in patients with mild cognitive impairment (MCI) or dementia. The aim of the study was to provide basis for preventing MCI in cognitive normal populations.MethodsThe data came from a longitudinal retrospective study involving individuals with brain magnetic resonance imaging scans, clinical visits, and cognitive assessment with interval of more than 3 years. Multiple machine-learning technologies, including random forest, support vector machine, logistic regression, eXtreme Gradient Boosting, and naïve Bayes, were used to establish a prediction model of a future risk of MCI through a combination of clinical and image variables.ResultsAmong these machine learning models; eXtreme Gradient Boosting (XGB) was the best classification model. The classification accuracy of clinical variables was 65.90%, of image variables was 79.54%, of a combination of clinical and image variables was 94.32%. The best result of the combination was an accuracy of 94.32%, a precision of 96.21%, and a recall of 93.08%. XGB with a combination of clinical and image variables had a potential prospect for the risk prediction of MCI. From clinical perspective, the degree of white matter hyperintensity (WMH), especially in the frontal lobe, and the control of systolic blood pressure (SBP) were the most important risk factor for the development of MCI.ConclusionThe best MCI classification results came from the XGB model with a combination of both clinical and imaging variables. The degree of WMH in the frontal lobe and SBP control were the most important variables in predicting MCI.

ObjectiveSepsis constitutes a significant global healthcare burden. Studies suggest a correlation between educational attainment and the likelihood of developing sepsis. Our goal was to utilize Mendelian randomization (MR) in order to examine the causal connection between educational achievement (EA) and sepsis, while measuring the mediating impacts of adjustable variables.MethodsWe collected statistical data summarizing educational achievement (EA), mediators, and sepsis from genome-wide association studies (GWAS). Employing a two-sample Mendelian randomization (MR) approach, we calculated the causal impact of education on sepsis. Following this, we performed multivariable MR analyses to assess the mediation proportions of various mediators, including body mass index (BMI), smoking, omega-3 fatty acids, and apolipoprotein A-I(ApoA-I).ResultsGenetic prediction of 1-SD (4.2 years) increase in educational attainment (EA) was negatively correlated with sepsis risk (OR = 0.83, 95% CI 0.71 to 0.96). Among the four identified mediators, ranked proportionally, they including BMI (38.8%), smoking (36.5%), ApoA-I (6.3%) and omega-3 (3.7%). These findings remained robust across a variety of sensitivity analyses.ConclusionThe findings of this study provided evidence for the potential preventive impact of EA on sepsis, which may be influenced by factors including and metabolic traits and smoking. Enhancing interventions targeting these factors may contribute to reducing the burden of sepsis.

Introduction This study comprehensively assessed the association between eight metabolites of urinary nicotine and cognitive impairment. Methods This cross-sectional study was based on the data of Shenzhen Aging Related Disorder Cohort (SADC), including 51 elderly community data variables such as demographic characteristics, neuropsychological assessment and environmental factors, from July 2017 to November 2018. Participant’s cognitive function was assessed by Mini-Mental State Examination (MMSE) scale and urinary nicotine metabolite [including cotinine N-β-D-glucuronide (CotGluc), rac 4-hydroxy-4-(3-pyridyl) butanoic acid dicyclohexylamine salt (HyPyBut), trans-3’-hydroxy cotinine O-β-D-glucuronide (OHCotGluc), and cotinine (Cot), etc.] concentrations were measured by high-performance liquid chromatographytandem mass spectrometry (LC-MS/MS). Generalized linear models and restricted cubic spline models were used to explore the relationships between the urinary levels of nicotine metabolite and cognitive function. Results A total of 296 individuals aged >60 years were included. Individuals in the third quartile of CotGluc had a 0.786 point (95% CI: -1.244 – -0.329) decrease or in the highest quartile of OHCotGluc had a 0.804 point (95% CI: -1.330 – -0.278) decreased in attention and calculation compared to those in the lowest quartile (all p for trend

Abstract Background Induction chemotherapy (ICT) augmentation is a common strategy for standard concurrent chemoradiotherapy (CCRT) of locoregionally advanced nasopharyngeal carcinoma (NPC). The survival condition is a crucial issue for patients with locoregionally advanced NPC. The survival of ICT patients with CCRT treatment versus standard CCRT alone should be elucidated via a systemic review and meta‐analysis of randomized clinical trials. Methods We compared ICT with CCRT and CCRT alone treatment to determine if ICT with CCRT can be associated with a significant benefit of survival conditions versus CCRT. Different survival indicators were analyzed for the ICT with CCRT. Twelve studies with a total of 3711 patients with locoregionally advanced NPC were enrolled. The focused outcome was the overall survival, progression‐free survival, distant metastasis‐free survival, and locoregional recurrence‐free survival. Results Our results showed that ICT with CCRT is associated with a significant benefit for the overall survival status versus CCRT treatment. Similar significant benefits in the survival condition were seen in progression‐free survival, distant metastasis‐free survival, and locoregional recurrence‐free survival. Conclusions The updated meta‐analysis results suggest that the ICT with CCRT might be associated with significant benefits of survival in overall, progression‐free, distant metastasis‐free, as well as locoregional recurrence‐free dimensions versus CCRT treatment. However, the bias of different kinds, doses, and regimens of chemotherapy agents and radiotherapy should not be ignored.

Abstract The pork industry is an essential part of the global food system, providing a significant source of protein for people around the world. A major factor restraining productivity and compromising animal wellbeing in the pork industry is disease outbreaks in pigs throughout the production process: widespread outbreaks can lead to losses as high as 10% of the U.S. pig population in extreme years. In this study, we present a machine learning model to predict the emergence of infection in swine production systems throughout the production process on a daily basis, a potential precursor to outbreaks whose detection is vital for disease prevention and mitigation. We determine features that provide the most value in predicting infection, which include nearby farm density, historical test rates, piglet inventory, feed consumption during the gestation period, and wind speed and direction. We utilize these features to produce a generalizable machine learning model, evaluate the model’s ability to predict outbreaks both seven and 30 days in advance, allowing for early warning of disease infection, and evaluate our model on two swine production systems and analyze the effects of data availability and data granularity in the context of our two swine systems with different volumes of data. Our results demonstrate good ability to predict infection in both systems with a balanced accuracy of $$85.3\%$$ 85.3 % on any disease in the first system and balanced accuracies (average prediction accuracy on positive and negative samples) of $$58.5\%$$ 58.5 % , $$58.7\%$$ 58.7 % , $$72.8\%$$ 72.8 % and $$74.8\%$$ 74.8 % on porcine reproductive and respiratory syndrome, porcine epidemic diarrhea virus, influenza A virus, and Mycoplasma hyopneumoniae in the second system, respectively, using the six most important predictors in all cases. These models provide daily infection probabilities that can be used by veterinarians and other stakeholders as a benchmark to more timely support preventive and control strategies on farms.

Large-scale imaging studies often face challenges stemming from heterogeneity arising from differences in geographic location, instrumental setups, image acquisition protocols, study design, and latent variables that remain undisclosed. While numerous regression models have been developed to elucidate the interplay between imaging responses and relevant covariates, limited attention has been devoted to cases where the imaging responses pertain to the domain of shape. This adds complexity to the problem of imaging heterogeneity, primarily due to the unique properties inherent to shape representations, including nonlinearity, high-dimensionality, and the intricacies of quotient space geometry. To tackle this intricate issue, we propose a novel approach: a shape-on-scalar regression model that incorporates confounder adjustment. In particular, we leverage the square root velocity function to extract elastic shape representations which are embedded within the linear Hilbert space of square integrable functions. Subsequently, we introduce a shape regression model aimed at characterizing the intricate relationship between elastic shapes and covariates of interest, all while effectively managing the challenges posed by imaging heterogeneity. We develop comprehensive procedures for estimating and making inferences about the unknown model parameters. Through real-data analysis, our method demonstrates its superiority in terms of estimation accuracy when compared to existing approaches.

Errors in data measurement and recording can induce data missing for photovoltaic (PV) operation. Flawed data, however, can greatly impair the performance of data-driven models such as the accuracy of PV generation forecasting. The super-resolution perception convolutional neural network (SRPCNN) is a powerful tool in data reconstruction from low frequency to high frequency and it can be used for data recovery. The SRPCNN, however, has problems in dealing with null values for PV data recovery. To solve this problem, an improved SRPCNN model, which integrates naïve SPRCNN and linear interpolation, is proposed in this paper. Experiments are carried out under 5 different missing rates. The improved model can handle null values better, and can have a better accuracy improvement than the naïve SPRCNN and other methods. To further improve the data recovery performance, a modified whale optimization algorithm is deployed to optimize the hyperparameters of SPRCNN. To verify the efficiency of the proposed model, extensive numerical experiments on different types of data from an actual PV power plant have been conducted by comparing with benchmarks. Compared with the naïve SRPCNN, the RMSE and MAE of the proposed model are reduced by more than 30% in various cases. Results show that the improved SRPCNN model is efficient in PV data recovery with various missing rates.

The composition and spatial distribution of tree species are pivotal for biodiversity conservation, ecosystem productivity, and carbon sequestration. However, the accurate classification of tree species in subtropical forests remains a formidable challenge due to their complex canopy structures and dense vegetation. This study addresses these challenges within the Jiangxi Lushan National Nature Reserve by leveraging high-resolution GF-2 remote sensing imagery and UAV multispectral images collected in 2018 and 2022. We extracted spectral, texture, vegetation indices, geometric, and topographic features to devise 12 classification schemes. Utilizing an object-oriented approach, we employed three machine learning algorithms—Random Forest (RF), k-Nearest Neighbor (KNN), and Classification and Regression Tree (CART)—to identify 12 forest types in these regions. Our findings indicate that all three algorithms were effective in identifying forest type in subtropical forests, and the optimal overall accuracy (OA) was more than 72%; RF outperformed KNN and CART; S12 based on feature selection was the optimal feature combination scheme; and the combination of RF and Scheme S12 (S12) yielded the highest classification accuracy, with OA and Kappa coefficients for 2018-RF-S12 of 90.33% and 0.82 and OA and Kappa coefficients for 2022-RF-S12 of 89.59% and 0.81. This study underscores the utility of combining multiple feature types and feature selection for enhanced forest type recognition, noting that topographic features significantly improved accuracy, whereas geometric features detracted from it. Altitude emerged as the most influential characteristic, alongside significant variables such as the Normalized Difference Greenness Index (NDVI) and the mean value of reflectance in the blue band of the GF-2 image (Mean_B). Species such as Masson pine, shrub, and moso bamboo were accurately classified, with the optimal F1-Scores surpassing 89.50%. Notably, a shift from single-species to mixed-species stands was observed over the study period, enhancing ecological diversity and stability. These results highlight the effectiveness of GF-2 imagery for refined, large-scale forest-type identification and dynamic diversity monitoring in complex subtropical forests.

As a hot technology trend, the federated learning (FL) cleverly combines data utilization and privacy protection by processing data locally on the client and only sharing model parameters with the server, embodying an efficient and secure collaborative learning model between clients and aggregated Servers. During the process of uploading parameters in FL models, there is susceptibility to unauthorized access threats, which can result in training data leakage. To ensure data security during transmission, the Authentication and Key Agreement (AKA) protocols are proposed to authenticate legitimate users and safeguard training data. However, existing AKA protocols for client–server (C/S) architecture show security deficiencies, such as lack of user anonymity and susceptibility to password guessing attacks. In this paper, we propose a robust 2FAKA-C/S protocol based on ECC and Hash-chain technology. Our security analysis shows that the proposed protocol ensures the session keys are semantically secure and can effectively resist various attacks. The performance analysis indicates that the proposed protocol achieves a total running time of 62.644 ms and requires only 800 bits of communication overhead, showing superior computational efficiency and lower communication costs compared to existing protocols. In conclusion, the proposed protocol securely protects the training parameters in a federated learning environment and provides a reliable guarantee for data transmission.