Functional near-infrared spectroscopy-based diagnosis support system for distinguishing between mild and severe depression using machine learning approaches.

Significance: Early diagnosis of depression is crucial for effective treatment. Our study utilizes functional near-infrared spectroscopy (fNIRS) and machine learning to accurately classify mild and severe depression, providing an objective auxiliary diagnostic tool for mental health workers. Aim: Develop prediction models to distinguish between severe and mild depression using fNIRS data. Approach: We collected the fNIRS data from 140 subjects and applied a complete ensemble empirical mode decomposition with an adaptive noise-wavelet threshold combined denoising method (CEEMDAN-WPT) to remove noise during the verbal fluency task. The temporal features (TF) and correlation features (CF) from 18 prefrontal lobe channels of subjects were extracted as predictors. Using recursive feature elimination with cross-validation, we identified optimal TF or CF and examined their role in distinguishing between severe and mild depression. Machine learning algorithms were used for classification. Results: The combination of TF and CF as inputs for the prediction model yielded higher classification accuracy than using either TF or CF alone. Among the prediction models, the SVM-based model demonstrates excellent performance in nested cross-validation, achieving an accuracy rate of 92.8%. Conclusions: The proposed model can effectively distinguish mild depression from severe depression.

Application of texture signatures based on multiparameter-magnetic resonance imaging for predicting microvascular invasion in hepatocellular carcinoma: Retrospective study.

BACKGROUND: Despite continuous changes in treatment methods, the survival rate for advanced hepatocellular carcinoma (HCC) patients remains low, highlighting the importance of diagnostic methods for HCC. AIM: To explore the efficacy of texture analysis based on multi-parametric magnetic resonance (MR) imaging (MRI) in predicting microvascular invasion (MVI) in preoperative HCC. METHODS: This study included 105 patients with pathologically confirmed HCC, categorized into MVI-positive and MVI-negative groups. We employed Original Data Analysis, Principal Component Analysis, Linear Discriminant Analysis (LDA), and Non-LDA (NDA) for texture analysis using multi-parametric MR images to predict preoperative MVI. The effectiveness of texture analysis was determined using the B11 program of the MaZda4.6 software, with results expressed as the misjudgment rate (MCR). RESULTS: Texture analysis using multi-parametric MRI, particularly the MI + PA + F dimensionality reduction method combined with NDA discrimination, demonstrated the most effective prediction of MVI in HCC. Prediction accuracy in the pulse and equilibrium phases was 83.81%. MCRs for the combination of T2-weighted imaging (T2WI), arterial phase, portal venous phase, and equilibrium phase were 22.86%, 16.19%, 20.95%, and 20.95%, respectively. The area under the curve for predicting MVI positivity was 0.844, with a sensitivity of 77.19% and specificity of 91.67%. CONCLUSION: Texture analysis of arterial phase images demonstrated superior predictive efficacy for MVI in HCC compared to T2WI, portal venous, and equilibrium phases. This study provides an objective, non-invasive method for preoperative prediction of MVI, offering a theoretical foundation for the selection of clinical therapy.

The effect of health quotient and time management skills on self-management behavior and glycemic control among individuals with type 2 diabetes mellitus.

Objective: The aim of this study was to evaluate the present status of self-management behavior and glycemic control in individuals diagnosed with Type 2 Diabetes Mellitus (T2D), as well as to examine the impact of health quotient (HQ) and time management skills on both self-management behavior and glycemic control. Methods: Between October 2022 and March 2023, a purposive sampling method had been utilized to select 215 participants with type T2D. The survey concluded a general information questionnaire, an HQ scale, a diabetes time management questionnaire and a self-management behavior questionnaire. The health quotient(HQ)encompasses the individuals' knowledge, attitude toward health, and the ability to maintain their own well-being. The diabetes time management questionnaire was reverse-scored, with higher scores indicating an enhanced competence in time management. The path among variables was analyzed using structural equation modeling(SEM). Results: SEM showed that the direct effect of HQ on time management was -0.566 (p < 0.05), the direct effect of time management on the effect of self-management was -0.617 (p < 0.05), the direct effect of HQ on self-management was 0.156, and the indirect effect was 0.349 (p < 0.05); the relationship between health quotient and self-management was partially mediated by time management, with a mediating effect size of 68.8%. In addition, self-management had a direct effect on HbAlc, with a size of -0.394 (p < 0.05); The impacts of both HQ and time management on HbAlc were found to be mediated by self-management, with HQ demonstrating an indirect effect of -0.199 (p < 0.05) and time management showing an indirect effect of 0.244 (p < 0.05). Conclusion: Health quotient and time management in patients with T2D serve as catalysts for self-management behavior. They affect HbAlc level indirectly through self-management practices. The suggestion is to prioritize the cultivation of rational time organization and management skills in T2D patients, as well as enhance their health quotient level. This can facilitate a more effective improvement in patients' self-management behaviors, ultimately achieving the objective of maintaining optimal glycemic control.

SPP1 represents a therapeutic target that promotes the progression of oesophageal squamous cell carcinoma by driving M2 macrophage infiltration.

BACKGROUND: Tumour-associated macrophages (TAMs) are an important component of the tumour microenvironment (TME). However, the crosstalk between oesophageal squamous cell carcinoma (ESCC) cells and TAMs remains largely unexplored. METHODS: Clinical samples and the TCGA database were used to evaluate the relevance of SPP1 and TAM infiltration in ESCC. Mouse models were constructed to investigate the roles of macrophages educated by SPP1 in ESCC. Macrophage phenotypes were determined using qRT‒PCR and immunohistochemical staining. RNA sequencing was performed to elucidate the mechanism. RESULTS: Increasing expression of SPP1 correlated with M2-like TAM accumulation in ESCC, and they both predicted poor prognosis in the ESCC cohort. Knockdown of SPP1 significantly inhibited the infiltration of M2 TAMs in xenograft tumours. In vivo mouse model experiments showed that SPP1-mediated education of macrophages plays an essential role in the progression of ESCC. Mechanistically, SPP1 recruited macrophages and promoted M2 polarisation via CD44/PI3K/AKT signalling activation and then induced VEGFA and IL6 secretion to sustain ESCC progression. Finally, blockade of SPP1 with RNA aptamer significantly inhibited tumour growth and M2 TAM infiltration in xenograft mouse models. CONCLUSIONS: This study highlights SPP1-mediated crosstalk between ESCC cells and TAMs in ESCC. SPP1 could serve as a potential target in ESCC therapy.

Parathyroid Hormone is Negatively Correlated with Glycated Hemoglobin in Newly Diagnosed Type 2 Diabetic Patients.

Objective: The growing evidence shows that parathyroid hormone (PTH) may affect glucose metabolism. However, the relationship between them is still controversial among diabetic patients. The current study aimed to investigate the relationship between PTH and glucose metabolism in the patients with newly diagnosed type 2 diabetes (T2D). Methods: A total of 532 participants, including 387 patients with newly diagnosed T2D and 145 healthy controls, were recruited in the present study. PTH and metabolic parameters were measured in all participants. Results: The PTH levels were significantly lower in the newly diagnosed T2D patients compared with the control group (35.10 (25.90, 47.20) vs. 47.15 (35.83, 58.65) pg/ml, P < 0.001). The T2D patients with a higher glycated hemoglobin (HbA1c) tertile had lower PTH levels than the patients with a lower HbA1c tertile (32.90 (24.85, 41.40) vs. 37.50 (26.10, 54.55) pg/ml, P < 0.001). Spearman correlation analysis showed that PTH was positively correlated with the body mass index (BMI), fasting insulin (FINS), homeostasis model assessment of ß-cell function (HOMA-ß), and homeostasis model assessment of insulin resistance (HOMA-IR) and negatively correlated with HbA1c, blood calcium (Ca), blood phosphorus (P), and 25-hydroxyvitamin D3 (25-OH-D3). Multiple linear regression analysis demonstrated that PTH was significantly associated with HbA1c (ß = -1.475, P=0.003) and HOMA-ß (ß = 0.090, P=0.001) after adjusting for age, sex, BMI, season, 25-OH-D3, Ca, and P. Conclusion: PTH was negatively correlated with HbA1c in the newly diagnosed T2D patients. Our results suggested that the PTH level within the reference range is related to islet ß-cell function and hyperglycemia.

AmCBF1 activates the expression of GhClpR1 to mediate dark-green leaves in cotton (Gossypium hirsutum).

KEY MESSAGE: The transcription factor AmCBF1 deepens the leaf colour of transgenic cotton by binding to the promoter of the chloroplast development-related protein GhClpR1 to promote photosynthesis. The ATP-dependent caseinolytic protease (Clp protease) family plays a crucial role within chloroplasts, comprising several Clp proteins to maintain chloroplast homeostasis. At present, research on Clp proteins mainly focuses on Arabidopsis, leaving its function in other plants, particularly in crops, less explored. In this study, we overexpressed AmCBF1 from Ammopiptanthus mongolicus (A. mongolicus) in wild type (R15), and found a significant darkening of leaf colour in transgenic plants (L28 and L30). RNA-seq analysis showed an enrichment of pathways associated with photosynthesis. Subsequent screening of differentially expressed genes revealed a significant up-regulation of GhClpR1, a gene linked to chloroplast development, in the transgenic strain. In addition, GhClpR1 was consistently expressed in upland cotton, with the highest expression observed in leaves. Subcellular localization analysis revealed that the protein encoded by GhClpR1 was located in chloroplasts. Yeast one hybrid and dual luciferase experiments showed that the AmCBF1 transcription factor positively regulates the expression of GhClpR1. VIGs-mediated silencing of GhClpR1 led to a significant yellowing phenotype in the leaves. This was accompanied by a reduction in chlorophyll content, and microscopic examination of chloroplast ultrastructure revealed severe developmental impairment. Finally, yeast two-hybrid assays showed that GhClpR1 interacts with the Clp protease complex accessory protein GhClpT2. Our study provides a foundation for studying the function of the Clp protease complex and a new strategy for cultivating high-light-efficiency cotton resources.

The effects of ambient temperature and feeding regimens on cecum bacteria composition and circadian rhythm in growing rabbits.

Seasonal environmental shifts and improper eating habits are the important causes of diarrhea in children and growing animals. Whether adjusting feeding time at varying temperatures can modify cecal bacterial structure and improve diarrhea remains unknown. Three batches growing rabbits with two groups per batch were raised under different feeding regimens (fed at daytime vs. nighttime) in spring, summer and winter separately, and contents were collected at six time points in 1 day and used 16S rRNA sequencing to investigate the effects of feeding regimens and season on the composition and circadian rhythms of cecum bacteria. Randomized forest regression screened 12 genera that were significantly associated with seasonal ambient temperature changes. Nighttime feeding reduced the abundance of the conditionally pathogenic bacteria Desulfovibrio and Alistipes in summer and Campylobacter in winter. And also increases the circadian rhythmic Amplicon Sequence Variants in the cecum, enhancing the rhythm of bacterial metabolic activity. This rhythmic metabolic profile of cecum bacteria may be conducive to the digestion and absorption of nutrients in the host cecum. In addition, this study has identified 9 genera that were affected by the combination of seasons and feeding time. In general, we found that seasons and feeding time and their combinations affect cecum composition and circadian rhythms, and that daytime feeding during summer and winter disrupts the balance of cecum bacteria of growing rabbits, which may adversely affect cecum health and induce diarrhea risk.

Biomedical image segmentation algorithm based on dense atrous convolution.

Biomedical images have complex tissue structures, and there are great differences between images of the same part of different individuals. Although deep learning methods have made some progress in automatic segmentation of biomedical images, the segmentation accuracy is relatively low for biomedical images with significant changes in segmentation targets, and there are also problems of missegmentation and missed segmentation. To address these challenges, we proposed a biomedical image segmentation method based on dense atrous convolution. First, we added a dense atrous convolution module (DAC) between the encoding and decoding paths of the U-Net network. This module was based on the inception structure and atrous convolution design, which can effectively capture multi-scale features of images. Second, we introduced a dense residual pooling module to detect multi-scale features in images by connecting residual pooling blocks of different sizes. Finally, in the decoding part of the network, we adopted an attention mechanism to suppress background interference by enhancing the weight of the target area. These modules work together to improve the accuracy and robustness of biomedical image segmentation. The experimental results showed that compared to mainstream segmentation networks, our segmentation model exhibited stronger segmentation ability when processing biomedical images with multiple-shaped targets. At the same time, this model can significantly reduce the phenomenon of missed segmentation and missegmentation, improve segmentation accuracy, and make the segmentation results closer to the real situation.

Part-Object Progressive Refinement Network for Zero-Shot Learning.

Zero-shot learning (ZSL) recognizes unseen images by sharing semantic knowledge transferred from seen images, encouraging the investigation of associations between semantic and visual information. Prior works have been devoted to the alignment of global visual features with semantic information, i.e., attribute vectors, or further mining the local part regions related to each attribute and then simply concatenating them for category decisions. Although effective, these works ignore intrinsic interactions between local parts and the whole object, which enables a more discriminative and representative knowledge transfer for ZSL. In this paper, we propose a Part-Object Progressive Refinement Network (POPRNet), where discriminative and transferable semantics are progressively refined by the cooperation between parts and the whole object. Specifically, POPRNet incorporates discriminative part semantics and object-centric semantics guided by semantic intensity to improve cross-domain transferability. To achieve part-object learning, a semantic-augment transformer (SaT) is proposed to model the part-object relation at the part-level via an encoder and at the object-level via a decoder, generating a comprehensive semantic representation to boost discriminability and transferability. By introducing the prototype updating module embedded with the prototype selection layers, the discriminative ability of the updated category prototype is enhanced to further improve the recognition performance of ZSL. Extensive experiments are conducted to demonstrate the superiority and competitiveness of our proposed POPRNet method on three public benchmark datasets. The code is available at https://github.com/ManLiuCoder/POPRNet.

Humoral immune response to tumor-associated antigen Ubiquilin 1 (UBQLN1) and its tumor-promoting potential in lung cancer.

BACKGROUND: This study aims to investigate the expression of UBQLN1 in lung cancer (LC) tissue and the diagnostic capability of autoantibody to UBQLN1 (anti-UBQLN1) in the detection of LC and the discrimination of pulmonary nodules (PNs). METHODS: Sera from 798 participants were used to discover and validate the level of autoantibodies via HuProt microarray and Enzyme-linked immunosorbent assay (ELISA). Logistic regression analysis was applied to establish model. Receiver operating characteristic curve (ROC) analysis was performed to evaluate the diagnostic potential. Immunohistochemistry was performed to detect UBQLN1 expression in 88 LC tissues and 88 para-tumor tissues. qRT-PCR and western blotting were performed to detect the expression of UBQLN1 at the mRNA and protein levels, respectively. Trans-well assay and cell counting kit-8 (CCK-8) was used to investigate the function of UBQLN1. RESULTS: Anti-UBQLN1 was identified with the highest fold change by protein microarray. The level of anti-UBQLN1 in LC patients was obviously higher than that in NC or patients with benign lung disease of validation cohort 1 (P<0.05). The area under the curve (AUC) of anti-UBQLN1 was 0.610 (95%CI: 0.508-0.713) while reached at 0.822 (95%CI: 0.784-0.897) when combining anti-UBQLN1 with CEA, CYFRA21-1, CA125 and three CT indicators (vascular notch sign, lobulation sign and mediastinal lymph node enlargement) in the discrimination of PNs. UBQLN1 protein was overexpressed in lung adenocarcinoma (LUAD) tissues compared to para-tumor tissues. UBQLN1 knockdown remarkably inhibited the migration, invasion and proliferation of LUAD cell lines. CONCLUSIONS: Anti-UBQLN1 might be a potential biomarker for the diagnosis of LC and the discrimination of PNs.

Harnessing the potential of HLA-G in cancer therapy: advances, challenges, and prospects.

Immune checkpoint blockades have been prized in circumventing and ablating the impediments posed by immunosuppressive receptors, reaching an exciting juncture to be an innovator in anticancer therapy beyond traditional therapeutics. Thus far, approved immune checkpoint blockades have principally targeted PD-1/PD-L1 and CTLA-4 with exciting success in a plethora of tumors and yet are still trapped in dilemmas of limited response rates and adverse effects. Hence, unveiling new immunotherapeutic targets has aroused immense scientific interest in the hope of expanding the clinical application of immune checkpoint blockades to scale new heights. Human leukocyte antigen-G (HLA-G), a non-classical major histocompatibility complex (MHC) class I molecule, is enriched on various malignant cells and is involved in the hindrance of immune effector cells and the facilitation of immunosuppressive cells. HLA-G stands out as a crucial next-generation immune checkpoint showing great promise for the benefit of cancer patients. Here, we provide an overview of the current understanding of the expression pattern and immunological functions of HLA-G, as well as its interaction with well-characterized immune checkpoints. Since HLA-G can be shed from the cell surface or released by various cells as free soluble HLA-G (sHLA-G) or as part of extracellular vesicles (EVs), namely HLA-G-bearing EVs (HLA-GEV), we discuss the potential of sHLA-G and HLA-GEV as predictive biomarkers. This review also addresses the advancement of HLA-G-based therapies in preclinical and clinical settings, with a focus on their clinical application in cancer.

Machine learning based biomarker discovery for chronic kidney disease-mineral and bone disorder (CKD-MBD).

INTRODUCTION: Chronic kidney disease-mineral and bone disorder (CKD-MBD) is characterized by bone abnormalities, vascular calcification, and some other complications. Although there are diagnostic criteria for CKD-MBD, in situations when conducting target feature examining are unavailable, there is a need to investigate and discover alternative biochemical criteria that are easy to obtain. Moreover, studying the correlations between the newly discovered biomarkers and the existing ones may provide insights into the underlying molecular mechanisms of CKD-MBD. METHODS: We collected a cohort of 116 individuals, consisting of three subtypes of CKD-MBD: calcium abnormality, phosphorus abnormality, and PTH abnormality. To identify the best biomarker panel for discrimination, we conducted six machine learning prediction methods and employed a sequential forward feature selection approach for each subtype. Additionally, we collected a separate prospective cohort of 114 samples to validate the discriminative power of the trained prediction models. RESULTS: Using machine learning under cross validation setting, the feature selection method selected a concise biomarker panel for each CKD-MBD subtype as well as for the general one. Using the consensus of these features, best area under ROC curve reached up to 0.95 for the training dataset and 0.74 for the perspective dataset, respectively. DISCUSSION/CONCLUSION: For the first time, we utilized machine learning methods to analyze biochemical criteria associated with CKD-MBD. Our aim was to identify alternative biomarkers that could serve not only as early detection indicators for CKD-MBD, but also as potential candidates for studying the underlying molecular mechanisms of the condition.

Oridonin-induced ferroptosis and apoptosis: a dual approach to suppress the growth of osteosarcoma cells.

BACKGROUND: Osteosarcoma (OS) is one of the most common aggressive bone malignancy tumors in adolescents. With the application of new chemotherapy regimens, finding new and effective anti-OS drugs to coordinate program implementation is urgent for the patients of OS. Oridonin had been proved to mediate anti-tumor effect on OS cells, but its mechanism has not been fully elucidated. METHODS: The effects of oridonin on the viability, clonal formation and migration of 143B and U2OS cells were detected by CCK-8, colony formation assays and wound-healing test. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was used to explore the mechanism of oridonin on OS. Western blot (WB), real-time quantitative PCR (qRT-PCR) were used to detect the expression levels of apoptosis and ferroptosis-relative proteins and genes. Annexin V-FITC apoptosis detection kit and flow cytometry examination were used to detect the level of apoptosis. Iron assay kit was used to evaluate the relative Fe2+ content. The levels of mitochondrial membrane potential and lipid peroxidation production was determined by mitochondrial membrane potential detection kit and ROS assay kit. RESULTS: Oridonin could effectively inhibit the survival, clonal formation and metastasis of OS cells. The KEGG results indicated that oridonin is associated with the malignant phenotypic signaling pathways of proliferation, migration, and drug resistance in OS. Oridonin was capable of inhibiting expressions of BAX, cl-caspase3, SLC7A11, GPX4 and FTH1 proteins and mRNA, while promoting the expressions of Bcl-2 and ACSL4 in 143B and U2OS cells. Additionally, we found that oridonin could promote the accumulation of reactive oxygen species (ROS) and Fe2+ in OS cells, as well as reduce mitochondrial membrane potential, and these effects could be significantly reversed by the ferroptosis inhibitor ferrostatin-1 (Fer-1). CONCLUSION: Oridonin can trigger apoptosis and ferroptosis collaboratively in OS cells, making it a promising and effective agent for OS therapy.

Recombinant adeno-associated virus 8-mediated inhibition of microRNA let-7a ameliorates sclerosing cholangitis in a clinically relevant mouse model.

BACKGROUND: Primary sclerosing cholangitis (PSC) is characterized by chronic inflammation and it predisposes to cholangiocarcinoma due to lack of effective treatment options. Recombinant adeno-associated virus (rAAV) provides a promising platform for gene therapy on such kinds of diseases. A microRNA (miRNA) let-7a has been reported to be associated with the progress of PSC but the potential therapeutic implication of inhibition of let-7a on PSC has not been evaluated. AIM: To investigate the therapeutic effects of inhibition of a miRNA let-7a transferred by recombinant adeno-associated virus 8 (rAAV8) on a xenobiotic-induced mouse model of sclerosing cholangitis. METHODS: A xenobiotic-induced mouse model of sclerosing cholangitis was induced by 0.1% 3,5-Diethoxycarbonyl-1,4-Dihydrocollidine (DDC) feeding for 2 wk or 6 wk. A single dose of rAAV8-mediated anti-let-7a-5p sponges or scramble control was injected in vivo into mice onset of DDC feeding. Upon sacrifice, the liver and the serum were collected from each mouse. The hepatobiliary injuries, hepatic inflammation and fibrosis were evaluated. The targets of let-7a-5p and downstream molecule NF-κB were detected using Western blot. RESULTS: rAAV8-mediated anti-let-7a-5p sponges can depress the expression of let-7a-5p in mice after DDC feeding for 2 wk or 6 wk. The reduced expression of let-7a-5p can alleviate hepato-biliary injuries indicated by serum markers, and prevent the proliferation of cholangiocytes and biliary fibrosis. Furthermore, inhibition of let-7a mediated by rAAV8 can increase the expression of potential target molecules such as suppressor of cytokine signaling 1 and Dectin1, which consequently inhibit of NF-κB-mediated hepatic inflammation. CONCLUSION: Our study demonstrates that a rAAV8 vector designed for liver-specific inhibition of let-7a-5p can potently ameliorate symptoms in a xenobiotic-induced mouse model of sclerosing cholangitis, which provides a possible clinical translation of PSC of human.

Multifunctional ZnO@DOX/ICG-LMHP Nanoparticles for Synergistic Multimodal Antitumor Activity.

Multifunctional nanoparticles are of significant importance for synergistic multimodal antitumor activity. Herein, zinc oxide (ZnO) was used as pH-sensitive nanoparticles for loading the chemotherapy agent doxorubicin (DOX) and the photosensitizer agent indocyanine green (ICG), and biocompatible low-molecular-weight heparin (LMHP) was used as the gatekeepers for synergistic photothermal therapy/photodynamic therapy/chemotherapy/immunotherapy. ZnO was decomposed into cytotoxic Zn2+ ions, leading to a tumor-specific release of ICG and DOX. ZnO simultaneously produced oxygen (O2) and reactive oxygen species (ROS) for photodynamic therapy (PDT). The released ICG under laser irradiation produced ROS for PDT and raised the tumor temperature for photothermal therapy (PTT). The released DOX directly caused tumor cell death for chemotherapy. Both DOX and ICG also induced immunogenic cell death (ICD) for immunotherapy. The in vivo and in vitro results presented a superior inhibition of tumor progression, metastasis and recurrence. Therefore, this study could provide an efficient approach for designing multifunctional nanoparticles for synergistic multimodal antitumor therapy.

Engineering M2 type macrophage-derived exosomes for autoimmune hepatitis immunotherapy via loading siRIPK3.

Autoimmune hepatitis (AIH) is a progressive liver disease mediated by the immune system that involves an imbalance in pro-inflammatory and regulatory mechanisms including regulatory T cells (Tregs), T helper 17 (Th17) cells, Th1, macrophages, and many other immune cells. Current steroid therapy for AIH has significant systemic side effects and is poorly tolerated by some individuals. Therefore, there is an urgent need for alternative treatments. Maintaining homeostasis in macrophage differentiation and activation is crucial for regulating immune responses in hepatitis. In this study, we loaded small interfering RNA (siRNA) targeting receptor-interacting protein kinase 3 (RIPK3) into M2-type macrophage-derived exosomes (M2 Exos) to create functionalized exosomes called M2 Exos/siRIPK3. These exosomes demonstrated a natural ability to target the liver in mice, as they were efficiently taken up by hepatic macrophages and showed significant and stable accumulation. M2 Exos/siRIPK3 effectively mitigated immune-mediated hepatitis by suppressing the expression of RIPK3, resulting in a reduced release of pro-inflammatory cytokines and chemokines in both liver tissues and serum. Additionally, M2 Exos/siRIPK3 exhibited immunomodulatory effects, as its administration resulted in a decreased proportion of hepatic and splenic Th17 cells, along with an increased ratio of Tregs. Overall, this study suggests that loading small molecule drugs onto M2 Exos could be a promising approach for developing immunomodulators that specifically target liver macrophages to treat AIH. This strategy has the potential to provide a safer and more effective alternative to current therapy for AIH patients.

Exploration of natural processes and anthropogenic inputs by Zn isotopes in suspended particulate matter: A case study from the Lancang River in Southwest China.

River is an important pathway for the biogeochemical cycle of Zn. This study reports Zn concentration and δ66Zn composition for suspended particulate matter (SPM) from Lancang River basin in Southwest China, and explore the impact of natural processes and human activities on Zn cycle. The SPM samples have a much higher average Zn content (162 mg kg-1) than that of the upper crust (67.0 mg kg-1), but it is close to the value of the Pearl River (187 mg kg-1). The enrichment factor (EF) values of Zn in SPM range from 1.08 to 6.88, with an average of 2.15, which does not show significant pollution characteristics. The δ66Zn values in SPM range from -0.67‰ to +0.63‰, with an average of +0.13‰. The δ66Zn values showed positive correlation with Ca/Mg ratios while showed little correlation with Zn contents in SPM. It indicated that anthropogenic sources have limited influence on SPM, and the Zn isotope composition in SPM is more likely to be inherited from the weathered rocks materials and influenced by natural fractionation processes in river water. This result contributes to understanding of the geochemical cycling process of Zn and its environmental effects in water.