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Abstract This phase III trial aimed to compare ARX788, a site-specific, construct-homogeneous antibody-drug conjugate, with lapatinib plus capecitabine in patients with human epidermal growth factor receptor 2 (HER2)-positive advanced breast cancer (ABC) who had progressed on one line of trastuzumab based regimen. Eligible patients were randomized (1:1) to receive ARX788 (1.5 mg/kg, IV, Q3W) or lapatinib plus capecitabine (LC: lapatinib 1250 mg QD; capecitabine 1000 mg/m2 BID, days 1–14, Q3W) and stratified by prior chemotherapy lines (0-1 versus >1) and visceral metastasis (yes versus no). The primary outcome was progression-free survival (PFS) assessed by a blinded independent central review (BICR). A total of 441 patients were randomly assigned to receive either ARX788 (n = 221) or LC (n = 220). The median PFS was 11.3 (95% confidence interval [CI], 8.4–13.8) months with ARX788 compared with 8.2 (95% CI, 6.9–8.7) months with LC, as per BICR (hazard ratio [HR] 0.64, p = 0.0006). Frequencies of treatment-related adverse events (TRAEs) of any grade were 98.6% and 99.1% for ARX788 and LC, respectively. Grade ≥3 TRAEs were 41.4% and 40.0%, respectively, the most common adverse events were blurred vision (12.3%), dry eye (9.1%), keratopathy (5.9%), and interstitial lung disease (ILD, 5.9%) with ARX788; hand-foot syndrome (18.1%) and hypokalemia (5.1%) with LC; all the hematological and gastrointestinal events of grade ≥3 with ARX788 were less than 3%. Six treatment-related deaths occurred, with three cases possibly related to ILD. ARX788 significantly improved PFS compared with LC in patients with HER2-positive ABC with a distinct toxicity profile, supporting it as a potential treatment option.

Abstract Non-nucleotide stimulators of interferon gene (STING) agonists hold promise as immunotherapeutic agents for postsurgical adjuvant treatment of tumors. However, their limited effect duration hampers therapeutic effectiveness, necessitating prolonged administration of multiple doses that heightens infection risk and impacts patient compliance. Here, we develop an implantable dual-drug depot in a sandwich-like configuration, with a non-nucleotide STING agonist (MSA-2) in the outer layers of 3D-printed scaffolds and an immunogenic apoptosis inducer (doxorubicin, DOX) in the inner layer of electrospun fibers. We discover that MSA-2 can elicit endoplasmic reticulum stress-mediated and general immunogenic apoptosis of cancer cells. The stimulations with tumor-associated antigens and damage-associated molecular patterns from cancer cells, along with proinflammatory factors secreted by matured dendritic cells and M1-polarized macrophages, can depolymerize intracellular microtubules guiding activated STING trafficking towards lysosomes for degradation. Collectively, the dual-drug depots can initiate a long-lasting cascaded immunotherapy and chemotherapy, suppressing postsurgical tumor recurrence and metastasis.

Abstract Background Patients suffer from esophageal squamous cell carcinoma (ESCC), which is the ninth highly aggressive malignancy. Tumor-infiltrating immune cells (TIIC) exert as major component of the tumor microenvironment (TME), showing possible prognostic value in ESCC. Methods Transcriptome data and scRNA-seq data of ESCC samples were extracted from the GEO and TCGA databases. Tissue Specific Index (TSI) was defined to identify potential TIIC-RNAs from the TME. Twenty machine learning algorithms were further applied to evaluate the prognostic efficacy of TIIC signature score. Gene colocalization analysis was performed. Differences in CNV on chromosomes and SNP sites of prognostic model genes were calculated. Results The most reliable model of TIIC signature score was developed based on three prognostic TIIC-RNAs. It showed a higher C-index than any other reported prognostic models. ESCC patients with high TIIC signature score showed poorer survival outcomes than low TIIC signature score. The activity of most immune cells decreased with the increase of TIIC score. TIIC signature score showed difference in the expression levels and methylation levels of DEGs. There was also significant different correlation with the degree of CNV amplification and CNV deletion of the immune checkpoint genes. Gene colocalization analysis showed two prognostic model genes (ATP6V0E1 and BIRC2). MR analysis found that rs148710154 and rs75146099 SNP sites of TIIC-RNA gene had a significant correlation between them gastro-oesophageal reflux and ESCC. Conclusion TIIC signature score was the first time developed which provided a novel strategy and guidance for the prognosis and immunotherapy of ESCC. It also gave the evidence in the important role of immune cells from the TME in the treatment of cancers.

The specific induction of hepatic differentiation presents a significant challenge in developing alternative liver cell sources and viable strategies for clinical therapy of acute liver failure (ALF). The past decade has witnessed the blossom of microRNAs in regenerative medicine. Herein, microRNA 122-functionalized tetrahedral framework nucleic acid (FNA-miR-122) has emerged as an unprecedented and potential platform for directing the hepatic differentiation of adipose-derived mesenchymal stem cells (ADMSCs), which offers a straightforward and cost-effective method for generating functional hepatocyte-like cells (FNA-miR-122-iHep). Additionally, we have successfully established a liver organoid synthesis strategy by optimizing the co-culture of FNA-miR-122-iHep with endothelial cells (HUVECs), resulting in functional Hep:HUE-liver spheroids. Transcriptome analysis not only uncovered the potential molecular mechanisms through which miR-122 influences hepatic differentiation in ADMSCs, but also clarified that Hep:HUE-liver spheroids could further facilitate hepatocyte maturation and improved tissue-specific functions, which may provide new hints to be used to develop a hepatic organoid platform. Notably, compared to transplanted ADMSCs and Hep-liver spheroid, respectively, both FNA-miR-122-iHep-based single cell therapy and Hep:HUE-liver spheroid-based therapy showed high efficacy in treating ALF in vivo. Collectively, this research establishes a robust system using microRNA to induce ADMSCs into functional hepatocyte-like cells and to generate hepatic organoids in vitro, promising a highly efficient therapeutic approach for ALF.

BackgroundThe use of highly active antiretroviral therapy has transformed AIDS into a chronic infectious disease, but issues of chronic inflammation and immune system activation persist. Modulating the gut microbiome of patients may improve this situation, yet the specific association mechanisms between HIV and the gut microbiome remain unclear. This study aims to explore the research hotspots and trends of the HIV and the gut microbiome, providing direction for future research.MethodsWe conducted a search of the Web of Science Core Collection database up to April 30, 2024 to retrieve articles related to the relationship between the HIV and the gut microbiome. The scientific achievements and research frontiers in this field were analyzed using CiteSpace, VOSviewer, and Bibliometrix statistical software.ResultsAs of April 30, 2024, a total of 379 articles met the inclusion criteria. The number of publications in this field peaked in 2023, and the number of articles published after 2020 declined. The country with the highest number of publications was the United States (184 articles), and the institution with the most publications was the University of Colorado (USA) (21 articles). The author with the most publications was Routy Jean-Pierre (Canada) (14 articles). High-frequency keywords, aside from the key terms, included “HIV,” “inflammation,” “immune activation,” “gut microbiota,” and “translocation.” Keyword burst results indicated that short-chain fatty acids, T cells and obesity might become the focus of future research.ConclusionThe research hotspots in this field should prioritize examining the role of the primary gut microbiome metabolite, short-chain fatty acids, in reducing immune system activation and inflammation. Another emerging area of interest could be the investigation into the annual increase in obesity rates within this field. Furthermore, understanding the metabolic mechanisms of short-chain fatty acids in T cells is essential. Additionally, multi-omics analysis holds potential.

More than 90% of deaths due to breast cancer (BC) are due to metastasis-related complications, with invasive ductal carcinoma (IDC) of the breast being the most common pathologic type of breast cancer and highly susceptible to metastasis to distant organs. BC patients who develop cancer metastases are more likely to have a poor prognosis and poor quality of life, so it is extremely important to recognize and diagnose whether distant metastases have occurred in IDC as early as possible. In this study, we develop a non-invasive breast cancer classification system for detecting cancer metastasis. We used Anaconda-Jupyter notebooks to develop various Python programming modules for text mining, data processing, and machine learning (ML) methods. A risk prediction model was constructed based on four algorithms: Random Forest, XGBoost, Logistic Regression, and SVM. Additionally, we developed a hybrid model based on a voting mechanism using these four algorithms as the base models. The models were compared and evaluated by the following metrics: accuracy, precision, recall, F1-score, and area under the ROC curve (AUC) values. The experimental results show that the hybrid model based on the voting mechanism exhibits the best prediction performance (accuracy: 0.867, precision: 0.929, recall: 0.805, F1-score: 0.856, AUC: 0.94). This stable risk prediction model provides a valuable reference support for doctors in assessing and diagnosing the risk of IDC hematogenous metastasis. It also improves the work efficiency of doctors and strives to provide patients with increased chances of survival.

To provide autonomous and accurate time service for deep space missions, a pulsar observation–based timekeeping method is documented in this paper, which utilizes pulsars as the time information source. Firstly, the pulsar observation noise is remodeled as the combination of the Gaussian noise and colored noise, and the detailed expression of the colored noise is presented in the paper. An improved Grey model (GM) is proposed to describe the onboard clock evolution, which models the grey action quantity as a time-varying coefficient and attenuates the dependence of the model on the initial state. On the basis of the modified observation noise model and GM, an unscented Kalman filtering (UKF) is adopted to estimate the onboard clock error. Numerical experiments are conducted to analyze the validity of the proposed method and the impact of spacecraft positioning error and pulsar selection on the proposed method. The proposed method offers an autonomous solution for onboard timekeeping in deep space missions.

Pulmonary arterial hypertension (PAH) is a malignant cardiovascular disease with a complex etiology, in which several types of cells play important roles. Sex differences in disease susceptibility and survival have been observed in PAH patients, but few studies have analyzed the effect of changes in cell type and number on sex differences in PAH at the single-cell level. In this study, we performed a series of analyses on GSE169471 and GSE228644 datasets and found significant changes in the ratio of several types of cells in male PAH lung tissues. Surprisingly, we found that the ratio of macrophages in male PAH samples was 7 times higher than that in females. Consistently, the ratio of M1 macrophages was also significantly increased in male PAH samples. The different expression genes (DEGs) in macrophages were mainly involved in the ribosome pathway, which is closely related to cell proliferation. Inhibition of ribosomal protein L39 (RPL39), a core gene in the ribosome pathway, can inhibit macrophage proliferation and attenuate the sex differences in PAH. In conclusion, our study suggests that ribosome pathway–associated cell proliferation of macrophages might be associated with sex differences in PAH.

Summary: Avian coccidiosis is a widespread intestinal disease found in poultry that causes substantial economic losses. To extensively investigate the molecular mechanism of drug resistance in Eimeria tenella, we analyzed the sporozoites and second-generation merozoites of drug-sensitive (DS), diclazuril-resistant (DZR) strain, and salinomycin-resistant (SMR) strains of E. tenella through transcriptome sequencing. Whole genome sequencing analyses were performed on resistant strains at different concentrations—11 sensitive strains, 16 field diclazuril-resistant strains, and 15 field salinomycin-resistant strains of E. tenella. Co-analysis indicated that the ABC transporter protein showed differential expression and base mutations in the two resistant strains compared with the DS strain. KEGG pathway analysis demonstrated that the expression of pABAS and HPPK-DHPS, which are associated with the folate biosynthetic pathway, showed downregulation only in the DZR strain with respect to the DS strain. Several key enzymes in the glycolytic pathway were differentially expressed between DS and SMR strains.

Alternanthera philoxeroides (Mart.) Griseb is a well-known invasive plant species worldwide. Cinnamomum camphora (L.) Presl. is a plant species that is rich in allelopathic substances which can impede the growth of many other plants. In this study, the allelopathic effects of C. camphora on the growth and development, and physiological-biochemical characteristics of A. philoxeroides were investigated. The findings revealed that the leaves of C. camphora exhibited the capability to suppress the asexual reproduction of A. philoxeroides. The addition of C. camphora leaves resulted in inhibition of the fresh weight, stem length, and stem node number of A. philoxeroides new stems, with the strength of inhibition increasing in proportion to the quantity of C. camphora leaves added. Furthermore, the inhibitory effect of C. camphora leaves on A. philoxeroides was significantly amplified under high temperatures (≥ 30°C). Two allelochemicals had strong inhibitory effects on the vegetative reproduction of A. philoxeroides. The inhibition intensities were all up to 100 % on stem vegetative propagation, were 90.40 % and 100 % on root vegetative propagation from camphor and linalool, respectively. Physiological-biochemical analyses of roots indicated that the two allelochemicals promoted the accumulation of hydrogen peroxide and MDA, disrupting the balance of antioxidant enzyme systems. The two allelochemicals had a strong inhibitory effect on CAT activity and a strong promoting effect on POD activity. The effect on SOD activity was greatly affected by the type and concentration of allelochemicals. Moreover, the two allelochemicals significantly inhibited the accumulation of osmotic regulating substance. The contents of soluble sugar, soluble protein, and proline were significantly down-regulated. In summary, the allelochemicals from C. camphora induced damage to biological membranes, disrupting antioxidant enzyme systems and inhibiting osmoregulation. This resulted in the retardation of growth, development, and potential mortality of A. philoxeroides. These findings would contribute to the knowledge base for A. philoxeroides prevention and control, and enrich the understanding of C. camphora allelopathic substances.

Enhancing the capabilities of unmanned space exploration, such as satellite monitoring and space science missions, requires efficient and reliable nuclear power systems. A viable solution is found in the 1–10 kWe power level of space nuclear reactor power systems, offering advantages such as a manageable research and development process, and relatively low investment requirements. This paper introduces a conceptual design for a 5 kWe space nuclear reactor power system, outlining its components and characteristics. The study includes a thorough analysis of potential challenges, encompassing heat pipe failure accidents, re-entry scenarios, and weight estimation considerations. The results demonstrate that the proposed space nuclear reactor power system effectively meets the safety requirements. The total mass of the power system is estimated at approximately 1.5 tons, with a specific mass of around 300 kg/kWe. This research contributes valuable insights for the design of space nuclear reactor power systems operating within a similar power range.

Cholesterol aggregation in dendritic cells (DCs) triggers an inflammatory response and accelerates the development of atherosclerosis (AS). Resveratrol (RES), a natural compound with anti-inflammatory and cholesterol metabolism regulatory properties, has been shown to influence the maturation and inflammatory functions of DCs. However, its relationship with cholesterol metabolism remains unclear. This study aimed to explore the roles of RES in cholesterol metabolism and inflammatory behaviors of DCs in the context of AS. We analyzed the effect of RES on cholesterol efflux from ApoE−/− bone marrow-derived dendritic cells (BMDCs) using qRT-PCR, Western blot, and cholesterol efflux assays; identified the inflammatory status of RES-treated BMDCs and co-cultured T cells using flow cytometry and ELISA; confirmed the effect of RES on blood lipids, atherosclerotic lesions, cholesterol metabolism, and inflammatory response in high-fat diet and lipopolysaccharide-treated ApoE−/− mice; and explored the potential targets of RES in regulating inflammatory behavior via molecular docking. The results revealed that RES promotes cholesterol efflux, increases the expression of efflux transporter ABCA1, and decreases liver X receptor alpha (LXRα) expression in response to a decrease in intracellular cholesterol in ApoE−/− BMDCs. RES also reduced MHC-II+ cells and downregulated costimulatory molecule CD80 in BMDCs with decreased IL-6 and increased IL-2 production, and suppressed T-cell activation and modulates IL-22 and IL-10 secretion via BMDCs. Furthermore, we confirmed that RES relieves arterial lesions and regulates blood lipids in ApoE−/− mice. RES demonstrated ABCA1 upregulation and LXRα downregulation effects in the aorta and regulated costimulation molecules and Th17/Treg cytokines in the spleen. Furthermore, RES showed multiple hydrogen bonding and low binding energy with ABCA1, suggesting that ABCA1 is a potential target of RES to modulate the inflammatory properties of BMDCs. Our study demonstrated that RES regulates cholesterol efflux and inflammatory behavior in BMDCs, contributing to the control of AS progression and offering new insights for managing inflammatory diseases.

Morphine has a crucial role in treating both moderate to severe pain and chronic pain. However, prolonged administration of morphine can lead to tolerance of analgesia, resulting in increased doses and poor treatment of pain. Many patients, such as those with terminal cancer, require high doses of morphine for long periods. Addressing morphine tolerance can help this group of patients to escape pain, and the mechanisms behind this need to be investigated. Microglia are the key cells involved in morphine tolerance and chronic morphine administration leads to microglia activation, which in turn leads to activation of internal microglia signalling pathways and protein transcription, ultimately leading to the release of inflammatory factors. Inhibiting the activation of microglia internal signalling pathways can reduce morphine tolerance. However, the exact mechanism of how morphine acts on microglia and ultimately leads to tolerance is unknown. This article discusses the mechanisms of morphine induced microglia activation, reviews the signalling pathways within microglia and the associated therapeutic targets and possible drugs, and provides possible directions for clinical prevention or retardation of morphine induced analgesic tolerance.

Abstract Background Clear cell carcinoma of the kidney is a common urological malignancy characterized by poor patient prognosis and treatment outcomes. Modulation of vasculogenic mimicry in tumor cells alters the tumor microenvironment and the influx of tumor-infiltrating lymphocytes, and the combination of its inducers and immune checkpoint inhibitors plays a synergistic role in enhancing antitumor effects. Methods We downloaded the data from renal clear cell carcinoma samples and vasculogenic mimicry-related genes to establish a new vasculogenic mimicry-related index (VMRI) using a machine learning approach. Based on VMRI, patients with renal clear cell carcinoma were divided into high VMRI and low VMRI groups, and patients’ prognosis, clinical features, tumor immune microenvironment, chemotherapeutic response, and immunotherapeutic response were systematically analyzed. Finally, the function of CDH5 was explored in renal clear cell carcinoma cells. Results VMRI can be used for prognostic and immunotherapy efficacy prediction in a variety of cancers, which consists of four vasculogenic mimicry-related genes (CDH5, MMP9, MAPK1, and MMP13), is a reliable predictor of survival and grade in patients with clear cell carcinoma of the kidney and has been validated in multiple external datasets. We found that the high VMRI group presented higher levels of immune cell infiltration, which was validated by pathological sections. We performed molecular docking prediction of vasculogenic mimicry core target proteins and identified natural small molecule drugs with the highest affinity for the target protein. Knockdown of CDH5 inhibited the proliferation and migration of renal clear cell carcinoma. Conclusions The VMRI identified in this study allows for accurate prognosis assessment of patients with renal clear cell carcinoma and identification of patient populations that will benefit from immunotherapy, providing valuable insights for future precision treatment of patients with renal clear cell carcinoma.

Abstract Background The Corona Virus Disease 2019 (COVID-19) pandemic has struck globally. Whether the related proteins of retinoic acid (RA) signaling pathway are causally associated with the risk of COVID-19 remains unestablished. We conducted a two-sample Mendelian randomization (MR) study to assess the associations of retinol, retinol binding protein 4 (RBP4), retinol dehydrogenase 16 (RDH16) and cellular retinoic acid binding protein 1 (CRABP1) with COVID-19 in European population. Methods The outcome utilized the summary statistics of COVID-19 from the COVID-19 Host Genetics Initiative. The exposure data were obtained from public genome wide association study (GWAS) database. We extracted SNPs from exposure data and outcome data. The inverse variance weighted (IVW), MR-Egger and Wald ratio methods were employed to assess the causal relationship between exposure and outcome. Sensitivity analyses were performed to ensure the validity of the results. Results The MR estimates showed that retinol was associated with lower COVID-19 susceptibility using IVW (OR: 0.69, 95% CI: 0.53–0.90, P: 0.0065), whereas the associations between retinol and COVID-19 hospitalization or severity were not significant. RBP4 was associated with lower COVID-19 susceptibility using the Wald ratio (OR: 0.83, 95% CI: 0.72–0.95, P: 0.0072). IVW analysis showed RDH16 was associated with increased COVID-19 hospitalization (OR: 1.10, 95% CI: 1.01–1.18, P: 0.0199). CRABP1 was association with lower COVID-19 susceptibility (OR: 0.95, 95% CI: 0.91–0.99, P: 0.0290) using the IVW. Conclusions We found evidence of possible causal association of retinol, RBP4, RDH16 and CRABP1 with the susceptibility, hospitalization and severity of COVID-19. Our study defines that retinol is significantly associated with lower COVID-19 susceptibility, which provides a reference for the prevention of COVID-19 with vitamin A supplementation.

N6-methyladenosine (m6A) is the most prevalent internal chemical modification in eukaryotic messenger RNA (mRNA), significantly impacting its lifecycle through dynamic and reversible processes involving methyltransferase, demethylase, and binding proteins. These processes regulate mRNA stability, splicing, nuclear export, translation, and degradation. Programmed cell death (PCD), a tightly controlled process encompassing apoptosis, pyroptosis, ferroptosis, autophagy, and necroptosis, plays a crucial role in maintaining cellular homeostasis, tissue development, and function. Recently, m6A modification has emerged as a significant research area due to its role in regulating PCD and its implications in cardiovascular diseases (CVDs). In this review, we delve into the intricate relationship between various PCD types and m6A modification, emphasizing their pivotal roles in the initiation and progression of CVDs such as myocardial ischemia-reperfusion (I/R), atherosclerosis (AS), pulmonary hypertension (PH), cardiomyopathy, doxorubicin (Dox)-induced cardiotoxicity (DIC), heart failure (HF), and myocardial infarction (MI). Our findings underscore the potential of elucidating the roles of m6A and PCD in CVD to pave new pathways for prevention and treatment strategies.

ABSTRACT Metabolic exchange plays a crucial role in shaping microbial community interactions and functions, including the exchange of small molecules such as cofactors. Cofactors are fundamental to enzyme catalytic activities; however, the role of cofactors in microbial stress tolerance is unclear. Here, we constructed a synergistic consortium containing two strains that could efficiently mineralize di-(2-ethylhexyl) phthalate under hyperosmotic stress. Integration of transcriptomic analysis, metabolic profiling, and a genome-scale metabolic model (GEM) facilitated the discovery of the potential mechanism of microbial interactions. Multi-omics analysis revealed that the vitamin B12-dependent methionine-folate cycle could be a key pathway for enhancing the hyperosmotic stress tolerance of synergistic consortium. Further GEM simulations revealed interspecies exchange of S-adenosyl-L-methionine and riboflavin, cofactors needed for vitamin B12 biosynthesis, which was confirmed by in vitro experiments. Overall, we proposed a new mechanism of bacterial hyperosmotic stress tolerance: bacteria might promote the production of vitamin B12 to enhance biofilm formation, and the species collaborate with each other by exchanging cofactors to improve consortium hyperosmotic stress tolerance. These findings offer new insights into the role of cofactors in microbial interactions and stress tolerance and are potentially exploitable for environmental remediation.IMPORTANCEMetabolic interactions (also known as cross-feeding) are thought to be ubiquitous in microbial communities. Cross-feeding is the basis for many positive interactions (e.g., mutualism) and is a primary driver of microbial community assembly. In this study, a combination of multi-omics analysis and metabolic modeling simulation was used to reveal the metabolic interactions of a synthetic consortium under hyperosmotic stress. Interspecies cofactor exchange was found to promote biofilm formation under hyperosmotic stress. This provides a new perspective for understanding the role of metabolic interactions in microbial communities to enhance environmental adaptation, which is significant for improving the efficiency of production activities and environmental bioremediation.

Abstract Liver fibrosis is a chronic pathological condition lacking specific clinical treatments. Stem cells, with notable potential in regenerative medicine, offer promise in treating liver fibrosis. However, stem cell therapy is hindered by potential immunological rejection, carcinogenesis risk, efficacy variation, and high cost. Stem cell secretome‐based cell‐free therapy offers potential solutions to address these challenges, but it is limited by low delivery efficiency and rapid clearance. Herein, an innovative approach for in situ implantation of smart microneedle (MN) arrays enabling precisely controlled delivery of multiple therapeutic agents directly into fibrotic liver tissues is developed. By integrating cell‐free and platinum‐based nanocatalytic combination therapy, the MN arrays can deactivate hepatic stellate cells. Moreover, they promote excessive extracellular matrix degradation by more than 75%, approaching normal levels. Additionally, the smart MN arrays can provide hepatocyte protection while reducing inflammation levels by ≈70–90%. They can also exhibit remarkable capability in scavenging almost 100% of reactive oxygen species and alleviating hypoxia. Ultimately, this treatment strategy can effectively restrain fibrosis progression. The comprehensive in vitro and in vivo experiments, supplemented by proteome and transcriptome analyses, substantiate the effectiveness of the approach in treating liver fibrosis, holding immense promise for clinical applications.

ObjectivePatient satisfaction reflects the social benefits of hospitals and is an important indicator of hospital performance. This study explores the mechanism through which inpatients’ trust in physicians, self-efficacy, and participation in medical decision-making impact their satisfaction with medical services.MethodsA questionnaire was administered to 814 inpatients in 10 randomly selected tertiary hospitals and 10 randomly selected secondary hospitals in Hangzhou, China. A correlation analysis and hierarchical linear regression were conducted to analyze the factors influencing inpatient satisfaction.ResultsThe outcome measures of trust in physicians and participation in medical decision-making behaviors had significant positive effects on inpatient satisfaction.Trust in physicians was shown to directly influence inpatient satisfaction, while inpatient participation in decision-making partially mediated this relationship. Inpatient participation in medical decision-making fully mediated the relationship between self-efficacy and inpatient satisfaction.ConclusionWhile inpatients were relatively satisfied, there is room for improvement. Healthcare providers should improve patient trust by actively listening to their needs and providing feedback, establishing effective communication mechanisms. Patient self-efficacy can be enhanced through health education, special lectures, and case sharing. Patients should also be encouraged to actively participate in medical decision-making.Practical implicationsBased on inpatient feedback during a preliminary survey, we refined this study’s questionnaire to enhance its feasibility for future research. This article shares key findings for healthcare managers and providers, advising that patient satisfaction can be enhanced through trust, self-efficacy, and participation.

BackgroundType 1 diabetes mellitus (T1DM) is a chronic metabolic disease that seriously jeopardizes human physical and mental health and reduces quality of life. Intestinal flora is one of the critical areas of exploration in T1DM research.ObjectiveThis study aims to explore the research hotspot and development trend of T1DM and intestinal flora to provide research direction and ideas for researchers.MethodsWe used the Web of Science (WOS) Core Collection and searched up to 18 November 2023, for articles on studies of the correlation between T1DM and intestinal flora. CiteSpace, VOSviewers and R package “bibliometrix” were used to conduct this bibliometric analysis.ResultsEventually, 534 documents met the requirements to be included, and as of 18 November 2023, there was an upward trend in the number of publications in the field, with a significant increase in the number of articles published after 2020. In summary, F Susan Wong (UK) was the author with the most publications (21), the USA was the country with the most publications (198), and the State University System of Florida (the United States) was the institution with the most publications (32). The keywords that appeared more frequently were T cells, fecal transplants, and short-chain fatty acids. The results of keywords with the most robust citation bursts suggest that Faecalibacterium prausnitzii and butyrate may become a focus of future research.ConclusionIn the future, intestinal flora will remain a research focus in T1DM. Future research can start from Faecalibacterium prausnitzii and combine T cells, fecal bacteria transplantation, and short-chain fatty acids to explore the mechanism by which intestinal flora affects blood glucose in patients with T1DM, which may provide new ideas for the prevention and treatment of T1DM.

Cover crops between rows in orchards can improve the development of soil resources and increase agricultural productivity. However, there have been few reports of cover crops that can act as a “green manure” in apple orchards across arid and semiarid zones. This study investigated the effects of planting interrow vegetation on soil properties and apple tree performance during a 32-month experiment. There were six treatments: clean cultivation as a control; natural grass planting; planting with ryegrass; planting with alfalfa; planting with tall fescue; and planting with villous wild pea cover crops. The treatments primarily affected the 0- to 20-cm surface soil layer. Soil carbon, nitrogen, and enzyme levels initially decreased (during the first 12–24 months); then, they increased (24–32 months). The cover crops significantly increased nutrient contents (soluble organic carbon, microbial carbon and nitrogen, alkaline dissolved nitrogen, nitrate nitrogen, and ammonium nitrogen) in the 0- to 20-cm soil layer by more than 19.6% and increased the related enzyme activities by more than 25.2%. The alfalfa and wild pea alleys had a stronger effect on the soil environment than the control, natural grass, ryegrass, and tall fescue alley treatments; however, after 32 months, the alfalfa treatment inhibited fruit tree growth and development. This was unexpected because alfalfa seemed to have a positive effect on soil fertility characteristics. Under local ecological conditions, villous wild pea had the greatest effect on apple orchard productivity and significantly increased short branching by 15.9%, fruit weight per fruit by 12.6%, yield per plant by 8.6%, and soluble sugar content by 10.5% compared with clean cultivation. The correlation analysis showed that there were significant or highly significant positive correlations between fruit tree performance and soil carbon, nitrogen, and enzyme activity levels as the soil layer depth increased. Therefore, under local ecological conditions, cover crops have a greater effect on orchard surface soil fertility than on deeper soils, and intercropping with villous wild pea potentially produces the greatest improvement in apple orchard productivity.

Abstract Ovarian cancer is the leading cause of gynecological cancer-related death. Drug resistance is the bottleneck in ovarian cancer treatment. The increasing use of novel drugs in clinical practice poses challenges for the treatment of drug-resistant ovarian cancer. Continuing to classify drug resistance according to drug type without understanding the underlying mechanisms is unsuitable for current clinical practice. We reviewed the literature regarding various drug resistance mechanisms in ovarian cancer and found that the main resistance mechanisms are as follows: abnormalities in transmembrane transport, alterations in DNA damage repair, dysregulation of cancer-associated signaling pathways, and epigenetic modifications. DNA methylation, histone modifications and noncoding RNA activity, three key classes of epigenetic modifications, constitute pivotal mechanisms of drug resistance. One drug can have multiple resistance mechanisms. Moreover, common chemotherapies and targeted drugs may have cross (overlapping) resistance mechanisms. MicroRNAs (miRNAs) can interfere with and thus regulate the abovementioned pathways. A subclass of miRNAs, “epi-miRNAs”, can modulate epigenetic regulators to impact therapeutic responses. Thus, we also reviewed the regulatory influence of miRNAs on resistance mechanisms. Moreover, we summarized recent phase I/II clinical trials of novel drugs for ovarian cancer based on the abovementioned resistance mechanisms. A multitude of new therapies are under evaluation, and the preliminary results are encouraging. This review provides new insight into the classification of drug resistance mechanisms in ovarian cancer and may facilitate in the successful treatment of resistant ovarian cancer.

Abstract Background Lipid metabolism plays a pivotal role in asthma pathogenesis. However, a comprehensive analysis of the importance of lipid metabolism-related genes (LMRGs) in regulating the immune microenvironment in asthma remains lacking. The transcriptome matrix was downloaded from the Gene Expression Omnibus (GEO) dataset. Differentially expressed analysis and weighted gene coexpression network analysis (WGCNA) were conducted on the GSE74986 dataset to select hub LMRGs, and gene set enrichment analysis (GSEA) was conducted to explore their biological functions. The CIBERSORT algorithm was used to determine immune infiltration in the asthma and control groups, and the correlation of diagnostic biomarkers and immune cells was performed via Spearman correlation analysis. Subsequently, a competitive endogenous RNA (ceRNA) network was constructed to investigate the hidden molecular mechanism of asthma. The expression levels of the hub genes were further validated in the GSE143192 dataset, and RT‒qPCR and immunofluorescence were performed to verify the reliability of the results in the OVA asthma model. Lastly, the ceRNA network was confirmed by qRT-PCR and RNAi experiments in the characteristic cytokine (IL-13)-induced asthma cellular model. Results ASAH1, ACER3 and SGPP1 were identified as hub LMRGs and were mainly involved in protein secretion, mTORC1 signaling, and fatty acid metabolism. We found more infiltration of CD8+ T cells, activated NK cells, and monocytes and less M0 macrophage infiltration in the asthma group than in the healthy control group. In addition, ASAH1, ACER3, and SGPP1 were negatively correlated with CD8+ T cells and activated NK cells, but positively correlated with M0 macrophages. Within the ceRNA network, SNHG9-hsa-miR-615-3p-ACER3, hsa-miR-212-5p and hsa-miR-5682 may play crucial roles in asthma pathogenesis. The low expression of ASAH1 and SGPP1 in asthma was also validated in the GSE74075 dataset. After SNHG9 knockdown, miR-615-3p expression was significantly upregulated, while that of ACER3 was significantly downregulated. Conclusion ASAH1, ACER3 and SGPP1 might be diagnostic biomarkers for asthma, and are associated with increased immune system activation. In addition, SNHG9-hsa-miR-615-3p-ACER3 may be viewed as effective therapeutic targets for asthma. Our findings might provide a novel perspective for future research on asthma.

Organoids, recognized as invaluable models in tumor and stem cell research, assume a pivotal role in the meticulous analysis of diverse datasets pertaining to their growth dynamics, drug screening processes and related phenomena. However, the manual scrutiny and conventional statistical methodologies employed in handling organoid data often grapple with challenges such as diminished precision and efficiency, heightened complexity, escalated human resource requirements, and a degree of subjectivity. Acknowledging the remarkable efficacy of artificial intelligence (AI) in the realms of biology and medicine, the incorporation of AI into organoid research stands poised to enhance the objectivity, precision and expediency of analyses. This integration empowers organoids to more effectively fulfill objectives such as disease modeling, drug screening and precision medicine. Notably, significant strides have been made in AI-driven analyses of organoid image data. The amalgamation of deep learning into image analysis facilitates a more meticulous delineation of the microstructural intricacies and nuanced changes within organoids, achieving a level of accuracy akin to that of experts. This not only elevates the precision of organoid morphology and growth recognition, but also contributes to substantial time and cost savings in research endeavors. Furthermore, the infusion of AI technology has yielded breakthroughs in the processing of organoid omics data, resulting in heightened efficiency in data processing and the identification of latent gene expression patterns. This furnishes novel tools for comprehending cellular development and unraveling the intricate mechanisms underlying various diseases. In addition to image data, AI techniques applied to diverse organoid datasets, encompassing electrical signals and spectra, have realized an unbiased classification of organoid types and states, embarking on a comprehensive journey towards characterizing organoids holistically. In the pivotal domain of drug screening for organoids, AI emerges as a stalwart companion, providing robust support for real-time process monitoring and result prediction. Leveraging high-content microscopy images and sophisticated deep learning models, researchers can dynamically monitor organoid responses to drugs, effecting non-invasive detection of drug impacts and amplifying the precision and efficiency of drug screening processes. Despite the significant strides made by AI in organoid research, challenges persist, encompassing hurdles in data acquisition, constraints in sample quality and quantity, and quandaries associated with model interpretability. Overcoming these challenges necessitates dedicated future research efforts aimed at enhancing data consistency, fortifying model interpretability, and exploring methodologies for the seamless fusion of multimodal data. Such endeavors are poised to usher in a more comprehensive and dependable application of AI in organoid research. In summation, the integration of AI technology introduces unparalleled opportunities to organoid research, resulting in noteworthy advancements. Nevertheless, interdisciplinary research and collaborative efforts remain imperative to navigate challenges and propel the more profound integration of AI into organoid research. The future holds promise for AI to assume an even more prominent role in advancing organoid research toward clinical translation and precision medicine.

Optical coherence tomography (OCT) offers high-resolution imaging of internal finger structures, making it attractive for fingerprint recognition. Anti-spoofing research in OCT includes both static and liveness anti-spoofing. Liveness anti-spoofing is commonly detected by additional detection equipment or by extracting the liveness information from the OCT data. However, previous methods suffer from long data acquisition and computation times as well as low recognition accuracy. To address these problems, this paper proposes a fast liveness anti-spoofing method. The method requires no additional detection equipment, is fast in data acquisition and calculation, and has high computational accuracy. This study not only explores the method's effectiveness but also performs parameter analysis and optimization on multiple scales. In addition, this paper presents a comprehensive mathematical model that enables various types of OCT devices to calculate the optimal anti-counterfeiting parameters under different conditions. The experimental results show that this method can substantially improve the accuracy and real-time performance of anti-spoofing, and applies to various types of OCT systems, has a promising application in fingerprint identification and other medical diagnostic fields.

Raman spectroscopy is a powerful tool for identifying substances, yet accurately analyzing mixtures remains challenging due to overlapping spectra. This study aimed to develop a deep learning-based framework to improve the identification of components in mixtures using Raman spectroscopy. We propose a three-branch feature fusion network that leverages spectral pairwise comparison and a multi-head self-attention mechanism to capture both local and global spectral features. To address limited data availability, traditional data augmentation techniques were combined with deep convolutional generative adversarial networks (DCGAN) to expand the dataset. Our framework significantly outperformed existing Raman spectroscopy-based methods in both qualitative and quantitative analyses. The model demonstrated superior accuracy compared to U-Net and ResNext, achieving higher detection accuracy for mixture components. This framework offers a promising solution for improving mixture identification in Raman spectroscopy, with potential applications in industries such as pharmaceuticals, food safety, and environmental monitoring.

This study aims to investigate the impact of straw addition on soil activation effects under different tillage practices, providing a scientific basis for establishing reasonable straw return measures in the southern Northeast Plain, thus enhancing soil fertility, and mitigating greenhouse effects. Soil samples were collected from various straw return practices that were conducted continuously for two years as follows: rotary tillage without straw return (RTO), deep tillage combined with straw incorporation (PT), rotary tillage with straw incorporation (RT), and no-till with straw cover (NT). The samples were incubated in the dark at 25 °C for 70 days. We measured the CO2 release rate and cumulative release, apparent activation effect, soil organic carbon, active microbial biomass organic carbon, soluble organic carbon, and easily oxidizable organic carbon to clarify the effects of straw addition on soil activation under different tillage practices. The results indicate that a straw addition promotes the mineralization of soil organic carbon while also increasing the content of active organic carbon components. The CO2 release rates and cumulative release under different tillage practices were as follows: PT > NT > RT. The contents of the active microbial biomass organic carbon, soluble organic carbon, and easily oxidizable organic carbon increased by 16.62% to 131.88%, 4.36% to 57.59%, and 12.10% to 57.97%, respectively, compared to the control without the straw addition. Except for the RT practice, the addition of straw significantly enhanced the instability of soil organic carbon in the PT, NT, and RTO practices, with increases of 51.75%, 48.29%, and 27.90%, respectively. Different straw return practices altered the physical and chemical properties of the soil, resulting in significant differences in the strength of the apparent activation effect. Notably, the apparent activation effect of RT was reduced by 86.42% compared to RTO, while that of NT was reduced by 36.99% compared to PT. A highly significant positive correlation was observed between the apparent activation effect and the unstable carbon components in the soil, indicating that higher levels of easily decomposable organic carbon corresponded to stronger apparent activation effects. In conclusion, it is recommended that in this region, rotary tillage should be adopted for straw return in the first 2 to 3 years, as this practice is beneficial for the formation and stabilization of organic carbon in the short term. As the duration of straw return increases, adjustments can be made based on the degree of soil organic carbon retention and soil fertility status.

The conventional Ant Colony Optimization (ACO) algorithm, applied to logistics robot path planning in a two-dimensional grid environment, encounters several challenges: slow convergence rate, susceptibility to local optima, and an excessive number of turning points in the planned paths. To address these limitations, an improved ant colony algorithm has been developed. First, the heuristic function is enhanced by incorporating artificial potential field (APF) attraction, which introduces the influence of the target point’s attraction on the heuristic function. This modification accelerates convergence and improves the optimization performance of the algorithm. Second, an additional pheromone increment, calculated from the difference in pheromone levels between the best and worst paths of the previous generation, is introduced during the pheromone update process. This adjustment adaptively enhances the path length optimality. Lastly, a triangle pruning method is applied to eliminate unnecessary turning points, reducing the number of turns the logistics robot must execute and ensuring a more direct and efficient path. To validate the effectiveness of the improved algorithm, extensive simulation experiments were conducted in two grid-based environments of varying complexity. Several performance indicators were utilized to compare the conventional ACO algorithm, a previously improved version, and the newly proposed algorithm. MATLAB simulation results demonstrated that the improved ant colony algorithm significantly outperforms the other methods in terms of path length, number of iterations, and the reduction of inflection points, confirming its superiority in logistics robot path planning.

Abstract Background The European LeukemiaNet (ELN) risk classification system for acute myeloid leukemia (AML) patients has been used worldwide. In 2022, the ELN risk classification system modified risk genes including CEBPA mutation status, myelodysplasia‐related (MR) gene mutations and internal tandem duplications of FLT3 (FLT3‐ITD). Methods We include newly diagnosed de novo AML patients at our center from January 2017 to December 2021, regardless of the further treatment received. Clinical data and date of survival were included. Survival analysis were performed using the Kaplan–Meier method, and the log‐rank test was used to compare survival between different risk groups. Results We include 363 newly diagnosed de novo AML patients from 2017 to 2021 to assess the accuracy of the ELN risk classification system. Their survival results show that the ELN‐2022 risk classification system is not superior to the ELN‐2017 version; for patients with FLT3‐ITD mutations but without FLT3 inhibitor treatment, their survival is similar to the ELN‐2022 adverse risk group. The ELN‐2022 risk classification system cannot accurately clarify ECOG performance status (PS) 2–4 patients, especially in the ELN‐2022 favorable risk group. Conclusion The ELN‐2022 risk stratification system may not be appropriate for patients unable to receive intensive therapy or FLT3 inhibitor; more real‐world data is needed to straify patients with worse ECOG PS and inferior intensive therapy.

Abstract The YOLOv4 approach has gained significant popularity in industrial object detection due to its impressive real-time processing speed and relatively favorable accuracy. However, it has been observed that YOLOv4 faces challenges in accurately detecting small objects. Its bounding box regression strategy is rigid and fails to effectively leverage the asymmetric characteristics of objects, limiting its ability to enhance object detection accuracy. This paper proposes an enhanced version of YOLOv4 called KR–AL–YOLO (keypoint regression strategy and angle loss based YOLOv4). The KR–AL–YOLO approach introduces two customized modules: an keypoint regression strategy and an angle-loss function. These modules contribute to improving the algorithm’s detection accuracy by enabling more precise localization of objects. Additionally, KR–AL–YOLO adopts an improved feature fusion technique, which facilitates enhanced information flow within the network, thereby further enhancing accuracy performance. Experimental evaluations conducted on the COCO2017 dataset demonstrate the effectiveness of the proposed method. KR–AL–YOLO achieves an average precision of 45.6%, surpassing both YOLOv4 and certain previously developed one-stage detectors. The utilization of keypoint regression strategy and the incorporation of robust feature fusion contribute to superior object detection accuracy in KR–AL–YOLO compared to YOLOv4.

As the most abundant liver-specific microRNA, microRNA-122 (miR122) played a crucial role in the differentiation of stem cells into hepatocytes. However, highly efficient miR122 delivery still confronts challenges including poor cellular uptake and easy biodegradation. Herein, we for the first time demonstrated that the tetrahedral DNA (TDN) nanoplatform had great potential in inducing the differentiation of human mesenchymal stem cells (hMSCs) into functional hepatocyte-like cells (HLCs) by transferring the liver-specific miR122 to hMSCs efficiently without any extrinsic factors. As compared with miR122, miR122-functionalized TDN (TDN-miR122) could significantly up-regulate the protein expression levels of mature hepatocyte markers and hepatocyte-specific marker genes in hMSCs, indicating that TDN-miR122 could particularly activate the hepatocyte-specific properties of hMSCs for developing cell-based therapies in vitro. The transcriptomic analysis further indicated the potential mechanism that TDN-miR122 assisted hMSCs differentiated into functional HLCs. The TDN-miR122-hMSCs exhibited hepatic cell morphology phenotype, significantly up-regulated specific hepatocyte genes and hepatic biofunctions in comparison with the undifferentiated MSCs. Preclinical in vivo transplantation appeared that TDN-miR122-hMSCs in combination with or without TDN could efficiently rescue acute liver failure injury through hepatocyte function supplement, anti-apoptosis, cellular proliferation promotion, and anti-inflammatory. Collectively, our findings may provide a new and facile approach for hepatic differentiation of hMSCs for acute liver failure therapy. Further large animal model explorations are needed to study their potential in clinical translation in the future.

Reactive oxygen species (ROS)-associated oxidative stress, inflammation storm, and massive hepatocyte necrosis are the typical manifestations of acute liver failure (ALF), therefore specific therapeutic interventions are essential for the devastating disease. Here, we developed a platform consisting of versatile biomimetic copper oxide nanozymes (Cu NZs)-loaded PLGA nanofibers (Cu NZs@PLGA nanofibers) and decellularized extracellular matrix (dECM) hydrogels for delivery of human adipose-derived mesenchymal stem/stromal cells-derived hepatocyte-like cells (hADMSCs-derived HLCs) (HLCs/Cu NZs@fiber/dECM). Cu NZs@PLGA nanofibers could conspicuously scavenge excessive ROS at the early stage of ALF, and reduce the massive accumulation of pro-inflammatory cytokines, herein efficiently preventing the deterioration of hepatocytes necrosis. Moreover, Cu NZs@PLGA nanofibers also exhibited a cytoprotection effect on the transplanted HLCs. Meanwhile, HLCs with hepatic-specific biofunctions and anti-inflammatory activity acted as a promising alternative cell source for ALF therapy. The dECM hydrogels further provided the desirable 3D environment and favorably improved the hepatic functions of HLCs. In addition, the pro-angiogenesis activity of Cu NZs@PLGA nanofibers also facilitated the integration of the whole implant with the host liver. Hence, HLCs/Cu NZs@fiber/dECM performed excellent synergistic therapeutic efficacy on ALF mice. This strategy using Cu NZs@PLGA nanofiber-reinforced dECM hydrogels for HLCs in situ delivery is a promising approach for ALF therapy and shows great potential for clinical translation.

For ceramic breeder pebbles used in fusion energy, the tritium release data under fusion neutron irradiation is very important and valuable. In this study, a tritium release system for ceramic tritium breeder is introduced, which is matched with the High Intensity DT Fusion Neutron Generator (HINEG-CAS). The HINEG-CAS has been built and operated by the Institute of Nuclear Energy Safety Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences (INEST, HFIPS, CAS), achieving a fusion neutron yield of 1012n/s since 2016. Innovative design and fabrication of sample container enables minimization of the unexpected tritium loss. The dedicated tritium release system can monitor the tritium release behavior over time for both tritiated water and tritium gas, using the bubblers-based tritium trapping system with automatic replacement technology, coupled with highly efficient catalytic oxidants and liquid scintillation counter (LSC). We have performed a tritium release experiment with the Li2TiO3 pebbles as ceramic tritium breeder, and obtained the tritium releasing data at room temperature over time and clarified the tritium chemical form in recovery. It is concluded that this newly established system can serve as a good sharing platform for evaluating prime candidate breeder materials, as well as facilitating detailed design or optimization of tritium involved systems (such as the tritium extraction system).