Ultrasensitive electrochemical sensor based on synergistic effect of Ag@MXene and antifouling cyclic multifunctional peptide for PD-L1 detection in serum.

A sensing interface co-constructed from the two-dimensional conductive material (Ag@MXene) and an antifouling cyclic multifunctional peptide (CP) is described. While the large surface area of Ag@MXene loads more CP probes, CP binds to Ag@MXene to form a fouling barrier and ensure the structural rigidity of the targeting sequence. This strategy synergistically enhances the biosensor's sensitivity and resistance to contamination. The SPR results showed that the binding affinity of the CP to the target was 6.23 times higher than that of the antifouling straight-chain multifunctional peptide (SP) to the target. In the 10 mg/mL BSA electrochemical fouling test, the fouling resistance of Ag@MXene + CP (composite sensing interface of CP combined with Ag@MXene) was 30 times higher than that of the bare electrode. The designed electrochemical sensor exhibited good selectivity and wide dynamic response range at PD-L1 concentrations from 0.1 to 50 ng/mL. The lowest detection limit was 24.54 pg/mL (S/N = 3). Antifouling 2D materials with a substantial specific surface area, coupled with non-straight chain antifouling multifunctional peptides, offer a wide scope for investigating the sensitivity and antifouling properties of electrochemical sensors.

Dissecting tumor microenvironment from spatially resolved transcriptomics data by heterogeneous graph learning.

Spatially resolved transcriptomics (SRT) has enabled precise dissection of tumor-microenvironment (TME) by analyzing its intracellular molecular networks and intercellular cell-cell communication (CCC). However, lacking computational exploration of complicated relations between cells, genes, and histological regions, severely limits the ability to interpret the complex structure of TME. Here, we introduce stKeep, a heterogeneous graph (HG) learning method that integrates multimodality and gene-gene interactions, in unraveling TME from SRT data. stKeep leverages HG to learn both cell-modules and gene-modules by incorporating features of diverse nodes including genes, cells, and histological regions, allows for identifying finer cell-states within TME and cell-state-specific gene-gene relations, respectively. Furthermore, stKeep employs HG to infer CCC for each cell, while ensuring that learned CCC patterns are comparable across different cell-states through contrastive learning. In various cancer samples, stKeep outperforms other tools in dissecting TME such as detecting bi-potent basal populations, neoplastic myoepithelial cells, and metastatic cells distributed within the tumor or leading-edge regions. Notably, stKeep identifies key transcription factors, ligands, and receptors relevant to disease progression, which are further validated by the functional and survival analysis of independent clinical data, thereby highlighting its clinical prognostic and immunotherapy applications.

Detoxification and underlying mechanisms towards toxic alkaloids by Traditional Chinese Medicine processing: A comprehensive review.

BACKGROUND: Alkaloids have attracted enduring interest worldwide due to their remarkable therapeutic effects, including analgesic, anti-inflammatory, and anti-tumor properties, thus offering a rich source for lead compound design and new drug discovery. However, some of these alkaloids possess intrinsic toxicity. Processing (Paozhi) is a pre-treatment step before the application of herbal medicines in traditional Chinese medicine (TCM) clinics, which has been employed for centuries to mitigate the toxicity of alkaloid-rich TCMs. PURPOSE: To explore the toxicity phenotypes, chemical basis, mode of action, detoxification processing methods, and underlying mechanisms, we can gain crucial insights into the safe and rational use of these toxic alkaloid-rich herbs. Such insights have the great potential to offer new strategies for drug discovery and development, ultimately improving the quality of life for millions of people. METHODS: Literatures published or early accessed until December 31, 2023, were retrieved from databases including PubMed, Web of Science, and CNKI. The following keywords, such as "toxicity", "alkaloid", "detoxification", "processing", "traditional Chinese medicine", "medicinal plant", and "plant", were used in combination or separately for screening. RESULTS: Toxicity of alkaloids in TCM includes hepatotoxicity, nephrotoxicity, neurotoxicity, cardiotoxicity, and other forms of toxicity, primarily induced by pyrrolizidines, quinolizidines, isoquinolines, indoles, pyridines, terpenoids, and amines. Factors such as whether the toxic-alkaloid enriched part is limited or heat-sensitive, and whether toxic alkaloids are also therapeutic components, are critical for choosing appropriate detoxification processing methods. Mechanisms of alkaloid detoxification includes physical removal, chemical decomposition or transformation, as well as biological modifications. CONCLUSION: Through this exploration, we review toxic alkaloids and the mechanisms underlying their toxicity, discuss methods to reduce toxicity, and unravel the intricate mechanisms behind detoxification. These offers insights into the quality control of herbs containing toxic alkaloids, safe and rational use of alkaloid-rich TCMs in clinics, new strategies for drug discovery and development, and ultimately helping improve the quality of life for millions of people.

GLUT3 transcriptional activation by ZEB1 fuels the Warburg effect and promotes ovarian cancer progression.

Ovarian cancer (OvCa) is characterized by early metastasis and high mortality rates, underscoring the need for deeper understanding of these aspects. This study explores the role of glucose transporter 3 (GLUT3) driven by zinc finger E-box-binding homeobox 1 (ZEB1) in OvCa progression and metastasis. Specifically, this study explored whether ZEB1 promotes glycolysis and assessed the potential involvement of GLUT3 in this process in OvCa cells. Our findings revealed that ZEB1 and GLUT3 were excessively expressed and closely correlated in OvCa. Mechanistically, ZEB1 activates the transcription of GLUT3 by binding to its promoter region. Increased expression of GLUT3 driven by ZEB1 dramatically enhances glycolysis, and thus fuels Warburg Effect to promote OvCa progression and metastasis. Consistently, elevated ZEB1 and GLUT3 expression in clinical OvCa is correlated with poor prognosis, reinforcing the profound contribution of ZEB1-GLUT3 axis to OvCa. These results suggest that activation of GLUT3 expression by ZEB1 is crucial for the proliferation and metastasis of OvCa via fueling glycolysis, shedding new light on OvCa treatment.

Computational prediction of protein interactions in single cells by proximity sequencing.

Proximity sequencing (Prox-seq) simultaneously measures gene expression, protein expression and protein complexes on single cells. Using information from dual-antibody binding events, Prox-seq infers surface protein dimers at the single-cell level. Prox-seq provides multi-dimensional phenotyping of single cells in high throughput, and was recently used to track the formation of receptor complexes during cell signaling and discovered a novel interaction between CD9 and CD8 in naïve T cells. The distribution of protein abundance can affect identification of protein complexes in a complicated manner in dual-binding assays like Prox-seq. These effects are difficult to explore with experiments, yet important for accurate quantification of protein complexes. Here, we introduce a physical model of Prox-seq and computationally evaluate several different methods for reducing background noise when quantifying protein complexes. Furthermore, we developed an improved method for analysis of Prox-seq data, which resulted in more accurate and robust quantification of protein complexes. Finally, our Prox-seq model offers a simple way to investigate the behavior of Prox-seq data under various biological conditions and guide users toward selecting the best analysis method for their data.

Dynamic immune recovery process after liver transplantation revealed by single-cell multi-omics analysis.

Elucidating the temporal process of immune remodeling under immunosuppressive treatment after liver transplantation (LT) is critical for precise clinical management strategies. Here, we performed a single-cell multi-omics analysis of peripheral blood mononuclear cells (PBMCs) collected from LT patients (with and without acute cellular rejection [ACR]) at 13 time points. Validation was performed in two independent cohorts with additional LT patients and healthy controls. Our study revealed a four-phase recovery process after LT and delineated changes in immune cell composition, expression programs, and interactions along this process. The intensity of the immune response differs between the ACR and non-ACR patients. Notably, the newly identified inflamed NK cells, CD14+RNASE2+ monocytes, and FOS-expressing monocytes emerged as predictive indicators of ACR. This study illuminates the longitudinal evolution of the immune cell landscape under tacrolimus-based immunosuppressive treatment during LT recovery, providing a four-phase framework that aids the clinical management of LT patients.

Determination of Maximum Tolerable Cold Ischemia Time in a Mouse Model of Cervical Heterotopic Uterus Transplantation.

BACKGROUND: Uterus transplantation (UTx) is an emerging treatment for uterine factor infertility. Determining the maximum tolerable cold ischemia time is crucial for successful UTx. However, the limit for cold ischemia in the uterus is unclear. This study aimed to examine cold ischemia's effects on mouse uteri and identify the maximum cold ischemia duration that uteri can endure. METHODS: We systematically assessed the tolerance of mouse uteri to extended cold ischemia, 24 h, 36 h, and 48 h, using the cervical heterotopic UTx model. Multiple indicators were used to evaluate ischemia-reperfusion injury, including reperfusion duration, macroscopic examination, oxidative stress, inflammation, and histopathology. The function of transplants was evaluated through estrous cycle monitoring and embryo transfer. RESULTS: Mouse uteri subjected to 48 h of cold ischemia exhibited significant delays and insufficiencies in reperfusion, substantial tissue necrosis, and loss of the estrous cycle. Conversely, uteri that underwent cold ischemia within 36 h showed long survival, regular estrous cycles, and fertility. CONCLUSIONS: Our study demonstrated that mouse uteri can endure at least 36 h of cold ischemia, extending the known limits for cold ischemia and providing a pivotal reference for research on the prevention and treatment of cold ischemic injury in UTx.

Musashi-2 potentiates colorectal cancer immune infiltration by regulating the post-translational modifications of HMGB1 to promote DCs maturation and migration.

Post-translational modifications (PTMs) of the non-histone protein high-mobility group protein B1 (HMGB1) are involved in modulating inflammation and immune responses. Recent studies have implicated that the RNA-binding protein (RBP) Musashi-2 (MSI2) regulates multiple critical biological metabolic and immunoregulatory functions. However, the precise role of MSI2 in regulating PTMs and tumor immunity in colorectal cancer (CRC) remains unclear. Here, we present data indicating that MSI2 potentiates CRC immunopathology in colitis-associated colon cancer (CAC) mouse models, cell lines and clinical specimens, specifically via HMGB1-mediated dendritic cell (DC) maturation and migration, further contributes to the infiltration of CD4+ and CD8+ T cells and inflammatory responses. Under stress conditions, MSI2 can exacerbate the production, nucleocytoplasmic transport and extracellular release of damage-associated molecular patterns (DAMPs)-HMGB1 in CRC cells. Mechanistically, MSI2 mainly enhances the disulfide HMGB1 production and protein translation via direct binding to nucleotides 1403-1409 in the HMGB1 3' UTR, and interacts with the cytoplasmic acetyltransferase P300 to upregulate its expression, further promoting the acetylation of K29 residue in HMGB1, thus leading to K29-HMGB1 nucleocytoplasmic translocation and extracellular release. Furthermore, blocking HMGB1 activity with glycyrrhizic acid (Gly) attenuates MSI2-mediated immunopathology and immune infiltration in CRC in vitro and in vivo. Collectively, this study suggests that MSI2 may improve the prognosis of CRC patients by reprogramming the tumor immune microenvironment (TIME) through HMGB1-mediated PTMs, which might be a novel therapeutic option for CRC immunotherapy.

Research on the path of building carbon peak in China based on LMDI decomposition and GA-BP model.

The building sector contributes significantly to carbon emissions, impeding China's progress toward its 2030 carbon emissions peak target due to the limited utilization of renewable energy sources. This study aims to forecast the peak and timing of carbon emissions in China's construction industry to chart a low-carbon roadmap for the sector's future. Initially, an extended logarithmic mean divisia index (LMDI) decomposition model, based on the Kaya identity, is proposed to gauge the contribution levels of driving factors affecting building carbon intensity. Subsequently, a hybrid prediction model (IGA-BP) is constructed, employing an optimized two-hidden-layer neural network via a genetic algorithm, to forecast building carbon emissions and intensity. Additionally, four scenarios are outlined, each defining pathways to simulate emissions peak, carbon peak timing, and intensity within the Chinese building sector from 2020 to 2050. The research findings reveal: (1) The final emission factor of buildings primarily drives the surge in building carbon intensity, while the industrial structure stands as the most significant limiting factor. (2) Compared to alternative models, the proposed hybrid prediction model more effectively captures the evolution pattern of carbon emissions. (3) The prediction results indicate that China's building carbon intensity has reached its peak. Pathway 12 closely aligns with the sector's carbon emissions peak, projecting a peak value of 5.609 billion tons in 2029. To attain this pathway, China needs to develop more precise and feasible emission reduction strategies for its buildings. Overall, the research outcomes furnish robust references for decision-making in future efforts aimed at reducing building emissions.

Single-cell characterization of infiltrating T cells identifies novel targets for gallbladder cancer immunotherapy.

Gallbladder cancer (GBC) is among the most common malignancies of biliary tract system due to its limited treatments. The immunotherapeutic targets for T cells are appealing, however, heterogeneity of T cells hinds its further development. We systematically construct T cell atlas by single-cell RNA sequencing; and utilized the identified gene signatures of high_CNV_T cells to predict molecular subtyping towards personalized therapeutic treatments for GBC. We identified 12 T cell subtypes, where exhausted CD8+ T cells, activated/exhausted CD8+ T cells, and regulatory T cells were predominant in tumors. There appeared to be an inverse relationship between Th17 and Treg populations with Th17 levels significantly reduced, whereas Tregs were concomitantly increased. Furthermore, we first established subtyping criterion to identify three subtypes of GBC based on their pro-tumorigenic microenvironments, e.g., the type 1 group shows more M2 macrophages infiltration, while the type 2 group is infiltrated by highly exhausted CD8+ T cells, B cells and Tregs with suppressive activities. Our study provides valuable insights into T cell heterogeneity and suggests that molecular subtyping based on T cells might provide a potential immunotherapeutic strategy to improve GBC treatment.

Musashi-2 Deficiency Triggers Colorectal Cancer Ferroptosis by Downregulating the MAPK Signaling Cascade to Inhibit HSPB1 Phosphorylation.

BACKGROUND: Musashi-2 (MSI2) is a critical RNA-binding protein (RBP) whose ectopic expression drives the pathogenesis of various cancers. Accumulating evidence suggests that inducing ferroptosis of tumor cells can inhibit their malignant biological behavior as a promising therapeutic approach. However, it is unclear whether MSI2 regulates cell death in colorectal cancer (CRC), especially the underlying mechanisms and biological effects in CRC ferroptosis remain elusive. METHODS: Experimental methods including qRT‒PCR, immunofluorescence, flow cytometry, western blot, co-immunoprecipitation, CCK-8, colony formation assay, in vitro cell transwell migration and invasion assays, in vivo xenograft tumor experiments, liver and lung CRC metastasis models, CAC mice models, transmission electron microscopy, immunohistochemistry, histopathology, 4D label-free proteomics sequencing, bioinformatic and database analysis were used in this study. RESULTS: Here, we investigated that MSI2 was upregulated in CRC and positively correlated with ferroptosis inhibitor molecules. MSI2 deficiency suppressed CRC malignancy by inhibiting cell proliferation, viability, migration and invasion in vitro and in vivo; and MSI2 deficiency triggered CRC ferroptosis by changing the intracellular redox state (ROS levels and lipid peroxidation), erastin induced cell mortality and viability, iron homeostasis (intracellular total irons and ferrous irons), reduced glutathione (GSH) levels and mitochondrial injury. Mechanistically, through 4D-lable free proteomics analysis on SW620 stable cell lines, we demonstrated that MSI2 directly interacted with p-ERK and MSI2 knockdown downregulated the p-ERK/p38/MAPK axis signaling pathway, which further repressed MAPKAPK2 and HPSB1 phosphorylation, leading to decreased expression of PCNA and Ki67 and increased expression of ACSL4 in cancer cells. Furthermore, HSPB1 could rescue the phenotypes of MSI2 deficiency on CRC ferroptosis in vitro and in vivo. CONCLUSIONS: This study indicates that MSI2 deficiency suppresses the growth and survival of CRC cells and promotes ferroptosis by inactivating the MAPK signaling pathway to inhibit HSPB1 phosphorylation, which leads to downregulation of PCNA and Ki67 and upregulation of ACSL4 in cancer cells and subsequently induces redox imbalance, iron accumulation and mitochondrial shrinkage, ultimately triggering ferroptosis. Therefore, targeted inhibition of MSI2/MAPK/HSPB1 axis to promote ferroptosis might be a potential treatment strategy for CRC.

Temsirolimus is a promising immunomodulatory agent for enhanced transplantation outcomes.

BACKGROUND: Identifying effective immunosuppressive strategies is critical for addressing immunological rejection following organ transplantation. This study explores the potential immunosuppressive effects and mechanisms of temsirolimus, a rapamycin derivative, in organ transplantation. METHODS: A mouse cardiac allograft model was established using a cervical cannula technique with BALB/c donors and C57BL/6 recipients. Mice were administered temsirolimus intragastrically and graft survival was evaluated. Histological staining was used to assess pathological changes. The BrdU assay was used to measure splenic T cell proliferation. Flow cytometry was used to quantify regulatory T cells (Tregs), CD4+ T cells, and CD8+ T cells. ELISA and qPCR assays were used to determine Foxp3, IL-4, IFN-γ, and TGF-ß expression. RESULTS: Temsirolimus displayed potent immunosuppressive effects at 20 mg/kg/day, significantly inhibiting T cell proliferation (84.6%, P < 0.0001) and prolonging graft survival (median 49 days vs. 8.5 days in controls, P < 0.0001). However, median survival decreased to 34.5 days upon withdrawal. Temsirolimus also reduced splenic CD4+ and CD8+ T cells (2.85% and 2.92%, P < 0.001) and antibody levels (IgM, IgG1, IgG2) by 11.85-29.09% (P < 0.0001) and increased Tregs, Foxp3, IL-4 (P < 0.01), and TGF-ß (P < 0.05), while decreasing IFN-γ (P < 0.001). CONCLUSIONS: Temsirolimus exhibited potent immunosuppressive effects, emerging as a strong candidate to mitigate organ transplant rejection.

SIRT2 inhibitor SirReal2 enhances anti-tumor effects of PI3K/mTOR inhibitor VS-5584 on acute myeloid leukemia cells.

BACKGROUND: Acute myeloid leukemia (AML) is a highly aggressive form of cancer that is frequently diagnosed in adults and small molecule inhibitors have gained significant attention as a potential treatment option for AML. METHODS: The up-regulated genes in AML were identified through bioinformatics analysis. Potential candidate agents were selected through pharmacogenomics analysis. Proteomic experiments were conducted to determine the molecular mechanism after inhibitor treatment. To evaluate drug synergy, both cellular functional experiments and an AML mouse model were used. RESULTS: Through bioinformatics analysis, we conducted a screening for genes that are highly expressed in AML, which led to the identification of nine small-molecule inhibitors. Among these inhibitors, the PI3K/mTOR inhibitor VS-5584 demonstrated significant effectiveness in inhibiting AML cell proliferation at low concentrations. Further testing revealed that VS-5584 induced apoptosis and cycle arrest of AML cells in a dose- and time-dependent manner. Proteomics analysis showed significant changes in protein expression profiles of AML cells after VS-5584 treatment, with 287 proteins being down-regulated and 71 proteins being up-regulated. The proteins that exhibited differential expression were primarily involved in regulating the cell cycle and apoptosis, as determined by GO analysis. Additionally, KEGG analysis indicated that the administration of VS-5584 predominantly affected the P53 and SIRT2 signaling pathways. The use of SIRT2 inhibitor SirReal2 alongside VS-5584 caused a significant reduction in the half-maximal inhibitory concentration (IC50 ) of VS-5584 on AML cells. In vivo, experiments suggested that VS-5584 combined with SirReal2 suppressed tumor growth in the subcutaneous model and extended the survival rate of mice injected with tumor cells via tail vein. CONCLUSIONS: Taken together, the PI3K/mTOR inhibitor VS-5584 was effective in suppressing AML cell proliferation. PI3K/mTOR inhibitor combined with SIRT2 inhibitor exhibited a synergistic inhibitory effect on AML cells. Our findings offer promising therapeutic strategies and drug candidates for the treatment of AML.

Computational prediction of protein interactions on single cells by proximity sequencing.

Proximity sequencing (Prox-seq) measures gene expression, protein expression, and protein complexes at the single cell level, using information from dual-antibody binding events and a single cell sequencing readout. Prox-seq provides multi-dimensional phenotyping of single cells and was recently used to track the formation of receptor complexes during inflammatory signaling in macrophages and to discover a new interaction between CD9/CD8 proteins on naïve T cells. The distribution of protein abundance affects identification of protein complexes in a complicated manner in dual-binding assays like Prox-seq. These effects are difficult to explore with experiments, yet important for accurate quantification of protein complexes. Here, we introduce a physical model for protein dimer formation on single cells and computationally evaluate several different methods for reducing background noise when quantifying protein complexes. Furthermore, we developed an improved method for analysis of Prox-seq single-cell data, which resulted in more accurate and robust quantification of protein complexes. Finally, our model offers a simple way to investigate the behavior of Prox-seq under various biological conditions and guide users toward selecting the best analysis method for their data.

Perspectives and trends in advanced optical and electrochemical biosensors based on engineered peptides.

With the advancement of life medicine, in vitro diagnostics (IVD) technology has become an auxiliary tool for early diagnosis of diseases. However, biosensors for IVD now face some disadvantages such as poor targeting, significant antifouling properties, low density of recognized molecules, and poor stability. In recent years, peptides have been demonstrated to have various functions in unnatural biological systems, such as targeting properties, antifouling properties, and self-assembly properties, which indicates that peptides can be engineered. These properties of peptides, combined with their good biocompatibility, can be well applied to the design of biosensors to solve the problems mentioned above. This review provides an overview of the properties of engineered functional peptides and their applications in enhancing biosensor performance, mainly in the field of optics and electrochemistry.

PD-L1 exosomes electrochemical sensor based on coordination of AgNCs and Zr4+: Multivalent peptide enhancing target capture efficiency and antifouling performance.

Programmed death ligand 1 (PD-L1) exosomes are important biomarkers of immune activation in the initial stages of treatment and can predict clinical responses to PD-1 blockade in various cancer patients. However, traditional PD-L1 exosome bioassays face challenges such as high interface fouling in complex detection environments, limited detection specificity, and poor clinical serum applicability. Inspired by the multi-branched structure of trees, a biomimetic tree-like multifunctional antifouling peptide (TMAP)-assisted electrochemical sensor was developed for high-sensitivity exosomes detection. Multivalent interaction of TMAP significantly enhances the binding affinity of PD-L1 exosomes, thanks to the designed branch antifouling sequence, TMAPs antifouling performance is further improved. The addition of Zr4+ forms coordination bonds with the exosome's lipid bilayer phosphate groups to achieve highly selective and stable binding without interference from protein activity. The specific coordination between AgNCs and Zr4+ contributes to a dramatic change in the electrochemical signals, and lowing detection limit. The designed electrochemical sensor exhibited excellent selectivity and a wide dynamic response within the PD-L1 exosome concentration range from 78 to 7.8 × 107 particles/mL. Overall, the multivalent binding ability of TMAP and the signal amplification characteristics of AgNCs have a certain driving role in achieving clinical detection of exosomes.

Investigation and Analysis of Risk Factors and Psychological Status of Chronic Obstructive Pulmonary Disease in Permanent Residents Aged 40 or Older in Hongyuan County, Aba Prefecture, Sichuan Province.

Background: COPD is an important public health problem worldwide, and there is a lack of epidemiological data on COPD in high-altitude areas in Sichuan province. Thus, we aimed to investigate the prevalence, risk factors and psychological status of COPD in Hongyuan County, Aba Prefecture, Sichuan Province, which is located at an average altitude of 3507 meters. Methods: The 40 years old or greater permanent residents of Hongyuan County were selected by random sampling method, and the lung function test and questionnaires were conducted to determine the disease situation of COPD. The prevalence of COPD was compared among different factors of investigation, and multivariate logistic regression analysis was used for different factors to determine the independent influencing factors of COPD disease. Results: A total of 456 permanent residents aged 40 years or older in Hongyuan County, 436 qualified for quality control, among which 53 cases confirmed COPD, the total prevalence was 12.16%, among which the prevalence was 14.55% for men and it was 8.07% for women. There were significant differences in different gender, ethnicity, age, smoking status, smoking years, educational level, heating style, history of tuberculosis, and prevalence of BMI (P <0.05). Binary logistic regression analysis showed that age ≥60 years (OR = 2.810, 95% CI: 1.0457.557), Han Nationality (OR: 3.238, 95% CI: 1.290-8.127), the heating method including biofuels (OR: 18.119, 95% CI: 4.140-79.303) and coals (OR: 6.973, 95% CI: 1.856-26.200), medical history of pulmonary tuberculosis (OR: 2.670, 95% CI: 1.278-5.578), the education level including junior high school (OR: 3.336, 95% CI: 1.2259.075), high school and above (OR: 5.910, 95% CI: 1.796-19.450), and smoking (OR: 10.774, 95% CI: 3.622-32.051) were independent risk factors for COPD disease. The prevalence of anxiety was 16.98%, and the prevalence of depression was 13.2%. Conclusion: The prevalence of COPD in Hongyuan County was higher than the national level; age, ethnic group, education, smoking, heating method, and history of tuberculosis are the independent influencing factors of COPD in Hongyuan County. The prevalence of anxiety and depression is low.

Pharmacological ascorbate potentiates combination nanomedicines and reduces cancer cell stemness to prevent post-surgery recurrence and systemic metastasis.

Conventional chemotherapy targets proliferative cancer cells to halt tumor progression or regress tumors. However, the plasticity of tumor cells enables their phenotypical changes to acquire chemo-resistance, leading to treatment failure or tumor recurrence after a successful treatment course. Here, we report the use of high-dose pharmacologic ascorbate to potentiate treatment efficacy of nanoscale coordination polymers (NCPs) delivering two clinical combinations of chemotherapeutics, carboplatin/docetaxel and oxaliplatin/SN38, and to target metabolic plasticity of tumor cells. Combination treatments of high-dose ascorbate and NCPs overcome multi-drug resistance by significantly reducing the abundance of cancer stem cells (CSCs) in solid tumors, as evidenced by reduced expression of tumor pluripotency factors. The clearance of CSCs inhibits post-surgery recurrence and systemic metastasis in multiple mouse models of cancer.

Genotype-guided model significantly improves accuracy of tacrolimus initial dosing after liver transplantation.

Background: The initial dose of tacrolimus after liver transplantation (LT) is critical for rapidly achieving the steady state of the drug concentration, minimizing the potential adverse reactions and warranting long-term patient prognosis. We aimed to develop and validate a genotype-guided model for determining personalized initial dose of tacrolimus. Methods: By combining pharmacokinetic modeling, pharmacogenomic analysis and multiple statistical methods, we developed a genotype-guided model to predict individualized tacrolimus initial dose after LT in the discovery (n = 150) and validation cohorts (n = 97) respectively. This model was further validated in a prospective, randomized and single-blind clinical trial from August, 2021 to February, 2022 (n = 40, ChiCTR2100050288). Findings: Our model included donor's and recipient's genotypes, recipient's weight and total bilirubin, which achieved an area under the curve of receiver operating characteristic curve (AUC of ROC) of 0.88 and 0.79 in the discovery and validation cohorts, respectively. We found that patients who were given tacrolimus within the recommended concentration range (RCR) (4-10 ng/mL), the new-onset metabolic syndromes are lower, especially for new-onset diabetes (p = 0.043). In the clinical trial, compared to those in experience-based (EB) group, patients in the model-based (MB) group were more likely to achieving the RCR (75% vs 40%, p = 0.025) with a more variable individualized dose (0.023-0.096 mg/kg/day vs 0.045-0.057 mg/kg/day). Moreover, significantly fewer medication adjustments were required for the MB group than the EB group (2.75 ± 2.01 vs 6.05 ± 3.35, p = 0.001). Interpretation: Our genotype-based model significantly improved the initial dosing accuracy of tacrolimus and reduced the number of medication adjustments, which are critical for improving the prognosis of LT patients. Funding: National Natural Science Foundation of China, Shanghai three-year action plan, National Science and Technology Major Project of China.

Raspberry-Like Gold Nanoparticles Based On Nanoclusters Anchored on Cyclodextrin-Functionalized Nanoparticles: Synthesis and Ultrasensitive Electrochemical Detection of Chromium(VI) Ions.

A facile synthetic strategy is devised to construct raspberry like gold nanoparticles (RbNPs) formed by gold nanoclusters wrapped around ß-cyclodextrin functionalized gold nanoparticles (CD-AuNPs@AuNCs). An efficient and sensitive electrochemical sensor for the detection of Cr(VI) has been developed based on RbNPs. The sensing platform exhibits an excellent wide linear range (100 pg mL-1 to 10 µg mL-1 ), extremely low detection limit (40.91 fg mL-1 i. e. 0.79 pM), which may pave a new way to fabricate other ultrasensitive electrochemical sensors based on the designed RbNPs.