Integrated analysis reveals a novel 5-fluorouracil resistance-based prognostic signature with promising implications for predicting the efficacy of chemotherapy and immunotherapy in patients with colorectal cancer.

BACKGROUND: 5-Fluorouracil (5-FU) has been used as a standard first-line treatment for colorectal cancer (CRC) patients. Although 5-FU-based chemotherapy and immune checkpoint blockade (ICB) have achieved success in treating CRC, drug resistance and low response rates remain substantial limitations. Thus, it is necessary to construct a 5-FU resistance-related signature (5-FRSig) to predict patient prognosis and identify ideal patients for chemotherapy and immunotherapy. METHODS: Using bulk and single-cell RNA sequencing data, we established and validated a novel 5-FRSig model using stepwise regression and multiple CRC cohorts and evaluated its associations with the prognosis, clinical features, immune status, immunotherapy, neoadjuvant therapy, and drug sensitivity of CRC patients through various bioinformatics algorithms. Unsupervised consensus clustering was performed to categorize the 5-FU resistance-related molecular subtypes of CRC. The expression levels of 5-FRSig, immune checkpoints, and immunoregulators were determined using quantitative real-time polymerase chain reaction (RT‒qPCR). Potential small-molecule agents were identified via Connectivity Map (CMap) and molecular docking. RESULTS: The 5-FRSig and cluster were confirmed as independent prognostic factors in CRC, as patients in the low-risk group and Cluster 1 had a better prognosis. Notably, 5-FRSig was significantly associated with 5-FU sensitivity, chemotherapy response, immune cell infiltration, immunoreactivity phenotype, immunotherapy efficiency, and drug selection. We predicted 10 potential compounds that bind to the core targets of 5-FRSig with the highest affinity. CONCLUSION: We developed a valid 5-FRSig to predict the prognosis, chemotherapeutic response, and immune status of CRC patients, thus optimizing the therapeutic benefits of chemotherapy combined with immunotherapy, which can facilitate the development of personalized treatments and novel molecular targeted therapies for patients with CRC.

DNA metabarcoding reveals ecological patterns and driving mechanisms of archaeal, bacterial, and eukaryotic communities in sediments of the Sansha Yongle Blue Hole.

The Sansha Yongle Blue Hole (SYBH) is the world's deepest marine blue hole with unique physicochemical characteristics. However, our knowledge of the biodiversity and community structure in SYBH sediments remains limited, as past studies have mostly focused on microbial communities in the water column. Here, we collected sediment samples from the aerobic zone (3.1 to 38.6 m) and the deep anaerobic zone (150 m, 300 m) of the SYBH and extracted DNA to characterize the archaeal, bacterial, and eukaryotic communities inhabiting these sediments. Our results showed that the archaeal and bacterial communities were dominated by Thaumarchaeota and Proteobacteria, respectively. The dominant taxa of eukaryotes in different sites varied greatly, mainly including Phaeophyceae, Annelida, Diatomea and Arthropoda. All three examined domains showed clear vertical distributions and significant differences in community composition between the aerobic and anaerobic zones. Sulfide played a prominent role in structuring the three domains, followed by salinity, nitrous oxide, pH, temperature and dissolved oxygen, all of which were positively correlated with the turnover component, the main contributor to beta diversity. Neutral community model revealed that stochastic processes contributed to more than half of the community variations across the three domains. Co-occurrence network showed an equal number of positive and negative interactions in the archaeal network, while positive interactions accounted for ~ 80% in the bacterial and eukaryotic networks. Our findings reveal the ecological features of prokaryotes and eukaryotes in SYBH sediments and shed new light on community dynamics and survival strategies in the special environment of marine blue holes.

Integrated analysis of ceRNA-miRNA changes in paraquat-induced pulmonary epithelial-mesenchymal transition via high-throughput sequencing.

Recent studies have shown that epithelial-mesenchymal transition (EMT) plays an important role in paraquat (PQ)-induced tissue fibrosis, which is the main cause of death in patients with PQ poisoning. However, no effective treatment for pulmonary interstitial fibrosis caused by PQ poisoning exists. It is of great significance for us to find new therapeutic targets through bioinformatics in PQ-induced EMT. We conducted transcriptome sequencing to determine the expression profiles of 1210 messenger RNAs (mRNAs), 558 long noncoding RNAs, 28 microRNAs (miRNAs), including 18 known-miRNAs, 10 novel-miRNAs and 154 circular RNAs in the PQ-exposed EMT group mice. Using gene ontology and Kyoto Encyclopaedia of Genes and Genomes analyses, we identified the pathways associated with signal transduction, cancers, endocrine systems and immune systems were involved in PQ-induced EMT. Furthermore, we constructed long noncoding RNA-miRNA-mRNA interrelated networks and found that upregulated genes included Il22ra2, Mdm4, Slc35e2 and Angptl4, and downregulated genes included RGS2, Gabpb2, Acvr1, Prkd3, Sp100, Tlr12, Syt15 and Camk2d. Thirteen new potential competitive endogenous RNA targets were also identified for further treatment of PQ-induced pulmonary tissue fibrosis. Through further study of the pathway and networks, we may identify new molecular targets in PQ-induced pulmonary EMT.

MAGP2 promotes osteogenic differentiation during fracture healing through its crosstalk with the ß-catenin pathway.

Osteogenic differentiation is important for fracture healing. Microfibrial-associated glycoprotein 2 (MAGP2) is found to function as a proangiogenic regulator in bone formation; however, its role in osteogenic differentiation during bone repair is not clear. Here, a mouse model of critical-sized femur fracture was constructed, and the adenovirus expressing MAGP2 was delivered into the fracture site. Mice with MAGP2 overexpression exhibited increased bone mineral density and bone volume fraction (BV/TV) at Day 14 postfracture. Within 7 days postfracture, overexpression of MAGP2 increased collagen I and II expression at the fracture callus, with increasing chondrogenesis. MAGP2 inhibited collagen II level but elevated collagen I by 14 days following fracture, accompanied by increased endochondral bone formation. In mouse osteoblast precursor MC3T3-E1 cells, MAGP2 treatment elevated the expression of osteoblastic factors (osterix, BGLAP and collagen I) and enhanced ALP activity and mineralization through activating ß-catenin signaling after osteogenic induction. Besides, MAGP2 could interact with lipoprotein receptor-related protein 5 (LRP5) and upregulated its expression. Promotion of osteogenic differentiation and ß-catenin activation mediated by MAGP2 was partially reversed by LRP5 knockdown. Interestingly, ß-catenin/transcription factor 4 (TCF4) increased MAGP2 expression probably by binding to MAGP2 promoter. These findings suggest that MAGP2 may interact with ß-catenin/TCF4 to enhance ß-catenin/TCF4's function and activate LRP5-activated ß-catenin signaling pathway, thus promoting osteogenic differentiation for fracture repair. mRNA sequencing identified the potential targets of MAGP2, providing novel insights into MAGP2 function and the directions for future research.

Management of acute carbamazepine poisoning: A narrative review.

Standard management protocols are lacking and specific antidotes are unavailable for acute carbamazepine (CBZ) poisoning. The objective of this review is to provide currently available information on acute CBZ poisoning, including its management, by describing and summarizing various therapeutic methods for its treatment according to previously published studies. Several treatment methods for CBZ poisoning will be briefly introduced, their advantages and disadvantages will be analyzed and compared, and suggestions for the clinical treatment of CBZ poisoning will be provided. A literature search was performed in various English and Chinese databases. In addition, the reference lists of identified articles were screened for additional relevant studies, including non-indexed reports. Non-peer-reviewed sources were also included. In the present review, 154 articles met the inclusion criteria including case reports, case series, descriptive cohorts, pharmacokinetic studies, and in vitro studies. Data on 67 patients, including 4 fatalities, were reviewed. Based on the summary of cases reported in the included articles, the cure rate of CBZ poisoning after symptomatic treatment was 82% and the efficiency of hemoperfusion was 58.2%. Based on the literature review, CBZ is moderately dialyzable and the recommendation for CBZ poisoning is supportive management and gastric lavage. In severe cases, extracorporeal treatment is recommended, with hemodialysis as the first choice.

Computational identification and clinical validation of a novel risk signature based on coagulation-related lncRNAs for predicting prognosis, immunotherapy response, and chemosensitivity in colorectal cancer patients.

Background: Coagulation is critically involved in the tumor microenvironment, cancer progression, and prognosis assessment. Nevertheless, the roles of coagulation-related long noncoding RNAs (CRLs) in colorectal cancer (CRC) remain unclear. In this study, an integrated computational framework was constructed to develop a novel coagulation-related lncRNA signature (CRLncSig) to stratify the prognosis of CRC patients, predict response to immunotherapy and chemotherapy in CRC, and explore the potential molecular mechanism. Methods: CRC samples from The Cancer Genome Atlas (TCGA) were used as the training set, while the substantial bulk or single-cell RNA transcriptomics from Gene Expression Omnibus (GEO) datasets and real-time quantitative PCR (RT-qPCR) data from CRC cell lines and paired frozen tissues were used for validation. We performed unsupervised consensus clustering of CRLs to classify patients into distinct molecular subtypes. We then used stepwise regression to establish the CRLncSig risk model, which stratified patients into high- and low-risk groups. Subsequently, diversified bioinformatics algorithms were used to explore prognosis, biological pathway alteration, immune microenvironment, immunotherapy response, and drug sensitivity across patient subgroups. In addition, weighted gene coexpression network analysis was used to construct an lncRNA-miRNA-mRNA competitive endogenous network. Expression levels of CRLncSig, immune checkpoints, and immunosuppressors were determined using RT-qPCR. Results: We identified two coagulation subclusters and constructed a risk score model using CRLncSig in CRC, where the patients in cluster 2 and the low-risk group had a better prognosis. The cluster and CRLncSig were confirmed as the independent risk factors, and a CRLncSig-based nomogram exhibited a robust prognostic performance. Notably, the cluster and CRLncSig were identified as the indicators of immune cell infiltration, immunoreactivity phenotype, and immunotherapy efficiency. In addition, we identified a new endogenous network of competing CRLs with microRNA/mRNA, which will provide a foundation for future mechanistic studies of CRLs in the malignant progression of CRC. Moreover, CRLncSig strongly correlated with drug susceptibility. Conclusion: We developed a reliable CRLncSig to predict the prognosis, immune landscape, immunotherapy response, and drug sensitivity in patients with CRC, which might facilitate optimizing risk stratification, guiding the applications of immunotherapy, and individualized treatments for CRC.

Identification of Diagnostic Metabolic Signatures in Thyroid Tumors Using Mass Spectrometry Imaging.

"Gray zone" thyroid follicular tumors are difficult to diagnose, especially when distinguishing between benign follicular thyroid adenoma (FTA) and malignant carcinoma (FTC). Thus, proper classification of thyroid follicular diseases may improve clinical prognosis. In this study, the diagnostic performance of metabolite enzymes was evaluated using imaging mass spectrometry to distinguish FTA from FTC and determine the association between metabolite enzyme expression with thyroid follicular borderline tumor diagnosis. Air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFAIDESI-MSI) was used to build a classification model for thyroid follicular tumor characteristics among 24 samples. We analyzed metabolic enzyme marker expression in an independent validation set of 133 cases and further evaluated the potential biological behavior of 19 thyroid borderline lesions. Phospholipids and fatty acids (FAs) were more abundant in FTA than FTC (p < 0.001). The metabolic enzyme panel, which included FA synthase and Ca2+-independent PLA2, was further validated in follicular thyroid tumors. The marker combination showed optimal performance in the validation group (area under the ROC, sensitivity, and specificity: 73.6%, 82.1%, and 60.6%, respectively). The findings indicate that AFAIDESI-MSI, in combination with low metabolic enzyme expression, could play a role in the diagnosis of thyroid follicular borderline tumors for strict follow-up.

Changes in COVID-19 vaccine hesitancy at different times among residents in Guangzhou, China.

Background: Vaccination as a fundamental pillar of promoting public health and interest is critical to limiting the COVID-19 pandemic. However, many citizens are still hesitant about this epidemic prevention measure. This article aimed to understand the COVID-19 vaccination and hesitancy rates among Guangzhou residents at different points in time as well as to explore the relevant factors that cause vaccination hesitancy. Methods: We conducted a total of nine cross-sectional surveys by enrolling 12,977 questionnaires among Guangzhou residents through the online survey software called "WenJuanXing" between April 2021 and December 2022, and residents made their choices by judging their willingness to vaccinate. These surveys collected data on the participants' sociodemographic characteristics, vaccination status, vaccine hesitancy, and factors influencing this hesitancy. The Chi-squared test was used for univariate analysis and the multivariate logistic regression model was used to further adjust the influence of the confounding factors to evaluate the main factors affecting the hesitancy of the COVID-19 vaccine at different periods. Results: Over the course of 2021-2022, a total of 12,977 residents in the study area were surveyed. The vaccine hesitancy rates fluctuated over time. From April to June 2021, the vaccine hesitancy rate decreased from 30% to 9.1% and then increased to 13.7% in November. However, from April to December 2022, the hesitancy rate continued to rise from 13.4% to 30.4%. Vaccination rates, the epidemic waves of COVID-19, and changes in policies may all be possible factors that contributed to these fluctuations in vaccine hesitancy rates. We found statistically significant correlations between factors, such as residence, education, and occupation, and vaccine hesitancy at certain points of time. The results of the surveys in April and June 2021 showed that rural residents showed higher vaccine hesitancy rate than urban residents. Their lower education level was associated with higher vaccine hesitancy. Workers and farmers are more likely to have vaccine hesitancy than people with other occupations. The univariate analysis showed that people with underlying medical conditions and lower perceived health status were more likely to experience vaccine hesitation. Logistic regression analysis revealed that the health status of individuals is the most important factor leading to vaccine hesitancy, and residents' underestimation of domestic risks and overconfidence in personal protection measures were also contributing factors. At different stages, vaccine hesitancy among residents was related to vaccine side effects, safety and efficacy, convenience fluctuation, and various factors. Conclusion: In the present study, we found that vaccine hesitancy did not display a consistent downward trend but it fluctuated over time. Higher education, residing in urban areas, lower perceived disease risk, and concerns about the vaccine's safety and side effects were risk factors for vaccine hesitancy. Implementing appropriate interventions and educational programs tailored to address these risk factors may prove to be effective in enhancing public confidence on vaccination.

Direct Knockdown of PDZ and LIM Domain 1 Using an Adenoviral Delivery System Accelerates Osteogenesis and Fracture Healing in Mice.

Substantial advances have been made in understanding the role of partial PDZ and LIM domain family's proteins in skeletal-related diseases. Yet, little is known about the effect of PDZ and LIM Domain 1 (Pdlim1) on osteogenesis and fracture repair. This study aimed to investigate whether direct gene delivery using an adenovirus vector carrying Pdlim1 (Ad-oePdlim1) or encoding shRNA-Pdlim1 (Ad-shPdlim1) could affect the osteogenic activity of preosteoblastic MC3T3-E1 cells in vitro, and influence the fracture healing of mice in vivo. We found that Ad-shPdlim1 transfection contributed to the calcified nodule formation in MC3T3-E1 cells. Downregulation of Pdlim1 enhanced the alkaline phosphatase activity and increased the expression of osteogenic markers (Runt-related transcription factor 2 [Runx2], collagen type I alpha 1 chain [Col1A1], osteocalcin [OCN], and osteopontin [OPN]). Further analysis indicated that Pdlim1 knockdown could activate ß-catenin signaling, as evidenced by the accumulation of ß-catenin in the nucleus and the increase levels of downstream regulators such as Lef1/Tcf7, axis inhibition protein 2, cyclin D1, and SRY-box transcription factor 9. By contrast, Pdlim1 overexpression resulted in inhibition of the osteogenic activity of MC3T3-E1 cells. In vivo, at day 3 after fracture,Ad-shPdlim1 adenovirus particles were injected into the fracture site of the femur of mice, and the process of fracture healing was evaluated by X-ray, micro-computed tomography and histological examination. Local injection of Ad-shPdlim1 promoted the early cartilage callus formation, restored bone mineral density, and accelerated cartilaginous ossification, with the upregulation of osteogenic gene (Runx2, Col1A1, OCN, and OPN) expression and activation of ß-catenin signaling. Thus, we concluded that inhibition of Pdlim1 contributed to osteogenesis and fracture healing by activating the ß-catenin signaling pathway.

Robotic natural orifice specimen extraction surgery versus conventional robotic resection for patients with colorectal neoplasms.

Background: Laparoscopic natural orifice specimen extraction surgery (NOSES) has been widely used in colorectal neoplasms. However, only a few studies have focused on robotic NOSES. This study compared the short-term clinical outcomes and long-term survival outcomes between robotic NOSES and conventional robotic resection (CRR) groups. Methods: From March 2016 to October 2018, a consecutive of 143 patients who underwent robotic sigmoid and rectal resection at the Department of Gastrointestinal Surgery, The Second Xiangya Hospital, Central South University, were considered for inclusion in this study. Propensity-score matching (PSM) was conducted to account for differences in the baseline characteristics. After PSM, 39 patients were included in the robotic NOSES group, and 39 patients in the CRR group. The baseline characteristics between the two groups were all balanced and comparable. Results: Patients in the NOSES group experienced less intraoperative blood loss (p=0.001), lower requirements for additional analgesia (p=0.020), shorter time to first flatus (p=0.010), and a shorter time to first liquid diet (p=0.003) than the CRR group. The 3-year overall survival rates (NOSES: 92.3% vs. CRR: 89.7% p=1.000) and 3-year disease-free survival rates (NOSES: 82.1% vs. CRR: 84.6% p=0.761) between the two groups were comparable. Conclusion: Robotic natural orifice specimen extraction surgery is a safe and feasible surgery for patients with colorectal neoplasms. Robotic NOSES is associated with better short-term clinical outcomes and similar long-term survival outcomes to conventional robotic resection.

Developing an m5C regulator-mediated RNA methylation modification signature to predict prognosis and immunotherapy efficacy in rectal cancer.

Background: Currently, a very small number of patients with colorectal cancer (CRC) respond to immune checkpoint inhibitor (ICI) treatment. Therefore, there is an urgent need to investigate effective biomarkers to determine the responsiveness to ICI treatment. Recently, aberrant 5-methylcytosine (m5C) RNA modification has emerged as a key player in the pathogenesis of cancer. Thus, we aimed to explore the predictive signature based on m5C regulator-related genes for characterizing the immune landscapes and predicting the prognosis and response to therapies. Methods: The Cancer Genome Atlas (TCGA) cohort was used as the training set, while GEO data sets, real-time quantitative PCR (RT-qPCR) analysis from paired frozen tissues, and immunohistochemistry (IHC) data from tissue microarray (TMA) were used for validation. We constructed a novel signature based on three m5C regulator-related genes in patients with rectal adenocarcinoma (READ) using a least absolute shrinkage and selection operator (LASSO)-Cox regression and unsupervised consensus clustering analyses. Additionally, we correlated the three-gene signature risk model with the tumor immune microenvironment, immunotherapy efficiency, and potential applicable drugs. Results: The m5C methylation-based signature was an independent prognostic factor, where low-risk patients showed a stronger immunoreactivity phenotype and a superior response to ICI therapy. Conversely, the high-risk patients had enriched pathways of cancer hallmarks and presented immune-suppressive state, which demonstrated that they are more insensitive to immunotherapy. Additionally, the signature markedly correlated with drug susceptibility. Conclusions: We developed a reliable m5C regulator-based risk model to predict the prognosis, clarify the molecular and tumor microenvironment status, and identify patients who would benefit from immunotherapy or chemotherapy. Our study could provide vital guidance to improve prognostic stratification and optimize personalized therapeutic strategies for patients with rectal cancer.

Transfusion-Related Acute Lung Injury Caused by HLA-II Antibodies: A Case Report.

OBJECTIVE: The aim of this study was to retrospectively analyze the etiology of a case of suspected transfusion-related acute lung injury (TRALI) occurring after blood transfusion. METHODS: The clinical symptoms, signs, imaging examinations, and laboratory test results of a patient with suspected TRALI after blood transfusion were retrospectively analyzed, and human leukocyte antigen (HLA) genotyping of the patient and HLA antibodies of the plasma donors were performed. RESULTS: The clinical manifestations of the patient were consistent with those of TRALI after blood transfusion. This TRALI was treated by timely ventilator support. The patient results of high-resolution HLA genotyping were HLA-A* 01:01, 11:01; HLA-B* 15:02, 37:01; HLA-C* 06:02, 08:01; DRB1* 10:01, 12:02; DRB3* 03:01, 03:01; DQA1* 01:05, 06:01; DQB1* 03:01, 05:01; DPA1* 01:03, 02:01; and DPB1* 02:01, 09:01. Of the 6 plasma donors tested, 3 were found to have HLA-II antibodies, which were HLA-DPA1*01:03, HLA-DQB1*03:01, and HLA-DQB1*03:01 antibodies. CONCLUSION: We described a case of TRALI caused by HLA-DQB1*03:01 antibody and DPA1*01:03 antibody.

Characterization of sialylation-related long noncoding RNAs to develop a novel signature for predicting prognosis, immune landscape, and chemotherapy response in colorectal cancer.

Aberrant sialylation plays a key biological role in tumorigenesis and metastasis, including tumor cell survival and invasion, immune evasion, angiogenesis, and resistance to therapy. It has been proposed as a possible cancer biomarker and a potential therapeutic target of tumors. Nevertheless, the prognostic significance and biological features of sialylation-related long noncoding RNAs (lncRNAs) in colorectal cancer (CRC) remain unclear. This study aimed to develop a novel sialylation-related lncRNA signature to accurately evaluate the prognosis of patients with CRC and explore the potential molecular mechanisms of the sialylation-related lncRNAs. Here, we identified sialylation-related lncRNAs using the Pearson correlation analysis on The Cancer Genome Atlas (TCGA) dataset. Univariate and stepwise multivariable Cox analysis were used to establish a signature based on seven sialylation-related lncRNAs in the TCGA dataset, and the risk model was validated in the Gene Expression Omnibus dataset. Kaplan-Meier curve analysis revealed that CRC patients in the low-risk subgroup had a better survival outcome than those in the high-risk subgroup in the training set, testing set, and overall set. Multivariate analysis demonstrated that the sialylation-related lncRNA signature was an independent prognostic factor for overall survival, progression-free survival, and disease-specific survival prediction. The sialylation lncRNA signature-based nomogram exhibited a robust prognostic performance. Furthermore, enrichment analysis showed that cancer hallmarks and oncogenic signaling were enriched in the high-risk group, while inflammatory responses and immune-related pathways were enriched in the low-risk group. The comprehensive analysis suggested that low-risk patients had higher activity of immune response pathways, greater immune cell infiltration, and higher expression of immune stimulators. In addition, we determined the sialylation level in normal colonic cells and CRC cell lines by flow cytometry combined with immunofluorescence, and verified the expression levels of seven lncRNAs using real-time quantitative polymerase chain reaction. Finally, combined drug sensitivity analysis using the Genomics of Drug Sensitivity in Cancer, Cancer Therapeutics Response Portal, and Profiling Relative Inhibition Simultaneously in Mixtures indicated that the sialylation-related lncRNA signature could serve as a potential predictor for chemosensitivity. Collectively, this is the first sialylation lncRNA-based signature for predicting the prognosis, immune landscape, and chemotherapeutic response in CRC, and may provide vital guidance to facilitate risk stratification and optimize individualized therapy for CRC patients.

Thermal coupling of the Indo-Pacific warm pool and Southern Ocean over the past 30,000 years.

The role of the tropical Pacific Ocean and its linkages to the southern hemisphere during the last deglacial warming remain highly controversial. Here we explore the evolution of Pacific horizontal and vertical thermal gradients over the past 30 kyr by compiling 340 sea surface and 7 subsurface temperature records, as well as one new ocean heat content record. Our records reveal that La Niña-like conditions dominated during the deglaciation as a result of the more intense warming in the western Pacific warm pool. Both the subsurface temperature and ocean heat content in the warm pool rose earlier than the sea surface temperature, and in phase with South Pacific subsurface temperature and orbital precession, implying that heat exchange between the tropical upper water column and the extratropical Southern Ocean facilitated faster warming in the western Pacific. Our study underscores the key role of the thermal coupling between the warm pool and the Southern Ocean and its relevance for future global warming.

Factors associated with treatment outcomes of patients with drug-resistant tuberculosis in China: A retrospective study using competing risk model.

Objectives: Drug-resistant tuberculosis remains a serious public health problem worldwide, particularly in developing countries, including China. This study determined treatment outcomes among a cohort in Guangzhou, China, and identified factors associated with them. Methods: We initiated a retrospective study using drug-resistant TB data in Guangzhou from 2016 to 2020, managed by Guangzhou Chest Hospital. A competing risk model was used to identify the factors associated with treatment failure and death, as well as loss to follow-up (LTFU). Results: A total of 809 patients were included in the study, of which 281 were under treatment. Of the remaining 528 who had clear treatment outcomes, the number and proportion of treatment success, treatment failure, death, and LTFU were 314 (59.5%), 14 (2.7%), 32 (6.0%), and 168 (31.8%), respectively. Being older and having cavities involving the upper lungs were risk factors for treatment failure and death, while non-Guangzhou household registration and interprovincial mobility were risk factors associated with LTFU. Conclusion: Treatment failure and death were significantly associated with cavitation in the lungs, and LTFU was significantly associated with household registration and geographical mobility. Early identification of factors associated with different treatment outcomes is extremely important for policymakers, health experts, and researchers to implement appropriate strategies and measures to treat and manage the TB-infected population in China.

Comprehensive Analysis of a Cancer-Immunity Cycle-Based Signature for Predicting Prognosis and Immunotherapy Response in Patients With Colorectal Cancer.

Immune checkpoint blockade (ICB) has been recognized as a promising immunotherapy for colorectal cancer (CRC); however, most patients have little or no clinical benefit. This study aimed to develop a novel cancer-immunity cycle-based signature to stratify prognosis of patients with CRC and predict efficacy of immunotherapy. CRC samples from The Cancer Genome Atlas (TCGA) were used as the training set, while the RNA data from Gene Expression Omnibus (GEO) data sets and real-time quantitative PCR (RT-qPCR) data from paired frozen tissues were used for validation. We built a least absolute shrinkage and selection operator (LASSO)-Cox regression model of the cancer-immunity cycle-related gene signature in CRC. Patients who scored low on the risk scale had a better prognosis than those who scored high. Notably, the signature was an independent prognostic factor in multivariate analyses, and to improve prognostic classification and forecast accuracy for individual patients, a scoring nomogram was created. The comprehensive results revealed that the low-risk patients exhibited a higher degree of immune infiltration, a higher immunoreactivity phenotype, stronger expression of immune checkpoint-associated genes, and a superior response to ICB therapy. Furthermore, the risk model was closely related to the response to multiple chemotherapeutic drugs. Overall, we developed a reliable cancer-immunity cycle-based risk model to predict the prognosis, the molecular and immune status, and the immune benefit from ICB therapy, which may contribute greatly to accurate stratification and precise immunotherapy for patients with CRC.

Quantifying the Effect of Public Activity Intervention Policies on COVID-19 Pandemic Containment Using Epidemiologic Data From 145 Countries.

OBJECTIVES: Most countries have adopted public activity intervention policies to control the coronavirus disease 2019 (COVID-19) pandemic. Nevertheless, empirical evidence of the effectiveness of different interventions on the containment of the epidemic was inconsistent. METHODS: We retrieved time-series intervention policy data for 145 countries from the Oxford COVID-19 Government Response Tracker from December 31, 2019, to July 1, 2020, which included 8 containment and closure policies. We investigated the association of timeliness, stringency, and duration of intervention with cumulative infections per million population on July 1, 2020. We introduced a novel counterfactual estimator to estimate the effects of these interventions on COVID-19 time-varying reproduction number (Rt). RESULTS: There is some evidence that earlier implementation, longer durations, and more strictness of intervention policies at the early but not middle stage were associated with reduced infections of COVID-19. The counterfactual model proved to have controlled for unobserved time-varying confounders and established a valid causal relationship between policy intervention and Rt reduction. The average intervention effect revealed that all interventions significantly decrease Rt after their implementation. Rt decreased by 30% (22%-41%) in 25 to 32 days after policy intervention. Among the 8 interventions, school closing, workplace closing, and public events cancellation demonstrated the strongest and most consistent evidence of associations. CONCLUSIONS: Our study provides more reliable evidence of the quantitative effects of policy interventions on the COVID-19 epidemic and suggested that stricter public activity interventions should be implemented at the early stage of the epidemic for improved containment.