Prediction of blood-brain barrier penetrating peptides based on data augmentation with Augur.

BACKGROUND: The blood-brain barrier serves as a critical interface between the bloodstream and brain tissue, mainly composed of pericytes, neurons, endothelial cells, and tightly connected basal membranes. It plays a pivotal role in safeguarding brain from harmful substances, thus protecting the integrity of the nervous system and preserving overall brain homeostasis. However, this remarkable selective transmission also poses a formidable challenge in the realm of central nervous system diseases treatment, hindering the delivery of large-molecule drugs into the brain. In response to this challenge, many researchers have devoted themselves to developing drug delivery systems capable of breaching the blood-brain barrier. Among these, blood-brain barrier penetrating peptides have emerged as promising candidates. These peptides had the advantages of high biosafety, ease of synthesis, and exceptional penetration efficiency, making them an effective drug delivery solution. While previous studies have developed a few prediction models for blood-brain barrier penetrating peptides, their performance has often been hampered by issue of limited positive data. RESULTS: In this study, we present Augur, a novel prediction model using borderline-SMOTE-based data augmentation and machine learning. we extract highly interpretable physicochemical properties of blood-brain barrier penetrating peptides while solving the issues of small sample size and imbalance of positive and negative samples. Experimental results demonstrate the superior prediction performance of Augur with an AUC value of 0.932 on the training set and 0.931 on the independent test set. CONCLUSIONS: This newly developed Augur model demonstrates superior performance in predicting blood-brain barrier penetrating peptides, offering valuable insights for drug development targeting neurological disorders. This breakthrough may enhance the efficiency of peptide-based drug discovery and pave the way for innovative treatment strategies for central nervous system diseases.

Applications of single­cell omics and spatial transcriptomics technologies in gastric cancer (Review).

Gastric cancer (GC) is a prominent contributor to global cancer-related mortalities, and a deeper understanding of its molecular characteristics and tumor heterogeneity is required. Single-cell omics and spatial transcriptomics (ST) technologies have revolutionized cancer research by enabling the exploration of cellular heterogeneity and molecular landscapes at the single-cell level. In the present review, an overview of the advancements in single-cell omics and ST technologies and their applications in GC research is provided. Firstly, multiple single-cell omics and ST methods are discussed, highlighting their ability to offer unique insights into gene expression, genetic alterations, epigenomic modifications, protein expression patterns and cellular location in tissues. Furthermore, a summary is provided of key findings from previous research on single-cell omics and ST methods used in GC, which have provided valuable insights into genetic alterations, tumor diagnosis and prognosis, tumor microenvironment analysis, and treatment response. In summary, the application of single-cell omics and ST technologies has revealed the levels of cellular heterogeneity and the molecular characteristics of GC, and holds promise for improving diagnostics, personalized treatments and patient outcomes in GC.

Accurately identifying hemagglutinin using sequence information and machine learning methods.

Introduction: Hemagglutinin (HA) is responsible for facilitating viral entry and infection by promoting the fusion between the host membrane and the virus. Given its significance in the process of influenza virus infestation, HA has garnered attention as a target for influenza drug and vaccine development. Thus, accurately identifying HA is crucial for the development of targeted vaccine drugs. However, the identification of HA using in-silico methods is still lacking. This study aims to design a computational model to identify HA. Methods: In this study, a benchmark dataset comprising 106 HA and 106 non-HA sequences were obtained from UniProt. Various sequence-based features were used to formulate samples. By perform feature optimization and inputting them four kinds of machine learning methods, we constructed an integrated classifier model using the stacking algorithm. Results and discussion: The model achieved an accuracy of 95.85% and with an area under the receiver operating characteristic (ROC) curve of 0.9863 in the 5-fold cross-validation. In the independent test, the model exhibited an accuracy of 93.18% and with an area under the ROC curve of 0.9793. The code can be found from https://github.com/Zouxidan/HA_predict.git. The proposed model has excellent prediction performance. The model will provide convenience for biochemical scholars for the study of HA.

Detection of KRAS mutation using plasma samples in non-small-cell lung cancer: a systematic review and meta-analysis.

Background: The aim of this study was to investigate the diagnostic accuracy of KRAS mutation detection using plasma sample of patients with non-small cell lung cancer (NSCLC). Methods: Databases of Pubmed, Embase, Cochrane Library, and Web of Science were searched for studies detecting KRAS mutation in paired tissue and plasma samples of patients with NSCLC. Data were extracted from each eligible study and analyzed using MetaDiSc and STATA. Results: After database searching and screening of the studies with pre-defined criteria, 43 eligible studies were identified and relevant data were extracted. After pooling the accuracy data from 3341 patients, the pooled sensitivity, specificity and diagnostic odds ratio were 71%, 94%, and 59.28, respectively. Area under curve of summary receiver operating characteristic curve was 0.8883. Subgroup analysis revealed that next-generation sequencing outperformed PCR-based techniques in detecting KRAS mutation using plasma sample of patients with NSCLC, with sensitivity, specificity, and diagnostic odds ratio of 73%, 94%, and 82.60, respectively. Conclusion: Compared to paired tumor tissue sample, plasma sample showed overall good performance in detecting KRAS mutation in patients with NSCLC, which could serve as good surrogate when tissue samples are not available.

The impact of COVID-19 lockdown on nursing higher education at Chengdu University.

BACKGROUND: To combat/control the COVID-19 pandemic, a complete lockdown was implemented in China for almost 6 months during 2020. PURPOSE: To determine the impact of a long-term lockdown on the academic performance of first-year nursing students via mandatory online learning, and to determine the benefits of online teaching. METHODS: The recruitment and academic performance of 1st-year nursing students were assessed between 2019 [prior to COVID-19, n = 195, (146 women)] and 2020 [during COVID-19, n = 180 (142 women)]. The independent sample t test or Mann-Whitney test was applied for a comparison between these two groups. RESULTS: There was no significant difference in student recruitment between 2019 and 2020. The overall performance of the first-year students improved in the Biochemistry, Immunopathology, Traditional Chinese Medicine Nursing and Combined Nursing courses via mandatory online teaching in 2020 compared with traditional teaching in 2019. CONCLUSION: Suspension of in-class learning but continuing education virtually online has occurred without negatively impacting academic performance, thus academic goals are more than achievable in a complete lockdown situation. This study offers firm evidence to forge a path for developments in teaching methods to better incorporate virtual learning and technology in order to adapt to fast-changing environments. However, the psychological/psychiatric and physical impact of the COVID-19 lockdown and the lack of face-to-face interaction on these students remains to be explored.

The outcomes of lockdown in the higher education sector during the COVID-19 pandemic.

To control COVID-19 pandemic, complete lockdown was initiated in 2020. We investigated the impact of lockdown on tertiary-level academic performance, by comparing educational outcomes amongst first-year students during second semester of their medical course prior to and during lockdown. Evidence: The demographics, including educational outcomes of the two groups were not significantly different during semester one (prior to the lockdown). The academic performance amongst women was better than men prior to lockdown. However, the scores were improved significantly for both sexes during lockdown in 2020, following the complete online teaching, compared to that in 2019, showing no significant difference between men and women in 2020, for English and Chinese History. There were significant different scores between men and women in lab-based Histology Practice in 2019 (in-person tuition) and 2020 (online digital tuition), although only a significant improvement in women was observed between 2019 and 2020. Implication: the forced change to online delivery of the second semester of the first-year medical program in 2020 due to the COVID-19 pandemic did not result in any decline in assessment outcomes in any of the subjects undertaken. We believe extensive online digital media should continue to be available to students in future.

Deep-STP: a deep learning-based approach to predict snake toxin proteins by using word embeddings.

Snake venom contains many toxic proteins that can destroy the circulatory system or nervous system of prey. Studies have found that these snake venom proteins have the potential to treat cardiovascular and nervous system diseases. Therefore, the study of snake venom protein is conducive to the development of related drugs. The research technologies based on traditional biochemistry can accurately identify these proteins, but the experimental cost is high and the time is long. Artificial intelligence technology provides a new means and strategy for large-scale screening of snake venom proteins from the perspective of computing. In this paper, we developed a sequence-based computational method to recognize snake toxin proteins. Specially, we utilized three different feature descriptors, namely g-gap, natural vector and word 2 vector, to encode snake toxin protein sequences. The analysis of variance (ANOVA), gradient-boost decision tree algorithm (GBDT) combined with incremental feature selection (IFS) were used to optimize the features, and then the optimized features were input into the deep learning model for model training. The results show that our model can achieve a prediction performance with an accuracy of 82.00% in 10-fold cross-validation. The model is further verified on independent data, and the accuracy rate reaches to 81.14%, which demonstrated that our model has excellent prediction performance and robustness.

Physical exercise/sports ameliorate the internet addiction from college students during the pandemic of COVID-19 in China.

The rapid advancement of modern technology has significantly driven progress in various IT-related activities, resulting in a substantial increase in internet penetration rates, particularly among college students. The utilization of the internet has become one of the most essential tools in our modern society. However, internet addiction (IA) has emerged as a serious concern, particularly among college students, adversely affecting academic performance and having significant psychological and psychiatric implications. The aim of the current study was to determine the impact of physical exercise, gender and academic year on IA among college students. In the present study, we investigated internet usage, engagement in sports activities, and academic performance among college students from Western, Middle, and Eastern regions of Chinese universities. It's noteworthy that most of the respondents were freshmen. Our findings indicate that freshmen students were more susceptible to experiencing IA. Approximately 75% of students engaged in leisure sports activities, revealing an inverse correlation between sports activity and IA. This correlation aligns with the level of sports involvement, emphasizing the potential benefits of physical activity in mitigating IA. However, our study did not uncover any correlation between geographic location and the occurrence of IA, nor did it find differences between medical and non-medical students. Furthermore, our study revealed no significant variations in IA among students from different ethnic backgrounds. The underlying mechanism of IA is being currently determined. Our data suggest that physical exercise, gender, and academic year have a significant impact on IA among college students.

Benefits and risks of drug combination therapy for diabetes mellitus and its complications: a comprehensive review.

Diabetes is a chronic metabolic disease, and its therapeutic goals focus on the effective management of blood glucose and various complications. Drug combination therapy has emerged as a comprehensive treatment approach for diabetes. An increasing number of studies have shown that, compared with monotherapy, combination therapy can bring significant clinical benefits while controlling blood glucose, weight, and blood pressure, as well as mitigating damage from certain complications and delaying their progression in diabetes, including both type 1 diabetes (T1D), type 2 diabetes (T2D) and related complications. This evidence provides strong support for the recommendation of combination therapy for diabetes and highlights the importance of combined treatment. In this review, we first provided a brief overview of the phenotype and pathogenesis of diabetes and discussed several conventional anti-diabetic medications currently used for the treatment of diabetes. We then reviewed several clinical trials and pre-clinical animal experiments on T1D, T2D, and their common complications to evaluate the efficacy and safety of different classes of drug combinations. In general, combination therapy plays a pivotal role in the management of diabetes. Integrating the effectiveness of multiple drugs enables more comprehensive and effective control of blood glucose without increasing the risk of hypoglycemia or other serious adverse events. However, specific treatment regimens should be tailored to individual patients and implemented under the guidance of healthcare professionals.

Impact of lockdown on the growth of children in China aged 3-6 years during the COVID-19 pandemic.

Background: Lockdowns in COVID-19 pandemic led to less physical activity and more intake of unhealthy food in children. The aim of this study was to investigate the negative impact of major lockdowns on the growth of children aged 3-6 years during COVID-19 pandemic period. Methods: Physical examination results in 2019 to 2022 from 5834 eligible children (2972 males and 2862 females) from Southwestern China who were 3 years old in 2019 were retrospectively collected. Height and weight data points were extracted from the results, and percentiles of height (height%), weight (weight%), and BMI (BMI%), and rates of overweight and obesity were calculated and compared between different years during the pandemic. Results: After analyzing the 15404 growth data points from 5834 children, a slowly increasing trend of height% from 2019 to 2022 was observed. Weight%, BMI%, overweight rate, obesity rate, and combined overweight and obesity rate had two peaks in 2020 and 2022 when major lockdowns were adopted and a drop in between (year 2021), except for obesity rate which did not drop in 2021. Similar results were shown after stratification by gender. Conclusion: The lockdowns in COVID-19 pandemic promoted obesity of kindergarten children, but did not show any negative impact on their height growth possibly due to over-nutrition of children during lockdowns. More efforts need to be made to limit the increase of obesity rate in kindergarten children during possible future lockdowns.

EGFR, HER2, and HER3 protein expression in paired primary tumor and lymph node metastasis of colorectal cancer.

Due to the difficulty in sampling of metastatic tumors, patient selection is commonly based on results of primary tumor samples when metastatic samples are not available. However, due to tumor heterogeneity, metastatic tumors may be different from primary tumors in their phenotypes. The aim of this study was to investigate the expression of EGFR, HER2, and HER3 between primary and lymph node metastatic lesions of colorectal cancer. Paired primary tumors and lymph node metastases from 79 patients with colorectal cancer were retrospectively collected and analyzed for EGFR, HER2, and HER3 expression. High EGFR, HER2, and HER3 expression (2+ and 3+) was found in 64.2%, 66.0%, and 85.0% of primary tumors, and 56.8%, 46.0%, and 76.0% of lymph node metastases, respectively. Correlation rates between primary and metastatic lesions were 67.1%, 63.3%, and 74.7% for EGFR, HER2, and HER3, respectively. Stage IV tumors (with distant metastasis) had higher correlation rates of HER2 expression compared to stage III tumors (without distant metastasis) (P = 0.050). Moderate correlation rates in EGFR, HER2, and HER3 expression were observed between primary and metastatic lesions of colorectal cancer. Tumor stage or existence of distant metastasis could serve as potential predictive markers for the correlation of HER2 expression between primary tumors and lymph node metastases of colorectal cancer.

The HER family as therapeutic targets in colorectal cancer.

The human epidermal growth factor receptor (HER, ErbB) family has four members, epidermal growth factor receptor (EGFR), HER2, HER3, and HER4. Although distinct in ligands and functions, all of the HER family members are receptor tyrosine kinases playing important roles in the pathogenesis of cancers. In the era of precision medicine, the HER family is one of the most important and successful cancer therapeutic targets, hallmarked by the approval of anti-EGFR therapies for the treatment of colorectal cancer and non-small cell lung cancer, and anti-HER2 therapies for the treatment of breast cancer and gastric cancer. This review briefly discusses how HER family members were discovered, their functions and roles in cancer, and most importantly, the developmental history and recent updates of therapies targeting HER family members, with colorectal cancer as a focus. We also discussed the patient selection and drug resistance to anti-EGFR therapies in the treatment of colorectal cancer.

Prevalence of targeted therapy-related genetic variations in NSCLC and their relationship with clinicopathological characteristics.

BACKGROUND: Non-small cell lung cancer (NSCLC) is the most common cancer type in China. Targeted therapies have been used to treat NSCLC for two decades, which is only suitable for a subgroup of patients with specific genetic variations. The aim of this study was to investigate the prevalence of genetic variations leading to sensitivity or resistance to targeted therapies in NSCLC, and their relationship with clinicopathological characteristics of the patients. METHODS: Tumor samples were collected from 404 patients who were diagnosed to have NSCLC and underwent surgery, transthoracic biopsy, bronchoscopy biopsy, or pleural aspiration in Sichuan Provincial People's Hospital from January 2019 to March 2020. Commercial amplification-refractory mutation system kits were used to detect targeted therapy-related genetic variations in those tumor samples. The prevalence of genetic variations and their relationship with patient clinicopathological characteristics were analyzed using statistical software, followed by subgroup analysis. RESULTS: In all, 50.7% of the NSCLC patients had sensitive genetic variations to anti-EGFR therapies, and 4.9% of those patients had co-existing resistant genetic variations. Fusions in ALK, ROS1, or RET were found in 7.7% of the patients, including 2 patients with co-existing EGFR exon 19 deletion or L858R. EGFR exon 19 deletion and L858R were more common in female patients and adenocarcinoma. Further subgroup analysis confirmed the observation in female patients in adenocarcinoma subgroup, and in adenocarcinoma in male patients. In addition, smokers were more likely to have squamous cell carcinoma and KRAS mutation and less likely to have EGFR L858R, which were also confirmed after standardization of gender except KRAS mutations. CONCLUSION: Nearly half of the NSCLC patients were eligible for anti-EGFR treatments. In NSCLC, female gender and adenocarcinoma may indicate higher chance of EGFR exon 19 deletion or L858R, and smoking history may indicate squamous cell carcinoma and EGFR L858R.

Reliability of BRAF mutation detection using plasma sample: A systematic review and meta-analysis

BACKGROUND: Testing of B-Raf proto-oncogene (BRAF) mutation in tumor is necessary before targeted therapies are given. When tumor samples are not available, plasma samples are commonly used for the testing of BRAF mutation. The aim of this study was to investigate the diagnostic accuracy of BRAF mutation testing using plasma sample of cancer patients. METHODS: Databases of Pubmed, Embase, and Cochrane Library were searched for eligible studies investigating BRAF mutation in paired tissue and plasma samples of cancer patients. A total of 798 publications were identified after database searching. After removing 229 duplicated publications, 569 studies were screened using the following exclusion criteria: (1) BRAF mutation not measured in plasma or in tumor sample; (2) lacking BRAF-wildtype or BRAF-mutated samples; (3) tissue and plasma samples not paired; (4) lacking tumor or plasma samples; (5) not plasma sample; (6) not cancer; (7) un-interpretable data. Accuracy data and relevant information were extracted from each eligible study by 2 independent researchers and analyzed using statistical software. RESULTS: After pooling the accuracy data from 3943 patients of the 53 eligible studies, the pooled sensitivity, specificity, and diagnostic odds ratio of BRAF mutation testing using plasma sample were 69%, 98%, and 55.78, respectively. Area under curve of summary receiver operating characteristic curve was 0.9435. Subgroup analysis indicated that BRAF mutation testing using plasma had overall higher accuracy (diagnostic odds ratio of 89.17) in colorectal cancer, compared to melanoma and thyroid carcinoma. In addition, next-generation sequencing had an overall higher accuracy in detecting BRAF mutation using plasma sample (diagnostic odds ratio of 63.90), compared to digital polymerase chain reaction (PCR) and conventional PCR, while digital PCR showed the highest sensitivity (74%) among the 3 techniques. CONCLUSION: BRAF testing using plasma sample showed an overall high accuracy compared to paired tumor tissue sample, which could be used for cancer genotyping when tissue sample is not available. Large prospective studies are needed to further investigate the accuracy of BRAF mutation testing in plasma sample.

The diagnostic accuracy of digital PCR, ARMS and NGS for detecting KRAS mutation in cell-free DNA of patients with colorectal cancer: A systematic review and meta-analysis.

INTRODUCTION: Before anti-EGFR therapy is given to patients with colorectal cancer, it is required to determine KRAS mutation status in tumor. When tumor tissue is not available, cell-free DNA (liquid biopsy) is commonly used as an alternative. Due to the low abundance of tumor-derived DNA in cell-free DNA samples, methods with high sensitivity were preferred, including digital polymerase chain reaction, amplification refractory mutation system and next-generation sequencing. The aim of this systemic review and meta-analysis was to investigate the accuracy of those methods in detecting KRAS mutation in cell-free DNA sample from patients with colorectal cancer. METHODS: Literature search was performed in Pubmed, Embase, and Cochrane Library. After removing duplicates from the 170 publications found by literature search, eligible studies were identified using pre-defined criteria. Quality of the publications and relevant data were assessed and extracted thereafter. Meta-DiSc and STATA softwares were used to pool the accuracy parameters from the extracted data. RESULTS: A total of 33 eligible studies were identified for this systemic review and meta-analysis. After pooling, the overall sensitivity, specificity, and diagnostic odds ratio were 0.77 (95%CI: 0.74-0.79), 0.87 (95%CI: 0.85-0.89), and 23.96 (95%CI: 13.72-41.84), respectively. The overall positive and negative likelihood ratios were 5.55 (95%CI: 3.76-8.19) and 0.29 (95%CI: 0.21-0.38), respectively. Area under curve of the summarized ROC curve was 0.8992. CONCLUSION: Digital polymerase chain reaction, amplification refractory mutation system, and next-generation sequencing had overall high accuracy in detecting KRAS mutation in cell-free DNA sample. Large prospective randomized clinical trials are needed to further convince the accuracy and usefulness of KRAS mutation detection using cfDNA/liquid biopsy samples in clinical practice. TRIAL REGISTRATION: PROSPERO CRD42020176682; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=176682.

Reliability of digital PCR in detecting KRAS mutation in colorectal cancer using plasma sample: A systematic review and meta-analysis.

BACKGROUND: Test on the KRAS somatic mutation status is necessary before cetuximab and panitumumab treatments are given to colorectal cancer patients. Metastatic colorectal cancer patients sometimes lack tumor tissue samples, and the testing of KRAS mutation in plasma samples requires highly sensitive methods. OBJECTIVES: The aim of this study was to evaluate the accuracy of digital PCR in detecting KRAS mutation in plasma samples of colorectal cancer patients. DATA SOURCES: Literature research was conducted in Pubmed, Embase, and Cochrane Library. STUDY ELIGIBILITY CRITERIA, PARTICIPANTS, AND INTERVENTIONS: Database searching found 188 relevant studies. After removing duplicates, eligible studies were selected from 151 publications using the following exclusion criteria: STUDY APPRAISAL AND SYNTHESIS METHODS:: Data were extracted from the eligible studies by 2 independent researchers. Pooled accuracy parameters were calculated from those extracted data using Meta-DiSc and STATA software. RESULTS: Twelve eligible studies were selected for the systematic review and meta-analysis. After calculation, the pooled sensitivity and specificity were 0.83 (95% CI: 0.79-0.86) and 0.91 (95%CI: 0.88-0.93), respectively. Pooled positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 7.30 (95%CI: 4.78-11.17), 0.22 (95%CI: 0.15-0.32), and 41.00 (95%CI: 21.07-79.78), respectively. Area under curve of the summarized ROC curve was 0.9322. LIMITATIONS: Although no significant bias was identified, number of included studies was still quite small, especially in subgroup analysis. CONCLUSIONS AND IMPLICATION OF KEY FINDINGS: Digital PCR showed high accuracy and could be a reliable detection method for KRAS mutation in plasma samples. Large-cohort prospective study is required to further confirm the usefulness of digital PCR in KRAS mutation detection.

The diagnostic accuracy of digital PCR, ARMS and NGS for detecting KRAS mutation in cell-free DNA of patients with colorectal cancer: A protocol for systematic review and meta-analysis.

INTRODUCTION: Cetuximab and panitumumab have been used clinically to treat metastatic colorectal cancer for more than 15 years. Before the treatment is given, it is required to determine the KRAS mutation status since it would lead to drug resistance. Tumor tissue sample is traditionally used for cancer genotyping. In recent years, liquid biopsy sample has been intensively investigated as a surrogate for tumor tissue sample due to its non-invasiveness and better presentation of tumor heterogeneity. The aim of this study is to systematically summarize the accuracy of KRAS mutation measurement in colorectal cancer using cell-free DNA in liquid biopsy samples, with tumor tissue sample as reference (gold standard). METHODS AND ANALYSIS: We will search literatures in the following databases: Pubmed, Embase, and Cochrane Library. Systemic review and meta-analysis will be performed to summarize the accuracy of KRAS mutation measurement in colorectal cancer using liquid biopsy sample, and subgroup analysis will be performed on different testing platforms, and on metastatic and non-metastatic colorectal cancer. TIMELINE: This study will start on June 1, 2020, and is expected to be finished by November 1, 2020. ETHICS AND DISSEMINATION: Ethical approval will not be required since the data obtained and analyzed in this study will not be on individual patients. Study results will be disseminated as an official publication in a peer-reviewed journal.Registration: PROSPERO CRD42020176682.

Association between the PON1 Q192R polymorphism and coronary heart disease in Chinese: A meta-analysis.

BACKGROUND: The relation has not been reported consistently between the PON1 Q192R polymorphism and coronary heart disease (CHD). To clarify the discrepancy, we performed the present meta-analysis to evaluate the association between the PON1 gene Q192R polymorphism and CHD risk in Chinese population. METHODS: We conducted a comprehensive search of the PubMed, EMBASE, and China National Knowledge Infrastructure databases for all available case-control studies. Two reviewers independently selected studies. Data were analyzed by STATA software package v 12.0. RESULTS: Thirteen studies investigating the association between the PON1 Q192R polymorphism and risk of CHD were selected in this meta-analysis with 4353 cases and 4882 controls. The association between the PON1 Q192R polymorphism and CHD is statistically significant under the recessive genetic model (R/R vs Q/R + Q/Q, odds ratio [OR] = 1.111, 95% confidence interval [CI] = 1.017-1.214). We observed no statistical association between PON1 Q192R polymorphism and risk of CHD under allele model (R vs Q, OR = 1.087, 95% CI = 0.976-1.209), homozygous model (RR vs QQ, OR = 1.192, 95% CI = 0.949-1.496), and dominant genetic model (Q/R + R/R vs Q/Q, OR = 1.127, 95% CI = 0.938-1.354). CONCLUSION: This meta-analysis suggests that the PON1 Q192R polymorphism has a weak association with CHD risk in Chinese.

A Chinese medicine warm compress (Wen Jing Zhi Tong Fang), combined with WHO 3-step analgesic ladder treatment for cancer pain relief: A comparative randomized trial.

INTRODUCTION: This study aimed to assess the effectiveness of Chinese medicine warm compress (CMWC) on back meridians in relieving cancer pain, reducing adjuvant analgesic doses and adverse reactions, and improving the quality of life (QOL). METHODS: A total of 62 patients (age range 39-82 years) diagnosed with a malignant tumor and suffering from cancer-related pain were randomly divided into a treatment group (group A) and a control group (group B) (n = 31 for each). The patients in both groups were administered appropriate drugs for 2 cycles of 7-day treatments according to the World Health Organization (WHO) 3-step ladder for cancer pain relief in adults. In addition, a CMWC was given to patients in group A. Pain relief was assessed using the visual analogue scale (VAS) at various time points before and after interventions in each group. Alteration of analgesic doses, adverse reactions, performance status (PS), and QOL were evaluated and any differences between groups A and B evaluated. RESULTS: VAS scores at various time points after treatment were significantly decreased compared with the baseline level in group A. Overall response rate was significantly improved in group A compared with group B (70.97% vs 29.03%, P < .001). Significant differences in clinical pain relief efficacy in various locations were found in group A after treatment vs before treatment (P < .05). Adjuvant analgesic doses were significantly changed in the control group compared to the treatment group after 1 cycle of 7-day treatment (22.58% vs 12.90%, P = .023). QOL were improved more in group A than in group B (3.00 ± 4.23 vs -2.06 ±â€Š2.38, P < .001). Significantly reduced adverse reactions were observed after treatment of group A compared with group B in terms of the overall incidence (3.23% vs 80.65%, P < .05) or incidence of constipation (3.23% vs 77.42%, P < .05). CONCLUSIONS: The application of CMWC on back meridians combined with WHO 3-step analgesic ladder treatment was effective in relieving cancer-related pain with reduced doses, less adverse reactions, and improved QOL.

Dihydroartemisinin inhibits the viability of cervical cancer cells by upregulating caveolin 1 and mitochondrial carrier homolog 2: Involvement of p53 activation and NAD(P)H:quinone oxidoreductase 1 downregulation.

Dihydroartemisinin (DHA) has been shown to inhibit the viability of various cancer cells. Previous studies have revealed that the mechanisms involved in the inhibitory effects of DHA are based on theactivation of p53 and the mitochondrial-related cell death pathway. However, the exact association between upstream signaling and the activation of cell death pathway remains unclear. In this study, we found that DHA treatment induced the upregulation of caveolin 1 (Cav1) and mitochondrial carrier homolog 2 (MTCH2) in HeLa cells, and this was associated with the DHA-induced inhibition of cell viability and DHA-induced apoptosis. Additionally, the overexpression of Cav1 and MTCH2 in HeLa cells enhanced the inhibitory effects of DHA on cell viability. Moreover, we also found that the upregulation of Cav1 contributed to the DHA-mediated p53 activation and the downregulation of the redox enzyme, NAD(P)H:quinone oxidoreductase 1 (NQO1), which have been reported to contribute to the activation of the cell death pathway. Of note, we also found that DHA induced the nuclear translocation and accumulation of both Cav1 and p53, indicating a novel potential mechanism, namely the regulation of p53 activation by Cav1. On the whole, our study identified Cav1 and MTCH2 as the molecular targets of DHA and revealed a new link between the upstream Cav1/MTCH2 upregulation and the downstream activation of the cell death pathway involved in the DHA-mediated inhibition of cell viability.