Pan-cancer discovery of somatic mutations from RNA sequencing data.

Identification of somatic mutations (SMs) is essential for characterizing cancer genomes. While DNA-seq is the prevalent method for identifying SMs, RNA-seq provides an alternative strategy to discover tumor mutations in the transcribed genome. Here, we have developed a machine learning based pipeline to discover SMs based on RNA-seq data (designated as RNA-SMs). Subsequently, we have conducted a pan-cancer analysis to systematically identify RNA-SMs from over 8,000 tumors in The Cancer Genome Atlas (TCGA). In this way, we have identified over 105,000 novel SMs that had not been reported in previous TCGA studies. These novel SMs have significant clinical implications in designing targeted therapy for improved patient outcomes. Further, we have combined the SMs identified by both RNA-seq and DNA-seq analyses to depict an updated mutational landscape across 32 cancer types. This new online SM atlas, OncoDB ( https://oncodb.org ), offers a more complete view of gene mutations that underline the development and progression of various cancers.

Oxymatrine induces apoptosis in non-small cell lung cancer cells by downregulating TRIM46.

Sophora flavescens Aiton, a traditional Chinese medicine that was supposed to predominantly play an anti-inflammatory role, has been used to treat multiple diseases, including cancer, for over two thousand years. Recently, it has attracted increasing attention due to the anti-tumor properties of Oxymatrine, one of the most active alkaloids extracted from S. flavescens. This study aims to explore it's anti-tumor effects in non-small cell lung cancer (NSCLC) and the underlying mechanisms. We first investigated the effects of oxymatrine on cell apoptosis in lung cancer cell lines A549 and PC9 as well as explored related genes in regulating the apoptosis by transcriptome analysis. Subsequently, to further study the role of TRIM46, we constructed two types of TRIM46 over-expression cells (A549TRIM46+ and PC9TRIM46+ cells) and then investigated the effect of TRIM46 on oxymatrine-induced apoptosis. Moreover, we explored the effect of TRIM46 on downstream signaling pathways. Transcriptome analysis suggested that shared differentially expressed genes (DEGs) in A549 and PC9 cells treated with oxymatrine were CACNA1I, PADI2, and TRIM46. According to TCGA database analysis, the abundance of TRIM46 expression was higher than CACNA1I, and PADI2 in lung cancer tissues, then was selected as the final DEG for subsequent studies. We observed that oxymatrine resulted in down-expression of TRIM46 as well as induced the apoptosis of the cancer cells in a dose- and time-dependent manner. Meanwhile, we found that apoptosis induced by oxymatrine was inhibited by over-expressing TRIM46. Furthermore, our study indicated that the NF-κB signaling pathway was involved in apoptosis suppressed by TRIM46. We conclude that TRIM46 is the direct target of oxymatrine to induce anti-tumor apoptosis and may activate the downstream NF-κB signaling pathway.

Th1 cell immune response in Talaromyces marneffei infection with anti-interferon-γ autoantibody syndrome.

Anti-interferon-γ autoantibody (AIGA) syndrome may be the basis of disseminated Talaromyces marneffei infection in human immunodeficiency virus (HIV)-negative adults. However, the pathogenesis of Th1 cell immunity in T. marneffei infection with AIGA syndrome is unknown. A multicenter study of HIV-negative individuals with T. marneffei infection was conducted between September 2018 and September 2020 in Guangdong and Guangxi, China. Patients were divided into AIGA-positive (AP) and AIGA-negative (AN) groups according to the AIGA titer and neutralizing activity. The relationship between AIGA syndrome and Th1 immune deficiency was investigated by using AP patient serum and purification of AIGA. Fifty-five HIV-negative adults with disseminated T. marneffei infection who were otherwise healthy were included. The prevalence of AIGA positivity was 83.6%. Based on their AIGA status, 46 and 9 patients were assigned to the AP and AN groups, respectively. The levels of Th1 cells, IFN-γ, and T-bet were higher in T. marneffei-infected patients than in healthy controls. However, the levels of CD4+ T-cell STAT-1 phosphorylation (pSTAT1) and Th1 cells were lower in the AP group than in the AN group. Both the serum of patients with AIGA syndrome and the AIGA purified from the serum of patients with AIGA syndrome could reduce CD4+ T-cell pSTAT1, Th1 cell differentiation and T-bet mRNA, and protein expression. The Th1 cell immune response plays a pivotal role in defense against T. marneffei infection in HIV-negative patients. Inhibition of the Th1 cell immune response may be an important pathological effect of AIGA syndrome.IMPORTANCEThe pathogenesis of Th1 cell immunity in Talaromyces marneffei infection with anti-interferon-γ autoantibody (AIGA) syndrome is unknown. This is an interesting study addressing an important knowledge gap regarding the pathogenesis of T. marneffei in non-HIV positive patients; in particular patients with AIGA. The finding of the Th1 cell immune response plays a pivotal role in defense against T. marneffei infection in HIV-negative patients, and inhibition of the Th1 cell immune response may be an important pathological effect of AIGA syndrome, which presented in this research could help bridge the current knowledge gap.

Understanding apoptotic induction by Sargentodoxa cuneata-Patrinia villosa herb pair via PI3K/AKT/mTOR signalling in colorectal cancer cells using network pharmacology and cellular studies.

ETHNOPHARMACOLOGICAL RELEVANCE: Sargentodoxa cuneata (Sargentodoxa cuneata (Oliv.) Rehder & E.H.Wilson, DXT)-Patrinia villosa(Patrinia villosa (Thunb.) Dufr, BJC) constitutes a commonly employed herb pair in Chinese medicine for colorectal cancer (CRC) treatment. Modern pharmacological investigations have revealed the anticancer activities of both Sargentodoxa cuneata and Patrinia villosa. Nevertheless, comprehensive studies are required to discern the specific antitumor active ingredients and mechanism of action when these two herbs are used in combination. AIM OF THE STUDY: Through the integration of network pharmacology, molecular docking techniques, experimental assays, and bioinformatics analysis, our study aims to forecast the active ingredients, potential targets, and molecular mechanisms underlying the therapeutic efficacy of this herb pair against CRC. MATERIALS AND METHODS: Plant names (1, Sargentodoxa cuneata (Oliv.) Rehder & E.H.Wilson; 2, Patrinia villosa (Thunb.) Dufr.) have been verified through WorldFloraOnline (www.worldFloraonline.org) and MPNs (http://mpns.kew.org). The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) were utilized for screening the active ingredients of the herb pair. The PharmMapper database was employed to predict the target proteins for each active ingredient. CRC-related targets were obtained from the Genecards database, Online Mendelian Inheritance in Man (OMIM) database, Disease Gene Network (DisGeNET) database, and Therapeutic Target Database (TTD). Common targets were identified by intersecting the target proteins of all active ingredients with CRC-related targets. Protein-protein interactions (PPI) for the common target proteins were constructed using the String database and Cytoscape 3.9.1 software. Network topology analysis facilitated the identification of core targets. These core targets were subjected to enrichment analysis of Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) using the Metascape database. Molecular docking was performed using Discovery Studio 2019 to investigate the interactions between the active ingredients and core target proteins. The core targets were validated through bioinformatics analysis using GEPIA, HPA, and the cBioPortal database. Finally, a series of experiments were conducted to further validate the results in vitro. RESULT: A total of 15 active ingredients and 255 herb targets were identified, resulting in 66 common targets in conjunction with 6113 disease targets. The PPI analysis highlighted AKT1, EGFR, CASP3, SRC, and ESR1 as core targets. KEGG enrichment analysis indicated significant enrichment in the PI3K-AKT signaling pathway, a pathway associated with cancer. Molecular docking experiments confirmed favorable interactions between dihydroguaiaretic acid and the core target proteins (AKT1, EGFR, CASP3, and ESR1). Bioinformatics analysis revealed differential expression of EGFR and CASP3 in normal and CRC tissues. Cellular experiments further verified that dihydroguaiaretic acid induces apoptosis in colorectal cancer cells through the PI3K-AKT signaling pathway. CONCLUSION: Our network pharmacology study has elucidated that the Sargentodoxa cuneata-Patrinia villosa herb pair exerts the negative regulation of the PI3K/AKT/mTOR signaling pathway, ultimately leading to the induction of apoptosis in colorectal cancer cells. This research has predicted and validated the active ingredients, potential targets, and molecular mechanisms of Sargentodoxa cuneata-Patrinia villosa in the treatment of CRC, providing scientific evidence for the use of traditional Chinese medicine in managing CRC.

Serum sphingolipids aid in diagnosing adult HIV-negative patients with pulmonary cryptococcosis: a clinical cohort study.

Background: Pulmonary cryptococcosis (PC) contributes to the ongoing global disease burden in human immunodeficiency virus (HIV)-negative populations. Since some PC patients are misdiagnosed under existing diagnostic guidelines, new diagnostic markers are needed to improve diagnostic accuracy and therapeutic efficacy and reduce disease risk. Methods: Our previously established sphingolipidomic approach was employed to explore the use of serum sphingolipids (SPLs) in diagnosing HIV-negative patients with PC. A clinical cohort of PC, pulmonary aspergillosis (PA), and tuberculosis (TB) patients and healthy controls was assessed to identify SPL biomarkers. Results: A total of 47 PC, 27 PA, and 18 TB patients and 40 controls were enrolled. PC and TB patients had similar clinical features, laboratory test results and radiological features, excluding plural effusion. The serum ceramide [Cer (d18:1/18:0)] level showed a significant increase in PC patients compared to controls and PA and TB patients (P<0.05). Cer (d18:1/18:0) was identified as a specific diagnostic biomarker for PC. The optimal cut-off value of greater than 18.00 nM showed a diagnostic sensitivity of 76.60% and a specificity of 95.00% and better distinguished PC patients from PA and TB patients. Furthermore, the serum Cer (d18:1/18:0) level gradually decreased after 3 and 6 months of treatment, suggesting the prediction potential for therapeutic efficacy of this biomarker. In addition, Cer (d18:1/18:0) analysis presented a higher sensitivity than the cryptococcal antigen (CrAg) assay. Conclusions: This is the first study to report the use of the SPL Cer (d18:1/18:0) as a serum biomarker for diagnosing Cryptococcus spp. infection in HIV-negative patients.

Kruppel-like factor 14 ameliorated obesity and related metabolic disorders by promoting adipose tissue browning.

Obesity has been identified as a serious and debilitating disease that threatens human health, but the current treatment strategies still have some shortcomings. Exercise and dieting are difficult for many people to adhere to, and a series of surgical risks and pain brought about by volume reduction have made it difficult for the current weight loss effect to meet human expectations. In this study, we first found that mice with overexpression of the transcription factor Kruppel-like factor 14 (KLF14) in subcutaneous adipose tissue gained weight more slowly while consuming a high-fat diet than did control mice, and these mice also showed reduced insulin resistance and liver lipid deposition abnormalities. Mechanistically, the browning of white adipose tissue was promoted in adipose tissue with KLF14 overexpression; therefore, we preliminarily concluded that KLF14 can improve obesity by promoting the browning of white adipose tissue and energy consumption, thus ameliorating obesity and related metabolic disturbances. In summary, our results revealed that KLF14 may promote white adipose tissue browning, thus ameliorating high-fat diet-induced obesity and hepatic steatosis, as well as serum lipid levels and insulin resistance, thereby achieving a positive effect on metabolism.NEW & NOTEWORTHY Our study first explored the role of KLF14 in the development and progression of HFD-induced obesity in male mice. Its beneficial effect on adipose browning and metabolic disorders suggests that KLF14 may provide us a new therapeutic strategy for obesity and related metabolic complications. This health problem is of global concern and needs to be addressed.

Development of a clinical scoring model to predict the overall and relapse­free survival of patients with hepatocellular carcinoma following a hepatectomy.

Hepatocellular carcinoma (HCC) is a highly lethal disease, and surgical resection is one of the major treatment methods used. However, to date, at least to the best of our knowledge, there is no effective prognostic scoring system for the overall survival (OS) and relapse-free survival (RFS) of patients following hepatectomy. The present study developed a low-cost and easy-to-use model based on the clinicopathological characteristics of patients with HCC for assessment of outcome prediction and risk stratification. A total of 690 patients with HCC undergoing surgery were included and randomly divided into two cohorts (n=345). Cox regression analysis was conducted to investigate the association between the clinicopathological and treatment features, and patient survival. Multivariate analysis revealed that ascites, vascular tumor thrombus, low tumor differentiation and extrahepatic metastasis were independent risk factors for OS. Extrahepatic metastasis and multiple tumors were independent risk factors to predict tumor recurrence. These variables were weighted to construct the ascites, vascular tumor thrombus, low tumor differentiation, extrahepatic metastasis and multiple tumors (AVLEM) score based on the cumulative incidence (CuI) of the aforementioned variables, and the patients were classified into grade 0 (CuI=0), grade 1 (CuI=1 for OS and CuI ≥1 for RFS), and grade 2 (CuI ≥2) subgroups, respectively. Kaplan-Meier analysis revealed that the OS and RFS differed significantly among the subgroups; however, the survival rate between the two cohorts did not exhibit any marked differences. On the whole, the present study demonstrates that with this AVLEM scoring system, patients with HCC with a high score had a poor OS and RFS; thus, it is suggested that such patients undergo imaging examinations following a hepatectomy more frequently.

Development and experimental analysis of a small integrated edge navigation sensor based on principle of circular arc array.

Signal, accuracy, and real-time performance of satellite, radar, and machine vision is a subject of concern in various complex agricultural environments. Therefore, the demand for a robust navigation sensor for indoor and vertical agricultural environment remains crucial, and it is a significant subject. In view of this, the relative edge pose detection method based on the ideal target band principle of the lateral center arc array, in this research, a small integrated arc array navigation sensor module based on adaptive detection arc technology, is developed, which costs about $100, autonomous edge navigation position, and attitude detection is realized in facility agriculture environment with continuous structured corridor or roadside features. In this research, a coupling method of reducing the radius of distance sensor arrangement, adjusting the unequal center angle, and increasing the detection distance is used to realize the miniaturization of the arc array arrangement. A semicircular modular rocket was designed to slide and adjust the center angle of the distance sensor, and the longitudinal installation position of the modularized sensor was adjusted by translating the circular arc of the detection; the convenient moving arrangement under different vehicle width and detection arc characteristics is realized. An adaptive construction method of detecting a circular arc based on self-calibrating detection distance of a distance sensor is proposed, which effectively reduces the difficulty of arranging the lateral central circular arc array; the fast construction of lateral detection arc is realized. In addition, in order to improve the accuracy and stability of the pose detection, the Mahalanobis distance algorithm and the standard Kalman filter are used to optimize the estimation of the ranging information and the relative pose of the edge. The experimental results show that the small integrated arc array navigation sensor module can independently construct photoelectric detection arcs with different characteristics to detect the position and attitude of the relative edge. When the road surface is concave and convex, the small integrated arc array navigation sensor module can still maintain the stable position and attitude detection of the relative edge for more than 30 s. In addition, when the walking speed of the autonomous navigation platform is 0.15 m/s to 0.35 m/s, the detection errors of lateral deviation and heading deviation relative to the road edge are less than 40 mm and 4.5°, respectively. The small integrated arc array navigation sensor module is less affected by the change of operating speed, and still has good accuracy and stability. The results show that the modularized edge navigation sensor has the advantages of fast and convenient use, high accuracy, and low cost; it can be applied to autonomous edge navigation control in greenhouse and plant and animal factories.

Development of Small-Molecule Fluorescent Probes Targeting Enzymes.

As biological catalysts, enzymes are vital in controlling numerous metabolic reactions. The regulation of enzymes in living cells and the amount present are indicators of the metabolic status of cell, whether in normal condition or disease. The small-molecule fluorescent probes are of interest because of their high sensitivity and selectivity, as well as their potential for automated detection. Fluorescent probes have been useful in targeting particular enzymes of interest such as proteases and caspases. However, it is difficult to develop an ideal fluorescent probe for versatile purposes. In the future, the design and synthesis of enzyme-targeting fluorescent probes will focus more on improving the selectivity, sensitivity, penetration ability and to couple the fluorescent probes with other available imaging molecules/technologies.

Development and Evaluation of Rapid and Accurate CRISPR/Cas13-Based RNA Diagnostics for Pneumocystis jirovecii Pneumonia.

Background: Pneumocystis jirovecii can result in a serious pulmonary infection, Pneumocystis jirovecii pneumonia, in immunocompetent hosts. The diagnosis of Pneumocystis jirovecii pneumonia has long been a major clinical concern, and there are limitations with the currently utilized immunostaining and polymerase chain reaction diagnosis/detection technologies (e.g., insufficient sensitivity and accuracy). Hence, we sought to establish a rapid and RNA-specific transcription mediated amplification and CRISPR/Cas13a-based diagnostics targeted P. jirovecii-mitochondrial large subunit ribosomal RNA. Methods: The procedure of the diagnostics included amplification of the extracted RNA samples by transcription mediated amplification, followed by CRISPR/Cas13 detection, and ultimately, the judgment of the results after 30 minutes of fluorescence signal. Later, the diagnostic performance of the CRISPR/Cas13-based diagnostics were tested on the 62 surplus clinical samples. Results: This CRISPR/Cas13-based diagnostics achieved limits of detection of approximately 2 copies/µL transcribed RNA templates, with no cross reaction to other respiratory pathogens, including bacteria and fungi. Similar to in-house quantitative real-time polymerase chain reaction, CRISPR/Cas13-based diagnostics was still positive in 243-fold diluted bronchial alveolar lavage fluid. A preliminary evaluation of 62 surplus bronchial alveolar lavage fluid samples from patients suspected of Pneumocystis jirovecii pneumonia showed that CRISPR/Cas13-based diagnostics achieved a 78.9% sensitivity and a 97.7% specificity in the diagnosis of Pneumocystis jirovecii pneumonia. Conclusion: Our study demonstrates that the CRISPR/Cas13-based diagnostics technique has good performance for the accurate and specific diagnosis of Pneumocystis jirovecii pneumonia.

Metabolomic, proteomic and lactylated proteomic analyses indicate lactate plays important roles in maintaining energy and C:N homeostasis in Phaeodactylum tricornutum.

BACKGROUND: Phaeodactylum tricornutum accumulates lipids while the growth also increases under high CO2, shedding light on its potential application in the reduction of CO2 emissions and at the same time acquiring biodiesel raw materials. However, the sensing and transducing of high C:N signals and the related response mechanism(s) remained unknown. RESULTS: In this study, a multiple omics analysis was performed with P. tricornutum under low nitrogen (LN) and high CO2 (HC) conditions. The results indicated that 2-oxoglutarate was significantly increased under both LN and HC. Meanwhile, proteins involved in carbon concentration mechanism decreased, indicated that 2-oxoglutarate might regulate C:N balance through suppressing carbon fixation. Lactate, which acts in energy metabolism, signal transduction and 'LactoylLys' modification on proteins, was the most upregulated metabolite under both LN and HC conditions. Meanwhile, proteins involved in carbon, nitrogen and energy metabolisms were significantly regulated. Western blotting analysis suggested that non-histone L-lactylation modification was enhanced under LN and HC. Moreover, lactylated proteins were enriched in photosynthesis, central carbon metabolism, nitrogen metabolism, fatty acid synthesis and oxidative phosphorylation. CONCLUSION: It is suggested that lactate might play important roles in energy homeostatic maintenance and C:N balance regulation in P. tricornutum through protein lactylation modification.

The Impact of Government Social Media Information Quality on Public Panic During the Infodemic.

The COVID-19 pandemic triggered the first global "Infodemic" in the era of social media. Understanding how governments deal with the negative impacts of the infodemic (e.g., public panic) has become a priority. This paper uses the theoretical framework of the Elaboration Likelihood Model (ELM) to explore mechanisms for alleviating panic associated with the infodemic. It considers, in particular, the quality of information circulated on Government Social Media (GSM) as the central route and local government trust as the peripheral route. An empirical study was conducted using data from a focus group interview and a questionnaire survey collected within the first three weeks following the citywide lockdown of Wuhan, China. The results show that as: (1) Quality of GSM information does not significantly reduce public panic, but local government trust significantly increases people's pandemic prevention knowledge; (2) Pandemic prevention knowledge is a critical mediator between information quality of GSM and public panic, as well as local government trust and public panic; and (3) Information quality of GSM significantly increases people's trust in local governments. This paper contributes to the literature on infodemic and government social media and provides implications for practice.

SQNN: A Spike-wave index Quantification Neural Network with a pre-labeling algorithm for epileptiform activity identification and quantification in children.

OBJECTIVE: Electrical status epilepticus during slow sleep (ESES) is a phenomenon identified by strong activation of epileptiform activity in the electroencephalogram (EEG) during sleep. For children disturbed by ESES, spike-wave index (SWI) is defined to quantify the epileptiform activity in the EEG during sleep. Accurate SWI quantification is important for clinical diagnosis and prognosis. To quantify SWI automatically, a deep learning method is proposed in this paper. APPROACH: Firstly, a pre-labeling algorithm (PreLA) composed of the adaptive wavelet enhanced decomposition and a slow-wave discrimination rule is designed to efficiently label the EEG signal. It enables the collection of large-scale EEG dataset with fine-grained labels. Then, an SWI Quantification Neural Network (SQNN) is constructed to accurately classify each sample point as normal or abnormal and to identify the abnormal events. SWI can be calculated automatically based on the total duration of abnormalities and the length of the signal. MAIN RESULTS: Experiments on two datasets demonstrate that the PreLA is effective and robust for labeling the EEG data and the SQNN accurately and reliably quantifies SWI without using any thresholds. The average estimation error of SWI is 3.12%, indicating that our method is more accurate and robust than experts and previous related works. The processing speed of SQNN is 100 times faster than that of experts. SIGNIFICANCE: Deep learning provides a novel approach to automatic SWI quantification and PreLA provides an easy way to label the EEG data with ESES syndromes. The results of the experiments indicate that the proposed method has a high potential for clinical diagnosis and prognosis of epilepsy in children.

SQNN: a spike-wave index quantification neural network with a pre-labeling algorithm for epileptiform activity identification and quantification in children.

Objective.Electrical status epilepticus during slow sleep (ESES) is a phenomenon identified by strong activation of epileptiform activity in the electroencephalogram (EEG) during sleep. For children disturbed by ESES, spike-wave index (SWI) is defined to quantify the epileptiform activity in the EEG during sleep. Accurate SWI quantification is important for clinical diagnosis and prognosis. To quantify SWI automatically, a deep learning method is proposed in this paper.Approach.Firstly, a pre-labeling algorithm (PreLA) composed of the adaptive wavelet enhanced decomposition and a slow-wave discrimination rule is designed to efficiently label the EEG signal. It enables the collection of large-scale EEG dataset with fine-grained labels. Then, an SWI quantification neural network (SQNN) is constructed to accurately classify each sample point as normal or abnormal and to identify the abnormal events. SWI can be calculated automatically based on the total duration of abnormalities and the length of the signal.Main results.Experiments on two datasets demonstrate that the PreLA is effective and robust for labeling the EEG data and the SQNN accurately and reliably quantifies SWI without using any thresholds. The average estimation error of SWI is 3.12%, indicating that our method is more accurate and robust than experts and previous related works. The processing speed of SQNN is 100 times faster than that of experts.Significance.Deep learning provides a novel approach to automatic SWI quantification and PreLA provides an easy way to label the EEG data with ESES syndromes. The results of the experiments indicate that the proposed method has a high potential for clinical diagnosis and prognosis of epilepsy in children.

Immunotherapy-Related Cardiotoxicity Re-Emergence in Non-Small Cell Lung Cancer - A Case Report.

PD-1/PD-L1 inhibitors activate immunological response and have become one of the main modalities of cancer treatment. However, they may result in the immune-related adverse events (irAEs). Immune-related cardiotoxicity is relatively rare but may become fatal. We will present a case of a male patient who experienced immunotherapy-related cardiotoxicity one year after received pembrolizumab treatment. The patient had atypical symptom presentation initially, but his condition deteriorated worsened rapidly and he developed severe cardiac disease. The patient experienced significant relief after corticosteroid treatment. Unfortunately, he experienced a reoccurence of the severe adverse event when discontinuing the use of corticosteroids. Ultimately, larger doses and longer courses of corticosteroid treatment cured the heart damage. Fortunately, we observed that lesions were stable and maintained for a long time after cessation of using pembrolizumab for eight months.

Quality assessment of Succus Bambusae oral liquids based on gas chromatography/mass spectrometry fingerprints and chemometrics.

RATIONALE: Succus Bambusae is consumed as a kind of herbal medicine and natural beverage in China. However, the current quality standards for Succus Bambusae are low and lack safety indicators, which makes it difficult to effectively guarantee its quality. Therefore, it is of great significance to study the identification and quality control technology for the product. METHODS: We have developed a set of qualitative and quantitative methods based on gas chromatography/mass spectrometry (GC/MS) for the analysis of volatile components in Succus Bambusae oral liquid (SBOL). Combining GC/MS fingerprint analysis and related chemometrics algorithms, with similarity evaluation, Hotelling T2 and distance to Model X (DModX) as criteria, the quality consistency of different batches was evaluated, and SBOL samples from different manufacturers were differentiated. RESULTS: Twenty-nine volatile components were preliminarily identified from 40 batches of SBOL samples from six manufacturers, and six Q-markers (Quality Markers) for the SBOLs were discussed and determined using GC/MS. The products from different manufacturers were distinguished using chemometrics. CONCLUSIONS: The results showed that the quality of the SBOL samples from different batches and different manufacturers fluctuated greatly, which suggested that research into the raw materials and manufacturing techniques should be strengthened to improve the quality of SBOL and ensure its quality consistency.

[Research progress on chemical constituents and quality control methods of Succus Bambusae].

Through the investigation of a large number of both domestic and overseas literatures and related quality standards, chemical compositions, quality evaluation system and quality control methods of Succus Bambusae were systematic summarized in this study. There were abundant chemical constituents in Succus Bambusae, mainly including volatile ingredients, amino acids, flavonoids, trace elements and vitamins, with high medicinal and edible value. The quality control methods involved traditional morphological identification, spectroscopy, chromatography and other techniques. However, the current quality standards of Succus Bambusae are relatively low, lacking safety indicators, and cannot effectively ensure its quality, seriously affecting the safety and effectiveness of its clinical use. Therefore, it is particularly important to establish a set of highly sensitive and specific quality evaluation system for Succus Bambusae. In this paper, the current research status of the chemical compositions and quality standards of Succus Bambusae were reviewed, with the purpose of providing a basis for further improvement of its quality evaluation system.

Xueshuantong Injection in Treating Deep Venous Thrombosis: A Systematic Review and Trial Sequential Analysis.

AIMS: In recent years, the incidence of deep venous thrombosis (DVT) presents an increasing trend year by year. The current evidence regarding the efficacy and safety of Xueshuantong injection for DVT is controversial. This systematic review (SR) aimed to assess the efficacy and safety of Xueshuantong injection in the treatment of DVT systematically and provide an evidence-based reference for clinical treatment. METHODS: Nine electronic databases were used to identify the literature consisting of randomized controlled trials (RCTs) with a date of search of 1 November 2020. Clinical effective rate and incidence rate of adverse events were investigated as primary outcomes. Patency rate of femoral vein, patency rate of popliteal vein, patency rate of posterior tibial vein, circumference difference, activated partial thromboplastin time (APTT), and D-dimer (D-D) were investigated as secondary outcomes. Revman 5.4.1 was used to analyze the results. Analysis of the power of evidence was performed with Trial Sequential Analysis (TSA). RESULTS: A total of 12 articles including 1018 patients were included. The results of the meta-analysis showed that the clinical effective rate in the experimental group was higher than that in the control group, the incidence rate of adverse events in the experimental group was higher than that in the control group; after the operation, the patency rate of femoral vein, patency rate of popliteal vein, patency rate of posterior tibial vein, circumference difference, APTT, and D-D in the experimental group were significantly improved compared with those in the control group, and the difference between the groups was statistically significant. TSA suggested that the meta-analysis concerning the clinical effectiveness of Xueshuantong injection in the treatment of DVT was of adequate power to reach firm conclusions. CONCLUSION: Based on the current analysis, Xueshuantong injection as an add-on treatment provided better treatment effect for DVT with adequate power but this benefit should be considered with caution because of the small number of studies included in the meta-analysis and the high or unclear risk of bias of the included trials, suggesting that further studies are needed.

Synthesis of spirocyclic Δ4-isoxazolines via [3 + 2] cycloaddition of indanone-derived ketonitrones with alkynes.

A [3 + 2] cycloaddition of indanone-derived nitrones and alkynes under mild conditions is developed, allowing facile synthesis of spirocyclicindenyl isoxazolines with structural diversity. The sequential protocol of generated in situ ketonitrone from unsaturated ketones and N-alkylhydroxylamines is also achieved successfully, affording the desired products in considerable yield with moderate to good diastereoselectivity. Moreover, the spirocyclic product can be conveniently transformed into indenyl-based allylic alcohol and enamide.

Detection of Pesticide Residues in Vegetables Sold in Changchun City, China.

ABSTRACT: We evaluated fresh vegetables for residues of 18 pesticides with different chemical structures, including organochlorine pesticides, organophosphorus pesticides, carbamate pesticides, and pyrethroid pesticides and estimated that the potential health risks for consumers. A total of 313 samples were collected from 12 kinds of vegetables in Changchun, the capital of Jilin Province, People's Republic of China. Pesticide residues were analyzed by gas chromatography and mass spectrometry, and the curves were highly linear at 0.01 to 1.00 µg/mL (R2 ≥ 0.99). The mean recovery rate of the pesticides was 62 to 110% (relative standard deviation of <5%). The limit of detection was 0.0001 to 0.0167 mg/kg, the limit of quantification was 0.0002 to 0.0556 mg/kg, and the overall detection rate was 28.43%. The prevalence of pesticides and of samples above the standard limit were highest in celery, the prevalence of pesticides was lowest in potatoes, and the prevalence of samples above the standard limit was lowest in cucumber. Three of the 18 pesticides were not detected: omethoate, chlorpyrifos, and fenvalerate. Among the 15 pesticides detected, the maximum risk factor of six (carbofuran, omethoate, phorate, dicofol, dimethoate, and dichlorvos) is >1, indicating possible harm to human health. Residues of a single pesticide may not adversely affect a person's health, but multiple pesticide residues could present a health risk.