[A meta-analysis of risk factors for multidrug-resistant tuberculosis in China].

Objective: To explore the main risk factors of multidrug-resistant tuberculosis (MDR-TB) in China and to provide evidence-based evidence for MDR-TB preventon and control. Methods: All relevant literatures were searched in thedatabases, such as Pubmed, Web of Science and CNKI, Wanfang, VIP and SinoMed from 2000 to 2021. Quality evaluation and data extraction were carried out, and then a meta-analysis was performed using Stata 16.0 software. Results: A total of 59 literatures (36 cross-sectional and 23 case-control) including 75 793 participants were included in this study, and meta-analysis results showed age (OR=1.27, 95%CI: 1.05-1.54), education level (OR=1.29, 95%CI: 1.02-1.65), positive sputum smear (OR=2.56, 95%CI: 1.09-6.04), pulmonary cavity (OR=1.99, 95%CI: 1.57-2.52), course of disease (OR=4.25, 95%CI: 1.95-9.30), history of tuberculosis treatment (OR=6.42,95%CI:5.40-7.63), treatment interruption (OR=2.81, 95%CI: 1.50-5.29), irregular medication (OR=5.02, 95%CI: 2.95-8.54), adverse drug reactions (OR=4.27, 95%CI: 2.22-8.19), combined chronic obstructive pulmonary disease (COPD) (OR=2.21, 95%CI: 1.45-3.37), tuberculosis exposure history (OR=1.99, 95%CI: 1.36-2.91), smoking history (OR=1.35, 95%CI: 1.09-1.66) and floating population (OR=1.60, 95%CI: 1.04-2.44) were associated with the occurrence of MDR-TB. Conclusions: The high risk groups were farmer, low education level, pulmonary cavity, long course of disease, history of tuberculosis treatment, treatment interruption, irregular medication, adverse drug reaction, co-COPD, contact history of tuberculosis, smoking history, rural residence, and floating population. We should pay attention to high-risk groups, strengthen management and take effective measures such as early screening, knowledge education on tuberculosis, standardized and personalized treatment and whole-course supervision.

[Predictions of achievement of Sustainable Development Goal to reduce age-standardized mortality rate of four major non-communicable diseases by 2030 in China].

Objective: To predicate whether China can achieve the United Nations Sustainable Development Goals (SDGs) 3.4.1 to reduce the age-standardized mortality rate of four major non-communicable diseases (NCDs) in residents aged 30-70 years by 2030 based on the trend of the mortality from 1990 to 2019. Methods: We collected the mortality data on cardiovascular diseases, cancers, chronic respiratory diseases, and diabetes by age, gender and year in China from the Global Disease Burden Study 2019 (GBD2019). The age-period-cohort (APC) Bayesian model was applied for modeling the age-standardized mortality rate of four major NCDs in China during 2020-2030 according to the trend of the mortality during 1990-2019, and comparing the predicted value in 2030 with the observed value in 2015 to evaluate the possibility of achieving SDGs 3.4.1. Results: The age-standardized mortality rate of the four major NCDs in China showed a downward trend during 1990-2019. It is predicted that the number of death of the four NCDs in Chinese residents aged 30-70 years would increase from 2.96 million in 2020 to 3.19 million in 2030, while the age-standardized mortality rate would decrease from 308.49/100 000 in 2020 to 277.80/100 000 in 2030. The age-standardized mortality rate in 2030 would only decrease by 15.94% (18.73% for males and 14.31% for females) compared with 330.46/100 000 in 2015, with a 25.09% decrease for cardiovascular diseases, 4.76% for cancers, 37.21% for chronic respiratory diseases, and unchanged for diabetes. Conclusion: Although the age-standardized mortality rate of four major NCDs declined from 1990 to 2019 in China, it is difficult to achieve the SDGs of a 1/3 mortality rate reduction by 2030 according to the current declining trend, suggesting more active and effective efforts for NCD prevention and control are needed.

[Clinicopathological characteristics and molecular alterations of primary cardiac leiomyosarcoma: report of five cases].

Objective: To investigate the clinical, pathologic and radiologic features and molecular alterations in patients with primary cardiac leiomyosarcoma (PCLMS). Methods: Five cases of PCLMS were collected in Beijing Anzhen Hospital from January 2016 to December 2020. The clinical, pathologic and radiologic data, and molecular alterations were analyzed, and the patients were followed up. Results: All five patients were female, and had no history of leiomyosarcoma in other parts of the body. The age of patients ranged from 37 to 62 years (median 47 years). The main clinical symptoms were chest pain and dyspnea, one also presented with palpitation and lower limb weakness and one with dizziness. Two tumors were located in the left atrium, two in the right atrium, and one in the right ventricle, and they maximal diameter ranged from 2.5 to 14.0 cm (mean 6.2 cm). The neoplasms presented as medium-echo masses with a broad base in the echocardiography, and as a low-density, solid mass when detected by contrast-enhanced CT. Histologically, two tumors were well-differentiated and three were moderately and poorly differentiated, and two included extensive, loose myxoid stroma. Immunohistochemical staining showed that PCLMS was positive for SMA, desmin, MDM2, and epidermal growth factor receptor. Fluorescence in situ hybridization showed ALK gene rearrangement in two cases, and COL1A1-PDGFB fusion in three cases. All cases received surgical excision and two cases received chemotherapy. Three patients died within 0-11 months (mean survival of 7.7 months) and two patients were alive. Conclusions: PCLMS is a malignant tumor with a high recurrence rate and poor prognosis. These cases may provide useful information to improve the diagnosis and management of PCLMS.

[Current status and projection of non-communicable diseases in 126 countries participating in the Belt and Road initiative].

Objective: To compare the indicators of non-communicable diseases (NCD) and predict the achieving time of United Nations (UN) Sustainable Development Goals (SDG) in 125 countries participating in the Belt and Road (B&R) initiative and China. Methods: Using the open access data of Global Burden of Disease study, we first got the premature mortality rates of four main chronic diseases (cardiovascular disease, cancer, diabetes and chronic respiratory diseases) and suicide mortality rate in the 126 countries from1990 to 2017. We transformed the value of each indicator into a scale of 0-100 in percentile for each country and applied geometric mean to calculate total NCD score for comparison among 126 countries. We then examined the association of NCD scores with socio-demographic index (SDI) values. Finally, we used annualized rates of change during 1990-2015 to predict achieving time of the UN goal by 2030 for each indicator of chronic diseases premature mortality rate and suicide mortality rates in each B&R country. Results: The integral median of total NCD score in the 126 countries in 2017 was 82.7. The score of China was 87.6, ranking 33(rd). The top three countries were Kuwait (98.1), Peru (97.5) and Italy (96.0). The last three countries were Papua New Guinea (28.9), Vanuatu (54.7) and Ukraine (58.0). The total NCD score showed positive correlation with SDI values (r=0.33) mainly due to chronic disease indicator (r=0.45). Fifteen countries will achieve the SDG goal of chronic disease premature mortality in or before 2030, but China will achieve it in 2038. Fifteen countries are expected to achieve the goal of suicide mortality, and China will acheive the goal ahead of schedule in 2024. Conclusions: The NCD rates varied widely among the countries along B&R. It is a challenge to achieve the SDG goal of chronic disease premature mortality rate by 2030 for China. In order to achieve the SDG goals by 2030, we should strengthen multilateral cooperation and complement each other's advantages, and reduce NCD mortality of people and improve people's health in countries along B&R.

[The therapeutic effect of carnosine combined with dexamethasone in the lung injury of seawater-drowning].

Objective: To explore the therapeutic effect of carnosine and dexamethasone in lung injury caused by seawater drowning. Methods: The in vitro experiments with A549 cells were divided into 5 groups: blank control group (C), seawater injury group (S), seawater injury+dexamethasone treatment group (S+D), seawater injury+carnosine treatment group (S+C), seawater injury dexamethasone and carnosine combined therapy(S+D+C) group. The optimal therapeutic dose of drugs for the treatment of seawater drowning lung injury was tested in vitro. Based on the optimal dose, the levels of TNF-α and IL-6 in each group at different time points were detected at the cell level by ELISA. The level of apoptosis was detected by flow cytometry. The in vivo experiments with SD rats were randomly divided into 5 groups (n=8 each): blank control group (RC),seawater drowning injury group (RS),seawater drowning injury+dexamethasone treatment group (RSD),seawater drowning injury+carnosine treatment group (RSC),seawater drowning injury+dexamethasone+carnosine combined treatment group (RSDC). The animal model with seawater inhalation acute lung injury was made by intratracheal infusion (4 ml/kg). The pathological changes of the lungs were observed. The expression of superoxide dismutase (SOD) in each group was detected by Western blot. Results: The results of in vitro experiments showed significant increase of apoptosis after seawater injury. The normal cell rate in group C was 98.3% while the apoptosis rate was 1.7%. The normal cell in group S was 18.8%, and the apoptosis rate was 81% (P<0.01). TNF-α and IL-6 levels in group S increased to 180.25 ng/L and 61.56 ng/L, respectively, which were statistically significant compared with group C (P<0.01). After drug protection, apoptosis was reduced in S+D group, S+C group and S+D+C group, with apoptosis rates of 65.4%, 70.9% and 42.6%, respectively. The contents of TNF-α and IL-6 also decreased in the S+D+C group (P<0.01). The results of in vivo experiments showed obvious lung injury and disordered lung tissue structures in the RS group at 4 h after modeling. There was hemorrhage in the pulmonary interstitium and a large number of inflammatory cells. Results of western blot showed that the expression of SOD increased in the RS group. Compared with RS group, the treatment alleviated acute lung injury and decreased the expression level of SOD in RSD, RSC and RSDC groups (P<0.01). Conclusion: Dexamethasone and carnosine reduced the influence of seawater inhalation on the lung in the rat model. The positive effect of combination of these two drugs on lung injury caused by seawater inhalation was stronger than a single drug.

[Clinicopathologic study of cardiac myxofibrosarcomas].

Objective: To investigate the clinicopathologic features of cardiac myxofibrosarcomas. Methods: The clinical data, pathomorphologic and immunohistochemical features were evaluated in five cases of cardiac myxofibrosarcoma collected from January 2009 to December 2014, with relevant literature review. Results: Five patients with cardiac myxofibrosarcoma, including four women and one man [age range 39-61 years; mean (50.4±9.0) years] were included. All tumors were broadbased and located mainly in the left atrium, with one case extending through the atrial wall and pericardium to the left lower lung lobe. The morphological grade was low in one case, intermediate in one, and high in three. Using Fédération Nationale des Centres de Lutte Contre le Cancer (FNLCC) grading system, one case was grade 1 and four cases were grade 2. Immunohistochemical analysis revealed diffuse and strong expression for vimentin in all cases. Smooth muscle actin and muscle specific actin were variably expressed. Complete tumor excision was performed in one case, and tumor debulking was performed in the other four cases. Clinical follow-up was available in three cases. One patient with en bloc excision of the tumor mass survived 13 months and the other two with tumor debulking died one month after surgery. Conclusions: The most common location for cardiac myxofibrosarcoma is the left atrium. Some myxofibrosarcoma may be histologically bland and misdiagnosed as myxoma due to histological similarities. Thus caution should be exercised in their microscopic differentiation. Precise imaging, multidisciplinary approach and adequate initial surgery may contribute to improving the clinical outcomes of myxofibrosarcoma.

Homology-free prediction of functional class of proteins and peptides by support vector machines.

Protein and peptide sequences contain clues for functional prediction. A challenge is to predict sequences that show low or no homology to proteins or peptides of known function. A machine learning method, support vector machines (SVM), has recently been explored for predicting functional class of proteins and peptides from sequence-derived properties irrespective of sequence similarity, which has shown impressive performance for predicting a wide range of protein and peptide classes including certain low- and non- homologous sequences. This method serves as a new and valuable addition to complement the extensively-used alignment-based, clustering-based, and structure-based functional prediction methods. This article evaluates the strategies, current progresses, reported prediction performances, available software tools, and underlying difficulties in using SVM for predicting the functional class of proteins and peptides.

Trends in the exploration of anticancer targets and strategies in enhancing the efficacy of drug targeting.

A number of therapeutic targets have been explored for developing anticancer drugs. Continuous efforts have been directed at the discovery of new targets as well as the improvement of therapeutic efficacy of agents directed at explored targets. There are 84 and 488 targets of marketed and investigational drugs for the treatment of cancer or cancer related illness. Analysis of these targets, particularly those of drugs in clinical trials and US patents, provides useful information and perspectives about the trends, strategies and progresses in targeting key cancer-related processes and in overcoming the difficulties in developing efficacious drugs against these targets. The efficacy of anticancer drugs directed at these targets is frequently compromised by counteractive molecular interactions and network crosstalk, negative and adverse secondary effects of drugs, and undesired ADMET profiles. Multi-component therapies directed at multiple targets and improved drug targeting methods are being explored for alleviating these efficacy-reducing processes. Investigation of the modes of actions of these combinations and targeting methods offers clues to aid the development of more effective anticancer therapies.

Machine learning approaches for predicting compounds that interact with therapeutic and ADMET related proteins.

Computational methods for predicting compounds of specific pharmacodynamic and ADMET (absorption, distribution, metabolism, excretion and toxicity) property are useful for facilitating drug discovery and evaluation. Recently, machine learning methods such as neural networks and support vector machines have been explored for predicting inhibitors, antagonists, blockers, agonists, activators and substrates of proteins related to specific therapeutic and ADMET property. These methods are particularly useful for compounds of diverse structures to complement QSAR methods, and for cases of unavailable receptor 3D structure to complement structure-based methods. A number of studies have demonstrated the potential of these methods for predicting such compounds as substrates of P-glycoprotein and cytochrome P450 CYP isoenzymes, inhibitors of protein kinases and CYP isoenzymes, and agonists of serotonin receptor and estrogen receptor. This article is intended to review the strategies, current progresses and underlying difficulties in using machine learning methods for predicting these protein binders and as potential virtual screening tools. Algorithms for proper representation of the structural and physicochemical properties of compounds are also evaluated.

MODEL-molecular descriptor lab: a web-based server for computing structural and physicochemical features of compounds.

Molecular descriptors represent structural and physicochemical features of compounds. They have been extensively used for developing statistical models, such as quantitative structure activity relationship (QSAR) and artificial neural networks (NN), for computer prediction of the pharmacodynamic, pharmacokinetic, or toxicological properties of compounds from their structure. While computer programs have been developed for computing molecular descriptors, there is a lack of a freely accessible one. We have developed a web-based server, MODEL (Molecular Descriptor Lab), for computing a comprehensive set of 3,778 molecular descriptors, which is significantly more than the approximately 1,600 molecular descriptors computed by other software. Our computational algorithms have been extensively tested and the computed molecular descriptors have been used in a number of published works of statistical models for predicting variety of pharmacodynamic, pharmacokinetic, and toxicological properties of compounds. Several testing studies on the computed molecular descriptors are discussed. MODEL is accessible at http://jing.cz3.nus.edu.sg/cgi-bin/model/model.cgi free of charge for academic use.

[Phenotype of peripheral blood mononuclear cells derived dendritic cells from patients with chronic hepatitis B.].

BACKGROUND: The aim of this study was to access phenotype changes of dendritic cells (DC) cultured from peripheral blood mononuclear cells (PBMC) in patients with chronic hepatitis B and to reveal the relationship between phenotype of DC and ALT or HBV DNA. METHODS: Indices of ALT and serum HBV DNA were measured in 37 patients with chronic hepatitis B and 21 healthy controls. Peripheral blood mononuclear cells were isolated from all patients and healthy controls, and cultured with granulocyte-macrophage colony-stumilating factor (GM-CSF), interleukin-4 (IL-4) and tumor necrosis factor- (TNF-)in RPMI 1640 medium that contained 10% fetal calf serum. After culturing for 7 days, the DC was counted and the phenotypes were detected by FACS. Then the data were statistically analysed. RESULTS: The DC was significantly fewer (P less than 0.05) in patients with chronic hepatitis B than the controls. In particular, the expressive level of CD83 and CD86 on DC's surface from patients with chronic hepatitis B were also significantly lower (P less than 0.05) than that from the controls. In the patients with hepatitis B, the indices of DC had a significantly negative correlation with the level of serum HBV DNA (P less than 0.05), but no significant relationship was found between ALT and indices of DC (P greater than 0.05). CONCLUSION: The DC cultured from patients with chronic hepatitis B were few and had immature phenotype. These changes had a significantly negative correlation with the level of serum HBV DNA, but had not correlation with the inflammatory reaction levels in the liver. DC was associated with the clearance of HBV in patients with hepatitis B.

PROFEAT: a web server for computing structural and physicochemical features of proteins and peptides from amino acid sequence.

Sequence-derived structural and physicochemical features have frequently been used in the development of statistical learning models for predicting proteins and peptides of different structural, functional and interaction profiles. PROFEAT (Protein Features) is a web server for computing commonly-used structural and physicochemical features of proteins and peptides from amino acid sequence. It computes six feature groups composed of ten features that include 51 descriptors and 1447 descriptor values. The computed features include amino acid composition, dipeptide composition, normalized Moreau-Broto autocorrelation, Moran autocorrelation, Geary autocorrelation, sequence-order-coupling number, quasi-sequence-order descriptors and the composition, transition and distribution of various structural and physicochemical properties. In addition, it can also compute previous autocorrelations descriptors based on user-defined properties. Our computational algorithms were extensively tested and the computed protein features have been used in a number of published works for predicting proteins of functional classes, protein-protein interactions and MHC-binding peptides. PROFEAT is accessible at http://jing.cz3.nus.edu.sg/cgi-bin/prof/prof.cgi.

Therapeutic targets: progress of their exploration and investigation of their characteristics.

Modern drug discovery is primarily based on the search and subsequent testing of drug candidates acting on a preselected therapeutic target. Progress in genomics, protein structure, proteomics, and disease mechanisms has led to a growing interest in and effort for finding new targets and more effective exploration of existing targets. The number of reported targets of marketed and investigational drugs has significantly increased in the past 8 years. There are 1535 targets collected in the therapeutic target database compared with approximately 500 targets reported in a 1996 review. Knowledge of these targets is helpful for molecular dissection of the mechanism of action of drugs and for predicting features that guide new drug design and the search for new targets. This article summarizes the progress of target exploration and investigates the characteristics of the currently explored targets to analyze their sequence, structure, family representation, pathway association, tissue distribution, and genome location features for finding clues useful for searching for new targets. Possible "rules" to guide the search for druggable proteins and the feasibility of using a statistical learning method for predicting druggable proteins directly from their sequences are discussed.

Prediction of functional class of the SARS coronavirus proteins by a statistical learning method.

The complete genome of severe acute respiratory syndrome coronavirus (SARS-CoV) reveals the existence of putative proteins unique to SARS-CoV. Identification of their function facilitates a mechanistic understanding of SARS infection and drug development for its treatment. The sequence of the majority of these putative proteins has no significant similarity to those of known proteins, which complicates the task of using sequence analysis tools to probe their function. Support vector machines (SVM), useful for predicting the functional class of distantly related proteins, is employed to ascribe a possible functional class to SARS-CoV proteins. Testing results indicate that SVM is able to predict the functional class of 73% of the known SARS-CoV proteins with available sequences and 67% of 18 other novel viral proteins. A combination of the sequence comparison method BLAST and SVMProt can further improve the prediction accuracy of SMVProt such that the functional class of two additional SARS-CoV proteins is correctly predicted. Our study suggests that the SARS-CoV genome possibly contains a putative voltage-gated ion channel, structural proteins, a carbon-oxygen lyase, oxidoreductases acting on the CH-OH group of donors, and an ATP-binding cassette transporter. A web version of our software, SVMProt, is accessible at http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi .

A gelatin matrix-thrombin tissue sealant (FloSeal) application in the management of groin breakdown after inguinal lymphadenectomy for vulvar cancer.

The rate of groin breakdown after radical wide vulvar excision and inguinal lymphadenectomy for vulvar cancer remains significant despite conservative surgical approaches. An 86-year-old Latin American woman underwent wide radical excision and bilateral inguinal lymphadenectomy for vulvar cancer. The postoperative course was complicated by bilateral groin wound separation and high output lymphorrhea. The patient responded to the application of a gelatin matrix-thrombin tissue sealant (FloSeal) to the bases of each groin with resolution in lymphorrhea and formation of granulation tissue. The application of a gelatin matrix-thrombin tissue sealant (FloSeal) may be a viable treatment in the management of groin breakdown in selected patients when conventional therapy produces suboptimal results.

Dysregulation of olfactory receptor neuron lineage in schizophrenia.

BACKGROUND: Growing evidence implicates abnormal neurodevelopment in schizophrenia. While neuron birth and differentiation is largely completed by the end of gestation, the olfactory epithelium (OE) is a unique part of the central nervous system that undergoes regeneration throughout life, thus offering an opportunity to investigate cellular and molecular events of neurogenesis and development postmortem. We hypothesized that OE neurons exhibit deviant progress through neurodevelopment in schizophrenia characterized by an increase in immature neurons. METHODS: Olfactory epithelium was removed at autopsy from 13 prospectively assessed elderly subjects who had schizophrenia and 10 nonpsychiatric control subjects. Sections were immunolabeled with antibodies that distinguish OE neurons in different stages of development, including basal cells (low-affinity nerve growth factor receptor, p75NGFR), postmitotic immature neurons (growth-associated protein 43 [GAP43]), and mature olfactory receptor neurons (olfactory marker protein). Absolute and relative densities of each cell type were determined. RESULTS: We observed a significantly lower density of p75NGFR basal cells (37%) in schizophrenia and increases in GAP43 + postmitotic immature neurons (316%) and ratios of GAP43 + postmitotic immature neurons to p75NGFR + cells (665%) and olfactory marker protein + mature neurons to p75NGFR + basal cells (328%). Neuroleptic-free schizophrenia subjects exhibited the highest GAP43 + postmitotic immature neuron values. CONCLUSIONS: Abnormal densities and ratios of OE neurons at different stages of development indicate dysregulation of OE neuronal lineage in schizophrenia. This could be because of intrinsic factors controlling differentiation or an inability to gain trophic support from axonal targets in the olfactory bulb. While caution is necessary in extrapolating developmental findings in mature OE to early brain development, similarities in molecular events suggest that such studies may be instructive.

Radiological evidence of progression of bronchiectasis.

Radiological evidence of progression of bronchiectasis was sought in a group of 84 consecutive adult patients admitted to a tertiary unit with a particular interest in the disease. Methodical comparison for each patient of the earliest and most recent chest X-rays (n = 84), bronchograms (n = 1) and thoracic computed tomography (CT) scans (n = 32) was performed. Fifteen patients (18%) were considered to show radiological evidence of progression of bronchiectasis, 14 on chest X-ray, two of whom also showed progression on CT scans, and in one patient on bronchography alone. The likelihood of finding evidence of radiological progression increased the longer the interval between examinations. Serial radiology allows identification of patients with progression of disease and indicates the need to review management strategy.