Analysis of Clinical Characteristics and Influencing Factors of Outcome in Patients with Tuberculosis Complicated with Diabetes / 医学研究杂志

Objective To analyze the clinical characteristics and influencing factors of outcomes of patients with tuberculosis compli-cated with diabetes in southern Xinjiang.Methods The clinical data of tuberculosis patients in the Second People's Hospital of Aksu,Kuqa Infectious Disease Hospital in Aksu District,and Kashgar Pulmonary Hospital from July 2018 to January 2019 were collected,and they were divided into tuberculosis combined with diabetes(TB+DM)group and simple tuberculosis(TB)group according to the pres-ence or absence of diabetes.Univariate analysis was used to compare the general conditions,clinical symptoms,and laboratory indicators of the two groups of patients and their different blood glucose control conditions.COX regression analysis was used to evaluate the inde-pendent related factors that affect the 6-month sputum negative in diabetic patients with pulmonary tuberculosis.Results Among the 293 cases of tuberculosis,36 cases were in the TB+DM group,including 18males and 18 were females,and 257 were in the TB group,including 154males and 103 females.The results of univariate analysis showed that the time of sputum culture,age,blood glucose con-trol,fever,night sweats,triglycerides(TG),aspartate transaminase(AST),platelet(PLT),and triglyceride(TG),cholesterol(TC),cumulative lung field and newly diagnosed bacterial load were significantly different between the groups under different blood glu-cose control conditions(P＜0.05).The results of multivariate COX regression analysis showed that blood glucose control(HR=61.179,95％CI:6.338-590.549),night sweats(HR=0.085,95％CI:0.018-0.412),and initial diagnosis of bacterial load(HR=0.487,95％CI:0.268-0.885)were the independent related factors that affects the 6-month sputum culture.Conclusion Disorders of glucose and lipid metabolism in patients with tuberculosis complicated with diabetes promote the growth of mycobacterium tuberculosis and damage the body's resistance to mycobacterium tuberculosis,while night sweats,large amount of bacteria in initial diagnosis and poor blood glucose control can prolong the time of sputum turning negative and affect the prognosis of patients.Therefore,early identification of related factors,attention to the treatment of complicated diabetes and timely individualized treatment can help shorten the time of sputum turning negative,reduce the medical burden on the society and patients

Proteomic analyses of smear-positive/negative tuberculosis patients uncover differential antigen-presenting cell activation and lipid metabolism.

Background: Tuberculosis (TB) remains a major global health concern, ranking as the second most lethal infectious disease following COVID-19. Smear-Negative Pulmonary Tuberculosis (SNPT) and Smear-Positive Pulmonary Tuberculosis (SPPT) are two common types of pulmonary tuberculosis characterized by distinct bacterial loads. To date, the precise molecular mechanisms underlying the differences between SNPT and SPPT patients remain unclear. In this study, we aimed to utilize proteomics analysis for identifying specific protein signatures in the plasma of SPPT and SNPT patients and further elucidate the molecular mechanisms contributing to different disease pathogenesis. Methods: Plasma samples from 27 SPPT, 37 SNPT patients and 36 controls were collected and subjected to TMT-labeled quantitative proteomic analyses and targeted GC-MS-based lipidomic analysis. Ingenuity Pathway Analysis (IPA) was then performed to uncover enriched pathways and functionals of differentially expressed proteins. Results: Proteomic analysis uncovered differential protein expression profiles among the SPPT, SNPT, and Ctrl groups, demonstrating dysfunctional immune response and metabolism in both SPPT and SNPT patients. Both groups exhibited activated innate immune responses and inhibited fatty acid metabolism, but SPPT patients displayed stronger innate immune activation and lipid metabolic inhibition compared to SNPT patients. Notably, our analysis uncovered activated antigen-presenting cells (APCs) in SNPT patients but inhibited APCs in SPPT patients, suggesting their critical role in determining different bacterial loads/phenotypes in SNPT and SPPT. Furthermore, some specific proteins were detected to be involved in the APC activation/acquired immune response, providing some promising therapeutic targets for TB. Conclusion: Our study provides valuable insights into the differential molecular mechanisms underlying SNPT and SPPT, reveals the critical role of antigen-presenting cell activation in SNPT for effectively clearing the majority of Mtb in bodies, and shows the possibility of APC activation as a novel TB treatment strategy.

Serological investigation of brucella infection using a dipstick assay among individuals with unexplained fever in farming-pastoral areas of Xinjiang, China.

OBJECTIVE: To evaluate the brucellosis detection of the dipstick assay coated with LPS antigen from Brucella melitensis vaccine strain M5 compared with Rose Bengal test (RB) and serum agglutination test (SAT), and investigate the brucella infection with the dipstick assay among people with unexplained fever in farming-pastoral areas of Xinjiang, China. METHODS: The dipstick assay was repeated to verify 130 positive and 200 negative serum samples, which had been confirmed by RB and SAT, for sensitivity and specificity analysis. Subsequently, 313 sera from people with unexplained fever in farming-pastoral areas including 6 counties in 3 regions where brucellosis is endemic and 200 sera from nonendemic city area (Urumqi City) in Xinjiang were detected with the dipstick assay for population infection rate survey. RESULTS: Sensitivity and specificity was 100% and 97% respectively with dipstick assay compared with RB and SAT. The average positive rate of sera from people with unexplained fever from farming-pastoral areas in Xinjiang was 18.5% (58/313) and the highest was 22.5% (9/40). CONCLUSIONS: The proportion of brucellosis infection among individuals with fever of unknown origin is relatively high in agricultural and pastoral areas of Xinjiang. The dipstick assay has a series of advantages such as low cost and fast speed, which make it suitable for the primary screening of high-risk populations.

Serum Proteomic Analysis for New Types of Long-Term Persistent COVID-19 Patients in Wuhan.

The emergence of a new type of COVID-19 patients, who were retested positive after hospital discharge with long-term persistent SARS-CoV-2 infection but without COVID-19 clinical symptoms (hereinafter, LTPPs), poses novel challenges to COVID-19 treatment and prevention. Why was there such a contradictory phenomenon in LTPPs? To explore the mechanism underlying this phenomenon, we performed quantitative proteomic analyses using the sera of 12 LTPPs (Wuhan Pulmonary Hospital), with the longest carrying history of 132 days, and mainly focused on 7 LTPPs without hypertension (LTPPs-NH). The results showed differential serum protein profiles between LTPPs/LTPPs-NH and health controls. Further analysis identified 174 differentially-expressed-proteins (DEPs) for LTPPs, and 165 DEPs for LTPPs-NH, most of which were shared. GO and KEGG analyses for these DEPs revealed significant enrichment of "coagulation" and "immune response" in both LTPPs and LTPPs-NH. A unity of contradictory genotypes in the 2 aspects were then observed: some DEPs showed the same dysregulated expressed trend as that previously reported for patients in the acute phase of COVID-19, which might be caused by long-term stimulation of persistent SARS-CoV-2 infection in LTPPs, further preventing them from complete elimination; in contrast, some DEPs showed the opposite expression trend in expression, so as to retain control of COVID-19 clinical symptoms in LTPPs. Overall, the contrary effects of these DEPs worked together to maintain the balance of LTPPs, further endowing their contradictory steady-state with long-term persistent SARS-CoV-2 infection but without symptoms. Additionally, our study revealed some potential therapeutic targets of COVID-19. Further studies on these are warranted. IMPORTANCE This study reported a new type of COVID-19 patients and explored the underlying molecular mechanism by quantitative proteomic analyses. DEPs were significantly enriched in "coagulation" and "immune response". Importantly, we identified 7 "coagulation system"- and 9 "immune response"-related DEPs, the expression levels of which were consistent with those previously reported for patients in the acute phase of COVID-19, which appeared to play a role in avoiding the complete elimination of SARS-CoV-2 in LTPPs. On the contrary, 6 "coagulation system"- and 5 "immune response"-related DEPs showed the opposite trend in expression. The 11 inconsistent serum proteins seem to play a key role in the fight against long-term persistent SARS-CoV-2 infection, further retaining control of COVID-19 clinical symptom of LTPPs. The 26 proteins can serve as potential therapeutic targets and are thus valuable for the treatment of LTPPs; further studies on them are warranted.

A bla SIM-1 and mcr-9.2 harboring Klebsiella michiganensis strain reported and genomic characteristics of Klebsiella michiganensis.

As a newly emerging Klebsiella pathogen, more and more Klebsiella michiganensis drug resistant strains have been reported in recent years, which posed serious threats to public health. Here we first reported a multidrug-resistant K. michiganensis strain 12084 with two bla SIM-1 and one mcr-9.2 genes isolated from the sputum specimen of a patient in the Second Affiliated Hospital of Zhejiang University School of Medicine and analyzed its genetic basis and drug-resistance phenotypes. Genetic analysis showed that this strain harbored three different incompatibility groups (IncHI2, IncHI5, and IncFIIpKPHS2:IncFIB-4.1) of plasmids (p12084-HI2, p12084-HI5, and p12084-FII). A total of 26 drug-resistance genes belonging to 12 classes of antibiotics were identified, most of which (24) were located on two plasmids (p12084-HI2 and p12084-HI5). Interestingly, two bla SIM-1 genes were identified to locate on p12084-HI2 and p12084-HI5, respectively, both of which were embedded in In630, indicating their genetic homogeny. It was noting that one bla SIM-1 gene was situated in a novel unit transposon (referred to as Tn6733) on the p12084-HI5 plasmid. We also discovered an mcr-9.2 gene on the p12084-HI2 plasmid. To the best of our knowledge, this is the first report of a bla SIM-1 and mcr-9.2 harboring K. michiganensis strain. We then investigated the population structure/classification, and antibiotic resistance for all 275 availably global K. michiganensis genomes. Population structure revealed that K. michiganensis could be divided into two main clades (Clade 1 and Clade 2); the most popular ST29 was located in Clade 1, while other common STs (such as ST50, ST27, and ST43) were located in Clade 2. Drug-resistance analysis showed 25.5% of the K. michiganensis strains (70/275) harboring at least one carbapenemase gene, indicating severe drug resistance of K. michiganensis beyond our imagination; this is a dangerous trend and should be closely monitored, especially for ST27 K. michiganensis with the most drug-resistant genes among all the STs. Overall, we reported a bla SIM-1 and mcr-9.2 harboring K. michiganensis strain, and further revealed the population structure/classification, and drug-resistance of K. michiganensis, which provided an important framework, reference, and improved understanding of K. michiganensis.

Combining metabolome and clinical indicators with machine learning provides some promising diagnostic markers to precisely detect smear-positive/negative pulmonary tuberculosis.

BACKGROUND: Tuberculosis (TB) had been the leading lethal infectious disease worldwide for a long time (2014-2019) until the COVID-19 global pandemic, and it is still one of the top 10 death causes worldwide. One important reason why there are so many TB patients and death cases in the world is because of the difficulties in precise diagnosis of TB using common detection methods, especially for some smear-negative pulmonary tuberculosis (SNPT) cases. The rapid development of metabolome and machine learning offers a great opportunity for precision diagnosis of TB. However, the metabolite biomarkers for the precision diagnosis of smear-positive and smear-negative pulmonary tuberculosis (SPPT/SNPT) remain to be uncovered. In this study, we combined metabolomics and clinical indicators with machine learning to screen out newly diagnostic biomarkers for the precise identification of SPPT and SNPT patients. METHODS: Untargeted plasma metabolomic profiling was performed for 27 SPPT patients, 37 SNPT patients and controls. The orthogonal partial least squares-discriminant analysis (OPLS-DA) was then conducted to screen differential metabolites among the three groups. Metabolite enriched pathways, random forest (RF), support vector machines (SVM) and multilayer perceptron neural network (MLP) were performed using Metaboanalyst 5.0, "caret" R package, "e1071" R package and "Tensorflow" Python package, respectively. RESULTS: Metabolomic analysis revealed significant enrichment of fatty acid and amino acid metabolites in the plasma of SPPT and SNPT patients, where SPPT samples showed a more serious dysfunction in fatty acid and amino acid metabolisms. Further RF analysis revealed four optimized diagnostic biomarker combinations including ten features (two lipid/lipid-like molecules and seven organic acids/derivatives, and one clinical indicator) for the identification of SPPT, SNPT patients and controls with high accuracy (83-93%), which were further verified by SVM and MLP. Among them, MLP displayed the best classification performance on simultaneously precise identification of the three groups (94.74%), suggesting the advantage of MLP over RF/SVM to some extent. CONCLUSIONS: Our findings reveal plasma metabolomic characteristics of SPPT and SNPT patients, provide some novel promising diagnostic markers for precision diagnosis of various types of TB, and show the potential of machine learning in screening out biomarkers from big data.

Bioinformation Analysis Reveals IFIT1 as Potential Biomarkers in Central Nervous System Tuberculosis.

OBJECTIVE: Central nervous system tuberculosis is the most serious form of extrapulmonary tuberculosis. We aim to discover potential biomarkers involved in the development of the disease. METHODS: Through gene difference analysis, construction of a protein interaction network and tissue specific analysis and other bioinformatics analysis methods, we found out the relatively high expression of important substances in the central nervous system, interferon induced protein with tetratricopeptide repeats 1. Subsequently, the lesion tissue and the resection margin tissue away from the lesion were collected from the 6 cases of central nervous system tuberculosis patients diagnosed from 2019 to 2020, and the pathological manifestations were observed by Hematoxylin and Eosin (H&E) staining, and the expression of IFIT1 was verified by immunohistochemistry. RESULTS: A total of 101 differential genes were analyzed between extrapulmonary tuberculosis patients and normal people, and they were mainly enriched in the interferon pathway. The protein interaction network unearthed 34 key genes. Through tissue specific analysis, it was found that IFIT1 is relatively high in the central nervous system. H&E staining showed the expression of multinucleated macrophages, and immunohistochemistry showed that IFIT1 was significantly positively expressed in the lesion tissue. CONCLUSION: IFIT1 is an important substance involved in central nervous system tuberculosis.

Study on the relationship between CXCR3 and its ligands and tubal tuberculosis.

OBJECTIVE: Chemokines play an important role in Mycobacterium tuberculosis infection. We aimed to investigate CXCR3, CXCL9, CXCL10 and CXCL11 to explore the correlation between the severity of tubal tuberculosis and chemokines. METHODS: 26 patients with tubal tuberculosis diagnosed in our hospital from 2016 to 2019 were selected as the experimental group, and 18 female patients who underwent high-risk pregnancy supervision in our hospital from 2016 to 2018 were selected as the control group. The pathological manifestations of tubal tuberculosis were observed by HE staining, the expressions of CXCR3 and its ligands in fallopian tubes were detected by immunohistochemistry. RESULTS: Typical granulomatous structure of tubal tuberculosis was observed by HE staining and most of them were accompanied by massive necrosis in the experimental group, while no granulomatous lesions were found in the control group. The results of immunohistochemical staining showed that CXCR3 and its ligands were expressed in the cytoplasm and nucleus of oviduct epithelial cells and inflammatory cells, in the granuloma area. CXCL9, CXCL10 and CXCL11 were related to the severity of the disease. KEY FINDINGS: CXCR3 and its ligands were positively expressed in tubal tuberculosis, especially CXCL9, CXCL10 and CXCL11 were positively correlated with the severity of fallopian tube disease. SIGNIFICANCE: It is helpful for clinical diagnosis and treatment detection, and provides a new therapeutic target for the study of female genital tuberculosis in the future.

Pancreas protective effects of Urolithin A on type 2 diabetic mice induced by high fat and streptozotocin via regulating autophagy and AKT/mTOR signaling pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Urolithin A (UroA), the main intestinal microflora metabolite of ellagic acid of berries, pomegranate,and some other traditional chinese herbals such as emblica officinalis,etc,has been reported to exhibit anti-inflammatory, anti-oxidative, anti-tumor and pro-autophagy effects. AIM OF THE STUDY: This study evaluated the anti-diabetic and pancreas-protective effects of UroA using a mice model of type 2 diabetes and preliminarily explored its effect on autophagy as well as the mechanism involved. MATERIALS AND METHODS: Type 2 diabetes model was induced by high-fat diet (HFD; 60% energy as fat) and low-dose streptozotocin (85 mg/kg) injection. Mice were administered with UroA (50 mg/kg/d) alone or UroA-chloroquine (autophagy inhibitor) combination for 8 weeks. RESULTS: UroA improved symptoms of diabetic mice such as high water intake volume, high urine volume, significantly decreased fasting blood glucose (FBG), after-glucose-loading glucose, glycated hemoglobin (GHb) levels, plasma C-peptide, malondialdehyde (MDA) and interleukin-1 ß level, increased reduced glutathione (GSH), interleukin-10 content, and glucose tolerance. UroA also improved pancreatic function indexes such as HOMA-ß as evidenced by improved pathological and ultrastructural features of the pancreas assessed by light microscopy and transmission electron microscopy (TEM). Accordingly, UroA decreased mitochondrial swelling and myelin-like cytoplasmic inclusions. UroA significantly upregulated the protein levels of microtubule-associated protein 1 light chain 3-II (LC3II) and beclin1, downregulated sequestosome 1 (p62) accompanied by decreased expression of apoptotic protein cleaved caspase3 in pancreas of diabetic mice. In addition, it increased the phosphorylation level of protein kinase B (p-Akt) and mammalian target of rapamycin (p-mTOR). Most of these effects of UroA were reversed by treatment with autophagy inhibitor chloroquine. CONCLUSIONS: Our findings reveal that the pancreas protective effects of UroA against diabetes were partially mediated by its regulation of autophagy and AKT/mTOR signal pathway.