Tuberculosis (TB) is the leading infectious cause of death worldwide. A major barrier to control of the pandemic is a lack of clinical biomarkers with the ability to distinguish active TB from healthy and sick controls and potential for development into point-of-care diagnostics. We conducted a prospective case control study to identify candidate urine-based diagnostic biomarkers of active pulmonary TB (discovery cohort) and obtained a separate blinded "validation" cohort of confirmed cases of active pulmonary TB and controls with non-tuberculous pulmonary disease for validation. Clean-catch urine samples were collected and analyzed using high performance liquid chromatography-coupled time-of-flight mass spectrometry. We discovered ten molecules from the discovery cohort with receiver-operator characteristic (ROC) area-under-the-curve (AUC) values >85%. These 10 molecules also significantly decreased after 60 days of treatment in a subset of 20 participants followed over time. Of these, a specific combination of diacetylspermine, neopterin, sialic acid, and N-acetylhexosamine exhibited ROC AUCs >80% in a blinded validation cohort of participants with active TB and non-tuberculous pulmonary disease. Urinary levels of diacetylspermine, neopterin, sialic acid, and N-acetylhexosamine distinguished patients with tuberculosis from healthy controls and patients with non-tuberculous pulmonary diseases, providing a potential noninvasive biosignature of active TB. This study was funded by Weill Cornell Medicine, the National Institute of Allergy and Infectious Diseases, the Clinical and Translational Science Center at Weill Cornell, the NIH Fogarty International Center grants, and the NIH Tuberculosis Research Unit (Tri-I TBRU).

Our objective was to develop a first 19 weeks risk prediction model with several potential gestational diabetes mellitus (GDM) predictors including hepatic and renal and coagulation function measur...

Social and economic disadvantage are hypothesized to increase the risk of disease and death via accelerated biological aging. Given that US blacks are socially and economically disadvantaged relative to whites, health disparities scholars expected that blacks would have shorter telomere length–a biomarker of cell aging–than whites. Yet the majority of studies have found that blacks have longer telomere length than whites. Using data from the National Health and Nutrition Examination Survey (n = 3,761; 28.3% non-Hispanic black, 71.7% non-Hispanic white), we found that leukocyte telomere length was 4.00% (95% CI: 1.12%, 6.87%) longer among blacks compared to whites in the full sample, but differences were greatest among those with lower SES (5.66%; 95% CI: 0.10%, 10.32%), intermediate among those with middle SES (4.14%; 95% CI: 0.05%, 8.24%), and smallest among those with higher SES (2.33%; 95% CI: −3.02%, 7.67%). These results challenge purely genetic explanations for race differences in telomere length and point to a potential social-environmental cause of longer telomere length in US blacks.

Background: Acute kidney injury (AKI) is the most common and life-threatening systemic complication of rhabdomyolysis. Inflammation plays an important role in the development of rhabdomyolysis-induced AKI. This study aimed to investigate the kidney model of AKI caused by rhabdomyolysis to verify the role of macrophage Toll-like receptor 4/nuclear factor-kappa B (TLR4/NF-κB) signaling pathway. Methods: C57BL/6 mice were injected with a 50% glycerin solution at bilateral back limbs to induce rhabdomyolysis, and CLI-095 or pyrrolidine dithiocarbamate (PDTC) was intraperitoneally injected at 0.5 h before molding. Serum creatinine levels, creatine kinase, the expression of tumor necrosis factor (TNF)-α, interleukin (IL)-1β and IL-6, and hematoxylin and eosin stainings of kidney tissues were tested. The infiltration of macrophage, mRNA levels, and protein expression of TLR4 and NF-κB were investigated by immunofluorescence double-staining techniques, reverse transcriptase-quantitative polymerase chain reaction, and Western blotting, respectively. In vitro, macrophage RAW264.7 was stimulated by ferrous myoglobin; the cytokines, TLR4 and NF-κB expressions were also detected. Results: In an in vivo study, using CLI-095 or PDTC to block TLR4/NF-κB, functional and histologic results showed that the inhibition of TLR4 or NF-κB alleviated glycerol-induced renal damages (P < 0.01). CLI-095 or PDTC administration suppressed proinflammatory cytokine (TNF-α, IL-6, and IL-1β) production and macrophage infiltration into the kidney (P < 0.01). Moreover, in an in vitro study, CLI-095 or PDTC suppressed myoglobin-induced expression of TLR4, NF-κB, and proinflammatory cytokine levels in macrophage RAW264.7 cells (P < 0.01). Conclusion: The pharmacological inhibition of TLR4/NF-κB exhibited protective effects on rhabdomyolysis-induced AKI by the regulation of proinflammatory cytokine production and macrophage infiltration.

Medicine-food homology is a long-standing concept in traditional Chinese medicine. YiNianKangBao (YNKB) tea is a medicine-food formulation based on Sichuan dark tea (Ya’an Tibetan tea), which is traditionally used for its lipid-lowering properties. In this study, we evaluated the effects of YNKB on dyslipidemia and investigated the mechanism underlying its correlation with gut microbiota and serum metabolite regulation. Wild-type mice were fed a normal diet as a control. Male ApoE-/- mice were randomly divided into three high-fat diet (HFD) groups, a model group, and two treated groups (100, 400 mg/kg/d for low, high-dose), and fed by gavage for 12 weeks. Serum lipid levels, composition of gut microbiota, and serum metabolites were then analyzed before treatment with YNKB. We extracted the ingredients of YNKB in boiled water for one hour. YNKB supplementation at a high dose of 400 mg/kg/day reduced bodyweight gains (relative epididymal fat pad and liver weight), and markedly attenuated serum lipid profiles and atherosclerosis index, with no significant differences present between the low-dose treatment and HFD groups. Gut microbiota and serum metabolic analysis indicated that significant differences were observed between normal, HFD, and YNKB treatment groups. These differences in gut microbiota exhibited strong correlations with dyslipidemia-related indexes and serum metabolite levels. Oral administration of high-dose YNKB also showed significant lipid-lowering activity against hyperlipidemia in apoE-deficient mice, which might be associated with composition alterations of the gut microbiota and changes in serum metabolite abundances. These findings highlight that YNKB as a medicine-food formulation derived from Sichuan dark tea could prevent dyslipidemia and improve the understanding of its mechanisms and the pharmacological rationale for preventive use.

With the surge of interest in metabolism and the appreciation of its diverse roles in numerous biomedical contexts, the number of metabolomics studies using liquid chromatography coupled to mass spectrometry (LC-MS) approaches has increased dramatically in recent years. However, variation that occurs independently of biological signal and noise (i.e. batch effects) in metabolomics data can be substantial. Standard protocols for data normalization that allow for cross-study comparisons are lacking. Here, we investigate a number of algorithms for batch effect correction and differential abundance analysis, and compare their performance. We show that linear mixed effects models, which account for latent (i.e. not directly measurable) factors, produce satisfactory results in the presence of batch effects without the need for internal controls or prior knowledge about the nature and sources of unwanted variation in metabolomics data. We further introduce an algorithm—RRmix—within the family of latent factor models and illustrate its suitability for differential abundance analysis in the presence of strong batch effects. Together this analysis provides a framework for systematically standardizing metabolomics data.