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Background Tuberculosis (TB) is difficult to diagnose under complex clinical conditions as electronic health records (EHRs) are often inadequate in making an affirmative diagnosis. As exosomal miRNAs emerged as promising biomarkers, we investigated the potential of using exosomal miRNAs and EHRs in TB diagnosis.MethodsA total of 370 individuals, including pulmonary tuberculosis (PTB), tuberculous meningitis (TBM), non-TB disease controls and healthy state controls, were enrolled. Exosomal miRNAs were profiled in the exploratory cohort using microarray and miRNA candidates were selected in the selection cohort using qRT-PCR. EHRs and follow-up information of the patients were collected accordingly. miRNAs and EHRs were used to develop diagnostic models for PTB and TBM in the selection cohort with the Support Vector Machine (SVM) algorithm. These models were further evaluated in an independent testing cohort.FindingsSix exosomal miRNAs (miR-20a, miR-20b, miR-26a, miR-106a, miR-191, miR-486) were differentially expressed in the TB patients. Three SVM models, "EHR+miRNA", "miRNA only" and "EHR only" were compared, and "EHR + miRNA" model achieved the highest diagnostic efficacy, with an AUC up to 0.97 (95% CI 0.80–0.99) in TBM and 0.97 (0.87–0.99) in PTB, respectively. However, "EHR only" model only showed an AUC of 0.67 (0.46–0.83) in TBM. After 2-month anti-tuberculosis therapy, overexpressed miRNAs presented a decreased expression trend (p= 4.80 × 10−5).InterpretationOur results showed that the combination of exosomal miRNAs and EHRs could potentially improve clinical diagnosis of TBM and PTB.FundFunds for the Central Universities, the National Natural Science Foundation of China.

Anthropogenic climate change is arguably one of the biggest problems that confront us today. There is ample evidence that climate change is likely to affect adversely many aspects of life for all people around the world, and that existing solutions such as geoengineering might be too risky and ordinary behavioural and market solutions might not be sufficient to mitigate climate change. In this paper, we consider a new kind of solution to climate change, what we call human engineering, which involves biomedical modifications of humans so that they can mitigate and/or adapt to climate change. We argue that human engineering is potentially less risky than geoengineering and that it could help behavioural and market solutions succeed in mitigating climate change. We also consider some possible ethical concerns regarding human engineering such as its safety, the implications of human engineering for our children and society, and we argue that these concerns can be addressed. Our upshot is that human engineering deserves further consideration in the debate about climate change.

Distinctive challenges confronting US scientists, administrators, institutional review boards, stem cell research oversight committees, and others who will need to make decisions about work involving stem cells and their derivatives and evaluate the ethics of early human trials include evaluating the risks, safety, and benefits of these trials, determining and evaluating cell line provenance, and determining inclusion criteria, informed consent, and the ethics of conducting early human trials in the public spotlight. Further study and deliberation by stakeholders is required to move toward professional and institutional policies and practices governing this research.

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Progress in regenerative medicine seems likely to produce new treatments for neurologic conditions that use human cells as therapeutic agents; at least one trial for such an intervention is already under way. The development of cell-based interventions for neurologic conditions (CBI-NCs) will likely include preclinical studies using animals as models for humans with conditions of interest. This paper explores predictive validity challenges and the proper role for animal models in developing CBI-NCs. In spite of limitations, animal models are and will remain an essential tool for gathering data in advance of first-in-human clinical trials. The goal of this paper is to provide a realistic lens for viewing the role of animal models in the context of CBI-NCs and to provide recommendations for moving forward through this challenging terrain.

Type 1 diabetes (T1D) is an autoimmune disease characterized by the immune cell-mediated progressive destruction of pancreatic β-cells. High-mobility group box 1 protein (HMGB1) has been recognized as a potential immune mediator to enhance the development of T1D. So we speculated that HMGB1 inhibitors could have anti-diabetic effect. Sodium butyrate is a short fatty acid derivative possessing anti-inflammatory activity by inhibiting HMGB1. In the current study, we evaluated the effects of sodium butyrate in streptozotocin (STZ)-induced T1D mice model. Diabetes was induced by multiple low-dose injections of STZ (40 mg/kg/day for 5 consecutive days), and then sodium butyrate (500 mg/kg/day) was administered by intraperitoneal injection for 7 consecutive days after STZ treatment. Blood glucose, incidence of diabetes, body weight, pancreatic histopathology, the amounts of CD4+T cell subsets, IL-1β level in serum and pancreatic expressions levels of HMGB1, and NF-κB p65 protein were analyzed. The results showed that sodium butyrate treatment decreased blood glucose and serum IL-1β, improved the islet morphology and decreased inflammatory cell infiltration, restored the unbalanced Th1/Th2 ratio, and down-regulated Th17 to normal level. In addition, sodium butyrate treatment can inhibit the pancreatic HMGB1 and NF-κB p65 protein expression. Therefore, we proposed that sodium butyrate should ameliorate STZ-induced T1D by down-regulating NF-κB mediated inflammatory signal pathway through inhibiting HMGB1.