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Background and purpose To investigate the association of neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and lymphocyte to monocyte ratio (LMR) with post-thrombolysis early neurological outcomes including early neurological improvement (ENI) and early neurological deterioration (END) in patients with acute ischemic stroke (AIS). Methods AIS patients undergoing intravenous thrombolysis were enrolled from April 2016 to September 2019. Blood cell counts were sampled before thrombolysis. Post-thrombolysis END was defined as the National Institutes of Health Stroke Scale (NIHSS) score increase of ≥ 4 within 24 h after thrombolysis. Post-thrombolysis ENI was defined as NIHSS score decrease of ≥ 4 or complete recovery within 24 h. Multinomial logistic regression analysis was performed to explore the relationship of NLR, PLR, and LMR to post-thrombolysis END and ENI. We also used receiver operating characteristic curve analysis to assess the discriminative ability of three ratios in predicting END and ENI. Results Among 1060 recruited patients, a total of 193 (18.2%) were diagnosed with END and 398 (37.5%) were diagnosed with ENI. Multinomial logistic model indicated that NLR (odds ratio [OR], 1.385; 95% confidence interval [CI] 1.238–1.551, P = 0.001), PLR (OR, 1.013; 95% CI 1.009–1.016, P = 0.001), and LMR (OR, 0.680; 95% CI 0.560–0.825, P = 0.001) were independent factors for post-thrombolysis END. Moreover, NLR (OR, 0.713; 95% CI 0.643–0.791, P = 0.001) served as an independent factor for post-thrombolysis ENI. Area under curve (AUC) of NLR, PLR, and LMR to discriminate END were 0.763, 0.703, and 0.551, respectively. AUC of NLR, PLR, and LMR to discriminate ENI were 0.695, 0.530, and 0.547, respectively. Conclusions NLR, PLR, and LMR were associated with post-thrombolysis END. NLR and PLR may predict post-thrombolysis END. NLR was related to post-thrombolysis ENI.

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The results of this study suggested total times of sharing injection equipment in the past 3 months and syphilis infection were significantly associated with HIV infection. Further seroepidemiologic prospective cohort studies should be conducted to clarify the impact of syphilis and high-risk sexual behaviors on HIV transmission through unprotected sexual intercourse.

HIV-1 seroconversion and subtype were evaluated, and factors associated with cohort retention were analyzed for subjects' baseline sociodemographic and behavioral characteristics in a 12-month follow-up study of injection drug users (IDUs). In November 2002, a community-based baseline survey was conducted to recruit 333 HIV-seronegative IDUs for a prospective cohort study in Xichang County of Sichuan Province, China. During the 12-month follow-up period, HIV incidence was 3.17 per 100 person-years (95% confidence interval [CI]: 0.98, 5.37), and all subtypes of 8 HIV-1 seroconversions were CRF_07BC. The retention rate at the 12-month follow-up visit was 70.3% (234 of 333 subjects). In a multiple logistic regression model, ethnicity (OR = 0.60, 95% CI: 0.34, 1.04) and appearing at the 6-month follow-up visit (OR = 9.03, 95% CI: 5.14, 15.89) were independently associated with retention. No drug-using or sexual behaviors were found to be associated with retention. This study confirmed one of drug-trafficking routes in mainland China, from Yunnan to Sichuan and then to Xinjiang. This study also suggested that HIV is spreading rapidly to more geographic areas along drug-trafficking routes in China, and a short-term follow-up rate may predict a long-term retention rate in this IDU cohort.

Osteoporosis (OP) is a chronic metabolic bone disease characterized by the decrease of bone tissue per unit volume under the combined action of genetic and environmental factors, which leads to the decrease of bone strength, makes the bone brittle, and raises the possibility of bone fracture. However, the exact mechanism that determines the progression of OP remains to be underlined. There are hundreds of trillions of symbiotic bacteria living in the human gut, which have a mutually beneficial symbiotic relationship with the human body that helps to maintain human health. With the development of modern high-throughput sequencing (HTS) platforms, there has been growing evidence that the gut microbiome may play an important role in the programming of bone metabolism. In the present review, we discuss the potential mechanisms of the gut microbiome in the development of OP, such as alterations of bone metabolism, bone mineral absorption, and immune regulation. The potential of gut microbiome-targeted strategies in the prevention and treatment of OP was also evaluated. Cite this article: Bone Joint Res 2020;9(8):524–530.

Background and purpose Acute ischaemic stroke (AIS) is a vital cause of mortality and morbidity in China. Many AIS patients develop early neurological deterioration (END). This study aimed to construct a nomogram to predict END in AIS patients. Methods Acute ischaemic stroke patients in Nanjing First Hospital were recruited as the training cohort. Additional patients in Nantong Third People’s Hospital were enrolled as the validation cohort. Multivariate logistic regression was utilized to establish the nomogram. Discrimination and calibration performance of the nomogram were tested by concordance index and calibration plots. Decision curve analysis was employed to assess the utility of the nomogram. Results In all, 1889 and 818 patients were recruited in the training and validation cohorts, respectively. Age [odds ratio (OR) 1.075; 95% confidence interval (CI) 1.059–1.091], diabetes mellitus (OR 1.673; 95% CI 1.181–2.370), atrial fibrillation (OR 3.297; 95% CI 2.005–5.421), previous antiplatelet medication (OR 0.473; 95% CI 0.301–0.744), hyper‐sensitive C‐reactive protein (OR 1.049; 95% CI 1.036–1.063) and baseline National Institutes of Health Stroke Scale (OR 1.071; 95% CI 1.045–1.098) were associated with END and incorporated in the nomogram. The concordance index was 0.826 (95% CI 0.785–0.885) and 0.798 (95% CI 0.749–0.847) in the training and validation cohorts. By decision curve analysis, the model was relevant between thresholds of 0.06 and 0.90 in the training cohort and 0.08 and 0.77 in the validation cohort. Conclusions The nomogram composed of hyper‐sensitive C‐reactive protein, age, diabetes mellitus, atrial fibrillation, previous antiplatelet medication and baseline National Institutes of Health Stroke Scale may predict the risk of END in AIS patients.