In recent years, accumulating evidence has supported the hypothesis that lower vitamin D status is associated with several known risk factors of stroke. However, the relationship between vitamin D and stroke is still uncertain. To explore if there was an association between vitamin D status and the risk of stroke, a systematic review and a meta-analysis were conducted by searching three databases: Pubmed, Embase, and the Cochrane Library. Following the application of inclusion and exclusion criteria, the relative risk estimates of all the included studies were pooled together to compare the risk of stroke between the lowest and the highest category of vitamin D. The Newcastle–Ottawa Scale (NOS) and the Cochrane Risk of Bias Tool were used to assess the risk of bias, and the publication bias was detected by using a funnel plot and Egger’s test. Nineteen studies were included and the pooled relative risk was 1.62 (95% CI: 1.34–1.96). Further analysis found that vitamin D status was associated with ischemic stroke (relative risk = 2.45, 95% CI: 1.56–3.86), but not with hemorrhagic stroke (relative risk = 2.50, 95% CI: 0.87–7.15). In conclusion, our meta-analysis supported the hypothesis that lower vitamin D status was associated with an increased risk of ischemic stroke. Further studies are required to confirm this association and to explore the association among different subtypes.

Extracting species calls from passive acoustic recordings is a common preliminary step to ecological analysis. For many species, particularly those occupying noisy, acoustically variable habitats, the call extraction process continues to be largely manual, a time-consuming and increasingly unsustainable process. Deep neural networks have been shown to offer excellent performance across a range of acoustic classification applications, but are relatively underused in ecology. We describe the steps involved in developing an automated classifier for a passive acoustic monitoring project, using the identification of calls of the Hainan gibbon Nomascus hainanus, one of the world's rarest mammal species, as a case study. This includes preprocessing-selecting a temporal resolution, windowing and annotation; data augmentation; processing-choosing and fitting appropriate neural network models; and post-processing-linking model predictions to replace, or more likely facilitate, manual labelling. Our best model converted acoustic recordings into spectrogram images on the mel frequency scale, using these to train a convolutional neural network. Model predictions were highly accurate, with per-second false positive and false negative rates of 1.5% and 22.3%. Nearly all false negatives were at the fringes of calls, adjacent to segments where the call was correctly identified, so that very few calls were missed altogether. A post-processing step identifying intervals of repeated calling reduced an 8-h recording to, on average, 22 min for manual processing, and did not miss any calling bouts over 72 h of test recordings. Gibbon calling bouts were detected regularly in multi-month recordings from all selected survey points within Bawangling National Nature Reserve, Hainan. We demonstrate that passive acoustic monitoring incorporating an automated classifier represents an effective tool for remote detection of one of the world's rarest and most threatened species. Our study highlights the viability of using neural networks to automate or greatly assist the manual labelling of data collected by passive acoustic monitoring projects. We emphasize that model development and implementation be informed and guided by ecological objectives, and increase accessibility of these tools with a series of notebooks that allow users to build and deploy their own acoustic classifiers.

K562 cells and peripheral blood mononuclear cells were treated with hydrogen peroxide (H 2 O 2 ) to determine the expression of Krüppel-like factor (KLF) 4. A full-length complementary DNA or an anti-sense oligonucleotide of KLF4 was transfected into cells, and expressions of B-cell lymphoma/leukemia-2 (bcl-2) and bcl-2-associated X (bax) proteins were analyzed. The results showed that H 2 O 2 treatment of cells resulted in an increase in KLF4 levels; KLF4 induced apoptosis and slowed cell growth, potentially resulting from upregulation of bax and down-regulation of bcl-2. Transcriptional activities on bcl-2 and bax were promoted following KLF4 overexpression potentially through KLF4 binding sites on corresponding promoters. All results indicate that KLF4 induces apoptosis in leukemia cells involving the bcl-2/bax pathway during H 2 O 2 stimulation, suggesting a potential mechanism for research on druginduced apoptosis.

The study supports the feasibility and effectiveness of the Chinese version of the CRM as an effective psychosocial intervention for Chinese patients with schizophrenia to improve psychopathology, social functioning and relapse and re-hospitalization rates.

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