To date, there is no report on the genetic diversity of ticks in these regions. A total of 370 representative ticks from the south and east regions of Kazakhstan (SERK) and Xinjiang Uygur Autonomous Region (XUAR) were selected for molecular comparison. A fragment of the mitochondrial cytochrome c oxidase subunit I (cox1) gene, ranging from 631 bp to 889 bp, was used to analyze genetic diversity among these ticks. Phylogenetic analyses indicated 7 tick species including Hyalomma asiaticum, Hyalomma detritum, Hyalomma anatolicum, Dermacentor marginatus, Rhipicephalus sanguineus, Rhipicephalus turanicus and Haemaphysalis erinacei from the SERK clustered together with conspecific ticks from the XUAR. The network diagram of haplotypes showed that i) Hy. asiaticum from Almaty and Kyzylorda Oblasts together with that from Yuli County of XUAR constituted haplogroup H-2, and the lineage from Chimkent City of South Kazakhstan was newly evolved; and ii) the R. turanicus ticks sampled in Israel, Almaty, South Kazakhstan, Usu City, Ulugqat and Baicheng Counties of XUAR were derivated from an old lineage in Alataw City of XUAR. These findings indicate that: i) Hy. asiaticum, R. turanicus and Ha. erinacei shared genetic similarities between the SERK and XUAR; and ii) Hy. marginatum and D. reticulatus show differences in their evolution.

Major depressive disorder (MDD), also referred to as depression, is one of the most common psychiatric disorders with a high economic burden. The etiology of depression is still not clear, but it is generally believed that MDD is a multifactorial disease caused by the interaction of social, psychological, and biological aspects. Therefore, there is no exact pathological theory that can independently explain its pathogenesis, involving genetics, neurobiology, and neuroimaging. At present, there are many treatment measures for patients with depression, including drug therapy, psychotherapy, and neuromodulation technology. In recent years, great progress has been made in the development of new antidepressants, some of which have been applied in the clinic. This article mainly reviews the research progress, pathogenesis, and treatment of MDD.

A correction to this paper has been published: https://doi.org/10.1007/s12264-021-00694-9.

Brain-computer interfaces (BCIs) have become one of the cutting-edge technologies in the world, and have been mainly applicated in medicine. In this article, we sorted out the development history and important scenarios of BCIs in medical application, analyzed the research progress, technology development, clinical transformation and product market through qualitative and quantitative analysis, and looked forward to the future trends. The results showed that the research hotspots included the processing and interpretation of electroencephalogram (EEG) signals, the development and application of machine learning algorithms, and the detection and treatment of neurological diseases. The technological key points included hardware development such as new electrodes, software development such as algorithms for EEG signal processing, and various medical applications such as rehabilitation and training in stroke patients. Currently, several invasive and non-invasive BCIs are in research. The R&D level of BCIs in China and the United State is leading the world, and have approved a number of non-invasive BCIs. In the future, BCIs will be applied to a wider range of medical fields. Related products will develop shift from a single mode to a combined mode. EEG signal acquisition devices will be miniaturized and wireless. The information flow and interaction between brain and machine will give birth to brain-machine fusion intelligence. Last but not least, the safety and ethical issues of BCIs will be taken seriously, and the relevant regulations and standards will be further improved.
Humans ; Brain-Computer Interfaces ; Medicine ; Algorithms ; Artificial Intelligence ; Brain