The results show that TL can significantly improve the performance of decoding models across subjects/sessions and can reduce the calibration time of brain-computer interface (BCI) systems. This review summarizes the current practical suggestions and performance outcomes in the hope that it will provide guidance and help for EEG research in the future.
  Co-prescribing medications that can interact with direct-acting oral anticoagulants (DOACs) may decrease their safety and efficacy. The aim of this study was to examine the co-prescribing of such medications with DOACs using the Australian national general practice dataset, MedicineInsight, over a five-year period.
 
  We performed five sequential cross-sectional analyses in patients with atrial fibrillation (AF) and a recorded DOAC prescription. Patients were defined as having a drug interaction if they had a recorded prescription of an interacting medication while they had had a recorded prescription of DOAC in the previous six months. The sample size for the cross-sectional analyses ranged from 5333 in 2014 to 19,196 in 2018.
 
  The proportion of patients who had potential drug interactions with a DOAC decreased from 45.9% (95% confidence interval (CI) 44.6%-47.4%) in 2014 to 39.9% (95% CI 39.2%-40.6%) in 2018, 
  for trend < 0.001. During this period, the most frequent interacting class of medication recorded as having been prescribed with DOACs was selective serotonin/serotonin and norepinephrine reuptake inhibitor (SSRI/SNRI) antidepressants, followed by non-steroidal anti-inflammatory drugs (NSAIDs), calcium channel blockers (CCBs) and amiodarone.
 
  Overall, potential drug interactions with DOACs have decreased slightly over the last five years; however, the rate of possible interaction with SSRIs/SNRIs has remained relatively unchanged and warrants awareness-raising amongst prescribers.
 Overall, potential drug interactions with DOACs have decreased slightly over the last five years; however, the rate of possible interaction with SSRIs/SNRIs has remained relatively unchanged and warrants awareness-raising amongst prescribers.The struggles of China's gay sex workers-men who sell sex to other men-illustrate how the multi-layered stigma that they experience acts as a form of necropolitical power and an instrument of the state's discrimination against gay sex workers who are living with HIV. One unintended side effect of this state power is the subsequent reluctance by medical professionals to care for gay sex workers who are living with HIV, and discrimination from Chinese government officers. Data obtained from 28 gay sex workers who are living with HIV provide evidence that the necropower of stigma is routinely exercised upon the bodies of gay sex workers. This article examines how the necropolitics of social death and state-sanctioned stigma are manifested throughout China's health system, discouraging gay sex workers from receiving health care. This process uses biopolitical surveillance measures as most of gay sex workers come from rural China and do not enjoy urban hukou, thus are excluded from the medical health care system in urban China. Public health priorities demand that the cultured scripts of gendered Chinese citizenship must reevaluate the marking of the body of gay sex workers as a non-entity, a non-human and socially "dead body."Cardiovascular diseases (CVDs), including asymptomatic myocardial ischemia, angina, myocardial infarction, and ischemic heart failure, are the leading cause of death globally. Early detection and treatment of CVDs significantly contribute to the prevention or delay of cardiovascular death.  https://www.selleckchem.com/products/bismuth-subnitrate.html  Electrocardiogram (ECG) records the electrical impulses generated by heart muscles, which reflect regular or irregular beating activity. Computer-aided techniques provide fast and accurate tools to identify CVDs using a patient's ECG signal, which have achieved great success in recent years. Latest computational diagnostic techniques based on ECG signals for estimating CVDs conditions are summarized here. The procedure of ECG signals analysis is discussed in several subsections, including data preprocessing, feature engineering, classification, and application. In particular, the End-to-End models integrate feature extraction and classification into learning algorithms, which not only greatly simplifies the process of data analysis, but also shows excellent accuracy and robustness. Portable devices enable users to monitor their cardiovascular status at any time, bringing new scenarios as well as challenges to the application of ECG algorithms. Computational diagnostic techniques for ECG signal analysis show great potential for helping health care professionals, and their application in daily life benefits both patients and sub-healthy people.
  Overcorrection of serum sodium (SNa) during therapy of hyponatremia can result in osmotic demyelination syndrome. Our aim was to determine the relationship between the isotonic saline solution dose (ISSD) administered and the 24-h SNa increase (24SNa) in patients with hypovolemic hyponatremia (HH).
 
  Retrospective study of HH patients treated with ISS in a tertiary hospital of Madrid, Spain, between 1 January-30 May 2019. The 24-h ISSD received and corresponding 24SNa were calculated. The latter was classified as 3 groups ≥8 mmol/L, ≥6 mmol/L, or <4 mmol/L. Multivariate regression analyses were performed and ROC curves calculated to study the relationship between ISSD and 24SNa.
 
  Thirty patients were included, age 72 years (60-80), 50% were women. 24SNa was ≥8 mmol/L/24 h in 33%, ≥6 mmol/L/24 h in 50%, and <4 mmol/L/24 h in 30%. Median ISSD in each group was 32 mL/kg/24 h (29-37), 31 mL/kg/24 h (25-33), and 20 mL/kg/24 h (14-22), respectively. An ISSD ≥ 30 mL/kg/24 h had an odds ratio (OR) of 16 (95% CI 2.5-95.1; 
  = 0.004) for a 24SNa ≥8 mmol/L, with a sensitivity and specificity of 80%.
 
  The 24SNa depends on ISSD. An ISSD between 23-30 mL/kg/24 h seems to be safe and effective.
 The 24SNa depends on ISSD. An ISSD between 23-30 mL/kg/24 h seems to be safe and effective.Monitoring of respiration and body movements during sleep is a part of screening sleep disorders related to health status. Nowadays, thermal-based methods are presented to monitor the sleeping person without any sensors attached to the body to protect privacy. A non-contact respiration monitoring based on thermal videos requires visible facial landmarks like nostril and mouth. The limitation of these techniques is the failure of face detection while sleeping with a fixed camera position. This study presents the non-contact respiration monitoring approach that does not require facial landmark visibility under the natural sleep environment, which implies an uncontrolled sleep posture, darkness, and subjects covered with a blanket. The automatic region of interest (ROI) extraction by temperature detection and breathing motion detection is based on image processing integrated to obtain the respiration signals. A signal processing technique was used to estimate respiration and body movements information from a sequence of thermal video.