Other studies have associated ZIP12 with other diseases such as cancer. Given that ZIP12 is highly expressed in the brain and that susceptibility-weighted MRI is associated with brain metal content, ZIP12 may affect neurological diseases and psychiatric illnesses such as Parkinson’s disease, Alzheimer’s disease, and schizophrenia. Furthermore, the induction of ZIP12 and resultant zinc uptake under pathophysiological conditions may be a critical component of disease pathology, such as in pulmonary hypertension. Drug compounds that bind metals like zinc may be able to treat diseases associated with impaired zinc homeostasis and altered ZIP12 function.

The worldwide increasing prevalence of dyslipidemia has become a global health concern. Various herbal remedies have been claimed to be effective for the treatment of dyslipidemia in traditional and folkloric medicine of different regions clinical trials have been conducted to investigate their efficacy. The aim of the current systematic review is to critically assess the meta-analyses of controlled trials (CT) evaluated herb medicines for dyslipidemia.

Relevant studies from Web of Science, PubMed, Scopus, and Cochrane Library databases based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist until January 2021 have been searched. All meta-analyses which pooled studies on the effect of herbal medicines on lipid profile including total cholesterol (TC), triglyceride (TG), and low- or high-density lipoprotein cholesterol (LDL-C, HDL-C) were also included. Meta-analyses of in vitro, animal or observational studies were excluded.

The overall of 141 meta-analyses were re HDL-C (2.72mg/dl). Overall, Curcumin, Curcuminoid, and Turmeric have resulted in the reduction of TC (25.13mg/dl), LDL-C (39.83mg/dl), TG (33.65mg/dl), and an increase in the HDL-C (4.31mg/dl).

The current systematic review shed light on the use of herbal medicines for the management of dyslipidemia. However, more well-conducted CTs are required to determine effective doses of herbal medicines.

The current systematic review shed light on the use of herbal medicines for the management of dyslipidemia. However, more well-conducted CTs are required to determine effective doses of herbal medicines.

Suxiao jiuxin pill (SJP) is a Chinese medical drug with anti-inflammatory, anti-apoptotic, and vasodilatory function. It is widely used in combination with other drugs for the treatment of coronary heart disease (CHD) and angina. Nevertheless, the effect of SJP on Cytochrome P450 (CYP450) enzymes and transporters’ activity related to drug metabolism is rarely studied.

The aim of this study was to investigate the effect of SJP on the activity of drug-metabolizing enzyme CYP450 and transporters.

Human primary hepatocytes were used in present study. Probe substrates of CYP450 enzymes were incubated in human liver microsomes (HLMs) with and without SJP while IC

values were calculated. The inhibitory effect of SJP on the activity of CYP1A2, 2B6, 2C8, 2C9, 2C19, 2D6 and 3A4 was evaluated. The inducing effect of SJP on the activity of CYP1A2, 2B6 and 3A4 was accessed. The inhibition of SJP on human OATP1B1 was investigated through cell-based assay. The inhibition of SJP on human MDR1 and BCRP was also estima used in combination with related conventional drugs, potential herb-drug interactions should be considered.Diffusion weighted imaging (DWI) is a widely recognized neuroimaging technique to evaluate the microstructure of brain white matter. The objective of this study is to establish an improved automated DWI marker for estimating white matter integrity and investigating ageing related cognitive decline. The concept of Wasserstein distance was introduced to help establish a new measure difference in distribution functions (DDF), which captures the difference of reshaping one’s mean diffusivity (MD) distribution to a reference MD distribution. This new DWI measure was developed using a population-based cohort (n=19,369) from the UK Biobank. Validation was conducted using the data drawn from two independent cohorts the Sydney Memory and Ageing Study, a community-dwelling sample (n=402), and the Renji Cerebral Small Vessel Disease Cohort Study (RCCS), which consisted of cerebral small vessel disease (CSVD) patients (n=171) and cognitively normal controls (NC) (n=43). DDF was associated with age across all three samples and better explained the variance of changes than other established DWI measures, such as fractional anisotropy, mean diffusivity and peak width of skeletonized mean diffusivity (PSMD). Significant correlations between DDF and cognition were found in the UK Biobank cohort and the MAS cohort. Binary logistic analysis and receiver operator characteristic curve analysis of RCCS demonstrated that DDF had higher sensitivity in distinguishing CSVD patients from NC than the other DWI measures. To demonstrate the flexibility of DDF, we calculated regional DDF which also showed significant correlation with age and cognition. DDF can be used as a marker for monitoring the white matter microstructural changes and ageing related cognitive decline in the elderly.Mapping the structural and functional connectivity of the central nervous system has become a key area within neuroimaging research. While detailed network structures across the entire brain have been probed using animal models, non-invasive neuroimaging in humans has thus far been dominated by cortical investigations. Beyond the cortex, subcortical nuclei have traditionally been less accessible due to their smaller size and greater distance from radio frequency coils. However, major neuroimaging developments now provide improved signal and the resolution required to study these structures. Here, we present an overview of the connectivity between the amygdala, brainstem, cerebellum, spinal cord and the rest of the brain. While limitations to their imaging and analyses remain, we also provide some recommendations and considerations for mapping brain connectivity beyond the cortex.Parametric imaging based on dynamic positron emission tomography (PET) has wide applications in neurology. Compared to indirect methods, direct reconstruction methods, which reconstruct parametric images directly from the raw PET data, have superior image quality due to better noise modeling and richer information extracted from the PET raw data. AZD2014 For low-dose scenarios, the advantages of direct methods are more obvious. However, the wide adoption of direct reconstruction is inevitably impeded by the excessive computational demand and deficiency of the accessible raw data. In addition, motion modeling inside dynamic PET image reconstruction raises more computational challenges for direct reconstruction methods. In this work, we focused on the 18F-FDG Patlak model, and proposed a data-driven approach which can estimate the motion corrected full-dose direct Patlak images from the dynamic PET reconstruction series, based on a proposed novel temporal non-local convolutional neural network. During network training, direct reconstruction with motion correction based on full-dose dynamic PET sinograms was performed to obtain the training labels.