Mutual Information-Based Brain Network Analysis in Post-stroke Patients With Different Levels of Depression

Post-stroke depression (PSD) is the most common stroke-related emotional disorder, and it severely affects the recovery process. However, more than half cases are not correctly diagnosed. This study was designed to develop a new method to assess PSD using EEG signal to analyze the specificity of PSD patients' brain network. We have 107 subjects attended in this study (72 stabilized stroke survivors and 35 non-depressed healthy subjects). A Hamilton Depression Rating Scale (HDRS) score was determined for all subjects before EEG data collection. According to HDRS score, the 72 patients were divided into 3 groups: post-stroke non-depression (PSND), post-stroke mild depression (PSMD) and post-stroke depression (PSD). Mutual information (MI)-based graph theory was used to analyze brain network connectivity. Statistical analysis of brain network characteristics was made with a threshold of 10–30% of the strongest MIs. The results showed significant weakened interhemispheric connections and lower clustering coefficient in post-stroke depressed patients compared to those in healthy controls. Stroke patients showed a decreasing trend in the connection between the parietal-occipital and the frontal area as the severity of the depression increased. PSD subjects showed abnormal brain network connectivity and network features based on EEG, suggesting that MI-based brain network may have the potential to assess the severity of depression post stroke

Medium chain fatty acid supplementation improves animal metabolic and immune status during the transition period: A study on dairy cattle

The transition period is the stage of the high incidence of metabolic and infectious diseases in dairy cows. Improving transition dairy cows’ health is crucial for the industry. This study aimed to determine the effects of dietary supplementation medium-chain fatty acids (MCFAs) on immune function, metabolic status, performance of transition dairy cows. Twenty multiparous Holstein cows randomly assigned to two treatments at 35 d before calving. 1) CON (fed the basal 2) MCFA treatment (basal diet was supplemented at an additional 20 g MCFAs mixture every day) until 70 d after calving. The results showed that the serum amyloid A myeloperoxidase concentrations in the blood of cows in MCFA treatment significantly decreased during the early lactation (from 1 d to 28 d after calving) 0.03, 0.04, respectively) compared with the CON, while the tumor necrosis factor concentration was significantly decreased at 56 d after calving (P = 0.02). In addition, the concentration of insulin in the pre-calving (from 21 d before calving to calving) blood of cows in MCFA treatment was significantly decreased (P = 0.04), and concentration of triglyceride also showed a downward trend at 28 d after calving 0.07). Meanwhile, MCFAs supplementation significantly decreased the concentrations of lithocholic acid, hyodeoxycholic acid, and hyocholic acid in the blood at 1 d calving (P = 0.02, < 0.01, < 0.01, respectively), and the level of hyocholic acid taurocholic acid concentrations (P < 0.01, = 0.01, respectively) decreased dramatically at 14 d after calving. However, compared with the CON, the pre-calving dry matter intake and the early lactation milk yield in MCFA treatment were significantly decreased (P = 0.05, 0.02, respectively). In conclusion, MCFAs supplementation transition diet could improve the immune function and metabolic status of dairy cows, and the health of transition cows might be beneficial from the endocrine status

Sex Differences in the Association between Night Shift Work and the Risk of Cancers: A Meta-Analysis of 57 Articles

Objectives. To identify the association between night shift work and the risk of various cancers with a comprehensive perspective and to explore sex differences in this association. Methods. We searched PubMed, Embase, and Web of Science for studies on the effect of night shift work on cancer, including case-control, cohort, and nested case-control studies. We computed risk estimates with 95% confidence intervals (CIs) in a random or fixed effects model and quantified heterogeneity using the I2 statistic. Subgroup, metaregression, and sensitivity analyses were performed to explore potential sources of heterogeneity. Contour-enhanced funnel plots and the trim and fill method were used together to analyze bias. Linear dose–response analysis was used to quantitatively estimate the accumulative effect of night shift work on the risk of cancer. Results. Fifty-eight studies were eligible for our meta-analysis, including 5,143,838 participants. In the random effects model, the pooled odds ratio (OR) of cancers was 1.15 (95% CI = 1.08–1.22, P<0.001; I2=76.2%). Night shift work increased the cancer risk in both men (OR = 1.14, 95% CI = 1.05–1.25, P=0.003) and women (OR = 1.12, 95% CI = 1.04–1.20, P=0.002). Subgroup analyses showed that night shift work positively increased the risk of breast (OR = 1.22, 95% CI = 1.08–1.38), prostate (OR = 1.26, 95% CI = 1.05–1.52), and digestive system (OR = 1.15, 95% CI = 1.01–1.32) cancers. For every 5 years of night shift work, the cancer risk increased by 3.2% (OR = 1.032, 95% CI = 1.013–1.051). Conclusion. This is the first meta-analysis identifying the positive association between night shift work and the risk of cancer and verifying that there is no sex difference in the effect of night shift work on cancer risk. Cancer risk increases with cumulative years of night shift work

A Matrix Metalloproteinase-1 Polymorphism, MMP1–1607 (1G>2G), Is Associated with Increased Cancer Risk: A Meta-Analysis Including 21,327 Patients

Although the matrix metalloproteinase-1 (MMP1) polymorphism MMP1–1607 (1G>2G) has been associated with susceptibility to various cancers, these findings are controversial. Therefore, we conducted this meta-analysis to explore the association between MMP1–1607 (1G>2G) and cancer risk. A systematic search of literature through PubMed, Embase, ISI Web of Knowledge, and Google Scholar yielded 77 articles with 21,327 cancer patients and 23,245 controls. The association between the MMP1–1607 (1G>2G) polymorphism and cancer risks was detected in an allele model (2G vs. 1G, overall risk [OR]: 1.174, 95% confidence interval [CI]: 1.107–1.244), a dominant model (2G2G/1G2G vs. 1G1G OR, OR: 1.192, 95% CI: 1.090–1.303), and a recessive model (2G2G vs. 1G2G/1G1G, OR: 1.231, 95% CI: 1.141–1.329). In subgroup analysis, these associations were detected in both Asians and Caucasians. After stratification by cancer types, associations were found in lung, colorectal, nervous system, renal, bladder, and nasopharyngeal cancers. This meta-analysis revealed that MMP1–1607 (1G>2G) polymorphism was significantly associated with elevated risk of cancers

PET Imaging of CD8 via SMART for Monitoring the Immunotherapy Response

Imaging of CD8 receptors on T-cells by positron emission tomography (PET) has been considered a promising strategy for monitoring the treatment response to immunotherapy. In this study, a trial of imaging CD8 with our newly developed sequential multiple-agent receptor targeting (SMART) technology was conducted. Mice bearing a subcutaneous colorectal CT26 tumor received three times different immunotherapy treatments (PD1 or CTLA4 or combined). On either day 7 or day 14 after the first time treatment, the PET imaging study was performed with sequentially administered TCO-modified anti-CD8 antibody and 64Cu-labeled MeTz-NOTA-RGD. However, no positive response was detected, probably due to (1) inappropriate selection of biomarkers for the SMART strategy, (2) limited TCO modification on the anti-CD8 antibody, and (3) inadequate response of the CT26 tumor to the selected immunotherapies. Therefore, the potential of applying SMART in imaging CD8 was not demonstrated in this study, and further optimization will be necessary before it can be applied in imaging CD8

Age Related Changes in Variability of Short-Term Heart Rate and Diastolic Period

Abstract Previous studies have proved that the heart rate variability (HRV

Altering Methane Emission, Fatty Acid Composition, and Microbial Profile during In Vitro Ruminant Fermentation by Manipulating Dietary Fatty Acid Ratios

This study evaluated the effects of different dietary n‐6/n‐3 polyunsaturated fatty acid (PUFA) ratios on in vitro ruminant fermentation. Methane production, fatty acid composition, and microbial profiles were compared after the in vitro fermentation of rumen fluid collected from cows that had been fed isoenergetic and isoproteic experimental diets at three different n‐6/n‐3 ratios: 3.04 (HN6, high n‐6 source), 2.03 (MN6, medium n‐6 source), and 0.8 (LN6, low n‐6 source). The fermented rumen fluid pH and total volatile fatty acid (VFA) levels were significantly decreased (p < 0.05) in the HN6 group as compared with those in the MN6 and LN6 groups. Additionally, the HN6 group produced a significantly lower (p < 0.05) proportion of methane than the MN6 group during in vitro fermentation. The MN6 and LN6 groups had significantly increased (p < 0.05) levels of C18:2n6 and C18:3n3 in the fermented rumen fluid, respectively, as compared with the HN6 group. The Chao 1 diversity index value was lower (p < 0.05) in the HN6 group than in the MN6 and LN6 groups. The observed species richness was significantly lower (p < 0.05) in the HN6 group than in the MN6 group. The reduced relative abundances of Lachnospiraceae UCG‐006 and Selenomonas in the HN6 group resulted in lower pH and VFA levels (i.e., acetate, propionate, butyrate, and total VFA) during in vitro fermentation. Furthermore, n‐6 and n‐3 PUFAs were toxic to Butyrivibrio_2 growth, resulting in high levels of incomplete biohydrogenation. Taken together, the study findings suggest that supplementation of high‐forage diets with high levels of n‐6 PUFAs could reduce methane emissions, whereas both VFA concentration and pH are reduced

Fourier Ptychography Reconstruction Based on Reweighted Amplitude Flow With Regularization by Denoising and Deep Decoder

Fourier ptychography (FP) is a computational imaging technique with the advantage that it can obtain large field-of-view (FOV) and high-resolution (HR) imaging. We propose an algorithm for Fourier ptychography based on reweighted amplitude flow (RAF) with regularization by denoising (RED) and deep decoder (DD), which is an untrained deep generative model. The proposed method includes two loops, using reweighted amplitude flow with regularization by denoising as an inner loop for phase retrieval and deep decoder for further denoising as an outer loop in the Fourier ptychography recovery system. The proposed method does not need any training dataset, just adds a little computer time during the image recovery process. The proposed method has no bias due to training images, which is different from other deep learning methods. The experimental results show that the proposed method can improve the reconstruction quality in both PSNR and SSIM