Sixteen prescribed Chinese herbal medicines provide time-dependent cardiorenal and survival benefits in patients with overall and advanced diabetic kidney disease: a real-world study in Taiwan

BackgroundA causal connection between oxidative stress and inflammation in diabetes, along with its associated renal and cardiovascular complications, has been established. Sixteen prescribed potentially renoprotective Chinese herbal medicines for diabetic kidney disease (PRCHMDKD), which are scientific Chinese medicine (botanical drug) and categorized into five classes (clearing heat, nourishing yin, dampness dispelling, tonifying qi, and harmonizing formulas), exhibit shared antioxidative properties and target multiple oxidative stress pathways. However, the time-response, cumulative effects, and safety (hyperkalemia risk) of these sixteen PRCHMDKD on cardiorenal and survival outcomes in patients with overall and advanced DKD remain unresolved.MethodsThis retrospective cohort study analyzed national health insurance claims data in 2000–2017. Four statistical methods, including Cox proportional hazards models, complementary restricted mean survival time (RMST), propensity score matching, and competing risk analysis for end-stage renal disease (ESRD), were employed to investigate this relationship. The study included 43,480 PRCHMDKD users and an equal number of matched nonusers within the overall DKD patient population. For advanced DKD patients, the cohort comprised 1,422 PRCHMDKD users and an equivalent number of matched nonusers.ResultsPRCHMDKD use in overall and advanced, respectively, DKD patients was associated with time-dependent reductions in adjusted hazard ratios for ESRD (0.66; 95% CI, 0.61–0.70 vs. 0.81; 0.65–0.99), all-cause mortality (0.48; 0.47–0.49 vs. 0.59; 0.50–0.70), and cardiovascular mortality (0.50; 0.48–0.53 vs. 0.61; 0.45–0.82). Significant differences in RMST were observed in overall and advanced, respectively, DKD patients, favoring PRCHMDKD use: 0.31 years (95% CI, 0.24–0.38) vs. 0.61 years (0.13–1.10) for ESRD, 2.71 years (2.60–2.82) vs. 1.50 years (1.03–1.98) for all-cause mortality, and 1.18 years (1.09–1.28) vs. 0.59 years (0.22–0.95) for cardiovascular mortality. Additionally, hyperkalemia risk did not increase. These findings remained consistent despite multiple sensitivity analyses. Notably, the cumulative effects of utilizing at least four or five classes and multiple botanical drugs from the sixteen PRCHMDKD provided enhanced renoprotection for patients with both overall and advanced DKD. This suggests that there is involvement of multiple targets within the oxidative stress pathways associated with DKD.ConclusionThis real-world study suggests that using these sixteen PRCHMDKD provides time-dependent cardiorenal and survival benefits while ensuring safety for DKD patients

Effects of dietary fatty acid composition on lipid metabolism and body fat accumulation in ovariectomized rats

BACKGROUND: Obesity is a state of excess energy storage resulting in body fat accumulation, and postmenopausal obesity is a rising issue. In this study using ovariectomized (OVX) rats, we mimicked low estrogen levels in a postmenopausal state in order to investigate the effects of different amounts and types of dietary fatty acids on body fat accumulation and body lipid metabolism. METHODS: At 9 weeks of age, rats ( RESULTS: After OVX, compared to the S group, the C group showed significantly higher body weight, and insulin and leptin levels. Compared to the C group, the H group had lower hepatic triglyceride level and FAS enzyme activity, and higher hepatic ACO and CPT-1 gene expressions and enzyme activities. CONCLUSIONS: An OVX leads to severe weight gain and lipid metabolism abnormalities, while according to previous studies, high fat diet may worsen the situation. However, during our experiment, we discovered that the experimental oil mixture with 60% MUFAs and P/S = 5 may ameliorate these imbalances

A novel regulatory event-based gene set analysis method for exploring global functional changes in heterogeneous genomic data sets

<p>Abstract</p> <p>Background</p> <p>Analyzing gene expression data by assessing the significance of pre-defined gene sets, rather than individual genes, has become a main approach in microarray data analysis and this has promisingly derive new biological interpretations of microarray data. However, the detection power of conventional gene list or gene set-based approaches is limited on highly heterogeneous samples, such as tumors.</p> <p>Results</p> <p>We developed a novel method, the regulatory <b>e</b>vent-based <b>G</b>ene <b>S</b>et <b>A</b>nalysis (eGSA), which considers not only the consistently changed genes but also every gene regulation (event) of each sample to overcome the detection limit. In comparison with conventional methods, eGSA can detect functional changes in heterogeneous samples more precisely and robustly. Furthermore, by utilizing eGSA, we successfully revealed novel functional characteristics and potential mechanisms of very early hepatocellular carcinoma (HCC).</p> <p>Conclusion</p> <p>Our study creates a novel scheme to directly target the major cellular functional changes in heterogeneous samples. All potential regulatory routines of a functional change can be further analyzed by the regulatory event frequency. We also provide a case study on early HCCs and reveal a novel insight at the initial stage of hepatocarcinogenesis. eGSA therefore accelerates and refines the interpretation of heterogeneous genomic data sets in the absence of gene-phenotype correlations.</p

GenEpi: gene-based epistasis discovery using machine learning.

BackgroundGenome-wide association studies (GWAS) provide a powerful means to identify associations between genetic variants and phenotypes. However, GWAS techniques for detecting epistasis, the interactions between genetic variants associated with phenotypes, are still limited. We believe that developing an efficient and effective GWAS method to detect epistasis will be a key for discovering sophisticated pathogenesis, which is especially important for complex diseases such as Alzheimer's disease (AD).ResultsIn this regard, this study presents GenEpi, a computational package to uncover epistasis associated with phenotypes by the proposed machine learning approach. GenEpi identifies both within-gene and cross-gene epistasis through a two-stage modeling workflow. In both stages, GenEpi adopts two-element combinatorial encoding when producing features and constructs the prediction models by L1-regularized regression with stability selection. The simulated data showed that GenEpi outperforms other widely-used methods on detecting the ground-truth epistasis. As real data is concerned, this study uses AD as an example to reveal the capability of GenEpi in finding disease-related variants and variant interactions that show both biological meanings and predictive power.ConclusionsThe results on simulation data and AD demonstrated that GenEpi has the ability to detect the epistasis associated with phenotypes effectively and efficiently. The released package can be generalized to largely facilitate the studies of many complex diseases in the near future

Slipped Capital Femoral Epiphysis as a Complication of Growth Hormone Therapy

Slipped capital femoral epiphysis (SCFE) is a rare complication of growth hormone (GH) therapy. Here, we report three patients who developed SCFE during GH therapy. The first two patients had hypopituitarism and had started GH therapy at the age of 15 years 6 months and 13 years 9 months, respectively. SCFE developed 4 years and 1 year after GH therapy, respectively. The third patient had Prader-Willi syndrome with obesity and hypogonadism and began GH therapy at the age of 12 years and 11 months. SCFE developed 2 months after starting GH therapy. Pain over the hip joints or over the knees is an early sign of SCFE. Despite recommendation, none of the three patients continued GH therapy. A high index of suspicion during GH therapy in patients at high risk of SCFE is important for early diagnosis and appropriate management. [J Formos Med Assoc 2007;106(2 Suppl):S46-S50

Renal and survival benefits of seventeen prescribed Chinese herbal medicines against oxidative-inflammatory stress in systemic lupus erythematosus patients with chronic kidney disease: a real-world longitudinal study

Background: Systemic lupus erythematosus (SLE) significantly links to LN, a type of CKD with high mortality despite modern Western treatments. About 70% of SLE patients develop LN, and 30% advance to end-stage renal disease (ESRD). Concerns about glucocorticoid side effects and LN worsening due to oxidative stress prompt alternative treatment searches. In Taiwan, over 85% of SLE patients opt for complementary methods, especially Chinese herbal medicine (CHM). We pinpointed seventeen CHMs for SLE (PRCHMSLE) with antioxidative and anti-inflammatory properties from national health insurance data (2000–2017). Our primary aim was to assess their impact on renal and survival outcomes in SLE patients progressing to CKD (SLE-CKD), with a secondary focus on the risks of hospitalization and hyperkalemia.Methods: We established a propensity-matched cohort of 1,188 patients with SLE-CKD, comprising 594 PRCHMSLE users and 594 nonusers. We employed Cox proportional hazards models and restricted mean survival time (RMST) analyses to assess the renal and survival outcomes of PRCHMSLE users. Moreover, we performed pooling and network analyses, specifically focusing on the renal effects linked to PRCHMSLE.Results: PRCHMSLE use was associated with decreased adjusted hazard ratios for ESRD (0.45; 95% confidence interval, 0.25–0.79, p = 0.006), all-cause mortality (0.56; 0.43–0.75, p &lt; 0.0001), non-cardiovascular mortality (0.56; 0.42–0.75, p &lt; 0.0001), and hospitalization (0.72; 0.52–0.96, p = 0.009). Hyperkalemia risk did not increase. Significant differences in RMST were observed: 0.57 years (95% confidence interval, 0.19–0.95, p = 0.004) for ESRD, 1.22 years (0.63–1.82, p &lt; 0.0001) for all-cause mortality, and 1.21 years (0.62–1.80, p &lt; 0.0001) for non-cardiovascular mortality, favoring PRCHMSLE use. Notably renoprotective PRCHMSLE included Gan-Lu-Ying, Anemarrhena asphodeloides Bunge [Asparagaceae; Rhizoma Anemarrhenae] (Zhi-Mu), Rehmannia glutinosa (Gaertn.) DC. [Orobanchaceae; Radix Rehmanniae] (Sheng-Di-Huang), Jia-Wei-Xiao-Yao-San, and Paeonia suffruticosa Andr. [Paeoniaceae; Cortex Moutan] (Mu-Dan-Pi). Network analysis highlighted primary treatment strategies with central components like Liu-Wei-Di-Huang-Wan, Paeonia suffruticosa Andr. [Paeoniaceae; Cortex Moutan] (Mu-Dan-Pi), Anemarrhena asphodeloides Bunge [Asparagaceae; Rhizoma Anemarrhenae] (Zhi-Mu), Rehmannia glutinosa (Gaertn.) DC. [Orobanchaceae; Radix Rehmanniae] (Sheng-Di-Huang), and Zhi-Bai-Di-Huang-Wan.Conclusion: This work underscores the pronounced renal and survival benefits associated with the seventeen PRCHMSLE in the treatment of SLE-CKD, concurrently mitigating the risks of hospitalization and hyperkalemia. This highlights their potential as alternative treatment options for individuals with this condition

Fuzzy Logic Controller Design for Intelligent Robots

This paper presents a fuzzy logic controller by which a robot can imitate biological behaviors such as avoiding obstacles or following walls. The proposed structure is implemented by integrating multiple ultrasonic sensors into a robot to collect data from a real-world environment. The decisions that govern the robot’s behavior and autopilot navigation are driven by a field programmable gate array- (FPGA-) based fuzzy logic controller. The validity of the proposed controller was demonstrated by simulating three real-world scenarios to test the bionic behavior of a custom-built robot. The results revealed satisfactorily intelligent performance of the proposed fuzzy logic controller. The controller enabled the robot to demonstrate intelligent behaviors in complex environments. Furthermore, the robot’s bionic functions satisfied its design objectives