In Taiwan, chronic kidney disease (CKD) is highly prevalent and traditional Chinese medicine (TCM) is one of the most commonly used complementary medicines. To date, little information is available on the utilization patterns for TCM among CKD patients, particularly those with late stage CKD. We conducted a cross-sectional hospital-based study to investigate this issue. In this study, late stage CKD patients were identified by ICD-9-CM codes: 585 and 586, and only CKD stage 3b, 4 and 5 patients were included in the analysis. Clinical information was retrieved from the electronic medical records database from January, 1, 2006 to December, 31, 2011. Among a total of 8,459 patients, 408 TCM users and 8,051 non-TCM users were identified and their data were analyzed. We found that TCM users were almost four times more likely to be older than 55 years than non-TCM users, after controlling for the other covariates (adjusted odds ratio [aOR]: 3.98, 95% confidence interval [CI]:[2.33, 6.81]). They were also less likely to have diabetes (aOR: 0.48), hypertension (aOR: 0.62) or gout (aOR: 0.62). Among all disease conditions, late stage CKD patients with neoplasms had the highest tendency to seek TCM treatment compared to non-neoplasm CKD patients (aOR: 5.39, 95% CI: [4.64, 6.26]). Among all TCM users, internal medicine outpatient services (providing CHMs only) is more frequently used than acupuncture/massage outpatient services (3,476 vs. 320 visits). Jia-Wei-Xiao-Yao-San (JWXYS) was the most commonly prescribed Chinese herbal medicine (CHM) for late CKD patients (36.2% of 4,494 prescriptions), followed by Bu-Yang-Huan-Wu-Tang (BYHWT)

Background: In the present work, we investigated the effects of aqueous extract of Maca (AEM) on energy metabolism and immunoregulation in spleen-deficient mice. Method: We established a cyclophosphamide-induced spleen-deficiency model with ginseng, a herb that strengthens splenic function, as a control. Sixty male Kunming mice were randomly divided among 5 groups: normal, model, ginseng control (1.5 g/kg), AEM high dose (1.5 g/kg), and AEM low dose (0.75 g/kg). All animals, except those in the normal group, were injected with cyclophosphamide to induce spleen deficiency. Furthermore, we investigated differences in the thermotropic behaviors of mice using the Animal Thermotropism Behavior Surveillance System to detect energy metabolism-related assays and immune regulation assays. Results: Mice given AEM exhibited tropism in response to hot plate exposure. AEM inhibited loss of body weight and immune organ atrophy caused by cyclophosphamide, increased the cAMP/cGMP ratio in blood, and enhanced the activities of Na +-K +-ATPase, Ca 2+-Mg 2+-ATPase, lactate dehydrogenase, and hepatic glycogen. AEM significantly reversed declining white blood cells and platelet counts, and increased the hemoglobin content within peripheral blood cells. AEM improved the protein levels of IFN-γ, TNF-β, IL-2, and IL-4 in the spleen. Conclusions: Maca possesses the Traditional Chinese Medicine (TCM) property of warm and appears to strengthen spleen function.

PGE1 may have positive effects on DKD by reducing UAER, decreasing albuminuria and lessening proteinuria, with no obvious serious adverse events. However, limited by the poor methodological quality of the included studies and the small number of participants, there is currently insufficient evidence for determining if PGE1 could be used for preventing the progression of DKD. Large, properly randomised, placebo-controlled, double-blind studies are urgently needed.

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Ultra-high dimensional data, such as gene and neuroimaging data, are becoming increasingly important in biomedical science. Identifying important biomarkers from the huge number of features can help us gain better insights into further researches. Variable screening is an efficient tool to achieve this goal under the large scale cases, which reduces the dimension of features into a moderate size by removing the major part of inactive ones. Developing novel variable screening methods for high-dimensional features with group structures is challenging, especially under the overlapped cases. For example, the huge-scaled genes usually can be partitioned into hundreds of pathways according to background knowledge. One primary characteristic for this type of data is that many genes may appear across more than one pathway, which means that different pathways are overlapped. However, existing variable screening methods only could deal with disjoint group structure cases. To fill this gap, we propose a novel variable screening method for the generalized linear model by incorporating overlapped partition structures with theoretical guarantee. Besides the sure screening property, we also test the performance of the proposed method through a series of numerical studies and apply it to statistical analysis of a breast cancer data.

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