Global, regional, and national burden of neurological disorders in 204 countries and territories worldwide.

Background: We aimed to determine the incidence and disability-adjusted life-years (DALYs) of neurological disorders worldwide from 1990 to 2019. Methods: We obtained age-standardised incidence and DALY rates of neurological disorders in 204 countries and territories from 1990 to 2019 from the Global Burden of Disease (GBD) database. We determined trends stratified by age, sex, region, country, and Social Development Index (SDI) and the risk factors contributing to DALYs associated with these neurological disorders. Results: The largest increases in the age-standardised incidence rates of neurological disorders in 1990-2019 occurred in four regions (East Asia: estimated annual percentage change (EAPC) = 0.19, tropical Latin America: EAPC = 0.07, Southern Latin America: EAPC = 0.03, Western Europe: EAPC = 0.03) and three countries (China: EAPC = 0.20, Ecuador: EAPC = 0.13, Italy: EAPC = 0.13). We observed the largest increases in age-standardised incidence rates for Parkinson disease, idiopathic epilepsy, and bipolar disorder, and in age-standardised DALY rates for Alzheimer disease and other dementias. High-SDI regions showed the highest EAPC for age-standardised incidence rates of Parkinson disease, depression, and motor neuron disease, and age-standardised DALY rates of neurological disorders. Conclusions: There is a need to control the increase in age-standardised incidence rates of neurological disorders in East Asia, tropical Latin America, Southern Latin America, and Western Europe, particularly in China, Ecuador, and Italy.

Metabolomic and transcriptomic profiling reveals the effect of dietary protein and lipid levels on growth performance in loach (Paramisgurnus dabryanus).

The subject of this study was to explore the optimum requirements of loach (Paramisgurnus dabryanus) regarding dietary proteins and lipids and discuss the underlying mechanism. We designed nine diets to determine the effects of different levels of dietary crude protein (CP: 30%, 35%, and 40%) and ether extract (EE: 6%, 10%, and 14%) on the growth performance and metabolism of P. dabryanus. In total, 2160 healthy P. dabryanus (5.19 ± 0.01 g) were divided into nine groups with four replications at 60 fish per barrel stocking density. The trial lasted for eight weeks. Serum and liver samples were gathered for metabolomic and transcriptomic analyses. The results showed that the specific growth rate of P. dabryanus in the CP40EE10 group was the fastest and notably higher than that in other groups (P< 0.05). Analysis of the metabolome results found that the mTOR signaling pathway, glycerophospholipid metabolism, D-arginine and D-ornithine metabolism were significantly enriched pathways in the CP40EE10 group compared with the other groups (P< 0.05). Moreover, the transcriptomic analysis of differentially expressed genes (DEGs) showed that the expression of ARG (arginase) involved in protein synthesis was significantly upregulated in the CP40EE10 group compared to the slowest growing group (P< 0.05). Additionally, the expression of SPLA2 (secretory phospholipase A2) involved in lipid metabolism and FBP (fructose-1,6-bisphosphatase) involved in glucose metabolism were all significantly downregulated in the CP30EE6 group compared with the CP40EE10 group (P< 0.05). Furthermore, the analysis of differentially expressed metabolites (DEMs) and DEGs co-enriched in the KEGG pathway revealed that the significantly enriched pathways were arginine and proline metabolism, glycerophospholipid metabolism, and glycolysis/gluconeogenesis in CP40EE10 compared with other groups (P< 0.05). We conclude that including 40% CP and 10% EE in the P. dabryanus diet could result in a better growth rate. We hypothesized from metabolomic and transcriptomic analyses that the CP40EE10 diet might promote the growth of P. dabryanus by promoting protein synthesis, lipid metabolism, and energy production.

Effects of different protein and lipid levels on the growth performance and intestinal microflora of loach (Paramisgurnus dabryanus).

The aim of this study was to examine the effects of dietary protein and lipid levels on the growth performance and homeostasis of the intestinal flora in Paramisgurnus dabryanus. An 8-wk 3 × 3 two-factorial experiment was conducted to investigate the interaction between dietary crude protein (CP: 30%, 35%, 40%) and ether extract (EE: 6%, 10%, 14%) on the growth rate and the intestinal microflora of P. dabryanus. A total of 2,160 fish (5.19 ± 0.01 g) were randomly allotted to 36 aquariums each with 60 fish. Fish were fed the experimental diet twice daily. Results revealed that weight gain rate (WGR), specific growth rate (SGR), protein efficiency ratio and net protein utilization significantly increased when increasing protein levels from 30% to 40% (P < 0.05). Both WGR and SGR enhanced first but reduced thereafter with maximum value at 10% lipid level as dietary lipid increased from 6% to 14% (P < 0.05). Significant interactions between protein and lipid were found with feed conversion rate, lipid efficiency ratio and net lipid utilization (P < 0.05). At the phylum level, Proteobacteria and Actinobacteria were the dominant bacteria; at the genus level, Burkholderia-Caballeronia-Paraburkholderia was the dominant bacteria. Fish fed the diet containing 10% lipid had a higher abundance of Proteobacteria and unclassified_f_Eenterobacteriaceae than those fed the 14% lipid diet, and a higher abundance of Rhodobacter than those fed the 6% lipid diet (P < 0.05). Analysis of the predicted functions showed that metabolism in the intestine of fish in the CP40EE10 group was more active than that in CP30EE14 group. Polynomial regression analysis found that a diet containing 40.87% protein and 9.88% lipid can be considered optimal for P. dabryanus.

Targeted Metabolomics With a Chemometric Study of Oxygenated Heterocyclic Aglycones as a Tool for Preliminary Authenticity Assessment of Orange and Grapefruit Juices.

Profiles of citrus juice oxygenated heterocyclic aglycones (OHAs), which are notable marker secondary metabolites, were used to assess the authenticity of sweet orange and grapefruit juices in situations where mandarin and pomelo juices might be adulterants. Thirty-nine known OHAs, including 10 methoxyflavones, 13 coumarins, and 16 furanocoumarins, as well as 13 tentatively screened OHAs, were analyzed in orange, mandarin, grapefruit and pomelo juices using our newly developed high-resolution HPLC-UV and fluorescence detection method. Quantitative OHA profiles from 158 pure juice samples were obtained to establish a purity discriminant model using an omics strategy. Reduction of OHA variables showed that three important methoxyflavones, i.e. isosinensetin, tangeretin and sinensetin provided the best discrimination ability between sweet orange and mandarin juices. There are two subtypes of pomelos, Shatianyou Group and Wendan Group, of which juices should be separately compared to grapefruit juice. Five OHAs, namely meranzin, 3,5,6,7,8,3',4'-heptamethoxyflavone, osthole, 6',7'-epoxybergamottin, and bergamottin were found to discriminate Shatianyou Group of pomelo juice from grapefruit juice; whereas three OHAs, namely bergaptol, isomeranzin, and 6',7'-dihydroxybergamottin were able to discriminate Wendan Group of pomelo juice from grapefruit juice. The established partial least squares discriminant analysis (PLS-DA) models were capable of detecting as little as 10% mandarin juice in sweet orange juice and 10% pomelo juice in grapefruit juice, allowing for fast prescreening of excess addition with good reliability (root mean square error of prediction, RMSEP < 5%).

Identification of Potential Immune Checkpoint Inhibitor Targets in Gliomas via Bioinformatic Analyses.

BACKGROUND: Glioma is a common tumor originating from the glial cells of the brain. Immune checkpoint inhibitors can potentially be used to treat gliomas, although no drug is currently approved. METHODS: The expression levels of the immune checkpoint genes in glioma and normal tissues, and their correlation with the IDH mutation status and complete 1p/19q codeletion, were analyzed using The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) databases. Survival analyses were conducted using the CGGA database. Protein-protein interaction and functional enrichment analyses were performed via the STRING database using GO, KEGG, and Reactome pathways. The correlation between the immune checkpoints and the immune cell infiltration was determined using the TISIDB and TIMER databases. RESULTS: HAVCR2 was overexpressed in the gliomas compared to normal brain tissues, as well as in the high-grade glioma patients and significantly downregulated in IDH mutant or 1p/19q codeletion patients. Overexpression of HAVCR2 was associated with poor survival in tumor grades II, III, and IV and was the most correlated with immune infiltration of B and T cells. CONCLUSION: HAVCR2 can be a potential therapeutic target for cancer immunotherapy for glioma patients.

Research on air pollutant concentration prediction method based on self-adaptive neuro-fuzzy weighted extreme learning machine.

In order to improve the prediction accuracy and real-time of the air pollutant concentration prediction, this paper proposes self-adaptive neuro-fuzzy weighted extreme learning machine (ANFIS-WELM) based on the weighted extreme learning machine (WELM) and the adaptive neuro-fuzzy inference system (ANFIS) combined air pollutant concentration prediction method. Firstly, Gaussian membership function parameters are selected to fuzzify the input values and calculate the membership degree of each input variable. Secondly, corresponding fuzzy rules are activated, and the firing strength is normalized to calculate the output matrix of hidden nodes. Then, the optimal parameters (C, M), weights are assigned to weighted ELM by using locally weighted linear regression, and the regularized WELM target formula with equality constraint is optimized by the Karush-Kuhn-Tucker (KKT) conditions, the output weight matrix is calculated, and finally the prediction output matrix is calculated. Based on the air pollutant concentration data collected in Datong, Taiwan, the data on the pollutants containing carbon monoxide (CO), nitric oxide (NO), PM2.5 (particulate matter) and PM10, are selected by different historical time series lengths, using genetic algorithm-backpropagation neural network (GA-BPNN), support vector regression (SVR), extreme learning machine (ELM), WELM, ANFIS, regularized extreme learning adaptive neuro-fuzzy inference system (R-ELANFIS) and ANFIS-WELM are built for predict the concentration of each pollutant collected by single monitoring point in single-step time series. The experimental results show that the ANFIS-WELM presented in this paper has better prediction accuracy and real-time performance, realizes the prediction of multi-step time series on the basis of the ANFIS-WELM, and realizes the engineering application of the ANFIS-WELM algorithm package on the self-developed mobile source emissions online monitoring data center software system.

[Some suggestions on the present translation of TCM terms].

The structures of "V + -ing + N" and "N + V + ed + N" were proposed, and their characteristics and advantages as well as practical application were introduced aiming at the existent problems in the present translation of TCM terms and solving them.

[Application of Nida's theory in English translation of traditional Chinese medicine].

The famous American translation theorist Eugene A. Nida has put forward lots of viewpoints and theories for translation work when he translated the Bible, which have important practical instructional meaning for translation of traditional Chinese medicine nowadays. The application of Nida's theories to translating practice of TCM is illustrated by specific examples in this paper.

[Some problems existing in current Chinese-English dictionaries of TCM nouns].

The paper discusses some problems existing in the current Chinese-English dictionaries of TCM nouns, points out their negative effects, hoping that people will attach great importance to the problems. Meanwhile the author puts forth the urgency of compiling high quality Chinese-English TCM dictionaries, and the role of such dictionaries in the standardization of English translation of TCM nouns.

Treatment of Shwachman syndrome by Japanese herbal medicine (Juzen-taiho-to): stimulatory effects of its fatty acids on hemopoiesis in patients.

Juzen-taiho-to (a Japanese herbal medicine) has been traditionally administered to patients with anemia, neutropenia, or wasting syndrome. We previously attempted to isolate and purify the hemopoiesis-stimulatory components in Juzen-taiho-to extracts using an in vitro hemopoietic stem cell (HSC) assay method in which mouse HSCs can proliferate on a stromal cell line (MS-5). We have found that fatty acids (particularly oleic acid and linolenic acid) actively promote the proliferation of HSCs, and that the effect is mediated by stromal cells, rather than by any direct action on the HSCs. In the present study, we show, using human normal bone marrow cells (BMCs) and umbilical cord blood cells, that similar stimulatory effects are due to the presence of oleic acid and linolenic acid, which stimulate the proliferation of HSCs in stroma-based culture systems. Furthermore, a marked stimulatory effect was noted on BMCs from patients with Shwachman syndrome, which shows pancreatic and bone marrow dysfunctions. We also show the data on hemopoietic recovery after the administration of Juzen-taiho-to to a patient with Shwachman syndrome. These findings suggest that decreased fatty acid levels in the blood, caused by exocrine pancreatic insufficiency, induce bone marrow dysfunction in Shwachman syndrome.