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Background and purposeWhile there is evidence that gut microbiota (GM) and blood metabolites are associated with ovarian cancer (OC), the precise mechanisms underlying this relationship are still unclear. This study used Mendelian randomization (MR) to elucidate the causal connections between GM, blood metabolite biomarkers, and OC.MethodsIn this study, we leveraged summary data for GM (5,959 individuals with genotype-matched GM), blood metabolites (233 circulating metabolic traits with 136,016 participants), and OC (63,702 participants with 23,564 cases and 40,138 controls) from genome-wide association studies (GWASs). We performed MR analysis to explore the causal relationship between GM and OC. Further, we harnessed univariable MR (UVMR) analysis to evaluate the causal associations between GM and circulating metabolites. Finally, we employed a two-step approach based on multivariable MR (MVMR) to evaluate the total genetic prediction effect of metabolites mediating the GM on the risk of OC to discover a potential causal relationship.ResultsIn the MR analysis, 24 gut bacteria were causally associated with the pathogenesis of OC, including 10 gut bacteria (Dorea phocaeense, Succinivibrionaceae, Raoultella, Phascolarctobacterium sp003150755, Paenibacillus J, NK4A144, K10, UCG-010 sp003150215, Pseudomonas aeruginosa, and Planococcaceae) that were risk factors, and 14 gut bacteria (CAG-177 sp002438685, GCA-900066135 sp900066135, Enorma massiliensis, Odoribacter laneus, Ruminococcus E sp003521625, Streptococcus sanguinis, Turicibacter sp001543345, Bacillus velezensis, CAG-977, CyanobacteriaStaphylococcus A fleurettii, Caloranaerobacteraceae, RUG472 sp900319345, and CAG-269 sp001915995) that were protective factors. The UVMR analysis showed that these 24 positive gut bacteria were causally related to lipoproteins, lipids, and amino acids. According to the MVMR analysis, Enorma massiliensis could reduce the risk of OC by raising the total cholesterol to total lipids ratio in large low-density lipoprotein (LDL) and cholesteryl esters to total lipids ratio in intermediate-density lipoprotein (IDL). Turicibacter sp001543345, however, could reduce the risk of OC by lowering free cholesterol in small high-density lipoprotein (HDL) and increasing the ratios of saturated fatty acids to total fatty acids, total cholesterol to total lipids ratio in very small very-low-density lipoprotein (VLDL), and cholesteryl esters to total lipids ratio in very small VLDL.ConclusionThe current MR study provides evidence that genetically predicted blood metabolites can mediate relationships between GM and OC.

Abstract Background DJ‐1 is a causative gene for Parkinson's disease. DJ‐1‐deficient mice develop gait‐associated progressive behavioural abnormalities and hypoactive forearm grip strength. However, underlying activity mechanisms are not fully explored. Methods Western blotting and quantitative real‐time polymerase chain reaction approaches were adopted to analyse DJ‐1 expression in skeletal muscle from aged humans or mice and compared with young subjects. Skeletal muscle‐specific‐DJ‐1 knockout (MDKO) mice were generated, followed by an assessment of the physical activity phenotypes (grip strength, maximal load capacity, and hanging, rotarod, and exercise capacity tests) of the MDKO and control mice on the chow diet. Muscular atrophy phenotypes (cross‐sectional area and fibre types) were determined by imaging and quantitative real‐time polymerase chain reaction. Mitochondrial function and skeletal muscle morphology were evaluated by oxygen consumption rate and electron microscopy, respectively. Tail suspension was applied to address disuse atrophy. RNA‐seq analysis was performed to indicate molecular changes in muscles with DJ‐1 ablation. Dual‐luciferase reporter assays were employed to identify the promoter region of Trim63 and Fbxo32 genes, which were indirectly regulated by DJ‐1 via the FoxO1 pathway. Cytoplasmic and nuclear fractions of DJ‐1‐deleted muscle cells were analysed by western blotting. Compound 23 was administered into the gastrocnemius muscle to mimic the of DJ‐1 deletion effects. Results DJ‐1 expression decreased in atrophied muscles of aged human (young men, n = 2; old with aged men, n = 2; young women, n = 2; old with aged women, n = 2) and immobilization mice (n = 6, P

Abstract Background Food-borne parasitic diseases decrease food safety and threaten public health. The snail species is an intermediate host for numerous human parasitic trematodes. Orientogalba ollula has been reported as intermediate hosts of many zoonotic trematodes. Here, we investigated the prevalence of zoonotic trematodes within O. ollula in Guangxi, China, and assessed their zoonotic potential. Methods Snails were collected from 54 sites in 9 cities throughout Guangxi. The snail and trematode larvae species were determined by combining morphological characteristics and molecular markers. The trematodes prevalence and constituent ratio were calculated and compared among different habitat environments. Phylogenetic trees of the trematode species were constructed using the neighbor-joining method with nuclear internal transcribed spacer 2 (ITS2) sequences. The developmental cycles of the isolated trematodes were examined by experimental infection in ducks. The developmental characteristics of Echinostoma revolutum was recorded by dissecting infected ducklings from 1-day post infection (dpi) to 10 dpi. Results The overall prevalence of trematode larvae was 22.1% (1818/8238) in O. ollula from 11 sample sites. Morphological together with molecular identification, showed that E. revolutum, Australapatemon sp., Hypoderaeum conoideum, Pharyngostomum cordatum, and Echinostoma sp. parasitized O. ollula, with the highest infection rate of E. revolutum (13.0%). However, no Fasciola larvae were detected. The trematodes prevalence and constituent ratio varied in two sub-biotypes (P

Abstract Background Some significant differences exist between the outcomes of left‐ and right‐sided colon cancer patients. The presence of nodal metastases is a critical prognostic factor, especially in the absence of distant metastasis. Our research studied the lymph nodes status of left‐ and right‐sided colon cancer patients to determine the influence of this factor on prognosis. Methods Our data were obtained from the Surveillance, Epidemiology and End Results (SEER) database. We used the chi‐square test to analyze the clinicopathological characteristics. The X‐tile program was adopted to acquire optimal cutoff points of lymph node index. Kaplan–Meier curves were used to analyze prognosis and multivariate Cox regression models were performed to identify the independent factors associated with survival. Nomograms were built to predict the overall survival of patients, Harrell's C‐index and calibration plots were used to validate the nomograms. Results The study included 189,941 patients with colon cancer without metastasis (left 69,885, right 120,056) between 2004 and 2015. There are more patients with adequate examined lymph nodes in right‐sided. Lymph node status in patients with right colon cancer has a more significant impact on the risk of death. LODDS (C‐index: 0.583; AIC: 6875.4) was used to assess lymph node status. The nomograms showed that lymph node status was the main factor to predict the outcome in right‐sided colon patients. Conclusions The influence of lymph node status on predicting prognosis is significantly different between patients with left and right colon cancer without metastasis. The tumor site needs to be considered when lymph node status is used to assess the outcome of patients.

Gastrodia elata f.glauca (G. elata) is a commonly used Chinese Medicinal Materials with great medicinal value. The medicinal plant and its endophytic bacteria are a symbiotic whole, and the endophytic bacteria are rich in species, and their metabolites are a treasure trove of natural compounds. However, there is a relative lack of analysis on the diversity, flora composition and network interactions of the endophytic bacteria of G. elata. In this study, high-throughput sequencing technology based on the Illumina Miseq platform was used to reveal the core microbiota by examining the diversity and community structures of tuber endophytic bacteria in G. elata grown under different regions and exploring the effect of region on its endophytic bacteria. Here, 1,265 endophytic ASVs were found to coexist with G. elata tuber in Guizhou and Hubei. At the phylum level, the dominant phyla were Proteobacteria, Actinobacteria and Acdobacteriota. At the family level, the dominant family were Comamonadaceae, Nocardicaece, Xanthobacteraceae, and Burkholderiaceae. At the genus level, Delftia and Rhodococcus were represented the core microbiota in G. elata tuber, which served as the dominant genera that coexisted in all samples tested. Moreover, we found that the beta diversity of endophytic bacteria in G. elata tuber was higher level in the Guizhou region than Hubei region. Overall, this study results to provide a reference for screening active strains and interaction between plants and endophytic bacteria.

A novel triazole fluorescent sensor was efficiently synthesized using binaphthol as the starting substrate with 85% total end product yield. This chiral fluorescence sensor was proved to have high specific enantioselectivity for lysine. The fluorescence intensity of R-1 was found to increase linearly when the equivalent amount of L-lysine (0–100 eq.) was gradually increased in the system. The fluorescence intensity of L-lysine to R-1 was significantly enhanced, accompanied by the red-shift of emission wavelength (389 nm to 411 nm), which was attributed to the enhanced electron transfer within the molecular structure, resulting in an ICT effect, while the fluorescence response of D-lysine showed a decreasing trend. The enantioselective fluorescence enhancement ratio for the maximum fluorescence intensity was 31.27 [ef = |(IL − I0)/(ID − I0)|, 20 eq. Lys], thus it can be seen that this fluorescent probe can be used to identify and distinguish between different configurations of lysine.

A 78 years old Chinese woman with five different cancer types and a family history of malignancy was the subject of this study. Pancreatic adenocarcinoma and gingival squamous cell carcinoma tissues were obtained from the patient and sequenced using Whole Exome Sequencing. Whole exome sequencing identified 20 mutation sites in six candidate genes. Sanger Sequencing was used for further validation. The results verified six mutations in three genes, OBSCN, TTN, and RPGRIP1L, in at least one cancer type. Immunohistochemistry was used to verify protein expression. mRNA expression analysis using The Cancer Genome Atlas database revealed that RPGRIP1L was highly expressed in several cancer types, especially in pancreatic adenocarcinoma, and correlated with patient survival and sensitivity to paclitaxel, probably through the TGF-β signaling pathway. The newly identified somatic mutations in RPGRIP1L might contribute to pathogenesis in the patients. Protein conformation simulation demonstrated that the alterations had caused the binding pocket at position 708 to change from concave to convex, which could restrict contraction and extension, and interfere with the physiological function of the protein. Further studies are required to determine the implication of RPGRIP1L in this family and in multiple primary tumors.

As the world becomes increasingly urbanized, it is vital for planners and policy-makers to understand the patterns of urban expansion and the underlying driving forces. This study examines the spatiotemporal patterns of urban expansion in the Texas Triangle megaregion and explores the drivers behind the expansion. The study used data from multiple sources, including land cover and imperviousness data from the National Land Cover Database (NLCD) 2001–2016, transportation data from the Texas Department of Transportation (TxDOT), and ancillary socio-demographic data from the U.S. Census Bureau. We conducted spatial cluster analysis and mixed-effect regression analysis. The results show that: (1) urban expansion in the Texas Triangle between 2001 and 2016 showed a decreasing trend, and 95% of the newly urbanized land was in metropolitan areas, especially at the periphery of the central cities; (2) urban expansion in non-metropolitan areas displayed a scattered pattern, comparing to the clustered form in metro areas; (3) the expansion process in the Texas Triangle exhibited a pattern of increased development compactness and intensity; and (4) population and economic growth played a definitive role in driving the urban expansion in the Texas Triangle while highway density also mattered. These results suggest a megaregion-wide emerging trend deviating from the sprawling development course known in Texas’ urban growth history. The changing trend can be attributed to the pro-sustainability initiatives taken by several anchor cities and metropolitan planning agencies in the Texas Triangle.

With the advent of powerful network processors (NPs) in the market, many computation-intensive tasks such as routing table lookup, classification, IPSec, and multimedia transcoding can now be accomplished more easily in a router. An NP consists of a number of on-chip processors to carry out packet level parallel processing operations. Ensuring good load balancing among the processors increases throughput. However, such multiprocessing also gives rise to increased out-of-order departure of processed packets. in this paper, we first propose an Ordered Round-Robin (ORR) scheme to schedule packets in a heterogeneous NP assuming that the workload is perfectly divisible. The processed loads from the processors are ordered perfectly. We analyze the throughput and derive expressions for the batch size, scheduling time, and maximum number of schedulable processors. To effectively schedule variable length packets in an NP, we propose a Pàcketized ORR (P-ORR) scheme by applying a combination of deficit round-robin (DRR) and surplus round-robin (SRR) schemes. We extend the algorithm to handle multiple flows based on a fair scheduling of flows depending on their reservations. Extensive sensitivity results are provided through analysis and simulation to show that the proposed algorithms satisfy both the load balancing and in-order requirements for parallel packet processing. [ABSTRACT FROM AUTHOR]

We consider a cluster-based multimedia Web server that dynamically generates video units to satisfy the bit rate and bandwidth requirements of a variety of clients. The media server partitions the job into several tasks and schedules them on the backend computing nodes for processing. For stream-based applications, the main design criteria of the scheduling are to minimize the total processing time and maintain the order of media units for each outgoing stream. In this paper, we first design, implement, and evaluate three scheduling algorithms, First Fit (FF), Stream-based Mapping (SM), and Adaptive Load Sharing (ALS), for multimedia transcoding in a cluster environment. We determined that it is necessary to predict the CPU load for each multimedia task and schedule them accordingly due to the variability of the individual jobs/tasks. We, therefore, propose an online prediction algorithm that can dynamically predict the processing time per individual task (media unit). We then propose two new load scheduling algorithms, namely, Prediction-based Least Load First (P-LLF) and Prediction-based Adaptive Partitioning (P-AP), which can use prediction to improve the performance. The performance of the system is evaluated in terms of system throughput, out-of-order rate of outgoing media streams, and load balancing overhead through real measurements using a cluster of computers. The performance of the new load balancing algorithms is compared with all other load balancing schemes to show that P-AP greatly reduces the delay jitter and achieves high throughput for a variety of workloads in a heterogeneous cluster. It strikes a good balance between the throughput and output order of the processed media units. [ABSTRACT FROM AUTHOR]