Characterization of bacterial diversity and screening of cellulose-degrading bacteria in the gut system of Glenea cantor (Fabricius) larvae

The intestinal bacteria of longhorn beetles would be ideal targets for pest control and lignocellulosic resources by destroying or exploiting their cellulose-degrading function. This article aims to investigate the diversity and community structure of intestinal bacteria the oligophagous longhorn beetle Glenea cantor. Additionally, it seeks to identify the presence of lignocellulose-degrading bacteria in the gut, and explore their role in consuming host kapok trees Bombax malabaricum. In this study, the bacterial community from G. cantor was examined by Illumina sequencing of 16S ribosomal RNA (rRNA) targeting the V3 and V4 regions. A total of 563,201 valid sequences and 814 OTUs were obtained. The dominant phyla were Proteobacteria, and the dominant genera were Acinetobacter and Lactococcus. The analysis of microbial diversity revealed a high bacterial diversity in the samples, with the gut bacteria playing a crucial role in the physiological activities of the host, particularly, 9 genera of intestinal bacteria with cellulose degradation function were found, highlighting their vital role in cellulose degradation. Five strains of cellulose-degrading bacteria, belonging to the genus Pseudomonas, were obtained from the intestinal tract of G. cantor larvae using traditional isolation and culture techniques as well as 16S rDNA sequencing. Among these strains, A4 exhibited a cellulase activity of 94.42 ± 0.42 U/mL, while A5 displayed the highest filter paper enzyme activity of 127.46 ± 3.54 U/mL. These results offered valuable insights into potential targets for pest control through internal attack digestion and cellulose-degrading bacteria in longhorn beetles

Anyons in a weakly interacting system

We describe a theoretical proposal for a system whose excitations are anyons with the exchange phase pi/4 and charge -e/2, but, remarkably, can be built by filling a set of single-particle states of essentially noninteracting electrons. The system consists of an artificially structured type-II superconducting film adjacent to a 2D electron gas in the integer quantum Hall regime with unit filling fraction. The proposal rests on the observation that a vacancy in an otherwise periodic vortex lattice in the superconductor creates a bound state in the 2DEG with total charge -e/2. A composite of this fractionally charged hole and the missing flux due to the vacancy behaves as an anyon. The proposed setup allows for manipulation of these anyons and could prove useful in various schemes for fault-tolerant topological quantum computation.Comment: 7 pages with 3 figures. For related work and info visit http://www.physics.ubc.ca/~fran

Pharmacokinetic Comparison of Ferulic Acid in Normal and Blood Deficiency Rats after Oral Administration of Angelica sinensis, Ligusticum chuanxiong and Their Combination

Radix Angelica Sinensis (RAS) and Rhizome Ligusticum (RLC) combination is a popular herb pair commonly used in clinics for treatment of blood deficiency syndrome in China. The aim of this study is to compare the pharmacokinetic properties of ferulic acid (FA), a main bioactive constituent in both RAS and RLC, between normal and blood deficiency syndrome animals, and to investigate the influence of compatibility of RAS and RLC on the pharmacokinetic of FA. The blood deficiency rats were induced by injecting 2% Acetyl phenylhydrazine (APH) on the first day, every other day, to a total of five times, at the dosage of 100, 50, 50, 30, 30 mg/kg body mass, respectively. Quantification of FA in rat plasma was achieved by using a simple and rapid HPLC method. Plasma samples were collected at different time points to construct pharmacokinetic profiles by plotting drug concentration versus time, and estimate pharmacokinetic parameters. Between normal and blood deficiency model groups, both AUC(0–t) and Cmax of FA in blood deficiency rats after RAS-RLC extract administration increased significantly (P < 0.05), while clearance (CL) decreased significantly. Among three blood deficiency model groups, t1/2α, Vd, AUC(0–t) and AUC(0–∞) all increased significantly in the RAS-RLC extract group compared with the RAS group. The results indicated that FA was absorbed better and eliminated slower in blood deficiency rats; RLC could significantly prolong the half-life of distribution, increase the volume of distribution and the absorption amount of FA of RAS in blood deficiency rats, which may be due to the synergic action when RAS and RLC were used together to treat blood deficiency syndrome

The global status of insect resistance to neonicotinoid insecticides

This document is the Accepted Manuscript version of the following article: Chris Bass, Ian Denholm, Martin S. Williamson, and Ralf Nauen, ‘The global status of insect resistance to neonicotinoid insecticides’, Pesticide Biochemistry and Physiology, Vol. 121, pp. 78-87, June 2015. The Version of Record is available online at doi: https://doi.org/10.1016/j.pestbp.2015.04.004. Published by Elsevier Copyright © 2015 Elsevier Inc.The first neonicotinoid insecticide, imidacloprid, was launched in 1991. Today this class of insecticides comprises at least seven major compounds with a market share of more than 25% of total global insecticide sales. Neonicotinoid insecticides are highly selective agonists of insect nicotinic acetylcholine receptors and provide farmers with invaluable, highly effective tools against some of the world's most destructive crop pests. These include sucking pests such as aphids, whiteflies, and planthoppers, and also some coleopteran, dipteran and lepidopteran species. Although many insect species are still successfully controlled by neonicotinoids, their popularity has imposed a mounting selection pressure for resistance, and in several species resistance has now reached levels that compromise the efficacy of these insecticides. Research to understand the molecular basis of neonicotinoid resistance has revealed both target-site and metabolic mechanisms conferring resistance. For target-site resistance, field-evolved mutations have only been characterized in two aphid species. Metabolic resistance appears much more common, with the enhanced expression of one or more cytochrome P450s frequently reported in resistant strains. Despite the current scale of resistance, neonicotinoids remain a major component of many pest control programmes, and resistance management strategies, based on mode of action rotation, are of crucial importance in preventing resistance becoming more widespread. In this review we summarize the current status of neonicotinoid resistance, the biochemical and molecular mechanisms involved, and the implications for resistance management.Peer reviewedFinal Accepted Versio

Brain injury-associated biomarkers of TGF-beta1, S100B, GFAP, NF-L, tTG, AbetaPP, and tau were concomitantly enhanced and the UPS was impaired during acute brain injury caused by Toxocara canis in mice

BACKGROUND: Because the outcomes and sequelae after different types of brain injury (BI) are variable and difficult to predict, investigations on whether enhanced expressions of BI-associated biomarkers (BIABs), including transforming growth factor beta1 (TGF-beta1), S100B, glial fibrillary acidic protein (GFAP), neurofilament light chain( NF-L), tissue transglutaminases (tTGs), beta-amyloid precursor proteins (AbetaPP), and tau are present as well as whether impairment of the ubiquitin-proteasome system (UPS) is present have been widely used to help delineate pathophysiological mechanisms in various BIs. Larvae of Toxocara canis can invade the brain and cause BI in humans and mice, leading to cerebral toxocariasis (CT). Because the parasitic burden is light in CT, it may be too cryptic to be detected in humans, making it difficult to clearly understand the pathogenesis of subtle BI in CT. Since the pathogenesis of murine toxocariasis is very similar to that in humans, it appears appropriate to use a murine model to investigate the pathogenesis of CT. METHODS: BIAB expressions and UPS function in the brains of mice inoculated with a single dose of 250 T. canis embryonated eggs was investigated from 3 days (dpi) to 8 weeks post- infection (wpi) by Western blotting and RT-PCR. RESULTS: Results revealed that at 4 and 8 wpi, T. canis larvae were found to have invaded areas around the choroid plexus but without eliciting leukocyte infiltration in brains of infected mice; nevertheless, astrogliosis, an indicator of BI, with 78.9~142.0-fold increases in GFAP expression was present. Meanwhile, markedly increased levels of other BIAB proteins including TGF-beta1, S100B, NF-L, tTG, AbetaPP, and tau, with increases ranging 2.0~12.0-fold were found, although their corresponding mRNA expressions were not found to be present at 8 wpi. Concomitantly, UPS impairment was evidenced by the overexpression of conjugated ubiquitin and ubiquitin in the brain. CONCLUSION: Further studies are needed to determine whether there is an increased risk of CT progression into neurodegenerative disease because neurodegeneration-associated AbetaPP and phosphorylated tau emerged in the brain. DOI: 10.1186/1471-2334-8-8

DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

The rapid development of open-source large language models (LLMs) has been truly remarkable. However, the scaling law described in previous literature presents varying conclusions, which casts a dark cloud over scaling LLMs. We delve into the study of scaling laws and present our distinctive findings that facilitate scaling of large scale models in two commonly used open-source configurations, 7B and 67B. Guided by the scaling laws, we introduce DeepSeek LLM, a project dedicated to advancing open-source language models with a long-term perspective. To support the pre-training phase, we have developed a dataset that currently consists of 2 trillion tokens and is continuously expanding. We further conduct supervised fine-tuning (SFT) and Direct Preference Optimization (DPO) on DeepSeek LLM Base models, resulting in the creation of DeepSeek Chat models. Our evaluation results demonstrate that DeepSeek LLM 67B surpasses LLaMA-2 70B on various benchmarks, particularly in the domains of code, mathematics, and reasoning. Furthermore, open-ended evaluations reveal that DeepSeek LLM 67B Chat exhibits superior performance compared to GPT-3.5

Automatic assessment of glioma burden: A deep learning algorithm for fully automated volumetric and bi-dimensional measurement

Background Longitudinal measurement of glioma burden with MRI is the basis for treatment response assessment. In this study, we developed a deep learning algorithm that automatically segments abnormal fluid attenuated inversion recovery (FLAIR) hyperintensity and contrast-enhancing tumor, quantitating tumor volumes as well as the product of maximum bidimensional diameters according to the Response Assessment in Neuro-Oncology (RANO) criteria (AutoRANO). Methods Two cohorts of patients were used for this study. One consisted of 843 preoperative MRIs from 843 patients with low- or high-grade gliomas from 4 institutions and the second consisted of 713 longitudinal postoperative MRI visits from 54 patients with newly diagnosed glioblastomas (each with 2 pretreatment “baseline” MRIs) from 1 institution. Results The automatically generated FLAIR hyperintensity volume, contrast-enhancing tumor volume, and AutoRANO were highly repeatable for the double-baseline visits, with an intraclass correlation coefficient (ICC) of 0.986, 0.991, and 0.977, respectively, on the cohort of postoperative GBM patients. Furthermore, there was high agreement between manually and automatically measured tumor volumes, with ICC values of 0.915, 0.924, and 0.965 for preoperative FLAIR hyperintensity, postoperative FLAIR hyperintensity, and postoperative contrast-enhancing tumor volumes, respectively. Lastly, the ICCs for comparing manually and automatically derived longitudinal changes in tumor burden were 0.917, 0.966, and 0.850 for FLAIR hyperintensity volume, contrast-enhancing tumor volume, and RANO measures, respectively. Conclusions Our automated algorithm demonstrates potential utility for evaluating tumor burden in complex posttreatment settings, although further validation in multicenter clinical trials will be needed prior to widespread implementation