Power scaling of high-power linearly polarized fiber lasers with <10 GHz linewidth

In this work, an all-fiberized polarization-maintained (PM) fiber laser has been demonstrated with a near-top-hat-shaped spectrum. By optimizing the modulation signal to generate near-top-hat-shaped spectrums, a 3-kW PM fiber laser has been achieved at &lt;10 GHz linewidth with the polarization extinction ratio of 96% and beam quality of 1.156, which is the highest output power ever reported with approximately 10 GHz linewidth, and further scaling of output power is limited by stimulated Brillouin scattering. By decomposing the mode content, the proportion of the fundamental mode in the output laser is above 97%. The stimulated Raman scattering suppression ratio reaches 62 dB at the maximal output power

The ORF7a Protein of SARS-CoV-2 Initiates Autophagy and Limits Autophagosome-Lysosome Fusion via Degradation of SNAP29 To Promote Virus Replication

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is closely related to various cellular aspects associated with autophagy. However, how SARS-CoV-2 mediates the subversion of the macroautophagy/autophagy pathway remains largely unclear. In this study, we demonstrate that overexpression of the SARS-CoV-2 ORF7a protein activates LC3-II and leads to the accumulation of autophagosomes in multiple cell lines, while knockdown of the viral ORF7a gene via shRNAs targeting ORF7a sgRNA during SARS-CoV-2 infection decreased autophagy levels. Mechanistically, the ORF7a protein initiates autophagy via the AKT-MTOR-ULK1-mediated pathway, but ORF7a limits the progression of autophagic flux by activating CASP3 (caspase 3) to cleave the SNAP29 protein at aspartic acid residue 30 (D30), ultimately impairing complete autophagy. Importantly, SARS-CoV-2 infection-induced accumulated autophagosomes promote progeny virus production, whereby ORF7a downregulates SNAP29, ultimately resulting in failure of autophagosome fusion with lysosomes to promote viral replication. Taken together, our study reveals a mechanism by which SARS-CoV-2 utilizes the autophagic machinery to facilitate its own propagation via ORF7a.Abbreviations: 3-MA: 3-methyladenine; ACE2: angiotensin converting enzyme 2; ACTB/β-actin: actin beta; ATG7: autophagy related 7; Baf A1: bafilomycin A1; BECN1: beclin 1; CASP3: caspase 3; COVID-19: coronavirus disease 2019; GFP: green fluorescent protein; hpi: hour post-infection; hpt: hour post-transfection; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MERS: Middle East respiratory syndrome; MTOR: mechanistic target of rapamycin kinase; ORF: open reading frame; PARP: poly(ADP-ribose) polymerase; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; shRNAs: short hairpin RNAs; siRNA: small interfering RNA; SNAP29: synaptosome associated protein 29; SQSTM1/p62: sequestosome 1; STX17: syntaxin 17; TCID50: tissue culture infectious dose; TEM: transmission electron microscopy; TUBB, tubulin, beta; ULK1: unc-51 like autophagy activating kinase 1

miRNA-135a promotes breast cancer cell migration and invasion by targeting HOXA10

<p>Abstract</p> <p>Background</p> <p>miRNAs are a group of small RNA molecules regulating target genes by inducing mRNA degradation or translational repression. Aberrant expression of miRNAs correlates with various cancers. Although miR-135a has been implicated in several other cancers, its role in breast cancer is unknown. <it>HOXA10 </it>however, is associated with multiple cancer types and was recently shown to induce p53 expression in breast cancer cells and reduce their invasive ability. Because <it>HOXA10 </it>is a confirmed miR-135a target in more than one tissue, we examined miR-135a levels in relation to breast cancer phenotypes to determine if miR-135a plays role in this cancer type.</p> <p>Methods</p> <p>Expression levels of miR-135a in tissues and cells were determined by poly (A)-RT PCR. The effect of miR-135a on proliferation was evaluated by CCK8 assay, cell migration and invasion were evaluated by transwell migration and invasion assays, and target protein expression was determined by western blotting. GFP and luciferase reporter plasmids were constructed to confirm the action of miR-135a on downstream target genes including <it>HOXA10</it>. Results are reported as means ± S.D. and differences were tested for significance using 2-sided Student"s t-test.</p> <p>Results</p> <p>Here we report that miR-135a was highly expressed in metastatic breast tumors. We found that the expression of miR-135a was required for the migration and invasion of breast cancer cells, but not their proliferation. <it>HOXA10</it>, which encodes a transcription factor required for embryonic development and is a metastasis suppressor in breast cancer, was shown to be a direct target of miR-135a in breast cancer cells. Our analysis showed that miR-135a suppressed the expression of <it>HOXA10 </it>both at the mRNA and protein level, and its ability to promote cellular migration and invasion was partially reversed by overexpression of <it>HOXA10</it>.</p> <p>Conclusions</p> <p>In summary, our results indicate that miR-135a is an onco-miRNA that can promote breast cancer cell migration and invasion. <it>HOXA10 </it>is a target gene for miR-135a in breast cancer cells and overexpression of <it>HOXA10 </it>can partially reverse the miR-135a invasive phenotype.</p

Detecting Disorders of Consciousness in Brain Injuries From EEG Connectivity Through Machine Learning

Disorders of consciousness (DoC) happen frequently in various brain injuries. Their detection helps timely treatment for better survival outcomes of DoC patients. It is conventionally undertaken via clinical examinations, typically behavioural assessments. However, these neurological examinations consume significant resources of manpower and time, making continuous DoC monitoring practically infeasible. To address this issue, a computer-aided approach is proposed in this article for automated DoC detection through extracting knowledge from electroencephalogram (EEG) signals. It introduces a new connectivity measure: Power Spectral Density Difference (PSDD) incorporating with a recursive Cosine function (CPSDD). Then, the approach classifies brain-injured patients into DoC (i.e., positive) and wakefulness (i.e., negative) classes through an ensemble of support vector machines (EOSVM), which is a type of machine-learning methods. It is further applied to a dataset of 607 patients with brain injuries. Our classification results show that the EOSVM classifier with the new connectivity measure CPSDD has achieved the best classification performance among 12 connectivity measures. For a setting of 97% majority voting from all SVMs, the EOSVM has diagnosed, in high confidence, 35% of patients with the accuracy, sensitivity, and specificity of 98.21%, 100%, and 95.79%, respectively. Thus, the classifier EOSVM incorporating with the new connectivity measure CPSDD is a promising tool for automatic detection of DoC in brain injuries.</p

An ensemble of Xgboost models for detecting disorders of consciousness in brain injuries through EEG connectivity

Disorders of consciousness (DoC) happen frequently in brain injuries. Automated DoC detection is desirable because conventional clinical examinations, typically behavioural assessments, consume significant resources of manpower and time. Extracting knowledge from electroencephalogram (EEG) signals and then employing machine learning to classify patients are an attractive way to achieve automatic detection of DoC. However, an EEG dataset from brain injuries always has much more subjects without DoC than the subjects with DoC. Because of the heavy imbalance of the dataset, even if the re-sampling technique is used, it is still challenging to achieve good classification performance from, e.g., eXtreme Gradient Boosting (Xgboost), one of the most effective machine learning methods. This paper develops an ensemble of multiple Xgboost models (EoXgboost) to improve the machine learning performance for DoC detection in the presence of severe class distribution skews. We also explore effective connectivity indices to distinguish brain injuries with and without DoC. A new combined connectivity measure is shown to be effective in detecting DoC in a dataset of 648 brain injuries. Our classification results show that our EoXgboost classifier with the new combined connectivity index has achieved the best classification performance than the single connectivity indices. Our EoXgboost has detected DoC in brain injuries with the accuracy of 99.07%, AUC of 98.74%, specificity of 99.77%, and sensitivity of 97.71%. This demonstrates that our EoXgboost is a promising tool for DoC detection in brain injuries.</p

Mulberry Leaf Dietary Supplementation Can Improve the Lipo-Nutritional Quality of Pork and Regulate Gut Microbiota in Pigs: A Comprehensive Multi-Omics Analysis

Mulberry leaves, a common traditional Chinese medicine, represent a potential nutritional strategy to improve the fat profile, also known as the lipo-nutrition, of pork. However, the effects of mulberry leaves on pork lipo-nutrition and the microorganisms and metabolites in the porcine gut remain unclear. In this study, multi-omics analysis was employed in a Yuxi black pig animal model to explore the possible regulatory mechanism of mulberry leaves on pork quality. Sixty Yuxi black pigs were divided into two groups: the control group (n = 15) was fed a standard diet, and the experimental group (n = 45) was fed a diet supplemented with 8% mulberry leaves. Experiments were performed in three replicates (n = 15 per replicate); the two diets were ensured to be nutritionally balanced, and the feeding period was 120 days. The results showed that pigs receiving the diet supplemented with mulberry leaves had significantly reduced backfat thickness (p p Muribaculaceae_norank, Prevotellaceae_NK3B31_group, and Limosilactobacillus. Simultaneously, the relative levels of L-tyrosine-ethyl ester, oleic acid methyl ester, 21-deoxycortisol, N-acetyldihydrosphingosine, and mulberrin were increased. Furthermore, we found that mulberry leaf supplementation significantly increased the mRNA expression of lipoprotein lipase, fatty acid-binding protein 4, and peroxisome proliferators-activated receptor γ in muscle (p p p p p < 0.01). Collectively, this omic profile is consistent with an increased ratio of IMF to backfat in the pig model

Nanostructured lipid carriers for MicroRNA delivery in tumor gene therapy

Abstract MicroRNAs (miRNAs), which are endogenous about 20–23 nucleotides non-coding RNAs, have been acted as post-transcriptional regulators of gene expression. Current studies demonstrated that miRNAs are promising candidates for tumor gene therapy because of their important biological functions in tumor cell proliferation, metastasis, apoptosis, and drug resistance. As an important delivery system, nanostructured lipid carriers (NLCs) have great potential in tumor gene therapy, particularly for miRNA delivery, due to low toxicity, low immunogenicity, long metabolic cycles, and easy modification. This article reviews recent research progress on NLCs for miRNA delivery in tumor gene therapy and prospective applications

Adsorption Properties of Pb²⁺ by Amino Group’s Functionalized Montmorillonite from Aqueous Solutions

The remediation of wastewater containing Pb²⁺ has attracted much attention due to the harm of Pb²⁺ to the environment and human health. A promising adsorbent, functionalized montmorillonite modified with a ligand diethylenetriamine (DETA) was prepared under mild reaction conditions. The modified montmorillonite (DETA-MMT) and nature montmorillonite (Na-MMT) were then characterized with the help of XRD, FTIR, TG/DTG, and BET. It was revealed that the modifier DETA was successfully inserted into interlayers of montmorillonite, as demonstrated by the characterizations. Batch adsorption experiments of Pb²⁺ onto Na-MMT and DETA-MMT in solutions were studied as a function of various parameters, such as pH, contact time, initial concentration, and temperature. The maximum adsorption capacity of DETA-MMT was 61.1 mg g^–1, which had more than doubled compared with that of Na-MMT. The adsorption thermodynamics of Pb²⁺ by DETA-MMT was studied, and it showed a endothermic process. The adsorption kinetics of two samples both fit well with the pseudo-second-order model. The adsorption isotherms of Na-MMT and DETA-MMT can be well described by the Langmuir isotherm and Freundlich isotherm, respectively. Furthermore, the adsorbed Pb²⁺ onto DETA-MMT can hardly be dissolved under weak acidic condition (pH >4) according to the desorption experiments of simulated acid rain and Tessier’s sequential extraction procedure