Notes

MiR-339 and galectin-3: analytical benefit within patients with respiratory tract obstruction following lung transplantation.
(iii) A two-layered ReliefF algorithm is used for feature ranking and feature selection. (iv) The most discriminative features are fed to various shallow classifiers, developed using a 10-fold cross-validation strategy for automated autism detection.

A support vector machine (SVM) classifier reached 96.44% accuracy based on features from the proposed model.

The results strongly indicate that the proposed hybrid deep lightweight feature extractor is suitable for autism detection using EEG signals. The model is ready to serve as part of an adjunct tool that aids neurologists during autism diagnosis in medical centers.
The results strongly indicate that the proposed hybrid deep lightweight feature extractor is suitable for autism detection using EEG signals. The model is ready to serve as part of an adjunct tool that aids neurologists during autism diagnosis in medical centers.Predicting protein-protein interaction sites (PPI sites) can provide important clues for understanding biological activity. Using machine learning to predict PPI sites can mitigate the cost of running expensive and time-consuming biological experiments. Here we propose PPISP-XGBoost, a novel PPI sites prediction method based on eXtreme gradient boosting (XGBoost). First, the characteristic information of protein is extracted through the pseudo-position specific scoring matrix (PsePSSM), pseudo-amino acid composition (PseAAC), hydropathy index and solvent accessible surface area (ASA) under the sliding window. Next, these raw features are preprocessed to obtain more optimal representations in order to achieve better prediction. In particular, the synthetic minority oversampling technique (SMOTE) is used to circumvent class imbalance, and the kernel principal component analysis (KPCA) is applied to remove redundant characteristics. Finally, these optimal features are fed to the XGBoost classifier to identify PPI sites. Using PPISP-XGBoost, the prediction accuracy on the training dataset Dset186 reaches 85.4%, and the accuracy on the independent validation datasets Dtestset72, PDBtestset164, Dset_448 and Dset_355 reaches 85.3%, 83.9%, 85.8% and 85.4%, respectively, which all show an increase in accuracy against existing PPI sites prediction methods. These results demonstrate that the PPISP-XGBoost method can further enhance the prediction of PPI sites.The term 'MicroRNA' (miRNA) refers to a class of small endogenous non-coding RNAs (ncRNAs) regenerated from hairpin transcripts. Recent studies reveal miRNAs' regulatory involvement in essential biological processes through translational repression or mRNA degradation. Recently, there is a growing body of literature focusing on the importance of miRNAs and their functions. In this respect, several databases have been developed to manage the dispersed data produced. Therefore, it is necessary to know the parameters and characteristics of each database to benefit their data. Besides, selecting the correct database is of great importance to scientists who do not have enough experience in this field. A comprehensive classification along with an explanation of the information contained in each database leads to facilitating access to these resources. In this regard, we have classified relevant databases into several categories, including miRNA sequencing and annotation, validated/predicted miRNA targets, disease-related miRNA, SNP in miRNA sequence or target site, miRNA-related pathways, or gene ontology, and mRNA-miRNA interactions. Hence, this review introduces available miRNA databases and presents a convenient overview to inform researchers of different backgrounds to find suitable miRNA-related bioinformatics web tools and relevant information rapidly.Strabismus is an eye disease that affects about 0.12%-9.86% of the population, which can cause irreversible sensory damage to vision and psychological problems. The most severe cases require surgical intervention, despite other less invasive techniques being available for a more conservative approach. As for surgeries, the treatment goal is to align the eyes to recover binocular vision, which demands knowledge, training, and experience. One of the leading causes of failure is human error during the measurement of deviation. Thus, this work proposes a new method based on the Decision Tree Regressor algorithms to assist in the surgical planning for horizontal strabismus to predict recoil and resection measures in the lateral and medial rectus muscles. In the presented method, two application approaches were taken, being in the form of multiple single target models, one procedure at a time, and the form of one multiple target model or all surgical procedures together. The method's efficiency is indicated by the average difference between the value indicated by the method and the physician's value. In our most accurate model, an average error of 0.66 mm was obtained for all surgical procedures, both for resection and recoil in the indication of the horizontal strabismus surgical planning. The results present the feasibility of using Decision Tree Regressor algorithms to perform the planning of strabismus surgeries, making it possible to predict correction values for surgical procedures based on medical data analysis and exceeding state-of-art.The spatial distribution and temporal trends of trace metals (i.e. Cd, Cu, Hg, Pb and Zn) and a metalloid (i.e. As) along the Spanish Mediterranean coast from 1993 to 2013 are presented with a new estimation of their background levels monitored using wild mussels. Over a 20 years period, yearly mussel monitoring was undertaken with a rigorous field sampling protocol using 3 pooled samples strategy (3 x n = 80, with 8 mussels in the 3.0 to 3.9 size categories at each site), obtained in the pre-spawning period (May-June) to minimize biological factors and seasonal variability, which is a fundamental element of the international programme. Spatial distribution was characterized every 5 years and temporal trends were determined in 11 locations. The main aims of the present long term study are to evaluate the environmental status of different coastal locations regarding trace metal levels and follow the evolution of these levels over time after the implementation of regulatory measures. Regarding spatial distributoast as a threshold criterion 1.62 mg/kg d.w. for Cd, 8.75 mg/kg d.w. for Cu, 0.202 mg/kg d.w. for Hg and 2.83 mg/kg d.w. for Pb. Exceptions should exist for As and Zn, for which there should be different levels in each demarcation, due to the geological, hydrological and oceanographic peculiarities of the Spanish coast. For the Levantine-Balearic demarcation, the proposed background concentrations are 117 mg/kg d.w. for As and 200 mg/kg d.w. for Zn., whereas in the Strait of Gibraltar-Alboran Sea demarcation, they are 27.5 mg/kg d.w. for As, and 471 mg/kg d.w. N6022 order for Zn. This work demonstrates the vital importance of defining the background levels of metal(loid)s at a regional or subregional level because, for areas not affected by anthropogenic causes which have high values as the result of natural processes, this would avoid the risk of constantly surpassing the levels proposed in directives.Cyclothone braueri (Stomiiformes, Gonostomatidae) is a widely distributed fish inhabiting the mesopelagic zone of marine tropical and temperate waters. Constituting one of the largest biomasses of the ocean, C. braueri is a key element in most of the ecological processes occurring in the twilight layer. We focused on the ecological processes linked to early life stages in relation to marine pelagic environmental drivers (temperature, salinity, food availability and geostrophic currents) considering different regions of the Central Mediterranean Sea. A multivariate morphometric analysis was carried out using six parameters with the aim of discerning different larval morphotypes, while a fragment of 367 bp representing the 12S ribosomal RNA gene was used to perform molecular analyses aimed at determining the intraspecific genetic variability. Analysis highlighted two geographically distinct morphotypes not genetically discernible and related to the different nutritional conditions due to spatial heterogeneities in terms of temperature and food availability. The body depth (BD) emerged as an appropriate morphometric parameter to detect the larval condition in this species. Molecular analysis highlighted a moderate genetic divergence in the fish population, showing the recurrence of two phylogroups not geographically separated.Tropical tunas are largely consumed worldwide, providing major nutritional benefits to humans, but also representing the main exposure to methylmercury, a potent neurotoxin that biomagnifies along food webs. The combination of ecological tracers (nitrogen and carbon stable isotopes, δ15N and δ13C) to mercury concentrations in tunas is scarce yet crucial to better characterize the influence of tuna foraging ecology on mercury exposure and bioaccumulation. Given the difficulties to get modern and historical tuna samples, analyses have to be done on available and unique samples. However, δ13C values are often analysed on lipid-free samples to avoid bias related to lipid content. While lipid extraction with non-polar solvents is known to have no effect on δ15N values, its impact on mercury concentrations is still unclear. We used white muscle tissues of three tropical tuna species to evaluate the efficiency and repeatability of different lipid extraction protocols commonly used in δ13C and δ15N analysis. Dichloromethane was more efficient than cyclohexane in extracting lipids in tuna muscle, while the automated method appeared more efficient but as repeatable as the manual method. Lipid extraction with dichloromethane had no effect on mercury concentrations. This may result from i) the affinity of methylmercury to proteins in tuna flesh, ii) the low lipid content in tropical tuna muscle samples, and iii) the non-polar nature of dichloromethane. Our study suggests that lipid-free samples, usually prepared for tropical tuna foraging ecology research, can be used equivalently to bulk samples to document in parallel mercury concentrations at a global scale.
Nasal natural killer/T-cell lymphoma (NNKTL) is an aggressive and poor prognostic malignant tumor along with high-level infection of Epstein-Barr virus (EBV). Gemcitabine (Gem) and Thymosin alpha 1 (Tα1) exert an anti-tumor effect in various cancers. However, the effect of the combination of Gem and Tα1 in NNKTL remains unknown.

SNK6 cells were treated with Gem, Tα1 and Gem plus Tα1 for 48h. The expression levels of EBV and inflammatory factors were measured by qRT-PCR assay. The effect of Gem and Tα1 on cell viability, proliferation, apoptosis, autophagy was detected by CCK-8, colony formation, flow cytometry, autophagic flux measurement, respectively. Western blot was used to evaluate the expression of proteins related to epithelial-mesenchymal transition (EMT), apoptosis and autophagy. In vivo xenograft models were used to further verify the roles of Gem and Tα1. Tumors were removed for weight measurement, H&E and IHC staining.

We identified that the half maximal inhibitory concentration (IC50) of Gem and Tα1 was 116.
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