Accurately identifying hemagglutinin using sequence information and machine learning methods

IntroductionHemagglutinin (HA) is responsible for facilitating viral entry and infection by promoting the fusion between the host membrane and the virus. Given its significance in the process of influenza virus infestation, HA has garnered attention as a target for influenza drug and vaccine development. Thus, accurately identifying HA is crucial for the development of targeted vaccine drugs. However, the identification of HA using in-silico methods is still lacking. This study aims to design a computational model to identify HA.MethodsIn this study, a benchmark dataset comprising 106 HA and 106 non-HA sequences were obtained from UniProt. Various sequence-based features were used to formulate samples. By perform feature optimization and inputting them four kinds of machine learning methods, we constructed an integrated classifier model using the stacking algorithm.Results and discussionThe model achieved an accuracy of 95.85% and with an area under the receiver operating characteristic (ROC) curve of 0.9863 in the 5-fold cross-validation. In the independent test, the model exhibited an accuracy of 93.18% and with an area under the ROC curve of 0.9793. The code can be found from https://github.com/Zouxidan/HA_predict.git. The proposed model has excellent prediction performance. The model will provide convenience for biochemical scholars for the study of HA

Benefits and risks of drug combination therapy for diabetes mellitus and its complications: a comprehensive review

Diabetes is a chronic metabolic disease, and its therapeutic goals focus on the effective management of blood glucose and various complications. Drug combination therapy has emerged as a comprehensive treatment approach for diabetes. An increasing number of studies have shown that, compared with monotherapy, combination therapy can bring significant clinical benefits while controlling blood glucose, weight, and blood pressure, as well as mitigating damage from certain complications and delaying their progression in diabetes, including both type 1 diabetes (T1D), type 2 diabetes (T2D) and related complications. This evidence provides strong support for the recommendation of combination therapy for diabetes and highlights the importance of combined treatment. In this review, we first provided a brief overview of the phenotype and pathogenesis of diabetes and discussed several conventional anti-diabetic medications currently used for the treatment of diabetes. We then reviewed several clinical trials and pre-clinical animal experiments on T1D, T2D, and their common complications to evaluate the efficacy and safety of different classes of drug combinations. In general, combination therapy plays a pivotal role in the management of diabetes. Integrating the effectiveness of multiple drugs enables more comprehensive and effective control of blood glucose without increasing the risk of hypoglycemia or other serious adverse events. However, specific treatment regimens should be tailored to individual patients and implemented under the guidance of healthcare professionals

Transport evidence of asymmetric spin-orbit coupling in few−-layer superconducting 1Td−-MoTe2_2

Two-dimensional (2D) transition metal dichalcogenides (TMDCs) MX2 (M=W, Mo, Nb, and X=Te, Se, S) with strong spin-orbit coupling (SOC) possess plenty of novel physics including superconductivity. Due to the Ising SOC, monolayer NbSe$_2$ and gated MoS$_2$ of 2H structure can realize the Ising superconductivity phase, which manifests itself with in-plane upper critical field far exceeding Pauli paramagnetic limit. Surprisingly, we find that a few-layer 1Td structure MoTe$_2$ also exhibits an in-plane upper critical field ($H_{c2,//}$) which goes beyond the Pauli paramagnetic limit. Importantly, the in-plane upper critical field shows an emergent two-fold symmetry which is different from the isotropic $H_{c2,//}$ in 2H structure TMDCs. We show that this is a result of an asymmetric SOC in 1Td structure TMDCs. The asymmetric SOC is very strong and estimated to be on the order of tens of meV. Our work provides the first transport evidence of a new type of asymmetric SOC in TMDCs which may give rise to novel superconducting and spin transport properties. Moreover, our findings mostly depend on the symmetry of the crystal and apply to a whole class of 1Td TMDCs such as 1Td-WTe$_2$ which is under intense study due to its topological properties.Comment: 34 pages, 12 figure

Gender images in tourism advertising and marketing : an examination of the portrayal of women in Asia.

This pilot study examines destination photographs presented in the tourism marketing collateral of four Asian markets - Japan, Malaysia, Singapore and Thailand - for gender depictions and representations.​Master of Mass Communicatio

The scaling behavior and mechanism of Ti2AlC MAX phase coatings in air and pure water vapor

The scale behavior of Ti2AlC coating at 750 degrees C in air and pure water vapor was investigated. A four-layered scale, a thick TiO2 and Al2O3 mix oxide outer layer, followed by a thin alpha-(Al, Cr)(2)O-3 sublayer, a thick Fe2O3 and TiO2 mix oxide mid-layer and a thin Al2O3-rich oxide inner layer in sequence, developed on the Ti2AlC coatings in air. Whereas internal oxidation occurred, no distinct oxide scale formed on the Ti2AlC coating in the case of the oxidation in pure water vapor. The Ti2AlC coating improved the oxidation resistance of 316LSS in air, especially in wet air. (C) 2015 Elsevier B.V. All rights reserved

Case Report: Active tuberculosis infection in CAR T-cell recipients post CAR T-cell therapy: a retrospective case series

High response rates in B-cell malignancies have been achieved with chimeric antigen receptor (CAR) T-cell therapy. Emerging reports indicate a risk of active tuberculosis (TB) with novel immunotherapy for tumors. However, studies of TB in patients post CAR T-cell therapy are limited. In this case series study, we describe five patients with active TB post CD19/CD22 target CAR T-cell therapy alone or following autologous stem cell transplantation (ASCT). One of the patients developed active TB within the first 30 days post CAR T-cell therapy, and fever was the dominant presenting symptom; extrapulmonary manifestations of active TB were common in the other four patients and manifested after the first 30 days of CAR T-cell therapy. Four of the five patients improved with anti-TB treatment, but one patient with isoniazid resistance died of central nervous system TB infection. Our study provides the first series report of active TB following CD19/CD22 target CAR T-cell therapy

Evaluation of Water Uptake and Root Distribution of Cherry Trees Under Different Irrigation Methods

Although water-saving measures are increasingly being adopted in orchards, little is known about how different irrigation methods enhance water use efficiency at the root system level. To study the allocation of water sources of water absorption by cherry roots under two irrigation methods, surface irrigation and drip irrigation, oxygen isotope tracing and root excavation were used in this study. We found that different irrigation methods have different effects on the average δ18O content of soil water in the soil profile. The IsoSource model was applied to calculate the contribution rate of water absorption by cherry roots under these irrigation methods. During the drought period in spring (also a key period of water consumption for cherry trees), irrigation water was the main source of water absorbed by cherry roots. In summer, cherry roots exhibited a wide range of water absorption sources. In this case, relative to the surface irrigation mode, the drip irrigation mode demonstrated higher irrigation water use efficiency. After two years of the above experiment, root excavation was used to analyze the effects of these irrigation methods on the distribution pattern of roots. We found that root distribution is mainly affected by soil depth. The root system indexes in 10–30 cm soil layer differ significantly from those in other soil layers. Drip irrigation increased the root length density (RLD) and root surface area (RSA) in the shallow soil. There was no significant difference in root biomass density (RBD) and root volume ratio (RVR) between the two irrigation treatments. The effects of these irrigation methods on the 2D distribution of cherry RBD, RLD, RSA and RVR, which indicated that the cherry roots were mainly concentrated in the horizontal depths of 20 to 100 cm, which was related to the irrigation wet zone. In the current experiment, more than 85% of cherry roots were distributed in the space with horizontal radius of 0 to 100 cm and vertical depth of 0 to 80 cm; above 95% of cherry roots were distributed in the space with the horizontal radius of 0 to 150 cm and the vertical depth of 0 to 80 cm. Compared with surface irrigation, drip irrigation makes RLD and RSA more concentrated in the horizontal range of 30–100 cm and vertical range of 0–70 cm

An article’s Altmetric Attention Scores (https://www.altmetric.com/details/6626097) (accessed on May 8, 2016).

<p>An article’s Altmetric Attention Scores (<a href="https://www.altmetric.com/details/6626097" target="_blank">https://www.altmetric.com/details/6626097</a>) (accessed on May 8, 2016).</p

Micro-motion Recognition of Spatial Cone Target Based on ISAR Image Sequences

The accurate micro-motions recognition of spatial cone target is the foundation of the characteristic parameter acquisition. For this reason, a micro-motion recognition method based on the distinguishing characteristics extracted from the Inverse Synthetic Aperture Radar (ISAR) sequences is proposed in this paper. The projection trajectory formula of cone node strong scattering source and cone bottom slip-type strong scattering sources, which are located on the spatial cone target, are deduced under three micro-motion types including nutation, precession, and spinning, and the correctness is verified by the electromagnetic simulation. By comparison, differences are found among the projection of the scattering sources with different micro-motions, the coordinate information of the scattering sources in the Inverse Synthetic Aperture Radar sequences is extracted by the CLEAN algorithm, and the spinning is recognized by setting the threshold value of Doppler. The double observation points Interacting Multiple Model Kalman Filter is used to separate the scattering sources projection of the nutation target or precession target, and the cross point number of each scattering source’s projection track is used to classify the nutation or precession. Finally, the electromagnetic simulation data are used to verify the effectiveness of the micro-motion recognition method

Six journals’ papers with AAS or CIT zero scores.

<p>Six journals’ papers with AAS or CIT zero scores.</p