FDGNet: Frequency Disentanglement and Data Geometry for Domain Generalization in Cross-Scene Hyperspectral Image Classification.

Cross-scene hyperspectral image classification (HSIC) poses a significant challenge in recognizing hyperspectral images (HSIs) from different domains. The current mainstream approaches based on domain adaptation (DA) methods need to access target data when aligning distributions between domains, limiting the applicability of the model. In contrast, recent domain generalization (DG) methods aim to directly generalize to unseen domains, eliminating the requirements for target data during training.

Discussing the safety and effectiveness of transcatheter arterial embolization combined with intravenous chemotherapy in treating locally advanced breast cancer.

To investigate the efficacy and safety of drug-eluting bead-transarterial chemoembolization (DEB-TACE) combined with systemic chemotherapy in HR+/Her2- locally advanced breast cancer (LABC) patients. A controlled study was conducted on LABC patients treated at Jianyang People's Hospital and the First Affiliated Hospital of Chengdu Medical College from December 2020 to June 2022. The patients were randomly divided into the experimental group and the control group.

Prediction of lncRNA and disease associations based on residual graph convolutional networks with attention mechanism.

LncRNAs are non-coding RNAs with a length of more than 200 nucleotides. More and more evidence shows that lncRNAs are inextricably linked with diseases. To make up for the shortcomings of traditional methods, researchers began to collect relevant biological data in the database and used bioinformatics prediction tools to predict the associations between lncRNAs and diseases, which greatly improved the efficiency of the study.

Hyperspectral Image Classification With Multi-Attention Transformer and Adaptive Superpixel Segmentation-Based Active Learning.

Deep learning (DL) based methods represented by convolutional neural networks (CNNs) are widely used in hyperspectral image classification (HSIC). Some of these methods have strong ability to extract local information, but the extraction of long-range features is slightly inefficient, while others are just the opposite. For example, limited by the receptive fields, CNN is difficult to capture the contextual spectral-spatial features from a long-range spectral-spatial relationship.

Rapid titration with oral sustained-release morphine plus subcutaneous morphine in a multi-center, randomized control study of cancer patients with moderate to severe cancer pain.

Background: Pain is one of the most common concomitant symptoms among cancer patients. Pharmacologic agents are regarded as a cornerstone of cancer pain management. 'Dose titration' with short-acting morphine is widely accepted.

Superpixel Guided Deformable Convolution Network for Hyperspectral Image Classification.

Convolutional neural networks are widely used in the field of hyperspectral image classification because of their excellent nonlinear feature extraction ability. However, as the sampling position of the regular convolution kernel is unchangeable, the regular convolution cannot distinctively extract the spatial and spectral information around the central pixel, which makes the classification results at the boundaries of ground objects over-smoothed and the classification performance degraded. Thus, we propose a novel superpixel guided deformable convolution network (SGDCN) for hyperspectral image classification.

Robotic laser position versus freehand in CT-guided percutaneous microwave ablation for single hepatocellular carcinoma (diameter < 3 cm): a preliminary study.

Purpose: To compare the accuracy and safety of robotic laser position (RLP) versus freehand for antenna CT-guided microwave ablation (MWA) of single hepatocellular carcinoma (HCC) (diameter < 3 cm).

Materials And Methods: This retrospective study was conducted between May 2020 and June 2021. A total of 40 patients with early HCC who underwent CT-guided MWA were divided into two groups: a freehand group ( = 20) and a RLP group ( = 20).

Hierarchical multi-label classification based on LSTM network and Bayesian decision theory for LncRNA function prediction.

Growing evidence shows that long noncoding RNAs (lncRNAs) play an important role in cellular biological processes at multiple levels, such as gene imprinting, immune response, and genetic regulation, and are closely related to diseases because of their complex and precise control. However, most functions of lncRNAs remain undiscovered. Current computational methods for exploring lncRNA functions can avoid high-throughput experiments, but they usually focus on the construction of similarity networks and ignore the certain directed acyclic graph (DAG) formed by gene ontology annotations.

E3 ubiquitin ligase PJA1 regulates lung adenocarcinoma apoptosis and invasion through promoting FOXR2 degradation.

Among all lung cancer cases, lung adenocarcinoma (LAC) represents nearly 40% and remains the leading cause of cancer deaths worldwide. Although the combination therapy of surgical treatment with radiotherapy, chemotherapy, and immunotherapy, has been used to treat LAC, unfortunately, high recurrence rates and poor survival remain. Therefore, novel prognostic markers and new targets for molecular targeted therapy in LAC is urgently needed.

Incidence of chemotherapy-induced nausea and vomiting among cancer patients receiving moderately to highly emetogenic chemotherapy in cancer centers in Sichuan, China.

Purpose: Nausea and vomiting are the most painful and feared side effects for patients during chemotherapy. Currently, most studies focus on the occurrence of CINV during the risk phase. We initiated this real-world study to understand the actual occurrence of CINV throughout all phases, to provide a basis to prevent CINV in patients during chemotherapy and improve their quality of life.

Characterization and phylogenetic analysis of the complete mitochondrial genome of (Diptera: Syrphidae).

The complete mitochondrial genome of was sequenced and reported here. The circle genome of the syrphid fly is 15,348 bp in length. There are 38 sequence elements including 13 protein coding genes, 22 tRNA genes, 2 rRNA genes, and a control region.

Complete mitochondrial genome of (Lepidoptera: Sesiidae).

is an important trunk borer of poplar and is widely distributed in China. Here, the complete mitochondrial genome of was sequenced. The circle genome of the clearwing moth is 15,454 bp in length.

RNF115-mediated ubiquitination of p53 regulates lung adenocarcinoma proliferation.

Lung adenocarcinoma (LAC) represents approximately 40% of all lung cancer cases and is the leading cause of cancer-associated mortality worldwide. Although combined treatment, including radiotherapy, chemotherapy, surgical treatment and immunotherapy, has been used in treating LAC, the five-year survival rate of patients with LAC has not significantly improved. Therefore, it is vital for cancer research to investigate novel prognostic markers and new targets for molecular targeted therapy in LAC.

A cluster-based hybrid sampling approach for imbalanced data classification.

When processing instrumental data by using classification approaches, the imbalanced dataset problem is usually challenging. As the minority class instances could be overwhelmed by the majority class instances, training a typical classifier with such a dataset directly might get poor results in classifying the minority class. We propose a cluster-based hybrid sampling approach CUSS (Cluster-based Under-sampling and SMOTE) for imbalanced dataset classification, which belongs to the type of data-level methods and is different from previously proposed hybrid methods.

A deep neural network based hierarchical multi-label classification method.

With the accumulation of data generated by biological experimental instruments, using hierarchical multi-label classification (HMC) methods to process these data for gene function prediction has become very important. As the structure of the widely used Gene Ontology (GO) annotation is the directed acyclic graph (DAG), GO based gene function prediction can be changed to the HMC problem for the DAG of GO. Due to HMC, algorithms for tree ontology are not applicable to DAG, and the accuracy of these algorithms is low.

Cross-Linking between Sodalite Nanoparticles and Graphene Oxide in Composite Membranes to Trigger High Gas Permeance, Selectivity, and Stability in Hydrogen Separation.

Thin membranes (900 nm) were prepared by direct transformation of infiltrated amorphous precursor nanoparticles, impregnated in a graphene oxide (GO) matrix, into hydroxy sodalite (SOD) nanocrystals. The amorphous precursor particles rich in silanols (Si-OH) enhanced the interactions with the GO, thus leading to the formation of highly adhesive and stable SOD/GO membranes via strong bonding. The cross-linking of SOD nanoparticles with the GO in the membranes promoted both the high gas permeance and enhanced selectivity towards H from a mixture containing CO and H O.

LINC00958 Accelerates Cell Proliferation and Migration in Non-Small Cell Lung Cancer Through JNK/c-JUN Signaling.

Non-small cell lung cancer (NSCLC) denotes the most common type of lung cancers with high mortality globally. Long non-coding RNAs (lncRNAs) with differential expression have been indicated to be participants in the pathogenesis and development of cancer. However, the precise role of lncRNAs in NSCLC is still largely obscure.

Fabrication of a Hydrogen-Bonded Organic Framework Membrane through Solution Processing for Pressure-Regulated Gas Separation.

Ordered and flexible porous frameworks with solution processability are highly desirable to fabricate continuous and large-scale membranes for the efficient gas separation. Herein, the first microporous hydrogen-bonded organic framework (HOF) membrane has been fabricated by an optimized solution-processing technique. The framework exhibits the superior stability because of the abundant hydrogen bonds and strong π-π interactions.

Impact of Dwell Time of Retrievable IVC Filters on IVC Lumen Diameter: A Series of 36 Cases.

Background: Inferior vena cava (IVC) filters are effective in preventing pulmonary embolism in patients at risk. This study aimed to investigate whether the dwell time of retrievable IVC filters have impact on IVC lumen diameter.

Methods: The clinical data of 36 patients treated with retrievable IVC filters from January 2016 to November 2018 were retrospectively collected.

Green Hydrogen Separation from Nitrogen by Mixed-Matrix Membranes Consisting of Nanosized Sodalite Crystals.

Nanosized sodalite (Nano-SOD) crystals were used as active filler to prepare mixed-matrix membranes (MMMs) for promoting the H /N gas-separation performance. The Nano-SOD crystals with extremely small crystallites (40-50 nm) were synthesized from a colloidal suspension free of organic structural directing agent and uniformly dispersed in the polyetherimide (PEI) matrix. The Nano-SOD filler with a suitable aperture size (2.

Retraction Note: The impact of repeated vaccination on influenza vaccine effectiveness: a systematic review and meta-analysis.

The authors have retracted this article, The impact of repeated vaccination on influenza vaccine effectiveness: a systematic review and meta-analysis.

A postprocessing method in the HMC framework for predicting gene function based on biological instrumental data.

Predicting gene function based on biological instrumental data is a complicated and challenging hierarchical multi-label classification (HMC) problem. When using local approach methods to solve this problem, a preliminary results processing method is usually needed. This paper proposed a novel preliminary results processing method called the nodes interaction method.

Mesenchymal stem cell therapy for paraquat poisoning: A systematic review and meta-analysis of preclinical studies.

Background: Paraquat (PQ) poisoning can cause multiple organ failure, in which the lung is the primary target organ. There is currently no treatment for PQ poisoning. Mesenchymal stem cells (MSCs), which differentiate into multiple cell types, have generated much enthusiasm regarding their use for the treatment of several diseases.

An expanded evaluation of protein function prediction methods shows an improvement in accuracy.

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging.