Altered structural covariance of the cortex and hippocampal formation in patients with lung cancer after chemotherapy.

Objective: In this retrospective study, we aimed to investigate changes in brain morphology and structural topological networks in patients with lung cancer (LC) with or without chemotherapy.

Methods: We retrospectively recruited 191 participants for this cross-sectional study, including 113 patients with LC without chemotherapy (Ch-), 38 patients with LC with chemotherapy (Ch+), and 40 healthy controls (HC) matched for age, sex, and education. The gray matter volume (GMV) and cortical properties were compared among the three groups.

Development and validation of a CT based radiomics nomogram for preoperative prediction of ISUP/WHO grading in renal clear cell carcinoma.

Background: Nuclear grading of clear cell renal cell carcinoma (ccRCC) is crucial for its diagnosis and treatment.

Objective: To develop and validate a machine learning model for preoperative assessment of ccRCC nuclear grading using CT radiomics.

Materials And Methods: This retrospective study analyzed 146 ccRCC patients who underwent surgery between June 2016 and January 2022 at two hospitals (the Quzhou Affiliated Hospital of Wenzhou Medical University with 117 cases and the Affiliated Cancer Hospital of University of Chinese Academy of Sciences with 29 cases).

Spatial Metabolomic Profiling of Pinelliae Rhizoma from Different Leaf Types Using Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging.

Pinelliae Rhizoma (PR), a highly esteemed traditional Chinese medicinal herb, is widely applied in clinical settings due to its diverse pharmacological effects, including antitussive, expectorant, antiemetic, sedative-hypnotic, and antitumor activities. exhibits morphological variation in its leaves, with types resembling peach, bamboo, and willow leaves. However, the chemical composition differences among the corresponding rhizomes of these leaf phenotypes remain unelucidated.

Dense pedestrian face detection in complex environments.

To address the problem of dense crowd face detection in complex environments, this paper proposes a face detection model named Deep and Compact Face Detection (DCFD), which adopts an improved lightweight EfficientNetV2 network to replace the backbone network of RetinaFace. A large kernel attention mechanism is introduced to address the face detection task more accurately. The backbone network, an improved efficient channel attention (ECA) mechanism, is added to further improve the algorithm performance.

Magnesium-Mediated Cross-Electrophile Couplings of Aryl 2-Pyridyl Esters with Aryl Bromides for Ketone Synthesis through In Situ-Formed Arylmagnesium Intermediates.

Aryl 2-pyridyl esters could efficiently undergo cross-electrophile couplings with aryl bromides with the aid of magnesium as a reducing metal in the absence of a transition-metal catalyst, leading to the unsymmetrical diaryl ketones in modest to good yields with wide functionality compatibility. In addition, the reaction could be easily scaled up and applied in the late-stage modification of biologically active molecules. Preliminary mechanistic study showed that the coupling reaction presumably proceeds through the in situ formation of arylmagnesium reagents as key intermediates.

Spatial Mapping of Bioactive Metabolites in the Roots of Three Species by Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging.

is a kind of medicinal plant that has made a great contribution to human health because of the presence of bioactive metabolites: saikosaponins and flavonoids. Despite their importance, it has been a challenge to visually characterize the spatial distribution of these metabolites in situ within the plant tissue, which is essential for assessing the quality of . The development of a new technology to identify and evaluate the quality of medicinal plants is therefore necessary.

NIR-II light therapy improves cognitive performance in MPTP induced Parkinson's disease rat models: A preliminary experimental study.

Cognitive impairment is an important component of non motor symptoms in Parkinson's disease (PD), and if not addressed in a timely manner, it can easily progress to dementia. However, no effective method currently exists to completely prevent or reverse cognitive impairment associated with PD. We therefore aimed to investigate the therapeutic effect of near-infrared region II light (NIR-II) region illumination on cognitive impairment in PD through behavioral experiments (water maze and rotary rod) and multiple fluorescence immunohistochemistry techniques.

Spatial distribution of metabolites in processing Ziziphi Spinosae Semen as revealed by matrix-assisted laser desorption/ionization mass spectrometry imaging.

Ziziphi Spinosae Semen (ZSS) is the first choice for the treatment of insomnia. This research aimed to reveal the spatial distribution of identifying quality markers of ZSS and to illustrate the metabolite quality characteristics of this herbal medicine. Here, we performed a matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) in situ to detect and image 33 metabolites in ZSS, including three saponins, six flavonoids, four alkaloids, eight fatty acids, and 12 amino acids.

Regulation of Bacterial Growth and Behavior by Host Plant.

Plants are associated with diverse bacteria in nature. Some bacteria are pathogens that decrease plant fitness, and others are beneficial bacteria that promote plant growth and stress resistance. Emerging evidence also suggests that plant-associated commensal bacteria collectively contribute to plant health and are essential for plant survival in nature.

Corrigendum: A preliminary exploration of the regression equation for performance in amateur half-marathon runners: a perspective based on respiratory muscle function.

[This corrects the article DOI: 10.3389/fphys.2024.

Combined Endurance and Resistance Exercise Mitigates Age-Associated Cardiac Dysfunction.

Aging is associated with a decline in cardiac function. Exercise has been shown to effectively reduce the risks of cardiovascular diseases. Here whether a combination of endurance and resistance exercises can improve cardiac function in aged mice during late life is investigated.

A comparison of the effects of two protocols of concurrent resistance and aerobic training on physical fitness in middle school students.

Objective: This study aimed to compare the effects of two concurrent training (CT) protocols on the physical fitness of middle school students.

Method: A 12-week quasi-experimental pre-test/post-test study was conducted with 157 middle school students (age = 12.48 ± 0.

A preliminary exploration of the regression equation for performance in amateur half-marathon runners: a perspective based on respiratory muscle function.

This document presents a study on the relationship between physical characteristics, respiratory muscle capacity, and performance in amateur half-marathon runners. The aim of this study was to establish a preliminary predictive model to provide insights into training and health management for runners. Participants were recruited from the 2023 Beijing Olympic Forest Park Half-Marathon, comprising 233 individuals.

Microfluidics-enabled fluorinated assembly of EGCG-ligands-siTOX nanoparticles for synergetic tumor cells and exhausted t cells regulation in cancer immunotherapy.

Immune checkpoint inhibitor (ICI)-derived evolution offers a versatile means of developing novel immunotherapies that targets programmed death-ligand 1 (PD-L1)/programmed death-1 (PD-1) axis. However, one major challenge is T cell exhaustion, which contributes to low response rates in "cold" tumors. Herein, we introduce a fluorinated assembly system of LFNPs/siTOX complexes consisting of fluorinated EGCG (FEGCG), fluorinated aminolauric acid (LA), and fluorinated polyethylene glycol (PEG) to efficiently deliver small interfering RNA anti-TOX (thymus high mobility group box protein, TOX) for synergistic tumor cells and exhausted T cells regulation.

Improved YOLOv7-based steel surface defect detection algorithm.

In response to the limited detection ability and low model generalization ability of the YOLOv7 algorithm for small targets, this paper proposes a detection algorithm based on the improved YOLOv7 algorithm for steel surface defect detection. First, the Transformer-InceptionDWConvolution (TI) module is designed, which combines the Transformer module and InceptionDWConvolution to increase the network's ability to detect small objects. Second, the spatial pyramid pooling fast cross-stage partial channel (SPPFCSPC) structure is introduced to enhance the network training performance.

Comparative Multi-Omics Analysis of Broomcorn Millet in Response to Infection.

is the causal agent of broomcorn millet () smut disease, which results in serious yield losses in broomcorn millet production. However, the molecular basis underlying broomcorn millet defense against is less understood. In this study, we investigated how broomcorn millet responds to infection by by employing a comprehensive multi-omics approach.

Commensal lifestyle regulated by a negative feedback loop between Arabidopsis ROS and the bacterial T2SS.

Despite the plant health-promoting effects of plant microbiota, these assemblages also comprise potentially detrimental microbes. How plant immunity controls its microbiota to promote plant health under these conditions remains largely unknown. We find that commensal bacteria isolated from healthy Arabidopsis plants trigger diverse patterns of reactive oxygen species (ROS) production dependent on the immune receptors and completely on the NADPH oxidase RBOHD that selectively inhibited specific commensals, notably Xanthomonas L148.

How plants manage pathogen infection.

To combat microbial pathogens, plants have evolved specific immune responses that can be divided into three essential steps: microbial recognition by immune receptors, signal transduction within plant cells, and immune execution directly suppressing pathogens. During the past three decades, many plant immune receptors and signaling components and their mode of action have been revealed, markedly advancing our understanding of the first two steps. Activation of immune signaling results in physical and chemical actions that actually stop pathogen infection.

Efficacy and Safety of QiShen YiQi Dripping Pills in the Treatment of Coronary Heart Disease Complicating Chronic Heart Failure (Syndrome of Qi Deficiency with Blood Stasis): Study Protocol for a Randomized, Placebo-Controlled, Double-Blind and Multi-Centre Phase II Clinical Trial.

Background: Heart failure (HF) is a serious and terminal stage of various cardiac diseases and the most common complication of coronary heart disease (CHD). Previous clinical studies have shown that Qishen Yiqi dropping pills (QSYQ) have the effect of treating chronic heart failure. This study aims to evaluate the clinical efficacy, safety and optimal effective dose of QSYQ in treating CHD complicating chronic HF with reduced ejection fraction (HFrEF).

A Multi-Scale Recursive Attention Feature Fusion Network for Image Super-Resolution Reconstruction Algorithm.

In recent years, deep convolutional neural networks (CNNs) have made significant progress in single-image super-resolution (SISR) tasks. Despite their good performance, the single-image super-resolution task remains a challenging one due to problems with underutilization of feature information and loss of feature details. In this paper, a multi-scale recursive attention feature fusion network (MSRAFFN) is proposed for this purpose.

Comparison of different prediction models for estimation of walking and running energy expenditure based on a wristwear three-axis accelerometer.

Objectively and efficiently measuring physical activity is a common issue facing the fields of medicine, public health, education, and sports worldwide. In response to the problem of low accuracy in predicting energy consumption during human motion using accelerometers, a prediction model for asynchronous energy consumption in the human body is established through various algorithms, and the accuracy of the model is evaluated. The optimal energy consumption prediction model is selected to provide theoretical reference for selecting reasonable algorithms to predict energy consumption during human motion.