Mindfulness meditation training reduces gaming cravings by reshaping the functional connectivity between default mode network and executive control-related brain regions.

BACKGROUND: Internet gaming disorder (IGD) can lead to psychological problems and cause behavioral problems in individuals. Traditional interventions have been ineffective in treating IGDs. Meanwhile, mindfulness meditation (MM) is an emerging method that has proven to be effective for treating psychiatry disorders. In this study, MM was used to intervene in IGD and to explore its neural mechanism. METHODS: Eighty participants were recruited through advertisements. Eventually, 61 completed the one-month training (MM/progressive muscle relaxation: 31/30), including a pre-test, eight training sessions, and a post-test. Regional homogeneity and degree centrality were calculated and the tests (pre- and post-) and group (MM and PMR) ANOVA was performed. The overlapping results were obtained as ROI for functional connectivity (FC) analyses. Behavioral data and neurotransmitters correlated with FC. RESULTS: Compared to PMR, MM decreased the severity of addiction and game craving in IGD. Brain imaging results showed that the FC between and within the executive control and default mode networks (DMN)/reward-related regions were enhanced. Significant negative correlations were observed between the FC and dopamine receptors D2, dopamine transporter (DAT), and acetylcholine receptors VAChT. Significant positive correlations were observed between FCs and serotonin and aminobutyric acid receptors. CONCLUSIONS: This study confirmed the effectiveness of MM in treating IGD. MM altered the default mode and enhanced the top-down control over game cravings. These findings were revealed by the correlations between brain regions and behavioral and bio-chemical effects. The results showed the neural mechanism of MM in reducing IGD and lay the foundation for future research.

Terahertz fingerprint reveals the effect of alcohols on sodium ions hydration shell.

Ion hydration plays a crucial role in numerous fundamental processes. Various spectroscopic methods are employed to investigate the slowing down of hydration bond dynamics in the proximity of both anions and cations. To date, most of these studies have primarily focused on the properties of binary systems. However, in comparison to ion-water binary systems, ternary systems that involve ions, water, and organic matter are more prevalent in nature and provide more realistic insights into biological processes. This study focuses on ion hydration in water and alcohol mixture using terahertz spectroscopy and x-ray diffraction (XRD). The results reveal a distinct behavior depending on the type of alcohol used. Specifically, the presence of both methanol and ethanol results in the disappearance of absorption peaks associated with NaCl hydrate at low temperatures. In contrast, tert-butanol does not exhibit such an effect, and isopropanol demonstrates a more complex response. By combining these terahertz spectroscopic findings with low-temperature XRD data, we gain insights into the formation, or lack thereof, of NaCl · 2H2O hydrate crystals. Crucially, our observations suggest a dominant correlation between the polarity of the alcohol molecules and its impact on the Na+ hydration. Strongly polar alcohols preferentially solvating the Na+ ion lead to the failure of hydrate formation, while weakly polar alcohols do not have this effect.

Melatonin attenuates renal ischemia-reperfusion injury by regulating mitochondrial dynamics and autophagy through AMPK/DRP1.

ABSTRACT: Ischemia-reperfusion injury (IRI) often stems from an imbalance between mitochondrial dynamics and autophagy. Melatonin mitigates IRI by regulating mitochondrial dynamics. However, the precise molecular mechanism underlying the role of melatonin in reducing IRI through modulating mitochondrial dynamics remains elusive. The objective of this study was to investigate whether pre-treatment with melatonin before IRI confers protective effects by modulating mitochondrial dynamics and mitophagy. Melatonin pre-treatment was administered to HK-2 cells and live rats before subjecting them to hypoxia-reoxygenation (HR) or IRI, respectively. Cells and rat kindey models were evaluated for markers of oxidative stress, autophagy, mitochondrial dynamics, and the expression of adenosine 5'-monophosphate (AMP)-activated protein kinase (AMPK) and phospho-AMPKα (P-AMPK). Following renal IRI, increased mitochondrial fission and autophagy were observed, accompanied by exacerbated cellular oxidative stress injury and aggravated mitochondrial dysfunction. Nevertheless, melatonin pre-treatment inhibited mitochondrial fission, promoted mitochondrial fusion, and attenuated autophagy levels. This intervention was correlated with a notable reduction in oxidative stress injury and remarkable restoration of mitochondrial functionality. IRI led to a decline in P-AMPK levels, whereas melatonin pre-treatment increased the level of P-AMPK levels. Silencing AMPK with small interfering RNA exacerbated mitochondrial damage, and in this context, melatonin pre-treatment did not alleviate mitochondrial fission or autophagy levels but resulted in sustained oxidative stress damage. Collectively, these findings indicate that melatonin pre-treatment shields the kidneys from IRI by mitigating excessive mitochondrial fission, moderating autophagy levels, and preserving appropriate mitochondrial fission, all in an AMPK-dependent manner.

Nanoscale detection of carbon dots-induced changes in actin skeleton of neural cells.

Understanding the cytotoxicity of fluorescent carbon dots (CDs) is crucial for their applications, and various biochemical assays have been used to study the effects of CDs on cells. Knowledge on the effects of CDs from a biophysical perspective is integral to the recognition of their cytotoxicity, however the related information is very limited. Here, we report that atomic force microscopy (AFM) can be used as an effective tool for studying the effects of CDs on cells from the biophysical perspective. We achieve this by integrating AFM-based nanomechanics with AFM-based imaging. We demonstrate the performance of this method by measuring the influence of CDs on living human neuroblastoma (SH-SY5Y) cells at the single-cell level. We find that high-dose CDs can mechanically induce elevated normalized hysteresis (energy dissipation during the cell deformation) and structurally impair actin skeleton. The nanomechanical change highly correlates with the alteration of actin filaments, indicating that CDs-induced changes in SH-SY5Y cells are revealed in-depth from the AFM-based biophysical aspect. We validate the reliability of the biophysical observations using conventional biological methods including cell viability test, fluorescent microscopy, and western blot assay. Our work contributes new and significant information on the cytotoxicity of CDs from the biophysical perspective.

DSG-GAN:A dual-stage-generator-based GAN for cross-modality synthesis from PET to CT.

PET/CT devices typically use CT images for PET attenuation correction, leading to additional radiation exposure. Alternatively, in a standalone PET imaging system, attenuation and scatter correction cannot be performed due to the absence of CT images. Therefore, it is necessary to explore methods for generating pseudo-CT images from PET images. However, traditional PET-to-CT synthesis models encounter conflicts in multi-objective optimization, leading to disparities between synthetic and real images in overall structure and texture. To address this issue, we propose a staged image generation model. Firstly, we construct a dual-stage generator, which synthesizes the overall structure and texture details of images by decomposing optimization objectives and employing multiple loss functions constraints. Additionally, in each generator, we employ improved deep perceptual skip connections, which utilize cross-layer information interaction and deep perceptual selection to effectively and selectively leverage multi-level deep information and avoid interference from redundant information. Finally, we construct a context-aware local discriminator, which integrates context information and extracts local features to generate fine local details of images and reasonably maintain the overall coherence of the images. Experimental results demonstrate that our approach outperforms other methods, with SSIM, PSNR, and FID metrics reaching 0.8993, 29.6108, and 29.7489, respectively, achieving the state-of-the-art. Furthermore, we conduct visual experiments on the synthesized pseudo-CT images in terms of image structure and texture. The results indicate that the pseudo-CT images synthesized in this study are more similar to real CT images, providing accurate structure information for clinical disease analysis and lesion localization.

Proteomic analysis of mitochondria associated membranes in renal ischemic reperfusion injury.

BACKGROUND: The mitochondria and endoplasmic reticulum (ER) communicate via contact sites known as mitochondria associated membranes (MAMs). Many important cellular functions such as bioenergetics, mitophagy, apoptosis, and calcium signaling are regulated by MAMs, which are thought to be closely related to ischemic reperfusion injury (IRI). However, there exists a gap in systematic proteomic research addressing the relationship between these cellular processes. METHODS: A 4D label free mass spectrometry-based proteomic analysis of mitochondria associated membranes (MAMs) from the human renal proximal tubular epithelial cell line (HK-2 cells) was conducted under both normal (N) and hypoxia/reperfusion (HR) conditions. Subsequent differential proteins analysis aimed to characterize disease-relevant signaling molecules. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was applied to total proteins and differentially expressed proteins, encompassing Biological Process (BP), Cell Component (CC), Molecular Function (MF), and KEGG pathways. Further, Protein-Protein Interaction Network (PPI) exploration was carried out, leading to the identification of hub genes from differentially expressed proteins. Notably, Mitofusion 2 (MFN2) and BCL2/Adenovirus E1B 19-kDa interacting protein 3(BNIP3) were identified and subsequently validated both in vitro and in vivo. Finally, the impact of MFN2 on MAMs during hypoxia/reoxygenation was explored through regulation of gene expression. Subsequently, a comparative proteomics analysis was conducted between OE-MFN2 and normal HK-2 cells, providing further insights into the underlying mechanisms. RESULTS: A total of 4489 proteins were identified, with 3531 successfully quantified. GO/KEGG analysis revealed that MAM proteins were primarily associated with mitochondrial function and energy metabolism. Differential analysis between the two groups showed that 688 proteins in HR HK-2 cells exhibited significant changes in expression level with P-value < 0.05 and HR/N > 1.5 or HR/N < 0.66 set as the threshold criteria. Enrichment analysis of differentially expressed proteins unveiled biological processes such as mRNA splicing, apoptosis regulation, and cell division, while molecular functions were predominantly associated with energy metabolic activity. These proteins play key roles in the cellular responses during HR, offering insights into the IRI mechanisms and potential therapeutic targets. The validation of hub genes MFN2 and BNIP3 both in vitro and vivo was consistent with the proteomic findings. MFN2 demonstrated a protective role in maintaining the integrity of mitochondria associated membranes (MAMs) and mitigating mitochondrial damage following hypoxia/reoxygenation injury, this protective effect may be associated with the activation of the PI3K/AKT pathway. CONCLUSIONS: The proteins located in mitochondria associated membranes (MAMs) are implicated in crucial roles during renal ischemic reperfusion injury (IRI), with MFN2 playing a pivotal regulatory role in this context.

Chromium immobilization from wastewater via iron-modified hydrochar: Different iron fabricants and practicality assessment.

The recycling of industrial solid by-products such as red mud (RM) has become an urgent priority, due to their large quantities and lack of reutilization methods can lead to resource wastage. In this work, RM was employed to fabricate green hydrochar (HC) to prepare zero-valent iron (ZVI) modified carbonous materials, and conventional iron salts (IS, FeCl3) was applied as comparison, fabricated HC labeled as RM/HC and IS/HC, respectively. The physicochemical properties of these HC were comprehensively characterized. Further, hexavalent chromium (Cr(VI)) removal performance was assessed (375.66 and 337.19 mg/g for RM/HC and IS/HC, respectively). The influence of dosage and initial pH were evaluated, while isotherms, kinetics, and thermodynamics analysis were also conducted, to mimic the surface interactions. The stability and recyclability of adsorbents also verified, while the practical feasibility was assessed by bok choy-planting experiment. This work revealed that RM can be used as a high value and green fabricant for HC the effective removal of chromium contaminants from the wastewater.

Near-Field Terahertz Morphological Reconstruction Nanoscopy for Subsurface Imaging of Protein Layers.

Protein layers formed on solid surfaces have important applications in various fields. High-resolution characterization of the morphological structures of protein forms in the process of developing protein layers has significant implications for the control of the layer's quality as well as for the evaluation of the layer's performance. However, it remains challenging to precisely characterize all possible morphological structures of protein in various forms, including individuals, networks, and layers involved in the formation of protein layers with currently available methods. Here, we report a terahertz (THz) morphological reconstruction nanoscopy (THz-MRN), which can reveal the nanoscale three-dimensional structural information on a protein sample from its THz near-field image by exploiting an extended finite dipole model for a thin sample. THz-MRN allows for both surface imaging and subsurface imaging with a vertical resolution of ∼0.5 nm, enabling the characterization of various forms of proteins at the single-molecule level. We demonstrate the imaging and morphological reconstruction of single immunoglobulin G (IgG) molecules, their networks, a monolayer, and a heterogeneous double layer comprising an IgG monolayer and a horseradish peroxidase-conjugated anti-IgG layer. The established THz-MRN presents a useful approach for the label-free and nondestructive study of the formation of protein layers.

Recent Advances of Aminopeptidases-Responsive Small-Molecular Probes for Bioimaging.

Aminopeptidases, enzymes with critical roles in human body, are emerging as vital biomarkers for metabolic processes and diseases. Aberrant aminopeptidase levels are often associated with diseases, particularly cancer. Small-molecule probes, such as fluorescent, fluorescent/photoacoustics, bioluminescent, and chemiluminescent probes, are essential tools in the study of aminopeptidases-related diseases. The fluorescent probes provide real-time insights into protein activities, offering high sensitivity in specific locations, and precise spatiotemporal results. Additionally, photoacoustic probes offer signals that are able to penetrate deeper tissues. Bioluminescent and chemiluminescent probes can enhance in vivo imaging abilities by reducing the background. This comprehensive review is focused on small-molecule probes that respond to four key aminopeptidases: aminopeptidase N, leucine aminopeptidase, Pyroglutamate aminopeptidase 1, and Prolyl Aminopeptidase, and their utilization in imaging tumors and afflicted regions. In this review, the design strategy of small-molecule probes, the variety of designs from previous studies, and the opportunities of future bioimaging applications are discussed, serving as a roadmap for future research, sparking innovations in aminopeptidase-responsive probe development, and enhancing our understanding of these enzymes in disease diagnostics and treatment.

Immunologic Crosstalk of Endoplasmic Reticulum Stress Signaling in Bladder Cancer.

Bladder cancer (BC) is a common malignant tumor of the urinary system. While current approaches involving adjuvant chemotherapy, radiotherapy, and immunotherapy have shown significant progress in BC treatment, challenges, such as recurrence and drug resistance, persist, especially in the case of muscle-invasive bladder cancer (MIBC). This is mainly due to the lack of pre-existing immune response cells in the tumor immune microenvironment. Micro-environmental changes (such as hypoxia and under-nutrition) can cause the aggregation of unfolded and misfolded proteins in the lumen, which induces endoplasmic reticulum (ER) stress. ER stress and its downstream signaling pathways are closely related to immunogenicity and tumor drug resistance. ER stress plays a pivotal role in a spectrum of processes within immune cells and the progression of BC cells, encompassing cell proliferation, autophagy, apoptosis, and resistance to therapies. Recent studies have increasingly recognized the potential of natural compounds to exhibit anti-BC properties through ER stress induction. Still, the efficacy of these natural compounds remains less than that of immune checkpoint inhibitors (ICIs). Currently, the ER stress-mediated immunogenic cell death (ICD) pathway is more encouraging, which can enhance ICI responses by mediating immune stemness. This article provides an overview of the recent developments in understanding how ER stress influences tumor immunity and its implications for BC. Targeting this pathway may soon emerge as a compelling therapeutic strategy for BC.

Alzheimer's disease prediction algorithm based on de-correlation constraint and multi-modal feature interaction.

Alzheimer's disease (AD) is a neurodegenerative disease characterized by various pathological changes. Utilizing multimodal data from Fluorodeoxyglucose positron emission tomography(FDG-PET) and Magnetic Resonance Imaging(MRI) of the brain can offer comprehensive information about the lesions from different perspectives and improve the accuracy of prediction. However, there are significant differences in the feature space of multimodal data. Commonly, the simple concatenation of multimodal features can cause the model to struggle in distinguishing and utilizing the complementary information between different modalities, thus affecting the accuracy of predictions. Therefore, we propose an AD prediction model based on de-correlation constraint and multi-modal feature interaction. This model consists of the following three parts: (1) The feature extractor employs residual connections and attention mechanisms to capture distinctive lesion features from FDG-PET and MRI data within their respective modalities. (2) The de-correlation constraint function enhances the model's capacity to extract complementary information from different modalities by reducing the feature similarity between them. (3) The mutual attention feature fusion module interacts with the features within and between modalities to enhance the modal-specific features and adaptively adjust the weights of these features based on information from other modalities. The experimental results on ADNI database demonstrate that the proposed model achieves a prediction accuracy of 86.79% for AD, MCI and NC, which is higher than the existing multi-modal AD prediction models.

Drought priming at seedling stage improves photosynthetic performance and yield of potato exposed to a short-term drought stress.

Potato (Solanum tuberosum L.) is an important food and vegetable crop worldwide. In recent years, the arid environment resulting from climate change has caused a sharp decline in potato yield. To clarify the effect of drought priming at the seedling stage on the tolerance of potato plants to drought stress during tuber expansion, we conducted a pot experiment to investigate the physiological response of the plants generated from seed potatoes of the variety 'Favorita' to varied water supply conditions: normal water supply at the seedling stage (control), normal water supply at the seedling stage and drought stress at the mid-tuber-expansion stage (non-primed), and drought priming at the seedling stage plus drought stress at the mid-tuber-expansion stage (primed). Drought priming resulted in an increase in the number of small vascular bundles in potato plants compared to non-primed plants. It also altered the shape and density of stomata, enhancing water use efficiency and reducing whole-plant transpiration. The primed plants maintained the basal stem cambium for a longer time under drought stress, which gained an extended differentiation ability to generate a greater number of small vascular bundles compared to non-primed plants. Drought priming increased the amount and rate of dry matter translocation, and so reduced the adverse effects on tubers of potato under drought stress. Therefore, drought priming at the seedling stage improved the photosynthetic performance and yield, and probably enhanced the drought tolerance of potato.

Three-stage pattern of rapid increase, plateau, and subsequent decline in vitamin D concentration during pregnancy among Chinese women: a large-scale survey.

Background: There is an incomplete understanding of fluctuations in vitamin D (VitD) concentration during pregnancy among Chinese women. Furthermore, previous research has yielded conflicting results in this area. This study aims to investigate the changes in VitD status and deficiency in Chinese pregnant women across various age groups, gestational weeks, and as well as seasonal variations through conducting a large-scale survey. Methods: A toal of 11,220 Chinese pregnant women between 2021 and April 2023 were included in this study. Generalized additive models (GAM), stratified analysis, and restricted cubic splines (RCS) were used to analyze changes in VitD status and deficiency risk during pregnancy. Results: Of the participants, 45.2% had deficient concentration of 25-hydroxyvitamin D. VitD concentration and deficiency rate do not show linear changes with age and gestational weeks. With increasing gestational weeks, VitD concentration rapidly increased in women with gestational age < 20 weeks, remained stable between 20 and 30 weeks, and decreased beyond 30 weeks; however, the odds of VitD deficiency showed three different patterns: a rapid decline, a stable period, and a mild increase, respectively. Based on the stratified regression analysis, VitD deficiency odds increased by 16% with each additional week of gestation in pregnant women with gestational age > 30 weeks, OR = 1.16 (1.10-1.22), p < 0.001. Interaction effect analysis indicated that pregnant women over 35 years with gestational weeks between 20 and 30 had the lowest odds of VitD deficiency. Conclusion: VitD concentration undergo three phases during pregnancy: rapid increase, plateau, and subsequent decrease. VitD deficiency odds was highest in pregnant women under 25 with gestational ages <20 and lowest in pregnant women over 35 with gestational ages between 20 and 30. The odds of deficiency increase slightly in pregnant women with gestational ages beyond 30 weeks, indicating that they may require additional VitD supplementation.

Identification of the role of MCM6 in bladder cancer prognosis, immunotherapy response, and in vitro experimental investigation using multi-omics analysis.

BACKGROUND: The tumor-promoting effects of MCM6 in numerous tumors have been widely revealed, yet its specific role in bladder cancer (BLCA) is still elusive. The objective of this research was to explore the underlying impact of MCM6 on BLCA. METHODS: Integrating transcriptomic and proteomic data, MCM6 was identified to be strongly correlated with BLCA through weighted gene co-expression network analysis(WGCNA) and venn analyses. Then, the clinical value of MCM6 was validated with public database data. The different molecular/immune characteristics and the benefit of immunotherapy were also found in MCM6-defined subgroups. Additionally, single-cell RNA sequencing (scRNA-seq) data was choose for quantify MCM6 expression in the distinct BLCA cell types. The biological role of MCM6 were evaluated via in vitro functional experiments. RESULTS: It was testified that the MCM6 could distinguish patients outcome in TCGA and GEO cohorts. Moreover, compared with the MCM6 low-expression group, the MCM6 high-expression group was related to more tumor-promoting related pathways, aggressive phenotypes, and benefit from immunotherapy. Analysis of scRNA-seq data resulted in MCM6 was mainly expressed in BLCA epithelial cells and the proportion of MCM6-expressing tumor epithelial cells is higher than the normal epithelial cells. Moreover, vitro experiments demonstrated that MCM6 knockdown repressed proliferation, cell cycle, migration, and invasion of BLCA cells. CONCLUSION: This research indicated MCM6 is a promising marker for both prognosis and immunotherapy benefit and could promote the cells proliferation, invasion and migration in BLCA.

Multi-feature fusion learning for Alzheimer's disease prediction using EEG signals in resting state.

Introduction: Diagnosing Alzheimer's disease (AD) lesions via visual examination of Electroencephalography (EEG) signals poses a considerable challenge. This has prompted the exploration of deep learning techniques, such as Convolutional Neural Networks (CNNs) and Visual Transformers (ViTs), for AD prediction. However, the classification performance of CNN-based methods has often been deemed inadequate. This is primarily attributed to CNNs struggling with extracting meaningful lesion signals from the complex and noisy EEG data. Methods: In contrast, ViTs have demonstrated proficiency in capturing global signal patterns. In light of these observations, we propose a novel approach to enhance AD risk assessment. Our proposition involves a hybrid architecture, merging the strengths of CNNs and ViTs to compensate for their respective feature extraction limitations. Our proposed Dual-Branch Feature Fusion Network (DBN) leverages both CNN and ViT components to acquire texture features and global semantic information from EEG signals. These elements are pivotal in capturing dynamic electrical signal changes in the cerebral cortex. Additionally, we introduce Spatial Attention (SA) and Channel Attention (CA) blocks within the network architecture. These attention mechanisms bolster the model's capacity to discern abnormal EEG signal patterns from the amalgamated features. To make well-informed predictions, we employ a two-factor decision-making mechanism. Specifically, we conduct correlation analysis on predicted EEG signals from the same subject to establish consistency. Results: This is then combined with results from the Clinical Neuropsychological Scale (MMSE) assessment to comprehensively evaluate the subject's susceptibility to AD. Our experimental validation on the publicly available OpenNeuro database underscores the efficacy of our approach. Notably, our proposed method attains an impressive 80.23% classification accuracy in distinguishing between AD, Frontotemporal dementia (FTD), and Normal Control (NC) subjects. Discussion: This outcome outperforms prevailing state-of-the-art methodologies in EEG-based AD prediction. Furthermore, our methodology enables the visualization of salient regions within pathological images, providing invaluable insights for interpreting and analyzing AD predictions.

Molecular subtypes based on N6-methyladenosine RNA methylation demonstrate the heterogeneity of immune and biological functions in pediatric septic shock.

Introduction: Septic shock in children is a highly heterogeneous syndrome involving different immune states and biological processes. We used a bioinformatics approach to explore the relationship between N6-methyladenosine (m6A) methylation and septic shock in children. Methods: A gene expression dataset including information on 98 children with septic shock was selected. To construct and evaluate a risk prediction model, machine learning was used to screen marker m6A regulators. Based on differentially expressed m6A regulators, molecular subtypes for paediatric septic shock were constructed. Subsequently, the differences in the m6Ascore, heterogeneity of immune cell infiltration, and heterogeneity of biological functions between the different subtypes were analyzed. Finally, real-time quantitative PCR (RT-qPCR) was performed to validate the expression of the marker m6A regulators. Results: Fifteen differentially expressed m6A regulators were identified. Six marker m6A regulators, including LRPPRC, ELAVL1, RBM15, CBLL1, FTO, and RBM15B, were screened using the random forest method. The risk prediction model for paediatric septic shock constructed using m6A markers had strong consistency and high clinical practicability. Two subtypes of paediatric septic shock have been identified based on the differential expression pattern of m6A regulators. Significant differences were observed in RNA epigenetics, immune statuses, and biological processes between the two m6A subtypes. Differentially expressed genes between the two subtypes were enriched in cell number homeostasis, redox responses, and innate immune system responses. Finally, the six marker m6A regulators were verified in additional samples. Conclusions: Based on the heterogeneity of m6A methylation-regulated genes, two different subtypes of septic shock in children with different RNA epigenetics, immune statuses, and biological processes were identified, revealing the heterogeneity of the disease largely attributable to differential m6A methylation. The findings will help explore and establish appropriate individualized treatments.

Exploring potential targets of HPV&BC based on network pharmacology and urine proteomics.

BACKGROUND: Bladder cancer (BC) caused by Human papillomavirus (HPV) infection remains a complex public health problem in developing countries. Although the HPV vaccine effectively prevents HPV infection, it does not benefit patients with BC who already have HPV. METHODS: Firstly, the differential genes of HPV-related BC patients were screened by transcriptomics, and then the prognostic and clinical characteristics of the differential genes were analyzed to screen out the valuable protein signatures. Furthermore, the compound components and targets of Astragali Radix (AR) were analyzed by network pharmacology, and the intersection targets of drug components and HPV_BC were screened out for pathway analysis. In addition, the binding ability of the compound to the Astragali-HPV_BC target was verified by molecular docking and virtual simulation. Finally, to identify potential targets in BC patients through urine proteomics and in vitro experiments. RESULTS: Eleven HPV_BC-related protein signatures were screened out, among which high expression of EGFR, CTNNB1, MYC, GSTM1, MMP9, CXCR4, NOTCH1, JUN, CXCL12, and KRT14 had a poor prognosis, while low expression of CASP3 had a poor prognosis. In the analysis of clinical characteristics, it was found that high-risk scores, EGFR, MMP9, CXCR4, JUN, and CXCL12 tended to have higher T stage, pathological stage, and grade. Pharmacological and molecular docking analysis identified a natural component of AR (Quercetin) and it corresponding core targets (EGFR). The OB of the natural component was 46.43, and the DL was 0.28, respectively. In addition, EGFR-Quercetin has high affinity. Urine proteomics and RT-PCR showed that EGFR was expressed explicitly in BC patients. Mechanism analysis revealed that AR component targets might affect HPV_BC patients through Proteoglycans in the cancer pathway. CONCLUSION: AR can target EGFR through its active component (Quercetin), and has a therapeutic effect on HPV_BC patients.

Which surgical approach is more favorable for pheochromocytoma of different sizes (< 6 cm vs. ≥ 6 cm)? A single retrospective center experience.

BACKGROUND: To compare the surgical effects of lateral transperitoneal approach (LTA) and posterior retroperitoneal approach (PRA) for pheochromocytoma of different sizes. METHODS: Data on patients with pheochromocytoma from 2014 to 2023 were collected from our hospital. According to different surgical approaches and tumor size, all patients were divided into four groups: tumor size < 6 cm for LTA and PRA and tumor size ≥ 6 cm for LTA and PRA. We compared these two surgical methods for pheochromocytoma of different sizes. RESULTS: A total of 118 patients with pheochromocytoma underwent successful laparoscopic surgery, including PRA group (n = 80) and LTA group (n = 38). In tumor size < 6 cm, the outcomes were no significant difference in LTA and PRA. In tumor size ≥ 6 cm, there was a significant difference in operation time (214.7 ± 18.9 vs. 154.3 ± 8.2, P = 0.007) and intraoperative blood loss (616.4 ± 181.3 vs. 201.4 ± 45.8, P = 0.037) between LTA and PRA. CONCLUSION: LTA and PRA were performed safely with similar operative outcomes in patients with pheochromocytoma size < 6 cm. While both LTA and PRA were executed with a commendable safety profile and comparable operative results in patients afflicted by pheochromocytomas < 6 cm, the PRA technique distinctly showcased advantages when addressing large-scale pheochromocytomas (≥ 6 cm). Notably, this manifested in reduced operative time, diminished intraoperative blood loss, decreased hospitalization expenses, and a paucity of procedural complications.

EAMNet: an Alzheimer's disease prediction model based on representation learning.

Objective. Brain18F-FDG PET images indicate brain lesions' metabolic status and offer the predictive potential for Alzheimer's disease (AD). However, the complexity of extracting relevant lesion features and dealing with extraneous information in PET images poses challenges for accurate prediction.Approach. To address these issues, we propose an innovative solution called the efficient adaptive multiscale network (EAMNet) for predicting potential patient populations using positron emission tomography (PET) image slices, enabling effective intervention and treatment. Firstly, we introduce an efficient convolutional strategy to enhance the receptive field of PET images during the feature learning process, avoiding excessive extraction of fine tissue features by deep-level networks while reducing the model's computational complexity. Secondly, we construct a channel attention module that enables the prediction model to adaptively allocate weights between different channels, compensating for the spatial noise in PET images' impact on classification. Finally, we use skip connections to merge features from different-scale lesion information. Through visual analysis, the network constructed in this article aligns with the regions of interest of clinical doctors.Main results. Through visualization analysis, our network aligns with regions of interest identified by clinical doctors. Experimental evaluations conducted on the ADNI (Alzheimer's Disease Neuroimaging Initiative) dataset demonstrate the outstanding classification performance of our proposed method. The accuracy rates for AD versus NC (Normal Controls), AD versus MCI (Mild Cognitive Impairment), MCI versus NC, and AD versus MCI versus NC classifications achieve 97.66%, 96.32%, 95.23%, and 95.68%, respectively.Significance. The proposed method surpasses advanced algorithms in the field, providing a hopeful advancement in accurately predicting and classifying Alzheimer's Disease using18F-FDG PET images. The source code has been uploaded tohttps://github.com/Haoliang-D-AHU/EAMNet/tree/master.

Terahertz label-free detection of nicotine-induced neural cell changes and the underlying mechanisms.

Nicotine exposure can lead to neurological impairments and brain tumors, and a label-free and nondestructive detection technique is urgently required by the scientific community to assess the effects of nicotine on neural cells. Herein, a terahertz (THz) time-domain attenuated total reflection (TD-ATR) spectroscopy approach is reported, by which the effects of nicotine on normal and cancerous neural cells, i.e., HEB and U87 cells, are successfully investigated in a label/stain-free and nondestructive manner. The obtained THz absorption coefficients of HEB cells exposed to low-dose nicotine and high-dose nicotine are smaller and larger, respectively, than the untreated cells. In contrast, the THz absorption coefficients of U87 cells treated by nicotine are always smaller than the untreated cells. The THz absorption coefficients can be well related to the proliferation properties (cell number and compositional changes) and morphological changes of neural cells, by which different types of neural cells are differentiated and the viabilities of neural cells treated by nicotine are reliably assessed. Collectively, this work sheds new insights on the effects of nicotine on neural cells, and provides a useful tool (THz TD-ATR spectroscopy) for the study of chemical-cell interactions.