Real-Space Topology-Engineering of Skyrmionic Spin Textures in a van der Waals Ferromagnet Fe3GaTe2.

Realizing magnetic skyrmions in two-dimensional (2D) van der Waals (vdW) ferromagnets offers unparalleled prospects for future spintronic applications. The room-temperature ferromagnet Fe3GaTe2 provides an ideal platform for tailoring these magnetic solitons. Here, skyrmions of distinct topological charges are artificially introduced and engineered by using magnetic force microscopy (MFM). The skyrmion lattice is realized by a specific field-cooling process and can be further erased and painted via delicate manipulation of the tip stray field. The skyrmion lattice with opposite topological charges (S = ±1) can be tailored at the target regions to form topological skyrmion junctions (TSJs) with specific configurations. The delicate interplay of TSJs and spin-polarized device current were finally investigated via the in situ transport measurements, alongside the topological stability of TSJs. Our results demonstrate that Fe3GaTe2 not only serves as a potential building block for skyrmion-based spintronic devices, but also presents prospects for Fe3GaTe2-based heterostructures with the engineered topological spin textures.

Unraveling metabolic characteristics and clinical implications in gastric cancer through single-cell resolution analysis.

Background: Gastric cancer is a highly prevalent malignant neoplasm. Metabolic reprogramming is intricately linked to both tumorigenesis and cancer immune evasion. The advent of single-cell RNA sequencing technology provides a novel perspective for evaluating cellular metabolism. This study aims to comprehensively investigate the metabolic pathways of various cell types in tumor and normal samples at high resolution and delve into the intricate regulatory mechanisms governing the metabolic activity of malignant cells in gastric cancer. Methods: Utilizing single-cell RNA sequencing data from gastric cancer, we constructed metabolic landscape maps for different cell types in tumor and normal samples. Employing unsupervised clustering, we categorized malignant cells in tumor samples into high and low metabolic subclusters and further explored the characteristics of these subclusters. Results: Our research findings indicate that epithelial cells in tumor samples exhibit significantly higher activity in most KEGG metabolic pathways compared to other cell types. Unsupervised clustering, based on the scores of metabolic pathways, classified malignant cells into high and low metabolic subclusters. In the high metabolic subcluster, it demonstrated the potential to induce a stronger immune response, correlating with a relatively favorable prognosis. In the low metabolic subcluster, a subset of cells resembling cancer stem cells (CSCs) was identified, and its prognosis was less favorable. Furthermore, a set of risk genes associated with this subcluster was discovered. Conclusion: This study reveals the intricate regulatory mechanisms governing the metabolic activity of malignant cells in gastric cancer, offering new perspectives for improving prognosis and treatment strategies.

Physical activity patterns and cognitive function in elderly women: a cross-sectional study from NHANES 2011-2014.

Background: Amid the backdrop of global aging, the increasing prevalence of cognitive decline among the elderly, particularly within the female demographic, represents a considerable public health concern. Physical activity (PA) is recognized as an effective non-pharmacological intervention for mitigating cognitive decline in older adults. However, the relationship between different PA patterns and cognitive function (CF) in elderly women remains unclear. Methods: This study utilized data from National Health and Nutrition Examination Survey (NHANES) 2011-2014 to investigate the relationships between PA, PA patterns [inactive, Weekend Warrior (WW), and Regular Exercise (RE)], and PA intensity with CF in elderly women. Multivariate regression analysis served as the primary analytical method. Results: There was a significant positive correlation between PA and CF among elderly women (ß-PA: 0.003, 95% CI: 0.000-0.006, P = 0.03143). Additionally, WW and RE activity patterns were associated with markedly better cognitive performance compared to the inactive group (ß-WW: 0.451, 95% CI: 0.216-0.685, P = 0.00017; ß-RE: 0.153, 95% CI: 0.085-0.221, P = 0.00001). Furthermore, our results indicate a progressive increase in CF with increasing PA intensity (ß-MPA- dominated: 0.16, 95% CI: 0.02-0.09, P = 0.0208; ß-VPA-dominated: 0.21, 95% CI: 0.09-0.34, P = 0.0011; ß-Total VPA: 0.31, 95% CI: -0.01-0.63, P = 0.0566). Conclusion: Our study confirms a positive association between PA and CF in elderly women, with even intermittent but intensive PA models like WW being correlated with improved CF. These findings underscore the significant role that varying intensities and patterns of PA play in promoting cognitive health among older age groups, highlighting the need for adaptable PA strategies in public health initiatives targeting this population.

Effects of social-ecological risk factors and resilience on the relationship between metabolic metrics and mental health among young adults.

The correlation between metabolic metrics and mental health remains underexplored, with few in-depth studies examining whether this association exists among college students and whether it might be moderated by socio-ecological risk factors (SERFs) and mediated by resilience. A follow-up study design investigated the association between baseline metabolic metrics, SERFs and resilience and mental health. A multivariable linear regression model using the PROCESS method established the relationship of SERFs, resilience and metabolic metrics with mental health. Participants were 794 adolescents (mean age: 18.64 [±0.90] years). In multivariable linear regression, the high-level SERFs (ß = 0.124), resilience (ß = -0.042), LCI (ß = 0.072), and RFM (ß = 0.145) were associated with higher depression symptoms, while CVH (ß = 0.602), TyG (ß = 0.295), TyG-BMI (ß = 0.004), and RC (ß = -0.041) were not. An association was also observed between SERFs, resilience, RFM and anxiety. Resilience mediated the relationship between metabolic metrics and depression and anxiety, and SERFs moderated this relationship, demonstrating the relationship between resilience, metabolic metrics, SERFs and mental health. By revealing the potential sociological mechanism underlying the relationship between metabolic metrics and adolescents' mental health, this study provides a theoretical basis for further exploration of the biological foundations of mental health.

High-spatial resolution ground-level ozone in Yunnan, China: A spatiotemporal estimation based on comparative analyses of machine learning models.

Monitoring ground-level ozone concentrations is a critical aspect of atmospheric environmental studies. Given the existing limitations of satellite data products, especially the lack of ground-level ozone characterization, and the discontinuity of ground observations, there is a pressing need for high-precision models to simulate ground-level ozone to assess surface ozone pollution. In this study, we have compared several widely utilized ensemble learning and deep learning methods for ground-level ozone simulation. Furthermore, we have thoroughly contrasted the temporal and spatial generalization performances of the ensemble learning and deep learning models. The 3-Dimensional Convolutional Neural Network (3-D CNN) model has emerged as the optimal choice for evaluating the daily maximum 8-h average ozone in Yunnan Province. The model has good performance: a spatial resolution of 0.05° × 0.05° and strong predictive power, as indicated by a Coefficient of Determination (R2) of 0.83 and a Root Mean Square Error (RMSE) of 12.54 µg/m³ in sample-based 5-fold cross-validation (CV). In the final stage of our study, we applied the 3-D CNN model to generate a comprehensive daily maximum 8-h average ozone dataset for Yunnan Province for the year 2021. This application has furnished us with a crucial high-resolution and highly accurate dataset for further in-depth studies on the issue of ozone pollution in Yunnan Province.

Interaction effect of screen time and sugar-sweetened beverages with depressive symptoms in adolescents: evidence from a large sample-based survey in China.

Excessive screen time and the consumption of sugar-sweetened beverages are found to be independent predictors of depressive symptoms. However, the potential interaction effect of screen time and sugar-sweetened beverages, that is, whether one exposure factor strengthens the association of another with depressive symptoms, remains unclear. A large-scale adolescent health surveillance survey was conducted in 27 schools in eight regions across China. A total of 22,868 students were recruited to complete an eligible questionnaire to provide details of their screen time and sugar-sweetened beverage consumption. Depressive symptoms were assessed using the Patient Health Questionnaire (PHQ-9). Multiplicative and additive interaction models were performed to estimate the interaction effects of screen time and sugar-sweetened beverages on depressive symptoms, and whether the relationship varied by age group was also examined. The multivariate logistic regression model showed that even if the confounding factors were controlled, screen time and sugar-sweetened beverages were still risk factors for depressive symptoms in adolescents. Interaction models indicated that screen time and sugar-sweetened beverages in combination were related to greater odds of depressive symptoms. Compared with late adolescents, early adolescents had a higher probability of depressive symptoms when exposed to the joint effects. Our study may hopefully deepen the understanding of the association between screen time and sugar-sweetened beverages and depressive symptoms. Future research should further explore how and why screen time and sugar-sweetened beverages affect individuals more profoundly in early adolescence than in late adolescence and how to mitigate this.

Metal-Free Activation of Molecular Oxygen by 9-Fluorenone-Based Porous Organic Polymers for Selective Aerobic Oxidation.

Oxygen activation is a critical step in heterogeneous oxidative processes, particularly in catalytic, electrolytic, and pharmaceutical applications. Among the various catalysts available for photocatalytic O2 activation, homogeneous aryl ketones are at the forefront. To avoid the degradation and deactivation of aryl ketones, 9-fluorenone-based porous organic polymers were designed and regulated by doping them with co-monomers. The obtained heterogeneous photocatalyst showed good performance in O2 activation, and its performance was better than that of homogeneous 9-fluorenone. The obtained heterogeneous photocatalyst showed good reusability. We believe that the presented method and findings represent an important step toward designing catalysts tailored for specific tasks.

Antibacterial effects and microarray-based molecular mechanisms of trans-cinnamaldehyde against Porphyromonas gingivalis.

Porphyromonas gingivalis (P. gingivalis) is one of the keystone pathogenic bacteria of periodontitis and peri-implantitis. This study aimed to investigate the antibacterial effects and molecular mechanisms of trans-cinnamaldehyde (TC), a safe extract from natural plants, on P. gingivalis. Minimum inhibitory and minimum bactericidal concentrations (MIC and MBC) of TC were determined, and scanning and transmission electron microscopies were used to assess the morphological changes. The overall biomass was estimated, and the metabolic activity of biofilms was determined at different TC concentrations. A microarray-based bioinformatics analysis was performed to elucidate the underlying molecular mechanisms of TC-inhibited P. gingivalis, and significant differences among groups were determined. TC showed an inhibitory effect on the proliferation and survival of planktonic P. gingivalis, of which the MIC and MBC were 39.07 µg/mL and 78.13 µg/mL, respectively. TC also significantly suppressed the formation and metabolic activity of P. gingivalis biofilm. The results of the significant pathways and gene ontology (GO) analyses revealed that TC treatment inhibited two metabolic pathways, accompanied by the downregulation of relative genes of nitrogen metabolism (NrfA, NrfH, and PG_2213) and starch and sucrose metabolism (PG_1681, PG_1682, and PG_1683). Thus, this study confirmed TC to be a natural antimicrobial agent against P. gingivalis and further demonstrated that TC suppressed the microbial activity on P. gingivalis through the disruption of physiological metabolism, which might inhibit the growth and the biofilm formation of P. gingivalis.

Hydrogenation of levulinic acid to γ-valerolactone over hydrophobic Ru@HCP catalysts.

This study introduces an efficient strategy for promoting the synthesis of γ-valerolactone (GVL) via levulinic acid (LA) hydrogenation. A series of hyper-crosslinked porous polymer (HCP) supported Ru catalysts with different monomers were prepared. The wettabilities were controlled by the surface functional groups. The hydrophobic catalysts showed much higher activity than the hydrophilic ones in the hydrogenation of LA to GVL, highly possible due to the substrate enrichment. Further insight showed that the reaction proceeded through the 4-HVA route. These results illustrated the importance of surface wettability in bio-based molecule upgrading, which is beneficial for catalyst design.

Chromosome-level genome assembly and population genomic analysis provide novel insights into the immunity and evolution of Sogatella furcifera.

Sogatella furcifera is a destructive agricultural pest causing large threats to rice production in China and Southeast Asian countries. Despite recent breakthroughs in long-read sequencing, high quality genomic data are very limited in S. furcifera. In present study, a chromosome-level assembly of the S. furcifera genome was completed (0.64 GB), comprising 15 chromosomes covered 95.04% of the estimated genome size, along with other 624 small scaffolds making up the remaining 4.96% of the genome of S. furcifera. A total of 24,669 protein-coding genes, 1211 long noncoding RNA and 7595 circular RNA transcripts were predicted in this study. Comparative genomic analysis revealed rapidly evolved genes were associated with multiple immune-related pathways in S. furcifera. Genome resequencing of 44 individuals from 12 geographic populations revealed frequent gene flow among populations. The systemic genomic analysis will provide more insights into the understanding of the immunity and evolutionary adaptation of S. furcifera.

Carboxymethyl konjac glucomannan-chitosan complex nanogels stabilized emulsions incorporated into alginate as microcapsule matrix for intestinal-targeted delivery of probiotics: In vivo and in vitro studies.

In this study, we developed a novel delivery system using carboxymethyl konjac glucomannan-chitosan (CMKGM-CS) nanogels stabilized single and double emulsion incorporated into alginate hydrogel as microcapsule matrix for intestinal-targeted delivery of probiotics. Through in vitro experiments, it was demonstrated that alginate hydrogel provided favorable biocompatible growth conditions for the proliferation of Lactobacillus reuteri (LR). The alginate hydrogel containing single (ASE) or double emulsions (ACG) enhanced the resistance of LR to various adverse environments. Simulated gastrointestinal digestion experiments revealed that the survivability of LR in free, CON, ASE and ACG group decreased by 6.45 log CFU/g, 4.21 log CFU/g, 1.26 log CFU/g and 0.65 log CFU/g, respectively. In vivo studies conducted in mice showed that ACG maintained its integrity during passage through the stomach and released the probiotics in the targeted intestinal area, whereas the pure alginate hydrogels (CON) were prematurely released in the gastrointestinal tract. Moreover, the viable counts of ACG in different intestinal segments (jejunum, ileum, cecum, and colon) were increased by 1.11, 1.42, 1.68, and 1.89 log CFU/g, respectively, after 72 h of oral administration compared to the CON group. This research contributed valuable insights into the development of an effective microbial delivery system with potential applications in the biopharmaceutical and food industries.

Proximate deconfined quantum critical point in SrCu2(BO3)2.

The deconfined quantum critical point (DQCP) represents a paradigm shift in quantum matter studies, presenting a "beyond Landau" scenario for order-order transitions. Its experimental realization, however, has remained elusive. Using high-pressure 11B nuclear magnetic resonance measurements on the quantum magnet SrCu2(BO3)2, we here demonstrate a magnetic field-induced plaquette singlet to antiferromagnetic transition above 1.8 gigapascals at a notably low temperature, Tc ≃ 0.07 kelvin. First-order signatures of the transition weaken with increasing pressure, and we observe quantum critical scaling at the highest pressure, 2.4 gigapascals. Supported by model calculations, we suggest that these observations can be explained by a proximate DQCP inducing critical quantum fluctuations and emergent O(3) symmetry of the order parameters. Our findings offer a concrete experimental platform for investigation of the DQCP.

Childhood maltreatment and non-suicidal self-injury among Chinese college students: The moderating roles of social phobia and perceived family economic status.

BACKGROUND: Non-suicidal self-injury is a heavy burden on affected college students with rippling effects throughout their lives. Childhood maltreatment is strongly associated with non-suicidal self-injury among college students. However, it remains unclear whether perceived family economic status and social phobia exert significant moderating effects on the relationship between childhood maltreatment and non-suicidal self-injury. OBJECTIVE: This study aimed to identify the perceived family economic status and social phobia moderating the association between childhood maltreatment and non-suicidal self-injury. PARTICIPANTS AND SETTING: This study used data (N = 5297) from two local medical colleges in Anhui province, China. METHODS: Respondents completed questionnaires on childhood maltreatment, non-suicidal self-injury, social phobia and perceived family economic status online. Data were analyzed using Spearman's correlation followed by multiple moderation models. RESULTS: The association between childhood maltreatment and non-suicidal self-injury was moderated by social phobia (ß = 0.03, p < 0.05) and perceived family economic status (ß = -0.30, p < 0.05). When considered together, both factors were found to play synergistic roles in the association between childhood maltreatment and non-suicidal self-injury in college students (ß = 0.08, p < 0.001). CONCLUSION: Our findings highlight that experience of childhood maltreatment, elevated social phobia, and low perceived family economic status increase the risk of non-suicidal self-injury. Future researches are recommended to conduct interventions from a more holistic perspective and integrate perceived family economic status as a relevant factor along with social phobia in coping with non-suicidal self-injury in college students.

Comparison of adverse childhood experience analytic approaches and associations with emotional and behavioral problems: A nationwide study among Chinese middle school students.

BACKGROUND: Adverse childhood experiences (ACEs) are demonstrated to be strongly associated with many health related problems, which have aroused extensive public attention. But the variety of analytic approaches of ACEs has limited researchers to differentiate those approaches across the outcomes. METHODS: A total of 22,686 middle school students were surveyed, and their ACEs and health related behaviors were collected. Four different analytic approaches were used to compare the effects of ACEs on four outcomes (non-suicidal self-injury, suicidal ideation, depression and anxiety symptoms). Logistic regression models were applied to verify the associations of adversities and four outcomes. R2 and the areas under the Receiver Operator Characteristic (ROC) curve were computed to compare the effects of four approaches. RESULTS: It was suggested that four measures of ACEs were significantly associated with all the outcomes in both the unadjusted and adjusted models (Ps all <0.05). R2 and areas under ROC curve showed that the contributions of four analytical approaches to different outcomes were diverse in this study. ACEs were more impactive to girls than to boys. CONCLUSION: ACEs are profound influencing factors of emotional and behavioral problems among middle school students. The selection of analytic approaches of ACEs depends on the need of research, and our study contributes to the choice of suitable analytic methods for future research of ACEs.

A pilot study on the use of a novel digital real-time evaluation system in undergraduate preclinical training of tooth preparation in fixed prosthodontics.

INTRODUCTION: In the light of the digital teaching, it is necessary that the effectiveness of a new digital real-time evaluation system in the preclinical training of tooth preparation be evaluated. MATERIALS AND METHODS: Forty undergraduate dental students of the fourth year were randomly divided into the control group and the experimental group to complete the training task of tooth preparation for porcelain fused to metal (PFM) crown restoring the upper right central incisor. The control students received conventional training with instructor's guidance. The experimental students received training with the digital system without instructor's guidance. Every student exercised preparation in two resin incisors in 3 h training by respective training methods. A third incisor was prepared on a dental model in the simulated head phantom by each student as the test on the next day. All students' tooth preparations were scored by the same two experienced experts. The experimental students were asked to answer a questionnaire regarding their attitudes and opinions on the digital evaluation system in preclinical training. RESULTS: There was no significant difference between the scores of the experimental group and the control group (p > .05). The students of two groups obtained the similar scores in the test (p > .05). Most of the students were supportive of the application of digital training system in the preclinical tooth preparation training course. CONCLUSIONS: The digital real-time evaluation system could provide effective training effects for the dental undergraduate students in the preclinical training of tooth preparation in fixed prosthodontics.

Co-occurrence patterns of adverse childhood experiences and their associations with non-suicidal self-injury and suicidal behaviors and gender difference among middle school students: A three-city survey in China.

BACKGROUND: Previous research has found increasing evidence of adverse childhood experiences (ACEs) leading to non-suicidal self-injury (NSSI) and suicidal behaviors. Most studies have focused on a certain type or timing of ACEs or the patterns of multiple types; however, few of them have examined the patterns of ACEs combined types and timing and the gender differences in the association between ACEs and self-harming behaviors. METHODS: A cross-sectional survey was conducted in three Chinese cities from November 2020 to May 2021. We asked 16,853 middle school students to anonymously complete a questionnaire to provide the details of their own ACEs and NSSI or suicidal behaviors. RESULTS: Latent class analysis identified four classes: high ACEs (10 %), high abuse/neglect (20.3 %), moderate ACEs (26.7 %) and low ACEs (43 %). Logistic regression models demonstrated that students in the high ACEs, high abuse/neglect and moderate ACEs subgroups were more likely to engage in NSSI and suicidal behaviors than students with low ACEs. Compared with boys, girls had a higher probability of engaging in NSSI and suicidal behaviors when exposed to the same level of ACEs. CONCLUSION: Co-occurrence of ACEs is associated with high risk of NSSI and suicidal behaviors. Our findings recognized the most dangerous patterns and latent class membership, which supply the evidence for policy makers to adopt preventive measures to protect high-risk individuals. Strategies to relieve the impact of ACEs, especially on girls, need to be considered comprehensively. LIMITATIONS: The study was limited by cross-sectional design, as causality could not be confirmed. In addition, because our survey was retrospective, potential recall bias can not be ignored.

A Deep Neural Network for Gastric Cancer Prognosis Prediction Based on Biological Information Pathways.

Background: Gastric cancer (GC) is one of the deadliest cancers in the world, with a 5-year overall survival rate of lower than 20% for patients with advanced GC. Genomic information is now frequently employed for precision cancer treatment due to the rapid advancements of high-throughput sequencing technologies. As a result, integrating multiomics data to construct predictive models for the GC patient prognosis is critical for tailored medical care. Results: In this study, we integrated multiomics data to design a biological pathway-based gastric cancer sparse deep neural network (GCS-Net) by modifying the P-NET model for long-term survival prediction of GC. The GCS-Net showed higher accuracy (accuracy = 0.844), area under the curve (AUC = 0.807), and F1 score (F1 = 0.913) than traditional machine learning models. Furthermore, the GCS-Net not only enables accurate patient survival prognosis but also provides model interpretability capabilities lacking in most traditional deep neural networks to describe the complex biological process of prognosis. The GCS-Net suggested the importance of genes (UBE2C, JAK2, RAD21, CEP250, NUP210, PTPN1, CDC27, NINL, NUP188, and PLK4) and biological pathways (Mitotic Anaphase, Resolution of Sister Chromatid Cohesion, and SUMO E3 ligases) to GC, which is consistent with the results revealed in biological- and medical-related studies of GC. Conclusion: The GCS-Net is an interpretable deep neural network built using biological pathway information whose structure represents a nonlinear hierarchical representation of genes and biological pathways. It can not only accurately predict the prognosis of GC patients but also suggest the importance of genes and biological pathways. The GCS-Net opens up new avenues for biological research and could be adapted for other cancer prediction and discovery activities as well.

Bioinspired gelatin nano-film implanted into composite scaffold exhibiting both expandable adhesion and enhanced proliferation.

Tissue engineering technology provides a new treatment to the cartilage damage. Recent progress has focused on coating strategies with the printed scaffold surface, using various materials such as bioactive nanocomposites. However, the fracture and exfoliation of printed scaffolds remain challenges due to their poor adhesion on smooth substrates. These limitations can be offset by developing a versatile film. Here, inspired by the mechanism of the wet adhesion of snails, we introduced a biomimetic nanoscale gelatin film between a smooth conductive slide and a scaffold, which enhanced early cell adhesion rates through water absorption, swelling and adhesion. A bionic technique of preparing gelatin nanofilms and PVP/PCL 3D scaffolds, which involved E-Jet atomization deposition and E-Jet printing techniques based on the electrohydrodynamic effect, was investigated. It is found that the composite scaffold with 400 nm gelatin nanofilm significantly enhances cell attachment (from 62 % to 87 %) and proliferation (increased 6.5 times in 7 days). Collectively, this study highlights the combination of biomimetic nanoscale adhesive film in promoting cell adhesion and cartilage differentiation, which benefiting from water absorption and swelling of gelatin nanofilm. This work provides a new idea for the potential application in the orthopedics field.

Interaction effects of screen time and fast-food consumption on suicidal behaviours: Evidence from a nationwide survey among Chinese adolescents.

BACKGROUND: Although screen time and fast-food consumption have been linked to suicidal behaviours, it is unclear whether their combined effects are associated with suicidal behaviours among adolescents. METHODS: A sample of 16,853 Chinese adolescents answered a standard questionnaire on screen time, fast-food consumption, and suicidal behaviours. A binomial logistic regression model was used to analyse the association between the three. An interaction model was used to examine the interaction effects of screen time and fast-food consumption on suicidal behaviours in adolescents. RESULTS: There were positive correlations between screen time, fast-food consumption, and suicidal behaviours, even after adjusting for confounding factors. Interaction analyses indicated that increased screen time on weekdays and fast-food consumption were associated with suicidal ideation. The relative excess risk of interaction, attributable proportions, and synergy index of interaction were 0.41, 0.15, and 1.32, respectively. Increased screen time on weekends and fast-food consumption were associated with suicidal ideation. The relative excess risk of interaction, attributable proportions, and synergy index of interaction were 0.37, 0.14, and 1.27, respectively. Similar additive interaction effects were exhibited in increased screen time and fast-food consumption on suicidal planning. Positive additive interaction effects were observed in increased screen time on weekdays and fast-food consumption on suicide attempts. LIMITATIONS: A cross-sectional study design was used; therefore, causal associations remain unclear. CONCLUSIONS: Screen time and fast-food consumption are cross-sectionally associated with suicidal behaviours among Chinese adolescents. Strategies should be considered to reduce screen time and fast-food consumption among adolescents.

Profiling the Tumor-Infiltrating Lymphocytes in Gastric Cancer Reveals Its Implication in the Prognosis.

Gastric cancer is the fifth most common malignancy and the third leading cause of cancer-related mortality worldwide. Immunotherapy offers promising new treatment options for gastric cancer patients; however, it is only effective in a limited fraction of patients. In this study, we evaluated the composition of 22 tumor-infiltrating lymphocytes (TILs) in TCGA Stomach Adenocarcinoma (STAD) using deconvolution-based method by analyzing the publicly available bulk tumor RNA-seq data. The patients were classified into high-TIL and low-TIL subtypes based on their immune cell profiles and prognosis outputs. The differentially expressed genes (DEGs) between the two subtypes were identified, and GO/KEGG analysis showed that broad immune genes, such as PD-L1 and PD-1, were highly expressed in the high-TIL subtype. A comprehensive protein-protein interaction (PPI) network centered on DEGs was built, and 16 hub genes of the network were further identified. Based on the hub genes, an elastic model with 11 gene signatures (NKG7, GZMB, IL2RB, CCL5, CD8A, IDO1, MYH1, GNLY, CXCL11, GBP5 and PRF1) was developed to predict the high-TIL subtype. In summary, our findings showed that the compositions of TILs within the tumor immune microenvironment of stomach cancer patients are highly heterogeneous, and the profiles of TILs have the potential to be predictive markers of patients' responses and overall survival outcomes.