Construction of N-doped carbon encapsulated CoP hollow nanofibers as multifunctional electrode materials for potassium-ion and lithium-sulfur batteries.

Herein, a composite of N-doped carbon coated phosphating cobalt hollow nanofibers (N/C@CoP-HNFs) was synthesized by electrospinning, phosphating, and carbon coating processes. When employed as multifunctional electrode materials for potassium-ion batteries (PIBs) and lithium-sulfur (Li-S) batteries, the N/C@CoP-HNFs demonstrated notable electrochemical properties. Specifically, it delivered an initial specific capacity of 420.4 mA h g-1 at a current density of 100 mA g-1, with a sustained capacity of 190.8 mA h g-1 after 200 cycles in PIBs, and a specific capacity of 1448 mA h g-1 at a current density of 0.5C in Li-S batteries, which is considered relatively high for these types of battery technology. This good performance may due to the combination of the carbon nitrogen layer and cobalt phosphide bilayer hollow tube structure, which is conducive to telescoping the diffusion length of ions and electrons and buffer volume variation, and effectively inhibits the shuttle effect. Density functional theory (DFT) calculations were also used to explore the energy storage mechanism of the material. The possible adsorption sites and corresponding adsorption energy of K+ were analyzed, and the advantages of the material were explored by calculating the diffusion barrier and state density. The theoretical simulations further validated the strong adsorption capability of CoP for polysulfides. This work is expected to provide new ideas for new energy storage materials.

Olfactory deficit: a potential functional marker across the Alzheimer's disease continuum.

Alzheimer's disease (AD) is a prevalent form of dementia that affects an estimated 32 million individuals globally. Identifying early indicators is vital for screening at-risk populations and implementing timely interventions. At present, there is an urgent need for early and sensitive biomarkers to screen individuals at risk of AD. Among all sensory biomarkers, olfaction is currently one of the most promising indicators for AD. Olfactory dysfunction signifies a decline in the ability to detect, identify, or remember odors. Within the spectrum of AD, impairment in olfactory identification precedes detectable cognitive impairments, including mild cognitive impairment (MCI) and even the stage of subjective cognitive decline (SCD), by several years. Olfactory impairment is closely linked to the clinical symptoms and neuropathological biomarkers of AD, accompanied by significant structural and functional abnormalities in the brain. Olfactory behavior examination can subjectively evaluate the abilities of olfactory identification, threshold, and discrimination. Olfactory functional magnetic resonance imaging (fMRI) can provide a relatively objective assessment of olfactory capabilities, with the potential to become a promising tool for exploring the neural mechanisms of olfactory damage in AD. Here, we provide a timely review of recent literature on the characteristics, neuropathology, and examination of olfactory dysfunction in the AD continuum. We focus on the early changes in olfactory indicators detected by behavioral and fMRI assessments and discuss the potential of these techniques in MCI and preclinical AD. Despite the challenges and limitations of existing research, olfactory dysfunction has demonstrated its value in assessing neurodegenerative diseases and may serve as an early indicator of AD in the future.

In vitro regeneration of triploid from mature endosperm culture of Passiflora edulis "Mantianxing".

The regeneration of shoots from endosperm tissue is a highly effective method to obtain triploid plants. In this study, we elucidated the establishment of an in vitro regeneration system from endosperm culture for the production of Passiflora edulis "Mantianxing." The highest callus induction rate (83.33%) was obtained on the media supplemented with 1.0 mg/L TDZ. Meanwhile, the MS medium containing 1.0 mg/L 6-BA and 0.4 mg/L IBA gave the optimum 75% shoot bud induction. Chromosome analysis revealed that the chromosomal count of P. edulis "Mantianxing" regenerated from endosperm tissues was 27 (2n = 3x = 27), which indicated that shoots regenerated from endosperm tissues were triploids. Triploid P. edulis had more drought resistance than diploid plants. Our study provided a method for breeding of passion fruit by means of a stable and reproducible regeneration system from endosperm culture, leading to the generation of triploid plants.

The relationship between psychological distress and the nursing humanistic care demands in postoperative cancer inpatients: a cross-sectional study.

PURPOSE: We aimed to investigate cancer patients' experiences of psychological distress after surgery and the factors that influence it, and to analyze the relationship between this and the nursing humanistic care demands. METHODS: This study used a convenience sampling method to survey 432 cancer patients undergoing surgical treatment in the specialized cancer hospital in Beijing. The survey used socio-demographic information, the Distress Management Screening Measures, and the Nursing Humanistic Care Demands questionnaire. Questionnaire Star was used to collect data online. SPSS24.0 software was used to test the relationship between psychological distress and nursing humanistic care demands. RESULTS: The mean scores for psychological distress and nursing humanistic care demands were 3.95 ± 2.71 and 147.02 ± 19.88, respectively, and showed a moderately positive correlation. The main issues that caused psychological distress in patients were: worry, financial problems, surroundings, nervousness, sleep, and pain. Regression analysis showed that gender, financial burden, personality trait, and need for humanistic care in nursing explained 24.5% of the total variance in the model and were independent predictors of psychological distress. CONCLUSION: Cancer inpatients have significant psychological distress after surgery and exhibit high levels of nursing humanistic care demands. This study fills the research gap on humanistic care for psychological distress management, nursing humanistic care demands positively predicted psychological distress. Nursing staff should pay attention to the psychological suffering of patients and develop individualized care measures to alleviate their psychological suffering by accurately identifying their nursing humanistic care demands.

Autophagy dysfunction contributes to NLRP1 inflammasome-linked depressive-like behaviors in mice.

BACKGROUND: Major depressive disorder (MDD) is a common but severe psychiatric illness characterized by depressive mood and diminished interest. Both nucleotide-binding oligomerization domain, leucine-rich repeat and pyrin domain-containing 1 (NLRP1) inflammasome and autophagy have been reported to implicate in the pathological processes of depression. However, the mechanistic interplay between NLRP1 inflammasome, autophagy, and depression is still poorly known. METHODS: Animal model of depression was established by chronic social defeat stress (CSDS). Depressive-like behaviors were determined by social interaction test (SIT), sucrose preference test (SPT), open field test (OFT), forced swim test (FST), and tail-suspension test (TST). The protein expression levels of NLRP1 inflammasome complexes, pro-inflammatory cytokines, phosphorylated-phosphatidylinositol 3-kinase (p-PI3K)/PI3K, phosphorylated-AKT (p-AKT)/AKT, phosphorylated-mechanistic target of rapamycin (p-mTOR)/mTOR, brain-derived neurotrophic factor (BDNF), phosphorylated-tyrosine kinase receptor B (p-TrkB)/TrkB, Bcl-2-associated X protein (Bax)/B-cell lymphoma-2 (Bcl2) and cleaved cysteinyl aspartate-specific proteinase-3 (caspase-3) were examined by western blotting. The mRNA expression levels of pro-inflammatory cytokines were tested by quantitative real-time PCR. The interaction between proteins was detected by immunofluorescence and coimmunoprecipitation. Neuronal injury was assessed by Nissl staining. The autophagosomes were visualized by transmission electron microscopy. Nlrp1a knockdown was performed using an adeno-associated virus (AAV) vector containing Nlrp1a-shRNA-eGFP infusion. RESULTS: CSDS exposure caused a bidirectional change in hippocampal autophagy function, which was activated in the initial period but impaired at the later stage. In addition, CSDS exposure increased the expression levels of hippocampal NLRP1 inflammasome complexes, pro-inflammatory cytokines, p-PI3K, p-AKT and p-mTOR in a time-dependent manner. Interestingly, NLRP1 is immunoprecipitated with mTOR but not PI3K/AKT and CSDS exposure facilitated the immunoprecipitation between them. Hippocampal Nlrp1a knockdown inhibited the activity of PI3K/AKT/mTOR signaling, rescued the impaired autophagy and ameliorated depressive-like behavior induced by CSDS. In addition, rapamycin, an autophagy inducer, abolished NLRP1 inflammasome-driven inflammatory reactions, alleviated depressive-like behavior and exerted a neuroprotective effect. CONCLUSIONS: Autophagy dysfunction contributes to NLRP1 inflammasome-linked depressive-like behavior in mice and the regulation of autophagy could be a valuable therapeutic strategy for the management of depression.

The role of serum thymidine kinase 1 activity in neoadjuvant-treated HER2-positive breast cancer: biomarker analysis from the Swedish phase II randomized PREDIX HER2 trial.

BACKGROUND: Thymidine kinase 1 (TK1) plays a pivotal role in DNA synthesis and cellular proliferation. TK1 has been studied as a prognostic marker and as an early indicator of treatment response in human epidermal growth factor 2 (HER2)-negative early and metastatic breast cancer (BC). However, the prognostic and predictive value of serial TK1 activity in HER2-positive BC remains unknown. METHODS: In the PREDIX HER2 trial, 197 HER2-positive BC patients were randomized to neoadjuvant trastuzumab, pertuzumab, and docetaxel (DPH) or trastuzumab emtansine (T-DM1), followed by surgery and adjuvant epirubicin and cyclophosphamide. Serum samples were prospectively collected from all participants at multiple timepoints: at baseline, after cycle 1, 2, 4, and 6, at end of adjuvant therapy, annually for a total period of 5 years and/or at the time of recurrence. The associations of sTK1 activity with baseline characteristics, pathologic complete response (pCR), event-free survival (EFS), and disease-free survival (DFS) were evaluated. RESULTS: No association was detected between baseline sTK1 levels and all the baseline clinicopathologic characteristics. An increase of TK1 activity from baseline to cycle 2 was seen in all cases. sTK1 level at baseline, after 2 and 4 cycles was not associated with pCR status. After a median follow-up of 58 months, 23 patients had EFS events. There was no significant effect between baseline or cycle 2 sTK1 activity and time to event. A non-significant trend was noted among patents with residual disease (non-pCR) and high sTK1 activity at the end of treatment visit, indicating a potentially worse long-term prognosis. CONCLUSION: sTK1 activity increased following neoadjuvant therapy for HER2-positive BC but was not associated with patient outcomes or treatment benefit. However, the post-surgery prognostic value in patients that have not attained pCR warrants further investigation. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02568839. Registered on 6 October 2015.

Identification and analysis of lipid metabolism-related genes in allergic rhinitis.

BACKGROUND: Studies have shown that the lipid metabolism mediator leukotriene and prostaglandins are associated with the pathogenesis of allergic rhinitis (AR). The aim of this study was to identify key lipid metabolism-related genes (LMRGs) related to the diagnosis and treatment of AR. MATERIALS AND METHODS: AR-related expression datasets (GSE75011, GSE46171) were downloaded through the Gene Expression Omnibus (GEO) database. First, weighted gene co-expression network analysis (WGCNA) was used to get AR-related genes (ARRGs). Next, between control and AR groups in GSE75011, differentially expressed genes (DEGs) were screened, and DEGs were intersected with LMRGs to obtain lipid metabolism-related differentially expressed genes (LMR DEGs). Protein-protein interaction (PPI) networks were constructed for these LMR DEGs. Hub genes were then identified through stress, radiality, closeness and edge percolated component (EPC) analysis and intersected with the ARRGs to obtain candidate genes. Biomarkers with diagnostic value were screened via receiver operating characteristic (ROC) curves. Differential immune cells screened between control and AR groups were then assessed for correlation with the diagnostic genes, and clinical correlation analysis and enrichment analysis were performed. Finally, real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) was made on blood samples from control and AR patients to validate these identified diagnostic genes. RESULTS: 73 LMR DEGs were obtained, which were involved in biological processes such as metabolism of lipids and lipid biosynthetic processes. 66 ARRGs and 22 hub genes were intersected to obtain four candidate genes. Three diagnostic genes (LPCAT1, SGPP1, SMARCD3) with diagnostic value were screened according to the AUC > 0.7, with markedly variant between control and AR groups. In addition, two immune cells, regulatory T cells (Treg) and T follicular helper cells (TFH), were marked variations between control and AR groups, and SMARCD3 was significantly associated with TFH. Moreover, SMARCD3 was relevant to immune-related pathways, and correlated significantly with clinical characteristics (age and sex). Finally, RT-qPCR results indicated that changes in the expression of LPCAT1 and SMARCD3 between control and AR groups were consistent with the GSE75011 and GSE46171. CONCLUSION: LPCAT1, SGPP1 and SMARCD3 might be used as biomarkers for AR.

Reconfiguration of brain network dynamics underlying spatial deficits in subjective cognitive decline.

Brain dynamics and the associations with spatial navigation in individuals with subjective cognitive decline (SCD) remain unknown. In this study, a hidden Markov model (HMM) was inferred from resting-state functional magnetic resonance imaging data in a cohort of 80 SCD and 77 normal control (NC) participants. By HMM, 12 states with distinct brain activity were identified. The SCD group showed increased fractional occupancy in the states with less activated ventral default mode, posterior salience, and visuospatial networks, while decreased fractional occupancy in the state with general network activation. The SCD group also showed decreased probabilities of transition into and out of the state with general network activation, suggesting an inability to dynamically upregulate and downregulate brain network activity. Significant correlations between brain dynamics and spatial navigation were observed. The combined features of spatial navigation and brain dynamics showed an area under the curve of 0.854 in distinguishing between SCD and NC. The findings may provide exploratory evidence of the reconfiguration of brain network dynamics underlying spatial deficits in SCD.

Predictors of placebo response in three large clinical trials of the V1a receptor antagonist balovaptan in autism spectrum disorder.

High rates of placebo response are increasingly implicated in failed autism spectrum disorder (ASD) clinical trials. Despite this, there are limited investigations of placebo response in ASD. We sought to identify baseline predictors of placebo response and quantify their influence on clinical scales of interest for three harmonized randomized clinical trials of balovaptan, a V1a receptor antagonist. We employed a two-step approach to identify predictors of placebo response on the Vineland-II two-domain composite (2DC) (primary outcome and a caregiver measure) and Clinical Global Impression (CGI) scale (secondary outcome and a clinician measure). The initial candidate predictor set of variables pertained to participant-level, site-specific, and protocol-related factors. Step 1 aimed to identify influential predictors of placebo response using Least Absolute Shrinkage and Selection Operator (LASSO) regression, while Step 2 quantified the influence of predictors via linear regression. Results were validated through statistical bootstrapping approaches with 500 replications of the analysis dataset. The pooled participant-level dataset included individuals with ASD aged 5 to 62 years (mean age 21 [SD 10]), among which 263 and 172 participants received placebo at Weeks 12 and 24, respectively. Although no influential predictors were identified for CGI, findings for Vineland-II 2DC are robust and informative. Decreased placebo response was predicted by higher baseline Vineland-II 2DC (i.e., more advanced adaptive function), longer trial duration, and European (vs United States) sites, while increased placebo response was predicted by commercial (vs academic) sites, attention deficit hyperactivity disorder and depression. Identification of these factors may be useful in anticipating and mitigating placebo response in drug development efforts in ASD and across developmental and psychiatric conditions.

Spatial navigation is associated with subcortical alterations and progression risk in subjective cognitive decline.

BACKGROUND: Subjective cognitive decline (SCD) may serve as a symptomatic indicator for preclinical Alzheimer's disease; however, SCD is a heterogeneous entity regarding clinical progression. We aimed to investigate whether spatial navigation could reveal subcortical structural alterations and the risk of progression to objective cognitive impairment in SCD individuals. METHODS: One hundred and eighty participants were enrolled: those with SCD (n = 80), normal controls (NCs, n = 77), and mild cognitive impairment (MCI, n = 23). SCD participants were further divided into the SCD-good (G-SCD, n = 40) group and the SCD-bad (B-SCD, n = 40) group according to their spatial navigation performance. Volumes of subcortical structures were calculated and compared among the four groups, including basal forebrain, thalamus, caudate, putamen, pallidum, hippocampus, amygdala, and accumbens. Topological properties of the subcortical structural covariance network were also calculated. With an interval of 1.5 years ± 12 months of follow-up, the progression rate to MCI was compared between the G-SCD and B-SCD groups. RESULTS: Volumes of the basal forebrain, the right hippocampus, and their respective subfields differed significantly among the four groups (p < 0.05, false discovery rate corrected). The B-SCD group showed lower volumes in the basal forebrain than the G-SCD group, especially in the Ch4p and Ch4a-i subfields. Furthermore, the structural covariance network of the basal forebrain and right hippocampal subfields showed that the B-SCD group had a larger Lambda than the G-SCD group, which suggested weakened network integration in the B-SCD group. At follow-up, the B-SCD group had a significantly higher conversion rate to MCI than the G-SCD group. CONCLUSION: Compared to SCD participants with good spatial navigation performance, SCD participants with bad performance showed lower volumes in the basal forebrain, a reorganized structural covariance network of subcortical nuclei, and an increased risk of progression to MCI. Our findings indicated that spatial navigation may have great potential to identify SCD subjects at higher risk of clinical progression, which may contribute to making more precise clinical decisions for SCD individuals who seek medical help.

Mediating effects of core competence between the transition shock and work readiness of newly graduated nurses in cancer hospitals: A cross-sectional study.

BACKGROUND: Newly graduated nurses face a dilemma of transitioning from student to clinical nurse roles, resulting in a low level of work readiness. The special professional environment of oncology hospitals requires newly graduated nurses to have specialized and novel theoretical knowledge and nursing skills. Therefore, they are constantly expected to develop better core competence. However, whether the core competence of newly graduated nurses mediates the relationship between transition shock and work readiness has not been investigated. OBJECTIVE: This study examined the relationship among transition shock, core competence, and work readiness of newly graduated nurses in cancer hospitals. DESIGN: A descriptive, cross-sectional study design. SETTING: This study was conducted at a tertiary cancer hospital in Beijing. PARTICIPATIONS: A convenience sample of 188 newly graduated nurses was studied from July to August 2022. METHODS: Sociodemographic data and Transition Shock Scale for Newly Graduated Nurses, Work Readiness Scale for Newly Graduated Nurses, and Core Competence Scale scores were collected using the online Questionnaire Star support platform. Pearson correlation and multiple regression analysis were applied using the Statistical Package for the Social Sciences version 24 to test the relationship among transition shock, core competencies, and work readiness. The Analysis of Moment Structures version 24.0 software was used to construct structural equation models. This report followed the Strengthening the Reporting of Observational studies in Epidemiology checklist. RESULTS: The transition shock of newly graduated nurses was negatively correlated with work readiness and core competence, whereas core competence was positively correlated with work readiness. Core competence partially mediated the effect between transition shock and work readiness, accounting for 19 % of the total effect. CONCLUSION: Core competence is the mediating variable between transition shock and work readiness of newly graduated nurses in oncology hospitals. During the transition period of newly graduated nurses, clinical nursing managers and teachers should pay attention to cultivating the core competence of newly graduated nurses to improve their work readiness.

Alterations in Dynamic Functional Connectivity in Patients with Cerebral Small Vessel Disease.

Cerebral small vessel disease (CSVD) is a common disease that seriously endangers people's health, and is easily overlooked by both patients and clinicians due to its near-silent onset. Dynamic functional connectivity (DFC) is a new concept focusing on the dynamic features and patterns of brain networks that represents a powerful tool for gaining novel insight into neurological diseases. To assess alterations in DFC in CSVD patients, and the correlation of DFC with cognitive function. We enrolled 35 CSVD patients and 31 normal control subjects (NC). Resting-state functional MRI (rs-fMRI) with a sliding-window approach and k-means clustering based on independent component analysis (ICA) was used to evaluate DFC. The temporal properties of fractional windows and the mean dwell time in each state, as well as the number of transitions between each pair of DFC states, were calculated. Additionally, we assessed the functional connectivity (FC) strength of the dynamic states and the associations of altered neuroimaging measures with cognitive performance. A dynamic analysis of all included subjects suggested four distinct functional connectivity states. Compared with the NC group, the CSVD group had more fractional windows and longer mean dwell times in state 4 characterized by sparse FC both inter-network and intra-networks. Additionally, the CSVD group had a reduced number of windows and shorter mean dwell times compared to the NC group in state 3 characterized by highly positive FC between the somatomotor and visual networks, and negative FC in the basal ganglia and somatomotor and visual networks. The number of transitions between state 2 and state 3 and between state 3 and state 4 was significantly reduced in the CSVD group compared to the NC group. Moreover, there was a significant difference in the FC strength between the two groups, and the altered temporal properties of DFC were significantly related to cognitive performance. Our study indicated that CSVD is characterized by altered temporal properties in DFC that may be sensitive neuroimaging biomarkers for early disease identification. Further study of DFC alterations could help us to better understand the progressive dysfunction of networks in CSVD patients.

Applicability of multidimensional convolutional neural networks on automated detection of diverse focal liver lesions in multiphase CT images.

PURPOSE: To investigate the applicability of multidimensional convolutional neural networks (CNNs) together with multiphase contrast-enhanced CT images on automated detection of diverse focal liver lesions (FLLs). METHODS: We trained detection models based on 2.5D and 3D CNN frameworks using 567 patients with 3892 FLLs and validated on a relatively large independent cohort of 1436 patients with 4723 lesions. The detection performance across different phases (arterial, portal venous [PV], and combined phases) was assessed for the 2.5D model. The lesions were divided into two groups with a cutoff size of 20 mm, and further subdivided into four subgroups of <10, 10-20, 20-50, and ≥50 mm, to verify the detection rates for lesions of different sizes for the 2.5D and 3D models. McNemar's test was used to compare the detection sensitivities among different methods. In addition, sensitivity with 95% confidence intervals and free-response receiver operating characteristics (FROC) curves were plotted for visualization of the detectability. RESULTS: In the 2.5D model, the detection rate of PV phase outperformed arterial phase, and a combination of the two phases further improved the performance over a single phase. The detection sensitivities in the arterial, PV, and combined phases were 0.737 versus 0.802 versus 0.832 for all lesions. The 3D model was superior to the 2.5D model for detecting benign lesions (0.896 vs. 0.807, p < 0.001), malignant lesions (0.940 vs. 0.918, p = 0.013), and all lesions (0.902 vs. 0.832, p < 0.001) regardless of size division. Particularly, the 3D model showed higher sensitivity than the 2.5D model in detecting lesions smaller than 20 mm (0.868 vs. 0.759, p < 0.001). For lesions larger than 20 mm, both the 3D and the 2.5D models achieved excellent detection performance. CONCLUSIONS: The proposed CNN detection model was demonstrated to adaptively learn the feature representations of diverse FLLs and generalize well to a large-scale validation dataset. The use of multiphase significantly improved the detectability of FLLs compared to single phase. 3D CNN framework showed an enhanced capability over the 2.5D in the detection of FLLs, particularly small lesions. The promising performance shows that the proposed CNN detection system could be a powerful clinical tool for the early detection of hepatic tumors.

A novel multimodal deep learning model for preoperative prediction of microvascular invasion and outcome in hepatocellular carcinoma.

BACKGROUND: Accurate preoperative identification of the microvascular invasion (MVI) can relieve the pressure from personalized treatment adaptation and improve the poor prognosis for hepatocellular carcinoma (HCC). This study aimed to develop and validate a novel multimodal deep learning (DL) model for predicting MVI based on multi-parameter magnetic resonance imaging (MRI) and contrast-enhanced computed tomography (CT). METHODS: A total of 397 HCC patients underwent both CT and MRI examinations before surgery. We established the radiological models (RCT, RMRI) by support vector machine (SVM), DL models (DLCT_ALL, DLMRI_ALL, DLCT + MRI) by ResNet18. The comprehensive model (CALL) involving multi-modality DL features and clinical and radiological features was constructed using SVM. Model performance was quantified by the area under the receiver operating characteristic curve (AUC) and compared by net reclassification index (NRI) and integrated discrimination improvement (IDI). RESULTS: The DLCT + MRI model exhibited superior predicted efficiency over single-modality models, especially over the DLCT_ALL model (AUC: 0.819 vs. 0.742, NRI > 0, IDI > 0). The DLMRI_ALL model improved the performance over the RMRI model (AUC: 0.794 vs. 0.766, NRI > 0, IDI < 0), but no such difference was found between the DLCT_ALL model and RCT model (AUC: 0.742 vs. 0.710, NRI < 0, IDI < 0). Furthermore, both the DLCT + MRI and CALL models revealed the prognostic power in recurrence-free survival stratification (P < 0.001). CONCLUSION: The proposed DLCT + MRI model showed robust capability in predicting MVI and outcomes for HCC. Besides, the identification ability of the multi-modality DL model was better than any single modality, especially for CT.

Expression patterns and prognostic implications of tumor-infiltrating lymphocytes dynamics in early breast cancer patients receiving neoadjuvant therapy: A systematic review and meta-analysis.

Purpose: High levels of tumor-infiltrating lymphocytes (TILs) are associated with better outcomes in early breast cancer and higher pathological response rates to neoadjuvant chemotherapy especially in the triple-negative (TNBC) and HER2+ subtypes. However, the dynamic changes in TILs levels after neoadjuvant treatment (NAT) are less studied. This systematic review and meta-analysis aimed to investigate the patterns and role of TILs dynamics change in early breast cancer patients receiving NAT. Methods: Medline, Embase, Web of Science Core Collection and PubMed Central databases were searched for eligible studies. Data were extracted independently by two researchers and discordances were resolved by a third. Pooled TILs rates pre- & post-treatment (overall and per subtype), pooled rates of ΔTILs and direction of change after NAT as well as correlation of ΔTILs with survival outcomes were generated in the outcome analysis. Results: Of 2116 identified entries, 34 studies fulfilled the criteria and provided adequate data for the outcomes of interest. A decreased level of TILs was observed after NAT in paired samples across all subtypes. The effect of NAT on TILs was most prominent in TNBC subtype with a substantial change, either increase or decrease, in 79.3% (95% CI 61.7-92.6%) of the patients as well as in HER2+ disease (14.4% increased vs 46.2% decreased). An increase in ΔTILs in TNBC was associated with better disease-free/relapse-free survival in pooled analysis (univariate HR = 0.59, 95% CI: 0.37-0.95, p = 0.03). Conclusion: This meta-analysis illustrates the TILs dynamics during NAT for breast cancer and indicates prognostic implications of ΔTILs in TNBC. The potential clinical utility of the longitudinal assessment of TILs during neoadjuvant therapy warrants further validation.

DNA methylation affects freezing tolerance in winter rapeseed by mediating the expression of genes related to JA and CK pathways.

Winter rapeseed is the largest source of edible oil in China and is especially sensitive to low temperature, which causes tremendous agricultural yield reduction and economic losses. It is still unclear how DNA methylation regulates the formation of freezing tolerance in winter rapeseed under freezing stress. Therefore, in this study, the whole-genome DNA methylation map and transcriptome expression profiles of freezing-resistant cultivar NTS57 (NS) under freezing stress were obtained. The genome-wide methylation assay exhibited lower levels of methylation in gene-rich regions. DNA methylation was identified in three genomic sequence contexts including CG, CHG and CHH, of which CG contexts exhibited the highest methylation levels (66.8%), followed by CHG (28.6%) and CHH (9.5%). Higher levels of the methylation were found in upstream 2 k and downstream 2 k of gene regions, whereas lowest levels were in the gene body regions. In addition, 331, 437, and 1720 unique differentially methylated genes (DMGs) were identified in three genomic sequence contexts in 17NS under freezing stress compared to the control. Function enrichment analysis suggested that most of enriched DMGs were involved in plant hormones signal transduction, phenylpropanoid biosynthesis and protein processing pathways. Changes of genes expression in signal transduction pathways for cytokinin (CK) and jasmonic acid (JA) implied their involvement in freezing stress responses. Collectively, these results suggested a critical role of DNA methylation in their transcriptional regulation in winter rapeseed under freezing stress.

Influencing Factors of Physical Activity in Patients with Lung Cancer Surgery and Its Correlation with Exercise Self-Efficacy and Perceived Social Support.

Purpose: The aim of the study is to understand the current status of physical activity in patients with lung cancer surgery, explore its influencing factors, and analyze the correlation between physical activity and exercise self-efficacy and perception of social support. Methods: The General Information Questionnaire was designed for 145 patients, Chinese version of EPIC-PAQ physical activity scale for lung cancer patients. The Exercise Self-Efficacy Scale (SEE) is used to evaluate the ability of people to organize and execute motor behaviors in various difficult situations. The Perceived Social Support Scale (PSSS) was used to emphasize individual self-understanding and self-feeling. Results: The median and quartile of total physical activity scores in lung cancer surgery patients were 73.0 (34.8, 129.7) points; univariate analysis showed that there were statistically significant differences in physical activity levels among lung cancer surgery patients with different ages, work status before hospitalization, and perceived disease severity. The results of multivariate analysis showed that age, perceived disease severity, exercise self-efficacy, and total score of perceived social support affected the physical activity level of patients (P < 0.05). Efficacy were positively correlated with perceived social support (P < 0.01). Conclusion: The level of physical activity of patients undergoing lung cancer surgery needs to be further improved. Physical activity is affected by patient age, perceived disease severity, exercise self-efficacy, and perceived social support and is positively correlated with exercise self-efficacy and perceived social support. Medical staff should provide targeted activity guidance according to the age and other characteristics of patients undergoing lung cancer surgery, enhance patients' exercise self-efficacy and comprehend social support, and improve their physical activity level, thereby promoting patients' early recovery.

Aging Promotes Chronic Stress-Induced Depressive-Like Behavior by Activating NLRP1 Inflammasome-Driven Inflammatory Signaling in Mice.

NLRP1 inflammasome has been reported to participate in many neurological disorders. Our previous study has demonstrated that NLRP1 inflammasome is implicated in chronic stress-induced depressive-like behaviors in mice. Age has been reported to be related to depression. Here we examine whether NLRP1 inflammasome is involved in the effect of age on depressive disorder. Two chronic stress stimuli, chronic social defeat stress (CSDS) and repeat social defeat stress (RSDS), were used to establish a depression model in mice of different ages. We found that aged mice exhibited worse depressive-like behaviors and locomotor activity compared to young mice. Interestingly, the expression of hippocampal NLRP1 inflammasome complexes and the levels of the inflammatory cytokines were increased in an age-dependent manner. Also, chronic stress-induced increase in the expression of the hippocampal chemokine C-X-C motif ligand 1 (CXCL1), and its cognate receptor, CXC-motif receptor 2 (CXCR2), was more remarkable in aged mice than that in young mice. Moreover, aged mice exhibited lower hippocampal BDNF levels compared to young mice. Hippocampal Nlrp1a knockdown reduced the levels of pro-inflammatory cytokines and the expression of CXCL1/CXCR2, restored BDNF levels, and alleviated chronic stress-induced depressive-like behaviors in aged mice. Our results suggest that NLRP1 inflammasome-CXCL1/CXCR2-BDNF signaling contributes to the effect of age on chronic stress-induced depressive-like behavior in mice.

CT-Based Radiomics for the Recurrence Prediction of Hepatocellular Carcinoma After Surgical Resection.

Purpose: To explore the effectiveness of radiomics signature in predicting the recurrence of hepatocellular carcinoma (HCC) and the benefit of postoperative adjuvant transcatheter arterial chemoembolization (PA-TACE). Patients and Methods: In this multicenter retrospective study, 364 consecutive patients with multi-phase computed tomography (CT) images were included. Recurrence-related radiomics features of intra- and peritumoral regions were extracted from the pre-contrast, arterial and portal venous phase, respectively. The radiomics model was established in the training cohort (n = 187) using random survival forests analysis to output prediction probability as "Rad-score" and validated by the internal (n = 92) and external validation cohorts (n = 85). Besides, the Clinical nomogram was developed by clinical-radiologic-pathologic characteristics, and the Combined nomogram was further constructed to evaluate the added value of the Rad-score for individualized recurrence-free survival (RFS) prediction, which is our primary and only endpoint. The performance of the three models was assessed by the concordance index (C-index). Furthermore, all the patients were stratified into high- and low-risk groups of recurrence by the median value of the Rad-score to analyze the benefit of PA-TACE. Results: The model built using radiomics signature demonstrated favorable prediction of HCC recurrence across all datasets, with C-index of 0.892, 0.812, 0.809, separately in the training, the internal and external validation cohorts. Univariate and multivariate analysis revealed that the Rad-score was an independent prognostic factor. Significant differences were found between the high- and low-risk group in RFS prediction in all three cohorts. Further analysis showed that compared with the low-risk group, patients with the high-risk received more benefits from PA-TACE. Conclusion: The newly developed Rad-score was not only a powerful biomarker in predicting the RFS of HCC but also a strong stratification basis to explore the high-risk patients who could benefit from PA-TACE.