Research progress on the role of mindfulness in intervention for adolescent obesity.

In the face of the increasingly serious background of overweight and obesity rates among adolescents in China, mindfulness, as an emerging therapeutic approach, has shown its unique effectiveness. This article reviewed the research progress of mindfulness in the intervention of adolescent obesity, summarized its effects on improving physiological and psychological indicators, and listed the different options for implementing mindfulness therapy. These studies supported the preliminary effectiveness of mindfulness in the intervention of adolescent obesity, providing a basis for mindfulness to become a new approach for obesity intervention in the future.

Antimony(V) Adsorption and Partitioning by Humic Acid-Modified Ferrihydrite: Insights into Environmental Remediation and Transformation Processes.

Antimony (Sb) migration in soil and water systems is predominantly governed by its adsorption onto ferrihydrite (FH), a process strongly influenced by natural organic matter. This study investigates the adsorption behavior, stability, and mechanism of FH and FH-humic acid (FH-HA) complexes on Sb(V), along with the fate of adsorbed Sb(V) during FH aging. Batch adsorption experiments reveal that initial pH and concentration significantly influence Sb(V) sorption. Lower pH levels decrease adsorption, while higher concentrations enhance it. Sb(V) adsorption increases with prolonged contact time, with FH exhibiting a higher adsorption capacity than FH-HA complexes. Incorporating HA onto FH surfaces reduces reactive adsorption sites, decreasing Sb(V) adsorption. Adsorbed FH-HA complexes exhibit a higher specific surface area than co-precipitated FH-HA, demonstrating stronger Sb(V) adsorption capacity under various conditions. X-ray photoelectron spectroscopy (XPS) confirms that Sb(V) adsorption primarily occurs through ligand exchange, forming Fe-O-Sb complexes. HA inhibits the migration of Sb(V), thereby enhancing its retention within the FH and FH-HA complexes. During FH transformation, a portion of Sb(V) may replace Fe(III) within converted iron minerals. However, the combination of relatively high adsorption capacity and significantly lower desorption rates makes adsorbed FH-HA complexes promising candidates for sustained Sb adsorption over extended periods. These findings enhance our understanding of Sb(V) behavior and offer insights for effective remediation strategies in complex environmental systems.

Effects of Trimethylamine N-Oxide in Improving Exercise Performance in Mice: A 1H-NMR-Based Metabolomic Analysis Approach.

To improve exercise performance, the supplement of nutrients has become a common practice before prolonged exercise. Trimethylamine N-oxide (TMAO) has been shown to ameliorate oxidative stress damage, which may be beneficial in improving exercise capacity. Here, we assessed the effects of TMAO on mice with exhaustive swimming, analyzed the metabolic changes, and identified significantly altered metabolic pathways of skeletal muscle using a nuclear magnetic resonance-based (NMR-based) metabolomics approach to uncover the effects of TMAO improving exercise performance of mice. We found that TMAO pre-administration markedly prolonged the exhaustive time in mice. Further investigation showed that TMAO pre-administration increased levels of 3-hydroxybutyrate, isocitrate, anserine, TMA, taurine, glycine, and glutathione and disturbed the three metabolic pathways related to oxidative stress and protein synthesis in skeletal muscle. Our results provide a metabolic mechanistic understanding of the effects of TMAO supplements on the exercise performance of skeletal muscle in mice. This work may be beneficial in exploring the potential of TMAO to be applied in nutritional supplementation to improve exercise performance. This work will lay a scientific foundation and be beneficial to exploring the potential of TMAO to apply in nutritional supplementation.

Prognostic Value of IGFBP6 in Breast Cancer: Focus on Glucometabolism.

IGFBP6, a member of the IGF binding protein (IGFBP) family, is a specific inhibitor of insulin-like growth factor II (IGF-II) and can inhibit the growth of malignant tumors overexpressing IGF-II. Type 2 diabetes (T2D) is a basic disorder of glucose metabolism that can be regulated by IGF-related pathways. We performed bioinformatics analysis of the TCGA database to explore the possible mechanism of IGFBP6 in breast cancer (BC) metabolism and prognosis and collected clinical samples from BC patients with and without T2D to compare and verify the prognostic effect of IGFBP6. In our study, the levels of IGFBP1-6 were positively correlated with overall survival (OS) in patients with breast cancer. IGFBP6 was upregulated in estrogen receptor (ER)-positive BC, and ER-positive and progesterone receptor (PR) positive patients had a higher expression level of IGFBP6 than ER-negative and PR-negative patients. IGFBP6 could be used as an independent prognostic factor in BC. The expression of IGFBP6 was decreased in BC tissue, and BC tissue from patients with T2D had lower IGFBP6 expression levels than BC tissue from patients without T2D. IGFBP6 is mainly involved in the PI3K-Akt and TGF-ß signaling pathways and tumor microenvironment regulation. In terms of metabolism, the expression of IGFBP6 was negatively correlated with that of most glucose metabolism-related genes. IGFBP6 expression was mainly correlated with mutations in TP53, PIK3CA, CDH1, and MAP3K1. In addition, the upregulation of IGFBP6 in BC increased the drug sensitivity to docetaxel, paclitaxel and gemcitabine. Overall, these results indicated that high expression of IGFBP6 is associated with a good prognosis in BC patients, especially in those without T2D. It is not only involved in the maintenance of the tumor microenvironment in BC but also inhibits the energy metabolism of cancer cells through glucose metabolism-related pathways. These findings may provide a new perspective on IGFBP6 as a potential prognostic marker for BC.

Proteome and Metabolome Profiling of Anticoagulant Disorders Induced by Familial Protein S Deficiency.

Protein S deficiency (PSD) is an autosomal dominant disorder characterized by congenital thrombophilia. Studies on PSD are limited yet, resulting in a lack of clarity about molecular changes during abnormal coagulation. Proteomics and metabolomics analyses were conducted on the plasma of PSD patients based on liquid and gas chromatography-mass spectrometry (LC- and GC-MS). Differential proteins and metabolites of PSD were then filtered by univariate statistical analysis and subjected to network analysis using the ingenuity pathway analysis (IPA) platform. The proteome and metabolome of PSD were obviously disturbed, and the biological pathway of coagulation and complement cascades was the most affected. During PSD, overall levels of anticoagulant protein decreased and negative regulation of thrombin production was reduced, causing the formation of fibrin clots and platelet aggregation. Furthermore, 9 differential proteins correlated significantly with protein S, comprising A2M, AGT, APOE, FGG, GPLD1, IGHV1-69, CFHR5, CPN2, and CA1. The biological networks suggested that the pathways of acute phase response, FXR/RXR activation, serotonin receptor signaling, and p70S6K signaling were associated with PSD, indicating an interaction disorder of inflammatory immune and lipid metabolism. The findings may contribute to knowledge of available functional molecules and biological pathways of familial PSD and help with treatment improvement. Data are available via ProteomeXchange with identifier PXD055111 and MetaboLights with reference number MTBLS2653.

Meibography signal intensity as a novel image biomarker for meibomian gland function: evidence from cross-sectional and longitudinal analyses.

Background: Meibomian gland dysfunction (MGD), one of the most common ocular surface diseases, can induce dry eye and reduce patients' quality of life. Methodological limitations have resulted in contradictory interpretations of gland function. This study sought to investigate the correlation between meibography signal intensity (SI) and meibomian gland (MG) function and to validate an MGD classification strategy based on different levels of SI. Methods: A multicenter, cross-sectional analysis was conducted on 817 eyes from 361 patients with MGD and 52 healthy controls. Additionally, 78 eyes from 39 patients with MGD who had undergone LipiFlow treatment were recruited for longitudinal analyses. The SI value was obtained via meibography using an automated analyzer, and all participants underwent ocular surface examinations. A cross-sectional analysis was performed to determine SI distribution and its relationship to clinical characteristics via a generalized estimating equation model. Longitudinal analyses were conducted on the treatment cohort using a mixed-effects model to explore the outcome in different SI levels. Results: Regression analysis revealed significant correlations between SI and lipid layer thickness (ß=0.016), meibum expressibility (ß=-0.676), meibum quality (ß=-0.251), and fluorescein-stained tear-film break-up time (FBUT) (ß=0.064) (all P values <0.001 for the above associations). Low-level SI MGD cases exhibited the most severe clinical signs, including the worst meibum expressibility (16% for level 3) and quality scores (19% for level 3), the shortest FBUT (3.82±0.13 s), and the thinnest lipid layer (65.68±2.58 nm), (all P values <0.05, respectively). Patients with medium SI showed the lowest ocular surface disease index (OSDI) value (26.64±1.06), the longest FBUT (4.56±0.08 s), and the thickest lipid layer (80.20±2.90 nm). After treatment, the high SI values reduced significantly at each follow-up point compared to baseline (all P values <0.05). The medium SI group demonstrated the greatest improvement in symptoms and signs, followed by the high SI group, and the low SI group. Conclusions: Automated measurements of SI can effectively reflect MG secretory activity. The proposed low, medium, and high SI classifications represent different functional subtypes of MGD.

Ultrasensitive Detection of Cancer Biomarkers Using Photonic-Crystal-Enhanced Single-Molecule Imaging.

The rapid and sensitive quantification of low-abundance protein markers holds immense significance in early disease diagnosis and treatment. Single-molecule fluorescence imaging exhibits very high detection sensitivity and thus has great application potential in this area. The single-molecule signal, however, is often susceptible to interference from background noise due to its inherently weak intensity. A variety of signal amplification techniques based on cascading reactions have been developed to improve the signal-to-noise ratio of single-molecule imaging. Nevertheless, the operation of these methods is typically complicated and time-consuming, which limits the clinical application. Herein, we introduce an enzyme-free, photonic-crystal-based single-molecule (PC-SM) biochip for cost-effective, time-efficient, and ultrasensitive detection of disease markers. The PC-SM biochip can enhance the signal-to-noise ratio of single molecules by nearly 3-fold compared with unamplified samples, through coupling of the single-molecule photon energy with the optical band gap of the photonic crystal. We used the PC-SM biochip to detect the low-abundance leukemia inhibitory factor in the blood of pancreatic cancer patients and healthy people and achieved a detection limit of 2.0 pg/L and an AUC of 0.9067. The method exhibits exceptional sensitivity and specificity, showing great application potential in various clinical settings.

The role of artificial intelligence in disease prediction: using ensemble model to predict disease mellitus.

The traditional complications of diabetes are well known and continue to pose a considerable burden to millions of people with diabetes mellitus (DM). With the continuous accumulation of medical data and technological advances, artificial intelligence has shown great potential and advantages in the prediction, diagnosis, and treatment of DM. When DM is diagnosed, some subjective factors and diagnostic methods of doctors will have an impact on the diagnostic results, so the use of artificial intelligence for fast and effective early prediction of DM patients can provide decision-making support to doctors and give more accurate treatment services to patients in time, which is of great clinical medical significance and practical significance. In this paper, an adaptive Stacking ensemble model is proposed based on the theory of "error-ambiguity decomposition," which can adaptively select the base classifiers from the pre-selected models. The adaptive Stacking ensemble model proposed in this paper is compared with KNN, SVM, RF, LR, DT, GBDT, XGBoost, LightGBM, CatBoost, MLP and traditional Stacking ensemble models. The results showed that the adaptive Stacking ensemble model achieved the best performance in five evaluation metrics: accuracy, precision, recall, F1 value and AUC value, which were 0.7559, 0.7286, 0.8132, 0.7686 and 0.8436. The model can effectively predict DM patients and provide a reference value for the screening and diagnosis of clinical DM.

Advances in anode current collectors with a lithiophilic gradient for lithium metal batteries.

The practical application of lithium metal batteries (LMBs) is inevitably associated with serious safety risks due to the uncontrolled growth of lithium dendrites. Thus, to inhibit the formation of lithium dendrites, many researchers have focused on constructing three-dimensional porous current collectors with a high specific surface area. However, the homogeneous structure of porous collectors does not effectively guide the deposition of lithium metal to the bottom, leading to a phenomenon known as "top-growth." Recently, the construction of 3D porous current collectors with a lithiophilic gradient has been widely reported and regarded as an effective approach to inhibit lithium top-growth, thus improving battery safety. In this review, we summarize the latest research progress on such anode current collector design strategies, including surface modification of different base materials, design of gradient structures, and field factors, emphasizing their lithium-affinity mechanism and the advantages and disadvantages of different collector designs. Finally, we provide a perspective on the future research directions and applications of gradient affinity current collectors.

Mitochondrial serine catabolism safeguards maintenance of the hematopoietic stem cell pool in homeostasis and injury.

Hematopoietic stem cells (HSCs) employ a very unique metabolic pattern to maintain themselves, while the spectrum of their metabolic adaptations remains incompletely understood. Here, we uncover a distinct and heterogeneous serine metabolism within HSCs and identify mouse HSCs as a serine auxotroph whose maintenance relies on exogenous serine and the ensuing mitochondrial serine catabolism driven by the hydroxymethyltransferase 2 (SHMT2)-methylene-tetrahydrofolate dehydrogenase 2 (MTHFD2) axis. Mitochondrial serine catabolism primarily feeds NAD(P)H generation to maintain redox balance and thereby diminishes ferroptosis susceptibility of HSCs. Dietary serine deficiency, or genetic or pharmacological inhibition of the SHMT2-MTHFD2 axis, increases ferroptosis susceptibility of HSCs, leading to impaired maintenance of the HSC pool. Moreover, exogenous serine protects HSCs from irradiation-induced myelosuppressive injury by fueling mitochondrial serine catabolism to mitigate ferroptosis. These findings reframe the canonical view of serine from a nonessential amino acid to an essential niche metabolite for HSC pool maintenance.

The "blownknee" patient's stress fracture of distal tibial component after unilateral TKA: A case report.

RATIONALE: Periprosthetic fractures (PPF) are rare complications of total knee arthroplasty (TKA). The most common PPF after TKA is supracondylar femoral fracture, which is a relatively rare complication that is usually associated with high-energy trauma, with a reported incidence ranging from 0.4 to 1.7% according to the AOANJRR. However, in TKA patients, it is rarer that the stress fracture around the tibial prosthesis occurs due to changes in the lower limb force line, increasing weight-bearing, and changes in walking gait. PATIENT CONCERNS: A 68-year-old woman visited our hospital with "both knees had aggravated pain and deformity for 8 years." TKA was performed first on the left knee and the patient was discharged within 1 week. Three months later, the patient complained of pain in the upper middle 1/3 part of the medial tibia for 2 weeks, which gradually worsened and affected weight-bearing. DIAGNOSES: Physical examination showed that the left knee joint presented varus deformity, and the right valgus deformity, which diagnosed as osteoarthritis of both knees and was so-called "blownknee". The disease was initially diagnosed as osteoarthritis of both knees on first admission and PPF of the tibia in second. INTERVENTIONS: Three operations were performed on this patient. The first was TKA of the left knee, the second was open reduction and internal fixation of the PPF of the tibia 3 months after the first operation, and the third was TKA of the right knee. OUTCOMES: Until now, the patient has had no recurrent PPF, and the fracture is healing from the last X-ray. LESSONS: Clinicians should be aware of the possibility of PPF after TKA, especially in such patients, the most preferred surgical treatment method was open reduction and internal fixation of fractures using locking plates, and if the PPF with loosened implants, Revision TKA, or megaprosthesis was the better choice.

Early Diagnostic Markers for Esophageal Squamous Cell Carcinoma: Copy Number Alteration Gene Identification and cfDNA Detection.

The high mortality rate of esophageal squamous cell carcinoma (ESCC) is exacerbated by the absence of early diagnostic markers. The pronounced heterogeneity of mutations in ESCC renders copy number alterations (CNAs) more prevalent among patients. The identification of CNA genes within esophageal squamous dysplasia (ESD), a precancerous stage of ESCC, is crucial for advancing early detection efforts. Utilization of liquid biopsies via droplet-based digital PCR (ddPCR) offers a novel strategy for detecting incipient tumor traces. This study undertook a thorough investigation of CNA profiles across ESCC development stages, integrating data from existing databases and prior investigations to pinpoint and confirm CNA markers conducive to early detection of ESCC. Targeted sequencing was employed to select potential early detection genes, followed by the establishment of prediction models for ESCC early detection using ddPCR. Our analysis revealed widespread CNAs during the ESD stage, mirroring the CNA landscape observed in ESCC. A total of 40 CNA genes were identified as highly frequent in both ESCC and ESD lesions, through a comprehensive gene-level CNA analysis encompassing ESD and ESCC tissues, ESCC cell lines, and pan-cancer data sets. Subsequent validation of 5 candidate markers via ddPCR underscored the efficacy of combined predictive models encompassing PIK3CA, SOX2, EGFR, MYC, and CCND1 in early ESCC screening, as evidenced by the area-under-the-curve values exceeding 0.92 (P < .0001) across various detection contexts. The findings highlighted the significant utility of CNA genes in the early screening of ESCC, presenting robust models that could facilitate early detection, broad-scale population screening, and adjunctive diagnosis.

Prognosis and metabolism with a Golgi apparatus-related genes-based formula in breast cancer.

The Golgi apparatus (GA), an organelle that processes, sorts, and transports proteins synthesized by the endoplasmic reticulum, is also involved in many cellular processes associated with cancer, such as angiogenesis, the innate immune response, and tumor invasion and migration. We aimed to construct a breast cancer (BC) prognosis prediction model based on GA-related genetic information to evaluate the prognosis of patients with BC more accurately than existing models and to stratify patients for clinical therapy. In this study, The Cancer Genome Atlas-breast invasive carcinoma was used as the training cohort, and the Molecular Taxonomy of Breast Cancer International Consortium cohort was used as the validation cohort. Using bioinformatics methods, we constructed a GA-related gene risk score (GRS). The GRS was used to divide BC patients into a high-GRS group and a low-GRS group, and functional analysis, survival analysis, mutation analysis, immune landscape analysis, and metabolic analysis were performed to compare the 2 groups. Finally, a nomogram was constructed for clinical application. The genes in the GRS model were mainly related to the glucose metabolism pathway, and the main mutations in the 2 groups of patients were mutations in TP53 and CHD1. The mutation rate in the high-GRS group was greater than that in the low-GRS group. The high GRS group had higher tumor immune activity glycolysis; the pentose phosphate pathway tended to be the dominant metabolic pathways in this group, while fatty acid oxidation and glutamine catabolism tended to be dominant in the low-GRS group. GA-related genes were used to construct a prediction model for BC patients and had high accuracy in predicting prognosis. The mutations associated with the GRS are mainly TP53 and CDH1. Interestingly, the GRS is correlated with glucose metabolism in terms of gene expression and functional enrichment. In summary, the role of GRS-related genes in glucose metabolism is worthy of further study.

Insights into ionizing radiation-induced bone marrow hematopoietic stem cell injury.

With the widespread application of nuclear technology across various fields, ionizing radiation-induced injuries are becoming increasingly common. The bone marrow (BM) hematopoietic tissue is a primary target organ of radiation injury. Recent researches have confirmed that ionizing radiation-induced hematopoietic dysfunction mainly results from BM hematopoietic stem cells (HSCs) injury. Additionally, disrupting and reshaping BM microenvironment is a critical factor impacting both the injury and regeneration of HSCs post radiation. However, the regulatory mechanisms of ionizing radiation injury to BM HSCs and their microenvironment remain poorly understood, and prevention and treatment of radiation injury remain the focus and difficulty in radiation medicine research. In this review, we aim to summarize the effects and mechanisms of ionizing radiation-induced injury to BM HSCs and microenvironment, thereby enhancing our understanding of ionizing radiation-induced hematopoietic injury and providing insights for its prevention and treatment in the future.

Post-marketing safety concern of PI3K inhibitors in the cancer therapies: an 8-year disproportionality analysis from the FDA adverse event reporting system.

BACKGROUND: ThePhosphoinositide 3-kinases (PI3Ks) family plays a crucial role intumorigenesis. Alpelisib (inhibiting PI3Kα), copanlisib (inhibiting PI3Kα andPI3Kδ), duvelisib (inhibiting PI3Kδ and PI3Kγ), and idelalisib (inhibitingPI3Kδ) were developed to target the PI3K pathway. However, the toxicity limitstheir application to some extent. It's necessary to investigate the adverseeffects (AEs) of these inhibitors. RESEARCH DESIGNAND METHODS: We conducted acomparative analysis of the safety signals of AEs in PI3K inhibitors usingdisproportionality analysis in the FDA Adverse Event Reporting System database(FAERS). RESULTS: Our studyidentified significant safety signals for metabolic disorders with all PI3Kinhibitors. Notable safety signals for gastrointestinal disorders were observedwith most PI3K inhibitors, with the exception of copanlisib. Common AEs shared amongall PI3K inhibitors included colitis and dehydration. Alpelisib displayedunique AEs associated with metabolic disorders, whereas copanlisib exhibitedidiosyncratic AEs linked to cardiac and vascular disorders. Stevens-Johnsonsyndrome emerged as a common severe adverse event (SAE) among alpelisib,copanlisib, and idelalisib, while febrile neutropenia was prevalent amongcopanlisib, duvelisib, and idelalisib. Intestinal perforation was solelyassociated with alpelisib. CONCLUSIONS: The safety profiles of the five PI3K inhibitorsvary concerning adverse events. These findings could guide drug selection andinform future prospective research.

Age­integrated breast imaging reporting and data system assessment model to improve the accuracy of breast cancer diagnosis.

Early diagnosis is an effective strategy for decreasing breast cancer mortality. Ultrasonography is one of the most predominant imaging modalities for breast cancer owing to its convenience and non-invasiveness. The present study aimed to develop a model that integrates age with Breast Imaging Reporting and Data System (BI-RADS) lexicon to improve diagnostic accuracy of ultrasonography in breast cancer. This retrospective study comprised two cohorts: A training cohort with 975 female patients from Renmin Hospital of Wuhan University (Wuhan, China) and a validation cohort with 500 female patients from Maternal and Child Health Hospital of Hubei Province (Wuhan, China). Logistic regression was used to construct a model combining BI-RADS score with age and to determine the age-based prevalence of breast cancer to predict a cut-off age. The model that integrated age with BI-RADS scores demonstrated the best performance compared with models based solely on age or BI-RADS scores, with an area under the curve (AUC) of 0.872 (95% CI: 0.850-0.894, P<0.001). Furthermore, among participants aged <30 years, the prevalence of breast cancer was lower than the lower limit of the reference range (2%) for BI-RADS subcategory 4A lesions but within the reference range for BI-RADS category 3 lesions, as indicated by linear regression analysis. Therefore, it is recommended that management for this subset of participants are categorized as BI-RADS category 3, meaning that biopsies typically indicated could be replaced with short-term follow-up. In conclusion, the integrated assessment model based on age and BI-RADS may enhance accuracy of ultrasonography in diagnosing breast lesions and young patients with BI-RADS subcategory 4A lesions may be exempted from biopsy.

A non-invasive artificial intelligence model for identifying axillary pathological complete response to neoadjuvant chemotherapy in breast cancer: a secondary analysis to multicenter clinical trial.

BACKGROUND: This study aims to develop a stacking model for accurately predicting axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) using longitudinal MRI in breast cancer. METHODS: We included patients with node-positive breast cancer who received NAC following surgery from January 2012 to June 2022. We collected MRIs before and after NAC, and extracted radiomics features from the tumour, peritumour, and ALN regions. The Mann-Whitney U test, least absolute shrinkage and selection operator, and Boruta algorithm were used to select features. We utilised machine learning techniques to develop three single-modality models and a stacking model for predicting ALN response to NAC. RESULTS: This study consisted of a training cohort (n = 277), three external validation cohorts (n = 313, 164, and 318), and a prospective cohort (n = 81). Among the 1153 patients, 60.62% achieved ypN0. The stacking model achieved excellent AUCs of 0.926, 0.874, and 0.862 in the training, external validation, and prospective cohort, respectively. It also showed lower false-negative rates (FNRs) compared to radiologists, with rates of 14.40%, 20.85%, and 18.18% (radiologists: 40.80%, 50.49%, and 63.64%) in three cohorts. Additionally, there was a significant difference in disease-free survival between high-risk and low-risk groups (p < 0.05). CONCLUSIONS: The stacking model can accurately predict ALN status after NAC in breast cancer, showing a lower false-negative rate than radiologists. TRIAL REGISTRATION NUMBER: The clinical trial numbers were NCT03154749 and NCT04858529.

Understanding the dynamics of TKI-induced changes in the tumor immune microenvironment for improved therapeutic effect.

BACKGROUND: The dynamic interplay between tyrosine kinase inhibitors (TKIs) and the tumor immune microenvironment (TME) plays a crucial role in the therapeutic trajectory of non-small cell lung cancer (NSCLC). Understanding the functional dynamics and resistance mechanisms of TKIs is essential for advancing the treatment of NSCLC. METHODS: This study assessed the effects of short-term and long-term TKI treatments on the TME in NSCLC, particularly targeting epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) mutations. We analyzed changes in immune cell composition, cytokine profiles, and key proteins involved in immune evasion, such as laminin subunit γ-2 (LAMC2). We also explored the use of aspirin as an adjunct therapy to modulate the TME and counteract TKI resistance. RESULTS: Short-term TKI treatment enhanced T cell-mediated tumor clearance, reduced immunosuppressive M2 macrophage infiltration, and downregulated LAMC2 expression. Conversely, long-term TKI treatment fostered an immunosuppressive TME, contributing to drug resistance and promoting immune escape. Differential responses were observed among various oncogenic mutations, with ALK-targeted therapies eliciting a stronger antitumor immune response compared with EGFR-targeted therapies. Notably, we found that aspirin has potential in overcoming TKI resistance by modulating the TME and enhancing T cell-mediated tumor clearance. CONCLUSIONS: These findings offer new insights into the dynamics of TKI-induced changes in the TME, improving our understanding of NSCLC challenges. The study underscores the critical role of the TME in TKI resistance and suggests that adjunct therapies, like aspirin, may provide new strategies to enhance TKI efficacy and overcome resistance.

Comparative proteomic analyses to investigate premature browning in high­oxygen modified atmosphere packaged beef patties.

This study compared the proteomics of beef patties under high­oxygen modified atmosphere packaging (HiOx-MAP) and vacuum packaging (VP) during heating. The color and oxidation stability of fresh patties, and myoglobin denaturation of cooked patties were also measured. The results suggested that HiOx-MAP patties contained more oxymyoglobin in fresh meat and had higher myoglobin denaturation during heating than VP patties, resulting in premature browning (PMB) during cooking. Proteomic analysis found that the overabundance of proteasome subunit beta type-2 (PSMB2) and peroxiredoxin-2 (PRDX2) in HiOx-55 °C, which can remove the damaged proteins and inhibit oxidation respectively, are of benefit to meat color stability during storage, however, this was still insufficient to inhibit the occurrence of PMB during cooking. The high abundance of lamin B1 (LMNB1) in VP-55 °C can maintain the stability of meat color. This research provides greater understanding, based on proteomic perspectives, of the molecular mechanism of PMB.

Effects of multi-walled carbon nanotubes and halloysite nanotubes on plasma lipid profiles and autophagic lipolysis pathways in mouse aortas and hearts.

Multi-walled carbon nanotubes (MWCNTs) and halloysite nanotubes (HNTs) are widely used tubular-structured nanomaterials (NMs), but their cardiovascular effects are not clear. This study compared the effects of MWCNTs and HNTs on lipid profiles in mouse plasma and gene expression profiles in aortas and hearts. Mice were intravenously injected with 50 µg NMs, once a day, for 5 days. Then, the plasma was collected for lipidomics analysis, and aortas and hearts were collected for RNA-sequencing analysis. While MWCNTs or HNTs did not induce obvious pathological changes in aortas or hearts, the lipid profiles in mouse plasma were altered. Further analysis revealed that MWCNTs more effectively upregulated sphingolipids and sterol lipids, whereas HNTs more effectively upregulated glycerophospholipids and fatty acyls. Consistently, RNA-sequencing data indicated that MWCNTs and HNTs altered signaling pathways related with lipid synthesis and metabolism, as well as those related with endoplasmic reticulum, lysosomes and autophagy, more significantly in aortas than in hearts. We further verified the changes of proteins involved in autophagic lipolysis, that MWCNTs were more effectively to suppress the autophagic biomarker LC3, whereas HNTs were more effectively to affect lipid metabolism proteins. These results may provide novel understanding about the influences of MWCNTs and HNTs on lipid profiles and lipid signaling pathways in cardiovascular systems. Importantly, previous studies considered HNTs as biocompatible materials, but the results from this study suggested that both MWCNTs and HNTs were capable to affect lipid profiles and autophagic lipolysis pathways in cardiovascular systems, although their exact influences were different.