Colorectal cancer (CRC) is the third most commonly diagnosed malignancy and the second leading cause of cancer-related mortality worldwide. Despite therapeutic advancements over recent decades, the prognosis for patients with metastatic CRC (mCRC) remains poor. Approximately 2%-4% of mCRC cases exhibit human epidermal growth factor receptor 2 (HER2) amplification or overexpression, defining a distinct molecular subtype. This HER2-positive status is strongly associated with primary resistance to anti-epidermal growth factor receptor (EGFR) therapies, which are the standard of care for patients with RAS wild-type tumors. Beyond its well-established role in breast and gastric cancers, HER2 has emerged as a pivotal biomarker and actionable therapeutic target in mCRC. However, selecting appropriate treatment strategies remains challenging due to patient heterogeneity and diverse molecular subtypes. This review systematically summarizes the molecular biology, diagnostic strategies, and advances in targeted therapies for HER2-positive mCRC. On the diagnostic front, we discuss the applications of immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), next-generation sequencing (NGS), and circulating tumor DNA (ctDNA) detection technologies. We highlight discrepancies in diagnostic criteria across key clinical trials—such as HERACLES, DESTINY, and MOUNTAINEER—underscoring the urgent need for standardized, CRC-specific definitions to ensure consistent patient selection and comparability of efficacy data across studies. Although NGS enables comprehensive genomic profiling, its cost-effectiveness relative to traditional methods must be carefully considered. Therapeutically, we summarize clinical trial data for HER2-directed agents, including tyrosine kinase inhibitors (TKIs) such as tucatinib and lapatinib, monoclonal antibodies like trastuzumab, bispecific antibodies, and antibody-drug conjugates (ADCs) such as trastuzumab deruxtecan. We review dual-targeting strategies and note recent FDA approvals that represent significant milestones in second-line treatment. Additionally, we explore the potential of combining immune checkpoint inhibitors with HER2-targeted therapies to enhance antitumor immunity through mechanisms including antibody-dependent cellular cytotoxicity (ADCC) and modulation of the tumor microenvironment. ADCs enable precise delivery of cytotoxic payloads, reducing off-target toxicity while effectively inhibiting oncogenic pathways. A substantial portion of this review is dedicated to dissecting the molecular mechanisms underlying primary and acquired resistance to HER2-targeted therapies—persistent challenges that limit clinical benefit. These mechanisms include reactivation of downstream signaling pathways such as PI3K/AKT/mTOR and MAPK, concurrent mutations in genes like KRAS or BRAF, and alterations in HER2 expression that compromise treatment efficacy. For instance, specific HER2 mutations (e.g., L755S) can reduce drug binding affinity, while ctDNA monitoring facilitates early detection of emerging resistance clones during disease progression, thereby enabling timely therapeutic adjustments. Tumor heterogeneity and dynamic interactions with the microenvironment further complicate resistance patterns observed in clinical practice. HER2-targeted therapy represents a new frontier in precision oncology for mCRC, offering renewed hope for improving patient outcomes. Realizing this potential will require continued optimization of diagnostic algorithms and treatment workflows. Future efforts must focus on overcoming resistance, validating liquid biopsy approaches for dynamic monitoring, and establishing unified clinical guidelines. HER2 has become an essential biomarker for stratifying mCRC patients beyond traditional RAS and BRAF status, underscoring the shift from empiric treatment to biomarker-driven precision medicine. International, multidisciplinary collaboration will be critical to validate emerging biomarkers and refine treatment algorithms globally.

Objective: To develop a prediction model for mild cognitive impairment (MCI) risk among the elderly, so as to provide a tool for MCI early screening. Methods : From July 2022 to September 2024, a multi-stage stratified random cluster sampling method was used to recruit permanent residents aged ≥65 years from the Xinjiang Uygur Autonomous Region as study participants. Data on sociodemographic characteristics, nutritional status, body composition indices, bone mineral density, and handgrip strength were collected through questionnaires and physical examinations. Sarcopenia was defined based on appendicular skeletal muscle index and handgrip strength. MCI was assessed using the Mini-Mental State Examination, with adjustments for educational level. Participants were randomly divided into a training set and a validation set in a 7∶3 ratio. LASSO regression and multivariable logistic regression models were employed to screen for predictors and construct an MCI risk prediction model. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: A total of 1 641 participants were surveyed, including 755 males (46.01%) and 886 females (53.99%). The majority of participants were aged 65-<75 years, comprising 1 154 individuals (70.32%). MCI was detected in 517 participants, corresponding to a detection rate of 31.51%. Resultsfrom LASSO regression and multivariate logistic regression analysis showed that residence (rural, OR = 2.323, 95% CI: 1.682-3.210), age (75-<85 years, OR = 1.405, 95% CI: 1.019-1.937; ≥85 years, OR = 3.655, 95% CI: 1.696-7.875), educational level (primary school, OR = 0.341, 95% CI: 0.247-0.472; junior high school, OR = 0.255, 95% CI: 0.160-0.408; high school, OR = 0.286, 95% CI: 0.154-0.531; bachelor's degree or above, OR = 0.120, 95% CI: 0.041-0.351), history of alcohol consumption (yes, OR = 3.216, 95% CI: 2.164-4.779), risk of malnutrition (yes, OR = 1.464, 95% CI: 1.064-2.014), sarcopenia (yes, OR = 3.197, 95% CI: 2.332-4.385), and waist-to-hip ratio (abnormal, OR = 1.540, 95% CI: 1.159-2.048) were identified as predictive factors for MCI among the elderly. In the training set, the area under the ROC curve, sensitivity, and specificity were 0.788, 0.719, and 0.712, respectively. In the validation set, the corresponding values were 0.784, 0.913, and 0.542, respectively. DCA demonstrated that the model provided a higher clinical net benefit for predicting MCI risk when the risk threshold probability ranged from 0.124 to 0.764. Conclusion The prediction model developed in this study demonstrates good discriminative ability and clinical utility, indicating its substantial value for predicting the MCI risk among the elderly.

ObjectiveTo investigate the mechanism by which activation of α7nicotinic acetylcholine receptors （α7nAChR） optimizes brown adipose tissue （BAT） thermogenesis in obese mice. MethodsObesity was induced in C57BL/6J mice via a high-fat diet. Fifty 8-week-old mice were randomly assigned to five groups： low-fat diet （Control）， high-fat diet （HFD）， high-fat diet plus a β3-adrenergic receptor agonist （HFD+β3）， high-fat diet plus a β3-adrenergic receptor agonist and an α7nAChR selective agonist （HFD+β3+GTS-21）， and high-fat diet plus a β3-adrenergic receptor agonist and an α7nAChR selective antagonist （HFD+β3+α-BGT）. Haematoxylin and eosin （HE） staining was used to evaluate BAT morphology. Transmission electron microscopy was performed to assess mitochondrial number and lipid droplet morphology in adipocytes. ELISA was used to measure levels of tumour necrosis factor-α （TNF-α）， interleukin（IL）-1β，IL-10， transforming growth factor-β （TGF-β）， cyclic adenosine monophosphate （cAMP）， and norepinephrine （NE）. RT-qPCR was conducted to determine mRNA expression levels of vascular endothelial growth factor A （VEGF-A）， nitric oxide synthase 2 （NOS2）， arginase 1 （Arg1）， uncoupling protein 1 （UCP1）， PR domain-containing protein 16 （PRDM16）， and peroxisome proliferator-activated receptor γ coactivator-1α （PGC-1α） in BAT. Immunohistochemistry was used to detect macrophage markers （CD31， CD86， and CD206）. Protein expression levels of UCP1， α7nAChR， nuclear factor-κB p65（NF-κB p65）， phosphorylated Janus kinase 2 （p-JAK2）， and phosphorylated signal transducer and activator of transcription 3 （p-STAT3） were analyzed by Western blot. ResultsCompared with the Control group， the HFD group showed enlarged lipid droplets and reduced mitochondrial numbers in adipocytes， accompanied by increased TNF-α and IL-1β and decreased IL-10， TGF-β， Arg1， and VEGF-A （all P<0.01）. Compared with the HFD+β3 group， the HFD+β3+GTS-21 group showed a smaller lipid droplet area and a higher mitochondrial number， along with reduced levels of pro-inflammatory factors， NOS2， and NF-κB p65， and increased levels of anti-inflammatory factors， Arg1， and phosphorylation of JAK2 and STAT3 （all P<0.01）. ConclusionActivation of α7nAChR in combination with a β3-adrenergic receptor agonist effectively enhances thermogenesis， alleviates local adipose tissue hypoxia， and shifts the local inflammatory phenotype toward an M2-like state， thereby reducing inflammation in brown adipose tissue and improving its thermogenic capacity.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Background Under the background of global warming, research on association between ambient temperature and risk of injury is needed. Objective To examine the effect of temperature on injury in Bao'an district, Shenzhen and identify the sensitive population, thereby providing a scientific basis for formulating prevention and control strategies and measures of injury. Methods The injury reports from the Injury Surveillance System and the meteorological data of Bao'an District between 2018 to 2022 were collected. The meteorological data were sourced from the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) land reanalysis data. Based on time-stratified case-crossover design, conditional logistic regression combined with distributed lag nonlinear model was used to evaluate the exposure-response association between ambient temperature and injury. The stratified analyses were further conducted by gender, age, and causes of injury. Results A total of 156205 injury cases were collected from the injury surveillance sentinel hospitals in Bao'an District of Shenzhen from 2018 to 2022, and the median of daily average temperature during the same period was 20.0 ℃. The exposure-response curve showed that the risk of injury was positively correlated with temperature. The linearized analysis revealed that each 1°C increase in temperature was associated with a 1.05% (95%CI: 0.68%, 1.42%) rise in injury risk (ER). Notably, the effect was greater in females (ER=1.31%, 95%CI: 0.67%, 1.94%) than males (ER=0.92%, 95%CI: 0.47%, 1.37%). Among age groups, adults ＞60 years faced the highest risk (ER=1.91%, 95%CI: −0.36%, 4.24%). The top three temperature-associated injury risks were sharp instrument injuries (ER=2.19%, 95%CI: 1.16%, 3.22%), animal injuries (ER=1.71%, 95%CI: 0.86%, 2.56%), and blunt injuries (ER=071%, 95%CI: −0.08%, 1.51%). The impact of temperature on unintentional injuries (ER=1.11%, 95%CI: 0.72%, 1.49%) was higher than that on intentional injuries (ER=0.43%, 95%CI: −0.85%, 1.72%). Severe injuries (ER=2.20%, 95%CI: −3.09%, 7.77%) were more affected by temperature than mild injuries (ER=1.00%, 95%CI: 0.58%, 1.43%) and moderate injuries (ER=1.15%, 95%CI: 0.42%, 1.89%). Conclusion The increase in ambient temperature associates with injury occurrence, and the impact of temperature exhibits obvious heterogeneity among different populations, indicating that targeted intervention measures should be taken for different populations and types of injuries.

OBJECTIVES: Lymph node metastasis in papillary thyroid cancer (PTC) is closely associated with tumor recurrence and patient survival. However, current technologies have limited sensitivity in detecting occult cervical lymph node metastases. Identifying accurate molecular markers for predicting PTC metastasis holds significant clinical value. This study aims to analyze WNT10A expression in PTC and its clinical significance, and to explore the role of WNT10A gene knockdown in PTC cell proliferation, invasion, and metastasis. METHODS: The expression of WNT10A in thyroid carcinoma was analyzed using the Gene Expression Profiling Interactive Analysis (GEPIA) and University of Alabama at Birminghara Cancer data analysis Portal (UALCAN) databases. Real-time RT-PCR was used to measure WNT10A mRNA levels in tumor and adjacent normal tissues from 32 PTC patients. Immunohistochemistry was conducted on 158 PTC specimens to assess WNT10A protein expression and its correlation with clinicopathological features. In vitro experiments were performed using K1 and TPC-1 cell lines. Cell proliferation was assessed using the Celigo system and methyl thiazolyl tetrazolium (MTT) assays; apoptosis was measured via flow cytometry; invasion and metastasis were evaluated using scratch and Transwell assays. A xenograft model was established in nude mice to observe tumor growth, and tumor weight and volume were compared between cell lines. Differentially expressed genes regulated by WNT10A were identified via mRNA sequencing, followed by Gene Ontology (GO) and ingenuity pathway analysis (IPA). Real-time PCR and Western blotting were used to validate the effects of WNT10A on key downstream mRNA and protein in the Tec kinase signaling pathway. RESULTS: WNT10A mRNA expression was significantly higher in thyroid cancer tissues compared to adjacent normal tissues according to GEPIA and UALCAN (both P<0.01). The real-time RT-PCR result showed that WNT10A mRNA expression in PTC tissues was high than that in adjacent tissues (P<0.01). Immunohistochemistry revealed significantly higher WNT10A protein expression in PTC tissues compared to adjacent tissues (P<0.01), and its expression correlated with multifocality, extrathyroidal invasion, and lymph node metastasis. WNT10A knockdown significantly inhibited proliferation, altered cell cycle distribution, and increased apoptosis in K1 and TPC-1 cells (all P<0.01). WNT10A silencing also reduced migration and invasion abilities in both cell lines. In vivo, WNT10A knockdown in TPC-1 cells suppressed tumor formation in nude mice. GO analysis and IPA suggested that the Tec kinase signaling pathway was a key downstream target of WNT10A. RT-PCR and Western blotting confirmed that WNT10A knockdown downregulated the expression of key genes (STAT3, MAPK8, TNFRSF21, and AKT2) in this pathway. CONCLUSIONS WNT10A is highly expressed in PTC and is associated with tumor proliferation, invasion, and metastasis. Its tumor-promoting effects may be mediated through suppression of the Tec kinase signaling pathway.
Humans ; Cell Proliferation ; Thyroid Cancer, Papillary/pathology* ; Thyroid Neoplasms/metabolism* ; Animals ; Wnt Proteins/metabolism* ; Neoplasm Invasiveness ; Mice ; Cell Line, Tumor ; Female ; Male ; Mice, Nude ; Apoptosis ; Lymphatic Metastasis ; Middle Aged ; Cell Movement ; Adult

Ovarian tumor (OT) is the most lethal form of gynecologic malignancy, with minimal improvements in patient outcomes over the past several decades. Metastasis is the leading cause of ovarian cancer-related deaths, yet the underlying mechanisms remain poorly understood. Psychological stress is known to activate the glucocorticoid receptor (NR3C1), a factor associated with poor prognosis in OT patients. However, the precise mechanisms linking NR3C1 signaling and metastasis have yet to be fully elucidated. In this study, we demonstrate that chronic restraint stress accelerates epithelial-mesenchymal transition (EMT) and metastasis in OT through an NR3C1-dependent mechanism involving nuclear protein 1 (NUPR1). Mechanistically, NR3C1 directly regulates the transcription of NUPR1, which in turn increases the expression of snail family transcriptional repressor 2 (SNAI2), a key driver of EMT. Clinically, elevated NR3C1 positively correlates with NUPR1 expression in OT patients, and both are positively associated with poorer prognosis. Overall, our study identified the NR3C1/NUPR1 axis as a critical regulatory pathway in psychological stress-induced OT metastasis, suggesting a potential therapeutic target for intervention in OT metastasis.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Deactivation of the mitochondrial pyruvate dehydrogenase complex (PDC) is important for the metabolic switching of cancer cell from oxidative phosphorylation to aerobic glycolysis. Studies examining PDC activity regulation have mainly focused on the phosphorylation of pyruvate dehydrogenase (E1), leaving other post-translational modifications largely unexplored. Here, we demonstrate that the acetylation of Lys 488 of pyruvate dehydrogenase complex component X (PDHX) commonly occurs in hepatocellular carcinoma, disrupting PDC assembly and contributing to lactate-driven epigenetic control of gene expression. PDHX, an E3-binding protein in the PDC, is acetylated by the p300 at Lys 488, impeding the interaction between PDHX and dihydrolipoyl transacetylase (E2), thereby disrupting PDC assembly to inhibit its activation. PDC disruption results in the conversion of most glucose to lactate, contributing to the aerobic glycolysis and H3K56 lactylation-mediated gene expression, facilitating tumor progression. These findings highlight a previously unrecognized role of PDHX acetylation in regulating PDC assembly and activity, linking PDHX Lys 488 acetylation and histone lactylation during hepatocellular carcinoma progression and providing a potential biomarker and therapeutic target for further development.
Humans ; Acetylation ; Carcinoma, Hepatocellular/genetics* ; Liver Neoplasms/genetics* ; Pyruvate Dehydrogenase Complex/genetics* ; Gene Expression Regulation, Neoplastic ; Animals ; Mice ; Cell Line, Tumor ; Protein Processing, Post-Translational ; Histones/metabolism* ; Disease Progression