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.

Osteoarthritis (OA), a highly prevalent degenerative joint disease worldwide, is defined by articular cartilage degradation, abnormal bone remodeling, and persistent chronic inflammation. It severely compromises patients’ quality of life, and currently, there is no radical cure. Abnormal mechanical stress is widely regarded as a core driver of OA pathogenesis, and the exploration of mechanical signal perception and transduction mechanisms has become crucial for deciphering OA’s pathophysiological processes. Piezo1, a key mechanosensitive cation channel belonging to the Piezo protein family, has recently gained significant attention due to its pivotal role in mediating cellular responses to mechanical stimuli in joint tissues. This review systematically examines Piezo1’s expression patterns, regulatory mechanisms, and pathological functions in OA, with a particular focus on its dual roles in modulating chondrocyte homeostasis and bone metabolism disorders, while also delving into the underlying molecular signaling pathways and potential therapeutic implications. Piezo1, consisting of approximately 2 500 amino acids and forming a unique trimeric propeller-like structure, is widely expressed in chondrocytes, osteocytes, mesenchymal stem cells, and synovial cells. It exhibits permeability to cations such as Ca²⁺, K⁺, and Na⁺, and directly responds to membrane tension changes induced by mechanical stimuli like fluid shear stress and mechanical overload. In OA patients and animal models, Piezo1 expression is significantly upregulated, especially in cartilage regions subjected to abnormal mechanical stress (e.g., human temporomandibular joint cartilage). This overexpression is closely associated with aggravated cartilage degeneration, increased chondrocyte apoptosis, accelerated cellular senescence, and intensified inflammatory responses. Mechanical overload and pro-inflammatory cytokines (e.g., IL-1β) are key inducers of Piezo1 upregulation: IL-1β activates the PI3K/AKT/mTOR signaling pathway to enhance Piezo1 expression, forming a pathogenic positive feedback loop that inhibits chondrocyte autophagy, promotes apoptosis, and further accelerates joint degeneration. Mechanistically, Piezo1 mediates OA progression through multiple interconnected pathways. When activated by mechanical stress, Piezo1 triggers excessive Ca²⁺ influx, leading to endoplasmic reticulum stress (ERS) and mitochondrial dysfunction, which directly induce chondrocyte apoptosis. This process involves the activation of downstream signaling cascades such as cGAS-STING and YAP-MMP13/ADAMTS5. YAP, a transcriptional regulator, upregulates the expression of matrix metalloproteinase 13 (MMP13) and aggrecanase (ADAMTS5), thereby accelerating cartilage matrix degradation. Additionally, Piezo1-driven Ca²⁺ overload promotes the accumulation of reactive oxygen species (ROS) and upregulates senescence markers (p16 and p21), accelerating chondrocyte senescence via the p38MAPK and NF-κB pathways. Senescent chondrocytes secrete senescence-associated secretory phenotype (SASP) factors (e.g., IL-6, IL-1β), further amplifying joint inflammation. In terms of bone metabolism, Piezo1 maintains joint homeostasis by promoting the differentiation of fibrocartilage stem cells into chondrocytes and balancing bone formation and resorption through regulating the FoxC1/YAP axis and RANKL/OPG ratio. Therapeutically, targeting Piezo1 shows promising potential. Preclinical studies have demonstrated that Piezo1 inhibitors (e.g., GsMTx4) can reduce joint damage and alleviate pain in OA mice. Simultaneously, siRNA-mediated co-silencing of Piezo1 and TRPV4 (another mechanosensitive channel) decreases intracellular Ca²⁺ concentration, inhibits chondrocyte apoptosis, and promotes cartilage repair. Conditional knockout of Piezo1 using Gdf5-Cre transgenic mice alleviates cartilage degeneration in post-traumatic OA models by downregulating MMP13 and ADAMTS5 expression. Despite existing challenges, such as off-target effects of inhibitors, inefficient local drug delivery, and interindividual genetic variability, strategies like developing selective Piezo1 antagonists, optimizing targeted nanocarriers, and combining Piezo1-targeted therapy with physical therapy provide viable avenues for clinical translation. The authors propose that Piezo1 serves as a critical therapeutic target for OA, and future research should focus on deciphering its context-dependent regulatory networks, developing tissue-specific intervention strategies, and validating their efficacy and safety in clinical trials to address the unmet medical needs of OA patients.

ObjectiveMigraine is a leading neurological disorder and the fourth most common cause of years lived with disability worldwide, affecting nearly 116 million individuals. Although pharmacological treatments are available, their efficacy is often limited by side effects and variable response rates. Repetitive transcranial magnetic stimulation (rTMS) over the dorsolateral prefrontal cortex (DLPFC) offers a safe, non-invasive alternative for migraine management. However, the neurophysiological mechanisms, particularly how rTMS modulates local cortical excitability and distributed pain-related circuits, remain poorly understood. Elucidating these mechanisms is essential for optimizing treatment protocols and improving clinical outcomes. MethodsThis study employed concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) to investigate neuroplastic and neurocircuitry mechanisms of DLPFC-rTMS in migraine. Study 1 compared 30 migraineurs and 28 healthy controls to identify abnormalities in TMS-evoked potentials (TEPs) and significant current density (SCD) within sensory-discriminative regions including the primary somatosensory cortex (S1) and posterior insula (pINS), cognitive-affective regions including the anterior insula (aINS) and midcingulate cortex (MCC), and a descending modulatory region, the periaqueductal gray (PAG). Study 2 used a single-blind, crossover, sham-controlled design in 34 healthy participants. Each participant received both active (10 Hz, 80% RMT, 1 500 pulses) and sham DLPFC-rTMS in counterbalanced order. TMS-EEG and cold pain tolerance were assessed before and after each session. ResultsIn Study 1, migraineurs showed a significantly less negative N120 amplitude compared to healthy controls (P=0.027, Cohen’s d=0.60), indicating local intracortical disinhibition. No group differences were observed for N40, P60, or P180 components. At the source level, migraineurs exhibited significantly higher SCD in the S1, pINS, aINS, and MCC (allQ<0.05), but not in the ventroposterior thalamus (vpTHAL), mediodorsal thalamus (mdTHAL), or PAG. In Study 2, active rTMS significantly reduced SCD from pre- to post-stimulation in the S1, aINS, and MCC (all Q<0.05). Sham stimulation also reduced SCD in the S1 (Q<0.05) but not in the aINS or MCC. Although no significant group-level analgesic effect was observed between active and sham conditions (P=0.107), correlation analyses revealed that greater SCD reductions in the S1 and MCC were significantly associated with higher post-rTMS pain tolerance (R=-0.487 and -0.495, both Q<0.01) and larger improvements in pain tolerance(R=-0.487 and -0.451, both Q<0.05). No such correlations were found following sham stimulation, suggesting that the behavioural relevance of neural changes is specific to active rTMS. ConclusionThis study provides novel evidence that migraineurs exhibit both local neuroplastic abnormalities (reduced N120 amplitude) and hyperactivity in key pain-processing regions (S1, pINS, aINS, MCC). A single session of DLPFC-rTMS reduced hyperactivity in the aINS, MCC, and S1. Notably, greater reductions in the S1 and MCC were associated with improved pain tolerance. These findings identify distinct cortical circuitries, particularly within the cognitive-affective pain network, that may serve as potential biomarkers for optimizing rTMS treatment in migraine and other chronic pain conditions. Future studies should validate these results in patient populations experiencing spontaneous migraine attacks and explore multi-session or accelerated rTMS protocols.

Testicular radiation injury is a structural and functional abnormality of the testes caused directly or indirectly by radiation, which disrupts spermatogenesis and compromises male fertility. The development of effective preventive and therapeutic interventions is essential because of the high prevalence of this condition in clinical settings and its profound effect on patients′ reproductive health and overall well-being. The concept of "the struggle between vital qi and pathogen" is first seen in the Treatise on Cold Pathogenic Diseases. It denotes the dynamic struggle between vital and pathogenic qi. The occurrence, development, and sequelae of all diseases reflect this ongoing conflict. In this context, this study defines the "vital qi" of the testis as its capacity to generate and preserve the essence of reproduction and to resist damage. The pathogenic qi associated with testicular radiation injury is categorized into two types: ionizing poison and retaining evil. The pathogenesis of testicular radiation damage is delineated into three stages by integrating the characteristics of vital and pathogenic qi: the injury, adhesion, and recovery phases. Based on the theoretical framework advanced by this study, the therapeutic approach for testicular radiation injury should adhere to the fundamental principle of strengthening vital qi and eliminating pathogenic factors. Although the primary focus of treatment should be on strengthening vital qi, it should also be complemented by strategies to eliminate pathogenic influences. This paper aims to provide a novel perspective and strategic approach to the traditional Chinese medicine diagnosis, prevention, and treatment of testicular radiation injury. By elucidating the process of testicular radiation injury and its corresponding treatment principles, it seeks to offer valuable insights for clinical practice.

Objective To investigate the levels of gross α and gross β activities in different water types within a 40-kilometer radius around the Zhangzhou Nuclear Power Plant prior to its operation. Methods In 2018, drinking water samples were collected from the area surrounding the nuclear power plant during both the wet and dry seasons, including source water, treated water, tap water, and well water. The gross α and gross β activity concentrations were measured using a low-background α/β counter, followed by statistical analysis. Results A total of 80 water samples from different sources around the Zhangzhou Nuclear Power Plant were collected. The average gross α and gross β activity concentrations during the wet season were (0.110 ± 0.036) Bq/L and (0.643 ± 0.028) Bq/L, respectively, while those during the dry season were (0.124 ± 0.032) Bq/L and (0.624 ± 0.026) Bq/L, respectively. There were no significant differences in the gross α and gross β activity concentrations between the wet and dry seasons for the overall sample set (P > 0.05). However, there were statistically significant differences in the gross α and gross β activity concentrations between the wet and dry seasons for source water and well water (Z_wet = −2.005, −2.123; Z_dry = −1.943, −3.090; P < 0.05). Conclusion The radioactivity levels in different water types within various ranges around the Zhangzhou Nuclear Power Plant before its operation were determined. The measured activity concentrations were at the same level as those from previous investigations in other regions of Fujian Province.

Hepatocellular carcinoma （HCC） is a malignant tumor with high incidence and mortality rates worldwide. Recent studies have shown that neutrophil extracellular traps （NETs） play an important role in the development， progression， and immune escape of HCC. NETs are released by neutrophils and mainly consist of DNA， histones， and antimicrobial molecules， and in addition to immune defense， they are also involved in the initiation， metastasis， and thrombosis of HCC. This article elaborates on the formation and regulatory mechanisms of NETs， explores their potential mechanisms in the initiation， metastasis， immune escape， and thrombosis of HCC， and discusses the prospect of NETs as a target for the diagnosis and treatment of HCC， in order to provide new ideas for the precise treatment of HCC in the future and promote the early diagnosis and effective treatment of HCC.

Objective:To explore behavioral and electrophysiological differences in risky decision-making between depressed patients with and without suicidal ideation.Methods:A total of 61 patients with first-episode untreated depression were enrolled in the depression clinic of Nanjing Brain Hospital from September 2023 to January 2024, which were divided into the suicidal ideation group( n=32) and the non-suicidal ideation group ( n=29).At the same time, healthy controls matched with sex, age and years of education were recruited from the community( n=36).The event-related potentials (ERP) of the participants were detected, and the amplitude and latency of feedback related negative waves (FRN) and P300 during the feedback phase under Iowa gambling task (IGT) were recorded. Statistical analysis was performed using SPSS 26.0 software.The inter-and intra-group differences of ERP indexes were compared using two-way ANOVA, and Spearman correlation analysis was conducted to examine the relationship between ERP indexes and scores of the Beck scale for suicidal ideation. Results:(1)Compared with healthy controls, depressed patients with and without suicidal ideation had both lower net scores in IGT (both P<0.05).(2)When comparing the mean FRN amplitude under different feedback types among the three groups, the main effect of feedback type ( F=8.799, P=0.004), the main effect of group ( F=6.396, P=0.002) and the interaction effect ( F=4.200, P=0.018)were all significant. Under gain feedback conditions, the mean FRN amplitude was lower in both depressed groups compared with healthy controls (both P<0.05). (3)The comparison of the mean P300 amplitude under different feedback types among the three groups showed that the main effect of group ( F=15.719, P<0.001) and the main effect of feedback type ( F=15.949, P=0.001) were both significant, while the interaction effect between group and feedback type was not significant ( F=1.573, P=0.213). The group with suicidal ideation ((0.85±0.21) μV) had a smaller amplitude than both the non-suicidal ideation group ((1.61±0.22) μV) and healthy controls ((2.46±0.20) μV) (both P<0.05). (4)In depressed patients, P300 mean amplitude under both loss and gain feedback conditions were both negatively correlated with suicidal ideation (loss: r=-0.435, P=0.001; gain: r=-0.318, P=0.013). Conclusion:Depressed patients with and without suicidal ideation both exhibit impaired risk decision-making. The decrease of P300 mean amplitude is more significant in depressed patients with suicidal ideation than those without suicidal ideation.P300 mean amplitude may serve as an electrophysiological marker to differentiate depressed patients with suicidal ideation and those without suicidal ideation.

Objective:To analyze the characteristics of electroencephalogram microstate parameters in first-episode drug-naive patients with major depressive disorder (MDD), so as to provide electrophysiological evidence for the pathogenesis and early diagnosis of MDD.Methods:Eighty-four first-episode, drug-naive outpatients diagnosed with MDD(MDD group) and 82 healthy controls(healthy group) participated in this study. Resting-state EEG data (5-6 min, with eyes closed) were recorded for all participants. Data preprocessing and microstate analysis were performed using MATLAB and EEGLAB software. Temporal parameters of resting-state brain network microstates were compared using SPSS 26.0.Results:This study identified four typical microstates: Class A microstate(auditory network), Class B microstate(visual network), Class C microstate(salient network), and Class D microstate(attention and control network). The coverage rate (0.16±0.06, 0.21±0.06), duration (67.72±7.07, 72.28±8.59), and incidence rate (2.38±0.68, 2.82±0.67) of microstate A in MDD group were significantly lower than those in healthy group ( F=22.115, 13.368, 18.779, all P<0.001), while the above indexes of microstate B in MDD group were significantly higher than those in healthy group(coverage rate: 0.24±0.07 vs 0.18±0.06, duration: 76.35±11.28 vs 69.46±8.52, incidence rat: 3.16±0.52 vs 2.52±0.57) ( F=41.287, 18.999, 52.245, all P<0.001). Additionally, the microstate D in MDD group showed significantly lower coverage rate(0.33±0.08, 0.36±0.08) and duration (89.66±15.38, 95.46±16.79)compared with healthy group( F=3.932, 4.215, both P<0.05). Notably, significant differences were observed in the transition probabilities between the following microstates: A→B, A→D, B→A, C→A, C→B, D→A and D→B (all P<0.05). Conclusion:First-episode drug-naive depressive patients are characterized by alterations in microstate A, microstate B, and microstate D, which may be the potential pathogenesis of MDD and may serve as electrophysiological indicators for early diagnosis of MDD.

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.