Volume 138 · Issue 17 · 2025

阻塞性睡眠呼吸暂停（OSA）是一种复杂的异质性疾病。^[1,2,3,4]全世界有超过10亿人受到OSA的影响，^[5]其定义为每小时睡眠的呼吸暂停次数（持续超过10秒的夜间呼吸停止）加上呼吸不足次数（伴随氧饱和度降低或持续超过10秒的觉醒的气流显著减少）。^[6,7]睡眠呼吸障碍会导致睡眠碎片化和持续的氧合-再氧合循环（称为间歇性低氧血症[IH]）。^[8,9]后一种现象（IH）引发一系列病理生理机制，主要由缺氧诱导因子-1（HIF-1）调节，^[10]这增加了心血管事件的风险。这些机制包括内皮功能障碍，^[11]动脉硬化、^[12]外周胰岛素敏感性降低、^[13]高凝状态、^[14]动脉性高血压的发病率较高^[15,16]和糖尿病。^[17]IH也与神经认知能力的增加有关，^[18]代谢紊乱^[19]，和其他合并症。^{[20,21,22,23]}

术语“心血管-肾脏-代谢(CKM)综合征”在过去几年中出现，以强调糖尿病、血脂异常、过度肥胖、高血压、心血管并发症和慢性肾脏疾病(CKD)之间的密切和相互作用的关系。^[1]它被定义并分为五个阶段，从缺乏CKM危险因素（0期）到建立临床心血管疾病（CVD）（4期），这突出了其病理生理学的进行性和早期识别的必要性，以便及时管理以防止CKM综合征的进展。^[1]这些CKM病症通常在同一患者中共存，并且各自对其他病症的进展产生负面影响，导致患者的临床结果恶化。CKM异常患者的患病率在全球范围内迅速增加，尤其是在东南亚地区，预计到2046年将继续增加。^[2]除了给患者及其家人带来的发病率、死亡率和痛苦之外，CKM疾病还给社会带来了不断升级的医疗负担。

Neoantigens exhibit high immunogenic potential and confer a uniqueness to tumor cells, making them ideal targets for personalized cancer immunotherapy. Neoantigens originate from tumor-specific genetic alterations, abnormal viral infections, or other biological mechanisms, including atypical RNA splicing events and post-translational modifications (PTMs). These neoantigens are recognized as foreign by the immune system, eliciting an immune response that largely bypasses conventional mechanisms of central and peripheral tolerance. Advances in next-generation sequencing (NGS), mass spectrometry (MS), and artificial intelligence (AI) have greatly expedited the rapid detection and forecasting of neoantigens, markedly propelling the development of diverse immunotherapeutic strategies, including cancer vaccines, adoptive cell therapy, and antibody treatment. In this review, we comprehensively explore the discovery and characterization of neoantigens and their clinical use within promising immunotherapeutic frameworks. Additionally, we address the current landscape of neoantigen research, the intrinsic challenges of the field, and potential pathways for clinical application in cancer treatment.

Colon cancer is a leading cause of cancer-related mortality worldwide, with surgical resection followed by adjuvant chemotherapy being the traditional standard for localized disease. However, the emergence of neoadjuvant therapies has introduced new possibilities for improving outcomes in locally advanced colon cancer (LACC). Neoadjuvant chemotherapy has demonstrated promising results in tumor downstaging, improved resectability, and reduced recurrence rates, as highlighted in trials like FOxTROT (Fluoropyrimidine oxaliplatin and targeted receptor pre-operative therapy), OPTICAL (A phase III study to evaluate the 3-year disease-free survival in patients with locally advanced colon cancer receiving either perioperative or postoperative chemotherapy with FOLFOX or CAPOX regimens), and NeoCol (Neoadjuvant chemotherapy versus standard treatment in patients with locally advanced colon cancer). For deficient mismatch repair (dMMR) tumors, neoadjuvant immunotherapy, exemplified by the NICHE (Neoadjuvant immune checkpoint inhibition and novel IO combinations in early-stage colon cancer) trial, has shown good pathologic response rates. Despite these advancements, challenges such as disease progression during treatment, staging inaccuracies, and chemotherapy-related toxicities underscore the need for precise patient selection and monitoring. Immunotherapy offers significant potential for dMMR tumors, potentially leading to non-surgical management strategies, while neoadjuvant chemotherapy presents a viable option for MMR-proficient (pMMR) patients, improving long-term outcomes in select populations. As the landscape of LACC management evolves, this review emphasizes the importance of personalized treatment strategies informed by biomarkers such as MMR status to maximize therapeutic efficacy and minimize risks. Future directions include refining the role of neoadjuvant therapies in clinical practice, expanding the use of immunotherapy, and exploring innovative combinations of systemic and targeted approaches to enhance survival and quality of life in patients with LACC. This review examines the current evidence supporting neoadjuvant approaches in pMMR and dMMR colon cancer, emphasizing their potential benefits and challenges.

Antibiotic-resistant (AR) bacterial wound infections (WIs) impose major burdens on healthcare systems, exacerbated by ineffective therapies and stalled antibiotic development. Phage therapy and phage-derived enzymes have gained traction as potent alternatives, leveraging targeted bactericidal mechanisms to combat AR pathogens. In this review, we summarised the antimicrobial mechanisms of both phage therapy and phage-derived enzymes as antimicrobial therapy, and outlined recent advances in their use for in vitro, in vivo and clinical applications for WI management. In addition, we also highlights recent advancements in their development, driven by genetic engineering, chemical modifications, and artificial intelligence. Finally, we identified the potential barriers and challenges they may encounter in clinical practice and the corresponding strategies to address these issues. The entire review gives us a comprehensive understanding of the latest advances in phages and their derivative enzyme therapies for treating WIs, in the hope that research in this field will continue to improve and innovate, accelerating the transition from the laboratory to application at the bedside and ultimately improving the efficacy of treatment for AR bacterial WIs.

Alzheimer’s disease (AD) is the most common cause of dementia and is a growing public health challenge. Neuroinflammation has been proposed as a prominent pathological feature of AD and has traditionally been attributed to the innate immune system. However, emerging evidence highlights the involvement of adaptive immunity, particularly T and B lymphocytes, in the neuroinflammatory processes of AD. It remains unclear how adaptive immune responses, originally intended to protect the body, contribute to chronic inflammation and neuronal dysfunction in AD. Here, we review the roles of adaptive immunity, cellular composition, and niches and their contribution to AD development and progression. Notably, we synthesize the crosstalk between adaptive immunity and the innate immune system of the central nervous system (CNS), which is mainly mediated by glial cells and myeloid cells, and their interrelationships with amyloid-β (Aβ)/Tau pathology. We hypothesized that the alterations observed in innate immunity in AD mirror age-related immune alterations, whereas the dysregulation of adaptive immunity contributes more accurately to disease-specific immune responses. Targeting adaptive immunity in the context of neuroinflammation may provide new insights into potential therapeutic strategies designed to modulate immune responses, thereby facilitating the diagnosis, intervention, and treatment of AD.

The purpose of this study was to evaluate the safety and efficacy of subsequent radiotherapy (RT) following first-line treatment with durvalumab plus chemotherapy in patients with extensive-stage small cell lung cancer (ES-SCLC).

A total of 122 patients with ES-SCLC from three hospitals during July 2019 to December 2021 were retrospectively analyzed. Inverse probability of treatment weighting (IPTW) analysis was performed to address potential confounding factors. The primary focus of our evaluation was to assess the impact of RT on progression-free survival (PFS) and overall survival (OS).

After IPTW analysis, 49 patients received durvalumab plus platinum-etoposide (EP) chemotherapy followed by RT (Durva + EP + RT) and 72 patients received immunochemotherapy (Durva + EP). The median OS was 17.2 months vs. 12.3 months (hazard ratio [HR]: 0.38, 95% confidence interval [CI]: 0.17-0.85, P = 0.020), and the median PFS was 8.9 months vs. 5.9 months (HR: 0.56, 95% CI: 0.32-0.97, P = 0.030) in Durva + EP + RT and Durva + EP groups, respectively. Thoracic radiation therapy (TRT) resulted in longer OS (17.2 months vs. 14.7 months) and PFS (9.1 months vs. 7.2 months) compared to RT directed to other metastatic sites. Among patients with oligo-metastasis, RT also showed significant benefits, with a median OS of 17.4 months vs. 13.7 months and median PFS of 9.8 months vs. 5.9 months compared to no RT. Continuous durvalumab treatment beyond progression (TBP) prolonged OS compared to patients without TBP, in both the Durva + EP + RT (NA vs. 15.8 months, HR: 0.48, 95% CI: 0.14-1.63, P = 0.238) and Durva + EP groups (12.3 months vs. 4.3 months, HR: 0.29, 95% CI: 0.10-0.81, P = 0.018). Grade 3 or 4 adverse events occurred in 13 (26.5%) and 13 (18.1%) patients, respectively, in the two groups; pneumonitis was mostly low-grade.

Addition of RT after first-line immunochemotherapy significantly improved survival outcomes with manageable toxicity in ES-SCLC.

The American Heart Association (AHA) introduced the concept of cardiovascular-kidney-metabolic (CKM) health and stage, reflecting the interaction among metabolism, chronic kidney disease (CKD), and the cardiovascular system. However, the association between CKM stage and the long-term risk of cardiovascular disease (CVD) has not been validated. This study aimed to evaluate the long-term CVD risk associated with CKM health metrics and CKM stage using data from a population-based cohort study.

In total, 5293 CVD-free participants were followed up to around 13 years in the Chinese Multi-provincial Cohort Study (CMCS). Considering the pathophysiologic progression of CKM health metrics abnormalities (comprising obesity, central adiposity, prediabetes, diabetes, hypertriglyceridemia, CKD, and metabolic syndrome), participants were divided into CKM stages 0, 1, and 2. The time-dependent Cox regression models were used to estimate the cardiovascular risk associated with CKM health metrics and stage. Additionally, broader CVD outcomes were examined, with a specific assessment of the impact of stage 3 in 2581 participants from the CMCS-Beijing subcohort.

Among participants, 91.2% (4825/5293) had at least one abnormal CKM health metric, 8.8% (468/5293), 13.3% (704/5293), and 77.9% (4121/5293) were in CKM stages 0, 1, and 2, respectively; and 710 incident CVD cases occurred during a median follow-up time of 13.3 years (interquartile range: 12.1 to 13.6 years). Participants with each poor CKM health metric exhibited significantly higher CVD risk. Compared with stage 0, the hazard ratio (HR) (95% confidence interval [CI]) for CVD incidence was 1.31 (0.84-2.04) in stage 1 and 2.27 (1.57-3.28) in stage 2. Significant interactive impacts existed between CKM stage and age or sex, with higher CVD risk related to increased CKM stages in participants aged <60 years or females.

These findings highlight the contribution of CKM health metrics and CKM stage to the long-term risk of CVD, suggesting the importance of multi-component recognition and management of poor CKM health in CVD prevention.

Peripheral helper T (T_PH) cells are uniquely positioned within pathologically inflamed non-lymphoid tissues to stimulate B-cell responses and antibody production. However, the phenotype, function, and clinical relevance of T_PH cells in hepatocellular carcinoma (HCC) are currently unknown.

Blood, tumor, and peritumoral liver tissue samples from 39 HCC patients (Sep 2016-Aug 2017) and 101 HCC patients (Sep 2011-Dec 2012) at the Third Affiliated Hospital of Sun Yat-sen University were used. Flow cytometry was used to quantify the expression, phenotype, and function of T_PH cells. Log-rank tests were performed to evaluate disease-free survival and overall survival in samples from 39 patients and 101 patients with HCC. T_PH cells, CD19⁺ B cells, and T follicular helper (T_FH) cells were cultured separately in vitro or isolated from C57/B6L mice in vivo for functional assays.

T_PH cells highly infiltrated tumor tissues, which was correlated with tumor size, early recurrence, and shorter survival time. The tumor-infiltrated T_PH cells showed a unique ICOS^hiCXCL13⁺IL-21^-MAF⁺BCL-6^- phenotype and triggered naïve B-cell differentiation into regulatory B cells. Triggering programmed cell death protein 1 (PD-1) induced the production of C-X-C motif chemokine ligand 13 (CXCL13) by T_PH cells, which then suppressed tumor-specific immunity and promoted disease progression.

Our study reveals a novel regulatory mechanism of T_PH cell-regulatory B-cell-mediated immunosuppression and provides an important perspective for determining the balance between the differentiation of protumorigenic T_PH cells and that of antitumorigenic T_FH cells in the HCC microenvironment.

Studies on the impact of blood glucose indicators on metabolism remain relatively scarce. The aim of this study was to investigate the associations between blood glucose indicators and metabolic disorders in China.

Data were from the Thyroid disorders, Iodine status and Diabetes Epidemiological survey (TIDE survey), which randomly selected 31 cities from 31 provinces in the Chinese mainland. A total of 68,383 participants without preexisting diabetes and have complete data on blood glucose, lipids, and blood pressure were included in the analysis. The diabetic population was divided into seven groups based on different types of elevated blood glucose levels, including fasting plasma glucose (FPG), postprandial glucose (PPG), and hemoglobin A1c (HbA1c): FPG ≥7 mmol/L; PPG ≥11.1 mmol/L; HbA1c ≥6.5%; FPG ≥7 mmol/L and PPG ≥11.1 mmol/L; FPG ≥7 mmol/L and HbA1c ≥6.5%; PPG ≥11.1 mmol/L and HbA1c ≥6.5%; FPG ≥7 mmol/L, PPG ≥11.1 mmol/L, and HbA1c ≥6.5%. The effects of each blood glucose indicator on metabolism were investigated separately. Weighted calculation was applied during the analysis, with the weighting coefficient based on the number of people corresponding to the population characteristics of each sample in the 2010 Chinese Census. A logistic regression model with restricted cubic splines (RCS) was employed to characterize the nonlinear associations of age and body mass index (BMI) with the risk of diabetes subtypes defined by distinct blood glucose indicators elevations, as well as the relationships between different blood glucose indicators (FPG, PPG, HbA1c) and the risk of metabolic disorders such as hypertension, hypertriglyceridemia, hypercholesterolemia, high low-density lipoprotein cholesterol (high LDL-C) and low high-density lipoprotein cholesterol (low HDL-C).

Among individuals with diabetes, elevated PPG alone was the most common abnormality, affecting 26.96% (1382/5127) of the population. Among the seven groups with only one elevated blood glucose indicator, individuals with elevated PPG alone exhibited the highest mean levels of triglycerides (TG) at 2.11 mmol/L (95% confidence interval [CI]: 1.97-2.25 mmol/L, P = 0.004), total cholesterol (TC) at 5.26 mmol/L (95% CI: 5.18-5.33 mmol/L, P <0.001), and low-density lipoprotein cholesterol (LDL-C) at 3.12 mmol/L, (95% CI: 3.06-3.19 mmol/L, P = 0.001). Individuals with elevated PPG alone showed a high prevalence of hypertension (806/1382, 58.32%), hypertriglyceridemia (676/1382, 48.91%), hypercholesterolemia (694/1382, 50.22%), High LDL-C (525/1382, 37.94%), and Low HDL-C (364/1382, 26.34%). The association of age and BMI with the risk of diabetes revealed that the older the patient, the steeper the RCS curve for the odds ratio (OR) of diabetes with elevated PPG alone (age = 60, OR = 2.79, 95% CI [2.49-3.12], P <0.01). Similarly, as BMI increased, the RCS curve for the OR of diabetes with elevated HbA1c alone also steepened (BMI = 35, OR = 3.75, 95% CI [3.23-4.35], P <0.001). Additionally, the RCS yielded a positive association between blood glucose indicators and metabolic diseases risk. In individuals with diabetes, RCS for both the ORs of metabolic diseases (hypertension, hypertriglyceridemia, hypercholesterolemia, high LDL-C, low HDL-C) and the levels of metabolic indicators (TG, TC, LDL-C, HDL-C) revealed some inflection points within the ranges of FPG 5-6 mmol/L, PPG 6-8 mmol/L, and HbA1c 5.5-6.0%.

PPG is more closely related to metabolic disorders than FPG and HbA1c in people with diabetes. For patients with diabetes and metabolic disorders, it may be necessary to monitor blood glucose fluctuations within specific ranges (FPG 5-6 mmol/L, PPG 6-8 mmol/L, and HbA1c 5.5-6.0%).

Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery.

PPCs were defined according to the European Perioperative Clinical Outcome standards as occurring within 7 postoperative days. Data of cases meeting inclusion/exclusion criteria were extracted from the anesthesia information management system to create three datasets: The development (data of Huashan Hospital, Fudan University from 2018 to 2020), temporal validation (data of Huashan Hospital, Fudan University in 2021) and external validation (data of other three hospitals in 2023) datasets. Machine learning models of six algorithms were trained using either 35 retrievable and plausible features or the 11 features selected by Lasso regression. Temporal validation was conducted for all models and the 11-feature models were also externally validated. Independent risk factors were identified and feature importance in top models was analyzed.

PPCs occurred in 712 of 7533 (9.5%), 258 of 2824 (9.1%), and 207 of 2300 (9.0%) patients in the development, temporal validation and external validation datasets, respectively. During cross-validation training, all models except Bayes demonstrated good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.840. In temporal validation of full-feature models, deep neural network (DNN) performed the best with an AUC of 0.835 (95% confidence interval [CI]: 0.805-0.858) and a Brier score of 0.069, followed by Logistic regression (LR), random forest and XGBoost. The 11-feature models performed comparable to full-feature models with very close but statistically significantly lower AUCs, with the top models of DNN and LR in temporal and external validations. An 11-feature nomogram was drawn based on the LR algorithm and it outperformed the minimally modified Assess respiratory RIsk in Surgical patients in CATalonia (ARISCAT) and Laparoscopic Surgery Video Educational Guidelines (LAS VEGAS) scores with a higher AUC (LR: 0.824, ARISCAT: 0.672, LAS: 0.663). Independent risk factors based on multivariate LR mostly overlapped with Lasso-selected features, but lacked consistency with the important features using the Shapley additive explanation (SHAP) method of the LR model.

The developed models, especially the DNN model and the nomogram, had good discrimination and calibration, and could be used for predicting PPCs in neurosurgical patients. The establishment of machine learning models and the ascertainment of risk factors might assist clinical decision support for improving surgical outcomes.

Senescent human skin primary fibroblast (FB) models have been established for studying aging-related, proliferative, and inflammatory skin diseases. The aim of this study was to compare the transcriptome characteristics of human primary dermal FBs from children and the elderly with four senescence models.

Human skin primary FBs were obtained from healthy children (FB-C) and elderly donors (FB-E). Senescence models were generated by ultraviolet B irradiation (FB-UVB), D-galactose stimulation (FB-D-gal), atazanavir treatment (FB-ATV), and replication exhaustion induction (FB-P30). Flow cytometry, immunofluorescence staining, real-time quantitative polymerase chain reaction, co-culturing with immune cells, and bulk RNA sequencing were used for systematic comparisons of the models.

In comparison with FB-C, FB-E showed elevated expression of senescence-related genes related to the skin barrier and extracellular matrix, proinflammatory factors, chemokines, oxidative stress, and complement factors. In comparison with FB-E, FB-UVB and FB-ATV showed higher levels of senescence and expression of the genes related to the senescence-associated secretory phenotype (SASP), and their shaped immune microenvironment highly facilitated the activation of downstream immune cells, including T cells, macrophages, and natural killer cells. FB-P30 was most similar to FB-E in terms of general transcriptome features, such as FB migration and proliferation, and aging-related characteristics. FB-D-gal showed the lowest expression levels of senescence-related genes. In comparisons with the single-cell RNA sequencing results, FB-E showed almost complete simulation of the transcriptional spectrum of FBs in elderly patients with atopic dermatitis, followed by FB-P30 and FB-UVB. FB-E and FB-P30 showed higher similarity with the FBs in keloids.

Each senescent FB model exhibited different characteristics. In addition to showing upregulated expression of natural senescence features, FB-UVB and FB-ATV showed high expression levels of senescence-related genes, including those involved in the SASP, and FB-P30 showed the greatest similarity with FB-E. However, D-galactose-stimulated FBs did not clearly present aging characteristics.

致编辑：腺癌是宫颈癌的第二大常见类型，其特点是早期病变隐匿，常规细胞学筛查检出率低。其发病率每年都在增加，约占宫颈癌病例的25%。^[1]宫颈腺癌具有高度异质性和侵袭性的特点，使其更容易复发和转移，预后较宫颈鳞癌差。^[2]鉴于其对放疗（RT）的敏感性降低，根治性切除是比同步放化疗（CCRT）更有效的治疗方法。^[3]具有中等危险因素（肿瘤直径≥3cm、淋巴血管间质浸润、宫颈间质浸润≥三分之二）的宫颈腺癌患者，其盆腔复发和远处转移的发生率高于鳞癌。^[4]对于这组患者，目前的治疗方案参考了Ryu提出的四因素模型等人^[5]2014年，由术后辅助放疗或CCRT组成。然而，RT对宫颈腺癌的总体疗效仍然低于对宫颈鳞癌的疗效。^[6]在这项研究中，我们分析了接受手术治疗的宫颈腺癌患者的临床资料。进一步探讨全身化疗（SCT）对宫颈腺癌治疗的意义，为宫颈腺癌术后辅助治疗（AT）提供参考。

致编辑：卵巢癌（OC）是全球女性死亡的第三大原因。^[1]大约90%的OC病例来源于上皮细胞，这些肿瘤具有不同的流行病学、分子和临床特征。^[2]高级别浆液性卵巢癌（HGSOC）是上皮性卵巢癌（EOC）最常见的亚型，已被广泛研究。^[3]卵巢癌肉瘤（OCS），也称为恶性混合中胚层肿瘤，是一种罕见的侵袭性肿瘤，通常发生在女性生殖道。^[4]在组织学上，OCS被认为是一种同时包含癌和肉瘤成分的高级病变。^[5]虽然OCS仅占EOC病例的1-4%，但它在所有EOC亚型中预后最差，^[6,7]中位生存期(MST)小于18个月。^[5]由于其罕见性，卵巢OCS很难通过前瞻性试验进行研究，导致对该疾病的了解有限。尽管如此，还没有专门针对OCS开发有针对性的治疗策略。

致编辑：全球人口迅速老龄化，急性梗阻性化脓性胆管炎（AOSC）已成为老年人急腹症的常见原因。传统开放手术面临越来越大的挑战，内镜逆行胰胆管造影（ERCP）是目前老年患者AOSC的主导治疗方法。尽管AOSC患者的腹腔镜经囊胆总管探查（LTCBDE）前景令人鼓舞，但所涉及的手术风险和较低的成功率仍然很大。我们的团队最近成功治疗了一名患有LTCBDE的AOSC患者，该患者年龄高达90岁。目标是评估LTCBDE挑战ERCP当前主导地位的潜力，建立共识，并最终使更广泛的老年AOSC患者群体受益。

致编辑：免疫球蛋白A肾病（IgAN）是世界范围内最常见的原发性肾小球肾炎。^[1]观察性研究表明循环炎性细胞因子和IgAN之间存在联系。^[2]然而，这些细胞因子在IgAN中的因果作用尚未被系统地了解。孟德尔随机化（MR）使用遗传变异作为观察流行病学中的工具变量（IVs）来推断可改变疾病风险因素的因果关系。由于遗传等位基因在受孕时被随机分配，这种方法减少了混杂和反向因果关系，并已被广泛用于探索暴露和疾病之间的因果关系。这项研究使用MR探索了循环炎性细胞因子和IgAN之间的因果关系，并确定了上游全身调节因子。

致编辑：作为一种异质性肿瘤，神经母细胞瘤占儿童癌症的7-8%，以及恶性肿瘤引起的儿童死亡的约15%。^[1,2]在神经母细胞瘤患者中，60%被诊断为高危，其中强化治疗后预后仍然较差。^[3]发现神经母细胞瘤的风险相关基因型和分子标志物是至关重要的，这将有助于建立早期诊断或治疗方法。NOP2/Sun RNA甲基转移酶(NSUN)家族成员，包括NSUN1-7是负责RNA 5-甲基胞嘧啶（m⁵(C)修改。^[4]以前，我们小组报道了单核苷酸多态性（SNPs）NSUN2基因有助于降低神经母细胞瘤风险。^[5]本研究旨在探讨NSUN3多态性与中国儿童神经母细胞瘤风险。