AIM: To evaluate safety, efficacy, visual quality, and patient satisfaction after optimized monovision Q-value-customized femtosecond laser-assisted in situ keratomileusis(FS-LASIK)for myopia, astigmatism, and presbyopia. METHODS: This prospective study enrolled patients suffering myopia, astigmatism, and presbyopia. At 1 y post operation, uncorrected distance, intermediate and near visual acuity(UDVA, UIVA, UNVA), refraction, corneal higher order aberrations(HOAs), Q value, objective visual quality, and near stereoacuity were evaluated. The impact of surgery on patients' living quality and their satisfaction were evaluated based on National Eye Institute Refractive Error Quality of Life Instrument(NEI RQL)scores at 1-year follow-up.RESULTS:The study enrolled 36 patients(72 eyes)including 12 males(33%)and 24 females(67%)with an average age of 46.03±3.60(range 40-53)y. One year postoperatively, 97% of patients achieved binocular UDVA of 1.0 or better, 89% achieved UIVA of 0.63 or better, and 97% achieved UNVA of 1.0 or better. The spherical equivalent refraction(SE)in dominant eye within ±1.00 D was 100%. SE in non-dominant eyes was uncorrected compared with the preoperative target correction, with a mean difference of -0.27±0.34 D before and after surgery(P<0.001). while in the non-dominant eyes, the anterior corneal Q-value within the 5 mm zone increased negatively compared with the preoperative value(-0.33±0.24 vs -0.21±0.09, P<0.001). In the non-dominant eye, spherical aberration and longitudinal spherical aberration were lower than preoperative values(both P<0.001). Besides, there were no significant changes in objective scatter index(OSI), modulation transfer function cutoff frequency(MTF cut off)and Strehl ratio(SR)in both dominant and non-dominant eyes(all P>0.05), and the near stereoacuity was better after surgery(P=0.007). Additionally, the patient satisfaction rate with the surgery was 94%, the satisfaction rates for UDVA and UNVA were both 98%. The 11% of patients required to wear low-diopter glasses when driving at night.CONCLUSION:Optimized monovision Q-value-customised FS-LASIK is a safe and effective procedure for correcting myopia, astigmatism, and presbyopia. It provides favorable subjective and objective visual quality and high patient satisfaction. The under correction in non-dominant eyes is observed, indicating the further optimization of nomogram is needed.

Objective To investigate the post-discharge exercise behavior and factors influencing moderate to vigorous intensity physical activity (MVPA) in patients undergoing lung surgery. Methods A total of 2874 patients from the large prospective, observational perioperative lung symptom study cohort (CN-PRO-Lung 3) in the Department of Thoracic Surgery at Sichuan Cancer Hospital between April 7, 2021, and January 31, 2024, were selected as the survey subjects. A survey was conducted using the Investigation of Exercise Behavior after Lung Surgery questionnaire and the International Physical Activity Questionnaire-Short Form (IPAQ-SF) among patients who underwent lung surgery. Binary logistic regression was used to analyze the factors influencing patients’ engagement in MVPA. Results A total of 702 patients were surveyed, including 252 males and 450 females, with an average age of (52.4±10.2) years. Patients with lung cancer accounted for 85.9%. Only 36.0% of the patients had regular exercise habits, while 42.3% did not engage in any physical activity. The three main barriers for postoperative exercise were physical discomfort (pain, coughing, shortness of breath, etc, 54.7%), lack of professional guidance (41.7%), and concerns about the surgical wound (28.9%). The proportions of patients engaging in vigorous, moderate, and low-intensity physical activity were 5.7%, 28.2%, and 66.1%, respectively. Multivariate analysis showed that patients with a personal annual income ≥50000 yuan (OR=1.52, 95%CI 1.01-2.29, P=0.044), high school education or above (OR=1.92, 95%CI 1.33-2.76, P<0.001), and lobectomy (OR=1.44, 95%CI 1.02-2.03, P=0.037) engaged in more MVPA. Conclusion Patients undergoing lung surgery have inadequate physical activity after discharge, particularly lacking in MVPA. Patients with higher income, higher educational levels, and lobectomy are more frequently engaged in MVPA. Measures such as symptom control, providing exercise guidance, and enhancing education on wound care may potentially improve the inadequate physical activity in lung surgery patients after discharge.

Objective: To investigate the clinicopathological characteristics and diagnostic-therapeutic strategies of oncocytic mucoepidermoid carcinoma (OMEC) of the parotid gland, and to enhance awareness of this rare variant among clinicians and pathologists. Methods: The clinical data, imaging findings, histopathological features, immunophenotype, and molecular characteristics of two patients with parotid OMEC were retrospectively analyzed, and the relevant literature was reviewed. Results: Case 1 was a 50-year-old man who presented with a painless mass behind the right earlobe for more than 2 years. The patient underwent extended parotidectomy with preservation of the facial nerve. Histopathological examination revealed that the tumor was predominantly composed of oncocytic cells with a small proportion of mucous cells. Immunohistochemically, the tumor cells were partially positive for cytokeratin 5/6, cytokeratin 7, and P63. Special staining with alcian blue, periodic acid-Schiff, and phosphotungstic acid hematoxylin yielded positive results. The diagnosis of right parotid OMEC was established. No recurrence or metastasis was observed during a 1 year follow-up. Case 2 was a 61-year-old man with a 3-month history of a mass beneath the left ear. After partial parotidectomy at an outside institution, pathological consultation at the Stomatological Hospital of Jilin University demonstrated that the tumor consisted almost entirely of oncocytic cells, exhibited infiltrative growth, and lacked typical mucous, epidermoid, and intermediate cells. Fluorescence in situ hybridization confirmed positive mastermind-like transcriptional activator 2 (MAML2) gene rearrangement, establishing the diagnosis of left parotid OMEC. The patient subsequently underwent total parotidectomy with preservation of the facial nerve, and no recurrence was detected during a short-term 3 months follow-up. A review of the literature indicated that OMEC most commonly arises in the parotid gland and is generally a low-grade malignancy with favorable prognosis. When tumors are composed exclusively of oncocytic cells, exhibit minimal cytological atypia, and lack the classical cellular components of mucoepidermoid carcinoma, they are highly prone to misdiagnosis as oncocytoma, nodular oncocytic hyperplasia, or other benign oncocytic lesions. Accurate differential diagnosis relies on recognition of infiltrative growth patterns, supportive immunophenotypic markers (e.g., P63 positivity), and detection of characteristic MAML2 gene rearrangement. Complete surgical excision remains the treatment of choice. Conclusion OMEC dominated by oncocytic cells carries a high risk of clinical misdiagnosis. Integrating the assessment Conclusion OMEC dominated by oncocytic cells carries a high risk of clinical misdiagnosis. Integrating the assessment of infiltrative histopathological features with immunohistochemistry and molecular detection of MAML2 rearrangement is crucial for accurate diagnosis, appropriate assessment of tumor behavior, and optimal surgical decision making.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Patients with lung cancer experience a heavy symptom burden during the perioperative period, which seriously affects their recovery and quality of life. Traditional symptom management models rely mainly on scheduled ward rounds during hospitalization and outpatient follow-up after discharge. However, they have limitations such as delayed symptom recognition, lack of post-discharge monitoring, and non-quantitative symptom assessment, which often lead to delayed interventions and low patient satisfaction. In recent years, the symptom management model based on electronic patient-reported outcomes (ePRO) has been increasingly valued in clinical practice. Existing high-level evidence from both domestic and international studies indicates that, through proactive monitoring, real-time alerts, and remote interventions, this model enables dynamic and continuous symptom management and helps improve patient recovery and healthcare experience. As a supplement to routine medical care, the ePRO-based symptom management model aims to enhance the quality of care rather than replace existing medical processes. To promote the standardized application of this model in perioperative lung cancer care, this consensus integrates domestic and international evidence. After multiple rounds of voting by more than 50 experts, it formulates 12 consensus statements covering the three core components, symptom monitoring, alerting, and intervention, to provide scientific and practical recommendations for clinical practice.

Objective To explore the accuracy of machine learning algorithms based on SHOX2 and RASSF1A methylation levels in predicting early-stage lung adenocarcinoma pathological types. Methods A retrospective analysis was conducted on formalin-fixed paraffin-embedded (FFPE) specimens from patients who underwent lung tumor resection surgery at Affiliated Hospital of Nantong University from January 2021 to January 2023. Based on the pathological classification of the tumors, patients were divided into three groups: a benign tumor/adenocarcinoma in situ (BT/AIS) group, a minimally invasive adenocarcinoma (MIA) group, and an invasive adenocarcinoma (IA) group. The methylation levels of SHOX2 and RASSF1A in FFPE specimens were measured using the LungMe kit through methylation-specific PCR (MS-PCR). Using the methylation levels of SHOX2 and RASSF1A as predictive variables, various machine learning algorithms (including logistic regression, XGBoost, random forest, and naive Bayes) were employed to predict different lung adenocarcinoma pathological types. Results A total of 272 patients were included. The average ages of patients in the BT/AIS, MIA, and IA groups were 57.97, 61.31, and 63.84 years, respectively. The proportions of female patients were 55.38%, 61.11%, and 61.36%, respectively. In the early-stage lung adenocarcinoma prediction model established based on SHOX2 and RASSF1A methylation levels, the random forest and XGBoost models performed well in predicting each pathological type. The C-statistics of the random forest model for the BT/AIS, MIA, and IA groups were 0.71, 0.72, and 0.78, respectively. The C-statistics of the XGBoost model for the BT/AIS, MIA, and IA groups were 0.70, 0.75, and 0.77, respectively. The naive Bayes model only showed robust performance in the IA group, with a C-statistic of 0.73, indicating some predictive ability. The logistic regression model performed the worst among all groups, showing no predictive ability for any group. Through decision curve analysis, the random forest model demonstrated higher net benefit in predicting BT/AIS and MIA pathological types, indicating its potential value in clinical application. Conclusion Machine learning algorithms based on SHOX2 and RASSF1A methylation levels have high accuracy in predicting early-stage lung adenocarcinoma pathological types.

With the widespread use of antibiotics, drug-resistant bacterial infections have become a significant threat to human health. Finding new antibacterial strategies that can effectively control drug-resistant bacterial infections has become an urgent task. Unlike small molecule drugs that target bacterial proteins, antisense oligonucleotide (ASO) can target genes related to bacterial resistance, pathogenesis, growth, reproduction and biofilm formation. By regulating the expression of these genes, ASO can inhibit or kill bacteria, providing a novel approach for the development of antibacterial drugs. To overcome the challenge of delivering antisense oligonucleotide into bacterial cells, various drug delivery systems have been applied in this field, including cell-penetrating peptides, lipid nanoparticles and inorganic nanoparticles, which have injected new momentum into the development of antisense oligonucleotide in the antibacterial realm. This review summarizes the current development of small nucleic acid drugs, the antibacterial mechanisms, targets, sequences and delivery vectors of antisense oligonucleotide, providing a reference for the research and development of antisense oligonucleotide in the treatment of bacterial infections.

ObjectiveTo investigate the trends in diabetes mortality and potential years of life lost (PYLL) among residents of Huangpu District, Shanghai from 1993 to 2021, to analyze the long-term trends of diabetic patients with different characteristics and to provide a reference for scientific prevention and control of diabetes in aging urban areas. MethodsDiabetes mortality data were obtained from the Huangpu District cause of death registration records in the Shanghai death cause registration system. Indicators such as crude mortality rate, standardized mortality rate, potential years of life lost (PYLL), average years of life lost (AYLL), annual percentage change (APC), and average annual percentage change (AAPC) were used to analyze diabetes-related mortality and life loss. Statistical analyses were performed using software SPSS 21.0 and Joinpoint 5.0.2. ResultsFrom 1993 to 2021, the average annual crude mortality rate of diabetes in Huangpu District was 46.56/100 000, and the average annual standardized mortality rate was 20.44/100 000. The crude mortality rate and standardized mortality rate of diabetes for female residents were higher than those for males. The crude mortality rate showed an overall increasing trend [AAPC=2.81% (95%CI: 0.20%‒5.49%), P<0.05], while the increase in standardized mortality rate significantly slowed [AAPC=0.15% (95%CI: -2.27%‒2.63%)], P<0.05]. The mortality rate rose rapidly in the 70‒74 years age group and peaked in the 85‒ years age group (607.69/100 000). Diabetes accounted for a cumulative PYLL of22 741 person-years, with an average annual AYLL of 1.88 years and an average annual potential years of life lost rate (PYLLR) of 0.82‰. Male residents had higher PYLL, AYLL, and PYLLR than females. ConclusionDiabetes mortality rates in Huangpu District have increased year by year, resulting in significant life loss. However, the age-standardized mortality rate increase has markedly slowed. Efforts should focus on elderly diabetic patients aged ≥70 years, by leveraging platforms such as community-based chronic disease health support centers, efforts should be made to enhance diabetes screening service for middle-aged and elderly residents. Consequently, elderly diabetic patients’ awareness of diabetes and responce to related complications is improved, which would be conducive to controling the progression of complications and reducing the mortolity risk of diabetes.

Purpose: It was aimed to clarify the casual connection between prostate cancer (PCa) and arthritis by utilizing two-sample Mendelian randomization (MR) analysis and data from National Health and Nutrition Examination Survey (NHANES) database. Materials and Methods: This study utilized NHANES data. Through association analysis and risk stratification analysis, the association between arthritis and PCa were examined. MR analysis was performed to elucidate the causal relationship between arthritis and PCa. Sensitivity analysis and Steiger directionality test confirmed the reliability of the MR analysis results. Results: A total of 23,608 (PCa:controls=413:23,195) participants after a sample exclusion and variable definition process were screened in NHANES database. Adjustments across three diverse models consistently revealed a notable influence of arthritis on PCa progression. Arthritis was identified as a risk factor for PCa (odds ratio [OR] 1.88, 95% confidence interval [CI] 1.36–2.62, p<0.001). Subsequent analysis indicated that in the arthritis-adjusted model with multiple covariates, the area under the curve of the receiver operating characteristic curve was 0.94. The inverse variance weighting method of MR analysis showed a causal relationship between rheumatoid arthritis (RA) and PCa (OR 1.090, 95% CI 1.053–1.128, p<0.001) as well as osteoar-thritis and PCa (OR 1.002, 95% CI 1.001–1.004, p=0.002). This suggested that RA and osteoarthritis were risk factors for PCa. The heterogeneity (p>0.05), horizontal pleiotropy (p>0.05), leave-one-out and Steiger test confirmed reliability of MR results. Conclusions NHANES database and MR analyses identified arthritis as a risk factor for PCa, offering fresh avenues for preventive and therapeutic approaches.

Growth and development-related diseases result from the interplay of biological, psychological, and social factors. The collaboration between healthcare, sports, and education sectors integrates multidisciplinary resources and strengths to promote standardized diagnostic and therapeutic processes. This approach establishes a comprehensive closed-loop system encompassing early screening and referral, diagnosis and comprehensive evaluation, intervention and support plan formulation, as well as long-term management andoutcome assessment. It provides systematic scientific support for the healthy growth of children and adolescents, shifting disease intervention to the subclinical stage. Against the backdrop of societal informatization and intelligent development, this diagnostic and therapeutic model not only safeguards the holistic health of children and adolescents but also offers novel perspectives and feasible pathways for managing growth and development-related diseases. The implementation of this systematic diagnostic and therapeutic paradigm presents an innovative solution with Chinese characteristics for addressing such conditions, while injecting new vitality into the advancement of national health initiatives.