Lung cancer is a leading cause of cancer-related morbidity and mortality worldwide. Coupled with the substantial workload, the clinical management of lung cancer is challenged by the critical need to efficiently and accurately process increasingly complex medical information. In recent years, large language models (LLMs) technology has undergone explosive development, demonstrating unique advantages in handling complex medical data by leveraging its powerful natural language processing capabilities, and its application value in the field of lung cancer diagnosis and treatment is continuously increasing. The paper systematically analyzes that the exceptional potential of LLMs in lung cancer auxiliary diagnosis, tumor feature extraction, automatic staging, progression/outcome analysis, treatment recommendations, medical documentation generation, and patient education. However, they face critical technical and ethical challenges including inconsistent performance in complex integrated decision-making (e.g., TNM staging, personalized treatment suggestions) and "black box" opacity issues, along with dilemmas such as training data biases, model hallucinations, data privacy concerns, and cross-lingual adaptation challenges ("data colonization"). Future directions should prioritize constructing high-quality multimodal corpora specific to lung cancer, developing interpretable and compliant specialized models, and achieving seamless integration with existing clinical workflows. Through dual drivers of technological innovation and ethical standardization, LLMs should be prudently advanced for holistic lung cancer management processes, ultimately promoting efficient, standardized, and personalized diagnosis and treatment practices.

The aim of this paper was to investigate the serotypes,virulence factors and drug resist-ance of clinical isolates of Pasteurella rnultocida of porcine origin in recent years.Morphological screening and polymerase chain reaction(PCR)were used to isolate and identify 119 isolates from nasal swabs and lung tissue samples sent from swine farms in Zhejiang Province from 2010 to 2024.The isolates of Pasteurella multocida were subjected to capsular polysaccharide serotyping,lipopolysaccharide serotyping,virulence factor detection and drug resistance analysis by PCR and Kirby-Bauer disc agar diffusion method(K-B).The results showed that there were 64 strains(53.7％)of A-type,54 strains(45.3％)of D-type and 1 strain(0.9％)of F-type among the capsu-lar polysaccharide serotypes,and 10 strains(8.4％)of L1-type,20 strains(16.8％)of L3-type,86 strains(72.2％)of L6-type,and 3 strains(2.6％)of undetermined type among the lipopolysaccha-ride serotypes.The amplification results of 10 virulence genes showed that the detection rate of virulence genes hgbA,higbB and fimA was over 86.0％,the detection rate of toxA was 8.4％,while the virulence gene tbpA was not detected.There were also differences in the distribution vir-ulence genes in different capsular polysaccharide serotypes.Virulence factor pfhA was detected in type A and F but not in type D.The detection rate of adhesin gene tadD in serotype A(92.2％)was significantly higher than that of type D(9.3％),and,on the contrary,the detection rate of ad-hesin gene hsf-l in serotype D(90.7％)was significantly higher than that of type A(20.3％).Drug resistance analysis revealed that Pasteurella multocida showed high susceptibility to antimi-crobial drugs such as amoxicillin,ampicillin,cephalosporins,doxycycline,fosfenicol and ciprofloxa-cin,and showed strong resistance to antimicrobial drugs such as lincomycin,cotrimoxazole,genta-micin and amikacin,and there were 54 multi-drug resistant strains(78.3％).In summary,capsular polysaccharide serotypes were dominated by type A and D,lipopolysaccharide serotypes were dom-inated by L6,the distribution of some virulence genes varied greatly among different serotypes,and the proportion of multi-resistant strains was high,which provide reference for the prevention and control of this disease.

Objective To summarize the clinical efficacy of robotic-assisted left thoracic small-incision minimally invasive direct coronary artery bypass grafting(MIDCAB).Methods A retrospective analysis was conducted on the procedures and treatment outcomes of robotic-assisted MIDCAB in the Army Medical Center of PLA from October 2016 to June 2023.Baseline clinical information,MIDCAB-related data,perioperative conditions and data during follow-up were collected and analyzed.Results There were 23 patients subjected,including 21 males and 2 females,with a mean age of 58.17±7.49 years,and a body mass index(BMI)of 23.99±3.25 kg/m2.All of them experienced angina pectoris,and 1 had a history of myocardial infarction,1 had dilated cardiomyopathy,2 patients had chronic obstructive pulmonary disease(COPD),and 10 had a history of percutaneous coronary intervention(PCI).Robotic-assisted MIDCAB procedure was successfully completed.No internal mammary artery injury or transformation of the procedure occurred in these cases,and excellent bridging vessel flow was achieved after anastomosis of the internal mammary artery to left anterior descending branch.The incision length in the left chest was 8(8,8)cm,the operation time was 380(300,465)min,the intraoperative bleeding volume was 300(100,400)mL,the length of ICU stay was 3(2,3)d,the amount of thoracic drainage was 780(525,1 040)mL,and the postoperative length from surgery to discharge was 11.17±2.38 d.No mortality was observed during or within 30 d of hospitalization,and 1 patient was readmitted due to pericardial effusion within 30 d,and was discharged after symptomatic treatment including pericardiocentesis and drainage.No deaths,major adverse cardiovascular and cerebrovascular events(MACCE),or re-revascularization occurred in all patients during outpatient and telephone follow-up.Conclusion Robotic-assisted internal mammary artery dissection is a delicate and safe technique,and coronary artery bypass grafting in minimally invasive small-incision off-pump is effective,safe and feasible,with satisfactory short-and mid-term outcomes.The technique is suitable for minimally invasive coronary artery disease surgery and is worthy of popularization and application.

Soil cadmium pollution can adversely affect the cultivation of the ornamental plant, Coleus scutellarioides. Upon cadmium contamination of the soil, the growth of C. scutellarioides is impeded, and it may even succumb to the toxic accumulation of cadmium. In this study, we investigated the effects of arbuscular mycorrhizal fungi (AMF) on the adaptation of C. scutellarioides to cadmium stress, by measuring the physiological metabolism and the degree of root damage of C. scutellarioides, with Aspergillus oryzae as the test fungi. The results indicated that cadmium stress increased the activity of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), and the content of malondialdehyde (MDA) and proline (Pro) within the cells of C. scutellarioides, but inhibited mycorrhizal infestation rate, root vigour and growth rate to a great degree. With the same cadmium concentration, the inoculation of AMF significantly improved the physiological indexes of C. scutellarioides. The maximum decrease of MDA content was 42.16%, and the content of secondary metabolites rosemarinic acid and anthocyanosides could be increased by up to 27.43% and 25.72%, respectively. Meanwhile, the increase of root vigour was as high as 35.35%, and the DNA damage of the root system was obviously repaired. In conclusion, the inoculation of AMF can promote the accumulation of secondary metabolites, alleviate root damage, and enhance the tolerance to cadmium stress in C. scutellarioides.
Cadmium/toxicity* ; Mycorrhizae/physiology* ; Plant Roots/drug effects* ; Soil Pollutants/toxicity* ; Stress, Physiological ; Superoxide Dismutase/metabolism*

Objective To explore the effect of repetitive transcranial magnetic stimulation(rTMS)on the sleep disorder and examination results of recruits.Methods At a training base,the Pittsburgh Sleep Quality Index(PSQI)was used to screen the recruits with sleep disorders(total score of PSQI>7).The recruits were randomly assigned to rTMS group or sham rTMS group.Both groups received cognitive and behavioral intervention therapy,including sleep health education and relaxation training.Moreover,the rTMS group was treated with rTMS at the right posterior parietal lobe by continuous theta burst stimulation(cTBS)twice a day at an interval of at least 50 min for 5 consecutive days as a course of treatment with an interval of 2 days for a total of 2 courses of treatment.The coil position and stimulus intensity of sham rTMS group were consistent with the rTMS group,but the head of subjects was perpendicular to the coil plane and there was no effective stimulation.Before and after treatment,PSQI,self-rating depression scale,generalized anxiety disorder-7 and health questionnaire-15 were used to evaluate the sleep,mood and physical state of the recruits.The training result was assessed one month after treatment.The total effective rate of PSQI improvement and examination results were compared between the two groups.The independent influencing factors of excellent examination result were analyzed.Results Among 351 recruits,83 with sleep disorders completed treatment and follow-up.There were 40 patients in the rTMS group and 43 patients in the sham rTMS group.There was no significant difference between the two groups at baseline.After treatment,the total effective rate of PSQI improvement in the rTMS group was higher than that in the sham rTMS group(77.50%vs 53.49%,P=0.022).The average examination score and excellent rate of the rTMS group were higher than those of the sham rTMS group(91.58±3.19 vs 89.47±4.67,P=0.020;85%vs 65.12%,P=0.037).Logistic regression analysis showed that the treatment mode(rTMS group)was the independent influencing factor of excellent examination results(P=0.032).Conclusion rTMS can effectively and safely improve the sleep disorders and examination results of recruits.rTMS may play a positive role in improving the learning and training effect of recruits,which needs to be further proved.

Acute respiratory distress syndrome(ARDS)is a common clinical syndrome in intensive care unit(ICU)with high morbidity and mortality.Recently,the new global definition of ARDS has redefined the diagnosis of ARDS,which is divided into non-intubated ARDS,intubated ARDS and ARDS with limited resources.Hypoxia is the main clinical manifestation of ARDS,and respiratory support therapy is the first-line treatment for ARDS.With respect to non-intubated ARDS,current guidelines do not provide a clear preference between high flow nasal cannula(HFNC)and non-invasive mechanical ventilation(NIV).In order to improve clinical managmet of non-intubated ARDS,we review the role of HFNC and NIV in non-intubated ARDS in this paper.

Intraluminal thrombus(ILT)at the vertebral artery origin is rare and often missed due to atypical symptoms.However,it poses a high risk of artery-to-artery embolism and severe posterior circulation ischemia.This article reports a case of missed diagnosis of ILT to improve the diagnostic ability.The patient,a 49-year-old male was admitted to emergency department with sudden dizziness accompanied by nausea for 12 hours.Head CT suggested posterior circulation ischemia.Patient was given aspirin 0.2 g/d and atorvastatin 20 mg/d orally and discharged from the hospital.Head MRI in the outpatient department showed a recent infarct in the right cerebellar hemisphere next day.On the 28th,dizziness recurred,accompanied by unsteady walking and right-sided hemisensory numbness.The symptoms persisted and did not improve.He was admitted to the hospital on the 29th.Cervical CTA showed severe stenosis at the origin of the right vertebral artery,filling defect in the distal lumen combined with the Donut sign.Thus,ILT was diagnosed.The drug treatment regimen was adjusted to aspirin 100 mg/d combined with clopidogrel 75 mg/d for a total of 15 weeks.High-resolution MRI of the cervical blood vessels in the outpatient department showed occlusion of the V1-V2 segment of the right vertebral artery.On November 2,endovascular treatment was performed under local anesthesia.At 90 days and 6 months of follow-up after the operation,no recurrence of cerebral ischemia events occurred,and the mRS score was 0.This case highlights the need for vigilance toward ILT in posterior circulation ischemia when initial imaging is inconclusive.Early dynamic CTA(5-7 days)combined with dual antiplatelets may prevent thrombus progression and improve outcomes.

Objective:To develop an artificial intelligence (AI)-guided intravitreal injection robot system to accurately detect the injection point on the ocular surface and guide the robotic arm to complete the intravitreal injection positioning task through 3D position calculation.Methods:The Dikablis subset of the TEyeD dataset was used.Training set, testing set, and validation set were constructed by using equal interval sampling strategy.The system read the ocular surface color RGB image with an RGBD camera, then used a PatchCrop-Transformer-based injection point detection algorithm to detect and locate key points such as the pupil, iris, and eyelid in the image.Next, it extracted the local 3D point cloud data near the injection point based on the depth information obtained by the camera.Through principal component analysis (PCA) of the local area point cloud data, the injection point and injection direction were determined.The key information was then passed to the robotic arm system.The end of the robotic arm adopted a remote center of motion (RCM) mechanism.After solving the forward and inverse kinematics, the joint movement path was obtained, and the robotic arm was controlled to move to 2 cm above the injection point.After confirmation by the doctor, the insertion, injection, and withdrawal operations were completed to ensure the stability and repeatability of the injection process.The mean square error (MSE) of key points localization and the success detection rate (SDR) within different pixel error ranges (2, 5, and 10 pixels) of the study method were compared with those of the NFDP, SLPT, and StarLoss methods, and the effects of random weight enhancement, fixed weight enhancement, and no enhancement methods on the MSE of key points localization were evaluated.The repeatability and absolute positioning accuracy of the robotic arm system were also evaluated.Results:After adding random weight enhancement, the model of this study outperformed the fixed weight enhancement and no enhancement methods in both MSE and SDR.The MSEs of the model proposed in this study for overall eye, pupil, and iris localization were 4.25, 2.41, and 1.54, respectively, which were lower than those of the NFDP, StarLoss, and SLPT methods.Within the error ranges of 5 and 10 pixels, the SDRs of the model proposed in this study were 72.09% and 92.68%, respectively, which were higher than those of the NFDP, StarLoss, and SLPT methods.The single-axis repeatability errors and absolute positioning errors of the robotic arm were within ±5 μm.Conclusions:The AI-guided intravitreal injection robot system integrates RGBD images to achieve automatic recognition of the ocular injection point and high-precision motion control through RCM mechanism design and corresponding kinematic solution methods.

Objective:To develop an artificial intelligence (AI)-guided intravitreal injection robot system to accurately detect the injection point on the ocular surface and guide the robotic arm to complete the intravitreal injection positioning task through 3D position calculation.Methods:The Dikablis subset of the TEyeD dataset was used.Training set, testing set, and validation set were constructed by using equal interval sampling strategy.The system read the ocular surface color RGB image with an RGBD camera, then used a PatchCrop-Transformer-based injection point detection algorithm to detect and locate key points such as the pupil, iris, and eyelid in the image.Next, it extracted the local 3D point cloud data near the injection point based on the depth information obtained by the camera.Through principal component analysis (PCA) of the local area point cloud data, the injection point and injection direction were determined.The key information was then passed to the robotic arm system.The end of the robotic arm adopted a remote center of motion (RCM) mechanism.After solving the forward and inverse kinematics, the joint movement path was obtained, and the robotic arm was controlled to move to 2 cm above the injection point.After confirmation by the doctor, the insertion, injection, and withdrawal operations were completed to ensure the stability and repeatability of the injection process.The mean square error (MSE) of key points localization and the success detection rate (SDR) within different pixel error ranges (2, 5, and 10 pixels) of the study method were compared with those of the NFDP, SLPT, and StarLoss methods, and the effects of random weight enhancement, fixed weight enhancement, and no enhancement methods on the MSE of key points localization were evaluated.The repeatability and absolute positioning accuracy of the robotic arm system were also evaluated.Results:After adding random weight enhancement, the model of this study outperformed the fixed weight enhancement and no enhancement methods in both MSE and SDR.The MSEs of the model proposed in this study for overall eye, pupil, and iris localization were 4.25, 2.41, and 1.54, respectively, which were lower than those of the NFDP, StarLoss, and SLPT methods.Within the error ranges of 5 and 10 pixels, the SDRs of the model proposed in this study were 72.09% and 92.68%, respectively, which were higher than those of the NFDP, StarLoss, and SLPT methods.The single-axis repeatability errors and absolute positioning errors of the robotic arm were within ±5 μm.Conclusions:The AI-guided intravitreal injection robot system integrates RGBD images to achieve automatic recognition of the ocular injection point and high-precision motion control through RCM mechanism design and corresponding kinematic solution methods.

Objective:To investigate the risk factors for delirium after free flap reconstruction surgery in elderly patients with head and neck cancer.Methods:This study retrospectively collected clinical data from 309 elderly patients with head and neck cancer who underwent radical resection and free flap reconstruction surgery in the Department of Operation & Anesthesiology, College & Hospital of Stomatology, Guangxi Medical University from January 2018 to December 2022. Among them, there were 197 males (63.8%) and 112 females (36.2%), with an average age of (66.8±5.5) years old. Based on the delirium diagnostic criteria outlined in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders, patients were evaluated for postoperative delirium within one week after surgery. They were then divided into a delirium group ( n=75) and a non-delirium group ( n=234). Perioperative indicators potentially related to postoperative delirium, including age, gender, past medical history, tumor characteristics, hematological tests, perioperative sleep disturbances, surgical procedures, intraoperative fluid intake and output, anesthetic dosage, postoperative pain, etc, were collected from the relevant medical record system.Variables with P<0.05 were included in a multivariate Logistic regression model to screen for independent risk factors for delirium. Results:The incidence of delirium after free flap reconstruction surgery for head and neck cancer in elderly patients was 24.3% (75/309). Multivariate Logistic regression analysis showed that male gender ( OR=2.802, P=0.005), perioperative sleep disturbances ( OR=7.104, P<0.001), and moderate-to-severe postoperative pain ( OR=6.903, P<0.001) were risk factors for postoperative delirium. Conclusions:Male gender, perioperative sleep disturbances, and moderate-to-severe postoperative pain are independent risk factors for delirium in these patients.