BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. TRIAL REGISTRATION ChiCTR 2100047474; https://www.chictr.org.cn/showproj.html?proj=128279 .
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Algorithms ; Lung Diseases/etiology* ; Machine Learning ; Neurosurgical Procedures/adverse effects* ; Postoperative Complications/diagnosis* ; Risk Factors ; ROC Curve

BACKGROUND: Non-invasive computed tomography angiography (CTA)-based fractional flow reserve (CT-FFR) could become a gatekeeper to invasive coronary angiography. Deep learning (DL)-based CT-FFR has shown promise when compared to invasive FFR. To evaluate the performance of a DL-based CT-FFR technique, DeepVessel FFR (DVFFR). METHODS: This retrospective study was designed for iScheMia Assessment based on a Retrospective, single-center Trial of CT-FFR (SMART). Patients suspected of stable coronary artery disease (CAD) and undergoing both CTA and invasive FFR examinations were consecutively selected from the Beijing Anzhen Hospital between January 1, 2016 to December 30, 2018. FFR obtained during invasive coronary angiography was used as the reference standard. DVFFR was calculated blindly using a DL-based CT-FFR approach that utilized the complete tree structure of the coronary arteries. RESULTS: Three hundred and thirty nine patients (60.5 ±10.0 years and 209 men) and 414 vessels with direct invasive FFR were included in the analysis. At per-vessel level, sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of DVFFR were 94.7%, 88.6%, 90.8%, 82.7%, and 96.7%, respectively. The area under the receiver operating characteristics curve (AUC) was 0.95 for DVFFR and 0.56 for CTA-based assessment with a significant difference (P < 0.0001). At patient level, sensitivity, specificity, accuracy, PPV and NPV of DVFFR were 93.8%, 88.0%, 90.3%, 83.0%, and 95.8%, respectively. The computation for DVFFR was fast with the average time of 22.5 ± 1.9 s. CONCLUSIONS The results demonstrate that DVFFR was able to evaluate lesion hemodynamic significance accurately and effectively with improved diagnostic performance over CTA alone. Coronary artery disease (CAD) is a critical disease in which coronary artery luminal narrowing may result in myocardial ischemia. Early and effective assessment of myocardial ischemia is essential for optimal treatment planning so as to improve the quality of life and reduce medical costs.

Objective To construct an aptamer-functionalized carboxylated graphene oxide(CGO)fluo-rescent sensor to achieve highly sensitive and specific detection of ketamine(KET)and its metabolite norketamine(NK)using an aptamer capable of simultaneously recognizing KET and NK.Methods A specific aptamer for simultaneous recognition of KET and NK was screened using graphene oxide-sys-tematic evolution of ligand by exponential enrichment(GO-SELEX)and molecular docking tech-niques.The aptamer,labeled with Cy5 fluorescence,was chemically conjugated to CGO to construct an aptamer-functionalized CGO fluorescent sensor.By optimizing detection conditions,including the mass concentration of CGO,aptamer concentration,reaction temperature,and incubation time,quantita-tive analysis of the target analytes was achieved using the ratio of fluorescence intensity changes be-fore and after target addition.The stability of the sensor in biological matrices was evaluated by moni-toring fluorescence intensity changes over incubation time in blank blood and urine,in comparison with the traditional physical adsorption-based CGO fluorescent sensor.Spiked recovery experiments in blank blood and urine were conducted to compare performance with that of HPLC-MS/MS.Results A specific aptamer A5 was selected and chemically conjugated with CGO to construct the aptamer-functionalized CGO fluorescent sensor.Under optimized conditions,the proposed fluorescent sensor ex-hibited a linear detection range of 1.0-5.0 ng/mL for KET,with a limit of detection(LOD)of 0.86 ng/mL;while for NK,the linear detection range was 1.0-5.0 ng/mL,with an LOD of 0.70 ng/mL.Com-pared with the CGO fluorescent sensor constructed via physical adsorption,this sensor demonstrated greater stability in blood and urine.The spiked recovery rates of KET and NK in blank blood and urine ranged from 81.50%to 110.03%,exhibiting detection performance comparable to that of HPLC-MS/MS.Conclusion The aptamer screening method offers a novel approach for selecting aptamers tar-geting drugs and their metabolites.The constructed aptamer-functionalized CGO fluorescent sensor pro-vides an efficient and reliable strategy for the high-performance detection of KET and NK.

Patient 1,a 12-day-old female infant,presented with fever,cough,dyspnea,and elevated infection markers,requiring respiratory support.Metagenomic next-generation sequencing(mNGS)of blood and bronchoalveolar lavage fluid revealed Legionella pneumophila(LP),leading to diagnoses of LP pneumonia and LP sepsis.The patient was treated with erythromycin for 15 days and azithromycin for 5 days,resulting in recovery and discharge.Patient 2,an 11-day-old female infant,presented with dyspnea,fever,elevated infection markers,and multiple organ dysfunction,requiring mechanical ventilation.mNGS of blood and cerebrospinal fluid indicated LP,leading to diagnoses of LP pneumonia,LP sepsis,and LP intracranial infection.The patient was treated with erythromycin for 19 days and was discharged after recovery.Neonatal LP pneumonia lacks specific clinical symptoms,and azithromycin is the preferred antimicrobial agent.The use of mNGS can provide early and definitive diagnosis for severe neonatal pneumonia of unknown origin.

Objective To explore early postoperative gait characteristics and clinical outcomes after total knee arthroplasty(TKA).Methods From February 2023 to July 2023,26 patients with unilateral knee osteoarthritis(KOA)were treated with TKA,including 4 males and 22 females,aged from 57 to 85 years old with an average of(67.58±6.49)years old;body mass in-dex(BMI)ranged from 18.83 to 38.28 kg·m-2 with an average of(26.43±4.15)kg·m-2;14 patients on the left side,12 pa-tients on the right side;according to Kellgren-Lawrence(K-L)classification,6 patients with grade Ⅲ and 20 patients with grade Ⅳ;the courses of disease ranged from 1 to 14 years with an average of(5.54±3.29)years.Images and videos of standing up and walking,walking side shot,squatting and supine kneeling were taken with smart phones before operation and 6 weeks after operation.The human posture estimation framework OpenPose were used to analyze stride frequency,step length,step length,step speed,active knee knee bending angle,stride length,double support phase time,as well as maximum hip flexion angle and maximum knee bending angle on squatting position.Western Ontario and McMaster Universities(WOMAC)arthritis index and Knee Society Score(KSS)were used to evaluate clinical efficacy of knee joint.Results All patients were followed up for 5 to 7 weeks with an average of(6.00±0.57)weeks.The total score of WOMAC decreased from(64.85±11.54)before op-eration to(45.81±7.91)at 6 weeks after operation(P＜0.001).The total KSS was increased from(101.19±9.58)before opera-tion to(125.50±10.32)at 6 weeks after operation(P＜0.001).The gait speed,stride frequency and stride length of the affected side before operation were(0.32±0.10)m·s-1,(96.35±24.18)steps·min-1,(0.72±0.14)m,respectively;and increased to(0.48±0.11)m·s 1,(104.20±22.53)steps·min-1,(0.79±0.10)m at 6 weeks after operation(P＜0.05).The lower limb support time and active knee bending angle decreased from(0.31±0.38)sand(125.21±11.64)° before operation to(0.11±0.04)s and(120.01±13.35)° at 6 weeks after operation(P＜0.05).Eleven patients could able to complete squat before operation,13 patients could able to complete at 6 weeks after operation,and 9 patients could able to complete both before operation and 6 weeks after operation.In 9 patients,the maximum bending angle of crouching position was increased from 76.29° to 124.11° before operation to 91.35° to 134.12° at 6 weeks after operation,and the maximum bending angle of hip was increased from 103.70° to 147.25° before operation to 118.61° to 149.48° at 6 weeks after operation.Conclusion Gait analysis technology based on artificial intelligence image recognition is a safe and effective method to quantitatively identify the changes of pa-tients'gait.Knee pain of KOA was relieved and the function was improved,the supporting ability of the affected limb was im-proved after TKA,and the patient's stride frequency,stride length and stride speed were improved,and the overall movement rhythm of both lower limbs are more coordinated.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*

Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS/MS) was used to rapidly identify the chemical components in Dracocephalum moldavica, and UPLC was employed to determine the content of its main components. MS analysis was performed using an electrospray ionization(ESI) source and data were collected in the negative ion mode. By comparing the retention time and mass spectra of reference compounds, and using a self-built compound database and the PubChem database, 68 compounds were identified from D. moldavica, including 36 flavonoids, 22 phenylpropanoids, 4 phenols, and 6 other compounds. On this basis, a UPLC quantitative method was established to simultaneously determine 8 main components, i.e., luteolin-7-O-glucuronide, apigenin-7-O-glucuronide, rosmarinic acid, diosmetin-7-O-glucuronide, tilianin, acacetin-7-O-glucuronide, acacetin-7-O-(6″-O-malonyl)-glucoside, and acacetin. A Waters ACQUITY BEH C_(18) column(2.1 mm × 100 mm, 1.7 μm) was used, with acetonitrile and a water solution containing 0.1% formic acid and 0.1% phosphoric acid as the mobile phase for gradient elution. The detection wavelength was set at 330 nm, with a flow rate of 0.4 mL·min~(-1), and the column temperature was maintained at 35 ℃. The 8 components demonstrated good linearity(r≥0.999 9) over a wide mass concentration range(50 or 100 times). The average recovery rate ranged from 97.5% to 105.1%, and the relative standard deviations(RSDs) were 0.90% to 3.4%(n= 6), indicating that the method was simple, accurate, and reliable. In 17 batches of D. moldavica samples, the content of these 8 components ranged from 0.405 to 2.10, 0.063 to 0.342, 0.446 to 2.43, 0.415 to 1.47, 1.57 to 4.34, 0.173 to 0.386, 1.00 to 5.40, and 0.069 to 0.207 mg·g~(-1), respectively. These results indicate significant differences in the internal quality of the samples, highlighting the need for strict quality control to ensure their pharmacodynamic efficacy. This study provides a scientific basis for the rapid discovery of pharmacodynamic substances, comprehensive quality control, and the formulation or revision of quality standards for D. moldavica.
Tandem Mass Spectrometry/methods* ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Lamiaceae/chemistry* ; Flavonoids/chemistry*

Objective: To investigate the natural regression and related factors of high-grade squamous intraepithelial lesion (HSIL) in the cervix of childbearing age women, and to evaluate the applicability of conservative management for future fertility needs. Methods: This study included 275 patients of reproductive age with fertility needs, who were diagnosed as HSIL by biopsy from April 30, 2015 to April 30, 2022, including 229 cases (83.3%) cervical intraepithelial neoplasia (CIN) Ⅱ and 46 cases (16.7%) CIN Ⅱ-Ⅲ. They were followed-up without immediate surgery in the First Affiliated Hospital of Nanjing Medical University. The median follow-up time was 12 months (range: 3-66 months). The regression, persistence and progression of lesions in patients with HSIL were analyzed during the follow-up period, the influencing factors related to regression and the time of regression were analyzed. Results: (1) Of the 275 HSIL patients, 213 cases (77.5%, 213/275) experienced regression of the lesion during the follow-up period. In 229 CIN Ⅱ patients, 180 cases (78.6%) regressed, 21 cases (9.2%) persisted, and 28 cases (12.2%) progressed. In 46 CIN Ⅱ-Ⅲ patients, 33 cases (71.7%) regressed, 12 cases (26.1%) persisted, and 1 case (2.2%) progressed to invasive squamous cell carcinoma stage Ⅰ a1. There was no significant difference in the regression rate between the two groups (χ²=1.03, P=0.309). (2) The average age at diagnosis, age <25 years old at diagnosis were independent influencing factor of HSIL regression in univariate analysis (all P<0.05). There was no significant difference between HSIL regression and pathological grading, the severity of screening results, human papillomavirus (HPV) genotype, colposcopy image characteristics, number of biopsies during follow-up and pregnancy experience (all P>0.05). (3) The median regression times for patients aged ≥25 years and <25 years at diagnosis were 15 and 12 months, respectively. Kaplan-Meier analysis showed that age ≥25 years at diagnosis significantly increased the median regression time compared to <25 years (χ²=6.02, P=0.014). Conclusions: For HSIL patients of childbearing age, conservative management without immediate surgical intervention is preferred if CINⅡ is fully evaluated through colposcopy examination. Age ≥25 years at diagnosis is a risk factor affecting the prognosis of HSIL patients.
Pregnancy ; Humans ; Female ; Adult ; Cervix Uteri/pathology* ; Uterine Cervical Neoplasms/pathology* ; Uterine Cervical Dysplasia/pathology* ; Biopsy ; Colposcopy/methods* ; Squamous Intraepithelial Lesions/pathology* ; Carcinoma in Situ/pathology* ; Papillomaviridae/genetics* ; Papillomavirus Infections/diagnosis* ; Squamous Intraepithelial Lesions of the Cervix/pathology*

Humans ; Consensus ; Hypersensitivity ; Desensitization, Immunologic/adverse effects* ; Immunotherapy/adverse effects* ; Injections, Subcutaneous ; Allergens

Arthropods of medical importance such as mosquitoes, ticks and sandflies are one of the key drivers of arthropod-borne diseases outbreak, posing a great threat to global public health security. For further understanding the transmission mechanisms of arthropod-borne diseases and establishing the prevention and control measures, a series of experiments of arthropods infection need to be carried out under laboratory conditions. Besides the regular biosafety requirements, some specific considerations need to be taken into account when performing arthropod infection and the infected arthropod rearing. Except for the physical containment composed of biosafety facilities, a comprehensive assessment of the biosafety risks during operations and corresponding preventive measures are also critical to eliminate or mitigate the biosafety risks. In this paper, we introduce our practice in handling mosquito infection with Risk Group 2 pathogens in Arthropod Containment Level-2 (ACL-2) laboratory, with an aim to provide a reference for researchers in related fields.