ObjectiveTo analyze the distribution, drug resistance characteristics, and changing trends of Acinetobacter baumannii (AB) isolated from environmental surfaces and healthcare workers’ hands in a grade Ⅱ level A general hospital in Xuhui District of Shanghai from 2018 to 2023, and to provide reference for infection control in the hospital. MethodsEnvironmental samples were collected quarterly from critical surfaces and healthcare workers’ hands in the intensive care unit (ICU), geriatrics, and respiratory departments from 2018 to 2023. Clinical isolates were obtained from all patients with AB infections in ICU, geriatrics, respiratory department, rehabilitation department, infectious diseases department, emergency department, cardiology department, and orthopedics of the hospital from 2018 to 2023. Retrospective analyses were performed on AB detection rates, strain origins, resistance rates to commonly used antimicrobial agents, and resistance gene features, comparing the antimicrobial resistance between clinically isolated strains and environmentally isolated strains. ResultsFrom 2018 to 2023, a total of 1 416 samples were collected from the hospital and a total of 272 strains of AB were detected, with a positive detection rate of 19.21%. The detection rate gradually decreased year-on-year (χ²_trend=45.290, P<0.001). The majority of samples originated from patient-contacted items (34.56%, 94/272), followed by shared items (26.84%, 73/272) and healthcare worker-contacted items (15.07%, 41/272). From 2018 to 2023, the resistance rate of AB on environmental surfaces and healthcare workers’ hands to commonly tested antibiotics in the hospital ranged from 10% to 40%. The resistance rates to cefotaxime (42.52%) and piperacillin (38.58%) were relative high, while the resistance to polymyxin E (1.57%), polymyxin B (2.36%), and doxycycline (3.94%) maintained low. The annual fluctuations in resistance to cefotaxime, piperacillin, ceftriaxone, tobramycin, doxycycline, minocycline and cotrimoxazole were statistically significant (all P<0.05). There were statistically significant differences in the resistance of clinical and environmental isolates to ampicillin/sulbactam, cefepime, ceftazidime, subamphetamine, meropenem, piperacillin, aztreonam, gentamicin, tobramycin, minocycline, ciprofloxacin, levofloxacin, and cotrimoxazole in the hospital from 2018 to 2023 (all P<0.05). The resistance rate of clinical isolates was generally high, especially to β-lactam and quinolone drugs, which were mostly above 80% [such as cefepime (93.86%), cefotaxime (97.37%), imipenem (98.25%), and ciprofloxacin (99.12%)]. The resistance rate of environmental isolated strains to similar antibiotics was relatively lower, mostly concentrated at 10%‒30%. The whole-genome sequencing of 34 carbapenem-resistant Acinetobacter baumannii (CRAB) strains isolated from the hospital environment in 2023 revealed that the main resistance mechanism was overexpression of efflux pumps (51.97%), followed by changes in target sites (32.46%). Among the 34 CRAB strains, carbapenem resistance genes OXA-23 and OXA-51 were detected in 6 strains (17.65%), while genes such as KPC, IMP, VIM, and SIM were not detected. ConclusionFrom 2018 to 2023, AB in the hospital environment exhibited high resistance rates to certain antimicrobial agents and carried multiple resistance genes, indicating a potential transmission risk. It is necessary to further strengthen bacterial resistance monitoring and hospital infection control, and use antibiotics reasonably.

Prostate cancer is the second most common cancer in men, accounting for 14.1% of new cancer cases in 2020. The aggressiveness of prostate cancer is highly variable, depending on its grade and stage at the time of diagnosis. Despite recent advances in prostate cancer treatment, some patients still experience recurrence or even progression after undergoing radical treatment. Accurate initial staging and monitoring for recurrence determine patient management, which in turn affect patient prognosis and survival. Classical imaging has limitations in the diagnosis and treatment of prostate cancer, but the use of novel molecular probes has improved the detection rate, specificity, and accuracy of prostate cancer detection. Molecular probe-based imaging modalities allow the visualization and quantitative measurement of biological processes at the molecular and cellular levels in living systems. An increased understanding of tumor biology of prostate cancer and the discovery of new tumor biomarkers have allowed the exploration of additional molecular probe targets. The development of novel ligands and advances in nano-based delivery technologies have accelerated the research and development of molecular probes. Here, we summarize the use of molecular probes in positron emission tomography (PET), single-photon emission computed tomography (SPECT), magnetic resonance imaging (MRI), optical imaging, and ultrasound imaging, and provide a brief overview of important target molecules in prostate cancer.
Humans ; Male ; Prostatic Neoplasms/diagnosis* ; Molecular Probes ; Molecular Imaging/methods* ; Magnetic Resonance Imaging ; Positron-Emission Tomography ; Tomography, Emission-Computed, Single-Photon ; Ultrasonography ; Optical Imaging ; Biomarkers, Tumor ; Precision Medicine/methods*

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder worldwide, causing dementia and affecting millions of individuals. One prominent characteristic in the brains of AD patients is glucose hypometabolism. In the context of galactose metabolism, intracellular glucose levels are heightened. Galactose mutarotase (GALM) plays a crucial role in maintaining normal galactose metabolism by catalyzing the conversion of β-D-galactose into α-D-galactose (α-D-G). The latter is then converted into glucose-6-phosphate, improving glucose metabolism levels. However, the involvement of GALM in AD progression is still unclear. In the present study, we found that the expression of GALM was significantly increased in AD patients and model mice. Genetic knockdown of GALM using adeno-associated virus did not change the expression of amyloid precursor protein (APP) and APP-cleaving enzymes including a disintegrin and metalloprotease 10 (ADAM10), β-site APP-cleaving enzyme 1 (BACE1), and presenilin-1 (PS1). Interestingly, genetic overexpression of GALM reduced APP and Aβ deposition by increasing the maturation of ADAM10, although it did not alter the expression of BACE1 and PS1. Further electrophysiological and behavioral experiments showed that GALM overexpression significantly ameliorated the deficits in hippocampal CA1 long-term potentiation (LTP) and spatial learning and memory in AD model mice. Importantly, direct α-D-G (20 mg/kg, i.p.) also inhibited Aβ deposition by increasing the maturation of ADAM10, thereby improving hippocampal CA1 LTP and spatial learning and memory in AD model mice. Taken together, our results indicate that GALM shifts APP processing towards α-cleavage, preventing Aβ generation by increasing the level of mature ADAM10. These findings indicate that GALM may be a potential therapeutic target for AD, and α-D-G has the potential to be used as a dietary supplement for the prevention and treatment of AD.
Animals ; ADAM10 Protein/metabolism* ; Alzheimer Disease/pathology* ; Amyloid Precursor Protein Secretases/metabolism* ; Disease Models, Animal ; Humans ; Mice ; Amyloid beta-Peptides/metabolism* ; Male ; Mice, Transgenic ; Membrane Proteins/metabolism* ; Cognitive Dysfunction/pathology* ; Mice, Inbred C57BL ; Amyloid beta-Protein Precursor/metabolism* ; Female ; Hippocampus/metabolism* ; Long-Term Potentiation/physiology*

Acute symptomatic osteoporotic thoracolumbar compression fracture (ASOTLF) can lead to chronic low back pain, kyphosis deformity, pulmonary dysfunction, loss of mobility, and even life-threatening complications. Vertebral augmentation is currently the mainstream treatment method for this condition. In 2019, the Editorial Board of Chinese Journal of Trauma and the Spinal Trauma Group of Orthopedic Surgeons Branch of Chinese Medical Doctor Association collaboratively led the development of Clinical guideline for vertebral augmentation for acute symptomatic osteoporotic thoracolumbar compression fractures. Six years later, with advances in clinical diagnosis and treatment techniques as well as accumulating evidence in related fields, the 2019 guideline requires updating. To this end, the Spinal Trauma Group of Orthopedic Surgeons Branch of Chinese Medical Doctor Association, the Spinal Health Professional Committee of China Human Health Science and Technology Promotion Association, and the Minimally Invasive Orthopedics Professional Committee of Shaanxi Medical Doctor Association have organized experts in the field to develop the Clinical guideline for vertebral augmentation of acute symptomatic osteoporotic thoracolumbar compression fractures ( version 2025) , based on the latest evidence-based medical researches. This guideline incorporates 3 recommendations retained from the 2019 version with updated strength of evidence, along with 12 new recommendations. It provides recommendations from six aspects of diagnosis, pain management, treatment option selection, prevention of postoperative complications, anti-osteoporosis therapy, and postoperative rehabilitation, aiming to provide a reference for standard treatment of vertebral augmentation for ASOTLF in hospitals at all levels.

Objective:To investigate the prognostic factors for esophageal cancer after radical resection and the application value of machine learning prediction model.Methods:The retrospective cohort study was conducted. The clinicopatholigical data of 406 esophageal cancer patients who were admitted to Qilu Hospital of Shandong University from January 2018 to March 2022 were collected. There were 357 males and 49 females, aged (64±8)years. All patients underwent radical resection of esophageal cancer. The 406 patients were randomly divided into a training set of 285 cases and a validation set of 121 cases at a 7∶3 ratio based on a random number table. The training set was used to construct prediction model, and the validation set was used to validate prediction model. Patients were divided into high-risk group and low-risk group based on risk scores. Observation indicators: (1) follow-up of patients and analysis of influencing factors for prognosis; (2) construction and validation of machine learning prediction models. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data between groups was conducted using the rank sum test. The Kaplan-Meier method was used to calculate survival rate and plot survival curve, and the Log-rank test was used for survival analysis. The Cox proportional hazard regression model was used for univariate and multivariate analyses. Independent influencing factors were included, and data processing, machine learning model construction, and visualization were performed using R packages including random survival forest (RSF), gradient boosting machine (GBM), least absolute shrinkage and selection operator Cox regression (LASSO-Cox), Cox proportional hazards model boosting (CoxBoost), survival support vector machine (survivalsvm), extreme gradient boosting (XGBoost), supervised principal component analysis (SuperPC), and Cox partial least squares regression (plsRcox). Receiver operating characteristic (ROC) curves were drawn, and sensitivity, specificity, and area under the curve (AUC) were calculated. The Delong test was used to assess the differences in AUC among different models in the training set, and the time-dependent ROC was used to compare the predictive performance of different models. Calibration curves were used to evaluate model accuracy, and decision curve analysis (DCA) was used to evaluate overall net benefit. Results:(1) Follow-up of patients and analysis of influencing factors for prognosis. All 406 patients were followed up postoperatively for 28(range, 6-36)months, with 1- and 3-year overall survival rate of 86.5% and 40.9%, respectively. The 285 patients in the training set were followed up postoperatively for 30(range, 6-36)months, with 1- and 3-year overall survival rate of 85.1% and 35.5%, respectively. The 121 patients in the validation set were followed up postoperatively for 25(range, 6-36)months, with 1- and 3-year overall survival rate of 87.0% and 43.2%, respectively. There was no significant difference in postoperative overall survival rate between the training set and the validation set ( χ2=3.20, P>0.05). Results of multivariate analysis showed that left thoracic surgical approach, preopera-tive neutrophil count, vascular invasion, perineural invasion, pathological T2-4 stage, pathological N2-3 stage, and postoperative pneumonia were independent risk factors affecting postoperative survival of 285 patients in the training set ( hazard ratio=1.466, 1.037, 1.482, 1.549, 5.268, 7.727, 22.202, 2.539, 2.686, 1.425, 95% confidence interval as 1.026-2.096, 1.003-1.073, 1.008-2.179, 1.105-2.170, 1.201-23.099, 1.833-32.576, 4.734-104.128, 1.577-4.087, 1.631-4.422, 1.018-1.994, P<0.05). (2) Construction and validation of machine learning prediction models. Independent risk factors affecting postoperative survival were included to construct RSF, GBM, LASSO-Cox, CoxBoost, survivalsvm, XGBoost, SuperPC, and plsRcox machine learning prediction models. Results of Delong test showed that there were significant differences in the AUC of RSF and GBM from the other six models ( P<0.05). Results of time-dependent ROC curve showed that all 8 machine learning predic-tion models had good discriminative ability in the training cohort, among which the RSF machine learning prediction model had the best predictive performance. Results of calibration curve showed that the RSF machine learning prediction model fitted well for predicting postoperative 1-, 2-, and 3-year overall survival in the training cohort, with high consistency with actual results. Results of decision curve analysis showed that within a threshold range of 0-0.80, the RSF machine learning prediction model provided a better overall net benefit. Further analysis showed that in the validation set, the AUC of RSF machine learning prediction model for postoperative 1-, 2-, and 3-year survival prediction were 0.786 (95% confidence interval as 0.609-0.962), 0.774 (95% confidence interval as 0.676-0.873), and 0.750 (95% confidence interval as 0.652-0.848), respectively. Results of calibration curve showed that the RSF machine learning prediction model fitted well for predicting postopera-tive 1-, 2-, and 3-year overall survival in the validation set, with high consistency with actual results. In the training set, the optimal cutoff value of the RSF machine learning prediction model risk score was 11.7. Patients with risk score ≥11.7 were classified as the high-risk group, and those with risk score <11.7 as the low-risk group. The median survival times of the two groups were 18.0 months and >36.0 months, respectively, showing a significant difference between them ( χ2=73.30, P<0.05). In the validation set, the optimal cutoff value of the RSF machine learning prediction model risk score was 11.7. Patients with risk score ≥11.7 were classified as the high-risk group, and those with risk score<11.7 as the low-risk group. The median survival times of the two groups were 17.0 months and>36.0 months for the high-risk and low-risk groups, respectively, showing a significant difference between them ( χ2=35.20, P<0.05). Conclusions:Left thoracic surgical approach, preoperative neutrophil count, vascular invasion, perineural invasion, pathological T2-4 stage, pathological N2-3 stage, and postoperative pneumonia are independent risk factors affecting survival of esophageal cancer patients after radical resection. The RSF machine learning prediction model constructed based on these factors can effectively distinguish the survival prognosis of high-risk and low-risk patients.

The biological characteristics of hepatocellular carcinoma(HCC)lead to a high incidence of portal vein tumor thrombus.It progresses rapidly,and the opportunity for radical surgical resection can be lost in a short term,resulting in poor prognosis.Reasonable down-staging treatment is a research focus for patients with unresectable HCC complicated with portal vein tumor thrombus to achieve a resectable range.This article reviews the potential population of HCC complicated with portal vein tumor thrombus with conversion therapy for HCC,analyzes the application of hepatic artery infusion chemotherapy,transcatheter arterial chemoembolization,radiotherapy,regional and systemic drug therapy in conversion therapy,and points out that the combination of multidisciplinary comprehensive treatments is the key to improve the prognosis of HCC patients with portal vein tumor thrombus.

Objective To investigate the effects of different anesthesia depths on stress states and inflammatory mediators in patients undergoing video-assisted thoracoscopic lobectomy.Methods A total of 89 lung cancer patients who underwent video-assisted thoracoscopic lobectomy were selected as study subjects.Based on intraoperative bispectral index(BIS)range,the patients were divided into deep anesthesia group(BIS of 40 to＜50,n=45)and shallow anesthesia group(BIS of 50 to＜60,n=44).Vital signs(mean arterial pressure,heart rate and blood oxygen saturation),anesthesia re-covery time,extubation time,dosage of vasoactive drugs,postoperative pain intensity[Visual Ana-logue Scale(VAS)],postoperative analgesic dosage,perioperative stress state[prostaglandin E2(PGE2),nerve growth factor(NGF)and substance P(SP)],levels of inflammatory mediators[neuron-specific enolase(NSE),tumor necrosis factor-α(TNF-α)and S100β protein]at different time points(before anesthesia induction,immediately after intubation,before lesion resection and at the end of surgery)and the incidence of anesthesia-related adverse reactions were compared between the two groups.Results Before lesion resection and at the end of surgery,the mean arterial pressure and heart rate in the deep anesthesia group were significantly lower than those in the shallow anesthe-sia group(P＜0.05).The anesthesia recovery time and extubation time in the deep anesthesia group were significantly longer than those in the shallow anesthesia group(P＜0.05).At the end of surgery and on postoperative day one,the levels of PGE2,NGF and SP in the deep anesthesia group were significantly lower than those in the shallow anesthesia group,while the levels f NSE,TNF-α and S100β protein were significantly higher than those in the shallow anesthesia group(P＜0.05).There were no significant differences in the dosage of vasoactive drugs,VAS scores,sufentanil dos-age and the incidence of anesthesia-related adverse reactions between thetwo groups(P＞0.05).Conclusion During one-lung ventilation in patients undergoing video-assisted thoracoscopic surgery lobectomy,deep anesthesia can effectively control surgical stress and maintain stability of intraopera-tive hemodynamics,but it is associated with delayed postoperative awakening and more pronounced inflammatory response.Shallow anesthesia results in faster postoperative awakening and lower levels of inflammatory mediators,but it is associated with more significant intraoperative stress response and unstable hemodynamics.

Objective To assess the clinical value of a novel surgical technique—Tubeless subxiphoid uniportal video-assisted thoracoscopic surgery with percutaneous suspension technique via balance-shaped sternal elevation device in the resection of anterior mediastinal masses. Methods Patients who underwent tubeless subxiphoid uniportal video-assisted thoracoscopic surgery via balance-shaped sternal elevation device in anterior mediastinal masses process at the Department of Thoracic Surgery, West China Hospital, Sichuan University from March to April 2025 were included, and their clinical data were analyzed. Results A total of 4 patients were included, with 2 males and 2 females, aged 58-75 years. The diameter of the tumor was 2.5-3.0 cm. The operation time was 60.0-150.0 min, intraoperative blood loss was 5-10 mL, pain score on the 3rd day after surgery was 0 points, and postoperative hospital stay was 2-3 days. All patients achieved complete resection of the masses and thymus without perioperative complications. Conclusion The tubeless subxiphoid uniportal video-assisted thoracoscopic surgery with percutaneous suspension technique via balance-shaped sternal elevation device technique optimizes surgical visualization and instrument maneuverability while avoiding complications related to conventional anesthesia and tubing, thereby markedly enhancing the minimally invasive profile of anterior mediastinal masses resections. In addition to maintaining procedural safety, this approach effectively reduces postoperative pain and accelerates patient recovery, highlighting its potential for widespread clinical adoption.

Objective:To explore the correlation between clinical and CT imaging features and epidermal growth factor receptor (EGFR) gene mutation in patients with non-small cell lung cancer (NSCLC) and screening of mutation prediction indicators.Methods:A retrospective case-control study was conducted. The clinical data of 178 NSCLC patients who were confirmed by pathology and underwent pre-treatment chest-enhanced CT scan and EGFR gene mutation testing in General Hospital of Ningxia Medical University from January 2015 to December 2019 were retrospectively analyzed. Patients were classified into EGFR mutation-positive and mutation-negative groups based on genetic testing results, and the clinical and CT imaging features were compared between the two groups; the multivariate logistic regression model was used to identify the independent influencing factors for EGFR gene mutation in NSCLC patients.Results:Among 178 NSCLC patients, 115 cases (64.6%) were EGFR gene mutation-positive and 63 cases (35.4%) were mutation-negative. Among the 115 EGFR gene mutation-positive patients, there were 61 cases (53.0%) of exon 19 deletion (19del) mutation, 45 cases (39.1%) of exon 21 L858R mutation, 8 cases (7.0%) of exon 20 mutation, and 1 case (0.9%) of exon 18 mutation. The proportions of female patients [60.0% (69/115) vs. 30.2% (19/63)] and patients with out smoking history [74.8% (86/115) vs. 36.5% (23/63)] in EGFR gene mutation-positive group were higher than those in the mutation-negative group, and the differences were statistically significant (both P < 0.001), while the proportions of patients with different pathological types and clinical stages in the two groups showed no statistically significant differences (both P > 0.05). The median maximum diameter of tumor [ M ( Q1, Q3)] detected by CT in the EGFR gene mutation-positive group was 3.70 (2.90, 4.70) cm, while in the mutation-negative group it was 5.30 (3.40, 6.80) cm, and the difference was statistically significant ( Z = -3.66, P < 0.001). The proportions of patients with air bronchogram [27.8% (32/115) vs. 7.9% (5/63)] and without emphysema [83.5% (96/115) vs. 55.6% (35/63)] in the EGFR gene mutation-positive group were higher than those in the mutation-negative group, and the differences were statistically significant (both P < 0.01). The results of multivariate logistic regression analysis showed that no smoking history (yes vs. no, OR = 0.218, 95% CI: 0.073-0.647), short maximum diameter of tumor detected by CT ( OR = 0.814, 95% CI: 0.676-0.981), air bronchogram (yes vs. no, OR = 5.354, 95% CI: 1.782-16.090), and no emphysema (yes vs. no, OR = 0.289, 95% CI: 0.128-0.653) were independent risk factors for EGFR gene mutation in NSCLC patients (all P < 0.05). Conclusions:Clinical and CT imaging features may relate to EGFR gene mutation status in NSCLC patients, and no smoking history, short maximum diameter of tumor detected by CT, air bronchogram and no emphysema may predict EGFR gene mutation.

Objective To explore the anti-inflammatory properties of the ethyl acetate extract(ETCB)derived from Trollius chinensis Bge.using in vitro RAW264.7 cells stimulated with lipopolysaccharide and an in vivo mouse auricle model induced by xylene.Utilizing UHPLC-Q-TOF-MS(LC-MS)and network pharmacology,the components of ETCB were analyzed,and its anti-inflammatory mechanisms were preliminarily explored.Methods The anti-inflammatory activity of various solvent extracts of Trollius chinensis Bge.was assessed through the Griess assay.The impact of ETCB on the production of TNF-α and IL-6 in RAW264.7 cells induced by lipopolysaccharide was evaluated using ELISA.Real-time qPCR was conducted to determine the effect of ETCB on the expression levels of inflammatory factors such as TNF-α,IL-6,and iNOS in cells.The anti-inflammatory efficacy was further validated in a xylene-induced ear inflammation mouse model by measuring ear swelling and tissue levels of IL-6 and TNF-α.The composition of ETCB was analyzed using LC-MS.Network pharmacology was employed to screen for effective components,targets,and pathways involved in the anti-inflammatory effects of Trollius chinensis Bge.,followed by molecular docking verification between core components and targets.Results ETCB demonstrated the most potent inhibitory effect on NO production in RAW264.7 cells stimulated by lipopolysaccharide,indicating its primary role in the anti-inflammatory activity of Trollius chinensis Bge..ETCB significantly reduced TNF-α and IL-6 levels in inflammatory cells(P<0.01)and inhibited the mRNA expression of TNF-α,IL-6,and iNOS.In the xylene-induced mouse ear inflammation model,ETCB effectively alleviated ear swelling and decreased tissue levels of TNF-α and IL-6.LC-MS analysis identified 30 chemical components in ETCB,including 21 flavonoids,7 organic acids,1 polysaccharide,and 1 anthocyanin.Network pharmacology prediction and screening revealed TNF,Akt1,PTGS2,EGFR,SRC,and MMP9 as core targets,with hydroxyquercetin,lignin from fragrant leaves,zeaxanthin from willows,plantain,thistle,and sophora flavins as key anti-inflammatory active ingredients.The molecular docking analysis revealed positive interactions,characterized by favorable binding energy,between the active components and key targets.Conclusion ETCB demonstrates strong anti-inflammatory properties both inside and outside the body,functioning through various targets and pathways.This establishes a basis for deeper understanding of the anti-inflammatory mechanism of Trollius chinensis Bge.