ObjectiveTo investigate the effect of folic acid-modified crebanine polyethylene glycol-polylactic acid hydroxyacetic acid copolymer（PEG-PLGA） nanoparticles（FA-Cre@PEG-PLGA NPs， hereinafter referred to as NPs） combined with ultrasonic irradiation on subcutaneous tumor of liver cancer in Kunming（KM） mice. MethodsEighty-four healthy male KM mice were utilized to establish a subcutaneous tumor model of mouse hepatocellular carcinoma with H22 cells， then mice were randomly divided into model group， placebo group， hydroxycamptothecin group（8 mg∙kg^-1）， low， medium and high dose crebanine raw material groups（2， 2.5， 3 mg∙kg^-1， hereinafter referred to as the low， medium and high dose crebanine groups， respectively）， low， medium and high dose NPs groups（2， 2.5， 3 mg∙kg^-1）， and low， medium and high dose NPs combined with ultrasonic irradiation groups（2， 2.5， 3 mg∙kg^-1， hereinafter referred to as the low， medium and high dose combination groups， respectively）. The corresponding doses of drugs were administered via tail vein injection， the model group received no treatment， while the placebo group was injected with an equivalent amount of normal saline. Dosing was conducted for a total of 10 times on alternate days. The body mass of the mice was monitored， and parameters such as body mass change rate， thymus index， spleen index， tumor volume， tumor weight， relative tumor growth rate（T/C）， and tumor inhibition rate（TGI） were calculated. Pathological changes in liver and kidney tissues as well as the tumor were observed by hematoxylin-eosin（HE） staining. Additionally， the levels of aspartate aminotransferase（AST）， alanine aminotransferase（ALT）， blood urea nitrogen（BUN） and creatinine（CREA） in serum of mice were detected by biochemical method. Furthermore， the effect of ultrasound on the distribution of NPs in subcutaneous tumors of mouse hepatocellular carcinoma was observed by in vivo imaging technique. ResultsAmong different treatment methods， the combination of NPs and ultrasound irradiation had the best therapeutic effect. Compared with the model group， the body mass growth rates of mice in the medium and high combination groups decreased， while the thymus index and spleen index increased， but there was no statistically significant difference in serum AST， ALT， BUN and CREA levels， indicating that NPs combined with ultrasound irradiation had little effect on the normal physiological state of the body， oth groups had TGI>40% and T/C<60%， indicating a clear anti-tumor effect. Pathological analysis showed that compared with the NPs groups， the combination groups exhibited varying degrees of necrosis in tumor cells， accompanied by less damage to the liver and kidneys. In vivo imaging of small animals showed that compared with the high dose NPs group， the high dose combination group had stronger tumor targeting ability（P<0.01）. ConclusionNPs combined with ultrasonic irradiation can not only effectively targeted the drug to the tumor site， inhibit the subcutaneous tumor growth of mouse liver cancer， but also decrease damage to liver and kidney tissues.

Intraoperative cell salvage (IOCS) has been widely applied as an important blood conservation measure in surgical operations. However, there is currently a lack of clinical practice guidelines for the implementation of IOCS in patients with malignant tumors. This report aims to provide clinicians with recommendations on the use of IOCS in patients with malignant tumors based on the review and assessment of the existed evidence. Data were derived from databases such as PubMed, Embase, the Cochrane Library and Wanfang. The guideline development team formulated recommendations based on the quality of evidence, balance of benefits and harms, patient preferences, and health economic assessments. This study constructed seven major clinical questions. The main conclusions of this guideline are as follows: 1) Compared with no perioperative allogeneic blood transfusion (NPABT), perioperative allogeneic blood transfusion (PABT) leads to a more unfavorable prognosis in cancer patients (Recommended); 2) Compared with the transfusion of allogeneic blood or no transfusion, IOCS does not lead to a more unfavorable prognosis in cancer patients (Recommended); 3) The implementation of IOCS in cancer patients is economically feasible (Recommended); 4) Leukocyte depletion filters (LDF) should be used when implementing IOCS in cancer patients (Strongly Recommended); 5) Irradiation treatment of autologous blood to be reinfused can be used when implementing IOCS in cancer patients (Recommended); 6) A careful assessment of the condition of cancer patients (meeting indications and excluding contraindications) should be conducted before implementing IOCS (Strongly Recommended); 7) Informed consent from cancer patients should be obtained when implementing IOCS, with a thorough pre-assessment of the patient's condition and the likelihood of blood loss, adherence to standardized internally audited management procedures, meeting corresponding conditions, and obtaining corresponding qualifications (Recommended). In brief, current evidence indicates that IOCS can be implemented for some malignant tumor patients who need allogeneic blood transfusion after physician full evaluation, and LDF or irradiation should be used during the implementation process.

Background Asthma poses a serious threat to children's growth, development, and mental health, thus there has been an increasing focus on the control of asthma morbidity in children and the assessment of its risk factors. A growing body of research has found that exposure to ambient air pollutants an significatly increase the risk of childhood asthma. Objective To understand the changes of ambient air pollutant concentrations in Nanjing and asthma outpatient visits to Nanjing Children's Hospital, and to quantitatively analyze the effects of exposure to different ambient air pollutants on children's asthma outpatient visits. Methods Daily data of ambient air pollutants fine particulate matter (PM_2.5), inhalable particle (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), ozone (O₃), meteorological factors (air temperature & relative humidity), and outpatient visits due to asthma in the hospital from January 1, 2019 to December 31, 2023 were collected, and a generalized additive model based on quasi poisson distributions was used to quantitatively analyze the short-term effects of ambient air pollutant exposure on outpatient visits due to asthma in the hospital. Results The annual average concentrations of PM_2.5, PM₁₀, SO₂, and NO₂ in Nanjing from 2019 to 2023 did not exceed the national limits. For single-day lagged effects, the single-pollutant model showed that the effects of PM_2.5, PM₁₀, NO₂, and CO on children's asthma outpatient visits were greatest for every 10 units increase at lag0, with excess risk (ER) of 1.39% (95%CI: 0.65%, 2.14%), 1.46% (95%CI: 0.97%, 1.95%), 5.46% (95%CI: 4.36%, 6.57%), and 0.18% (95%CI: 0.11%, 0.26%), respectively, and SO₂ reached the maximum effect at lag1, with an ER of 23.15% (95%CI: 13.57%, 33.53%) for each 10 units increase in concentration. Different pollutants reached their maximum cumulative lag effects at different time. The PM₁₀, PM_2.5, SO₂, NO₂, and CO showed the largest cumulative lag effects at lag01, lag01, lag02, lag02, and lag03, respectively, with ERs of 1.35% (95%CI: 0.77%, 1.92%), 0.96% (95%CI: 0.10%, 1.83%), 28.50% (95%CI: 15.49%, 42.98%), 6.92% (95%CI: 5.53%, 8.33%), and 0.31% (95%CI: 0.20%, 0.42%), respectively. The influences of PM_2.5 and PM₁₀ on outpatient visits due to asthma in the hospital became more pronounced with advancing age, while the associations with NO₂, SO₂, and CO were weakened as children grew older. Conclusion Ambient air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, CO) can increase childhood asthma visits, and different pollutants have varied effects on the number of asthmatic children's visits at different ages.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Subarachnoid hemorrhage (SAH) is a serious intracranial hemorrhage characterized by acute bleeding into the subarachnoid space. The effects of shikonin, a natural compound from the roots of Lithospermum erythrorhizon, on oxidative stress and blood–brain barrier (BBB) injury in SAH was evaluated in this study. A rat model of SAH was established by endovascular perforation to mimic the rupture of intracranial aneurysms. Rats were then administered 25 mg/kg of shikonin or dimethylsulfoxide after surgery. Brain edema, SAH grade, and neurobehavioral scores were measured after 24 h of SAH to evaluate neurological impairment. Concentrations of the oxidative stress markers superoxide dismutase (SOD), glutathione (GSH), and malondialdehyde (MDA) in the brain cortex were determined using the corresponding commercially available assay kits. Evans blue staining was used to determine BBB permeability. Western blotting was used to quantify protein levels of tight junction proteins zonula occludens-1, Occludin, and Claudin-5. After modeling, the brain water content increased significantly whereas the neurobehavioral scores of rats with SAH decreased prominently. MDA levels increased and the levels of the antioxidant enzymes GSH and SOD decreased after SAH. These changes were reversed after shikonin administration. Shikonin treatment also inhibited Evans blue extravasation after SAH. Furthermore, reduction in the levels of tight junction proteins after SAH modeling was rescued after shikonin treatment. In conclusion, shikonin exerts a neuroprotective effect after SAH by mitigating BBB injury and inhibiting oxidative stress in the cerebral cortex.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Subarachnoid hemorrhage (SAH) is a serious intracranial hemorrhage characterized by acute bleeding into the subarachnoid space. The effects of shikonin, a natural compound from the roots of Lithospermum erythrorhizon, on oxidative stress and blood–brain barrier (BBB) injury in SAH was evaluated in this study. A rat model of SAH was established by endovascular perforation to mimic the rupture of intracranial aneurysms. Rats were then administered 25 mg/kg of shikonin or dimethylsulfoxide after surgery. Brain edema, SAH grade, and neurobehavioral scores were measured after 24 h of SAH to evaluate neurological impairment. Concentrations of the oxidative stress markers superoxide dismutase (SOD), glutathione (GSH), and malondialdehyde (MDA) in the brain cortex were determined using the corresponding commercially available assay kits. Evans blue staining was used to determine BBB permeability. Western blotting was used to quantify protein levels of tight junction proteins zonula occludens-1, Occludin, and Claudin-5. After modeling, the brain water content increased significantly whereas the neurobehavioral scores of rats with SAH decreased prominently. MDA levels increased and the levels of the antioxidant enzymes GSH and SOD decreased after SAH. These changes were reversed after shikonin administration. Shikonin treatment also inhibited Evans blue extravasation after SAH. Furthermore, reduction in the levels of tight junction proteins after SAH modeling was rescued after shikonin treatment. In conclusion, shikonin exerts a neuroprotective effect after SAH by mitigating BBB injury and inhibiting oxidative stress in the cerebral cortex.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.