Based on CT scan data,a bionic model of lumbar spine injuries with high biofidelity is developed and validated through cadaver experiments.Decoupling the constraint system that affects occupants during collisions due to inertial forces and the subsequent pressure exerted by the seat upon returning to position,a simulated fall experiment is designed.The simulated outcomes are trained and predicted using deep learning algorithms,and the accuracy of the trained neural network prediction model is verified.Key parameters are analyzed for correlation using principal component analysis and cross-reverse methods.The results shows that the predicted lumbar spine injury model obtained from training has high reliability(R2>0.9).Comprehensive analysis reveals that after experiencing axial impact,the L4 vertebral body bears the highest impact load and can be used as a representative measure of lumbar spine injury.Among the environmental variables,the axial force on the L4 lumbar spine is mainly affected by torso mass and fall height,both of which have positive correlations.Torso mass,fall height,and posture angle all have positive effects on internal energy.Conversely,torso mass and fall height have negative correlations with stress.These research findings provide a scientific basis for further elucidating lumbar spine injury mechanisms in intelligent cockpit environments,devising corresponding safety protection measures,and evaluating occupant safety in automobiles.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Based on CT scan data,a bionic model of lumbar spine injuries with high biofidelity is developed and validated through cadaver experiments.Decoupling the constraint system that affects occupants during collisions due to inertial forces and the subsequent pressure exerted by the seat upon returning to position,a simulated fall experiment is designed.The simulated outcomes are trained and predicted using deep learning algorithms,and the accuracy of the trained neural network prediction model is verified.Key parameters are analyzed for correlation using principal component analysis and cross-reverse methods.The results shows that the predicted lumbar spine injury model obtained from training has high reliability(R2>0.9).Comprehensive analysis reveals that after experiencing axial impact,the L4 vertebral body bears the highest impact load and can be used as a representative measure of lumbar spine injury.Among the environmental variables,the axial force on the L4 lumbar spine is mainly affected by torso mass and fall height,both of which have positive correlations.Torso mass,fall height,and posture angle all have positive effects on internal energy.Conversely,torso mass and fall height have negative correlations with stress.These research findings provide a scientific basis for further elucidating lumbar spine injury mechanisms in intelligent cockpit environments,devising corresponding safety protection measures,and evaluating occupant safety in automobiles.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

BACKGROUND:At present,a large number of studies have found that Liuwei Dihuang Pill can be used to treat osteoporosis,but there are few related studies on the differentiation and mineralization of osteoblasts induced by wear particles using Liuwei Dihuang Pill. OBJECTIVE:To investigate the positive effect of different concentrations of Liuwei Dihuang Pill-containing serum on titanium particle-induced mouse MC3T3-E1 osteoblast in vitro osteolysis model. METHODS:Drug-containing serum was extracted after oral administration of Liuwei Dihuang Pill.The best concentration of Liuwei Dihuang Pill-containing serum and titanium particles on the viability of MC3T3-E1 cells was screened.MC3T3-E1 cells were divided into three groups.The blank group was given osteoblastic differentiation culture.The model group was given titanium particles(5 μg/mL)ossification culture.The drug-containing serum group was given titanium particles(5 μg/mL)+ Liuwei Dihuang Pill-containing serum(10%,15%and 20%doses).Osteoblast viability was detected by CCK-8 assay.Cell alkaline phosphatase activity was detected by alkaline phosphatase staining.Cell mineralization was detected by silver nitrate(Von Kossa)and alizarin red staining.Expression levels of bone differentiation-related genes Runx-2,Osterix,Ocn,Axin,Alp,and Opn were detected by qRT-PCR.Wnt/β-catenin signaling pathways β-catenin,p-GSK-3β,GSK-3β,Runx2 and Osterix protein expression levels were detected by western blot assay. RESULTS AND CONCLUSION:(1)Liuwei Dihuang Pill-containing serum culture reversed the decrease in alkaline phosphatase activity of MC3T3E-1 cells induced by titanium particles,increased the alizarin red staining and calcification of MC3T3E-1 cells,increased the expression of osteogenesis-related genes in MC3T3E-1 cells,and increased the expression of proteins related to the Wnt/β-catenin signaling pathway.(2)These findings indicate that Liuwei Dihuang Pill-containing serum can reverse the inhibitory effect of titanium particles on the differentiation and mineralization of osteoblasts,upregulate the expression of osteogenesis-related genes,and its mechanism is related to the regulation of Wnt/β-catenin signaling pathway,suggesting that Liuwei Dihuang Pill is expected to become an effective drug for preventing aseptic loosening of artificial joints.

Objective:To obtain hepatitis B virus capsid-like particles (CLPs) displaying B-cell linear epitopes of SARS-CoV-2 spike protein and evaluate their immunogenicity.Methods:Four recombinant plasmids expressing fusion proteins (M1-HBc, S1-57-HBc, S14P5-HBc and S21P2-HBc) were constructed by separately replacing codon of alanine at position 80 of hepatitis B virus core protein (HBc) with four genes coding for four B-cell linear epitopes (M1, S1-57, S14P5 and S21P2). These four recombinant proteins were expressed in E. coli BL21 Star (DE3) strains. The expression products were identified using SDS-PAGE, Western blot and native agarose gel electrophoresis (NAGE). CLPs were purified by sucrose density gradient ultracentrifugation, verified for antigenicity by Western blot and used to immunize BALB/c mice. Serum antibody titers were detected by ELISA. Results:The recombinant fusion proteins M1-HBc and S1-57-HBc self-assembled into M1-CLP and S1-57-CLP. The titer of antibody against S1-57 polypeptide in S1-57-CLP-immunized mouse serum approached 1∶1 000 000.Conclusions:Hepatitis B virus CLPs displaying SARS-CoV-2 M1 or S1-57 linear epitopes are successfully expressed in a prokaryotic system and purified. S1-57-CLP has good immunogenicity. This study provides a new idea for the development of novel diagnostic reagents and vaccines for SARS-CoV-2.

Objective To study the value of ropivacaine combined with dexmedetomidine for deep plane block anesthesia of anterior serratus muscle in breast mass resection.Methods A total of 88 patients who underwent elective breast mass resection in Rugao People's Hospital from February 2020 to February 2022 were selected and divided into two groups according to the random number table,with 44 patients in each group.Before induction of anesthesia,deep plane block anesthesia of anterior serratus muscle was performed in both groups.Ropivacaine was used in group R,and ropivacaine and dexmedetomidine were used in group RD.Intraoperative propofol dosage,intraoperative remifentanil dosage,sufentanil dosage within 24 hours after operation,and extubation time were compared between the two groups.Mean arterial pressure(MAP)and heart rate(HR)were recorded before anesthesia(T0),during skin incision(T1),at 15 minutes of surgery(T2),and at 30 minutes of surgery(T3).Visual analog scale(VAS)score was recorded at 4,8,12 and 24 hours after surgery.The adverse reactions were observed.Results The dosages of propofol,remifentanil and sufentanil in the RD group were less than those in the R group,and the extubation time of the RD group was shorter than that of the R group(P<0.05).MAP and HR increased first and then decreased with the operation time in both groups(P<0.05).MAP and HR in the RD group were lower than those in the R group at T1,T2 and T3(P<0.05).Postoperative VAS scores of the two groups increased first and then decreased with time(P<0.05).The VAS scores in the RD group were lower than those in the R group 4,8,12 and 24 hours after surgery(P<0.05).The incidence of adverse reactions in the RD group was lower than that in the R group(P<0.05).Conclusion Ropivacaine combined with dexmedetomidine for deep plane block of anterior serratus muscle in breast mass resection can reduce the use of anesthetics,maintain the hemodynamic stability,and reduce the degree of postoperative pain.It has high safety.

Objective The CRISPR/Cas9 system was utilized to generate an Apoe knockout mice model to support further investigations of the role of Apoe in lipid metabolism and atherosclerosis.Methods Two single guide RNAs designed for Apoe in C57BL/6J mice were co-injected with Cas9 mRNA into fertilized eggs,followed by transplantation into ICR recipient mice to obtain F0 generation mice.KO mice were identified by polymerase chain reaction(PCR)screening of tail DNA.Apoe mRNA expression in various tissues was assessed by quantitative real-time PCR and lipid indexes were measured in serum samples.Lipid accumulation in the inner lining of aortic vessels was detected by oil red O staining.Results PCR and sequencing confirmed the successful construction of Apoe KO mice(C57BL/6-Apoeem1/Nifdc).Apoe mRNA levels were significantly reduced in the liver,brain,spleen,kidney,and lung tissues of Apoe KO homozygous mice(Apoe-/-),as shown by reverse transcription quantitative real-time PCR.Serum total cholesterol and low-density lipoprotein cholesterol levels were increased in Apoe-/-mice,and high-density lipoprotein cholesterol levels were decreased in male Apoe-/-mice.Extensive lipid plaques were observed in the inner lining of the arteries in Apoe-/-mice compared with WT mice,under normal chow consumption conditions.Conclusions This study successfully established an Apoe KO mice model exhibiting a typical abnormal lipid metabolism phenotype with arterial lipid accumulation,even without a high-fat diet intervention.This work provides background data for the Apoe KO mice resource and a new model for the study of abnormal lipid metabolism.

Objective We generated ob mice(C57BL/6N-Lepem1/Nifdc)with Lep gene knockout(ob/ob)using the CRISPR/Cas9 system,to establish a suitable animal model for preclinical drug evaluation for clinical diseases such as diabetes.Methods According to the principle of CRISPR/Cas9 target design,single guide RNA targeting the mouse Lep gene was designed for transcription in vitro,and microinjected with Cas9 mRNA into mouse zygotes.Mouse tail DNA was extracted and detected by polymerase chain reaction and sequencing,followed by mating of positive and wild-type mice.Blood biochemistry and liver pathology were assessed in homozygous ob mice.Results Eight positive mice were identified and a stable mouse strain was selected for further breeding.Serum triglycerides,total cholesterol,and alanine aminotransferase levels were significantly higher in homozygous ob mice than in wild-type mice,and liver pathology showed inflammatory infiltration and lipid vacuolar transformations.Conclusions We successfully established a Lep gene knockout mouse model,which will provide an important addition to the national rodent experimental animal database and an animal model for preclinical drug evaluation.