Fatigue driving is a major cause of traffic accidents,which poses a great threat to public safety and property.In order to reduce the losses caused by fatigue driving,many researchers have devoted themselves to the study about fatigue driving,such as driver behavior monitoring,brainwave monitoring,eye tracking and facial expression analysis.Each of these methods has its own advantages and disadvantages.Behavioral monitoring reflects the fatigue state by analyzing the driver's driving habits and facial expression,which is easy to operate but prone to be affected by the external environment.Brainwave monitoring is more accurate and can detect the fatigue state in real time,but the equipment is complicated and costly,which limits its large-scale application.The detection based on eye-tracking and facial expression analysis also has a certain potential for application,but errors may occur under different light conditions.Herein the review introduces the effects of fatigue on driving ability and compares the research results of various fatigue driving detection methods by searching,collating,analyzing and summarizing the relevant literatures at home and abroad.Various detection methods are analyzed and summarized,and it is pointed out that the fatigue driving detection method based on multi-feature information fusion will become a research hotspot.

Objective:To identify the key differentially expressed gene, BTF3, in cutaneous squamous cell carcinoma(cSCC)using bioinformatics methods and to preliminarily explore the potential mechanisms of BTF3 and its co-expressed genes in cSCC development. Methods:The cSCC-related datasets(GSE98767, GSE42677, GSE45164)were obtained from the Gene Expression Omnibus(GEO)database.Differential expression analysis revealed BTF3 as a significantly differentially expressed gene in cSCC.A BTF3-related co-expressed gene network was constructed and subjected to gene ontology(GO)enrichment analysis to investigate the biological processes, molecular functions, and cellular components that were significantly enriched.The study selected 60 paraffin-embedded tissue samples from the First Affiliated Hospital of Jinzhou Medical University, collected between 2020 and 2024.This cohort included 30 samples from cSCC patients and 30 samples from patients who underwent excision of melanocytic nevi.Immunohistochemical experiments were conducted to assess the expression of BTF3 in cSCC tissues.Additionally, single-sample gene set enrichment analysis(ssGSEA)was performed to assess the relevance of BTF3 to immune cells, and protein-protein interaction(PPI)analysis was employed to identify critical gene networks. Results:BTF3 was significantly overexpressed in cSCC, as confirmed by immunohistochemistry.The receiver operating characteristic(ROC)curve indicated that BTF3 exhibited moderate classification accuracy.Co-expression analysis revealed that positively correlated genes with BTF3 included EIF3E and HSPA14, while negatively correlated genes included SZRD1 and ARHGEF2.GO analysis demonstrated that BTF3 was enriched in biological processes such as glucose metabolism, signaling in response to deoxyribonucleic acid (DNA)damage, endogenous apoptotic signaling pathways, platelet morphogenesis, and platelet formation.Additionally, ssGSEA indicated a significant association of BTF3 with memory B cells and a notable correlation with low CD56-expressing natural killer cells. Conclusions:BTF3 is significantly overexpressed in cSCC and may represent a promising diagnostic and therapeutic target by influencing key gene networks and modulating the immune microenvironment.

Spine fracture and dislocation are common traumatic spinal conditions that often require surgical intervention due to compromised spinal stability. Surgical approaches include anterior, posterior, and combined anterior-posterior spinal procedures. According to the specific surgical requirements, patients may be placed in the prone position or repositioned between prone and supine positions during surgery. Intraoperative repositioning has become an essential step in patient positioning. However, during repositioning, patients with spinal fracture and dislocation are at increased risk for complications such as hemodynamic instability, nerve injury, and pressure injuries to the skin and soft tissue. Notably, due to the instability of the spinal cord, even minor manipulations can further exacerbate the damage, potentially leading to severe outcomes like paraplegia. Although the current clinical guidelines provide instructive recommendations for standard position, there remains no specific protocols for intraoperative repositioning in patients with spine fracture and dislocation. With a concern for the lack of clinical studies on positioning techniques, risk prevention, and operational norms for special patients, no applicable guidelines or standards are available. A consensus was required to provide clinical reference, meet the requirements of surgical treatment, and minimize the safety risks of patients caused by improper placement of positions. Professional Committee of Operating Room Nursing of Shaanxi Nursing Association organized experts in nursing management and operating room nursing from major hospitals across China to formulate Expert consensus on intraoperative repositioning for patients with spinal fracture and dislocation ( version 2025). The consensus provides 11 recommendations covering pre-repositioning preparation, intraoperative maneuvers, and post-repositioning observation, aiming to provide references for clinical standardization of the intraoperative repositioning process and protection of patients′ safety.

Objective To investigate the effect of secondary preventive scheme on recurrence rate of ce-rebrovascular event based on China ischemic stroke subclassification(CISS)of intracranial arterial stenosis is-chemic stroke(IS).Methods A total of 192 patients with intracranial arterial stenosis IS were prospectively included and the secondary preventive scheme was formulated according to whether or not based on the patho-genesis.Then the patients were divided into the personalized treatment group and conventional treatment group.The personalized group conducted the classification and was given different the secondary preventive schemes the artery-artery embolism group was given the active lipid-lowering scheme to make the low density lipoprotein(LDL)reaching the standard;the low hypoperfusion group was given the smooth pressure reduc-tion program;the carrier artery occlusion perforating artery group was given the routine secondary prevention program;the mixture mechanism group was given the corresponding schemes superposition according to dif-ferent mechanisms].The conventional treatment group was given the conventional secondary preventive scheme.The difference in the recurrence rate of cerebrovascular events on 90 d was compared between the two groups.Meanwhile the univariate and multivariate logistic regression were used to analyze the influencing fac-tors of recurrence of cerebrovascular events on 90 d in intracranial arterial stenosis IS.Results Among 192 study subjects,there were 90 cases in the personalized treatment group(20 cases of vector artery occlusion and perforator artery,44 cases of arterial-arterial embolization,6 cases of hypoperfusion and 20 cases of mixed mechanism).There were 102 cases in the conventional treatment group(16 cases of perforator artery occlu-sion of the vector artery,52 cases of arterial-arterial embolism,8 cases of hypoperfusion and 26 cases of mixed mechanism).The occurrence rate of cerebrovascular events on 90 d in the personalized treatment group was significantly decreased compared to the conventional treatment group(7.8%vs.17.6%,χ2=4.112,P=0.043).The Logistic regression analysis revealed that the active lipid-lowering scheme for LDL reaching the standard was the independent protective factor of the cerebrovascular event recurrence on 90 d(OR=0.128,95%CI:1.150-71.170).Conclusion The personalized secondary prevention scheme based on pathogenesis reduces the recurrence rate of cerebrovascular event in intracranial arterial stenosis IS,in which making the LDL reaching the standard by the active lipid-lowering scheme is the independent protective factor for cerebro-vascular event recurrence in intracranial arterial stenosis IS.

Objective To study the relationship between the mandibular bone arch and the dental arch in patients with skeletal Class Ⅱ malocclusion and compare it with the Class Imalocclusion by establishing a 3D digital model.Methods A total of 25 cases with skeletal Class Ⅱ malocclusion and 25 cases with skeletal Class Ⅰ normal occlusion were selected.The mandibular model was scanned and a three-dimensional digital model was set up.After the determination of the WALA ridge and the FA point,the reference plane and coordinate system was established.Four degree polynomial curve fitting was performed with WALA ridge and FA point coordinates to re-present the corresponding basal and dental arch curves.The width difference between the basal arch curve and the dental arch curve was measured and calculated at 3 mm,10 mm,and 18 mm away from the horizontal axis of the coordinate.The differences of basal bone and dental arch width between skeletal Class Ⅱ and skeletal Class Ⅰ malocclusion was compared.Results The width differences be-tween the arch and the dental arch in the anterior,middle and posterior mandibular segments of skeletal Class Ⅱ patients were-1.58 mm,1.80 mm and 3.80 mm,respectively.The width differences between the arch and the dental arch in the anterior,middle and pos-terior mandibular segments of skeletal Class Ⅰ patients were 2.08 mm,2.92 mm and 4.24 mm,respectively.There was a significant difference between skeletal Class Ⅱ and skeletal Class Ⅰ in the anterior and middle segments(P＜0.05),but no significant difference in the posterior segment(P＞0.05).Conclusion In skeletal Class Ⅰ patients,the width of the basal bone is larger than that of the dental arch,and the dental arch was located medial to the basal bone.In skeletal Class Ⅱ patients,the width of the anterior arch is larger than the width of the basal bone,that is,the dental arch is located outside the basal bone.The width difference of the basal arch in skeletal Class Ⅱ is smaller than that in skeletal Class Ⅰ.

Alzheimer's disease(AD)is a progressive,irreversible neurodegenerative disorder characterized by gradual brain cell degeneration,leading to progressive decline in cognitive function and ultimately death.Early identification and intervention are critical to AD diagnosis.In recent years,deep learning has further advanced image-based AD classification methods and facilitated the application of deep models in the early AD diagnosis.To achieve accurate early diagnosis and subsequent classification of AD,researchers have integrated deep learning with magnetic resonance imaging to develop more precise models.By analyzing and synthesizing relevant domestic and international literature,this review introduces commonly used public datasets and evaluation criteria for AD,analyzes the application of magnetic resonance imaging in AD classification and its integration with deep learning methods,and highlights the roles of techniques such as convolutional neural networks,transfer learning,attention mechanisms,and multimodal approaches in AD classification.It also discusses the advantages,limitations,and developmental trends of deep learning in AD classification,aiming to provide new insights for the application of deep learning in AD research.

Objective To study the relationship between the mandibular bone arch and the dental arch in patients with skeletal Class Ⅱ malocclusion and compare it with the Class Imalocclusion by establishing a 3D digital model.Methods A total of 25 cases with skeletal Class Ⅱ malocclusion and 25 cases with skeletal Class Ⅰ normal occlusion were selected.The mandibular model was scanned and a three-dimensional digital model was set up.After the determination of the WALA ridge and the FA point,the reference plane and coordinate system was established.Four degree polynomial curve fitting was performed with WALA ridge and FA point coordinates to re-present the corresponding basal and dental arch curves.The width difference between the basal arch curve and the dental arch curve was measured and calculated at 3 mm,10 mm,and 18 mm away from the horizontal axis of the coordinate.The differences of basal bone and dental arch width between skeletal Class Ⅱ and skeletal Class Ⅰ malocclusion was compared.Results The width differences be-tween the arch and the dental arch in the anterior,middle and posterior mandibular segments of skeletal Class Ⅱ patients were-1.58 mm,1.80 mm and 3.80 mm,respectively.The width differences between the arch and the dental arch in the anterior,middle and pos-terior mandibular segments of skeletal Class Ⅰ patients were 2.08 mm,2.92 mm and 4.24 mm,respectively.There was a significant difference between skeletal Class Ⅱ and skeletal Class Ⅰ in the anterior and middle segments(P＜0.05),but no significant difference in the posterior segment(P＞0.05).Conclusion In skeletal Class Ⅰ patients,the width of the basal bone is larger than that of the dental arch,and the dental arch was located medial to the basal bone.In skeletal Class Ⅱ patients,the width of the anterior arch is larger than the width of the basal bone,that is,the dental arch is located outside the basal bone.The width difference of the basal arch in skeletal Class Ⅱ is smaller than that in skeletal Class Ⅰ.

Fatigue driving is a major cause of traffic accidents,which poses a great threat to public safety and property.In order to reduce the losses caused by fatigue driving,many researchers have devoted themselves to the study about fatigue driving,such as driver behavior monitoring,brainwave monitoring,eye tracking and facial expression analysis.Each of these methods has its own advantages and disadvantages.Behavioral monitoring reflects the fatigue state by analyzing the driver's driving habits and facial expression,which is easy to operate but prone to be affected by the external environment.Brainwave monitoring is more accurate and can detect the fatigue state in real time,but the equipment is complicated and costly,which limits its large-scale application.The detection based on eye-tracking and facial expression analysis also has a certain potential for application,but errors may occur under different light conditions.Herein the review introduces the effects of fatigue on driving ability and compares the research results of various fatigue driving detection methods by searching,collating,analyzing and summarizing the relevant literatures at home and abroad.Various detection methods are analyzed and summarized,and it is pointed out that the fatigue driving detection method based on multi-feature information fusion will become a research hotspot.

Alzheimer's disease(AD)is a progressive,irreversible neurodegenerative disorder characterized by gradual brain cell degeneration,leading to progressive decline in cognitive function and ultimately death.Early identification and intervention are critical to AD diagnosis.In recent years,deep learning has further advanced image-based AD classification methods and facilitated the application of deep models in the early AD diagnosis.To achieve accurate early diagnosis and subsequent classification of AD,researchers have integrated deep learning with magnetic resonance imaging to develop more precise models.By analyzing and synthesizing relevant domestic and international literature,this review introduces commonly used public datasets and evaluation criteria for AD,analyzes the application of magnetic resonance imaging in AD classification and its integration with deep learning methods,and highlights the roles of techniques such as convolutional neural networks,transfer learning,attention mechanisms,and multimodal approaches in AD classification.It also discusses the advantages,limitations,and developmental trends of deep learning in AD classification,aiming to provide new insights for the application of deep learning in AD research.

Objective:To identify the key differentially expressed gene, BTF3, in cutaneous squamous cell carcinoma(cSCC)using bioinformatics methods and to preliminarily explore the potential mechanisms of BTF3 and its co-expressed genes in cSCC development. Methods:The cSCC-related datasets(GSE98767, GSE42677, GSE45164)were obtained from the Gene Expression Omnibus(GEO)database.Differential expression analysis revealed BTF3 as a significantly differentially expressed gene in cSCC.A BTF3-related co-expressed gene network was constructed and subjected to gene ontology(GO)enrichment analysis to investigate the biological processes, molecular functions, and cellular components that were significantly enriched.The study selected 60 paraffin-embedded tissue samples from the First Affiliated Hospital of Jinzhou Medical University, collected between 2020 and 2024.This cohort included 30 samples from cSCC patients and 30 samples from patients who underwent excision of melanocytic nevi.Immunohistochemical experiments were conducted to assess the expression of BTF3 in cSCC tissues.Additionally, single-sample gene set enrichment analysis(ssGSEA)was performed to assess the relevance of BTF3 to immune cells, and protein-protein interaction(PPI)analysis was employed to identify critical gene networks. Results:BTF3 was significantly overexpressed in cSCC, as confirmed by immunohistochemistry.The receiver operating characteristic(ROC)curve indicated that BTF3 exhibited moderate classification accuracy.Co-expression analysis revealed that positively correlated genes with BTF3 included EIF3E and HSPA14, while negatively correlated genes included SZRD1 and ARHGEF2.GO analysis demonstrated that BTF3 was enriched in biological processes such as glucose metabolism, signaling in response to deoxyribonucleic acid (DNA)damage, endogenous apoptotic signaling pathways, platelet morphogenesis, and platelet formation.Additionally, ssGSEA indicated a significant association of BTF3 with memory B cells and a notable correlation with low CD56-expressing natural killer cells. Conclusions:BTF3 is significantly overexpressed in cSCC and may represent a promising diagnostic and therapeutic target by influencing key gene networks and modulating the immune microenvironment.