Parametric analysis of craniocerebral injury mechanism in pedestrian traffic accidents based on finite element methods.

PURPOSE: The toughest challenge in pedestrian traffic accident identification lies in ascertaining injury manners. This study aimed to systematically simulate and parameterize 3 types of craniocerebral injury including impact injury, fall injury, and run-over injury, to compare the injury response outcomes of different injury manners. METHODS: Based on the Total Human Model for Safety (THUMS) and its enhanced human model THUMS-hollow structures, a total of 84 simulations with 3 injury manners, different loading directions, and loading velocities was conducted. Von Mises stress, intracranial pressure, maximum principal strain, cumulative strain damage measure, shear stress, and cranial strain were employed to analyze the injury response of all areas of the brain. To examine the association between injury conditions and injury consequences, correlation analysis, principal component analysis, linear regression, and stepwise linear regression were utilized. RESULTS: There is a significant correlation observed between each criterion of skull and brain injury (p < 0.01 in all Pearson correlation analysis results). A 2-phase increase of cranio-cerebral stress and strain as impact speed increases. In high-speed impact (> 40 km/h), the Von Mises stress on the skull was with a high possibility exceed the threshold for skull fracture (100 MPa). When falling and making temporal and occipital contact with the ground, the opposite side of the impacted area experiences higher frequency stress concentration than contact at other conditions. Run-over injuries tend to have a more comprehensive craniocerebral injury, with greater overall deformation due to more adequate kinetic energy conduction. The mean value of maximum principal strain of brain and Von Mises stress of cranium at run-over condition are 1.39 and 403.8 MPa, while they were 1.31, 94.11 MPa and 0.64, 120.5 MPa for the impact and fall conditions, respectively. The impact velocity also plays a significant role in craniocerebral injury in impact and fall loading conditions (the p of all F test < 0.05). A regression equation of the craniocerebral injury manners in pedestrian accidents was established. CONCLUSION: The study distinguished the craniocerebral injuries caused in different manners, elucidated the biomechanical mechanisms of craniocerebral injury, and provided a biomechanical foundation for the identification of craniocerebral injury in legal contexts.

Single-cell and spatial transcriptomics reveals that PTPRG activates the m6A methyltransferase VIRMA to block mitophagy-mediated neuronal death in Alzheimer's disease.

Neuronal death is one of the key pathologies in Alzheimer's disease (AD). How neuronal death begins in AD is far from clear, so clarifying this process may help develop effective therapies. This study collected single-cell RNA sequencing data of 85 AD samples and 83 control samples, covering the prefrontal cortex, internal olfactory cortex, superior parietal lobe, superior frontal gyrus, caudal internal olfactory cortex, somatosensory cortex, hippocampus, superior frontal cortex and peripheral blood mononuclear cells. Additionally, spatial transcriptomic data of coronal sections from 6 AppNL-G-F AD mice and 6 control C57Bl/6 J mice were acquired. The main single-cell and spatial transcriptomics results were experimentally validated in wild type and 5 × FAD mice. We found that the microglia subpopulation Mic_PTPRG can communicate with specific types of neurons (especially excitatory ExNeu_PRKN_VIRMA and inhibitory InNeu_PRKN_VIRMA neuronal subpopulations) and cause them to express PTPRG during AD progression. Within neurons, PTPRG binds and upregulates the m6A methyltransferase VIRMA, thus inhibiting translation of PRKN mRNA to prevent the clearance of damaged mitochondria in neurons through suppressing mitophagy. As the disease progresses, the energy and nutrient metabolic pathways in neurons are reprogrammed, leading to their death. Consistently, we determined that PTPTRG can physically interact with VIRMA in mouse brains and PRKN is significantly upregulated in 5 × FAD mouse brain. Altogether, our findings demonstrate that PTPRG activates the m6A methyltransferase VIRMA to block mitophagy-mediated neuronal death in AD, which is a potential pathway, through which microglia and neuronal PTPRG modify neuronal connections in the brain during AD progression.

Research Progress and Forensic Application of Human Vascular Finite Element Modeling and Biomechanics.

The finite element method (FEM) is a mathematical method for obtaining approximate solutions to a wide variety of engineering problems. With the development of computer technology, it is gradually applied to the study of biomechanics of human body. The application of the combination of FEM and biomechanics in exploring the relationship between vascular injury and disease, and pathological mechanisms will be a technological innovation for traditional forensic medicine. This paper reviews the construction and development of human vascular FEM modeling, and its research progress on the vascular biomechanics. This paper also looks to the application prospects of FEM modeling in forensic pathology.

Survey on the Construction Status of Forensic Virtual Autopsy Laboratory and the Applicability of Laboratory Accreditation.

OBJECTIVES: To survey the development status and actual needs of virtual autopsy technology in China and to clarify the applicability of forensic virtual autopsy laboratory accreditation. METHODS: The questionnaire was set up included three aspects：(1) the current status of virtual autopsy technology development; (2) the accreditation elements such as personnel, equipment, entrustment and acceptance, methods, environmental facilities; (3) the needs and suggestions of practicing institutions. A total of 130 forensic pathology institutions were surveyed by online participation through the Questionnaire Star platform. RESULTS: Among the 130 institutions, 43.08% were familiar with the characteristics of virtual autopsy technology, 35.38% conducted or received training in virtual autopsy, and 70.77% have establishment needs (including maintenance). Relevant elements were suitable for laboratory accreditation. CONCLUSIONS: Virtual autopsy identification has gained social recognition. There is a demand for accreditation of forensic virtual autopsy laboratory. After the preliminary assessment, considering the characteristics and current situation of this technology, China National Accreditation Service for Conformity Assessment (CNAS) can first carry out the accreditation pilot of virtual autopsy project at large comprehensive forensic institutions with higher identification capability, and then CNAS can popularize the accreditation in a wide range when the conditions are suitable.

Eukaryotic initiation factor 4 A-3 promotes glioblastoma growth and invasion through the Notch1-dependent pathway.

BACKGROUND: As an adult tumor with the most invasion and the highest mortality rate, the inherent heterogeneity of glioblastoma (GBM) is the main factor that causes treatment failure. Therefore, it is important to have a deeper understanding of the pathology of GBM. Some studies have shown that Eukaryotic Initiation Factor 4A-3 (EIF4A3) can promote the growth of many people's tumors, and the role of specific molecules in GBM remains unclear. METHODS: The correlation between the expression of EIF4A3 gene and its prognosis was studied in 94 GBM patients using survival analysis. Further in vitro and in vivo experiments, the effect of EIF4A3 on GBM cells proliferation, migration, and the mechanism of EIF4A3 on GBM was explored. In addition, combined with bioinformatics analysis, we further confirmed that EIF4A3 contributes to the progress of GBM. RESULTS: The expression of EIF4A3 was upregulated in GBM tissues, and high expression of EIF4A3 is associated with poor prognosis in GBM. In vitro, knockdown of EIF4A3 significantly reduced the proliferation, migration, and invasion abilities of GBM cells, whereas overexpression of EIF4A3 led to the opposite effect. The analysis of differentially expressed genes related to EIF4A3 indicates that it is involved in many cancer-related pathways, such as Notch and JAK-STAT3 signal pathway. In Besides, we demonstrated the interaction between EIF4A3 and Notch1 by RNA immunoprecipitation. Finally, the biological function of EIF4A3-promoted GBM was confirmed in living organisms. CONCLUSION: The results of this study suggest that EIF4A3 may be a potential prognostic factor, and Notch1 participates in the proliferation and metastasis of GBM cells mediated by EIF4A3.

A study to characterize the mechanical properties and material constitution of adult descending thoracic aorta based on uniaxial tensile test and digital image correlation.

The mechanical properties and material constitution of the aorta are important in forensic science and clinical medicine. Existing studies on the material constitution of the aorta do not satisfy the practical requirements of forensic and clinical medicine, as the reported failure stress and failure strain values for human aortic materials have a high dispersion. In this study, descending thoracic aortas were obtained from 50 cadavers (dead within 24 h) free of thoracic aortic disease, aged from 27 to 86 years old, which were divided into six age groups. The descending thoracic aorta was divided into proximal and distal segments. A customized 4-mm cutter was used to punch a circumferential and an axial dog-bone-shaped specimen from each segment; the aortic ostia and calcification were avoided. Instron 8,874 and digital image correlation were used to perform a uniaxial tensile test on each sample. Four samples from each descending thoracic aorta produced ideal stress-strain curves. All parameter-fitting regressions from the selected mathematical model converged, and the best-fit parameters of each sample were obtained. The elastic modulus of collagen fiber, failure stress, and the strain showed a decreasing trend with age, while the elastic modulus of elastic fiber showed an increasing trend with age. The elastic modulus of collagen fiber, failure stress, and strain of circumferential tensile were all greater than those for axial tensile. There was no statistical difference in model parameters and physiological moduli between the proximal and distal segments. The failure stress and strain in the proximal circumferential, distal circumferential, and distal axial tensile were all greater for the male group than for the female group. Finally, the Fung-type hyperelastic constitutive equations were fitted for the different segments in different age groups.

Comparison of CT Values between Thrombus and Postmortem Clot Based on Cadaveric Pulmonary Angiography.

OBJECTIVES: To explore the difference in CT values between pulmonary thromboembolism and postmortem clot in postmortem CT pulmonary angiography (CTPA) to further improve the application value of virtual autopsy. METHODS: Postmortem CTPA data with the definite cause of death from 2016 to 2019 were collected and divided into pulmonary thromboembolism group (n=4), postmortem clot group (n=5), and control group (n=5). CT values of pulmonary trunk and left and right pulmonary artery contents in each group were measured and analyzed statistically. RESULTS: The average CT value in the pulmonary thromboembolism group and postmortem clot group were (168.4±53.8) Hu and (282.7±78.0) Hu, respectively, which were lower than those of the control group (1 193.0±82.9) Hu (P<0.05). The average CT value of the postmortem clot group was higher than that of the pulmonary thromboembolism group (P<0.05). CONCLUSIONS: CT value is reliable and feasible as a relatively objective quantitative index to distinguish pulmonary thromboembolism and postmortem clot in postmortem CTPA. At the same time, it can provide a scientific basis to a certain extent for ruling out pulmonary thromboembolism deaths.

Exploration of novel biomarkers in Alzheimer's disease based on four diagnostic models.

Background: Despite tremendous progress in diagnosis and prediction of Alzheimer's disease (AD), the absence of treatments implies the need for further research. In this study, we screened AD biomarkers by comparing expression profiles of AD and control tissue samples and used various models to identify potential biomarkers. We further explored immune cells associated with these biomarkers that are involved in the brain microenvironment. Methods: By differential expression analysis, we identified differentially expressed genes (DEGs) of four datasets (GSE125583, GSE118553, GSE5281, GSE122063), and common expression direction of genes of four datasets were considered as intersecting DEGs, which were used to perform enrichment analysis. We then screened the intersecting pathways between the pathways identified by enrichment analysis. DEGs in intersecting pathways that had an area under the curve (AUC) > 0.7 constructed random forest, least absolute shrinkage and selection operator (LASSO), logistic regression, and gradient boosting machine models. Subsequently, using receiver operating characteristic curve (ROC) and decision curve analysis (DCA) to select an optimal diagnostic model, we obtained the feature genes. Feature genes that were regulated by differentially expressed miRNAs (AUC > 0.85) were explored further. Furthermore, using single-sample GSEA to calculate infiltration of immune cells in AD patients. Results: Screened 1855 intersecting DEGs that were involved in RAS and AMPK signaling. The LASSO model performed best among the four models. Thus, it was used as the optimal diagnostic model for ROC and DCA analyses. This obtained eight feature genes, including ATP2B3, BDNF, DVL2, ITGA10, SLC6A12, SMAD4, SST, and TPI1. SLC6A12 is regulated by miR-3176. Finally, the results of ssGSEA indicated dendritic cells and plasmacytoid dendritic cells were highly infiltrated in AD patients. Conclusion: The LASSO model is the optimal diagnostic model for identifying feature genes as potential AD biomarkers, which can supply new strategies for the treatment of patients with AD.

Emerging role of artificial intelligence in diagnosis, classification and clinical management of glioma.

Glioma represents a dominant primary intracranial malignancy in the central nervous system. Artificial intelligence that mainly includes machine learning, and deep learning computational approaches, presents a unique opportunity to enhance clinical management of glioma through improving tumor segmentation, diagnosis, differentiation, grading, treatment, prediction of clinical outcomes (prognosis, and recurrence), molecular features, clinical classification, characterization of the tumor microenvironment, and drug discovery. A growing body of recent studies apply artificial intelligence-based models to disparate data sources of glioma, covering imaging modalities, digital pathology, high-throughput multi-omics data (especially emerging single-cell RNA sequencing and spatial transcriptome), etc. While these early findings are promising, future studies are required to normalize artificial intelligence-based models to improve the generalizability and interpretability of the results. Despite prominent issues, targeted clinical application of artificial intelligence approaches in glioma will facilitate the development of precision medicine of this field. If these challenges can be overcome, artificial intelligence has the potential to profoundly change the way patients with or at risk of glioma are provided with more rational care.

Detection of multiple biomarkers associated with satellite cell fate in the contused skeletal muscle of rats for wound age estimation.

From the perspective of forensic wound age estimation, experiments related to skeletal muscle regeneration after injury have rarely been reported. Here, we examined the time-dependent expression patterns of multiple biomarkers associated with satellite cell fate, including the transcription factor paired box 7 (Pax7), myoblast determination protein (MyoD), myogenin, and insulin-like growth factor (IGF-1), using immunohistochemistry, western blotting, and quantitative real-time PCR in contused skeletal muscle. An animal model of skeletal muscle contusion was established in 30 Sprague-Dawley male rats, and another five rats were employed as non-contused controls. Morphometrically, the data obtained from the numbers of Pax7 + , MyoD + , and myogenin + cells were highly correlated with the wound age. Pax7, MyoD, myogenin, and IGF-1 expression patterns were upregulated after injury at both the mRNA and protein levels. Pax7, MyoD, and myogenin protein expression levels confirmed the results of the morphometrical analysis. Additionally, the relative quantity of IGF-1 protein > 0.92 suggested a wound age of 3 to 7 days. The relative quantity of Pax7 mRNA > 2.44 also suggested a wound age of 3 to 7 days. Relative quantities of Myod1, Myog, and Igf1 mRNA expression > 2.78, > 7.80, or > 3.13, respectively, indicated a wound age of approximately 3 days. In conclusion, the expression levels of Pax7, MyoD, myogenin, and IGF-1 were upregulated in a time-dependent manner during skeletal muscle wound healing, suggesting the potential for using them as candidate biomarkers for wound age estimation in skeletal muscle.

The value of PMCTA in the diagnosis of coronary atherosclerosis in isolated human hearts.

Postmortem computed tomography (PMCT) has a limited value in investigating coronary artery disease, despite several obvious advantages over the conventional autopsy. To address this issue, postmortem computed tomography angiography (PMCTA) has been introduced into various studies, where it has been used to investigate natural and unnatural deaths involving vascular damage, occlusion, or other pathologies of the vascular system. To investigate the application value of PMCTA in the diagnosis of coronary artery stenosis in ex situ hearts, the water-based contrast media were injected into isolated hearts, scaned, and finally compared with gold standards (autopsy and histology findings of the coronary artery). This study involved 16 subjects from the Academy of Forensic Science who were suspected to have died of sudden death without traumatic injuries. Unenhanced PMCT was performed first, followed by PMCTA using a water-based contrast agent, injected into the coronary arteries of isolated hearts using a self-designed angiography device. The image data were reconstructed into three-dimensional (3D) angiography images using software in the angiography facility. The 3D images were recorded and evaluated by two radiologists and then statistically analysed. The results of PMCTA were consistent with the gold standards for the diagnosis of coronary artery stenosis (P > 0.05). However, water-based contrast media can only be used to examine the pathological changes of blood vessels, which may have limitations in the diagnosis of causes of death such as myocardial oedema. PMCTA can be used as a new method to evaluate the degree of coronary atherosclerosis in addition to traditional autopsy. The 3D reconstruction technique reveals the coronary artery lesions more objectively and vividly and provides the opportunity to re-read the data at any time. Key points: The methods and parameters for coronary angiography in isolated human hearts were standardized based on the previous researcher.PMCTA in isolated human hearts is including the 3D reconstruction technique that reveals the coronary artery lesions more objectively and vividly, and provides the opportunity to re-read the data at anytime.PMCTA could only be used to examine the pathological changes of blood vessels, which might have limitations for the diagnosis of causes of death.PMCTA in isolated human hearts can be viewed as an auxiliary method for establishing the cause of death, which can provide an assessment of degree and extent of arterial stenosis and accurately help determine the abnormal location.

Analysis of forensic autopsy cases associated with epilepsy: Comparison between sudden unexpected death in epilepsy (SUDEP) and not-SUDEP groups.

Background and aims: Epilepsy is a common and chronic neurological disorder characterized by seizures that increase the risk of mortality. SUDEP is the most common seizure-related category of death. The study aimed to evaluate the key characteristics between SUDEP and not-SUDEP death cases. Methods: A retrospective study of forensic autopsy cases from 2002 to 2021, performed by the Academy of Forensic Science (Ministry of Justice, China), identified a total of 31 deaths associated with epilepsy. We compared the different characteristics between individuals who died of SUDEP (SUDEP group) and individuals with epilepsy died suddenly due to unrelated causes (not-SUDEP group). Results and conclusions: 13 cases met the general accepted definition of SUDEP; and 18 cases were classified as not-SUDEP. The mean age of the not-SUDEP group was significantly higher than that of the SUDEP groups (p < 0.05) and there were more cases without a clear cause of epilepsy in the SUDEP group than in the not-SUDEP group (p < 0.05). Death position differed significantly between the two groups, with more cases dying in the prone position in the SUDEP group (p < 0.05). Complete autopsies were performed in 24 of the 31 cases. There were no significant differences in heart, lungs and brain weights, or in ventricular thickness (p > 0.05) between the SUDEP and not-SUDEP groups. In addition, compared to the not-SUDEP group, the SUDEP group featured a significantly more cases with coronary lesions (grades 1-3, p < 0.05). Neuropathological lesions were identified in 12 of the 13 SUDEP cases (92.3%), cardiac lesions were present in 10 cases (76.9%) and pulmonary edema and pulmonary congestion were present in all cases. The primary cause of death in 13 of the 31 cases was seizure disorder or epilepsy. The primary mechanism of death in SUDEP group was mainly asphyxia while that in the not-SUDEP group was cardiopulmonary failure (p < 0.05). Patients in the prone position had a significantly higher risk of asphyxia than those who were not. Here, we investigated the key characteristics between SUDEP and not-SUDEP death cases, which may help to facilitate forensic diagnosis in presumed SUDEP cases.

Multiobjective optimization algorithm for accurate MADYMO reconstruction of vehicle-pedestrian accidents.

In vehicle-pedestrian accidents, the preimpact conditions of pedestrians and vehicles are frequently uncertain. The incident data for a crash, such as vehicle deformation, injury of the victim, distance of initial position and rest position of accident participants, are useful for verification in MAthematical DYnamic MOdels (MADYMO) simulations. The purpose of this study is to explore the use of an improved optimization algorithm combined with MADYMO multibody simulations and crash data to conduct accurate reconstructions of vehicle-pedestrian accidents. The objective function of the optimization problem was defined as the Euclidean distance between the known vehicle, human and ground contact points, and multiobjective optimization algorithms were employed to obtain the local minima of the objective function. Three common multiobjective optimization algorithms-nondominated sorting genetic algorithm-II (NSGA-II), neighbourhood cultivation genetic algorithm (NCGA), and multiobjective particle swarm optimization (MOPSO)-were compared. The effect of the number of objective functions, the choice of different objective functions and the optimal number of iterations were also considered. The final reconstructed results were compared with the process of a real accident. Based on the results of the reconstruction of a real-world accident, the present study indicated that NSGA-II had better convergence and generated more noninferior solutions and better final solutions than NCGA and MOPSO. In addition, when all vehicle-pedestrian-ground contacts were considered, the results showed a better match in terms of kinematic response. NSGA-II converged within 100 generations. This study indicated that multibody simulations coupled with optimization algorithms can be used to accurately reconstruct vehicle-pedestrian collisions.

Preliminary study on the mechanisms of ankle injuries under falling and impact conditions based on the THUMS model.

Ankle injuries are common in forensic practice, which are mainly caused by falling and traffic accidents. Determining the mechanisms and manners of ankle injuries is a critical and challenging problem for forensic experts. The identification of the injury mechanism is still experience-based and strongly subjective. There also lacks systematic research in current practice. In our study, based on the widely used Total Human Model of Safety 4.0 (THUMS 4.0), we utilized the finite element (FE) method to simulate ankle injuries caused by falls from different heights (5 m, 10 m and 20 m) with different landing postures (natural posture, inversion, eversion, plantar-flexion and dorsi-flexion) and injuries caused by impacts from different directions (anterior-posterior, lateral-medial and posterior-anterior) with different speeds (10 m/s, 15 m/s and 20 m/s) at different sites (ankle and lower, middle and upper sections of leg). We compared the injury morphology and analyzed the mechanisms of ankle injuries. The results showed that falling causes a specific compression fracture of the distal tibia, while fractures of the tibia and fibula diaphysis and ligament injuries caused by falling from a lower height or inversion, planter flexion or dorsiflexion at a large angle are not distinguishable from the similar injury patterns caused by impact on the middle and upper segments of the leg. No obvious compression fracture of the tibia distal was caused by the impacts, whereas ligament injuries and avulsion fractures of the medial or lateral condyle and fractures of the diaphysis of the tibia and fibula were observed. Systematic studies will be helpful in reconstructing the ankle injury processes and analyzing the mechanisms in forensic practice, providing a deeper understanding of ankle injury mechanisms for forensic experts.

Potential biomarkers of Alzheimer's disease and cerebral small vessel disease.

Background: Cerebral small vessel disease (CSVD) is associated with the pathogenesis of Alzheimer's disease (AD). Effective treatments to alleviate AD are still not currently available. Hence, we explored markers and underlying molecular mechanisms associated with AD by utilizing gene expression profiles of AD and CSVD patients from public databases, providing more options for early diagnosis and its treatment. Methods: Gene expression profiles were collected from GSE63060 (for AD) and GSE162790 (for CSVD). Differential analysis was performed between AD and mild cognitive impairment (MCI) or CSVD progression and CSVD no-progression. In both datasets, differentially expressed genes (DEGs) with the same expression direction were identified as common DEGs. Then protein-protein interaction (PPI) network was constructed for common DEGs. Differential immune cells and checkpoints were calculated between AD and MCI. Results: A total of 146 common DEGs were identified. Common DEGs were mainly enriched in endocytosis and oxytocin signaling pathways. Interestingly, endocytosis and metabolic pathways were shown both from MCI to AD and from CSVD no-progression to CSVD progression. Moreover, SIRT1 was identified as a key gene by ranking degree of connectivity in the PPI network. SIRT1 was associated with obesity-related genes and metabolic disorders. Additionally, SIRT1 showed correlations with CD8 T cells, NK CD56 bright cells, and checkpoints in AD. Conclusion: The study revealed that the progression of AD is associated with abnormalities in gene expression and metabolism and that the SIRT1 gene may serve as a promising therapeutic target for the treatment of AD.

Reconstruction of a real-world car-to-pedestrian collision using geomatics techniques and numerical simulations.

The aim of this study is to provide an improved method for traffic accident reconstruction based on geomatics techniques and numerical simulations. A combination of various techniques was used. First, an unmanned aerial vehicle (UAV), laser scanner and structured-light scanner were used to obtain information on the accident scene, vehicle and victim. The collected traces provided detailed initial impact conditions for subsequent numerical simulations. Then, multi-body system (MBS) simulations were conducted to reconstruct the kinematics of the car-to-pedestrian collision. Finally, a finite element (FE) simulation using the THUMS model was performed to predict injuries. A real-life vehicle-pedestrian collision was used to verify the feasibility and effectiveness of this method. The reconstruction result revealed that the kinematic and injury predictions of the numerical simulations effectively conformed to the surveillance video and investigation of the actual accident. UAV photogrammetry was demonstrated to be more efficient in accident data collection than hand sketch and measurement, and 3D laser scanning enabled an easier and more accurate modeling process of vehicle. The present study shows the feasibility of this method for use in traffic accident reconstruction.

Cerebral hemorrhage caused by shaking adult syndrome? Evidence from biomechanical analysis using 3D motion capture and finite element models.

The present study combined three-dimensional (3D) motion capture with finite element simulation to reconstruct a real shaking adult syndrome (SAS) case and further explore the injury biomechanics of SAS. The frequency at which an adult male can shake the head of another person, head-shaking amplitude, and displacement curves was captured by the VICON 3D motion capture system. The captured shaking frequency and shaking curve were loaded on the total human model for safety (THUMS) head to simulate the biomechanical response of brain injury when a head was shaken in anterior-posterior, left-right, and left anterior-right posterior directions at frequencies of 4 Hz (Hz), 5 Hz, 6 Hz, and 7 Hz. The biomechanical response of the head on impact in the anterior, posterior, left, left anterior, and right posterior directions at the equivalent velocity of 6 Hz shaking was simulated. The violent shaking frequency of the adult male was 3.2-6.8 Hz; head shaking at these frequencies could result in serious cerebral injuries. SAS-related injuries have obvious directionality, and sagittal shaking can easily cause brain injuries. There was no significant difference between the brain injuries caused by shaking in the simulated frequency range (4-7 Hz). Impact and shaking at an equivalent velocity could cause brain injuries, though SAS more commonly occurred due to the cumulative deformation of brain tissue. Biomechanical studies of SAS should play a positive role in improving the accuracy of forensic identification and reducing this form of abuse and torture in detention or places of imprisonment.

Identification of molecular signatures associated with sleep disorder and Alzheimer's disease.

Background: Alzheimer's disease (AD) and sleep disorders are both neurodegenerative conditions characterized by impaired or absent sleep. However, potential common pathogenetic mechanisms of these diseases are not well characterized. Methods: Differentially expressed genes (DEGs) were identified using publicly available human gene expression profiles GSE5281 for AD and GSE40562 for sleep disorder. DEGs common to the two datasets were used for enrichment analysis, and we performed multi-scale embedded gene co-expression network analysis (MEGENA) for common DEGs. Fast gene set enrichment analysis (fGSEA) was used to obtain common pathways, while gene set variation analysis (GSVA) was applied to quantify those pathways. Subsequently, we extracted the common genes between module genes identified by MEGENA and genes of the common pathways, and we constructed protein-protein interaction (PPI) networks. The top 10 genes with the highest degree of connectivity were classified as hub genes. Common genes were used to perform Metascape enrichment analysis for functional enrichment. Furthermore, we quantified infiltrating immune cells in patients with AD or sleep disorder and in controls. Results: DEGs common to the two disorders were involved in the citrate cycle and the HIF-1 signaling pathway, and several common DEGs were related to signaling pathways regulating the pluripotency of stem cells, as well as 10 other pathways. Using MEGENA, we identified 29 modules and 1,498 module genes in GSE5281, and 55 modules and 1,791 module genes in GSE40562. Hub genes involved in AD and sleep disorder were ATP5A1, ATP5B, COX5A, GAPDH, NDUFA9, NDUFS3, NDUFV2, SOD1, UQCRC1, and UQCRC2. Plasmacytoid dendritic cells and T helper 17 cells had the most extensive infiltration in both AD and sleep disorder. Conclusion: AD pathology and pathways of neurodegeneration participate in processes contributing in AD and sleep disorder. Hub genes may be worth exploring as potential candidates for targeted therapy of AD and sleep disorder.

Exploring Early Physical Examination Diagnostic Biomarkers for Alzheimer's Disease Based on Least Absolute Shrinkage and Selection Operator.

Neurodegenerative diseases such as Alzheimer's disease (AD) are an increasing public health challenge. There is an urgent need to shift the focus to accurate detection of clinical AD at the physical examination stage. The purpose of this study was to identify biomarkers for AD diagnosis. Differential expression analysis was performed on a dataset including prefrontal cortical samples and peripheral blood samples of AD to identify shared differentially expressed genes (DEGs) shared between the two datasets. In addition, a minimum absolute contraction and selection operator (LASSO) model based on shared-DEGs identified nine signature genes (MT1X, IGF1, DLEU7, TRIM36, PTPRC, WNK2, SPG20, C8orf59, and BRWD1) that accurately predict AD occurrence. Enrichment analysis showed that the signature gene was significantly associated with the AD-related p53 signaling pathway, T-cell receptor signaling pathway, HIF-1 signaling pathway, AMPK signaling pathway, and FoxO signaling pathway. Thus, our results identify not only biomarkers for diagnosing AD but also potentially specific pathways. The AD biomarkers proposed in this study could serve as indicators for prevention and diagnosis during physical examination.

REPS1 as a Potential Biomarker in Alzheimer's Disease and Vascular Dementia.

Vascular dementia (VD) and Alzheimer's disease (AD) are common types of dementia for which no curative therapies are known. In this study, we identified hub genes associated with AD and VD in order to explore new potential therapeutic targets. Genes differentially expressed in VD and AD in all three datasets (GSE122063, GSE132903, and GSE5281) were identified and used to construct a protein-protein interaction network. We identified 10 modules containing 427 module genes in AD and VD. Module genes showing an area under the diagnostic curve > 0.60 for AD or VD were used to construct a least absolute shrinkage and selection operator model and were entered into a support vector machine-recursive feature elimination algorithm, which identified REPS1 as a hub gene in AD and VD. Furthermore, REPS1 was associated with activation of pyruvate metabolism and inhibition of Ras signaling pathway. Module genes, together with differentially expressed microRNAs from the dataset GSE46579, were used to construct a regulatory network. REPS1 was predicted to bind to the microRNA hsa_miR_5701. Single-sample gene set enrichment analysis was used to explore immune cell infiltration, which suggested a negative correlation between REPS1 expression and infiltration by plasmacytoid dendritic cells in AD and VD. In conclusion, our results suggest core pathways involved in both AD and VD, and they identify REPS1 as a potential biomarker of both diseases. This protein may aid in early diagnosis, monitoring of treatment response, and even efforts to prevent these debilitating disorders.