To explore the clinical efficacy of scalp electroacupuncture combined with rehabilitation training for aphasia after head injury, and analyze its effect on patients\' language function and quality of life. Our hospital randomly enrolled 100 aphasia patients caused by head injury treated from March 2020 to March 2022 as the experimental object and divided them into the control group and experimental group, with 50 cases in each group. The general rehabilitation training was performed to the control group and the scalp electroacupuncture combined with rehabilitation training was performed to the experimental group to compare their mini-mental state examination scores, communicative activities in daily living scores, aphasia battery of Chinese scores, quality of life scores, mental status scale in nonpsychiatric settings scores, National Institutes of Health Stroke Scale scores, effective rates, satisfaction of patients, and adverse reaction rates. In the between-group comparison, the patients in the experimental group had significantly higher mini-mental state examination scores, communicative activities in daily living scores, aphasia battery of Chinese scores, quality of life scores, effective rates, and satisfaction, and significantly lower mental status scale in nonpsychiatric settings scores, National Institutes of Health Stroke Scale scores and adverse reaction rates, which was statistically significant (P < .05 in all cases). The combination treatment of scalp electroacupuncture and rehabilitation training can effectively improve the language function and quality of life of patients with aphasia after head injury and remarkably enhance the treatment effect.

BACKGROUND: Craniocerebral injuries can cause inflammation and oxidative stress, and can have permanent effects on cognitive function. Moreover, over time, excessive expression of inflammatory factors and high levels of oxidative stress will be detrimental to recovery from craniocerebral injury and may exacerbate neurological damage, further damaging neurons and other cellular structures. In this study, we investigated changes in inflammation and stress indicators in patients with severe craniocerebral injuries, and analyzed associations with concurrent cognitive impairment.
METHODS: 82 patients with severe craniocerebral injuries admitted to Longyou County People\'s Hospital during January 2022-June 2023 were selected for retrospective study. Levels of inflammatory factors and the degree of oxidative stress were recorded and compared between the acute and chronic phases. Inflammatory measures included interleukin-6 (IL-6), interleukin-10 (IL-10), tumor necrosis factor-alpha (TNF-α) and C-reactive protein (CRP), and oxidative stress indicators included human cortisol (Cor), norepinephrine (NE), and superoxide dismutase (SOD). The patients\' cognitive function was evaluated using the Mini-Mental State Examination (MMSE), and the incidence of cognitive impairment was assessed. Spearman\'s correlation was used to analyze associations between inflammatory and oxidative stress measures and MMSE scores; logistic regression was used to analyze the related factors affecting the patients\' concurrent cognitive impairment; and the receiver operating characteristic (ROC) curve was used to test the predictive value of inflammatory and oxidative stress measures on the patients\' concurrent cognitive impairment in the acute phase and the chronic phase.
RESULTS: Patients had higher levels of IL-6, IL-10, TNF-α, CRP, Cor, and NE, and lower levels of SOD, in the acute phase compared to the chronic phase (p < 0.05). MMSE scores were higher in the acute phase than in the chronic phase (p < 0.05). A total of 50 cases were complicated by cognitive impairment, and the incidence of cognitive impairment was 60.98%. The levels of IL-6, IL-10, TNF-α, CRP, Cor, and NE in the chronic phase were positively correlated with the concurrent cognitive impairment, and the level of SOD was negatively correlated with the concurrent cognitive impairment (p < 0.05). Single-factor analysis showed that age and levels of IL-6, IL-10, TNF-α, CRP, Cor, and NE were higher in the cognitively impaired group than in the cognitively normal group, SOD levels were lower than in the cognitively normal group, and percentages of below-secondary school and frontal lobe damage were higher than those in the cognitively normal group (p < 0.05). Logistic regression analysis showed that below-secondary school, frontal lobe injury, higher levels of IL-6, IL-10, TNF-α, and CRP in the chronic phase, and lower levels of SOD in the chronic phase were all relevant factors affecting the patients\' concurrent cognitive impairment. As shown by the ROC curve, the area under the curve (AUC) for the combination of indicators was 0.949, sensitivity was 0.980, and specificity was 0.844.
CONCLUSIONS: The incidence of cognitive impairment is higher in patients with severe craniocerebral injury, and the levels of inflammation and oxidative stress, which are not conducive to recovery, are higher in patients in the acute stage. The risk of concurrent cognitive impairment is higher in patients with a lower level of literacy, frontal lobe injury, and high levels of inflammatory factors and oxidative stress in the chronic stage; these indicators, therefore, have a significant predictive effect on the prognosis of the patients.

Due to the escalating occurrence and high casualty rates of accidents involving Electric Two-Wheelers (E2Ws), it has become a major safety concern on the roads. Additionally, with the widespread adoption of current autonomous driving technology, a greater challenge has arisen for the safety of vulnerable road participants. Most existing trajectory planning methods primarily focus on the safety, comfort, and dynamics of autonomous vehicles themselves, often overlooking the protection of vulnerable road users (VRUs), typically E2W riders. This paper aims to investigate the kinematic response of E2Ws in vehicle collisions, including the 15 ms Head Injury Criterion (HIC15). It analyzes the impact of key collision parameters on head injuries, establishes injury prediction models for anticipated scenarios, and proposes a trajectory planning framework for autonomous vehicles based on predicting head injuries of VRUs. Firstly, a multi-rigid-body model of two-wheeler-vehicle collision was established based on a real accident database, incorporating four critical collision parameters (initial collision velocity, initial collision position, and collision angle). The accuracy of the multi-rigid-body model was validated through verifications with real fatal accidents to parameterize the collision scenario. Secondly, a large-scale effective crash dataset has been established by the multi-parameterized crash simulation automation framework combined with Monte Carlo sampling algorithm. The training and testing of the injury prediction model were implemented based on the MLP + XGBoost regression algorithm on this dataset to explore the potential relationship between the head injuries of the E2W riders and the crash variables. Finally, based on the proposed injury prediction model, this paper generated a trajectory planning framework for autonomous vehicles based on head collision injury prediction for VRUs, aiming to achieve a fair distribution of collision risks among road users. The accident reconstruction results show that the maximum error in the final relative positions of the E2W, the car, and the E2W rider compared to the real accident scene is 11 %, demonstrating the reliability of the reconstructed model. The injury prediction results indicate that the MLP + XGBoost regression prediction model used in this article achieved an R2 of 0.92 on the test set. Additionally, the effectiveness and feasibility of the proposed trajectory planning algorithm were validated in a manually designed autonomous driving traffic flow scenario.

Traumatic brain injury (TBI) is a major cause of morbidity and mortality globally. We unveiled the diagnostic value of serum NLRP3, metalloproteinase-9 (MMP-9) and interferon-γ (IFN-γ) levels in post-craniotomy intracranial infections and hydrocephalus in patients with severe craniocerebral trauma to investigate the high risk factors for these in patients with TBI, and the serological factors predicting prognosis, which had a certain clinical predictive value. Study subjects underwent bone flap resection surgery and were categorized into the intracranial infection/hydrocephalus/control (without postoperative hydrocephalus or intracranial infection) groups, with their clinical data documented. Serum levels of NLRP3, MMP-9 and IFN-γ were determined using ELISA kits, with their diagnostic efficacy on intracranial infections and hydrocephalus evaluated by receiver operating characteristic curve analysis. The independent risk factors affecting postoperative intracranial infections and hydrocephalus were analysed by logistic multifactorial regression. The remission after postoperative symptomatic treatment was counted. The intracranial infection/control groups had significant differences in Glasgow Coma Scale (GCS) scores, opened injury, surgical time and cerebrospinal fluid leakage, whereas the hydrocephalus and control groups had marked differences in GCS scores, cerebrospinal fluid leakage and subdural effusion. Serum NLRP3, MMP-9 and IFN-γ levels were elevated in patients with post-craniotomy intracranial infections/hydrocephalus. The area under the curve values of independent serum NLRP3, MMP-9, IFN-γ and their combination for diagnosing postoperative intracranial infection were 0.822, 0.722, 0.734 and 0.925, respectively, and for diagnosing hydrocephalus were 0.865, 0.828, 0.782 and 0.957, respectively. Serum NLRP3, MMP-9 and IFN-γ levels and serum NLRP3 and MMP-9 levels were independent risk factors influencing postoperative intracranial infection and postoperative hydrocephalus, respectively. Patients with hydrocephalus had a high remission rate after postoperative symptomatic treatment. Serum NLRP3, MMP-9 and IFN-γ levels had high diagnostic efficacy in patients with postoperative intracranial infection and hydrocephalus, among which serum NLRP3 level played a major role.

OBJECTIVE: 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 were 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.
CONCLUSIONS: 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.

The automatic cutting of coal and rock surface morphology modeling based on the actual geological environment of coal mine underground excavation and mining is of great significance for improving the surface quality of coal and rock after cutting and enhancing the safety and stability of advanced support. To this end, using the principle of coordinate transformation, the kinematic trajectory of the cutting head of the tunneling machine is established, and the contour morphology of the cutting head under variable cutting technology is obtained. Then, based on the regenerative vibration theory of the cutting head, a dynamic model of the cutting head coal wall is established, and the coordinate relationship of the cutting head in the tunnel coordinate system under vibration induction is analyzed. Based on fractal theory and Z-MAP method, a simulation method for the surface morphology of coal and rock after cutting is proposed, which is driven by the cutting trajectory Under the coupling effect of cutting vibration induction and random fragmentation of coal and rock, simulation of the surface morphology of comprehensive excavation tunnels was conducted, and relevant experiments were conducted to verify the results. A 1:3 similarity experimental model of EBZ160 tunneling machine was used to build a cutting head coal and rock system cutting experimental platform for comparative experiments of cutting morphology. Furthermore, statistical methods were used to compare and evaluate the simulated roof with the actual roof. The results show that the relative errors between the maximum range of peaks and valleys, the peak skewness coefficient of height standard deviation, and the kurtosis coefficient of the actual roof are 1.3%, 24.5%, 16%, and 2.9%, respectively. Overall, this indicates that the surface morphology distribution characteristics of the simulated roof and the actual roof are similar, verifying the effectiveness of the modeling and simulation method proposed in this paper, and providing theoretical support for the design and optimization of advanced support in the future.

OBJECTIVE: The current study aimed to assess the protective performance of helmets equipped with multi-directional impact protection system (MIPS) under various oblique impact loads.
METHODS: Initially, a finite element model of a bicycle helmet with MIPS was developed based on the scanned geometric parameters of an actual bicycle helmet. Subsequently, the validity of model was confirmed using the KASK WG11 oblique impact test method. Three different impact angles (30°, 45°, and 60°) and 2 varying impact speeds (5 m/s and 8 m/s) were employed in oblique tests to evaluate protective performance of MIPS in helmets, focusing on injury assessment parameters such as peak linear acceleration (PLA) and peak angular acceleration (PAA) of the head.
RESULTS: The results demonstrated that in all impact simulations, both assessment parameters were lower during impact for helmets equipped with MIPS compared to those without. The PAA was consistently lower in the MIPS helmet group, whereas the difference in PLA was not significant in the no-MIPS helmet group. For instance, at an impact velocity of 8 m/s and a 30° inclined anvil, the MIPS helmet group exhibited a PAA of 3225 rad/s2 and a PLA of 281 g. In contrast, the no-MIPS helmet group displayed a PAA of 8243 rad/s2 and a PLA of 292 g. Generally, both PAA and PLA parameters decreased with the increase of anvil angles. At a 60° anvil angles, PAA and PLA values were 664 rad/s2 and 20.7 g, respectively, reaching their minimum.
CONCLUSIONS: The findings indicated that helmets incorporating MIPS offer enhanced protection against various oblique impact loads. When assessing helmets for oblique impacts, the utilization of larger angle anvils and rear impacts might not adequately evaluate protective performance during an impact event. These findings will guide advancements in helmet design and the refinement of oblique impact test protocols.

BACKGROUND: Although the Head Injury Criteria (HIC) has been widely applied to assess head impact injuries, it faces two outstanding problems: 1) HIC is affected strongly by the cut-off frequency when processing acceleration signals. And these cut-off frequencies are experiential and lack unified guidelines; 2) If the head was impacted on a different part, should the corresponding HIC threshold be the same? If these problems are not resolved, it could potentially lead to a critical misinterpretation of the safety assessment.
METHODS: Finite element method was used to reconstruct head impacts. The head model includes tissues like skull, brainstem, cerebrospinal fluid, etc. The head model was impacted in the frontal, occipital, parietal or lateral direction with different impact velocities. Acceleration signals of the head model were extracted directly from the skull and the head centroid node. To obtain a robust HIC, the filtering class of acceleration signals were analyzed carefully. Then, the relation between rigid body HIC and the centroid node HIC were studied systematically.
RESULTS: When the filtering class of rigid body acceleration and centroid node acceleration reached the cut-off frequency, the corresponding derivative of HIC tended to change smoothly. Using these cut-off frequencies, robust HICs were obtained. The rigid body HIC far exceeded that of centroid node HIC, such as 8, 9, 14 and 31 times exceeded in the frontal, occipital, parietal and lateral impact conditions, respectively. Moreover, approximate linear relations were found between the rigid body HIC and the centroid node HIC in different impact directions, respectively. From these relations, the injury thresholds of rigid body HIC of various directions were given quantitatively.
CONCLUSIONS: The rational filtering class like CFC 800 and CFC 700 were given for rigid body HIC and centroid node HIC, respectively. The rigid body HIC had a significant discrepancy from the centroid node HIC. Linear relations between the rigid body HIC and centroid node HIC were found, and their slopes changed with impact directions. From these relations, we can adjust the injury thresholds reasonably if the head receives different impacts. These findings can effectively enhance the applicability of HIC.

Growing skull fracture (GSF) is an uncommon form of head trauma among young children. In prior research, the majority of GSFs were typically classified based on pathophysiological mechanisms or the duration following injury. However, considering the varying severity of initial trauma and the disparities in the time elapsed between injury and hospital admission among patients, our objective was to devise a clinically useful classification system for GSFs among children, grounded in both clinical presentations and imaging findings, in order to guide clinical diagnosis and treatment decisions. The clinical and imaging data of 23 patients less than 12 years who underwent GSF were retrospectively collected and classified into four types. The clinical and imaging characteristics of the different types were reviewed in detail and statistically analyzed. In all 23 patients, 5 in type I, 7 in type II, 8 in type III, and 3 in type IV. 21/23 (91.3%) were younger than 3 years. Age ≤ 3 years and subscalp fluctuating mass were common in type I-III (P = 0.026, P = 0.005). Fracture width ≥ 4 mm was more common in type II-IV (P = 0.003), while neurological dysfunction mostly occurred in type III and IV (P < 0.001).Skull \"crater-like\" changes were existed in all type IV. 10/12 (83.3%) patients with neurological dysfunction had improved in motor or linguistic function. There was not improved in patients with type IV. GCS in different stage has its unique clinical and imaging characteristics. This classification could help early diagnosis and treatment for GCS, also could improve the prognosis significantly.

Vulnerable Road users (VRUs) often suffer multiple fatal head injury types simultaneously in road accidents. In this study, a head-weighted injury criterion (HWIC4) was proposed for assessing the risk of head AIS 4+ injuries considering multiple injury types. Firstly, the kinematic characteristics of VRUs in the 50 in-depth accidents were reconstructed by using multi-body system models, and head injuries were reconstructed using eight head kinematic-based injury criteria and eight brain tissue injury criteria via the THUMS (Ver. 4.0.2) head finite element model. The predictive capability of each injury criterion to predict head AIS 4+ injuries was assessed and four better predictors (HIC15, angular acceleration, coup pressure, and maximum principal strain) were selected. The different head injury types and the weighting parameters for each injury type were taken into account in the development of HWIC4. Finally, the effectiveness and evaluation of HWIC4 for head AIS 4+ injury was validated based on the area under of receiver operating characteristic (AUROC) curve and reconstruction results from 10 additional selected accident cases. The results showed that HWIC4 has a good predictive capability for head AIS 4+ injuries with an AUROC of 0.983, which means that HWIC4 is superior and more reliable than a single head injury criterion. This knowledge further improves the capability of head injury criteria to predict head AIS 4+ injuries.