Topical rhubarb charcoal-crosslinked chitosan/silk fibroin sponge scaffold for the repair of diabetic ulcers improves hepatic lipid deposition in db/db mice via the AMPK signalling pathway.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is closely linked to metabolic syndrome, characterised by insulin resistance, hyperglycaemia, abnormal lipid metabolism, and chronic inflammation. Diabetic ulcers (DUs) comprise consequential complications that arise as a result of T2DM. To investigate, db/db mice were used for the disease model. The findings demonstrated that a scaffold made from a combination of rhubarb charcoal-crosslinked chitosan and silk fibroin, designated as RCS/SF, was able to improve the healing process of diabetic wounds in db/db mice. However, previous studies have primarily concentrated on investigating the impacts of the RSC/SF scaffold on wound healing only, while its influence on the entire body has not been fully elucidated. MATERIAL AND METHODS: The silk fibroin/chitosan sponge scaffold containing rhubarb charcoal was fabricated in the present study using a freeze-drying approach. Subsequently, an incision with a diameter of 8 mm was made on the dorsal skin of the mice, and the RCS/SF scaffold was applied directly to the wound for 14 days. Subsequently, the impact of RCS/SF scaffold therapy on hepatic lipid metabolism was assessed through analysis of serum and liver biochemistry, histopathology, quantitative real-time PCR (qRT-PCR), immunohistochemistry, and Western blotting. RESULTS: The use of the RCS/SF scaffold led to an enhancement in the conditions associated with serum glucolipid metabolism in db/db mice. An assessment of hepatic histopathology further confirmed this enhancement. Additionally, the qRT-PCR analysis revealed that treatment with RCS/SF scaffold resulted in the downregulation of genes associated with fatty acid synthesis, fatty acid uptake, triglyceride (TG) synthesis, gluconeogenesis, and inflammatory factors. Moreover, the beneficial effect of the RCS/SF scaffold on oxidative stress was shown by assessing antioxidant enzymes and lipid peroxidation. Additionally, the network pharmacology analysis verified that the adenosine monophosphate-activated protein kinase (AMPK) signalling pathway had a vital function in mitigating non-alcoholic fatty liver disease (NAFLD) by utilizing R. officinale. The measurement of AMPK, sterol regulatory element binding protein 1 (SREBP1), fatty acid synthase (FASN), and acetyl CoA carboxylase (ACC) gene and protein expression provided support for this discovery. Furthermore, the molecular docking investigations revealed a robust affinity between the active components of rhubarb and the downstream targets of AMPK (SREBP1 and FASN). CONCLUSION: By regulating the AMPK signalling pathway, the RCS/SF scaffold applied topically effectively mitigated hepatic lipid accumulation, decreased inflammation, and attenuated oxidative stress. The present study, therefore, emphasises the crucial role of the topical RCS/SF scaffold in regulating hepatic lipid metabolism, thereby confirming the concept of "external and internal reshaping".

Higher Toxicity of Gaseous Organics Relative to Particulate Matters Emitted from Typical Cooking Processes.

Cooking emission is known to be a significant anthropogenic source of air pollution in urban areas, but its toxicities are still unclear. This study addressed the toxicities of fine particulate matter (PM2.5) and gaseous organics by combining chemical fingerprinting analysis with cellular assessments. The cytotoxicity and reactive oxygen species activity of gaseous organics were ∼1.9 and ∼8.3 times higher than those of PM2.5, respectively. Moreover, these values of per unit mass PM2.5 were ∼7.1 and ∼15.7 times higher than those collected from ambient air in Shanghai. The total oleic acid equivalent quantities for carcinogenic and toxic respiratory effects of gaseous organics, as estimated using predictive models based on quantitative structure-property relationships, were 1686 ± 803 and 430 ± 176 µg/mg PM2.5, respectively. Both predicted toxicities were higher than those of particulate organics, consistent with cellular assessment. These health risks are primarily attributed to the high relative content and toxic equivalency factor of the organic compounds present in the gas phase, including 7,9-di-tert-butyl-1-oxaspiro(4,5)deca-6,9-diene-2,8-dione, 2-ethylhexanoic acid, and 2-phenoxyethoxybenzene. Furthermore, these compounds and fatty acids were identified as prominent chemical markers of cooking-related emissions. The obtained results highlight the importance of control measures for cooking-emitted gaseous organics to reduce the personal exposure risks.

Robust point light source calibration method for near-field photometric stereo using feature points selection.

In this paper, we present a robust method for nonisotropic point light source calibration through feature points selection. By analyzing the relationship between the observed surface and its image intensity under near-field lighting, the feature points selection method is first developed to effectively address the noisy observations and improve calibration robustness. Afterward, to enhance efficiency and accuracy of the calibration, a cost function of l p-norm is established based on the above relationship, and an improved Newton method-based iteration process is applied to calculate the light source parameters. The simulations demonstrate that the proposed method is capable of achieving robust calibration results with the estimation error less than 2.7 mm and 0.8°, even though the image intensities are corrupted by Gaussian white noise with standard deviation up to 0.4. The experimental validation is performed using a self-designed photometric stereo system, where the calibration of point light sources is conducted, and measurements are taken on a standard sphere and compressor blade based on the obtained calibration results, which demonstrates the effectiveness of what we believe to be a new method.

6-Gingerol Ameliorates Hepatic Steatosis, Inflammation and Oxidative Stress in High-Fat Diet-Fed Mice through Activating LKB1/AMPK Signaling.

6-Gingerol, one of the major pharmacologically active ingredients extracted from ginger, has been reported experimentally to exert hepatic protection in non-alcoholic fatty liver disease (NAFLD). However, the molecular mechanism remains largely elusive. RNA sequencing indicated the significant involvement of the AMPK signaling pathway in 6-gingerol-induced alleviation of NAFLD in vivo. Given the significance of the LKB1/AMPK pathway in metabolic homeostasis, this study aims to investigate its role in 6-gingerol-induced mitigation on NAFLD. Our study showed that 6-gingerol ameliorated hepatic steatosis, inflammation and oxidative stress in vivo and in vitro. Further experiment validation suggested that 6-gingerol activated an LKB1/AMPK pathway cascade in vivo and in vitro. Co-immunoprecipitation analysis demonstrated that the 6-gingerol-elicited activation of an LKB1/AMPK pathway cascade was related to the enhanced stability of the LKB1/STRAD/MO25 complex. Furthermore, radicicol, an LKB1 destabilizer, inhibited the activating effect of 6-gingerol on an LKB1/AMPK pathway cascade via destabilizing LKB1/STRAD/MO25 complex stability in vitro, thus reversing the 6-gingerol-elicited ameliorative effect. In addition, molecular docking analysis further predicated the binding pockets of LKB1 necessary for binding with 6-gingerol. In conclusion, our results indicate that 6-gingerol plays an important role in regulating the stability of the LKB1/STRAD/MO25 complex and the activation of LKB1, which might weigh heavily in the 6-gingerol alleviation of NAFLD.

Phase noise estimation based white light scanning interferometry for high-accuracy surface profiling.

White light scanning interferometry (WLSI) has been an extremely powerful technique in precision measurements. In this work, a phase noise estimation based surface recovery algorithm is proposed, which can significantly improve the measurement accuracy by decreasing the noise level in phase map coming from the systemic and environmental disturbances. The noise existed in phase map is firstly researched in spectrum domain and defined as the linear combination of complex terms at each angular wavenumber. Afterwards, based on the theoretical linearity of the phase distribution, the surface features can be redefined through establishing the function with respect to phase noise. By applying least square estimation (LSE), a spectral coefficient is defined to determine the optimal estimation of phase noise that represents the best statistical consistency with the actual case, from which a more accurate surface after removing most phase noise will then be generated. In order to testify the noise elimination ability of the proposed method, a nano-scale step height standard (9.5nm±1.0nm) is scanned, and the measurement result 9.49nm with repeatability 0.17nm is successfully achieved. Moreover, a leading edge of an aero-engine blade is also tested to investigate the potential of this method in industrial inspections. The measurement comparison with AFM is also displayed.

High-detectivity organic photodetectors with double bulk heterojunction enabled by water transfer printing.

Suppressing the dark current is an effective strategy to boost the detection capability of organic photodetectors (OPDs). In this Letter, the water transfer printing method is demonstrated in double bulk heterojunction (BHJ) OPDs, which is solvent-independent rather than the traditional sequential spin-coating method, enabling the elimination of the negative effects of solvents on the underlying film and the suppressing of the dark current. As a result, a photo detectivity up to 1012 Jones was obtained in the wide spectral range of 400-900 nm with a small working area of 3 mm2.

[Planning of ecologically suitable areas for Ligusticum chuanxiong under background of soil cadmium pollution].

Chuanxiong Rhizoma is a traditional Chinese medicinal material mainly produced in Sichuan and Chongqing of China. In recent years, the cadmium content in Chuanxiong Rhizoma produced in most of the genuine producing areas has exceeded the standard, which makes Chuanxiong Rhizoma difficult to be exported. To solve the problem of excessive cadmium content in soil, this study employed the MaxEnt model to simulate the potential geographic distribution of Ligusticum chuanxiong and evaluate important environmental factors, and re-plan its ecologically suitable areas based on the mineral distribution characteristics and soil cadmium pollution status. The results showed that the places suitable for L. chuanxiong growing covered an area of 335 523.69 km~2, mainly in central and eastern Sichuan, southern Shaanxi and most parts of Chongqing. Among them, the highly suitable areas of L. chuanxiong were mainly concentrated in Chengdu, Ya'an, Deyang, and Mianyang. Solar radiation, annual precipitation, and annual range of temperature were evaluated as important variables affecting the distribution of L. chuanxiong, with the contribution rates of 62.3%, 13.3%, and 6.8%, respectively. In addition, Qionglai county, Chongqing county, Mianyang city(Youxian district and Fucheng district), Qingchuan county, and Xinjin county were classified into the first-class ecologically suitable zone, covering a total area of 2 768.87 km~2. The se-cond-class ecologically suitable zone was even wider, involving such counties as Tongjiang county, Renshou county, Jianyang county, and Nanjiang county, and the total area reached 43 616.92 km~2. The re-planning of the ecologically suitable areas for L. chuanxiong has provided strong data support for the cultivation and resource development of L. chuanxiong and also new ideas for solving the problem of excessive cadmium content in L. chuanxiong.

[6-Gingerol ameliorates adipose tissue insulin resistance in aging rats].

This study investigated the effects and mechanisms of 6-gingerol on adipose tissue insulin resistance in naturally aging rats with glycolipid metabolism disorders. Twenty-seven aging male SD rats were randomly divided into a model group(aged, n=9) and two groups treated with 6-gingerol at 0.05 mg·kg~(-1)(G-L, n=9) and 0.2 mg·kg~(-1)(G-H, n=9). Six young rats were randomly assigned to a normal control group(NC). Rats were treated for seven weeks by gavage. Non-esterified fatty acid(NEFA) and insulin content was determined by enzyme-linked immunosorbent assay(ELISA), and adipose tissue insulin resistance index(Adipo-IR) was calculated. HE staining was used to observe the size of adipocytes in epididymal white adipose tissue(eWAT). The gene and protein expression levels of adiponectin receptor 1(AdipoR1), AMP-activated protein kinase α(AMPKα), phosphorylated AMPK(p-AMPKα~(Thr172)), peroxisome proliferator-activated receptor-γ coactivator-1α(PGC-1α), phosphatidylinositol 3-kinase(PI3 K), protein kinase B(Akt), phosphorylated Akt(p-Akt~(Ser473)), tumor necrosis factor-α(TNF-α), c-Jun N-terminal kinase 1/2(JNK1/2), phosphorylated JNK1/2(p-JNK~(Thr183/Tyr185)), interleukin-1ß(IL-1ß), and interleukin-6(IL-6) in adiponectin(APN), insulin, and inflammatory factor signaling pathways were detected by Western blot and real-time RCR, respectively. The results showed that 6-gingerol at a high dose could significantly decrease the fasting plasma content of NEFA and insulin and reduce Adipo-IR. Additionally, 6-gingerol at a high dose significantly increased the protein and mRNA expression of APN, AdipoR1, PGC-1α, and PI3 K in eWAT, elevated the relative expression of p-AMPK~(Thr172) and p-Akt~(Ser 473), reduced the protein and mRNA expression of TNF-α, IL-1, and IL-6 in eWAT, and decreased the relative expression of p-JNK1 and p-JNK2. This study reveals that 6-gingerol can improve insulin sensitivity of adipose tissues in aging rats with glycolipid metabolism disorders, and this effect is presumedly achieved by enhancing the PI3 K/Akt signaling pathway, inhibiting adipose tissue inflammation, increasing APN synthesis, enhancing AdipoR1 expression, and activating its downstream AMPK/PGC-1α signaling pathway.

A low-volume air sampling method for legacy and novel brominated flame retardants in indoor environment using a newly developed sorbent mixture.

Brominated flame retardants (BFRs) are a series of stable and outstanding flame retardants bringing human exposure risks in indoor environment. However, sampling methods now available for BFRs are solvent-consuming and relatively complicated. This study provides a new option of low-volume air sampling device using cartridges with a sorbent mixture for different types of legacy and novel BFRs. In this study, we found that HC-C18 sorbent is most suitable for polybrominated diphenyl ethers (PBDEs) and novel BFRs (NBFRs) enrichment, and that NH2 for hexabromocyclododecanes (HBCDs). The sorbent mixture was optimized using a complex of HC-C18 and NH2 sorbents with elution recovery of 69.4% ± 7.9-117% ± 10%, pumping-through recovery of 84.5% ± 7.9-127% ± 36%, and breakthrough recovery of 70.8% ± 3.4-118% ± 6% for PBDEs, NBFRs, and HBCDs in indoor air. A sequential elution was also achieved using hexane for PBDEs and NBFRs and ethyl acetate for HBCDs. The method was validated with field sampling at nine student dormitory rooms. For legacy BFRs, all the isomers of HBCDs were detected in the air of nine rooms with the median concentrations of 91, 33, and 25 pg/m3 for (±)α-HBCD, (±)ß-HBCD, (±)γ-HBCD, respectively, while PBDEs were hardly detected. In contrast, NBFRs were detected at total concentrations of 15-811 pg/m3. Pentabromotoluene (PBT) was the most frequently detected NBFRs with a median concentration of 4 pg/m3, followed by EHTBB at 56 pg/m3 and HBBZ at 21 pg/m3. For the risk assessment, the total hazard index value for air inhalation of BFRs was estimated at 6.1⎓10-4-0.35, which are consistently lower than 1, indicating no immediate health risk, while their long-term effects remain worth concerns.

Polymeric Micelles in Cancer Immunotherapy.

Cancer immunotherapies have generated some miracles in the clinic by orchestrating our immune system to combat cancer cells. However, the safety and efficacy concerns of the systemic delivery of these immunostimulatory agents has limited their application. Nanomedicine-based delivery strategies (e.g., liposomes, polymeric nanoparticles, silico, etc.) play an essential role in improving cancer immunotherapies, either by enhancing the anti-tumor immune response, or reducing their systemic adverse effects. The versatility of working with biocompatible polymers helps these polymeric nanoparticles stand out as a key carrier to improve bioavailability and achieve specific delivery at the site of action. This review provides a summary of the latest advancements in the use of polymeric micelles for cancer immunotherapy, including their application in delivering immunological checkpoint inhibitors, immunostimulatory molecules, engineered T cells, and cancer vaccines.

Edge and Cloud Collaborative Entity Recommendation Method towards the IoT Search.

There are massive entities with strong denaturation of state in the physical world, and users have urgent needs for real-time and intelligent acquisition of entity information, thus recommendation technologies that can actively provide instant and precise entity state information come into being. Existing IoT data recommendation methods ignore the characteristics of IoT data and user search behavior; thus the recommendation performances are relatively limited. Considering the time-varying characteristics of the IoT entity state and the characteristics of user search behavior, an edge-cloud collaborative entity recommendation method is proposed via combining the advantages of edge computing and cloud computing. First, an entity recommendation system architecture based on the collaboration between edge and cloud is designed. Then, an entity identification method suitable for edge is presented, which takes into account the feature information of entities and carries out effective entity identification based on the deep clustering model, so as to improve the real-time and accuracy of entity state information search. Furthermore, an interest group division method applied in cloud is devised, which fully considers user's potential search needs and divides user interest groups based on clustering model for enhancing the quality of recommendation system. Simulation results demonstrate that the proposed recommendation method can effectively improve the real-time and accuracy performance of entity recommendation in comparison with traditional methods.

Detection of Salmonella Typhimurium on Spinach Using Phage-Based Magnetoelastic Biosensors.

Phage-based magnetoelastic (ME) biosensors have been studied as an in-situ, real-time, wireless, direct detection method of foodborne pathogens in recent years. This paper investigates an ME biosensor method for the detection of Salmonella Typhimurium on fresh spinach leaves. A procedure to obtain a concentrated suspension of Salmonella from contaminated spinach leaves is described that is based on methods outlined in the U.S. FDA Bacteriological Analytical Manual for the detection of Salmonella on leafy green vegetables. The effects of an alternative pre-enrichment broth (LB broth vs. lactose broth), incubation time on the detection performance and negative control were investigated. In addition, different blocking agents (BSA, Casein, and Superblock) were evaluated to minimize the effect of nonspecific binding. None of the blocking agents was found to be superior to the others, or even better than none. Unblocked ME biosensors were placed directly in a concentrated suspension and allowed to bind with Salmonella cells for 30 min before measuring the resonant frequency using a surface-scanning coil detector. It was found that 7 h incubation at 37 °C in LB broth was necessary to detect an initial spike of 100 cfu/25 g S. Typhimurium on spinach leaves with a confidence level of difference greater than 95% (p < 0.05). Thus, the ME biosensor method, on both partly and fully detection, was demonstrated to be a robust and competitive method for foodborne pathogens on fresh products.

The Effects of Ambient Temperature and Atmospheric Humidity on the Diffusion Dynamics of Hydrogen Fluoride Gas Leakage Based on the Computational Fluid Dynamics Method.

In order to investigate the impact of environmental temperature and atmospheric humidity on the leakage and diffusion of hydrogen fluoride (HF) gas, this study focused on the real scenario of an HF chemical industrial park. Based on the actual dispersion scenario of HF gas, a proportionally scaled-down experimental platform for HF gas leakage was established to validate the accuracy and feasibility of numerical simulations under complex conditions. Using the validated model, the study calculated the complex scenarios of HF leakage and diffusion within the temperature range of 293 K to 313 K and the humidity range of 0% to 100%. The simulation results indicated that different environmental temperatures had a relatively small impact on the hazardous areas (the lethal area, severe injury area, light injury area, and maximum allowable concentration (MAC) area) formed by HF gas leakage. At 600 s of dispersion, the fluctuation range of hazardous area sizes under different temperature conditions was between 3.11% and 13.07%. In contrast to environmental temperature, atmospheric relative humidity had a more significant impact on the dispersion trend of HF leakage. Different relative humidity levels mainly affected the areas of the lethal zone, light injury zone, and MAC zone. When HF continued to leak and disperse for 600 s, compared to 0% relative humidity, 100% relative humidity reduced the lethal area by 35.7%, while increasing the light injury area and MAC area by 27.26% and 111.6%, respectively. The impact on the severe injury area was relatively small, decreasing by 1.68%. The results of this study are crucial for understanding the dispersion patterns of HF gas under different temperature and humidity conditions.

P2Y12 inhibitor use predicts hematoma expansion in patients with intracerebral hemorrhage.

OBJECTIVE: Hematoma expansion (HE) predicts disability and death after acute intracerebral hemorrhage (ICH). Aspirin and anticoagulants have been associated with HE. We tested the hypothesis that P2Y12 inhibitors predict subsequent HE in patients. We explored laboratory measures of P2Y12 inhibition and dual antiplatelet therapy with aspirin (DAPT). METHODS: We prospectively identified patients with ICH. Platelet activity was measured with the VerifyNow-P2Y12 assay. Hematoma volumes for initial and follow-up CTs were calculated using a validated semi-automated technique. HE was defined as the difference between hematoma volumes on the initial and follow-up CT scans. Nonparametric statistics were performed with Kruskal-Wallis H, and correction for multiple comparisons performed with Dunn's test. RESULTS: In 194 patients, 15 (7.7%) were known to take a P2Y12 inhibitor (clopidogrel in all but one). Patients taking a P2Y12 inhibitor had more HE compared to patients not taking a P2Y12 inhibitor (3.5 [1.2-11.9] vs. 0.1 [-0.8-1.4] mL, p = 0.004). Patients taking DAPT experienced the most HE (7.2 [2.6-13.8] vs. 0.0 [-1.0-1.1] mL, p = 0.04). The use of P2Y12 inhibitors was associated with less P2Y12 activity (178 [149-203] vs. 288 [246-319] P2Y12 reaction units, p = 0.005). INTERPRETATION: Patients taking a P2Y12 inhibitor had more HE and less P2Y12 activity. The effect was most pronounced in patients on DAPT, suggesting a synergistic effect of P2Y12 inhibitors and aspirin with respect to HE. Acute reversal of P2Y12 inhibitors in acute ICH requires further study.

Brain Deformation Estimation With Transfer Learning for Head Impact Datasets Across Impact Types.

OBJECTIVE: The machine-learning head model (MLHM) to accelerate the calculation of brain strain and strain rate, which are the predictors for traumatic brain injury (TBI), but the model accuracy was found to decrease sharply when the training/test datasets were from different head impacts types (i.e., car crash, college football), which limits the applicability of MLHMs to different types of head impacts and sports. Particularly, small sizes of target dataset for specific impact types with tens of impacts may not be enough to train an accurate impact-type-specific MLHM. METHODS: To overcome this, we propose data fusion and transfer learning to develop a series of MLHMs to predict the maximum principal strain (MPS) and maximum principal strain rate (MPSR). RESULTS: The strategies were tested on American football (338), mixed martial arts (457), reconstructed car crash (48) and reconstructed American football (36) and we found that the MLHMs developed with transfer learning are significantly more accurate in estimating MPS and MPSR than other models, with a mean absolute error (MAE) smaller than 0.03 in predicting MPS and smaller than [Formula: see text] in predicting MPSR on all target impact datasets. High performance in concussion detection was observed based on the MPS and MPSR estimated by the transfer-learning-based models. CONCLUSION: The MLHMs can be applied to various head impact types for rapidly and accurately calculating brain strain and strain rate. SIGNIFICANCE: This study enables developing MLHMs for the head impact type with limited availability of data, and will accelerate the applications of MLHMs.

Enhancing the photodynamic effect of curcumin through modification with TiO2 nanoparticles and cationic polymers.

Curcumin (CUR), a natural compound extracted from turmeric, has shown potential as a photosensitizer in photodynamic therapy (PDT). The aim of this work was to enhance the efficacy of CUR by modifying it using titanium dioxide (TiO2) nanoparticles and a cationic polymer called Sofast to create a nanocomposite TiO2-CUR-Sofast (TCS). Compared to unmodified CUR, TCS exhibited a broadening toward longer wavelength in the absorption wavelength within the 400-550 nm range, leading to improved CUR absorption. Cellular uptake efficiency of TCS was also enhanced, and it demonstrated nearly 4.7-fold higher reactive oxygen species (ROS) generation than CUR. Furthermore, TCS displayed the ability to attach to the cell membrane and enter cells within a 30-min incubation period. Upon irradiation, TCS exhibited remarkable cytotoxicity, resulting in a significant reduction in the viability of various cancer cells. Autofluorescence lifetime imaging of intracellular reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and flavin adenine dinucleotide (FAD) enzymes indicated that cancer cells treated with TCS and irradiation undergo a metabolic pathway shift from oxidative phosphorylation to glycolysis. These findings highlight the potential of TCS as an effective PDT agent for cancer treatment.

AI-based denoising of head impact kinematics measurements with convolutional neural network for traumatic brain injury prediction.

OBJECTIVE: Wearable devices are developed to measure head impact kinematics but are intrinsically noisy because of the imperfect interface with human bodies. This study aimed to improve the head impact kinematics measurements obtained from instrumented mouthguards using deep learning to enhance traumatic brain injury (TBI) risk monitoring. METHODS: We developed one-dimensional convolutional neural network (1D-CNN) models to denoise mouthguard kinematics measurements for tri-axial linear acceleration and tri-axial angular velocity from 163 laboratory dummy head impacts. The performance of the denoising models was evaluated on three levels: kinematics, brain injury criteria, and tissue-level strain and strain rate. Additionally, we performed a blind test on an on-field dataset of 118 college football impacts and a test on 413 post-mortem human subject (PMHS) impacts. RESULTS: On the dummy head impacts, the denoised kinematics showed better correlation with reference kinematics, with relative reductions of 36% for pointwise root mean squared error and 56% for peak absolute error. Absolute errors in six brain injury criteria were reduced by a mean of 82%. For maximum principal strain and maximum principal strain rate, the mean error reduction was 35% and 69%, respectively. On the PMHS impacts, similar denoising effects were observed and the peak kinematics after denoising were more accurate (relative error reduction for 10% noisiest impacts was 75.6%). CONCLUSION: The 1D-CNN denoising models effectively reduced errors in mouthguard-derived kinematics measurements on dummy and PMHS impacts. SIGNIFICANCE: This study provides a novel approach for denoising head kinematics measurements in dummy and PMHS impacts, which can be further validated on more real-human kinematics data before real-world applications.

Short tandem repeats of human genome are intrinsically unstable in cultured cells in vivo.

Short tandem repeats (STRs) are a class of abundant structural or functional elements in the human genome and exhibit a polymorphic nature of repeat length and genetic variation within human populations. Interestingly, STR expansions underlie about 60 neurological disorders. However, "stutter" artifacts or noises render it difficult to investigate the pathogenesis of STR expansions. Here, we systematically investigated STR instability in cultured human cells using GC-rich CAG and AT-rich ATTCT tandem repeats as examples. We found that triplicate bidirectional Sanger sequencing with PCR amplification under proper conditions can reliably assess STR length. In addition, we found that next-generation sequencing with paired-end reads bidirectionally covering STR regions can accurately and reliably assay STR length. Finally, we found that STRs are intrinsically unstable in cultured human cell populations and during single-cell cloning. Our data suggest a general method for accurately and reliably assessing STR length and have important implications in investigating pathogenesis of STR expansion diseases.

Big Data in Stroke: How to Use Big Data to Make the Next Management Decision.

The last decade has seen significant advances in the accumulation of medical data, the computational techniques to analyze that data, and corresponding improvements in management. Interventions such as thrombolytics and mechanical thrombectomy improve patient outcomes after stroke in selected patients; however, significant gaps remain in our ability to select patients, predict complications, and understand outcomes. Big data and the computational methods needed to analyze it can address these gaps. For example, automated analysis of neuroimaging to estimate the volume of brain tissue that is ischemic and salvageable can help triage patients for acute interventions. Data-intensive computational techniques can perform complex risk calculations that are too cumbersome to be completed by humans, resulting in more accurate and timely prediction of which patients require increased vigilance for adverse events such as treatment complications. To handle the accumulation of complex medical data, a variety of advanced computational techniques referred to as machine learning and artificial intelligence now routinely complement traditional statistical inference. In this narrative review, we explore data-intensive techniques in stroke research, how it has informed the management of stroke patients, and how current work could shape clinical practice in the future.

Finite element evaluation of an American football helmet featuring liquid shock absorbers for protecting against concussive and subconcussive head impacts.

Introduction: Concern has grown over the potential long-term effects of repeated head impacts and concussions in American football. Recent advances in impact engineering have yielded the development of soft, collapsible, liquid shock absorbers, which have demonstrated the ability to dramatically attenuate impact forces relative to existing helmet shock absorbers. Methods: To further explore how liquid shock absorbers can improve the efficacy of an American football helmet, we developed and optimized a finite element (FE) helmet model including 21 liquid shock absorbers spread out throughout the helmet. Using FE models of an anthropomorphic test headform and linear impactor, a previously published impact test protocol representative of concussive National Football League impacts (six impact locations, three velocities) was performed on the liquid FE helmet model and four existing FE helmet models. We also evaluated the helmets at three lower impact velocities representative of subconcussive football impacts. Head kinematics were recorded for each impact and used to compute the Head Acceleration Response Metric (HARM), a metric factoring in both linear and angular head kinematics and used to evaluate helmet performance. The head kinematics were also input to a FE model of the head and brain to calculate the resulting brain strain from each impact. Results: The liquid helmet model yielded the lowest value of HARM at 33 of the 36 impact conditions, offering an average 33.0% (range: -37.5% to 56.0%) and 32.0% (range: -2.2% to 50.5%) reduction over the existing helmet models at each impact condition in the subconcussive and concussive tests, respectively. The liquid helmet had a Helmet Performance Score (calculated using a summation of HARM values weighted based on injury incidence data) of 0.71, compared to scores ranging from 1.07 - 1.21 from the other four FE helmet models. Resulting brain strains were also lower in the liquid helmet. Discussion: The results of this study demonstrate the promising ability of liquid shock absorbers to improve helmet safety performance and encourage the development of physical prototypes of helmets featuring this technology. The implications of the observed reductions on brain injury risk are discussed.