ABSTRACT
BACKGROUND: The objective of this study was to define clinically meaningful phenotypes of intracerebral hemorrhage (ICH) using machine learning. METHODS: We used patient data from two US medical centers and the Antihypertensive Treatment of Acute Cerebral Hemorrhage-II clinical trial. We used k-prototypes to partition patient admission data. We then used silhouette method calculations and elbow method heuristics to optimize the clusters. Associations between phenotypes, complications (e.g., seizures), and functional outcomes were assessed using the Kruskal-Wallis H-test or χ2 test. RESULTS: There were 916 patients; the mean age was 63.8 ± 14.1 years, and 426 patients were female (46.5%). Three distinct clinical phenotypes emerged: patients with small hematomas, elevated blood pressure, and Glasgow Coma Scale scores > 12 (n = 141, 26.6%); patients with hematoma expansion and elevated international normalized ratio (n = 204, 38.4%); and patients with median hematoma volumes of 24 (interquartile range 8.2-59.5) mL, who were more frequently Black or African American, and who were likely to have intraventricular hemorrhage (n = 186, 35.0%). There were associations between clinical phenotype and seizure (P = 0.024), length of stay (P = 0.001), discharge disposition (P < 0.001), and death or disability (modified Rankin Scale scores 4-6) at 3-months' follow-up (P < 0.001). We reproduced these three clinical phenotypes of ICH in an independent cohort (n = 385) for external validation. CONCLUSIONS: Machine learning identified three phenotypes of ICH that are clinically significant, associated with patient complications, and associated with functional outcomes. Cerebellar hematomas are an additional phenotype underrepresented in our data sources.
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In order to study the effects of temperature, wind speed, and leakage volume on the diffusion of heavy gas leakage, this paper establishes a scaling model for the experimental study of gas leakage and diffusion by using the similarity theory with a certain factory as the target. And carbon dioxide gas is selected to replace the toxic and harmful heavy gas to carry out experiments under different temperatures (0-40 °C), wind speeds (0-2 m/s), and leakage velocities (2.5-12.5 L/min), respectively. The results showed that the diffusion rate of heavy gas expanded with increasing temperature under the conditions of wind speed of 0.25 m/s and leakage velocity of 1.5 L/min. When the temperature was increased from 0 to 40 °C, the concentration increase at each location was 125-290% at 600 s. Under the condition of temperature of 20 °C and leakage velocity of 5 L/min, the concentration at each location increased linearly with diffusion time when there was wind, while the linear relationship was not obvious when there was no wind. The effect on the concentration was larger when the wind speed was less than 1 m/s and smaller when the wind speed was greater than 1 m/s. At 20 °C and a wind speed of 0.5 m/s, the concentration of carbon dioxide at each location was increasing as the leakage increased. As the leakage velocity increases from 2.5 to 12.5 L/min, the carbon dioxide concentration at 600 s spreads 2-14 times. The research in this paper provides some decision support for the rescue work, which is important for improving the emergency rescue capability of the leakage accident.
ABSTRACT
Implantable drug delivery systems formed upon injection offer a host of advantages, including localized drug administration, sustained release, minimized side effects, and enhanced patient compliance. Among the various techniques utilized for the development of in situ forming drug implants, solvent-induced phase inversion emerges as a particularly promising approach. However, synthetic polymer-based implants have been associated with undesirable effects arising from polymer degradation. In response to this challenge, a novel category of drug delivery systems, known as phospholipids-based phase separation gels (PPSGs), has emerged. These gels, characterized by their low initial viscosity, exhibit injectability and undergo rapid transformation into in situ implants when exposed to an aqueous environment. A typical PPSG formulation comprises biodegradable components, such as phospholipids, pharmaceutical oil, and a minimal amount of ethanol. The minimized organic solvents in the composition show good biocompatibility. And the relatively simple composition holds promise for industrial-scale manufacturing. This comprehensive review provides an overview of the principles and advancements in PPSG systems, with specific emphasis on their suitability as drug delivery systems for a wide range of active pharmaceutical ingredients (APIs), spanning from small molecules to peptides and proteins. Additionally, we explore the critical parameters and underlying principles governing the formulation of PPSG-based drug delivery strategies, offering valuable insights on optimization strategies.
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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.
Subject(s)
Aspirin , Cerebral Hemorrhage , Clopidogrel , Hematoma , Platelet Aggregation Inhibitors , Purinergic P2Y Receptor Antagonists , Humans , Male , Cerebral Hemorrhage/diagnostic imaging , Cerebral Hemorrhage/drug therapy , Aged , Purinergic P2Y Receptor Antagonists/administration & dosage , Purinergic P2Y Receptor Antagonists/pharmacology , Middle Aged , Female , Aspirin/administration & dosage , Clopidogrel/administration & dosage , Hematoma/diagnostic imaging , Aged, 80 and over , Disease Progression , Prospective Studies , Dual Anti-Platelet TherapyABSTRACT
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.
ABSTRACT
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.
ABSTRACT
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".
Subject(s)
Chitosan , Diabetes Complications , Diabetes Mellitus, Type 2 , Fibroins , Non-alcoholic Fatty Liver Disease , Rheum , Mice , Animals , AMP-Activated Protein Kinases/genetics , AMP-Activated Protein Kinases/metabolism , Rheum/metabolism , Charcoal/metabolism , Charcoal/pharmacology , Charcoal/therapeutic use , Fibroins/metabolism , Fibroins/pharmacology , Fibroins/therapeutic use , Diabetes Mellitus, Type 2/metabolism , Molecular Docking Simulation , Ulcer/metabolism , Ulcer/pathology , Liver/metabolism , Lipid Metabolism , Non-alcoholic Fatty Liver Disease/pathology , Diabetes Complications/pathology , Inflammation/pathology , Fatty Acids/metabolism , Lipids/therapeutic useABSTRACT
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.
Subject(s)
Curcumin , Nanoparticles , Photochemotherapy , Curcumin/pharmacology , Photochemotherapy/methods , Polymers , Photosensitizing Agents/pharmacologyABSTRACT
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.
Subject(s)
Brain , Machine Learning , Humans , Brain/diagnostic imaging , Brain/physiopathology , Football/injuries , Brain Injuries, Traumatic/physiopathology , Head/physiology , Accidents, Traffic , Biomechanical Phenomena/physiology , Models, BiologicalABSTRACT
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.
ABSTRACT
Protecting human health from fine particulate matter (PM) pollution is the ambitious goal of clean air actions, but current control strategies largely ignore the role of source-specific PM toxicity. Here, we proposed health-oriented control strategies by integrating the unequal toxic potencies of the most polluting industrial PMs. Iron and steel industry (ISI)-emitted PM2.5 exhibit about one order of magnitude higher toxic potency than those of cement and power industries. Compared with the current mass-based control strategy (prioritizing implementation of ultralow emission standards in the power sector), the proposed health-oriented control strategy (priority control of the ISI sector) could generate 5.4 times higher reduction in population-weighted toxic potency-adjusted PM2.5 exposure among polluting industries in China. Furthermore, the marginal abatement cost per unit of toxic potency-adjusted mass of ISI-emitted PM2.5 is only a quarter of that of the other two sectors under ultralow emission scenarios. We highlight that a health-oriented air pollution control strategy is urgently required to achieve cost-effective reductions in particulate exposure risks.
ABSTRACT
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 â¼1.9 and â¼8.3 times higher than those of PM2.5, respectively. Moreover, these values of per unit mass PM2.5 were â¼7.1 and â¼15.7 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.
Subject(s)
Air Pollutants , Air Pollution, Indoor , Particulate Matter/analysis , Air Pollutants/analysis , Gases/analysis , China , Cooking/methods , Environmental Monitoring/methods , Air Pollution, Indoor/analysisABSTRACT
L-aspartic acid, L-threonine, L-isoleucine, l-lysine, and L-methionine constitute the l-aspartate amino acids (AFAAs). Except for L-aspartic acid, these are essential amino acids that cannot be synthesized by humans or animals themselves. E. coli and C. glutamicum are the main model organisms for AFAA production. It is necessary to reconstitute microbial cell factories and the physiological state of industrial fermentation cells for in-depth research into strains with higher AFAA production levels and optimal growth states. Considering that the anabolic pathways of the AFAAs and engineering modifications have rarely been reviewed in the latest progress, this work reviews the central metabolic pathways of two strains and strategies for the metabolic engineering of AFAA synthetic pathways. The challenges posed by microbial physiology in AFAA production and possible strategies to address them, as well as future research directions for constructing strains with high AFAA production levels, are discussed in this review article.
Subject(s)
Amino Acids , Corynebacterium glutamicum , Humans , Amino Acids/metabolism , Aspartic Acid/metabolism , Metabolic Engineering , Escherichia coli/genetics , Escherichia coli/metabolism , Corynebacterium glutamicum/metabolism , FermentationABSTRACT
Diabetic patients often experience long-term risks due to chronic inflammation and delayed re-epithelialization during impaired wound healing. Although the severity of this condition is well known, the treatment options for diabetic wounds are limited. Rhubarb charcoal, a well-known traditional Chinese medicine, has been used to treat skin wounds for thousands of years. We produced a chitosan/silk fibroin sponge scaffold loaded with natural carbonized rhubarb and crosslinked it by freeze-drying to create a highly efficient RCS/SF scaffold. Rhubarb carbon and carboxymethyl chitosan exhibit antibacterial activity and promote wound healing. Owing to its 3D porous structure, this scaffold is antibacterial and pro-angiogenic. It also possesses remarkable properties, such as excellent swelling and biocompatibility. The supportive effect of carbonized rhubarb on mouse fibroblast migration is mediated at the cellular/tissue level by increased skin neovascularization and re-epithelization. Compared to the control group, RCS/SF scaffolds promoted faster healing, increased neovascularization, enhanced collagen deposition, and re-epithelialization within two weeks. The scaffold's pro-healing properties and efficient release of carbonized rhubarb, with rapid hemostatic and good sterilization effects, make it an outstanding candidate for treating diabetic wounds and novel therapeutic interventions for diabetic ulcers.
Subject(s)
Chitosan , Diabetes Mellitus , Fibroins , Rheum , Humans , Mice , Animals , Fibroins/pharmacology , Charcoal , Chitosan/chemistry , Wound Healing , Diabetes Mellitus/drug therapy , Inflammation , Hemostasis , Anti-Bacterial Agents/pharmacologyABSTRACT
Previous studies show that astragaloside IV (ASIV) has anti-renal fibrosis effects. However, its mechanism remains elusive. In this study, we investigated the anti-fibrosis mechanisms of ASIV on chronic kidney disease (CKD) in vivo and in vitro. A CKD model was induced in rats with adenine (200 mg/kg/d, i.g.), and an in vitro renal fibrosis model was induced in human kidney-2 (HK-2) cells treated with TGF-ß1. We revealed that ASIV significantly alleviated renal fibrosis by suppressing the expressions of epithelial-mesenchymal transition (EMT)-related proteins, including fibronectin, vimentin, and alpha-smooth muscle actin (α-SMA), and G2/M arrest-related proteins, including phosphorylated p53 (p-p53), p21, phosphorylated histone H3 (p-H3), and Ki67 in both of the in vivo and in vitro models. Transcriptomic analysis and subsequent validation showed that ASIV rescued ALDH2 expression and inhibited AKT/mTOR-mediated autophagy. Furthermore, in ALDH2-knockdown HK-2 cells, ASIV failed to inhibit AKT/mTOR-mediated autophagy and could not blunt EMT and G2/M arrest. In addition, we further demonstrated that rapamycin, an autophagy inducer, reversed the treatment of ASIV by promoting autophagy in TGF-ß1-treated HK-2 cells. A dual-luciferase report assay indicated that ASIV enhanced the transcriptional activity of the ALDH2 promoter. In addition, a further molecular docking analysis showed the potential interaction of ALDH2 and ASIV. Collectively, our data indicate that ALDH2-mediated autophagy may be a novel target in treating renal fibrosis in CKD models, and ASIV may be an effective targeted drug for ALDH2, which illuminate a new insight into the treatment of renal fibrosis and provide new evidence of pharmacology to elucidate the anti-fibrosis mechanism of ASIV in treating renal fibrosis.
Subject(s)
Renal Insufficiency, Chronic , Transforming Growth Factor beta1 , Rats , Humans , Animals , Transforming Growth Factor beta1/metabolism , Epithelial-Mesenchymal Transition , Proto-Oncogene Proteins c-akt/metabolism , Apoptosis , Molecular Docking Simulation , Tumor Suppressor Protein p53 , Cell Line, Tumor , G2 Phase Cell Cycle Checkpoints , Fibrosis , TOR Serine-Threonine Kinases/metabolism , Autophagy , Aldehyde Dehydrogenase, Mitochondrial/metabolismABSTRACT
Machine learning head models (MLHMs) are developed to estimate brain deformation for early detection of traumatic brain injury (TBI). However, the overfitting to simulated impacts and the lack of generalizability caused by distributional shift of different head impact datasets hinders the broad clinical applications of current MLHMs. We propose brain deformation estimators that integrates unsupervised domain adaptation with a deep neural network to predict whole-brain maximum principal strain (MPS) and MPS rate (MPSR). With 12,780 simulated head impacts, we performed unsupervised domain adaptation on on-field head impacts from 302 college football (CF) impacts and 457 mixed martial arts (MMA) impacts using domain regularized component analysis (DRCA) and cycle-GAN-based methods. The new model improved the MPS/MPSR estimation accuracy, with the DRCA method significantly outperforming other domain adaptation methods in prediction accuracy (p<0.001): MPS RMSE: 0.027 (CF) and 0.037 (MMA); MPSR RMSE: 7.159 (CF) and 13.022 (MMA). On another two hold-out testsets with 195 college football impacts and 260 boxing impacts, the DRCA model significantly outperformed the baseline model without domain adaptation in MPS and MPSR estimation accuracy (p<0.001). The DRCA domain adaptation reduces the MPS/MPSR estimation error to be well below TBI thresholds, enabling accurate brain deformation estimation to detect TBI in future clinical applications.
ABSTRACT
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.
ABSTRACT
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.
Subject(s)
Genome, Human , Microsatellite Repeats , Humans , Microsatellite Repeats/genetics , High-Throughput Nucleotide Sequencing/methods , Polymerase Chain ReactionABSTRACT
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.
Subject(s)
Non-alcoholic Fatty Liver Disease , Protein Serine-Threonine Kinases , Animals , Mice , AMP-Activated Protein Kinase Kinases , AMP-Activated Protein Kinases/metabolism , Diet, High-Fat , Inflammation/drug therapy , Inflammation/metabolism , Liver/metabolism , Mice, Inbred C57BL , Molecular Docking Simulation , Non-alcoholic Fatty Liver Disease/drug therapy , Non-alcoholic Fatty Liver Disease/etiology , Non-alcoholic Fatty Liver Disease/metabolism , Oxidative Stress , Protein Serine-Threonine Kinases/metabolismABSTRACT
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.