Modeling of polyethylene, poly(l-lactide), and CNT composites: a dissipative particle dynamics study

Dissipative particle dynamics (DPD), a mesoscopic simulation approach, is used to investigate the effect of volume fraction of polyethylene (PE) and poly(l-lactide) (PLLA) on the structural property of the immiscible PE/PLLA/carbon nanotube in a system. In this work, the interaction parameter in DPD simulation, related to the Flory-Huggins interaction parameter χ, is estimated by the calculation of mixing energy for each pair of components in molecular dynamics simulation. Volume fraction and mixing methods clearly affect the equilibrated structure. Even if the volume fraction is different, micro-structures are similar when the equilibrated structures are different. Unlike the blend system, where no relationship exists between the micro-structure and the equilibrated structure, in the di-block copolymer system, the micro-structure and equilibrated structure have specific relationships

Audio-Based Wildfire Detection on Embedded Systems

The occurrence of wildfires often results in significant fatalities. As wildfires are notorious for their high speed of spread, the ability to identify wildfire at its early stage is essential in quickly obtaining control of the fire and in reducing property loss and preventing loss of life. This work presents a machine learning wildfire detecting data pipeline that can be deployed on embedded systems in remote locations. The proposed data pipeline consists of three main steps: audio preprocessing, feature engineering, and classification. Experiments show that the proposed data pipeline is capable of detecting wildfire effectively with high precision and is capable of detecting wildfire sound over the forest’s background soundscape. When being deployed on a Raspberry Pi 4, the proposed data pipeline takes 66 milliseconds to process a 1 s sound clip. To the knowledge of the author, this is the first edge-computing implementation of an audio-based wildfire detection syste

MicroRNA-22 Can Reduce Parathymosin Expression in Transdifferentiated Hepatocytes

Pancreatic acinar cells AR42J-B13 can transdifferentiate into hepatocyte-like cells permissive for efficient hepatitis B virus (HBV) replication. Here, we profiled miRNAs differentially expressed in AR42J-B13 cells before and after transdifferentiation to hepatocytes, using chip-based microarray. Significant increase of miRNA expression, including miR-21, miR-22, and miR-122a, was confirmed by stem-loop real-time PCR and Northern blot analyses. In contrast, miR-93, miR-130b, and a number of other miRNAs, were significantly reduced after transdifferentiation. To investigate the potential significance of miR-22 in hepatocytes, we generated cell lines stably expressing miR-22. By 2D-DIGE, LC-MS/MS, and Western blot analyses, we identified several potential target genes of miR-22, including parathymosin. In transdifferentiated hepatocytes, miR-22 can inhibit both mRNA and protein expression of parathymosin, probably through a direct and an indirect mechanism. We tested two computer predicted miR-22 target sites at the 3′ UTR of parathymosin, by the 3′ UTR reporter gene assay. Treatment with anti-miR-22 resulted in significant elevation of the reporter activity. In addition, we observed an in vivo inverse correlation between miR-22 and parathymosin mRNA in their tissue distribution in a rat model. The phenomenon that miR-22 can reduce parathymosin protein was also observed in human hepatoma cell lines Huh7 and HepG2. So far, we detected no major effect on several transdifferentiation markers when AR42J-B13 cells were transfected with miR-22, or anti-miR-22, or a parathymosin expression vector, with or without dexamethasone treatment. Therefore, miR-22 appears to be neither necessary nor sufficient for transdifferentiation. We discussed the possibility that altered expression of some other microRNAs could induce cell cycle arrest leading to transdifferentiation

Audio-Based Wildfire Detection on Embedded Systems

The occurrence of wildfires often results in significant fatalities. As wildfires are notorious for their high speed of spread, the ability to identify wildfire at its early stage is essential in quickly obtaining control of the fire and in reducing property loss and preventing loss of life. This work presents a machine learning wildfire detecting data pipeline that can be deployed on embedded systems in remote locations. The proposed data pipeline consists of three main steps: audio preprocessing, feature engineering, and classification. Experiments show that the proposed data pipeline is capable of detecting wildfire effectively with high precision and is capable of detecting wildfire sound over the forest’s background soundscape. When being deployed on a Raspberry Pi 4, the proposed data pipeline takes 66 milliseconds to process a 1 s sound clip. To the knowledge of the author, this is the first edge-computing implementation of an audio-based wildfire detection system

Deep convolutional neural network for rib fracture recognition on chest radiographs

IntroductionRib fractures are a prevalent injury among trauma patients, and accurate and timely diagnosis is crucial to mitigate associated risks. Unfortunately, missed rib fractures are common, leading to heightened morbidity and mortality rates. While more sensitive imaging modalities exist, their practicality is limited due to cost and radiation exposure. Point of care ultrasound offers an alternative but has drawbacks in terms of procedural time and operator expertise. Therefore, this study aims to explore the potential of deep convolutional neural networks (DCNNs) in identifying rib fractures on chest radiographs.MethodsWe assembled a comprehensive retrospective dataset of chest radiographs with formal image reports documenting rib fractures from a single medical center over the last five years. The DCNN models were trained using 2000 region-of-interest (ROI) slices for each category, which included fractured ribs, non-fractured ribs, and background regions. To optimize training of the deep learning models (DLMs), the images were segmented into pixel dimensions of 128 × 128.ResultsThe trained DCNN models demonstrated remarkable validation accuracies. Specifically, AlexNet achieved 92.6%, GoogLeNet achieved 92.2%, EfficientNetb3 achieved 92.3%, DenseNet201 achieved 92.4%, and MobileNetV2 achieved 91.2%.DiscussionBy integrating DCNN models capable of rib fracture recognition into clinical decision support systems, the incidence of missed rib fracture diagnoses can be significantly reduced, resulting in tangible decreases in morbidity and mortality rates among trauma patients. This innovative approach holds the potential to revolutionize the diagnosis and treatment of chest trauma, ultimately leading to improved clinical outcomes for individuals affected by these injuries. The utilization of DCNNs in rib fracture detection on chest radiographs addresses the limitations of other imaging modalities, offering a promising and practical solution to improve patient care and management

Associations between blood glucose level and outcomes of adult in-hospital cardiac arrest: a retrospective cohort study

Additional file 3: Table S3. Features, interventions, and outcomes of cardiac arrest events stratified by the presence of measurement of blood glucose level after sustained return of spontaneous circulation

Cytochrome P450 Metabolism of Betel Quid-Derived Compounds: Implications for the Development of Prevention Strategies for Oral and Pharyngeal Cancers

Betel quid (BQ) products, with or without tobacco, have been classified by the International Agency for Research on Cancer (IARC) as group I human carcinogens that are associated with an elevated risk of oral potentially malignant disorders (OPMDs) and cancers of the oral cavity and pharynx. There are estimated 600 million BQ users worldwide. In Taiwan alone there are 2 million habitual users (approximately 10% of the population). Oral and pharyngeal cancers result from interactions between genes and environmental factors (BQ exposure). Cytochrome p450 (CYP) families are implicated in the metabolic activation of BQ- and areca nut-specific nitrosamines. In this review, we summarize the current knowledge base regarding CYP genetic variants and related oral disorders. In clinical applications, we focus on cancers of the oral cavity and pharynx and OPMDs associated with CYP gene polymorphisms, including CYP1A1, CYP2A6, CYP2E1, and CYP26B1. Our discussion of CYP polymorphisms provides insight into the importance of screening tests in OPMDs patients for the prevention of oral and pharyngeal cancers. Future studies will establish a strong foundation for the development of chemoprevention strategies, polymorphism-based clinical diagnostic tools (e.g., specific single-nucleotide polymorphism (SNP) “barcodes”), and effective treatments for BQ-related oral disorders

Patients Infected with CRF07_BC Have Significantly Lower Viral Loads than Patients with HIV-1 Subtype B: Mechanism and Impact on Disease Progression

The circulating recombinant form (CRF) 07_BC is the most prevalent HIV-1 strain among injection drug users (IDUs) in Taiwan. It contains a 7 amino-acid deletion in its p6gag. We conducted a cohort study to compare viral loads and CD4 cell count changes between patients infected with subtype B and CRF07_BC and to elucidate its mechanism. Twenty-one patients infected with CRF07_BC and 59 patients with subtype B were selected from a cohort of 667 HIV-1/AIDS patients whom have been followed up for 3 years. Generalized estimated equation was used to analyze their clinical data and the results showed that patients infected with CRF07_BC had significantly lower viral loads (about 58,000 copies per ml less) than patients with subtype B infection (p = 0.002). The replicative capacity of nine CRF07_BC and four subtype B isolates were compared and the results showed that the former had significantly lower replicative capacity than the latter although all of them were CCR5- tropic and non-syncytium inducing viruses. An HIV-1-NL4-3 mutant virus which contains a 7 amino-acid deletion in p6gag (designated as 7d virus) was generated and its live cycle was investigated. The results showed that 7d virus had significantly lower replication capacity, poorer protease-mediated processing and viral proteins production. Electron microscopic examination of cells infected with wild-type or 7d virus demonstrated that the 7d virus had poorer and slower viral maturation processes: more viruses attached to the cell membrane and higher proportion of immature virions outside the cells. The interaction between p6gag and Alix protein was less efficient in cells infected with 7d virus. In conclusion, patients infected with CRF07_BC had significantly lower viral loads than patients infected with subtype B and it may due to the deletion of 7 amino acids which overlaps with Alix protein-binding domain of the p6gag

Comparison of Immediate and 2-Year Outcomes between Excimer Laser-Assisted Angioplasty with Spot Stent and Primary Stenting in Intermediate to Long Femoropopliteal Disease

Background. To compare the clinical outcomes between excimer laser-assisted angioplasty (ELA) with spot stent (group A) and primary stenting (group B) in intermediate to long femoropopliteal disease. Methods. Outcomes of 105 patients totaling 119 legs treated with two different strategies were analyzed retrospectively in a prospectively maintained database. Results. Baseline characteristics were similar in both groups. Better angiographic results and lesser increase of serum C-reactive protein levels (0.60 ± 0.72 versus 2.98 ± 0.97 mg/dL, P<0.001) after the intervention were obtained in Group B. Group A had inferior 1-year outcomes due to higher rate of binary restenosis (67% versus 32%, P=0.001) and lower rate of primary patency (40% versus 58%, P=0.039). Rates of amputation-free survival, target vessel revascularization, assisted primary patency, and stent fracture at 24 months were similar in both groups (80% versus 82%, P=0.979, 65% versus 45%, P=0.11, 78% versus 80%, P=0.75 and 6.3% versus 6.8%, P=0.71, resp.). Conclusion. Greater vascular inflammation after ELA with spot stent resulted in earlier restenosis and inferior 1-year clinical outcomes than primary stenting. This benefit was lost in the primary stenting group at 2 years due to late catch-up restenosis. Active surveillance with prompt intervention was required to maintain the vessel patency