Assessment of DVJ and TJA in youth athletes was rater dependent. Players with subjectively assessed reduced or poor knee control had smaller normalized knee separation distance in DVJ.

Assessment of DVJ and TJA in youth athletes was rater dependent. Players with subjectively assessed reduced or poor knee control had smaller normalized knee separation distance in DVJ.Formaldehyde (FA), a simple reactive carbonyl molecule, is endogenously produced in the cell at various physiological condition. At elevated level, FA causes severe cell toxicity as well as damage in macromolecules such proteins and DNA. For detecting FA in living cell, we identify a small but effective fluorescent turn on probe comprising single benzene-based orothophenylenediamine compound. Further study reveals that carboxylic group in orothophenylenediamine plays the important role in enhancing fluorescent signal than another electron withdrawing group. It is even interesting to observe the occurrence of fluorescent enhancement in glutathione (GSH) environment which is generally abundant in every cell. Our probe enables to detect FA over other bio-analytes efficiently with limit of detection of 123 nM and 355-fold of enhancement in cellular mimicking conditions. Moreover, this probe could be useful in discriminating cell that has high concentration of FA as well as GSH.Long-term illumination of the retina with blue-light-excited phosphor-converted light-emitting diodes (LEDs) may result in decreased retinal function, even if the levels of blue light emitted are low. New low-color-temperature dual-primary-color LEDs have been developed that are composed of only two LED chips a red chip and a yellow chip. These LEDs are expected to become a new type of healthy lighting source because they do not emit blue light, they lack phosphor, and they solve the problem of low efficiency encountered with phosphor-converted low-color-temperature LEDs. Many studies have indicated that these new low-color-temperature LEDs are likely to have therapeutic effects. However, the biological safety of these LEDs needs to be explored before the therapeutic effects are explored. Therefore, this experiment was conducted to investigate the effects of the new low-color-temperature LEDs and fluorescent white LEDs on three types of retinal cells. We observed that the viability and numbers of retinal cells decreased gradually with increasing LED color temperature. The new low-color-temperature LEDs caused less death and adverse effects on proliferation than the fluorescent white LEDs. After irradiation with high-color-temperature LEDs, the expression of Zonula Occludens-1 (ZO-1) was decreased and discontinuous in ARPE-19 cells; the stress protein hemeoxygenase-1 (HO-1) was upregulated in R28 cells; and glial fibrillary acidic protein (GFAP) and vimentin were upregulated in rMC-1 cells. We therefore conclude that the new white LEDs cause almost no damage to retinal cells and reduce the potential human health risks of chronic exposure to fluorescent white LEDs.Medroxyprogesterone acetate (MPA) is a frequently used hormonal contraceptive that has been shown to significantly increase HIV-1 susceptibility by approximately 40 %. However, the underlying mechanism by which this occurs remains unknown. Here, we examined the biological response to MPA by vaginal epithelial cells, the first cells to encounter HIV-1 during sexual transmission, in order to understand the potential mechanism(s) of MPA-mediated increase of HIV-1 infection. Using microarray analysis and in vitro assays, we characterized the response of vaginal epithelial cells, grown in biologically relevant air-liquid interface (ALI) cultures, to physiological levels of female sex hormones, estradiol (E2), progesterone (P4), or MPA. Transcriptional profiling of E2, P4 or MPA-treated vaginal epithelial cells indicated unique transcriptional profiles associated with each hormone. MPA treatment increased transcripts of genes related to cholesterol/sterol synthesis and decreased transcripts related to cell division and cell-cell adhesion, results not seen with E2 or P4 treatments. MPA treatment also resulted in unique gene expression indicative of decreased barrier integrity. Functional assays confirmed that MPA, but not E2 or P4 treatments, resulted in increased epithelial barrier permeability and inhibited cell cycle progression. The effects of MPA on vaginal epithelial cells seen in this study may help explain the increase of HIV-1 infection in women who use MPA as a hormonal contraceptive.This study proposes a fully automated approach for the left atrial segmentation from routine cine long-axis cardiac magnetic resonance image sequences using deep convolutional neural networks and Bayesian filtering. The proposed approach consists of a classification network that automatically detects the type of long-axis sequence and three different convolutional neural network models followed by unscented Kalman filtering (UKF) that delineates the left atrium. Instead of training and predicting all long-axis sequence types together, the proposed approach first identifies the image sequence type as to 2, 3 and 4 chamber views, and then performs prediction based on neural nets trained for that particular sequence type. The datasets were acquired retrospectively and ground truth manual segmentation was provided by an expert radiologist. In addition to neural net based classification and segmentation, another neural net is trained and utilized to select image sequences for further processing using UKF to impose temporal consistency over cardiac cycle. A cyclic dynamic model with time-varying angular frequency is introduced in UKF to characterize the variations in cardiac motion during image scanning. The proposed approach was trained and evaluated separately with varying amount of training data with images acquired from 20, 40, 60 and 80 patients. Evaluations over 1515 images with equal number of images from each chamber group acquired from an additional 20 patients demonstrated that the proposed model outperformed state-of-the-art and yielded a mean Dice coefficient value of 94.1%, 93.7% and 90.1% for 2, 3 and 4-chamber sequences, respectively, when trained with datasets from 80 patients.The coronavirus disease, named COVID-19, has become the largest global public health crisis since it started in early 2020. CT imaging has been used as a complementary tool to assist early screening, especially for the rapid identification of COVID-19 cases from community acquired pneumonia (CAP) cases. The main challenge in early screening is how to model the confusing cases in the COVID-19 and CAP groups, with very similar clinical manifestations and imaging features. To tackle this challenge, we propose an Uncertainty Vertex-weighted Hypergraph Learning (UVHL) method to identify COVID-19 from CAP using CT images. In particular, multiple types of features (including regional features and radiomics features) are first extracted from CT image for each case. Then, the relationship among different cases is formulated by a hypergraph structure, with each case represented as a vertex in the hypergraph. The uncertainty of each vertex is further computed with an uncertainty score measurement and used as a weight in the hypergraph. Finally, a learning process of the vertex-weighted hypergraph is used to predict whether a new testing case belongs to COVID-19 or not. Experiments on a large multi-center pneumonia dataset, consisting of 2148 COVID-19 cases and 1182 CAP cases from five hospitals, are conducted to evaluate the prediction accuracy of the proposed method. Results demonstrate the effectiveness and robustness of our proposed method on the identification of COVID-19 in comparison to state-of-the-art methods.The efficient diagnosis of COVID-19 plays a key role in preventing the spread of this disease. The computer-aided diagnosis with deep learning methods can perform automatic detection of COVID-19 using CT scans. However, large scale annotation of CT scans is impossible because of limited time and heavy burden on the healthcare system. To meet the challenge, we propose a weakly-supervised deep active learning framework called COVID-AL to diagnose COVID-19 with CT scans and patient-level labels. The COVID-AL consists of the lung region segmentation with a 2D U-Net and the diagnosis of COVID-19 with a novel hybrid active learning strategy, which simultaneously considers sample diversity and predicted loss. With a tailor-designed 3D residual network, the proposed COVID-AL can diagnose COVID-19 efficiently and it is validated on a large CT scan dataset collected from the CC-CCII. The experimental results demonstrate that the proposed COVID-AL outperforms the state-of-the-art active learning approaches in the diagnosis of COVID-19. With only 30% of the labeled data, the COVID-AL achieves over 95% accuracy of the deep learning method using the whole dataset. The qualitative and quantitative analysis proves the effectiveness and efficiency of the proposed COVID-AL framework.Accurately counting the number of cells in microscopy images is required in many medical diagnosis and biological studies. This task is tedious, time-consuming, and prone to subjective errors. However, designing automatic counting methods remains challenging due to low image contrast, complex background, large variance in cell shapes and counts, and significant cell occlusions in two-dimensional microscopy images. In this study, we proposed a new density regression-based method for automatically counting cells in microscopy images. The proposed method processes two innovations compared to other state-of-the-art density regression-based methods. First, the density regression model (DRM) is designed as a concatenated fully convolutional regression network (C-FCRN) to employ multi-scale image features for the estimation of cell density maps from given images. Second, auxiliary convolutional neural networks (AuxCNNs) are employed to assist in the training of intermediate layers of the designed C-FCRN to improve the DRM performance on unseen datasets. Experimental studies evaluated on four datasets demonstrate the superior performance of the proposed method.Temporal correlation in dynamic magnetic resonance imaging (MRI), such as cardiac MRI, is informative and important to understand motion mechanisms of body regions. Modeling such information into the MRI reconstruction process produces temporally coherent image sequence and reduces imaging artifacts and blurring. However, existing deep learning based approaches neglect motion information during the reconstruction procedure, while traditional motion-guided methods are hindered by heuristic parameter tuning and long inference time. We propose a novel dynamic MRI reconstruction approach called MODRN and an end-to-end improved version called MODRN(e2e), both of which enhance the reconstruction quality by infusing motion information into the modeling process with deep neural networks. The central idea is to decompose the motion-guided optimization problem of dynamic MRI reconstruction into three components Dynamic Reconstruction Network, Motion Estimation and Motion Compensation. Extensive experiments have demonstrated the effectiveness of our proposed approach compared to other state-of-the-art approaches.Hepatocellular carcinoma (HCC), as the most common type of primary malignant liver cancer, has become a leading cause of cancer deaths in recent years. Accurate segmentation of HCC lesions is critical for tumor load assessment, surgery planning, and postoperative examination. As the appearance of HCC lesions varies greatly across patients, traditional manual segmentation is a very tedious and time-consuming process, the accuracy of which is also difficult to ensure. Therefore, a fully automated and reliable HCC segmentation system is in high demand. In this work, we present a novel hybrid neural network based on multi-task learning and ensemble learning techniques for accurate HCC segmentation of hematoxylin and eosin (H&E)-stained whole slide images (WSIs). First, three task-specific branches are integrated to enlarge the feature space, based on which the network is able to learn more general features and thus reduce the risk of overfitting. Second, an ensemble learning scheme is leveraged to perform feature aggregation, in which selective kernel modules (SKMs) and spatial and channel-wise squeeze-and-excitation modules (scSEMs) are adopted for capturing the features from different spaces and scales. Our proposed method achieves state-of-the-art performance on three publicly available datasets, with segmentation accuracies of 0.797, 0.923, and 0.765 in the PAIP, CRAG, and UHCMC&CWRU datasets, respectively, which demonstrates its effectiveness in addressing the HCC segmentation problem. To the best of our knowledge, this is also the first work on the pixel-wise HCC segmentation of H&E-stained WSIs.8-oxo-7,8-dihydro-2′-deoxyguanosine (8-oxodG), a major product of DNA oxidation, is a pre-mutagenic lesion which is prone to mispair, if left unrepaired, with 2′-deoxyadenosine during DNA replication. While unrepaired or incompletely repaired 8-oxodG has classically been associated with genome instability and cancer, it has recently been reported to have a role in the epigenetic regulation of gene expression. Despite the growing collection of genome-wide 8-oxodG mapping studies that have been used to provide new insight on the functional nature of 8-oxodG within the genome, a comprehensive view that brings together the epigenetic and the mutagenic nature of the 8-oxodG is still lacking. To help address this gap, this review aims to provide (i) a description of the state-of-the-art knowledge on both the mutagenic and epigenetic roles of 8-oxodG; (ii) putative molecular models through which the 8-oxodG can cause genome instability; (iii) a possible molecular model on how 8-oxodG, acting as an epigenetic signal, could cause the translocations and deletions which are associated with cancer.Homologous recombination (HR), considered the highest fidelity DNA double-strand break (DSB) repair pathway that a cell possesses, is capable of repairing multiple DSBs without altering genetic information. However, in „last resort” scenarios, HR can be directed to low fidelity subpathways which often use non-allelic donor templates. Such repair mechanisms are often highly mutagenic and can also yield chromosomal rearrangements and/or deletions. While the choice between HR and its less precise counterpart, non-homologous end joining (NHEJ), has received much attention, less is known about how cells manage and prioritize HR subpathways. In this review, we describe work focused on how chromatin and nuclear architecture orchestrate subpathway choice and repair template usage to maintain genome integrity without sacrificing cell survival. Understanding the relationships between nuclear architecture and recombination mechanics will be critical to understand these cellular repair decisions.The purpose of this study was to examine how camera resolution and suspect-camera distance affect the accuracy and precision of suspect height estimations using PhotoModeler software. Sixteen individuals were measured and recorded standing at 15 pre-set distances on 7 security cameras, each with a different resolution setting. A height scale was used to measure each individual’s height prior to recording and was also used as a reference height. Height estimates were taken in PhotoModeler by extracting video frames that were calibrated using 3D point model data obtained from a laser scan of the test site. Errors were calculated for the measurements and compared using the Kruskal-Wallis H-test, which indicated significant differences for errors among different resolutions and distances (p less then 0.01). Interaction plots, however, demonstrated little difference in errors for most resolutions and positions. The accuracy and precision of height estimates began to decrease with resolutions under 960H and distances over 36.5 m.Three-dimensional facial images are becoming more and more widespread. As such images provide more information about facial morphology than 2D imagery, they show great promise for use in future forensic applications, including age estimation and verification. This paper proposes an approach using random forests, a machine learning method, to develop and test models for classification of legal age thresholds (15 years and 18 years) using 3D facial landmarks. Our approach was developed on a set of 3D facial scans from 394 Czech individuals (194 males and 200 females) aged between 10 and 25 years. The dataset was retrieved from a sizable database of Central European faces – The FIDENTIS 3D Face Database. Three main types of input variables were processed using random forests I) shape (size-invariant) coordinates of 3D landmarks, II) size and shape coordinates of 3D landmarks, and III) inter-landmark distances, angles and indices. The performance rates for the combinations of variables and age threshold were expressed in terms of sensitivity and specificity. The overall accuracy rates varied from 71.4%-91.5% (when the male and female samples were pooled). In general, higher accuracy was achieved for the age limit of 18 years than for 15 years. Whereas size-variant variables showed a better performance rate for the age limit of 15 years, the size-invariant variables (i.e., shape variables) were better for classifying individuals under 18 years. The verification models grounded on traditional variables (distances, angles, indices) yielded consistently higher performance rates on females than on males, whereas the inverse trend was observed for the models built on 3D coordinates. The results indicate that age verification based on 3D facial data with processing by the random forests method has high potential for further forensic or biometric applications.

Neuronal excitotoxicity induces a plethora of downstream signaling pathways, resulting in the calcium overload-induced excitotoxic cell death, a well-known phenomenon in cerebrovascular and neurodegenerative disorders. The naturally occurring phytosterol, stigmasterol (ST) is known for its potential role in cholesterol homeostasis and neuronal development. However, the ability of ST to protect against the induced excitotoxicity in hippocampal neurons has not been investigated yet.

The present study aimed to investigate whether ST could protect against hypoxia/reoxygenation (H/R)-induced excitotoxicity in hippocampal neurons.

After H/R, neurons were initially subjected to trypan blue exclusion assay for the assessment of cell viability. Live staining using fluorescence dyes namely JC-1 (5,5′,6,6′-tetrachloro-1,1′,3,3′-tetraethylbenzimidazolyl-carbocyanine iodide), DCFDA (2′,7′-dichlorofluorescein diacetate) and FM1-43 (N-(3-triethylammoniumpropyl)-4-(4-(dibutylamino)styryl) were used to measure MMP, ROS ed that ST interacted with the ligand binding domain of liver X receptor β (LXRβ), a known binding receptor of ST, through multiple hydrogen bonding.

Collectively, these findings revealed that ST exhibited a promising neuroprotective effect by regulating both pre- and post-synaptic events following H/R, particularly, attenuation of GluN2B-mediated excitotoxicity and oxidative stress, and induction of mitophagy, and suggested that ST might be a therapeutic promise against ischemic stroke and its associated neurological disorders.

Collectively, these findings revealed that ST exhibited a promising neuroprotective effect by regulating both pre- and post-synaptic events following H/R, particularly, attenuation of GluN2B-mediated excitotoxicity and oxidative stress, and induction of mitophagy, and suggested that ST might be a therapeutic promise against ischemic stroke and its associated neurological disorders.

Homocysteine (Hcy) induced vascular endothelial dysfunction is known to be closely associated with oxidative stress and impaired NO system. 1,8-Dihydroxy-3-methoxy-6-methylanthracene-9,10-dione (physcion) has been known to has antioxidative and anti-inflammatory properties.

The purpose of the present study was to define the protective effect of physcion on Hcy-induced endothelial dysfunction and its mechanisms involved.

Hyperhomocysteinemia (HHcy) rat model was induced by feeding 3% methionine. A rat thoracic aortic ring model was used to investigate the effects of physcion on Hcy-induced impairment of endothelium-dependent relaxation. Two doses, low (L, 30 mg/kg/day) and high (H, 50 mg/kg/day) of physcion were used in the present study. To construct Hcy-injured human umbilical vein endothelial cells (HUVECs) model, the cells treated with 3 mM Hcy. The effects of physcion on Hcy-induced HUVECs cytotoxicity and apoptosis were studied using MTT and flow cytometry. Confocal analysis was used to determine t candidate agent for the prevention of cardiovascular disease induced by Hcy.

The PACIFIC trial demonstrated that durvalumab significantly improved progression-free and overall survival (PFS/OS), versus placebo, in patients with Stage III NSCLC and stable or responding disease following concurrent, platinum-based chemoradiotherapy (CRT). A range of CT and RT regimens were permitted, and used, in the trial. We report post-hoc, exploratory analyses of clinical outcomes from PACIFIC according to CRT-related variables.

Patients were randomized 21 (1-42 days post-CRT) to up to 12 months durvalumab (10 mg/kg intravenously every 2 weeks) or placebo. Efficacy and safety were analyzed in patient subgroups defined by the following baseline variables platinum-based CT (cisplatin/carboplatin); vinorelbine, etoposide, or taxane-based CT (all yes/no); total RT dose (<60 Gy/60-66 Gy/>66 Gy); time from last RT dose to randomization (<14 days/≥14 days); and use of pre-CRT induction CT (yes/no). Treatment effects for time-to-event endpoints were estimated by hazard ratios (HRs) from unstrate factors in each subgroup preclude robust conclusions.

Durvalumab prolonged PFS and OS irrespective of treatment variables related to prior CRT to which patients with Stage III NSCLC had previously stabilized or responded. Limited patient numbers and imbalances in baseline factors in each subgroup preclude robust conclusions.

To characterize the benefit-risk profile of pemetrexed and platinum in combination with pembrolizumab in patients with non-squamous non-small cell lung cancer in the KEYNOTE-189 study, with reference to historical pemetrexed maintenance data from the PARAMOUNT, PRONOUNCE, and JVBL randomized studies.

To harmonize the treatment setting across the studies in our comparative analysis, we selected patients from KEYNOTE-189 who received ≥5 cycles of pemetrexed (pembrolizumab/pemetrexed/platinum, N = 310; placebo/pemetrexed/platinum, N = 135) and pooled data from PARAMOUNT (N = 359), PRONOUNCE (N = 98), and JVBL (N = 29) who received ≥5 cycles of pemetrexed (total, N = 486). For the 2 selected populations from KEYNOTE-189 and the pooled historical data, progression-free survival (PFS) was evaluated by Kaplan-Meier estimator and Cox proportional hazards model. Tumor response and grade ≥3 treatment-emergent adverse events (TEAEs) for the aforementioned population were summarized by descriptive statistics.

In thxed maintenance data.

Improved PFS was shown with pembrolizumab/pemetrexed/platinum compared with placebo/pemetrexed/platinum in the patient group with pemetrexed maintenance (≥5 cycles) in KEYNOTE-189. The PFS and safety profile of the control arm in KEYNOTE-189 were comparable with historical pemetrexed maintenance data.Photon-induced nuclear excitation (i.e. photo-excitation) can be used for production of nuclear isomers, which have potential applications in astrophysics, energy storage, medical diagnosis and treatment. This paper presents a feasibility study on photo-excitation production of four nuclear isomers (103mRh, 113m,115mIn and 176mLu) with intense γ-ray source based on laser-electron Compton scattering (LCS). The decay properties of these isomers and their potential applications in medical diagnosis and treatment were reviewed. The cross-section curve, simulated yield and activity of product of each photo-excitation process were calculated. The cutoff energy of LCS γ-ray beam was optimized by adjusting electron beam energy in order to maximize the isomer activity. It is found that the specific activity of the above-mentioned isomers can exceed ~0.2 GBq/g for 6-h target irradiation at an intensity of 1013 γ/s. Our simulation results suggest the prospect of producing medically interesting radionuclides with photo-excitation using the state-of-art LCS γ-ray beam facility.Enhancing the positional information acquisition during Mars entry blackout improves the Mars landing mission reliability. A positioning method based on the high-penetration of X-rays was developed to solve the problem. The X-ray signal attenuation was estimated. The positioning performance and the influence of X-ray signal transmission system were also evaluated. Results indicated that the X-ray signal attenuation is extremely low, and the X-ray-based method is expected to be a potential application for obtaining high-precision positional information during Mars entry blackout.Automated production of [18F]MK-6240 was implemented for the first time in the CFN-MPS200 module. Three consecutive productions of [18F]MK-6240 complied with the product specifications. Formulated [18F]MK-6240 maintained stability, as measured by radio-high-performance liquid chromatography (HPLC), as well as clarity and pH, over a period of 8 h. Our established method can facilitate multi-center trials and widespread use of [18F]MK-6240.N-(2-18F-fluoropropionyl)-l-glutamate (18F-FPGLU), a new N-substituted 18F-labeling l-glutamate, is a potential amino acid tracer for oncology PET imaging with good tumor-to-background contrast in several tumor-bearing mice. Herein, we evaluated the potential value of 18F-FPGLU for PET imaging of glioma in orthotopic glioma-bearing SD rats. A series of competitive inhibition experiments with various types of inhibitors were conducted with C6 cells to investigate the transport mechanism of 18F-FPGLU in glioma. Establishment of orthotopic rat C6 glioma-bearing SD rats models was confirmed by MRI. Then PET imaging of 18F-FPGLU was performed on the orthotopic C6 glioma-bearing SD rats and compared with that of 18F-FDG. After the rats sacrificed, the whole brain was collected and immunofluorescence staining of glial fibrillary acidic protein (GFAP) and matrix metalloproteinase 2 (MMP2) were processed. Na+-dependent system XAG- and Na+-independent system XC- are the mainly transporters of 18F-FPGLU in C6 cells. N-methyl-d-aspartate (NMDA) receptor, which is associated with the invasiveness and proliferation of glioma cells, is also involved in the uptake of 18F-FPGLU. High uptake and retention of 18F-FPGLU was observerd in orthotopic glioma with good visualization and the tumor/background ratio reached 2.35 at 60 min post-injection, which was significantly higher than that of 18F-FDG (1.72) in small-animal PET images. High expression of MMP-2 and GFAP was observed in the immunofluorescence staining of glioma xerography slices. 18F-FPGLU seems to be a better potential PET tracer than 18F-FDG for brain glioma imaging with good visualization and ability to assess the tumor activity.

Structure and self-assembly of surfactants in the solution shows a fundamental influence on its viscosity. Through molecular simulations using Martini force field, synergistic effects in aggregation as well as the viscosity changes of a binary ionic surfactant system can be modelled. Simulations Coarse-grained molecular dynamics simulations are performed to model the SDS/CAPB binary surfactant solution, and both equilibrium and non-equilibrium methods are used to calculate the viscosity of the equilibrated micellar systems.

Our simulation results indicate that the new version of the Martini force field can provide more reasonable self-assembly of surfactant, both single and binary system. Synergistic effects in micelle formation for SDS/CAPB have been successfully reproduced, that is, the formation of cylindrical micelles or even wormlike micelles at a lower concentration when compared with the pure system. Meanwhile, both equilibrium and non-equilibrium methods provide quantitatively comparable viscosityresponding with the formation of rodlike or wormlike micelles, and a full parameter optimization of force field is still necessary.

Organic radical polymers with tailored pendant functionalities have emerged as exciting and promising materials for their application versatility. Moreover, eco-friendly polymer-based organic nanomaterials with redox-active pendant side groups can replace the harmful heavy metal-based inorganic materials. On the other hand, self-assembled nanomaterials are of great interest and attracted more attention recently for their promising application in different advanced fields, but it is yet challenging to predict suitable hydrophilic-lipophilic balance (HLB) for stimuli-responsive random copolymers assembly due to structural irregularity. Among several experimental techniques, electron paramagnetic resonance (EPR) spectroscopy plays a unique and promising role in revealing structural and dynamic information of nanostructured radical containing materials.

In this study, a series of spin labeled amphiphilic random copolymers poly(methyl methacrylate-co-acrylic acid) have been synthesized and characterized by FT-sfer process of the nanoparticles in solution was diffusion regulated and depended on the accessibility of radicals. The radical (spin labeled) polymers offer a broad way to develop stimuli-responsive materials in various colloidal nanostructures by changing the microenvironment, appreciating their potential advanced applications in electronic devices, catalysis, stimuli-triggered drug/gene delivery and reactive oxygen species (ROS) scavenger.

Protein nanoparticles have attracted increased interest due to their broad applications ranging from drug delivery and vaccines to biocatalysts and biosensors. The morphology and the size of the nanoparticles play a crucial role in determining their suitability for different applications. Yet, effectively controlling the size of the nanoparticles is still a significant challenge in their manufacture. The hypothesis of this paper is that the assembly conditions and size of protein particles can be tuned via a mechanical route by simply modifying the mixing time and strength, while keeping the chemical parameters constant.

We use an acoustically actuated, high throughput, ultrafast, microfluidic mixer for the assembly of protein particles with tuneable sizes. The performance of the acoustic micro-mixer is characterized via Laser Doppler Vibrometry and image processing. The assembly of protein nanoparticles is monitored by dynamic light scattering (DLS) and transmission electron microscopy (TEM).

By changihe acoustic microfluidic mixer approach produces smaller particles with a more uniform size distribution, promising a new way to manufacture protein particles with controllable quality.The CoN which with excellent performance was introduced into Mn0.2Cd0.8S through simple electrostatic self-assembly for the first time, then the composite photocatalyst with low cost and high catalytic activity was prepared. The introduction of CoN improves the absorption intensity of catalyst to visible light. CoN accepts photo-induced electrons from Mn0.2Cd0.8S as an excellent electron acceptor in the form of active sites due to its suitable conduction band position and good conductivity. The surface interaction of composite photocatalyst formed by electrostatic self-assembly is strong, which is conducive to the directional transfer of photogenic carriers from Mn0.2Cd0.8S to CoN, greatly inhibits the recombination of photogenic carriers and improves the separation and the transfer rate of photogenic carriers. The introduction of CoN greatly improved the hydrogen production rate of photocatalyst up to 14.612 mmol g-1 h-1, it was 17.3 times that of pure MCS. This work provides inspiration for transition metal nitrides as cocatalysts in the sphere of photocatalytic splitting of water for hydrogen production.

Reverse Janus emulsion, with droplets composed by „two rooms” of water phases, is a novel multiple emulsion attributed to excellent integration capability and biocompatibility. However, significant instability compared with normal Janus emulsions renders the stability issue of great importance. Moreover, the ultra-low aqueous-aqueous inner interfacial tension, the anisotropic nature of the droplets with distinct lobe composition, and the random orientation in the continuous phase endow the complicated and various demulsification mechanisms.

Reverse Janus emulsion of (W

+W

)/O, employing typical salt-alcohol aqueous two-phase system (ATPS) as inner phases, is prepared in batch scale by conventional one-step vortex mixing. The demulsification process is detected by multiple light scattering technique, which provides real-time, in-situ, and quantitative information of emulsion evolution. Moreover, the fusion pattern of the anisotropic droplets is illustrated by the combination with light microscopy and sizfindings are instructive in the stability of aqueous based multiple emulsions with advanced morphologies and meanwhile, promote the future application of this novel emulsion in food science, pharmacy, and biomimetic compartmentalization.The transboundary River Ganga serves as a conduit for meltwater from the Himalayas and is a major freshwater source for two thirds of Indian population before emptying into the Sundarban Delta, the largest estuary in the Bay of Bengal. Endocrine disrupting compounds (EDCs) such as phthalic acid esters (PAEs) and bisphenol A (BPA) used as organic plastic additives can pollute the aquatic environment receiving plastic litter. Hence, we have investigated these EDCs in water samples from Ganga and Sundarban wetland of India. Since these compounds exhibit estrogenic potential, we have further measured steroids and evaluated the estrogenic activity (estradiol equivalents, BioE2Eqs) using an in-vitro bioassay (E-Screen). Further BioE2Eqs were compared with the sum of predicted estradiol equivalents based on the chemical concentrations of PAEs and BPA by E-Screen (ChemE2Eq) and YES factors (ChemYES). Caffeine was measured as a marker for anthropogenic wastewater discharge. Results showed that the highest BioE2Eq (belChlorine dioxide (ClO2) has emerged as a promising alternative to free chlorine for water disinfection and/or pre-oxidation due to its reduced yields of chlorinated disinfection byproducts. ClO2 decomposes to form chlorite (ClO2-), which influences the following advanced oxidation processes (AOPs) for micropollutant abatement in drinking water. This study aims at investigating the effects of ClO2- on the concentrations of reactive species (e.g., radicals and ozone) and on the formation of chlorate in the UV/chlorine AOP. Results showed that the concentration of ClO · in the UV/chlorine process remarkably decreased by 98.20-100.00% in the presence of ClO2- at concentration of 0.1-1.0 mg·L-1 as NaClO2. The concentrations of HO · and ozone decreased by 42.71-65.42% and by 22.02-64.31%, respectively, while the concentration of Cl · was less affected (i.e., 31.00-36.21% reduction). The overall concentrations of the reactive species were differentially impacted by ClO2-’s multiple roles in the process. UV photolysis of ClO2- generated HO · but not Cl · , ClO · or ozone under the drinking water relevant conditions. ClO2- also competed with chlorine for UV photons but this effect was minor ( less then 1.0%). The radicals/ozone scavenging by ClO2- outcompeted the above two to lead to the overall decreasing concentrations of the reactive species, in consistency with the kinetic model predicted trends. ClO2- reacted with radicals and ozone to form chlorate (ClO3-) but not perchlorate (ClO4-). HO · played a dominant role in ClO3- formation. The findings improved the fundamental understanding on micropollutant abatement and inorganic byproduct formation by the UV/chlorine process and other AOPs in ClO2–containing water.Effect of ferrate [Fe(VI)] pre-oxidation on improving FeCl3/ultrafiltration (UF) of algae-laden source water was investigated. Fe(VI) disrupted algae cells and the in situ formed ferric (hydr)oxides aggregated with cell debris. Particle size and zeta potential of algae increased by 20% and 55% on average, respectively, after treatment with 0.02 mM of Fe(VI). These variations facilitated the formation of algae-ferric floc. Fe(VI) degraded algal extracellular organic matter into lower molecular weight products (fulvic-like and humic-like substances). Membrane flux, reversible membrane resistance (Rr) and irreversible membrane resistance (Rir) were improved by 51%, 61%, and 52% in Fe(VI) (0.02 mM)/FeCl3/UF treatment group compared with FeCl3/UF treatment after three filtration cycles. Fe(VI)/FeCl3/UF removed more than 10% ~ 34% of the dissolved organic compounds (DOC) and 6% ~ 17% of the total nitrogen (TN) compared with FeCl3/UF. Due to the enhanced removal of DOC and TN, formation potential of 12 kinds of carbonaceous-disinfection byproducts (C-DBPs) and 7 kinds of nitrogenous-disinfection byproducts (N-DBPs) decreased by 32.5% and 22.5%, respectively. Fe(VI) pre-oxidant was effective for alleviating membrane fouling and reducing formation potential of DBPs in algal laden water treatment.Iodinated disinfection by-products (I-DBPs) have recently emerged as part of the pool of DBPs of public health concern. Due to limitations in measuring individual I-DBPs in a water sample, the surrogate measure of total organic iodine (TOI) is often used to account for the sum of all I-DBPs. In this study, TOI and total iodine (TI) are quantified in raw and treated waters in treatment trains at three sites in the Northeast United States. The occurrence, magnitude, and seasonality of these species was investigated within each sampling train and across the different sites. A regression model was developed to explore how TOI occurrence varies with routinely measured physical and chemical parameters in a water sample. The TOI and TI concentration at the three sites ranged from below the method detection limit to 18 µg/L and from 3 and 18.9 µg/L, respectively. There was substantial inter-monthly variability in TOI without a clear seasonal signal, and the concentration of TOI did not increase upon treatment. The results of the multivariate regression model showed that dissolved organic carbon (DOC), specific UV254 absorbance (SUVA), combined chlorine residual (TCl2), and pH were all significantly related to TOI concentration to varying degrees. A Tobit model was fit to show TOI predictions against observed (measured) TOI values. The model could explain approximately 46% of the variance of TOI concentrations in the treated waters.To evaluate the green photocatalytic disinfection for practical applications, disinfection of different types of real sewage using magnetic photocatalyst RGO/Fe,N-TiO2/Fe3O4@SiO2 (RGOFeNTFS) under simulated solar light was investigated low-salinity sewage after tertiary treatment, low-salinity sewage after secondary biological treatment, high-salinity sewage after secondary biological treatment, and high-salinity sewage after chemically enhanced primary treatment. The classification of the sewage as high and low-salinity is based on the regions of sewage source that use seawater and freshwater for toilet flushing, respectively. It shows potential of solar-light-driven photocatalytic disinfection in low-salinity sewage around 20 min (for sewage after tertiary treatment) and 45 min (for sewage after secondary treatment) of photocatalytic disinfection are required for sewage to meet the discharge standard, and no bacterial regrowth is observed in the treated sewage after 48 h. However, due to the poorer water quality, the high-salinity sewage requires a relatively long reaction time (more than 240 min) to meet the discharge standard, showing minimal practical significance. Further, the complex characteristics of real sewage, such as organic matter, suspended matter, multivalent-ions, pH and DO level significantly influence photocatalytic disinfection, and should be carefully reviewed in evaluating the photocatalytic disinfection of sewage. Besides, RGOFeNTFS shows a good reusability over three cycles for photocatalytic disinfection of low-salinity sewage samples. Moreover, the non-toxicity, indicated by phytoplankton in seawater, of both RGOFeNTFS ( less then = 3 g/L) and treated low-salinity sewage demonstrates the feasibility of the practical application of photocatalytic disinfection using RGOFeNTFS under irradiation of solar light.Conventional wastewater treatment plants are not designed to treat micropollutants; thus, for 20 years, several complementary treatment systems, such as surface flow wetlands have been used to address this issue. Previous studies demonstrate that higher residence time and low global velocities promote nutrient removal rates or micropollutant photodegradation. Nevertheless, these studies were restricted to the system limits (inlet/outlet). Therefore, detailed knowledge of water flow is crucial for identifying areas that promote degradation and optimise surface flow wetlands. The present study combines 3D water flow numerical modelling and liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS/MS). Using this numerical model, validated by tracer experimental data, several velocity areas were distinguished in the wetland. Four areas were selected to investigate the waterflow influence and led to the following results on the one hand, the number and concentration of micropollutants are independent of the waterflow, which could be due to several assumptions, such as the chronic exposure associated with a low Reynolds number; on the other hand, the potential degradation products (metabolites) were also assessed in the sludge to investigate the micropollutant biodegradation processes occurring in the wetland; micropollutant metabolites or degradation products were detected in higher proportions (both number and concentration) in lower flow rate areas. The relation to higher levels of plant and microorganism metabolites suggests higher biological activity that promotes degradation.Chlorination can lead to the formation of hazardous chlorinated disinfection byproducts (Cl-DBPs). We identified tyrosine (Tyr) and tryptophan (Trp) as precursors of toxic Cl-DBPs and developed a halogen extraction code to complement ultra performance liquid chromatography in tandem with high resolution mass spectrometry (UPLC-HRMS) in detecting and identifying Cl-DBPs. We detected 20 and 11 Cl-DBPs formed from chlorination of Tyr and Trp, respectively, and identified the structures of 15 Cl-DBPs. Fourteen structures were previously unreported. We also proposed the tentative formation pathways of these newly identified Cl-DBPs. Their incidence in real water sources demonstrated that these Cl-DBPs are likely to form during chlorination of reclaimed water. We computationally predicted the toxicity of these Cl-DBPs, which was relatively high, indicating that these Cl-DBPs could be hazardous and were of valid concern. Combining analytical data with the halogen extraction code can identify Cl-DBPs accurately from complex compounds. This analytical method can be used to identify Cl-DBPs of water treatment procedures in further studies.Life-saving interventions utilize endotracheal intubation to secure a patient’s airway, but performance of the clinical standard of care endotracheal tube (ETT) is inadequate. For instance, in the current COVID-19 crisis, patients can expect prolonged intubation. This protracted intubation may produce health complications such as tracheal stenosis, pneumonia, and necrosis of tracheal tissue, as current ETTs are not designed for extended use. In this work, we propose an improved ETT design that seeks to overcome these limitations by utilizing unique geometries which enable a novel expanding cylinder. The mechanism provides a better distribution of the contact forces between the ETT and the trachea, which should enhance patient tolerability. Results show that at full expansion, our new ETT exerts pressures in a silicone tracheal phantom well within the recommended standard of care. Also, preliminary manikin tests demonstrated that the new ETT can deliver similar performance in terms of air pressure and air volume when compared with the current gold standard ETT. The potential benefits of this new architected ETT are threefold, by limiting exposure of healthcare providers to patient pathogens through streamlining the intubation process, reducing downstream complications, and eliminating the need of multiple size ETT as one architected ETT fits all.Asthma is highly comorbid with anxiety in youth. We investigated the hypothalamic-pituitary-adrenal (HPA) axis and microglia as mechanisms underlying asthma and anxiety comorbidity. We induced asthma symptoms in developing BALB/cJ mice with house dust mite (HDM) for airway inflammation and methacholine (MCH) for bronchoconstriction. On the last day of exposure, we analyzed samples at six timepoints. Lung IL-5 and IL-1β expression peaked 4 h after final HDM exposure. Circulating corticosterone was blunted in a sex- and treatment-specific temporal pattern. Hippocampal IL-1β expression and microglial area were marginally increased 24 h after MCH exposure. These results provide a foundation for further work investigating asthma-anxiety mechanisms.Driver sleepiness is a major contributor to road crashes. A system that monitors and warns the driver at a certain, critical level of arousal, could aid in reducing sleep-related crashes. To determine how driver sleepiness detection systems perform, a systematic review of the sensitivity and specificity outcomes was performed. In total, 21 studies were located that met inclusion criteria for the review. The range of sensitivity outcomes was between 39.0-98.8 % and between 73.0-98.9 % for specificity outcomes. There was considerable variation in the outcomes of the studies employing only one physiological measure (mono-signal approach), whereas, a poly-signal approach with multiple physiological signals resulted in more consistency with higher outcomes on both sensitivity and specificity metrics. Only six of the 21 studies had both sensitivity and specificity outcomes above 90.0 %, which included mono- and poly-signal approaches. Moreover, increases in the number of features used in the sleepiness detection system did not result in higher sensitivity and specificity outcomes. Overall, there was considerable variability between the studies reviewed, including measures of ground truth, the features employed and the machine learning approach of the systems. A critical need for progressing any system is a revalidation of the system on a new sample of users. These aspects indicate considerable progress is needed with physiological-based driver sleepiness systems before they are at a sufficient standard to be deployed on-road.Road safety remains a challenge with numerous Vulnerable Road Users (VRUs) suffering from injuries and death every year. Pedestrian protection using active safety systems, such as Automated Emergency Braking (AEB), is an effective measure to combat the situation. Furthermore, the perception of precrash scenarios plays an important role in active safety research. It is essential to understand and define precrash scenarios. This study aimed to apply the obtained typical car-to-pedestrian precrash scenarios from Chinese severely injured pedestrian traffic accidents to develop and test active safety systems. The National Automobile Accident In-Depth Investigation System (NAIS) recorded 467 cases from 2011 to 2018 in China, and 12 items were selected from the NAIS database as description variables for the precrash scenario. The items were divided into four categories car, pedestrian, road, and environment. Group decision theory was applied to evaluate the importance of each variable in its category. A total of 34 enarios of pedestrian AEB or Forward Collision Warning (FCW) in China.

The aim of this study is to evaluate the effectiveness of a seat-integrated mobilization system for maintaining vigilance under monotonous driving situations.

For this purpose, vigilance indicators were compared intra-individually in a test condition with mobilization (seat-integrated stimulation) and a placebo condition under standardized conditions in a real driving study (N = 31). During a monotonous two-hour ride, physiological (brain activity by the EEG alpha spindle rate), performance-based (reaction times) and subjective indicators were recorded.

The necessary precondition for the paradigm of inducing fatigue through monotony was confirmed by a significant increase in the EEG alpha spindle rate and the subjective vigilance indices. The mobilization system had a significant impact on the most fatigue-sensitive parameter of the alpha spindle rate, whereas the other parameters of vigilance did not reflect a significant effect of mobilization.

The Mobilization Seat is an effective measure to prevent drivers’ fatigue during monotonous situations.

The Mobilization Seat is an effective measure to prevent drivers’ fatigue during monotonous situations.Estimating the speed-crash relationship has long been a focus area of interest in roadway safety analysis. Because of many confounding factors that may influence both speeds and crashes, the relationship cannot be appropriately established without considering the corresponding roadway contexts and accounting for their effects on speeds and crashes. This paper investigates the speed-crash relationship for city streets by jointly modeling speed, roadway characteristics, and crashes using a path analysis approach that has been recently introduced into safety analysis while incorporating a wide range of roadway and traffic related variables and additional speed measures. The results from the coherent path analysis identified multiple speed measures of interest that have a statistically significant association with crashes as well as having intuitive and useful interpretation. The results also supported a positive relationship between speed variability and crash occurrence (i.e., larger spread/variability in operational speed is associated with more crashes).The proliferation of digital textual archives in the transportation safety domain makes it imperative for the inventions of efficient ways of extracting information from the textual data sources. The present study aims at utilizing crash narratives complemented by crash metadata to discern the prevalence and co-occurrence of themes that contribute to crash incidents. Ten years (2009-2018) of Michigan traffic fatal crash narratives were used as a case study. The structural topic modeling (STM) and network topology analysis were used to generate and examine the prevalence and interaction of themes from the crash narratives that were mainly categorized into pre-crash events, crash locations and involved parties in the traffic crashes. The main advantage of the STM over the other topic modeling approaches is that it allows the researchers to discover themes from documents and estimate how the topic relates to the document metadata. Topics with the highest prevalence for the angle, head-on, rear-end, sideswipe and single motor vehicle crashes were crash at stop-sign, crossing the centerline, unable to stop, lane change maneuver and run-off-road crash, respectively.