In Vivo Corneal Biomechanical Response to Three Different Laser Corneal Refractive Surgeries.

PURPOSE: To compare the effects of three common refractive surgeries on corneal biomechanics. METHODS: Two hundred seven patients who had refractive surgery were included in this study, of whom 65 received transepithelial photorefractive keratectomy (tPRK), 73 received femtosecond laser-assisted laser in situ keratomileusis (FSLASIK), and 69 received small incision lenticule extraction (SMILE). Each patient had biomechanical measurements using the Corvis ST (Oculus Optikgeräte GmbH) preoperatively and at 3 and 6 months postoperatively. The measurements included five parameters expected to be associated with corneal biomechanics: deformation amplitude ratio at 2 mm (DAR2), integrated inverse radius (IIR), stiffness parameter at first applanation (SP-A1), highest concavity time (HCT), and the updated stress-strain index (SSIv2). The variations in these parameters postoperatively among the three surgeries, and their relationship with corneal thickness (CCT) and intraocular pressure measured by the Dynamic Contour Tonometer (DCT-IOP) were analyzed. RESULTS: SP-A1 decreased significantly from preoperatively to 3 months postoperatively in all three groups, whereas DAR2 and IIR increased significantly, all indicating stiffness losses. Between 3 and 6 months postoperatively, the results were inconsistent, with DAR2 decreasing (indicating stiffness increases) and IIR increasing (denoting stiffness decreases) in the FS-LASIK and SMILE groups. The decrease in SSIv2 (the only measure of corneal material stiffness) postoperatively was comparatively less pronounced at both 3 and 6 months postoperatively. On the other hand, HCT remained generally stable after all three surgeries. Unlike DAR2, IIR, and SP-A1, the changes postoperatively in stiffness parameters HCT and SSIv2 were independent of the corresponding changes in both DCT-IOP and CCT. CONCLUSIONS: Among the stiffness parameters considered, SSIv2 was not correlated with CCT or DCT-IOP, and holds promise for representing the corneal material stiffness and how it remains largely unaffected by refractive surgeries. Overall, FS-LASIK had the most significant impact on corneal stiffness, followed by SMILE, and finally tPRK. [J Refract Surg. 2024;40(5):e344-e352.].

Inhalation of 2, 4-di-tert-butylphenol-Loaded micelles suppresses respiratory syncytial virus infection in mice.

Human respiratory syncytial virus (RSV) is a common cause of respiratory infections in infants, young children, and elderly people. However, there are no effective treatments or vaccines available in most countries. In this study, we explored the anti-RSV potential of 2, 4-Di-tert-butylphenol (2, 4-DTBP), a compound derived from Houttuynia cordata Thunb. To overcome the poor solubility of 2, 4-DTBP, we encapsulated it in polymeric micelles and delivered it by inhalation. We found that 2, 4-DTBP-loaded micelles inhibited RSV infection in vitro and improved survival, lung pathology, and viral clearance in RSV-infected mice. Our results suggested that 2, 4-DTBP-loaded micelle is a promising novel therapeutic agent for RSV infection.

Precise and low-power closed-loop neuromodulation through algorithm-integrated circuit co-design.

Implantable neuromodulation devices have significantly advanced treatments for neurological disorders such as Parkinson's disease, epilepsy, and depression. Traditional open-loop devices like deep brain stimulation (DBS) and spinal cord stimulators (SCS) often lead to overstimulation and lack adaptive precision, raising safety and side-effect concerns. Next-generation closed-loop systems offer real-time monitoring and on-device diagnostics for responsive stimulation, presenting a significant advancement for treating a range of brain diseases. However, the high false alarm rates of current closed-loop technologies limit their efficacy and increase energy consumption due to unnecessary stimulations. In this study, we introduce an artificial intelligence-integrated circuit co-design that targets these issues and using an online demonstration system for closed-loop seizure prediction to showcase its effectiveness. Firstly, two neural network models are obtained with neural-network search and quantization strategies. A binary neural network is optimized for minimal computation with high sensitivity and a convolutional neural network with a false alarm rate as low as 0.1/h for false alarm rejection. Then, a dedicated low-power processor is fabricated in 55 nm technology to implement the two models. With reconfigurable design and event-driven processing feature the resulting application-specific integrated circuit (ASIC) occupies only 5mm2 silicon area and the average power consumption is 142 µW. The proposed solution achieves a significant reduction in both false alarm rates and power consumption when benchmarked against state-of-the-art counterparts.

First Report of Colletotrichum fructicola Causing Leaf Spot on Smilax glabra Roxb in China.

Smilax glabra Roxb is a medicinal plant distributed in 17 countries and used in the production of food and tea (Wu et al. 2022). In May 2021, a leaf spot disease was observed on ~60% of S. glabra plants in a field (∼0.4 ha) in Qinzhou City, Guangxi Province. Initially, small, circular, brown spots appeared on the leaf surfaces, which then gradually expanded into large, sunken, dark brown necrotic areas. As disease progressed, lesions merged into large spots, eventually leading to defoliation. To determine the causal agent, six symptomatic plants were collected from the field. Small pieces (∼5 mm2) were cut from the infected leaves (n = 12), sterilized for two min in 1% NaOCl, and rinsed three times in sterile water. Then, the leaf tissues were placed on potato dextrose agar (PDA) with chloramphenicol (0.1 g/liter) and incubated for 3 days at 28°C (12-h photoperiod). Pure cultures were obtained by transferring hyphal tips from recently germinated spores or colony edges onto PDA. Among the 17 isolates, 15 exhibited similar morphologies. Two single-spore isolates (TFL45.1 and TFL46.2) were subjected to further morphological and molecular characterization. Colonies on PDA were grayish green with a white outer ring and cottony surface, and pale blackish green on the reverse side. Conidia were hyaline, aseptate, straight, and cylindrical, with rounded ends, and 11.4 to 16.5 µm × 4.1 to 6.1 µm (average 13.9 × 4.8 µm, n = 100). Appressoria were brown to dark brown, with a smooth edge and different shapes such as ovoid, elliptical or irregular, and 6.8 to 8.9 µm × 5.9 to 7.8 µm (average 7.7 × 6.6 µm, n = 25). For molecular identification, eight target gene sequences, internal transcribed spacer (ITS), glyceraldehydes-3-phosphate dehydrogenase (GAPHD), calmodulin (CAL), partial actin (ACT), chitin synthase (CHS-1), glutamine synthetase (GS), manganese superoxide dismutase (SOD2), and ß-tubulin (TUB) were selected for PCR amplification (Weir et al. 2012). The resulting sequences were deposited in GenBank (OR399160-61 and OR432537-50). BLASTn analysis of the obtained sequences showed 99-100% identity with those of the ex-type strain C. fructicola ICMP:18581 (JX010165, JX010033, FJ917508, FJ907426, JX009866, JX010095, JX010327, JX010405) (Weir et al. 2012). In addition, a phylogenetic analysis confirmed the isolates as C. fructicola. Therefore, based on morphological and molecular characteristics (Park et al. 2018; Weir et al. 2012), the isolates were identified as C. fructicola. To verify pathogenicity, three healthy leaves on each of six two-year-old S. glabra plants were inoculated with ∼5 mm2 mycelial discs or aliquots of 10 µl suspension (106 conidia/ml) of the strain TFL46.2, and six control plants were inoculated with sterile PDA discs or sterile water. All plants were enclosed in plastic bags and incubated in a greenhouse at 25°C (12-h photoperiod). Six days post-inoculation, leaf spot symptoms appeared on the inoculated leaves. No symptoms were detected in the controls. Experiments were replicated three times with similar results. To fulfill Koch's postulates, C. fructicola was consistently re-isolated from symptomatic tissue and confirmed by morphology and sequencing of the eight genes, whereas no fungus was isolated from the control plants. To our knowledge, this is the first report of C. fructicola causing leaf spot disease on S. glabra. Further studies will be needed to develop strategies against this disease based on the identification of this pathogen.

Minimally Invasive Hypoglossal Nerve Stimulator Enabled by ECG Sensor and WPT to Manage Obstructive Sleep Apnea.

A hypoglossal nerve stimulator (HGNS) is an invasive device that is used to treat obstructive sleep apnea (OSA) through electrical stimulation. The conventional implantable HGNS device consists of a stimuli generator, a breathing sensor, and electrodes connected to the hypoglossal nerve via leads. However, this implant is bulky and causes significant trauma. In this paper, we propose a minimally invasive HGNS based on an electrocardiogram (ECG) sensor and wireless power transfer (WPT), consisting of a wearable breathing monitor and an implantable stimulator. The breathing external monitor utilizes an ECG sensor to identify abnormal breathing patterns associated with OSA with 88.68% accuracy, achieved through the utilization of a convolutional neural network (CNN) algorithm. With a skin thickness of 5 mm and a receiving coil diameter of 9 mm, the power conversion efficiency was measured as 31.8%. The implantable device, on the other hand, is composed of a front-end CMOS power management module (PMM), a binary-phase-shift-keying (BPSK)-based data demodulator, and a bipolar biphasic current stimuli generator. The PMM, with a silicon area of 0.06 mm2 (excluding PADs), demonstrated a power conversion efficiency of 77.5% when operating at a receiving frequency of 2 MHz. Furthermore, it offers three-voltage options (1.2 V, 1.8 V, and 3.1 V). Within the data receiver component, a low-power BPSK demodulator was ingeniously incorporated, consuming only 42 µW when supplied with a voltage of 0.7 V. The performance was achieved through the implementation of the self-biased phase-locked-loop (PLL) technique. The stimuli generator delivers biphasic constant currents, providing a 5 bit programmable range spanning from 0 to 2.4 mA. The functionality of the proposed ECG- and WPT-based HGNS was validated, representing a highly promising solution for the effective management of OSA, all while minimizing the trauma and space requirements.

Identification and Quantification of the Main Psychoactive Ingredients of Cannabis in Urine Using Excitation-Eemission Matrix Fluorescence Coupled with Parallel Factor Analysis.

Cannabis is the most prevalent abused substance after alcohol, and its consumption severely harms human health and thus adversely impacts society. The identification and quantification of cannabis in urine play important roles in practical forensics. Excitation-emission matrix (EEM) fluorescence spectroscopy coupled with parallel factor (PARAFAC) analysis was developed to identify and quantify the four main ingredients of cannabis in urine samples. The main ingredients of cannabis including Δ-9-tetrahydrocannabinol (THC), cannabidiol, cannabinol, and tetrahydrocannabinolic acid (THC-COOH) exhibited diverse fluorescence characteristics, and the concentrations of these compounds depicted a positive linear relationship with the fluorescence intensity at the ng/mL level. The EEM/PARAFAC method adequately characterized and discriminated the four ingredients in calibration and prediction samples with a low root-mean-square error of prediction (RMSEP; 0.03-0.07 µg/mL) and limit of quantitation (LOQ; 0.26-0.71 µg/mL). The prediction results of the EEM/PARAFAC method well correlated with that of GC-MS with a low RMSEP range (0.01-0.05 µg/mL) and LOQ range (0.07-0.44 µg/mL) in urine samples. The EEM spectroscopic investigation coupled with the PARAFAC algorithm results in an organic, solvent-less, fast, reliable tool to perform accurate and rapid screening of cannabis abusers.

Circulating bile acid profile characteristics in PCOS patients and the role of bile acids in predicting the pathogenesis of PCOS.

Background: The metabolic profile of bile acids and their potential role as biomarkers in the pathogenesis of polycystic ovary syndrome (PCOS) have not been thoroughly characterized. Assessing their predictive value for PCOS is of significant importance. Methods: In this study, we enrolled 408 women with PCOS and 204 non-PCOS controls. The serum bile acid profile was measured using high-performance liquid chromatography-tandem mass spectrometry (LC/MS). We analyzed the differences in serum bile acid profiles between PCOS patients using the OPLS-DA model. Additionally, we examined the relationship between bile acid profiles and parameters related to glucose metabolism and hyperandrogenism. ROC analysis was employed to identify potential biomarkers for PCOS pathogenesis. XGboost was utilized for cross-validation. Results: The bile acid profile was found to be altered in PCOS patients. Specifically, the primary and secondary unconjugated bile acid fractions were significantly higher in the PCOS population. We identified five bile acid metabolite candidates that exhibited the most significant differences between PCOS and non-PCOS controls. DCA was associated with deposition index, fasting and postprandial insulin but was influenced by testosterone. CDCA and LCA combined with testosterone showed potential as biomarkers for the pathogenesis of PCOS. Conclusion: The circulating bile acid profile undergoes changes in PCOS. DCA is associated with deposition index, fasting and postprandial insulin and its level is influenced by testosterone. CDCA and LCA combined with testosterone have the potential to serve as biomarkers for the pathogenesis of PCOS.

Association of retinopathy with risk of all-cause and specific-cause mortality in the National Health and Nutrition Examination Survey, 2005 to 2008.

Objective: This study aimed to elucidate the relationship between retinopathy status or severity and the all-cause and specific-cause mortality risk based on the updated National Health and Nutrition Examination Survey (NHANES) database and 2019 Public Access Link mortality file. Methods: In this prospective cohort study, a total of 6,797 participants aged over 40 years based on NHANES 2005-2008 were analyzed. The severity of retinopathy was classified into 4 grades-no retinopathy, mild non-proliferative retinopathy (NPR), moderate to severe NPR, and proliferative retinopathy (PR). Multiple covariate-adjusted Cox proportional hazards regression models and Fine and Gray competing risk regression models were used to assess the all-cause and cause-specific mortality risks, respectively. The propensity score matching (PSM) approach was also applied additionally to adequately balance between-group covariates to validate our findings. Results: A final total of 4,808 participants representing 18,282,772 United States (US) non-hospitalized participants were included for analysis, 50.27% were male (n = 2,417), 55.32% were non-hispanic white (n = 2,660), and mean [SE] age, 56.10 [0.40] years. After a median follow-up of 12.24 years (interquartile range, 11.16-13.49 years), 1,164 participants died of all-cause mortality, of which 941 (80.84%) died without retinopathy and 223 (19.16%) died with retinopathy at baseline. The presence of retinopathy was associated with increased all-cause mortality, cardiovascular disease (CVD), and diabetes mellitus (DM)-specific mortality, and the results remain consistent after PSM. Severity analysis showed that only mild NPR was associated with an increased all-cause mortality risk (hazard ratio (HR) = 2.01; 95% confidence interval (CI), 1.00-4.03), while increased CVD and DM-specific mortality risk were associated with all grades of retinopathy and were exponentially greater with increasing retinopathy severity, and the trend test was also significant (P for trend 0.004 and 0.04, respectively). Discussion: Our findings suggest that the diagnosis of retinopathy is an independent risk factor for all-cause mortality in people over 40 years old. Retinopathy grading is significantly associated with the survival risk of patients with CVD or DM, it can be a valuable predictor in the stratified management and risk warning of CVD or DM patients, as well as in the monitoring of systemic vasculopathy status.

Simultaneous sensing of strain and temperature based on the inline-MZI embedded point-shaped taper structure with low crosstalk.

An embedded spherical dot taper structure (EDT) based on the MZI principle is proposed in this paper, which is mainly fabricated by using two special arc discharges in the preparation process. The proposed structure involves two specialized arc discharge techniques. First, an oversaturated discharge fusion process creates a micro-arc spherical area on the fiber end face to form the first link type. Second, an unsaturated discharge-pulling taper fusion joint creates a local micro-extrusion operation on this micro-arc fiber end face to form the second link. The thermal stress from instantaneous discharge causes a reverse spherical expansion zone to form in the end face structure, similar to the micromachining of long-period fiber gratings that use local CO2 laser etching to create modulated zones. The study involves a mathematical and theoretical analysis of how geometric parameters in the spherical modulation zone impact the structure's characteristic spectrum. The research demonstrates the potential for this structure to function as a light-intensity modulated strain sensor device through both theoretical and experimental means. As per the experimental findings, the optimized structure displays a high level of strain sensing sensitivity at 0.03 dB/µÎµ and temperature sensing sensitivity of 73 pm/°C (20°C-75°C) and 169 pm/°C (75°C-120°C). Additionally, it possesses excellent cross-sensitivity at only ∼0.0015 µÎµ/°C. Therefore, this sensor presents a favorable option for strain and temperature synchronization sensing and monitoring components, and exhibits notable application prospects in precision engineering, which encompasses mechanical manufacturing, the power and electrical industry, healthcare domain, and certain specialized areas of small-scale precision engineering.

Computer-aided shape features extraction and regression models for predicting the ascending aortic aneurysm growth rate.

OBJECTIVE: ascending aortic aneurysm growth prediction is still challenging in clinics. In this study, we evaluate and compare the ability of local and global shape features to predict the ascending aortic aneurysm growth. MATERIAL AND METHODS: 70 patients with aneurysm, for which two 3D acquisitions were available, are included. Following segmentation, three local shape features are computed: (1) the ratio between maximum diameter and length of the ascending aorta centerline, (2) the ratio between the length of external and internal lines on the ascending aorta and (3) the tortuosity of the ascending tract. By exploiting longitudinal data, the aneurysm growth rate is derived. Using radial basis function mesh morphing, iso-topological surface meshes are created. Statistical shape analysis is performed through unsupervised principal component analysis (PCA) and supervised partial least squares (PLS). Two types of global shape features are identified: three PCA-derived and three PLS-based shape modes. Three regression models are set for growth prediction: two based on gaussian support vector machine using local and PCA-derived global shape features; the third is a PLS linear regression model based on the related global shape features. The prediction results are assessed and the aortic shapes most prone to growth are identified. RESULTS: the prediction root mean square error from leave-one-out cross-validation is: 0.112 mm/month, 0.083 mm/month and 0.066 mm/month for local, PCA-based and PLS-derived shape features, respectively. Aneurysms close to the root with a large initial diameter report faster growth. CONCLUSION: global shape features might provide an important contribution for predicting the aneurysm growth.

Identification of Fusarium sacchari Causing Foliar Blight on Begonia semperflorens in China.

Begonia semperflorens Link et Otto (Begoniaceae) is a flowering, ornamental plant widely cultivated in China. In April of 2020, a foliar blight disease on B. semperflorens was observed in plant nurseries (∼0.2 ha), with ~ 20% disease incidence (n = 150) in Nanning, Guangxi Province, China. Initial symptoms included irregular to circular, grayish white spots surrounded by a dark brown halo, mainly scattered on the edges the leaves. In severe infections, the spots frequently coalesced to form large, blighted areas, followed by defoliation. To isolate the pathogen, three representative plants exhibiting symptoms were collected from the nurseries. Leaf tissues (5 × 5 mm) were cut from the margin of necrotic lesions (n = 18), surface disinfected in 1% NaOCl for 2 min, then rinsed three times in sterile H2O. Then the tissues were plated on potato dextrose agar (PDA), and incubated at 28°C (12 h photoperiod) for 3 days. Hyphal tips from recently germinated spores were transferred to PDA to purify fungal isolates. A total of 11 isolates (85% isolation frequency) with similar morphological characteristics were obtained. Colonies on PDA plates were villose, had a dense growth of white aerial mycelia and appeared pale but becoming violet with age. On Spezieller Nährstoffarmer Agar (SNA), the macroconidia were slender, slight falcate, two to three septate, and 23.5 to 48.8 × 2.8 to 4.8 µm (n = 60), and the microconidia were abundant and formed in false heads on monophialides or polyphialides, slim, oval, zero to one septate, and 7.8 to 22.4 × 2.4 to 4.0 µm (n = 60). For molecular identification, the internal transcribed spacer (ITS) region of rDNA, and partial translation elongation factor-1 alpha (TEF-1α), and RNA polymerase second largest subunit (RPB2) genes of the representative isolate HT-2B were amplified and sequenced using primer pairs ITS1/ITS4 (White et al. 1990), EF-1/EF-2 (O'Donnell et al. 1998), and 5f2/11ar (Liu et al. 1999, Reeb et al. 2004), respectively. The obtained sequences were deposited in NCBI GenBank under the accession numbers OQ048268 (TIS), OP994260 (TEF-1α), OP994262 (RPB2) and showed 99.4%, 99.8%, and 99.4% similarity with the corresponding sequences (X94168，AF160278，and JX171580, respectively) of Fusarium sacchari from type material. In addition, a phylogenetic analysis showed that HT-2B was grouped with F. sacchari. Therefore, based on morphological (Leslie et al. 2005) and molecular characteristics, the isolates were identified as F. sacchari. To test pathogenicity, three healthy leaves on each of three B. semperflorens plants were stab-wounded with a sterile syringe and inoculated with a 10-µl droplet of a conidial suspension (106 spores/ml) of the isolate HT-2B. As a control, another three leaves were wound inoculated with sterilized dH2O. All plants were enclosed in transparent plastic bags and incubated in a greenhouse at 28°C (12 h photoperiod, ~ 80% relative humidity). Six days post-inoculation, symptoms appeared on the inoculated leaves. No symptoms were detected on control plants. Experiments were replicated three times with similar results. To fulfill Koch's postulates, the F. sacchari isolates were consistently re-isolated from symptomatic tissue and confirmed by morphology and sequencing, whereas no fungus was isolated from the control plants. To our knowledge, this is the first report of F. sacchari causing foliar blight on B. semperflorens in China. This result will help develop management strategies for this disease.

Calibration of the Mechanical Boundary Conditions for a Patient-Specific Thoracic Aorta Model Including the Heart Motion Effect.

OBJECTIVE: We propose a procedure for calibrating 4 parameters governing the mechanical boundary conditions (BCs) of a thoracic aorta (TA) model derived from one patient with ascending aortic aneurysm. The BCs reproduce the visco-elastic structural support provided by the soft tissue and the spine and allow for the inclusion of the heart motion effect. METHODS: We first segment the TA from magnetic resonance imaging (MRI) angiography and derive the heart motion by tracking the aortic annulus from cine-MRI. A rigid-wall fluid-dynamic simulation is performed to derive the time-varying wall pressure field. We build the finite element model considering patient-specific material properties and imposing the derived pressure field and the motion at the annulus boundary. The calibration, which involves the zero-pressure state computation, is based on purely structural simulations. After obtaining the vessel boundaries from the cine-MRI sequences, an iterative procedure is performed to minimize the distance between them and the corresponding boundaries derived from the deformed structural model. A strongly-coupled fluid-structure interaction (FSI) analysis is finally performed with the tuned parameters and compared to the purely structural simulation. RESULTS AND CONCLUSION: The calibration with structural simulations allows to reduce maximum and mean distances between image-derived and simulation-derived boundaries from 8.64 mm to 6.37 mm and from 2.24 mm to 1.83 mm, respectively. The maximum root mean square error between the deformed structural and FSI surface meshes is 0.19 mm. This procedure may prove crucial for increasing the model fidelity in replicating the real aortic root kinematics.

Segmentation of 4D Flow MRI: Comparison between 3D Deep Learning and Velocity-Based Level Sets.

A thoracic aortic aneurysm is an abnormal dilatation of the aorta that can progress and lead to rupture. The decision to conduct surgery is made by considering the maximum diameter, but it is now well known that this metric alone is not completely reliable. The advent of 4D flow magnetic resonance imaging has allowed for the calculation of new biomarkers for the study of aortic diseases, such as wall shear stress. However, the calculation of these biomarkers requires the precise segmentation of the aorta during all phases of the cardiac cycle. The objective of this work was to compare two different methods for automatically segmenting the thoracic aorta in the systolic phase using 4D flow MRI. The first method is based on a level set framework and uses the velocity field in addition to 3D phase contrast magnetic resonance imaging. The second method is a U-Net-like approach that is only applied to magnitude images from 4D flow MRI. The used dataset was composed of 36 exams from different patients, with ground truth data for the systolic phase of the cardiac cycle. The comparison was performed based on selected metrics, such as the Dice similarity coefficient (DSC) and Hausdorf distance (HD), for the whole aorta and also three aortic regions. Wall shear stress was also assessed and the maximum wall shear stress values were used for comparison. The U-Net-based approach provided statistically better results for the 3D segmentation of the aorta, with a DSC of 0.92 ± 0.02 vs. 0.86 ± 0.5 and an HD of 21.49 ± 24.8 mm vs. 35.79 ± 31.33 mm for the whole aorta. The absolute difference between the wall shear stress and ground truth slightly favored the level set method, but not significantly (0.754 ± 1.07 Pa vs. 0.737 ± 0.79 Pa). The results showed that the deep learning-based method should be considered for the segmentation of all time steps in order to evaluate biomarkers based on 4D flow MRI.

Biomechanical properties of 3D printable material usable for synthetic personalized healthy human aorta.

With the development of three-dimensional (3D) printing, 3D-printed products have been widely used in medical fields, such as plastic surgery, orthopedics, dentistry, etc. In cardiovascular research, 3D-printed models are becoming more realistic in shape. However, from a biomechanical point of view, only a few studies have explored printable materials that can represent the properties of the human aorta. This study focuses on 3D-printed materials that might simulate the stiffness of human aortic tissue. First, the biomechanical properties of a healthy human aorta were defined and used as reference. The main objective of this study was to identify 3D printable materials that possess similar properties to the human aorta. Three synthetic materials, NinjaFlex (Fenner Inc., Manheim, USA), FilasticTM (Filastic Inc., Jardim Paulistano, Brazil), and RGD450+TangoPlus (Stratasys Ltd.©, Rehovot, Israel), were printed in different thicknesses. Uniaxial and biaxial tensile tests were performed to compute several biomechanical properties, such as thickness, stress, strain, and stiffness. We found that with the mixed material RGD450+TangoPlus, it was possible to achieve a similar stiffness to healthy human aorta. Moreover, the 50-shore-hardness RGD450+TangoPlus had similar thickness and stiffness to the human aorta.

A reusable, impurity-tolerant and noble metal-free catalyst for hydrocracking of waste polyolefins.

One-step conversion of low-purity polyolefins to value-added products without pretreatments represents a great opportunity for chemical recycling of waste plastics. However, additives, contaminants, and heteroatom-linking polymers tend to be incompatible with catalysts that break down polyolefins. Here, we disclose a reusable, noble metal-free and impurity-tolerant bifunctional catalyst, MoSx-Hbeta, for hydroconversion of polyolefins into branched liquid alkanes under mild conditions. The catalyst works for a wide scope of polyolefins, including different kinds of high-molecular weight polyolefins, polyolefins mixed with various heteroatom-linking polymers, contaminated polyolefins, and postconsumer polyolefins with/without cleaning under 250°C and 20 to 30 bar H2 in 6 to 12 hours. A 96% yield of small alkanes was successfully achieved even at a temperature as low as 180°C. These results demonstrate the great potentials of hydroconversion in practical use of waste plastics as a largely untapped carbon feedstock.

Protocol for vision transformer-based evaluation of drug potency using images processed by an optimized Sobel operator.

Conventional approaches for screening anticancer drugs rely on chemical reactions, which are time consuming, labor intensive, and costly. Here, we present a protocol for label-free and high-throughput assessment of drug efficacy using a vision transformer and a Conv2D. We describe the steps for cell culture, drug treatment, data collection, and preprocessing. We then detail the building of deep learning models and their use to predict drug potency. This protocol can be adapted for screening chemicals that affect the density or morphological features of cells. For complete details on the use and execution of this protocol, please refer to Wang et al.1.

Photothermal CO-PROX reaction over ternary CuCoMnOx spinel oxide catalysts: the effect of the copper dopant and thermal treatment.

The purification of carbon monoxide in H2-rich streams is an urgent problem for the practical application of fuel cells, and requires the development of efficient and economical catalysts for the preferential oxidation of CO (CO-PROX). In the present work, a facile solid phase synthesis method followed by an impregnation method were adopted to prepare a ternary CuCoMnOx spinel oxide, which shows superior catalytic performance with CO conversion of 90% for photothermal CO-PROX at 250 mW cm-2. The dopant of copper species leads to the incorporation of Cu ions into the CoMnOx spinel lattice forming a ternary CuCoMnOx spinel oxide. The appropriate calcination temperature (300 °C) contributes to the generation of abundant oxygen vacancies and strong synergetic Cu-Co-Mn interactions, which are conducive to the mobility of oxygen species to participate in CO oxidation reactions. On the other hand, the highest photocurrent response of CuCoMnOx-300 also promotes the photo-oxidation activity of CO due to the high carrier concentration and efficient carrier separation. In addition, the in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) confirmed that doping copper species could enhance the CO adsorption capacity of the catalyst due to the generation of Cu+ species, which significantly increased the CO oxidation activity of the CuCoMnOx spinel oxide. The present work provides a promising and eco-friendly solution to remove the trace CO in H2-rich gas over CuCoMnOx ternary spinel oxide with solar light as the only energy source.

Assessment of shape-based features ability to predict the ascending aortic aneurysm growth.

The current guidelines for the ascending aortic aneurysm (AsAA) treatment recommend surgery mainly according to the maximum diameter assessment. This criterion has already proven to be often inefficient in identifying patients at high risk of aneurysm growth and rupture. In this study, we propose a method to compute a set of local shape features that, in addition to the maximum diameter D, are intended to improve the classification performances for the ascending aortic aneurysm growth risk assessment. Apart from D, these are the ratio DCR between D and the length of the ascending aorta centerline, the ratio EILR between the length of the external and the internal lines and the tortuosity T. 50 patients with two 3D acquisitions at least 6 months apart were segmented and the growth rate (GR) with the shape features related to the first exam computed. The correlation between them has been investigated. After, the dataset was divided into two classes according to the growth rate value. We used six different classifiers with input data exclusively from the first exam to predict the class to which each patient belonged. A first classification was performed using only D and a second with all the shape features together. The performances have been evaluated by computing accuracy, sensitivity, specificity, area under the receiver operating characteristic curve (AUROC) and positive (negative) likelihood ratio LHR+ (LHR-). A positive correlation was observed between growth rate and DCR (r = 0.511, p = 1.3e-4) and between GR and EILR (r = 0.472, p = 2.7e-4). Overall, the classifiers based on the four metrics outperformed the same ones based only on D. Among the diameter-based classifiers, k-nearest neighbours (KNN) reported the best accuracy (86%), sensitivity (55.6%), AUROC (0.74), LHR+ (7.62) and LHR- (0.48). Concerning the classifiers based on the four shape features, we obtained the best accuracy (94%), sensitivity (66.7%), specificity (100%), AUROC (0.94), LHR+ (+∞) and LHR- (0.33) with support vector machine (SVM). This demonstrates how automatic shape features detection combined with risk classification criteria could be crucial in planning the follow-up of patients with ascending aortic aneurysm and in predicting the possible dangerous progression of the disease.

Segmentation of the aorta in systolic phase from 4D flow MRI: multi-atlas vs. deep learning.

OBJECTIVE: In the management of the aortic aneurysm, 4D flow magnetic resonance Imaging provides valuable information for the computation of new biomarkers using computational fluid dynamics (CFD). However, accurate segmentation of the aorta is required. Thus, our objective is to evaluate the performance of two automatic segmentation methods on the calculation of aortic wall pressure. METHODS: Automatic segmentation of the aorta was performed with methods based on deep learning and multi-atlas using the systolic phase in the 4D flow MRI magnitude image of 36 patients. Using mesh morphing, isotopological meshes were generated, and CFD was performed to calculate the aortic wall pressure. Node-to-node comparisons of the pressure results were made to identify the most robust automatic method respect to the pressures obtained with a manually segmented model. RESULTS: Deep learning approach presented the best segmentation performance with a mean Dice similarity coefficient and a mean Hausdorff distance (HD) equal to 0.92+/- 0.02 and 21.02+/- 24.20 mm, respectively. At the global level HD is affected by the performance in the abdominal aorta. Locally, this distance decreases to 9.41+/- 3.45 and 5.82+/- 6.23 for the ascending and descending thoracic aorta, respectively. Moreover, with respect to the pressures from the manual segmentations, the differences in the pressures computed from deep learning were lower than those computed from multi-atlas method. CONCLUSION: To reduce biases in the calculation of aortic wall pressure, accurate segmentation is needed, particularly in regions with high blood flow velocities. Thus, the deep learning segmen-tation method should be preferred.

First Report of Epicoccum latusicollum Causing Leaf Blight on Curcuma kwangsiensis in China.

Curcuma kwangsiensis S. G. Lee et C. F. Liang is a traditional Chinese medicinal plant distributed in Guangxi and Yunnan Province, China. In May 2021, a leaf blight disease on C. kwangsiensi was observed in a plantation (~ 2 ha) in Lingshan county (21°51'00″N, 108°44'00″E), Guangxi Province. Disease incidence was up to 30% (n = 200). Initially, yellow to brown, irregular, water-soaked spots appeared at the tips or margins of leaves. As the disease progressed, the lesions gradually enlarged, merged. Finally, the entire leaf wilted, leading to defoliation. To isolate the pathogen, eighteen small pieces ( ~ 5 mm2) were cut from the margin of the necrotic lesions, surface disinfected with 1% NaOCl solution for 2 min, and rinsed three times in sterile water. Then the tissues were plated onto potato dextrose agar (PDA) and incubated for 3 days at 28°C. Hyphal tips from recently germinated spores were transferred to PDA to obtain pure cultures. Twelve isolates were obtained, of which ten isolates with similar morphological characterization. Two single-spore isolates (CK45.1 and CK45.2) were subjected to further morphological and molecular characterization. Colonies on PDA were villose, had a dense growth of aerial mycelia, and appeared white to grayish eventually. Pycnidia were brown, predominantly spheroidal, and 45.0 to 205.4 µm in diameter (n = 60). Conidia were ellipsoidal, aseptate, and 3.8 to 6.1 × 1.8 to 3.6 µm (n = 90). Morphological characteristics are similar to those of Epicoccum latusicollum (Chen et al. 2017).For molecular identification, primers ITS1/ITS4 (White et al. 1990), LR0R/LR5 (Vilgalys and Hester 1990, Rehner and Samuels 1994), RPB2-Ep-F (GGTCTTGTGTGCCCCGCTGAGAC)/RPB2-Ep-R TCGGGTGACATGACAATCATGGC), and TUB2-Ep-F (GTTCACCTTCAAACCGGTCAATG)/TUB2-Ep-R (AAGTTGTCGGGACGGAAGAGCTG) were used to amplify the internal transcribed spacer (ITS), partial nuclear large subunit rDNA (LSU), RNA polymerase II second largest subunit (rpb2), and ß-tubulin (tub2) genes, respectively. The obtained ITS (OP788080-81), LSU (OP811325-26), rpb2 (OP811267-68) and tub2 (OP811269-70) sequences showed 99.8% (478/479, and 478/479 bp), 99.9% (881/882, and 870/871 bp), 99.8 to 100% (429/431, and 429/430 bp), and 99.7% (332/333, and 332/333 bp) identity with those of ex-type strain E. latusicollum CGMCC 3.18346 (KY742101, KY742255, KY742174, KY742343). In addition, a phylogenetic analysis confirmed the isolates as E. latusicollum. Therefore, based on morphological and molecular characteristics, the isolates were identified as E. latusicollum. To verify pathogenicity, healthy leaves on nine plants (1 leaf per plant) were inoculated with mycelial discs from 5-day-old water-agar medium (WA) cultures of the strain CK45.1. Each leaf had four inoculation sites, two were inoculated with a representative strain, and two treated with pollution-free WA discs served as control. Plants were covered with transparent plastic bags and maintained in a greenhouse at 25°C with a 12 h photoperiod. Six days post-inoculation, the inoculated sites of leaves showed brown lesions, while the control remained healthy. The experiments repeated three times showed similar results. Koch's postulates were fulfilled by re-isolation of E. latusicollum from the lesions. To our knowledge, this is the first report of E. latusicollum causing leaf blight of C. kwangsiensi in China. This report might provide important information for growers to manage this disease.