Enhancing the health benefits of air quality improvement: a comparative study across diverse scenarios.

In many studies, linear methods were used to calculate health benefits of air quality improvement, but the relationship between air pollutants and diseases may be complex and nonlinear. In addition, previous studies using reference number as average number of diseases may overestimate the health benefits. Therefore, the nonlinear model estimation and resetting of the reference number were very important. Hospital admission data for coronary heart disease (CHD), meteorological data, and air pollutant data of Zibo City from 2015 to 2019 were collected. The generalized additive model (GAM) was used to explore the association between air pollutants and hospital admission for CHD, and to evaluate the effects on health benefits under different reference number settings. A total of 21,105 hospitalized cases for CHD were reported in Zibo during the study period. The results of the GAM showed there was a log-linear exposure-response relationship between O3 and hospital admissions for CHD, with RR (relative risk) of 1.0143 (95% CI: 1.0047 ~ 1.0239). There were log-nonlinear exposure-response relationships between PM10, PM2.5, SO2, and hospital admissions for CHD. With the increase of pollutants concentrations, the risk for hospital admission showed a trend of increasing first and then decreasing. Compared with the average hospital admissions as the reference number, health benefits calculated by hospital admissions predicted by the GAM model yielded lower. Using the World Health Organization air quality guidelines as reference, attributable fractions of O3, PM10, and PM2.5 were 1.97% (95% CI: 0.63 ~ 3.40%), 11.82% (95% CI: 8.60 ~ 15.24%), and 11.82% (95% CI: 8.79 ~ 15.04%), respectively. When quantifying health benefits brought by improving air quality, corresponding calculation methods should first be determined according to the exposure-response relationships between air pollutants and outcomes. Then, applying the average hospital admissions as reference number may overestimate health benefits resulting from improved air quality.

An automated two-stage approach to kidney and tumor segmentation in CT imaging.

BACKGROUND: The incidence of kidney tumors is progressively increasing each year. The precision of segmentation for kidney tumors is crucial for diagnosis and treatment. OBJECTIVE: To enhance accuracy and reduce manual involvement, propose a deep learning-based method for the automatic segmentation of kidneys and kidney tumors in CT images. METHODS: The proposed method comprises two parts: object detection and segmentation. We first use a model to detect the position of the kidney, then narrow the segmentation range, and finally use an attentional recurrent residual convolutional network for segmentation. RESULTS: Our model achieved a kidney dice score of 0.951 and a tumor dice score of 0.895 on the KiTS19 dataset. Experimental results show that our model significantly improves the accuracy of kidney and kidney tumor segmentation and outperforms other advanced methods. CONCLUSION: The proposed method provides an efficient and automatic solution for accurately segmenting kidneys and renal tumors on CT images. Additionally, this study can assist radiologists in assessing patients' conditions and making informed treatment decisions.

Soil selenium enhanced the resistance of oilseed rape to Sclerotinia sclerotiorum by optimizing the plant microbiome.

Plant can recruit beneficial microbes to enhance their ability to resist disease. Selenium is well established as a beneficial element in plant growth, but its role in mediating microbial disease resistance remained poorly understood. Here, we investigated the correlation between selenium, oilseed rape rhizosphere microbes and Sclerotinia sclerotiorum. Soil application of 0.5 and 1.0 mg/kg selenium significantly increased the resistance of oilseed rape to Sclerotinia sclerotiorum compared with no selenium application, and the disease inhibition rate was higher than 20%. The disease resistance of oilseed rape was related to rhizosphere microorganisms, and beneficial bacteria isolated from the rhizosphere inhibited Sclerotinia stem rot. Burkholderia cepacia, and synthetic community enhanced plant disease resistance through transcriptional regulation and activated plant-induced systemic resistance to protect plants. Besides, inoculation of isolated bacteria optimized the bacterial community structure of leaves and enriched beneficial microorganisms such as Bacillus, Pseudomonas and Sphingomonas. Bacillus isolated from the leaves were sprayed on the detached leaves, and it also performed a significant inhibition effect on Sclerotinia sclerotiorum. Overall, our results suggested that selenium drive plant rhizosphere microorganisms to increase resistance to Sclerotinia sclerotiorum in oilseed rape.

Transcriptome analysis and development of EST-SSR markers in the mushroom Auricularia heimuer.

Auricularia heimuer, the third most frequently cultivated edible mushroom species worldwide, has high medicinal value. However, a shortage of molecular marker hinders the efficiency and accuracy of genetic breeding efforts for A. heimuer. High-throughput transcriptome sequencing data are essential for gene discovery and molecular markers development. This study aimed to clarify the distribution of SSR loci across the A. heimuer transcriptome and to develop highly informative EST-SSR markers. These tools can be used for phylogenetic analysis, functional gene mining, and molecular marker-assisted breeding of A. heimuer. This study used Illumina high-throughput sequencing technology to obtain A. heimuer transcriptome data. The results revealed 37,538 unigenes in the A. heimuer transcriptome. Of these unigenes, 24,777 (66.01%) were annotated via comparison with the COG, Pfam, and NR databases. Overall, 2510 SSRs were identified from the unigenes, including 6 types of SSRs. The most abundant type of repeats were trinucleotides (1425, 56.77%), followed by mononucleotides (391, 15.58%) and dinucleotides (456, 18.17%). Primer pairs for 102 SSR loci were randomly designed for validity confirmation and polymorphism identification; this process yielded 53 polymorphic EST-SSR markers. Finally, 13 pairs of highly polymorphic EST-SSR primers were used to analyze the genetic diversity and population structure of 52 wild A. heimuer germplasms, revealing that the 52 germplasms could be divided into three categories. These results indicated that SSR loci were abundant in types, numbers, and frequencies, providing a potential basis for germplasm resource identification, genetic diversity analysis, and molecular marker-assisted breeding of A. heimuer.

Efficient electrocardiogram generation based on cardiac electric vector simulation model.

This study introduces a novel Cardiac Electric Vector Simulation Model (CEVSM) to address the computational inefficiencies and low fidelity of traditional electrophysiological models in generating electrocardiograms (ECGs). Our approach leverages CEVSM to efficiently produce reliable ECG samples, facilitating data augmentation essential for the computer-aided diagnosis of myocardial infarction (MI). Significantly, experimental results show that our model dramatically reduces computation time compared to conventional models, with the self-adapting regression transformation matrix method (SRTM) providing clear advantages. SRTM not only achieves high fidelity in ECG simulations but also ensures exceptional consistency with the gold standard method, greatly enhancing MI localization accuracy by data augmentation. These advancements highlight the potential of our model to generate dependable ECG training samples, making it highly suitable for data augmentation and significantly advancing the development and validation of intelligent MI diagnostic systems. Furthermore, this study demonstrates the feasibility of applying life system simulations in the training of medical big models.

Fish sonar image recognition algorithm based on improved YOLOv5.

Fish stock assessment is crucial for sustainable marine fisheries management in rangeland ecosystems. To address the challenges posed by the overfishing of offshore fish species and facilitate comprehensive deep-sea resource evaluation, this paper introduces an improved fish sonar image detection algorithm based on the you only look once algorithm, version 5 (YOLOv5). Sonar image noise often results in blurred targets and indistinct features, thereby reducing the precision of object detection. Thus, a C3N module is incorporated into the neck component, where depth-separable convolution and an inverse bottleneck layer structure are integrated to lessen feature information loss during downsampling and forward propagation. Furthermore, lowercase shallow feature layer is introduced in the network prediction layer to enhance feature extraction for pixels larger than $ 4 \times 4 $. Additionally, normalized weighted distance based on a Gaussian distribution is combined with Intersection over Union (IoU) during gradient descent to improve small target detection and mitigate the IoU's scale sensitivity. Finally, traditional non-maximum suppression (NMS) is replaced with soft-NMS, reducing missed detections due to occlusion and overlapping fish targets that are common in sonar datasets. Experiments show that the improved model surpasses the original model and YOLOv3 with gains in precision, recall and mean average precision of 2.3%, 4.7% and 2.7%, respectively, and 2.5%, 6.3% and 6.7%, respectively. These findings confirm the method's effectiveness in raising sonar image detection accuracy, which is consistent with model comparisons. Given Unmanned Underwater Vehicle advancements, this method holds the potential to support fish culture decision-making and facilitate fish stock resource assessment.

Effects of extreme temperature events on deaths and its interaction with air pollution.

BACKGROUND: Both extreme temperature events (ETEs) and air pollution affected human health, and their effects were often not independent. Previous studies have provided limited information on the interactions between ETEs and air pollution. METHODS: We collected data on deaths (non-accidental, cardiovascular, and respiratory) in Zibo City along with daily air pollution and meteorological data from January 2015 to December 2019. Distributed lag non-linear model was used to explore the health effects of ETEs on deaths. Non-parametric binary response model, hierarchical model and joint effect model were used to further explore the interaction between ETEs and air pollution in different seasons. Meanwhile, subgroup analysis by gender and age (≥ 65 years old and < 65 years old) was conducted to identify the vulnerable population. RESULTS: ETEs increased death risk, especially for cardiovascular and respiratory deaths. Heat waves had a stronger impact than cold spells. Cold spells had a longer lag and fluctuating trend. Heat waves had a short-term impact, followed by a decrease. Females and those aged ≥ 65 were more affected, but subgroup differences were not significant. During ETEs and non-ETEs, there were different effects on deaths with per IQR increase in air pollutant concentrations. Joint effect models revealed that there was a significant interaction between ETEs and air pollution on non-accidental deaths. The interaction between PM2.5 and cold spells was antagonistic in the cold season. In the warm season, the health effects of heat waves and high O3 concentration were enhanced. The relative excess risk due to interaction (RERI) of cold spells and PM2.5 in total population was -0.09 (95 % CI: -0.17, -0.01), and 9 % (95 % CI: 1 %, 17 %) of the total effect was attributable to interaction. Subgroup analysis confirmed the interactions in females and those aged ≥ 65. CONCLUSIONS: Significant association observed between ETEs and deaths. Females and ≥ 65 age groups were vulnerable. There were interactions between ETEs and air pollution. The effect of PM2.5 on deaths decreased during cold spells, while the effect of O3 increased during heat waves. In addition to improving air quality, it is necessary to further strengthen the prevention and control of ETEs.

Near-Infrared Light-Driven Photocatalysis with an Emphasis on Two-Photon Excitation: Concepts, Materials, and Applications.

Efficient utilization of sunlight in photocatalysis is widely recognized as a promising solution for addressing the growing energy demand and environmental issues resulting from fossil fuel consumption. Recently, there have been significant developments in various near-infrared (NIR) light-harvesting systems for artificial photosynthesis and photocatalytic environmental remediation. This review provides an overview of the most recent advancements in the utilization of NIR light through the creation of novel nanostructured materials and molecular photosensitizers, as well as modulating strategies to enhance the photocatalytic processes. A special focus is given to the emerging two-photon excitation NIR photocatalysis. The unique features and limitations of different systems are critically evaluated. In particular, it highlights the advantages of utilizing NIR light and two-photon excitation compared to UV-visible irradiation and one-photon excitation. Ongoing challenges and potential solutions for the future exploration of NIR light-responsive materials are also discussed.

Ni(OH)2 surface-modified hierarchical ZnIn2S4 nanosheets: dual photocatalytic application and mechanistic insights.

The simultaneous utilization of electrons and holes to couple photocatalytic H2 production with selective biomass transformation has attracted immense interest toward achieving sustainability in the fields of energy and chemical industry. In this study, by assembling highly dispersed Ni(OH)2 onto ZnIn2S4 (ZIS), efficient H2 evolution along with highly selective photocatalytic oxidation of furfuryl alcohol (FA) to furfural (FF) in pure water was achieved under anaerobic conditions. The H2 production and FA conversion rates over the optimal Ni-ZIS sample reached about 686 and 583 µmol g-1 h-1, respectively, about 4.9 and 1.7 folds as those of pure ZIS. Moreover, the formation of by-products with C-C coupling was dramatically suppressed over Ni-ZIS, resulting in higher selectivity for FF (97%), which is about 2.7-fold that of pure ZIS (36%). Deep mechanistic studies were conducted to reveal the structural evolution and cocatalyst effects of Ni(OH)2. This study not only offers a feasible paradigm for modifying the surface of catalysts to tune the photoactivity and selectivity for product-oriented alcohol oxidation coupled with efficient H2 production in water but also reveals the working mechanism of the deposited Ni(OH)2 over ZIS toward coupling reactions.

Microencapsulated Limosilactobacillus reuteri Encoding Lactoferricin-Lactoferrampin Targeted Intestine against Salmonella typhimurium Infection.

Salmonella enterica serovar Typhimurium (S. typhimurium) is an important foodborne pathogen that infects both humans and animals and develops acute gastroenteritis. As porcine intestines are relatively similar to the human ones due to their relatively similar sizes and structural similarity, S. typhimurium causes analogous symptoms in both. Novel strategies for controlling S. typhimurium infection are also desired, such as mucosal-targeted delivery of probiotics and antimicrobial peptides. The bovine lactoferricin-lactoferrampin-encoding Limosilactobacillus reuteri (LR-LFCA) strain improves intestinal barrier function by strengthening the intestinal barrier. Weaned piglets were selected for oral administration of microencapsulated LR-LFCA (microcapsules entrap LR-LFCA into gastro-resistant polymers) and then infected with S. typhimurium for 3 days. We found that orally administering microencapsulated LR-LFCA to weaned piglets attenuated S. typhimurium-induced production of inflammatory factors in the intestinal mucosa by inhibiting the nuclear factor-kappa B (NF-κB) and P38 mitogen-activated protein kinases (MAPK) signaling pathway. Moreover, microencapsulated LR-LFCA administration significantly suppressed the oxidative stress that may correlate with gut microbiota (reduced Salmonella population and increased α-diversity and Lactobacillus abundance) and intestinal function (membrane transport and metabolism). Our work demonstrated that microencapsulated LR-LFCA effectively targeted intestine delivery of Lactobacillus and antimicrobial peptides and modulated gut microbiota and mucosal immunity. This study reveals a novel targeting mucosal strategy against S. typhimurium infection.

Maleic acid and malonic acid reduced the pathogenicity of Sclerotinia sclerotiorum by inhibiting mycelial growth, sclerotia formation and virulence factors.

Sclerotinia sclerotiorum is a necrotrophic plant pathogenic fungus with broad distribution and host range. Bioactive compounds derived from plant extracts have been proven to be effective in controlling S. sclerotiorum. In this study, the mycelial growth of S. sclerotiorum was effectively inhibited by maleic acid, malonic acid, and their combination at a concentration of 2 mg/mL, with respective inhibition rates of 32.5%, 9.98%, and 67.6%. The treatment of detached leaves with the two acids resulted in a decrease in lesion diameters. Interestingly, maleic acid and malonic acid decreased the number of sclerotia while simultaneously increasing their weight. The two acids also disrupted the cell structure of sclerotia, leading to sheet-like electron-thin regions. On a molecular level, maleic acid reduced oxalic acid secretion, upregulated the expression of Ss-Odc2 and downregulated CWDE10, Ss-Bi1 and Ss-Ggt1. Differently, malonic acid downregulated CWDE2 and Ss-Odc1. These findings verified that maleic acid and malonic acid could effectively inhibit S. sclerotiorum, providing promising evidence for the development of an environmentally friendly biocontrol agent.

[A review on intelligent auxiliary diagnosis methods based on electrocardiograms for myocardial infarction].

Myocardial infarction (MI) has the characteristics of high mortality rate, strong suddenness and invisibility. There are problems such as the delayed diagnosis, misdiagnosis and missed diagnosis in clinical practice. Electrocardiogram (ECG) examination is the simplest and fastest way to diagnose MI. The research on MI intelligent auxiliary diagnosis based on ECG is of great significance. On the basis of the pathophysiological mechanism of MI and characteristic changes in ECG, feature point extraction and morphology recognition of ECG, along with intelligent auxiliary diagnosis method of MI based on machine learning and deep learning are all summarized. The models, datasets, the number of ECG, the number of leads, input modes, evaluation methods and effects of different methods are compared. Finally, future research directions and development trends are pointed out, including data enhancement of MI, feature points and dynamic features extraction of ECG, the generalization and clinical interpretability of models, which are expected to provide references for researchers in related fields of MI intelligent auxiliary diagnosis.

Dual transformation therapy for giant hepatocellular carcinoma: Two case reports and review of literature.

BACKGROUND: In the translational therapy of giant hepatocellular carcinoma (HCC), hepatic arterial infusion chemotherapy (HAIC) combined with anti-PD-1 immunotherapy and tyrosine kinase inhibitors (TKI) after laparoscopic portal vein ligation (PVL) is extremely rare. This is a dual conversion therapy that combines surgery and oncology. Here, we report two cases of successful surgical completion after dual conversion therapy. CASE SUMMARY: We report that a 54-year-old man and a 69-year-old woman were diagnosed with primary HCC combined with hepatitis B cirrhosis (case 2 also combined with fatty liver) on physical examination. Due to the insufficient residual liver volume assessed before surgery, laparoscopic right PVL was performed, followed by HAIC combined with anti-PD-1 immunotherapy and TKI. Finally, surgical resection was successfully completed, and pathology confirmed that the tumor was mostly necrotic (90%) in one case, and no live tumor tissue was found in the other case. CONCLUSION: In the process of surgical transformation, our treatment plan takes into account the control and transformation of oncology at the same time, which is expected to provide more opportunities for radical hepatectomy and improve the prognosis of patients with large liver cancer.

DOA Estimation for Coherent Sources Based on Uniformly Distributed Two Concentric Rings Array.

The direction estimation of the coherent source in a uniform circular array is an essential part of the signal processing area of the array, but the traditional uniform circular array algorithm has a low localization accuracy and a poor localization effect on the coherent source. To solve this problem, this paper proposes a two-dimensional direction of arrival (DOA) estimation for the coherent source in broadband. Firstly, the central frequency of the coherent sound source is estimated using the frequency estimation method of the delayed data, and a real-valued beamformer is constructed using the concept of the multiloop phase mode. Then, the cost function in the beam space is obtained. Finally, the cost function is searched in two dimensions to locate the sound source. In this paper, we simulate the DOA of the sound source at different frequencies and signal-to-noise ratios and analyze the resolution of the circular array. The simulation results show that the proposed algorithm can estimate the direction of arrival with high precision and achieve the desired results.

Wet-chemical intercalation of Bi4TaO8Br with self-adaptive structural deformation for enhanced photocatalytic performance.

A small specific surface area and severe charge carrier recombination greatly limit the photocatalytic efficiency of semiconductors. Herein, we developed a novel wet-chemical intercalation strategy by using the NaBH4 reagent for in situ intercalation-assisted expansion and surface/interface reconstruction of Bi4TaO8Br, which exhibits an enhanced specific surface area and charge carrier separation features. This work highlights intercalation of semiconductors for achieving enhanced photocatalytic performance and provides a new idea to synergistically regulate the morphology and surface/interface composition of semiconductors.

Chemical bonding and facet modulating of p-n heterojunction enable vectorial charge transfer for enhanced photocatalysis.

Heterojunctions have been proved to be the promising photocatalysts for hazardous contaminants removal, but the inferior interfacial contact, low carrier mobility and random carrier diffusion seriously hamper the photoactivity improvement of the conventional heterojunctions. Herein, SO chemically bonded p-n oriented heterostructure is fabricated via selectively anchoring of p-type Ag2S nanoparticles on the lateral facet of n-type Bi4TaO8Cl nanosheet. Such a p-n heterojunction engineering on specific facet of Bi4TaO8Cl semiconductor derives ingenious double internal electric field (IEF), which not only effectively creates the spatially separated oxidation and reduction sites, but also delivers the powerful driving forces for impactful spatial directed photocarrier transfer along the cascade path. Additionally, our experimental and theoretical analyses jointly signify that the interfacial SO bond could serve as an efficient atomic-level interfacial channel, which is conducive to encouraging the vectorial charge separation and migration kinetic. As a result, the Ag2S/Bi4TaO8Cl oriented heterojunction exhibits significantly enhanced visible light driven photocatalytic redox ability for tetracycline oxidation and hexavalent chromium reduction than those of single component and the traditional random/mixed heterojunctions. This study could provide a deeper insight into the synergistic effects of multi-IEF modulation and interfacial chemical bond bridging on optimizing the photogenerated carrier behaviors.

Deep learning-based diagnosis of disease activity in patients with Graves' orbitopathy using orbital SPECT/CT.

PURPOSE: Orbital [99mTc]TcDTPA orbital single-photon emission computed tomography (SPECT)/CT is an important method for assessing inflammatory activity in patients with Graves' orbitopathy (GO). However, interpreting the results requires substantial physician workload. We aim to propose an automated method called GO-Net to detect inflammatory activity in patients with GO. MATERIALS AND METHODS: GO-Net had two stages: (1) a semantic V-Net segmentation network (SV-Net) that extracts extraocular muscles (EOMs) in orbital CT images and (2) a convolutional neural network (CNN) that uses SPECT/CT images and the segmentation results to classify inflammatory activity. A total of 956 eyes from 478 patients with GO (active: 475; inactive: 481) at Xiangya Hospital of Central South University were investigated. For the segmentation task, five-fold cross-validation with 194 eyes was used for training and internal validation. For the classification task, 80% of the eye data were used for training and internal fivefold cross-validation, and the remaining 20% of the eye data were used for testing. The EOM regions of interest (ROIs) were manually drawn by two readers and reviewed by an experienced physician as ground truth for segmentation GO activity was diagnosed according to clinical activity scores (CASs) and the SPECT/CT images. Furthermore, results are interpreted and visualized using gradient-weighted class activation mapping (Grad-CAM). RESULTS: The GO-Net model combining CT, SPECT, and EOM masks achieved a sensitivity of 84.63%, a specificity of 83.87%, and an area under the receiver operating curve (AUC) of 0.89 (p < 0.01) on the test set for distinguishing active and inactive GO. Compared with the CT-only model, the GO-Net model showed superior diagnostic performance. Moreover, Grad-CAM demonstrated that the GO-Net model placed focus on the GO-active regions. For EOM segmentation, our segmentation model achieved a mean intersection over union (IOU) of 0.82. CONCLUSION: The proposed Go-Net model accurately detected GO activity and has great potential in the diagnosis of GO.

Case Report: A case of hepatocellular carcinoma with aberrant right hepatic artery treated with transarterial chemoembolization and infusion chemotherapy separately to bilobar lesion combining with systemic therapies and sequential hepatectomy.

Background: Hepatocellular carcinoma (HCC) with a dismal prognosis is the second most deadly malignancy globally. Surgery is believed to be a curative approach. Nevertheless, there is still a considerable probability of postoperative recurrence. Most patients present in advanced stages with a surgically and oncologically unresectable disease. Systemic medicines are increasingly important to downstage the disease and further improve survival. Case summary: A 67-year-old Chinese man with uncontrolled hepatitis B was discovered to have liver masses with abnormal serum vitamin K absence or antagonist-II (PIVKA-II) level during checkup for upper abdominal discomfort. Abdominal multiphase computerized tomography (CT) and gadoxetate disodium-enhanced magnetic resonance imaging (MRI) showed the bulky bilobar HCCs of Barcelona Clinic Liver Cancer stage B and China Liver Cancer Staging stage IIa. Furthermore, the aberrant right hepatic artery (RHA) originates from the superior mesenteric artery. Due to the location being adjacent to important vasculatures and massive size of the right-sided lesion, curative resection appears to be challenging. To achieve a favorable surgical margin, repeated hepatic arterial infusion chemotherapy (HAIC) was adopted through the variant RHA, while transarterial chemoembolization (TACE) was delivered to the left lobe to arrest tumor growth. Furthermore, sintilimab plus lenvatinib served as the sequential systemic therapy. After 5 months of conversion treatment, the partial response with a decreased serum PIVKA-II level was attained. The R0 hepatectomy was then performed without postoperative complications. The immunohistochemistry and next-generation sequencing results suggested that the two-side HCCs existing tumor heterogeneity were not completely consistent. The patient continues to be without evidence of disease. Conclusion: Our case highlights a favorable outcome in a man with bilobar bulky HCC after undergoing the comprehensive therapeutic schedule that includes personalized intervention and systemic drug therapy. In terms of conversion therapy, our case provides a secure and practical reference for managing unresectable bilobar HCC coexisting with the aberrant hepatic artery.

A new method incorporating deep learning with shape priors for left ventricular segmentation in myocardial perfusion SPECT images.

Accurate segmentation of the left ventricle (LV) is crucial for evaluating myocardial perfusion SPECT (MPS) and assessing LV functions. In this study, a novel method combining deep learning with shape priors was developed and validated to extract the LV myocardium and automatically measure LV functional parameters. The method integrates a three-dimensional (3D) V-Net with a shape deformation module that incorporates shape priors generated by a dynamic programming (DP) algorithm to guide its output during training. A retrospective analysis was performed on an MPS dataset comprising 31 subjects without or with mild ischemia, 32 subjects with moderate ischemia, and 12 subjects with severe ischemia. Myocardial contours were manually annotated as the ground truth. A 5-fold stratified cross-validation was used to train and validate the models. The clinical performance was evaluated by measuring LV end-systolic volume (ESV), end-diastolic volume (EDV), left ventricular ejection fraction (LVEF), and scar burden from the extracted myocardial contours. There were excellent agreements between segmentation results by our proposed model and those from the ground truth, with a Dice similarity coefficient (DSC) of 0.9573 ± 0.0244, 0.9821 ± 0.0137, and 0.9903 ± 0.0041, as well as Hausdorff distances (HD) of 6.7529 ± 2.7334 mm, 7.2507 ± 3.1952 mm, and 7.6121 ± 3.0134 mm in extracting the LV endocardium, myocardium, and epicardium, respectively. Furthermore, the correlation coefficients between LVEF, ESV, EDV, stress scar burden, and rest scar burden measured from our model results and the ground truth were 0.92, 0.958, 0.952, 0.972, and 0.958, respectively. The proposed method achieved a high accuracy in extracting LV myocardial contours and assessing LV functions.

Photocatalytic Ketyl Radical Initiated Cketyl -Csp2 /Csp3 Coupling on ZnIn2 S4.

Visible-light-driven C-C bond formation utilizing ketyl radical (Cketyl ) species has attracted increasing attention recently, as it provides a direct route for the synthesis of complex molecules. However, the most-developed homogeneous photocatalytic systems for the generation and utilization of ketyl radicals usually entail noble metal-based (e. g., Ru and Ir) photosensitizers, which suffer from not only high cost but also potential degradation and hence pose challenges in product separation and purification. In contrast, readily accessible, inexpensive, and recyclable semiconductors represent a class of attractive and alternative photocatalysts but remain much less explored for photocatalytic ketyl radical initiated C-C bond formation. This work demonstrates that a wide range of industrially important chemicals, including substituted chromanes and tertiary alcohols, can be produced on ZnIn2 S4 under visible light irradiation through intramolecular cyclization (Cketyl -Csp2 ) and intermolecular cross-coupling (Cketyl -Csp3 ) reactions, respectively, using ketyl radicals. A suite of experimental studies aided by computational investigation were carried out to shed light on the mechanistic insights of these two types of ketyl radical initiated C-C coupling reactions on ZnIn2 S4 .