Search

Dental anatomy education for dental technology students should be developed in alignment with digital dental laboratory practices. We hypothesized that a virtually assisted sketching-based dental anatomy teaching module could improve students' acquisition of skills essential for digital restoration design. The second-year dental technology curriculum included a novel virtual technology-assisted sketching-based module for dental anatomy education. Pre- and post-course assessments evaluated students' skill sets and knowledge bases. Computer-aided design (CAD) scores were analyzed after one year to assess how the skills students developed through this module impacted their subsequent CAD performance. Participants who undertook the dental sketching-based teaching module demonstrated significantly improved theoretical knowledge of dental anatomy, dental aesthetic perception, and spatial reasoning skills. A partial least squares structural equation model indicated that the positive effects of this module on subsequent CAD performance were indirectly mediated by dental aesthetic perception, spatial reasoning, and practice time. A virtually assisted sketching-based dental anatomy teaching module significantly improved students' acquisition of skills and knowledge and positively mediated dental technology students' CAD performance.

Abstract Hand, foot, and mouth disease (HFMD) is a prevalent acute infectious disease caused by enteroviruses, presenting substantial public health challenges in Shanghai, especially among children. The dynamic nature of HFMD’s etiology necessitates an ongoing evaluation of its epidemiological and virological trends to inform effective control strategies. This study aims to investigate the epidemiological patterns and viral evolution of HFMD in Fengxian District, Shanghai, China, with a focus on shifts in predominant viral strains over a 14-year period. We conducted a retrospective analysis of HFMD cases reported to the National Notifiable Disease Reporting System in Fengxian District from January 1, 2009 to December 31, 2022. Epidemiological trends, strain prevalence, and demographic impacts were assessed. A total of 27,272 HFMD cases were documented during the study period, with incidence showing pronounced seasonal fluctuations—peaking in spring and summer and a lesser peak in autumn. The disease incidence demonstrated significant positive correlations with several meteorological variables: daily average temperature (r = 0.30, P

BackgroundLarge language models (LLMs) have the potential to enhance clinical flow and improve medical education, but they encounter challenges related to specialized knowledge in ophthalmology. ObjectiveThis study aims to enhance ophthalmic knowledge by refining a general LLM into an ophthalmology-specialized assistant for patient inquiries and medical education. MethodsWe transformed Llama2 into an ophthalmology-specialized LLM, termed EyeGPT, through the following 3 strategies: prompt engineering for role-playing, fine-tuning with publicly available data sets filtered for eye-specific terminology (83,919 samples), and retrieval-augmented generation leveraging a medical database and 14 ophthalmology textbooks. The efficacy of various EyeGPT variants was evaluated by 4 board-certified ophthalmologists through comprehensive use of 120 diverse category questions in both simple and complex question-answering scenarios. The performance of the best EyeGPT model was then compared with that of the unassisted human physician group and the EyeGPT+human group. We proposed 4 metrics for assessment: accuracy, understandability, trustworthiness, and empathy. The proportion of hallucinations was also reported. ResultsThe best fine-tuned model significantly outperformed the original Llama2 model at providing informed advice (mean 9.30, SD 4.42 vs mean 13.79, SD 5.70; P

The increasing effects of climate change have prompted the initiation of various programs aimed at achieving carbon neutrality and environmental sustainability. Tourism, through activities such as air travel and hotel stay, significantly contributes to global warming. This study examines the relationship between carbon emissions and tourism in China, using data from 1990 to 2022, and applies the Autoregressive Distributed Lag (ARDL) approach to estimate both long-run and short-run coefficients. The results indicate that tourism exacerbates the challenges China faces in achieving carbon neutrality, with long-term carbon emissions being positively correlated with the number of travelers, fossil fuel energy consumption, economic growth, financial development, gross fixed capital formation, and population growth. However, a negative correlation is observed between carbon emissions and the use of renewable energy. These findings are further validated through Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegration Regression (CCR) techniques. The study suggests that enhancing the use of renewable energy is crucial for developing sustainable tourism practices and aiding China in its efforts to reach carbon neutrality.

In order to improve the recognition accuracy of radar targets and the recognition performance under incomplete angular domain data, a high resolution range profile (HRRP) recognition algorithm based on time series forest is proposed. The basic principle of time series forest algorithm and the basic steps of HRRP target recognition are introduced in detail. The experimental results of measured HRRP data show that compared with k-nearest neighbors(KNN), support vector machine(SVM), random forest(RF), convolutional neural network(CNN), long short-term memory(LSTM) and other classical target recognition algorithms, the proposed algorithm has better recognition performance and better angular domain promotion ability. Under the condition of training only 1/2 and 1/3 angular domain data, the average recognition rate of the full angular domain data is better than 85%, which is an average increase of 5.2% compared with the above method.

Abstract Fundus fluorescein angiography (FFA) is a crucial diagnostic tool for chorioretinal diseases, but its interpretation requires significant expertise and time. Prior studies have used Artificial Intelligence (AI)-based systems to assist FFA interpretation, but these systems lack user interaction and comprehensive evaluation by ophthalmologists. Here, we used large language models (LLMs) to develop an automated interpretation pipeline for both report generation and medical question-answering (QA) for FFA images. The pipeline comprises two parts: an image-text alignment module (Bootstrapping Language-Image Pre-training) for report generation and an LLM (Llama 2) for interactive QA. The model was developed using 654,343 FFA images with 9392 reports. It was evaluated both automatically, using language-based and classification-based metrics, and manually by three experienced ophthalmologists. The automatic evaluation of the generated reports demonstrated that the system can generate coherent and comprehensible free-text reports, achieving a BERTScore of 0.70 and F1 scores ranging from 0.64 to 0.82 for detecting top-5 retinal conditions. The manual evaluation revealed acceptable accuracy (68.3%, Kappa 0.746) and completeness (62.3%, Kappa 0.739) of the generated reports. The generated free-form answers were evaluated manually, with the majority meeting the ophthalmologists’ criteria (error-free: 70.7%, complete: 84.0%, harmless: 93.7%, satisfied: 65.3%, Kappa: 0.762–0.834). This study introduces an innovative framework that combines multi-modal transformers and LLMs, enhancing ophthalmic image interpretation, and facilitating interactive communications during medical consultation.

Abstract With the development of deep learning, a higher level of perception of the environment such as the semantic level can be achieved in the simultaneous localization and mapping (SLAM) domain. However, previous works did not achieve a natural-language level of perception. Therefore, LP-SLAM (Language-Perceptive RGB-D SLAM) is proposed that leverages large language models (LLMs). The texts in the scene can be detected by scene text recognition (STR) and mapped as landmarks with a task-driven selection. A text error correction chain (TECC) is designed with a similarity classification method, a two-stage memory strategy, and a text clustering method. The proposed architecture is designed to deal with the mis-detection and mis-recognition cases of STR and to provide accurate text information to the framework. The proposed framework takes input images and generates a 3D map with sparse point cloud and task-related texts. Finally, a natural user interface (NUI) is designed based on the constructed map and LLM, which gives position instructions based on users’ natural queries. The experimental results validated the proposed TECC design and the overall framework. We publish the virtual dataset with ground truth, as well as the source code for further research. https://github.com/GroupOfLPSLAM/LP_SLAM .

Abstract Age-related macular degeneration (AMD) is the leading cause of central vision impairment among the elderly. Effective and accurate AMD screening tools are urgently needed. Indocyanine green angiography (ICGA) is a well-established technique for detecting chorioretinal diseases, but its invasive nature and potential risks impede its routine clinical application. Here, we innovatively developed a deep-learning model capable of generating realistic ICGA images from color fundus photography (CF) using generative adversarial networks (GANs) and evaluated its performance in AMD classification. The model was developed with 99,002 CF-ICGA pairs from a tertiary center. The quality of the generated ICGA images underwent objective evaluation using mean absolute error (MAE), peak signal-to-noise ratio (PSNR), structural similarity measures (SSIM), etc., and subjective evaluation by two experienced ophthalmologists. The model generated realistic early, mid and late-phase ICGA images, with SSIM spanned from 0.57 to 0.65. The subjective quality scores ranged from 1.46 to 2.74 on the five-point scale (1 refers to the real ICGA image quality, Kappa 0.79–0.84). Moreover, we assessed the application of translated ICGA images in AMD screening on an external dataset (n = 13887) by calculating area under the ROC curve (AUC) in classifying AMD. Combining generated ICGA with real CF images improved the accuracy of AMD classification with AUC increased from 0.93 to 0.97 (P

Abstract Lipid droplets (LDs) are dynamic lipid storage organelles that can be degraded by autophagy machinery to release neutral lipids, a process called lipophagy. However, specific receptors and regulation mechanisms for lipophagy remain largely unknown. Here, we identify that ATG14, the core unit of the PI3KC3-C1 complex, also targets LD and acts as an autophagic receptor that facilitates LD degradation. A negative regulator, Syntaxin18 (STX18) binds ATG14, disrupting the ATG14-ATG8 family members interactions and subverting the PI3KC3-C1 complex formation. Knockdown of STX18 activates lipophagy dependent on ATG14 not only as the core unit of PI3KC3-C1 complex but also as the autophagic receptor, resulting in the degradation of LD-associated anti-viral protein Viperin. Furthermore, coronavirus M protein binds STX18 and subverts the STX18-ATG14 interaction to induce lipophagy and degrade Viperin, facilitating virus production. Altogether, our data provide a previously undescribed mechanism for additional roles of ATG14 in lipid metabolism and virus production.

Supernumerary teats (SNTs) or nipples often emerge around the mammary line. This study performed a genome-wide selective sweep analysis (GWS) at the copy number variant (CNV) level using two selected signal calculation methods (VST and FST) to identify candidate genes associated with SNTs in goats. A total of 12,310 CNVs were identified from 37 animals and 123 CNVs, with the top 1% VST values including 84 candidate genes (CDGs). Of these CDGs, minichromosome maintenance complex component 3, ectodysplasin A receptor associated via death domain, and cullin 5 demonstrated functions closely related to mammary gland development. In addition, 123 CNVs with the top 1% FST values were annotated to 97 CDGs. 5-Hydroxytryptamine receptor 2A, CCAAT/enhancer-binding protein alpha, and the polymeric immunoglobulin receptor affect colostrum secretion through multiple signaling pathways. Two genes, namely, RNA-binding motif protein 46 and β-1,3-galactosyltransferase 5, showed a close relation to mammary gland development. Six CNVs were identified and annotated to five genes by intersecting the top 1% of candidate CNVs with both parameters. These genes include LOC102185621, LOC102190481, and UDP-glucose pyrophosphorylase 2, which potentially affect the occurrence of BC through multiple biological processes, such as cell detoxification, glycogen synthesis, and phospholipid metabolism. In conclusion, we discovered numerous genes related to mammary development and breast cancer (BC) through a GWS, which suggests the mechanism of SNTs in goats and a certain association between mammary cancer and SNTs.

Agave is a significant fiber crop in tropical regions, known for its high fiber strength. Lignin is closely associated with fiber strength, and phenylalanine ammonia-lyase (PAL) serves as the initial enzyme in biosynthesis of lignin. Hence, it is of considerable significance to study the genes of PAL family to analyze the characteristics and mechanism of sisal fiber development. In this research, we conducted a transcriptomic analysis of Agave schidigera, a widely recognized ornamental plant in agave. Approximately 29.85 million clean reads were acquired through Illumina sequencing. In total, 116,602 transcripts including 72,160 unigenes were assembled, and 22.06~63.56% of those unigenes were annotated in public databases. Two, six, six and six PAL genes were successfully identified and cloned from A. schidigera, A. deserti, A. tequilana and A. H11648, respectively. After phylogenetic analysis, these genes were clustered into two branches. Genes AhPLA2a and AhPLA2c exhibited higher expression levels compared to other genes but had different expression patterns. Moreover, AhPLA2a and AhPLA2c were expressed at high levels under full-nutrient, nitrogen-free and phosphorus-free stresses. Most PAL genes were induced by Phytophthora nicotianae Breda, especially AhPAL1a, AhPAL1b, AhPAL2b and AhPAL2c. This research is the first work to present a de novo transcriptome dataset for A. schidigera, enriching its bioinformation of transcripts. The cloned PAL genes and the expression analyses will form the basis of future research on lignin biosynthesis, the relationship between lignin and fiber strength, and stress resistance in Agave species.

Introduction Transcatheter aortic valve replacement (TAVR) has become an important treatment in patients with aortic valve disease with the continuous advancement of technology and the improvement of outcomes. However, TAVR-related complications still increase patient morbidity and mortality. Remote ischaemic preconditioning (RIPC) is a simple procedure that provides perioperative protection for many vital organs. However, the efficiency of RIPC on TAVR remains unclear based on inconsistent conclusions from different clinical studies. Therefore, we will perform a protocol for a systematic review and meta-analysis to identify the efficiency of RIPC on TAVR.Methods and analysis English databases (PubMed, Web of Science, Ovid Medline, Embase and Cochrane Library), Chinese electronic databases (Wanfang Database, VIP Database and China National Knowledge Infrastructure) and trial registry databases will be searched from inception to December 2023 to identify randomised controlled trials of RIPC on TAVR. We will calculate mean differences or standardised mean differences with 95% CIs for continuous data, and the risk ratio (RR) with 95% CIs for dichotomous data by Review Manager version 5.4. Fixed-effects model or random-effects model will be used according to the degree of statistical heterogeneity assessed by the I-square test. We will evaluate the risk of bias using the Cochrane risk-of-bias tool 2 and assess the evidence quality of each outcome by the Grading of Recommendations Assessment, Development and Evaluation. The robustness of outcomes will be evaluated by trial sequential analysis. In addition, we will evaluate the publication bias of outcomes by Funnel plots and Egger’s regression test.Ethics and dissemination Ethical approval was not required for this systematic review protocol. The results will be disseminated through peer-reviewed publications.PROSPERO registration number CRD42023462926

Background: Fundus Autofluorescence (FAF) is a valuable imaging technique used to assess metabolic alterations in the retinal pigment epithelium (RPE) associated with various age-related and disease-related changes. The practical uses of FAF are ever-growing. This study aimed to evaluate the effectiveness of a generative deep learning (DL) model in translating color fundus (CF) images into synthetic FAF images and explore its potential for enhancing screening of age-related macular degeneration (AMD). Methods: A generative adversarial network (GAN) model was trained on pairs of CF and FAF images to generate synthetic FAF images. The quality of synthesized FAF images was assessed objectively by common generation metrics. Additionally, the clinical effectiveness of the generated FAF images in AMD classification was evaluated by measuring the area under the curve (AUC), using the LabelMe dataset. Results: A total of 8410 FAF images from 2586 patients were analyzed. The synthesized FAF images exhibited an impressive objectively assessed quality, achieving a multi-scale structural similarity index (MS-SSIM) of 0.67. When evaluated on the LabelMe dataset, the combination of generated FAF images and CF images resulted in a noteworthy improvement in AMD classification accuracy, with the AUC increasing from 0.931 to 0.968. Conclusions: This study presents the first attempt to use a generative deep learning model to create authentic and high-quality FAF images from CF images. The incorporation of the translated FAF images on top of CF images improved the accuracy of AMD classification. Overall, this study presents a promising approach to enhance large-scale AMD screening.

Chouioia cunea are known to exploit in varying degrees a wide range of lepidopteran species and its offspring development may vary with host species. This study examined its preimaginal development and larval gut microbiota in parasitizing five folivorous lepidopteran hosts including Hyphantria cunea (referred to thereafter as CcHc), Antherea pernyi (CcAp), Helicoverpa armigera (CcHa), Spodoptera exigua (CcSe), and Spodoptera frugiperda (CcSf). Though rates of parasitism and offspring eclosion did not change with host species, the development period and number of offspring eclosed varied with hosts, with the shortest period in CcSf and the highest number from CcAp. For offspring larval gut microbiota, though phylum Proteobacteria was dominant for attacking CcAp, Firmicutes was so for the other hosts. All microbial genera except Enterococcus were less abundant for CcSf than the other hosts. The database-based predictions indicate a significant positive correlation between Cutibacterium and Aureimonas with the relative number of wasp emergence, while Blastomonas exhibits a strong positive association with the developmental period. Our results imply the potential relevance of the gut microbial community in offspring larvae to host species attacked by C. cunea.

Shanghai as an international metropolis is representative of modern urban agriculture in China, so it is of great significance to analyse the pesticide residue in vegetables grown in Shanghai. This study investigated the residue of 68 commonly used pesticides (divided into insecticides, fungicides, herbicides and plant growth regulators) in 7028 vegetable samples in Shanghai from 2018 to 2021, and estimated the dietary intake risk of these pesticides. These samples were divided into 6 categories. A total of 29.21% of vegetable samples had pesticide residues, and 0.47% of samples exceeded the maximum residue limits (MRLs) set by the national food safety standard of China. Leafy vegetables had the highest detection rate of pesticide residues (32.9%), multiple detection rate (12.2%), pesticide residue concentration (35.7 mg/kg), and the number of samples exceeding the MRL (30). There were 36 out of 68 pesticides detected in vegetables, and the top 3 were dimethomorph, propamocarb and acetamiprid. The target hazard quotient (THQ) and hazard index (HI) of these noticeablepesticides were all less than 1, illustrating that there may be no obvious health hazard for residents exposed to the pesticide levels. This study can promote the green development of the pesticide industry and provide important reference data for the monitoring of pesticide residues and their hazards under modern urban agriculture.

Abstract Along the development of ionic porous organic polymers, simple and efficient synthetic methods are actively pursued. Herein, the Debus–Radziszewski reaction is applied to synthesize ionic conjugated microporous polymers (iCMPs) in one step. A series of imidazolium‐linked iCMP‐X (X = 1, 2, 3) are developed for CO2 sorption and in situ conversion with epoxide into cyclic carbonates. The as‐synthesized iCMPs are characterized in detail by scanning electron microscope, solid‐state nuclear magnetic resonance, X‐ray photoelectron spectroscopy, X‐ray diffraction analysis, N2/CO2 sorption, and more. Among all synthesized iCMPs, iCMP‐1 possesses the highest specific surface area and in turn the strongest CO2 sorption capacity. Moreover, through a simple anion ion exchange reaction with halide, iCMP‐1 is transformed to iCMP‐1@Cl that embodies significant catalytic capability for converting CO2 into cyclic carbonates.

Introduction Deep neck space abscesses (DNAs) are serious surgical emergencies, associated with life-threatening complications. Surgical incision and drainage combined with antibiotics is the main treatment for DNAs, but drawbacks still exist. Ultrasound-guided puncture drainage is an alternative treatment for some DNAs with limited clinical evidence. Hence, the optimal drainage technique for the treatment of DNAs remains unclear. Therefore, we will perform a protocol for a systematic review and meta-analysis to identify the efficacy of ultrasound-guided puncture drainage for DNAs.Methods and analysis PubMed, Ovid Medline, Cochrane Library, Embase, Web of Science, China National Knowledge Infrastructure, Wanfang database, VIP database and trial registry databases will be searched from inception to September 2023 to identify randomised controlled trials of patients diagnosed with DNAs accepting ultrasound-guided puncture drainage. The primary outcome will be the length of hospital stay. The secondary outcomes will be the cure rate, incidence of retreatment, complications and overall cost to the healthcare system. Fixed-effects or random-effects model will be used according to the statistical heterogeneity. Mean differences or standardised mean differences with 95% CIs for continuous data and risk ratio (RR) with 95% CIs for dichotomous data. The Cochrane risk-of-bias tool 2, Grading of Recommendations Assessment, Development and Evaluation (GRADE) and trial sequential analysis will be conducted to evaluate the evidence quality and control the random errors. Funnel plots and Egger’s regression test will be performed to evaluate publication bias.Ethics and dissemination Ethical approval was not required for this systematic review protocol. The results will be disseminated through peer-reviewed publications.PROSPERO registration number CRD42023441031.

BackgroundAlthough well-documented, the causal relationships between diet-derived circulating antioxidants, oxidative stress, and osteoarthritis (OA) are equivocal. The objective of this study is to employ two-sample Mendelian randomization (MR) to investigate possible causal relationships among dietary-derived circulating antioxidants, oxidative stress damage indicators, and OA risk.MethodsSingle-nucleotide polymorphisms for diet-derived circulating antioxidants (ascorbate, β-carotene, lycopene, retinol, and α-and γ-tocopherol), assessed as absolute levels and metabolites, as well as oxidative stress injury biomarkers (GSH, GPX, CAT, SOD, albumin, and total bilirubin), were retrieved from the published data and were used as genetic instrumental variables. Summary statistics for gene–OA associations were obtained from publicly available and two relatively large-scale GWAS meta-analyses to date. The inverse-variance weighting method was utilized as the primary MR analysis. Moreover, multivariable MR was used to determine if mediators (BMI and smoking) causally mediated any connection. Furthermore, for each exposure, MR analyses were conducted per outcome database and then meta-analyzed.ResultsGenetically predicted absolute retinol level was causally associated with hip OA risk [odds ratios (ORs) = 0.40, 95% confidence interval (CI) = 0.24–0.68, FDR-corrected p = 0.042]. Moreover, genetically predicted albumin level was causally associated with total OA risk (OR = 0.80, 95% CI = 0.75–0.86, FDR-corrected p = 2.20E-11), as well as the risk of hip OA (OR = 0.75, 95% CI = 0.68–0.84, FDR-corrected p = 1.38E-06) and knee OA (OR = 0.82, 95% CI = 0.76–0.89, FDR-corrected p = 4.49E-06). In addition, MVMR confirmed that the effect of albumin on hip OA is independent of smoking initiation, alcoholic drinks per week, and moderate-to-vigorous physical activity levels but may be influenced by BMI.ConclusionEvidence from our study supports a potentially protective effect of high levels of retinol and albumin on OA risk.

As heavy metals in soil could enrich in biomass and pose health risk to human, it is vital to monitor their contaminations to ensure qualified agricultural production. In this study, we collected >4000 soil samples from agricultural fields in Shanghai during 2010∼2020, and unveiled heavy metal contamination status in this metropolitan. We found that although Shanghai has a long industrialization history, the heavy metal levels in agricultural soil are within safe ranges according to national standard. Specifically, the median levels of Cd, Hg, As, Pb, Cr and Cu are 0.11, 0.13, 7.47, 23.80, 41.00 and 28.30 mg/kg, respectively, which are as good as, or even better than national averages. However, there are spatial and temporal heterogeneities for heavy metal contaminations in Shanghai. For example, the levels of Cd, Hg and Cr are relatively higher in some districts with high industry density, which should be further monitored in the future. Moreover, while the levels for Cd, Cr and Pb have decreased, the level for Hg has mildly increased during this period which needs counteractive measures. Correlation analysis of heavy metal levels and soil fertility parameters suggested overuse of fertilizers may be related to heavy metal contamination in some regions. In summary, our study present by far the largest and most comprehensive landscape of heavy metal contamination in Shanghai agricultural soil, which will be useful for future policy-design and land use planning to ensure safe agricultural production.

Purpose: To develop and validate a deep learning model that can transform color fundus (CF) photography into corresponding venous and late-phase fundus fluorescein angiography (FFA) images. Design: Cross-sectional study. Participants: We included 51 370 CF-venous FFA pairs and 14 644 CF-late FFA pairs from 4438 patients for model development. External testing involved 50 eyes with CF-FFA pairs and 2 public datasets for diabetic retinopathy (DR) classification, with 86 952 CF from EyePACs, and 1744 CF from MESSIDOR2. Methods: We trained a deep-learning model to transform CF into corresponding venous and late-phase FFA images. The translated FFA images’ quality was evaluated quantitatively on the internal test set and subjectively on 100 eyes with CF-FFA paired images (50 from external), based on the realisticity of the global image, anatomical landmarks (macula, optic disc, and vessels), and lesions. Moreover, we validated the clinical utility of the translated FFA for classifying 5-class DR and diabetic macular edema (DME) in the EyePACs and MESSIDOR2 datasets. Main Outcome Measures: Image generation was quantitatively assessed by structural similarity measures (SSIM), and subjectively by 2 clinical experts on a 5-point scale (1 refers real FFA); intragrader agreement was assessed by kappa. The DR classification accuracy was assessed by area under the receiver operating characteristic curve. Results: The SSIM of the translated FFA images were > 0.6, and the subjective quality scores ranged from 1.37 to 2.60. Both experts reported similar quality scores with substantial agreement (all kappas > 0.8). Adding the generated FFA on top of CF improved DR classification in the EyePACs and MESSIDOR2 datasets, with the area under the receiver operating characteristic curve increased from 0.912 to 0.939 on the EyePACs dataset and from 0.952 to 0.972 on the MESSIDOR2 dataset. The DME area under the receiver operating characteristic curve also increased from 0.927 to 0.974 in the MESSIDOR2 dataset. Conclusions: Our CF-to-FFA framework produced realistic FFA images. Moreover, adding the translated FFA images on top of CF improved the accuracy of DR screening. These results suggest that CF-to-FFA translation could be used as a surrogate method when FFA examination is not feasible and as a simple add-on to improve DR screening. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Training a neural network to reconstruct images from time-series waveforms obtained from fiber optic probes not only yields high-quality, content-aware images but can also acquire different types of images from lower quality training images. Image reconstruction, as an inverse problem, involves using collected signals and system models to retrieve desired images, encountering mathematical challenges like distortion and degradation. In this paper, we introduce REcaNet, a multi-mode fiber image restoration model based on an enhanced residual convolutional neural network (CNN). The network employs a symmetrical architecture that downscales the image before upscaling it for restoration, and it reconstructs the high-level semantic feature map generated by the encoder to the original image resolution. Additionally, we incorporate weight initialization, attention mechanisms, and residual connections to enhance the final restored feature map with more low-dimensional features and promote fusion of features from distinct layers. The algorithm performs well on three datasets collected by multi-mode fibers, namely Minist, Clothes, and Omiglot. Among them, various indicators such as SSIM have been significantly improved.

Aim of the Study: Brachial plexus block (BPB) is widely used for patients undergoing upper limb surgeries. Ropivacaine is the most commonly used local anesthetic for BPB. This study aimed to identify the optimal ropivacaine concentration for BPB in adult patients undergoing upper limb surgeries.Materials and Methods: PubMed, Embase, the Cochrane Library, and Web of Science were searched to identify randomized controlled trials (RCTs) that compared the effects of different concentrations of ropivacaine for BPB in adult patients undergoing upper limb surgeries. The primary outcomes were the onset time of sensory and motor block. RevMan 5.4 software was used for analysis. The GRADE approach was used to assess evidence quality.Results: Nine studies involving 504 patients were included. Compared to 0.5% ropivacaine, 0.75% ropivacaine shortened the onset time of sensory (WMD, −2.54; 95% CI; −4.84 to −0.24;

Efficient and selective gold recovery from electronic waste is highly demanded. Here, authors demonstrate the application of a porous organic polycarbene adsorbent with up to 2.09 g/g gold-capturing capability.

Abstract Background The lack of a satisfactory strategy for postoperative pain management significantly impairs the quality of life for many patients. However, existing nanoplatforms cannot provide a longer duration of nerve blockage with intensity-adjustable characteristics under imaging guidance for clinical applications. Results To overcome this challenge, we proposed a biocompatible nanoplatform that enables high-definition ultrasound imaging-guided, intensity-adjustable, and long-lasting analgesia in a postoperative pain management model in awake mice. The nanoplatform was constructed by incorporating perfluoropentane and levobupivacaine with red blood cell membranes decorated liposomes. The fabricated nanoplatform can achieve gas-producing and can finely escape from immune surveillance in vivo to maximize the anesthetic effect. The analgesia effect was assessed from both motor reactions and pain-related histological markers. The findings demonstrated that the duration of intensity-adjustable analgesia in our platform is more than 20 times longer than free levobupivacaine injection with pain relief for around 3 days straight. Moreover, the pain relief was strengthened by repeatable ultrasound irradiation to effectively manage postoperative pain in an intensity-adjustable manner. No apparent systemic and local tissue injury was detected under different treatments. Conclusion Our results suggest that nanoplatform can provide an effective strategy for ultrasound imaging-guided intensity-adjustable pain management with prolonged analgesia duration and show considerable transformation prospects.

The electrochemical behavior of thermally sprayed Zn–Cu–Ti coating corroded in 3.5 wt% NaCl neutral salt spray for different days was investigated by electrochemical measurements. Electrochemical investigation shows that pitting corrosion occurs on the coating. Sacrificial anode protection and corrosion product protection play a dominant role. Coating corrosion can be divided into five stages: dissolution of surface oxides, deposition of corrosion products, stable dissolution of the coating, formation and development of occluded cell corrosion, and accelerated corrosion stage. The degradation mechanism and the role of galvanic protection of coating have been discussed by a proposed corrosion model.

Abstract COVID-19 raises attention to epidemic transmission in various places. This study analyzes the transmission risks associated with human activity places at multiple scales, including different types of settlements and eleven types of specific establishments (restaurants, bars, etc.), using COVID-19 data in 906 urban areas across four continents. Through a difference-in-difference approach, we identify the causal effects of activities at various places on epidemic transmission. We find that at the micro-scale, though the transmission risks at different establishments differ across countries, sports, entertainment, and catering establishments are generally more infectious. At the macro-scale, contradicting common beliefs, it is consistent across countries that transmission does not increase with settlement size and density. It is also consistent that specific establishments play a lesser role in transmission in larger settlements, suggesting more transmission happening elsewhere. These findings contribute to building a system of knowledge on the linkage between places, human activities, and disease transmission.

Currently, Chinese herbal feed additives (CHFA) are commonly utilized in domestic pig farms. However, their impact on the sperm quality and reproductive capacity of imported breeding boars has yet to be thoroughly explored. In this study, the effect of CHFA on the sperm quality and reproductive capacity of the imported Duroc boars was investigated. Sixteen boars were randomly divided into control group and experimental (CHFA treated) group and fed normal or CHFA-levels containing diets, respectively. The sperm quality and reproductive hormone levels were periodically tested, and the reproductive capacity with breeding sows were evaluated. The results showed that the CHFA treated group boars significantly improved sperm volume, sperm concentration, and motility and reduced the sperm abnormalities. Furthermore, the serum levels of reproductive hormone such as follicle-stimulating hormone (FSH), luteinizing hormone (LH), and testosterone (T) in the CHFA treated group were significantly higher than those in the control group. Although there was no significant difference in the initial birth weight of piglets between the two groups, the CHFA treated group had a significantly higher average number of piglets born, the average number of piglets born alive, the number of piglets weaned at 28 days, and the weaning weight compared to the control group. These findings suggest that CHFA can significantly improve the sperm quality of breeding boars and enhance their reproductive hormone levels as well as the reproductive capacity, providing direct evidence for the further application of CHFA in the management of breeding boars in China.

Genipin is a natural crosslinker that improves the functional properties of proteins by modifying its structures. This study aimed to investigate the effects of sonication on the emulsifying properties of different genipin concentration-induced myofibrillar protein (MP) cross-linking. The structural characteristics, solubility, emulsifying properties, and rheological properties of genipin-induced MP crosslinking without sonication (Native), sonication before crosslinking (UMP), and sonication after crosslinking (MPU) treatments were determined, and the interaction between genipin and MP were estimated by molecular docking. The results demonstrated that hydrogen bond might be the main forces for genipin binding to the MP, and 0.5 μM/mg genipin was a desirable concentration for protein cross-linking to improve MP emulsion stability. Ultrasound treatment before and after crosslinking were better than Native treatment to improve the emulsifying stability index (ESI) of MP. Among the three treatment groups at the 0.5 μM/mg genipin treatment, the MPU treatment group showed the smallest size, most uniform protein particle distribution, and the highest ESI (59.89%). Additionally, the highest α-helix (41.96%) in the MPU + G5 group may be conducive to the formation of a stable and multilayer oil–water interface. Furthermore, the free groups, solubility, and protein exposure extent of the MPU groups were higher than those of UMP and Native groups. Therefore, this work suggests that the treatment of cross-linking followed by ultrasound (MPU) could be a desirable approach for improving the emulsifying stability of MP.

The significant improvement of decolorization and disinfection technologies has been a hotspot in wastewater reutilization. In this study, we realized a novel construction of K-doped nano-ZnO and borneol based hydrogel composite material (K-ZnO/B-hydrogel) by low-temperature in situ sol–gel growth. The techniques such as fourier transform infrared (FTIR), X-ray diffraction (XRD), x-ray photoelectron spectroscopy (XPS), scanning electron microscope (SEM) and X-ray energy dispersive spectroscopy (EDS) were applied to recognize the synthesized hydrogel. The results revealed that K-doped ZnO nanoparticles had been uniformly decorated onto the B-hydrogel. Ultraviolet-visible (UV–vis) absorption spectra showed that impurity doping of potassium element into ZnO could reduce the band gap, improving the visible light absorption efficiency. Under LED illumination, the photodegrading rate of K-ZnO/B-hydrogel was approximately 2.3 times greater than that of K-ZnO/B-hydrogel on methylene blue (MB) removal. Remarkably, aside from CO _2 and H _2 O, no by-products were generated during the photodegradation process. In addition, the antimicrobial activities against Escherichia coli ( E. coli ) and Staphylococcus aureus ( S. aureus ) of K-ZnO/B-hydrogel achieved up to 99.9%, which were at least 1.5 times higher than K-ZnO/B-hydrogel. This composite will push ahead with a closed-loop wastewater treatment system for dye and pathogenic microorganism disposal, which combines the excellent adsorption ability of hydrogel and the outstanding photocatalytic ability of ZnO nanoparticles with easy sample handling and separation, and help to eliminate secondary pollution.

Bio-based polyurethanes are novel material with potential advantages for sustainable development, and their development play significant roles in promoting sustainability. Curcumin, a natural monomer, possesses high biological activity and features a symmetrical chemical structure with various functional groups such as phenolic hydroxyl, carbonyl and benzene ring. The presence of hydroxyl groups in the structure of curcumin provides essential conditions for its involvement in polyurethane synthesis. This review article provides an overview of the applications of curcumin as a chain extender, crosslinking agent and end-capper in polyurethanes, as well as its effects on the chemical structure, mechanical properties, and chemical stability of polyurethanes. Furthermore, the functional applications of curcumin-based polyurethanes in various fields such as medicine, food packaging, and coatings are discussed. Finally, considering the current research status and inherent properties of curcumin, the future prospects of curcumin-based polyurethanes are contemplated.

In the preparation of plasma electrolytic oxidation (PEO) coating, the rapid heating of freely-happened electron avalanche under traditional discharge (TD) mode inevitably results in a strong eruption of electric breakdown melt. The PEO coating is loose and invariably composed of a very thin inner dense layer and an outer loose layer, as a result of which its properties and application have been limited greatly. In this work, for purpose of weakening the eruption of breakdown melt, thickening the inner dense layer, densifying the outer loose layer and improving the performance of PEO coating, ordinal discharge (OD) mode of PEO coating is developed by regulating the mass ratio of MgF2 to MgO (α) and voltage in the PEO investigation on AZ61 magnesium alloy in KF-KOH electrolyte. The formation mechanism under different discharge mode, electrochemical corrosion and wear of PEO coatings are investigated. The results show that the suitable α and voltage for effective OD are 1.3 and 130 V under which the freely-happened electron avalanche in MgF2 under TD mode can be restricted by the adequate adjacent MgO. Compared with TD mode, the inner dense layer, in which the (1¯01¯) plane of MgF2 is parallel to the (111) plane of MgO at their well-knit semi-coherent interface, is thickened to 2.4∼7.2 times, the corrosion potential (Ecorr) improvement is enlarged to 3.6∼13.2 times and the corrosion current intensity (Icorr) is reduced from 10.8∼9.499 to 0.433 (10−6 A/cm2). The outer loose layer is densified and the wear rate is lessened 65.5%∼89.8% by the evident melioration in surface porosity, impedance and hardness. This work deepens the understanding about the discharge of PEO coating and provides an available OD mode for preparing excellent PEO coating.