A vascularized adipose organoid model using stromal vascular fraction cells from ruminant animals.

In vitro cell culture serves as an efficient system for studying animal cell behavior in a controlled setting. Here, we present a 3D culture model for forming ruminant adipose organoids using stromal vascular fraction cells. We describe steps for forming cell spheroids and growing them on a Matrigel-coated surface. We then detail procedures for inducing organoids to undergo angiogenesis and adipogenesis followed by capillary sprouting. This protocol can be utilized to study the interaction between blood vessels and adipocytes. For complete details on the use and execution of this protocol, please refer to Yu et al.1.

Cost-effectiveness and cost-utility of a digital technology-driven hierarchical healthcare screening pattern in China.

Utilization of digital technologies for cataract screening in primary care is a potential solution for addressing the dilemma between the growing aging population and unequally distributed resources. Here, we propose a digital technology-driven hierarchical screening (DH screening) pattern implemented in China to promote the equity and accessibility of healthcare. It consists of home-based mobile artificial intelligence (AI) screening, community-based AI diagnosis, and referral to hospitals. We utilize decision-analytic Markov models to evaluate the cost-effectiveness and cost-utility of different cataract screening strategies (no screening, telescreening, AI screening and DH screening). A simulated cohort of 100,000 individuals from age 50 is built through a total of 30 1-year Markov cycles. The primary outcomes are incremental cost-effectiveness ratio and incremental cost-utility ratio. The results show that DH screening dominates no screening, telescreening and AI screening in urban and rural China. Annual DH screening emerges as the most economically effective strategy with 341 (338 to 344) and 1326 (1312 to 1340) years of blindness avoided compared with telescreening, and 37 (35 to 39) and 140 (131 to 148) years compared with AI screening in urban and rural settings, respectively. The findings remain robust across all sensitivity analyses conducted. Here, we report that DH screening is cost-effective in urban and rural China, and the annual screening proves to be the most cost-effective option, providing an economic rationale for policymakers promoting public eye health in low- and middle-income countries.

Mental health status among children and adolescents in one-child and multichild families: a meta-analysis of comparative studies.

PURPOSE OF REVIEW: Controversy remains about the difference in mental health status among children and adolescents between one-child and multichild families in China. Thus, we conducted a meta-analysis of studies comparing mental health status between both groups and explored their potential moderating factors. RECENT FINDINGS: Totally, 113 eligible studies encompassing 237 899 participants (one-child families: 83 125; multichild families: 154 774) were included. The pooled SMD of SCL-90 total score was -0.115 [95% confidence interval (95% CI): -0.152; -0.078; I2  = 86.9%]. Specifically, children and adolescents from one-child families exhibited lower scores in terms of somatization (SMD = -0.056; 95% CI: -0.087; -0.026), obsessive-compulsive symptoms (SMD = -0.116; 95% CI: -0.154; -0.079), interpersonal sensitivity (SMD = -0.140; 95% CI: -0.171; -0.109), depression (SMD = -0.123; 95% CI: -0.159; -0.088); anxiety (SMD = -0.121; 95% CI: -0.151; -0.092); phobic anxiety (SMD = -0.124; 95% CI: -0.166; -0.081); paranoid ideation (SMD = -0.040; 95% CI: -0.070; -0.009); and psychoticism (SMD = -0.119; 95% CI: -0.148; -0.089). Study publication year was significantly associated with differences in mental health status between both groups ( P  = 0.015). SUMMARY: Children and adolescents from one-child families had better mental health status compared to those from multichild families in China. Future studies should investigate the underlying factors contributing to such mental health differences, and the potential interventions that could address these mental health problems.

Rehabilitation clinicians' use of mainstream wireless technologies in practice: a scoping review.

PURPOSE: This scoping review was conducted to understand the barriers, facilitators, and education and training needs of rehabilitation clinicians in their use of mainstream wireless technologies (MWT) to support people with disabilities and older adults. It was also conducted to understand the functional skills of clients that were targeted with MWT use. MATERIALS AND METHODS: This scoping review was reported using PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) and the Population (or Participants)/Concept/Context) framework. We searched PubMed; ProQuest to access APA PsycINFO; Web of Science Core Collection; and EBSCOhost to access Cumulated Index to Nursing and Allied Health Literature (CINAHL), Ovid MEDLINE ALL, and Education Resources Information Center (ERIC). Articles published between 2015-2022 were retrieved. RESULTS: A total of 90 articles were included. Most interventions were apps, smartphones, and tablets; were geared toward adults; and targeted motor, cognitive and speech skills. An infographic on barriers and facilitators was generated as a decision support tool for clinicians when implementing MWT. The topic, format, timing, and source of information clinicians need are also delineated. CONCLUSION: MWT such as apps, smartphones and tablets are being used by rehabilitation clinicians to address motor, cognitive, and speech skills, most commonly in adults. Clinicians voice a need for more education and training. Barriers and facilitators exist at the clinician-, technology-, client-, institution-, and policy levels.Implications For RehabilitationA total of 90 articles from 2015-2022 were included in this scoping reviewMost interventions were apps, smartphones, and tablets; were geared toward adults; and targeted motor, cognitive and speech skills.An infographic was generated as a decision support tool for clinicians when implementing mainstream wireless technologies in clinical practice.Clinicians' education and training needs with regard to mainstream wireless technologies are broad. Materials on a variety of topics, in different formats, from multiple sources are needed.This review also discusses implications of findings on policy, technology development, and future research.

BARX1 repressed FOXF1 expression and activated Wnt/ß-catenin signaling pathway to drive lung adenocarcinoma.

BACKGROUND: Underlying molecular mechanisms of BARX homeobox 1 (BARX1) in lung adenocarcinoma (LUAD) remain elusive. METHODS: Abnormally expressed genes in LUAD tissues were analyzed by RNA-sequencing. CCK-8, colony formation, transwell, and wound healing assays examined proliferation, colony formation, invasion, and migration of LUAD cells, respectively. Electrophoretic mobility shift assay and chromatin immunoprecipitation assay examined the interaction between BARX1 and Forkhead Box F1 (FOXF1). Xenograft mouse model of LUAD was constructed to monitor the growth and metastasis of tumor. RESULTS: BARX1 was upregulated, FOXF1 was downregulated in LUAD tissues and cells. There was a negative correlation between BARX1 and FOXF1 expression. BARX1 deficiency limited malignant phenotypes of LUAD cells, including proliferation, invasion, migration and EMT. In vivo, BARX1 knockdown suppressed tumor growth and metastasis in A549-drove xenograft mouse model. BARX1 interacted with FOXF1 promoter and repressed FOXF1 expression. Upregulation of BARX1 promoted the expression of Wnt5a, ß-catenin, and phosphorylated-glycogen synthase kinase-3 beta (p-GSK3ß), whereas inhibited FOXF1, p-ß-catenin, and GSK3ß in LUAD cells. BARX1 knockdown caused an opposite result. Rescue assays uncovered that FOXF1 reversed the impact of BARX1 on malignant phenotypes and Wnt/ß-catenin of LUAD cells. CONCLUSION: BARX1 repressed FOXF1 expression and activated Wnt/ß-catenin signaling pathway to drive lung adenocarcinoma.

Room-Temperature Strong Coupling of Few-Exciton in a Monolayer WS2 with Plasmon and Dispersion Deviation.

Engineering room-temperature strong coupling of few-exciton in transition-metal dichalcogenides (TMDCs) with plasmons promises to construct compact and high-performance quantum optical devices. But it remains unimplemented due to their in-plane excitons. Here, we demonstrate the strong coupling of few-exciton within 10 in monolayer WS2 with the plasmonic mode with a large tangential component of the electric field tightly trapped around the sharp corners of an Au@Ag nanocuboid, the fewest number of excitons observed in the TMDC family so far. Furthermore, we for the first time report a significant deviation with a relative difference of up to 100.6% between the spectrum and eigenlevel splitting dispersions, which increases with decreasing coupling strength. It is also shown that the coupling strength obtained by the conventional concept of both being equal to the measured spectrum splitting is markedly overestimated. Our work enriches the understanding of strong light-matter interactions at room temperature.

Spatial distribution and migration of lead and zinc and the influence of parent materials in typical paddy soils of Hunan Province, China.

This study aimed to investigate the distribution and migration characteristics of lead (Pb) and zinc (Zn) in paddy soils in Hunan Province, China. A total of 343 soil samples from 63 profiles were collected from typical regions. The concentration, spatial distribution, and migration behaviors of Pb and Zn in the paddy soils were examined. The results showed that (1) the concentration ranges of Pb and Zn in the surface layer were 17.62-114.07 mg/kg and 44.98-146.84 mg/kg, respectively. (2) The content was higher in the middle and lower reaches of the Xiangjiang River basin horizontally and exhibited shallow enrichment characteristics vertically. (3) Pb migration was weaker than Zn migration, and the parent material had the most significant influence on Pb and Zn content in the bottom soil layer. The research results will clarify the characteristics of Pb and Zn contents in paddy soils in Hunan Province, further understand the horizontal distribution and vertical migration and transformation characteristics of Pb and Zn contents in paddy soils, and provide basic data for scientific rice cultivation and safe food production.

Dietary Supplementation with Lauric Acid Improves Aerobic Endurance in Sedentary Mice via Enhancing Fat Mobilization and Glyconeogenesis.

BACKGROUND: Lauric acid (LA), a major, natural, medium-chain fatty acid, is considered an efficient energy substrate for intense exercise and in patients with long-chain fatty acid ß-oxidation disorders. However, few studies have focused on the role of LA in exercise performance and related glucolipid metabolism in vivo. OBJECTIVES: We aimed to investigate the effect of dietary supplementation with LA on exercise performance and related metabolic mechanisms. METHODS: Male C57BL/6N mice (14 wk old) were fed a basal diet or a diet containing 1% LA, and a series of exercise tests, including a high-speed treadmill test, aerobic endurance exercises, a 4-limb hanging test, and acute aerobic exercises, were performed. RESULTS: Dietary supplementation with 1.0% LA accelerated the recovery from fatigue after explosive exercise (P < 0.05) and improved aerobic endurance and muscle strength in sedentary mice (P = 0.039). Lauric acid intake not only changed muscle fatty acid profiles, including increases in C12:0 and n-6/n-3 PUFAs (P < 0.001) and reductions in C18:0, C20:4n-6, C22:6n-3, and n-3 PUFAs (P < 0.05) but also enhanced fat mobilization from adipose tissue and fatty acid oxidation in the liver, at least partly via the AMP-activated protein kinase-acetyl CoA carboxylase pathway (P < 0.05). Likewise, LA supplementation promoted liver glyconeogenesis and conserved muscular glycogen during acute aerobic exercise (P < 0.05), which was accompanied by an increase in the mitochondrial DNA copy number and Krebs cycle activity in skeletal muscle (P < 0.05). CONCLUSIONS: Dietary supplemental LA serves as an efficient energy substrate for sedentary mice to improve aerobic exercise endurance and muscle strength through regulation of glucolipid metabolism. These findings imply that LA supplementation might be a promising nutritional strategy to improve aerobic exercise performance in sedentary people.

Early Visual Deprivation Impairs Functional Development of the Visual Ventral Stream.

Purpose: To probe the dynamic alternations of neural networks in real-time visual processing after visual deprivation (VD) removal. Methods: A prospective cross-sectional study was conducted. Twenty children with a history of early binocular VD caused by congenital cataracts and 20 matched typically developing (TD) children were enrolled. The event-related potential (ERP) data were obtained via high-density electroencephalography. ERP data were analyzed based on three components (P1, N170, and P2), three test conditions (objects, human faces, and Chinese characters), and peak time and region of interest (ROI) chosen on a grand average head map collapsed from the averaged waveform of each group. Source localization and alpha power spectrum density were applied to define the functional pattern of brain areas and evaluate the attention function. Results: The VD group showed significantly lower P1 amplitudes than the TD group under all conditions in peak ROIs, which were situated in the left occipito-temporal region. For both VD and TD groups, there were strong N170 effects in the character and human face conditions in the component's peak ROIs. Furthermore, source mapping indicated that the VD group generally showed significantly lower activation in the visual cortex and ventral stream, whereas the beyond network areas (mostly frontal areas) intensively participated in functional compensation in the VD group. The VD group showed significant poststimulus alpha desynchronization in object recognition. Conclusions: Our research described the mechanisms of visual networks after early binocular VD removal. Our findings may provide a new basis for the poor visual recovery after early binocular VD removal and offer clues for visual recovery strategies.

Early detection of visual impairment in young children using a smartphone-based deep learning system.

Early detection of visual impairment is crucial but is frequently missed in young children, who are capable of only limited cooperation with standard vision tests. Although certain features of visually impaired children, such as facial appearance and ocular movements, can assist ophthalmic practice, applying these features to real-world screening remains challenging. Here, we present a mobile health (mHealth) system, the smartphone-based Apollo Infant Sight (AIS), which identifies visually impaired children with any of 16 ophthalmic disorders by recording and analyzing their gazing behaviors and facial features under visual stimuli. Videos from 3,652 children (≤48 months in age; 54.5% boys) were prospectively collected to develop and validate this system. For detecting visual impairment, AIS achieved an area under the receiver operating curve (AUC) of 0.940 in an internal validation set and an AUC of 0.843 in an external validation set collected in multiple ophthalmology clinics across China. In a further test of AIS for at-home implementation by untrained parents or caregivers using their smartphones, the system was able to adapt to different testing conditions and achieved an AUC of 0.859. This mHealth system has the potential to be used by healthcare professionals, parents and caregivers for identifying young children with visual impairment across a wide range of ophthalmic disorders.

Acceptance and Perception of Artificial Intelligence Usability in Eye Care (APPRAISE) for Ophthalmologists: A Multinational Perspective.

Background: Many artificial intelligence (AI) studies have focused on development of AI models, novel techniques, and reporting guidelines. However, little is understood about clinicians' perspectives of AI applications in medical fields including ophthalmology, particularly in light of recent regulatory guidelines. The aim for this study was to evaluate the perspectives of ophthalmologists regarding AI in 4 major eye conditions: diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD) and cataract. Methods: This was a multi-national survey of ophthalmologists between March 1st, 2020 to February 29th, 2021 disseminated via the major global ophthalmology societies. The survey was designed based on microsystem, mesosystem and macrosystem questions, and the software as a medical device (SaMD) regulatory framework chaired by the Food and Drug Administration (FDA). Factors associated with AI adoption for ophthalmology analyzed with multivariable logistic regression random forest machine learning. Results: One thousand one hundred seventy-six ophthalmologists from 70 countries participated with a response rate ranging from 78.8 to 85.8% per question. Ophthalmologists were more willing to use AI as clinical assistive tools (88.1%, n = 890/1,010) especially those with over 20 years' experience (OR 3.70, 95% CI: 1.10-12.5, p = 0.035), as compared to clinical decision support tools (78.8%, n = 796/1,010) or diagnostic tools (64.5%, n = 651). A majority of Ophthalmologists felt that AI is most relevant to DR (78.2%), followed by glaucoma (70.7%), AMD (66.8%), and cataract (51.4%) detection. Many participants were confident their roles will not be replaced (68.2%, n = 632/927), and felt COVID-19 catalyzed willingness to adopt AI (80.9%, n = 750/927). Common barriers to implementation include medical liability from errors (72.5%, n = 672/927) whereas enablers include improving access (94.5%, n = 876/927). Machine learning modeling predicted acceptance from participant demographics with moderate to high accuracy, and area under the receiver operating curves of 0.63-0.83. Conclusion: Ophthalmologists are receptive to adopting AI as assistive tools for DR, glaucoma, and AMD. Furthermore, ML is a useful method that can be applied to evaluate predictive factors on clinical qualitative questionnaires. This study outlines actionable insights for future research and facilitation interventions to drive adoption and operationalization of AI tools for Ophthalmology.

Delays in Seeking Medical Services in Elderly Patients With Senile Cataract.

Delay in seeking medical services is common in elderly populations, which leads to disease progression and life difficulty. This study aims to assess the prevalence of delay in medical visits and treatment and define associated effects and factors in patients with senile cataract, which may help obtain a better understanding of late-life psychopathology and provide the basis for interventions. Patients aged more than 60 years were prospectively recruited in Zhongshan Ophthalmic Center (ZOC). All participants were diagnosed with binocular senile cataract and decided to have primary surgery in ZOC. The distributions of the popularity of delaying outpatient visits and treatment, the degrees of visual impairment, the influences on quality of life, and the reasons for delaying treatment among participants were accessed by the descriptive statistics. Factors associated with the perceptions of cataract treatment were accessed using a binary logistic regression model. A total of 400 senile patients aged from 60 to 94 years were enrolled. At diagnosis, 82 (20.5%) participants had a low vision with monocular acuity of both eyes below 0.05. All participants have felt that their normal lives were affected, and 64 (16%) participants felt that their lives were affected severely. Only 17 (4.25%) participants have sought for medical services immediately after feeling vision loss, and 294 (73.50%) participants have felt vision loss since a year ago before seeking medical help. A total of 298 (74.50%) participants have delayed the surgery time, and 229 (57.25%) patients delayed it for more than 12 months. There were 147 (36.75%) participants delaying surgery on account of no knowledge about it and 114 (28.50%) participants delaying surgery because of fear. There are a high proportion of elderly patients with senile cataract delaying their outpatient visits and surgery treatment, whose normal lives were severely affected. Increasing medical service propaganda about cataract and other common diseases in elderly populations would probably be helpful for improving perceptions of diseases and decreasing medical delays. Public needs to draw more attention to the healthy and medical status of the elderly ocular patients.

Development of a Prognostic Alternative Splicing Signature Associated With Tumor Microenvironment Immune Profiles in Lung Adenocarcinoma.

Background: Alternative splicing (AS), a pivotal post-transcriptional process across more than 95% of human transcripts, is involved in transcript structural variations and protein complexity. Clinical implications of AS events and their interaction with tumor immunity were systematically analyzed in lung adenocarcinoma (LUAD). Methods: Transcriptome profiling as well as AS data of LUAD were retrospectively curated. Then, the network of the overall survival (OS)-relevant AS events with splicing factors was established. After screening OS-relevant AS events, a LASSO prognostic model was conducted and evaluated with ROC curves. A nomogram that integrated independent prognostic indicators was created. Immune response and immune cell infiltration were estimated with ESTIMATE, CIBERSORT, and ssGSEA algorithms. Drug sensitivity was inferred with pRRophetic package. Results: In total, 2415 OS-relevant AS events were identified across LUAD patients. The interaction network of splicing factors with OS-relevant AS events uncovered the underlying regulatory mechanisms of AS events in LUAD. Thereafter, a prognostic model containing 12 AS events was developed, which acted as a reliable and independent prognostic indicator following verification. A nomogram that constituted stage and risk score displayed great effectiveness in evaluating the survival likelihood. Moreover, the AS-based prognostic model was in relation to immune response and immune cell infiltration. Patients with a high-risk score displayed therapeutic superiority to cisplatin, erlotinib, gefitinib, and gemcitabine. Finally, three AS-relevant genes (CDKN2A, TTC39C, and PKIB) were identified as prognostic markers. Conclusion: Collectively, our findings developed an AS event signature with powerful prognostic predictive efficacy in LUAD.

A Germline Mutation in ATR Is Associated With Lung Adenocarcinoma in Asian Patients.

Background: Familial lung cancer (FLC) accounts for 8% of lung adenocarcinoma. It is known that a few germline mutations are associated with risk increasing and may provide new screening and treatment option. The goal of this study is to identify an FLC gene among three members of an FLC family. Methods: To uncover somatic and embryonic mutations linked with familial lung cancer, whole exome sequencing was done on surgical tissues and peripheral blood from three sisters in a family diagnosed with pulmonary lung adenocarcinoma (LUAD). At the same time, single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing data in public databases were enrolled to identify specific gene expression level. Results: Ataxia Telangiectasia and Rad3-Related Protein (ATR) gene C.7667C >G (p.T2556S) mutation were found in 3 patients with familial lung cancer. Whole-genome sequencing revealed that the three sisters exhibited similar somatic mutation patterns. Besides ATR mutations, common mutated genes (BRCA1, EGFR, and ROS1) that characterize LUAD were also found in 5 tumor samples. Analysis for the ATR expression in LUAD patients by single-cell sequencing data, we found ATR expression of tumor patients at high level in immune cells when compared with normal patients, but the expression of ATR in stromal cells has the opposite result. Conclusion: We found a germline mutation in the ATR gene in three sisters of a Chinese family affected by familial lung cancer, which may be a genetic factor for lung cancer susceptibility.

Prediction of the Short-Term Therapeutic Effect of Anti-VEGF Therapy for Diabetic Macular Edema Using a Generative Adversarial Network with OCT Images.

PURPOSE: To generate and evaluate individualized post-therapeutic optical coherence tomography (OCT) images that could predict the short-term response of anti-vascular endothelial growth factor (VEGF) therapy for diabetic macular edema (DME) based on pre-therapeutic images using generative adversarial network (GAN). METHODS: Real-world imaging data were collected at the Department of Ophthalmology, Qilu Hospital. A total of 561 pairs of pre-therapeutic and post-therapeutic OCT images of patients with DME were retrospectively included in the training set, 71 pre-therapeutic OCT images were included in the validation set, and their corresponding post-therapeutic OCT images were used to evaluate the synthetic images. A pix2pixHD method was adopted to predict post-therapeutic OCT images in DME patients that received anti-VEGF therapy. The quality and similarity of synthetic OCT images were evaluated independently by a screening experiment and an evaluation experiment. RESULTS: The post-therapeutic OCT images generated by the GAN model based on big data were comparable to the actual images, and the response of edema resorption was also close to the ground truth. Most synthetic images (65/71) were difficult to differentiate from the actual OCT images by retinal specialists. The mean absolute error (MAE) of the central macular thickness (CMT) between the synthetic OCT images and the actual images was 24.51 ± 18.56 µm. CONCLUSIONS: The application of GAN can objectively demonstrate the individual short-term response of anti-VEGF therapy one month in advance based on OCT images with high accuracy, which could potentially help to improve treatment compliance of DME patients, identify patients who are not responding well to treatment and optimize the treatment program.

Evolution of small cell lung cancer tumor mutation: from molecular mechanisms to novel viewpoints.

Small cell lung cancer (SCLC) is a clinically common malignant tumor originating from the lung neuroendocrine stem cells, which has a poor prognosis and accounts for approximately 15% of all lung cancer cases. However, research on its treatment has been slow, and the 5-year survival rate of patients with SCLC has been < 5% for many years. In recent years, the development and popularization of gene sequencing technology have facilitated the understanding of the gene mutation landscape and tumor evolution of SCLC, thereby leading to a more accurate prediction of the prognosis of SCLC and the development of individualized treatment. In this review, we aimed to discuss the mutation evolution of SCLC from the perspective of a tumor evolution theory and described the sequence of mutation evolution in the occurrence and development of SCLC. In addition, we summarized the existing whole-exome sequencing (WES) data of SCLC cases at our center along with relevant publications on sequencing. Thereafter, we discuss the role of different mutated pathways in the occurrence of SCLC to predict its prognosis more accurately and summarized individualized treatment strategies.

The Fundus Structural and Functional Predictions of DME Patients After Anti-VEGF Treatments.

Diabetic retinopathy (DR) is an important complication with a high incidence of 34.6% in the diabetic populations. DR could finally lead to vision impairment without effective interventions, during which, diabetic macular edema (DME) is a key phase causing visual loss. Up to date, antivascular endothelial growth factor (anti-VEGF) therapy is the first-line treatment for DME which has achieved relatively better clinical outcomes than traditional treatments. However, there are several kinds of anti-VEGF medicines, and patients are sensitive to different anti-VEGF treatments. In addition, its effectiveness is unstable. Considering the patients' need to accept continual anti-VEGF treatments and its price is comparatively high, it is clinically important to predict the prognosis after different anti-VEGF treatments. In our research, we used the demographic and clinical data of 254 DME patients and 2,763 optical coherence tomography (OCT) images from three countries to predict the fundus structural and functional parameters and treatment plan in 6 months after different anti-VEGF treatments. Eight baseline features combined with 11 models were applied to conduct seven prediction tasks. Accuracy (ACC), the area under curve (AUC), mean absolute error (MAE), and mean square error (MSE) were respectively used to evaluate the classification and regression tasks. The ACC and AUC of structural predictions of retinal pigment epithelial detachment were close to 1.000. The MAE and MSE of visual acuity predictions were nearly 0.3 to 0.4 logMAR. The ACC of treatment plan regarding continuous injection was approaching 70%. Our research has achieved great performance in the predictions of fundus structural and functional parameters as well as treatment plan, which can help ophthalmologists improve the treatment compliance of DME patients.

Inhibition on de novo synthesis of PCDD/Fs by an N-P-containing compound: Carbon gasification and kinetics.

In this study, an N-P-containing compound (ammonium dihydrogen phosphate (ADP)) and an auxiliary material (CaO) were used to inhibit the formation of polychlorinated dibenzo-p-dioxins/dibenzofurans (PCDD/Fs). ADP significantly inhibited the formation of PCDD/Fs by the inhibition efficiencies of 98.45% for total concentration and 96.55% for toxic concentration. ADP was the best single inhibitor on toxic PCDFs (96.55%), and the inhibition on toxic PCDDs improved after ADP (90.91%) coupled with CaO (95.69%). In the temperature range of 300-350 °C, ADP inhibited the carbon gasification by reducing CO2 and CO (400%-500% (20 K/min)), which could attributed to the formation of Cu2P2O7 and copper nitrides from the Cu deactivation by P and N, respectively. However, the synergy of ADP and CaO decreased CO and CO2 by 200%-300% (20 K/min), because CaO could promote carbon gasification. In addition, the apparent activation energy (Ea) increased from 78.50 kJ/mol to 102.04 kJ/mol with the addition of ADP but decreased to 73.92 kJ/mol after adding ADP and CaO. These results revealed that one inhibition route of de novo synthesis was the inhibition of carbon gasification by ADP, while CaO mainly inhibited de novo synthesis via the consumption of HCl and Cl2. Furthermore, a reaction mechanism function in model fly ash was built as f(α)=2α-1/2/3, which included carbon gasification and de novo synthesis. The results pave the way for further research on the inhibition kinetics of PCDD/F and development of other inhibitors.

Predicting Central Serous Chorioretinopathy Recurrence Using Machine Learning.

Purpose: To predict central serous chorioretinopathy (CSC) recurrence 3 and 6 months after laser treatment by using machine learning. Methods: Clinical and imaging features of 461 patients (480 eyes) with CSC were collected at Zhongshan Ophthalmic Center (ZOC) and Xiamen Eye Center (XEC). The ZOC data (416 eyes of 401 patients) were used as the training dataset and the internal test dataset, while the XEC data (64 eyes of 60 patients) were used as the external test dataset. Six different machine learning algorithms and an ensemble model were trained to predict recurrence in patients with CSC. After completing the initial detailed investigation, we designed a simplified model using only clinical data and OCT features. Results: The ensemble model exhibited the best performance among the six algorithms, with accuracies of 0.941 (internal test dataset) and 0.970 (external test dataset) at 3 months and 0.903 (internal test dataset) and 1.000 (external test dataset) at 6 months. The simplified model showed a comparable level of predictive power. Conclusion: Machine learning achieves high accuracies in predicting the recurrence of CSC patients. The application of an intelligent recurrence prediction model for patients with CSC can potentially facilitate recurrence factor identification and precise individualized interventions.

Predicting Post-Therapeutic Visual Acuity and OCT Images in Patients With Central Serous Chorioretinopathy by Artificial Intelligence.

To predict visual acuity (VA) and post-therapeutic optical coherence tomography (OCT) images 1, 3, and 6 months after laser treatment in patients with central serous chorioretinopathy (CSC) by artificial intelligence (AI). Real-world clinical and imaging data were collected at Zhongshan Ophthalmic Center (ZOC) and Xiamen Eye Center (XEC). The data obtained from ZOC (416 eyes of 401 patients) were used as the training set; the data obtained from XEC (64 eyes of 60 patients) were used as the test set. Six different machine learning algorithms and a blending algorithm were used to predict VA, and a pix2pixHD method was adopted to predict post-therapeutic OCT images in patients after laser treatment. The data for VA predictions included clinical features obtained from electronic medical records (20 features) and measured features obtained from fundus fluorescein angiography, indocyanine green angiography, and OCT (145 features). The data for OCT predictions included 480 pairs of pre- and post-therapeutic OCT images. The VA and OCT images predicted by AI were compared with the ground truth. In the VA predictions of XEC dataset, the mean absolute errors (MAEs) were 0.074-0.098 logMAR (within four to five letters), and the root mean square errors were 0.096-0.127 logMAR (within five to seven letters) for the 1-, 3-, and 6-month predictions, respectively; in the post-therapeutic OCT predictions, only about 5.15% (5 of 97) of synthetic OCT images could be accurately identified as synthetic images. The MAEs of central macular thickness of synthetic OCT images were 30.15 ± 13.28 µm and 22.46 ± 9.71 µm for the 1- and 3-month predictions, respectively. This is the first study to apply AI to predict VA and post-therapeutic OCT of patients with CSC. This work establishes a reliable method of predicting prognosis 6 months in advance; the application of AI has the potential to help reduce patient anxiety and serve as a reference for ophthalmologists when choosing optimal laser treatments.