KA-mediated excitotoxicity induces neuronal ferroptosis through activation of ferritinophagy.

OBJECTIVES: This study aims to elucidate the role of Fe2+ overload in kainic acid (KA)-induced excitotoxicity, investigate the involvement of ferritinophagy selective cargo receptor NCOA4 in the pathogenesis of excitotoxicity. METHODS: Western blotting was used to detect the expression of FTH1, NCOA4, Lamp2, TfR, FPN, and DMT1 after KA stereotaxic injection into the unilateral striatum of mice. Colocalization of Fe2+ with lysosomes in KA-treated primary cortical neurons was observed by using confocal microscopy. Desferrioxamine (DFO) was added to chelate free iron, a CCK8 kit was used to measure cell viability, and the Fe2+ levels were detected by FerroOrange. BODIPY C11 was used to determine intracellular lipid reactive oxygen species (ROS) levels, and the mRNA levels of PTGS2, a biomarker of ferroptosis, were measured by fluorescent quantitative PCR. 3-Methyladenine (3-MA) was employed to inhibit KA-induced activation of autophagy, and changes in ferritinophagy-related protein expression and the indicated biomarkers of ferroptosis were detected. Endogenous NCOA4 was knocked down by lentivirus transfection, and cell viability and intracellular Fe2+ levels were observed after KA treatment. RESULTS: Western blot results showed that the expression of NCOA4, DMT1, and Lamp2 was significantly upregulated, while FTH1 was downregulated, but there were no significant changes in TfR and FPN. The fluorescence results indicated that KA enhanced the colocalization of free Fe2+ with lysosomes in neurons. DFO intervention could effectively rescue cell damage, reduce intracellular lipid peroxidation, and decrease the increased transcript levels of PTGS2 caused by KA. Pretreatment with 3-MA effectively reversed KA-induced ferritinophagy and ferroptosis. Endogenous interference with NCOA4 significantly improved cell viability and reduced intracellular free Fe2+ levels in KA-treated cells. CONCLUSION: KA-induced excitotoxicity activates ferritinophagy, and targeting ferritinophagy effectively inhibits downstream ferroptosis. Interference with NCOA4 effectively attenuates KA-induced neuronal damage. This study provides a potential therapeutic target for excitotoxicity related disease conditions.

Crowd-sourced machine learning prediction of long COVID using data from the National COVID Cohort Collaborative.

BACKGROUND: While many patients seem to recover from SARS-CoV-2 infections, many patients report experiencing SARS-CoV-2 symptoms for weeks or months after their acute COVID-19 ends, even developing new symptoms weeks after infection. These long-term effects are called post-acute sequelae of SARS-CoV-2 (PASC) or, more commonly, Long COVID. The overall prevalence of Long COVID is currently unknown, and tools are needed to help identify patients at risk for developing long COVID. METHODS: A working group of the Rapid Acceleration of Diagnostics-radical (RADx-rad) program, comprised of individuals from various NIH institutes and centers, in collaboration with REsearching COVID to Enhance Recovery (RECOVER) developed and organized the Long COVID Computational Challenge (L3C), a community challenge aimed at incentivizing the broader scientific community to develop interpretable and accurate methods for identifying patients at risk of developing Long COVID. From August 2022 to December 2022, participants developed Long COVID risk prediction algorithms using the National COVID Cohort Collaborative (N3C) data enclave, a harmonized data repository from over 75 healthcare institutions from across the United States (U.S.). FINDINGS: Over the course of the challenge, 74 teams designed and built 35 Long COVID prediction models using the N3C data enclave. The top 10 teams all scored above a 0.80 Area Under the Receiver Operator Curve (AUROC) with the highest scoring model achieving a mean AUROC of 0.895. Included in the top submission was a visualization dashboard that built timelines for each patient, updating the risk of a patient developing Long COVID in response to clinical events. INTERPRETATION: As a result of L3C, federal reviewers identified multiple machine learning models that can be used to identify patients at risk for developing Long COVID. Many of the teams used approaches in their submissions which can be applied to future clinical prediction questions. FUNDING: Research reported in this RADx® Rad publication was supported by the National Institutes of Health. Timothy Bergquist, Johanna Loomba, and Emily Pfaff were supported by Axle Subcontract: NCATS-STSS-P00438.

Correction: Highly stable color-tunable organic long-persistent luminescence from a single-component exciplex copolymer for in vitro antibacterial.

[This corrects the article DOI: 10.1039/D4SC02839B.].

Ternary deep eutectic solvents for esterification of 2-methylpropenoic acid with alcohols.

In this paper, a set of novel ternary deep eutectic solvents (T-DESs) is synthesized and applied in the esterification of 2-methylpropenoic acid with alcohols. T-DESs have multiple functions, serving as a catalyst, polymerization inhibitor, and solvent, and demonstrate excellent catalytic esterification reaction activity (up to 96% yield). The optimal T-DESs 1 can be recycled 14 times without any decrease in its catalytic activity, thus solving the problems of methacrylate product separation with a polymerization inhibitor, catalyst recovery, and organic solvent pollution.

Highly stable color-tunable organic long-persistent luminescence from a single-component exciplex copolymer for in vitro antibacterial.

Developing exciplex-based organic long-persistent luminescence (OLPL) materials with high stability is very important but remains a formidable challenge in a single-component system. Here, we report a facile strategy to achieve highly stable OLPL in an amorphous exciplex copolymer system via through-space charge transfer (TSCT). The copolymer composed of electron donor and acceptor units can not only exhibit effective TSCT for intra/intermolecular exciplex emission but also construct a rigid environment to isolate oxygen and suppress non-radiative decay, thereby enabling stable exciplex-based OLPL emission with color-tunable feature for more than 100 h under ambient conditions. These single-component OLPL copolymers demonstrate robust antibacterial activity against Escherichia coli under visible light irradiation. These results provide a solid example to exploit highly stable exciplex-based OLPL in polymers, shedding light on how the TSCT mechanism may potentially contribute to OLPL in a single-component molecular system and broadening the scope of OLPL applications.

Linguistic-Driven Partial Semantic Relevance Learning for Skeleton-Based Action Recognition.

Skeleton-based action recognition, renowned for its computational efficiency and indifference to lighting variations, has become a focal point in the realm of motion analysis. However, most current methods typically only extract global skeleton features, overlooking the potential semantic relationships among various partial limb motions. For instance, the subtle differences between actions such as "brush teeth" and "brush hair" are mainly distinguished by specific elements. Although combining limb movements provides a more holistic representation of an action, relying solely on skeleton points proves inadequate for capturing these nuances. Therefore, integrating detailed linguistic descriptions into the learning process of skeleton features is essential. This motivates us to explore integrating fine-grained language descriptions into the learning process of skeleton features to capture more discriminative skeleton behavior representations. To this end, we introduce a new Linguistic-Driven Partial Semantic Relevance Learning framework (LPSR) in this work. While using state-of-the-art large language models to generate linguistic descriptions of local limb motions and further constrain the learning of local motions, we also aggregate global skeleton point representations and textual representations (which generated from an LLM) to obtain a more generalized cross-modal behavioral representation. On this basis, we propose a cyclic attentional interaction module to model the implicit correlations between partial limb motions. Numerous ablation experiments demonstrate the effectiveness of the method proposed in this paper, and our method also obtains state-of-the-art results.

Amyloid-ß but not tau accumulation is strongly associated with longitudinal cognitive decline.

OBJECTIVE: Alzheimer's disease (AD) pathology is featured by the extracellular accumulation of amyloid-ß (Aß) plaques and intracellular tau neurofibrillary tangles in the brain. We studied whether Aß and tau accumulation are independently associated with future cognitive decline in the AD continuum. METHODS: Data were acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI) public database. A total of 1272 participants were selected based on the availability of Aß-PET and CSF tau at baseline and of those 777 participants with follow-up visits. RESULTS: We found that Aß-PET and CSF tau pathology were related to cognitive decline across the AD clinical spectrum, both as potential predictors for dementia progression. Among them, Aß-PET (A + T- subjects) is an independent reliable predictor of longitudinal cognitive decline in terms of ADAS-13, ADNI-MEM, and MMSE scores rather than tau pathology (A - T+ subjects), indicating tau accumulation is not closely correlated with future cognitive impairment without being driven by Aß deposition. Of note, a high percentage of APOE ε4 carriers with Aß pathology (A+) develop poor memory and learning capacity. Interestingly, this condition is not recurrence in terms of the ADNI-MEM domain when adding APOE ε4 status. Finally, the levels of Aß-PET SUVR related to glucose hypometabolism more strongly in subjects with A + T- than A - T+ both happen at baseline and longitudinal changes. CONCLUSIONS: In conclusion, Aß-PET alone without tau pathology (A + T-) measure is an independent reliable predictor of longitudinal cognitive decline but may nonetheless forecast different status of dementia progression. However, tau accumulation alone without Aß pathology background (A - T+) was not enough to be an independent predictor of cognitive worsening.

Regulation of FSP1 myristoylation by NADPH: A novel mechanism for ferroptosis inhibition.

Excitotoxicity is a prevalent pathological event in neurodegenerative diseases. The involvement of ferroptosis in the pathogenesis of excitotoxicity remains elusive. Transcriptome analysis has revealed that cytoplasmic reduced nicotinamide adenine dinucleotide phosphate (NADPH) levels are associated with susceptibility to ferroptosis-inducing compounds. Here we show that exogenous NADPH, besides being reductant, interacts with N-myristoyltransferase 2 (NMT2) and upregulates the N-myristoylated ferroptosis suppressor protein 1 (FSP1). NADPH increases membrane-localized FSP1 and strengthens resistance to ferroptosis. Arg-291 of NMT2 is critical for the NADPH-NMT2-FSP1 axis-mediated suppression of ferroptosis. This study suggests that NMT2 plays a pivotal role by bridging NADPH levels and neuronal susceptibility to ferroptosis. We propose a mechanism by which the NADPH regulates N-myristoylation, which has important implications for ferroptosis and disease treatment.

Cellular senescence imaging and senolysis monitoring in cancer therapy based on a ß-galactosidase-activated aggregation-induced emission luminogen.

Cellular senescence is a permanent state of cell cycle arrest characterized by increased activity of senescence associated ß-galactosidase (SA-ß-gal). Notably, cancer cells have been also observed to exhibit the senescence response and are being considered for sequential treatment with pro-senescence therapy followed by senolytic therapy. However, there is currently no effective agent targeting ß-galactosidase (ß-Gal) for imaging cellular senescence and monitoring senolysis in cancer therapy. Aggregation-induced emission luminogen (AIEgen) demonstrates strong fluorescence, good photostability, and biocompatibility, making it a potential candidate for imaging cellular senescence and monitoring senolysis in cancer therapy when endowed with ß-Gal-responsive capabilities. In this study, we introduced a ß-Gal-activated AIEgen named QM-ß-gal for cellular senescence imaging and senolysis monitoring in cancer therapy. QM-ß-gal exhibited good amphiphilic properties and formed aggregates that emitted a fluorescence signal upon ß-Gal activation. It showed high specificity towards the activity of ß-Gal in lysosomes and successfully visualized DOX-induced senescent cancer cells with intense fluorescence both in vitro and in vivo. Encouragingly, QM-ß-gal could image senescent cancer cells in vivo for over 14 days with excellent biocompatibility. Moreover, it allowed for the monitoring of senescent cancer cell clearance during senolytic therapy with ABT263. This investigation indicated the potential of the ß-Gal-activated AIEgen, QM-ß-gal, as an in vivo approach for imaging cellular senescence and monitoring senolysis in cancer therapy via highly specific and long-term fluorescence imaging. STATEMENT OF SIGNIFICANCE: This work reported a ß-galactosidase-activated AIEgen called QM-ß-gal, which effectively imaged DOX-induced senescent cancer cells both in vitro and in vivo. QM-ß-gal specifically targeted the increased expression and activity of ß-galactosidase in senescent cancer cells, localized within lysosomes. It was cleared rapidly before activation but maintained stability after activation in the DOX-induced senescent tumor. The AIEgen exhibited a remarkable long-term imaging capability for senescent cancer cells, lasting over 14 days and enabled monitoring of senescent cancer cell clearance through ABT263-induced apoptosis. This approach held promise for researchers seeking to achieve prolonged imaging of senescent cells in vivo.

OsACA9, an Autoinhibited Ca2+-ATPase, Synergically Regulates Disease Resistance and Leaf Senescence in Rice.

Calcium (Ca2+) is a versatile intracellular second messenger that regulates several signaling pathways involved in growth, development, stress tolerance, and immune response in plants. Autoinhibited Ca2+-ATPases (ACAs) play an important role in the regulation of cellular Ca2+ homeostasis. Here, we systematically analyzed the putative OsACA family members in rice, and according to the phylogenetic tree of OsACAs, OsACA9 was clustered into a separated branch in which its homologous gene in Arabidopsis thaliana was reported to be involved in defense response. When the OsACA9 gene was knocked out by CRISPR/Cas9, significant accumulation of reactive oxygen species (ROS) was detected in the mutant lines. Meanwhile, the OsACA9 knock out lines showed enhanced disease resistance to both rice bacterial blight (BB) and bacterial leaf streak (BLS). In addition, compared to the wild-type (WT), the mutant lines displayed an early leaf senescence phenotype, and the agronomy traits of their plant height, panicle length, and grain yield were significantly decreased. Transcriptome analysis by RNA-Seq showed that the differentially expressed genes (DEGs) between WT and the Osaca9 mutant were mainly enriched in basal immune pathways and antibacterial metabolite synthesis pathways. Among them, multiple genes related to rice disease resistance, receptor-like cytoplasmic kinases (RLCKs) and cell wall-associated kinases (WAKs) genes were upregulated. Our results suggest that the Ca2+-ATPase OsACA9 may trigger oxidative burst in response to various pathogens and synergically regulate disease resistance and leaf senescence in rice.

Impairment of autophagy promotes human conjunctival fibrosis and pterygium occurrence via enhancing the SQSTM1-NF-κB signaling pathway.

Pterygium is a common ocular disease with a high recurrence rate, characterized by hyperplasia of subconjunctival fibrovascular tissue. Autophagy, an important process to maintain cellular homeostasis, participates in the pathogenic fibrosis of different organs. However, the exact role of autophagy in pterygium pathogenesis remains unknown. Here, we found that autophagic activity was decreased in human pterygium tissues compared with adjacent normal conjunctival tissues. The in vitro model of fibrosis was successfully established using human primary conjunctival fibroblasts (ConFB) treated with transforming growth factor-ß1 (TGF-ß1), evidenced by increased fibrotic level and strong proliferative and invasive capabilities. The autophagic activity was suppressed during TGF-ß1- or ultraviolet-induced fibrosis of ConFB. Activating autophagy dramatically retarded the fibrotic progress of ConFB, while blocking autophagy exacerbated this process. Furthermore, SQSTM1, the main cargo receptor of selective autophagy, was found to significantly promote the fibrosis of ConFB through activating the PKCι-NF-κB signaling pathway. Knockdown of SQSTM1, PKCι, or p65 in ConFB delayed TGF-ß1-induced fibrosis. Overexpression of SQSTM1 drastically abrogated the inhibitory effect of rapamycin or serum starvation on TGF-ß1-induced fibrosis. Collectively, our data suggested that autophagy impairment of human ConFB facilitates fibrosis via activating the SQSTM1-PKCι-NF-κB signaling cascades. This work was contributory to elucidating the mechanism of autophagy underlying pterygium occurrence.

Research Advances in Mechanical Properties and Applications of Dual Network Hydrogels.

Hydrogels with a three-dimensional network structure are particularly outstanding in water absorption and water retention because water exists stably in the interior, making the gel appear elastic and solid. Although traditional hydrogels have good water absorption and high water content, they have poor mechanical properties and are not strong enough to be applied in some scenarios today. The proposal of double-network hydrogels has dramatically improved the toughness and mechanical strength of hydrogels that can adapt to different environments. Based on ensuring the properties of hydrogels, they themselves will not be damaged by excessive pressure and tension. This review introduces preparation methods for double-network hydrogels and ways to improve the mechanical properties of three typical gels. In addition to improving the mechanical properties, the biocompatibility and swelling properties of hydrogels enable them to be applied in the fields of biomedicine, intelligent sensors, and ion adsorption.

Peritumor Edema Serves as an Independent Predictive Factor of Recurrence Patterns and Recurrence-Free Survival for High-Grade Glioma.

Objective: This study is aimed at analyzing the factors affecting the recurrence patterns and recurrence-free survival (RFS) of high-grade gliomas (HGG). Methods: Eligible patients admitted to the Affiliated Hospital of Xuzhou Medical University were selected. Subsequently, the effects of some clinical data including age, gender, WHO pathological grades, tumor site, tumor size, clinical treatments, and peritumoral edema (PTE) area and molecular markers (Ki-67, MGMT, IDH-1, and p53) on HGG patients' recurrence patterns and RFS were analyzed. Results: A total number of 77 patients were enrolled into this study. After analyzing all the cases, it was determined that tumor size and tumor site had a significant influence on the recurrent patterns of HGG, and PTE was an independent predict factor of recurrence patterns. Specifically, when the PTE was mild (<1 cm), the recurrence pattern tended to be local; in contrast, HGG was more likely to progress to marginal recurrence and distant recurrence. Furthermore, age and PTE were significantly associated with RFS; the median RFS of the population with PTE < 1 cm (23.60 months) was obviously longer than the population with PTE ≥ 1 cm (5.00 months). Conclusions: PTE is an independent predictor of recurrence patterns and RFS for HGG. Therefore, preoperative identification of PTE in HGG patients is crucially important, which is helpful to accurately estimate the recurrence pattern and RFS.

Paraganglioma of the Urinary Bladder in a Dog.

A 3-year-old male Bichon Frise developed lethargy, anorexia and haematuria. B-scan ultrasonography examination revealed a small, irregular, soft-textured mass in the bladder. Histopathologically, there was an incomplete fibrous pseudocapsule around the tumour tissue and although there was clear demarcation from the surrounding tissue, there was invasion of the capsule. Tumour cells proliferated in nests or cords of variable size, separated by fibrovascular tissue. The neoplastic cells were immunopositive for chromogranin A, synaptophysin and neuron-specific enolase, and electron microscopy revealed that they contained cytoplasmic secretory granules. On the basis of these findings, the tumour was diagnosed as a primary paraganglioma of the urinary bladder.

Tumor-induced erythroid precursor-differentiated myeloid cells mediate immunosuppression and curtail anti-PD-1/PD-L1 treatment efficacy.

Despite the unprecedented success of immune checkpoint inhibitors (ICIs) as anti-cancer therapy, it remains a prevailing clinical need to identify additional mechanisms underlying ICI therapeutic efficacy and potential drug resistance. Here, using lineage tracking in cancer patients and tumor-bearing mice, we demonstrate that erythroid progenitor cells lose their developmental potential and switch to the myeloid lineage. Single-cell transcriptome analyses reveal that, notwithstanding quantitative differences in erythroid gene expression, erythroid differentiated myeloid cells (EDMCs) are transcriptionally indistinguishable from their myeloid-originated counterparts. EDMCs possess multifaceted machinery to curtail T cell-mediated anti-tumor responses. Consequently, EDMC content within tumor tissues is negatively associated with T cell inflammation for the majority of solid cancers; moreover, EDMC enrichment, in accordance with anemia manifestation, is predictive of poor prognosis in various cohorts of patients undergoing ICI therapy. Together, our findings reveal a feedforward mechanism by which tumors exploit anemia-triggered erythropoiesis for myeloid transdifferentiation and immunosuppression.

Autophagy facilitates age-related cell apoptosis-a new insight from senile cataract.

Age-related cell loss underpins many senescence-associated diseases. Apoptosis of lens epithelial cells (LECs) is the important cellular basis of senile cataract resulted from prolonged exposure to oxidative stress, although the specific mechanisms remain elusive. Our data indicated the concomitance of high autophagy activity, low SQSTM1/p62 protein level and apoptosis in the same LEC from senile cataract patients. Meanwhile, in primary cultured LECs model, more durable autophagy activation and more obvious p62 degradation under oxidative stress were observed in LECs from elder healthy donors, compared with that from young healthy donors. Using autophagy-deficiency HLE-B3 cell line, autophagy adaptor p62 was identified as the critical scaffold protein sustaining the pro-survival signaling PKCι-IKK-NF-κB cascades, which antagonized the pro-apoptotic signaling. Moreover, the pharmacological inhibitor of autophagy, 3-MA, significantly inhibited p62 degradation and rescued oxidative stress-induced apoptosis in elder LECs. Collectively, this study demonstrated that durable activation of autophagy promoted age-related cell death in LECs. Our work contributes to better understanding the pathogenesis of senescence-associated diseases.

Optimization of determinant factors associated with the efficiency of experimental autoimmune uveitis induction in C57BL/6 mice.

Background: Experimental autoimmune uveitis (EAU) is a widely used animal model for uveitis research. The C57BL/6 mouse strain is the most commonly used mouse strain in the research of genetic modification, but C57BL/6 mice are not sufficiently susceptible to EAU induction, partly due to experimental factors. This work aims to optimize relevant factors to improve the efficiency of EAU induction in C57BL/6 mice. Methods: To induce EAU, mice were immunized via intraperitoneal injection with pertussis (PTX) and subcutaneous injection with interphotoreceptor retinoid-binding protein peptide 1-20 (IRBP1-20) emulsified with complete Freund's adjuvant (CFA). The severity of inflammation was assessed using several approaches. The relevant experimental factors were evaluated, including methods of emulsification and doses of peptide and PTX. Results: Uveitis occurred at 8-12 days after immunization and reached its peak at 18-20 days, while T helper type 17 (Th17) cells peaked earlier at 14-18 days after immunization. Based on clinical and histological scores, 500 µg of IRBP peptide was the optimal dose required to induce EAU. The PTX dose demonstrated no influence on EAU incidence, but potentially affected the severity of uveitis. A single injection of 1,000 ng of PTX induced the most severe EAU and the highest proportion of Th17 cells. Compared to extruded emulsion, sonicated emulsion produced a higher incidence, higher histological score, and a 2-day-earlier onset of EAU. Electron microscopy showed a significantly different microstructure between the 2 emulsions. Conclusions: This work optimized the protocols of EAU induction and obtained a high and stable induction rate with severe inflammation in the C57BL/6 mouse strain. Our results facilitate future experimental research involving uveitis.

AI-Model for Identifying Pathologic Myopia Based on Deep Learning Algorithms of Myopic Maculopathy Classification and "Plus" Lesion Detection in Fundus Images.

Background: Pathologic myopia (PM) associated with myopic maculopathy (MM) and "Plus" lesions is a major cause of irreversible visual impairment worldwide. Therefore, we aimed to develop a series of deep learning algorithms and artificial intelligence (AI)-models for automatic PM identification, MM classification, and "Plus" lesion detection based on retinal fundus images. Materials and Methods: Consecutive 37,659 retinal fundus images from 32,419 patients were collected. After excluding 5,649 ungradable images, a total dataset of 32,010 color retinal fundus images was manually graded for training and cross-validation according to the META-PM classification. We also retrospectively recruited 1,000 images from 732 patients from the three other hospitals in Zhejiang Province, serving as the external validation dataset. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, and quadratic-weighted kappa score were calculated to evaluate the classification algorithms. The precision, recall, and F1-score were calculated to evaluate the object detection algorithms. The performance of all the algorithms was compared with the experts' performance. To better understand the algorithms and clarify the direction of optimization, misclassification and visualization heatmap analyses were performed. Results: In five-fold cross-validation, algorithm I achieved robust performance, with accuracy = 97.36% (95% CI: 0.9697, 0.9775), AUC = 0.995 (95% CI: 0.9933, 0.9967), sensitivity = 93.92% (95% CI: 0.9333, 0.9451), and specificity = 98.19% (95% CI: 0.9787, 0.9852). The macro-AUC, accuracy, and quadratic-weighted kappa were 0.979, 96.74% (95% CI: 0.963, 0.9718), and 0.988 (95% CI: 0.986, 0.990) for algorithm II. Algorithm III achieved an accuracy of 0.9703 to 0.9941 for classifying the "Plus" lesions and an F1-score of 0.6855 to 0.8890 for detecting and localizing lesions. The performance metrics in external validation dataset were comparable to those of the experts and were slightly inferior to those of cross-validation. Conclusion: Our algorithms and AI-models were confirmed to achieve robust performance in real-world conditions. The application of our algorithms and AI-models has promise for facilitating clinical diagnosis and healthcare screening for PM on a large scale.

Stretchable, Stable, and Degradable Silk Fibroin Enabled by Mesoscopic Doping for Finger Motion Triggered Color/Transmittance Adjustment.

As a kind of biocompatible material with long history, silk fibroin is one of the ideal platforms for on-skin and implantable electronic devices, especially for self-powered systems. In this work, to solve the intrinsic brittleness as well as poor chemical stability of pure silk fibroin film, mesoscopic doping of regenerated silk fibroin is introduced to promote the secondary structure transformation, resulting in huge improvement in mechanical flexibility (∼250% stretchable and 1000 bending cycles) and chemical stability (endure 100 °C and 3-11 pH). Based on such doped silk film (SF), a flexible, stretchable and fully bioabsorbable triboelectric nanogenerator (TENG) is developed to harvest biomechanical energy in vitro or in vivo for intelligent wireless communication, for example, such TENG can be attached on the fingers to intelligently control the electrochromic function of rearview mirrors, in which the transmittance can be easily adjusted by changing contact force or area. This robust TENG shows great potential application in intelligent vehicle, smart home and health care systems.

Analyzing fundus images to detect diabetic retinopathy (DR) using deep learning system in the Yangtze River delta region of China.

BACKGROUND: This study aimed to establish and evaluate an artificial intelligence-based deep learning system (DLS) for automatic detection of diabetic retinopathy. This could be important in developing an advanced tele-screening system for diabetic retinopathy. METHODS: A DLS with a convolutional neural network was developed to recognize fundus images of referable diabetic retinopathy. A total data set of 41,866 color fundus images were obtained from 17 cities in the Yangtze River Delta Urban Agglomeration (YRDUA). Five experienced retinal specialists and 15 ophthalmologists were recruited to verify images. For training, 80% of the data set was used, and the other 20% served as the validation data set. To effectively understand the learning process, the DLS automatically superimposed a heatmap on the original image. The regions utilized by the DLS were highlighted for diagnosis. RESULTS: Using the local validation data set, the DLS achieved an area under the curve of 0.9824. Based on the manual screening criteria, an operating point was set at about 0.9 sensitivity to evaluate the DLS. Specificity was recorded at 0.9609 and sensitivity was 0.9003. The DLSs showed excellent reliability, repeatability, and high efficiency. After analyzing the misclassification, it was found that 88.6% of the false-positives were mild non-proliferative diabetic retinopathy (NPDR) whereas, 81.6% of the false-negatives were intraretinal microvascular abnormalities. CONCLUSIONS: The DLS efficiently detected fundus images from complex sources in the real world. Incorporating DLS technology in tele-screening will advance the current screening programs to offer a cost-effective and time-efficient solution for detecting diabetic retinopathy.