Accurate prediction of myopic progression and high myopia by machine learning.

Background: Myopia is a leading cause of visual impairment in Asia and worldwide. However, accurately predicting the progression of myopia and the high risk of myopia remains a challenge. This study aims to develop a predictive model for the development of myopia. Methods: We first retrospectively gathered 612 530 medical records from five independent cohorts, encompassing 227 543 patients ranging from infants to young adults. Subsequently, we developed a multivariate linear regression algorithm model to predict the progression of myopia and the risk of high myopia. Result: The model to predict the progression of myopia achieved an R2 value of 0.964 vs a mean absolute error (MAE) of 0.119D [95% confidence interval (CI): 0.119, 1.146] in the internal validation set. It demonstrated strong generalizability, maintaining consistent performance across external validation sets: R2 = 0.950 vs MAE = 0.119D (95% CI: 0.119, 1.136) in validation study 1, R2 = 0.950 vs MAE = 0.121D (95% CI: 0.121, 1.144) in validation study 2, and R2 = 0.806 vs MAE = -0.066D (95% CI: -0.066, 0.569) in the Shanghai Children Myopia Study. In the Beijing Children Eye Study, the model achieved an R2 of 0.749 vs a MAE of 0.178D (95% CI: 0.178, 1.557). The model to predict the risk of high myopia achieved an area under the curve (AUC) of 0.99 in the internal validation set and consistently high area under the curve values of 0.99, 0.99, 0.96 and 0.99 in the respective external validation sets. Conclusion: Our study demonstrates accurate prediction of myopia progression and risk of high myopia providing valuable insights for tailoring strategies to personalize and optimize the clinical management of myopia in children.

Promotion of rice seedlings growth and enhancement of cadmium immobilization under cadmium stress with two types of organic fertilizer.

Cadmium (Cd)-contaminated soil poses a severe threat to crop production and human health, while also resulting in a waste of land resources. In this study, two types of organic fertilizer (ZCK: Low-content available iron; Z2: High-content available iron) were applied to Cd-contaminated soil for rice cultivation, and the effects of the fertilizer on rice growth and Cd passivation were investigated in conjunction with soil microbial analysis. Results showed that Z2 could alter the composition, structure, and diversity of microbial communities, as well as enhance the complexity and stability of the microbial network. Both 2% and 5% Z2 significantly increased the fresh weight and dry weight of rice plants while suppressing Cd absorption. The 2% Z2 exhibited the best Cd passivation effect. Gene predictions suggested that Z2 may promote plant growth by regulating microbial production of organic acids that dissolve phosphorus and potassium. Furthermore, it is suggested that Z2 may facilitate the absorption and immobilization of soil cadmium through the regulation of microbial cadmium efflux and uptake systems, as well as via the secretion of extracellular polysaccharides. In summary, Z2 can promote rice growth, suppress Cd absorption by rice, and passivate soil Cd by regulating soil microbial communities.

Transcriptome analysis reveals the molecular mechanisms by which carbon dots regulate the growth of Chlamydomonas reinhardtii.

Carbon dots (CDs) have attracted increasing attention for their ability to artificially improve photosynthesis. Microalgal bioproducts have emerged as promising sources of sustainable nutrition and energy. However, the gene regulation mechanism of CDs on microalgae remains unexplored. The study synthesized red-emitting CDs and applied them to Chlamydomonas reinhardtii. Results showed that 0.5 mg/L-CDs acted as light supplements to promote cell division and biomass in C. reinhardtii. CDs improved the energy transfer of PS II, photochemical efficiency of PS II, and photosynthetic electron transfer. The pigment content and carbohydrate production slightly increased, while protein and lipid contents significantly increased (by 28.4% and 27.7%, respectively) in a short cultivation time. Transcriptome analysis identified 1166 differentially expressed genes. CDs resulted in faster cell growth by up-regulating the expression of genes associated with cell growth and death, promoting sister chromatid separation, accelerating the mitotic process and shortening the cell cycle. CDs improved the ability of energy conversion by up-regulating photosynthetic electron transfer-related genes. Carbohydrate metabolism-related genes were regulated and provided more available pyruvate for the citrate cycle. The study provides evidence for the genetic regulation of microalgal bioresources by artificially synthesized CDs.

Factors associated with loss to follow-up before and after treatment initiation among patients with tuberculosis: A 5-year observation in China.

Background: Loss to follow-up (LTFU) is a significant barrier to the completion of anti-tuberculosis (TB) treatment and a major predictor of TB-associated deaths. Currently, research on LTFU-related factors in China is both scarce and inconsistent. Methods: We collected information from the TB observation database of the National Clinical Research Center for Infectious Diseases. The data of all patients who were documented as LTFU were assessed retrospectively and compared with those of patients who were not LTFU. Descriptive epidemiology and multivariable logistic regression analyses were conducted to identify the factors associated with LTFU. Results: A total of 24,265 TB patients were included in the analysis. Of them, 3,046 were categorized as LTFU, including 678 who were lost before treatment initiation and 2,368 who were lost afterwards. The previous history of TB was independently associated with LTFU before treatment initiation. Having medical insurance, chronic hepatitis or cirrhosis, and providing an alternative contact were independent predictive factors for LTFU after treatment initiation. Conclusion: Loss to follow-up is frequent in the management of patients with TB and can be predicted using patients' treatment history, clinical characteristics, and socioeconomic factors. Our research illustrates the importance of early assessment and intervention after diagnosis. Targeted measures can improve patient engagement and ultimately treatment adherence, leading to better health outcomes and disease control.

New evidence of the Hoyle-like structure in 16O.

An experiment of 12C(16O,16O → 4α)12C was performed at a beam energy of 96 MeV. A large number of 4-α events were recorded in coincidence and with full particle identification (PID). This was made possible by employing a series of silicon-strip-based telescopes that provided excellent position and energy resolutions. Four narrow resonances just above the 15.1 MeV state were firmly identified in the α + 12C(7.65 MeV; Hoyle state) decay channel. Combined with the theoretical predictions, these resonant states provide new evidence for the predicted possible Hoyle-like structure in 16O above the 4-α separation threshold. Some very high-lying 4-α resonant states have also been observed and need to be further investigated.

Monolithic MOF-Based Metal-Insulator-Metal Resonator for Filtering and Sensing.

Metal-insulator-metal (MIM) configurations based on Fabry-Pérot resonators have advanced the development of color filtering through interactions between light and matter. However, dynamic color changes without breaking the structure of the MIM resonator upon environmental stimuli are still challenging. Here, we report monolithic metal-organic framework (MOF)-based MIM resonators with tunable bandwidth that can boost both dynamic optical filtering and active chemical sensing by laser-processing microwell arrays on the top metal layer. Programmable tuning of the reflection color of the MOF-based MIM resonator is achieved by controlling the MOF layer thicknesses, which is demonstrated by simulation of light-matter interactions on subwavelength scales. Laser-processed microwell arrays are used to boost sensing performance by extending the pathway for diffusion of external chemicals into nanopores of the MOFs. Both experiments and molecular dynamics simulations demonstrate that tailoring the period and height of the microwell array on the MIM resonator can advance the high detection sensitivity of chemicals.

A stable solid-state lithium-oxygen battery enabled by heterogeneous silicon-based interface.

Solid-state lithium-metal batteries using inorganic solid-state electrolyte (SSE) instead of liquid-electrolyte, especially lithium-oxygen (Li-O2) battery, have attracted much more attention due to their high-energy density and safety. However, the poor interface contact between electrodes and SSEs makes these batteries lose most of their capacity and power during cycling. Here we report that by coating a heterogeneous silicon carbide on lithium metal anode and Li1.5Al0.5Ge1.5P3O12(LAGP)-SSE, a good interface contact is created between the electrode and electrolyte that can effectively reduce the interface impedance and improve the cycle performance of the assembled battery. As a result, the solid-sate Li-O2battery demonstrates a cycle lifespan of ∼78 cycles being at least 3-times higher than the solid-state Li-O2battery without silicon carbide with a capacity limitation of 1000 mAh g-1at 250 mA g-1. The characterization of discharge products indicates a typical two-electron convention of oxygen-to-lithium oxide for the solid-state Li-O2battery system. This work paves a way for developing high-energy long-cycle solid-state lithium-metal battery. The work provides insights into the interface between the Li-metal and SSE to develop high-energy long-cycle all solid-state Li-metal batteries.

Inhibitory effects and molecular mechanisms of ginsenoside Rg1 on the senescence of hematopoietic stem cells.

Hematopoietic stem cells (HSCs) produce all blood cell lineages and maintain life-long hematopoiesis. However, the self-renewal ability and differentiation capacity of HSCs reduces with age. The senescence of HSCs can lead to the imbalance of hematopoietic homeostasis and immune disorder and induce a variety of age-related diseases. Recent studies have shown that therapeutic interventions targeting the senescence of HSCs may prevent disease progression. Ginsenoside Rg1 (Rg1), extracted from roots or stems of ginseng, has beneficial antiaging activities. It has been reported that Rg1 can inhibit the senescence of HSCs. Here, we reviewed recent advances of Rg1 in inhibiting the senescence of HSCs and discussed related molecular mechanisms. Bioinformatics and network databases have been widely applied to drug discoveries. Here, we predicted potential antiaging targets of Rg1 explored by bioinformatic methods, which may help discover new targets of Rg1 and provide novel strategies for delaying the aging process of HSCs.

Umbilical cord derived mesenchymal stem cell-GelMA microspheres for accelerated wound healing.

Mesenchymal stem cells (MSCs) are an ideal seed cell for tissue engineering and stem cell transplantation. MSCs combined with biological scaffolds play an important role in promoting the repair of cutaneous wound. However, direct administration of MSCs is challenging for MSCs survival and integration into tissues. Providing MSCs with a biocompatible scaffold can improve MSCs survival, but the effect of gelatin methacrylate (GelMA) loaded MSCs from umbilical cord MSCs (UC-MSCs) in wound healing remains unknown. Here, we investigated the ability of GelMA with UC-MSCs complexes to promote migration and proliferation and the effect on wound healing in mouse models. We discovered that UC-MSCs attached to GelMA and promoted the proliferation and migration of fibroblasts. Both UC-MSCs and UC-MSCs-derived extracellular vesicles accelerated wound healing. MSC + Gelatin methacrylate microspheres (GMs) application decreased expression of transforming growth factor-ß(TGF-ß) and Type III collagen (Col3)in vivo, leading to new collagen deposition and angiogenesis, and accelerate wound healing and skin tissue regeneration. Taken together, these findings indicate MSC + GMs can promote wound healing by regulating wound healing-related factors in the paracrine. Therefore, our research proves that GelMA is an ideal scaffold for the top management of UC-MSCs in wound healing medical practice.

A deep-learning system predicts glaucoma incidence and progression using retinal photographs.

BackgroundDeep learning has been widely used for glaucoma diagnosis. However, there is no clinically validated algorithm for glaucoma incidence and progression prediction. This study aims to develop a clinically feasible deep-learning system for predicting and stratifying the risk of glaucoma onset and progression based on color fundus photographs (CFPs), with clinical validation of performance in external population cohorts.MethodsWe established data sets of CFPs and visual fields collected from longitudinal cohorts. The mean follow-up duration was 3 to 5 years across the data sets. Artificial intelligence (AI) models were developed to predict future glaucoma incidence and progression based on the CFPs of 17,497 eyes in 9346 patients. The area under the receiver operating characteristic (AUROC) curve, sensitivity, and specificity of the AI models were calculated with reference to the labels provided by experienced ophthalmologists. Incidence and progression of glaucoma were determined based on longitudinal CFP images or visual fields, respectively.ResultsThe AI model to predict glaucoma incidence achieved an AUROC of 0.90 (0.81-0.99) in the validation set and demonstrated good generalizability, with AUROCs of 0.89 (0.83-0.95) and 0.88 (0.79-0.97) in external test sets 1 and 2, respectively. The AI model to predict glaucoma progression achieved an AUROC of 0.91 (0.88-0.94) in the validation set, and also demonstrated outstanding predictive performance with AUROCs of 0.87 (0.81-0.92) and 0.88 (0.83-0.94) in external test sets 1 and 2, respectively.ConclusionOur study demonstrates the feasibility of deep-learning algorithms in the early detection and prediction of glaucoma progression.FUNDINGNational Natural Science Foundation of China (NSFC); the High-level Hospital Construction Project, Zhongshan Ophthalmic Center, Sun Yat-sen University; the Science and Technology Program of Guangzhou, China (2021), the Science and Technology Development Fund (FDCT) of Macau, and FDCT-NSFC.

Construction of Core-Shell NanoMOFs@microgel for Aqueous Lubrication and Thermal-Responsive Drug Release.

The construction of porous nanocarriers with good lubricating performance and stimuli-responsive drug release is significant for the synergetic therapy of osteoarthritis (OA). Although metal-organic framework nanoparticles (nanoMOFs) as carriers can support drug delivery, achieving the synergy of aqueous lubrication and stimuli-responsive drug release is challenging. In this work, a core-shell nanoMOFs@poly(N-isopropylacrylamide) (PNIPAm) microgel hybrid via one-pot soap-free emulsion polymerization is developed. Programmable growth of the PNIPAm microgel layer on the surface of nanoMOFs is achieved by tuning the concentration of the monomer and the crosslinker in the reaction. Reversible swelling-collapsing behaviors of the hybrid are realized by tuning the temperature below and above the lower critical solution temperature. When used as water lubrication additives, the hybrid enables reductions in both the coefficient of friction and wear volume. In vitro thermal-responsive drug release is demonstrated on the diclofenac sodium-loaded hybrid by controlling the swelling and collapsing states of the PNIPAm nanolayer. Moreover, the good biocompatibility of the hybrid is verified by culturing toward HeLa and BEAS-2B cells. These results establish a nanoMOFs@microgel hybrid that can achieve friction and wear reduction and thermal-responsive drug release.

The tissue origin of human mesenchymal stem cells dictates their therapeutic efficacy on glucose and lipid metabolic disorders in type II diabetic mice.

BACKGROUND: The therapeutic efficacy of mesenchymal stem cells (MSCs) of different tissue origins on metabolic disorders can be varied in many ways but remains poorly defined. Here we report a comprehensive comparison of human MSCs derived from umbilical cord Wharton's jelly (UC-MSCs), dental pulp (PU-MSCs), and adipose tissue (AD-MSCs) on the treatment of glucose and lipid metabolic disorders in type II diabetic mice. METHODS: Fourteen-to-fifteen-week-old male C57BL/6 db/db mice were intravenously administered with human UC-MSCs, PU-MSCs, and AD-MSCs at various doses or vehicle control once every 2 weeks for 6 weeks. Metformin (MET) was given orally to animals in a separate group once a day at weeks 4 to 6 as a positive control. Body weight, blood glucose, and insulin levels were measured every week. Glucose tolerance tests (GTT) and insulin tolerance tests (ITT) were performed every 2 weeks. All the animals were sacrificed at week 6 and the blood and liver tissues were collected for biochemical and histological examinations. RESULTS: UC-MSCs showed the strongest efficacy in reducing fasting glucose levels, increasing fasting insulin levels, and improving GTT and ITT in a dose-dependent manner, whereas PU-MSCs showed an intermediate efficacy and AD-MSCs showed the least efficacy on these parameters. Moreover, UC-MSCs also reduced the serum low-density lipoprotein cholesterol (LDL-C) levels with the most prominent potency and AD-MSCs had only very weak effect on LDL-C. In contrast, AD-MSCs substantially reduced the lipid content and histological lesion of liver and accompanying biomarkers of liver injury such as serum aspartate transaminase (AST) and alanine aminotransferase (ALT) levels, whereas UC-MSCs and PU-MSCs displayed no or modest effects on these parameters, respectively. CONCLUSIONS: Taken together, our results demonstrated that MSCs of different tissue origins can confer substantially different therapeutic efficacy in ameliorating glucose and lipid metabolic disorders in type II diabetes. MSCs with different therapeutic characteristics could be selected according to the purpose of the treatment in the future clinical practice.

Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images.

Regular screening for the early detection of common chronic diseases might benefit from the use of deep-learning approaches, particularly in resource-poor or remote settings. Here we show that deep-learning models can be used to identify chronic kidney disease and type 2 diabetes solely from fundus images or in combination with clinical metadata (age, sex, height, weight, body-mass index and blood pressure) with areas under the receiver operating characteristic curve of 0.85-0.93. The models were trained and validated with a total of 115,344 retinal fundus photographs from 57,672 patients and can also be used to predict estimated glomerulal filtration rates and blood-glucose levels, with mean absolute errors of 11.1-13.4 ml min-1 per 1.73 m2 and 0.65-1.1 mmol l-1, and to stratify patients according to disease-progression risk. We evaluated the generalizability of the models for the identification of chronic kidney disease and type 2 diabetes with population-based external validation cohorts and via a prospective study with fundus images captured with smartphones, and assessed the feasibility of predicting disease progression in a longitudinal cohort.

A deep-learning pipeline for the diagnosis and discrimination of viral, non-viral and COVID-19 pneumonia from chest X-ray images.

Common lung diseases are first diagnosed using chest X-rays. Here, we show that a fully automated deep-learning pipeline for the standardization of chest X-ray images, for the visualization of lesions and for disease diagnosis can identify viral pneumonia caused by coronavirus disease 2019 (COVID-19) and assess its severity, and can also discriminate between viral pneumonia caused by COVID-19 and other types of pneumonia. The deep-learning system was developed using a heterogeneous multicentre dataset of 145,202 images, and tested retrospectively and prospectively with thousands of additional images across four patient cohorts and multiple countries. The system generalized across settings, discriminating between viral pneumonia, other types of pneumonia and the absence of disease with areas under the receiver operating characteristic curve (AUCs) of 0.94-0.98; between severe and non-severe COVID-19 with an AUC of 0.87; and between COVID-19 pneumonia and other viral or non-viral pneumonia with AUCs of 0.87-0.97. In an independent set of 440 chest X-rays, the system performed comparably to senior radiologists and improved the performance of junior radiologists. Automated deep-learning systems for the assessment of pneumonia could facilitate early intervention and provide support for clinical decision-making.

Enhanced Transmission from Visible to Terahertz in ZnTe Crystals with Scalable Subwavelength Structures.

The zinc blend nonlinear crystal of zinc telluride (ZnTe) is currently one of the most commonly used electro-optical material for terahertz (THz) probe and imaging. We report herein how to engineer the surface behavior of a ZnTe single crystal to design subwavelength structures (SWSs) for enhancing ultrabroadband transmission. Polystyrene (PS) nanoparticle monolayers with a maximum coverage of 85.2% were produced on the ZnTe crystal by an eccentric spin-coating technique combined with surface wettability engineering. Subsequently, the well-defined conical SWS arrays were fabricated on the ZnTe crystal by reactive ion etching over the PS monolayer template, with the size of the SWS arrays customized by optimizing the etching process. Finally, we demonstrated ultrabroadband antireflection on the surface structured ZnTe crystals in the visible-near-infrared, infrared, and terahertz regions with transmittance increase of 11.6%, 10.0%, and 24.8%, which are attributed to the decrease of surface Fresnel reflection by SWS. Notably, in 0.2-1.0 THz, the transmittance reached over 70%. Our work provides a new strategy to enhance the THz generation efficiency and detection sensitivity based on ZnTe crystals by surface engineering.

Robust Hybrid Omniphobic Surface for Stain Resistance.

Inspired by natural living surfaces, researchers have developed many excellent anti-smudge coatings, but there remain some critical challenges such as complex or expensive fabrications, poor long-term stability, non-transparency, etc., which may limit their large-area application. In this work, we designed a robust and transparent omniphobic coating with a one-step dip coating method. The perfluoropolyether chains were grafted on a smooth glass surface, and the coating surface not only presented good liquid repellency and stain resistance but also owned excellent mechanical wear resistance. The stain resistance property and wettability have barely changed after hundreds of thousands of friction cycles in air or even in an organic solvent surrounding. The robust hybrid coating possesses simple preparation, an excellent property, and durability, which may bring a widespread interest in the engineering application field.

Regulation of ROS in myeloid-derived suppressor cells through targeting fatty acid transport protein 2 enhanced anti-PD-L1 tumor immunotherapy.

Despite the remarkable success and efficacy of immune checkpoint blockade (ICB) therapy against the PD-1/PD-L1 axis, it induces sustained responses in a sizeable minority of cancer patients due to the activation of immunosuppressive factors such as myeloid-derived suppressor cells (MDSCs). Inhibiting the immunosuppressive function of MDSCs is critical for successful cancer ICB therapy. Interestingly, lipid metabolism is a crucial factor in modulating MDSCs function. Fatty acid transport protein 2 (FATP2) conferred the function of PMN-MDSCs in cancer via the upregulation of arachidonic acid metabolism. However, whether regulating lipid accumulation in MDSCs by targeting FATP2 could block MDSCs reactive oxygen species (ROS) production and enhance PD-L1 blockade-mediated tumor immunotherapy remains unexplored. Here we report that FATP2 regulated lipid accumulation, ROS, and immunosuppressive function of MDSCs in tumor-bearing mice. Tumor cells-derived granulocyte macrophage-colony stimulating factor (GM-CSF) induced FATP2 expression in MDSCs by activation of STAT3 signaling pathway. Pharmaceutical blockade of FATP2 expression in MDSCs by lipofermata decreased lipid accumulation, reduced ROS, blocked immunosuppressive activity, and consequently inhibited tumor growth. More importantly, lipofermata inhibition of FATP2 in MDSCs enhanced anti-PD-L1 tumor immunotherapy via the upregulation of CD107a and reduced PD-L1 expression on tumor-infiltrating CD8+T-cells. Furthermore, the combination therapy blocked MDSC's suppressive role on T- cells thereby enhanced T-cell's ability for the production of IFN-γ. These findings indicate that FATP2 plays a key role in modulating lipid accumulation-induced ROS in MDSCs and targeting FATP2 in MDSCs provides a novel therapeutic approach to enhance anti-PD-L1 cancer immunotherapy.

Variants of WNT7A and GPR124 are associated with hemorrhagic transformation following intravenous thrombolysis in ischemic stroke.

AIMS: The canonical Wnt signaling pathway plays an essential role in blood-brain barrier integrity and intracerebral hemorrhage in preclinical stroke models. Here, we sought to explore the association between canonical Wnt signaling and hemorrhagic transformation (HT) following intravenous thrombolysis (IVT) in acute ischemic stroke (AIS) patients as well as to determine the underlying cellular mechanisms. METHODS: 355 consecutive AIS patients receiving IVT were included. Blood samples were collected on admission, and HT was detected at 24 hours after IVT. 117 single-nucleotide polymorphisms (SNPs) of 28 Wnt signaling genes and exon sequences of 4 core cerebrovascular Wnt signaling components (GPR124, RECK, FZD4, and CTNNB1) were determined using a customized sequencing chip. The impact of identified genetic variants was further studied in HEK 293T cells using cellular and biochemical assays. RESULTS: During the study period, 80 patients experienced HT with 27 parenchymal hematoma (PH). Compared to the non-PH patients, WNT7A SNPs (rs2163910, P = .001, OR 2.727; rs1124480, P = .002, OR 2.404) and GPR124 SNPs (rs61738775, P = .012, OR 4.883; rs146016051, P < .001, OR 7.607; rs75336000, P = .044, OR 2.503) were selectively enriched in the PH patients. Interestingly, a missense variant of GPR124 (rs75336000, c.3587G>A) identified in the PH patients resulted in a single amino acid alteration (p.Cys1196Tyr) in the intracellular domain of GPR124. This variant substantially reduced the activity of WNT7B-induced canonical Wnt signaling by decreasing the ability of GPR124 to recruit cytoplasmic DVL1 to the cellular membrane. CONCLUSION: Variants of WNT7A and GPR124 are associated with increased risk of PH in patients with AIS after intravenous thrombolysis, likely through regulating the activity of canonical Wnt signaling.