Image Analysis-Based Machine Learning for the Diagnosis of Retinopathy of Prematurity: A Meta-analysis and Systematic Review.

TOPIC: To evaluate the performance of machine learning (ML) in the diagnosis of retinopathy of prematurity (ROP) and to assess whether it can be an effective automated diagnostic tool for clinical applications. CLINICAL RELEVANCE: Early detection of ROP is crucial for preventing tractional retinal detachment and blindness in preterm infants, which has significant clinical relevance. METHODS: Web of Science, PubMed, Embase, IEEE Xplore, and Cochrane Library were searched for published studies on image-based ML for diagnosis of ROP or classification of clinical subtypes from inception to October 1, 2022. The quality assessment tool for artificial intelligence-centered diagnostic test accuracy studies was used to determine the risk of bias (RoB) of the included original studies. A bivariate mixed effects model was used for quantitative analysis of the data, and the Deek's test was used for calculating publication bias. Quality of evidence was assessed using Grading of Recommendations Assessment, Development and Evaluation. RESULTS: Twenty-two studies were included in the systematic review; 4 studies had high or unclear RoB. In the area of indicator test items, only 2 studies had high or unclear RoB because they did not establish predefined thresholds. In the area of reference standards, 3 studies had high or unclear RoB. Regarding applicability, only 1 study was considered to have high or unclear applicability in terms of patient selection. The sensitivity and specificity of image-based ML for the diagnosis of ROP were 93% (95% confidence interval [CI]: 0.90-0.94) and 95% (95% CI: 0.94-0.97), respectively. The area under the receiver operating characteristic curve (AUC) was 0.98 (95% CI: 0.97-0.99). For the classification of clinical subtypes of ROP, the sensitivity and specificity were 93% (95% CI: 0.89-0.96) and 93% (95% CI: 0.89-0.95), respectively, and the AUC was 0.97 (95% CI: 0.96-0.98). The classification results were highly similar to those of clinical experts (Spearman's R = 0.879). CONCLUSIONS: Machine learning algorithms are no less accurate than human experts and hold considerable potential as automated diagnostic tools for ROP. However, given the quality and high heterogeneity of the available evidence, these algorithms should be considered as supplementary tools to assist clinicians in diagnosing ROP. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

NOP16 is a histone mimetic that regulates Histone H3K27 methylation and gene repression.

Post-translational modifications of histone tails alter chromatin accessibility to regulate gene expression. Some viruses exploit the importance of histone modifications by expressing histone mimetic proteins that contain histone-like sequences to sequester complexes that recognize modified histones. Here we identify an evolutionarily conserved and ubiquitously expressed, endogenous mammalian protein Nucleolar protein 16 (NOP16) that functions as a H3K27 mimic. NOP16 binds to EED in the H3K27 trimethylation PRC2 complex and to the H3K27 demethylase JMJD3. NOP16 knockout selectively globally increases H3K27me3, a heterochromatin mark, without altering methylation of H3K4, H3K9, or H3K36 or acetylation of H3K27. NOP16 is overexpressed and linked to poor prognosis in breast cancer. Depletion of NOP16 in breast cancer cell lines causes cell cycle arrest, decreases cell proliferation and selectively decreases expression of E2F target genes and of genes involved in cell cycle, growth and apoptosis. Conversely, ectopic NOP16 expression in triple negative breast cancer cell lines increases cell proliferation, cell migration and invasivity in vitro and tumor growth in vivo , while NOP16 knockout or knockdown has the opposite effect. Thus, NOP16 is a histone mimic that competes with Histone H3 for H3K27 methylation and demethylation. When it is overexpressed in cancer, it derepresses genes that promote cell cycle progression to augment breast cancer growth.

Inhibiting Mn Migration by Sb-Pinning Transition Metal Layers in Lithium-Rich Cathode Material for Stable High-Capacity Properties.

Owing to the interacted anion and cation redox dynamics in Li2 MnO3 , the high energy density can be obtained for lithium-rich manganese-based layered transition metal (TM) oxide [Li1.2 Ni0.2 Mn0.6 O2 , LNMO]. However, irreversible migration of Mn ions and oxygen release during highly de-lithiation can destroy its layered structure, leading to voltage and capacity decline. Herein, non-TM antimony (Sb) is pinned to the TM layer of LNMO by a facile sol-gel method. High-resolution ex and in situ characterization technologies manifest that the introduction of trace Sb inhibits the migration of Mn ions, forming a more stable structure. Sb can impressively adjust the Mn-O interaction between anions and cations, beneficial to decrease the energy level of Mn 3d and O 2p orbitals and expand their band gap according to the  theoretical calculation results. As a result, the discharge specific capacity and the energy density for SbLi1.2 [Ni0.2 Mn0.6 ]O2 (SLNMO) reaches as high as 301 mAh g-1 and 1019.6 Wh kg-1 at 0.1 C, respectively. Moreover, the voltage decay is reduced by 419.8 mV compared with LNMO. The regulative interaction between Mn 3d and isolated O 2p bands provides an accurate guidance for solving electrochemical performance deficiencies of lithium-rich manganese-based cathode oxide.

Ru-Incorporated Nickel Diselenide Nanosheet Arrays with Accelerated Adsorption Kinetics toward Overall Water Splitting.

Developing high-efficiency electrocatalysts toward overall water splitting is an increasingly important area for sustainable energy evolution. Theoretical calculation results demonstrate that the incorporation of Ru optimizes the Gibbs free energy of adsorption of H2 O molecules and intermediates for the hydrogen/oxygen evolution reactions (HER/OER) on metal selenide sites, thus boosting electrocatalytic overall water splitting. Accordingly, ruthenium modified nickel diselenide nanosheet arrays are designed and construct on nickel foam (Ru-NiSe2 /NF). The obtained Ru-NiSe2 /NF electrode with a stable 3D structure shows greatly improved OER and HER activity in alkaline solution. Particularly, toward OER, it only requires 210 mV to obtain a current density of 10 mA cm-2 , and the formation of the intermediate nickel oxyhydroxide as active center during the OER process is captured by in situ Raman. Moreover, the overall water splitting can be driven by a voltage of merely 1.537 V to obtain 10 mA cm-2 . This work provides an available strategy for selenides to enhance electrochemical properties and inspires more studies to explore highly efficient electrocatalysts toward full water splitting.

Stabilizing Fe-N-C Catalysts as Model for Oxygen Reduction Reaction.

The highly efficient energy conversion of the polymer-electrolyte-membrane fuel cell (PEMFC) is extremely limited by the sluggish oxygen reduction reaction (ORR) kinetics and poor electrochemical stability of catalysts. Hitherto, to replace costly Pt-based catalysts, non-noble-metal ORR catalysts are developed, among which transition metal-heteroatoms-carbon (TM-H-C) materials present great potential for industrial applications due to their outstanding catalytic activity and low expense. However, their poor stability during testing in a two-electrode system and their high complexity have become a big barrier for commercial applications. Thus, herein, to simplify the research, the typical Fe-N-C material with the relatively simple constitution and structure, is selected as a model catalyst for TM-H-C to explore and improve the stability of such a kind of catalysts. Then, different types of active sites (centers) and coordination in Fe-N-C are systematically summarized and discussed, and the possible attenuation mechanism and strategies are analyzed. Finally, some challenges faced by such catalysts and their prospects are proposed to shed some light on the future development trend of TM-H-C materials for advanced ORR catalysis.

Selection of valid reference genes for quantitative real-time PCR in Cotesia chilonis (Hymenoptera: Braconidae) exposed to different temperatures.

In quantitative real-time PCR (qRT-PCR), data are normalized using reference genes, which helps to control for internal differences and reduce error among samples. In this study, the expression profiles of eight candidate housekeeping genes, 18S ribosomal (18S rRNA), elongation factor (EF1), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal protein L10 (RPL10), ribosomal protein L17 (RPL17), histone 3 (H3), arginine kinase (AK), amd ß-Actin (ACTB), were evaluated in the parasitic wasp Cotesia chilonis in response to different temperatures. Specifically, the performance and stabilities of these genes were compared in adult wasps maintained in a growth condition at 27°C (normal storage conditions) and in adults obtained from pupae refrigerated at 4°C for five days (cold storage conditions). Data were analyzed using the ΔCt method, BestKeeper, NormFinder, and geNorm. The optimal numbers and stabilities of reference genes varied between the two temperature treatments (27°C and 4°C). In samples stored at normal developmental temperature (27°C), the requirement for normalization in response to low temperature exposures was three genes (18S, H3, AK), whereas normalization in response to high temperature exposures required only two reference genes (GAPDH, ACTB). In samples stored at cold temperature (4°C), for low temperature exposures two reference genes (RPL17, RPL10) were required for standardization, while following high temperature exposures three reference genes (18S, H3, ACTB) were needed. This study strengthens understanding of the selection of reference genes before qRT-PCR analysis in C. chilonis. The reference genes identified here will facilitate further investigations of the biological characteristics of this important parasitoid.

Sisyphus effects in hydrogen electrochemistry on metal silicides enabled by silicene subunit edge.

Nonmetal elements strictly govern the electrochemical performance of molybdenum compounds. Yet, the exact role played by nonmetals during electrocatalysis remains largely obscure. With intermetallic MoSi2 comprising silicene subunits, we present an unprecedented hydrogen evolution reaction (HER) behavior in aqueous alkaline solution. Under continuous operation, the HER activity of MoSi2 shows a more than one order of magnitude improvement in current density from 1.1 to 21.5 mA cm-2 at 0.4 V overpotential. Meanwhile, this activation behavior is highly reversible, such that voltage withdrawal leads to catalyst inactivation but another operation causes reactivation. Thus, the system shows dynamics strikingly analogous to the legendary Sisyphus' labor, which drops and recovers in a stepwise manner repeatedly, but never succeeds in reaching the top of the mountain. Isomorphic WSi2 behaves almost the same as MoSi2, whereas other metal silicides with silicyne subunits, including CrSi2 and TaSi2, do not exhibit any anomalous behavior. A thin amorphous shell of MoSi2 is observed after reaction, within which the Si remains partially oxidized while the oxidation state of Mo is basically unchanged. First-principles calculations further reveal that the adsorption of hydroxide ions on silicene subunit edges and the subsequent Si vacancy formation in MoSi2 jointly lead to the anomalous HER kinetics of the adjacent Mo active centers. This work demonstrates that the role of nonmetal varies dramatically with the electronic and crystallographic structures of silicides and that silicene structural subunit may serve as a promoter for boosting HER in alkaline media.

The Marriage of the FeN4 Moiety and MXene Boosts Oxygen Reduction Catalysis: Fe 3d Electron Delocalization Matters.

Iron-nitrogen-carbon (Fe-N-C) is hitherto considered as one of the most satisfactory alternatives to platinum for the oxygen reduction reaction (ORR). Major efforts currently are devoted to the identification and maximization of carbon-enclosed FeN4 moieties, which act as catalytically active centers. However, fine-tuning of their intrinsic ORR activity remains a huge challenge. Herein, a twofold activity improvement of pristine Fe-N-C through introducing Ti3 C2 Tx MXene as a support is realized. A series of spectroscopy and magnetic measurements reveal that the marriage of FeN4 moiety and MXene can induce remarkable Fe 3d electron delocalization and spin-state transition of Fe(II) ions. The lower local electron density and higher spin state of the Fe(II) centers greatly favor the Fe d z 2 electron transfer, and lead to an easier oxygen adsorption and reduction on active FeN4 sites, and thus an enhanced ORR activity. The optimized catalyst shows a two- and fivefold higher specific ORR activity than those of pristine catalyst and Pt/C, respectively, even exceeding most Fe-N-C catalysts ever reported. This work opens up a new pathway in the rational design of Fe-N-C catalysts, and reflects the critical influence of Fe 3d electron states in FeN4 moiety supported on MXene in ORR catalysis.

MoB/g-C3 N4 Interface Materials as a Schottky Catalyst to Boost Hydrogen Evolution.

Proton adsorption on metallic catalysts is a prerequisite for efficient hydrogen evolution reaction (HER). However, tuning proton adsorption without perturbing metallicity remains a challenge. A Schottky catalyst based on metal-semiconductor junction principles is presented. With metallic MoB, the introduction of n-type semiconductive g-C3 N4 induces a vigorous charge transfer across the MoB/g-C3 N4 Schottky junction, and increases the local electron density in MoB surface, confirmed by multiple spectroscopic techniques. This Schottky catalyst exhibits a superior HER activity with a low Tafel slope of 46 mV dec-1 and a high exchange current density of 17 µA cm-2 , which is far better than that of pristine MoB. First-principle calculations reveal that the Schottky contact dramatically lowers the kinetic barriers of both proton adsorption and reduction coordinates, therefore benefiting surface hydrogen generation.

[Raman spectra and photoluminescence spectra of InGaN/GaN multiquantum wells annealed].

InGaN/GaN multiquantum well, grown by MOCVD on a sapphire substrate and annealed under the conditions of 700 and 900 degrees C x (20 min)(-1), was studied by means of mirco-Raman spectroscopy and photoluminescence. The Raman peak of E2, A1 showed red shift after multiquantum were wells annealed, and the HWHM of Raman peakdecreased imperceptibly. Moreover,the photoluminescence peak of the sample annealed under the condition of 700 degrees x (20 min)(-1) showed a red shift, then appeared a blue shift under the condition of 900 degrees C x (20 min)(-1). These results clearly showed that the sample annealed induced strain stress relief that could explain Raman peak shift, but the piezoelectric field induced the quantum-confined Stark effect, which can't agree with the photoluminescence experiment. Sample annealed could change the width of quantum well and InGa phase segregated; these factors influencing structure of quantum well could explain the results of photoluminescence spectra.