Combined effects of cadmium and sulfamethoxazole on Eisenia fetida: Insights into accumulation, subcellular partitioning, biomarkers and toxicological responses.

Cadmium (Cd) and sulfamethoxazole (SMX) frequently coexist in farmlands, yet their synergistic toxicological impacts on terrestrial invertebrates remain unexplored. In this study, earthworms were exposed to artificial soils percolated with Cd (5 mg/kg), SMX (5 mg/kg) or combination of them for 7 days, followed by a 12-day elimination phase in uncontaminated soil. The uptake of Cd and SMX by the earthworms, along with their subcellular distribution, was meticulously analyzed. Additionally, a suite of biomarkers-including superoxide dismutase (SOD), catalase (CAT), malondialdehyde (MDA), and weight loss-were evaluated to assess the health status of the earthworms and the toxicological effects of the Cd and SMX mixture. Notably, the cotreatment with Cd and SMX resulted in a significantly higher weight loss in Eisenia fetida (41.25 %) compared to exposure to Cd alone (26.84 %). Moreover, the cotreatment group exhibited substantially higher concentrations of Cd in the total internal body, fraction C (cytosol), and fraction E (tissue fragments and cell membranes) in Eisenia fetida compared to Cd alone counterparts. The combined exposure also significantly elevated the SMX levels in the total body and fraction C compared with the SMX-only treated earthworms. Additionally, Eisenia fetida subjected to the combined treatment showed markedly increased activities of SOD, CAT, and MDA compared to those treated with Cd alone. The effect addition indices (EAIs), ranging from 1.00 to 2.23, unequivocally demonstrated a synergistic effect of the combined treatments. Interestingly, relocating the earthworms to clean soil did not mitigate the observed adverse effects. These findings underscore the increased risk posed by the Cd-SMX complex to terrestrial invertebrates in agricultural areas.

The varicella-zoster virus ORF16 protein promotes both the nuclear transport and the protein abundance of the viral DNA polymerase subunit ORF28.

Although all herpesviruses utilize a highly conserved replication machinery to amplify their viral genomes, different members may have unique strategies to modulate the assembly of their replication components. Herein, we characterize the subcellular localization of seven essential replication proteins of varicella-zoster virus (VZV) and show that several viral replication enzymes such as the DNA polymerase subunit ORF28, when expressed alone, are localized in the cytoplasm. The nuclear import of ORF28 can be mediated by the viral DNA polymerase processivity factor ORF16. Besides, ORF16 could markedly enhance the protein abundance of ORF28. Noteworthily, an ORF16 mutant that is defective in nuclear transport still retained the ability to enhance ORF28 abundance. The low abundance of ORF28 in transfected cells was due to its rapid degradation mediated by the ubiquitin-proteasome system. We additionally reveal that radicicol, an inhibitor of the chaperone Hsp90, could disrupt the interaction between ORF16 and ORF28, thereby affecting the nuclear entry and protein abundance of ORF28. Collectively, our findings imply that the cytoplasmic retention and rapid degradation of ORF28 may be a key regulatory mechanism for VZV to prevent untimely viral DNA replication, and suggest that Hsp90 is required for the interaction between ORF16 and ORF28.

Generative organic electronic molecular design informed by quantum chemistry.

Generative molecular design strategies have emerged as promising alternatives to trial-and-error approaches for exploring and optimizing within large chemical spaces. To date, generative models with reinforcement learning approaches have frequently used low-cost methods to evaluate the quality of the generated molecules, enabling many loops through the generative model. However, for functional molecular materials tasks, such low-cost methods are either not available or would require the generation of large amounts of training data to train surrogate machine learning models. In this work, we develop a framework that connects the REINVENT reinforcement learning framework with excited state quantum chemistry calculations to discover molecules with specified molecular excited state energy levels, specifically molecules with excited state landscapes that would serve as promising singlet fission or triplet-triplet annihilation materials. We employ a two-step curriculum strategy to first find a set of diverse promising molecules, then demonstrate the framework's ability to exploit a more focused chemical space with anthracene derivatives. Under this protocol, we show that the framework can find desired molecules and improve Pareto fronts for targeted properties versus synthesizability. Moreover, we are able to find several different design principles used by chemists for the design of singlet fission and triplet-triplet annihilation molecules.

Hydrothermal Synthesis of Functionalized Carbon Nanodots and Their Clusters as Ionic Probe for High Sensitivity and Selectivity for Sulfate Anions with Excellent Detection Level.

Nitrogen-doped carbon nanodots (CNDs) were synthesized and utilized as sensing probes to detect different anions and metallic ions within aqueous solutions. The pristine CNDs were developed through a one-pot hydrothermal synthesis. o-Phenylenediamine was used as the precursor. A similar hydrothermal synthesis technique in the presence of polyethylene glycol (PEG) was adopted to form the PEG-coated CND clusters (CND-100k). Through photoluminescence (PL) quenching, both CND and PEG-coated CND suspensions display ultra-high sensitivity and selectivity towards HSO4- anions (Stern-Volmer quenching constant (KSV) value: 0.021 ppm-1 for CND and 0.062 ppm-1 for CND-100k) with an ultra-low detection limit (LOD value: 0.57 ppm for the CND and 0.19 ppm for CND-100k) in the liquid phase. The quenching mechanism of N-doped CNDs towards HSO4- ions involves forming the bidentate as well as the monodentate hydrogen bonding with the sulfate anionic moieties. The detection mechanism of metallic ions analyzed through the Stern-Volmer formulation reveals that the CND suspension is well suited for the detection of Fe3+ (KSV value: 0.043 ppm-1) and Fe2+ (KSV value: 0.0191 ppm-1) ions, whereas Hg2+ (KSV value: 0.078 ppm-1) sensing can be precisely performed by the PEG-coated CND clusters. Accordingly, the CND suspensions developed in this work can be employed as high-performance PL probes for detecting various anions and metallic ions in the liquid phase.

Optofluidic Accumulation of Silica Beads on Gel-Based Three-Dimensional SERS Substrate To Enhance Sensitivity Using Multiple Photonic Nanojets.

This paper presents a gel-based three-dimensional (3D) substrate for surface-enhanced Raman spectroscopy (SERS) mediated by photonic nanojets (PNJs) to enhance the sensitivity of SERS detection. The porous structure of the gel-based substrate allowed small molecules to diffuse into the substrate, while the placement of silica beads on the substrate surface resulted in the generation of photonic nanojets during SERS measurements. Because the gel-based SERS substrate had electromagnetic (EM) hot spots along the Z-direction for several tens of microns, the focuses of the PNJs, which were located a few microns away from the substrate surface, could excite the EM hot spots located within the substrate. Our objective was to maximize SERS signal intensity by coating the substrate with a close-packed array of silica beads to enable the generation of multiple PNJs. The bead array was formed using an optical fiber decorated with gold nanorods (AuNRs) to create a temperature gradient in a mixture containing silica beads, thereby enabling their arrangement and deposition in arbitrary locations across the substrate. In experiments, the Raman enhancement provided by multiple PNJs significantly exceeded that provided by single PNJs. The proposed PNJ-mediated SERS method reduced the limit of detection for malachite green by 100 times, compared to SERS results obtained using the same substrate without beads. The proposed enhancement scheme using a gel-based 3D SERS substrate with a close-packed array of silica beads could be utilized to achieve high-sensitivity SERS detection for a variety of molecules in a diverse range of applications.

Reorganization Energy Predictions with Graph Neural Networks Informed by Low-Cost Conformers.

A critical bottleneck for the design of high-conductivity organic materials is finding molecules with low reorganization energy. To enable high-throughput virtual screening campaigns for many types of organic electronic materials, a fast reorganization energy prediction method compared to density functional theory is needed. However, the development of low-cost machine-learning-based models for calculating the reorganization energy has proven to be challenging. In this paper, we combine a 3D graph-based neural network (GNN) recently benchmarked for drug design applications, ChIRo, with low-cost conformational features for reorganization energy predictions. By comparing the performance of ChIRo to another 3D GNN, SchNet, we find evidence that the bond-invariant property of ChIRo enables the model to learn from low-cost conformational features more efficiently. Through an ablation study with a 2D GNN, we find that using low-cost conformational features on top of 2D features informs the model for making more accurate predictions. Our results demonstrate the feasibility of reorganization energy predictions on the benchmark QM9 data set without needing DFT-optimized geometries and demonstrate the types of features needed for robust models that work on diverse chemical spaces. Furthermore, we show that ChIRo informed with low-cost conformational features achieves comparable performance with the previously reported structure-based model on π-conjugated hydrocarbon molecules. We expect this class of methods can be applied to the high-throughput screening of high-conductivity organic electronics candidates.

The role of the electrolyte in non-conjugated radical polymers for metal-free aqueous energy storage electrodes.

Metal-free aqueous batteries can potentially address the projected shortages of strategic metals and safety issues found in lithium-ion batteries. More specifically, redox-active non-conjugated radical polymers are promising candidates for metal-free aqueous batteries because of the polymers' high discharge voltage and fast redox kinetics. However, little is known regarding the energy storage mechanism of these polymers in an aqueous environment. The reaction itself is complex and difficult to resolve because of the simultaneous transfer of electrons, ions and water molecules. Here we demonstrate the nature of the redox reaction for poly(2,2,6,6-tetramethylpiperidinyloxy-4-yl acrylamide) by examining aqueous electrolytes of varying chao-/kosmotropic character using electrochemical quartz crystal microbalance with dissipation monitoring at a range of timescales. Surprisingly, the capacity can vary by as much as 1,000% depending on the electrolyte, in which certain ions enable better kinetics, higher capacity and higher cycling stability.

Charge Transfer in Spatially Defined Organic Radical Polymers.

Charge transfer in nonconjugated redox-active polymers is influenced by redox site proximity and polymer flexibility, but it is challenging to observe these effects independently. In this work, spatially defined radical-containing polymers are synthesized by using acyclic diene metathesis (ADMET) polymerization of α,ω-dienes bearing a central activated ester. Postpolymerization functionalization with 4-amino-2,2,6,6-tetramethylpiperidine-1-oxyl (4-amino-TEMPO) introduces TEMPO radical groups onto the polymer backbone through amide linkages to yield spatially defined polymers with radical units every 9, 11, 15, and 21 carbons. Increased radical spacing leads to reduced spin-spin coupling and increased chain flexibility. The glass transition temperatures (Tg) range from 47.6 to -13.8 °C, depending on the radical spacing. The spatially defined TEMPO-substituted polymer with a spacing length of 15 carbons displays the lowest Tg and the shortest hopping distance, as shown through molecular dynamics simulations. Also, this polymer displays kinetics 1000 times faster than the commonly studied TEMPO-containing polymer poly(2,2,6,6-tetramethylpiperidinyloxy-4-ylacrylamide) (PTAm). Remarkably, comparison of the diffusion and kinetics attributed to the redox reaction reveals that both the apparent diffusion coefficient and the self-exchange reaction rate constant are correlated to the polymer's Tg as log[Dapp] and log[kex,app] ∼ Tg, respectively. Critically, these data demonstrate that controlling the spacing of redox-active groups along a polymer backbone strongly influences backbone flexibility and radical packing, which leads to synergetic improvements in the charge transfer kinetics of nonconjugated redox-active polymers.

Local structure elucidation of tungsten-substituted vanadium dioxide (V[Formula: see text]W[Formula: see text]O[Formula: see text]).

Initially, vanadium dioxide seems to be an ideal first-order phase transition case study due to its deceptively simple structure and composition, but upon closer inspection there are nuances to the driving mechanism of the metal-insulator transition (MIT) that are still unexplained. In this study, a local structure analysis across a bulk powder tungsten-substitution series is utilized to tease out the nuances of this first-order phase transition. A comparison of the average structure to the local structure using synchrotron x-ray diffraction and total scattering pair-distribution function methods, respectively, is discussed as well as comparison to bright field transmission electron microscopy imaging through a similar temperature-series as the local structure characterization. Extended x-ray absorption fine structure fitting of thin film data across the substitution-series is also presented and compared to bulk. Machine learning technique, non-negative matrix factorization, is applied to analyze the total scattering data. The bulk MIT is probed through magnetic susceptibility as well as differential scanning calorimetry. The findings indicate the local transition temperature ([Formula: see text]) is less than the average [Formula: see text] supporting the Peierls-Mott MIT mechanism, and demonstrate that in bulk powder and thin-films, increasing tungsten-substitution instigates local V-oxidation through the phase pathway VO[Formula: see text] V[Formula: see text]O[Formula: see text] V[Formula: see text]O[Formula: see text].

Electromagnetic Force-Driven Needle-Free in Ovo Injection Device.

Needle-free injections are mainly used for administering human or mammalian vaccines or drugs. However, poultry vaccines, in ovo injections to embryos, subcutaneous injections to chickens, and intramuscular injections are administered using needle injections. This article presents a new needle-free in ovo injection device method that uses push-pull solenoids to eject liquid jets, mainly for embryonic eggs of chickens. Furthermore, our study investigated the suitable jet pressures for using this method and the post-injection hatching rates in 18-day-old embryonic eggs. Using this method, we could deliver the liquid to the allantoic and amniotic cavities or the muscle tissue through the egg membrane of the air chamber using a jet pressure of ~6-7 MPa or ~8 MPa. After injecting 0.25 mL of 0.9% saline into 18-day-old Lohmann breed layer embryonic eggs and specific pathogen-free (SPF) embryonic eggs at a jet pressure of ~7 MPa, we observed hatching rates of 98.3% and 85.7%, respectively. This study's electromagnetic needle-free in ovo injection device can apply vaccine or nutrient solution injection for embryo eggs and serve as a reference for future studies on needle-free in ovo injection automation systems, jet pressure control, and injection pretreatment processes.

Duck Eggshell Crack Detection by Nondestructive Sonic Measurement and Analysis.

Duck eggs are a good source of essential nutrients for the human body. However, transportation, processing, and handling can easily cause cracks in the eggshells. These cracks can lead to microbial contamination, reducing the shelf life and compromising food safety. In this study, a method for the nondestructive testing of cracks in duck eggshells was developed. First, the acoustic emission signals of intact and cracked eggshells were measured, and the most significant frequency features were selected to establish a calibration curve for cracked eggshells. Logistic regression using the frequency features was then adopted to predict intact and cracked eggshells. Then, we establish a set of optimal regression models and used independent samples for verification. The overall accuracy rates of the calibration and prediction models using five frequencies of bandwidth (1500, 5000, 6000, 8500, and 10,000 Hz) were 89.7% and 87.6%, respectively. Sound measurement enables a simple and quantitative method for duck egg crack detection and classification. This nondestructive and cost-effective method can be used for duck egg quality screening and can be integrated into duck egg processing machinery.

Effects of electromagnetic waves on oocyte maturation and embryonic development in pigs.

Our living environment has been full of electromagnetic radiation (EMR) due to the prevailing electronic devices and equipment. Intermediate frequency electromagnetic field (IF-EMF) or waves constitute a significant part of EMR; therefore, an increasing number of household electrical appliances have become a source of IF-EMF, and concerns about IF-EMF on health are gaining more attention. However, little information is available about its impact on female reproductive traits, such as germ cell viability and early embryonic development, particularly at the cellular and molecular levels. In this study, we used porcine oocytes as a model system to explore the effect of IF-EMF at various intensities on the in vitro maturation (IVM) of oocytes and their subsequent embryonic development. Our results showed that no difference in oocyte maturation rates was detected among groups, but the cleavage and blastocyst rates of parthenotes derived from EMF-treated oocytes decreased with the weaker IF-EMF intensity (25 and 50 Gauss) groups compared to the control group (P < 0.05). For cytoplasmic maturation, the weaker IF-EMF intensity groups also showed a peripheral pattern of mitochondrial distribution resembling that of immature oocytes and increased autophagy activity. No obvious differences in cytoskeletal distribution and total cell numbers of blastocysts were investigated in the four IF-EMF treatments compared to those in the control group. Although the underlying mechanism associated with EMF effects on oocytes and embryos is still elusive, we have demonstrated that low intensity IF-EMF exerts harmful effects on porcine oocytes during the maturation stage, carrying over such effects to their subsequent embryonic development.

Real-Time Gauging of the Gelling Maturity of Duck Eggs Pickled in Strong Alkaline Solutions.

Although many ultraviolet-visible-near-infrared transmission spectroscopy techniques have been applied to chicken egg studies, such techniques are not suitable for duck eggs because duck eggshells are much thicker than chicken eggshells. In this study, a high-transmission spectrometer using an equilateral prism as a dispersive element and a flash lamp as a light source was constructed to nondestructively detect the transmission spectrum of duck eggs and monitor the pickling of eggs. The evolution of egg transmittance was highly correlated with the albumen during pickling. The transmittance exponentially decays with time during this period, and the decay rate is related to the pickling rate. The colors of the albumen and yolk remain almost unchanged in the first stage. A multiple linear regression analysis model that realizes a one-to-one association between the days of pickling and the transmission spectra was constructed to determine the pickling duration in the second stage. The coefficient of determination reached 0.88 for a single variable, wavelength, at 590 nm. This method can monitor the maturity of pickled eggs in real time and does not require the evolution of light transmittance.

Deactivation-free ethanol steam reforming at nickel-tipped carbon filaments.

Ni based catalysts have been widely studied for H2 production due to the ability of Ni to break C-C and C-H bonds. In this work, we study inverse catalysts prepared by well-controlled sub-monolayer deposition of CeO2 nanocubes onto Ni thin films for ethanol steam reforming (ESR). Results show that controlling the coverage of CeO2 nanocubes on Ni enhances H2 production by more than an order of magnitude compared to pure Ni. Contrary to the idea that C deposits must be continuously oxidized for sustained H2 production, the surface of the most active catalysts show significant C deposition, yet no deactivation is observed. HAADF-STEM analysis reveals the formation of carbon filaments (CFILs), which propel Ni particles upward at the filament tips via a catalytic tip growth mechanism, resulting in a Ni@CFIL active phase for ESR. Near-ambient pressure XPS indicates that the Ni@CFIL active phase forms as a result of C gradients at the interface between regions of pure Ni metal and domains of closely packed CeO2 nanocubes. These results show that the mesoscale morphology of deposited CeO2 nanocubes is responsible for templating the formation of a Ni@CFIL catalyst, which resists deactivation leading to highly active and stable H2 production from ethanol.

Supersensitive CeOx-based nanocomposite sensor for the electrochemical detection of hydroxyl free radicals.

It is well known that an excess of hydroxyl radicals (˙OH) in the human body is responsible for oxidative stress-related diseases. An understanding of the relationship between the concentration of ˙OH and those diseases could contribute to better diagnosis and prevention. Here we present a supersensitive nanosensor integrated with an electrochemical method to measure the concentration of ˙OH in vitro. The electrochemical sensor consists of a composite comprised of ultrasmall cerium oxide nanoclusters (<2 nm) grafted to a highly conductive carbon deposited on a screen-printed carbon electrode (SPCE). Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were used to analyze the interaction between cerium oxide nanoclusters and ˙OH. The CV results demonstrated that this electrochemical sensor had the capacity of detecting ˙OH with a high degree of accuracy and selectivity, achieving a consistent performance. Additionally, EIS results confirmed that our electrochemical sensor was able to differentiate ˙OH from hydrogen peroxide (H2O2), which is another common reactive oxygen species (ROS) found in the human body. The limit of detection (LOD) observed with this electrochemical sensor was of 0.6 µM. Furthermore, this nanosized cerium oxide-based electrochemical sensor successfully detected in vitro the presence of ˙OH in preosteoblast cells from newborn mouse bone tissue. The supersensitive electrochemical sensor is expected to be beneficially used in multiple applications, including medical diagnosis, fuel-cell technology, and food and cosmetic industries.

Nondestructive Detection of the Gel State of Preserved Eggs Based on Dielectric Impedance.

After completing the production of preserved eggs, traditionally, the degree of gelling is judged by allowing workers to tap the preserved eggs with their fingers and sense the resulting oscillations. The amount of oscillation is used for the quality classification. This traditional method produces varying results owing to the differences in the sensitivity of the individual workers, who are not objective. In this study, dielectric detection technology was used to classify the preserved eggs nondestructively. The impedance in the frequency range of 2-300 kHz was resolved into resistance and reactance, and was plotted on a Nyquist diagram. Next, the diagram curve was fitted in order to obtain the equivalent circuit, and the difference in the compositions of the equivalent circuits corresponding to gelled and non-gelled preserved eggs was analyzed. A preserved egg can be considered an RLC series circuit, and its decay rate is consistent with the decay rate given by mechanical vibration theory. The Nyquist diagrams for the resistance and reactance of preserved eggs clearly showed that the resistance and reactance of gelled and non-gelled eggs were quite different, and the classification of the eggs was performed using Bayesian network (BN). The results showed that a BN classifier with two variables, i.e., resistance and reactance, can be used to classify preserved eggs as gelled or non-gelled, with an accuracy of 81.0% and a kappa value of 0.62. Thus, a BN classifier based on resistance and reactance demonstrates the ability to classify the quality of preserved egg gel. This research provides a nondestructive method for the inspection of the quality of preserved egg gel, and provides a theoretical basis for the development of an automated preserved egg inspection system that can be used as the scientific basis for the determination of the quality of preserved eggs.

Quality Assessment during Incubation Using Image Processing.

The fertilized egg is an indispensable production platform for making egg-based vaccines. This study was divided into two parts. In the first part, image processing was employed to analyze the absorption spectrum of fertilized eggs; the results show that the 580-nm band had the most significant change. In the second part, a 590-nm-wavelength LED was selected as the light source for the developed detection device. Using this device, sample images (in RGB color space) of the eggs were obtained every day during the experiment. After calculating the grayscale value of the red layer, the receiver operating characteristic curve was used to analyze the daily data to obtain the area under the curve. Subsequently, the best daily grayscale value for classifying unfertilized eggs and dead-in-shell eggs was obtained. Finally, an industrial prototype of the device designed and fabricated in this study was operated and verified. The results show that the accuracy for detecting unfertilized eggs was up to 98% on the seventh day, with the sensitivity and Youden's index being 82% and 0.813, respectively. On the ninth day, both accuracy and sensitivity reached 100%, and Youden's index reached a value of 1, showing good classification ability. Considering the industrial operating conditions, this method was demonstrated to be commercially applicable because, when used to detect unfertilized eggs and dead-in-shell eggs on the ninth day, it could achieve accuracy and sensitivity of 100% at the speed of five eggs per second.

Origin and Suppression of Beam Damage-Induced Oxygen-K Edge Artifact from γ-Al2O3 using Cryo-EELS.

Gamma-alumina (γ-Al2O3), like other low-Z oxides, is readily damaged when exposed to an electron beam. This typically results in the formation of a characteristic pre-edge peak in the oxygen-K edge of electron energy-loss spectra (EELS) acquired during or after the damage process. This artifact can mask the presence of intrinsic O-K edge fine structure that would reveal chemical properties of the material; therefore, its suppression is key. In this work, we systematically investigate the conditions that give rise to the damage-induced O-K pre-edge peak and show that it can be effectively suppressed by performing EELS experiments at cryogenic (cryo) temperatures. Prolonged exposure of γ-Al2O3 to a focused electron beam results in a hole bored through the sample; this was used as a reproducible beam damage condition. O-K edge EELS spectra were collected from a single-crystal γ-Al2O3 sample both during and after focused electron beam hole drilling, and at room and cryo temperatures, using a monochromated scanning transmission electron microscope (STEM). The characteristic 531 eV pre-edge peak visible in the room temperature EELS spectra was completely suppressed in the cryo-EELS spectra, even in the presence of a visible drilled hole. We then correlated these experimental observations with multiple-scattering EELS simulations to determine the likely atomistic origin of the damage-induced O-K pre-edge peak. The findings indicate that the pre-edge peak is caused primarily by the presence of surface O-O bonds formed during beam damage, and that operating at cryo temperature suppresses the formation of surface O-O bonds, thus preventing formation of the O-K pre-edge peak. Additionally, Al-L2,3 edge EELS spectra revealed Al loss primarily from tetrahedral sites during hole drilling.

Prediction of visual outcomes by an artificial neural network following intravitreal injection and laser therapy for retinopathy of prematurity.

AIMS: To construct a program to predict the visual acuity (VA), best corrected VA (BCVA) and spherical equivalent (SE) of patients with retinopathy of prematurity (ROP) from 3 to 12 years old after intravitreal injection (IVI) of anti-vascular endothelial growth factor and/or laser photocoagulation treatment. METHODS: This retrospective study employed a feedforward artificial neural network with an error backpropagation learning algorithm to predict visual outcomes based on patient birth data, treatment received and age at follow-up. Patients were divided into two groups based on prior treatments. The main outcome measures were the difference between the predicted and actual values of visual outcomes. These were analysed using the normalised root mean square error (RMSE). Two-way repeated measures analysis of variance was used to compare the predictive accuracy by this algorithm. RESULTS: A total of 60 ROP infants with prior treatments were included. In the IVI group, the normalised average RMSE for VA, BCVA, and SE was 0.272, 0.185 and 0.131, respectively. In the laser group, the normalised average RMSE for VA, BCVA and SE was 0.190, 0.250 and 0.104, respectively. This result shows that better predictive power was obtained for SE than for VA or BCVA in both the IVI and laser groups (p<0.001). In addition, the algorithm performed slightly better in predicting visual outcomes in the laser group (p<0.001). CONCLUSIONS: This algorithm offers acceptable power for predicting visual outcomes in patients with ROP with prior treatment. Predictions of SE were more precise than predictions of for VA and BCVA in both groups.

Proton pump inhibitors therapy and the risk of pneumonia: a systematic review and meta-analysis of randomized controlled trials and observational studies.

OBJECTIVE: We aimed to summarize the current evidence regarding the risk of pneumonia associated with proton pump inhibitors (PPI) treatment. METHODS: We searched PubMed, Embase, and CENTRAL from the 1970 through December 2017. We included both randomized controlled trials (RCTs) and observational studies. We used random-effect model to calculate the summary effect estimates and quantified the heterogeneity by I2 statistics. RESULTS: A total of 7,643,982 patients from 10 RCTs and 48 observational studies were included in this meta-analysis. The primary meta-analysis demonstrated PPIs use was significantly associated with increased risk of pneumonia, but the heterogeneity was high (odds ratio [OR], 1.43; 95% confidence interval [CI], 1.30-1.57; I2, 95.4%). The sensitivity analysis indicated PPIs were not statistically associated with increased risk of pneumonia among patients concomitantly taking nonsteroidal anti-inflammatory drugs (OR, 1.11; 95% CI, 0.94-1.31; I2, 5.8%). The funnel plot demonstrated significant publication bias, especially for observational studies. CONCLUSIONS: The presence of significant between-study heterogeneity and publication bias raised concerns regarding the validity of the primary meta-analytic result. Protopathic bias, or reverse causality, may cause overestimated association. Studies that adopted a design to account for protopathic bias did not show a significant association between PPI use and risk of pneumonia.