Clinical and pathogen features of COVID-19-associated infections during an Omicron strain outbreak in Guangzhou, China.

Although the Omicron variant has been associated with greater transmissibility and tropism of the upper respiratory tract, the clinical and pathogenic features of patients infected with the Omicron variant during an outbreak in China have been unclear. Adults with COVID-19 were retrospectively enrolled from seven medical centers in Guangzhou, China, and clinical information and specimens ( BALF, sputum, and throat swabs) from participants were collected. Conventional detection methods, metagenomics next-generation sequencing (mNGS), and other methods were used to detect pathogens in lower respiratory tract samples. From December 2022 to January 2023, we enrolled 836 patients with COVID-19, among which 56.7% patients had severe/critical illness. About 91.4% of patients were infected with the Omicron strain (BA.5.2). The detection rate of possible co-infection pathogens was 53.4% by mNGS, including Klebsiella pneumoniae (16.3%), Aspergillus fumigatus (12.2%), and Pseudomonas aeruginosa (11.8%). The co-infection rate was 19.5%, with common pathogens being Streptococcus pneumoniae (11.5%), Haemophilus influenzae (9.2%), and Adenovirus (6.9%). The superinfection rate was 75.4%, with common pathogens such as Klebsiella pneumoniae (26.1%) and Pseudomonas aeruginosa (19.4%). Klebsiella pneumoniae (27.1%% vs 6.1%, P < 0.001), Aspergillus fumigatus (19.6% vs 5.3%, P = 0.001), Acinetobacter baumannii (18.7% vs 4.4%, P = 0.001), Pseudomonas aeruginosa (16.8% vs 7.0%, P = 0.024), Staphylococcus aureus (14.0% vs 5.3%, P = 0.027), and Streptococcus pneumoniae (0.9% vs 10.5%, P = 0.002) were more common in severe cases. Co-infection and superinfection of bacteria and fungi are common in patients with severe pneumonia associated with Omicron variant infection. Sequencing methods may aid in the diagnosis and differential diagnosis of pathogens. IMPORTANCE: Our study has analyzed the clinical characteristics and pathogen spectrum of the lower respiratory tract associated with co-infection or superinfection in Guangzhou during the outbreak of the Omicron strain, particularly after the relaxation of the epidemic prevention and control strategy in China. This study will likely prompt further research into the specific issue, which will benefit clinical practice.

Integrative Proteomic and Metabolomic Elucidation of Cardiomyopathy with in vivo, in vitro Models and Clinical Samples.

Cardiomyopathy is a prevalent cardiovascular disease that affects individuals of all ages and can lead to life-threatening heart failure. Despite its variety in types, each with distinct characteristics and causes, our understanding of cardiomyopathy at a systematic biology level remains incomplete. Mass spectrometry-based techniques have emerged as powerful tools, providing a comprehensive view of the molecular landscape and aiding in the discovery of biomarkers and elucidation of mechanism. This review highlights the significant potential of integrating proteomic and metabolomic approaches with specialized databases to identify biomarkers and therapeutic targets across different types of cardiomyopathies. In vivo and in vitro models, such as genetically modified mice, patient-derived or induced pluripotent stem cells, and organ chips, are invaluable in exploring the pathophysiological complexities of this disease. By integrating omics approaches with these sophisticated modelling systems, our comprehension of the molecular underpinnings of cardiomyopathy can be greatly enhanced, facilitating the development of diagnostic markers and therapeutic strategies. Among the promising therapeutic targets are those involved in extracellular matrix remodeling, sarcomere damage, and metabolic remodeling. These targets hold potential for the advancement of precision therapy in cardiomyopathy, offering hope for more effective treatments tailored to the specific molecular profiles of patients.

Single-Cell Time-Resolved Metabolomics and Lipidomics Reveal Apoptotic and Ferroptotic Heterogeneity during Foam Cell Formation.

Macrophage-derived foam cells play a crucial role in plaque formation and rupture during the progression of atherosclerosis. Traditional studies have often overlooked the heterogeneity of foam cells, focusing instead on populations of cells. To address this, we have developed time-resolved, single-cell metabolomics and lipidomics approaches to explore the heterogeneity of macrophages during foam cell formation. Our dynamic metabolomic and lipidomic analyses revealed a dual regulatory axis involving inflammation and ferroptosis. Further, single-cell metabolomics and lipidomics have delineated a continuum of macrophage states, with varied susceptibilities to apoptosis and ferroptosis. Single-cell transcriptomic profiling confirmed these divergent fates, both in established cell lines and in macrophages derived from peripheral blood monocytes. This research has uncovered the complex molecular interactions that dictate these divergent cell fates, providing crucial insights into the pathogenesis of atherosclerosis.

Electronic cooling and energy harvesting using ferroelectric polymer composites.

Thermal management emerges as a grand challenge of next-generation electronics. Efforts to develop compact, solid-state cooling devices have led to the exploration of the electrocaloric effect of ferroelectric polymers. Despite recent advances, the applications of electrocaloric polymers on electronics operating at elevated temperatures remain essentially unexplored. Here, we report that the ferroelectric polymer composite composed of highly-polarized barium strontium titanate nanofibers and electron-accepting [6,6] phenyl-C61-butyric acid methyl ester retains fast electrocaloric responses and stable cyclability at elevated temperatures. We demonstrate the effectiveness of electrocaloric cooling in a polymer composite for a pyroelectric energy harvesting device. The device utilizes a simulated central processing unit (CPU) as the heat source. Our results show that the device remains operational even when the CPU is overheated. Furthermore, we show that the composite functions simultaneously as a pyroelectric energy converter to harvest thermal energy from an overheated chip into electricity in the electrocaloric process. This work suggests a distinct approach for overheating protection and recycling waste heat of microelectronics.

Magnesium Ion: A New Switch in Tumor Treatment.

The magnesium ion is an essential cation in the human body and participates in numerous physiological activities. A deficiency in magnesium ions is closely associated with tumor development, and supplementation with magnesium ions has been shown to partially inhibit tumor growth. However, the specific mechanisms by which magnesium ions suppress tumor proliferation remain unclear. Currently, studies have revealed that mitochondria may serve as a crucial intermediate link in the regulation of tumors by magnesium ions. Mitochondria might intervene in the proliferation and invasion of tumor cells by modulating energy metabolism and oxidative stress levels. Regrettably, there has been no comprehensive review of the role of magnesium in cancer therapy to date. Therefore, this article provides a comprehensive scrutiny of the relationship between magnesium ions and tumors, aiming to offer insights for clinical tumor treatment strategies involving magnesium ion intervention.

Long Noncoding RNA NR_030777 Alleviates Cobalt Nanoparticles-Induced Neurodegenerative Damage by Promoting Autophagosome-Lysosome Fusion.

Potential exposure to cobalt nanoparticles (CoNPs) occurs in various fields, including hard alloy industrial production, the increasing use of new energy lithium-ion batteries, and millions of patients with metal-on-metal joint prostheses. Evidence from human, animal, and in vitro experiments suggests a close relationship between CoNPs and neurotoxicity. However, a systematic assessment of central nervous system (CNS) impairment due to CoNPs exposure and the underlying molecular mechanisms is lacking. In this study, we found that CoNPs induced neurodegenerative damage both in vivo and in vitro, including cognitive impairment, ß-amyloid deposition and Tau hyperphosphorylation. CoNPs promoted the formation of autophagosomes and impeding autophagosomal-lysosomal fusion in vivo and in vitro, leading to toxic protein accumulation. Moreover, CoNPs exposure reduced the level of transcription factor EB (TFEB) and the abundance of lysosome, causing a blockage in autophagosomal-lysosomal fusion. Interestingly, overexpression of long noncoding RNA NR_030777 mitigated CoNPs-induced neurodegenerative damage in both in vivo and in vitro models. Fluorescence in situ hybridization assay revealed that NR_030777 directly binds and stabilizes TFEB mRNA, alleviating the blockage of autophagosomal-lysosomal fusion and ultimately restoring neurodegeneration induced by CoNPs in vivo and in vitro. In summary, our study demonstrates that autophagic dysfunction is the main toxic mechanism of neurodegeneration upon CoNPs exposure and NR_030777 plays a crucial role in CoNPs-induced autophagic dysfunction. Additionally, the proposed adverse outcome pathway contributes to a better understanding of CNS toxicity assessment of CoNPs.

Robust Long-Nanowire Fabrication by Clean-Phase-Assisted Micro Chemical Pen for Enhanced Bioassay Sensitivity.

Long nanowires offer an increased surface area for biomolecule immobilization, facilitating enhanced binding capacity and sensitivity in the detection of target analytes. However, robust long-nanowire fabrication remains a significant challenge. In this paper, we developed a novel construction of a micro chemical pen (MCP), called a clean-assisted micro chemical pen (CAMCP), for robust long-nanowire fabrication. CAMCP, based on localized hydrodynamic flow confinement, was conducted by incorporating a clean phase to effectively dissolve aggregated silver particles in the aspiration channel's shell, thereby enhancing the MCP's longevity by 60.84%, allowing for an 840 µm extension in nanowire patterning capability. A 4600-aspect ratio (length:1200 µm, width: 260 nm) nanowire was fabricated by CAMCP and utilized as a nanowire sensor, showing a 39.7% increase in IgA detection sensitivity compared to a 3000-aspect ratio sensor. Furthermore, the longer nanowire sensor exhibited enhanced signal responses, a higher signal-to-noise ratio, and a lower limit of detection (LOD). The preponderant bioassay performances of the longer nanowire sensor in bioassays, facilitated by CAMCP, open up its possibilities for chemical-synthesis nanowires (NWs) in ultrasensitive biodetection.

Multi-omics analysis identified extracellular vesicles as biomarkers for cardiovascular diseases.

Cell-derived extracellular vesicles (EVs) have emerged as a promising non-invasive liquid biopsy technique due to their accessibility and their ability to encapsulate and transport diverse biomolecules. EVs have garnered substantial research interest, notably in cardiovascular diseases (CVDs), where their roles in pathophysiology and as diagnostic and prognostic biomarkers are increasingly recognized. This review provides a comprehensive overview of EVs, starting with their origins, followed by the techniques used for their isolation and characterization. We explore the diverse cargo of EVs, including nucleic acids, proteins, lipids, and metabolites, highlighting their roles in intercellular communication and as potential biomarkers. We then delve into the application of genomics, transcriptomics, proteomics, and metabolomics in the analysis of EVs, particularly within the context of CVDs. Finally, we discuss how integrated multi-omics approaches are unveiling novel biomarkers, offering fresh insights into the diagnosis and prognosis of CVDs. This review underscores the growing importance of EVs in clinical diagnostics and the potential of multi-omics to propel future advancements in CVD biomarker discovery.

Integrating a deep neural network and Transformer architecture for the automatic segmentation and survival prediction in cervical cancer.

Background: Automated tumor segmentation and survival prediction are critical to clinical diagnosis and treatment. This study aimed to develop deep-learning models for automatic tumor segmentation and survival prediction in magnetic resonance imaging (MRI) of cervical cancer (CC) by combining deep neural networks and Transformer architecture. Methods: This study included 406 patients with CC, each with comprehensive clinical information and MRI scans. We randomly divided patients into training, validation, and independent test cohorts in a 6:2:2 ratio. During the model training, we employed two architecture types: one being a hybrid model combining convolutional neural network (CNN) and ransformer (CoTr) and one of pure CNNs. For survival prediction, the hybrid model combined tumor image features extracted by segmentation models with clinical information. The performance of the segmentation models was evaluated using the Dice similarity coefficient (DSC) and 95% Hausdorff distance (HD95). The performance of the survival models was assessed using the concordance index. Results: The CoTr model performed well in both contrast-enhanced T1-weighted (ceT1W) and T2-weighted (T2W) imaging segmentation tasks, with average DSCs of 0.827 and 0.820, respectively, which outperformed other the CNN models such as U-Net (DSC: 0.807 and 0.808), attention U-Net (DSC: 0.814 and 0.811), and V-Net (DSC: 0.805 and 0.807). For survival prediction, the proposed deep-learning model significantly outperformed traditional methods, yielding a concordance index of 0.732. Moreover, it effectively divided patients into low-risk and high-risk groups for disease progression (P<0.001). Conclusions: Combining Transformer architecture with a CNN can improve MRI tumor segmentation, and this deep-learning model excelled in the survival prediction of patients with CC as compared to traditional methods.

Microfluidic Engineering of Addressable Multicompartmental Microspheres for Multicellular Systems.

With the advantages of high-throughput manufacturing and customizability, on-microsphere construction of in vitro multicellular analytical systems has garnered significant attention. However, achieving a precise, biocompatible cell arrangement and spatial signal analysis in hydrogel microspheres remains challenging. In this work, a microfluidic method is reported for the biocompatible generation of addressable supersegmented multicompartmental microspheres. Additionally, these microspheres are developed as novel label-free multicellular systems. In the microfluidic approach, controllable microfluidics is used to finely tune the internal microstructure of the microspheres, and the gas ejector ensures the biocompatibility of the preparation process. As a proof of concept, six- and twenty-compartment microspheres were obtained without the addition of any biohazardous reagents. For microsphere decoding, the visualization of two basic compartments can provide clues for identifying label-free cells due to the structural regularity of the microspheres. Finally, by encapsulating cells of different types, these microspheres as multicellular systems were successfully used for cell coculture and drug testing. These biocompatible, scalable, and analyzable microspheres will open up new prospects for biomedical analysis.

Efficacy and safety of extracorporeal shock wave therapy for upper limb tendonitis: a systematic review and meta-analysis of randomized controlled trials.

Objective: This study synthesized the highest level of evidence to analyse the effectiveness and safety of using extracorporeal shock wave therapy (ESWT) to treat upper limb tendonitis, which was unknown. Design: We conducted a systematic review and meta-analysis of 18 randomized controlled trials (RCTs) in PubMed, Embase, Web of Science, Medline, and the Cochrane Library. Methods: Two researchers performed the screening, data extraction, literature quality assessment, and heterogeneity analysis of the searched RCTs. Results: The main types of morbidity included rotator cuff tendonitis, lateral epicondylitis, finger tendonitis, and long bicipital tendonitis. The results of the meta-analysis showed that ESWT was effective in relieving pain in all four types of tendonitis. In addition, ESWT was more effective in relieving pain in patients with upper limb tendonitis than placebo at the 3- and 6-month follow-ups, especially with radial ESWT (RESWT). Data analysis of the forest plot showed that the experimental group with ESWT as an intervention had a significant improvement in function in patients with rotator cuff tendonitis at the 3-month follow-up. However, subgroup analysis showed that low-energy ESWT was effective in improving function in patients with calcified and non-calcified rotator cuff tendonitis, whereas it was not effective in relieving pain. Conclusion: ESWT can effectively improve the functional activity in patients with rotator cuff tendonitis and may produce positive analgesic effects in patients with upper limb tendonitis. The incidence of adverse effects is low. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023403594, identifier: PROSPERO, CRD42023403594.

Impact of COVID-19 on adverse reactions to subcutaneous specific immunotherapy in children:a retrospective cohort study.

BACKGROUND: COVID-19 is a new infectious disease. To investigate whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection increases the adverse reactions of subcutaneous specific immunotherapy (SCIT) in children. METHODS: This study was conducted by collecting relevant data from children who underwent house dust mite SCIT from April 3, 2021, to March 18, 2023, including information on the time of COVID-19 infection, symptoms, and adverse reactions after each allergen injection. A mixed effects model was used to analyze the changes in adverse reactions before and after the COVID-19 infection. RESULTS: Among the records of adverse reactions from 2658 injections in 123 children who underwent SCIT, the overall adverse reaction rate before COVID-19 infection was 39.8% and 30.0% after COVID-19 infection. Compared with pre-infection with COVID-19, the risks of overall adverse reactions, local adverse reactions, and systemic adverse reactions of immunotherapy after COVID-19 infection were reduced (odds ratio [OR] = 0.24, 0.31, and 0.28, all P < 0.05). Among the local adverse reactions, the incidence of the unvaccinated group was the highest (15.3% vs. 7.1%). The incidence of overall and local adverse reactions to SCIT decreased in 2-vaccinated COVID-19 recipients (OR = 0.29-0.31, P < 0.05). CONCLUSIONS: In children, SARS-CoV-2 infection does not increase the incidence of adverse reactions to SCIT. This finding can provide a basis for the implementation of allergen-specific immunotherapy (AIT) during the COVID-19 pandemic.

Maternal gestational diabetes mellitus associates with altered gut microbiome composition and head circumference abnormalities in male offspring.

The impact of gestational diabetes mellitus (GDM) on maternal or infant microbiome trajectory remains poorly understood. Utilizing large-scale longitudinal fecal samples from 264 mother-baby dyads, we present the gut microbiome trajectory of the mothers throughout pregnancy and infants during the first year of life. GDM mothers had a distinct microbiome diversity and composition during the gestation period. GDM leaves fingerprints on the infant's gut microbiome, which are confounded by delivery mode. Further, Clostridium species positively correlate with a larger head circumference at month 12 in male offspring but not females. The gut microbiome of GDM mothers with male fetuses displays depleted gut-brain modules, including acetate synthesis I and degradation and glutamate synthesis II. The gut microbiome of female infants of GDM mothers has higher histamine degradation and dopamine degradation. Together, our integrative analysis indicates that GDM affects maternal and infant gut composition, which is associated with sexually dimorphic infant head growth.

Microbiological characteristics of the lower airway in adults with bronchiectasis: a prospective cohort study.

BACKGROUND: Microbial infection and colonization are frequently associated with disease progression and poor clinical outcomes in bronchiectasis. Identification of pathogen spectrum is crucial for precision treatment at exacerbation of bronchiectasis. METHODS: We conducted a prospective cohort study in patients with bronchiectasis exacerbation onset and stable state. Bronchoalveolar lavage fluid (BALF) was collected for conventional microbiological tests (CMTs) and metagenomic Next-Generation Sequencing (mNGS). Bronchiectasis patients were monitored for documenting the time to the next exacerbation during longitudinal follow-up. RESULTS: We recruited 168 eligible participants in the exacerbation cohorts, and 38 bronchiectasis patients at stable state at longitudinal follow-up. 141 bronchiectasis patients at exacerbation onset had definite or probable pathogens via combining CMTs with mNGS reports. We identified that Pseudomonas aeruginosa, non-tuberculous mycobacteria, Haemophilus influenzae, Nocardia spp, and Staphylococcus aureus were the top 5 pathogens with a higher detection rate in our cohorts via combination of CMTs and mNGS analysis. We also observed strong correlations of Pseudomonas aeruginosa, Haemophilus influenzae, non-tuberculous mycobacteria with disease severity, including the disease duration, Bronchiectasis Severity Index, and lung function. Moreover, the adjusted pathogenic index of potential pathogenic microorganism negatively correlated (r = -0.7280, p < 0.001) with the time to the next exacerbation in bronchiectasis. CONCLUSION: We have revealed the pathogenic microbial spectrum in lower airways and the negative correlation of PPM colonization with the time to the next exacerbation in bronchiectasis. These results suggested that pathogens contribute to the progression of bronchiectasis.

Causal relationship between Helicobacter pylori infection and IgA nephropathy: a bidirectional two-sample mendelian randomization study.

IgA nephropathy (IgAN) is one of the most common primary glomerulonephritis, and serum Helicobacter pylori (H. pylori) antibody levels are increased in patients with IgA N, but the role of H. pylori infection in the pathogenesis of IgAN is unclear. In this study, we investigated whether there is a causal relationship and reverse causality between IgAN and H. pylori infection by using a bidirectional two-sample Mendelian randomization (MR) analysis. This study was estimated using inverse variance weighted (IVW), MR-Egger and weighted median methods, with the IVW method having the strongest statistical efficacy. Seven common serum H. pylori antibodies were selected as exposure factors for positive MR analysis. The results showed that there was no evidence of a causal relationship between H. pylori infection and IgAN. Reverse MR analysis showed that there was also no evidence that the occurrence of IgAN leads to an increased risk of H. pylori infection.

The U-shape relationship between insulin resistance-related indexes and chronic kidney disease: a retrospective cohort study from National Health and Nutrition Examination Survey 2007-2016.

BACKGROUND: There is ongoing debate on the correlation between chronic kidney disease (CKD) and insulin resistance (IR)-related indices. Our objective was to explore the prognostic ability of IR-related indexes for the prevalence of CKD, as well as the mortality from all causes and cardiovascular disease (CVD) in CKD patients. METHODS: The data used in this study came from the National Health and Nutrition Examination Survey (NHANES). Binary logistic regression analysis, Cox proportional hazards model, and restricted cubic spline (RCS) were used to analyze the relationship between IR-related indexes, including metabolic score of IR (METS-IR), homeostatic model assessment for IR (HOMA-IR), triglyceride glucose index (TyG), triglyceride glucose-waist-to-height ratio (TyG-WHtR), triglyceride glucose-body mass index (TyG-BMI), with CKD and its all-cause mortality and CVD mortality. Subgroup analysis was performed to test the stability of the results. Finally, the predictive power of IR-related indexes for CKD was tested by the receiver operating characteristic (ROC) curve. RESULTS: Among the recruited 10,660 participants, 15.42% were CKD patients. All IR-related indexes were found to be nonlinearly correlated to the prevalence of CKD in the study. When the TyG index was higher than 9.05, it was positively associated with CKD (OR: 1.77, 95% CI 1.44-2.18). Moreover, increased TyG-WHtR level was correlated with a greater prevalence of CKD when it was higher than 4.3 (OR: 1.31, 95% CI 1.19-1.45). Other IR-related indexes (METS-IR, HOMA-IR, and TyG-BMI) showed fewer notable correlations with CKD. The association of IR-related indexes and the prevalence of CKD remained consistent in most subgroups (P for interactions > 0.05). TyG-WHtR was also the predictor of all-cause mortality in CKD patients (HR: 1.34, 95% CI 1.14-1.58), while other IR-related indexes were not correlated with the all-cause mortality or CVD mortality in CKD patients (P > 0.05). Otherwise, ROC curves showed that TyG-WHtR had more robust diagnostic efficacy than other IR-related indexes (METS-IR, HOMA-IR, TyG, and TyG-BMI) in predicting CKD (area under the curve: 0.630, 95% CI 0.615-0.644). CONCLUSIONS: IR-related biomarkers (METS-IR, HOMA-IR, TyG, and TyG-BMI) were positively correlated with the prevalence of CKD. Moreover, TyG-WHtR enhanced CKD and its all-cause mortality prediction. In patients with elevated levels of IR-related indexes, the early detection and intervention of IR may reduce the occurrence of CKD and the prognosis of CKD patients.

Development of a Zr-Based Metal-Organic Framework (UiO-66) for a Cooperative Flame Retardant in the PC/ABS.

Polycarbonate/acrylonitrile butadiene styrene (PC/ABS) blends are widely used as engineering plastic alloys; however, they have a low fire safety level. To improve the flame-retardant property of PC/ABS, a zirconium-based metal-organic framework material (UiO-66) was synthesized with zirconium chloride and terephthalic acid and used as a flame-retardant cooperative agent. Its flame-retardant performance and mode of action in the PC/ABS blends were carefully investigated. The results showed that UiO-66 had good thermal stability and delayed the pyrolysis of the materials, thus significantly enhancing the efficiency of intumescent flame retardants. By compounding 7.0 wt% hexaphenyloxy-cyclotri-phosphazene (HPCTP) with 3.0 wt% UiO-66, the PC/ABS blends reached a limiting oxygen index value of 27.0% and V0 rating in the UL-94 test, showing significantly improved resistance to combustion dripping. In addition, UiO-66 enhanced the smoke and heat suppression characteristics of the intumescent flame-retardant materials. Finally, the flame-retardant mode of action in the blends was indicative of UiO-66 having a cooperative effect on the flame-retardant performance of PC/ABS/HPCTP materials. This work provides good ideas for further development of the flame-retardant ABS/PC.

Evaluating the small aperture intraocular lens: depth of focus and the role of refraction and preoperative corneal astigmatism on visual performance.

PURPOSE: To evaluate depth of focus (DOF) and visual acuities (VAs) by manifest refractive spherical equivalent (MRSE) and degree of preoperative corneal astigmatism with the IC-8® small aperture intraocular lens (SA IOL) (AptheraTM, Bausch & Lomb, Inc). SETTING: 21 investigational sites in the United States. DESIGN: Prospective, multi-center, open-label, parallel-group, non-randomized, examiner-masked, one-year clinical study. METHODS: Included patients had cataract and ≤1.5D preoperative corneal astigmatism. Patients received either the SA IOL in one eye targeted to -0.75D and a monofocal or monofocal toric IOL in the other targeted to plano (SA IOL Group) or bilateral monofocal/monofocal toric IOLs targeted to plano (Control Group). Monocular and binocular assessments included defocus curves and uncorrected VAs (distance, intermediate, and near) by postoperative MRSE; monocular VAs were assessed by degree of preoperative corneal astigmatism. RESULTS: The SA IOL Group (n=343) achieved 0.82D additional binocular DOF versus the Control Group (n=110), and SA IOL eyes achieved 0.91D additional monocular DOF over fellow eyes. Across all MRSEs, the SA IOL Group achieved monocular uncorrected VAs of 20/40 or better and binocular uncorrected VAs of 20/32 or better across all distances. Additionally, SA IOL eyes with higher (1.0-1.5D) versus lower (<1.0D) preoperative corneal astigmatism achieved equivalent monocular uncorrected VAs. CONCLUSIONS: The SA IOL provides increased DOF versus monofocal/monofocal toric IOLs and consistent monocular and binocular vision across several postoperative MRSEs and up to 1.5D of preoperative corneal astigmatism, giving patients with cataract and mild astigmatism the potential for an extended range of vision and reliable visual outcomes.

Using the High-Entropy Approach to Obtain Multimetal Oxide Nanozymes: Library Synthesis, In Silico Structure-Activity, and Immunoassay Performance.

High-entropy nanomaterials exhibit exceptional mechanical, physical, and chemical properties, finding applications in many industries. Peroxidases are metalloenzymes that accelerate the decomposition of hydrogen peroxide. This study uses the high-entropy approach to generate multimetal oxide-based nanozymes with peroxidase-like activity and explores their application as sensors in ex vivo bioassays. A library of 81 materials was produced using a coprecipitation method for rapid synthesis of up to 100 variants in a single plate. The A and B sites of the magnetite structure, (AA')(BB'B'')2O4, were substituted with up to six different cations (Cu/Fe/Zn/Mg/Mn/Cr). Increasing the compositional complexity improved the catalytic performance; however, substitutions of single elements also caused drastic reductions in the peroxidase-like activity. A generalized linear model was developed describing the relationship between material composition and catalytic activity. Binary interactions between elements that acted synergistically or antagonistically were identified, and a single parameter, the mean interaction effect, was observed to correlate highly with catalytic activity, providing a valuable tool for the design of high-entropy-inspired nanozymes.