Systematic Optimization of Universal Real-Time Hypersensitive Fast Detection Method for HBsAg in Serum Based on SERS.

Hepatitis B virus (HBV) is a major cause of liver cirrhosis and hepatocellular carcinoma, with HBV surface antigen (HBsAg) being a crucial marker in the clinical detection of HBV. Due to the significant harm and ease of transmission associated with HBV, HBsAg testing has become an essential part of preoperative assessments, particularly for emergency surgeries where healthcare professionals face exposure risks. Therefore, a timely and accurate detection method for HBsAg is urgently needed. In this study, a surface-enhanced Raman scattering (SERS) sensor with a sandwich structure was developed for HBsAg detection. Leveraging the ultrasensitive and rapid detection capabilities of SERS, this sensor enables quick detection results, significantly reducing waiting times. By systematically optimizing critical factors in the detection process, such as the composition and concentration of the incubation solution as well as the modification conditions and amount of probe particles, the sensitivity of the SERS immune assay system was improved. Ultimately, the sensor achieved a sensitivity of 0.00576 IU/mL within 12 min, surpassing the clinical requirement of 0.05 IU/mL by an order of magnitude. In clinical serum assay validation, the issue of false positives was effectively addressed by adding a blocker. The final sensor demonstrated 100% specificity and sensitivity at the threshold of 0.05 IU/mL. Therefore, this study not only designed an ultrasensitive SERS sensor for detecting HBsAg in actual clinical serum samples but also provided theoretical support for similar systems, filling the knowledge gap in existing literature.

Metabolomic profiling of the aqueous humor in patients with pediatric cataract.

Pediatric cataract, including congenital and developmental cataract, is a kind of pediatric vision-threatening disease with extensive phenotypic heterogeneity and multiple mechanisms. We aimed to investigate the metabolite profile of aqueous humor (AH) in patients with pediatric cataracts, and identify underlying mutual correlations between differential metabolites. Metabolomic profiles of AH were analyzed and compared between pediatric cataract patients (n = 33) and age-related cataract patients without metabolic diseases (n = 29), using global untargeted metabolomics with ultra-high-performance liquid chromatography tandem mass spectrometry. Principal component analysis, partial least squares discriminant analysis and heat map were applied. Enriched pathway analysis was conducted using Kyoto Encyclopedia of Genes and Genomes. Receiver-operating characteristic (ROC) analyses were employed to select potential biomarkers. A total of 318 metabolites were identified, of which 54 differential metabolites (25 upregulated and 29 downregulated) were detected in pediatric cataract group compared with controls (variable importance of projection >1.0, fold change ≥1.5 or ≤ 0.667 and P < 0.05). A significant accumulation of N-Acetyl-Dl-glutamic acid was observed in pediatric cataract group. The differential metabolites were mainly enriched in histidine metabolism (increased L-Histidine and decreased 1-Methylhistamine) and the tryptophan metabolism (increased N-Formylkynurenine and L-Kynurenine). 5-Aminosalicylic acid showed strong positive mutual inter-correlation with L-Tyrosinemethylester and N,N-Diethylethanolamine, both of which were down-regulated in pediatric cataract group. The ROC analysis implied 11 metabolites served as potential biomarkers for pediatric cataract patients (all area under the ROC curve ≥0.900). These results illustrated novel potential metabolites and metabolic pathways in pediatric cataract, which provides new insights into the pathophysiology of pediatric cataract.

Cost-effectiveness and cost-utility of a digital technology-driven hierarchical healthcare screening pattern in China.

Utilization of digital technologies for cataract screening in primary care is a potential solution for addressing the dilemma between the growing aging population and unequally distributed resources. Here, we propose a digital technology-driven hierarchical screening (DH screening) pattern implemented in China to promote the equity and accessibility of healthcare. It consists of home-based mobile artificial intelligence (AI) screening, community-based AI diagnosis, and referral to hospitals. We utilize decision-analytic Markov models to evaluate the cost-effectiveness and cost-utility of different cataract screening strategies (no screening, telescreening, AI screening and DH screening). A simulated cohort of 100,000 individuals from age 50 is built through a total of 30 1-year Markov cycles. The primary outcomes are incremental cost-effectiveness ratio and incremental cost-utility ratio. The results show that DH screening dominates no screening, telescreening and AI screening in urban and rural China. Annual DH screening emerges as the most economically effective strategy with 341 (338 to 344) and 1326 (1312 to 1340) years of blindness avoided compared with telescreening, and 37 (35 to 39) and 140 (131 to 148) years compared with AI screening in urban and rural settings, respectively. The findings remain robust across all sensitivity analyses conducted. Here, we report that DH screening is cost-effective in urban and rural China, and the annual screening proves to be the most cost-effective option, providing an economic rationale for policymakers promoting public eye health in low- and middle-income countries.

Correction: Mechanistic insights into Ag+ induced size-growth from [Au6(DPPP)4]2+ to [Au7(DPPP)4]2+ clusters.

[This corrects the article DOI: 10.1039/D2NA00301E.].

Early Diagnosis of Syndromic Congenital Cataracts in a Large Cohort of Congenital Cataracts.

PURPOSE: To explore the factors related to the diagnosis yield of syndromic congenital cataracts and describe the phenotype-genotype correlation in congenital cataract patients. DESIGN: Prospective cohort study. METHODS: Setting: the participants from underwent clinical examinations between 2021 and 2022. Facial and anterior eye segment photographs, pre- and postoperative ocular parameters, and medical and family histories were recorded. Bioinformatics analysis was performed using whole-exome sequencing data. Statistical and correlation analyses were performed using the basic characteristics, deep phenotype, and genotype data. PARTICIPANTS: 115 patients with unrelated congenital cataract. INTERVENTIONS: performing clinical examinations, whole-exome sequencing, and bioinformatics analysis for all participants. MAIN OUTCOMES AND MEASURES: factors related to the genetic diagnosis yield of syndromic congenital cataracts. RESULTS: Bilaterally asymmetrical cataracts were identified to be associated with syndromic congenital cataracts. The overall genetic diagnostic yield in the cohort was 72.2%. In total, 34.8% of the probands were early diagnosed with various syndromes with the help of genetic information. A phenotype-genotype correlation was detected for some genes and deep phenotypes. CONCLUSIONS: We highlight the importance of screening syndromic diseases in the patients with asymmetrical congenital cataracts. Application of whole-exome sequencing helps provide early diagnosis and treatment for the patients with syndromic congenital cataracts. This study also achieved a high genetic diagnostic yield, expanded the genotypic spectrum, and found phenotype-genotype correlations. A comprehensive analysis of cataract symmetricity, family history, and deep phenotypes makes the genotype prediction of some congenital cataract patients possible.

Comparing the impact of three-dimensional digital visualization technology versus traditional microscopy on microsurgeons in microsurgery: a prospective self-controlled study.

BACKGROUND: Emerging three-dimensional digital visualization technology (DVT) provides more advantages than traditional microscopy in microsurgery; however, its impact on microsurgeons' visual and nervous systems and delicate microsurgery is still unclear, which hinders the wider implementation of DVT in digital visualization for microsurgery. METHODS AND MATERIAL: Forty-two microsurgeons from the Zhongshan Ophthalmic Center were enrolled in this prospective self-controlled study. Each microsurgeon consecutively performed 30 min conjunctival sutures using a three-dimensional digital display and a microscope, respectively. Visual function, autonomic nerve activity, and subjective symptoms were evaluated before and immediately after the operation. Visual functions, including accommodative lag, accommodative amplitude, near point of convergence and contrast sensitivity function (CSF), were measured by an expert optometrist. Heart rate variability was recorded by a wearable device for monitoring autonomic nervous activity. Subjective symptoms were evaluated by questionnaires. Microsurgical performance was assessed by the video-based Objective Structured Assessment of Technical Skill (OSATS) tool. RESULTS: Accommodative lag decreased from 0.63 (0.18) diopters (D) to 0.55 (0.16) D ( P =0.014), area under the log contrast sensitivity function increased from 1.49 (0.15) to 1.52 (0.14) ( P =0.037), and heart rate variability decreased from 36.00 (13.54) milliseconds (ms) to 32.26 (12.35) ms ( P =0.004) after using the DVT, but the changes showed no differences compared to traditional microscopy ( P >0.05). No statistical significance was observed for global OSATS scores between the two rounds of operations [mean difference, 0.05 (95% CI: -1.17 to 1.08) points; P =0.95]. Subjective symptoms were quite mild after using both techniques. CONCLUSIONS: The impact of DVT-based procedures on microsurgeons includes enhanced accommodation and sympathetic activity, but the changes and surgical performance are not significantly different from those of microscopy-based microsurgery. Our findings indicate that short-term use of DVT is reliable for microsurgery and the long-term effect of using DVT deserve more consideration.

Myxofibrosarcoma involving brachial plexus diagnoses by contrast-enhanced ultrasound: A case report.

RATIONALE: Myxofibrosarcoma most commonly arises as a slowly enlarging, painless mass. We describe an unusual case of low-grade myxofibrosarcoma in the axillary fossa, which infiltrated the brachial plexus, axillary artery, and axillary vein, causing severe pain. The low incidence and complex anatomical structure make imaging examination and surgery face great challenges. To the best of our knowledge, such presentation of a low-grade myxofibrosarcoma that showed an extreme infiltrative growth pattern and presented severe pain has not been reported before. PATIENT CONCERNS: We reported a case of low-grade myxofibrosarcoma developed around the axillary neurovascular bundle, with multiple peripheral metastases in an 87-year-old male. Physical examination revealed a mass on the right axillary fossa measuring 5 × 4 cm. The patient underwent computed tomography but no definite diagnosis was obtained. Because he had claustrophobia and could not perform MRI examination. Thus, he underwent conventional ultrasound and contrast-enhanced ultrasound. Ultrasonic examination not only accurately determines the invasion scope of the tumor, but also clearly shows that the nerve has suffered from the invasion of the exogenous tumor and multiple metastatic foci around it. The contrast enhancement mode of the tumor showed centripetal high-enhancement, uneven internal enhancement, visible enhanced bridge, and non-enhancing central area. DIAGNOSES: Combined with the results of conventional ultrasound and contrast-enhanced ultrasound, we highly suspected it to be soft tissue sarcoma, giving strong clinical assistance. INTERVENTIONS: Given the risk of sarcoma implantation along the needle track and the underestimation of tumor malignancy, an excisional biopsy was considered the most practical choice to avoid unnecessary pain and potential implantation. OUTCOMES: The patient underwent surgery and a histopathological examination of the lesion confirmed it as low-grade myxofibrosarcoma. LESSONS SUBSECTIONS: This report describes a rare case of myxofibrosarcoma of the axillary fossa. High-resolution ultrasound is increasingly used for the initial assessment of soft-tissue masses. However, there are few reports about the ultrasound and contrast-enhanced ultrasound examinations of myxofibrosarcoma. Accurate preoperative diagnosis and proper treatment strategies are critical in managing patients with myxofibrosarcoma. Our case may provide diagnosis experiences and will help better understand and treat this disease.

LensAge index as a deep learning-based biological age for self-monitoring the risks of age-related diseases and mortality.

Age is closely related to human health and disease risks. However, chronologically defined age often disagrees with biological age, primarily due to genetic and environmental variables. Identifying effective indicators for biological age in clinical practice and self-monitoring is important but currently lacking. The human lens accumulates age-related changes that are amenable to rapid and objective assessment. Here, using lens photographs from 20 to 96-year-olds, we develop LensAge to reflect lens aging via deep learning. LensAge is closely correlated with chronological age of relatively healthy individuals (R2 > 0.80, mean absolute errors of 4.25 to 4.82 years). Among the general population, we calculate the LensAge index by contrasting LensAge and chronological age to reflect the aging rate relative to peers. The LensAge index effectively reveals the risks of age-related eye and systemic disease occurrence, as well as all-cause mortality. It outperforms chronological age in reflecting age-related disease risks (p < 0.001). More importantly, our models can conveniently work based on smartphone photographs, suggesting suitability for routine self-examination of aging status. Overall, our study demonstrates that the LensAge index may serve as an ideal quantitative indicator for clinically assessing and self-monitoring biological age in humans.

DeepQuality improves infant retinopathy screening.

Image quality variation is a prominent cause of performance degradation for intelligent disease diagnostic models in clinical applications. Image quality issues are particularly prominent in infantile fundus photography due to poor patient cooperation, which poses a high risk of misdiagnosis. Here, we developed a deep learning-based image quality assessment and enhancement system (DeepQuality) for infantile fundus images to improve infant retinopathy screening. DeepQuality can accurately detect various quality defects concerning integrity, illumination, and clarity with area under the curve (AUC) values ranging from 0.933 to 0.995. It can also comprehensively score the overall quality of each fundus photograph. By analyzing 2,015,758 infantile fundus photographs from real-world settings using DeepQuality, we found that 58.3% of them had varying degrees of quality defects, and large variations were observed among different regions and categories of hospitals. Additionally, DeepQuality provides quality enhancement based on the results of quality assessment. After quality enhancement, the performance of retinopathy of prematurity (ROP) diagnosis of clinicians was significantly improved. Moreover, the integration of DeepQuality and AI diagnostic models can effectively improve the model performance for detecting ROP. This study may be an important reference for the future development of other image-based intelligent disease screening systems.

Protocol to analyze fundus images for multidimensional quality grading and real-time guidance using deep learning techniques.

Data quality issues have been acknowledged as one of the greatest obstacles in medical artificial intelligence research. Here, we present DeepFundus, which employs deep learning techniques to perform multidimensional classification of fundus image quality and provide real-time guidance for on-site image acquisition. We describe steps for data preparation, model training, model inference, model evaluation, and the visualization of results using heatmaps. This protocol can be implemented in Python using either the suggested dataset or a customized dataset. For complete details on the use and execution of this protocol, please refer to Liu et al.1.

Clinical efficacy and tendon integrity of patients with subscapularis tear by the technique of arthroscopic single external row repair.

Background: With the development of arthroscopic technology and equipment, arthroscopy can effectively repair the tear of the subscapular muscle. However, it is difficult to expose the subscapular muscle and operate it under a microscope. In this study, the SwiveLock® C external row anchor under arthroscopy was applied to repair the tear of the subscapular muscle in a single row, which is relatively easy to operate with reliable suture and fixation, and its efficacy was evaluated. Purpose: This study aimed to assess the clinical efficacy and the tendon integrity of patients who had subscapularis tears by adopting the single-row repair technique with a SwiveLock® C external row anchor. Methods: Patients who had the subscapular muscle tear either with or without retraction were included, and their follow-up time was at least 1 year. The degree of tendon injury was examined by magnetic resonance imaging (MRI) and confirmed by arthroscopy. The tendon was repaired in an arthroscopic manner by utilizing the single-row technique at the medial margin of the lesser tuberosity. One double-loaded suture SwiveLock® C anchor was applied to achieve a strong fixation between the footprint and tendon. The range of motion, pain visual simulation score, American Shoulder and Elbow Surgeons (ASES) score, and Constant score of shoulder joint were evaluated for each patient before the operation, 3 months after the operation, and at least 1 year after the operation. Results: In total, 110 patients, including 31 males and 79 females, with an average age of 68.28 ± 8.73 years were included. Arthroscopic repair of the subscapular tendon with SwiveLock® C external anchor can effectively improve the range of motion of the shoulder joint. At the last follow-up, the forward flexion of the shoulder joint increased from 88.97 ± 26.33° to 138.38 ± 26.48° (P < 0.05), the abduction range increased from 88.86 ± 25.27° to 137.78 ± 25.64° (P < 0.05), the external rotation range increased from 46.37 ± 14.48° to 66.49 ± 14.15° (P < 0.05), and the internal rotation range increased from 40.03 ± 9.01° to 57.55 ± 7.43° (P < 0.05). The clinical effect is obvious. The constant shoulder joint score increased from 40.14 ± 15.07 to 81.75 ± 11.00 (P < 0.05), the ASES score increased from 37.88 ± 13.24 to 82.01 ± 9.65 (P < 0.05), and the visual analog scale score decreased from 5.05 ± 2.11 to 1.01 ± 0.85 (P < 0.05). In the 6th month after the operation, two cases (1.81%) were confirmed to have re-tears via MRI. Conclusion: In this study, we repaired the subscapularis muscle with a single-row technique fixed by SwiveLock® C anchor and FiberWire® sutures and evaluated its efficacy. The results showed that the clinical effect of single-row arthroscopic repair was satisfactory and that reliable tendon healing could be achieved.

Early Visual Deprivation Impairs Functional Development of the Visual Ventral Stream.

Purpose: To probe the dynamic alternations of neural networks in real-time visual processing after visual deprivation (VD) removal. Methods: A prospective cross-sectional study was conducted. Twenty children with a history of early binocular VD caused by congenital cataracts and 20 matched typically developing (TD) children were enrolled. The event-related potential (ERP) data were obtained via high-density electroencephalography. ERP data were analyzed based on three components (P1, N170, and P2), three test conditions (objects, human faces, and Chinese characters), and peak time and region of interest (ROI) chosen on a grand average head map collapsed from the averaged waveform of each group. Source localization and alpha power spectrum density were applied to define the functional pattern of brain areas and evaluate the attention function. Results: The VD group showed significantly lower P1 amplitudes than the TD group under all conditions in peak ROIs, which were situated in the left occipito-temporal region. For both VD and TD groups, there were strong N170 effects in the character and human face conditions in the component's peak ROIs. Furthermore, source mapping indicated that the VD group generally showed significantly lower activation in the visual cortex and ventral stream, whereas the beyond network areas (mostly frontal areas) intensively participated in functional compensation in the VD group. The VD group showed significant poststimulus alpha desynchronization in object recognition. Conclusions: Our research described the mechanisms of visual networks after early binocular VD removal. Our findings may provide a new basis for the poor visual recovery after early binocular VD removal and offer clues for visual recovery strategies.

EE-Explorer: A Multimodal Artificial Intelligence System for Eye Emergency Triage and Primary Diagnosis.

PURPOSE: To develop a multimodal artificial intelligence (AI) system, EE-Explorer, to triage eye emergencies and assist in primary diagnosis using metadata and ocular images. DESIGN: A diagnostic, cross-sectional, validity and reliability study. METHODS: EE-Explorer consists of 2 models. The triage model was developed from metadata (events, symptoms, and medical history) and ocular surface images via smartphones from 2038 patients presenting to Zhongshan Ophthalmic Center (ZOC) to output 3 classifications: urgent, semiurgent, and nonurgent. The primary diagnostic model was developed from the paired metadata and slitlamp images of 2405 patients from ZOC. Both models were externally tested on 103 participants from 4 other hospitals. A pilot test was conducted in Guangzhou to evaluate the hierarchical referral service pattern assisted by EE-Explorer for unspecialized health care facilities. RESULTS: A high overall accuracy, as indicated by an area under the receiver operating characteristic curve (AUC) of 0.982 (95% CI, 0.966-0.998), was obtained using the triage model, which outperformed the triage nurses (P < .001). In the primary diagnostic model, the diagnostic classification accuracy (CA) and Hamming loss (HL) in the internal testing were 0.808 (95% CI 0.776-0.840) and 0.016 (95% CI 0.006-0.026), respectively. In the external testing, model performance was robust for both triage (average AUC, 0.988, 95% CI 0.967-1.000) and primary diagnosis (CA, 0.718, 95% CI 0.644-0.792; and HL, 0.023, 95% CI 0.000-0.048). In the pilot test in the hierarchical referral settings, EE-explorer demonstrated consistently robust performance and broad participant acceptance. CONCLUSION: The EE-Explorer system showed robust performance in both triage and primary diagnosis for ophthalmic emergency patients. EE-Explorer can provide patients with acute ophthalmic symptoms access to remote self-triage and assist in primary diagnosis in unspecialized health care facilities to achieve rapid and effective treatment strategies.

DeepFundus: A flow-cytometry-like image quality classifier for boosting the whole life cycle of medical artificial intelligence.

Medical artificial intelligence (AI) has been moving from the research phase to clinical implementation. However, most AI-based models are mainly built using high-quality images preprocessed in the laboratory, which is not representative of real-world settings. This dataset bias proves a major driver of AI system dysfunction. Inspired by the design of flow cytometry, DeepFundus, a deep-learning-based fundus image classifier, is developed to provide automated and multidimensional image sorting to address this data quality gap. DeepFundus achieves areas under the receiver operating characteristic curves (AUCs) over 0.9 in image classification concerning overall quality, clinical quality factors, and structural quality analysis on both the internal test and national validation datasets. Additionally, DeepFundus can be integrated into both model development and clinical application of AI diagnostics to significantly enhance model performance for detecting multiple retinopathies. DeepFundus can be used to construct a data-driven paradigm for improving the entire life cycle of medical AI practice.

Early detection of visual impairment in young children using a smartphone-based deep learning system.

Early detection of visual impairment is crucial but is frequently missed in young children, who are capable of only limited cooperation with standard vision tests. Although certain features of visually impaired children, such as facial appearance and ocular movements, can assist ophthalmic practice, applying these features to real-world screening remains challenging. Here, we present a mobile health (mHealth) system, the smartphone-based Apollo Infant Sight (AIS), which identifies visually impaired children with any of 16 ophthalmic disorders by recording and analyzing their gazing behaviors and facial features under visual stimuli. Videos from 3,652 children (≤48 months in age; 54.5% boys) were prospectively collected to develop and validate this system. For detecting visual impairment, AIS achieved an area under the receiver operating curve (AUC) of 0.940 in an internal validation set and an AUC of 0.843 in an external validation set collected in multiple ophthalmology clinics across China. In a further test of AIS for at-home implementation by untrained parents or caregivers using their smartphones, the system was able to adapt to different testing conditions and achieved an AUC of 0.859. This mHealth system has the potential to be used by healthcare professionals, parents and caregivers for identifying young children with visual impairment across a wide range of ophthalmic disorders.

DFT Insights into the Variety in the Coordination Modes of the Equatorial Halides in [Au13 Ag12 (PR3 )10 X8 ]+ (X=Cl/Br) Clusters.

The bonding character within metal nanoclusters represents an intriguing topic, shedding light on the inherent driving force for the packing preference in nanomaterials. Herein, density functional theory (DFT) calculations were conducted to investigate the correlation of the series of isomeric [Au13 Ag12 (PR3 )10 X8 ]+ (X=Cl/Br) clusters, which are mainly differentiated by the coordination mode of the equatorial halides (µ2 -, µ3 - and µ4 -) in the rod-like, bi-icosahedral framework. The theoretical simulation corroborates the variety in the configuration of the Au13 Ag12 clusters and elucidates the fast isomerization kinetics among the different configurations. The easy tautomerization and the variety in chloride binding modes correspond to a fluxionality character of the equatorial halides and are verified by the potential energy curve analysis. The structural flexibility of the central Au3 Ag10 block is the main driving force, while the relatively stronger Ag-X bonding interaction (compared to that of Au-X), and a sufficient number of halides are also requisite for the associating Ag-X tautomerizations.

Structured copper-hydride nanoclusters provide insight into the surface-vacancy-defect to non-defect structural evolution.

Exploring the structural evolution of clusters with similar sizes and atom numbers induced by the removal or addition of a few atoms contributes to a deep understanding of structure-property relationships. Herein, three well-characterized copper-hydride nanoclusters that provide insight into the surface-vacancy-defect to non-defect structural evolution were reported. A surface-defective copper hydride nanocluster [Cu28(S-c-C6H11)18(PPh2Py)3H8]2+ (Cu28-PPh2Py for short) with only one C 1 symmetry axis was synthesized using a one-pot method under mild conditions, and its structure was determined. Through ligand regulation, a 29th copper atom was inserted into the surface vacancy site to give two non-defective copper hydride nanoclusters, namely [Cu29(SAdm)15Cl3(P(Ph-Cl)3)4H10]+ (Cu29-P(Ph-Cl)3 for short) with one C 3 symmetry axis and (Cu29(S-c-C6H11)18(P(Ph-pMe)3)4H10)+ (Cu29-P(Ph-Me)3 for short) with four C 3 symmetry axes. The optimized structures show that the 10 hydrides cap four triangular and all six square-planar structures of the cuboctahedral Cu13 core of Cu29-P(Ph-Me)3, while the 10 hydrides cap four triangular and six square-planar structures of the anti-cuboctahedral Cu13 core of Cu29-P(Ph-Cl)3, with the eight hydrides in Cu28-PPh2Py capping four triangular and four square planar-structures of its anti-cuboctahedral Cu13 core. Cluster stability was found to increase sequentially from Cu28-PPh2Py to Cu29-P(Ph-Cl)3 and then to Cu29-P(Ph-Me)3, which indicates that stability is affected by the overall structure of the cluster. Structural adjustments to the metal core, shell, and core-shell bonding model, in moving from Cu28-PPh2Py to Cu29-P(Ph-Cl)3 and then to Cu29-P(Ph-Me)3, enable the structural evolution and mechanism responsible for their physicochemical properties to be understood and provide valuable insight into the structures of surface vacancies in copper nanoclusters and structure-property relationships.

Mechanistic Insights into Oxidation-Induced Size Conversion of [Au6(dppp)4]2+ to [Au8(dppp)4Cl2]2.

Oxidation-induced conversion of gold nanoclusters is an important strategy for preparing novel atomically precise clusters and elucidating the kinetic correlations of different clusters. Herein, the oxidation-induced growth from [Au6(dppp)4]2+ to [Au8(dppp)4Cl2]2+ (reported by Konishi and co-workers) has been studied by density functional theory calculations. A successive oxidation → Cl- coordination → oxidation → Cl- coordination sequence occurs first to activate the Au6 structure, resulting in the high Au(core)-Au(corner) bond cleavage activity and the subsequent formation of [Au2(dppp)2Cl]+ and [Au4(dppp)2Cl]+ fragments. Then, the dimerization of two Au4 fragments and the rearrangement of the diphosphine coordination occur to generate the thermodynamically stable [Au8(dppp)4Cl2]2+ products. The proposed mechanism agrees with the experimental outcome for the fast reaction rate and the residual of the Au2 components. Specifically, a multivariate linear regression analysis indicates the strong correlation of the oxidation potential of Au6, Au8, Au23, and Au25 clusters with the HOMO energy, the number of Au atoms, and cluster charge state. The main conclusions [e.g., oxidation-induced Au(corner)-Au(core) bond activation, easy 1,2-P transfer steps, etc.] of this study might be widely applicable in improving our understanding of the mechanism of other cluster-conversion reactions.

Optical coherence tomography angiography for the characterisation of retinal microvasculature alterations in pregnant patients with anaemia: a nested case‒control study.

AIMS: To characterise retinal microvascular alterations in the eyes of pregnant patients with anaemia (PA) and to compare the alterations with those in healthy controls (HC) using optical coherence tomography angiography (OCTA). METHODS: This nested case‒control study included singleton PA and HC from the Eye Health in Pregnancy Study. Fovea avascular zone (FAZ) metrics, perfusion density (PD) in the superficial capillary plexus, deep capillary plexus and flow deficit (FD) density in the choriocapillaris (CC) were quantified using FIJI software. Linear regressions were conducted to evaluate the differences in OCTA metrics between PA and HC. Subgroup analyses were performed based on comparisons between PA diagnosed in the early or late trimester and HC. RESULTS: In total, 99 eyes of 99 PA and 184 eyes of 184 HC were analysed. PA had a significantly reduced FAZ perimeter (ß coefficient=-0.310, p<0.001), area (ß coefficient=-0.121, p=0.001) and increased circularity (ß coefficient=0.037, p<0.001) compared with HC. Furthermore, higher PD in the central (ß coefficient=0.327, p=0.001) and outer (ß coefficient=0.349, p=0.007) regions were observed in PA. PA diagnosed in the first trimester had more extensive central FD (ß coefficient=4.199, p=0.003) in the CC, indicating impaired perfusion in the CC. CONCLUSION: It was found that anaemia during pregnancy was associated with macular microvascular abnormalities, which differed in PA as pregnancy progressed. The results suggest that quantitative OCTA metrics may be useful for risk evaluation before clinical diagnosis. TRIAL REGISTRATION NUMBERS: 2021KYPJ098 and ChiCTR2100049850.

Comparing the accuracy of shear wave elastography and strain elastography in the diagnosis of breast tumors: A systematic review and meta-analysis.

BACKGROUND: Shear wave elastography (SWE) and strain elastography (SE) are 2 new ultrasonic technologies which have developed rapidly in recent years. Elastography transforms the elastic information of tissue into optical information for display, thus more intuitive display of tissue elasticity. Conflicting results have been obtained in different scholars' studies on the accuracy comparison of the 2 elastography technologies in the diagnosis of breast tumors. This meta-analysis aims to compare the accuracy of the 2 elastography technologies in the diagnosis of breast tumors, and provide a reference for clinical decision making. METHODS: We have searched Chinese and English literatures on the accuracy of SWE and SE in the diagnosis of breast tumors from PubMed, Web of Science, China national knowledge infrastructure and Wanfang databases, and the time was up to December30, 2020. Two literature reviewers screened the literatures according to the screening criteria, and Quality Assessment of Diagnostic Accuracy Study tool was used to evaluate the quality of included literatures. Meta Disc1.4 and Stata14.0 softwares were used to perform heterogeneity test, sensitivity analysis and publication bias test. RESULTS: Ten literatures included 1599 patients and 1709 breast lesions. The final results in the SWE as follow: The pooled sensitivity was 0.852 (95% confidence interval [CI] [0.826-0.874]), the pooled specificity (Spe) was 0.799 (95% CI [0.776-0.820]), the pooled positive likelihood ratio was 4.758 (95% CI [3.443-6.576]), the pooled negative likelihood ratio was 0.192 (95% CI [0.147-0.250]), the pooled diagnostic odds ratio was 29.071 (95% CI [16.967-49.811]), and the area under the summary receiver operating characteristic curve was 0.9159. The final results in the SE as follow: The pooled sensitivity was 0.843 (95% CI [0.817-0.866]), the pooled Spe was 0.766 (95% CI [0.743-0.789]), the pooled positive likelihood ratio was 4.387 (95% CI [3.088-6.233]), the pooled negative likelihood ratio was 0.216 (95% CI [0.179-0.261]), the pooled diagnostic odds ratio was 22.610 (95% CI [15.622-32.724]), and the area under the summary receiver operating characteristic curve was 0.8987. CONCLUSION: The sensitivity and Spe of SWE were higher than those of SE, suggesting that SWE may have a higher accuracy in the diagnosis of breast tumors. REGISTER NAME: PROSPERO. Registration number: CRD42021251110.