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Flexible and transparent hafnium oxide-based ferroelectric films are attracting widespread attention because of the increasing demand for wearable electronic devices. However, the ultra-low voltage operation with robust and stable ferroelectricity, which is a prerequisite for portable device applications, has not been realized simultaneously. Here, we report flexible Hf0.5Zr0.5O2 ferroelectric films with a saturation voltage of only 1.3/3 V and remanent polarization (2Pr) of 38/60 µC·cm2. Negligible wake-up effect and superior stability resistance to compressive/tensile stress and high temperature up to 150 °C are also demonstrated. The polarization switching dynamics under bending are investigated based on the switching current measurement, suggesting that the intrinsic switching speeds keep almost constant at different bending radii. In addition, there is a negative correlation between the activation field and the compressive or tensile stress, which is due to the lowered energy barrier induced by the in-plane strain applied to the [111]-oriented hexagonal cell. Our work sheds light on the application of flexible, stable, and HfO2-based ferroelectric thin films with ultra-low consumption.

Abstract Social network analysis and shared-patient physician networks have become effective ways of studying physician collaborations. Assortative mixing or “homophily” is the network phenomenon whereby the propensity for similar individuals to form ties is greater than for dissimilar individuals. Motivated by the public health concern of risky-prescribing among older patients in the United States, we develop network models and tests involving novel network measures to study whether there is evidence of homophily in prescribing and deprescribing in the specific shared-patient network of physicians linked to the US state of Ohio in 2014. Evidence of homophily in risky-prescribing would imply that prescribing behaviors help shape physician networks and would suggest strategies for interventions seeking to reduce risky-prescribing (e.g., strategies to directly reduce risky prescribing might be most effective if applied as group interventions to risky prescribing physicians connected through the network and the connections between these physicians could be targeted by tie dissolution interventions as an indirect way of reducing risky prescribing). Furthermore, if such effects varied depending on the structural features of a physician’s position in the network (e.g., by whether or not they are involved in cliques—groups of actors that are fully connected to each other—such as closed triangles in the case of three actors), this would further strengthen the case for targeting groups of physicians involved in risky prescribing and the network connections between them for interventions. Using accompanying Medicare Part D data, we converted patient longitudinal prescription receipts into novel measures of the intensity of each physician’s risky-prescribing. Exponential random graph models were used to simultaneously estimate the importance of homophily in prescribing and deprescribing in the network beyond the characteristics of physician specialty (or other metadata) and network-derived features. In addition, novel network measures were introduced to allow homophily to be characterized in relation to specific triadic (three-actor) structural configurations in the network with associated non-parametric randomization tests to evaluate their statistical significance in the network against the null hypothesis of no such phenomena. We found physician homophily in prescribing and deprescribing. We also found that physicians exhibited within-triad homophily in risky-prescribing, with the prevalence of homophilic triads significantly higher than expected by chance absent homophily. These results may explain why communities of prescribers emerge and evolve, helping to justify group-level prescriber interventions. The methodology may be applied, adapted or generalized to study homophily and its generalizations on other network and attribute combinations involving analogous shared-patient networks and more generally using other kinds of network data underlying other kinds of social phenomena.

AIM: To investigate the effects of fibrillin-1 (FBN1) deletion on the integrity of retina-blood barrier function and the apoptosis of vascular endothelial cells under diabetic conditions. METHODS: Streptozotocin (STZ)-induced diabetic mice were used to simulate the diabetic conditions of diabetic retinopathy (DR) patients, and FBN1 expression was detected in retinas from STZ-diabetic mice and controls. In the Gene Expression Omnibus (GEO) database, the GSE60436 dataset was selected to analyze FBN1 expressions in fibrovascular membranes from DR patients. Using lentivirus to knock down FBN1 levels, vascular leakage and endothelial barrier integrity were detected by Evans blue vascular permeability assay, fluorescein fundus angiography (FFA) and immunofluorescence labeled with tight junction marker in vivo. High glucose-induced monkey retinal vascular endothelial cells (RF/6A) were used to investigate effects of FBN1 on the cells in vitro. The vascular endothelial barrier integrity and apoptosis were detected by trans-endothelial electrical resistance (TEER) assay and flow cytometry, respectively. RESULTS: FBN1 mRNA expression was increased in retinas of STZ-induced diabetic mice and fibrovascular membranes of DR patients (GSE60436 datasets) using RNA-seq approach. Besides, knocking down of FBN1 by lentivirus intravitreal injection significantly inhibited the vascular leakage compared to STZ-DR group by Evans blue vascular permeability assay and FFA detection. Expressions of tight junction markers in STZ-DR mouse retinas were lower than those in the control group, and knocking down of FBN1 increased the tight junction levels. In vitro, 30 mmol/L glucose could significantly inhibit viability of RF/6A cells, and FBN1 mRNA expression was increased under 30 mmol/L glucose stimulation. Down-regulation of FBN1 reduced high glucose (HG)-stimulated retinal microvascular endothelial cell permeability, increased TEER, and inhibited RF/6A cell apoptosis in vitro. CONCLUSION: The expression level of FBN1 increases in retinas and vascular endothelial cells under diabetic conditions. Down-regulation of FBN1 protects the retina of early diabetic rats from retina-blood barrier damage, reduce vascular leakage, cell apoptosis, and maintain vascular endothelial cell barrier function.

Fonsecaea monophora is one of the common pathogenic species of Chromoblastomycosis (CBM). Antimicrobial photodynamic therapy (aPDT) shows promise as a new treatment for CBM. In this study, we evaluated the effectiveness of COP1T-HA which is a porous organic cage and aPDT against Fonsecaea spp. in vitro.

A reliable character system is crucial to taxonomy and systematics, and it promises valid downstream inferences, e.g., estimates of diversity and disparity, reconstruction of evolutionary history, and even stratigraphic correlations. Modern taxonomy and systematics of extant cockroaches requires an integrative study involving multiple lines of evidence with emphasis on genital and reproductive characteristics and molecular data. In contrast, many fossil cockroach taxa published recently are based solely on forewings. Many studies have shown that forewing-based taxa are questionable. In order to find out how much of the phylogenetic signal we could ascertain from venational similarity, and how confident we could be, this study used forewing characters to reconstruct phylogenies of the genera of well-recognized family-group taxa. The intuitively reconstructed phylogeny of 75 extant genera failed to recover those taxa or their relationships. Parsimony analyses of various datasets all yielded strong polyphyly and chaotic relationships. In conclusion, the forewing of cockroaches is not a universally competent character system. The underlying causes are the complicated nature of veins and the limitations of current analytical techniques. The uncertainty in forewing-based taxonomy and systematics has been underestimated in the literature. Forewing-based fossil taxa warrant re-evaluation; some of them are herein deemed nomina dubia in their current state.

Deep learning has significantly advanced the field of pipeline circumferential guided wave testing. However, the scarcity of defective samples in non-destructive testing datasets poses a significant challenge due to data imbalance. Traditional computer vision augmentation techniques, such as rotation and flipping, are often not directly applicable to guided wave data due to its unique characteristics. To address this issue, we propose a novel approach that combines the strengths of convolutional neural networks (CNNs) and random forest (RF) classifiers. Raw detection data are preprocessed using continuous wavelet transform to generate informative time-frequency images. Random forests enhance predictive accuracy by combining multiple decision trees. The experiment results demonstrate the effectiveness of the proposed CNN-RF approach, particularly in handling imbalanced datasets. When the data imbalance ratio is more than 1/2, the shallow, lightweight CNN could effectively extract signal features and lead to approximately a 56.5% speedup. When the imbalance ratio is less than 1/2, the ResNet34-RF model significantly outperforms the standard CNN model. This approach holds potential for contributing to the miniaturization, lightweight design, and mobility of guided wave detection systems and devices.

Mycobacterium chelonae and Sporothrix globosa, both of which are opportunistic pathogens, have been proved to be possible multidrug resistant. However, are all recurring symptoms in chronic infections related to decreasing susceptibility? Here we report a case of sporotrichosis secondary to M. chelonae infection. In addition, we find that the blackish-red spots under the dermoscopic view can be employed as a signal for the early identification and regression of subcutaneous fungal infection.

Summary: Background: Labiaplasty is one of the top cosmetic procedures patients are seeking in the past two years. However, treatment of disease in posterior fourchette caused by various etiological factors was less investigated and neglected. Methods: Three types of posterior fourchette deformity were proposed: (1) Redundant posterior fourchette, (2) Relaxed posterior fourchette, and (3) Constricted posterior fourchette. Local flap transfer technique was applied. Y–V-plasty and 5-Z-Flap-plasty were used to treat web type and tight type of the constricted posterior fourchette, respectively. Follow-ups were arranged on the Internet or at the outpatient clinic. Visual analogue scale (VAS) was utilized to evaluate sexual discomfort in the satisfaction questionnaires during follow-up. Results: A total of 48 patients with constricted posterior fourchette deformity from May 2022 to May 2023 were reviewed in the study. Y–V-plasty could decrease VAS in patients with web-type deformity by 4.13 ± 1.46 (p＜0.001). 5-Z-Flap-plasty could decrease VAS in patients with tight-type deformity by 3.76 ± 1.53 (p＜0.05). Satisfaction rates of the web type and tight type were 93.1% (27/29) and 86.7% (13/15) respectively. Complications include two cases of hematoma, one case of persistent pain and two cases of dehiscence. Conclusion: Constricted posterior fourchette seriously affects the quality of life. Y–V-plasty and 5-Z-Flap-plasty can be utilized to treat the two subtypes of constricted posterior fourchette, which can effectively reduce the pain score of patients with high satisfaction and few long-term complications.

Abstract Background Teeth identification has a pivotal role in the dental curriculum and provides one of the important foundations of clinical practice. Accurately identifying teeth is a vital aspect of dental education and clinical practice, but can be challenging due to the anatomical similarities between categories. In this study, we aim to explore the possibility of using a deep learning model to classify isolated tooth by a set of photographs. Methods A collection of 5,100 photographs from 850 isolated human tooth specimens were assembled to serve as the dataset for this study. Each tooth was carefully labeled during the data collection phase through direct observation. We developed a deep learning model that incorporates the state-of-the-art feature extractor and attention mechanism to classify each tooth based on a set of 6 photographs captured from multiple angles. To increase the validity of model evaluation, a voting-based strategy was applied to refine the test set to generate a more reliable label, and the model was evaluated under different types of classification granularities. Results This deep learning model achieved top-3 accuracies of over 90% in all classification types, with an average AUC of 0.95. The Cohen’s Kappa demonstrated good agreement between model prediction and the test set. Conclusions This deep learning model can achieve performance comparable to that of human experts and has the potential to become a valuable tool for dental education and various applications in accurately identifying isolated tooth.

Skin dysbiosis caused by Cutibacterium acnes contributes greatly to the complex pathogenesis of acne, and antimicrobial photodynamic therapy (PDT) has emerged as a promising treatment option for acne treatment. Hypocrellin, a photosensitizer extracted from a traditional Chinese medicinal fungus, has showed effective antimicrobial activity. This study aimed to evaluate the antibacterial ability of hypocrellin mediated PDT against Cutibacterium acnes. Using modified broth dilution method and morphological observation, the antibacterial effect was tested under a series of experimental conditions. The results showed that hypocrellin initiates type II photodynamic reactions by inducing amount of reactive oxygen species, particularly singlet oxygen. Within a certain concentration range, hypocrellin effectively maintained the antibacterial efficacy with minimal damage to keratinocyte cells. These results provide new insights into the use of PDT for acne treatment.

BackgroundThe relationship between white matter hyperintensities (WMH) and the core features of Alzheimer’s disease (AD) remains controversial. Further, due to the prevalence of co-pathologies, the precise role of WMH in cognition and neurodegeneration also remains uncertain.MethodsHerein, we analyzed 1803 participants with available WMH volume data, extracted from the ADNI database, including 756 cognitively normal controls, 783 patients with mild cognitive impairment (MCI), and 264 patients with dementia. Participants were grouped according to cerebrospinal fluid (CSF) pathology (A/T profile) severity. Linear regression analysis was applied to evaluate the factors associated with WMH volume. Modeled by linear mixed-effects, the increase rates (Δ) of the WMH volume, cognition, and typical neurodegenerative markers were assessed. The predictive effectiveness of WMH volume was subsequently tested using Cox regression analysis, and the relationship between WMH/ΔWMH and other indicators such as cognition was explored through linear regression analyses. Furthermore, we explored the interrelationship among amyloid-β deposition, cognition, and WMH using mediation analysis.ResultsHigher WMH volume was associated with older age, lower CSF amyloid-β levels, hypertension, and smoking history (all p ≤ 0.001), as well as cognitive status (MCI, p

Objective: Diabetic nephropathy (DN) is a serious complication that may occur during the later stages of diabetes, and can be further exacerbated by podocyte damage. Piperazine ferulate (PF) has well-defined nephroprotective effects and is used clinically in the treatment of chronic nephritis and other kidney diseases. However, the renoprotective effects and mechanisms of PF on DN are not clear. This study aims to investigate the protective effect of PF on DN and its mechanism of action, to inform the clinical application of PF in DN treatment.Methods: Network pharmacology was performed to predict the mechanism of action of PF in DN. Male Sprague Dawley rats were intraperitoneally injected with STZ (60 mg/kg) to establish a DN model, and then assessed for renal injury after 12 weeks of administration. In vitro, rat podocytes were treated with 25 mmol/L glucose and cultured for 24 h, followed by an assessment of cell injury.Results: Our results showed that PF significantly improved renal function, reduced renal pathological changes, decreased inflammatory response, and alleviated podocyte damage in DN rats. PF also attenuated glucose-induced podocyte injury in vitro. Regarding molecular mechanisms, our study demonstrated that PF downregulated the expression of genes and proteins related to AGE-RAGE-mediated inflammatory signaling.Conclusion: In summary, PF exerts its renoprotective effects by decreasing inflammation and protecting against podocyte injury through the inhibition of the AGE/RAGE/NF-κB/NLRP3 pathway. Overall, these data support the clinical potential of PF as a renoprotective agent in DN.