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Abstract Retinal segmentation is a prerequisite for quantifying retinal structural features and diagnosing related ophthalmic diseases. Canny operator is recognized as the best boundary detection operator so far, and is often used to obtain the initial boundary of the retina in retinal segmentation. However, the traditional Canny operator is susceptible to vascular shadows, vitreous artifacts, or noise interference in retinal segmentation, causing serious misdetection or missed detection. This paper proposed an improved Canny operator for automatic segmentation of retinal boundaries. The improved algorithm solves the problems of the traditional Canny operator by adding a multi-point boundary search step on the basis of the original method, and adjusts the convolution kernel. The algorithm was used to segment the retinal images of healthy subjects and age-related macular degeneration (AMD) patients; eleven retinal boundaries were identified and compared with the results of manual segmentation by the ophthalmologists. The average difference between the automatic and manual methods is: 2–6 microns (1–2 pixels) for healthy subjects and 3–10 microns (1–3 pixels) for AMD patients. Qualitative method is also used to verify the accuracy and stability of the algorithm. The percentage of “perfect segmentation” and “good segmentation” is 98% in healthy subjects and 94% in AMD patients. This algorithm can be used alone or in combination with other methods as an initial boundary detection algorithm. It is easy to understand and improve, and may become a useful tool for analyzing and diagnosing eye diseases.

Abstract It is unclear about the functional role of microRNA-133a-3p (miR-133a-3p) in intracranial aneurysm (IA). Hence, the aim of the present study was to investigate the regulatory role of miR-133a-3p on the regulation of vascular endothelial injury-induced IA through phosphoserine aminotransferase 1 (PSAT1)/glycogen synthase kinase 3β (GSK3β)/β-catenin signaling pathway. Normal intracranial arteriole tissues and IA tissues were gathered from patients with brain trauma and IA. The expression of miR-133a-3p, PSAT1, GSK3β, and β-catenin in tissues was determined by RT-qPCR and western blot analysis. The endothelial cells (ECs) of the human IA were cultured and treated with miR-133a-3p mimic and si-PSAT1 to determine their functions in endothelial cell migration, apoptosis, and proliferation. The expression of miR-133a-3p, PSAT1, GSK3β, β-catenin, Ki-67, CyclinD1, Bax, and Bcl-2 in ECs were tested by RT-qPCR or western blot analysis. Moreover, IA rat model was established to detect the pathological changes and the expression of miR-133a-3p, PSAT1, GSK3β, β-catenin, VEGF, and MMP-9 in IA tissues in vivo. Expression of miR-133a-3p was related to the number and size of IA. MiR-133a-3p expression was deceased and the PSAT1, GSK3β, and β-catenin expression was raised in IA. Restored miR-133a-3p and depleted PSAT1 alleviated the pathological change; reduced PSAT1, GSK3β, and β-catenin expression in IA; suppressed apoptosis and advanced proliferation and migration of IA ECs, as well as reduced VEGF and MMP-9 expression in IA tissues in vivo. Our study suggests that overexpression of miR-133a-3p or downregulation of PSAT1 restrains endothelial cell damage and advances endothelial cell proliferation via inhibiting the GSK3β/β-catenin pathway in IA. MiR-133a-3p might be a potential candidate marker and therapeutic target for IA.

The size and shape of the foveal avascular zone (FAZ) have a strong positive correlation with several vision-threatening retinovascular diseases. The identification, segmentation and analysis of FAZ are of great significance to clinical diagnosis and treatment. We presented an adaptive watershed algorithm to automatically extract FAZ from retinal optical coherence tomography angiography (OCTA) images. For the traditional watershed algorithm, “over-segmentation” is the most common problem. FAZ is often incorrectly divided into multiple regions by redundant “dams”. This paper analyzed the relationship between the “dams” length and the maximum inscribed circle radius of FAZ, and proposed an adaptive watershed algorithm to solve the problem of “over-segmentation”. Here, 132 healthy retinal images and 50 diabetic retinopathy (DR) images were used to verify the accuracy and stability of the algorithm. Three ophthalmologists were invited to make quantitative and qualitative evaluations on the segmentation results of this algorithm. The quantitative evaluation results show that the correlation coefficients between the automatic and manual segmentation results are 0.945 (in healthy subjects) and 0.927 (in DR patients), respectively. For qualitative evaluation, the percentages of “perfect segmentation” (score of 3) and “good segmentation” (score of 2) are 99.4% (in healthy subjects) and 98.7% (in DR patients), respectively. This work promotes the application of watershed algorithm in FAZ segmentation, making it a useful tool for analyzing and diagnosing eye diseases.

The virtual lens model has important value in ophthalmic research, clinical diagnosis, and treatment. However, the establishment of personalized lens models and the verification of accommodation accuracy have not been paid much attention. We proposed a personalized lens model establishment and the accommodation accuracy evaluation method based on sweep-source optical coherence tomography (SS-OCT). Firstly, SS-OCT is used to obtain a single lens image in the maximum accommodation state. After refraction correction, boundary detection, and curve fitting, the central curvature radius, thickness, and lens nucleus contour of the anterior and posterior surfaces of the lens were obtained. Secondly, a personalized finite element model improved from Burd’s model was established using these individual parameters, and the adaptation process of the lens model was simulated by pulling the suspensory ligament. Finally, the shape and refractive power changes of the real human lens under different accommodation stimuli were collected and compared with the accommodation process of the finite element model. The results show that the accommodation process of the finite element model is highly consistent with that of the real lens. From the un-accommodation state to the maximum-accommodation state, the difference rate of all geometric and refractive parameters between the two is less than 5%. Thus, the personalized lens finite element model obtained by the calibration and correction of the existing model can accurately simulate the regulation process of a specific human lens. This work helps to provide a valuable theoretical basis and research ideas for the study of clinical diagnosis and treatment of related diseases.

The purpose of this study is to investigate the current state of post-traumatic growth (PTG) and identify its influencing factors in discharged COVID-19 patients. PTG refers to individual experiences of significant positive change arising from the struggle with a major life crisis. This descriptive cross-sectional study used the convenient sampling method to recruit 140 discharged COVID-19 patients in Hunan, China. The results show that the PTG of the discharged COVID-19 patients was positively correlated with self-esteem, post-traumatic stress disorder, coping style tendency, and social support, but negatively correlated with the time from onset to diagnosis. Our findings could provide guidance on improving the psychological state and well-being of discharged COVID-19 patients.

Objective: To investigate the mechanism of electroacupuncture (EA) for treating depression and to explore the role of brevican in the medial prefrontal cortex (mPFC) in modulating stress susceptibility and the antidepressant effects of EA in rats. Methods: Twenty-four Sprague–Dawley (SD) rats were equally divided into three groups: green fluorescent protein (GFP) + control, GFP + chronic unpredicted mild stress (CUMS), and short-hairpin RNA targeting on brevican (shBcan) + CUMS. Another 24 SD rats were equally divided into CUMS + GFP, CUMS + GFP + EA, and CUMS + shBcan + EA groups. Behavioral tests were conducted to assess depression-like behavior. Western blot analysis was used to evaluate the expression of brevican, aggrecan, GLuA1, and PSD95 in mPFC subregions. Results: Behavioral parameter evaluation show that rats in the shBcan + CUMS group exhibited a significantly reduced sucrose preference (P = .0002) and increased immobility time (P = .0011) compared to those in rats in the GFP + CUMS group. Western blotting showed that brevican expression was significantly downregulated in the PrL of the shBcan + CUMS group compared with that in the GFP + CUMS group (P = .0192). Furthermore, compared to the CUMS + GFP + EA group, the CUMS + shBcan + EA group exhibited a significantly decreased sucrose preference (P = .0334), increased immobility time (P = .0465), and increased latency to food (P = .0261). In the CUMS + shBcan + EA group, the EA-induced brevican and PSD95 overexpression was reversed, compared with that in the CUMS + GFP + EA group (P = .0454 and P = .0198, respectively). Conclusion: EA exerts its antidepressant effects through the modulation of brevican expression in rats. Our findings highlight the important role for brevican in stress susceptibility, which could be a potential target for treating depression.

Abstract Background Solanum aculeatissimum and Solanum torvum belong to the Solanum species, and they are essential plants known for their high resistance to diseases and adverse conditions. They are frequently used as rootstocks for grafting and are often crossbred with other Solanum species to leverage their resistance traits. However, the phylogenetic relationship between S. aculeatissimum and S. torvum within the Solanum genus remains unclear. Therefore, this paper aims to sequence the complete chloroplast genomes of S. aculeatissimum and S. torvum and analyze them in comparison with 29 other previously published chloroplast genomes of Solanum species. Results We observed that the chloroplast genomes of S. aculeatissimum and S. torvum possess typical tetrameric structures, consisting of one Large Single Copy (LSC) region, two reverse-symmetric Inverted Repeats (IRs), and one Small Single Copy (SSC) region. The total length of these chloroplast genomes ranged from 154,942 to 156,004 bp, with minimal variation. The highest GC content was found in the IR region, while the lowest was in the SSC region. Regarding gene content, the total number of chloroplast genes and CDS genes remained relatively consistent, ranging from 128 to 134 and 83 to 91, respectively. Nevertheless, there was notable variability in the number of tRNA genes and rRNAs. Relative synonymous codon usage (RSCU) analysis revealed that both S. aculeatissimum and S. torvum preferred codons that utilized A and U bases. Analysis of the IR boundary regions indicated that contraction and expansion primarily occurred at the junction between SSC and IR regions. Nucleotide polymorphism analysis and structural variation analysis demonstrated that chloroplast variation in Solanum species mainly occurred in the LSC and SSC regions. Repeat sequence analysis revealed that A/T was the most frequent base pair in simple repeat sequences (SSR), while Palindromic and Forward repeats were more common in long sequence repeats (LSR), with Reverse and Complement repeats being less frequent. Phylogenetic analysis indicated that S. aculeatissimum and S. torvum belonged to the same meristem and were more closely related to Cultivated Eggplant. Conclusion These findings enhance our comprehension of chloroplast genomes within the Solanum genus, offering valuable insights for plant classification, evolutionary studies, and potential molecular markers for species identification.

Mathematical models for controlling centrally oriented and non-centrally oriented rotary wheels of a mobile robot are considered. Based on the analysis of the kinematics of the mobile robot, the dependences of the rotation angle of the rear and front free wheel on the angular velocities of the right and left differentially driven drive wheel were obtained. For a specific mobile robot with certain kinematic parameters, graphs of the dependences of the angle of rotation of the free wheels on the radius of rotation of each wheel and graphs of the dependences of the angle of rotation of the free wheels on the angular velocities of the driving wheels were constructed. The results obtained made it possible to establish a pattern between the angle of rotation of the castor wheels and the design characteristics of the robot. A certain range of angular velocities of the driving wheels in accordance with the limiting values of the caster wheel rotation angles makes it possible to take into account the obtained mathematical models to increase the stability of the movement of the mobile robot.

With the deepening of the process of global economic integration, international trade supply chain financial services have also flourished. International trade supply chain financial services have played an important role in solving supply chain enterprise financing. As far as the energy industry is concerned, international trade supply chain financial services can provide sufficient credit support for energy companies. This solves the financing dilemma of small and medium-sized energy companies in import and export trade, and can also improve the capital turnover rate of large energy companies. However, because the international trade supply chain financial service still faces the influence of risks such as corporate credit risk, bank operational risk, and supply chain enterprise information transmission risk, its function of providing financing has not been fully exerted. Early warning and control of risks existing in international trade supply chain financial services can fully play the role of international trade supply chain financial services in promoting the development of the energy industry. Therefore, this article used three artificial intelligence (AI) algorithms, including artificial neural network, genetic algorithm and particle swarm algorithm, to analyze the risk of financial services in the international trade supply chain of the energy industry. A risk early-warning model about the financial services of the international trade supply chain of the energy industry was constructed, and an experimental study on the risk early-warning model was carried out. Research showed that the risk early warning model based on AI algorithm enabled banks to improve the accuracy of corporate credit assessment by 7.43% and the accuracy of information collection by 5.61%. It improved the forecast accuracy of external environmental risks by 3.52%, and reduced bank operational risk by 6.58% and legal and regulatory risk by 7.06%.

IntroductionAutomatically and accurately delineating the primary nasopharyngeal carcinoma (NPC) tumors in head magnetic resonance imaging (MRI) images is crucial for patient staging and radiotherapy. Inspired by the bilateral symmetry of head and complementary information of different modalities, a multi-modal neural network named BSMM-Net is proposed for NPC segmentation.MethodsFirst, a bilaterally symmetrical patch block (BSP) is used to crop the image and the bilaterally flipped image into patches. BSP can improve the precision of locating NPC lesions and is a simulation of radiologist locating the tumors with the bilateral difference of head in clinical practice. Second, modality-specific and multi-modal fusion features (MSMFFs) are extracted by the proposed MSMFF encoder to fully utilize the complementary information of T1- and T2-weighted MRI. The MSMFFs are then fed into the base decoder to aggregate representative features and precisely delineate the NPC. MSMFF is the output of MSMFF encoder blocks, which consist of six modality-specific networks and one multi-modal fusion network. Except T1 and T2, the other four modalities are generated from T1 and T2 by the BSP and DT modal generate block. Third, the MSMFF decoder with similar structure to the MSMFF encoder is deployed to supervise the encoder during training and assure the validity of the MSMFF from the encoder. Finally, experiments are conducted on the dataset of 7633 samples collected from 745 patients.Results and discussionThe global DICE, precision, recall and IoU of the testing set are 0.82, 0.82, 0.86, and 0.72, respectively. The results show that the proposed model is better than the other state-of-the-art methods for NPC segmentation. In clinical diagnosis, the BSMM-Net can give precise delineation of NPC, which can be used to schedule the radiotherapy.

Organic ultraviolet filters (OUVFs) and nanoplastics (NPs) are two important new pollutants that coexist widely in freshwater and coastal habitats. Both OUVFs and MPs can be taken up by aquatic organisms and may be toxic or co-toxic. In this study, the neurotoxicity and interaction neurotoxicity of the typical OUVFs butyl methoxydibenzoyl methane (BM-DBM) and polystyrene nanoplastics (PS-NPs) on zebrafish at environmental concentrations were comprehensively investigated at the tissue and molecular levels using transgenic or non-transgenic zebrafish. Results showed that both BM-DBM and PS-NPs induced abnormal expression of developmental genes neurogenin 1, glial fibrillary acidic protein, Finkel-Biskis-Jinkins osteosarcoma oncogene, growth-associated protein 43, synapsin IIa, and apoptosis regulator a (Bcl2a), Bcl2 associated x and apoptosis-related cysteine peptidase a, neuronal loss, motor neuron axon deletion, neuronal apoptosis and behavioral abnormalities in larvae thus being neurotoxic. BM-DBM also specifically interferes with neurotransmitter systems and affects signaling between neurons. In addition, PS-NPs and BM-BDM exerted synergistic and antagonistic effects in inducing apoptosis in neuronal cells and developmental neurotoxicity, respectively. Our results highlight the neurotoxic risk of PS-NPs and BM-BDM and the complex interactive neurotoxic effects of the two. We anticipate that our study may lay the foundation for ecological risk assessment of OUVFs and PS-NPs and exploration of complex interactions between PS-NPs and hydrophobic organic pollutants.

The amount of money individuals were willing to accept (WTA) to discontinue using prominent Chinese social media platforms (WeChat/QQ), the willingness to pay (WTP) for using these platforms, as well as WTA/WTP disparities were investigated in between-groups and within-subjects design studies to examine their existence, size, and psychological correlates in the form of personality and social media use habits.Individuals were recruited at Chinese universities in three separate surveys. For between-groups investigations, four samples were investigated: WTA and WTP samples for investigations in the context of WeChat as well as WTA and WTP samples for QQ. For within-subjects investigations, individuals completed items on WTA and WTP for WeChat/QQ, the Big Five Inventory, time spent on WeChat/QQ, and the short Bergen Social Media Addiction Scale. Two samples providing data on WeChat and QQ, respectively, were investigated.Across study designs and for both WeChat and QQ we found evidence for high WTA and comparatively low WTP scores, thus, large WTA/WTP disparities. Individual differences in the disparities were negatively associated with Openness across social media platforms. The results reveal a generally low acceptance to pay for social media use, which is important against the background of discussions on monetary payment models. Moreover, a complex interplay between individual characteristics, characteristics of the service, and how and why the service is used seems to underly WTA and the WTA/WTP disparity. Finally, methodological implications of the present results for forthcoming studies assessing valuation (WTA, WTP) in the context of social media are discussed.

In the age of digitalization, social media has played a significant role in quickly spreading the news about current affairs. From December 2019 to now, coronavirus disease 2019 (COVID-19), with its several mutated shapes, has more transmissible potential catastrophe and has become a severe phenomenon issue worldwide. The international spread of the epidemic has created fear among people, especially employees working physically in different organizations. The present research aimed to measure the impact of social media on its users in the China. The social media users more often were influenced by shocking news instructively and destructively. The research analysis was based on service sector employees and data collected from 630 respondents via a structured questionnaire. This research was confirmed the negative impact of fear on social media on the performance of employees. This research was also confirmed the moderation impact of the COVID-19 vaccine on the relationship between social media fear and employee performance. This research recommends that the China Censor Board checked the news and its validity to reduce the fear of COVID-19 among employees. This research will become a roadmap for organizations and media controllers to understand the impact of social media during an intense situation. The telecommunication sector will reduce psychological disease and enhance the work capability of employees by controlling unnecessary and unapproved material about sensitive issues.

The present study investigates links between fear of COVID-19, the personality trait of neuroticism, social networks use disorder, and smartphone use disorder (SNUD and SmUD, respectively) tendencies. In an online survey, N = 932 participants recruited at a Chinese University (237 males and 695 females) completed self-reports on fear of COVID-19, neuroticism (and other personality traits from the Big Five Inventory-44), the Bergen Social Media Addiction Scale (assessing tendencies toward SNUD), and the Smartphone Addiction Scale short version—assessing individual differences in tendencies toward SmUD.Our findings showed that all variables of main interest were positively correlated with each other. A mediation model suggested that SNUD (in parts) mediated the association between fear of COVID-19 and SmUD. Although neuroticism was robustly correlated with all mentioned variables, no moderation effect could be observed on the investigated fear-of-COVID-19-SNUD-link.The findings of this work provide further evidence that the smartphone itself is only a device giving individuals access to software applications, which might be excessively used. Beyond that, the present data indicate neuroticism to be a risk factor with respect to fear of COVID-19, SNUD, and SmUD, although the study is limited by its cross-sectional study design.

Unlike previous studies in which a single index was used to measure audit quality, this study establishes a new comprehensive index to measure audit quality via Discretionary Accrual, as estimated by Jones’ basic model (1991) and Audit Opinions. The former is used to measure the quality of financial statements, and the latter is used to measure the auditors’ independence in the mainstream international literature. We examine whether and how an auditor’s gender affects the quality of his or her audits under the framework of empathy theory and gender role socialization theory. Using a large sample of 9861 auditor-firm-year observations from Chinese A-share–listed companies from 2011 to 2015, we find that the audit quality of signed auditors shows significant gender differences: these significant gender differences differ from the findings of previous studies that female auditors could provide a higher-quality audit than male auditors; that is, in our study the audit quality of the male auditors exceeds that of the female auditors. After distinguishing the positive and negative directions of the Discretionary Accrual, we find no significant gender differences in audit quality between male and female auditors when the earnings had been adjusted upward by the client; that is, female and male auditors had the same audit risk perception. However, when the client adjusted earnings downward, which indicates a lower audit risk for the auditor, the audit quality of female auditors was significantly lower than that of the male auditors. After controlling for the age and position of the auditors, we also find that the gender differences in the auditors’ audit quality decreased significantly or even disappeared when the auditor’s age exceeded 45 years and/or their position was manager or above. These results are consistent with the empathy theory and gender role socialization theory. Keywords: Auditor characteristics, Sex difference, Gender difference, Audit quality, Personal characteristics