Dietary inflammatory potential and the risk of nonfatal cardiovascular diseases in the China Health and Nutrition Survey.

BACKGROUND: To our knowledge, no evidence exists to link dietary inflammatory potential to cardiovascular disease (CVD) in China. Furthermore, the precise mechanisms underlying the link between a pro-inflammatory diet and CVD remain incompletely understood. OBJECTIVE: We aimed to investigate the relationship between dietary inflammatory potential and nonfatal CVD in the Chinese population and to explore the mediating role of insulin resistance. METHODS: A total of 4822 adults who participated in the China Health and Nutrition Survey (CHNS) were included in this analysis. The dietary inflammatory index (DII) was used to assess dietary inflammatory potential. Cox proportional hazards models and restricted cubic spline were applied to assess the longitudinal associations. The triglyceride-glucose (TyG) index was calculated to measure insulin resistance. Mediation analysis using a two-stage regression method for survival data was employed to explore the mediating effects of the TyG index on the association between DII score and nonfatal CVD. RESULTS: During a median follow-up of 18 y, 234 incident cases of nonfatal CVD, including 136 strokes and 114 myocardial infarctions (MIs), were observed. For each standard deviation of the DII score, nonfatal CVD incidence increased by 15% (hazard ratio [HR]: 1.15, 95% confidence interval [CI]: 1.01-1.31), and stroke incidence increased by 22% (HR = 1.22, 95% CI: 1.03-1.45). DII score displayed a linear association with nonfatal CVD and stroke (P for nonlinearity = 0.250 and 0.238, respectively). No significant association was found between the DII score and MI. Mediation analyses showed that the TyG index mediated 5.90% and 9.35% of the total association between DII score and nonfatal CVD and stroke, respectively. CONCLUSIONS: This study provides evidence that dietary inflammatory potential is positively associated with nonfatal CVD and stroke in Chinese adults, and the association was partly mediated by insulin resistance.

Compact plasmon modulator based on the spatial control of carrier density in indium tin oxide.

To keep pace with the demands of semiconductor integration technology, a semiconductor device should offer a small footprint. Here, we demonstrate a compact electro-optic modulator by controlling the spatial distribution of carrier density in indium tin oxide (ITO). The proposed structure is mainly composed of a symmetrical metal electrode layer, calcium fluoride dielectric layer, and an ITO propagating layer. The carrier density on the surface of the ITO exhibits a periodical distribution when the voltage is applied on the electrode, which greatly enhances the interaction between the surface plasmon polaritons (SPPs) and the ITO. This structure can not only effectively improve the modulation depth of the modulator, but also can further reduce the device size. The numerical results indicate that when the length, width, and height of the device are 14 µm, 5 µm, and 8 µm, respectively, the modulation depth can reach 37.1 dB at a wavelength of 3.66 µm. The structure can realize a broadband modulation in theory only if we select a different period of the electrode corresponding to the propagating wavelength of SPPs because the modulator is based on the scattering effect principle. This structure could potentially have high applicability for optoelectronic integration, optical communications, and optical sensors in the future.

Artificial intelligence assisted pterygium diagnosis: current status and perspectives.

Pterygium is a prevalent ocular disease that can cause discomfort and vision impairment. Early and accurate diagnosis is essential for effective management. Recently, artificial intelligence (AI) has shown promising potential in assisting clinicians with pterygium diagnosis. This paper provides an overview of AI-assisted pterygium diagnosis, including the AI techniques used such as machine learning, deep learning, and computer vision. Furthermore, recent studies that have evaluated the diagnostic performance of AI-based systems for pterygium detection, classification and segmentation were summarized. The advantages and limitations of AI-assisted pterygium diagnosis and discuss potential future developments in this field were also analyzed. The review aims to provide insights into the current state-of-the-art of AI and its potential applications in pterygium diagnosis, which may facilitate the development of more efficient and accurate diagnostic tools for this common ocular disease.

Biomedical association analysis between G2/M checkpoint genes and susceptibility to HIV-1 infection and AIDS progression from a northern chinese MSM population.

BACKGROUND: MSM are at high risk of HIV infection. Previous studies have shown that the cell cycle regulation plays an important role in HIV-1 infection, especially at the G2/M checkpoint. ATR, Chk1, Cdc25C and CDK1 are key genes of G2/M checkpoint. However, the association between SNPs of these genes and susceptibility to HIV-1 infection and AIDS progression remains unknown. METHODS: In this study, 42 tSNPs from the above four G2/M checkpoint genes were genotyped in 529 MSM and 529 control subjects from northern China to analyze this association. RESULTS: The results showed that rs34660854 A and rs75368165 A in ATR gene and rs3756766 A in Cdc25C gene could increase the risk of HIV-1 infection (P = 0.049, OR = 1.234, 95% CI 1.001-1.521; P = 0.020, OR = 1.296, 95% CI 1.042-1.611; P = 0.011, OR = 1.392, 95% CI 1.080-1.794, respectively), while Chk1 rs10893405 (P = 0.029, OR = 1.629, 95% CI 1.051-2.523) were significantly associated with AIDS progression. Besides, rs34660854 (P = 0.019, OR = 1.364, 95% CI 1.052-1.769; P = 0.022, OR = 1.337, 95% CI 1.042-1.716, under Codominant model and Dominant model, respectively) and rs75368165 (P = 0.006, OR = 1.445, 95% CI = 1.114-1.899; P = 0.007, OR = 1.418, 95% CI 1.099-1.831, under Codominant model and Dominant model, respectively) in ATR gene, rs12576279 (P = 0.013, OR = 0.343, 95% CI 0.147-0.800; P = 0.048, OR = 0.437, 95% CI 0.192-0.991, under Codominant model and Dominant model, respectively) and rs540436 (P = 0.012, OR = 1.407, 95% CI 1.077-1.836; P = 0.021, OR = 1.359, 95% CI 1.048-1.762, under Codominant model and Dominant model, respectively) in Chk1 gene, rs3756766 (P = 0.013, OR = 1.455, 95% CI 1.083-1.954; P = 0.009, OR = 1.460, 95% CI 1.098-1.940, under Codominant model and Dominant model, respectively) in Cdc25C gene and rs139245206 (P = 0.022, OR = 5.011, 95% CI 1.267-19.816; P = 0.020, OR = 5.067, 95% CI 1.286-19.970, under Codominant model and Recessive model, respectively) in CDK1 gene were significantly associated with HIV-1 infection under different models. CONCLUSIONS: We found that genetic variants of G2/M checkpoint genes had a molecular influence on the occurrence of HIV-1 infection and AIDS progression in a northern Chinese MSM population.

Optical coherence tomography image despeckling based on tensor singular value decomposition and fractional edge detection.

Optical coherence tomography (OCT) imaging is a technique that is frequently used to diagnose medical conditions. However, coherent noise, sometimes referred to as speckle noise, can dramatically reduce the quality of OCT images, which has an adverse effect on how OCT images are used. In order to enhance the quality of OCT images, a speckle noise reduction technique is developed, and this method is modelled as a low-rank tensor approximation issue. The grouped 3D tensors are first transformed into the transform domain using tensor singular value decomposition (t-SVD). Then, to cut down on speckle noise, transform coefficients are thresholded. Finally, the inverse transform can be used to produce images with speckle suppression. To further enhance the despeckling results, a feature-guided thresholding approach based on fractional edge detection and an adaptive backward projection technique are also presented. Experimental results indicate that the presented algorithm outperforms several comparison methods in relation to speckle suppression, objective metrics, and edge preservation.

Research on classification method of high myopic maculopathy based on retinal fundus images and optimized ALFA-Mix active learning algorithm.

AIM: To conduct a classification study of high myopic maculopathy (HMM) using limited datasets, including tessellated fundus, diffuse chorioretinal atrophy, patchy chorioretinal atrophy, and macular atrophy, and minimize annotation costs, and to optimize the ALFA-Mix active learning algorithm and apply it to HMM classification. METHODS: The optimized ALFA-Mix algorithm (ALFA-Mix+) was compared with five algorithms, including ALFA-Mix. Four models, including ResNet18, were established. Each algorithm was combined with four models for experiments on the HMM dataset. Each experiment consisted of 20 active learning rounds, with 100 images selected per round. The algorithm was evaluated by comparing the number of rounds in which ALFA-Mix+ outperformed other algorithms. Finally, this study employed six models, including EfficientFormer, to classify HMM. The best-performing model among these models was selected as the baseline model and combined with the ALFA-Mix+ algorithm to achieve satisfactory classification results with a small dataset. RESULTS: ALFA-Mix+ outperforms other algorithms with an average superiority of 16.6, 14.75, 16.8, and 16.7 rounds in terms of accuracy, sensitivity, specificity, and Kappa value, respectively. This study conducted experiments on classifying HMM using several advanced deep learning models with a complete training set of 4252 images. The EfficientFormer achieved the best results with an accuracy, sensitivity, specificity, and Kappa value of 0.8821, 0.8334, 0.9693, and 0.8339, respectively. Therefore, by combining ALFA-Mix+ with EfficientFormer, this study achieved results with an accuracy, sensitivity, specificity, and Kappa value of 0.8964, 0.8643, 0.9721, and 0.8537, respectively. CONCLUSION: The ALFA-Mix+ algorithm reduces the required samples without compromising accuracy. Compared to other algorithms, ALFA-Mix+ outperforms in more rounds of experiments. It effectively selects valuable samples compared to other algorithms. In HMM classification, combining ALFA-Mix+ with EfficientFormer enhances model performance, further demonstrating the effectiveness of ALFA-Mix+.

[CT and MRI fusion based on generative adversarial network and convolutional neural networks under image enhancement].

Aiming at the problems of missing important features, inconspicuous details and unclear textures in the fusion of multimodal medical images, this paper proposes a method of computed tomography (CT) image and magnetic resonance imaging (MRI) image fusion using generative adversarial network (GAN) and convolutional neural network (CNN) under image enhancement. The generator aimed at high-frequency feature images and used double discriminators to target the fusion images after inverse transform; Then high-frequency feature images were fused by trained GAN model, and low-frequency feature images were fused by CNN pre-training model based on transfer learning. Experimental results showed that, compared with the current advanced fusion algorithm, the proposed method had more abundant texture details and clearer contour edge information in subjective representation. In the evaluation of objective indicators, Q AB/F, information entropy (IE), spatial frequency (SF), structural similarity (SSIM), mutual information (MI) and visual information fidelity for fusion (VIFF) were 2.0%, 6.3%, 7.0%, 5.5%, 9.0% and 3.3% higher than the best test results, respectively. The fused image can be effectively applied to medical diagnosis to further improve the diagnostic efficiency.

Comprehensive evaluation for the sustainable development of fresh agricultural products logistics enterprises based on combination empowerment-TOPSIS method.

To solve the problems of environmental pollution and resource waste caused by the rapid development of cold chain logistics of fresh agricultural products and improve the competitiveness of logistics enterprises in the market, a performance evaluation method of cold chain logistics enterprises based on the combined empowerment-TOPSIS was proposed. Firstly, from the five dimensions of cold supply chain capacity, service quality, economic efficiency, informatization degree and development ability, a comprehensive evaluation system of logistics enterprises' sustainable development is constructed, which consists of 16 indicators, such as storage and preservation capacity, distribution accuracy, and equipment input rate. Then, G1 method and entropy weight method are used to calculate the subjective and objective weights of the evaluation indicators, and the combined weights are calculated with the objective of minimizing the deviation of the subjective and objective weighted attributes. Finally, the TOPSIS method is used to calculate the comprehensive evaluation indicators. The results show that the established performance evaluation model can effectively evaluate the performance of fresh agricultural products logistics enterprises and provide theoretical basis for enterprise logistics management.

Association of Polymorphisms in NHEJ Pathway Genes with HIV-1 Infection and AIDS Progression in a Northern Chinese MSM Population.

Background and Aims: Men who have sex with men (MSM) are at high risk of HIV infection. The nonhomologous end joining (NHEJ) pathway is the main way of double-stranded DNA break (DSB) repair in the higher eukaryotes and can repair the DSB timely at any time in cell cycle. It is also indicated that the NHEJ pathway is associated with HIV-1 infection since the DSB in host genome DNA occurs in the process of HIV-1 integration. The aim of the present investigation was to evaluate associations of single-nucleotide polymorphisms (SNPs) in NHEJ pathway genes with susceptibility to HIV-1 infection and AIDS progression among MSM residing in northern China. Methods: A total of 481 HIV-1 seropositive men and 493 HIV-1 seronegative men were included in this case-control study. Genotyping of 22 SNPs in NHEJ pathway genes was performed using the SNPscan™ Kit. Results: Positive associations were observed between XRCC6 rs132770 and XRCC4 rs1056503 genotypes and the susceptibility to HIV-1 infection. In gene-gene interaction analysis, significant SNP-SNP interactions of XRCC6 and XRCC4 genetic variations were found to play a potential role in the risk of HIV-1 infection. In stratified analysis, XRCC5 rs16855458 was significantly associated with CD4+ T cell counts in AIDS patients, whereas LIG4 rs1805388 was linked to the clinical phases of AIDS patients. Conclusions: NHEJ gene polymorphisms can be considered to be risk factors of HIV-1 infection and AIDS progression in the northern Chinese MSM population.

Identification of Tumor Microenvironment and DNA Methylation-Related Prognostic Signature for Predicting Clinical Outcomes and Therapeutic Responses in Cervical Cancer.

Background: Tumor microenvironment (TME) has been reported to have a strong association with tumor progression and therapeutic outcome, and epigenetic modifications such as DNA methylation can affect TMB and play an indispensable role in tumorigenesis. However, the potential mechanisms of TME and DNA methylation remain unclear in cervical cancer (CC). Methods: The immune and stromal scores of TME were generated by the ESTIMATE algorithm for CC patients in The Cancer Genome Atlas (TCGA) database. The TME and DNA methylation-related genes were identified by the integrative analysis of DNA promoter methylation and gene expression. The least absolute shrinkage and selection operator (LASSO) Cox regression was performed 1,000 times to further identify a nine-gene TME and DNA methylation-related prognostic signature. The signature was further validated in Gene Expression Omnibus (GEO) dataset. Then, the identified signature was integrated with the Federation International of Gynecology and Obstetrics (FIGO) stage to establish a composite prognostic nomogram. Results: CC patients with high immunity levels have better survival than those with low immunity levels. Both in the training and validation datasets, the risk score of the signature was an independent prognosis factor. The composite nomogram showed higher accuracy of prognosis and greater net benefits than the FIGO stage and the signature. The high-risk group had a significantly higher fraction of genome altered than the low-risk group. Eleven genes were significantly different in mutation frequencies between the high- and low-risk groups. Interestingly, patients with mutant TTN had better overall survival (OS) than those with wild type. Patients in the low-risk group had significantly higher tumor mutational burden (TMB) than those in the high-risk group. Taken together, the results of TMB, immunophenoscore (IPS), and tumor immune dysfunction and exclusion (TIDE) score suggested that patients in the low-risk group may have greater immunotherapy benefits. Finally, four drugs (panobinostat, lenvatinib, everolimus, and temsirolimus) were found to have potential therapeutic implications for patients with a high-risk score. Conclusions: Our findings highlight that the TME and DNA methylation-related prognostic signature can accurately predict the prognosis of CC and may be important for stratified management of patients and precision targeted therapy.

Association of APEX1 and XRCC1 Gene Polymorphisms With HIV-1 Infection Susceptibility and AIDS Progression in a Northern Chinese MSM Population.

Background: Some studies have shown that the base excision repair (BER) pathway has an effect on HIV-1 replication. APEX1 and XRCC1 as key BER genes may affect DNA repair capacity. However, the roles of single nucleotide polymorphisms (SNPs) in APEX1 and XRCC1 and their impact on HIV-1 infection and AIDS progression remain unclear. Methods: A custom-designed 48-Plex SNPscan Kit was used for detection of single nucleotide polymorphisms. 601 HIV-1-infected men who have sex with men (MSM) and 624 age-matched healthy individuals were recruited in northern China. Four SNPs (rs1130409, rs1760944, rs2307486 and rs3136817) in APEX1 gene and three SNPs (rs1001581, rs25487 and rs25489) in XRCC1 gene were genotyped. The generalized multifactor dimension reduction (GMDR) method was used to identify the SNP-SNP interactions. Results: In this study, rs1130409 G allele, rs1001581 C allele and rs25487 C allele were associated with a higher risk of HIV-1 infection susceptibility (p = 0.020, p = 0.007 and p = 0.032, respectively). The frequencies of APEX1 haplotype TT and XRCC1 haplotype CT showed significant differences between cases and controls (p = 0.0372 and p = 0.0189, respectively). Interestingly, stratified analysis showed that the frequency of rs1001581 C allele was significantly higher in AIDS patients with the CD4+ T-lymphocyte count <200 cells/µl than those with >200 cells/µl (p = 0.022). Moreover, significant gene-gene interactions among rs1130409, rs1001581 and rs25487 were identified by GMDR (p = 0.0107). Specially, individuals with five to six risk alleles have a higher susceptibility to HIV-1 infection than those with zero to two risk alleles (p < 0.001). Conclusion: APEX1 and XRCC1 gene polymorphisms were associated with the susceptibility to HIV-1 infection and AIDS progression in MSM populations in northern China.