Development and Validation of an Internet-Based Remote Perimeter (Perimouse).

Purpose: We sought to validate the feasibility of Perimouse, an internet-based remote perimeter that allows for natural fixation and can be performed on most computers via a web page. Methods: In this cross-sectional study, Perimouse evaluated the visual field of 45 healthy people and 27 patients with primary open-angle glaucoma on a laptop. Participants used a mouse cursor to locate new dots on the screen that were determined by preset saccade vectors. A "click and confirm" strategy was used to eliminate the unwanted visual search. Dot brightness was either fixed at 12 dB in the suprathreshold program (screening program) or variable in the threshold program. We compared Perimouse outcomes with the Humphrey Field Analyzer (HFA) 24-2 Swedish Interactive Testing Algorithm standard program. Results: In the screening program, Perimouse showed moderate to high concordance with HFA. The intraclass coefficient ranged from 0.58 to 0.86 in different areas of Garway-Heath mapping. In the threshold program, normal subjects had threshold ranging from 19 to 16 dB, presenting sensitivity changes according to the "hill of vision". The test-retest difference was 0.09 dB. Habitual spectacle correction and environmental luminance (2-337 lux) had little impact on the central or peripheral threshold (P > 0.05). The correlation between Perimouse and HFA threshold sensitivity was strong (R = 0.950), although Perimouse mean defect was 4.40 dB higher than the HFA mean defect. Conclusions: Perimouse is a reliable visual field test that correlates strongly with HFA. It shows potential for population screening and monitoring visual field defects. Translational Relevance: Perimouse assesses the visual field using saccade vectors without eye trackers, enhancing its accessibility via a web page.

Multiparametric MRI-based radiomics combined with pathomics features for prediction of the efficacy of neoadjuvant chemotherapy in breast cancer.

Purpose: The aim of this study is to investigate a new method that combines radiological and pathological breast cancer information to predict discrepancies in pathological responses for individualized treatment planning. We used baseline multiparametric magnetic resonance imaging and hematoxylin and eosin-stained biopsy slides to extract quantitative feature information and predict the pathological response to neoadjuvant chemotherapy in breast cancer patients. Methods: We retrospectively collected data from breast cancer patients who received neoadjuvant chemotherapy in our hospital from August 2016 to January 2018; multiparametric magnetic resonance imaging (contrast-enhanced T1-weighted imaging and diffusion-weighted imaging) and whole slide image of hematoxylin and eosin-stained biopsy sections were collected. Quantitative imaging features were extracted from the multiparametric magnetic resonance imaging and the whole slide image were used to construct a radiopathomics signature model powered by machine learning methods. Models based on multiparametric magnetic resonance imaging or whole slide image alone were also constructed for comparison and referred to as the radiomics signature and pathomics signature models, respectively. Four modeling methods were used to establish prediction models. Model performances were evaluated using receiver operating characteristic curve analysis and the area under the curve, accuracy, sensitivity, specificity, positive predictive value, and negative predictive value. Results: The radiopathomics signature model had favourable performance for the prediction of pathological complete response in the training set (the best value: area under the curve 0.83, accuracy 0.84, and sensitivity 0.87), and in the test set (the best value: area under the curve 0.91, accuracy 0.90, and sensitivity 0.88). In the test set, the radiopathomics signature model also significantly outperformed the radiomics signature (the best value: area under the curve 0.83, accuracy 0.64, and sensitivity 0.62), pathomics signature (the best value: area under the curve 0.60, accuracy 0.74, and sensitivity 0.62) (p > 0.05). Decision curve analysis and calibration curves confirmed the excellent performance of these prediction models in discrimination, calibration, and clinical usefulness. Conclusions: The results of this study suggest that radiopathomics, the combination of both radiological information regarding the whole tumor and pathological information at the cellular level, could potentially predict discrepancies in pathological response and provide evidence for rational treatment plans.

Factors associated with overdiagnosis of benign pulmonary nodules as malignancy: a retrospective cohort study.

OBJECTIVE: To establish a preoperative model for the differential diagnosis of benign and malignant pulmonary nodules (PNs), and to evaluate the related factors of overdiagnosis of benign PNs at the time of imaging assessments. MATERIALS AND METHODS: In this retrospective study, 357 patients (median age, 52 years; interquartile range, 46-59 years) with 407 PNs were included, who underwent surgical histopathologic evaluation between January 2020 and December 2020. Patients were divided into a training set (n = 285) and a validation set (n = 122) to develop a preoperative model to identify benign PNs. CT scan features were reviewed by two chest radiologists, and imaging findings were categorized. The overdiagnosis rate of benign PNs was calculated, and bivariate and multivariable logistic regression analyses were used to evaluate factors associated with benign PNs that were over-diagnosed as malignant PNs. RESULTS: The preoperative model identified features such as the absence of part-solid and non-solid nodules, absence of spiculation, absence of vascular convergence, larger lesion size, and CYFRA21-1 positivity as features for identifying benign PNs on imaging, with a high area under the receiver operating characteristic curve of 0.88 in the validation set. The overdiagnosis rate of benign PNs was found to be 50%. Independent risk factors for overdiagnosis included diagnosis as non-solid nodules, pleural retraction, vascular convergence, and larger lesion size at imaging. CONCLUSION: We developed a preoperative model for identifying benign and malignant PNs and evaluating factors that led to the overdiagnosis of benign PNs. This preoperative model and result may help clinicians and imaging physicians reduce unnecessary surgery.

Transcriptome profile analysis revealed the potential mechanism of LIPUS treatment for Adriamycin-induced chronic kidney disease rat.

Background: Developing effective therapeutic strategies to delay the progression of chronic kidney disease (CKD) remains a significant challenge. Low-intensity pulsed ultrasound (LIPUS) has demonstrated potential for treating CKD, but the underlying molecular mechanisms are still elusive. This study aimed to evaluate the therapeutic efficacy of LIPUS and to elucidate the involved genes and signaling pathways. Methods: The CKD model was established in rats using Adriamycin (ADR). The bilateral kidneys of CKD rats were continuously stimulated with LIPUS for a period of four weeks. The therapeutic efficacy was defined by renal function and histopathological evaluation. RNA sequencing was employed to profile the transcriptome of rat kidneys in each group. Cluster analysis was utilized to identify differentially expressed genes (DEGs), followed by enrichment analysis of their associated pathways using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Results: LIPUS treatment improved ADR-induced renal dysfunction in the CKD group. Renal fibrosis and pathological damages were also alleviated in the ADR + LIPUS group compared to the ADR group. Cluster analysis identified 844 DEGs. GO enrichment analysis revealed enrichment in inflammatory response terms, while KEGG enrichment analysis highlighted the nuclear factor kappa B (NF-κB) signaling and ferroptosis-related pathways. Conclusion: Continuous LIPUS treatment improved ADR-induced renal fibrosis and dysfunction. The therapeutic effect of LIPUS was primarily due to its ability to suppress the CKD-related inflammation, which was associated with the modulation of the NF-κB and ferroptosis signaling pathways. These findings provide a new insight into the potential molecular mechanisms of LIPUS in treating CKD. Further research is necessary to confirm these findings and to identify potential therapeutic targets within these pathways.

Effects of hypertension on subcortical nucleus morphological alternations in patients with type 2 diabetes.

Objectives: Type 2 diabetes mellitus(T2DM) and hypertension(HTN) are common comorbidities, and known to affect the brain. However, little is known about the effects of the coexisting HTN on brain in T2DM patients. So we aim to investigate the impact of HTN on the subcortical nucleus morphological alternations in T2DM patients. Materials & methods: This work was registered by the clinicaltrials.gov (grant number NCT03564431). We recruited a total of 92 participants, comprising 36 only T2DM patients, 28 T2DM patients with HTN(T2DMH) and 28 healthy controls(HCs) in our study. All clinical indicators were assessed and brain image data was collected for each participant. Voxel-based morphometry(VBM), automatic volume and vertex-based shape analyses were used to determine the subcortical nucleus alternations from each participant's 3D-T1 brain images and evaluate the relationship between the alternations and clinical indicators. Results: T2DMH patients exhibited volumetric reduction and morphological alterations in thalamus compared to T2DM patients, whereas T2DM patients did not demonstrate any significant subcortical alterations compared to HCs. Furthermore, negative correlations have been found between thalamic alternations and the duration of HTN in T2DMH patients. Conclusion: Our results revealed that HTN may exacerbate subcortical nucleus alternations in T2DM patients, which highlighted the importance of HTN management in T2DM patients to prevent further damage to the brain health.

Low intensity pulsed ultrasound ameliorates Adriamycin-induced chronic renal injury by inhibiting ferroptosis.

OBJECTIVE: It is very important to develop a new therapeutic strategy to cope with the increasing morbidity and mortality of chronic kidney disease (CKD). As a kind of physical therapy, low intensity pulsed ultrasound (LIPUS) has remarkable anti-inflammatory and repair-promoting effects and is expected to become a new therapeutic method for CKD. This study aims to clarify the treatment effect of LIPUS on CKD-related renal inflammation and fibrosis, and to further explore the potential signal network of LIPUS treatment for ameliorating chronic renal injury. METHODS: A rat model simulating the progress of CKD was established by twice tail-vein injection of Adriamycin (ADR). Under anesthesia, bilateral kidneys of CKD rats were continuously stimulated by LIPUS for four weeks. The parameters of LIPUS were 1.0 MHz, 60 mW/cm2, 50% duty cycle and 20 min/d. RESULTS: LIPUS treatment effectively inhibited ADR-induced renal inflammation and fibrosis, and improved CKD-related to oxidative stress and ferroptosis. In addition, the therapeutic effect of LIPUS is closely related to the regulation of TGF-ß1/Smad and Nrf2/keap1/HO-1 signalling pathways. DISCUSSION: This study provides a new direction for further mechanism research and lays an important foundation for clinical trials.

Diagnostic accuracy of glioma pseudoprogression identification with positron emission tomography imaging: a systematic review and meta-analysis.

Background: Positron emission tomography (PET) imaging is a promising molecular neuroimaging technique and has been proposed as one of the criteria for glioma management. However, there is some controversy concerning the diagnostic accuracy of PET using different radiotracers to differentiate between glioma pseudoprogression (PsP) and true progression (TPR). The purpose of this meta-analysis was to systematically evaluate the methodological quality and clinical value of original studies for distinguishing PsP from TPR in glioma. Methods: The Medline, Web of Science, Embase, Cochrane Library, and ClinicalTrials.gov were searched from inception until September 1, 2022. Retrieved clinical studies only investigated the PsP cases but did not include the cases of radiation necrosis or other treatment-related changes. Eligible studies were screened for data extraction and evaluated by 2 independent reviewers using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. A random effects model was used to describe summary receiver operating characteristics. Meta-regression and subgroup analyses were applied to identify any sources of heterogeneity. Results: The meta-analysis included 20 studies, comprising 317 (30.9%) patients with PsP and 708 (69.1%) with TPR. The summary sensitivity and specificity of general PET for identifying PsP were 0.86 [95% confidence interval (CI): 0.77-0.91] and 0.84 (95% CI: 0.79-0.88), respectively. The statistical heterogeneity was explained by sample size, study design, World Health Organization (WHO) grade, gold standard, and radiotracer type. The summary sensitivity and specificity of O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET PET) were 0.80 (95% CI: 0.68-0.88) and 0.81 (95% CI: 0.75-0.85), respectively. The maximum tumor-to-brain ratio (TBRmax) and the mean tumor-to-brain ratio (TBRmean) both showed excellent diagnostic performance in 18F-FET studies, the summary sensitivity was 0.83 (95% CI: 0.72-0.91) and 0.79 (95% CI: 0.65-0.98), respectively, and the specificity was 0.76 (95% CI: 0.68-0.84) and 0.78 (95% CI: 0.64-0.88), respectively. Conclusions: PET imaging is generally accurate in identifying glioma PsP. Considering the credibility of meta-evidence and the practicability of using radiotracer, 18F-FET PET holds the highest clinical value, while TBRmax and TBRmean should be regarded as reliable parameters. PET used with the radiotracers and multiple-parameter combinations of PET with magnetic resonance imaging (MRI) and radiomics analysis have broad research and application prospects, whose diagnostic values for identifying glioma PsP warrant further investigation.

Multi-omics study of key genes, metabolites, and pathways of periodontitis.

OBJECTIVE: This study aimed to explore the key genes, metabolites, and pathways that influence periodontitis pathogenesis by integrating transcriptomic and metabolomic studies. DESIGN: Gingival crevicular fluid samples from periodontitis patients and healthy controls were collected for liquid chromatography/tandem mass-based metabolomics. RNA-seq data for periodontitis and control samples were obtained from the GSE16134 dataset. Differential metabolites and differentially expressed genes (DEGs) between the two groups were then compared. Based on the protein-protein interaction (PPI) network module analysis, key module genes were selected from immune-related DEGs. Correlation and pathway enrichment analyses were performed for differential metabolites and key module genes. A multi-omics integrative analysis was performed using bioinformatic methods to construct a gene-metabolite-pathway network. RESULTS: From the metabolomics study, 146 differential metabolites were identified, which were mainly enriched in the pathways of purine metabolism and Adenosine triphosphate binding cassette transporters (ABC transporters). The GSE16134 dataset revealed 102 immune-related DEGs (458 upregulated and 264 downregulated genes), 33 of which may play core roles in the key modules of the PPI network and are involved in cytokine-related regulatory pathways. Through a multi-omics integrative analysis, a gene-metabolite-pathway network was constructed, including 28 genes (such as platelet derived growth factor D (PDGFD), neurturin (NRTN), and interleukin 2 receptor, gamma (IL2RG)); 47 metabolites (such as deoxyinosine); and 8 pathways (such as ABC transporters). CONCLUSION: PDGFD, NRTN, and IL2RG may be potential biomarkers of periodontitis and may affect disease progression by regulating deoxyinosine to participate in the ABC transporter pathway.

Contrast enhanced magnetic resonance imaging-based radiomics nomogram for preoperatively predicting expression status of Ki-67 in meningioma: a two-center study.

Background: The aim of this study was to develop and validate a radiomics nomogram for preoperative prediction of Ki-67 proliferative index (Ki-67 PI) expression in patients with meningioma. Methods: A total of 280 patients from 2 independent hospital centers were enrolled. Patients from center I were randomly divided into a training cohort of 168 patients and a test cohort of 72 patients, and 40 patients from center II served as an external validation cohort. Interoperator reproducibility test, Z-score standardization, analysis of variance (ANOVA), and least absolute shrinkage and selection operator (LASSO) binary logistic regression were used to select radiomics features, which were extracted from contrast-enhanced T1-weighted imaging (CE-T1WI) imaging. The radiomics signature for predicting Ki-67 PI expression was developed and validated using 4 classifiers including logistic regression (LR), decision tree (DT), support vector machine (SVM), and adaptive boost (AdaBoost). Finally, combined radiological characteristics with radiomics signature were used to establish the nomogram to predict the risk of high Ki-67 PI expression in patients with meningioma. Results: Fourteen radiomics features were used to construct the radiomics signature. The radiomics nomogram that incorporated the radiomics signature and radiological characteristics showed excellent discrimination in the training, test, and validation cohorts with areas under the curve of 0.817 (95% CI: 0.753-0.881), 0.822 (95% CI: 0.727-0.916), and 0.845 (95% CI: 0.708-0.982), respectively. In addition, the calibration curve for the nomogram demonstrated good agreement between prediction and actual observation. Conclusions: The proposed contrast enhanced magnetic resonance imaging (MRI)-based radiomics nomogram could be an effective tool to predict the risk of Ki-67 high expression in patients with meningioma.

Prediction of brain age using quantitative parameters of synthetic magnetic resonance imaging.

Objective: Brain tissue changes dynamically during aging. The purpose of this study was to use synthetic magnetic resonance imaging (syMRI) to evaluate the changes in relaxation values in different brain regions during brain aging and to construct a brain age prediction model. Materials and methods: Quantitative MRI was performed on 1,000 healthy people (≥ 18 years old) from September 2020 to October 2021. T1, T2 and proton density (PD) values were simultaneously measured in 17 regions of interest (the cerebellar hemispheric cortex, pons, amygdala, hippocampal head, hippocampal tail, temporal lobe, occipital lobe, frontal lobe, caudate nucleus, lentiform nucleus, dorsal thalamus, centrum semiovale, parietal lobe, precentral gyrus, postcentral gyrus, substantia nigra, and red nucleus). The relationship between the relaxation values and age was investigated. In addition, we analyzed the relationship between brain tissue values and sex. Finally, the participants were divided into two age groups: < 60 years old and ≥ 60 years old. Logistic regression analysis was carried out on the two groups of data. According to the weight of related factors, a brain age prediction model was established and verified. Results: We obtained the specific reference value range of different brain regions of individuals in different age groups and found that there were differences in relaxation values in brain tissue between different sexes in the same age group. Moreover, the relaxation values of most brain regions in males were slightly higher than those in females. In the study of age and brain relaxation, it was found that brain relaxation values were correlated with age. The T1 values of the centrum semiovale increased with age, the PD values of the centrum semiovale increased with age, while the T2 values of the caudate nucleus and lentiform nucleus decreased with age. Seven brain age prediction models were constructed with high sensitivity and specificity, among which the combined T1, T2 and PD values showed the best prediction efficiency. In the training set, the area under the curve (AUC), specificity and sensitivity were 0.959 [95% confidence interval (CI): 0.945-0.974], 91.51% and 89.36%, respectively. In the test cohort, the above indicators were 0.916 (95% CI: 0.882-0.951), 89.24% and 80.33%, respectively. Conclusion: Our study provides specific reference ranges of T1, T2, and PD values in different brain regions from healthy adults of different ages. In addition, there are differences in brain relaxation values in some brain regions between different sexes, which help to provide new ideas for brain diseases that differ according to sex. The brain age model based on synthetic MRI is helpful to determine brain age.

Mechanism of Catechol-O-methyltransferase Regulating Orofacial Pain Induced by Tooth Movement.

OBJECTIVE: To explore the mechanism of catechol-O-methyltransferase (COMT) in tooth movement pain. METHODS: The experimental groups were randomly allocated into the healthy control, sham operation, model, model+shCOMT experimental, model+shCOMT control, and model+COMT antagonist groups. A tooth movement pain model was established. The pain stimulation and behavior test were performed. The duration of grooming behavior was determined. The appropriate experimental force and duration for application were selected. COMT shRNA vector was constructed and packaged as adenovirus. The shCOMT adenovirus was injected into the left infraorbital foramen. Seven days later, the trigeminal ganglia of all treatment groups were obtained. The COMT and IL-17 expressions were detected by western blot. The appropriate COMT antagonist concentration was selected. The pathological results of each group were detected by HE staining. The tooth movement distance was determined. The COMT gene expression was detected by FISH. The COMT and IL-17 expressions in the right trigeminal ganglion tissue of each group were detected by western blot. RESULTS: The 60 g force and 14-day duration required the lowest stimulus intensity, the duration of grooming behavior was the longest, and the effect on COMT and IL-17 was the most significant. In the model group, formation of digestive cavity was seen in the trigeminal ganglion tissue, with infiltration of inflammatory cells, upregulation of the COMT and IL-17 expressions, and significant increase in the tooth movement distance. Compared with the model group, the shCOMT experimental group and the COMT antagonist group significantly improved the trigeminal ganglion tissue injury, significantly decreased the tooth movement distance, and significantly inhibited the COMT and IL-17 expressions. CONCLUSION: The efficiency of tooth movement can be influenced by interfering the COMT-related gene expression. This proves that the COMT system can regulate the orthodontic tooth movement pain.

[A cross-sectional survey of attention and knowledge level among dental students in Jiangxi province during the epidemic period of COVID-19].

PURPOSE: To investigate the level of attention and knowledge level of dental students in Jiangxi province during the epidemic period of COVID-19, and provide data support for optimizing the training program of dental professionals in the future. METHODS: Two thousand and sixty-five valid questionnaires were collected from stomatological colleges in Jiangxi province through internet. SPSS 20.0 software was used for statistical analysis, Chi-square test and binary logistic regression were used for single factor and multi factor analysis. RESULTS: According to the survey, 74.72% of dental students expressed their concern about the epidemic situation, and 75.93% expressed that they checked the number of confirmed cases in China once or more every day. Students with higher education background, licensed doctor certificate and better family status paid more attention to the epidemic period and frequently checked the information(P<0.05). The categories of information most concerned by all respondents was data such as the number of newly diagnosed patients and the number of cured cases, followed by the diagnosis and treatment of patients with COVID-19.The average score of knowledge about epidemic situation was 5.60±1.88. Analysis of influencing factors showed that the knowledge level of women was higher than that of men（OR=1.371，95%CI:1.143-1.644）.Medical students from Hubei province had a good level of knowledge, high education, party members, and students with medical qualifications had a high level of knowledge about epidemic situation of COVID-19(P<0.05). CONCLUSIONS: The epidemic period of COVID-19 is a high concern among dental students in Jiangxi province , and the awareness rate of related knowledge is low. In order to improve the quality of dental personnel training, the medical colleges or school should strengthen the training of students' operations in the hospital, and add relevant courses of public health emergency in the training program.