The value of a neural network based on multi-scale feature fusion to ultrasound images for the differentiation in thyroid follicular neoplasms.

OBJECTIVE: The objective of this research was to create a deep learning network that utilizes multiscale images for the classification of follicular thyroid carcinoma (FTC) and follicular thyroid adenoma (FTA) through preoperative US. METHODS: This retrospective study involved the collection of ultrasound images from 279 patients at two tertiary level hospitals. To address the issue of false positives caused by small nodules, we introduced a multi-rescale fusion network (MRF-Net). Four different deep learning models, namely MobileNet V3, ResNet50, DenseNet121 and MRF-Net, were studied based on the feature information extracted from ultrasound images. The performance of each model was evaluated using various metrics, including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, F1 value, receiver operating curve (ROC), area under the curve (AUC), decision curve analysis (DCA), and confusion matrix. RESULTS: Out of the total nodules examined, 193 were identified as FTA and 86 were confirmed as FTC. Among the deep learning models evaluated, MRF-Net exhibited the highest accuracy and area under the curve (AUC) with values of 85.3% and 84.8%, respectively. Additionally, MRF-Net demonstrated superior sensitivity and specificity compared to other models. Notably, MRF-Net achieved an impressive F1 value of 83.08%. The curve of DCA revealed that MRF-Net consistently outperformed the other models, yielding higher net benefits across various decision thresholds. CONCLUSION: The utilization of MRF-Net enables more precise discrimination between benign and malignant thyroid follicular tumors utilizing preoperative US.

Markedly hypoechoic: a new definition improves the diagnostic performance of thyroid ultrasound.

OBJECTIVES: To determine the contribution of a modified definition of markedly hypoechoic in the differential diagnosis of thyroid nodules. METHODS: A total of 1031 thyroid nodules were included in this retrospective multicenter study. All of the nodules were examined with US before surgery. The US features of the nodules were evaluated, in particular, the classical markedly hypoechoic and modified markedly hypoechoic (decreased or similar echogenicity relative to the adjacent strap muscles). The sensitivity, specificity, and AUC of classical/modified markedly hypoechoic and the corresponding ACR-TIRADS, EU-TIRADS, and C-TIRADS categories were calculated and compared. The inter- and intraobserver variability in the evaluation of the main US features of the nodules was assessed. RESULTS: There were 264 malignant nodules and 767 benign nodules. Compared with classical markedly hypoechoic as a diagnostic criterion for malignancy, using modified markedly hypoechoic as the criterion resulted in a significant increase in sensitivity (28.03% vs. 63.26%) and AUC (0.598 vs. 0.741), despite a significant decrease in specificity (91.53% vs. 84.88%) (p < 0.001 for all). Compared to the AUC of the C-TIRADS with the classical markedly hypoechoic, the AUC of the C-TIRADS with the modified markedly hypoechoic increased from 0.878 to 0.888 (p = 0.01); however, the AUCs of the ACR-TIRADS and EU-TIRADS did not change significantly (p > 0.05 for both). There was substantial interobserver agreement (κ = 0.624) and perfect intraobserver agreement (κ = 0.828) for the modified markedly hypoechoic. CONCLUSION: The modified definition of markedly hypoechoic resulted in a significantly improved diagnostic efficacy in determining malignant thyroid nodules and may improve the diagnostic performance of the C-TIRADS. CLINICAL RELEVANCE STATEMENT: Our study found that, compared with the original definition, modified markedly hypoechoic significantly improved the diagnostic performance in differentiating malignant from benign thyroid nodules and the predictive efficacy of the risk stratification systems. KEY POINTS: • Compared with the classical markedly hypoechoic as a diagnostic criterion for malignancy, the modified markedly hypoechoic resulted in a significant increase in sensitivity and AUC. • The C-TIRADS with the modified markedly hypoechoic achieved higher AUC and specificity than that with the classical markedly hypoechoic (p = 0.01 and < 0.001, respectively).

A Review of the Role of Ultrasound Radiomics and Its Application and Limitations in the Investigation of Thyroid Disease.

The incidence of thyroid disease has gradually increased in recent years. Conventional ultrasound is one of the most critical thyroid imaging methods, but it still has certain limitations. The use of B-model ultrasound (BMUS) diagnosis of thyroid disease will be affected by a doctors' clinical experience. The ultrasound radiomics is based on ultrasound images to delineate the region of interest (ROI), and then extract features to quantify the disease information contained in the image, which helps to analyze the correlation between the image and the clinical pathology of the disease. By building a powerful model, it can be used to diagnose benign and malignant thyroid nodules, predict lymph node status in thyroid cancer, analyze molecular biological characteristics, and predict the survival of thyroid cancer patients. At present, the application of ultrasound radiomics in the thyroid is pervasive. These ultrasound radiomics studies have further promoted the progress of ultrasonic technology in the field of thyroid disease. Clinicians should be familiar with the workflow of ultrasound radiomics and understand the application of this technology to the thyroid. In this article, we first describe the workflow of ultrasound radiomics, followed by an overview of the application of ultrasound radiomics to the thyroid. Finally, some current limitations of the technology and areas for future improvement are discussed. This article aims to review the role of ultrasound radiomics and its application and limitations in the investigation of thyroid disease.

Deep learning with convolutional neural network in the assessment of breast cancer molecular subtypes based on US images: a multicenter retrospective study.

OBJECTIVES: To evaluate the prediction performance of deep convolutional neural network (DCNN) based on ultrasound (US) images for the assessment of breast cancer molecular subtypes. METHODS: A dataset of 4828 US images from 1275 patients with primary breast cancer were used as the training samples. DCNN models were constructed primarily to predict the four St. Gallen molecular subtypes and secondarily to identify luminal disease from non-luminal disease based on the ground truth from immunohistochemical of whole tumor surgical specimen. US images from two other institutions were retained as independent test sets to validate the system. The models' performance was analyzed using per-class accuracy, positive predictive value (PPV), and Matthews correlation coefficient (MCC). RESULTS: The model achieved good performance in identifying the four breast cancer molecular subtypes in the two test sets, with accuracy ranging from 80.07% (95% CI, 76.49-83.23%) to 97.02% (95% CI, 95.22-98.16%) and 87.94% (95% CI, 85.08-90.31%) to 98.83% (95% CI, 97.60-99.43) for the two test cohorts for each sub-category, respectively. In terms of 4-class weighted average MCC, the model achieved 0.59 for test cohort A and 0.79 for test cohort B. Specifically, the DCNN also yielded good diagnostic performance in discriminating luminal disease from non-luminal disease, with a PPV of 93.29% (95% CI, 90.63-95.23%) and 88.21% (95% CI, 85.12-90.73%) for the two test cohorts, respectively. CONCLUSION: Using pretreatment US images of the breast cancer, deep learning model enables the assessment of molecular subtypes with high diagnostic accuracy. TRIAL REGISTRATION: Clinical trial number: ChiCTR1900027676 KEY POINTS: • Deep convolutional neural network (DCNN) helps clinicians assess tumor features with accuracy. • Multicenter retrospective study shows that DCNN derived from pretreatment ultrasound imagine improves the prediction of breast cancer molecular subtypes. • Management of patients becomes more precise based on the DCNN model.

A Review of the Role of the S-Detect Computer-Aided Diagnostic Ultrasound System in the Evaluation of Benign and Malignant Breast and Thyroid Masses.

Computer-aided diagnosis (CAD) systems have attracted extensive attention owing to their performance in the field of image diagnosis and are rapidly becoming a promising auxiliary tool in medical imaging tasks. These systems can quantitatively evaluate complex medical imaging features and achieve efficient and high-diagnostic accuracy. Deep learning is a representation learning method. As a major branch of artificial intelligence technology, it can directly process original image data by simulating the structure of the human brain neural network, thus independently completing the task of image recognition. S-Detect is a novel and interactive CAD system based on a deep learning algorithm, which has been integrated into ultrasound equipment and can help radiologists identify benign and malignant nodules, reduce physician workload, and optimize the ultrasound clinical workflow. S-Detect is becoming one of the most commonly used CAD systems for ultrasound evaluation of breast and thyroid nodules. In this review, we describe the S-Detect workflow and outline its application in breast and thyroid nodule detection. Finally, we discuss the difficulties and challenges faced by S-Detect as a precision medical tool in clinical practice and its prospects.

Ultrasonographic characteristics of Killian-Jamieson diverticula.

PURPOSE: A Killian-Jamieson diverticulum (KJD) may be mistaken for a thyroid nodule on ultrasound (US). The purpose of this retrospective study was to search for specific US features that would help differentiate between KJD and thyroid nodules. METHODS: A total of 12 patients with KJD who had undergone an US examination of the neck were identified. The size, shape, boundary, echopattern, location, color flow signals on color Doppler US of KJD and the relationship between the lesion and esophageal wall were analyzed. The change of size, shape and internal echotexture were also observed when the lesion was compressed with the probe and when the patient was asked to drink water. RESULTS: All KJD were confirmed by barium esophagography. All KJD were posterior to the left thyroid lobe on US, and were associated with a semicircular hypoechoic anterior wall. The internal echotexture was heterogeneous. In eight cases, the connection to the esophageal wall was seen. When compressing with the US probe or when the patients swallowed water, the size, shape or internal echotexture of the lesion changed. CONCLUSION: The specific criteria for US diagnosis of KJD included the connection to the esophageal wall and the fact that the internal echotexture, shape and size of KJD changed in real-time when the patient swallowed water or when the lesion was compressed with the transducer.

Integrative systems and functional analyses reveal a role of dopaminergic signaling in myelin pathogenesis.

BACKGROUND: Myelin sheaths surrounding axons are critical for electrical signal transmission in the central nervous system (CNS). Diseases with myelin defects such as multiple sclerosis (MS) are devastating neurological conditions for which few effective treatments are available. Dysfunction of the dopaminergic system has been observed in multiple neurological disorders. Its role in myelin pathogenesis, however, is unclear. METHODS: This work used a combination of literature curation, bioinformatics, pharmacological and genetic manipulation, as well as confocal imaging techniques. Literature search was used to establish a complete set of genes which is associated with MS in humans. Bioinformatics analyses include pathway enrichment and crosstalk analyses with human genetic association studies as well as gene set enrichment and causal relationship analyses with transcriptome data. Pharmacological and CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9) genetic manipulation were applied to inhibit the dopaminergic signaling in zebrafish. Imaging techniques were used to visualize myelin formation in vivo. RESULTS: Systematic analysis of human genetic association studies revealed that the dopaminergic synapse signaling pathway is enriched in candidate gene sets. Transcriptome analysis confirmed that expression of multiple dopaminergic gene sets was significantly altered in patients with MS. Pathway crosstalk analysis and gene set causal relationship analysis reveal that the dopaminergic synapse signaling pathway interacts with or is associated with other critical pathways involved in MS. We also found that disruption of the dopaminergic system leads to myelin deficiency in zebrafish. CONCLUSIONS: Dopaminergic signaling may be involved in myelin pathogenesis. This study may offer a novel molecular mechanism of demyelination in the nervous system.

Long-short diffeomorphism memory network for weakly-supervised ultrasound landmark tracking.

Ultrasound is a promising medical imaging modality benefiting from low-cost and real-time acquisition. Accurate tracking of an anatomical landmark has been of high interest for various clinical workflows such as minimally invasive surgery and ultrasound-guided radiation therapy. However, tracking an anatomical landmark accurately in ultrasound video is very challenging, due to landmark deformation, visual ambiguity and partial observation. In this paper, we propose a long-short diffeomorphism memory network (LSDM), which is a multi-task framework with an auxiliary learnable deformation prior to supporting accurate landmark tracking. Specifically, we design a novel diffeomorphic representation, which contains both long and short temporal information stored in separate memory banks for delineating motion margins and reducing cumulative errors. We further propose an expectation maximization memory alignment (EMMA) algorithm to iteratively optimize both the long and short deformation memory, updating the memory queue for mitigating local anatomical ambiguity. The proposed multi-task system can be trained in a weakly-supervised manner, which only requires few landmark annotations for tracking and zero annotation for deformation learning. We conduct extensive experiments on both public and private ultrasound landmark tracking datasets. Experimental results show that LSDM can achieve better or competitive landmark tracking performance with a strong generalization capability across different scanner types and different ultrasound modalities, compared with other state-of-the-art methods.

Integrative bioinformatics and experimental validation of hub genetic markers in acne vulgaris: Toward personalized diagnostic and therapeutic strategies.

BACKGROUND: Acne vulgaris is a widespread chronic inflammatory dermatological condition. The precise molecular and genetic mechanisms of its pathogenesis remain incompletely understood. This research synthesizes existing databases, targeting a comprehensive exploration of core genetic markers. METHODS: Gene expression datasets (GSE6475, GSE108110, and GSE53795) were retrieved from the GEO. Differentially expressed genes (DEGs) were identified using the limma package. Enrichment analyses were conducted using GSVA for pathway assessment and clusterProfiler for GO and KEGG analyses. PPI networks and immune cell infiltration were analyzed using the STRING database and ssGSEA, respectively. We investigated the correlation between hub gene biomarkers and immune cell infiltration using Spearman's rank analysis. ROC curve analysis validated the hub genes' diagnostic accuracy. miRNet, TarBase v8.0, and ChEA3 identified miRNA/transcription factor-gene interactions, while DrugBank delineated drug-gene interactions. Experiments utilized HaCaT cells stimulated with Propionibacterium acnes, treated with retinoic acid and methotrexate, and evaluated using RT-qPCR, ELISA, western blot, lentiviral transduction, CCK-8, wound-healing, and transwell assays. RESULTS: There were 104 genes with consistent differences across the three datasets of paired acne and normal skin. Functional analyses emphasized the significant enrichment of these DEGs in immune-related pathways. PPI network analysis pinpointed hub genes PTPRC, CXCL8, ITGB2, and MMP9 as central players in acne pathogenesis. Elevated levels of specific immune cell infiltration in acne lesions corroborated the inflammatory nature of the disease. ROC curve analysis identified the acne diagnostic potential of four hub genes. Key miRNAs, particularly hsa-mir-124-3p, and central transcription factors like TFEC were noted as significant regulators. In vitro validation using HaCaT cells confirmed the upregulation of hub genes following Propionibacterium acnes exposure, while CXCL8 knockdown reduced pro-inflammatory cytokines, cell proliferation, and migration. DrugBank insights led to the exploration of retinoic acid and methotrexate, both of which mitigated gene expression upsurge and inflammatory mediator secretion. CONCLUSION: This comprehensive study elucidated pivotal genes associated with acne pathogenesis, notably PTPRC, CXCL8, ITGB2, and MMP9. The findings underscore potential biomarkers, therapeutic targets, and the therapeutic potential of agents like retinoic acid and methotrexate. The congruence between bioinformatics and experimental validations suggests promising avenues for personalized acne treatments.

Global research trends of infantile hemangioma: A bibliometric and visualization analysis from 2000 to 2022.

Background: Infantile hemangioma (IH) has received global attention, resulting in a significant volume of literature. However, there is a lack of bibliometric analyses specifically focusing on IH publications. This study aims to fill this gap by conducting a comprehensive analysis of IH publications, investigating their characteristics, contribution distribution, and developmental trends. By enhancing our understanding of IH and identifying potential research topics and collaborators, this study will contribute to the advancement of the field. Methods: A total of 4333 articles and reviews on IH were collected from the Web of Science (WoS) database, spanning the years 2000-2022. The study encompassed a comprehensive analysis of IH publications, evaluating their quantity and quality. Additionally, we profiled publishing groups based on country, institution, author publication records, and collaboration networks. Lastly, we identified and summarized the prominent research topics. Results: Annual publications on IH have increased over the past 20 years. The United States has the highest number of publications and the highest total number of citations. Pediatric Dermatology was the most influential journal in the IH field. The citation analysis indicated that the articles published by Léauté-Labrèze in 2008 had the highest number of citations. The articles published by North PE in 2000 and Boye E in 2001 laid a certain research foundation for this field. Concerning institutions, most of the cooperative relationships were established in the same country/region. The United States has the largest number of scientific research institutions and IH researchers, leading most of the cross-country collaboration. The University of California, San Francisco, Medical College of Wisconsin, Harvard University, and Shanghai Jiaotong University were the research centers that published the most IH-related research. Frieden IJ, Mulliken JB, and Drolet BA were the top three most influential authors. Frieden IJ, Garzon MC, and Mulliken JB were the top three authors with the most cited frequency. In addition, keywords and keyword co-occurrence networks prompted that the pathological mechanism of IH, clinical analysis, and other vascular anomalies are research hotspots. Analysis of trending topics suggests that research on IH has evolved from treatment-focused studies towards investigations of other vascular diseases and a series of clinical case studies. Currently, clinical case studies receive the most attention in the field. Conclusions: This comprehensive bibliometric study provides a thorough analysis of post-2000 publications in the field of IH, offering insights into current research trends for the first time. The findings suggest that future investigations will continue to prioritize understanding IH mechanisms, treatment approaches, and treatment evaluation. Furthermore, the exploration of other vascular diseases and the inclusion of clinical case studies are expected to contribute to advancements in IH clinical practice. By identifying potential collaborators, partner institutions, and new research avenues, this study offers valuable guidance for future in-depth research on IH.

Construction of a vascularized fascia-prosthesis compound model with axial pedicle for ear reconstruction surgery.

Background: To design a vascular pedicled fascia-prosthesis compound model that can be used for ear reconstruction surgery. Methods: A vascularized tissue engineering chamber model was constructed in New Zealand rabbits, and fresh tissues were obtained after 4 weeks. The histomorphology and vascularization of the newly born tissue compound were analyzed and evaluated by tissue staining and Micro-CT scanning. Results: The neoplastic fibrous tissue formed in the vascularized tissue engineering chamber with the introduction of abdominal superficial vessels, similar to normal fascia, was superior to the control group in terms of vascularization, vascular density, total vascular volume, and total vascular volume/total tissue volume. Conclusion: In vivo, introducing abdominal superficial vessels in the tissue engineering chamber prepped for ear prosthesis may form a well-vascularized pedicled fascia-prosthesis compound that can be used for ear reconstruction.

Causal association between serum 25-Hydroxyvitamin D levels and cutaneous melanoma: a two-sample Mendelian randomization study.

Background: Despite numerous observational studies on the association between serum 25-Hydroxyvitamin D levels and cutaneous melanoma, causal inferences remain ambiguous due to confounding and reverse causality. This study aimed to elucidate the causal relationship between serum 25-Hydroxyvitamin D levels and melanoma incidence using Mendelian randomization (MR). Methods: A two-sample MR was conducted using genetic variants associated with serum 25-Hydroxyvitamin D levels as instrumental variables. Summary statistics for these variants were derived from genome-wide association studies, and those for melanoma risk were obtained from a comprehensive melanoma case-control study. Robustness of the results was assessed through sensitivity analyses, including the "leave-one-out" approach and tests for potential pleiotropy. Results: The MR analysis provided substantial evidence of a positive causal relationship between serum 25-Hydroxyvitamin D levels and the incidence of cutaneous melanoma, suggesting that each unit increase in serum 25-Hydroxyvitamin D levels corresponds with an increased risk of melanoma. Tests for pleiotropy showed minimal effects, and the sensitivity analysis confirmed no disproportionate influence by any individual single nucleotide polymorphism (SNP). Conclusion: The findings indicated a potentially causal positive association between serum 25-Hydroxyvitamin D levels and melanoma risk, challenging traditional beliefs about vitamin D's role in melanoma. This emphasizes the need for a balanced and personalized approach to vitamin D supplementation and sun exposure, particularly in high-risk populations. These results should be interpreted with caution due to potential unrecognized pleiotropy and confounding factors. Future research should focus on validating these findings in diverse populations and exploring underlying biological mechanisms.

A Preliminary Study of Ultrasound-Guided Microwave Ablation for Nonpuerperal Mastitis Treatment.

Introduction: This study investigated the feasibility of ultrasound (US)-guided microwave ablation (MWA) as a treatment for nonpuerperal mastitis (NPM). Methods: Fifty-three patients with NPM diagnosed by biopsy and treated with US-guided MWA at the Affiliated Hospital of Nantong University between September 2020 and February 2022 were classified according to whether they underwent MWA alone (n = 29) or MWA with incision and drainage (n = 24). Patients were followed up by interviews, physical and US examinations, and evaluation of breast skin at 1 week and 1, 2, and 3 months after treatment. Data from these patients were prospectively collected and retrospectively analyzed. Results: The overall mean patient age was 34.42 ± 9.20 years. The groups differed significantly by age, involved quadrants, and the initial maximum diameter of lesions. In the MWA group, the cure rate was 34.48%, and the apparent efficiency rate was 65.52%. In the MWA with incision and drainage, the apparent efficiency rate was 91.66%, and the effective rate was 4.17%. The excellent rate for breast aesthetics in the MWA group was 79.31%, and the good rate was 20.69%. The excellent rate in the MWA with incision and drainage group was 45.83%, the good rate was 41.67%, and the qualified rate was 12.5%. The mean maximum diameter of lesions in the two groups decreased significantly. Conclusion: For NPM with small lesions in a single quadrant, MWA therapy is a direct and effective method. For larger lesions involving two or more quadrants, the combined treatment of MWA with incision and drainage showed significant improvement in a short period. MWA treatment of NPM has importance for further research and clinical applications.

Chronic kidney disease-induced muscle atrophy: Molecular mechanisms and promising therapies.

Chronic kidney disease (CKD) is a high-risk chronic catabolic disease due to its high morbidity and mortality. CKD is accompanied by many complications, leading to a poor quality of life, and serious complications may even threaten the life of CKD patients. Muscle atrophy is a common complication of CKD. Muscle atrophy and sarcopenia in CKD patients have complex pathways that are related to multiple mechanisms and related factors. This review not only discusses the mechanisms by which inflammation, oxidative stress, mitochondrial dysfunction promote CKD-induced muscle atrophy but also explores other CKD-related complications, such as metabolic acidosis, vitamin D deficiency, anorexia, and excess angiotensin II, as well as other related factors that play a role in CKD muscle atrophy, such as insulin resistance, hormones, hemodialysis, uremic toxins, intestinal flora imbalance, and miRNA. We highlight potential treatments and drugs that can effectively treat CKD-induced muscle atrophy in terms of complication treatment, nutritional supplementation, physical exercise, and drug intervention, thereby helping to improve the prognosis and quality of life of CKD patients.

Engineering tumor-specific catalytic nanosystem for NIR-II photothermal-augmented and synergistic starvation/chemodynamic nanotherapy.

BACKGROUND: As an emerging therapeutic modality, chemodynamic therapy (CDT), converting hydrogen peroxide (H2O2) into highly toxic reactive oxygen species (ROS), has been developed for tumor-specific therapy. However, the deficiency of endogenous H2O2 and high concentration of glutathione (GSH) in the tumor microenvironment (TME) weaken the CDT-based tumor-therapeutic efficacy. Herein, a photothermal-enhanced tumor-specific cascade catalytic nanosystem has been constructed on the basis of glucose oxidase (GOD)-functionalized molybdenum (Mo)-based polyoxometalate (POM) nanoclusters, termed as GOD@POMs. METHODS: GOD@POMs were synthesized by a facile one-pot procedure and covalently conjugation. Then, its structure was characterized by scanning electron microscope (SEM), transmission electron microscope (TEM), Fourier transform infrared (FTIR) spectroscopy and X-ray photoelectron spectroscopy (XPS). In addition, ultraviolet-visible-near-infrared (UV-vis-NIR) absorption spectrum and infrared thermal camera were applied to evaluate the catalytic and photothermal performance, respectively. Moreover, to confirm the therapeutic effects in vitro, cell counting kit-8 (CCK-8) assay, live/dead staining and ROS staining were performed. Furthermore, the biosafety of GOD@POMs was investigated via blood routine, blood biochemistry and hematoxylin and eosin (H&E) staining in Kunming mice. Besides, the C6 glioma tumor-bearing mice were constructed to evaluate its anti-tumor effects in vivo and its photoacoustic (PA) imaging capability. Notably, RNA sequencing, H&E, TdT-mediated dUTP nick end labeling (TUNEL) and Ki-67 staining were also conducted to disclose its underlying anti-tumor mechanism. RESULTS: In this multifunctional nanosystem, GOD can effectively catalyze the oxidation of intratumoral glucose into gluconic acid and H2O2, achieving the cancer starvation therapy. Meanwhile, the generated gluconic acid decreases the pH in TME resulting in POM aggregation, which enables PA imaging-guided tumor-specific photothermal therapy (PTT), especially in the second near-infrared (NIR-II) biological window. Importantly, the Mo (VI) sites on POM can be reduced to Mo (V) active sites in accompany with GSH depletion, and then the post-produced Mo (V) transforms in situ overproduced H2O2 into singlet oxygen (1O2) via Russell mechanism, achieving self-enhanced CDT. Moreover, the PTT-triggered local tumor temperature elevation augments the synergistic nanocatalytic-therapeutic efficacy. CONCLUSIONS: Consequently, the integration of GOD-induced starvation therapy, H2O2 self-supply/GSH-depletion enhanced Mo-based CDT, and POM aggregation-mediated PTT endow the GOD@POMs with remarkable synergistic anticancer outcomes with neglectable adverse effects.

Ultrasound Radiomics Nomogram to Diagnose Sub-Centimeter Thyroid Nodules Based on ACR TI-RADS.

The aim of the present study was to develop a radiomics nomogram to assess whether thyroid nodules (TNs) < 1 cm are benign or malignant. From March 2021 to March 2022, 156 patients were admitted to the Affiliated Hospital of Nantong University, and from September 2017 to March 2022, 116 patients were retrospectively collected from the Jiangsu Provincial Hospital of Integrated Traditional Chinese and Western Medicine. These patients were divided into a training group and an external test group. A radiomics nomogram was established using multivariate logistics regression analysis using the radiomics score and clinical data, including the ultrasound feature scoring terms from the thyroid imaging reporting and data system (TI-RADS). The radiomics nomogram incorporated the correlated predictors, and compared with the clinical model (training set AUC: 0.795; test set AUC: 0.783) and radiomics model (training set AUC: 0.774; test set AUC: 0.740), had better discrimination performance and correction effects in both the training set (AUC: 0.866) and the test set (AUC: 0.866). Both the decision curve analysis and clinical impact curve showed that the nomogram had a high clinical application value. The nomogram constructed based on TI-RADS and radiomics features had good results in predicting and distinguishing benign and malignant TNs < 1 cm.

Identification of genes associated with sudden cardiac death: a network- and pathway-based approach.

BACKGROUND: Sudden cardiac death (SCD) accounts for a large proportion of the total deaths across different age groups. Although numerous candidate genes related to SCD have been identified by genetic association studies and genome wide association studies (GWAS), the molecular mechanisms underlying SCD are still unclear, and the biological functions and interactions of these genes remain obscure. To clarify this issue, we performed a comprehensive and systematic analysis of SCD-related genes by a network and pathway-based approach. METHODS: By screening the publications deposited in the PubMed and Gene-Cloud Biotechnology Information (GCBI) databases, we collected the genes genetically associated with SCD, which were referred to as the SCD-related gene set (SCDgset). To analyze the biological processes and biochemical pathways of the SCD-related genes, functional analysis was performed. To explore interlinks and interactions of the enriched pathways, pathway crosstalk analysis was implemented. To construct SCD-specific molecular networks, Markov cluster algorithm and Steiner minimal tree algorithm were employed. RESULTS: We collected 257 genes that were reported to be associated with SCD and summarized them in the SCDgset. Most of the biological processes and biochemical pathways were related to heart diseases, while some of the biological functions may be noncardiac causes of SCD. The enriched pathways could be roughly grouped into two modules. One module was related to calcium signaling pathway and the other was related to MAPK pathway. Moreover, two different SCD-specific molecular networks were inferred, and 23 novel genes potentially associated with SCD were also identified. CONCLUSIONS: In summary, by means of a network and pathway-based methodology, we explored the pathogenetic mechanism underlying SCD. Our results provide valuable information in understanding the pathogenesis of SCD and include novel biomarkers for diagnosing potential patients with heart diseases; these may help in reducing the corresponding risks and even aid in preventing SCD.

Proteomic Analysis of Silk Fibroin Reveals Diverse Biological Function of Different Degumming Processing From Different Origin.

Silk, as a kind of natural fibrin, has been prepared into various biomaterials due to its excellent biocompatibility and mechanicalness. However, there are some controversies on the biocompatibility of silk fibroin (SF), especially when it coexists with sericin. In this study, two kinds of silk from Jiangsu and Zhejiang were degummed with two concentrations of Na2CO3 solution, respectively, to obtain four kinds of silk fibroin. The effects of different degumming treatments on silk fibroin properties were analyzed by means of color reaction, apparent viscosity measurement, and transmission electron microscope and isobaric tags for relative and absolute quantification analyses, and the effects of different silk fibroin membranes on the growth of Schwann cells were evaluated. The results showed that the natural silk from Zhejiang treated with 0.05% Na2CO3 solution had a fuller structure, higher apparent viscosity, and better protein composition. While SF obtained by degumming with 0.5% Na2CO3 solution was more beneficial to cell adhesion and proliferation due to the thorough removal of sericin. This study may provide important theoretical and experimental bases for the selection of biomaterials for fabricating artificial nerve grafts.

Integrated analysis of ceRNA network and tumor-infiltrating immune cells in esophageal cancer.

BACKGROUND: Esophageal cancer (ESCA) is one of the most commonly diagnosed cancers in the world. Tumor immune microenvironment is closely related to tumor prognosis. The present study aimed at analyzing the competing endogenous RNA (ceRNA) network and tumor-infiltrating immune cells in ESCA. METHODS: The expression profiles of mRNAs, lncRNAs, and miRNAs were downloaded from the Cancer Genome Atlas database. A ceRNA network was established based on the differentially expressed RNAs by Cytoscape. CIBERSORT was applied to estimate the proportion of immune cells in ESCA. Prognosis-associated genes and immune cells were applied to establish prognostic models basing on Lasso and multivariate Cox analyses. The survival curves were constructed with Kaplan-Meier method. The predictive efficacy of the prognostic models was evaluated by the receiver operating characteristic (ROC) curves. RESULTS: The differentially expressed mRNAs, lncRNAs, and miRNAs were identified. We constructed the ceRNA network including 23 lncRNAs, 19 miRNAs, and 147 mRNAs. Five key molecules (HMGB3, HOXC8, HSPA1B, KLHL15, and RUNX3) were identified from the ceRNA network and five significant immune cells (plasma cells, T cells follicular helper, monocytes, dendritic cells activated, and neutrophils) were selected via CIBERSORT. The ROC curves based on key genes and significant immune cells all showed good sensitivity (AUC of 3-year survival: 0.739, AUC of 5-year survival: 0.899, AUC of 3-year survival: 0.824, AUC of 5-year survival: 0.876). There was certain correlation between five immune cells and five key molecules. CONCLUSION: The present study provides an effective bioinformatics basis for exploring the potential biomarkers of ESCA and predicting its prognosis.

Adipose-derived stem cells combined with platelet-rich plasma enhance wound healing in a rat model of full-thickness skin defects.

BACKGROUND: Wound healing is impaired in patients with diabetes due to the multifactorial etiology of the disease, which limits the therapeutic efficacy of various approaches. This study hypothesizes that the combination of adipose-derived stem cells (ADSCs) and platelet-rich plasma (PRP) might achieve optimally efficient diabetic wound healing. METHODS: ADSCs were isolated from the adipose tissues of Sprague-Dawley (SD) rats. PRP was prepared by using a two-step centrifugation technique. A diabetic wound model was established on the backs of SD rats to evaluate the effect of ADSCs incorporated into PRP. Hematoxylin and eosin staining, immunofluorescence, and immunohistochemistry were performed to observe the changes in neovascularization. ELISA and Western blot were utilized to detect the angiogenesis-related protein expression levels. The proliferation of endothelial cells was assessed by the MTS assay. RESULTS: ADSCs incorporated into PRP induced a higher wound closure rate than ADSCs, PRP, and negative control. The expression levels of VEGF, p-STAT3, and SDF-1 in the ADSC+PRP group were higher than those in the other groups. Moreover, the proliferation of endothelial cells was strongly stimulated by treatment with the combination of ADSC-conditioned medium (ADSC-CM) and PRP. CONCLUSIONS: PRP enhanced diabetic wound healing induced by ADSCs, and its promoting effect involved neovascularization.