Low-temperature sintering of silver nanoparticles on paper by surface modification.

Ultralow-temperature sintering plays a vital role in the development of flexible printed electronics, which improves flexibility and reduces energy consumption. This study investigates the ultralow-temperature sintering of large-sized silver nanoparticles (Ag NPs) by laser modification of the substrate surface. Ag NPs in conductive ink were sintered at only 60 °C. Designing the appropriate size of modified regions, the sintered Ag layer exhibits a sheet resistance of only 0.274 Ω and withstands 10 000 folding cycles. Energy-dispersive x-ray spectroscopy showed that TiO2 formed by laser ablation promotes the sintering of Ag NPs and joining with the substrate. A paper-based flexible integrated circuit board was also prepared.

Establishment and evaluation of a nomogram for in-hospital new-onset atrial fibrillation after percutaneous coronary intervention for acute myocardial infarction.

Background: New-onset atrial fibrillation (NOAF) is prognostic in acute myocardial infarction (AMI). The timely identification of high-risk patients is essential for clinicians to improve patient prognosis. Methods: A total of 333 AMI patients were collected who underwent percutaneous coronary intervention (PCI) at Zhejiang Provincial People's Hospital between October 2019 and October 2020. Least absolute shrinkage and selection operator regression (Lasso) and multivariate logistic regression analysis were applied to pick out independent risk factors. Secondly, the variables identified were utilized to establish a predicted model and then internally validated by 10-fold cross-validation. The discrimination, calibration, and clinical usefulness of the prediction model were evaluated using the receiver operating characteristic (ROC) curve, calibration curve, Hosmer-Lemeshow test decision curve analyses, and clinical impact curve. Result: Overall, 47 patients (14.1%) developed NOAF. Four variables, including left atrial dimension, body mass index (BMI), CHA2DS2-VASc score, and prognostic nutritional index, were selected to construct a nomogram. Its area under the curve is 0.829, and internal validation by 10-fold cross-folding indicated a mean area under the curve is 0.818. The model demonstrated good calibration according to the Hosmer-Lemeshow test (P = 0.199) and the calibration curve. It showed satisfactory clinical practicability in the decision curve analyses and clinical impact curve. Conclusion: This study established a simple and efficient nomogram prediction model to assess the risk of NOAF in patients with AMI who underwent PCI. This model could assist clinicians in promptly identifying high-risk patients and making better clinical decisions based on risk stratification.

Characterization of SARS-CoV-2-specific humoral immunity and associated factors in the healthy population post-vaccination.

OBJECTIVES: To investigate factors that may influence humoral immunity post-vaccination with a COVID-19-inactivated vaccine (SC2IV). METHODS: A total of 1596 healthy individuals from the Seventh Affiliated Hospital, Sun Yat-sen University (1217) and Shenzhen Baotian Hospital (379) were enrolled in this study among which 694 and 218 participants were vaccinated with two-dose SC2IV, respectively. Physical examination indices were recorded. The levels of neutralizing antibody (NA), Spike IgG, receptor-binding domain (RBD) IgG, RBD IgG + IgM + IgA, and nucleocapsid IgG of SARS-CoV-2 were measured by a non-virus ELISA kit. Multiple statistical analyses were carried out to identify factors that influence humoral immunity post-vaccination. RESULTS: The two-dosage vaccination could induce NA in more than 90 % of recipients. The NA has the strongest correlation with anti-RBD IgG. Age is the most important independent index that affects the NA level, while basophil count, creatine kinase-MB, mean corpuscular hemoglobin, the ratio of albumin to urine creatinine, and thyroglobulin antibody have relatively minor contributions. Indices that affect the NA level were different between males and females. Antibodies targeting other epitopes of SARS-CoV-2 were detected in recipients without anti-RBD. CONCLUSIONS: The factors identified in association with the NA level post-vaccination may help to evaluate the protective effect, risk of re-infection, the severity of symptoms, and prognosis for vaccine recipients in clinical.

GDU-952, a novel AhR agonist ameliorates skin barrier abnormalities and immune dysfunction in DNFB-induced atopic dermatitis in mice.

The aryl hydrocarbon receptor (AhR) is widely expressed in the skin. It controls immune-mediated skin responses to various external environmental signals, promote terminal differentiation of epidermal keratinocytes and participates the maintenance of the skin barrier function. As a therapeutic target, AhR activation modulates many diseases progression driven by immune/inflammatory processes such as atopic dermatitis (AD) and psoriasis. In this study, we revealed that GDU-952 is a novel AhR agonist, which is able to decreases IgE serum levels, to inhibit pro-inflammatory cytokines such as IL-6 and TNF-α and to induce immunoregulatory effects through restoring Th1/Th2 immune balance and promoting CD4+FOXP3+regulatory T (Treg) populations in AD skin lesions. Furthermore, GDU-952 can strengthen the skin barrier function through upregulating epidermal differentiation-related and tight junction proteins. This may alleviate AD symptoms, such as dermatitis scores, epidermal hyperplasia and mast cell infiltration. These results offer a rationale for further preclinical/clinical studies to evaluate the possible use of GDU-952 in the management of AD.

Efficacy and safety of modified fasting therapy for weight loss in 2054 hospitalized patients.

OBJECTIVE: The aim of this study was to evaluate the efficacy and safety of modified fasting therapy, and a retrospective study was conducted to analyze changes in clinical indicators of hospitalized fasting patients. METHODS: A total of 2054 hospitalized fasting patients were enrolled in this observational study. All participants underwent 7 days of modified fasting therapy. The clinical efficacy biomarkers, safety indicators, and body composition were measured before and after fasting. RESULTS: The modified fasting therapy reduced body weight, BMI, abdominal circumference, systolic blood pressure, and diastolic blood pressure significantly. Blood glucose and indicators of body composition were improved to various extents (all p < 0.05). There was a small increase in liver function, kidney function, uric acid, electrolytes, blood count, coagulation, and uric biomarkers. Subgroup analysis results showed that cardiovascular diseases benefited from modified fasting therapy. CONCLUSIONS: At present this study is the largest retrospective population-based study about modified fasting therapy. The results from 2054 patients showed that the modified fasting therapy lasting 7 days was efficient and safe. It led to improvements in physical health and body weight-associated indicators, as well as body composition and relevant cardiovascular risk factors.

Development of a joint diagnostic model of thyroid papillary carcinoma with artificial neural network and random forest.

Objective: Papillary thyroid carcinoma (PTC) accounts for 80% of thyroid malignancy, and the occurrence of PTC is increasing rapidly. The present study was conducted with the purpose of identifying novel and important gene panels and developing an early diagnostic model for PTC by combining artificial neural network (ANN) and random forest (RF). Methods and results: Samples were searched from the Gene Expression Omnibus (GEO) database, and gene expression datasets (GSE27155, GSE60542, and GSE33630) were collected and processed. GSE27155 and GSE60542 were merged into the training set, and GSE33630 was defined as the validation set. Differentially expressed genes (DEGs) in the training set were obtained by "limma" of R software. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis as well as immune cell infiltration analysis were conducted based on DEGs. Important genes were identified from the DEGs by random forest. Finally, an artificial neural network was used to develop a diagnostic model. Also, the diagnostic model was validated by the validation set, and the area under the receiver operating characteristic curve (AUC) value was satisfactory. Conclusion: A diagnostic model was established by a joint of random forest and artificial neural network based on a novel gene panel. The AUC showed that the diagnostic model had significantly excellent performance.

The Prognostic Implication of the BRAF V600E Mutation in Papillary Thyroid Cancer in a Chinese Population.

Background: The BRAF V600E mutation is an important genetic event in papillary thyroid cancer (PTC). This study aimed to provide additional information regarding the association of the BRAF V600E mutation with PTC prognosis. Methods: A retrospective single-center study based on a Chinese population was performed to analyze the association of the BRAF V600E mutation with several clinicopathological features. Kaplan-Meier survival curves and Cox proportional hazards regression analysis were applied to implement the survival analysis. Results: The BRAF V600E mutation was present in 1102 (87.7%) of the 1257 patients and was significantly associated with older age, conventional subtype, multifocality, advanced TNM stage, and a reduced prevalence of Hashimoto's thyroiditis. The Kaplan-Meier survival curves demonstrated that the difference between the BRAF V600E-positive and BRAF V600E-negative groups was significant with a log-rank P-value of 0.048. The Cox proportional hazards regression analysis adjusted HR was 3.731 (95% CI, 1.457 to 9.554). We further demonstrated that larger tumor size (>1 cm), extrathyroidal extension (ETE), and lateral lymph node metastasis (LNM) were associated with a higher probability of PTC recurrence in patients harboring the BRAF V600E mutation. Conclusions: The BRAF V600E mutation remains an independent risk factor for PTC recurrence and may be useful for clinical decisions when it combines with some pathological factors.

Prediction of lung metastases in thyroid cancer using machine learning based on SEER database.

PURPOSE: Lung metastasis (LM) is one of the most frequent distant metastases of thyroid cancer (TC). This study aimed to develop a machine learning algorithm model to predict lung metastasis of thyroid cancer for providing relative information in clinical decision-making. METHODS: Data comprising of demographic and clinicopathological characteristics of patients with thyroid cancer were extracted from the National Institutes of Health (NIH)'s Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015, which is employed to develop six machine learning algorithm models support vector machine (SVM), logistic regression (LR), eXtreme gradient boosting (XGBoost), decision tree (DT), random forest (RF), and k-nearest neighbor (KNN). Compared and evaluated models by the following indicators: accuracy, precision, recall rate, F1-score, the area under the ROC curve (AUC) value and Brier score, and interpreted the association between clinicopathological characteristics and target variables based on the best model. RESULTS: Nine thousand nine hundred and fifty patients were selected, which including 212 patients (2.1%) with lung metastasis, and 9738 patients without lung metastasis (97.9%). Multivariate logistic regression showed that age, T stage, N stage, and histological type were independent factors in TC with LM. Evaluation indicators of the best model- RF were as following: accuracy (0.99), recall rate (0.88), precision (0.61), F1-score (0.72), AUC value (0.99), and the Brier score (0.016). CONCLUSION: RF learning model performed better and can be applied to forecast lung metastasis of thyroid cancer, and offer valuable and significant reference for clinicians' decision-making in advance.

The Strategy of Conditionally Replicating Adenovirus-Mediated PreS2 Mini-Antibody Expression Has Dual Effects of Inhibiting HBV Infection and Preventing Hepatocellular Carcinoma.

AIM: To investigate the inhibitory effect of hepatitis B virus (HBV) preS2 mini-antibody (mPreS2) against HBV infection, HBV-associated liver injury and HBV-associated hepatic carcinogenesis. METHODS: A recombinant adenovirus vector with the human survivin promoter and mPreS2 gene, Ad5SVP-mPreS2, was constructed. Fluorescence microscopy examination and TCID 50 analysis were utilized to determine the specific proliferation of recombinant adenovirus in liver cancer cells. Western blot analysis was used to determine the mPreS2 expression levels. Enzyme-linked immunosorbent assay (ELISA) was used to examine HBsAg levels to evaluate the inhibitory effect of mPreS2 against HBV infection. The protective effects on hepatic function and preventive effects against hepatic carcinogenesis of Ad5SVP-mPreS2 were studied in diethylnitrosamine (DEN)-treated HBV transgenic Imprinting Control Region mice. RESULTS: The recombinant adenovirus regulated by the human survivin promoter proliferated exclusively in liver cancer cells rather than normal liver cells. The expression levels of mPreS2 were increased in liver cancer cells compared with normal liver cells, and mPreS2 could be used to recognize liver cells from HBV transgenic mice. ELISA showed that HBsAg levels were decreased in the group treated with Ad5SVP-mPreS2. Ad5SVP-mPreS2 had a protective effect on hepatic function in a DEN-induced liver injury model because of lower serum levels of alanine transaminase and aspartate transaminase. Additionally, HBV transgenic mice treated with Ad5SVP-mPreS2 had fewer and smaller cancerous nodes after induction with DEN than untreated mice. CONCLUSION: Conditionally replicating adenovirus-mediated mPreS2 expression inhibited HBV infection and had an inhibitory effect on liver injury and hepatocellular carcinogenesis in HBV transgenic mice.

FAM172A promotes follicular thyroid carcinogenesis and may be a marker of FTC.

Our aims were to uncover the role of FAM172A (Family with sequence similarity 172 member A) in the pathogenesis of follicular thyroid carcinoma (FTC) and to evaluate its value in the differential diagnosis between malignant and benign thyroid follicular lesions. FAM172A expression was evaluated by q-PCR, immunoblotting and immunohistochemistry (IHC). The ability of proliferation, migration and invasion of cells were assessed by Cell Counting Kit-8 assay (CCK8), clone-formation and Transwell assays. Nude mouse tumorigenicity assays were used to investigate the role of FAM172A in the pathogenesis of FTC in vivo. The value of FAM172A in the differential diagnosis for FTC was assessed using 120 formalin-fixed paraffin-embedded (FFPE) tissues after the operation and 81 fine-needle aspiration biopsy (FNAB) samples before the operation. FAM172A was highly expressed in FTC tissues and FTC cell lines. Downregulation of FAM172A inhibited the proliferation, invasion and migration of FTC cells through Erk1/2 and JNK pathways. Subcutaneous tumorigenesis in nude mice showed that knockdown of FAM172A inhibited tumor growth and progression in vivo. The FAM172A IHC scores of 3.5 had 92% sensitivity and 63% specificity to separate FTC from benign/borderline thyroid follicular lesions, and 92% sensitivity and 80% specificity to discriminate FTC from benign thyroid follicular lesions in postoperative FFPE samples. The corresponding values were 75 and 78%, and 75 and 89% in preoperative FNA samples, respectively. FAM172A plays an important role in the pathogenesis of FTC through Erk1/2 and JNK pathways. FAM172A may be a potential marker for the preoperative diagnosis of FTC based on the IHC results of thyroid FNAB samples.

Wearable Circuits Sintered at Room Temperature Directly on the Skin Surface for Health Monitoring.

A soft body area sensor network presents a promising direction in wearable devices to integrate on-body sensors for physiological signal monitoring and flexible printed circuit boards (FPCBs) for signal conditioning/readout and wireless transmission. However, its realization currently relies on various sophisticated fabrication approaches such as lithography or direct printing on a carrier substrate before attaching to the body. Here, we report a universal fabrication scheme to enable printing and room-temperature sintering of the metal nanoparticle on paper/fabric for FPCBs and directly on the human skin for on-body sensors with a novel sintering aid layer. Consisting of polyvinyl alcohol (PVA) paste and nanoadditives in the water, the sintering aid layer reduces the sintering temperature. Together with the significantly decreased surface roughness, it allows for the integration of a submicron-thick conductive pattern with enhanced electromechanical performance. Various on-body sensors integrated with an FPCB to detect health conditions illustrate a system-level example.