Corrigendum: Genomic evolution of BA.5.2 and BF.7.14 derived lineages causing SARS-CoV-2 outbreak at the end of 2022 in China.

[This corrects the article DOI: 10.3389/fpubh.2023.1273745.].

Interventions to Improve Endoscopic Screening Adherence of Cancer in High-Risk Populations: A Scoping Review.

Background: Colorectal, and gastric cancers have the second, and fourth mortality rates worldwide, respectively. Endoscopic screening is a crucial diagnostic tool for colorectal, and gastric cancers. Effective interventions can improve adherence to endoscopic screening in high-risk populations, which is important for cancer prevention and mortality reduction. This study aimed to identify interventions that could improve adherence to endoscopic screening for cancer in high-risk populations. Methods: Combination keywords including colorectal cancer, gastric cancer, screening adherence, and interventions were used to search for articles in PubMed, Web of Science, Cochrane Library, and MEDLINE Complete. The review methodology was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-SCR). Results: A total of 12 articles were included in this review: 9 randomized controlled trials(RCT) and 3 quasi-experimental studies(QEDs). Among the extracted studies, 11 were about colorectal cancer, and 1 was about gastric cancer. Most studies used lecture-based or Information Technology-based health education interventions. Narrative interventions have proven to be novel and effective approaches for promoting adherence to endoscopic screening. Health education interventions included cancer epidemiology, cancer risk factors, warning symptoms, and screening methods. Conclusion: All interventions involved were effective in increasing individual knowledge of cancer-related endoscopic screening, willingness to undergo screening, and screening behaviors. These findings provide a reference for designing endoscopy-related cancer screening interventions.

Factors affecting the compliance of hepatocellular carcinoma screening among high-risk populations: A systematic review and meta-analysis.

BACKGROUND: Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide and the third leading cause of cancer mortality. HCC has high morbidity, high mortality, and low survival rates. Screening is one of the most significant methods of lowering incidence and death while also increasing survival. OBJECTIVES: The aim of this study was to identify the facilitators and barriers to participation in HCC screening among high-risk populations. METHODS: A comprehensive and systematic search was undertaken in PubMed, Web of Science, MEDLINE, EMBACE, EBSCOhost and the Cochrane Library. A combination of synonyms of the keywords including HCC, screening, factors and adherence were used for searching. Studies addressing the facilitators and barriers to HCC screening compliance in at-risk individuals were included. Data were synthesized using Review Manager version 5.4. A random/fixed effects model meta-analysis was performed to estimate the pooled data and expressed with odds ratio (OR) and 95% confidence interval (CI). RESULTS: A total of seven articles met the inclusion criteria. Qualitative (n = 1) and quantitative (n = 6) studies using various types of surgery were conducted. The most commonly mentioned barriers were insufficient knowledge and awareness of HCC screening, unawareness of the necessity for early detection of HCC and lack of physician recommendation. A meta-analysis of seven studies showed that individuals with a family history of HCC increased screening uptake by nearly three times (OR: 2.69, 95% CI: 1.93, 3.75). Other most frequently reported facilitators include age, education level, and perceived risk et al. CONCLUSIONS: Many barriers to HCC screening were found. Meanwhile, this review points out that improving the awareness of high-risk populations toward HCC screening is expected to enhance compliance, thereby promoting early diagnosis of liver cancer, reducing mortality, and alleviating the burden of HCC.

Transmission dynamics of Zika virus with multiple infection routes and a case study in Brazil.

The Zika virus (ZIKV) is a serious global public health crisis. A major control challenge is its multiple transmission modes. This paper aims to simulate the transmission patterns of ZIKV using a dynamic process-based epidemiological model written in ordinary differential equations, which incorporates the human-to-mosquito infection by bites and sewage, mosquito-to-human infection by bites, and human-to-human infection by sex. Mathematical analyses are carried out to calculate the basic reproduction number and backward bifurcation, and prove the existence and stability of the equilibria. The model is validated with infection data by applying it to the 2015-2016 ZIKV epidemic in Brazil. The results indicate that the reproduction number is estimated to be 2.13, in which the contributions by mosquito bite, sex and sewage account for 85.7%, 3.5% and 10.8%, respectively. This number and the morbidity rate are most sensitive to parameters related to mosquito ecology, rather than asymptomatic or human-to-human transmission. Multiple transmission routes and suitable temperature exacerbate ZIKV infection in Brazil, and the vast majority of human infection cases were prevented by the intervention implemented. These findings may provide new insights to improve the risk assessment of ZIKV infection.

The global distribution and the risk prediction of relapsing fever group Borrelia: a data review with modelling analysis.

BACKGROUND: The recent discovery of emerging relapsing fever group Borrelia (RFGB) species, such as Borrelia miyamotoi, poses a growing threat to public health. However, the global distribution and associated risk burden of these species remain uncertain. We aimed to map the diversity, distribution, and potential infection risk of RFGB. METHODS: We searched PubMed, Web of Science, GenBank, CNKI, and eLibrary from Jan 1, 1874, to Dec 31, 2022, for published articles without language restriction to extract distribution data for RFGB detection in vectors, animals, and humans, and clinical information about human patients. Only articles documenting RFGB infection events were included in this study, and data for RFGB detection in vectors, animals, or humans were composed into a dataset. We used three machine learning algorithms (boosted regression trees, random forest, and least absolute shrinkage and selection operator logistic regression) to assess the environmental, ecoclimatic, biological, and socioeconomic factors associated with the occurrence of four major RFGB species: Borrelia miyamotoi, Borrelia lonestari, Borrelia crocidurae, and Borrelia hermsii; and mapped their worldwide risk level. FINDINGS: We retrieved 13 959 unique studies, among which 697 met the selection criteria and were used for data extraction. 29 RFGB species have been recorded worldwide, of which 27 have been identified from 63 tick species, 12 from 61 wild animals, and ten from domestic animals. 16 RFGB species caused human infection, with a cumulative count of 26 583 cases reported from Jan 1, 1874, to Dec 31, 2022. Borrelia recurrentis (17 084 cases) and Borrelia persica (2045 cases) accounted for the highest proportion of human infection. B miyamotoi showed the widest distribution among all RFGB, with a predicted environmentally suitable area of 6·92 million km2, followed by B lonestari (1·69 million km2), B crocidurae (1·67 million km2), and B hermsii (1·48 million km2). The habitat suitability index of vector ticks and climatic factors, such as the annual mean temperature, have the most significant effect among all predictive models for the geographical distribution of the four major RFGB species. INTERPRETATION: The predicted high-risk regions are considerably larger than in previous reports. Identification, surveillance, and diagnosis of RFGB infections should be prioritised in high-risk areas, especially within low-income regions. FUNDING: National Key Research and Development Program of China.

Research and experimental verification on the mechanisms of cellular senescence in triple-negative breast cancer.

Background: Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with high heterogeneity, poor prognosis, and a low 10-year survival rate of less than 50%. Although cellular senescence displays extensive effects on cancer, the comprehensions of cellular senescence-related characteristics in TNBC patients remains obscure. Method: Single-cell RNA sequencing (scRNA-seq) data were analyzed by Seurat package. Scores for cellular senescence-related pathways were computed by single-sample gene set enrichment analysis (ssGSEA). Subsequently, unsupervised consensus clustering was performed for molecular cluster identification. Immune scores of patients in The Cancer Genome Atlas (TCGA) dataset and associated immune cell scores were calculated using Estimation of STromal and Immune cells in MAlignantTumours using Expression data (ESTIMATE) and Microenvironment Cell Populations-counter (MCP-counter), Tumor Immune Estimation Resource (TIMER) and Estimating the Proportion of Immune and Cancer cells (EPIC) methods, respectively. Immunotherapy scores were assessed using TIDE. Furthermore, feature genes were identified by univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses; these were used to construct a risk model. Additionally, quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and transwell assay were conducted for in vitro validation of hub genes. Result: TNBC was classified into three subtypes based on cellular senescence-related pathways as clusters 1, 2, and 3. Specifically, cluster 1 showed the best prognosis, followed by cluster 2 and cluster 3. The levels of gene expression in cluster 2 were the lowest, whereas these were the highest in cluster 3. Moreover, clusters 1 and 3 showed a high degree of immune infiltration. TIDE scores were higher for cluster 3, suggesting that immune escape was more likely in patients with the cluster 3 subtype who were less likely to benefit from immunotherapy. Next, the TNBC risk model was constructed and validated. RT-qPCR revealed that prognostic risk genes (MMP28, ACP5 and KRT6A) were up-regulated while protective genes (CT83) were down-regulated in TNBC cell lines, validating the results of the bioinformatics analysis. Meanwhile, cellular experiments revealed that ACP5 could promote the migration and invasion abilities in two TNBC cell lines. Finally, we evaluated the validity of prognostic models for assessing TME characteristics and TNBC chemotherapy response. Conclusion: In conclusion, these findings help to assess the efficacy of targeted therapies in patients with different molecular subtypes, have practical applications for subtype-specific treatment of TNBC patients, and provide information on prognostic factors, as well as guidance for the revelation of the molecular mechanisms by which senescence-associated genes influence TNBC progression.

Molecular mechanism of the metal-independent production of hydroxyl radicals by thiourea dioxide and H2O2.

It is well-known that highly reactive hydroxyl radicals (HO•) can be produced by the classic Fenton system and our recently discovered haloquinone/H2O2 system, but rarely from thiol-derivatives. Here, we found, unexpectedly, that HO• can be generated from H2O2 and thiourea dioxide (TUO2), a widely used and environmentally friendly bleaching agent. A carbon-centered radical and sulfite were detected and identified as the transient intermediates, and urea and sulfate as the final products, with the complementary application of electron spin-trapping, oxygen-18 isotope labeling coupled with HPLC/MS analysis. Density functional theory calculations were conducted to further elucidate the detailed pathways for HO• production. Taken together, we proposed that the molecular mechanism for HO• generation by TUO2/H2O2: TUO2 tautomerizes from sulfinic acid into ketone isomer (TUO2-K) through proton transfer, then a nucleophilic addition of H2O2 on the S atom of TUO2-K, forming a S-hydroperoxide intermediate TUO2-OOH, which dissociates homolytically to produce HO•. Our findings represent the first experimental and computational study on an unprecedented new molecular mechanism of HO• production from simple thiol-derived sulfinic acids, which may have broad chemical, environmental, and biomedical significance for future research on the application of the well-known bleaching agent and its analogs.

[Development of a Catalytic Hairpin Assembly-Based Fluorescent Assay for the Rapid Detection of SARS-CoV-2 Target RNA]. / åŸºäºŽå‚¬åŒ–å‘å¤¹è‡ªç»„è£ æŠ€æœ¯çš„æ–°åž‹å† çŠ¶ç— æ¯’é¶RNAå¿«é€Ÿè§å ‰æ£€æµ‹æ³•çš„å»ºç«‹.

Objective: To develop a catalytic hairpin assembly (CHA)-based fluorescent assay for the detection of the target RNA of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), so as to realize the rapid nucleic acid testing of SARS-CoV-2. Methods: A 24-nt segment of the SARS-CoV-2 nucleocapsid protein gene (N gene, NC_045512.2) was chosen as the target RNA and the hairpin motif 1 (H1) and hairpin motif 2 (H2) were designed based on the principle of CHA reaction. The H1 motif was labelled with a fluorophore group as well as a quencher group. When the target RNA was added to the hairpin motifs, CHA reaction was triggered at room temperature (25 ℃), which led to the amplification of fluorescence signal, thereby enabling the rapid detection of the target RNA. After the optimization of the hairpin motifs and the experimental conditions, the sensitivity and the specificity of the testing method were measured to evaluate its performance. Results: We successfully constructed a CHA-based fluorescent assay specifically for the target RNA of SARS-CoV-2. With this method, testing could be completed at room temperature within 30 min. This testing method exhibited excellent specificity and could be used to accurately distinguish the perfectly-matched target RNA from the target RNA with single-base mutations. In addition, the testing method demonstrated good sensitivity, with a detection limit of 50 pmol/L. Conclusion: The proposed assay enables the simple and rapid detection of the SARS-CoV-2 target RNA with excellent sensitivity and specificity, showing great promise for further optimization and subsequent clinical application for the rapid detection of SARS-CoV-2 nucleic acid.

A Shear-Stiffening Mouthguard with Excellent Shock Absorption Capability and Remoldability via a Dynamic Dual Network.

Mouthguards are used to reduce injuries and the probability of them to orofacial tissues when impacted during sports. However, the usage of a mouthguard is low due to the discomfort caused by the thickness of the mouthguard. Herein, we have constructed a dynamic dual network to fabricate a shear-stiffening mouthguard with remoldability, which are called remoldable shear-stiffening mouthguards (RSSMs). Based on diboron/oxygen dative bonds, RSSMs show a shear-stiffening effect and excellent shock absorption ability, which can absorb more than 90% of the energy of a blank. Even reducing the thickness to half, RSSMs can reduce approximately 25% of the transmitted force and elongate by about 1.6-fold the buffer time compared to commercial mouthguard materials (Erkoflex and Erkoloc-pro). What is more, owing to the dynamic dual network, RSSMs show good remolding performance with unchanged shear-stiffening behavior and impact resistance, which conforms to the existing vacuum thermoforming mode. In addition, RSSMs exhibit stability in artificial saliva and biocompatibility. In conclusion, this work will broaden the range of mouthguard materials and offer a platform to apply shear-stiffening materials to biomedical applications and soft safeguarding devices.

The reduced mortality of malignant melanoma at the population level is mainly attributable to treatment advances for the past decade.

BACKGROUND: Cutaneous malignant melanoma (CMM) causes most skin cancer deaths in the United States (US). The mortality has been decreasing in the US population. We hypothesize that this population-level reduction is mainly attributable to the treatment advances, rather than the successful primary and secondary prevention. METHODS: Using data from the Surveillance, Epidemiology, and End Results (SEER) databases, we collected the incidence, incidence-based mortality (IBM), and 5-year survival (5-YS) rates of CMM from 1994 to 2019. Trends by stage and sex were examined by joinpoint regression analyses and age-period-cohort analyses. RESULTS: The overall incidence of CMM rose by 1.6% yearly from 1994 to 2006 (95% confidence interval [CI]: 0.9% to 2.2%) and then increased with a numerical trend. And we projected the incidence will continue to increase until 2029. In contrast, the IBM for all CMM has decreased yearly by 2.8% (95% CI: -3.9% to -1.8%) since 2010 after continuously increasing by 3.8% annually (95% CI: 3.2% to 4.4%) from 1996 to 2010. For early-stage (localized and regional) CMM, we found the incidence since 2005 plateaued without further increase, while the incidence for CMM at distant stage continuously increased by 1.4% per year (95% CI: 0.9% to 2.0%). Improvements in 5-YS were observed over the study period for all CMM and were most obvious in distant stage. And significant period effects were noted around the year 2010. CONCLUSION: This study demonstrated improved survival and reduced mortality of CMM at the US population level since 2010, which were consistent with the introduction of novel therapies. Encouraging effects of primary prevention among adolescents in the most recent cohorts were found. However, the plateaued overall incidence and early diagnosis rates indicated that advances in primary and secondary prevention are very much needed to further control the burden of CMM.

The m6A methyltransferase RBM15 affects tumor cell stemness and progression of cervical cancer by regulating the stability of lncRNA HEIH.

Cervical cancer (CC), as a common female malignant tumor in the world, is an important risk factor endangering women's health worldwide. The purpose of this study was to investigate the role of RBM15 in CC. The TCGA database was used to screen differentially expressed m6A genes in normal and tumor tissues. QRT-PCR was used to quantify HEIH, miR-802, EGFR, cell stemness, and epithelial-mesenchymal transition (EMT)-related genes. The interaction between HEIH and miR-802 was verified by dual-luciferase reporter assay and RIP assay. The occurrence of tumor cells after different treatments was detected by CCK-8, transwell and EdU staining. BALB/c nude mice were used to examine the effects of different treatments on tumor growth and cell stemness in vivo. RBM15 was upregulated in tumor tissues and cells. M6A was highly enriched in HEIH and enhances its RNA stability. HEIH acts as an oncogenic lncRNA to promote CC cell proliferation, migration and tumor growth. Mechanistically, HEIH regulates tumor cell stemness and promotes the proliferation and migration of CC cells by competitively adsorbing miR-802 and up-regulating the expression of EGFR. In short, our data shown that the m6A methyltransferase RBM15 could affect tumor cell proliferation, metastasis and cell stemness by stabilizing HEIH expression.

SARS-CoV-2 immunity in animal models.

The COVID-19 pandemic, which was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a worldwide health crisis due to its transmissibility. SARS-CoV-2 infection results in severe respiratory illness and can lead to significant complications in affected individuals. These complications encompass symptoms such as coughing, respiratory distress, fever, infectious shock, acute respiratory distress syndrome (ARDS), and even multiple-organ failure. Animal models serve as crucial tools for investigating pathogenic mechanisms, immune responses, immune escape mechanisms, antiviral drug development, and vaccines against SARS-CoV-2. Currently, various animal models for SARS-CoV-2 infection, such as nonhuman primates (NHPs), ferrets, hamsters, and many different mouse models, have been developed. Each model possesses distinctive features and applications. In this review, we elucidate the immune response elicited by SARS-CoV-2 infection in patients and provide an overview of the characteristics of various animal models mainly used for SARS-CoV-2 infection, as well as the corresponding immune responses and applications of these models. A comparative analysis of transcriptomic alterations in the lungs from different animal models revealed that the K18-hACE2 and mouse-adapted virus mouse models exhibited the highest similarity with the deceased COVID-19 patients. Finally, we highlighted the current gaps in related research between animal model studies and clinical investigations, underscoring lingering scientific questions that demand further clarification.

Hypofractionated radiotherapy for refractory or relapsed aggressive B-cell lymphoma in the rituximab era.

BACKGROUND: Radiotherapy (RT) is an effective and available local treatment for patients with refractory or relapsed (R/R) aggressive B-cell lymphomas. However, the value of hypofractionated RT in this setting has not been confirmed. METHODS: We retrospectively analyzed patients with R/R aggressive B-cell lymphoma who received hypofractionated RT between January 2020 and August 2022 at a single institution. The objective response rate (ORR), overall survival (OS), progression-free survival (PFS) and acute side effects were analyzed. RESULTS: A total of 30 patients were included. The median dose for residual disease was 36 Gy, at a dose per fraction of 2.3-5 Gy. After RT, the ORR and complete response (CR) rates were 90% and 80%, respectively. With a median follow-up of 10 months (range, 2-27 months), 10 patients (33.3%) experienced disease progression and three died. The 1-year OS and PFS rates for all patients were 81.8% and 66.3%, respectively. The majority (8/10) of post-RT progressions involved out-of-field relapses. Patients with relapsed diseases, no response to systemic therapy, multiple lesions at the time of RT, and no response to RT were associated with out-of-field relapses. PFS was associated with response to RT (P = 0.001) and numbers of residual sites (P < 0.001). No serious non-hematological adverse effects (≥ grade 3) associated with RT were reported. CONCLUSION: These data suggest that hypofractionated RT was effective and tolerable for patients with R/R aggressive B-cell lymphoma, especially for those that exhibited localized residual disease.

Single-cell RNA sequencing reveals the immunoregulatory roles of PegIFN-α in patients with chronic hepatitis B.

BACKGROUND AND AIMS: Chronic hepatitis B (CHB) is caused by HBV infection and affects the lives of millions of people worldwide by causing liver inflammation, cirrhosis, and liver cancer. Interferon-alpha (IFN-α) therapy is a conventional immunotherapy that has been widely used in CHB treatment and achieved promising therapeutic outcomes by activating viral sensors and interferon-stimulated genes (ISGs) suppressed by HBV. However, the longitudinal landscape of immune cells of CHB patients and the effect of IFN-α on the immune system are not fully understood. APPROACH AND RESULTS: Here, we applied single-cell RNA sequencing (scRNA-seq) to delineate the transcriptomic landscape of peripheral immune cells in CHB patients before and after PegIFN-α therapy. Notably, we identified three CHB-specific cell subsets, pro-inflammatory (Pro-infla) CD14+ monocytes, Pro-infla CD16+ monocytes and IFNG+ CX3CR1- NK cells, which highly expressed proinflammatory genes and positively correlated with HBsAg. Furthermore, PegIFN-α treatment attenuated percentages of hyperactivated monocytes, increased ratios of long-lived naive/memory T cells and enhanced effector T cell cytotoxicity. Finally, PegIFN-α treatment switched the transcriptional profiles of entire immune cells from TNF-driven to IFN-α-driven pattern and enhanced innate antiviral response, including virus sensing and antigen presentation. CONCLUSIONS: Collectively, our study expands the understanding of the pathological characteristics of CHB and the immunoregulatory roles of PegIFN-α, which provides a new powerful reference for the clinical diagnosis and treatment of CHB.

Effects of aerosol water content and acidity on the light absorption of atmospheric humic-like substances in winter.

Atmospheric humic-like substances (HULIS) could affect regional climate due to their strong light-absorbing capacity. Daily fine particulate matter (PM2.5) samples were collected from December 18, 2016 to January 8, 2017 at an urban site in Chongqing, Southwest China. The mean concentration of HULIS in terms of carbon (HULIS-C) was 6.4 ± 3.4 µg m-3, accounting for 72% of water-soluble organic carbon. The mass absorption efficiency at 365 nm (MAE365) and absorption Ångström index (AAE) of atmospheric HULIS were 2.8 ± 0.30 m2 g-1 C and 4.6 ± 0.37, respectively. Good correlations between the light absorption coefficients of HULIS at 365 nm (Abs365) and the concentrations of K+, elemental carbon, NO3-, and NH4+ were observed, with correlation coefficients higher than 0.83, indicating that biomass burning and secondary formation were potential sources of light-absorbing HULIS, as evidenced by abundant fluorescent components related to less-oxygenated HULIS. Comparing the changes in Abs365 values, concentrations of major water-soluble inorganic ions and carbonaceous compounds in PM2.5, and environmental factors during the clean and pollution periods, we found that extensive biomass burning during the pollution period contributed significantly to the increase of Abs365 values. Moreover, the aerosol pH during the pollution period was close to 4, and NO2 concentration and aerosol water content were about 1.6 and 2.7 times higher than those during the clean period, respectively, which were favorable to form secondary HULIS through aqueous phase reactions in the presence of high NOx, resulting in an evident increase in its light absorption. Knowledge generated from this study is critical for evaluating the regional radiative forcing of brown carbon in southwest China.

The Prognosis and Immunotherapy Prediction Model of Ovarian Serous Cystadenocarcinoma Patient was Constructed Based on Cuproptosis-Related LncRNA.

Cuproptosis can serve as potential prognostic predictors in patients with cancer. However, the role of this relationship in ovarian serous cystadenocarcinoma (OV) remains unclear. 376 OV tumor samples were obtained from the Cancer Genome Atlas (TCGA) database, and long non-coding RNAs (lncRNAs) related to cuproptosis were obtained through correlation analysis. The risk assessment model was further constructed by univariate Cox regression analysis and LASSO Cox regression. Bioinformatics was used to analyze the regulatory effect of relevant risk assessment models on tumor mutational burden (TMB) and immune microenvironment. We obtained 5 lncRNAs (AC025287.2, AC092718.4, AC112721.2, LINC00996, and LINC01639) and incorporated them into the Cox proportional hazards model. Kaplan-Meier (KM) curve analysis of the prognosis found that the high-risk group was associated with a poorer prognosis. The receiver operating characteristic (ROC) curve showed stronger predictive power compared to other clinicopathological features. Immune infiltration analysis showed that high-risk scores were inversely correlated with CD8+ T cells, CD4+ T cells, macrophages, NK cells, and B cells. Functional enrichment analysis found that they may act via the extracellular matrix (ECM)-interacting proteins and other pathways. We successfully constructed a reliable cuproptosis-related lncRNA model for the prognosis of OV.

US of thyroid nodules: can AI-assisted diagnostic system compete with fine needle aspiration?

OBJECTIVES: Artificial intelligence (AI) systems can diagnose thyroid nodules with similar or better performance than radiologists. Little is known about how this performance compares with that achieved through fine needle aspiration (FNA). This study aims to compare the diagnostic yields of FNA cytopathology alone and combined with BRAFV600E mutation analysis and an AI diagnostic system. METHODS: The ultrasound images of 637 thyroid nodules were collected in three hospitals. The diagnostic efficacies of an AI diagnostic system, FNA-based cytopathology, and BRAFV600E mutation analysis were evaluated in terms of sensitivity, specificity, accuracy, and the κ coefficient with respect to the gold standard, defined by postsurgical pathology and consistent benign outcomes from two combined FNA and mutation analysis examinations performed with a half-year interval. RESULTS: The malignancy threshold for the AI system was selected according to the Youden index from a retrospective cohort of 346 nodules and then applied to a prospective cohort of 291 nodules. The combination of FNA cytopathology according to the Bethesda criteria and BRAFV600E mutation analysis showed no significant difference from the AI system in terms of accuracy for either cohort in our multicenter study. In addition, for 45 included indeterminate Bethesda category III and IV nodules, the accuracy, sensitivity, and specificity of the AI system were 84.44%, 95.45%, and 73.91%, respectively. CONCLUSIONS: The AI diagnostic system showed similar diagnostic performance to FNA cytopathology combined with BRAFV600E mutation analysis. Given its advantages in terms of operability, time efficiency, non-invasiveness, and the wide availability of ultrasonography, it provides a new alternative for thyroid nodule diagnosis. CLINICAL RELEVANCE STATEMENT: Thyroid ultrasonic artificial intelligence shows statistically equivalent performance for thyroid nodule diagnosis to FNA cytopathology combined with BRAFV600E mutation analysis. It can be widely applied in hospitals and clinics to assist radiologists in thyroid nodule screening and is expected to reduce the need for relatively invasive FNA biopsies. KEY POINTS: • In a retrospective cohort of 346 nodules, the evaluated artificial intelligence (AI) system did not significantly differ from fine needle aspiration (FNA) cytopathology alone and combined with gene mutation analysis in accuracy. • In a prospective multicenter cohort of 291 nodules, the accuracy of the AI diagnostic system was not significantly different from that of FNA cytopathology either alone or combined with gene mutation analysis. • For 45 indeterminate Bethesda category III and IV nodules, the AI system did not perform significantly differently from BRAFV600E mutation analysis.

A hybrid graph network model for ASD diagnosis based on resting-state EEG signals.

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder and early diagnosis is crucial for effective treatment. Stable and effective biomarkers are essential for understanding the underlying causes of the disorder and improving diagnostic accuracy. Electroencephalography (EEG) signals have proven to be reliable biomarkers for diagnosing ASD. Extracting stable connectivity patterns from EEG signals helps ensure robustness in ASD diagnostic systems. In this study, we propose a hybrid graph convolutional network framework called Rest-HGCN, which utilizes resting-state EEG signals to capture differential patterns of brain connectivity between normal children and ASD patients using graph learning strategies. The Rest-HGCN combines brain network analysis techniques and data-driven strategies to extract discriminative graph features from resting-state EEG signals. By automatically extracting differential graph patterns from these signals, the Rest-HGCN achieves reliable ASD diagnosis. To evaluate the performance of Rest-HGCN, we conducted ASD diagnosis experiments using k-fold cross-validation on the public ABC-CT resting EEG dataset. The proposed Rest-HGCN model achieved accuracies of 87.12 % and 85.32 % in single-subject and cross-experiment analyses, respectively. The results suggest that Rest-HGCN can effectively capture discriminant graph patterns from resting EEG signals and achieve robust ASD diagnosis. This may provide an effective and convenient tool for clinical ASD diagnosis.

Discovery of a Novel Benzothiadiazine-Based Selective Aldose Reductase Inhibitor as Potential Therapy for Diabetic Peripheral Neuropathy.

Aldose reductase 2 (ALR2), an activated enzyme in the polyol pathway by hyperglycemia, has long been recognized as one of the most promising targets for complications of diabetes, especially in diabetic peripheral neuropathy (DPN). However, many of the ALR2 inhibitors have shown serious side effects due to poor selectivity over aldehyde reductase (ALR1). Herein, we describe the discovery of a series of benzothiadiazine acetic acid derivatives as potent and selective inhibitors against ALR2 and evaluation of their anti-DPN activities in vivo. Compound 15c, carrying a carbonyl group at the 3-position of the thiadiazine ring, showed high potent inhibition against ALR2 (IC50 = 33.19 nmol/L) and ∼16,109-fold selectivity for ALR2 over ALR1. Cytotoxicity assays ensured the primary biosafety of 15c. Further pharmacokinetic assay in rats indicated that 15c had a good pharmacokinetic feature (t1/2 = 5.60 h, area under the plasma concentration time curve [AUC(0-t)] = 598.57 ± 216.5 µg/mL * h), which was superior to epalrestat (t1/2 = 2.23 h, AUC[0-t] = 20.43 ± 3.7 µg/mL * h). Finally, in a streptozotocin-induced diabetic rat model, 15c significantly increased the nerve conduction velocities of impaired sensory and motor nerves, achieved potent inhibition of d-sorbitol production in the sciatic nerves, and significantly increased the paw withdrawal mechanical threshold. By combining the above investigations, we propose that 15c might represent a promising lead compound for the discovery of an antidiabetic peripheral neuropathy drug.

Amine-functionalized Schiff base covalent organic frameworks supported PdAuIr nanoparticles as high-performance catalysts for formic acid dehydrogenation and hexavalent chromium reduction.

Formic acid (FA) holds significant potential as a liquid hydrogen storage medium. However, it is important to improve the reaction rates and extend the practical applications of FA dehydrogenation and Cr(VI) reduction through the development of efficient heterogeneous catalysts. This study reports the synthesis of a uniformly dispersed PdAuIr nanoparticles (NPs) catalyst loaded with amine groups covalent organic frameworks (COFs). The alloyed NPs demonstrated exceptional effectiveness in FA dehydrogenation rate and Cr(VI) reduction. The initial turnover of frequency (TOF) value for FA dehydrogenation without additives was 9970 h-1 at 298 K, the apparent activation energy (Ea) was 30.3 kJ/mol and the rate constant (k) for Cr(VI) reduction was 0.742 min-1. Additionally, it showcased the ability to undergo recycling up to six times with minimal degradation in performance. The results indicate that its remarkable catalytic performance can be attributed primarily to the favorable mass transfer attributes of the aminated COFs supports, the strong metal-support interaction (SMSI), and the synergistic effects among the metals. This study offers a novel perspective on the advancement of efficient and durable heterogeneous catalysts with diverse capabilities, thereby making significant contributions to the fields of energy and environmental preservation.