A deep learning algorithm to identify carotid plaques and assess their stability.

Background: Carotid plaques are major risk factors for stroke. Carotid ultrasound can help to assess the risk and incidence rate of stroke. However, large-scale carotid artery screening is time-consuming and laborious, the diagnostic results inevitably involve the subjectivity of the diagnostician to a certain extent. Deep learning demonstrates the ability to solve the aforementioned challenges. Thus, we attempted to develop an automated algorithm to provide a more consistent and objective diagnostic method and to identify the presence and stability of carotid plaques using deep learning. Methods: A total of 3,860 ultrasound images from 1,339 participants who underwent carotid plaque assessment between January 2021 and March 2023 at the Shanghai Eighth People's Hospital were divided into a 4:1 ratio for training and internal testing. The external test included 1,564 ultrasound images from 674 participants who underwent carotid plaque assessment between January 2022 and May 2023 at Xinhua Hospital affiliated with Dalian University. Deep learning algorithms, based on the fusion of a bilinear convolutional neural network with a residual neural network (BCNN-ResNet), were used for modeling to detect carotid plaques and assess plaque stability. We chose AUC as the main evaluation index, along with accuracy, sensitivity, and specificity as auxiliary evaluation indices. Results: Modeling for detecting carotid plaques involved training and internal testing on 1,291 ultrasound images, with 617 images showing plaques and 674 without plaques. The external test comprised 470 ultrasound images, including 321 images with plaques and 149 without. Modeling for assessing plaque stability involved training and internal testing on 764 ultrasound images, consisting of 494 images with unstable plaques and 270 with stable plaques. The external test was composed of 279 ultrasound images, including 197 images with unstable plaques and 82 with stable plaques. For the task of identifying the presence of carotid plaques, our model achieved an AUC of 0.989 (95% CI: 0.840, 0.998) with a sensitivity of 93.2% and a specificity of 99.21% on the internal test. On the external test, the AUC was 0.951 (95% CI: 0.962, 0.939) with a sensitivity of 95.3% and a specificity of 82.24%. For the task of identifying the stability of carotid plaques, our model achieved an AUC of 0.896 (95% CI: 0.865, 0.922) on the internal test with a sensitivity of 81.63% and a specificity of 87.27%. On the external test, the AUC was 0.854 (95% CI: 0.889, 0.830) with a sensitivity of 68.52% and a specificity of 89.49%. Conclusion: Deep learning using BCNN-ResNet algorithms based on routine ultrasound images could be useful for detecting carotid plaques and assessing plaque instability.

Genetic alterations predict poor efficacy, outcomes and resistance to second-line osimertinib treatment in non-small cell lung cancer.

The genetic heterogeneity of non-small cell lung cancer (NSCLC) may impact clinical response and outcomes to targeted therapies. In second-line osimertinib treatment for NSCLC, real-world data on genetic biomarkers for treatment efficacy and prognosis remain incomplete. This real-world study involved 68 NSCLC patients receiving first-generation epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). All of these patients developed resistance, and 49 of them subsequently underwent second-line osimertinib treatment. A 639-gene DNA panel was employed to assess the impact of molecular alterations on treatment efficacy, clinical outcomes and resistance. The findings showed that the median progression-free survival (PFS) for second-line osimertinib therapy was 13.3 months. Genes alterations such as P21 (RAC1) activated kinase 5 (PAK5), RNA binding motif protein 10 (RBM10), and EPH receptor A3 (EPHA3) mutations were associated with significantly shorter PFS in osimertinib therapy. At multivariate analysis, they were all independent risk predictors of shorter PFS. Additionally, the median overall survival (OS) for osimertinib was 26.2 months. Glutamate ionotropic receptor NMDA type subunit 2A (GRIN2A), hepatocyte growth factor (HGF), and RBM10 mutations were significantly associated with poorer OS in osimertinib treatment. The multivariate analysis demonstrated that only RBM10 mutation emerged as an independent risk predictor of shorter OS. In vitro experiments showed that RBM10 mutations could promote the proliferation and migration ability of NSCLC cells and reduced cell apoptosis. The resistance mechanisms to osimertinib were heterogeneous. Histone cluster 1 H2B family member D (HIST1H2BD) acted as a novel resistance mechanism to osimertinib. Previously unreported HIST1H2BD mutations (p.K25Q and p.E36D) were detected in the NSCLC tissues. In vitro experiments confirmed that HIST1H2BD mutations led to resistance to osimertinib. In summary, we demonstrate that genetic biomarkers, such as PAK5, RBM10, and EPHA3, are independent predictors of PFS in second-line osimertinib treatment, with RBM10 emerging as an independent predictor of OS. Additionally, HIST1H2BD represents a novel resistance mutation to osimertinib. All of these findings offer valuable insights for making personalized treatment strategies for NSCLC patients.

Individualized folic acid supplementation based on MTHFR and MTRR gene polymorphisms reduces the risk of gestational diabetes mellitus in a Chinese population.

OBJECTIVE: Folic acid (FA) may contribute to the development of gestational diabetes mellitus (GDM), but available studies are inconsistent. We studied the genotype distribution and allele frequencies of methylenetetrahydrofolate reductase (MTHFR) C677T, A1298C, and methionine synthase reductase (MTRR) A66G polymorphisms in pregnant Chinese women and compared the effects of individualized and traditional FA supplementation on GDM. METHODS: In this retrospective study, genotype distribution and allele frequencies in 968 pregnant women were tested. FA metabolism was tested by dividing patients into four groups, each of which was supplemented with different doses of FA at different times. Pregnancy complications were followed up and compared to 1940 pregnant women traditionally supplemented with FA in the same hospital as a control group. RESULTS: The allele frequencies were 63.3% (C) and 36.7% (T) for MTHFR C677T, 79.3% (A) and 20.7% (C) for MTHFR A1298C and 75.0% (A) and 25.0% (G) for MTRR A66G. The incidence of GDM after FA supplementation was significantly lower in the case group compared to the control group, especially in high-risk pregnancies. CONCLUSION: Using genetic polymorphisms to elucidate FA metabolism in pregnant women and providing appropriate FA supplementation can be effective in reducing GDM, especially in high-risk groups.

Using combined CT-clinical radiomics models to identify epidermal growth factor receptor mutation subtypes in lung adenocarcinoma.

Background: To investigate the value of computed tomography (CT)-based radiomics signatures in combination with clinical and CT morphological features to identify epidermal growth factor receptor (EGFR)-mutation subtypes in lung adenocarcinoma (LADC). Methods: From February 2012 to October 2019, 608 patients were confirmed with LADC and underwent chest CT scans. Among them, 307 (50.5%) patients had a positive EGFR-mutation and 301 (49.5%) had a negative EGFR-mutation. Of the EGFR-mutant patients, 114 (37.1%) had a 19del -mutation, 155 (50.5%) had a L858R-mutation, and 38 (12.4%) had other rare mutations. Three combined models were generated by incorporating radiomics signatures, clinical, and CT morphological features to predict EGFR-mutation status. Patients were randomly split into training and testing cohorts, 80% and 20%, respectively. Model 1 was used to predict positive and negative EGFR-mutation, model 2 was used to predict 19del and non-19del mutations, and model 3 was used to predict L858R and non-L858R mutations. The receiver operating characteristic curve and the area under the curve (AUC) were used to evaluate their performance. Results: For the three models, model 1 had AUC values of 0.969 and 0.886 in the training and validation cohorts, respectively. Model 2 had AUC values of 0.999 and 0.847 in the training and validation cohorts, respectively. Model 3 had AUC values of 0.984 and 0.806 in the training and validation cohorts, respectively. Conclusion: Combined models that incorporate radiomics signature, clinical, and CT morphological features may serve as an auxiliary tool to predict EGFR-mutation subtypes and contribute to individualized treatment for patients with LADC.

Liraglutide-induced structural modulation of the gut microbiota in patients with type 2 diabetes mellitus.

Accumulating evidence has suggested the importance of gut microbiota in the development of type 2 diabetes mellitus (T2DM). In the present study, 40 patients with T2DM were treated with liraglutide for 4 months. Feces samples and clinical characteristics were collected from these 40 T2DM patients before and after the liraglutide treatment. The diversity and composition of gut microbiota in the two groups were determined by sequencing the V4 region of bacterial 16S rRNA genes. Meanwhile, blood glucose, insulin, hemoglobin A1c (HbA1c), and lipid metabolism were also measured in the pre- and post-liraglutide-treatment groups. We find that Baseline HbA1c was associated with liraglutide treatment response (R 2 = 0.527, ß =  - 0.726, p < 0.0001). After adjusted for baseline HbA1c, blood urea nitrogen was associated with liraglutide treatment response. Besides, our results showed reduced gut microbial alpha diversity, different community structure distribution and altered microbial interaction network in patients treated with liraglutide. The liner discriminant analysis (LDA) effect size (LEfSe) analysis showed that 21 species of bacteria were abundant in the pre-liraglutide-treatment group and 15 species were abundant in the post-liraglutide-treatment group. In addition, we also find that Megamonas were significantly correlated with older age, diabetes duration and diabetic retinopathy, Clostridum were significantly correlated with family history of diabetes and Oscillospira were significantly correlated with both diabetic retinopathy and diabetic peripheral neuropathy. Functional analysis based on Kyoto Encyclopedia of Genes and Genomes (KEGG) and cluster of orthologous groups (COG) annotations enriched three KEGG metabolic pathways and six functional COG categories in the post-liraglutide-treatment group. In conclusion, our research suggests that baseline HbA1c, blood urea nitrogen and gut microbiota are associated with the liraglutide treatment applied on patients with T2DM. These findings may contribute to the beneficial effects of liraglutide against diabetes.

Effect of Psychological-Behavioral Intervention on the Depression and Anxiety of COVID-19 Patients.

The COVID-19 epidemic has caused increasing public panic and mental health stress. In this study, we explore the prevalence and factors linked to anxiety and depression in hospitalized patients with COVID-19. A total of 144 patients diagnosed with COVID-19 underwent depression and anxiety assessment by using the Hospital Anxiety and Depression Scale (HADS). Social support level was also evaluated by the Perceived Social Support Scale (PSSS) at admission. Results showed that gender, age, oxygen saturation, and social support were associated with anxiety for COVID-19 patients. In addition, age, family infection with SARS-CoV-2, and social support were the risk factors associated with depression. Moreover, we designed a psychological-behavioral intervention (PBI) program that included psychological support and breathing exercises, and explored its effects on patients with COVID-19. Of the 144 participants, 26 patients with both anxiety and depression symptoms (cutoff score of ≥8 on HADS-A and HADS-D) were randomly assigned to the intervention group and the control group at a 1:1 ratio. After 10-day treatment, the HADS scores of depression and anxiety were significantly reduced in the intervention group, and PSSS scores were also significantly improved. However, no significant differences in HADS and PSSS scores between pre- and post-treatment were found in the control group. Our findings indicate that mental concern and appropriate intervention are essential parts of clinical care for COVID-19 patients.

Estimation of the LDL subclasses in ischemic stroke as a risk factor in a Chinese population.

BACKGROUND: Acute ischemic stroke (AIS) is one of the leading causes of mortality and long-term disability worldwide. Our study aims to clarify the role of low-density lipoproteins (LDL) subclasses in the occurrence of AIS and develop a risk xprediction model based on these characteristics to identify high-risk people. METHODS: Five hundred and sixty-six patients with AIS and 197 non-AIS controls were included in this study. Serum lipids and other baseline characteristics including fasting blood glucose (GLU), serum creatinine (Scr), and blood pressure were investigated in relation to occurrence of AIS. The LDL subfractions were classified and measured with the Lipoprint System by a polyacrylamide gel electrophoresis technique. RESULTS: Levels of LDL-3, LDL-4 and LDL-5 subclasses were significantly higher in the AIS group compared to the non-AIS group and lower level of LDL-1 was prevalent in the AIS patients. Consistently, Spearman correlation coefficient demonstrated that sd-demonevels, especially LDL-3 and LDL-4 levels, were significantly positively correlated with AIS. Furthermore, there is a significant positive correlation between small dense LDL (sd-LDL, that is LDL-3 to 7) levels and serum lipids including total cholesterol (TC), Low density lipoprotein cholesterol (LDL-C), and Triglyceride (TG). Increased LDL-3 and LDL-4 as well as decreased LDL-1 and LDL-2 were correlated to the occurrence of AIS, even in the people with normal LDL-C levels. A new prediction model including 12 variables can accurately predict the AIS risk in Chinese patients (AUC = 0.82 ± 0.04). CONCLUSIONS: Levels of LDL subclasses should be considered in addition to serum LDL-C in assessment and management of AIS. A new prediction model based on clinical variables including LDL subtractions can help clinicians identify high of AIS, even in the people with norm.

Efficacy and safety of tocilizumab in COVID-19 patients.

In this retrospective study we assessed the efficacy and safety of tocilizumab in patients with critical or severe coronavirus disease 2019 (COVID-19). We enrolled 181 patients admitted to Huoshenshan Hospital (Wuhan, China) with confirmed COVID-19 between January 2020 and February 2020. Ninety-two patients were treated with tocilizumab, and 89 patients were treated conventionally. We analyzed the clinical manifestations, changes in CT scan images, and laboratory tests before and after tocilizumab treatment, and compared these results with the conventionally treated group. A significant reduction in the level of C-reactive protein was observed 1 week after tocilizumab administration. In some cases this meant the end of the IL-6-related cytokine storm. In addition, tocilizumab relieved fever, cough, and shortness of breath with no reported adverse drug reactions. These findings suggest tocilizumab improves clinical outcomes and is effective for treatment of patients with critical or severe COVID-19. However, future clinical trials are needed to better understand the impact of tocilizumab interference with IL-6 and provide a therapeutic strategy for treatment of COVID-19.

Assessing vitamin D related genetic variants, status, and influence factors in pregnant women in Eastern and Central China.

Vitamin D deficiency has recently become a global public health problem. However, it is still unclear if gene polymorphisms in the vitamin D pathway influence vitamin D levels among pregnant women in Eastern and Central China. The objective of this study was to assess factors influencing vitamin D levels in pregnant women. A total of 326 participants in Shandong and Henan provinces in China were enrolled from August 2017 to April 2019. Serum 25(OH)D levels and single nucleotide polymorphisms (SNPs) in the vitamin D pathway were measured using the blood samples collected in the first trimester, second trimester, and third trimester. Data on demographics, lifestyle, and health behavior were collected using a questionnaire. Statistical analyses were performed using the R software. The prevalence of 25(OH)D deficiency was significantly more severe in pregnant women. The average 25(OH)D value of all enrolled pregnant women was 14.57 ± 7.21 ng/ml (deficiency). Only 15 (4.60%) participants had a 25(OH)D concentration ≥30 ng/ml (sufficient). The prevalence of four ranks of vitamin D levels from severe 25(OH)D deficiency to 25(OH)D sufficiency (<10, 10-20, 20-30, and ≥30 ng/ml) was 29.14%, 52.45%, 13.80%, and 4.60%, respectively. Variants of GC (rs1155563) and CYP24A1 (rs6013897) were significantly associated with both 25(OH)D concentrations and vitamin D deficiency among pregnant women, respectively. Our findings suggest that pregnant women in Eastern and Central China are at high risk of vitamin D deficiency. Genetic mutants in the vitamin D pathway (GC and CYP24A1) were significantly associated with 25(OH)D levels in pregnant women in Eastern and Central China.

Genome survey, high-resolution genetic linkage map construction, growth-related quantitative trait locus (QTL) identification and gene location in Scylla paramamosain.

Scylla paramamosain is one of the most economically important crabs in China. In this study, the first genome survey sequencing of this crab was performed, and the results revealed that the estimated genome size was 1.21 Gb with high heterozygosity (1.3%). Then, RAD technology was used to construct a high-resolution linkage map for this species. A total of 24,444 single nucleotide polymorphism (SNP) makers were grouped into 47 linkage groups. The total length of the linkage groups was 3087.53 cM with a markers interval of 0.92 cM. With the aid of transcriptome and genome scaffold data, 4,271 markers were linked to genes, including several important growth-related genes such as transforming growth factor-beta regulator I, immune related-gene C-type lectin and ecdysone pathway gene broad-complex-like protein. Further, 442 markers, representing 279 QTLs, associated with 24 traits were identified, and of these markers, 78 were linked to genes. Some interesting genes, such as dedicator of cytokinesis protein 3, tenascin-X and DNA helicase MCM8, were believed to have important relationship with specific traits and merit further exploration. The results of this study will accelerate the genetic improvement and genome sequencing analysis of the mud crab.

An amine oxidase gene from mud crab, Scylla paramamosain, regulates the neurotransmitters serotonin and dopamine in vitro.

Amine oxidase, which participates in the metabolic processing of biogenic amines, is widely found in organisms, including higher organisms and various microorganisms. In this study, the full-length cDNA of a novel amine oxidase gene was cloned from the mud crab, Scylla paramamosain, and termed SpAMO. The cDNA sequence was 2,599 bp in length, including an open reading frame of 1,521 bp encoding 506 amino acids. Two amino acid sequence motifs, a flavin adenine dinucleotide-binding domain and a flavin-containing amine oxidoreductase, were highly conserved in SpAMO. A quantitative real-time polymerase chain reaction analysis showed that the expression level of SpAMO after quercetin treatment was time- and concentration-dependent. The expression of SpAMO tended to decrease and then increase in the brain and haemolymph after treatment with 5 mg/kg/d quercetin; after treatment with 50 mg/kg/d quercetin, the expression of SpAMO declined rapidly and remained low in the brain and haemolymph. These results indicated that quercetin could inhibit the transcription of SpAMO, and the high dose (50 mg/kg/d) had a relatively significant inhibitory effect. SpAMO showed the highest catalytic activity on serotonin, followed by dopamine, ß-phenylethylamine, and spermine, suggesting that the specific substrates of SpAMO are serotonin and dopamine. A bioinformatics analysis of SpAMO showed that it has molecular characteristics of spermine oxidase, but a quercetin test and enzyme activity study indicated that it also functions like monoamine oxidase. It is speculated that SpAMO might be a novel amine oxidase in S. paramamosain that has the functions of both spermine oxidase and monoamine oxidase.