MI-DenseCFNet: deep learning-based multimodal diagnosis models for Aureus and Aspergillus pneumonia.

OBJECTIVE: To build and merge a diagnostic model called multi-input DenseNet fused with clinical features (MI-DenseCFNet) for discriminating between Staphylococcus aureus pneumonia (SAP) and Aspergillus pneumonia (ASP) and to evaluate the significant correlation of each clinical feature in determining these two types of pneumonia using a random forest dichotomous diagnosis model. This will enhance diagnostic accuracy and efficiency in distinguishing between SAP and ASP. METHODS: In this study, 60 patients with clinically confirmed SAP and ASP, who were admitted to four large tertiary hospitals in Kunming, China, were included. Thoracic high-resolution CT lung windows of all patients were extracted from the picture archiving and communication system, and the corresponding clinical data of each patient were collected. RESULTS: The MI-DenseCFNet diagnosis model demonstrates an internal validation set with an area under the curve (AUC) of 0.92. Its external validation set demonstrates an AUC of 0.83. The model requires only 10.24s to generate a categorical diagnosis and produce results from 20 cases of data. Compared with high-, mid-, and low-ranking radiologists, the model achieves accuracies of 78% vs. 75% vs. 60% vs. 40%. Eleven significant clinical features were screened by the random forest dichotomous diagnosis model. CONCLUSION: The MI-DenseCFNet multimodal diagnosis model can effectively diagnose SAP and ASP, and its diagnostic performance significantly exceeds that of junior radiologists. The 11 important clinical features were screened in the constructed random forest dichotomous diagnostic model, providing a reference for clinicians. CLINICAL RELEVANCE STATEMENT: MI-DenseCFNet could provide diagnostic assistance for primary hospitals that do not have advanced radiologists, enabling patients with suspected infections like Staphylococcus aureus pneumonia or Aspergillus pneumonia to receive a quicker diagnosis and cut down on the abuse of antibiotics. KEY POINTS: • MI-DenseCFNet combines deep learning neural networks with crucial clinical features to discern between Staphylococcus aureus pneumonia and Aspergillus pneumonia. • The comprehensive group had an area under the curve of 0.92, surpassing the proficiency of junior radiologists. • This model can enhance a primary radiologist's diagnostic capacity.

Effects of altitude on thyroid disorders according to Chinese three-rung, ladder-like topography: national cross-sectional study.

BACKGROUND: Chinese topography appears a three-rung ladder-like distribution of decreasing elevation from northwest to southeast, which is divided by two sloping edges. Previous studies have reported that prevalence of thyroid diseases differed by altitude, and geographical factors were associated with thyroid disorders. To explore the association between three-rung ladder-like regions and thyroid disorders according to unique Chinese topographic features, we conducted an epidemiological cross-sectional study from 2015-2017 that covered all 31 mainland Chinese provinces. METHODS: A total of 78,470 participants aged ≥ 18 years from a nationally representative cross-sectional study were included. Serum thyroid peroxidase antibody, thyroglobulin antibody, and thyroid-stimulating hormone levels; urine iodine concentration; and thyroid volume were measured. The three-rung ladder-like distribution of decreasing elevation from northwest to southeast in China was categorized into three topographic groups according to elevation: first ladder, > 3000 m above sea level; second ladder, descending from 3000-500 m; and third ladder, descending from 500 m to sea level. The third ladder was further divided into groups A (500-100 m) and B (< 100 m). Associations between geographic factors and thyroid disorders were assessed using linear and binary logistic regression analyses. RESULTS: Participants in the first ladder group were associated with lower thyroid peroxidase (ß = -4.69; P = 0.00), thyroglobulin antibody levels (ß = -11.08; P = 0.01), and the largest thyroid volume (ß = 1.74; P = 0.00), compared with the other groups. The second ladder group was associated with autoimmune thyroiditis (odds ratio = 1.30, 95% confidence interval [1.18-1.43]) and subclinical hypothyroidism (odds ratio = 0.61, 95%confidence interval [0.57-0.66]) (P < 0.05) compared with the first ladder group. Group A (third ladder) (500-100 m) was associated with thyroid nodules and subclinical hypothyroidism (P < 0.05). Furthermore, group B (< 100 m) was positively associated with autoimmune thyroiditis, thyroid peroxidase and thyroglobulin antibody positivity, and negatively associated with overt hypothyroidism, subclinical hypothyroidism, and goiter compared with the first ladder group(P < 0.05). CONCLUSION: We are the first to investigate the association between different ladder regions and thyroid disorders according to unique Chinese topographic features. The prevalence of thyroid disorders varied among the three-rung ladder-like topography groups in China, with the exception of overt hyperthyroidism.

A graph auto-encoder model for miRNA-disease associations prediction.

Emerging evidence indicates that the abnormal expression of miRNAs involves in the evolution and progression of various human complex diseases. Identifying disease-related miRNAs as new biomarkers can promote the development of disease pathology and clinical medicine. However, designing biological experiments to validate disease-related miRNAs is usually time-consuming and expensive. Therefore, it is urgent to design effective computational methods for predicting potential miRNA-disease associations. Inspired by the great progress of graph neural networks in link prediction, we propose a novel graph auto-encoder model, named GAEMDA, to identify the potential miRNA-disease associations in an end-to-end manner. More specifically, the GAEMDA model applies a graph neural networks-based encoder, which contains aggregator function and multi-layer perceptron for aggregating nodes' neighborhood information, to generate the low-dimensional embeddings of miRNA and disease nodes and realize the effective fusion of heterogeneous information. Then, the embeddings of miRNA and disease nodes are fed into a bilinear decoder to identify the potential links between miRNA and disease nodes. The experimental results indicate that GAEMDA achieves the average area under the curve of $93.56\pm 0.44\%$ under 5-fold cross-validation. Besides, we further carried out case studies on colon neoplasms, esophageal neoplasms and kidney neoplasms. As a result, 48 of the top 50 predicted miRNAs associated with these diseases are confirmed by the database of differentially expressed miRNAs in human cancers and microRNA deregulation in human disease database, respectively. The satisfactory prediction performance suggests that GAEMDA model could serve as a reliable tool to guide the following researches on the regulatory role of miRNAs. Besides, the source codes are available at https://github.com/chimianbuhetang/GAEMDA.

Stanniocalcin-1 secreted by human umbilical mesenchymal stem cells regulates interleukin-10 expression via the PI3K/AKT/mTOR pathway in alveolar macrophages.

Acute respiratory distress syndrome (ARDS) is a syndrome of acute respiratory failure caused by infection, trauma, shock, aspiration or drug reaction. The pathogenesis of ARDS is characterized as an unregulated inflammatory storm, which causes endothelial and epithelial layer damage, leading to alveolar fluid accumulation and pulmonary edema. Previous studies have shown the potential role of mesenchymal stem cells (MSC) in combating the inflammatory cascade by increasing the anti-inflammatory mediator interleukin-10 (IL-10). However, the involved mechanisms are unclear. Here we investigated whether a key immunomodulatory regulator, stanniocalcin-1 (STC-1), was secreted by MSC to activate phosphoinositide 3-kinase/protein kinase B (PI3K/AKT)/ mammalian target of rapamycin (mTOR) signaling pathway to increase IL-10 expression in alveolar macrophages. Lipopolysaccharide (LPS)-stimulated alveolar macrophages co-cultured with human umbilical mesenchymal stem cells (HUMSC) secreted high levels of IL-10. HUMSC co-cultured with alveolar macrophages expressed high STC-1 levels and increased PI3K, AKT and mTOR phosphorylation after LPS activation in alveolar macrophages. STC-1 knockdown in HUMSC decreased the phosphorylation of PI3K, AKT and mTOR and suppressed IL-10 expression in alveolar macrophages. Rapamycin (an mTOR inhibitor) reduced IL-10 secretion in alveolar macrophages. These results, together with our previous study and others, indicate that the PI3K/AKT/mTOR pathway is involved in the regulation of IL-10 production by STC-1 secreted by HUMSC in alveolar macrophages.

Determination of the Predictive Roles and Potentially Pathogenic Antigen Epitopes of α-Enolase Related to the Development of Miscarriage in Females with Autoimmune Thyroiditis.

Autoimmune thyroiditis (AIT) is a common endocrine disease which causes a significantly increased risk of miscarriage. Our recent study has shown that the increased ENO1 autoantibody (ENO1Ab) expression in an experimental AIT mouse model was induced by thyroglobulin (Tg) immunization only. In this study, we explored the potential roles of ENO1Ab in miscarriage occurrence among AIT women, and the specific epitopes of ENO1 targeted by ENO1Ab. A total of 432 euthyroid pregnant participants were selected from the project of Subclinical Hypothyroid during Early Pregnancy, including 48 women with AIT and miscarriage, 96 with miscarriage but no AIT, 96 with AIT but no miscarriage, and 192 without either AIT or miscarriage. The enzyme-linked immunosorbent assay was used to determine the serum levels of total IgG against ENO1 and 18 predicted antigen epitopes of ENO1. The results showed that women with AIT and miscarriage had the highest serum levels of ENO1Ab compared to the other groups. Logistic regression analysis showed that the serum ENO1Ab was an independent risk factor for miscarriage, especially among AIT females. The serum level of total IgG against the predicted epitope peptide 6 (i.e., P6 and aa168-183) of ENO1 was significantly increased in women with AIT and miscarriage when compared with those of both the AIT non-miscarriage group and non-AIT miscarriage group. This pilot study suggests that serum ENO1Ab may have a fair predictive value for AIT-related miscarriage, and the autoantibody specific to P6 epitope may especially be more specifically related to this disorder.

Dietary Supplementation of Aspirin Promotes Drosophila Defense against Viral Infection.

Aspirin, also known as acetylsalicylic acid, is widely consumed as a pain reliever and an anti-inflammatory as well as anti-platelet agent. Recently, our studies using the animal model of Drosophila demonstrated that the dietary supplementation of aspirin renovates age-onset intestinal dysfunction and delays organismal aging. Nevertheless, it remains probable that aspirin plays functional roles in other biological activities, for instance antiviral defense reactions. Intriguingly, we observed that the replications of several types of viruses were drastically antagonized in Drosophila macrophage-like S2 cells with the addition of aspirin. Further in vivo experimental approaches illustrate that adult flies consuming aspirin harbor higher resistances to viral infections with respect to flies without aspirin treatment. Mechanistically, aspirin positively contributes to the Drosophila antiviral defense largely through mediating the STING (stimulator of interferon genes) but not the IMD (immune deficiency) signaling pathway. Collectively, our studies uncover a novel biological function of aspirin in modulating Drosophila antiviral immunity and provide theoretical bases for exploring new antiviral treatments in clinical trials.

Postpartum Levothyroxine Adjustment and Its Impact Factors in Women With Hypothyroidism in Pregnancy.

OBJECTIVE: Women with hypothyroidism need to increase exogenous thyroid hormone levels during pregnancy to reduce adverse outcomes. Few studies have reported the effect of gestational levothyroxine (LT4) variations on postpartum LT4 treatment. METHODS: Women were classified as having subclinical hypothyroidism (SCH) (n = 101), overt hypothyroidism (OH) caused by autoimmune thyroiditis (AIT-OH), OH following thyroidectomy for benign thyroid disease (BA-OH) (n = 66), and OH after surgery for papillary thyroid cancer (PTC-OH) (n = 46). Thyroid function was monitored, and LT4 therapy was adjusted accordingly. RESULTS: After delivery, all women with SCH stopped LT4 treatment, and 57.4% of them restarted LT4 treatment in the following 1 year, independently of the gestational LT4 variations. Among patients with OH, after adjusted by gestational body weight, 49.1% of them had LT4 doses less than the prepregnancy dose (baseline) in late pregnancy, leading to LT4 reduction in postpartum. The LT4 dose was reduced to approximately 50% baseline for women with AIT-OH and BA-OH and reduced by 27% for women with PTC-OH. The reduction reasons for AIT-OH and BA-OH were thyroid-stimulating hormone levels of <2.5 mU/L during pregnancy and postpartum thyrotoxicosis occurrence (39.4%), and for PTC-OH, the reason was thyroid-stimulating hormone overinhibition (<1.0 mU/L) before delivery. CONCLUSION: For patients with SCH, postpartum LT4 treatment could initially be suspended. For women with OH, if the LT4 dose in late pregnancy was less than baseline, a prepregnancy dose reduced by 50%, 50%, and 27% should be applied after delivery for women with AIT-OH, BA-OH, and PTC-OH, respectively.

Reversible Photoswitching between Fluorescence and Room Temperature Phosphorescence by Manipulating Excited State Dynamics in Molecular Aggregates.

Regulation of fluorescence-phosphorescence pathways in organic molecular aggregate remains a challenge due to the complicated singlet-triplet excited state dynamics process. Herein, we demonstrated a successful example (o-BFT) to realize photoreversible fluorescence and room temperature phosphorescence (RTP) switching based on an effective strategy of integrating a phosphor (dibenzofuran) with a photoswitch (dithienylbenzothiophene). o-BFT exhibited dual emission of fluorescence and RTP in both powder and doping polymer film. Notably, the long-lived RTP of o-BFT could be repeatedly erased and restored through reversible photocyclization and decyclization under alternate ultraviolet and visible photoirradiation. In-depth theoretical and spectroscopic investigations revealed that the triplet inactivation was dominated by a photo-controlled triplet-to-singlet Förster resonance energy transfer from light-activated o-BFT to photoisomer c-BFT. Yet, the initial fluorescence could be preserved in this process to afford a photoreversible fluorescence-RTP switching.

Protective effects of N-acetylcysteine on a chemical-induced murine model of asthma.

INTRODUCTION: Oxidative stress is involved in the pathophysiology of inflammatory airway diseases, including asthma. In this study, we elucidated the possible protective effects of the antioxidant N-acetylcysteine (NAC) on a toluene diisocyanate (TDI)-induced murine asthma model. METHODS: Male BALB/c mice were sensitized and challenged with TDI to generate a chemical-induced asthma model. NAC was given intraperitoneally to mice immediately after each TDI challenge. Airway reactivity to methacholine and bronchoalveolar lavage fluid was analyzed. Lungs were examined by histology. RESULTS: NAC treatment dramatically reduced the increased airway hyperresponsiveness, inflammatory infiltration, and goblet cell metaplasia in TDI-exposed mice. Numbers of total cells, neutrophils, and eosinophils in the bronchoalveolar lavage fluid of TDI-challenged mice were significantly higher than vehicle control, but the administration of NAC decreased these inflammatory cell counts. TDI exposure led to significantly increased levels of interleukin 4 (IL-4) and IL-5, which were also suppressed by NAC. In addition, diminished lung reduced oxidized glutathione ratio and superoxide dismutase activity were observed after TDI challenge, and these changes were attenuated by NAC. CONCLUSION: NAC treatment has beneficial effects in TDI-induced asthma.

Correlation between loss of Smad4 and clinical parameters of non-small cell lung cancer: an observational cohort study.

BACKGROUND: SMAD4 has been found to be inactivated to varying degrees in many types of cancer; the purpose of this study was to investigate the correlation between SMAD4 expression in non-small cell lung cancer (NSCLC) and clinical pathological parameters. METHODS: The serum concentration of SMAD4 was measured by enzyme-linked immunosorbent assay and its histological expression was quantified by immunohistochemistry. RESULTS: The serum concentration of Smad4 in patients with NSCLC was lower than that in benign lung disease patients and healthy individuals (P < 0.001) and its concentration was related to the histological classification, pathological differentiation, lymphatic metastasis and clinical stage of NSCLC. The sensitivity and specificity of serum Smad4 were 91.56% and 61.56% for screening NSCLC from healthy individuals and 84.55% and 60.36% for screening NSCLC from patients with benign lung disease. Logistic regression analysis showed that the degree of cell differentiation (P < 0.001), lymph node metastasis (P < 0.001) and clinical stage of NSCLC (P = 0.007) affected the expression of Smad4, and had a strong correlation with the expression of Smad4. The expression of Smad4 in NSCLC tissues was lower than that in normal lung tissues (P = 0.009) and its expression was related to the degree of tissue differentiation, lymph node metastasis and clinical stage (P < 0.05). CONCLUSIONS: The downregulation or deletion of Smad4 is related to the malignant biological behavior of NSCLC and serum Smad4 could be considered as a potential molecular indicator for diagnosis and evaluation of NSCLC.

Efficient framework for predicting MiRNA-disease associations based on improved hybrid collaborative filtering.

BACKGROUND: Accumulating studies indicates that microRNAs (miRNAs) play vital roles in the process of development and progression of many human complex diseases. However, traditional biochemical experimental methods for identifying disease-related miRNAs cost large amount of time, manpower, material and financial resources. METHODS: In this study, we developed a framework named hybrid collaborative filtering for miRNA-disease association prediction (HCFMDA) by integrating heterogeneous data, e.g., miRNA functional similarity, disease semantic similarity, known miRNA-disease association networks, and Gaussian kernel similarity of miRNAs and diseases. To capture the intrinsic interaction patterns embedded in the sparse association matrix, we prioritized the predictive score by fusing three types of information: similar disease associations, similar miRNA associations, and similar disease-miRNA associations. Meanwhile, singular value decomposition was adopted to reduce the impact of noise and accelerate predictive speed. RESULTS: We then validated HCFMDA with leave-one-out cross-validation (LOOCV) and two types of case studies. In the LOOCV, we achieved 0.8379 of AUC (area under the curve). To evaluate the performance of HCFMDA on real diseases, we further implemented the first type of case validation over three important human diseases: Colon Neoplasms, Esophageal Neoplasms and Prostate Neoplasms. As a result, 44, 46 and 44 out of the top 50 predicted disease-related miRNAs were confirmed by experimental evidence. Moreover, the second type of case validation on Breast Neoplasms indicates that HCFMDA could also be applied to predict potential miRNAs towards those diseases without any known associated miRNA. CONCLUSIONS: The satisfactory prediction performance demonstrates that our model could serve as a reliable tool to guide the following research for identifying candidate miRNAs associated with human diseases.

FCGCNMDA: predicting miRNA-disease associations by applying fully connected graph convolutional networks.

Growing evidence indicates that the development and progression of multiple complex diseases are influenced by microRNA (miRNA). Identifying more miRNAs as biomarkers for clinical diagnosis, treatment and prognosis is vital to promote the development of bioinformatics and medicine. Considering that the traditional biological experimental methods are generally time-consuming and expensive, high-efficient computational methods are encouraged to uncover potential disease-related miRNAs. In this paper, FCGCNMDA is presented to predict latent miRNA-disease associations by utilizing fully connected graph convolutional networks. Specially, our method first constructs a fully connected graph in which edge weights represent correlation coefficient between any two pairs of miRNA-disease pair, and then feeds this fully connected graph along with miRNA-disease pairs feature matrix into a two-layer graph convolutional networks (GCN) for training. At last, we utilize the trained network to predict the scores for unknown miRNA-disease pairs. As a result, FCGCNMDA achieves AUC value of [Formula: see text] and AUPRC value of [Formula: see text] in HMDD v2.0 based on five-fold cross validation. Moreover, case studies on Lymphoma, Breast Neoplasms and Prostate Neoplasms shown that 98%, 98%, 98% of the top 50 selected miRNAs were validated by recent experimental evidence. From above results, we can deduce that FCGCNMDA can be regarded as reliable method for potential miRNA-disease associations prediction.

Using discriminative vector machine model with 2DPCA to predict interactions among proteins.

BACKGROUND: The interactions among proteins act as crucial roles in most cellular processes. Despite enormous effort put for identifying protein-protein interactions (PPIs) from a large number of organisms, existing firsthand biological experimental methods are high cost, low efficiency, and high false-positive rate. The application of in silico methods opens new doors for predicting interactions among proteins, and has been attracted a great deal of attention in the last decades. RESULTS: Here we present a novelty computational model with the adoption of our proposed Discriminative Vector Machine (DVM) model and a 2-Dimensional Principal Component Analysis (2DPCA) descriptor to identify candidate PPIs only based on protein sequences. To be more specific, a 2DPCA descriptor is employed to capture discriminative feature information from Position-Specific Scoring Matrix (PSSM) of amino acid sequences by the tool of PSI-BLAST. Then, a robust and powerful DVM classifier is employed to infer PPIs. When applied on both gold benchmark datasets of Yeast and H. pylori, our model obtained mean prediction accuracies as high as of 97.06 and 92.89%, respectively, which demonstrates a noticeable improvement than some state-of-the-art methods. Moreover, we constructed Support Vector Machines (SVM) based predictive model and made comparison it with our model on Human benchmark dataset. In addition, to further demonstrate the predictive reliability of our proposed method, we also carried out extensive experiments for identifying cross-species PPIs on five other species datasets. CONCLUSIONS: All the experimental results indicate that our method is very effective for identifying potential PPIs and could serve as a practical approach to aid bioexperiment in proteomics research.

A Clinical Risk Scoring System of Acute Respiratory Distress Syndrome-Induced Acute Kidney Injury.

BACKGROUND This study investigated the risk factors affecting development and prognosis of acute kidney injury (AKI) in patients with acute respiratory distress syndrome (ARDS). MATERIAL AND METHODS A total of 501 ARDS cases were retrospectively enrolled (296 males and 205 females) admitted to the First People's Hospital of Lianyungang from Aug 2015 to Aug 2017. Multivariable logistic modeling was conducted to select significant variables, and the assigned integer score was proportional to the adjusted odds ratio (OR). Then, the sum of weighted variables was utilized to estimate the score in patients. RESULTS Patients with ARDS who had unconsciousness (OR=2.778, 95% CI: 1.396-5.528), hypertension (OR=1.771, 95% CI: 1.089-2.881), ARDS (moderate-severe) (OR=1.630, 95% CI: 1.027-2.588), AST (OR=2.093, 95% CI: 1.251-3.499), and D-dimer (OR=2.372, 95% CI: 1.316-4.275) were more likely to also have AKI. The score was allocated in proportion to the corresponding adjusted OR, hypertension, ARDS (moderate-severe), aspartate aminotransferase (AST), D-dimer (2 points each), and unconsciousness (3 points). The incidences of AKI in group A (score 0-2, n=9), group B (score 3-4, n=16), group C (score 5-6, n=33), and group D (score ≥7, n=72) were 10.98%, 16.00%, 31.13%, and 49.66%, respectively (P<0.001). Higher scores were associated with higher prevalence of AKI, and the trend was statistically significant (P<0.001). CONCLUSIONS This scoring system may provide a risk-integrative evaluation for AKI in patients with ARDS.

SOX9 Is an Astrocyte-Specific Nuclear Marker in the Adult Brain Outside the Neurogenic Regions.

Astrocytes have in recent years become the focus of intense experimental interest, yet markers for their definitive identification remain both scarce and imperfect. Astrocytes may be recognized as such by their expression of glial fibrillary acidic protein, glutamine synthetase, glutamate transporter 1 (GLT1), aquaporin-4, aldehyde dehydrogenase 1 family member L1, and other proteins. However, these proteins may all be regulated both developmentally and functionally, restricting their utility. To identify a nuclear marker pathognomonic of astrocytic phenotype, we assessed differential RNA expression by FACS-purified adult astrocytes and, on that basis, evaluated the expression of the transcription factor SOX9 in both mouse and human brain. We found that SOX9 is almost exclusively expressed by astrocytes in the adult brain except for ependymal cells and in the neurogenic regions, where SOX9 is also expressed by neural progenitor cells. Transcriptome comparisons of SOX9+ cells with GLT1+ cells showed that the two populations of cells exhibit largely overlapping gene expression. Expression of SOX9 did not decrease during aging and was instead upregulated by reactive astrocytes in a number of settings, including a murine model of amyotrophic lateral sclerosis (SOD1G93A), middle cerebral artery occlusion, and multiple mini-strokes. We quantified the relative number of astrocytes using the isotropic fractionator technique in combination with SOX9 immunolabeling. The analysis showed that SOX9+ astrocytes constitute ∼10-20% of the total cell number in most CNS regions, a smaller fraction of total cell number than previously estimated in the normal adult brain.SIGNIFICANCE STATEMENT Astrocytes are traditionally identified immunohistochemically by antibodies that target cell-specific antigens in the cytosol or plasma membrane. We show here that SOX9 is an astrocyte-specific nuclear marker in all major areas of the CNS outside of the neurogenic regions. Based on SOX9 immunolabeling, we document that astrocytes constitute a smaller fraction of total cell number than previously estimated in the normal adult mouse brain.

Varying precipitation conditions allow directing the composition and physical properties of soy protein concentrates.

Soy protein concentrates (SPCs) are common food ingredients. They typically contain 65% (w/w) protein and ∼30% (w/w) carbohydrate. SPCs can be obtained with various protein precipitation conditions. A systematic study of the impact of these different protein precipitation protocols on the SPC protein composition and physical properties is still lacking. Here, SPCs were prepared via three different protocols, that is, isoelectric (pH 3.5-5.5), aqueous ethanol (50%-70% [v/v]), and Ca2+ ion (5-50 mM) based precipitations, and analyzed for (protein) composition, protein thermal properties, dispersibility, and water-holding capacity. SPCs precipitated at pH 5.5 or by adding 15 mM Ca2+ ions had a lower 7S/11S globulin ratio (∼0.40) than that (∼0.50) of all other SPC samples. Protein in SPCs obtained by isoelectric precipitation denatured at a significantly higher temperature than those in ethanol- or Ca2+ -precipitated SPCs. Precipitation with 50%-60% (v/v) ethanol resulted in pronounced denaturation of 2S albumin and 7S globulin fractions in SPCs. Additionally, increasing the precipitation pH from 3.5 to 5.5 and increasing the Ca2+ ion concentration from 15 to 50 mM caused a strong decrease of both the dispersibility of the protein in SPC and its water-holding capacity at pH 7.0. In conclusion, this study demonstrates that the SPC production process can be directed to obtain ingredients with versatile protein physicochemical properties toward potential food applications. PRACTICAL APPLICATION: This study demonstrates that applying different protein precipitation protocols allows obtaining SPCs that vary widely in (protein) composition and physical properties (such as protein dispersibility and water-holding capacity). These varying traits can greatly influence the suitability of SPCs as functional ingredients for specific applications, such as the production of food foams, emulsions, gels, and plant-based meat alternatives. The generated knowledge may allow targeted production of SPCs for specific applications.

Subclinical hypothyroidism increases insulin resistance in normoglycemic people.

Objective: To investigate the effect of simple subclinical hypothyroidism (SCH) and type 2 diabetes mellitus (T2DM) combined with SCH on insulin resistance. Design and methods: A total of 622 people with newly diagnosed T2DM were selected as the study subjects, and 621 normoglycemic people were selected as control subjects. According to the diagnostic criteria of thyroid diseases, the subjects were divided into a normal thyroid function group and a subclinical hypothyroidism group. Both groups received a physical examination, and blood samples were collected. The measurement indexes included FPG, FINS, OGTT2hPG, OGTT2hINS, HbA1c, TC, TG, HDL-C, LDL-C, TSH, FT3 and FT4. HOMA-IR, HOMA-ß, and TFQI (thyroid feedback quantile index) were calculated. Results: There was no significant difference in age or sex distribution between the T2DM group and the normoglycemic group (P>0.05). The prevalence of thyroid dysfunction in the T2DM group was significantly higher than that in the normoglycemic group (16.39% vs. 11.27%, P<0.05), and among the different types of thyroid dysfunction, the prevalence of SCH was the highest at 14.95% (P<0.05). There was no significant difference in BMI, waist-hip ratio, blood lipid profile, HOMA-ß, and HOMA-IR values between the T2DM with subclinical hypothyroidism group (T2DM+SCH+ group) and the normal thyroid function group (T2DM+SCH- group) (P>0.05). The BMI, waist-hip ratio and HOMA-IR values of the normoglycemic group with subclinical hypothyroidism (T2DM-SCH+ group) were significantly higher than those of the normoglycemic group with normal thyroid function (T2DM-SCH- group) (P<0.05), and there were no significant differences between the T2DM+SCH- and T2DM+SCH+ groups (P>0.05). HOMA-ß values were significantly higher in the T2DM-SCH+ group than in the T2DM-SCH-, T2DM+SCH- and T2DM+SCH+ groups (P<0.05). As the TFQI value increased, the body weight, waist-hip ratio, diastolic blood pressure, FPG, OGTT2hPG and HbA1c values gradually increased in the T2DM group and normoglycemic group (P<0.05). HDL-C, FINS, OGTT2hINS and HOMA-ß values gradually decreased (P<0.05). Conclusion: Subclinical hypothyroidism only increases insulin resistance in normoglycemic people. As the sensitivity of the central thyroid decreases, the risk of developing diabetes increases.

High-contrast reversible multiple color-tunable solid luminescent ionic polymers for dynamic multilevel anti-counterfeiting.

Dynamic color-tunable luminescent materials, which possess huge potential applications in advanced multilevel luminescence anti-counterfeiting, are of considerable interest. However, it remains challenging to develop simple high-contrast reversible multiple (triple or more than triple) color-tunable high-efficiency solid luminescent materials with low cost, facile synthesis, and good processability. Herein, by simply grafting charged multi-color AIEgen-based chromophores into polymers, a series of high-efficiency multiple color-tunable luminescent single ionic polymers are constructed through tuning feed ratios, counter anions and reaction solvents. Remarkably, some ionic polymers can not only achieve rare high-contrast reversible multiple color-tunable emission in solid states in response to different solvent stimuli, but also could realize excitation-dependent color-tunable emission. To the best of our knowledge, such charming multiple (triple or more than triple) color-tunable solid polymers responding to multiple external stimuli are still rare. Based on comparative studies of emission spectra, excitation spectra and fluorescence lifetimes before and after swelling, it could be inferred that solvent stimuli could induce microstructure changes of these ionic polymers and then change the aggregated-states of their corresponding AIE-active emission centers. Moreover, the different solvent stimuli could induce to produce different degrees of microstructure changes, resulting in their unique multiple color-tunable emission. More significantly, these smart color-tunable ionic polymers show great promise for applications in dynamic multilevel (three-level or even more than three-level) anti-counterfeiting.

Prevalence and risk factors of hypothyroidism after universal salt iodisation: a large cross-sectional study from 31 provinces of China.

OBJECTIVES: To investigate the prevalence and risk factors of hypothyroidism after universal salt iodisation for 20 years in mainland China. DESIGN: Nationwide, cross-sectional survey. SETTING AND PARTICIPANTS: The Thyroid Disorders, Iodine Status and Diabetes epidemiological study included adults from 31 provinces of China. Data included demographic, physical characteristics, urine, serum thyroid-stimulating hormone (TSH), thyroid-peroxidase antibody (TPOAb), thyroglobulin antibody (TgAb) and thyroid ultrasonography. Subclinical hypothyroidism (SCH) was classified into severe SCH (TSH >10 mU/L) and mild SCH (TSH 4.2-9.9 mU/L). A total of 78 470 (38 182 men and 40 288 women) participants were included in the final analysis. RESULTS: The prevalence of hypothyroidism was 13.95%. The prevalence rates of overt hypothyroidism (OH) and SCH were 1.02% and 13.93%, which mild SCH was significantly higher than severe SCH (12.18% vs 0.75%). Prevalence was higher in women than in men, and this gender difference was noted among all age groups. The prevalence of mild SCH, severe SCH and OH increases by 1.16%, 1.40% and 1.29% for every 10 years older. TPOAb or/and TgAb positive were significantly associated with OH and severe SCH (OR 15.9, p<0.001). However, SCH was positively correlated with increased urine iodine concentration, but this correlation was only in antibody-negative female patients. In non-autoimmune and male populations, there was a U-shaped relationship between severe SCH and OH and urine iodine concentration. CONCLUSIONS: Mild SCH is the most common form of hypothyroidism, which is related to iodine intake. Severe SCH is more similar to OH which autoimmune is the main cause. The various effects of iodine on hypothyroidism depend on thyroid autoimmune and gender.

LncRNA UCA1 Participates in De Novo Synthesis of Guanine Nucleotides in Bladder Cancer by Recruiting TWIST1 to Increase IMPDH1/2.

Metabolic dysregulation has been identified as one of the hallmarks of cancer biology. Based on metabolic heterogeneity between bladder cancer tissues and adjacent tissues, we discovered several potential driving factors for the bladder cancer occurrence and development. Metabolic genomics showed purine metabolism pathway was mainly accumulated in bladder cancer. Long noncoding RNA urothelial carcinoma-associated 1 (LncRNA UCA1) is a potential tumor biomarker for bladder cancer diagnosis and prognosis, and it increases bladder cancer cell proliferation, migration, and invasion via the glycolysis pathway. However, whether UCA1 plays a role in purine metabolism in bladder cancer is unknown. Our findings showed that UCA1 could increase the transcription activity of guanine nucleotide de novo synthesis rate limiting enzyme inosine monophosphate dehydrogenase 1 (IMPDH1) and inosine monophosphate dehydrogenase 2 (IMPDH2), triggering in guanine nucleotide metabolic reprogramming. This process was achieved by UCA1 recruiting the transcription factor TWIST1 which binds to the IMPDH1and IMPDH2 promoter region. Increased guanine nucleotide synthesis pathway products stimulate RNA polymerase-dependent production of pre-ribosomal RNA and GTPase activity in bladder cancer cells, hence increasing bladder cancer cell proliferation, migration, and invasion. We have demonstrated that UCA1 regulates IMPDH1/2-mediated guanine nucleotide production via TWIST1, providing additional evidence of metabolic reprogramming.