Screening of active components of Ganoderma lucidum and decipher its molecular mechanism to improve learning and memory disorders.

Learning and memory impairment (LMI), a common degenerative central nervous system disease. Recently, more and more studies have shown that Ganoderma lucidum (GL) can improve the symptoms of LMI. The active ingredients in GL and their corresponding targets were screened through TCMSP (Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform) and BATMAN-TCM (Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine) databases, and the potential LMI targets were searched for through GeneCard (GeneCards Human Gene Database) and DrugBank. Then, we construct a "main active ingredient-target" network and a protein-protein interaction (PPI) network diagram.The GO (Gene Ontology) functional enrichment analysis and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway annotation analysis were performed on the common targets through DAVID (Database for Annotation Visualization and Integrated Discovery) to clarify the potential molecular mechanism of action of active ingredients in GL. The TNF protein was verified by western blot;Twenty one active ingredients in GL and 142 corresponding targets  were screened out, including 59 targets shared with LMI. The 448 biological processes shown by the GO functional annotation results and 55 signal pathways shown by KEGG enrichment analysis were related to the improvement of LMI by GL, among which the correlation of Alzheimer disease pathway is the highest, and TNF was the most important protein; TNF can improve LMI.GL can improve LMI mainly by 10 active ingredients in it, and they may play a role by regulating Alzheimer disease pathway and TNF protein.

Swarm intelligence based deep learning model via improved whale optimization algorithm and Bi-directional long short-term memory for fault diagnosis of chemical processes.

The chemical production process typically possesses complexity and high risks. Effective fault diagnosis is a key technology for ensuring the reliability and safety of chemical production processes. In this study, a comprehensive fault diagnosis method based on time-varying filtering empirical mode decomposition (TVF-EMD), kernel principal component analysis (KPCA), and an improved whale optimization algorithm (WOA) to optimize bi-directional long short-term memory (BiLSTM) is proposed. This research utilizes TVF-EMD and KPCA to analyze and preprocess the raw data, eliminating noise and and reducing the dimensions of the fault data. Subsequently, BiLSTM is employed for fault data classification. To address the hyperparameters within BiLSTM, the enhanced WOA is used for optimization. Finally, the efficacy and superiority of this approach are validated through two fault diagnosis examples.

Screening for diagnostic targets in tuberculosis and study on its pathogenic mechanism based on mRNA sequencing technology and miRNA-mRNA-pathway regulatory network.

Purpose: Tuberculosis is common infectious diseases, characterized by infectivity, concealment and chronicity, and the early diagnosis is helpful to block the spread of tuberculosis and reduce the resistance of Mycobacterium tuberculosis to anti-tuberculosis drugs. At present, there are obvious limitations in the application of clinical detection methods used for the early diagnosis of tuberculosis. RNA sequencing (RNA-Seq) has become an economical and accurate gene sequencing method for quantifying transcripts and detecting unknown RNA species. Methods: A peripheral blood mRNA sequencing was used to screen the differentially expressed genes between healthy people and tuberculosis patients. A protein-protein interaction (PPI) network of differentially expressed genes was constructed through Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The potential diagnostic targets of tuberculosis were screened by the calculation of degree, betweenness and closeness in Cytoscape 3.9.1 software. Finally, the functional pathways and the molecular mechanism of tuberculosis were clarified in combination of the prediction results of key gene miRNAs, and by Gene Ontology (GO) enrichment analysis and the Kyoto Encyclopedia Genes and Genomes (KEGG) pathway annotation analysis. Results: 556 Differential genes of tuberculosis were screened out by mRNA sequencing. Six key genes (AKT1, TP53, EGF, ARF1, CD274 and PRKCZ) were screened as the potential diagnostic targets for tuberculosis by analyzing the PPI regulatory network and using three algorithms. Three pathways related to the pathogenesis of tuberculosis were identified by KEGG pathway analysis, and two key miRNAs (has-miR-150-5p and has-miR-25-3p) that might participate in the pathogenesis of tuberculosis were screened out by constructing a miRNA-mRNA pathway regulatory network. Conclusion: Six key genes and two important miRNAs that could regulate them were screened out by mRNA sequencing. The 6 key genes and 2 important miRNAs may participate in the pathogenesis of infection and invasion of Mycobacterium tuberculosis through herpes simplex virus 1 infection, endocytosis and B cell receptor signaling pathways.

Comparison of the efficacy of expandable interbody fusion cage (EXP-IFC) and non-expandable interbody fusion cage (NE-IFC) in MIS-TLIF for lumbar degenerative diseases: A systematic retrospective study on 62 patients.

Objectives: To investigate the clinical and radiographic outcomes of EXP-IFC in single-level MIS-TLIF. Methods: This study included patients aged ≥18 years who received a single-level MIS-TLIF procedure with at least 1 year of follow-up. Outcome measures: clinical features, preoperative and neurological complications. Imaging analysis included disc height (DH) restoration, surgical and contralateral side foraminal height (FH), lumbar lordosis angle (LL), segmental lordosis (SL). Visual analog scale (VAS) score for low back pain (VAS-LBP) and leg pain (VAS-LP), Oswestry Disability Index (ODI) and Japanese Orthopaedic Association (JOA) score were used to evaluate clinical outcomes. Statistical analysis was performed using independent sample t-test and sample t-test. The significance was set to p < 0.05 in univariate analysis. Results: A total of 62 patients undergoing single level MIS-TLIFs between January 2017 and January 2019 were included, with 32 NE-IFC 46.9% female, mean age 54.86 ± 11.65, mean body mass index (BMI) 24.59 ± 3.63) and 30 EXP (40% female, mean age 58.32 ± 12.99, mean BMI 24.45 ± 2.76) with no significant differences in demographics. There were no significant differences between two groups in Operative time (OT), Estimated blood loss (EBL) and Length of stay (LOS). No significant differences were found in VAS-LBP, VAS-LP, JOA and ODI in post-operation and the last follow-up between the two groups. The imaging outcome demonstrated that the mean increase in DH was significantly greater for the patients with EXP-IFC than those with NE-IFC group at 1 year follow-up (8.92 ± 0.51 mm EXP-IFC vs. 7.96 ± 0.96 mm NE-IFC, p < 0.001). The mean change in FH of operative and contralateral sides were observed to be significantly higher for the patients with EXP-IFC at 1 year follow-up (operative side:17.67 ± 2.29 mm EXP-IFC vs. 16.01 ± 2.73 mm NE-IFC, p = 0.042; contralateral side:17.32 ± 2.26 mm EXP-IFC vs. 16.10 ± 2.32 mm NE-IFC, p < 0.001), but changes in LL and SL were not significantly different. At the last follow-up, we did not find any significant difference in the fusion rate between the two groups. Conclusion: Our results indicated that there may be no significant difference in short-term clinical outcomes between EXP-IFC and NE-IFC, but the use of EXP-IFC in MIS-TLIF can provide a significant restoration of disc height, and neural foraminal height compared to NE-IFC.

A multi-scale evolutionary deep learning model based on CEEMDAN, improved whale optimization algorithm, regularized extreme learning machine and LSTM for AQI prediction.

With the rapid development of economy, air pollution occurs frequently, which has a huge negative impact on human health and urban ecosystem. Air quality index (AQI) can directly reflect the degree of air pollution. Accurate AQI trend prediction can provide reliable information for the prevention and control of air pollution, but traditional forecasting methods have limited performance. To this end, a dual-scale ensemble learning framework is proposed for the complex AQI time series prediction. First, complete ensemble empirical mode decomposition adaptive noise (CEEMDAN) and sample entropy (SE) are used to decompose and reconstruct AQI series to reduce the difficulty of direct modeling. Then, according to the characteristics of high and low frequencies, the high-frequency components are predicted by the long short-term memory neural network (LSTM), and the low-frequency items are predicted by the regularized extreme learning machine (RELM). At the same time, the improved whale optimization algorithm (WOA) is used to optimize the hyper-parameters of RELM and LSTM models. Finally, the hybrid prediction model proposed in this paper predicts the AQI of four cities in China. This work effectively improves the prediction accuracy of AQI, which is of great significance to the sustainable development of the cities.

Residual based attention-Unet combing DAC and RMP modules for automatic liver tumor segmentation in CT.

Purpose: Due to the complex distribution of liver tumors in the abdomen, the accuracy of liver tumor segmentation cannot meet the needs of clinical assistance yet. This paper aims to propose a new end-to-end network to improve the segmentation accuracy of liver tumors from CT. Method: We proposed a hybrid network, leveraging the residual block, the context encoder (CE), and the Attention-Unet, called ResCEAttUnet. The CE comprises a dense atrous convolution (DAC) module and a residual multi-kernel pooling (RMP) module. The DAC module ensures the network derives high-level semantic information and minimizes detailed information loss. The RMP module improves the ability of the network to extract multi-scale features. Moreover, a hybrid loss function based on cross-entropy and Tversky loss function is employed to distribute the weights of the two-loss parts through training iterations. Results: We evaluated the proposed method in LiTS17 and 3DIRCADb databases. It significantly improved the segmentation accuracy compared to state-of-the-art methods. Conclusions: Experimental results demonstrate the satisfying effects of the proposed method through both quantitative and qualitative analyses, thus proving a promising tool in liver tumor segmentation.

An improved residual U-Net with morphological-based loss function for automatic liver segmentation in computed tomography.

This paper proposes an improved ResU-Net framework for automatic liver CT segmentation. By employing a new loss function and data augmentation strategy, the accuracy of liver segmentation is improved, and the performance is verified on two public datasets LiTS17 and SLiver07. Firstly, to speed up the convergence of the model, the residual module is used to replace the original convolution module of U-Net. Secondly, to suppress the problem of pixel imbalance, the opposite number of Dice is proposed to replace the cross-entropy loss function, and the morphological method is introduced to weigh the pixels. Finally, to improve the generalization ability of the model, random affine transformation and random elastic deformation are employed for data augmentation. From 20 training datasets of Sliver07, 16 sets were selected as the training set, two sets were used for verification, and two sets were used for the test; meanwhile, from 131 training datasets of LiTS2017, eight sets were selected as the test set. In the experiment, four evaluation metrics, including DICE global, DICE per case, VOE, and RVD, were calculated, with the accuracies of 94.28, 94.24 ± 2.07, 10.83 ± 3.70, and -0.25 ± 2.74, respectively. Compared with U-Net and ResU-Net, the performance of the proposed method is significantly improved. The experimental results show that, although the method's complexity is high, it has a faster convergence speed and stronger generalization ability. The segmentation effect on the 2D image is significantly improved, and the scalability on 3D data is also robust. In addition, the proposed method performs well in the case of low-contrast neighboring organs, which proves the robustness of the proposed method.

VSHR: A Mathematical Model for the Prediction of Second-Wave COVID-19 Epidemics in Malaysia.

Since December 2019, a novel coronavirus (COVID-19) has spread all over the world, causing unpredictable economic losses and public fear. Although vaccines against this virus have been developed and administered for months, many countries still suffer from secondary COVID-19 infections, including the United Kingdom, France, and Malaysia. Observations of COVID-19 infections in the United Kingdom and France and their governance measures showed a certain number of similarities. A further investigation of these countries' COVID-19 transmission patterns suggested that when a turning point appeared, the values of their stringency indices per population density (PSI) were nearly proportional to their absolute infection rate (AIR). To justify our assumptions, we developed a mathematical model named VSHR to predict the COVID-19 turning point for Malaysia. VSHR was first trained on 30-day infection records prior to the United Kingdom, Germany, France, and Belgium's known turning points. It was then transferred to Malaysian COVID-19 data to predict this nation's turning point. Given the estimated AIR parameter values in 5 days, we were now able to locate the turning point's appearance on June 2nd, 2021. VSHR offered two improvements: (1) gathered countries into groups based on their SI patterns and (2) generated a model to identify the turning point for a target country within 5 days with 90% CI. Our research on COVID-19's turning point for a country is beneficial for governments and clinical systems against future COVID-19 infections.

Evaluation of iodine nutritional status during pregnancy by estimated 24-h urinary iodine excretion: population variation range and individual accuracy.

OBJECTIVE: To explore the accuracy of estimated 24-h urinary iodine excretion (24-h UIEest) in assessing iodine nutritional status. DESIGN: Fasting venous blood, 24-h and spot urine samples were collected during the day. The urinary iodine concentration (UIC) and urinary creatinine concentration (UCrC) were measured, and the urinary iodine-to-creatinine ratio (UI/Cr), 24-h UIEest, and 24-h urinary iodine excretion (24-h UIE) were calculated. At the population level, correlation and consistency between UIC, UI/Cr, 24-h UIEest and 24-h UIE were assessed using correlation analysis and Bland-Altman plots. At the individual level, receiver operating characteristic (ROC) curves were used to analyse the accuracy of the above indicators for evaluating insufficient and excessive iodine intake. The reference interval of 24-h UIEest was established based on percentile values. SETTING: Indicator can accurately evaluate individual iodine nutrition during pregnancy remains controversial. PARTICIPANTS: Pregnant women (n 788). RESULTS: Using 24-h UIE as standard, the correlation coefficients of 24-h UIEest from different periods of the day ranged from 0·409 to 0·531, and the relative average differences ranged from 4·4 % to 10·9 %. For diagnosis of insufficient iodine intake, the area under the ROC curve of 24-h UIEest was 0·754, sensitivity and specificity were 79·6 % and 65·4 %, respectively. For diagnosis of excessive iodine intake, the area of 24-h UIEest was 0·771, sensitivity and specificity were 66·7 % and 82·0 %, respectively. The reference interval of 24-h UIEest was 58·43-597·65 µg. CONCLUSIONS: Twenty-four-hour UIEest can better indicate iodine nutritional status at a relatively large sample size in a given population of pregnant women. It can be used for early screening at the individual level to obtain more lead time for pregnant women.

24 h urinary creatinine excretion during pregnancy and its application in appropriate estimation of 24 h urinary iodine excretion.

BACKGROUND: Urinary creatinine can be used to adjust urinary iodine to evaluate iodine nutritional status during pregnancy. However, the reference intervals and impact factors of urinary creatinine are unknown. METHODS: 24 h urine creatinine concentration (24 hUCr) and spot UCr at four different time periods of the day of pregnant women from Part 1 (n = 743) were measured. Linear regression analysis was performed to identify the impact factors of 24 h urinary creatinine excretion (24 hUCrE) and obtain the estimated 24 h urinary creatinine excretion (24 hUCrEest). Then measured urinary iodine concentration (UIC) of 24 h and at fasting of pregnant women from Part 2 (n = 325), used spot urinary iodine to creatinine concentration ratio (UIC/UCr) and 24 hUCrEest to calculate the estimated 24 h urinary iodine excretion (24 hUIEest), finally checked the consistency and correlation of 24 hUIEest and 24 h urinary iodine excretion (24 hUIE). RESULTS: In Part 1, the median 24 hUCrE was 1.24(IQR0.98-1.76)g, and the reference interval was 0.61-2.93 g. The median 24 hUCr was 0.76 (IQR0.57-1.01)g/L, and the reference interval was 0.36-1.88 g/L. Multiple linear regression results showed that pregnancy weight was an influencing factor to 24 hUCrE after adjusting by gestational weeks, age, pre-pregnancy BMI, and percentage of body fat (F = 45.029, p＜0.001). In Part 2, there was no statistically significant difference between 24 hUIEest and 24 hUIE (Z =-0.767, p = 0.443). Using 24hUIE as the gold standard, the relative average difference in 24hUIEest was 4.2 %, the relative average differences for UIC and UIC/UCr were 32.4 % and 37.2 %. The reference interval of 24 hUIE and 24 hUIEest were 88.43-585.90 µg and 50.97-700.39 µg, respectively. CONCLUSIONS: The reference intervals of 24 hUCrE, spot UCr, 24 hUIE, and 24 hUIEest during pregnancy were established. 24 hUCrE has important application value in iodine nutrition evaluation to gain more lead time for pregnant women with iodine nutrition-related diseases.

Maduramicin induces cardiotoxicity via Rac1 signaling-independent methuosis in H9c2 cells.

Maduramicin frequently induces severe cardiotoxicity in target and nontarget animals in clinic. Apoptotic and non-apoptotic cell death mediate its cardiotoxicity; however, the underlying non-apoptotic cell death induced by maduramicin remains unclear. In current study, a recently described non-apoptotic cell death "methuosis" caused by maduramicin was defined in mammalian cells. Rat myocardial cell H9c2 was used as an in vitro model, showing excessively cytoplasmic vacuolization upon maduramicin (0.0625-5 µg/mL) exposure for 24 h. Maduramicin-induced reversible cytoplasmic vacuolization of H9c2 cells in a time- and concentration-dependent manner. The vacuoles induced by maduramicin were phase lucent with single membrane and were not derived from the swelling of organelles such as mitochondria, endoplasmic reticulum, lysosome, and Golgi apparatus. Furthermore, maduramicin-induced cytoplasmic vacuoles are generated from micropinocytosis, which was demonstrated by internalization of extracellular fluid-phase marker Dextran-Alexa Fluor 488 into H9c2 cells. Intriguingly, these cytoplasmic vacuoles acquired some characteristics of late endosomes and lysosomes rather than early endosomes and autophagosomes. Vacuolar H+ -ATPase inhibitor bafilomycin A1 efficiently prevented the generation of cytoplasmic vacuoles and decreased the cytotoxicity of H9c2 cells triggered by maduramicin. Mechanism studying indicated that maduramicin activated H-Ras-Rac1 signaling pathway at both mRNA and protein levels. However, the pharmacological inhibition and siRNA knockdown of Rac1 rescued maduramicin-induced cytotoxicity of H9c2 cells but did not alleviate cytoplasmic vacuolization. Based on these findings, maduramicin induces methuosis in H9c2 cells via Rac-1 signaling-independent seriously cytoplasmic vacuolization.

Encapsulating Halofuginone Hydrobromide in TPGS Polymeric Micelles Enhances Efficacy Against Triple-Negative Breast Cancer Cells.

BACKGROUND: Halofuginone hydrobromide (HF) is a synthetic analogue of the naturally occurring quinazolinone alkaloid febrifugine, which has potential therapeutic effects against breast cancer, however, its poor water solubility greatly limits its pharmaceutical application. D-α-tocopherol polyethylene glycol 1000 succinate (TPGS) is a water-soluble derivative of vitamin E, which can self-assemble to form polymeric micelles (PMs) for encapsulating insoluble anti-tumor drugs, thereby effectively enhancing their anti-cancer effects. METHODS: HF-loaded TPGS PMs (HTPMs) were manufactured using a thin-film hydration technique, followed by a series of characterizations, including the hydrodynamic diameter (HD), zeta potential (ZP), stability, drug loading (DL), encapsulation efficiency (EE), and in vitro drug release. The anti-cancer effects and potential mechanism of HTPMs were investigated in the breast cell lines MDA-MB-231 and MCF-7, and normal breast epithelial cell line Eph-ev. The breast cancer-bearing BALB/c nude mouse model was successfully established by subcutaneous injection of MDA-MB-231 cells and used to evaluate the in vivo therapeutic effect and safety of the HTPMs. RESULTS: The optimized HTPMs had an HD of 17.8±0.5 nm and ZP of 14.40±0.1 mV. These PMs exhibited DL of 12.94 ± 0.46% and EE of 90.6 ± 0.85%, along with excellent storage stability, dilution tolerance and sustained drug release in pH-dependent manner within 24 h compared to free HF. Additionally, the HTPMs had stronger inhibitory effects than free HF and paclitaxel against MDA-MB-231 triple-negative breast cancer cells, and little toxicity in normal breast epithelial Eph-ev cells. The HTPMs induced cell cycle arrest and apoptosis of MDA-MB-231 by disrupting the mitochondrial membrane potential and enhancing reactive oxygen species formation. Evaluation of in vivo anti-tumor efficacy demonstrated that HTPMs exerted a stronger tumor inhibition rate (68.17%) than free HF, and exhibited excellent biocompatibility. CONCLUSION: The findings from this study indicate that HTPMs holds great clinical potential for treating triple-negative breast cancer.

Iodine Nutrition and the Prevalence Status of Thyroid Nodules in the Population: a Cross-sectional Survey in Heilongjiang Province, China.

The aim of this study was to determine the iodine nutritional status and the epidemiological characteristics of thyroid nodules (TNs) in the adult population of Heilongjiang Province. From December 2017 to December 2018, a total of 3661 adults aged 20-70 years were selected through probability proportional to size (PPS) sampling for a cross-sectional survey. During the field epidemiological investigation, each participant received a questionnaire survey and thyroid ultrasonography examination. The iodine concentrations in casual urine specimens and household edible salt were measured. The household coverage of iodized salt was 86.56%. The median urinary iodine concentration (MUIC) in the adult population in Heilongjiang Province was 161.57 µg/L (25th-75th percentile: 100.35-245.15 µg/L). The prevalence of TNs was 36.88%, and the prevalence in females was significantly higher than that in males (41.25% vs 32.50%, χ2 = 11.841, P < 0.01). The prevalence of TNs increased with age (χ2trend = 49.80, P < 0.001). The prevalence of multiple TNs increased with age (χ2trend = 48.709, P < 0.001). There was no significant difference in the MUIC between healthy control group and those with TNs (Z = - 1.386, P = 0.166). The female, age (40-49 age group, 50-59 age group, 60-70 age group), BMI (obesity, overweight), history of hypertension, history of diabetes, and smoking history were all independent risk factors that affected the occurrence of TNs. The iodine nutritional status of the adult population in Heilongjiang Province was adequate. The prevalence of TNs was higher in middle-aged and elderly women, so these individuals should be the focus of the prevention and treatment of thyroid nodule disease.

Ionophore Toxin Maduramicin Produces Haff Disease-Like Rhabdomyolysis in a Mouse Model.

Maduramicin is a toxic ionophore antibiotic that is isolated from Streptomyces, frequently occurring in an aquatic environment. To understand the potential role of maduramicin in crayfish consumption related Haff disease, a mouse model was established in this study. Two exposure routes of maduramicin in the abdominal muscle and the hepatopancreas tissue homogenates of crayfish were given intragastrically to mice in different doses for seven days. Action changes, clinical symptoms, feed consumption, body weight, blood biochemistry, and histopathology examination of mice were observed and analyzed. In the natural exposure group, relatively low concentration of maduramicin in crayfish muscle and hepatopancreas had no obvious effects on mental state, body weight, blood biochemical indexes, or histologic appearance. However, in the artificial exposure group, with increasing concentrations, maduramicin in crayfish muscle and hepatopancreas homogenates both induced mental sluggishness and weight loss of mice. Blood biochemical examination showed that 3.5 mg·kg-1 and 7 mg·kg-1 maduramicin in crayfish tissue homogenates significantly increased levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), blood urea nitrogen (BUN), lactate dehydrogenase (LDH), and creatine kinase (CK). Additionally, histopathological examination showed that multiple organs were damaged by maduramicin, including degeneration of liver cells, shedding of renal epithelial cells, and disturbance and partial lysis of myocardial and skeletal muscle filaments in the mice. In summary, maduramicin may not cause Haff disease through contamination of the aquatic environment under normal conditions. Maduramicin can be used as a potential toxin tool to establish a rhabdomyolysis disease animal model for drug development.

Maduramicin triggers methuosis-like cell death in primary chicken myocardial cells.

Maduramicin frequently induces severe cardiotoxicity in broiler chickens as well as in humans who consume maduramicin accidentally. Apoptosis and non-apoptotic cell death occur concurrently in the process of maduramicin-induced cardiotoxicity; however, the underlying mechanism of non-apoptotic cell death is largely unknown. Here, we report the relationship between maduramicin-caused cytoplasmic vacuolization and methuosis-like cell death as well as the underlying mechanism in primary chicken myocardial cells. Maduramicin induced a significant increase of cytoplasmic vacuoles with a degree of cell specificity in primary chicken embryo fibroblasts and chicken hepatoma cells (LMH), along with a decrease of ATP and an increase of LDH. The accumulated vacuoles were partly derived from cellular endocytosis rather than the swelling of endoplasm reticulum, lysosomes, and mitochondria. Moreover, the broad-spectrum caspase inhibitor carbobenzoxy-Val-Ala-Asp-fluoromethylketone (z-VAD-fmk) did not prevent maduramicin-induced cytoplasmic vacuolization. DNA ladder and cleavage of PARP were not observed in chicken myocardial cells during maduramicin exposure. Pretreatment with 3-methyladenine (3-MA) and cholorquine (CQ) of chicken myocardial cells did not attenuate cytoplasmic vacuolization and cytotoxicity, although LC3 and p62 were activated. Bafilomycin A1 almost completely prevented the generation of cytoplasmic vacuoles and significantly attenuated cytotoxicity induced by maduramicin, along with downregulation of K-Ras and upregulation of Rac1. Taken together, "methuosis" due to excessive cytoplasmic vacuolization mediates the cardiotoxicity of maduramicin. This provides new insights for understanding a nonclassical form of cell death in the field of drug-induced cytotoxicity.

Determination of Reference Intervals of Ratios of Concentrations of Urinary Iodine to Creatinine and Thyroid Hormone Concentrations in Pregnant Women Consuming Adequate Iodine in Harbin, Heilongjiang Province.

The objectives of this study were to explore reference intervals of ratios of concentrations of urinary iodine to creatinine (UIC/UCr) in pregnant women, to determine specific reference intervals for thyroid hormone concentrations (FT3, FT4, TSH) in the first trimester of pregnancy, and provide a comprehensive evaluation of iodine nutritional status and thyroid function. Cross-sectional data analysis, including questionnaires and thyroid ultrasonograms, were used to exclude subjects who had a history of thyroid disease, a family history of thyroid disease, or thyroid morphological abnormalities. Tests of thyroid hormone were evaluated together with urinary iodine concentration (UIC), urinary creatinine concentration (UCr), and salt iodine concentration in pregnant women. For the sample of pregnant women eligible for inclusion, the 95% reference intervals of the bilateral limits of UIC/UCr and thyroid hormone concentrations in pregnant women were determined by the percentile method. Pregnant women were recruited in Harbin, Heilongjiang Province, a particular geographical area of China, where iodine nutrition is adequate. The median UIC was 141.47 µg/L, while the median UIC/UCr was 141.12 µg/g. The reference intervals of thyroid hormone concentrations in the first trimester were FT3 3.63-6.12 pmol/L, FT4 11.89-22.91 pmol/L, and TSH 0.013-3.814 mIU/L. The reference intervals of UIC/UCr were 52.47 to 532.09 µg/g (first trimester 47.25-353.91 µg/g, second trimester 57.95-639.08 µg/g, third trimester 46.98-494.73 µg/g).The established UIC/UCr medical reference intervals and thyroid hormone concentration reference intervals may be used for iodine nutritional assessment and thyroid disease screening in pregnant women.

Prediction of water positions in the binding sites of proteins based on collections of multi-source heterogeneous atoms.

Water molecules play an important role in mediating the interactions between proteins and ligands. However, it is difficult to distinguish the key water molecules directly because they are widely and irregularly distributed. Based on the results of statistical analysis, a composite tetrahedral model is proposed to predict the potential hydration sites in the binding sites of crystal structures. By analyzing the different protein atoms and ligand atoms that interact with water molecules, the unified representation and measurement of these multi-source heterogeneous atoms in the multi-dimensional feature space were adopted. The potential hydration sites could be predicted based on the results of the preference analysis and the shape-matching method. A test set was used to evaluate the model performance and extensive comparison with the tetrahedral-water-cluster model and Dowser++ revealed that the composite tetrahedral model can not only predict the potential sites of multiple key water molecules in the binding sites but also has a better prediction accuracy.

Formation of high crystalline LDH sludge for removing Cu and Zn from wastewater by controlled double-jet precipitation.

In order to improve the heavy metal wastewater treatment by avoiding formation of amorphous sludge phase, we develop a faster formation of high crystalline layered double hydroxide (LDH) sludge to remove Cu and Zn from wastewater by controlled double-jet precipitation (CDJP) without hydrothermal or heat aging post-treatment. A series of experimental procedures are conducted to determine the optimal parameters. Results show that the optimal adding rate, pH value, and stirring rate is 0.5 mL min-1, 9.0, and 500 rpm, respectively. The CuZnAl-LDH phase sludge is formed in a well-crystallized hexagonal platelet, which assembled into a flower-like architecture. Comparative studies show that the formation of amorphous LDH sludge in conventional precipitation (CP) could be divided roughly into two stages-from the mixed copper hydroxide, zinc hydroxide, and scarbroite to the mixed low crystallinity CuAl-LDH and ZnAl-LDH. However, in CDJP method, the high crystalline LDH sludge evolved from a new four-step evolution process that is the formation of an amorphous (quasi-)multinary metastable ternary CuZnAl-LDH phase, followed by the indiffusion of cations and substitution of anions to fabricate crystalline LDH, the integrated LDH hexagonal platelets assembled into a flower-like architecture by the screw dislocation growth mechanism, the coarsening growth of each ternary LDH platelet, respectively. Thereinto, the formation of (quasi-)multinary metastable LDH phase instead of metal hydroxide in initial stage would be an obvious advantage of the CDJP method compared to CP method due to the former skipping the sequential precipitation.