Profiles of HBcrAg and pgRNA in Pregnant Women With Chronic HBV Under Different Disease Phases and Antiviral Prophylaxis.

Background: Pregnant women with chronic hepatitis B (CHB) exhibit unique clinical features in terms of postpartum immune system reconstitution and recovery from pregnancy-related changes. However, current studies focus primarily on the outcomes of maternal-infant transmission and postpartum hepatitis flares. We aimed to evaluate the profiles of hepatitis B core-related antigen (HBcrAg) and pregenomic RNA (pgRNA) in pregnant women with CHB. Methods: This retrospective analysis included treatment-naïve pregnant women with CHB who were followed up regularly in an outpatient clinic from 2014 to 2021. Baseline HBcrAg and pgRNA levels were compared in patients with different disease phases. Changes in these parameters were examined in a subset of patients receiving antiviral prophylaxis. HBcrAg and pgRNA levels were measured before treatment, at 32 weeks of gestation, and postpartum. Results: The final analysis included a total of 121 patients, 100 of whom were hepatitis B e antigen (HBeAg)-positive (96 and 4 in the immune-tolerant and -indeterminate phases, respectively) and 21 of whom were HBeAg-negative (6 and 15 in the immune-active and -inactive carrier phases, respectively). The HBeAg-negative group vs the HBeAg-positive group had lower levels of baseline HBcrAg (median [interquartile range {IQR}], 3.7 [3.0-5.9] vs 8.6 [8.4-8.7] log10 U/mL; P < .01) and pgRNA (median [IQR], 0.0 [0.0-2.5] vs 7.8 [7.6-8.1] log10 copies/mL; P < .01). The serum levels of HBcrAg and pgRNA were highest in immune-tolerant carriers and lowest in immune-inactive carriers. In HBeAg-positive patients, the correlation coefficients of HBcrAg and pgRNA with hepatitis B virus (HBV) DNA were 0.40 and 0.43, respectively; in HBeAg-negative patients, they were 0.53 and 0.51, respectively (all P < .05). The correlation coefficients with hepatitis B surface antigen (HBsAg) were 0.55 and 0.52 (P < .05) in HBeAg-positive patients, respectively, while in HBeAg-negative patients they were 0.42 and 0.37, respectively (P > .05). Among 96 patients receiving antiviral prophylaxis, we detected a rapid decrease in HBV DNA to an undetectable level during treatment but relatively stable levels of pgRNA and HBcrAg. Conclusions: HBcrAg and pgRNA levels are lower in HBeAg-negative patients than in HBeAg-positive patients. These 2 markers are significantly associated with HBV DNA irrespective of HBeAg status, while they are significantly associated with HBsAg only in HBeAg-positive patients.

Interpretable and explainable hybrid model for daily streamflow prediction based on multi-factor drivers.

Streamflow time series data typically exhibit nonlinear and nonstationary characteristics that complicate precise estimation. Recently, multifactorial machine learning (ML) models have been developed to enhance the performance of streamflow predictions. However, the lack of interpretability within these ML models raises concerns about their inner workings and reliability. This paper introduces an innovative hybrid architecture, the TCN-LSTM-Multihead-Attention model, which combines two layers of temporal convolutional networks (TCN) followed by one layer of long short-term memory (LSTM) units, integrated with a Multihead-Attention mechanism for predicting streamflow with streamflow causation-driven prediction samples (RCDP), employing local and global interpretability studies through Shapley values and partial dependency analysis. The find_peaks method was used to identify peak flow events in the test dataset, validating the model's generality and uncovering the physical causative patterns of streamflow. The results show that (1) compared to the LSTM model with the same hyperparameter settings, the proposed TCN-LSTM-Multihead-Attention hybrid model increased the R2 by 52.9%, 2.5%, 43.1%, and 10.7% respectively at four stations in the test set predictions using RCDP samples. Moreover, comparing the prediction results of the hybrid model under different samples in Hengshan station, the R2 for RCDP increased by 5.06% and 1.22% compared to streamflow autoregressive prediction samples (RAP) and meteorological-soil volumetric water content coupled autoregressive prediction samples (MCSAP) respectively. (2) Historical streamflow data from the preceding 3 days predominantly influences predictions due to strong autocorrelation, with flow quantity (Q) typically emerging as the most significant feature alongside precipitation (P), surface soil moisture (SSM), and adjacent station flow data. (3) During periods of low and normal flow, historical data remains the most crucial factor; however, during flood periods, the roles of upstream inflow and precipitation become significantly more pronounced. This model facilitates the identification and quantification of various hydrodynamic impacts on flow predictions, including upstream flood propagation, precipitation, and soil moisture conditions. It also elucidates the model's nonlinear relationships and threshold responses, thereby enhancing the interpretability and reliability of streamflow predictions.

[Analysis of differential metabolites of spikes of Prunella vulgaris at different stages based on UPLC-MS/MS].

Prunella vulgaris, aptly named for its withering at the summer solstice, displays significant variation in quality arising from differing harvest time. However, research on the chemical composition changes of its spikes at various stages is limited, and the specific metabolites remain unclear. In order to elucidate the metabolites and metabolic pathways of the spikes of P. vulgaris, the current study deployed ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS) and targeted metabolomics to characterize the compound variability in the spikes of P. vulgaris across different periods. Multivariate statistical techniques such as principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) were used to identify the differences in metabolites, and relevant metabolic pathways were analyzed. A total of 602 metabolites were identified by metabolomics, of which organic acids and their derivatives were the most abundant, followed by flavonoids. Multiple differential metabolites, including p-hydroxybenzoic acids and gallic acids were identified based on variable importance in projection(VIP)>1 and P<0.05. The results of enrichment analysis suggested that isoflavonoids biosynthesis, aminobenzoate degradation, benzoate degradation, anthocyanins biosynthesis, metabolic pathways, microbial metabolism in different environments, secondary plant metabolite biosynthesis, tryptophan metabolism, and phenylpropanoid synthesis were the main metabolic pathways. These results intend to elucidate the dynamic changes of differential metabolites of P. vulgaris and provide a theoretical basis for further study of the harvesting mechanism of spikes of P. vulgaris.

Effects of Physical Activity Interventions on Self-Perceived Health Status among Lung Cancer Patients: Systematic Review and Meta-Analysis.

Patients with lung cancer may experience deterioration in quality of life due to adverse effects caused by their disease and its treatment. Although exercise programs have been shown to improve quality of life in certain stages of the disease, the overall impact on this population is unknown. The objective of this research was to evaluate the effect of physical activity on the self-perception of quality of life, physical wellbeing and dyspnea in lung cancer patients. Thirteen articles were included. Five meta-analyses were performed using the standardized mean difference (SMD) with 95% confidence intervals (CI) to evaluate the target outcomes. Results showed significant differences in quality of life (p = 0.01; SMD = 0.43, 95% CI = 0.10, 0.75), physical functioning (p = 0.01; SMD = 0.27, 95% CI = 0.06, 0.49) and physical wellbeing (p = 0.01; SMD = 0.37, 95% CI = 0.08, 0.67) in favour of participants who have undergone the programme compared to those who have not, without significant differences between the two groups in dyspnea. This study shows how physical activity interventions could have positive effects on physical functioning and physical wellbeing but could also be effective for improving quality of life in patients with lung cancer.

Imaging investigation of cervicocranial artery dissection by using high resolution magnetic resonance VWI and MRA: qualitative and quantitative analysis at different stages.

BACKGROUND: To explore the value of magnetic resonance angiography (MRA) and high resolution magnetic resonance vessel wall imaging (HRMR-VWI) in cervicocranial artery dissection (CCAD) for the disease diagnosis, course staging and treatment. On the basis of qualitative evaluation, this study also extract the changes of different stages in vessel wall in different vessel segments to identify imaging indicators for the quantitative evaluation of CCAD. METHODS: We retrospectively enrolled 34 patients with CCAD (38branches) with conventional MRA and HRMR-VWI examinations. Two radiologists independently analyzed imaging features of vessel wall and lumen in the different stages, and the typical sign detection of artery dissection were compared between MRA and HRMR-VWI. Then the parameters of vessel wall was quantitatively evaluated by the post-processing software (Vesselmass, Leiden University Medical Center, Leiden, The Netherlands. RESULTS: HRMR-VWI revealed typical sign detection of artery dissection in all patients in the acute and subacute stage. Among them, the intimal flap/double lumen sign ditection were more common than the MRA, there was significant difference (P = 0.012). MRA revealed typical sign detection of artery dissection in more than half the patients, and the detection was no significant difference at the chronic stage between MRA and HRMR-VWI (P = 1.000/1.000/0.761). In the acute and subacute stage, the typical sign detection of intramural hematoma and Grade II enhancement revealed by HR-MRI was higher than the observations in the chronic stage (P = 0.000/0.000/0.016), while there was no significant difference by MRA (P = 0.902). The values of wall thickness, relative signal intensity of vessel wall enhancement, relative signal intensity of intramural hematoma (IMH), and percentage of stenosis in CCAD decreased from acute to subacute and then to chronic stages. Each quantitative parameter in patients with CCAD in the early stages (i.e., acute and subacute stages) was significantly different from that in patients with CCAD in the recovered group at chronic stage (P < 0.05). Wall thickness and relative signal intensity of vessel wall enhancement in patients with CCAD in the early stages were not significantly different from those in patients with CCAD in the incompletely recovered group at chronic stage (P > 0.05). CONCLUSIONS: As the only noninvasive imaging technology, HRMR-VWI displays the structure of the vessel wall in vivo, showing not only excellent performance in the early diagnosis of CCAD, but also describing the changes of different stages in the qualitative and quantitative characteristics of vessel wall. It also helps to guide the diseasediagnosis, course staging and treatment of CCAD. Although the diagnostic efficacy of MRA was not as good as HRMR-VWI, it should be the first choice of method for routine examination in evaluating CCAD, especially at the chronic stage of CCAD.

CT characteristics of recurrent acute pancreatitis and acute pancreatitis in different stages-a retrospective cross-sectional study.

Background: Acute pancreatitis (AP), recurrent acute pancreatitis (RAP), and chronic pancreatitis (CP) are a continuum of the same disease. The course of RAP and AP is a dynamic process. Previous studies are contradictory regarding the severity of RAP and AP. We conducted this study to investigate the computed tomography (CT) characteristics of RAP and AP in the early and late stages; respectively. Methods: Patients who underwent contrast-enhanced computed tomography for symptoms during RAP or AP episodes were retrospectively collected from three tertiary hospitals in Sichuan Province, China from January 2015 to December 2019. The patients were categorized into RAP and AP groups based on recurrence and initial events. Both the RAP and AP groups were divided into early (first week) and late stages (after the first week) based on the 2012 revised Atlanta classification (RAC). Patient demographic data, RAC, CT findings, CT severity index (CTSI) scores, and extrapancreatic inflammation on CT scores in the early and late phases were analyzed between the two groups. The Wilcoxon signed-rank test, χ2 test, and Fisher's exact test were used to compare continuous and categorical variables between the two groups respectively. Results: In 683 RAP and 1,829 AP patients, the most common etiologies were hypertriglyceridemia and cholelithiasis, respectively. The RAP group had lower extrapancreatic inflammation on CT scores and Acute Physiology and Chronic Health Evaluation II scores than the AP group in the early stage (both P<0.001). The RAP group had higher CTSI scores than the AP group in the late stage (P=0.022). Conclusions: Compared with AP patients, the most common cause of RAP patients was hypertriglyceridemia in China, and the severity of RAP was lower than that of initial AP in the early stage and higher than that of initial AP in the late stage.

[Changes in Secondary Inorganic Ions in PM2.5 at Different Pollution Stages Before and After COVID-19 Control].

To investigate the change characteristics of secondary inorganic ions in PM2.5 at different pollution stages before and after COVID-19, the online monitoring of winter meteorological and atmospheric pollutant concentrations in Zhengzhou from December 15, 2019 to February 15, 2020 was conducted using a high-resolution (1 h) online instrument. This study analyzed the causes of the haze process of COVID-19, the diurnal variation characteristics of air pollutants, and the distribution characteristics of air pollutants at different stages of haze.The results showed that Zhengzhou was mainly controlled by the high-pressure ridge during the haze process, and the weather situation was stable, which was conducive to the accumulation of air pollutants. SNA was the main component of water-soluble ions, accounting for more than 90%. Home isolation measures during COVID-19 had different impacts on the distribution characteristics of air pollutants in different haze stages. After COVID-19, the concentration of PM2.5 in the clean, occurrence, and dissipation stages increased compared with that before COVID-19 but significantly decreased in the development stage. The home isolation policy significantly reduced the high value of PM2.5. The concentrations of NO2, SO2, NH3, and CO were the highest in the haze development stage, showing a trend of first increasing and then decreasing. The concentration of O3 was lowest in the pre-COVID-19 development stage but highest in the post-COVID-19 development stage. The linear correlation between[NH4+]/[SO42-] and[NO3-]/[SO42-] at different time periods before and after COVID-19 was strong, indicating that the home isolation policy of COVID-19 did not change the generation mode of NO3-, and the corresponding reaction was always the main generation mode of NO3-. The correlation between[excess-NH4+] and[NO3-] was high in different periods before COVID-19, and NO3- generation was related to the increase in NH3 or NH4+ in the process of PM2.5 pollution in Zhengzhou.

Morphological feature recognition of different differentiation stages of induced ADSCs based on deep learning.

In order to accurately identify the morphological features of different differentiation stages of induced Adipose Derived Stem Cells (ADSCs) and judge the differentiation types of induced ADSCs, a morphological feature recognition method of different differentiation stages of induced ADSCs based on deep learning is proposed. Using the super-resolution image acquisition method of ADSCs differentiation based on stimulated emission depletion imaging, after obtaining the super-resolution images at different stages of inducing ADSCs differentiation, the noise of the obtained image is removed and the image quality is optimized through the ADSCs differentiation image denoising model based on low rank nonlocal sparse representation; The denoised image is taken as the recognition target of the morphological feature recognition method for ADSCs differentiation image based on the improved Visual Geometry Group (VGG-19) convolutional neural network. Through the improved VGG-19 convolutional neural network and class activation mapping method, the morphological feature recognition and visual display of the recognition results at different stages of inducing ADSCs differentiation are realized. After testing, this method can accurately identify the morphological features of different differentiation stages of induced ADSCs, and is available.

Transcriptome profiling reveals differential gene expression in the rumen of Hu lambs at different developmental stages.

The development of the rumen is a critical physiological challenge in newborn ruminants. However, the molecular mechanism underlying different stages of rumen development in sheep remains poorly understood. Here, RNA sequencing and bioinformatics analysis were performed to compare the transcription profiles of rumen development at 7, 28 and 56 days of birth (D7, D28 and D56). We identified 1246, 2257 and 627 differentially expressed genes (DEGs) between D7 and D28, between D7 and D56, between D28 and D56, respectively. Also, 70 DGEs were co-expressed at these three time points. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated most DEGs mainly related to transporter activity, channel activity and metabolism pathways. Noteworthy, the expression levels of most genes (CA4, CA9, CA12 and CA14) in nitrogen metabolic pathways were negatively correlated with the papilla length and width, but the papilla length and width were positively correlated with the expression of genes (PLA2G3, SLC26A9, SLC34A3) in ion transport pathway, suggesting that these genes may be involved in nitrogen metabolic and ion transport pathway and thus affect rumen development. These results provide new insight into the changes in RNA expression at different time points of rumen development in Hu sheep.

Transcriptome identification and characterization of long non-coding RNAs in the ovary of hens at four stages.

Long non-coding RNAs (lncRNAs) play important roles in transcriptional and post-transcriptional regulation. LncRNAs, which are defined as non-coding RNAs more than 200 bp in length, are involved in key biological processes, such as cell proliferation and differentiation, epigenetic regulation, and gene transcriptional translation. Recent studies have shown that lncRNAs also play major regulatory roles in the reproduction of mammals. However, knowledge of the roles of lncRNAs in the chicken ovary lacking. In this study, we performed RNA-seq analyses of ovarian tissue from Hy-Line brown laying hens at four physiological stages [15, 20, 30, and 68 weeks of age (W)]. We identified 657 lncRNA transcripts that were differentially expressed during ovarian development, the number of down-regulated lncRNAs was higher than the number of up-regulated lncRNAs during development. We predicted the cis and trans target genes of the DE lncRNAs and constructed a lncRNA-mRNA interaction network, which indicated that the DE genes (DEGs) and the target genes of the DE lncRNAs are mainly involved in signaling pathways associated with ovarian development, including oocyte meiosis, calcium signaling pathways, ECM-receptor interactions, and ribosome and focal adhesion. Overall, we found that twelve lncRNAs were strongly involved in ovarian development: LNC_013443, LNC_001029, LNC_005713, LNC_016762, ENSGALT00000101857, LNC_003913, LNC_013692, LNC_012219, LNC_004140, ENSGALT00000096941, LNC_009356, and ENSGALT00000098716. In summary, our study utilized RNA-seq analysis of hen ovaries to explore key lncRNAs involved in ovarian development and function. Furthermore, the comprehensive analysis identified the target genes of these lncRNAs providing a better understanding of the mechanisms underlying ovarian development in hens and a theoretical basis for further research.

Genetic parameters and genome-wide association for milk production traits and somatic cell score in different lactation stages of Shanghai Holstein population.

The aim of this study was to investigate the genetic parameters and genetic architectures of six milk production traits in the Shanghai Holstein population. The data used to estimate the genetic parameters consisted of 1,968,589 test-day records for 305,031 primiparous cows. Among the cows with phenotypes, 3,016 cows were genotyped with Illumina Bovine SNP50K BeadChip, GeneSeek Bovine 50K BeadChip, GeneSeek Bovine LD BeadChip v4, GeneSeek Bovine 150K BeadChip, or low-depth whole-genome sequencing. A genome-wide association study was performed to identify quantitative trait loci and genes associated with milk production traits in the Shanghai Holstein population using genotypes imputed to whole-genome sequences and both fixed and random model circulating probability unification and a mixed linear model with rMVP software. Estimated heritabilities (h2) varied from 0.04 to 0.14 for somatic cell score (SCS), 0.07 to 0.22 for fat percentage (FP), 0.09 to 0.27 for milk yield (MY), 0.06 to 0.23 for fat yield (FY), 0.09 to 0.26 for protein yield (PY), and 0.07 to 0.35 for protein percentage (PP), respectively. Within lactation, genetic correlations for SCS, FP, MY, FY, PY, and PP at different stages of lactation estimated in random regression model were ranged from -0.02 to 0.99, 0.18 to 0.99, 0.04 to 0.99, 0.04 to 0.99, 0.01 to 0.99, and 0.33 to 0.99, respectively. The genetic correlations were highest between adjacent DIM but decreased as DIM got further apart. Candidate genes included those related to production traits (DGAT1, MGST1, PTK2, and SCRIB), disease-related (LY6K, COL22A1, TECPR2, and PLCB1), heat stress-related (ITGA9, NDST4, TECPR2, and HSF1), and reproduction-related (7SK and DOCK2) genes. This study has shown that there are differences in the genetic mechanisms of milk production traits at different stages of lactation. Therefore, it is necessary to conduct research on milk production traits at different stages of lactation as different traits. Our results can also provide a theoretical basis for subsequent molecular breeding, especially for the novel genetic loci.

Blastocyst Stage Affects the Isolation and Culture of Buffalo Naive/Primed Embryonic Stem-Like Cells.

Since embryonic stem cells (ESCs) were first identified, significant progress has been achieved. However, the establishment of buffalo ESCs (bESCs) is still unclear. This study was undertaken to explore the effect of the blastocyst stage on the isolation of bESCs. Firstly, our results indicated that the pluripotent genes were mainly expressed at the early stages of blastocyst, and the attachment and colony formation rates of bESCs derived from expanded blastocyst and hatched blastocyst were significantly higher than early blastocyst and blastocyst. In the meantime, bESCs showed positive alkaline phosphatase activity and expressed genes like OCT4, NANOG, SOX2, c-MYC, CDH1, KLF4, and TBX3. Immunofluorescence also confirmed the expression of OCT4, SOX2. Embryoid bodies expressing three marker genes were generated from the differentiation experiment, and fibroblast, epithelial, and neuron-like cells were induced. Moreover, naive-related genes KLF4, TBX3, primed-related genes FGF5, ACTA2 were expressed in the cells, but not REX-1. Immunofluorescence and western blot confirmed the FGF5 expression. Furthermore, bESCs could maintain pluripotency with the signal of LIF and bFGF. In summary, our results indicated that expanded blastocyst and hatched blastocyst are more suitable for bESCs isolation.

Melatonin increases bone mass in normal, perimenopausal, and postmenopausal osteoporotic rats via the promotion of osteogenesis.

BACKGROUND: Osteoporosis is a disease threatening the health of millions of individuals. Melatonin is found to be a potential anti-osteoporosis drug. However, whether melatonin plays a role against osteoporosis at different stages of the menopause and the underlying mechanisms are unknown. METHODS: Ovariectomy was utilized as a model of perimenopausal and postmenopausal osteoporosis. A total of 100 mg/kg melatonin, or solvent alone, was added to the drinking water of the rats over 8 weeks. Perimenopausal rats immediately received intervention following ovariectomy while postmenopausal rats received intervention 8 weeks after ovariectomy. All rats underwent overdose anesthesia following intervention after which blood samples and femurs were collected for further analysis. Rat femurs were scanned using micro-CT and examined histologically. The serum levels of melatonin and osteogenic biochemical markers were measured and the expression of osteogenesis-associated genes (Runx2, Sp7) were quantified by real-time quantitative PCR. Alkaline phosphatase (ALP) activity and the gene expression (Col1a1, Runx2, Alpl, and Bglap) were measured after bone marrow mesenchymal stem cells (BMSCs) were osteogenically induced, both with and without melatonin in vitro. ALP staining and Alizarin Red S staining were used to identify osteogenesis. RESULTS: Analysis by micro-CT and histological staining demonstrated that bone mass decreased and bone microarchitecture deteriorated over time after ovariectomy. Intervention with melatonin increased bone mass in normal, perimenopausal, and postmenopausal osteoporotic rats. Serum levels of ALP continuously increased after ovariectomy while osteocalcin levels initially rose, then decreased. Melatonin increased the serum levels of ALP and osteocalcin and mRNA expression levels of Runx2 and Sp7 in normal and postmenopausal rats, the opposite of the markers in perimenopausal rats. In vitro study demonstrated that 100 µmol/L melatonin increased the mRNA expression of Col1a1, Runx2, and Alpl three and/or seven days after intervention, and Alpl and Bglap 14 d after intervention. Melatonin increased ALP activity and the extent of ALP and matrix mineralization in the late stage of osteogenesis. CONCLUSIONS: Bone mass continuously decreased after ovariectomy, while melatonin increased bone mass and ameliorated bone metabolism in normal, perimenopausal, and postmenopausal osteoporotic rats due to the induction of osteogenic differentiation in BMSCs.

Metabolomic study on bleomycin-induced pulmonary fibrosis rat models at different stages / 中国药理学通报

Aim To study the variations of endogenous differential metabolites and metabolic pathways in PF rat model induced by bleomycin based on GC-MS.Methods The rat model for pulmonary fibrosis was induced by intratracheal instillation of bleomycin.Model rats were randomly divided into 7 days group of PF model(M7), 14 days group of model(M14), 21 days group of model(M21)and 28 days group of model(M28), with 6-8 rats in each group.On the 8th, 15th, 22nd and 29th days of the modeling, the rat model was evaluated by histopathology and hydroxyproline(HYP)detection.The non-targeted metabolomics was studied by GC-MS in order to find the related metabolites in the serum of PF rats and the metabolic pathways were analysed by MetaboAnalyst.Results Compared with control group, the phenomenon of rat lung lesions gradually appeared in each model group(M7, M14, M21, M28)with the modeling process.9, 14, 35, and 13 statistically significant metabolites were screened and identified respectively in M7, M14, M21 and M28.Among them, glycerol and phosphate were the early significant changes of pulmonary fibrosis.3-(3-hydroxyphenyl)propionic acid, alanine, galactonic acid, and serine changed significantly in the later stages of pulmonary fibrosis, and linoleic acid was the common main different metabolite.The main pathways affecting metabolism involved lipid metabolism, amino acid metabolism.Conclusion Abnormal amino acid metabolism and lipid metabolism are the main metabolic characteristics during the formation and development of PF by BLM.

Psychological stress of university students in the hardest-hit areas at different stages of the COVID-19 epidemic.

BACKGROUND: The outbreak of COVID-19 has caused extremely many serious consequences for the country and the world. In fact, it has seriously affected people's mental health. The purpose of this study is to understand the psychological stress among college students in different stages of epidemics in hard-hit areas such as Hubei. Moreover, to highlight the factors that influencing, their psychological conditions with the emphasis of further corresponding suggestions. METHODS: This study includes self-designed questionnaires in order to assess and analyze the psychological state of over 17,000 college students during the outbreak period in January and home quarantine in February. The questionnaire contains three aspects and six dimensions: pressure responses: stress susceptibility (SS), stress adjustment (SA), risk cognition: cognition of danger (CD), cognition of illness (CI) and stress reactions: emotional responses (ER), somatic responses (SR). This survey was done by an online questionnaire (www.wjx.cn) to investigate the psychological stress information of college students, and analyzed the data by SPSS 22.0 for Windows. RESULTS: Regarding the stress susceptibility, participants were more likely stressed in February than in January. Regarding the stress adjustment, the number of participants requiring pressure regulation or release in the February survey was significantly lower than that the effective in the January survey. The mean of the cognition of danger reduced significantly in February than in January, in other words, participants were highly worried about the epidemic in January than in February. Regarding the cognition of illness, participants in January had a more pessimistic attitude towards the epidemic than those in February. The emotional responses of the participants in February were more severe than those in January, while the somatic responses reduced significantly in February compared with January. Furthermore, females have stronger stress reactions than males. However, the SR doesn't have significant differences between females and males. CONCLUSION: After two surveys in January and February, it was found that the psychological stress of college students in Hubei was significantly different at different stages of the epidemic, where the epidemic developed, the psychological stress of college students become more severe. The psychological stress of the college students in Hubei Province, as a severely affected area, should be paid more attention.

Three-dimensional construction of micrometer level in rat stomach by synchrotron radiation.

BACKGROUND: The structural changes of gastric mucosa are considered as an important window of early gastric lesions. This article shows an imaging method of the stomach that does not use imaging agents. X-ray phase-contrast images of different stages of gastric development were taken using micrometer level X-ray in-line phase-contrast imaging (XILPCI) technique on synchrotron radiation facility. The aim of the study was to demonstrate that the imaging technique is an appropriate method for micron imaging of the gastric structures. METHODS: The stomachs of 4-, 6- and 12-week-old rats were removed and cleaned. XILPCI has 1000 times greater soft tissue contrast than that of X-ray traditional absorption radiography. The projection images of the rats stomachs were recorded by an XILPCI charge coupled device (CCD) at 9-µm image resolution. RESULTS: The X-ray in-line phase-contrast images of the different stages of rats' gastric specimens clearly showed the gastric architectures and the details of the gastro-duodenal region. 3-dimensional (3D) stomach anatomical structure images were reconstruction. CONCLUSION: The reconstructed gastric 3D images can clearly display the internal structure of the stomach. XILPCI may be a useful method for medical research in the future.

Cystic fibrosis transmembrane conductance regulator-associated ligand protects dopaminergic neurons by differentially regulating metabotropic glutamate receptor 5 in the progression of neurotoxin 6-hydroxydopamine-induced Parkinson's disease model.

Due to limitations in early diagnosis and treatments of Parkinson's disease (PD), it is necessary to explore the neuropathological changes that occur early in PD progression and to design neuroprotective therapies to prevent or delay the ongoing degeneration process. Metabotropic glutamate receptor 5 (mGlu5) has shown both diagnostic and therapeutic potential in preclinical studies on PD. Clinical trials using mGlu5 negative allosteric modulators to treat PD have, however, raised limitations about the neuroprotective role of mGlu5. It is likely that mGlu5 has different regulatory roles in different stages of PD. Here, we investigated a protective role of cystic fibrosis transmembrane conductance regulator-associated ligand (CAL) in the progression of PD by differential regulation of mGlu5 expression and activity to protect against 6-hydroxydopamine (6-OHDA)-induced neurotoxicity. Following treatment with 6-OHDA, mGlu5 and CAL expressions were elevated in the early stage and reduced in the late stage, both in vitro and in vivo. Activation of mGlu5 in the early stage by (RS)-2-chloro-5-hydroxyphenylglycine, or blocking mGlu5 in the late stage by 2-methyl-6-(phenylethynyl) pyridine, increased cell survival and inhibited apoptosis, but these effects were significantly weakened by knockdown of CAL. CAL alleviated 6-OHDA-induced neurotoxicity by regulating mGlu5-mediated signaling pathways, thereby maintaining the physiological function of mGlu5 in different disease stages. In PD rat model, CAL deficiency aggravated 6-OHDA toxicity on dopaminergic neurons and increased motor dysfunction because of lack of regulation of mGlu5 activity. These data reveal a potential mechanism by which CAL specifically regulates the opposite activity of mGlu5 in progression of PD to protect against neurotoxicity, suggesting that CAL is a favorable endogenous target for the treatment of PD.

Detection of breast cancer of various clinical stages based on serum FT-IR spectroscopy combined with multiple algorithms.

BACKGROUND: Breast cancer screening is time consuming, requires expensive equipment, and has demanding requirements for doctors. Hence, a large number of breast cancer patients may miss screening and early treatment, which greatly threatens their health around the world. Infrared spectroscopy may be able to be used as a screening tool for breast cancer detection. Fourier transform infrared (FT-IR) spectroscopy of serum was combined with traditional machine learning algorithms to achieve an auxiliary diagnosis that could quickly and accurately distinguish patients with different stages of breast cancer, including stage 1 disease, from control subjects without breast cancer. MATERIALS AND METHODS: FT-IR spectroscopy were performed on the serum of 114 non-cancer control subjects, 35 patients with stage I, 43 patients with stage II, and 29 patients with stage III & IV breast cancer. Due to the experimental sample imbalance, we used the oversampling to process the four classes of sample. The oversampling selected Synthetic Minority Oversampling Technique (SMOTE). Subsequently, we used the random discarding method in undersampling to do experiments as well. The average FT-IR spectroscopy results for the four groups showed differences in phospholipids, nucleic acids, lipids, and proteins between non-cancer control subjects and breast cancer patients at different stages. Based on these differences, four classification models were used to classify stage I, II, III & IV breast cancer patients and non-cancer control subjects. First, standard normal variate transformation (SNV) was used to preprocess the original data, and then partial least squares (PLS) was used for feature extraction. Finally, the five models were established including extreme learning machine (ELM), k-nearest neighbor (KNN), genetic algorithms based on support vector machine (GA-SVM), particle swarm optimization-support vector machine (PSO-SVM) and grid search-support vector machine (GS-SVM). CONCLUSION: In oversampling experiment, the GS-SVM classifier obtained the highest average classification accuracy of 95.45 %; the diagnostic accuracy of non-cancer control subjects was 100 %; breast cancer stage I was 90 %; breast cancer stage II was 84.62 %; and breast cancer stage III & IV was 100 %. In undersampling experiment, the GA-SVM model obtained the highest average classification accuracy of 100 %; the diagnostic accuracy of non-cancer control subjects was 100 %; breast cancer stage I was 100 %; breast cancer stage II was 100 %; and breast cancer stage III & IV was 100 %. The results show that FT-IR spectroscopy combined with powerful classification algorithms has great potential in distinguishing patients with different stages of breast cancer from non-cancer control subjects. In addition, this research provides a reference for future multiclassification studies of cervical cancer, ovarian cancer and other female high-incidence cancers through serum FT-IR spectroscopy.

Comparison of surface enhanced Raman spectroscopy and Raman spectroscopy for the detection of breast cancer based on serum samples.

In this study, surface enhanced Raman spectroscopy (SERS) and Raman spectroscopy (RS), are employed for the classification of different stages of breast cancer using clinically diagnosed serum samples from breast cancer patients and healthy individuals. These serum samples are compared for their spectral features acquired by SERS and RS to establish spectral features that can be considered as spectral markers of breast cancer diagnosis and classification. SERS features related to DNA, proteins and lipids were observed which are solely observed in the serum samples of patients at different stages of breast cancer as compared to healthy samples. In order to explore the capability of SERS and RS and their comparison as an analytical tool for the efficient understanding of the progression of breast cancer, Principal Component Analysis (PCA) is done for the SERS and RS spectra of control, stage 2, stage 3 and stage 4. Furthermore, the Partial Least Squares-Discriminant Analysis (PLS-DA) was performed to compare the diagnostic performance of SERS and Raman spectroscopy for the classification of disease positive samples and healthy ones. The sensitivity and specificity and area under receiver operating characteristic (AUROC) curve values for SERS data were 90%, 98.4%, and 94% respectively which were higher as compared to Raman spectral data for which these values were found to be 88.2%, 97.7%, and 83.4% respectively.

Effects of QDs exposure on the reproductive and embryonic developmental toxicity in mice at various pregnancy stages.

Quantum dots (QDs) have recently attracted considerable attention in the biomedical fields because of their unique and excellent optical properties. However, information on their health effects, particularly in the reproductive system, is limited. The present study focuses on the effects of intravenous injection of CdSe/ZnS QDs on the reproductive system and embryo development at various stages of pregnancy in mice. The CdSe/ZnS QDs intravenously injected in mice during pregnancy accumulated in the maternal liver, uterus and placenta. This accumulation affected the growth and development of the embryo during the early and middle stages of pregnancy. Moreover, genotoxicity to the placenta after exposure to CdSe/ZnS QDs was demonstrated by the increased expression levels of genes related to oxidative stress and apoptosis and the reduced expression levels of genes related to the nutrient and waste transportation. Alterations in the gene expression levels have hindered the transport of metabolites across the placenta, which in turn affected the ability of the fetus to obtain nutrients.