UNASSIGNED: This study aims to develop an artificial intelligence model utilizing clinical blood markers, ultrasound data, and breast biopsy pathological information to predict the distant metastasis in breast cancer patients.
UNASSIGNED: Data from two medical centers were utilized, Clinical blood markers, ultrasound data, and breast biopsy pathological information were separately extracted and selected. Feature dimensionality reduction was performed using Spearman correlation and LASSO regression. Predictive models were constructed using LR and LightGBM machine learning algorithms and validated on internal and external validation sets. Feature correlation analysis was conducted for both models.
UNASSIGNED: The LR model achieved AUC values of 0.892, 0.816, and 0.817 for the training, internal validation, and external validation cohorts, respectively. The LightGBM model achieved AUC values of 0.971, 0.861, and 0.890 for the same cohorts, respectively. Clinical decision curve analysis showed a superior net benefit of the LightGBM model over the LR model in predicting distant metastasis in breast cancer. Key features identified included creatine kinase isoenzyme (CK-MB) and alpha-hydroxybutyrate dehydrogenase.
UNASSIGNED: This study developed an artificial intelligence model using clinical blood markers, ultrasound data, and pathological information to identify distant metastasis in breast cancer patients. The LightGBM model demonstrated superior predictive accuracy and clinical applicability, suggesting it as a promising tool for early diagnosis of distant metastasis in breast cancer.

UNASSIGNED: Traumatic brain injury (TBI) is the major reason for the death of young people and is well known for its high mortality and morbidity. This paper aim to predict the 24h survival of patients with TBI.
UNASSIGNED: A total of 1224 samples were involved in this analysis, and the clinical indicators involved included age, gender, blood pressure, MGAP and other fields, among which the target variable was \"outcome\", which was a binary variable. The methods mainly involved in this paper include data visualization analysis, single factor analysis, feature engineering analysis, random forest model (RF), K-Nearst Neighbors (KNN) model, and so on. Logistic regression model (LR) and deep neural network model (DNN). We will oversample the training set using the SMOTE method because of the very unbalanced labeling of the sample itself.
UNASSIGNED: Although the accuracy of all models is very high, the recall rate is relatively low. The DNN model with the best performance only reaches 0.17, and the corresponding AUC is 0.80. After resampling, we find that the recall rate of positive samples of all models has increased a lot, but the AUC of some models has decreased. Finally, the optimal model is LR, whose positive sample recall rate is 0.67 and AUC is 0.82.
UNASSIGNED: Through resampling, we obtained that the best model is the RF model, whose recall rate and AUC are the best, and the AUC level is about 0.87, indicating that the accuracy performance of the model is still good.

With the tremendous development of massively parallel sequencing (MPS) in the last decade, it has been widely applied in basic science, clinical diagnostics, microbial genomics, as well as forensic genetics. MPS has lots of advantages that may facilitate the kinship analysis. In this study, 243 Chinese Han individuals from 17 families were involved and sequenced using the ForenSeq™ DNA Signature Prep Kit (Verogen, Inc., San Diego, USA), which provided the sequence information of 27 autosomal STRs (A-STRs), 7 X chromosomal STRs (X-STRs), 24 Y chromosomal STRs (Y-STRs) and 94 identity-informative SNPs (iSNPs). A total of 275 pairs of parent-child, 123 pairs of full siblings, 1 pair of twins, 1 pair of half siblings, 158 pairs of grandparent-grandchild, 222 pairs of uncle/aunt-nephew/niece and 121 pairs of first cousins, as well as 701 pairs of unrelated individuals were identified. Using both likelihood ratio (LR) and identical by state (IBS) methods, the kinship analysis was conducted among these relative and non-relative pairs based on the A-STRs and SNPs. As a result, the ForenSeq Signature Kit could solve the analysis of parent-child (t1 = -4, t2 = 4), full siblings (t1 = -2, t2 = 2) and most second-degree kinships (t1 = -1, t2 = 1) using the LR method. When the IBS method was applied, 123 full sibling pairs had a higher average IBS value than other kinship groups in this study. And the IBS method could play a role in the testing of parent-child and full siblings.

This study aimed to determine the risk factors of ischemic/hemorrhagic stroke in patients suffering moyamoya disease (MMD), as well as to compare the effects of six analysis methods.
In the present retrospective study, the data originated from the database of Jiang Xi Province Medical Big Data Engineering & Technology Research Center. In addition, the information of patients with MMD that were admitted to the second affiliated hospital of Nanchang university from January 1st, 2012 to December 31st, 2019 was acquired. Six different machine learning methods were adopted to build the models, and XGboost, Logistic regression (LR) and Support vector machine (SVM) models were adopted to determine the risk factors of ischemic/hemorrhagic stroke in patients with MMD because of their excellent performance. Next, the effects of the built models were compared and validated in internal and independent external validation sets. The external validation set involving 204 cases from January 1st, 2018 to December 31st, 2019.
On the whole, 790 patients with MMD were screened, i.e., 397 patients with cerebral infarction and 393 patients with cerebral hemorrhage. In the internal validation set, XGboost model exhibited significant discrimination (AUC>0.75), with its area under the curve (AUC) reaching 0.874 (95% CI: 0.859, 0.889). Compared with the LR and SVM models, the XGboost model in the internal validation set achieved the improved accuracy by 3.2% and 3.1%, respectively, whereas no significant difference was identified.
XGboost model could be more efficient in analyzing the risk factors of ischemic/hemorrhagic stroke in patients with MMD; the risk factors of hemorrhagic stroke in MMD might be closely related to Suzuki stages, presence of an aneurysm, rural residence, hospitalization times and age of onset.

Interleukin 18 (IL-18) is a proinflammatory cytokine with an ability to accelerate cell proliferation through activating other factors. However, little is yet understood of the role of IL-18 in the regulation of liver regeneration (LR). To study the effect of IL-18 on LR, the gene expression profiles of hepatocytes isolated from rat regenerative liver were determined by Rat Genome 230 2.0 microarray. Next, the synergistic effects of genes associated to IL-18 pathway were analyzed by expression profile function Et. Then, the expression level of IL-18 was examined by RT-PCR and ELISA. Finally, the effect of IL-18 on hepatocyte proliferation was detected by injecting recombinant rat IL-18 (rrIL-18) into rats immediately after partial hepatectomy (PH) and the rate of hepatocyte proliferation was detected by BrdU labeling. The microarray result showed that the expressions of 13 genes of IL-18 pathway and 49 cell proliferation genes regulated by the pathway were significantly altered at transcriptional level. The Et values of three branches of IL-18 pathway, NF-κB, p38 and JNK, were markedly enhanced during the priming and progressing phases of rat LR. The mRNA level of IL-18 was significantly elevated at 2 and 36 h, and its level in plasma was also significantly increased at 2h, and reached the peaks at 12h and 48 h after PH (p<0.05). The number of BrdU positive cells was dramatically increased in rats treated with IL-18 compared to PBS control group (p<0.01). In conclusion, IL-18 promotes rat hepatocyte proliferation in the LR priming and progressing phases after PH.

Chlorophyll content, one of the most important physiological parameters related to plant photosynthesis, is usually used to predict yield potential. To map the quantitative trait loci (QTLs) underlying the chlorophyll content of rice leaves, a double haploid (DH) population was developed from an indica/japonica (Zhenshan 97/Wuyujing 2) crossing and two backcross populations were established subsequently by backcrossing DH lines with each of their parents. The contents of chlorophyll a and chlorophyll b were determined by using a spectrophotometer to directly measure the leaf chlorophyll extracts. To determine the leaf chlorophyll retention along with maturation, all measurements were performed on the day of heading and were repeated 30 days later. A total of 60 QTLs were resolved for all the traits using these three populations. These QTLs were distributed on 10 rice chromosomes, except chromosomes 5 and 10; the closer the traits, the more clustering of the QTLs residing on common rice chromosomal regions. In general, the majority of QTLs that specify chlorophyll a content also play a role in determining chlorophyll b content. Strangely, chlorophyll content in this study was found mostly to be lacking or to have a negative correlation with yield. In both backcross F1 populations, overdominant (or underdominant) loci were more important than complete or partially dominant loci for main-effect QTLs and epistatic QTLs, thereby supporting previous findings that overdominant effects are the primary genetic basis for depression in inbreeding and heterosis in rice.

Hepatic stimulatory substance (HSS), which encodes a sulfhydryl oxidase enzyme, promotes liver regeneration (LR) and maintains the viability of hepatocytes. Surprisingly, we found that the levels of the HSS mRNA and expressed protein were both strongly repressed at 12h after a 70% partial hepatectomy (PH) in mice. Understanding the mechanism and effect of this extraordinary suppression can provide a novel path for exploring the molecular function of HSS during LR. We observed that the EGF levels in the serum were negatively correlated with HSS expression in regenerating livers. Treating primary mouse hepatocytes or Hepa1-6 cells with EGF suppressed HSS mRNA expression. This suppression was transcriptional and was mediated by the effect of EGF on the phosphorylation of CCAAT/enhancer-binding protein β (C/EBPβ), which regulates HSS expression. We further showed that the enhanced phosphorylation of C/EBPβ after PH promoted its interaction with the HSS promoter and repressed HSS expression at early time-points after PH. Interestingly, the knockdown of HSS caused a dramatic decrease in E-cadherin expression in hepatocytes. E-cadherin expression was also significantly suppressed at 12h after PH. Moreover, the pre-injection of HSS-expressing adenovirus vectors prevented E-cadherin suppression after PH. Treatment with C/EBPβ siRNA reversed the EGF-mediated inhibition of HSS expression and led to enhanced E-cadherin expression and reduced cell migration. Our findings suggest that C/EBPβ directly inhibits the HSS promoter after PH and that this inhibition can downregulate E-cadherin expression. These data provide novel insight into the potential role of HSS in hepatic structural reconstruction during LR.

To explore the relevance of rat liver regeneration (LR) to acute hepatic failure (AHF), Rat Genome 230 2.0 Array was used to detect their gene expression profiles in this study, and the reliability of the detection results was confirmed by real-time-PCR. 1012 genes were found to be significantly changed in AHF occurrence and 948 genes in LR. Hierarchical clustering analysis showed that physiological activities of AHF and those of LR had no time correlation. Hierarchical clustering analysis (which is performed to group genes based on the similarity of expression patterns) showed that physiological activities of AHF and those of LR had no time correlation. K-means clustering analysis (which is used to check the difference in the relevant predictor variables between different groups is significant or not) demonstrated that gene expression trend of C1 group (genes relate to categories of stimulus-response and cell apoptosis, etc.) in AHF and in LR was extremely similar, that those of their C2 group (categories of regulation of homeostasis and hormone stimulation, etc.) were contrary, and that those of their C3 (material and energy metabolism and oxidation reduction, etc.), C4 (Cell cycle-related genes) and C5 (cell proliferation-related genes) groups were also similar with the gene expression changes of LR more abundant. GO classifications and functional clustering analysis (which was used to statistics the numbers or composition of proteins or genes at a function level) revealed that cellular processes including immune response, inflammatory reaction, cell migration and adhesion, etc. were increased both in AHF and in LR, whereas material and energy metabolism were decreased. Of them, stimulus response, inflammatory reaction and regulation of apoptosis, etc. were stronger in AHF occurrence than in LR, but ion homeostasis, hormonal response, regulation of cell division and proliferation, etc. were weaker in AHF occurrence. Gene expression changes and physiological activities of AHF and those of LR not only have similarities but also differences.

Alginate oligosaccharides (AOS), which are marine oligosaccharides, are involved in regulating plant root growth, but the promotion mechanism for AOS remains unclear. Here, AOS (10-80 mg L(-1)) were found to induce the generation of nitric oxide (NO) in the root system of wheat (Triticum aestivum L.), which promoted the formation and elongation of wheat roots in a dose-dependent manner. NO inhibitors suggested that nitrate reductase (NR), rather than nitric oxide synthase (NOS), was essential for AOS-induced root development. Further studies confirmed that AOS-induced NO generation in wheat roots by up-regulating the gene expression and enzyme activity of NR at the post-transcriptional level. The anatomy and RT-PCR results showed that AOS accelerated the division and growth of stele cells, leading to an increase in the ratio of stele area to root transverse area. This could be inhibited by the NR inhibitor, sodium tungstate, which indicated that NO catalyzed by the NR was involved in AOS regulation of root development. Taken together, in the early stage of AOS-induced root development, NO generation was a novel mechanism by which AOS regulated plant growth. The results also showed that this marine resource could be widely used for crop development.

BACKGROUND: High risk human papillomavirus (HPV) infection is the major cause of cervical cancer. Several epidemiological studies have performed HPV screening in Chinese women, but no report was for Shanghai suburb women.
OBJECTIVE: To understand the prevalence of HPV infection and risk factors in Shanghai suburbs.
METHODS: Between March 2011 and May 2011, 10,000 female volunteers lived in Fengxian District of Shanghai were recruited for the detection of 21 HPV types using PCR and fast flow hybridization of gene chip array. For the 508 HPV-positive patients, we performed the liquid-based ThinPrep cytology test (TCT) and histological examination for the diagnosis of local cervical lesions. The questionnaire surveyed demographic and behavioral indicators for the evaluation of risk factors of HPV infection.
RESULTS: We found that the HPV-positive rate was 12.6%. The five top HPV types were as follows (in descending order): HPV52, 16, 58, 18 and 33. Moreover, HPV-positive rates were higher in women with older age, lower educational level, younger age of the first sexual intercourse, multiple sexual partners, no usage of condom for contraception, multiple deliveries, vaginal delivery, menopause, vaginal inflammation, cervical erosion and no regular cervical cytological examination. We also found that an HPV genotyping in combination with TCT and histological examination could improve early diagnosis for local cervical lesions.
CONCLUSIONS: HPV infection was associated with age, sexual behavior and chronic inflammation of the cervix and vagina. We recommend popularizing HPV genotyping in women with high risk factors for the early diagnosis and prevention of cervical cancer.