Unveiling the overlooked threat: antibiotic resistance in groundwater near an abandoned sulfuric acid plant in Xingyang, China.

Groundwater near a sulfuric acid plant in Xingyang, Henan, China was sampled from seven distinct sites to explore the prevalence of antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs). Results showed that genes aadA, blaCTX-M, tetA, qnrA, and sul1 were detected with 100% frequency followed by aac(6')-Ib (85.71%), ermB (85.71%), and tetX (71.42%). Most abundant ARGs were sul1 in LSA2 (1.15 × 1011 copies/mL), tetA in LSA6 (4.95 × 1010 copies/mL), aadA in LSA2 (4.56 × 109 copies/mL), blaCTX-M in LSA4 (1.19 × 109 copies/mL), and ermB in LSA5 (1.07 × 109 copies/mL). Moreover, in LSA2, intl1 as a marker of class 1 integron emerged as the most abundant gene as part of MGE (2.25 × 1011 copies/mL), trailed by ISCR1 (1.57 × 109 copies/mL). Environmental factors explained 81.34% of ARG variations, with a strong positive correlation between the intl2 and blaCTX-M genes, as well as the ISCR1 gene and qnrA, tetA, intl2, and blaCTX-M. Furthermore, the intI1 gene had a strong positive connection with the aadA, tetA, and sul1 genes. Moreover, the aac(6')-Ib gene was associated with As, Pb, Mg, Ca, and HCO3-. The intl2 gene was also shown to be strongly associated with Cd. Notably, network analysis highlighted blaCTX-M as the most frequently appearing gene across networks of at least five genera. Particularly, Lactobacillus, Plesiomonas, and Ligilactobacillus demonstrated correlations with aadA, qnrA, blaCTX-M, intI2, and ISCR1. Based on 16S rRNA sequencing, the dominant phyla were Proteobacteria, Firmicutes, Bacteroidota, Acidobacteriota, and Actinobacteriota, with dominant genera including Pseudomonas, Ligilactobacillus, Azoarcus, Vogesella, Streptococcus, Plesiomonas, and Ferritrophicum. These findings enhance our understanding of ARG distribution in groundwater, signaling substantial contamination by ARGs and potential risks to public health.

Chiral-Boron-Complex-Catalyzed Asymmetric [3 + 2] Cycloaddition of ß-Trifluoromethyl α,ß-Unsaturated Ketones with N,N'-Cyclic Azomethine Imines.

The (R)-3,3'-(3,5-(CF3)2-C6H3)2-BINOL-boron-complex-catalyzed asymmetric 1,3-dipolar cycloaddition of ß-trifluoromethyl α,ß-unsaturated ketone with N,N'-cyclic azomethine imines was developed to afford N,N'-bicyclic pyrazolidine derivatives bearing a stereogenic carbon center containing CF3 motifs in high yields with excellent diastereo- and enantioselectivities (up to >20:1 dr, and >99% ee). This catalytic system features mild reaction conditions, high efficiency, and a broad substrate scope.

The Correlation of Mouse Double Minute 4 (MDM4) Polymorphisms (rs4245739, rs1563828, rs11801299, rs10900598, and rs1380576) with Cancer Susceptibility: A Meta-Analysis.

BACKGROUND Mouse double minute 4 (MDM4) has been extensively investigated as a negative regulator of P53, its negative feedback loop, and the effect of its genetic polymorphisms on cancers. However, many studies showed varying and even conflicting results. Therefore, we employed meta-analysis to further assess the intensity of the connection between MDM4 polymorphisms and malignancies. MATERIAL AND METHODS We searched eligible articles in 5 databases (Cochrane Library, PubMed, Web of Science, Wan Fang Database, and China National Knowledge Infrastructure) up to August 2021. Odds ratios (ORs) and 95% confidence intervals (CIs) were utilized to probe the correlation of 5 MDM4 polymorphisms (rs4245739, rs1563828, rs11801299, rs10900598, and rs1380576) with carcinomas. We employed meta-regression and subgroup analysis to probe for sources of heterogeneity; Funnel plots, Begg's test, and Egger's test were used to evaluate publication bias. Sensitivity analysis was applied to assess the stability of the study. RESULTS Twenty-two studies, comprising 77 reports with 29 853 cases and 72 045 controls, were included in our meta-analysis. We found that rs4245739 polymorphism was a factor in reducing overall cancer susceptibility (dominant model, OR=0.85, 95% CI=0.76-0.95; heterozygous model, OR=0.86, 95% CI=0.78-0.96; additive model, OR=0.87, 95% CI=0.79-0.95), especially in Asian populations, and it also reduces the risk for esophageal squamous cell carcinoma (ESCC). The remaining 4 SNPs were not associated with cancers. CONCLUSIONS The rs4245739 polymorphism might reduce the risk of malignancies, especially in Asian populations, and it is a risk-reducing factor for ESCC incidence. However, rs1563828, rs11801299, rs10900598, and rs1380576 are not relevant to cancer susceptibility.

Risk factors and prognosis of sentinel lymph node metastasis in breast-conserving breast cancer: A retrospective study based on the SEER database.

At present, the risk factors and prognosis of sentinel lymph node metastasis (SLNM) are analyzed based on the study of axillary lymph node metastasis, but whether there is a difference between the two is unclear. Therefore, an accurate and appropriate predictive model needs to be proposed to evaluate patients undergoing sentinel lymph node biopsy (SLNB) for breast cancer. We selected 16983 women with breast cancer from the Surveillance Epidemiology and End Results (SEER) database. They were randomly assigned to two cohorts, one for development (n = 11891) and one for validation (n = 5092). multi-factor logistics regression was used to distinguish risk factors affecting SLNM. The potential prognostic factors were identified using the COX regression analysis. The hazard ratio (HR) and 95% confidence interval (95%CI) were calculated for all results. Multiple Cox models are included in the nomogram, with a critical P value of .05. In order to evaluate the model's performance, Concordance index and receiver operating characteristic curves were used. Six independent risk factors affecting SLNM were screened out from the Logistic regression, including tumor location, number of regional lymph nodes (2-5), ER positive, PR positive, tumor size (T2-3), and histological grade (Grade II-III) are independent risk factors for SLNM in patients (P < .05). Eight prognostic factors were screened out in the multivariate COX regression analysis (P < .05): Age: Age 60 to 79 years, Age ≥ 80 years; Race; Histological grading: Grade II, Grade III; No radiotherapy; Tumor size: T2, T3; ER positive:, sentinel lymph node positive, married. Histological grade, tumor location, T stage, ER status, PR status and the number of SLNB are significantly correlated with axillary SLNM. Age, ethnicity, histological grade, radiotherapy, tumor size, ER status, SLN status, and marital status were independent risk factors for Breast cancer specific survival (BCSS). Moreover, the survival rate of patients with 3 positive SLNs was not significantly different from that with one or two positive SLNs, We concluded that patients with stage N1 breast cancer were exempt from axillary lymph node dissection, which is worthy of further study.

Development and validation of a CT-based radiomics model to predict survival-graded fibrosis in pancreatic ductal adenocarcinoma.

BACKGROUND: Tumor fibrosis plays an important role in chemotherapy resistance in pancreatic ductal adenocarcinoma (PDAC), however there remains a contradiction in the prognostic value of fibrosis. We aimed to investigate the relationship between tumor fibrosis and survival in patients with PDAC, classify patients into high- and low-fibrosis groups, and develop and validate a CT-based radiomics model to non-invasively predict fibrosis before treatment. MATERIALS AND METHODS: This retrospective, bicentric study included 295 patients with PDAC without any treatments before surgery. Tumor fibrosis was assessed using the collagen fraction (CF). Cox regression analysis was used to evaluate the associations of CF with overall survival (OS) and disease-free survival (DFS). Receiver operating characteristic (ROC) analyses were used to determine the rounded threshold of CF. An integrated model (IM) was developed by incorporating selected radiomic features and clinical-radiological characteristics. The predictive performance was validated in the test cohort (Center 2). RESULTS: The CFs were 38.22±6.89% and 38.44±8.66% in center 1 (131 patients, 83 males) and center 2 (164 patients, 100 males), respectively (P=0.814). Multivariable Cox regression revealed that CF was an independent risk factor in the OS and DFS analyses at both centers. ROCs revealed that 40% was the rounded cut-off value of CF. IM predicted CF with areas under the curves (AUCs) of 0.825 (95% confidence interval [CI], 0.749-0.886) and 0.745 (95% CI, 0.671-0.810) in the training and test cohorts, respectively. Decision curve analyses revealed that IM outperformed radiomics model and clinical-radiological model for CF prediction in both cohorts. CONCLUSIONS: Tumor fibrosis was an independent risk factor for survival of patients with PDAC, and a rounded cut-off value of 40% provided a good differentiation of patient prognosis. The model combining CT-based radiomics and clinical-radiological features can satisfactorily predict survival-grade fibrosis in patients with PDAC.

Learning-Assisted Fast Determination of Regularization Parameter in Constrained Image Reconstruction.

OBJECTIVE: To leverage machine learning (ML) for fast selection of optimal regularization parameter in constrained image reconstruction. METHODS: Constrained image reconstruction is often formulated as a regularization problem and selecting a good regularization parameter value is an essential step. We solved this problem using an ML-based approach by leveraging the finding that for a specific constrained reconstruction problem defined for a fixed class of image functions, the optimal regularization parameter value is weakly subject-dependent and the dependence can be captured using few experimental data. The proposed method has four key steps: a) solution of a given constrained reconstruction problem for a few (say, 3) pre-selected regularization parameter values, b) extraction of multiple approximated quality metrics from the initial reconstructions, c) predicting the true quality metrics values from the approximated values using pre-trained neural networks, and d) determination of the optimal regularization parameter by fusing the predicted quality metrics. RESULTS: The effectiveness of the proposed method was demonstrated in two constrained reconstruction problems. Compared with L-curve-based method, the proposed method determined the regularization parameters much faster and produced substantially improved reconstructions. Our method also outperformed state-of-the-art learning-based methods when trained with limited experimental data. CONCLUSION: This paper demonstrates the feasibility and improved reconstruction quality by using machine learning to determine the regularization parameter in constrained reconstruction. SIGNIFICANCE: The proposed method substantially reduces the computational burden of the traditional methods (e.g., L-curve) or relaxes the requirement of large training data by modern learning-based methods, thus enhancing the practical utility of constrained reconstruction.

Deep learning for differentiation of osteolytic osteosarcoma and giant cell tumor around the knee joint on radiographs: a multicenter study.

OBJECTIVES: To develop a deep learning (DL) model for differentiating between osteolytic osteosarcoma (OS) and giant cell tumor (GCT) on radiographs. METHODS: Patients with osteolytic OS and GCT proven by postoperative pathology were retrospectively recruited from four centers (center A, training and internal testing; centers B, C, and D, external testing). Sixteen radiologists with different experiences in musculoskeletal imaging diagnosis were divided into three groups and participated with or without the DL model's assistance. DL model was generated using EfficientNet-B6 architecture, and the clinical model was trained using clinical variables. The performance of various models was compared using McNemar's test. RESULTS: Three hundred thirty-three patients were included (mean age, 27 years ± 12 [SD]; 186 men). Compared to the clinical model, the DL model achieved a higher area under the curve (AUC) in both the internal (0.97 vs. 0.77, p = 0.008) and external test set (0.97 vs. 0.64, p < 0.001). In the total test set (including the internal and external test sets), the DL model achieved higher accuracy than the junior expert committee (93.1% vs. 72.4%; p < 0.001) and was comparable to the intermediate and senior expert committee (93.1% vs. 88.8%, p = 0.25; 87.1%, p = 0.35). With DL model assistance, the accuracy of the junior expert committee was improved from 72.4% to 91.4% (p = 0.051). CONCLUSION: The DL model accurately distinguished osteolytic OS and GCT with better performance than the junior radiologists, whose own diagnostic performances were significantly improved with the aid of the model, indicating the potential for the differential diagnosis of the two bone tumors on radiographs. CRITICAL RELEVANCE STATEMENT: The deep learning model can accurately distinguish osteolytic osteosarcoma and giant cell tumor on radiographs, which may help radiologists improve the diagnostic accuracy of two types of tumors. KEY POINTS: • The DL model shows robust performance in distinguishing osteolytic osteosarcoma and giant cell tumor. • The diagnosis performance of the DL model is better than junior radiologists'. • The DL model shows potential for differentiating osteolytic osteosarcoma and giant cell tumor.

[Identification of the polymorphs of clopidogrel bisulfate based on the steric morphology parameters of crystals].

The crystal form of solid substance had intrinsic correlation with its three dimensional crystal morphology. Based on the characterization of the three dimensional crystal morphology of clopidogrel bisulfate, this research is to establish a model based on the three dimensional morphological parameters. The granular samples composed of polymorphs of clopidogrel bisulfate and microcrystalline cellulose (MCC) were scanned by synchrotron radiation X-ray microscopic CT technology (SR-microCT) and the three dimensional structural models for which were constructed. Seven groups of three dimensional morphological parameters were calculated. Finally, the mathematical model was established with the multi-layer perception (MLP) artificial neutral network methods to identify and predict the polymorphs of clopidogrel bisulfate. The success rate of the model prediction for the polymorphs of clopidogrel bisulfate was 92.7% and the area under the ROC curve was 96.2%. The polymorphs of drugs could be identified and predicted through the numerical description of the three dimensional morphology. The volume, number of the vertices and the surface area were the major determinants for the identification of the polymorphs of clopidogrel bisulfate.

Subspace Model-Assisted Deep Learning for Improved Image Reconstruction.

Image reconstruction from limited and/or sparse data is known to be an ill-posed problem and a priori information/constraints have played an important role in solving the problem. Early constrained image reconstruction methods utilize image priors based on general image properties such as sparsity, low-rank structures, spatial support bound, etc. Recent deep learning-based reconstruction methods promise to produce even higher quality reconstructions by utilizing more specific image priors learned from training data. However, learning high-dimensional image priors requires huge amounts of training data that are currently not available in medical imaging applications. As a result, deep learning-based reconstructions often suffer from two known practical issues: a) sensitivity to data perturbations (e.g., changes in data sampling scheme), and b) limited generalization capability (e.g., biased reconstruction of lesions). This paper proposes a new method to address these issues. The proposed method synergistically integrates model-based and data-driven learning in three key components. The first component uses the linear vector space framework to capture global dependence of image features; the second exploits a deep network to learn the mapping from a linear vector space to a nonlinear manifold; the third is an unrolling-based deep network that captures local residual features with the aid of a sparsity model. The proposed method has been evaluated with magnetic resonance imaging data, demonstrating improved reconstruction in the presence of data perturbation and/or novel image features. The method may enhance the practical utility of deep learning-based image reconstruction.

Chiral-Boron-Complex-Catalyzed Asymmetric [3 + 2] Cycloaddition of 2'-Hydroxychalcones with N,N'-Cyclic Azomethine Imines.

We report the (R)-3,3'-I2-BINOL-boron-complex-catalyzed asymmetric 1,3-dipolar cycloaddition of 2'-hydroxychalcones with N,N'-cyclic azomethine imines, providing the corresponding N,N'-bicyclic pyrazolidine derivatives with three contiguous tertiary stereocenters in high yields with excellent diastereo- and enantioselectivities (up to >99:1 diastereomeric ratio and >99% enantiomeric excess). This catalytic system exhibits advantages of mild reaction conditions, high efficiency, and broad substrate scopes.

The correlation of leukocyte-specific protein 1 (LSP1) rs3817198(T>C) polymorphism with breast cancer: A meta-analysis.

BACKGROUND: Multiple studies have investigated the correlation of single nucleotide polymorphisms (SNPs) in leukocyte-specific protein 1 (LSP1) with susceptibility to breast cancer (BC) and have yielded inconsistent conclusions, particularly rs3817198(T > C). Consequently, we performed a meta-analysis to estimate this relationship more comprehensively. METHODS: Four databases were utilized to locate eligible publications: PubMed, Embase, Web of Science, and China National Knowledge Infrastructure. This meta-analysis included 14 studies, including 22 reports of 33194 cases and 36661 controls. The relationship of rs3817198 polymorphism with breast cancer was estimated using odds ratios (ORs) with 95% confidence intervals (CIs). The LSP1 co-expression network was constructed by STRING, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using DAVIDE. Download TCGA breast cancer mRNA-seq data and analyze the relationship between LSP1 expression and breast cancer chemotherapy sensitivity. RESULTS: The results indicated that rs3817198(T > C) was positively correlated to with breast malignancy (dominant model: OR = 1.11, 95%CI = 1.06-1.17; recessive model: OR = 1.10, 95%CI = 1.04-1.15; heterozygous model: OR = 1.09, 95%CI = 1.04-1.15; homozygous model: OR = 1.18, 95%CI = 1.09-1.28; additive model: OR = 1.09, 95%CI = 1.05-1.13), among Caucasians and Asians. However, rs3817198(T > C) may reduce the risk of breast carcinoma in Africans. Rs3817198(T > C) might result in breast carcinoma in individuals with BRCA1 and BRCA2 variants and can contribute to estrogen receptor (ER)-positive breast carcinoma. The expression of LSP1 was inversely correlated with the IC50 of doxorubicin (P = 8.91e-15, Cor = -0.23), 5-fluorouracil (P = 1.18e-22, Cor = -0.29), and cisplatin (P = 1.35e-42, Cor = -0.40). CONCLUSION: Our study identified that LSP1 rs3817198 polymorphism might result in breast malignancy, particularly among Caucasians and Asians, but lower breast cancer susceptibility in African populations. The expression of LSP1 was negatively correlated with the IC50 of doxorubicin, 5-fluorouracil, and cisplatin.

The correlation of BTLA rs1982809 polymorphism with cancer susceptibility: A meta-analysis of 8634 participators.

BACKGROUND: The connection between B and T lymphocyte attenuator rs1982809 polymorphism and cancer risk has been investigated by several studies and yielded different results. Therefore, we adopted the meta-analysis method to assess the association of rs1982809 polymorphism with the susceptibility of cancers synthetically. METHODS: Eligible publications were gathered by retrieving PubMed, Web of Science, Embase, Wan Fang, and China National Knowledge Infrastructure. We utilized odds ratio (OR) and 95% confidence intervals (95% CI) to assess correlation intensity and performed subgroup analyses, sensitivity analyses, and publication bias assessments. RESULTS: Six researches that encompassed 3678 cases and 4866 controls were incorporated into our meta-analysis. The rs1982809 polymorphism was proved to be connected with cancer risk by the meta-analysis in the additive model (G vs A: OR = 1.11, 95% CI = 1.04-1.19, Pheterogeneity= .096). Subgroup analyses revealed that this SNP is regarded as a susceptible factor for cancers in the dominant, heterozygous, and additive model (AG + GG vs AA: OR = 1.46, 95% CI = 1.19-1.80, Pheterogeneity= .592; AG vs AA: OR = 1.47, 95% CI = 1.19-1.82, Pheterogeneity= .536; G vs A: OR = 1.32, 95% CI = 1.12-1.55, Pheterogeneity= .745) in Caucasians; And this SNP may increase the susceptibility to lung cancer (GG vs AG+AA: OR = 1.20, CI = 1.01-1.44, Pheterogeneity= .854; G vs A: OR = 1.17, CI = 1.02-1.33, Pheterogeneity= .232). CONCLUSION: The paper concludes that B and T lymphocyte attenuator rs1982809 polymorphism may contribute to cancers, especially in Caucasians, and it may associate with lung cancer.

One-Step Regeneration of Hairy Roots to Induce High Tanshinone Plants in Salvia miltiorrhiza.

Salvia miltiorrhiza is a traditional Chinese medicinal plant of Labiatae, which has been widely utilized to treat a variety of cardiovascular and cerebrovascular diseases. However, due to the long growth cycle, low content of active ingredients, and serious quality deterioration of S. miltiorrhiza, the use of biotechnology to improve S. miltiorrhiza to meet the growing demand for clinical applications has become a research hotspot. In this study, a novel one-step hairy root regeneration method was developed, which could rapidly obtain hairy roots and regenerated plants with high tanshinone content. By optimizing the parameters of Agrobacterium rhizogenes transformation in S. miltiorrhiza, it was finally established that the explants were infected in Ar.qual (OD600 = 0.6) for 10 min, co-cultured for 3 days, and then screened on the screening medium containing 7.5 mg/l hygromycin, the maximum transformation frequency can reach 73.85%. GFP and PCR detection yielded a total of 9 positive transgenic hairy root lines and 11 positive transgenic regenerated plants. SmGGPPS1 was successfully overexpressed in positive transgenic regenerated plants, according to the results of qRT-PCR. The content of tanshinone IIA and cryptotanshinone were dramatically enhanced in transgenic regenerated plants and hairy roots by Ultra Performance Liquid Chromatography analysis. Based on the Agrobacterium-mediated transformation of S. miltiorrhiza, this study developed a new method for regenerating plants with transgenic hairy roots. This method provides a foundation for the breeding of S. miltiorrhiza and the sustainable development of medicinal plant resources, as well as provides a useful reference for the application of other species.

The Hypoglycemic Effect of JinQi Jiangtang Tablets Is Partially Dependent on the Palmatine-Induced Activation of the Fibroblast Growth Factor Receptor 1 Signaling Pathway.

JinQi Jiangtang tablet (JQJTT) is a Chinese patent medicine that has been shown to be beneficial for patients with diabetes both preclinically and clinically; however, the molecular mechanism underlying the effects of JQJTT remains unclear. In this study, surface plasmon resonance fishing was employed to identify JQJTT constituent molecules that can specifically bind to fibroblast growth factor receptor 1 (FGFR1), leading to the retrieval of palmatine (PAL), a key active ingredient of JQJTT. In vivo and in vitro experiments demonstrated that PAL can significantly stimulate FGFR1 phosphorylation and upregulate glucose transporter type 1 (GLUT-1) expression, thereby facilitating glucose uptake in insulin resistance (IR) HepG2 cells as well as alleviating hyperglycemia in diabetic mice. Our results revealed that PAL functions as an FGFR1 activator and that the hypoglycemic effect of JQJTT is partially dependent on the PAL-induced activation of the FGFR1 pathway. In addition, this study contributed to the understanding the pharmacodynamic basis and mechanism of action of JQJTT and provided a novel concept for future research on PAL.

Oxidative stress activates the TRPM2-Ca2+-NLRP3 axis to promote PM2.5-induced lung injury of mice.

PM2.5, a main particulate air pollutant, poses a serious hazard to human health. The exposure to PM2.5 increases mortality and morbidity of many respiratory diseases such as asthma, chronic obstructive pulmonary diseases and even lung cancer. The contribution of reactive oxygen species (ROS) in the PM2.5-induced acute lung injury process was confirmed in our previous research, but the molecular mechanism based for it remains unclarified. In this research, ROS-induced lung injury after exposure to PM2.5 was explored in vivo and in vitro. The in vivo study indicated that N-acetyl-L-cysteine (NAC) could attenuate the accumulation of inflammatory cells, the thickening of alveolar wall and the degree of lung injury. Furthermore, we found ROS could regulate the intracellular Ca2+ level, expression of the Transient Receptor Potential Melastatin 2 (TRPM2), NLRP3 and its downstream inflammatory factors in vivo. In vitro experiments with A549 cells and primary type II alveolar epithelium cells (SD cells) showed that ROS induced by PM2.5 exposure could mediate intracellular Ca2+ mobilization via TRPM2, with a subsequent activation of NLRP3. In our present study, we demonstrated the contribution of the ROS-TRPM2-Ca2+-NLRP3 pathway in PM2.5-induced acute lung injury and offered a potential therapeutical target valid for related pathology.

Is overnight fresh juice drinkable? The shelf life prediction of non-industrial fresh watermelon juice based on the nutritional quality, microbial safety quality, and sensory quality.

OBJECTIVE: The aim of this study was to obtain the time range of non-industrial fresh watermelon juice (FWJ), which is widely used in the catering industry under different storage conditions, with safe-drinkable quality, and the drinking time range of fresh juice with good nutritional quality and sensory quality. METHOD: The quality of non-industrial FWJ was audited by assessing the shelf life of non-industrial FWJ through microbial safety, nutritional, and sensory quality investigating during 24 h of storage at 4, 25, and 37°C. RESULTS: According to the microbial safety quality, the safe drinking time of FWJ was within 12, 4, and 4 h when stored at 4, 25, and 37°C, respectively. Based on the nutritional and sensory quality, FWJ was drinking with good quality within 2 h, and with just acceptable quality for no more than 4 h when stored at 4 or 25°C. Electronic nose and gas chromatography-mass spectrometry (GC-MS) could effectively distinguish and identify the changes in volatile components in FWJ under different storage conditions. CONCLUSION: It is a feasible method to predict the shelf life of non-industrial FWJ by this method, and hence to guarantee non-industrial FWJ being drinking with safety and health, and it might be used in many other fresh juice shelf life predictions.

Multimodal classification of drug-naïve first-episode schizophrenia combining anatomical, diffusion and resting state functional resonance imaging.

The accurate diagnosis in the early stage of schizophrenia (SZ) is of great importance yet remains challenging. The classification between SZ and control groups based on magnetic resonance imaging (MRI) data using machine learning method could be helpful for SZ diagnosis. Increasing evidence showed that the combination of multimodal MRI data might further improve the classification performance However, medication effect has a profound influence on patients' anatomical and functional features and may reduce the classification efficiency. In this paper, we proposed a multimodal classification method to discriminate drug-naïve first-episode schizophrenia patients from healthy controls (HCs) by a combined structural MRI, diffusion tensor imaging (DTI) and resting state-functional MRI data. To reduce the feature dimension of multimodal data, we applied sparse coding (SC) for feature selection and multi-kernel support vector machine (SVM) for feature combination and classification. The best classification performance with the classification accuracy of 84.29% and area under the receiver operating characteristic (ROC) curve (AUC) of 81.64% was achieved when all modality data were combined. Interestingly, the identified functional markers were mainly found in default mode network (DMN) and cerebellar connections, while the structural markers were within limbic system and prefrontal-thalamo-hippocampal circuit.

Alterations in Brain Structural Connectivity After Unilateral Upper-Limb Amputation.

Previous studies have indicated that amputation induces reorganization of functional brain network. However, the influence of amputation on structural brain network remains unclear. In this study, using diffusion tensor imaging (DTI), we aimed to investigate the alterations in fractional anisotropy (FA) network after unilateral upper-limb amputation. We acquired DTI from twenty-two upper-limb amputees (15 dominant-side and 7 nondominant-side amputees) as well as fifteen healthy controls. Using DTI tractography and graph theoretical approaches, we examined the topological changes in FA network of amputees. Compared with healthy controls, dominant-side amputees showed reduced global mean strength, increased characteristic path length, and decreased nodal strength in the contralateral sensorimotor system and visual areas. In particular, the nodal strength of the contralateral postcentral gyrus was negatively correlated with residual limb usage, representing a use-dependent reorganization. In addition, the nodal strength of the contralateral middle temporal gyrus was positively correlated with the magnitude of phantom limb sensation. Our results suggested a degeneration of FA network after dominant-side upper-limb amputation.

Dramatic improvement of the solubility of pseudolaric acid B by cyclodextrin complexation: preparation, characterization and validation.

As one of the most important technologies to improve the solubility of poorly water-soluble drugs, the solubilization effects of cyclodextrins (CDs) complexation are, on occasions, not as large as expected, which tends to detract from the wider application of CDs. In this study, a dramatic improvement of the solubility of pseudolaric acid B (PAB) by CDs has been found with a 600 fold increase by HP-ß-CD complexation. In addition, the solubility enhancement of PAB by various CDs, including α-CD, ß-CD, γ-CD, HP-ß-CD and SBE-ß-CD was investigated by phase solubility studies. The inclusion complex of PAB/HP-ß-CD was prepared by different methods and characterized by differential scanning calorimetry (DSC), powder X-ray diffractometry (XRD), nuclear magnetic resonance spectroscopy ((1)H NMR) together with molecular simulation. The results indicated that the solubility of PAB was increased to 15.78mgmL(-1) in the presence of 30% HP-ß-CD, which is a 600 fold increase compared with that in pure water. And the chemical stability of PAB in PBS (pH 7.4) can be enhanced. The results of DSC and XRD showed the absence of crystallinity in the PAB/HP-ß-CD inclusion complex prepared by the saturated water solution method. The results of (1)H NMR together with molecular simulation indicated the conjugated diene side-chain of PAB was included into the cavity of HP-ß-CD, with the free energy of -20.34±4.69kJmol(-1). While the enzymatic degradation site of the carboxyl polar bond is located in the hydrophilic outer of HP-ß-CD resulted in no significant difference for the enzymatic degradation rate between PAB and PAB/HP-ß-CD complexes in rat plasma. In summary, the PAB/HP-ß-CD inclusion complex prepared in this study can greatly improve the solubility and chemical stability of PAB, which will result in the in vivo administration of PAB as a liquid solution.

A study of 131iodine-labeling of histamine-indomethacin: its in vivo therapeutic effect and anti-tumor mechanisms in Lewis-bearing lung cancer.

BACKGROUND: In our research,we study the effect of 131iodine-labeled histamine-indomethacin (131I-His-IN). We focus on its in vivo therapeutic effect and anti-tumor mechanisms in Lewis-bearing lung cancer. METHODS: 131I-His-IN was administered by garage to the mice. At different timepoints, we made autoradiography (ARG) slices to observe the distribution of 131I-His-IN in the cellular, and the sliced samples underwent hematoxylin and eosin (HE) staining for observation of tumor necrosis. Before treatment, the groups of mice underwent 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography-computed tomography (PET-CT) scans ,and they were then given physiologic saline, iodine 131 (131I), indomethacin (IN), Histamine-indomethacin (His-IN), and 131I-His-IN, respectively, three times daily for seven days. Seven days later, all the mice underwent 18F-FDG PET-CT scans again. We calculated the maximum standard uptake value (SUVmax) of the region of interest (ROI) and tumor inhibition rate at the same time. RESULTS: In ARG groups, black silver particle was concentrated in the nucleus and cytoplasm. 131I-His-IN mainly concentrated in tumor tissues. At 8 hours after 131I-His-IN, the radioactivity uptake in tumor tissue was higher than in other organs (F=3.46, P<0.05). For the 18F-FDG PET-CT imaging, the tumor tissuses SUVmax of the ROI was lower compared to other groups after the treatment with 131I-His-IN. The tumor inhibitory rate (54.8%) in 131I-His-IN group was higher than in other groups, too. In the 131I-His-IN group the vascular endothelial growth factor (VEGF) decreased gradually compared to other groups. The tumor tissue necrotized obviously in 131I-His-IN group. CONCLUSIONS: Through these animal experiments, we found 131I-His-IN could inhibit the Lewis lung cancer cells. 131I-His-IN focused at the cell nucleus and cytoplasm. It could reduce VEGF and increase tumor inhibitory rate. At the same time, 18F-FDG PET-CT scan could be used for a curative effect and monitoring of disease prognosis.