Novel artificial intelligence machine learning approaches to precisely predict survival and site-specific recurrence in cervical cancer: A multi-institutional study

BackgroundMachine learning (ML) has been gradually integrated into oncologic research but seldom applied to predict cervical cancer (CC), and no model has been reported to predict survival and site-specific recurrence simultaneously. Thus, we aimed to develop ML models to predict survival and site-specific recurrence in CC and to guide individual surveillance.MethodsWe retrospectively collected data on CC patients from 2006 to 2017 in four hospitals. The survival or recurrence predictive value of the variables was analyzed using multivariate Cox, principal component, and K-means clustering analyses. The predictive performances of eight ML models were compared with logistic or Cox models. A novel web-based predictive calculator was developed based on the ML algorithms.ResultsThis study included 5112 women for analysis (268 deaths, 343 recurrences): (1) For site-specific recurrence, larger tumor size was associated with local recurrence, while positive lymph nodes were associated with distant recurrence. (2) The ML models exhibited better prognostic predictive performance than traditional models. (3) The ML models were superior to traditional models when multiple variables were used. (4) A novel predictive web-based calculator was developed and externally validated to predict survival and site-specific recurrence.ConclusionML models might be a better analytic approach in CC prognostic prediction than traditional models as they can predict survival and site-specific recurrence simultaneously, especially when using multiple variables. Moreover, our novel web-based calculator may provide clinicians with useful information and help them make individual postoperative follow-up plans and further treatment strategies.     

Interrogation of phosphor-specific interaction on a high-throughput label-free optical biosensor system–Epic® system

The Epic^® system, a high-throughput label-free optical biosensor system, is applied for the biochemical interrogation of phosphor-specific interactions of the 14-3-3 protein and its substrates. It has shown the capability not only for high-throughput characterization of binding rank and affinity but also for the exploration of potential interacting kinases for the substrates. A perspective of biochemical applications for diagnostics and biomarker discovery, as well as cell-based applications for endogenous receptors and viral infection characterization, are also provided.     

Live/dead state is not the factor influencing adhesion ability of Bifidobacterium animalis KLDS2.0603

Two essential requirements for probiotic bifidobacteria are that they be “live” and have “colonization” ability, following FAO/WHO guideline recommendations. The amount of research on the adhesion ability of bifidobacteria compares poorly with that of other probiotic bacteria, such as lactobacilli. The aim of the present study was to determine how gastrointestinal conditions affect the adhesion ability of bifidobacteria, and to investigate the relationship between the adhesion ability and the live/dead state of bifidobacteria. The adhesion ability of Bifidobacterium animalis KLDS2.0603 that had been subjected to the digestive enzymes, pepsin, trypsin, and proteinase K, was decreased significantly, but these treatments did not significantly change the strain’s survival rates, which were 98.78%, 97.60%, and 97.63% respectively. B. animalis KLDS2.0603 subjected to LiCl retained its adhesion ability but had a lower survival rate (59.28%) than the control group (P<0.01). B. animalis KLDS 2.0603 subjected to sodium metaperiodate exhibited higher adhesion ability than the control group (P<0.01), but the bacterial cells were killed totally. The results of transmission electron microscopy and laser scanning confocal microscopy showed that live/dead state of bifidobacteria was not one of the main factors that affected the adhesion ability of bifidobacteira, and that the substances affecting the adhesion ability of bifidobacteria were on the outer surface layer of the bifidobacterial cells. Our results also indicated that the substances related to the adhesion ability of bifidobacteria are proteinaceous. The above results will help us to understand the adhesion and colonization processes of bifidobacteria in the human gastrointestinal tract.     

Molecular characterization of methicillin-resistant Panton-valentine leukocidin positive <Emphasis Type="Italic">staphylococcus aureus</Emphasis> clones disseminating in Tunisian hospitals and in the community

Background

The spread of MRSA strains at hospitals as well as in the community are of great concern worldwide. We characterized the MRSA clones isolated at Tunisian hospitals and in the community by comparing them to those isolated in other countries.

Results

We characterized 69 MRSA strains isolated from two Tunisian university hospitals between the years 2004-2008. Twenty-two of 28 (79%) community-associated MRSA (CA-MRSA) strains and 21 of 41 (51%) healthcare-associated MRSA (HA-MRSA) strains were PVL-positive. The PVL-positive strains belonged to predicted founder group (FG) 80 in MLST and carried either type IVc SCCmec or nontypeable SCCmec that harbours the class B mec gene complex. In contrast, very diverse clones were identified in PVL-negative strains: three FGs (5, 15, and 22) for HA-MRSA strains and four FGs (5, 15, 45, and 80) for CA-MRSA strains; and these strains carried the SCCmec element of either type I, III, IVc or was nontypeable. The nucleotide sequencing of phi7401PVL lysogenized in a CA-MRSA strain JCSC7401, revealed that the phage was highly homologous to phiSA2mw, with nucleotide identities of more than 95%. Furthermore, all PVL positive strains were found to carry the same PVL phage, since these strains were positive in two PCR studies, identifying gene linkage between lukS and mtp (major tail protein) and the lysogeny region, both of which are in common with phi7401PVL and phiSa2mw.

Conclusions

Our experiments suggest that FG80 S. aureus strains have changed to be more virulent by acquiring phi7401PVL, and to be resistant to β-lactams by acquiring SCCmec elements. These novel clones might have disseminated in the Tunisian community as well as at the Tunisian hospitals by taking over existing MRSA clones.

     

Design,synthesis, and biological evaluation of novel substituted thiourea derivatives as potential anticancer agents for NSCLC by blocking K-Ras protein-effectors interactions

Abstract

Mutation of the proto-oncogene K-Ras is one of the most common molecular mechanisms in non-small cell lung cancer. Many drugs for treating lung cancer have been developed, however, due to clinical observed K-Ras mutations, corresponding chemotherapy and targeted therapy for such mutation are not efficient enough. In this study, on the basis of the crystal structure of K-Ras, 21 analogues (TKR01–TKR21) containing urea or thiourea were rationally designed, which can effectively inhibit the lung cancer cell A549 growth. The designing of these compounds was based on the structure of K-Ras protein, and the related groups were replaced by bioisosteres to improve the affinity and selectivity. Biological testing revealed that compound TKR15 could significantly inhibit the proliferation of A549 cell with IC₅₀ of 0.21?µM. Docking analysis showed that the TKR15 can effectively bind to the hydrophobic cavity and form a hydrogen bond with the Glu37. In addition, through flow apoptosis assay and immunofluorescence staining assay, it confirmed that this compound can inhibit A549 cell proliferation with the mechanism of blocking K-Ras^G12V protein and effector proteins interactions through the apoptotic pathway. In conclusion, our studies in finding novel potent compound (TKR15) with confirmed mechanism showed great potential for further optimisation and other medicinal chemistry relevant studies.     

CARAGANA FABR. PROMOTES REVEGETATION AND SOIL REHABILITATION IN SALINE-ALKALI WASTELAND

To determine how plantations of Caragana microphylla shrubs affect saline-alkali soil amelioration and revegetation, we investigated the vegetation and sampled soils from saline-alkali wasteland (SAW), perennial Caragana forestland (PCF), Caragana forest after fire disturbance (CFF). Results showed that with the development of Caragana Fabr., highly dominant species of Poaceae family, including Elymus dahuricus, Thermopsis lanceolata, Stipa tianschanica, died out in PCF. Moreover, Papilionaceae family, including Lespedeza indica, Oxytropis psammocharis, and Astragalus scaberrimus, was established both in PCF and CFF. Phytoremediation of saline-alkali wasteland (SAW) was achieved by plantation, resulting in the reduced soil pH, sodium adsorption ratio, exchangeable sodium percentage, salinity, and Na⁺ concentration around Caragana shrubs. Greater amounts of soil organic, total nitrogen, ammonium nitrogen, available phosphorus, and available potassium were observed in PCF topsoil than in SAW topsoil. The concentration of mineralized N in PCF soil was significantly lower than that in SAW soil at all sampled depths, indicating that Caragana shrubs were just using N and therefore less measured in soils. Fire disturbance resulted in decreased soil pH and salinity, but increased organic content, total nitrogen, and ammonium nitrogen. The improved soil parameters and self-recovery of shrubs indicated that Caragana shrubs were well established after burning event.     

MicroRNA-92a Upholds Bmp Signaling by Targeting noggin3 during Pharyngeal Cartilage Formation

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Highlights? mir92a inactivation leads to loss of pharyngeal cartilages in zebrafish embryos ? mir92a is required for chondrogenic progenitor proliferation and survival ? Bmp signaling is positively regulated by mir92a in the pharyngeal region ? nog3 mRNA is degraded by mir92a to maintain Bmp activity     

Identification and Validation of Urinary Metabolite Biomarkers for Major Depressive Disorder

Major depressive disorder (MDD) is a widespread and debilitating mental disorder. However, there are no biomarkers available to aid in the diagnosis of this disorder. In this study, a nuclear magnetic resonance spectroscopy–based metabonomic approach was employed to profile urine samples from 82 first-episode drug-naïve depressed subjects and 82 healthy controls (the training set) in order to identify urinary metabolite biomarkers for MDD. Then, 44 unselected depressed subjects and 52 healthy controls (the test set) were used to independently validate the diagnostic generalizability of these biomarkers. A panel of five urinary metabolite biomarkers—malonate, formate, N-methylnicotinamide, m-hydroxyphenylacetate, and alanine—was identified. This panel was capable of distinguishing depressed subjects from healthy controls with an area under the receiver operating characteristic curve (AUC) of 0.81 in the training set. Moreover, this panel could classify blinded samples from the test set with an AUC of 0.89. These findings demonstrate that this urinary metabolite biomarker panel can aid in the future development of a urine-based diagnostic test for MDD.Major depressive disorder (MDD)¹ is a debilitating mental disorder affecting up to 15% of the general population and accounting for 12.3% of the global burden of disease (1, 2). Currently, the diagnosis of MDD still relies on the subjective identification of symptom clusters rather than empirical laboratory tests. The current diagnostic modality results in a considerable error rate (3), as the clinical presentation of MDD is highly heterogeneous and the current symptom-based method is not capable of adequately characterizing this heterogeneity (4). An approach that can be used to circumvent these limitations is to identify disease biomarkers to support objective diagnostic laboratory tests for MDD.Metabonomics, which can measure the small molecules in given biosamples such as plasma and urine without bias (5), has been extensively used to characterize the metabolic changes of diseases and thus facilitate the identification of novel disease-specific signatures as putative biomarkers (6–10). Nuclear magnetic resonance (NMR) spectroscopy–based metabonomic approaches characterized by sensitive, high-throughput molecular screening have been employed previously in identifying novel biomarkers for a variety of neuropsychiatric disorders, including stroke, bipolar disorder, and schizophrenia (11–13).Specifically with regard to MDD, several animal studies have already characterized the metabolic changes in the blood and urine (14–19). These studies provide valuable clues as to the pathophysiological mechanism of MDD. However, no study has been designed with the aim of diagnosing this disease. Recently, using an NMR-based metabonomic approach, this research group identified a unique plasma metabolic signature that enables the discrimination of MDD from healthy controls with both high sensitivity and specificity (20). These findings motivated further study on urinary diagnostic metabolite biomarkers for MDD, which would be more valuable from a clinical applicability standpoint, as urine can be more non-invasively collected. Moreover, previous studies have also demonstrated the feasibility of identifying diagnostic metabolite biomarkers of psychiatric disorders in the urine. For example, using an NMR-based metabonomics approach, Yap et al. (21) identified a unique urinary metabolite signature that clearly discriminated autism patients from healthy controls. As systemic metabolic disturbances have been observed in the urine of a depressed animal model, it is likely that diagnostic metabolite markers for MDD can be detected in human urine.Therefore, in this study, NMR spectroscopy combined with multivariate pattern recognition techniques were used to profile 82 first-episode drug-naïve MDD subjects and 82 healthy controls (the training set) in order to identify potential metabolite biomarkers for MDD. Furthermore, 44 unselected MDD subjects and 52 healthy controls (the test set) were employed to independently validate the diagnostic performance of these urinary metabolite biomarkers.