Revolutionizing pediatric neuroblastoma treatment: unraveling new molecular targets for precision interventions.

Neuroblastoma (NB) is the most frequent solid tumor in pediatric cases, contributing to around 15% of childhood cancer-related deaths. The wide-ranging genetic, morphological, and clinical diversity within NB complicates the success of current treatment methods. Acquiring an in-depth understanding of genetic alterations implicated in the development of NB is essential for creating safer and more efficient therapies for this severe condition. Several molecular signatures are being studied as potential targets for developing new treatments for NB patients. In this article, we have examined the molecular factors and genetic irregularities, including those within insulin gene enhancer binding protein 1 (ISL1), dihydropyrimidinase-like 3 (DPYSL3), receptor tyrosine kinase-like orphan receptor 1 (ROR1) and murine double minute 2-tumor protein 53 (MDM2-P53) that play an essential role in the development of NB. A thorough summary of the molecular targeted treatments currently being studied in pre-clinical and clinical trials has been described. Recent studies of immunotherapeutic agents used in NB are also studied in this article. Moreover, we explore potential future directions to discover new targets and treatments to enhance existing therapies and ultimately improve treatment outcomes and survival rates for NB patients.

Computational insights into KRAS G12C inhibition: exploring possible repurposing of Azacitidine and Ribavirin.

Kirsten rat sarcoma (KRAS) stands out as the most prevalent mutated oncogene, playing a crucial role in the initiation and progression of various cancer types, including colorectal, lung and pancreatic cancer. The oncogenic modifications of KRAS are intricately linked to tumor development and are identified in 22% of cancer patients. This has spurred the necessity to explore inhibition mechanisms, with the aim of investigating and repurposing existing drugs for diagnosing cancers dependent on KRAS G12C In this investigation, 26 nucleoside-based drugs were collected from literature to assess their effectiveness against KRAS G12C. The study incorporates in-silico molecular simulations and molecular docking examinations of these nucleoside-derived drugs with the KRAS G12C protein using Protein Data Bank (PDB) ID: 5V71. The docking outcomes indicated that two drugs, Azacitidine and Ribavirin, exhibited substantial binding affinities of -8.7 and -8.3 kcal/mol, respectively. These drugs demonstrated stability in binding to the active site of the protein during simulation studies. Root mean square deviation (RMSD) analyses indicated that the complexes closely adhered to an equilibrium RMSD value ranging from 0.17 to 0.2 nm. Additionally, % occupancies, bond angles and the length of hydrogen bonds were calculated. These findings suggest that Azacitidine and Ribavirin may potentially serve as candidates for repurposing in individuals with KRAS-dependent cancers.Communicated by Ramaswamy H. Sarma.

Systematic evaluation of the Precision ID GlobalFiler™ NGS STR panel v2 using single-source samples of various quantity and quality and mixed DNA samples.

Massively parallel sequencing (MPS) techniques were developed approximately 15 years ago. Meanwhile, several MPS kits for forensic identification, phenotypic information, ancestry, and mitochondrial DNA analysis have been developed and their use has been established. Sequencing short tandem repeats (STRs) has certain advantages over the currently used length-based genotyping methods, which are based on PCR amplification followed by capillary electrophoresis (CE). MPS is more discriminative and includes the possibility of testing high numbers of targets (> 100), different types of markers [STRs and single nucleotide polymorphisms (SNPs)], as well as the use of smaller amplicons (< 300 bp). This study evaluated in 24 experimental runs the Precision ID GlobalFiler™ NGS STR panel v2 from ThermoFisher, which targets 31 autosomal STRs, amelogenin, and three Y-markers (one STR, SRY, and Yindel). Single-source samples were used in 18 experimental runs, for systematic evaluation. These included assessing library preparation benchmark conditions, limited DNA input, as well as testing repeatability, number of samples per run, and degraded DNA samples. Full profiles were consistently obtained from as little as 50 pg DNA input. Using the optional recovery PCR method improved outcomes for samples with low DNA input. Full profiles were also obtained from severely degraded DNA samples with degradation indices (DI) of > 60. In addition, six experimental runs were performed testing various two-person mixtures with mixture ratios ranging from 1:20 to 20:1. Major and minor contributors were distinguishable by their read counts (coverage), because less DNA input yielded lower read counts, analogous to the traditional CE technology, where less DNA produces lower peak heights. Mixture ratios of approximately 1:1 were indistinguishable, while a greater imbalance, i.e., higher mixture ratios, made the mixture more distinguishable between major and minor contributors. Based on this information, the highest success rate of correctly deconvoluted four-allelic loci was from mixtures with 1:3 ratios. At higher mixture ratios, the drop-out rate of the minor contributor increased, reducing the number of four-allelic loci.

Intraconal Retroorbital Cavernous Hemangioma - A Case Report.

Cavernous hemangioma of orbit is a benign, noninfiltrative, slowly progressive vascular neoplasm. It is usually asymptomatic but patients may present with proptosis and diminished vision due to compression of second cranial nerve, optic nerve. This can be usually diagnosed with the help of clinical examination and computed tomography (CT) or magnetic resonance imaging (MRI). Small sized tumours are worth wait and watch while large ones need surgical excision. In our case report, A 65-year-old male patient presented to the head and neck surgery with proptosis of left eye since 5 years along with decreased vision since 4 years. MDCT scan (orbits plain) suggestive of large solid retroocular, intraconal mass in left orbit leading to proptosis of left eyeball. The patient underwent excision of tumour through a transnasal endoscopic approach. Histopathological examination of the tumour identified as cavernous hemangioma. It is safe and effective way to access and excise the orbital tumours through the transnasal endoscopic approach. It is essential to have experienced surgeon in endoscopic procedures. The patient had satisfactory results at three months follow up and showed no symptoms or relapse on CT scans of orbital region. Supplementary Information: The online version contains supplementary material available at 10.1007/s12070-023-03984-y.

Short Stature for Age in Children of 5 to 16 Years: The First Research from the Northern Himalayan Region of India.

Introduction: Anthropometric parameters play vital role in monitoring growth in pediatrics. Many etiological factors lead to short stature. So, before assessing the etiological factors short stature needs to be addressed. This study aimed to screen short stature for age in school-going children aged 5 to 16 years in Uttarakhand. Material and Methods: In this cross-sectional observational study, the height (through stadiometer) and weight (through weight machine) of 4189 students of government and private school in Rishikesh (Uttarakhand) aged 5-16 years were measured after the verbal assent of the students and individual's height is in the 3rd percentile for the mean height of a given age, sex, and population group and was considered short stature. The data collection was performed from October 2019 to July 2021. The data were categorized according to different age groups to 5-8 years, 9-12 years, and 13-16 years. The data were recorded in Microsoft (MS) Excel spreadsheet program. Statistical Package for the Social Sciences (SPSS) v23 (IBM Corp.) was used for data analysis. Descriptive statistics were elaborated in the form of means or standard deviations and medians or Interquartile range IQRs for continuous variables and frequencies and percentages for categorical variables. The Chi-square test was used for group comparisons for categorical data. Results: 7.1% of children were short stature (height 143.16 ± 15.09 cm) in the Himalayan belt, and males were more prone to short stature at age of 9-12 years. Conclusion: In the growing phase of children, the etiology of short stature has to be rectified, so the children can achieve such proper growth. Parents and physicians have to assess and monitor the growth of children timely. This study can be a stepping stone for further epidemiological studies.

An integrated pipeline for prediction of Clostridioides difficile infection.

With the expansion of electronic health records(EHR)-linked genomic data comes the development of machine learning-enable models. There is a pressing need to develop robust pipelines to evaluate the performance of integrated models and minimize systemic bias. We developed a prediction model of symptomatic Clostridioides difficile infection(CDI) by integrating common EHR-based and genetic risk factors(rs2227306/IL8). Our pipeline includes (1) leveraging phenotyping algorithm to minimize temporal bias, (2) performing simulation studies to determine the predictive power in samples without genetic information, (3) propensity score matching to control for the confoundings, (4) selecting machine learning algorithms to capture complex feature interactions, (5) performing oversampling to address data imbalance, and (6) optimizing models and ensuring proper bias-variance trade-off. We evaluate the performance of prediction models of CDI when including common clinical risk factors and the benefit of incorporating genetic feature(s) into the models. We emphasize the importance of building a robust integrated pipeline to avoid systemic bias and thoroughly evaluating genetic features when integrated into the prediction models in the general population and subgroups.

Comparison of Mechanical Properties, Physical Properties, and Biocompatibility of Four Different Denture Base Resins: An In vitro Study.

Four new dental replacement base tars were evaluated in vitro to determine their mechanical qualities, authentic properties, and biocompatibility. Materials and Methods: In this experiment, we employed SR Triplet HOT (a fiber-developed heat fix tar), Sunflex (a multipurpose force fix sap), Trevalon-Hello (a high-impact heat fix tar), DPI (a digital pigment imaging system), and a variety of other pigments and inks (normal power fix tar). For these models, the ISO specification 1567 for dental substitute base gums called for testing of flexural strength, hardness, impact strength, water sorption and dissolvability, and cytotoxicity. Results: All the strength and mechanical properties tested had a statistically significant difference when intergroup analysis was performed. Conclusion: The exceptional physical and mechanical capabilities of the Sunflex denture base resin, together with its biocompatibility with oral tissues, make it a good candidate for use as a denture base material in routine clinical practice.

Point-of-Care Serum Amyloid A as a Diagnostic Marker for Neonatal Sepsis.

OBJECTIVES: To evaluate diagnostic accuracy of point-of-care Serum Amyloid A (POC-SAA) and its comparison with procalcitonin for diagnosis of neonatal sepsis. METHODS: The present diagnostic accuracy study consecutively recruited neonates with suspected sepsis. Blood samples for sepsis screen, culture, high sensitivity C-reactive protein (CRP) (hs-CRP, as a part of sepsis screen), procalcitonin and POC-SAA were collected before starting antibiotics. The optimum cut-off level of biomarkers (POC-SAA and procalcitonin) was determined by receiver-operating-characteristics curve (ROC) analysis. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of POC-SAA and procalcitonin were derived for 'clinical sepsis (neonates with suspected sepsis and either positive sepsis screen and/or blood culture)' and 'culture positive sepsis' (neonates with suspected sepsis and positive blood culture). RESULTS: Seventy-four neonates with mean±SD gestational age of 32.8±3.7 wk were evaluated for suspected sepsis, of which the proportion of 'clinical sepsis' and 'culture positive sepsis' was 37.8% had 16.2%, respectively. At a cut-off of 25.4 mg/L, POC-SAA had sensitivity, specificity, PPV and NPV of 53.6%, 80.4%, 62.5% and 74.0%, respectively for diagnosis of clinical sepsis. The sensitivity, specificity, PPV and NPV of POC-SAA for detection of culture positive sepsis were 83.3%, 61.3%, 29.4% and 95.0%, respectively at a cut-off of 10.3 mg/L. There was no significant difference in the diagnostic accuracy of biomarkers for detection of culture positive sepsis (area under the curve, AUC of POC-SAA vs. procalcitonin vs. hs-CRP: 0.72 vs. 0.85 vs. 0.85; p = 0.21). CONCLUSIONS: POC-SAA is comparable to procalcitonin and hs-CRP for diagnosis of neonatal sepsis.

Predictors of Post-Stroke Depression: A Retrospective Cohort Study.

Despite reports of a high incidence and various predictors of post-stroke depression (PSD), the underdiagnosis and undertreatment rates of PSD are still high. This study aimed to examine the incidence of depression in stroke patients and identify factors associated with PSD. This was a retrospective cohort study on ischemic stroke patients from the Geisinger Neuroscience Ischemic Stroke (GNSIS) registry. The following statistical analyses were performed to predict PSD in the studied population: a Kaplan−Meier estimator and a Cox proportional hazards model. A total of 5882 patients were included in the study. The median age at the time of an ischemic stroke was 72 years and 56% were males. A total of 294 patients were diagnosed with PSD within one year of a stroke. The cumulative incidence of depression was found to be 6.4% (95% CI 5.7−7.1%) at one year for the entire cohort. Women were found to have a higher risk of PSD than men (HR for women = 1.47, 95% CI 1.18−1.85, p = 0.001). A history of prior stroke (HR = 1.58, 95% CI 1.18−2.11, p = 0.002) and myocardial infarction (HR = 1.47, 95% CI 1.05−2.06, p = 0.025) were associated with PSD. Medicaid patients had a higher risk for PSD (HR = 2.16, 95% CI 1.5−3.12, p < 0.001) than those with commercial insurance or health maintenance organization plans. Our findings showed that women, patients with a history of prior stroke or myocardial infarction, and with Medicaid insurance were more likely to develop PSD. Through an observational study on the EHR data, we confirmed that chronic stress, including financial and health-related stress, irrespective of age, significantly increased the risk for PSD.

Investigation of the Utility of Features in a Clinical De-identification Model: A Demonstration Using EHR Pathology Reports for Advanced NSCLC Patients.

BACKGROUND: Electronic health record (EHR) systems contain a large volume of texts, including visit notes, discharge summaries, and various reports. To protect the confidentiality of patients, these records often need to be fully de-identified before circulating for secondary use. Machine learning (ML) based named entity recognition (NER) model has emerged as a popular technique of automatic de-identification. OBJECTIVE: The performance of a machine learning model highly depends on the selection of appropriate features. The objective of this study was to investigate the usability of multiple features in building a conditional random field (CRF) based clinical de-identification NER model. METHODS: Using open-source natural language processing (NLP) toolkits, we annotated protected health information (PHI) in 1,500 pathology reports and built supervised NER models using multiple features and their combinations. We further investigated the dependency of a model's performance on the size of training data. RESULTS: Among the 10 feature extractors explored in this study, n-gram, prefix-suffix, word embedding, and word shape performed the best. A model using combination of these four feature sets yielded precision, recall, and F1-score for each PHI as follows: NAME (0.80; 0.79; 0.80), LOCATION (0.85; 0.83; 0.84), DATE (0.86; 0.79; 0.82), HOSPITAL (0.96; 0.93; 0.95), ID (0.99; 0.82; 0.90), and INITIALS (0.97; 0.49; 0.65). We also found that the model's performance becomes saturated when the training data size is beyond 200. CONCLUSION: Manual de-identification of large-scale data is an impractical procedure since it is time-consuming and subject to human errors. Analysis of the NER model's performance in this study sheds light on a semi-automatic clinical de-identification pipeline for enterprise-wide data warehousing.

Biliary diversion in progressive familial intrahepatic cholestasis: a systematic review and meta-analysis.

BACKGROUND: Biliary diversion (BD) is indicated in progressive familial intrahepatic cholestasis (PFIC) with refractory pruritus. Three types-partial external biliary drainage (PEBD), partial internal biliary drainage (PIBD), and ileal exclusion (IE) are described, with no consensus about the relative efficacy of these procedures. METHODS: PubMed, Scopus, and Google Scholar were searched for publications on PFIC and BD. Improvement in pruritus, serum bile acid (BA), and need for liver transplantation (LT) were compared between the various BD procedures. RESULTS: 25 studies [424 children (PEBD-301, PIBD-93, IE-30)] were included. Pruritus resolved in 59.5% [PIBD:72% (95%CI 43-96%), PEBD:57% (95%CI 43-71%) and IE:48% (95%CI 14-82%)] cases. Significant overlap in confidence intervals indicated no significant differences. Absolute decrease in BA (AUROC-0.72) and bilirubin (AUROC-0.69) discriminated responders and non-responders. Eventually, 27% required LT: PIBD 10.7%, PEBD32%, IE 27%. The post-operative BA (AUROC-0.9) and bilirubin (AUROC-0.85) determined need for LT. Complications were commoner in PEBD than PIBD (38% vs 21.8%: p=0.02). CONCLUSION: 59.5% children have pruritus relief after BD and 27% need LT. PIBD has lower complications and LT requirement than PEBD. However, this requires cautious interpretation as the 2 groups differed in PFIC type and follow-up duration.

Evaluation of ArmedXpert software tools, MixtureAce and Mixture Interpretation, to analyze MPS-STR data.

Massively parallel sequencing (MPS) technologies have revolutionized studies of genomic variations and transformed DNA analysis in multiple fields. Assays based on MPS must be capable of discriminating variations introduced by the method, i.e. artifacts from true polymorphisms. In PCR-MPS methods targeting microsatellite markers, artifacts can arise from PCR mis-incorporation, PCR strand slippage (stutter), and sequencing error. Reliable detection of artifacts in mixed DNA samples is a significant challenge that must be addressed in forensic DNA analysis. The ArmedXpert (NicheVision) software tools, MixtureAce™ and Mixture Interpretation, can analyze MPS data by categorizing sequence reads in alleles, stutter, and non-stutter artifacts and analyzing autosomal STR loci of mixed samples. In this study, we evaluated the ArmedXpert tools for the analysis of STR profiles of single-sourced and mixed samples generated by the ForenSeq™ DNA Signature Prep kit (Verogen). Data from eight experimental runs (240 samples) were analyzed: one benchmark run, two runs testing sensitivity with down to 50 pg DNA input, one run testing artificially degraded samples and DNA derived from bones, blood cards and teeth, as well as four runs with mixed DNA samples of varying ratios, sex, and different number of contributors (two to six). The MixtureAce stutter thresholds were initially set following the recommendations from Verogen, plus a non-stutter artifact threshold was set at 5% of allele read counts. A benchmark run, of 30 samples, plus two controls, containing 2310 total alleles, revealed over 5000 artifacts, above an analytical threshold of 10. A total of 4869 artifacts were correctly classified, while 435 were mis-classified as alleles due to exceedance of initial threshold settings. False positives must be resolved by an analyst, which can be time consuming. Stutter thresholds were adjusted based on the benchmark data and the samples were re-tested, resulting in only 57 false positive allele calls. The revised settings were then used in the analysis of the remaining seven experimental runs. Results show that MixtureAce can accurately classify artifacts and alleles when laboratory-specific threshold settings are used. The Mixture Interpretation tool was applied on two- and three-person mixtures. This tool utilized the analyzed data from MixtureAce to calculate, based on the number of alleles at a locus and their read counts, possible deconvolution outcomes with their respective ratios.

Cerebrospinal fluid CD4+ T cell infection in humans and macaques during acute HIV-1 and SHIV infection.

HIV-1 replication within the central nervous system (CNS) impairs neurocognitive function and has the potential to establish persistent, compartmentalized viral reservoirs. The origins of HIV-1 detected in the CNS compartment are unknown, including whether cells within the cerebrospinal fluid (CSF) produce virus. We measured viral RNA+ cells in CSF from acutely infected macaques longitudinally and people living with early stages of acute HIV-1. Active viral transcription (spliced viral RNA) was present in CSF CD4+ T cells as early as four weeks post-SHIV infection, and among all acute HIV-1 specimens (N = 6; Fiebig III/IV). Replication-inactive CD4+ T cell infection, indicated by unspliced viral RNA in the absence of spliced viral RNA, was even more prevalent, present in CSF of >50% macaques and human CSF at ~10-fold higher frequency than productive infection. Infection levels were similar between CSF and peripheral blood (and lymph nodes in macaques), indicating comparable T cell infection across these compartments. In addition, surface markers of activation were increased on CSF T cells and monocytes and correlated with CSF soluble markers of inflammation. These studies provide direct evidence of HIV-1 replication in CD4+ T cells and broad immune activation in peripheral blood and the CNS during acute infection, likely contributing to early neuroinflammation and reservoir seeding. Thus, early initiation of antiretroviral therapy may not be able to prevent establishment of CNS viral reservoirs and sources of long-term inflammation, important targets for HIV-1 cure and therapeutic strategies.

At the Intersection of Gut Microbiome and Stroke: A Systematic Review of the Literature.

Background: Ischemic and hemorrhagic stroke are associated with a high rate of long-term disability and death. Recent investigations focus efforts to better understand how alterations in gut microbiota composition influence clinical outcomes. A key metabolite, trimethylamine N-oxide (TMAO), is linked to multiple inflammatory, vascular, and oxidative pathways. The current biochemical underpinnings of microbial effects on stroke remain largely understudied. The goal of our study is to explore the current literature to explain the interactions between the human gut microbiome and stroke progression, recovery, and outcome. We also provide a descriptive review of TMAO. Methods: A systematic literature search of published articles between January 1, 1990, and March 22, 2020, was performed on the PubMed database to identify studies addressing the role of the microbiome and TMAO in the pathogenesis and recovery of acute stroke. Our initial investigation focused on human subject studies and was further expanded to include animal studies. Relevant articles were included, regardless of study design. The analysis included reviewers classifying and presenting selected articles by study design and sample size in a chart format. Results: A total of 222 titles and abstracts were screened. A review of the 68 original human subject articles resulted in the inclusion of 24 studies in this review. To provide further insight into TMAO as a key player, an additional 40 articles were also reviewed and included. Our findings highlighted that alterations in richness and abundance of gut microbes and increased plasma TMAO play an important role in vascular events and outcomes. Our analysis revealed that restoration of a healthy gut, through targeted TMAO-reducing therapies, could provide alternative secondary prevention for at-risk patients. Discussion: Biochemical interactions between the gut microbiome and inflammation, resulting in metabolic derangements, can affect stroke progression and outcomes. Clinical evidence supports the importance of TMAO in modulating underlying stroke risk factors. Lack of standardization and distinct differences in sample sizes among studies are major limitations.

Machine Learning to Predict Tamoxifen Nonadherence Among US Commercially Insured Patients With Metastatic Breast Cancer.

PURPOSE: Adherence to tamoxifen citrate among women diagnosed with metastatic breast cancer can improve survival and minimize recurrence. This study aimed to use real-world data and machine learning (ML) methods to classify tamoxifen nonadherence. METHODS: A cohort of women diagnosed with metastatic breast cancer from 2012 to 2017 were identified from IBM MarketScan Commercial Claims and Encounters and Medicare claims databases. Patients with < 80% proportion of days coverage in the year following treatment initiation were classified as nonadherent. Training and internal validation cohorts were randomly generated (4:1 ratio). Clinical procedures, comorbidity, treatment, and health care encounter features in the year before tamoxifen initiation were used to train logistic regression, boosted logistic regression, random forest, and feedforward neural network models and were internally validated on the basis of area under receiver operating characteristic curve. The most predictive ML approach was evaluated to assess feature importance. RESULTS: A total of 3,022 patients were included with 40% classified as nonadherent. All models had moderate predictive accuracy. Logistic regression (area under receiver operating characteristic 0.64) was interpreted with 94% sensitivity (95% CI, 89 to 92) and 0.31 specificity (95% CI, 29 to 33). The model accurately classified adherence (negative predictive value 89%) but was nondiscriminate for nonadherence (positive predictive value 48%). Variable importance identified top predictive factors, including age ≥ 55 years and pretreatment procedures (lymphatic nuclear medicine, radiation oncology, and arterial surgery). CONCLUSION: ML using baseline administrative data predicts tamoxifen nonadherence. Screening at treatment initiation may support personalized care, improve health outcomes, and minimize cost. Baseline claims may not be sufficient to discriminate adherence. Further validation with enriched longitudinal data may improve model performance.

Aging mitigates the severity of obesity-associated metabolic sequelae in a gender independent manner.

BACKGROUND: Understanding gender-associated bias in aging and obesity-driven metabolic derangements has been hindered by the inability to model severe obesity in female mice. METHODS: Here, using chow- or high fat diet (HFD)-feeding regimens at standard (TS) and thermoneutral (TN) housing temperatures, the latter to model obesity in female mice, we examined the impact of gender and aging on obesity-associated metabolic derangements and immune responsiveness. Analysis included quantification of: (i) weight gain and adiposity; (ii) the development and severity of glucose dysmetabolism and non-alcoholic fatty liver disease (NAFLD); and (iii) induction of inflammatory pathways related to metabolic dysfunction. RESULTS: We show that under chow diet feeding regimen, aging was accompanied by increased body weight and white adipose tissue (WAT) expansion in a gender independent manner. HFD feeding regimen in aged, compared to young, male mice at TS, resulted in attenuated glucose dysmetabolism and hepatic steatosis. However, under TS housing conditions only aged, but not young, HFD fed female mice developed obesity. At TN however, both young and aged HFD fed female mice developed severe obesity. Independent of gender or housing conditions, aging attenuated the severity of metabolic derangements in HFD-fed obese mice. Tempered severity of metabolic derangements in aged mice was associated with increased splenic frequency of regulatory T (Treg) cells, Type I regulatory (Tr1)-like cells and circulating IL-10 levels and decreased vigor of HFD-driven induction of inflammatory pathways in adipose and liver tissues. CONCLUSION: Our findings suggest that aging-associated altered immunological profile and inflammatory vigor may play a dominant role in the attenuation of obesogenic diet-driven metabolic dysfunction.

Development of a "meta-model" to address missing data, predict patient-specific cancer survival and provide a foundation for clinical decision support.

OBJECTIVE: Like most real-world data, electronic health record (EHR)-derived data from oncology patients typically exhibits wide interpatient variability in terms of available data elements. This interpatient variability leads to missing data and can present critical challenges in developing and implementing predictive models to underlie clinical decision support for patient-specific oncology care. Here, we sought to develop a novel ensemble approach to addressing missing data that we term the "meta-model" and apply the meta-model to patient-specific cancer prognosis. MATERIALS AND METHODS: Using real-world data, we developed a suite of individual random survival forest models to predict survival in patients with advanced lung cancer, colorectal cancer, and breast cancer. Individual models varied by the predictor data used. We combined models for each cancer type into a meta-model that predicted survival for each patient using a weighted mean of the individual models for which the patient had all requisite predictors. RESULTS: The meta-model significantly outperformed many of the individual models and performed similarly to the best performing individual models. Comparisons of the meta-model to a more traditional imputation-based method of addressing missing data supported the meta-model's utility. CONCLUSIONS: We developed a novel machine learning-based strategy to underlie clinical decision support and predict survival in cancer patients, despite missing data. The meta-model may more generally provide a tool for addressing missing data across a variety of clinical prediction problems. Moreover, the meta-model may address other challenges in clinical predictive modeling including model extensibility and integration of predictive algorithms trained across different institutions and datasets.

Production, Purification and Characterization of a Novel Bacteriocin Produced by Bacillus subtilis VS Isolated from Mango (Mangifera indica L)

Abstract Bacteriocin has been identified as an excellent alternative to chemical preservatives due to its astonishing antimicrobial activity against food spoiling and food-borne pathogens. So there is a need to identify the newer and potent sources of bacteriocin producers. This study aims the isolation of potent bacteriocin producing microorganism from fresh fruits and vegetables, its production, purification, and characterization. Firstly, 43 isolates were analysed for its antimicrobial potential, out of which7 were found to inhibit the growth of various pathogens. Considering the results of antimicrobial activity; the microorganism isolated from mango was regarded as the most potent one; which was identified as Bacillus subtilis VS.70% ammonium sulphate precipitated and dialysed bacteriocin was purified using DEAE cellulose and sephadex G75 chromatography. Bacteriocin was purified by 24.64 fold with 8.65% recovery and its molecular weight was found to be 31.2kDa. The Purified bacteriocin was found to be stable at broad pH and temperature. It was found to be degraded by various proteases studied confirming its proteinaceous nature. Considering all these attributes; the purified bacteriocin isolated from Bacillus subtilis VS can be exploited by various food industries.