Cisplatin-induced bone marrow failure in an adult patient with Fanconi anemia.

INTRODUCTION: Fanconi anemia (FA) is a genetic disorder characterized by bone marrow failure typically developing in the first decade of life, congenital abnormalities, and an increased predisposition to malignancy. However, patients with FA can remain undiagnosed until adulthood and present with solid organ malignancies. Due to impaired DNA repair mechanisms, patients with FA are highly susceptible to severe bone marrow toxicity when treated with cisplatin. CASE REPORT: A 38-year-old woman, diagnosed with locally advanced squamous cell carcinoma (SCC) of the uterine cervix, underwent treatment with weekly cisplatin concurrent with radiotherapy. After the second week of cisplatin treatment, she presented with severe pancytopenia. The prolonged and severe pancytopenia following cisplatin and radiation, along with cervical SCC in the absence of risk factors and the presence of parental consanguinity, raised the possibility of FA as the underlying cause. Whole exome sequencing revealed a homozygous FANCI c.668A > C (p.Lys223Thr) missense variant confirming the diagnosis of FA. MANAGEMENT AND OUTCOME: The pancytopenia exhibited a protracted course, necessitating admission and supportive treatment with antibiotics, red blood cell and platelet transfusions, as well as filgrastim and eltrombopag. Eventually, the pancytopenia improved after approximately 40 days of hospitalization. DISCUSSION: SCC of the head and neck or gynecologic organs in a young adult without known risk factors should prompt consideration of FA. Cisplatin should be avoided in patients with FA.

Bioremoval of tannins and heavy metals using immobilized tannase and biomass of Aspergillus glaucus.

BACKGROUND: The presence of inorganic pollutants and heavy metals in industrial effluents has become a serious threat and environmental issues. Fungi have a remarkable ability to exclude heavy metals from wastewater through biosorption in eco-friendly way. Tannase plays an important role in bioconversion of tannin, a major constituent of tannery effluent, to gallic acid which has great pharmaceutical applications. Therefore, the aim of the current study was to exploit the potential of tannase from Aspergillus glaucus and fungal biomass waste for the bioremediation of heavy metals and tannin. RESULTS: Tannase from A. glaucus was partially purified 4.8-fold by ammonium sulfate precipitation (80%). The enzyme was optimally active at pH 5.0 and 40 °C and stable at this temperature for 1 h. Tannase showed high stability at different physiological conditions, displayed about 50% of its activity at 60 °C and pH range 5.0-6.0. Immobilization of tannase was carried out using methods such. as entrapment in Na-alginate and covalent binding to chitosan. The effects of Na-alginate concentrations on the beads formation and enzyme immobilization revealed that maximum immobilization efficiency (75%) was obtained with 3% Na-alginate. A potential reusability of the immobilized enzyme was showed through keeping 70% of its relative activity up to the fourth cycle. The best bioconversion efficiency of tannic acid to gallic acid by immobilized tannase was at 40 °C with tannic acid concentration up to 50 g/l. Moreover, bioremediation of heavy metal (Cr3+, Pb2+, Cu2+, Fe3+, and Mn2+) from aqueous solution using A. glaucus biomass waste was achieved with uptake percentage of (37.20, 60.30, 55.27, 79.03 and 21.13 respectively). The biomass was successfully used repeatedly for removing Cr3+ after using desorbing agent (0.1 N HCl) for three cycles. CONCLUSION: These results shed the light on the potential use of tannase from locally isolated A. glaucus in the bioremediation of industrial tanneries contained heavy metals and tannin.

Drugst.One - a plug-and-play solution for online systems medicine and network-based drug repurposing.

In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In response, computational systems and network medicine tools have emerged to identify potential drug repurposing candidates. However, these tools often require complex installation and lack intuitive visual network mining capabilities. To tackle these challenges, we introduce Drugst.One, a platform that assists specialized computational medicine tools in becoming user-friendly, web-based utilities for drug repurposing. With just three lines of code, Drugst.One turns any systems biology software into an interactive web tool for modeling and analyzing complex protein-drug-disease networks. Demonstrating its broad adaptability, Drugst.One has been successfully integrated with 21 computational systems medicine tools. Available at https://drugst.one, Drugst.One has significant potential for streamlining the drug discovery process, allowing researchers to focus on essential aspects of pharmaceutical treatment research.

Assessing donor-recipient arterial pressure dynamics in STA-MCA bypass for moyamoya disease.

BACKGROUND: In bypass surgery for moyamoya disease (MMD), the superficial temporal artery's (STA) pressure needs to surpass that of the cortical M4 recipient of the middle cerebral artery (MCA), boosting cerebral blood flow into the MCA and enhancing cerebral circulation. This study investigates the STA-MCA arterial pressure parameters and gradients during bypass surgery, aiming to deepen our understanding of hemodynamic shifts pre- and post-operation. METHODS: DSA imaging data were prospectively collected from patients diagnosed with bilateral MMD who underwent STA-MCA bypass surgery between 2022 and 2023 and stratified according to the Suzuki stage. The mean arterial pressure (MAP) of the donor and recipient arteries was directly measured during the STA-MCA bypass procedure, and these data were statistically analyzed and evaluated. RESULTS: Among 48 MMD patients, Suzuki grading revealed that 43.8% were in early stages (II and III), while 56.2% were in advanced stages (IV, V, and VI). Predominantly, 77.1% presented with ischemic-type MMD and 22.9% with hemorrhagic type. Pre-bypass assessments showed that 62.5% exhibited antegrade blood flow direction, and 37.5% had retrograde. The mean recipient artery pressure was 35.0 ± 2.3 mmHg, with a mean donor-recipient pressure gradient (δP) of 46.4 ± 2.5 mmHg between donor and recipient arteries. Post-bypass, mean recipient artery pressure increased to 73.3 ± 1.6 mmHg. No significant correlation (r = 0.18, P = 0.21) was noted between δP and Suzuki staging. CONCLUSION: Our study elucidated that cerebral blood pressure significantly decreases beyond the moyamoya network at the distal M4 segment. Furthermore, we observed bidirectional flow in MCA territories and a significant positive pressure gradient between the STA and M4 segments. The lack of correlation between Suzuki stages and M4 pressures indicates that angiographic severity may not reflect hemodynamic conditions before surgery, highlighting the need for customized surgical approaches.

The potential role of SNHG16/ miRNA-146a/ TRAF6 signaling pathway in the protective effect of zoledronate against colorectal cancer and associated osteoporosis in mouse model.

Bone fracture as a consequence of colorectal cancer (CRC) and associated osteoporosis (OP) is considered a risk factor for increasing the mortality rate among CRC patients. SNHG16/ miRNA-146a/ TRAF6 signaling pathway is a substantial contributor to neoplastic evolution, progression, and metastasis. Here, we investigated the effect of zoledronate (ZOL) on the growth of CRC and associated OP in a mouse model. Thirty Balb/c mice were divided into Naïve, azoxymethane (AOM)/dextran sodium sulfate (DSS), and ZOL groups. Body weight and small nucleolar RNA host gene 16 (SNHG16) expression, microRNA-146a, and TRAF6 in bone, colon, and stool were investigated. Samples of colon and bone were collected and processed for light microscopic, immunohistochemical staining for cytokeratin 20 (CK20), nuclear protein Ki67 (pKi-67), and caudal type homeobox transcription factor 2 (CDx2) in colon and receptor activator of nuclear factor kB (RANK) and osteoprotegerin (OPG) in bone. A computerized tomography (CT) scan of the femur and tibia was studied. ZOL produced a significant decrease in the expression of SNHG16 and TRAF6 and an increase in miRNA-146a in the colon and bone. ZOL administration improved the histopathological changes in the colon, produced a significant decrease in CK20 and Ki-67, and increased CDx2 expressions. In bone, ZOL prevented osteoporotic changes and tumour cell invasion produced a significant decrease in RANK and an increase in OPG expressions, alongside improved bone mineral density in CT scans. ZOL could be a promising preventive therapy against colitis-induced cancer and associated OP via modulation expression of SNHG16, miRNA-146a, and TRAF6.

Can digital twin efforts shape microorganism-based alternative food?

With the continuous increment in global population growth, compounded by post-pandemic food security challenges due to labor shortages, effects of climate change, political conflicts, limited land for agriculture, and carbon emissions control, addressing food production in a sustainable manner for future generations is critical. Microorganisms are potential alternative food sources that can help close the gap in food production. For the development of more efficient and yield-enhancing products, it is necessary to have a better understanding on the underlying regulatory molecular pathways of microbial growth. Nevertheless, as microbes are regulated at multiomics scales, current research focusing on single omics (genomics, proteomics, or metabolomics) independently is inadequate for optimizing growth and product output. Here, we discuss digital twin (DT) approaches that integrate systems biology and artificial intelligence in analyzing multiomics datasets to yield a microbial replica model for in silico testing before production. DT models can thus provide a holistic understanding of microbial growth, metabolite biosynthesis mechanisms, as well as identifying crucial production bottlenecks. Our argument, therefore, is to support the development of novel DT models that can potentially revolutionize microorganism-based alternative food production efficiency.

The effects of dexmedetomidine on intraoperative neurophysiologic monitoring modalities during corrective scoliosis surgery in pediatric patients: A systematic review.

BACKGROUND: During scoliosis surgery, motor evoked potentials (MEP), and somatosensory evoked potentials (SSEP) have been reported to be affected by the use of higher doses of anesthetic agents. Dexmedetomidine, a sympatholytic agent, an alpha-2 receptor agonist, has been used as an adjunctive agent to lower anesthetic dose. However, there is conflicting evidence regarding the effects of dexmedetomidine on the intraoperative neurophysiological monitoring of MEP and SSEP during surgery, particularly among pediatric patients. OBJECTIVES: This systematic review aimed to determine whether, during spinal fusion surgery in pediatric patients with scoliosis, dexmedetomidine alters MEP amplitude or SSEP latency and amplitude and, if so, whether different doses of dexmedetomidine display different effects (PROSPERO registration number CRD42022300562). METHODS: We searched PubMed, Scopus, and Cochrane Library on January 1, 2022 and included randomized controlled trials, observational cohort and case-control studies and case series investigating dexmedetomidine in the population of interest and comparing against a standardized anesthesia regimen without dexmedetomidine or comparing multiple doses of dexmedetomidine. Animal and in vitro studies and conference abstracts were excluded. RESULTS: We found substantial heterogeneity in the risk of bias (per Cochrane-preferred tools) of the included articles (n = 5); results are summarized without meta-analysis. Articles with the lowest risk of bias indicated that dexmedetomidine was associated with MEP loss and that higher doses of dexmedetomidine increased risk. In contrast, articles reporting no association between dexmedetomidine and MEP loss suffered from higher risk of bias, including suspected or confirmed problems with confounding, outcome measurement, participant selection, results reporting, and lack of statistical transparency and power. CONCLUSION: Given the limitations of the studies available in the literature, it would be advisable to conduct rigorous randomized controlled trials with larger sample sizes to assess the effects of dexmedetomidine use of in scoliosis surgery in pediatric patients.

How I do it: direct pressure measurement in moyamoya bypass.

BACKGROUND: The direct quantitative measurement of donor and recipient pressures in patients with moyamoya vasculopathy (MMV) during superficial temporal artery-middle cerebral artery (STA-MCA) bypass surgery has yet to be reported in academic literature. METHOD: Using a wireless pressure wire, we describe our approach to measuring seven pressure parameters in MMV patients step-by-step. CONCLUSION: Direct intraluminal pressure measurement of donor and recipient arteries provides a practical and accurate means to quantify cerebral hemodynamic parameters in MMV patients, enhancing understanding of individualized hemodynamic changes pre- and post-surgery.

The Treatment Outcomes of Radiotherapy and Surgical Treatment for Patients with Cavernous Sinus Hemangioma: A Meta-Analysis.

OBJECTIVE: Cavernous sinus hemangiomas (CSHs) are infrequent benign neoplasms. This meta-analysis was conducted with the objective of examining the prognostic outcomes of surgical interventions and radiotherapy (RT) in patients diagnosed with CSHs. METHODS: A comprehensive literature search was performed across PubMed, Embase, and Web of Science databases, with traceability up to June 22, 2021. The evaluation of continuous variables was conducted by applying the weighted mean difference (WMD) and 95% confidence interval. A one-arm meta-analysis was used to scrutinize the tumor control rate, clinical improvement rate, recovery rates of abducens nerve palsy and visual disturbance, total resection rate, and the incidence rate of permanent nerve palsy post-treatment. RESULTS: In total, 29 articles were incorporated into the meta-analysis. Post-RT for CSHs, a significant reduction in tumor volume was observed (WMD [95% confidence interval] = -17.16 [-21.52, -12.80] cm3). The tumor control rate, clinical improvement rate, recovery rate of abducens nerve palsy, and the recovery rate of visual disturbance were 97.1% (92.9, 99.7), 91.9% (82.3, 98.5), 95.6% (83.2, 100.0), and 86.3% (65.0, 99.5), respectively. Following surgical treatment, the total resection rate, mean intraoperative blood loss, recovery rate of visual disturbance, incidence rate of permanent nerve palsy, and recovery rate of abducens nerve palsy were 73.2% (57.1, 86.9), 971.17 mL (584.07, 1358.27), 66.4% (32.4, 0.942), 16.0% (4.6, 31.1), and 70.6% (51.0, 87.7), respectively. Notably, the recovery rate of abducens nerve palsy post-RT was markedly higher than postsurgical treatment. CONCLUSIONS: The results of this meta-analysis underscore that RT is an effective and safe treatment modality for CSHs. Furthermore, the prognostic outcomes of RT demonstrated superiority over surgical intervention.

Drugst.One - A plug-and-play solution for online systems medicine and network-based drug repurposing.

In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In response, computational systems and network medicine tools have emerged to identify potential drug repurposing candidates. However, these tools often require complex installation and lack intuitive visual network mining capabilities. To tackle these challenges, we introduce Drugst.One, a platform that assists specialized computational medicine tools in becoming user-friendly, web-based utilities for drug repurposing. With just three lines of code, Drugst.One turns any systems biology software into an interactive web tool for modeling and analyzing complex protein-drug-disease networks. Demonstrating its broad adaptability, Drugst.One has been successfully integrated with 21 computational systems medicine tools. Available at https://drugst.one, Drugst.One has significant potential for streamlining the drug discovery process, allowing researchers to focus on essential aspects of pharmaceutical treatment research.

Globally invariant behavior of oncogenes and random genes at population but not at single cell level.

Cancer is widely considered a genetic disease. Notably, recent works have highlighted that every human gene may possibly be associated with cancer. Thus, the distinction between genes that drive oncogenesis and those that are associated to the disease, but do not play a role, requires attention. Here we investigated single cells and bulk (cell-population) datasets of several cancer transcriptomes and proteomes in relation to their healthy counterparts. When analyzed by machine learning and statistical approaches in bulk datasets, both general and cancer-specific oncogenes, as defined by the Cancer Genes Census, show invariant behavior to randomly selected gene sets of the same size for all cancers. However, when protein-protein interaction analyses were performed, the oncogenes-derived networks show higher connectivity than those relative to random genes. Moreover, at single-cell scale, we observe variant behavior in a subset of oncogenes for each considered cancer type. Moving forward, we concur that the role of oncogenes needs to be further scrutinized by adopting protein causality and higher-resolution single-cell analyses.

Purification, characterization, and enzyme kinetics of a glutathione S transferase from larvae of the camel tick Hyalomma dromedarii.

BACKGROUND: Glutathione s-transferases (GSTs) perform an essential role in detoxification of xenobiotics and endogenous compounds via their conjugation to reduce glutathione. RESULTS: A GST enzyme, designated tick larvae glutathione S transferase (TLGST), was purified from larvae of the camel tick Hyalomma dromedarii via ammonium sulfate precipitation, glutathione-Sepharose affinity column and Sephacryl S-300 chromatography. TLGST-specific activity was found to be 1.56 Umg-1 which represents 39 folds and 32.2% recovery. The molecular weight of TLGST purified from camel tick larvae was found as 42 kDa by gel filtration. TLGST has a pI value of 6.9 and was found a heterodimeric protein of 28 and 14 kDa subunits as detected on SDS-PAGE. The Lineweaver-Burk plot calculated the km for CDNB to be 0.43 mM with Vmax value of 9.2 Umg-1. TLGST exhibited its optimal activity at pH 7.9. Co2+, Ni2+ and Mn2+ increased the activity of TLGST while Ca2+, Cu2+, Fe2+ and Zn2+ inhibited it. TLGST was inhibited by cumene hydroperoxide, p-hydroxymercuribenzoate, lithocholic acid, hematin, triphenyltin chloride, p-chloromercuribenzoic acid (pCMB), N-p-Tosyl-L-phenylalanine chloromethyl ketone (TPCK), iodoacetamide, EDTA and quercetin. pCMB inhibited TLGST competitively with Ki value of 0.3 mM. CONCLUSIONS: These findings will help to understand the various physiologic conditions of ticks and targeting TLGST could be significant tool for development of prospective vaccines against ticks as a bio-control strategy to overcome the rapid grows in pesticide-resistant tick populations.

Perspective: Multiomics and Machine Learning Help Unleash the Alternative Food Potential of Microalgae.

Food security has become a pressing issue in the modern world. The ever-increasing world population, ongoing COVID-19 pandemic, and political conflicts together with climate change issues make the problem very challenging. Therefore, fundamental changes to the current food system and new sources of alternative food are required. Recently, the exploration of alternative food sources has been supported by numerous governmental and research organizations, as well as by small and large commercial ventures. Microalgae are gaining momentum as an effective source of alternative laboratory-based nutritional proteins as they are easy to grow under variable environmental conditions, with the added advantage of absorbing carbon dioxide. Despite their attractiveness, the utilization of microalgae faces several practical limitations. Here, we discuss both the potential and challenges of microalgae in food sustainability and their possible long-term contribution to the circular economy of converting food waste into feed via modern methods. We also argue that systems biology and artificial intelligence can play a role in overcoming some of the challenges and limitations; through data-guided metabolic flux optimization, and by systematically increasing the growth of the microalgae strains without negative outcomes, such as toxicity. This requires microalgae databases rich in omics data and further developments on its mining and analytics methods.

Revisiting maintenance immunosuppression in patients with renal transplant failure: early weaning of immunosuppression versus prolonged maintenance-systematic review and meta-analysis.

INTRODUCTION: Prolonged immunosuppression after dialysis start has been assumed to reduce sensitization, need for graft nephrectomy, and to favor re-transplantation. In contrast, immunosuppression is considered to increase the risk of mortality, infection, and malignancy. We aimed to assess the evidence regarding superiority of early or late withdrawal of maintenance immunosuppression post renal transplant failure. METHODS: A literature search of the PubMed, WOS, Ovid, and Scopus databases was conducted. Combined relative risks, (RRs), mean differences, and 95% confidence intervals (CIs) were calculated by using a random-effect model. RESULTS: Ten studies involving 1187 patients with kidney transplant failure were included. No difference could be detected between patients with early withdrawal of  immunosuppressive drugs (≤ 3 months) or prolonged immunosuppressive treatment (> 3 months) regarding mortality (95% CI 0.91-2.28), panel reactive antibodies (PRAs) (95% CI - 0.75-30.10), re-transplantation rate (95% CI 0.55-1.35), infectious episodes (95% CI 0.67, 1.17), cancer (95% CI 0.26-1.54), and graft nephrectomy (95% CI 0.82-1.63). Similarly, no difference was found between immunosuppressive drug withdrawal over < 6 or ≥ 6 months regarding mortality (95% CI 0.16, 2.89), re-transplantation rate (95% CI 0.85-1.55), cancer (95% CI 0.37-1.63), and allograft nephrectomy (95% CI 0.87-4.33). CONCLUSION: Prolonged maintenance immunosuppression post kidney transplant failure is not associated with increased risk of mortality, infection, or malignancy, or reduced risk of sensitization or allograft nephrectomy compared with early withdrawal.

Application of GeneCloudOmics: Transcriptomic Data Analytics for Synthetic Biology.

Research in synthetic biology and metabolic engineering require a deep understanding on the function and regulation of complex pathway genes. This can be achieved through gene expression profiling which quantifies the transcriptome-wide expression under any condition, such as a cell development stage, mutant, disease, or treatment with a drug. The expression profiling is usually done using high-throughput techniques such as RNA sequencing (RNA-Seq) or microarray. Although both methods are based on different technical approaches, they provide quantitative measures of the expression levels of thousands of genes. The expression levels of the genes are compared under different conditions to identify the differentially expressed genes (DEGs), the genes with different expression levels under different conditions. DEGs, usually involving thousands in number, are then investigated using bioinformatics and data analytic tools to infer and compare their functional roles between conditions. Dealing with such large datasets, therefore, requires intensive data processing and analyses to ensure its quality and produce results that are statistically sound. Thus, there is a need for deep statistical and bioinformatics knowledge to deal with high-throughput gene expression data. This represents a barrier for wet biologists with limited computational, programming, and data analytic skills that prevent them from getting the full potential of the data. In this chapter, we present a step-by-step protocol to perform transcriptome analysis using GeneCloudOmics, a cloud-based web server that provides an end-to-end platform for high-throughput gene expression analysis.

Optimization of tannase production by Aspergillus glaucus in solid-state fermentation of black tea waste.

Tannases are valuable industrial enzymes used in food, pharmaceutical, cosmetic, leather manufacture and in environmental biotechnology. In this study, 15 fungal isolates were obtained from Egyptian cultivated soil and marine samples. The isolated fungi were qualitatively and quantitatively screened for their abilities to produce tannase. The selected fungal isolate NRC8 giving highest tannase activity was identified by molecular technique (18S rRNA) as Aspergillus glaucus. Among different tannin-containing wastes tested, the black tea waste was the best substrate for tannase production by Aspergillus glaucus in solid-state fermentation (SSF). Optimization of the different process parameters required for maximum enzyme production was carried out to design a suitable SSF process. Maximal tannase production was achieved with moisture content of 75%, an inoculums size of 6 × 108 spore/ml and sodium nitrate 0.2% (pH of 5.0) at 30 °C after 5 days of incubation. Box-Behnken experiment was designed to get a quadratic model for further optimization studies. Four-factor response-surface method with 27 runs was prepared using independent parameters including (moisture content %, initial pH, substrate concentration (g) and sodium nitrate concentration (g) for tannase model. The F- and P-values of the model were 4.30 and 0.002, respectively, which implied that the model is significant. In addition, the lack-of-fit was 1040.37 which indicates the same significance relative to the pure error. A. glaucus tannase was evaluated by the efficiency of conversion of tannic acid to gallic acid. Moreover, production of gallic acid from SSF process of A. glaucus using black tea waste was found to be 38.27 mg/ml. The best bioconversion efficiency was achieved at 40 °C with tannic acid concentration up to 200 g/L.

Metabolomics and modelling approaches for systems metabolic engineering.

Metabolic engineering involves the manipulation of microbes to produce desirable compounds through genetic engineering or synthetic biology approaches. Metabolomics involves the quantitation of intracellular and extracellular metabolites, where mass spectrometry and nuclear magnetic resonance based analytical instrumentation are often used. Here, the experimental designs, sample preparations, metabolite quenching and extraction are essential to the quantitative metabolomics workflow. The resultant metabolomics data can then be used with computational modelling approaches, such as kinetic and constraint-based modelling, to better understand underlying mechanisms and bottlenecks in the synthesis of desired compounds, thereby accelerating research through systems metabolic engineering. Constraint-based models, such as genome scale models, have been used successfully to enhance the yield of desired compounds from engineered microbes, however, unlike kinetic or dynamic models, constraint-based models do not incorporate regulatory effects. Nevertheless, the lack of time-series metabolomic data generation has hindered the usefulness of dynamic models till today. In this review, we show that improvements in automation, dynamic real-time analysis and high throughput workflows can drive the generation of more quality data for dynamic models through time-series metabolomics data generation. Spatial metabolomics also has the potential to be used as a complementary approach to conventional metabolomics, as it provides information on the localization of metabolites. However, more effort must be undertaken to identify metabolites from spatial metabolomics data derived through imaging mass spectrometry, where machine learning approaches could prove useful. On the other hand, single-cell metabolomics has also seen rapid growth, where understanding cell-cell heterogeneity can provide more insights into efficient metabolic engineering of microbes. Moving forward, with potential improvements in automation, dynamic real-time analysis, high throughput workflows, and spatial metabolomics, more data can be produced and studied using machine learning algorithms, in conjunction with dynamic models, to generate qualitative and quantitative predictions to advance metabolic engineering efforts.

Uncovering the Contribution of Moderate-Penetrance Susceptibility Genes to Breast Cancer by Whole-Exome Sequencing and Targeted Enrichment Sequencing of Candidate Genes in Women of European Ancestry.

Rare variants in at least 10 genes, including BRCA1, BRCA2, PALB2, ATM, and CHEK2, are associated with increased risk of breast cancer; however, these variants, in combination with common variants identified through genome-wide association studies, explain only a fraction of the familial aggregation of the disease. To identify further susceptibility genes, we performed a two-stage whole-exome sequencing study. In the discovery stage, samples from 1528 breast cancer cases enriched for breast cancer susceptibility and 3733 geographically matched unaffected controls were sequenced. Using five different filtering and gene prioritization strategies, 198 genes were selected for further validation. These genes, and a panel of 32 known or suspected breast cancer susceptibility genes, were assessed in a validation set of 6211 cases and 6019 controls for their association with risk of breast cancer overall, and by estrogen receptor (ER) disease subtypes, using gene burden tests applied to loss-of-function and rare missense variants. Twenty genes showed nominal evidence of association (p-value < 0.05) with either overall or subtype-specific breast cancer. Our study had the statistical power to detect susceptibility genes with effect sizes similar to ATM, CHEK2, and PALB2, however, it was underpowered to identify genes in which susceptibility variants are rarer or confer smaller effect sizes. Larger sample sizes would be required in order to identify such genes.

OpenPIP: An Open-source Platform for Hosting, Visualizing and Analyzing Protein Interaction Data.

Knowing which proteins interact with each other is essential information for understanding how most biological processes at the cellular and organismal level operate and how their perturbation can cause disease. Continuous technical and methodological advances over the last two decades have led to many genome-wide systematically-generated protein-protein interaction (PPI) maps. To help store, visualize, analyze and disseminate these specialized experimental datasets via the web, we developed the freely-available Open-source Protein Interaction Platform (openPIP) as a customizable web portal designed to host experimental PPI maps. Such a portal is often required to accompany a paper describing the experimental data set, in addition to depositing the data in a standard repository. No coding skills are required to set up and customize the database and web portal. OpenPIP has been used to build the databases and web portals of two major protein interactome maps, the Human and Yeast Reference Protein Interactome maps (HuRI and YeRI, respectively). OpenPIP is freely available as a ready-to-use Docker container for hosting and sharing PPI data with the scientific community at http://openpip.baderlab.org/ and the source code can be downloaded from https://github.com/BaderLab/openPIP/.

Influence of probiotics on water quality in intensified Litopenaeus vannamei ponds under minimum-water exchange.

The effects of two probiotics on NH3 degradation, as well as the magnetic field (21.56 m tesla) on the germination and proliferation of Bacillus spores, were studied in-vitro. Additionally, the effect of these probiotics on water quality maintenance in Litopenaeus vannamei holding ponds was investigated. For 180 min, NH3 degradation was assessed as follows: Set 1: ammonia-free tap water with NH3; Probiotic A (5 × 1010 viable Bacillus spores/g) with NH3; Probiotic B (multi spp. 2 × 109 CFU/g) with NH3; and Set 2: same as set 1 with 30 mg L-1 OM. The magnetic field was tested on Probiotic A (3.5 × 107 CFU) for 36 h in triplicate. In the presence of organic matter, both probiotics degrade NH3. The viable Bacillus count increased within 6 h of being exposed to the magnetic field, reaching its peak after 36 h. Firstly, fifteen ponds (250,000 PL/acre) were investigated, then 360 water samples were collected from the same corresponding pond for 8 weeks, and subjected to T1: control; T2: Probiotic A (0.007 g/m3/2 weeks); T3: Probiotic B (0.03 g/m3/2 weeks). Both probiotics with TVC and NH3 demonstrated a negative correlation, on the other hand, they showed a significant (P ≤ 0.01) improvement in DO and pH. Overall, both probiotics were able to degrade NH3 and the magnetic field (21.56 m tesla) was efficient to improve the germination and proliferation of Bacillus spores in-vitro. Probiotics were also effective for reducing TVC and NH3 levels by increasing dissolved oxygen and pH in pond water.