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We then mine these networks to identify subnetworks with correlated phosphorylation patterns. We apply the proposed framework to two mass-spectrometry based phosphorylation datasets for breast cancer, and observe that (i) the phosphorylation pattern of the identified subnetworks are highly correlated with clinically identified subtypes, and (ii) the identified subnetworks are highly reproducible across datasets that are derived from different studies. Our results show that integration of quantitative phosphorylation data with network frameworks can provide mechanistic insights into the differences between the signaling mechanisms that drive breast cancer subtypes. Furthermore, the reproducibility of the identified subnetworks suggests that phosphorylation can provide robust classification of disease response and markers.

CoPPNet is available at http//compbio.case.edu/coppnet/.

Supplementary data are available at Bioinformatics online.

Supplementary data are available at Bioinformatics online.

Repeated bone mineral density (BMD) testing to screen for osteoporosis requires resources. For patient counseling and optimal resource use, it is important for clinicians to know whether repeated BMD measurement (compared with baseline BMD measurement alone) improves the ability to discriminate between postmenopausal women who will and will not experience a fracture.

To assess whether a second BMD measurement approximately 3 years after the initial assessment is associated with improved ability to estimate fracture risk beyond the baseline BMD measurement alone.

The Women's Health Initiative is a prospective observational study. Participants in the present cohort study included 7419 women with a mean (SD) follow-up of 12.1 (3.4) years between 1993 and 2010 at 3 US clinical centers. Data analysis was conducted between May 2019 and December 2019.

Incident major osteoporotic fracture (ie, hip, clinical spine, forearm, or shoulder fracture), hip fracture, baseline BMD, and absolute change in BMD were asse after the initial measurement was not associated with improved discrimination between women who did and did not experience subsequent hip fracture or major osteoporotic fracture beyond the baseline BMD value alone and should not routinely be performed.

The spread of antibiotic resistance among bacterial strains has been associated with consumption of food contaminated with both pathogenic and nonpathogenic bacteria. The objective of this study was to determine the prevalence of antibiotic resistant Escherichia coli isolates in local and imported retail raw chicken meat in Qatar. A total of 270 locally produced (chilled) and imported (chilled or frozen) whole chicken carcasses were obtained from three Hypermarket stores in Qatar. The 216 E. coli isolates recovered from the chicken samples were subjected to antibiotic susceptibility testing with the disk diffusion method. Extended-spectrum β-lactamase (ESBL) production was evaluated with the double disk synergy test. Isolates harboring colistin resistance were identified with a multiplex PCR assay and DNA sequencing. Nearly 89% (192) of the 216 isolates were resistant to at least one of the 18 antibiotics tested. Isolates from local and imported chicken carcasses had relatively higher resistance to sulfamethoxazole (62% of isolates), tetracycline (59.7%), ampicillin and trimethoprim (52.3% each), ciprofloxacin (47.7%), cephalothin (45.4%), and colistin (31.9%). Less resistance was found to amoxicillin-clavulanic acid (6%), ceftriaxone (5.1%), nitrofurantoin (4.2%), piperacillin-tazobactam (4.2%), cefepime (2.3%), meropenem (1.4%), ertapenem (0.9%), and amikacin (0.9%). Nine isolates (4.2%) were ESBL producers, and 137 (63.4%) were multidrug resistant. The percentages of multidrug-resistant, ESBL-producing, and colistin resistant isolates were significantly higher among isolates from local chilled than from imported chilled and frozen chicken samples. Our findings indicate the high prevalence of antibiotic-resistant E. coli in chicken meat sold at retail in Qatar.

Difficulties associated with addressing research problems can revolve around the collection of data from private entities. selleck chemicals llc Potential issues can arise when collecting food samples or food safety data from industry or third-party sources because of concerns about distribution or exposure of potentially sensitive information. Industry is cautious of its involvement in research projects because issues associated with production levels, capital investment, regulatory inquiries, unwarranted publicity, or other legal aspects can arise depending on the nature of information gathered, and information may be inadvertently released into the public domain. Well-designed clinical trials with animals or humans use blinding methods to reduce bias. link2 In this study, a similar strategy was applied to acquisition of sensitive data to gather meaningful food safety related data while assuring that information provided was not at risk. Blinding methods for collecting electronic data and material samples were created to obtain materials and records directly from participating frozen food companies. This approach provided insight into current industry practices without potential downsides for participating companies. Analysis of food safety concerns using industry data and the distribution of findings can be of assistance industry-wide for conducting risk assessments and developing improved research-based food safety plans. The method described was designed to collect information using blinding protocols to reduce bias and prevent traceback to the original source. The use of blinding protocols promotes industry participation and creates data collection with anonymity for the original source, which can improve reliability of the research and applicability for industry. These blinding protocols are suitable for use in future food safety research projects involving data within and between various segments of the food industry and could be used to encourage collection of valuable industry samples and data.

This study aimed to evaluate the changes in variance components over time to identify a subset of data from the Italian Simmental (IS) population that would yield the most appropriate estimates of genetic parameters and breeding values for beef traits to select young bulls. Data from bulls raised between 1986 and 2017 were used to estimate genetic parameters and breeding values for four beef traits (average daily gain [ADG], body size [BS], muscularity [MUS], and feet and legs [FL]). The phenotypic mean increased during the years of the study for ADG, but it decreased for BS, MUS, and FL. The complete dataset (ALL) was divided into four generational subsets (Gen1, Gen2, Gen3, and Gen4). Additionally, ALL was divided into two larger subsets the first one (OLD) combined data from Gen1 and Gen2 to represent the starting population, and the second one (CUR) combined data from Gen3 and Gen4 to represent a subpopulation with stronger ties to the current population. Genetic parameters were estimated with a four-traiarameters that more appropriately represent the structure of the current population, yielding accurate GEBV to select young animals and increasing the likelihood of higher genetic gains.The objective was to estimate the genetic parameters of performance and resilience of growing pigs under disease. Data were from 3,139 Yorkshire × Landrace wean-to-finish pigs that were exposed to a natural polymicrobial disease challenge that was established by entering naturally infected animals into a nursery barn, targeting various viral and bacterial diseases. The challenge was maintained by entering batches of 60 or 75 healthy nursery pigs every 3 wk in a continuous flow system. link3 Traits analyzed included average daily gain (ADG), feed intake (ADFI) and duration (ADFD); feed conversion ratio (FCR); residual feed intake (RFI); mortality (MOR); number of health treatments (TRT); health scores (HScore); carcass weight (CWT), back fat (CBF) and loin depth (CLD); dressing percentage (DRS); lean yield (LYLD); day-to-day variation in feed intake and duration (VARFI and VARDUR); and the proportion of off-feed days (OFFFI and OFFDUR). Analyses were performed by mixed linear models with genomic relationships. The rtions with TRT (0.18 to 0.81) and MOR (0.33 to 0.87). In conclusion, performance and resilience traits under a polymicrobial disease challenge are heritable and can be changed by selection. Phenotypes extracted from feed intake patterns can be used as genetic indicator traits for disease resilience. Most promising is day-to-day variation in intake duration, which had a sizeable heritability (0.23) and favorable genetic correlations with MOR (0.79) and treatment rate (0.20).

Can a counselling tool be developed for couples with different types of azoospermia to predict the probability of clinical pregnancy in ICSI after surgical sperm retrieval?

A prediction model for clinical pregnancy in ICSI after surgical sperm retrieval in different types of azoospermia was created and clinical type of azoospermia, testicular size, male FSH, male LH, male testosterone, female age, female antral follicle count (AFC) and female anti-Müllerian hormone (AMH) were used as predictors.

Prediction models are used frequently to predict treatment success in reproductive medicine; however, there are few prediction models only for azoospermia couples who intend to conceive through surgical sperm retrieval and ICSI. Furthermore, no specific clinical types of azoospermia have been reported as predictors.

A cohort study of 453 couples undergoing ICSI was conducted between 2016 and 2019 in an academic teaching hospital.

Couples undergoing ICSI with surgically retrieved sperm were included, with 302s that we could include in the analysis was limited due to the success rate of surgical sperm retrieval, although this did not affect the establishment and validation of our model. Finally, this prediction model was developed in a single centre. Although our model was validated in an independent dataset from our centre, validation for different clinical populations belonging to other centres is required before it can be exported.

This model enables the differentiation between couples with a low or high chance of reaching a clinical pregnancy through ICSI after surgical sperm retrieval. As such it can provide couples dealing with azoospermia a new approach to help them choose between surgical sperm retrieval with ICSI and the use of donor sperm.

This work was supported by a grant from the National Natural Science Foundations of China (81501246 and 81501020 and 81671443). The authors declare no competing interest.

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N/A.Severe outcomes and death from the novel coronavirus disease 2019 (COVID-19) appear to be characterized by an exaggerated immune response with hypercytokinemia leading to inflammatory infiltration of the lungs and acute respiratory distress syndrome. Risk of severe COVID-19 outcomes is consistently lower in women than men worldwide, suggesting that female biological sex is instrumental in protection. This mini-review discusses the immunomodulatory and anti-inflammatory actions of high physiological concentrations of the steroids 17β-estradiol (E2) and progesterone (P4). We review how E2 and P4 favor a state of decreased innate immune inflammatory response while enhancing immune tolerance and antibody production. We discuss how the combination of E2 and P4 may improve the immune dysregulation that leads to the COVID-19 cytokine storm. It is intended to stimulate novel consideration of the biological forces that are protective in women compared to men, and to therapeutically harness these factors to mitigate COVID-19 morbidity and mortality.

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