Tag: pubmed

Tissue Cell. 2022 Feb 4;76:101752. doi: 10.1016/j.tice.2022.101752. Online ahead of print.

ABSTRACT

INTRODUCTION: BCC (Basal Cell Carcinoma) and trichoblastoma are skin tumors originating from the hair follicle. BCC is the most common non-melanoma skin cancer. Differential diagnosis of BCC from trichoblastoma, which is a common benign tumor in terms of histology, morphology, and immunohistochemistry, is not possible. The effects of adipokines on tumorigenesis have attracted attention.

MATERIALS AND METHODS: By examining the effects of Asprosin and Meteorine like peptide (METRNL) on these tumors, it is aimed to reach new information in the differential diagnosis of BCC and trichoblastoma. Twenty normal healthy tissue, 17 basal cell carcinoma and 12 trichoblastoma samples were included in the study.

RESULTS: Increased expression of Asprosin and METRNL was observed in tumor and stromal tissues in BCC. Although overexpression of METRNL was observed in the lesion area in trichoblastoma, no increase in Asprosin expression was observed. Asprosin and METRNL immunoreactivity were found to be statistically significantly higher in BCC samples compared to control and trichoblastoma.

CONCLUSION: Asprosin and METRNL can be used in the diagnosis of BCC. METRNL can be used in the diagnosis of trichoblastoma. These biomarkers are helpful for differentiation between BCC and trichoblastoma.

PMID:35144124 | DOI:10.1016/j.tice.2022.101752

Pract Radiat Oncol. 2022 Feb 7:S1879-8500(22)00044-3. doi: 10.1016/j.prro.2022.01.005. Online ahead of print.

ABSTRACT

PURPOSE/OBJECTIVE(S): In patients with borderline resectable or locally advanced pancreatic adenocarcinoma (BRPC/LAPC), local failure rates after resection remain significant, even in the setting of neoadjuvant chemotherapy and radiation. Sub-optimal local control may relate to variable radiation target delineation, as no consensus exists around clinical tumor volume (CTV) design in this context. In the surgical literature, recent attention has been given to the “Triangle” volume (TV) as a source of subclinical, residual disease. In order to understand whether the TV can inform optimal CTV design, we mapped locoregional failures after resection in a large cohort of BRPC/LAPC patients and compared locations of failure to the TV.

MATERIALS/METHODS: Patients with BRPC/LAPC of the head/neck diagnosed between 2016-2019 who developed locoregional failure after surgery following neoadjuvant chemotherapy and radiation were identified. Descriptive statistics were generated to report the frequency of locoregional failures located within the TV and the frequency of new vascular involvement at time of failure, as compared to vascular involvement at diagnosis. Additionally, dosimetric coverage of the TV with the pre-operative radiation plan that had been utilized was assessed.

RESULTS: In 31 patients who experienced locoregional failure, the centroid of failure was located within the TV in 28 cases (90%). Extent of vascular involvement at time of locoregional failure included vasculature that had not been involved at diagnosis in 13 cases (42%). The pre-operative radiation plan that had been utilized provided a median V33 Gy and V25 Gy of the TV of only 53% (IQR: 34-72%) and 70% (IQR: 48-85%), respectively.

CONCLUSION: The TV encompassed the vast majority of locoregional failures, but dosimetric coverage of the TV was poor when only targeting gross disease and the full circumference of involved vasculature. As such, the TV may better serve as a basis for CTV design in BRPC/LAPC patients undergoing neoadjuvant radiation.

PMID:35144016 | DOI:10.1016/j.prro.2022.01.005

CPT Pharmacometrics Syst Pharmacol. 2022 Feb 10. doi: 10.1002/psp4.12765. Online ahead of print.

ABSTRACT

Promising drug development efforts may frequently fail due to unintended adverse reactions. Several methods have been developed to analyze such data, aiming to improve pharmacovigilance and drug safety. In this work, we provide a brief review of key directions to quantitatively analyzing adverse events and explore the potential of augmenting these methods using additional molecular data descriptors. We argue that molecular expansion of adverse event data may provide a path to improving the insights gained through more traditional pharmacovigilance approaches. Examples include the ability to assess statistical relevance with respect to underlying biomolecular mechanisms, the ability to generate plausible causative hypotheses and/or confirmation where possible, the ability to computationally study potential clinical trial designs and/or results, as well as the further provision of advanced features incorporated in innovative methods, such as machine learning. In summary, molecular data expansion provides an elegant way to extend mechanistic modeling, systems pharmacology, and patient centered approaches for the assessment of drug safety. We anticipate that such advances in real world data informatics and outcome analytics will help to better inform public health, via the improved ability to prospectively understand and predict various types of drug-induced molecular perturbations and adverse events.

PMID:35143713 | DOI:10.1002/psp4.12765

J Mother Child. 2022 Feb 8. doi: 10.34763/jmotherandchild.20212503SI.d-21-00013. Online ahead of print.

ABSTRACT

BACKGROUND: The paper focuses on Bulgarian adolescents’ behaviours that put their health at risk and their relationship to family-related characteristics: structure of family and material status, family support, communication with parents, parental monitoring and school-related parental support. It also discusses intervention programs with a focus on parent support gradient.

MATERIAL AND METHODS: The analysis is based on the Bulgarian sample of Health Behaviour in School-Aged Children survey, the 2018 round. Logistic regression models of current cigarette smoking, regular alcohol consumption, sexual debut and current cannabis use are applied. Main national programs on adolescent health and the parental involvement component in them are also discussed.

RESULTS: The statistical analyses reveal significant gender and age differences in Bulgarian adolescents’ health risk behaviours. Girls have significantly higher odds of smoking and are less likely to report an early start of sexual life. Odds of cigarette smoking and regular alcohol consumption increase with age. Children living with one parent have significantly higher odds of smoking, regular alcohol consumption and current cannabis use. Interactions between FAS and family support reveal that students who report low family support, regardless of the material status of the family, have significantly higher odds of health risk behaviours.

CONCLUSION: The main contribution of the analysis reveals the alleviating effect of family support on socio-economic inequalities between families. An evidence-based approach delineating a preventive potential of family support on Bulgarian adolescents’ health risk behaviours despite the level of family affluence provides solid arguments for increasing national family support programs.

PMID:35143718 | DOI:10.34763/jmotherandchild.20212503SI.d-21-00013

Clin Transplant. 2022 Feb 10:e14611. doi: 10.1111/ctr.14611. Online ahead of print.

ABSTRACT

Lay-caregivers in organ transplantation (to candidates, recipients, and donors) are essential to pre- and post-operative care, but report significant caregiving-related stressors. This review aims to summarize studies testing non-pharmacological interventions aimed at improving organ transplant caregiver-reported outcomes.

METHODS: In accordance with PRISMA, we conducted a systematic review (searched PubMed, Embase, Cochrane Central, PsycInfo, and CINAHL, no start-date restriction through 7/1/2021). Quality of comparative studies assessed by ROBS-2 or ROBINS.

RESULTS: Twelve studies met inclusion. Study designs, interventions, and outcomes varied. Sample sizes were small across caregivers to adult (nine studies, five with caregiver samples ns≤50) and pediatric patients (three studies, caregiver samples ns≤16). Study designs included seven single-arm interventions, two pre-post with comparison cohorts, and three randomized-controlled trials. Eight studies included transplant-specific education as the intervention, an interventional component, or as the comparison group. Outcomes included transplant specific knowledge, mental health, and intervention acceptability. Of the nine pre-post caregiver assessments and/or comparison groups, four studies demonstrated no statistically significant intervention effects.

CONCLUSION: Few interventions addressing the needs of organ transplant caregivers have been empirically evaluated. Existing interventions were well-received by caregivers. Given complexities of care in transplantation, research is needed evaluating interventions using rigorous trial methodology with adequate samples. This article is protected by copyright. All rights reserved.

PMID:35143701 | DOI:10.1111/ctr.14611

Fam Med. 2022 Feb;54(2):114-122. doi: 10.22454/FamMed.2022.189296.

ABSTRACT

BACKGROUND AND OBJECTIVES: Structural racism is a cause of health disparities. Graduate medical education is tasked with training physicians who understand and address disparities. Addressing health disparities includes education on racism, such as racial justice curricula (RJC). We surveyed program directors (PDs) about the prevalence and characteristics of RJC in family medicine residency programs (FMRPs).

METHODS: RJC questions were included in the 2020 Council of Academic Family Medicine Educational Research (CERA) survey of FMRP PDs. We calculated univariate and bivariate statistics to describe respondent characteristics and attitudes, program characteristics, curriculum characteristics, and barriers to implementation.

RESULTS: Of 624 PDs, 312 (50%) responded and 283/312 (90.7%) completed RJC questions. Less than one-third of FMRPs reported RJC, of which 98.9% focused on implicit/unconscious bias. Program characteristics associated with RJC included location, percent underrepresented minorities in medicine (URMM) residents and faculty, and percent patients identifying as Black, Latino/a, and Native American. FMRPs with RJC were more likely to have PDs who reported favorable attitudes toward including RJC and believed it is important for family physicians to understand structural racism. The greatest barrier to implementation of RJC was lack of faculty training.

CONCLUSIONS: In this national survey, most FMRPs reported no RJC. Most respondent PDs endorsed that it is important for family physicians to understand structural racism and that RJC should be included in residency. Lack of faculty training was the greatest barrier to implementation. Research is needed to evaluate existing RJC and explore strategies for overcoming barriers to implemention.

PMID:35143683 | DOI:10.22454/FamMed.2022.189296

Fam Med. 2022 Feb;54(2):123-128. doi: 10.22454/FamMed.2022.410546.

ABSTRACT

BACKGROUND AND OBJECTIVES: Contraception is a core component of family medicine residency curriculum. Institutional environments can influence residents’ access to contraceptive training and thus their ability to meet the reproductive health needs of their patients.

METHODS: Contraceptive training questions were included in the 2020 Council of Academic Family Medicine Educational Research Alliance (CERA) survey of family medicine residency program directors. The survey asked how many faculty and residents opt out of providing contraceptive methods for moral or religious reasons, and whether training sites have institutional restrictions on contraception. We performed descriptive statistics and regression to identify program characteristics associated with having a resident or faculty opt out of providing contraceptive care.

RESULTS: Of 626 program directors, 249 responded to the survey, and 237 answered the contraceptive questions. Percentages of program directors reporting any residents or faculty who opted out of contraceptive services are as follows: pill/patch/ring (residents 27%; faculty 17%), emergency contraception (residents 40%, faculty 33%), or intrauterine devices/implants (resident 29%; faculty 23%). Programs in the South (OR 2.78; 1.19-6.49) and those with Catholic affiliation (OR 2.35; 1.23-4.91) had higher adjusted odds of at least one opt-out faculty but were not associated with having opt-out residents. Eleven percent of programs had at least one training site with institutional restrictions on contraception.

CONCLUSIONS: To ensure that residents have access to adequate contraceptive training, residencies should proactively seek faculty and training environments that meet residents’ needs, and should make limitations on services clear to potential residents and patients.

PMID:35143684 | DOI:10.22454/FamMed.2022.410546

Mol Biol Evol. 2022 Feb 10:msac034. doi: 10.1093/molbev/msac034. Online ahead of print.

ABSTRACT

Bioinformatic research relies on large-scale computational infrastructures which have a non-zero carbon footprint but so far, no study has quantified the environmental costs of bioinformatic tools and commonly run analyses. In this work, we estimate the carbon footprint of bioinformatics (in kilograms of CO2 equivalent units, kgCO2e) using the freely available Green Algorithms calculator (www.green-algorithms.org). We assessed (i) bioinformatic approaches in genome-wide association studies (GWAS), RNA sequencing, genome assembly, metagenomics, phylogenetics and molecular simulations, as well as (ii) computation strategies, such as parallelisation, CPU (central processing unit) vs GPU (graphics processing unit), cloud vs. local computing infrastructure and geography. In particular, we found that biobank-scale GWAS emitted substantial kgCO2e and simple software upgrades could make it greener, e.g. upgrading from BOLT-LMM v1 to v2.3 reduced carbon footprint by 73%. Moreover, switching from the average data centre to a more efficient one can reduce carbon footprint by ∼34%. Memory over-allocation can also be a substantial contributor to an algorithm’s greenhouse gas (GHG) emissions. The use of faster processors or greater parallelisation reduces running time but can lead to greater carbon footprint. Finally, we provide guidance on how researchers can reduce power consumption and minimise kgCO2e. Overall, this work elucidates the carbon footprint of common analyses in bioinformatics and provides solutions which empower a move toward greener research.

PMID:35143670 | DOI:10.1093/molbev/msac034

Hum Reprod. 2022 Feb 10:deac020. doi: 10.1093/humrep/deac020. Online ahead of print.

ABSTRACT

STUDY QUESTION: Can use of a commercially available time-lapse algorithm for Day 5 blastocyst selection improve pregnancy rates compared with morphology alone?

SUMMARY ANSWER: The use of a time-lapse selection model to choose blastocysts for fresh single embryo transfer on Day 5 did not improve ongoing pregnancy rate compared to morphology alone.

WHAT IS KNOWN ALREADY: Evidence from time-lapse monitoring suggests correlations between timing of key developmental events and embryo viability. No good quality evidence exists to support improved pregnancy rates following time-lapse selection.

STUDY DESIGN, SIZE, DURATION: A prospective multicenter randomized controlled trial including 776 randomized patients was performed between 2018 and 2021. Patients with at least two good quality blastocysts on Day 5 were allocated by a computer randomization program in a proportion of 1:1 into either the control group, whereby single blastocysts were selected for transfer by morphology alone, or the intervention group whereby final selection was decided by a commercially available time-lapse model. The embryologists at the time of blastocyst morphological scoring were blinded to which study group the patients would be randomized, and the physician and patients were blind to which group they were allocated until after the primary outcome was known. The primary outcome was number of ongoing pregnancies in the two groups.

PARTICIPANTS/MATERIALS, SETTING, METHODS: From 10 Nordic IVF clinics, 776 patients with a minimum of two good quality blastocysts on Day 5 (D5) were randomized into one of the two study groups. A commercial time-lapse model decided the final selection of blastocysts for 387 patients in the intervention (time-lapse) group, and blastocysts with the highest morphological score were transferred for 389 patients in the control group. Only single embryo transfers in fresh cycles were performed.

MAIN RESULTS AND THE ROLE OF CHANCE: In the full analysis set, the ongoing pregnancy rate for the time-lapse group was 47.4% (175/369) and 48.1% (181/376) in the control group. No statistically significant difference was found between the two groups: mean difference -0.7% (95% CI -8.2, 6.7, P = 0.90). Pregnancy rate (60.2% versus 59.0%, mean difference 1.1%, 95% CI -6.2, 8.4, P = 0.81) and early pregnancy loss (21.2% versus 18.5%, mean difference 2.7%, 95% CI -5.2, 10.6, P = 0.55) were the same for the time-lapse and the control group. Subgroup analyses showed that patient and treatment characteristics did not significantly affect the commercial time-lapse model D5 performance. In the time-lapse group, the choice of best blastocyst changed on 42% of occasions (154/369, 95% CI 36.9, 47.2) after the algorithm was applied, and this rate was similar for most treatment clinics.

LIMITATIONS, REASONS FOR CAUTION: During 2020, the patient recruitment rate slowed down at participating clinics owing to coronavirus disease-19 restrictions, so the target sample size was not achieved as planned and it was decided to stop the trial prematurely. The study only investigated embryo selection at the blastocyst stage on D5 in fresh IVF transfer cycles. In addition, only blastocysts of good morphological quality were considered for transfer, limiting the number of embryos for selection in both groups: also, it could be argued that this manual preselection of blastocysts limits the theoretical selection power of time-lapse, as well as restricting the results mainly to a good prognosis patient group. Most patients were aimed for blastocyst stage transfer when a minimum of five zygotes were available for extended culture. Finally, the primary clinical outcome evaluated was pregnancy to only 6-8 weeks.

WIDER IMPLICATIONS OF THE FINDINGS: The study suggests that time-lapse selection with a commercially available time-lapse model does not increase chance of ongoing pregnancy after single blastocyst transfer on Day 5 compared to morphology alone.

STUDY FUNDING/COMPETING INTEREST(S): The study was financed by a grant from the Swedish state under the ALF-agreement between the Swedish government and the county councils (ALFGBG-723141). Vitrolife supported the study with embryo culture dishes and culture media. During the study period, T.H. changed his employment from Livio AB to Vitrolife AB. All other authors have no conflicts of interests to disclose.

TRIAL REGISTRATION NUMBER: ClinicalTrials.gov registration number NCT03445923.

TRIAL REGISTRATION DATE: 26 February 2018.

DATE OF FIRST PATIENT’S ENROLMENT: 11 June 2018.

PMID:35143661 | DOI:10.1093/humrep/deac020

Bioinformatics. 2022 Feb 10:btac076. doi: 10.1093/bioinformatics/btac076. Online ahead of print.

ABSTRACT

MOTIVATION: The identification of pathways and biological processes from differential gene expression is central for interpretation of data collected by transcriptomics assays. Gene-Set Enrichment Analysis (GSEA) is the most common used algorithm to calculate the significance of the relevancy of an annotated gene set with a differential expression signature. To compute significance, GSEA implements permutation tests which are slow and inaccurate for comparing many differential expression signatures to thousands of annotated gene sets.

RESULTS: Here we present blitzGSEA, an algorithm that is based on the same running sum statistic as GSEA, but instead of performing permutations, blitzGSEA approximates the enrichment score probabilities based on Gamma distributions. blitzGSEA achieves dramatic improvement in performance compared with prior GSEA implementations, while approximating small p-values more accurately.

AVAILABILITY: A python package, together with all source code, and a detailed user guide are available from GitHub at: https://github.com/MaayanLab/blitzgsea.

SUPPLEMENTARY INFORMATION: Supplementary text and figures are available at Bioinformatics online.

PMID:35143610 | DOI:10.1093/bioinformatics/btac076