Vascular hamartoma in the distal region of the anterior face of the left forearm, a rare lesion: a case report

The word hamartoma is derived from the Greek word hamartia meaning "to err" or "to blame", with the addition of "-oma" denoting a tumor-like growth. Hamartomas are non-malignant tissue malformations characterized by defective dissemination of fully differentiated cells and soft tissue native to the affected organ. If the tissues involved are composed of blood vessels, they are called vascular hamartomas. In our manuscript we describe the case of a 16-year-old adolescent with the presence of a tumor in the distal region, anterior face of the left forearm, who underwent an excisional biopsy with histopathological report of vascular hamartoma, currently with adequate postoperative evolution. The most commonly reported site of occurrence of vascular hamartomas is on the face and they are generally asymptomatic and silent at different stages of life. The definitive diagnosis for this type of pathology is by histopathology. Vascular hamartomas are a rarely reported benign pathology, due to their low incidence, this can make timely diagnosis difficult, as well as the ideal treatment for these patients

OMWS: A Web Service Interface for Ecological Niche Modelling

[EN] Ecological niche modelling (ENM) experiments often involve a high number of tasks to be performed. Such tasks may consume a significant amount of computing resources and take a long time to complete, especially when using personal computers. OMWS is a Web service interface that allows more powerful computing back-ends to be remotely exploited by other applications to carry out ENM tasks. Its latest version includes a new operation that can be used to specify complex workflows in a single request, adding the possibility of using workflow management systems on parallel computing back-end. In this paper we describe the OMWS protocol and compare its most recent version with the previous one by running the same ENM experiment using two functionally equivalent clients, each designed for one of the OMWS interface versions. Different back-end configurations were used to investigate how the performance scales for each protocol version when more processing power is made available. Results show that the new version outperforms (in a factor of 2) the previous one when more computing resources are used.The latest version of OMWS contains improvements coming from different sets of requirements originated from two projects that funded their corresponding implementation: EUBrazilOpenBio14, with grants from the European Commission and the National Council for Scientific and Technological Development of Brazil (CNPq) of the Brazilian Ministry of Science and Technology (MCT), and BioVeL, with grants from the European Commission. Server infrastructure was operated through a provisioning system developed in the frame of the Spanish project CLUVIEM (TIN2013-44390-R) funded by the "Ministerio de Economía y Competitividad".Giovanni, RD.; Torres Serrano, E.; Amaral, RB.; Blanquer Espert, I.; Rebello, V.; Canhos, VP. (2015). OMWS: A Web Service Interface for Ecological Niche Modelling. Biodiversity Informatics. 10:35-44. https://doi.org/10.17161/bi.v10i0.4853S35441

Alternative Dosing Regimen of Exemestane in a Randomized Presurgical Trial: The Role of Obesity in Biomarker Modulation

In a 3-arm presurgical trial, four-six weeks exemestane 25 mg three times/week (TIW) was non-inferior to 25 mg/day (QD) in suppressing circulating estradiol in postmenopausal women with ER-positive breast cancer. Since obesity may decrease exemestane efficacy, we analyzed changes in sex steroids, adipokines, Ki-67, and drug levels in relation to obesity. Postmenopausal women with early-stage ER-positive breast cancer were randomized to either exemestane 25 mg QD (n = 57), 25 mg TIW (n = 57), or 25 mg/week (QW, n = 62) for 4-6 weeks before breast surgery. Serum and tissue pre- and post-treatment biomarkers were stratified by body mass index (BMI)\u3c or ≥30 kg/

Efficacy of Alternative Dose Regimens of Exemestane in Postmenopausal Women With Stage 0 to II Estrogen Receptor-Positive Breast Cancer: A Randomized Clinical Trial

IMPORTANCE: Successful therapeutic cancer prevention requires definition of the minimal effective dose. Aromatase inhibitors decrease breast cancer incidence in high-risk women, but use in prevention and compliance in adjuvant settings are hampered by adverse events. OBJECTIVE: To compare the noninferiority percentage change of estradiol in postmenopausal women with estrogen receptor-positive breast cancer given exemestane, 25 mg, 3 times weekly or once weekly vs a standard daily dose with a noninferiority margin of -6%. DESIGN, SETTING, AND PARTICIPANTS: This multicenter, presurgical, double-blind phase 2b randomized clinical trial evaluated 2 alternative dosing schedules of exemestane. Postmenopausal women with estrogen receptor-positive breast cancer who were candidates for breast surgery were screened from February 1, 2017, to August 31, 2019. Blood samples were collected at baseline and final visit; tissue biomarker changes were assessed from diagnostic biopsy and surgical specimen. Biomarkers were measured in different laboratories between April 2020 and December 2021. INTERVENTIONS: Exemestane, 25 mg, once daily, 3 times weekly, or once weekly for 4 to 6 weeks before surgery. MAIN OUTCOMES AND MEASURES: Serum estradiol concentrations were measured by solid-phase extraction followed by liquid chromatography-tandem mass spectrometry detection. Toxic effects were evaluated using the National Cancer Institute terminology criteria, and Ki-67 was assessed by immunohistochemistry. RESULTS: A total of 180 women were randomized into 1 of the 3 arms; median (IQR) age was 66 (60-71) years, 63 (60-69) years, and 65 (61-70) years in the once-daily, 3-times-weekly, and once-weekly arms, respectively. In the intention-to-treat population (n = 171), the least square mean percentage change of serum estradiol was -89%, -85%, and -60% for exemestane once daily (n = 55), 3 times weekly (n = 56), and once weekly (n = 60), respectively. The difference in estradiol percentage change between the once-daily and 3-times-weekly arms was -3.6% (P for noninferiority = .37), whereas in compliant participants (n = 153), it was 2.0% (97.5% lower confidence limit, -5.6%; P for noninferiority = .02). Among secondary end points, Ki-67 and progesterone receptor were reduced in all arms, with median absolute percentage changes of -7.5%, -5.0%, and -4.0% for Ki-67 in the once-daily, 3-times-weekly, and once-weekly arms, respectively (once daily vs 3 times weekly, P = .31; once daily vs once weekly, P = .06), and -17.0%, -9.0%, and -7.0% for progesterone receptor, respectively. Sex hormone-binding globulin and high-density lipoprotein cholesterol had a better profile among participants in the 3-times-weekly arm compared with once-daily arm. Adverse events were similar in all arms. CONCLUSIONS AND RELEVANCE: In this randomized clinical trial, exemestane, 25 mg, given 3 times weekly in compliant patients was noninferior to the once-daily dosage in decreasing serum estradiol. This new schedule should be further studied in prevention studies and in women who do not tolerate the daily dose in the adjuvant setting

Prognostic significance of FLT3-ITD length in AML patients treated with intensive regimens

FLT3-ITD mutations are detected in approximately 25% of newly diagnosed adult acute myeloid leukemia (AML) patients and confer an adverse prognosis. The FLT3-ITD allelic ratio has clear prognostic value. Nevertheless, there are numerous manuscripts with contradictory results regarding the prognostic relevance of the length and insertion site (IS) of the FLT3-ITD fragment. We aimed to assess the prognostic impact of these variables on the complete remission (CR) rates, overall survival (OS) and relapse-free survival (RFS) of AML patients with FLT3-ITDmutations. We studied the FLT3-ITD length of 362 adult AML patients included in the PETHEMA AML registry. We tried to validate the thresholds of ITD length previously published (i.e., 39 bp and 70 bp) in intensively treated AML patients (n = 161). We also analyzed the mutational profile of 118 FLT3-ITD AML patients with an NGS panel of 39 genes and correlated mutational status with the length and IS of ITD. The AUC of the ROC curve of the ITD length for OS prediction was 0.504, and no differences were found when applying any of the thresholds for OS, RFS or CR rate. Only four out of 106 patients had ITD IS in the TKD1 domain. Our results, alongside previous publications, confirm that FLT3-ITD length lacks prognostic value and clinical applicability. © 2021, The Author(s)

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

Cancer health disparities in racial/ethnic minorities in the United States

There are well-established disparities in cancer incidence and outcomes by race/ethnicity that result from the interplay between structural, socioeconomic, socio-environmental, behavioural and biological factors. However, large research studies designed to investigate factors contributing to cancer aetiology and progression have mainly focused on populations of European origin. The limitations in clinicopathological and genetic data, as well as the reduced availability of biospecimens from diverse populations, contribute to the knowledge gap and have the potential to widen cancer health disparities. In this review, we summarise reported disparities and associated factors in the United States of America (USA) for the most common cancers (breast, prostate, lung and colon), and for a subset of other cancers that highlight the complexity of disparities (gastric, liver, pancreas and leukaemia). We focus on populations commonly identified and referred to as racial/ethnic minorities in the USA—African Americans/Blacks, American Indians and Alaska Natives, Asians, Native Hawaiians/other Pacific Islanders and Hispanics/Latinos. We conclude that even though substantial progress has been made in understanding the factors underlying cancer health disparities, marked inequities persist. Additional efforts are needed to include participants from diverse populations in the research of cancer aetiology, biology and treatment. Furthermore, to eliminate cancer health disparities, it will be necessary to facilitate access to, and utilisation of, health services to all individuals, and to address structural inequities, including racism, that disproportionally affect racial/ethnic minorities in the USA.Fil: Zavala, Valentina A.. University of California; Estados UnidosFil: Bracci, Paige M.. University of California; Estados UnidosFil: Carethers, John M.. University of Michigan; Estados UnidosFil: Carvajal Carmona, Luis. University of California at Davis; Estados UnidosFil: Coggins, Nicole B.. University of California at Davis; Estados UnidosFil: Cruz Correa, Marcia R.. Universidad de Puerto Rico; Puerto RicoFil: Davis, Melissa. No especifíca;Fil: de Smith, Adam J.. University of California; Estados UnidosFil: Dutil, Julie. Ponce Research Institute; Puerto RicoFil: Figueiredo, Jane C.. Cedars Sinai Medical Center; Estados UnidosFil: Fox, Rena. University of California; Estados UnidosFil: Graves, Kristi D.. University Of Georgetown; Estados UnidosFil: Gomez, Scarlett Lin. University of California; Estados UnidosFil: Llera, Andrea Sabina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Neuhausen, Susan L.. No especifíca;Fil: Newman, Lisa. No especifíca;Fil: Nguyen, Tung. University of California; Estados UnidosFil: Palmer, Julie R.. National Institutes of Health; Estados UnidosFil: Palmer, Nynikka R.. University of California; Estados UnidosFil: Pérez Stable, Eliseo J.. National Institutes of Health; Estados UnidosFil: Piawah, Sorbarikor. University of California; Estados UnidosFil: Rodriquez, Erik J.. National Institutes of Health; Estados UnidosFil: Sanabria Salas, María Carolina. Instituto Nacional de Cancerología; ColombiaFil: Schmit, Stephanie L.. University of Southern California; Estados UnidosFil: Serrano Gomez, Silvia J.. Instituto Nacional de Cancerología; ColombiaFil: Stern, Mariana Carla. University of Southern California; Estados UnidosFil: Weitzel, Jeffrey. No especifíca;Fil: Yang, Jun J.. St. Jude Children’s Research Hospital; Estados UnidosFil: Zabaleta, Jovanny. No especifíca;Fil: Ziv, Elad. University of California; Estados UnidosFil: Fejerman, Laura. University of California; Estados Unido

Advancing microbiome research with machine learning : key findings from the ML4Microbiome COST action

The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve healthcare practices in the era of precision medicine. However, several challenges must be addressed to exploit the benefits of ML in this field fully. In particular, there is a need to establish "gold standard" protocols for conducting ML analysis experiments and improve interactions between microbiome researchers and ML experts. The Machine Learning Techniques in Human Microbiome Studies (ML4Microbiome) COST Action CA18131 is a European network established in 2019 to promote collaboration between discovery-oriented microbiome researchers and data-driven ML experts to optimize and standardize ML approaches for microbiome analysis. This perspective paper presents the key achievements of ML4Microbiome, which include identifying predictive and discriminatory 'omics' features, improving repeatability and comparability, developing automation procedures, and defining priority areas for the novel development of ML methods targeting the microbiome. The insights gained from ML4Microbiome will help to maximize the potential of ML in microbiome research and pave the way for new and improved healthcare practices

Tropical and Boreal Forest Atmosphere Interactions : A Review

This review presents how the boreal and the tropical forests affect the atmosphere, its chemical composition, its function, and further how that affects the climate and, in return, the ecosystems through feedback processes. Observations from key tower sites standing out due to their long-term comprehensive observations: The Amazon Tall Tower Observatory in Central Amazonia, the Zotino Tall Tower Observatory in Siberia, and the Station to Measure Ecosystem-Atmosphere Relations at Hyytiala in Finland. The review is complemented by short-term observations from networks and large experiments. The review discusses atmospheric chemistry observations, aerosol formation and processing, physiochemical aerosol, and cloud condensation nuclei properties and finds surprising similarities and important differences in the two ecosystems. The aerosol concentrations and chemistry are similar, particularly concerning the main chemical components, both dominated by an organic fraction, while the boreal ecosystem has generally higher concentrations of inorganics, due to higher influence of long-range transported air pollution. The emissions of biogenic volatile organic compounds are dominated by isoprene and monoterpene in the tropical and boreal regions, respectively, being the main precursors of the organic aerosol fraction. Observations and modeling studies show that climate change and deforestation affect the ecosystems such that the carbon and hydrological cycles in Amazonia are changing to carbon neutrality and affect precipitation downwind. In Africa, the tropical forests are so far maintaining their carbon sink. It is urgent to better understand the interaction between these major ecosystems, the atmosphere, and climate, which calls for more observation sites, providing long-term data on water, carbon, and other biogeochemical cycles. This is essential in finding a sustainable balance between forest preservation and reforestation versus a potential increase in food production and biofuels, which are critical in maintaining ecosystem services and global climate stability. Reducing global warming and deforestation is vital for tropical forests.Peer reviewe