Abelnelson5669

While a combination of R-(+)-limonene and (+)-α-pinene resulted in a 97% reduction in the number of P. juglandis caught, the combination did not consistently result in greater flight trap catch reduction than individual limonene enantiomers. The repellent effect of limonene may be valuable in the development of a semiochemical-based tool for management of P. juglandis and thousand cankers disease.

Prediction of genomic annotations from DNA sequences using deep learning is today becoming a flourishing field with many applications. Nevertheless, there are still difficulties in handling data in order to conveniently build and train models dedicated for specific end-user's tasks. keras_dna is designed for an easy implementation of Keras models (TensorFlow high level API) for genomics. It can handle standard bioinformatic files formats as inputs such as bigwig, gff, bed, wig, bedGraph, or fasta and returns standardized inputs for model training. keras_dna is designed to implement existing models but also to facilitate the development of news models that can have single or multiple targets or inputs.

Freely available with a MIT License using pip install keras_dna or cloning the github repo at https//github.com/etirouthier/keras_dna.git.

julien.mozziconacci@mnhn.fr and etienne.routhier@upmc.fr.

An extensive documentation can be found online at https//keras-dna.readthedocs.io/en/latest/.

An extensive documentation can be found online at https//keras-dna.readthedocs.io/en/latest/.

Ovarian cancer causes high mortality rate worldwide, and despite numerous attempts, the outcome for patients with ovarian cancer are still not well improved. Microarray-based gene expressional analysis provides with valuable information for discriminating functional genes in ovarian cancer development and progression. However, due to the differences in experimental design, the results varied significantly across individual datasets.

In the present study, the data of gene expression in ovarian cancer were downloaded from Gene Expression Omnibus (GEO) and 16 studies were included. A meta-analysis based gene expression analysis was performed to identify differentially expressed genes (DEGs). The most differentially expressed genes in our meta-analysis were selected for gene expression and gene function validation.

A total of 972 DEGs with P-value < 0.001 were identified in ovarian cancer, including 541 up-regulated genes and 431 down-regulated genes, among which 92 additional DEGs were found as gained Dovel diagnostic and therapeutic targets in ovarian cancer.

Little is known about the specific breastmilk components responsible for protective effects on infant obesity. Whether 12,13-dihydroxy-9Z-octadecenoic acid (12,13-diHOME), an oxidized linoleic acid metabolite and activator of brown fat metabolism, is present in human milk, or linked to infant adiposity, is unknown.

To examine associations between concentrations of 12,13-diHOME in human milk and infant adiposity.

Prospective cohort study from 2015 to 2019, following participants from birth to 6 months of age.

Academic medical centers.

Volunteer sample of 58 exclusively breastfeeding mother-infant pairs; exclusion criteria included smoking, gestational diabetes, and health conditions with the potential to influence maternal or infant weight gain.

Infant anthropometric measures including weight, length, body mass index (BMI), and body composition at birth and at 1, 3, and 6 months postpartum.

We report for the first time that 12,13-diHOME is present in human milk. Higher milk 12,13-diHOME level was associated with increased weight-for-length Z-score at birth (β = 0.5742, P = 0.0008), lower infant fat mass at 1 month (P = 0.021), and reduced gain in BMI Z-score from 0 to 6 months (β = -0.3997, P = 0.025). We observed similar associations between infant adiposity and milk abundance of related oxidized linoleic acid metabolites 12,13-Epoxy-9(Z)-octadecenoic acid (12,13-epOME) and 9,10-Dihydroxy-12-octadecenoic acid (9,10-diHOME), and metabolites linked to thermogenesis including succinate and lyso-phosphatidylglycerol 180. Milk abundance of 12,13-diHOME was not associated with maternal BMI, but was positively associated with maternal height, milk glucose concentration, and was significantly increased after a bout of moderate exercise.

We report novel associations between milk abundance of 12,13-diHOME and adiposity during infancy.

We report novel associations between milk abundance of 12,13-diHOME and adiposity during infancy.

Mortality Tracker is an in-browser application for data wrangling, analysis, dissemination and visualization of public time series of mortality in the United States. It was developed in response to requests by epidemiologists for portable real time assessment of the effect of COVID-19 on other causes of death and all-cause mortality. This is performed by comparing 2020 real time values with observations from the same week in the previous 5 years, and by enabling the extraction of temporal snapshots of mortality series that facilitate modeling the interdependence between its causes.

Our solution employs a scalable "Data Commons at Web Scale" approach that abstracts all stages of the data cycle as in-browser components. Specifically, the data wrangling computation, not just the orchestration of data retrieval, takes place in the browser, without any requirement to download or install software. check details This approach, where operations that would normally be computed server-side are maped to in-browser SDKs, is sometimes loosely described as Web APIs, a designation adopted here.

https//episphere.github.io/mortalitytracker; webcast demo youtu.be/ZsvCe7cZzLo.

https//episphere.github.io/mortalitytracker; webcast demo youtu.be/ZsvCe7cZzLo.Angiotensin-converting enzyme II (ACE2) is a homologue of angiotensin-converting enzyme discovered in 2000. From the initial discovery, it was recognized that the kidneys were organs very rich on ACE2. Subsequent studies demonstrated the precise localization of ACE2 within the kidney and the importance of this enzyme in the metabolism of Angiotensin II and the formation of Angiotensin 1-7. With the recognition early in 2020 of ACE2 being the main receptor of severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2), the interest in this protein has dramatically increased. In this review, we will focus on kidney ACE2; its localization, its alterations in hypertension, diabetes, the effect of ACE inhibitors and angiotensin type 1 receptor blockers (ARBs) on ACE2 and the potential use of ACE2 recombinant proteins therapeutically for kidney disease. We also describe the emerging kidney manifestations of COVID-19, namely the frequent development of acute kidney injury. The possibility that binding of SARS-CoV-2 to kidney ACE2 plays a role in the kidney manifestations is also briefly discussed.