Effects of energy and protein status on reproductive parameters and presence of subclinical ketosis in Brown Swiss cows postpartum

This study aimed to determine protein and energy metabolites in postpartum Brown Swiss cows and their effect on the presence of subclinical ketosis and reproductive parameters. One hundred cows from four farms in the Mantaro Valley (Junín, Perú) were grouped according to parity (1, 2, 3 and 4). The variables of the metabolic profile (total proteins, blood urea nitrogen [BUN], glucose, βhydroxybutyrate [B-HB]), milk production and body condition were estimated between 7 to 60 days postpartum in 7-day intervals. Likewise, the calving-first heat interval and the pregnancy rate at first service were recorded. The determination of subclinical ketosis was based on a semi-quantitative analysis by levels of B-HB in milk (µmol/l) using a commercial kit. BUN levels ranged between 11.74 and 15.92 mg/dl, being higher in fourth parity cows (p<0.05). The averages of total protein (6.54-7.90 g/dl) were homogeneous between calvings. The glucose values presented an inverse response, being lower in cows of third and fourth parity compared to cows of first and second parity (p<0.05). Similarly, the highest levels of milk production were observed in third parity cows (14.41 ± 5.42 l/d) and fourth parity (15.43 ± 4.36 l/d) with respect to first and second calvers (p<0.05). Body condition was lower in cows with subclinical ketosis. The calving - first heat interval and the pregnancy rate at first service were lower in cows with subclinical ketosis (p<0.05).

On the Dependence of Prion and Amyloid Structure on the Folding Environment

Currently available analyses of amyloid proteins reveal the necessity of the existence of radical structural changes in amyloid transformation processes. The analysis carried out in this paper based on the model called fuzzy oil drop (FOD) and its modified form (FOD-M) allows quantifying the role of the environment, particularly including the aquatic environment. The starting point and basis for the present presentation is the statement about the presence of two fundamentally different methods of organizing polypeptides into ordered conformations—globular proteins and amyloids. The present study shows the source of the differences between these two paths resulting from the specificity of the external force field coming from the environment, including the aquatic and hydrophobic one. The water environment expressed in the fuzzy oil drop model using the 3D Gauss function directs the folding process towards the construction of a micelle-like system with a hydrophobic core in the central part and the exposure of polarity on the surface. The hydrophobicity distribution of membrane proteins has the opposite characteristic: Exposure of hydrophobicity at the surface of the membrane protein with an often polar center (as in the case of ion channels) is expected. The structure of most proteins is influenced by a more or less modified force field generated by water through the appropriate presence of a non-polar (membrane-like) environment. The determination of the proportion of a factor different from polar water enables the assessment of the protein status by indicating factors favoring the structure it represents.

hENT1 Predicts Benefit from Gemcitabine in Pancreatic Cancer but Only with Low CDA mRNA

Gemcitabine or 5-fluorouracil (5-FU) based treatments can be selected for pancreatic cancer. Equilibrative nucleoside transporter 1 (hENT1) predicts adjuvant gemcitabine treatment benefit over 5-FU. Cytidine deaminase (CDA), inside or outside of the cancer cell, will deaminate gemcitabine, altering transporter affinity. ESPAC-3(v2) was a pancreatic cancer trial comparing adjuvant gemcitabine and 5-FU. Tissue microarray sections underwent in situ hybridization and immunohistochemistry. Analysis of both CDA and hENT1 was possible with 277 patients. The transcript did not correlate with protein levels for either marker. High hENT1 protein was prognostic with gemcitabine; median overall survival was 26.0 v 16.8 months (p = 0.006). Low CDA transcript was prognostic regardless of arm; 24.8 v 21.2 months with gemcitabine (p = 0.02) and 26.4 v 14.6 months with 5-FU (p = 0.02). Patients with low hENT1 protein did better with 5-FU, but only if the CDA transcript was low (median survival of 5-FU v gemcitabine; 29.3 v 18.3 months, compared with 14.2 v 14.6 with high CDA). CDA mRNA is an independent prognostic biomarker. When added to hENT1 protein status, it may also provide treatment-specific predictive information and, within the frame of a personalized treatment strategy, guide to either gemcitabine or 5FU for the individual patient.

Protein status of people with phenylketonuria: a scoping review protocol

IntroductionPhenylketonuria (PKU) is a disorder of protein metabolism resulting in an accumulation of phenylalanine in the body. Dietary management consists of altering the sources of ingested protein to limit phenylalanine intake. Current dietary protein guidelines for PKU are based on limited scientific evidence, thus it remains unclear whether current practice leads to optimal protein status in people with PKU. To date, no attempt has been made to systematically evaluate the protein status of people with PKU, using a combination of validated anthropometric, biochemical and functional measurement tools. Furthermore, factors known to influence protein status in the general population warrant consideration when determining protein status in individuals with PKU, alongside factors unique to PKU such as the type of protein substitute consumed. Understanding the impact of these variables on protein status is crucial to developing a personalised approach to protein recommendations for optimising health and functional outcomes in people with PKU. Therefore, the aim of this scoping review is to examine existing evidence regarding the protein status of people with PKU, and to investigate the nutritional and lifestyle variables that influence protein status.Methods and analysisThis review will be guided by Arksey and O’Malley’s framework, along with guidance from Levac et al, Pawliuk et al and the Joanna Briggs Institute. The following databases will be searched: MEDLINE (Ovid), Embase, CENTRAL, Web of Science and Scopus, alongside grey literature. Identified literature will be assessed by two independent reviewers for inclusion. Descriptive numerical analysis will be performed and a narrative summary will accompany the tabulated results describing how study findings relate to the review questions.Ethics and disseminationThis review protocol does not require ethical approval. Findings will be disseminated through peer-reviewed publication, presented at relevant conferences, and shared with a patient research advisory group to inform discussions on future research.

PTEN and DNA Ploidy Status by Machine Learning in Prostate Cancer

Machine learning (ML) is expected to improve biomarker assessment. Using convolution neural networks, we developed a fully-automated method for assessing PTEN protein status in immunohistochemically-stained slides using a radical prostatectomy (RP) cohort (n = 253). It was validated according to a predefined protocol in an independent RP cohort (n = 259), alone and by measuring its prognostic value in combination with DNA ploidy status determined by ML-based image cytometry. In the primary analysis, automatically assessed dichotomized PTEN status was associated with time to biochemical recurrence (TTBCR) (hazard ratio (HR) = 3.32, 95% CI 2.05 to 5.38). Patients with both non-diploid tumors and PTEN-low had an HR of 4.63 (95% CI 2.50 to 8.57), while patients with one of these characteristics had an HR of 1.94 (95% CI 1.15 to 3.30), compared to patients with diploid tumors and PTEN-high, in univariable analysis of TTBCR in the validation cohort. Automatic PTEN scoring was strongly predictive of the PTEN status assessed by human experts (area under the curve 0.987 (95% CI 0.968 to 0.994)). This suggests that PTEN status can be accurately assessed using ML, and that the combined marker of automatically assessed PTEN and DNA ploidy status may provide an objective supplement to the existing risk stratification factors in prostate cancer.

PD-L1 Expression Is an Independent Marker for Lymph Node Metastasis in Middle Eastern Endometrial Cancer

Programmed death ligand 1 (PD-L1) expression in endometrial cancer (EC) tumor cells have been reported in several studies with inconsistent results. Furthermore, there is scarcity of data on the prevalence and prognostic significance of PD-L1 expression in EC from Middle Eastern ethnicity. We aimed to assess PD-L1 expression in a large cohort of Middle Eastern EC and to correlate this with clinico-pathological factors, as well as mismatch repair (MMR) protein status and patients’ outcome. PD-L1 expression was investigated using immunohistochemistry on tissue microarray in an unselected cohort of 440 EC. Kaplan–Meier and logistic regression analysis were used to compare the outcome and prognostic factors. PD-L1 expression in tumor tissue was detected in 18.9% (83/440) EC cases with no impact on survival. When stratified for MMR protein status, PD-L1 expression was similar for both MMR deficient and MMR proficient ECs. However, the expression of PD-L1 in tumor cells was significantly associated with type II (non-endometrioid) histology (p = 0.0005) and lymph node metastasis (p = 0.0172). Multivariate analysis showed PD-L1 expression to be an independent risk factor for lymph node metastasis (odds ratio: 2.94; 95% CI: 1.26–6.84; p = 0.0123). In conclusion, PD-L1 was strongly associated with non-endometrioid EC and was an independent prognostic marker of lymph node metastasis.

Relationship with programmed cell death ligand 1 (PD-L1) and DTI features in brain metastases of non-small cell lung cancer; Preliminary study

Objectives: The purpose of the study was to determine DTI properties of brain metastases in subjects with non-small cell lung carcinoma (NSCLC), to evaluate whether there was a correlation between DTI findings and programmed cell death ligand-1 (PD-L1). Methods: The study population (n:22) was assigned to PD-L1 negative (Group 1: PD-L1 expression<%50) (n=11) or positive (Group 2: PD-L1 expression ≥%50) (n=11). We compared ADC and FA values measured from the enhanced solid metastases and peritumoral edema area with PD-L1 protein status. Results: The mean ADC values were lower in group 2 compared to group 1. The peritumoral ADC values were higher in group 2 compared to group 1. Mean peritumoral edema FA values are lower in group 2 compared to group 1. The peritumoral edema nADC values were higher in group 2 compared to group 1. As PD-L1 expression frequency increased, ADC values in the peritumoral edema area increased and FA values decreased. Conclusions: We thought that the existence of PD-L1 protein doesn’t affect ADC and FA values of brain metastasis (BM) originating from NSCLC. DTI characteristics of the peritumoral edema area could be a guide in determining PD-L1 protein status of brain metastases of NSCLC. The relationship between PD-L1 expression status and DTI features in BM from NSCLC could help us to have an idea in response to immunotherapy.