Impacts of Stocking Density on Development and Puberty Attainment of Replacement Beef Heifers

The following experiment presented herein compared growth, physical activity, stress-related responses, and puberty attainment in heifers reared on high- (HIDENS) or low-stocking densities (LOWDENS). Sixty Angus x Hereford heifers were ranked by age and BW (210 ± 2 d and 220 ± 2 kg, respectively) on d 0, and assigned to: a) 1 of 3 drylot pens (10 × 14 m pens; 10 heifers/pen) resulting in a stocking density of 14 m²/heifer (HIDENS; n = 3), or b) 1 of 3 pastures (25-ha pastures; 10 heifers/pasture), resulting in a stocking density of 25,000 m²/heifer (LOWDENS; n = 3). Pastures utilized herein were harvested for hay prior to the beginning of this experiment, and negligible forage was available for grazing to LOWDENS heifers throughout the experimental period (d 0 to 182). Heifers received the same limit-fed diet during the experiment, which averaged (DM basis) 4.0 kg/heifer daily of alfalfa-grass hay and 3.0 kg/heifer daily of a corn-based concentrate. Heifer shrunk BW was recorded after 16 h of feed and water withdrawal on d -3 and d 183 for ADG calculation. On d 0, heifers were fitted with a pedometer fixed behind their right shoulder. Each week during the experiment, pedometer results were recorded and blood samples were collected for puberty evaluation via plasma progesterone. Plasma samples collected on d 0, 28, 56, 84, 112, 140, 161, and 182 were also analyzed for concentrations of cortisol and IGF-I. On d 28, 102, and 175, blood samples were also collected for RNA isolation and analysis of heat shock protein (HSP) 70 and HSP72 mRNA expression. On d 0, 49, 98, 147, and 182, hair samples were collected from the tail switch for analysis of hair cortisol concentrations. No treatment effects were detected (P = 0.66) for heifer BW or ADG. Heifers from LOWDENS had more (P < 0.01) steps/week compared with HIDENS. Heifers from LOWDENS had greater (P = 0.05) mRNA expression of HSP72, and tended (P = 0.10) to have greater mRNA expression of HSP70 compared with HIDENS. Plasma concentrations of cortisol and IGF-I were often greater (P ≤ 0.05) in LOWDENS vs. HIDENS heifers (treatment × day interaction; P < 0.01). Hair cortisol concentrations were greater (P < 0.01) for HIDENS vs. LOWDENS heifers beginning on d 98 (treatment × day interaction; P < 0.01). Heifers from HIDENS experienced delayed puberty attainment and had a lower (P < 0.01) proportion of pubertal heifers on d 182 compared with LOWDENS (treatment × day interaction; P < 0.01). In summary, HIDENS negatively impacted heifer stress-related and physiological responses, and delayed puberty attainment compared with LOWDENS

The impact of coronavirus disease 2019 on genitourinary and prostate cancer care and clinical trials: a qualitative exploration of the Australian and New Zealand experience.

Abstract: Purpose: This qualitative study aimed to understand the impact of the coronavirus disease 2019 pandemic from March to November 2020 on healthcare delivery and clinical trials for genitourinary (GU) cancers in Australia. Methods: Annually a pre‐conference workshop is hosted by the Australian New Zealand Urogenital and Prostate Cancer Trials Group for supportive care health professionals. In November 2020, those that selected to attend were invited to participate in a focus group. Workshop and focus group discussions were recorded and transcripts were analyzed thematically. Results: Seventy‐two individuals involved in GU cancer care and clinical trials took part. Participants described negative changes to GU cancer care and clinical trials from the pandemic due to reduced clinical services and increased wait times. Trial recruitment was paused temporarily during lockdowns, and standard treatment protocols were used to limit hospital visits. Trial process changes included electronic capture of informed consent, home delivery of oral medications, and delegations of assessments. These changes increased administrative activity for clinical trial teams and Human Research Ethics Committees. A transition to telehealth enabled continuity of service delivery and trials but reduced the opportunity for face‐to‐face patient consultations with increasing concern about the failure to detect supportive care needs. Conclusion: The pandemic has prompted a critical review of service delivery and clinical trials for people with GU cancers

An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge

BACKGROUND: There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data was donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. RESULTS: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. CONCLUSIONS: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups

Imbalance-Aware Machine Learning for Predicting Rare and Common Disease-Associated Non-Coding Variants

Disease and trait-associated variants represent a tiny minority of all known genetic variation, and therefore there is necessarily an imbalance between the small set of available disease-associated and the much larger set of non-deleterious genomic variation, especially in non-coding regulatory regions of human genome. Machine Learning (ML) methods for predicting disease-associated non-coding variants are faced with a chicken and egg problem - such variants cannot be easily found without ML, but ML cannot begin to be effective until a sufficient number of instances have been found. Most of state-of-the-art ML-based methods do not adopt specific imbalance-aware learning techniques to deal with imbalanced data that naturally arise in several genome-wide variant scoring problems, thus resulting in a significant reduction of sensitivity and precision. We present a novel method that adopts imbalance-aware learning strategies based on resampling techniques and a hyper-ensemble approach that outperforms state-of-the-art methods in two different contexts: the prediction of non-coding variants associated with Mendelian and with complex diseases. We show that imbalance-aware ML is a key issue for the design of robust and accurate prediction algorithms and we provide a method and an easy-to-use software tool that can be effectively applied to this challenging prediction task

parSMURF, a high-performance computing tool for the genome-wide detection of pathogenic variants

BACKGROUND: Several prediction problems in computational biology and genomic medicine are characterized by both big data as well as a high imbalance between examples to be learned, whereby positive examples can represent a tiny minority with respect to negative examples. For instance, deleterious or pathogenic variants are overwhelmed by the sea of neutral variants in the non-coding regions of the genome: thus, the prediction of deleterious variants is a challenging, highly imbalanced classification problem, and classical prediction tools fail to detect the rare pathogenic examples among the huge amount of neutral variants or undergo severe restrictions in managing big genomic data. RESULTS: To overcome these limitations we propose parSMURF, a method that adopts a hyper-ensemble approach and oversampling and undersampling techniques to deal with imbalanced data, and parallel computational techniques to both manage big genomic data and substantially speed up the computation. The synergy between Bayesian optimization techniques and the parallel nature of parSMURF enables efficient and user-friendly automatic tuning of the hyper-parameters of the algorithm, and allows specific learning problems in genomic medicine to be easily fit. Moreover, by using MPI parallel and machine learning ensemble techniques, parSMURF can manage big data by partitioning them across the nodes of a high-performance computing cluster. Results with synthetic data and with single-nucleotide variants associated with Mendelian diseases and with genome-wide association study hits in the non-coding regions of the human genome, involhing millions of examples, show that parSMURF achieves state-of-the-art results and an 80-fold speed-up with respect to the sequential version. CONCLUSIONS: parSMURF is a parallel machine learning tool that can be trained to learn different genomic problems, and its multiple levels of parallelization and high scalability allow us to efficiently fit problems characterized by big and imbalanced genomic data. The C++ OpenMP multi-core version tailored to a single workstation and the C++ MPI/OpenMP hybrid multi-core and multi-node parSMURF version tailored to a High Performance Computing cluster are both available at https://github.com/AnacletoLAB/parSMURF

Predictive value of decreased p27Kip1 protein expression for the recurrence-free and long-term survival of prostate cancer patients

The p27Kip1 gene has been identified as inductor of cell cycle arrest at the G1 checkpoint to prevent entry of somatic cells into the S phase of the cell cycle when substantial DNA damage has occurred. It has been suggested that decreased expression of the p27Kip1 protein may contribute to the development of human malignancies due to loss of critical antiproliferative mechanisms. In the present study, 95 specimens (T1–T4) from 95 randomly selected patients undergoing radical prostatectomy at the Urological Department of Hannover University (82 patients) as well as in the Josef Hospital Regensburg (13 patients) between 1981 and 1992 for whom tissue blocks for immunohistochemical investigation were available, were investigated for different biological and clinical characteristics as possible predictors for recurrence-free and long-term survival: age, depth of tumour infiltration, histological grade, lymph node status, as well as decreased expression of the p27Kip1 protein. After a median follow-up up of 56 months (24–151 months), seven of 21 (33%) patients (Group 1) with loss of p27Kip1 protein expression or a relative amount of <10% of positively stained tumour cells developed recurrent disease in contrast to 17 of 74 (23%) patients (Group 2) with retained p27Kip1 protein expression (≥10% of positively stained tumour cells). The median recurrence-free survival was 14 months (5–40 months) for patients from Group 1 and 31 months (7–133 months) for Group 2 patients (P = 0.02). In multivariate analysis, loss of p27Kip1 protein expression was identified as the only independent prognostic parameter for recurrence-free survival. In contrast, neither the univariate nor the multivariate analysis showed a correlation between loss of p27Kip1 protein expression and the long-term survival of the patients. Prospective studies are urgently needed to confirm the independent prognostic value of decreased p27Kip1 protein expression together with overexpression of the p53 tumour suppressor protein in patients with localized prostate cancer. The availability of more refined prognostically important biological variables in addition to established prognostic factors like tumour stage or Gleason score might help decision making in patients at high risk for the development of local recurrence or systemic tumour progression. © 1999 Cancer Research Campaig

Growth factor and co-receptor release by structural regulation of substrate metalloprotease accessibility

Release of cytokines, growth factors and other life-essential molecules from precursors by a-disintegrin-and-metalloproteases (ADAMs) is regulated with high substrate-specificity. We hypothesized that this is achieved by cleavage-regulatory intracellular-domain (ICD)-modifications of the precursors. We show here that cleavage-stimuli-induced specific ICD-modifications cause structural substrate changes that enhance ectodomain sensitivity of neuregulin-1 (NRG1; epidermal-growth-factor) or CD44 (receptor-tyrosine-kinase (RTK) co-receptor) to chymotrypsin/trypsin or soluble ADAM. This inside-out signal transfer required substrate homodimerization and was prevented by cleavage-inhibitory ICD-mutations. In chimeras, regulation could be conferred to a foreign ectodomain, suggesting a common higher-order structure. We predict that substrate-specific protease-accessibility-regulation controls release of numerous ADAM substrates

Viability and Burden of Leishmania in Extralesional Sites during Human Dermal Leishmaniasis

Understanding of the dynamics and distribution of Leishmania in the human host is fundamental to the targeting of control measures and their evaluation. Amplification of parasite gene sequences in clinical samples from cutaneous leishmaniasis patients has provided evidence of Leishmania in blood, other tissues and sites distinct from the lesion and of persistence of infection after clinical resolution of disease. However, there is uncertainty about the interpretation of the presence of Leishmania DNA as indicative of viable parasites. Because RNA is short-lived and labile, its presence provides an indicator of viability. We amplified Leishmania 7SLRNA, a molecule involved in intracellular protein translocation, to establish viability and estimate parasite load in blood monocytes, tonsil swab samples, and tissue fluid from healthy skin of patients with dermal leishmaniasis. Results showed that during active dermal leishmaniasis, viable Leishmania are present in blood monocytes, tonsils and normal skin in quantities similar to that in lesions, demonstrating widespread dissemination of infection and subclinical involvement of tissues beyond the lesion site. Leishmania 7SLRNA will be useful in deciphering the role of human infection in transmission