Bioactive peptides in preterm human milk: Impact of maternal characteristics and their association to neonatal outcomes

Human milk adipokines in term babies seem partially determined by maternal factors and affect infant's development. We aimed to describe bioactive peptide concentration in very preterm human milk and associations to maternal characteristics and postnatal growth. Mothers delivering ≤32 weeks of gestation and their infant/s were recruited. At 4 weeks of lactation, an aliquot of 24-h-pooled milk was collected for exclusively breastfeeding dyads. Insulin, leptin, adiponectin, and milk fat globule epidermal growth factor-8 (MFG-E8) were measured by enzyme-linked immunoabsorbent assay in skimmed milk. One hundred mothers (28.8 ± 2.3 weeks at delivery) provided a milk sample. Milk insulin was related to gestational age, pre-pregnancy body mass index (BMI), and galactagogue treatment (final model: adjusted R2 : 0.330, p < 0.0001; adjusted β coefficients: galactagogue treatment: 0.348, p 0.001; pre-pregnancy BMI: 0.274, p 0.009; gestational age: -0.290, p 0.007). Adiponectin was higher in mothers with gestational diabetes (30.7 ± 6.5 vs. 24.8 ± 8 ng/mL, p 0.044). Leptin was associated with pre-pregnancy BMI (Spearman's ρ: 0.648, p < 0.0001) and MFG-E8 to presence of labor and multiple pregnancy (final linear regression model, R2 : 0.073, p 0.028, adjusted β coefficients: presence of labor -0.229, p 0.050; twins: -0.192, p 0.099). Milk adiponectin was associated with a greater decrease in length z-scores from birth to 28 days (Pearson's r: -0.225, p 0.032) and to discharge (Pearson's r: -0.290, p 0.003). Milk MFG-E8 was lower in milk of mothers whose babies experienced late-onset sepsis (13.3 ± 5.8 vs. 16.8 ± 6.3 μg/mL, p 0.023). Adipokines levels in preterm human milk are partially related to maternal metabolic status. Milk peptide concentration associates with early neonatal growth trajectories.

WFA-GPU: gap-affine pairwise read-alignment using GPUs

MOTIVATION

Advances in genomics and sequencing technologies demand faster and more scalable analysis methods that can process longer sequences with higher accuracy. However, classical pairwise alignment methods, based on dynamic programming (DP), impose impractical computational requirements to align long and noisy sequences like those produced by PacBio and Nanopore technologies. The recently proposed wavefront alignment (WFA) algorithm paves the way for more efficient alignment tools, improving time and memory complexity over previous methods. However, high-performance computing (HPC) platforms require efficient parallel algorithms and tools to exploit the computing resources available on modern accelerator-based architectures.

RESULTS

This paper presents WFA-GPU, a GPU (graphics processing unit)-accelerated tool to compute exact gap-affine alignments based on the WFA algorithm. We present the algorithmic adaptations and performance optimizations that allow exploiting the massively parallel capabilities of modern GPU devices to accelerate the alignment computations. In particular, we propose a CPU-GPU co-design capable of performing inter-sequence and intra-sequence parallel sequence alignment, combining a succinct WFA-data representation with an efficient GPU implementation. As a result, we demonstrate that our implementation outperforms the original multi-threaded WFA implementation by up to 4.3× and up to 18.2× when using heuristic methods on long and noisy sequences. Compared to other state-of-the-art tools and libraries, the WFA-GPU is up to 29× faster than other GPU implementations and up to four orders of magnitude faster than other CPU implementations. Furthermore, WFA-GPU is the only GPU solution capable of correctly aligning long reads using a commodity GPU.

AVAILABILITY AND IMPLEMENTATION

WFA-GPU code and documentation are publicly available at https://github.com/quim0/WFA-GPU.

Control of Brain State Transitions with a Photoswitchable Muscarinic Agonist

The ability to control neural activity is essential for research not only in basic neuroscience, as spatiotemporal control of activity is a fundamental experimental tool, but also in clinical neurology for therapeutic brain interventions. Transcranial-magnetic, ultrasound, and alternating/direct current (AC/DC) stimulation are some available means of spatiotemporal controlled neuromodulation. There is also light-mediated control, such as optogenetics, which has revolutionized neuroscience research, yet its clinical translation is hampered by the need for gene manipulation. As a drug-based light-mediated control, the effect of a photoswitchable muscarinic agonist (Phthalimide-Azo-Iper (PAI)) on a brain network is evaluated in this study. First, the conditions to manipulate M2 muscarinic receptors with light in the experimental setup are determined. Next, physiological synchronous emergent cortical activity consisting of slow oscillations-as in slow wave sleep-is transformed into a higher frequency pattern in the cerebral cortex, both in vitro and in vivo, as a consequence of PAI activation with light. These results open the way to study cholinergic neuromodulation and to control spatiotemporal patterns of activity in different brain states, their transitions, and their links to cognition and behavior. The approach can be applied to different organisms and does not require genetic manipulation, which would make it translational to humans.

PD-L1 as a Prognostic Factor in Early-Stage Colon Carcinoma within the Immunohistochemical Molecular Subtype Classification

BACKGROUND

There is a patent need to better characterize early-stage colorectal cancer (CRC) patients. PD-1 ligand (PD-L1) expression has been proposed as a prognostic factor but yields mixed results in different settings. The Consensus Molecular Subtype (CMS) classification has yet to be integrated into clinical practice. We sought to evaluate the prognostic value of PD-L1 expression overall and within CMS in early-stage colon cancer patients, in the hope of assisting treatment choice in this setting.

METHODS

Tissue-microarrays were constructed from tumor samples of 162 stage II/III CRC patients. They underwent automatic immunohistochemical staining for PD-L1 and the proposed CMS panel. Primary endpoints were overall survival (OS) and disease-free survival (DFS).

RESULTS

PD-L1 expression was significantly and independently associated with better prognosis (HR = 0.46 (0.26-0.82), p = 0.009) and was mostly seen in immune cells of the tumor-related stroma. CMS4 five-folds the risk of mortalitycompared with CMS1 (HR = 5.58 (1.36, 22.0), p = 0.034). In the subgroup CMS2/CMS3 analysis, PD-L1 expression significantly differentiated individuals with better OS (p = 0.004) and DFS (p < 0.001).

CONCLUSIONS

Our study suggests that PD-L1 expression is an independent prognostic factor in patients with stage II/III colon cancer. Additionally, it successfully differentiates patients with better prognosis in the CMS2/CMS3 group and may prove significant for the clinical relevance of the CMS classification.

Molecular and Cellular Mechanisms Affected in ALS

Amyotrophic lateral sclerosis (ALS) is a terminal late-onset condition characterized by the loss of upper and lower motor neurons. Mutations in more than 30 genes are associated to the disease, but these explain only ~20% of cases. The molecular functions of these genes implicate a wide range of cellular processes in ALS pathology, a cohesive understanding of which may provide clues to common molecular mechanisms across both familial (inherited) and sporadic cases and could be key to the development of effective therapeutic approaches. Here, the different pathways that have been investigated in ALS are summarized, discussing in detail: mitochondrial dysfunction, oxidative stress, axonal transport dysregulation, glutamate excitotoxicity, endosomal and vesicular transport impairment, impaired protein homeostasis, and aberrant RNA metabolism. This review considers the mechanistic roles of ALS-associated genes in pathology, viewed through the prism of shared molecular pathways.

Interactive virtual 3D models of renal cancer patient anatomies alter partial nephrectomy surgical planning decisions and increase surgeon confidence compared to volume-rendered images

Purpose

To determine whether the interactive visualisation of patient-specific virtual 3D models of the renal anatomy influences the pre-operative decision-making process of urological surgeons for complex renal cancer operations.

Methods

Five historic renal cancer patient pre-operative computed tomography (CT) datasets were retrospectively selected based on RENAL nephrectomy score and variety of anatomy. Interactive virtual 3D models were generated for each dataset using image segmentation software and were made available for online visualisation and manipulation. Consultant urologists were invited to participate in the survey which consisted of CT and volume-rendered images (VRI) for the control arm, and CT with segmentation overlay and the virtual 3D model for the intervention arm. A questionnaire regarding anatomical structures, surgical approach, and confidence was administered.

Results

Twenty-five participants were recruited (54% response rate), with 19/25 having > 5 years of renal surgery experience. The median anatomical clarity score increased from 3 for the control to 5 for the intervention arm. A change in planned surgical approach was reported in 19% of cases. Virtual 3D models increased surgeon confidence in the surgical decisions in 4/5 patient datasets. There was a statistically significant improvement in surgeon opinion of the potential utility for decision-making purposes of virtual 3D models as compared to VRI at the multidisciplinary team meeting, theatre planning, and intra-operative stages.

Conclusion

The use of pre-operative interactive virtual 3D models for surgery planning influences surgical decision-making. Further studies are needed to investigate if the use of these models changes renal cancer surgery outcomes.

Electronic supplementary material

The online version of this article (10.1007/s11548-019-01913-5) contains supplementary material, which is available to authorized users.

Challenging the heterogeneity of disease presentation in malignant melanoma-impact on patient treatment

There is an increasing global interest to support research areas that can assist in understanding disease and improving patient care. The National Cancer Institute (NIH) has identified precision medicine-based approaches as key research strategies to expedite advances in cancer research. The Cancer Moonshot program ( https://www.cancer.gov/research/key-initiatives/moonshot-cancer-initiative ) is the largest cancer program of all time, and has been launched to accelerate cancer research that aims to increase the availability of therapies to more patients and, ultimately, to eradicate cancer. Mass spectrometry-based proteomics has been extensively used to study the molecular mechanisms of cancer, to define molecular subtypes of tumors, to map cancer-associated protein interaction networks and post-translational modifications, and to aid in the development of new therapeutics and new diagnostic and prognostic tests. To establish the basis for our melanoma studies, we have established the Southern Sweden Malignant Melanoma Biobank. Tissues collected over many years have been accurately characterized with respect to the tumor and patient information. The extreme variability displayed in the protein profiles and the detection of missense mutations has confirmed the complexity and heterogeneity of the disease. It is envisaged that the combined analysis of clinical, histological, and proteomic data will provide patients with a more personalized medical treatment. With respect to disease presentation, targeted treatment and medical mass spectrometry analysis and imaging, this overview report will outline and summarize the current achievements and status within malignant melanoma. We present data generated by our cancer research center in Lund, Sweden, where we have built extensive capabilities in biobanking, proteogenomics, and patient treatments over an extensive time period.