Selective Fetal Growth Restriction Leading to Cerebral Injury in Monochorionic Twins: A Case Report.

Monochorionic twin pregnancies carry a risk of perinatal complications due to shared placental anastomoses, which can cause uneven blood distribution and lead to conditions like selective fetal growth restriction (sFGR). This case describes a monochorionic pregnancy complicated by preeclampsia and late-onset sFGR of twin B. Labor was prematurely induced and a 45% weight discordance between the twins was confirmed.

Laser-Based Length-Measuring Board for the Measurement of Infant Body Length from Outside an Incubator: Proposal and Assessment of a Model.

Introduction: Opening the incubator side wall to insert a non-sterile length-measuring device carries the risk of microbial contamination and thermal instability for preterm infants. To reduce this inconvenience, a laser-based length-measuring board is proposed to measure body length from outside the incubator.

Methods: This device has two laser-line-shaped cursors which can be pointed to opposite ends of a segment to be measured.

Deep learning-based object detection algorithms in medical imaging: Systematic review.

Over the past decade, Deep Learning (DL) techniques have demonstrated remarkable advancements across various domains, driving their widespread adoption. Particularly in medical image analysis, DL received greater attention for tasks like image segmentation, object detection, and classification. This paper provides an overview of DL-based object recognition in medical images, exploring recent methods and emphasizing different imaging techniques and anatomical applications.

Efficiently accelerated bioimage analysis with NanoPyx, a Liquid Engine-powered Python framework.

The expanding scale and complexity of microscopy image datasets require accelerated analytical workflows. NanoPyx meets this need through an adaptive framework enhanced for high-speed analysis. At the core of NanoPyx, the Liquid Engine dynamically generates optimized central processing unit and graphics processing unit code variations, learning and predicting the fastest based on input data and hardware.

A holistic study on the effects of a rural flood detention basin: Flood peaks, water quality and grass growth.

Nature-based Solutions (NbS) are widely advocated to have multiple benefits, including in flood risk reduction, water quality improvement and ecosystem health. There are, however, few empirical studies quantifying such multi-functionality. Given the ongoing pressures of flooding and poor water quality within Europe, there is an urgent need for empirical evidence to assess the potential for NbS features to address these issues.

Craniotabes in Newborns and the Role of Maternal Vitamin D Deficiency: A Case Series.

Craniotabes is characterized by the softening of skull bones in newborns. It can be associated with conditions like rickets, congenital syphilis, and osteogenesis imperfecta. In otherwise healthy newborns, craniotabes is often linked to in utero vitamin D deficiency.

Pancreatic Intraepithelial Neoplasia Revealed by Diffusion-Tensor MRI.

Objectives: Detecting premalignant lesions for pancreatic ductal adenocarcinoma, mainly pancreatic intraepithelial neoplasia (PanIN), is critical for early diagnosis and for understanding PanIN biology. Based on PanIN's histology, we hypothesized that diffusion tensor imaging (DTI) and T2* could detect PanIN.

Materials And Methods: DTI was explored for the detection and characterization of PanIN in genetically engineered mice (KC, KPC).

Revisiting the description of Atractoscion macrolepis (Perciformes: Sciaenidae): Another argument for comprehensive taxonomy.

Atractoscion macrolepis was described as a species separate to A. aequidens, distinguished by a geographically-separated distribution, genetic evidence and a diagnostic meristic character: the number of pored lateral line scales. However, the distinction of these species and description of A.

CellTracksColab is a platform that enables compilation, analysis, and exploration of cell tracking data.

In life sciences, tracking objects from movies enables researchers to quantify the behavior of single particles, organelles, bacteria, cells, and even whole animals. While numerous tools now allow automated tracking from video, a significant challenge persists in compiling, analyzing, and exploring the large datasets generated by these approaches. Here, we introduce CellTracksColab, a platform tailored to simplify the exploration and analysis of cell tracking data.

Design of a sensor to estimate suspended sediment transport in situ using the measurements of water velocity, suspended sediment concentration and depth.

- The sediment transport plays a major role in every aquatic ecosystem. However, the lack of instruments to monitor this process has been an obstacle to understanding its effects. We present the design of a single sensor built to measure water velocity, suspended sediment concentration and depth in situ, and how to associate the three variables to estimate and analyse sediment transport.

Congruent patterns of cryptic cladogenesis revealed using RADseq and Sanger sequencing in a velvet worm species complex (Onychophora: Peripatopsidae: Peripatopsis sedgwicki).

In the present study, first generation DNA sequencing (mitochondrial cytochrome c oxidase subunit one, COI) and reduced-representative genomic RADseq data were used to understand the patterns and processes of diversification of the velvet worm, Peripatopsis sedgwicki species complex across its distribution range in South Africa. For the RADseq data, three datasets (two primary and one supplementary) were generated corresponding to 1,259-11,468 SNPs, in order to assess the diversity and phylogeography of the species complex. Tree topologies for the two primary datasets were inferred using maximum likelihood and Bayesian inferences methods.

Pattern-centric transformation of omics data grounded on discriminative gene associations aids predictive tasks in TCGA while ensuring interpretability.

The increasing prevalence of omics data sources is pushing the study of regulatory mechanisms underlying complex diseases such as cancer. However, the vast quantities of molecular features produced and the inherent interplay between them lead to a level of complexity that hampers both descriptive and predictive tasks, requiring custom-built algorithms that can extract relevant information from these sources of data. We propose a transformation that moves data centered on molecules (e.

Lower-Body Power, Body Composition, Speed, and Agility Performance among Youth Soccer Players.

Speed and agility have been described as crucial abilities for soccer players. The purpose of this study was to analyze, in detail, the variance in speed and agility tasks explained by lower-body power after controlling for age and body composition. The participants were 96 male soccer players aged 16.

40S Ribosomal protein S6 kinase integrates daylength perception and growth regulation in Arabidopsis thaliana.

Plant growth occurs via the interconnection of cell growth and proliferation in each organ following specific developmental and environmental cues. Therefore, different photoperiods result in distinct growth patterns due to the integration of light and circadian perception with specific Carbon (C) partitioning strategies. In addition, the TARGET OF RAPAMYCIN (TOR) kinase pathway is an ancestral signaling pathway that integrates nutrient information with translational control and growth regulation.

Cell constriction requires processive septal peptidoglycan synthase movement independent of FtsZ treadmilling in Staphylococcus aureus.

Bacterial cell division requires recruitment of peptidoglycan (PG) synthases to the division site by the tubulin homologue, FtsZ. Septal PG synthases promote septum growth. FtsZ treadmilling is proposed to drive the processive movement of septal PG synthases and septal constriction in some bacteria; however, the precise mechanisms spatio-temporally regulating PG synthase movement and activity and FtsZ treadmilling are poorly understood.

The rise of data-driven microscopy powered by machine learning.

Optical microscopy is an indispensable tool in life sciences research, but conventional techniques require compromises between imaging parameters like speed, resolution, field of view and phototoxicity. To overcome these limitations, data-driven microscopes incorporate feedback loops between data acquisition and analysis. This review overviews how machine learning enables automated image analysis to optimise microscopy in real time.

Impact of truncating diffusion MRI scans on diffusional kurtosis imaging.

Objective: Diffusional kurtosis imaging (DKI) extends diffusion tensor imaging (DTI), characterizing non-Gaussian diffusion effects but requires longer acquisition times. To ensure the robustness of DKI parameters, data acquisition ordering should be optimized allowing for scan interruptions or shortening. Three methodologies were used to examine how reduced diffusion MRI scans impact DKI histogram-metrics: 1) the electrostatic repulsion model (Opt); 2) spherical codes (Opt); 3) random (Random).

LncRNAs: the art of being influential without protein.

The plant long noncoding (lnc)RNA field is on the brink of transitioning from large-scale identification of lncRNAs to their functional characterization. Due to the cross-kingdom conservation of interaction types and molecular functions, there is much to be learned from mammalian lncRNA research. Here, we discuss the different molecular processes involving lncRNAs from the regulation of chromatin to splicing.

Rare cause of jaundice in a term newborn.

Neonatal jaundice is a frequently observed occurrence in full-term newborns and typically manifests between 48 and 96 hours following birth. Early-onset jaundice is primarily induced by pathological factors, namely sepsis, hemolysis and an excessive accumulation of bilirubin resulting from the breakdown of red blood cells.We present a case involving a full-term newborn with an uneventful perinatal history, who exhibited jaundice within the initial day of life and was subsequently admitted to the neonatal intensive care unit to commence intensive phototherapy.

Harnessing artificial intelligence to reduce phototoxicity in live imaging.

Fluorescence microscopy is essential for studying living cells, tissues and organisms. However, the fluorescent light that switches on fluorescent molecules also harms the samples, jeopardizing the validity of results - particularly in techniques such as super-resolution microscopy, which demands extended illumination. Artificial intelligence (AI)-enabled software capable of denoising, image restoration, temporal interpolation or cross-modal style transfer has great potential to rescue live imaging data and limit photodamage.