Dietetics Students' Perceived Facilitators and Barriers to Clinical Training in Malaysia: A Qualitative Theory-Guided Analysis

This study explored barriers and facilitators experienced by Malaysian dietetics graduates during clinical training in local healthcare settings. A qualitative study with phenomenological design was conducted on fifteen purposely selected fresh dietetics graduates, with a mean age of 24.7±0.8 years from seven local universities. Virtual interviews were conducted via the Cisco Webex and were verbatim transcribed and thematically analyzed using NVivo 12 Plus software. Data collection continued until data saturation was reached. Nine Theoretical Domain Frameworks (TDF-derived domains), comprising of 1) knowledge, 2) skills; 3) belief about capabilities; 4) intention; 5) goals; 6) memory, attention, and decision process; 7) environmental context and resources; 8) social influences; and 9) emotions domains, was utilized to develop open-ended questions in the semi-structured questionnaire. Within these domains, frequently associated sub-themes of perceived facilitators were identified: early preparation and comprehension. Pre-clinical classes that involve solving diverse and challenging cases equip students with practical understanding of clinical training. Curriculum-based university clinics offer valuable insights into hospital dietetics practice. Resources availability is crucial for effective Nutrition Care Process (NCP) implementation and aids in evidence-based nutrition counseling. Conversely, the factor that hinders clinical training reported by dietetics graduates is a lack of knowledge and readiness, particularly concerning their perceived knowledge before clinical training. Dissatisfaction also arises from challenges in building rapport, gathering patient information during counseling, and difficulties in assessing dietary recall with patients from diverse cultural backgrounds, affecting their readiness for dietetics practice and therefore, highlighting the need to enhance multicultural knowledge and cultural competency training among dietetics students. The findings from this study may assist in developing strategies to promote impactful experiences and enhance dietetic students' preparedness for clinical practice

Knowledge of nutrition during pregnancy and associated factors among antenatal mothers

Background: Nutritional requirement increases during pregnancy can influence the growth, development, and health of the mother and her newborn child. Understanding the antenatal mothers’ nutrition knowledge is essential to developing effective strategies to curb malnutrition and encouraging healthier dietary behaviors. The aim of this study was to assess the level and associated factors of nutritional knowledge during pregnancy among antenatal mothers in a tertiary teaching hospital in northeast Malaysia. Materials and Methods: A cross-sectional study was done on 88 randomly selected antenatal mothers at the Obstetrics and Gynecology Clinic during their antenatal care visits. Data was collected using a pretested self-administered questionnaire between December 2015 and February 2016. The Kruskal-Wallis test was used to determine the association of selected socio-demographic variables and obstetric data with nutritional knowledge score among antenatal mothers. Results: The mean age of the participants was 32.06 ± 5.56 years. More than half (63.6%) of the antenatal mothers had good nutritional knowledge level. Higher occupational status (p=0.030) and monthly household income (p=0.016) of participants were significantly associated with higher nutritional knowledge score. Conclusion: These findings highlight the current knowledge gap that exists in antenatal mothers. It can be concluded that nutritional education ought to be intensified to address this issue

Categorization of species as native or nonnative using DNA sequence signatures without a complete reference library.

New genetic diagnostic approaches have greatly aided efforts to document global biodiversity and improve biosecurity. This is especially true for organismal groups in which species diversity has been underestimated historically due to difficulties associated with sampling, the lack of clear morphological characteristics, and/or limited availability of taxonomic expertise. Among these methods, DNA sequence barcoding (also known as "DNA barcoding") and by extension, meta-barcoding for biological communities, has emerged as one of the most frequently utilized methods for DNA-based species identifications. Unfortunately, the use of DNA barcoding is limited by the availability of complete reference libraries (i.e., a collection of DNA sequences from morphologically identified species), and by the fact that the vast majority of species do not have sequences present in reference databases. Such conditions are critical especially in tropical locations that are simultaneously biodiversity rich and suffer from a lack of exploration and DNA characterization by trained taxonomic specialists. To facilitate efforts to document biodiversity in regions lacking complete reference libraries, we developed a novel statistical approach that categorizes unidentified species as being either likely native or likely nonnative based solely on measures of nucleotide diversity. We demonstrate the utility of this approach by categorizing a large sample of specimens of terrestrial insects and spiders (collected as part of the Moorea BioCode project) using a generalized linear mixed model (GLMM). Using a training data set of known endemic (n = 45) and known introduced species (n = 102), we then estimated the likely native/nonnative status for 4,663 specimens representing an estimated 1,288 species (412 identified species), including both those specimens that were either unidentified or whose endemic/introduced status was uncertain. Using this approach, we were able to increase the number of categorized specimens by a factor of 4.4 (from 794 to 3,497), and the number of categorized species by a factor of 4.8 from (147 to 707) at a rate much greater than chance (77.6% accuracy). The study identifies phylogenetic signatures of both native and nonnative species and suggests several practical applications for this approach including monitoring biodiversity and facilitating biosecurity

Adhesion of aerosol deposition traces targeted for flexible electronics applications

•Emergence of wearable electronics - from medical to consumer products. •Requirement: To realise conductive traces on flexible substrates. •Common printing techniques: screen printing and inkjet printing. •Aerosol deposition (AD)1 is an emerging potential technology as it offers room temperature deposition. •From literature others have used AD to deposit metal base layers onto flexible substrates. To the authors’ best knowledge, there has been no work reported on the deposition of copper onto flexible substrates. •Copper is an attractive option as it is relatively cheap compared to other metals (eg. silver)

ProBDNF Collapses Neurite Outgrowth of Primary Neurons by Activating RhoA

BACKGROUND: Neurons extend their dendrites and axons to build functional neural circuits, which are regulated by both positive and negative signals during development. Brain-derived neurotrophic factor (BDNF) is a positive regulator for neurite outgrowth and neuronal survival but the functions of its precursor (proBDNF) are less characterized. METHODOLOGY/PRINCIPAL FINDINGS: Here we show that proBDNF collapses neurite outgrowth in murine dorsal root ganglion (DRG) neurons and cortical neurons by activating RhoA via the p75 neurotrophin receptor (p75NTR). We demonstrated that the receptor proteins for proBDNF, p75NTR and sortilin, were highly expressed in cultured DRG or cortical neurons. ProBDNF caused a dramatic neurite collapse in a dose-dependent manner and this effect was about 500 fold more potent than myelin-associated glycoprotein. Neutralization of endogenous proBDNF by using antibodies enhanced neurite outgrowth in vitro and in vivo, but this effect was lost in p75NTR(-/-) mice. The neurite outgrowth of cortical neurons from p75NTR deficient (p75NTR(-/-)) mice was insensitive to proBDNF. There was a time-dependent reduction of length and number of filopodia in response to proBDNF which was accompanied with a polarized RhoA activation in growth cones. Moreover, proBDNF treatment of cortical neurons resulted in a time-dependent activation of RhoA but not Cdc42 and the effect was absent in p75NTR(-/-) neurons. Rho kinase (ROCK) and the collapsin response mediator protein-2 (CRMP-2) were also involved in the proBDNF action. CONCLUSIONS: proBDNF has an opposing role in neurite outgrowth to that of mature BDNF. Our observations suggest that proBDNF collapses neurites outgrowth and filopodial growth cones by activating RhoA through the p75NTR signaling pathway

The Cenozoic history of palms:Global diversification, biogeography and the decline of megathermal forests

10.1111/geb.13436GLOBAL ECOLOGY AND BIOGEOGRAPHY313425-43

Adaptive weights learning in CNN feature fusion for crime scene investigation image classification

The combination of features from the convolutional layer and the fully connected layer of a convolutional neural network (CNN) provides an effective way to improve the performance of crime scene investigation (CSI) image classification. However, in existing work, as the weights in feature fusion do not change after the training phase, it may produce inaccurate image features which affect classification results. To solve this problem, this paper proposes an adaptive feature fusion method based on an auto-encoder to improve classification accuracy. The method includes the following steps: Firstly, the CNN model is trained by transfer learning. Next, the features of the convolution layer and the fully connected layer are extracted respectively. These extracted features are then passed into the auto-encoder for further learning with Softmax normalisation to obtain the adaptive weights for performing final classification. Experiments demonstrated that the proposed method achieves higher CSI image classification performance compared with fix weights feature fusion. © 2021 Informa UK Limited, trading as Taylor & Francis Group

Subnanogram proteomics: impact of LC column selection, MS instrumentation and data analysis strategy on proteome coverage for trace samples

One of the greatest challenges for mass spectrometry (MS)-based proteomics is the limited ability to analyze small samples. Here we investigate the relative contributions of liquid chromatography (LC), MS instrumentation and data analysis methods with the aim of improving proteome coverage for sample sizes ranging from 0.5 ng to 50 ng. We show that the LC separations utilizing 30-μm-i.d. columns increase signal intensity by >3-fold relative to those using 75-μm-i.d. columns, leading to 32% increase in peptide identifications. The Orbitrap Fusion Lumos MS significantly boosted both sensitivity and sequencing speed relative to earlier generation Orbitraps (e.g., LTQ-Orbitrap), leading to a ∼3-fold increase in peptide identifications and 1.7-fold increase in identified protein groups for 2 ng tryptic digests of the bacterium S. oneidensis. The Match Between Runs algorithm of open-source MaxQuant software further increased proteome coverage by ∼ 95% for 0.5 ng samples and by ∼42% for 2 ng samples. Using the best combination of the above variables, we were able to identify >3,000 proteins from 10 ng tryptic digests from both HeLa and THP-1 mammalian cell lines. We also identified >950 proteins from subnanogram archaeal/bacterial cocultures. The present ultrasensitive LC-MS platform achieves a level of proteome coverage not previously realized for ultra-small sample loadings, and is expected to facilitate the analysis of subnanogram samples, including single mammalian cells

Giant thermal hysteresis in Verwey transition of single domain Fe3O4 nanoparticles

Most interesting phenomena of condensed matter physics originate from interactions among different degrees of freedom, making it a very intriguing yet challenging question how certain ground states emerge from only a limited number of atoms in assembly. This is especially the case for strongly correlated electron systems with overwhelming complexity. The Verwey transition of Fe3O4 is a classic example of this category, of which the origin is still elusive 80 years after the first report. Here we report, for the first time, that the Verwey transition of Fe3O4 nanoparticles exhibits size-dependent thermal hysteresis in magnetization, 57Fe NMR, and XRD measurements. The hysteresis width passes a maximum of 11 K when the size is 120 nm while dropping to only 1 K for the bulk sample. This behavior is very similar to that of magnetic coercivity and the critical sizes of the hysteresis and the magnetic single domain are identical. We interpret it as a manifestation of charge ordering and spin ordering correlation in a single domain. This work paves a new way of undertaking researches in the vibrant field of strongly correlated electron physics combined with nanoscience.Comment: 13 pages, 4 figure

Multi-Modality Imaging of Atheromatous Plaques in Peripheral Arterial Disease: Integrating Molecular and Imaging Markers

Peripheral artery disease (PAD) is a common and debilitating condition characterized by the narrowing of the limb arteries, primarily due to atherosclerosis. Non-invasive multi-modality imaging approaches using computed tomography (CT), magnetic resonance imaging (MRI), and nuclear imaging have emerged as valuable tools for assessing PAD atheromatous plaques and vessel walls. This review provides an overview of these different imaging techniques, their advantages, limitations, and recent advancements. In addition, this review highlights the importance of molecular markers, including those related to inflammation, endothelial dysfunction, and oxidative stress, in PAD pathophysiology. The potential of integrating molecular and imaging markers for an improved understanding of PAD is also discussed. Despite the promise of this integrative approach, there remain several challenges, including technical limitations in imaging modalities and the need for novel molecular marker discovery and validation. Addressing these challenges and embracing future directions in the field will be essential for maximizing the potential of molecular and imaging markers for improving PAD patient outcomes