Reflective writing develops meta-cognition among students. Therefore, it is of interest to compare effectiveness of post lecture reflective writing to didactic lecture between individual and group reflective writing. Hence, we included 124 first-year students from AIIMS Bhopal, India and divided them in two groups of 62 students. Both groups took a pre-test using a reflection questionnaire. Students were taught reflective writing. Both groups attended physiology lectures on two different topics. First lecture on body fluids where Group A wrote reflections individually and Group B did so in sub-groups (B1 to B6). After another lecture on Pathophysiology of oedema, Group A wrote reflections in groups and Group B wrote individually (A1 to A6). Both groups took a test in the form of MCQ about reflective writing on lectures. After intervention both groups took a post-test using a reflection questionnaire. Mean and standard deviation of Pre-test is 3.86 ± 0.86 and Post-test is 7.58 ± 1.01, respectively. The Mean and standard deviation of reflection who wrote individually is 38.05 ± 4.41 and in group is 27.45 ± 3.93, respectively with p-value < 0.05. Evaluation of students who wrote reflection in groups after second lecture the mean and standard deviation of reflection who wrote individually is 38.22 ± 4.64 and in group is 27.03 ± 2.87 respectively with p-value < 0.05. The performance of students who wrote reflection in groups is not satisfactory as compared to students who wrote their reflection individually.

Body fluid analysis has become a critical component of diagnostic and clinical decision-making for a wide spectrum of human pathologies. An automated microscope, a high-quality digital camera, and a software designed to identify and automatically preclassify cells and other features in stained smears comprise the most recent generation of digital morphologic analyzers. The time necessary for expert operator reclassification is another aspect that must be considered at this stage of development, because identifying and sorting distinct elements in body fluids still necessitates the involvement of an expert morphologist.

An overview of the role of glycosylation in prostate cancer (PCa) development and progression is presented, focusing on recent advancements in defining the N-glycome through glycomic profiling and glycoproteomic methodologies. Glycosylation is a common post-translational modification typified by oligosaccharides attached N-linked to asparagine or O-linked to serine or threonine on carrier proteins. These attached sugars have crucial roles in protein folding and cellular recognition processes, such that altered glycosylation is a hallmark of cancer pathogenesis and progression. In the past decade, advancements in N-glycan profiling workflows using Matrix Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) technology have been applied to define the spatial distribution of glycans in PCa tissues. Multiple studies applying N-glycan MALDI-MSI to pathology-defined PCa tissues have identified significant alterations in N-glycan profiles associated with PCa progression. N-glycan compositions progressively increase in number, and structural complexity due to increased fucosylation and sialylation. Additionally, significant progress has been made in defining the glycan and glycopeptide compositions of prostatic-derived glycoproteins like prostate-specific antigen in tissues and biofluids. The glycosyltransferases involved in these changes are potential drug targets for PCa, and new approaches in this area are summarized. These advancements will be discussed in the context of the further development of clinical diagnostics and therapeutics targeting glycans and glycoproteins associated with PCa progression. Integration of large scale spatial glycomic data for PCa with other spatial-omic methodologies is now feasible at the tissue and single-cell levels.

Total antioxidants play a crucial role in human health, and detection of the total antioxidant capacity (TAC) has broad application prospects in fields such as food safety, environmental assessment, and disease diagnosis. However, a long detection time, cumbersome steps, high cost, reliance on professional equipment, and nonportability still remain significant challenges. In this work, an efficient strategy of point-of-care testing (POCT) of the TAC in body fluids by nanozyme-catalyzed colorimetric paper-based microfluidic sensors is proposed. The paper-based microfluidic sensors coupled with a smartphone can reduce testing costs and provide portability. The nanozyme prepared by the solvothermal method presents Michaelis constants of 0.11 and 0.129 mM for H2O2 and TMB, respectively. A method for immobilizing nanozymes and chromogenic agents on a paper-based microfluidic chip is established. Based on smartphone photography and image grayscale extraction, the TAC can be qualitatively detected with a detection limit and linear range of 33.4 and 50-700 μM, respectively. Furthermore, the proposed sensor can realize the one-step quantitative analysis of the TAC in body fluids (blood, saliva, and sweat) within 15 min. The proposed nanozyme-catalyzed colorimetric paper-based microfluidic sensors presented in this study exhibit promising application prospects in the fields of biochemical analysis and POCT.

Magnesium-based biodegradable metal bone implants exhibit superior mechanical properties compared to biodegradable polymers for orthopedic and cardiovascular stents. In this study, MgZZC-x (x = 1, 1.2) alloys were screened by in vitro biocompatibility tests in three simulated body fluids under nontoxic conditions. The MgZZC-1 alloys with better biocompatibility were selected to predict the days required for complete degradation. The evolution of degradation products was analyzed, and the mechanism of formation of the product film was inferred. A degradation kinetic model was established to investigate the effect of MEM components on the degradation of the alloys. The results demonstrate that the proteins in MEM can greatly retard the degradation progress by attaching to the surface of MgZZC-1 alloys, which are predicted to degrade completely within 341 days. The carbonate and phosphate buffers were adjusted to pH in MEM solution, delaying the degradation of magnesium alloys. This process in MEM more accurately reflects the actual degradation in the body and is superior to that in Hanks and SBF solutions. This study will promote the application of biodegradable materials in clinical medicine.

Zr-50Ti alloys are promising biomaterials due to their excellent mechanical properties and low magnetic susceptibility. However, Zr-50Ti alloys do not inherently bond well with bone. This study aims to enhance the bioactivity and bonding strength of Zr-50Ti alloys for orthopedic implant materials. Initially, the surface of Zr-50Ti alloys was treated with a sulfuric acid solution to create a microporous structure, increasing surface roughness and area. Subsequently, low crystalline calcium phosphate (L-CaP) precipitation was controlled by adding Mg2+ and/or CO32- ions in modified simulated body fluid (m-SBF). The treated Zr-50Ti alloys were then subjected to cold isostatic pressing to force m-SBF into the micropores, followed by incubation to allow L-CaP formation. The apatite-forming process was tested in simulated body fluid (SBF). The results demonstrated that the incorporation of Mg2+ and/or CO32- ions enabled the L-CaP to cover the entire surface of Zr-50Ti alloys within only one day. After short-term soaking in SBF, the L-CaP layer, modulated by Mg2+ and/or CO32- ions, formed a uniform hydroxyapatite (HA) coating on the surface of the Zr-50Ti alloys, showing potential for optimized bone integration. After soaking in SBF for 14 days, the bonding strength between the apatite layer and alloy has the potential to meet the orthopedic application requirement of 22 MPa. This study demonstrates an effective method to enhance the bioactivity and bonding strength of Zr-50Ti alloys for orthopedic applications.

The secreted proteins of human body fluid have the potential to be used as biomarkers for diseases. These biomarkers can be used for early diagnosis and risk prediction of diseases, so the study of secreted proteins of human body fluid has great application value. In recent years, the deep-learning-based transformer language model has transferred from the field of natural language processing (NLP) to the field of proteomics, leading to the development of protein language models (PLMs) for protein sequence representation. Here, we propose a deep learning framework called ESM Predict Secreted Proteins (ESMSec) to predict three types of proteins secreted in human body fluid. The ESMSec is based on the ESM2 model and attention architecture. Specifically, the protein sequence data are firstly put into the ESM2 model to extract the feature information from the last hidden layer, and all the input proteins are encoded into a fixed 1000 × 480 matrix. Secondly, multi-head attention with a fully connected neural network is employed as the classifier to perform binary classification according to whether they are secreted into each body fluid. Our experiment utilized three human body fluids that are important and ubiquitous markers. Experimental results show that ESMSec achieved average accuracy of 0.8486, 0.8358, and 0.8325 on the testing datasets for plasma, cerebrospinal fluid (CSF), and seminal fluid, which on average outperform the state-of-the-art (SOTA) methods. The outstanding performance results of ESMSec demonstrate that the ESM can improve the prediction performance of the model and has great potential to screen the secretion information of human body fluid proteins.

A rapid, straightforward, and sensitive approach to quantifying enantiomeric barbiturates in serum was developed by integrating ultrasound-assisted dispersive liquid-liquid microextraction (UA-DLLME) with large-volume sample stacking (LVSS) in capillary electrophoresis (CE). UA-DLLME was employed for sample preparation, and on-column preconcentration by using LVSS with polarity switching was implemented to enhance sensitivity. We thoroughly investigated and optimized various parameters influencing extraction and stacking to achieve optimal detection performance with the highest enrichment efficiencies. Under optimal extraction conditions (injection of a mixed solution containing 40 μL of CHCl3 and 200 μL of tetrahydrofuran into 1 mL of a sample solution at pH 10.0), LVSS was performed using 600 mM Tris-boric acid (pH 9.5) containing 35 mM hydroxypropyl-β-cyclodextrin and sodium taurodeoxycholate hydrate. A voltage of 20 kV was applied and a preinjection water plug was loaded at a height of 25 cm for 10 s. Subsequently, the sample solution was injected at a height of 25 cm for 480 s, after which a voltage of -20 kV was applied and the sample stacking was initiated. The stacking process was completed when 95 % of the separation current was attained. Under optimized conditions, the contraction folds of the four barbiturate analytes (R, S-Secobarbital, R, S-pentobarbital) were improved by approximately 6400-fold, achieving detection limits of 0.1 ng/mL. The limits of quantification for all analyte enantiomers were 0.5-50 ng/mL, demonstrating good linearity (r > 0.997). Migration times exhibited a relative standard deviation of less than 1.7 %, whereas peak areas for the four analytes exhibited a deviation of 8.7 %. Finally, the established method was effectively applied to the analysis of human serum samples.

Risperidone (Ris) is a second-generation antipsychotic that belongs to the chemical class of benzisoxazole derivatives. 9-Hydroxy (9OH-) Ris is well known among the six reported metabolites of Ris and had been examined using not only blood but also other matrices, but the other five metabolites reported such as benzisoxazole ring-cleaved Ris (c-Ris) and c-9OH-Ris had been detected only in blood, urine and feces. In the present work, large peaks of c-Ris and c-9OH-Ris were detected in the liver, kidney, cerebrum, blood, pericardial fluid, bile and urine obtained from two cadavers. There is a potential that c-Ris and c-9OH-Ris will be good markers to prove Ris consumption in forensic toxicology cases. For example, the peak ratios of c-Ris against the parent Ris in the kidney and blood were as high as 3.9 and 3.6 in cadaver 1; and 7.0 and 7.9 in cadaver 2, respectively. In addition to the previously reported six metabolites, five new metabolites such as dehydrogenated-Ris, 7-keto-Ris and three benzisoxazole ring-cleaved metabolites were disclosed in the present work, and the pathways for the totally eleven metabolites detected in human solid tissues and body fluids have also been proposed, because such pathways were neither reported nor discussed previously.

The study assessed the impact of procedural errors on the remote dielectric sensing system (ReDS), a non-invasive lung fluid assessment technology, in an Asian cohort. Healthy volunteers underwent ReDS measurements following manufacturer\'s instructions, with two consecutive measurements one minute apart. A subset of 20 participants had modified procedure settings. Reliability was measured using intraclass correlation coefficient (ICC). The study included 86 healthy volunteers, and all ReDS measurements fell within the recommended normal range. The intra-rater reliability of ReDS measurements was excellent, with an ICC of 0.968. Among the subset of 20 subjects, deviations in height and weight did not significantly affect ReDS values. However, deviations in chest size by ± 3 cm had a noticeable impact on ReDS measures, and incorrect station selection led to fluctuations in ReDS readings. In conclusion, the ReDS system demonstrated excellent intra-rater reliability and applicability in an Asian cohort. Procedural errors, such as chest size measurement and station selection, significantly influenced ReDS measurements. Adherence to standardized operating procedures is crucial to ensure accurate and consistent results. These findings highlight the importance of adherence to manufacturer instructions when utilizing ReDS for lung fluid assessment, thereby enhancing its reliability and clinical applicability.