Medicine Research Research Articles

Clinical Performance Comparison of a Long Versus a Short Axial Field-of-View PET/CT Using EARL-Compliant Reconstructions

PurposeTo ensure comparable PET/CT image quality between or within centres, clinical inter-system performance comparisons following European Association of Nuclear Medicine Research Ltd. (EARL) guidelines is required. In this work the performance of the long axial field-of-view Biograph Vision Quadra is compared to its predecessor, the short axial field-of-view Biograph Vision.ProceduresTo this aim, patients with suspected tumour lesions received a single weight-based (3 MBq/kg) 2-deoxy-2-[18F]fluoro-D-glucose injection and underwent routine clinical (∼\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim$$\\end{document} 15 min) scans on the Vision and 3-min scans on the Quadra in listmode in balanced order. Image quality (IQ), image noise (IN), and tumour demarcation (TD) were assessed visually by four nuclear medicine physicians using a 5-point Likert scale and semiquantitative analysis was performed using standardised uptake values (SUVs). Inter-reader agreement was tested using Wilcoxon’s signed rank test and the SUVs were statistically compared using a paired t-test.ResultsTwenty patients (mean age, 60 years ± 8.8 [standard deviation], 16 male) were enrolled. Inter-reader agreement ranged from good to very good for IQ and IN (0.62 ≤ W ≤ 0.81), and fair for TD (0.29 ≤ W ≤ 0.39). Furthermore, a significant difference was found for TD (p = 0.015) between the systems, showing improved TD for the Quadra.ConclusionThis study demonstrates that the Quadra can be used in routine clinical practice with multiple PET/CT systems or in multicentre studies. This system provides comparable diagnostic image quality and semiquantitative accuracy, improved TD, and has the advantage of shorter scan durations.

Advances in Type 1 Diabetes Mellitus Management in Children.

Recent advancements in the management of type 1 diabetes mellitus (T1DM) have significantly improved outcomes and quality of life for patients, particularly children. Technological innovations, such as continuous glucose monitoring (CGM) systems and insulin pump therapy, including hybrid closed-loop systems, have enhanced glycemic control by providing real-time data and automated insulin delivery. Ultrarapid-acting insulins and adjunctive pharmacotherapies, like sodium-glucose transport protein 2 (SGLT2) inhibitors and glucagon-like peptide 1 (GLP-1) receptor agonists, offer improved postprandial glucose management and reduced insulin requirements. Immunotherapy and beta-cell replacement therapies, including stem cell research and encapsulation devices, aim to preserve or restore endogenous insulin production. Digital health platforms and telemedicine have expanded access to education and support, fostering better self-management. Future directions in precision medicine, artificial intelligence, and microbiome research hold promise for personalized and potentially curative treatments. Collectively, these advances are transforming T1DM management, reducing disease burden, and enhancing the prospects for children with T1DM.

Commercial Diagnostics and Emerging Precision Medicine Technologies in Psoriasis and Atopic Dermatitis.

While psoriasis and atopic dermatitis (AD) are two common dermatological conditions, their diagnosis and therapeutic decision-making pathways are often complex. As a result, there has been increased focus on the development of precision medicine approaches for psoriasis and AD. Two companies at the forefront of dermatology precision medicine research are Mindera Health and Castle Biosciences. Here, we review the technologies developed by these two companies using a dermal diagnostic patch and superficial skin scrapings, respectively, their research published to date, and their future research goals. Research from both companies shows promise in predicting the response of inflammatory skin disease to biologics using minimally invasive techniques. However, challenges to adoption include insurance coverage and patient trust in the technologies. While there are several differences between Mindera Health and Castle Biosciences, they have a shared goal of utilizing minimally invasive technologies to sample skin and predict response to biologic treatments using a panel of optimized biomarkers.

Scaffolds imparting anthelmintic activity: recent advancements and SAR studies.

Helminthiasis, affecting billions globally, poses a significant health concern, especially in impoverished regions with inadequate sanitation. The intricate anatomical complexity of helminths requires specialized treatment approaches. There is currently no effective vaccine against helminth infections. Anthelmintics, crucial for combating these infections, target neuromuscular functions in parasites without harming the host. However, the emergence of resistance to existing anthelmintics, notably benzimidazoles, presents a growing global challenge. This review delves into the structure-activity relationship of previously synthesized core anthelmintic scaffolds-Benzimidazole, coumarin, pyrazoline, triazole, and others-to elucidate their promising anthelmintic activities. Understanding the structure-activity relationship of these novel benzimidazole derivatives, Coumarin derivatives, and others is crucial in designing potent anthelmintics, overcoming resistance, and optimizing efficacy to combat the escalating global burden of helminth infections. In the present review, we cover recently studied compounds (from the year 2019 to till date) which have promising anthelmintic activity. This review will be useful for the pharmacology and medicinal chemistry researchers working in the area anthelmintics with various scaffolds like aminobenzothiazole, benzimidazole, benzothiazole, coumarin, chromene, spiroketal, pyrazoline, triazole, etc. to design novel potent anthelmintic compound.

Immunomodulatory, Antioxidant, and Potential Anticancer Activity of the Polysaccharides of the Fungus Fomitiporia chilensis.

Fomitiporia species have aroused the interest of numerous investigations that reveal their biological activity and medicinal potential. The present investigation shows the antioxidant, anticancer, and immunomodulatory activity of acidic polysaccharides obtained from the fungus Fomitiporia chilensis. The acidic polysaccharides were obtained for acidic precipitation with 2% O-N-cetylpyridinium bromide. Chemical analysis was performed using FT-IR and GC-MS methods. The antioxidant capacity of acidic polysaccharides from F. chilensis was evaluated by scavenging free radicals with an ABTS assay. Macrophage proliferation and cytokine production assays were used to determine the immunomodulatory capacity of the polysaccharides. Anti-tumor and cytotoxicity activity was evaluated with an MTT assay in the U-937, HTC-116, and HGF-1 cell lines. The effect of polysaccharides on the cell cycle of the HCT-116 cell line was determined for flow cytometry. Fourier Transform-infrared characterization revealed characteristic absorption peaks for polysaccharides, whereas the GC-MS analysis detected three peaks corresponding to D-galactose, galacturonic acid, and D-glucose. The secreted TNF-α concentration was increased when the cell was treated with 2 mg mL-1 polysaccharides, whereas the IL-6 concentration was increased with all of the evaluated polysaccharide concentrations. A cell cycle analysis of HTC-116 treated with polysaccharides evidenced that the acidic polysaccharides from F. chilensis induce an increase in the G0/G1 cell cycle phase, increasing the apoptotic cell percentage. Results from a proteomic analysis suggest that some of the molecular mechanisms involved in their antioxidant and cellular detoxifying effects and justify their traditional use in heart diseases. Proteomic data are available through ProteomeXchange under identifier PXD048361. The study on acidic polysaccharides from F. chilensis has unveiled their diverse biological activities, including antioxidant, anticancer, and immunomodulatory effects. These findings underscore the promising therapeutic applications of acidic polysaccharides from F. chilensis, warranting further pharmaceutical and medicinal research exploration.

Exploring the potential of omics technologies in medicinal plant research: A review in Colombia

This review presents advances in the implementation of high-throughput sequencing and its application to the knowledge of medicinal plants. We conducted a bibliographic search of papers published in PubMed, Science Direct, Google Scholar, Scopus, and Web of Science databases and analyzed the obtained data using VOSviewer (version 1.6.19). Given that medicinal plants are a source of specialized metabolites with immense therapeutic values and important pharmacological properties, plant researchers around the world have turned their attention toward them and have begun to examine them widely. Recent advances in sequencing technologies have reduced cost and time demands and accelerated medicinal plant research. Such research leverages full genome sequencing, as well as RNA (ribonucleic acid) sequencing and the analysis of the transcriptome, to identify molecular markers of species and functional genes that control key biological traits, as well as to understand the biosynthetic pathways of bioactive metabolites and regulatory mechanisms of environmental responses. As such, the omics (e.g., transcriptomics, metabolomics, proteomics, and genomics, among others) have been widely applied within the study of medicinal plants, although their usage in Colombia is still few and, in some areas, scarce.

Size and shape control of microgel-encapsulating tumor spheroid via a user-friendly solenoid valve-based sorter and its application on precise drug testing

The precision of previous cancer research based on tumor spheroids, especially the microgel-encapsulating tumor spheroids, was limited by the high heterogeneity in the tumor spheroid size and shape. Here, we reported a user-friendly solenoid valve-based sorter to reduce this heterogeneity. The artificial intelligence algorithm was employed to detect and segmentate the tumor spheroids in real-time for the size and shape calculation. A simple off-chip solenoid valve-based sorting actuation module was proposed to sort out target tumor spheroids with the desired size and shape. Utilizing the developed sorter, we successfully uncovered the drug response variations on cisplatin of lung tumor spheroids in the same population but with different sizes and shapes. Moreover, with this sorter, the precision of drug testing on the spheroid population level was improved to a level comparable to the precise but complex single spheroid analysis. The developed sorter also exhibits significant potential for organoid morphology and sorting for precision medicine research.

Exploring the anti-hepatocellular carcinoma effects of Xianglian Pill: Integrating network pharmacology and RNA sequencing via in silico and in vitro studies

BackgroundLiver cancer represents a most common and fatal cancer worldwide. Xianglian Pill (XLP) is an herbal formula holding great promise in clearing heat for treating diseases in an integrative and holistic way. However, due to the complex constituents and multiple targets, the exact molecular mechanisms of action of XLP are still unclear. PurposeThis study is focused on hepatocellular carcinoma (HCC), the most common type of liver cancer. The aim of this study is to develop a fast and efficient model to investigate the anti-HCC effects of XLP, and its underlying mechanisms. Materials and methodsHepG2, Hep3B, Mahlavu, HuH-7, or Li-7 cells were employed in the studies. The ingredients were analyzed using liquid chromatography tandem mass spectrometry (LC-MS). RNA sequencing combined with network pharmacology was used to elucidate the therapeutic mechanism of XLP in HCC via in silico and in vitro studies. An approach was constructed to improve the accuracy of prediction in network pharmacology by combining big data and omics. ResultsFirst, we identified 13 potential ingredients in the serum of XLP-administered rats using LC-MS. Then the network pharmacology was performed to predict that XLP demonstrates anti-HCC effects via targeting 94 genes involving in 13 components. Modifying the database thresholds might impact the accuracy of network pharmacology analysis based on RNA sequencing data. For instance, when the matching rate peak is 0.43, the correctness rate peak is 0.85. Moreover, 9 components of XLP and 6 relevant genes have been verified with CCK-8 and RT-qPCR assay, respectively. ConclusionBased on the crossing studies of RNA sequencing and network pharmacology, XLP was found to improve HCC through multiple targets and pathways. Additionally, the study provides a way to optimize network pharmacology analysis in herbal medicine research.

Evaluation of Chinese herbal medicine's neuroprotective effects: Regulation for neurological disorders

Chinese herbal medicine is a type of medicine composed of plants unique to China, which has been found to have significant neuroprotective effects in recent years. The research on its neuroprotective mechanism has become a hot topic. At present, neuroprotective mechanisms have been found to be closely related to balancing ion channels, inhibiting apoptosis of nerve cells and promoting nerve growth. In this work, we summarize the recent progress of research on neuroprotective mechanisms of Chinese herbal medicine and the existing clinical trials.The significance of this study is not only to summarize its therapeutic mechanism, but also to improve the status of Chinese herbal medicine at the international level. It is hoped that more international scholars will join in the research of Chinese herbal medicine.

Hydra for 21st Century—A Fine Model in Freshwater Research

Hydra is known for its natural occurrence, anatomical simplicity, intricate physiology, regenerative capacity, and ease of maintenance and manipulation in laboratory environments. It has proven to be a valuable model organism in various disciplines. Its applications range from developmental biology, stem cell research, animal physiology to environmental toxicology including ecotoxicology. The sensitivity of Hydra to a variety of environmental stressors and chemical agents such as metals, nanomaterials, and toxic organic compounds provides valuable insights into physiological mechanisms affected by environmental stressors and pollution, and Hydra can be of great use in environmental monitoring. Furthermore, since green Hydra lives in a symbiotic relationship with unicellular photoautotrophic algae, it is a suitable model organism for symbiosis research. Recently, it has become a popular model in holobiont research. The adaptability and importance of Hydra also extends to aquatic science and aquatic ecology, particularly in the context of monitoring and water pollution. Since the 1980s, Hydra has been increasingly used in various fields of research and has established itself as an important versatile model organism in numerous scientific studies. Hydra also represents an outstanding model in the fields of education and STEM. Hydra continues to be an important model in the 21st century, contributing significantly to our understanding of the biology of water and advancing freshwater research, and possibly finding its way to regenerative medicine and tumor pathobiology research.

Novel loci linked to serum lipid traits are identified in a genome-wide association study of a highly admixed Brazilian population - the 2015 ISA Nutrition

BackgroundCardiovascular diseases (CVDs) comprise major causes of death worldwide, leading to extensive burden on populations and societies. Alterations in normal lipid profiles, i.e., dyslipidemia, comprise important risk factors for CVDs. However, there is lack of comprehensive evidence on the genetic contribution to dyslipidemia in highly admixed populations. The identification of single nucleotide polymorphisms (SNPs) linked to blood lipid traits in the Brazilian population was based on genome-wide associations using data from the São Paulo Health Survey with Focus on Nutrition (ISA-Nutrition).MethodsA total of 667 unrelated individuals had genetic information on 330,656 SNPs available, and were genotyped with Axiom™ 2.0 Precision Medicine Research Array. Genetic associations were tested at the 10− 5 significance level for the following phenotypes: low-density lipoprotein cholesterol (LDL-c), very low-density lipoprotein cholesterol (VLDL-c), high-density lipoprotein cholesterol (HDL-c), HDL-c/LDL-c ratio, triglycerides (TGL), total cholesterol, and non-HDL-c.ResultsThere were 19 significantly different SNPs associated with lipid traits, the majority of which corresponding to intron variants, especially in the genes FAM81A, ZFHX3, PTPRD, and POMC. Three variants (rs1562012, rs16972039, and rs73401081) and two variants (rs8025871 and rs2161683) were associated with two and three phenotypes, respectively. Among the subtypes, non-HDL-c had the highest proportion of associated variants.ConclusionsThe results of the present genome-wide association study offer new insights into the genetic structure underlying lipid traits in underrepresented populations with high ancestry admixture. The associations were robust across multiple lipid phenotypes, and some of the phenotypes were associated with two or three variants. In addition, some variants were present in genes that encode ncRNAs, raising important questions regarding their role in lipid metabolism.

Right parasternal echocardiographic reference values in the healthy male Iranian Shall sheep.

Among the large animals, the heart of sheep is functionally and structurally very similar to the human heart. In research, sheep are used as an animal model to study the process of cardiac disease pathogenesis and treatment. Therefore, determining the normal values of the heart structures of sheep with echocardiography is of particular emphasis. The purpose of the present research is to define the normal echocardiography values of heart in Iranian Shall breed sheep. In 20 healthy Iranian Shall male sheep weighing 30-35kg and aged 4-6 months, standing echocardiography was done from the right parasternal approach concentrated on the 3rd to 5th intercostal spaces by 2.5-5MHz phased array transducer in the longitudinal and transverse views by B-mode, M-mode and Doppler systems. In M-mode echocardiographic, the parameters of interventricular septal, left ventricular internal diameter, left ventricular free wall, right ventricular free wall and right ventricular internal diameter in diastole and systole as well as end point septal separation, ejection fraction (EF) slope, aortic root diameter, left atrial appendage, left atrial diameter/aortic valve diameter, left ventricular ejection time, fractional shortening, end-diastolic volume, end-systolic volume, EF, stroke volume and cardiac output and in pulsed-wave spectral Doppler echocardiographic, the parameters of mitral valve maximum velocity (Vmax), mitral valve mean velocity (Vmean), mitral valve maximum pressure gradient (PGmax), mitral valve mean pressure gradient (PGmean), mitral valve velocity time integral (VTI), mitral valve E-wave (MV-E), MV-E pressure gradient, mitral valve A-wave (MV-A), MV-A pressure gradient, aortic Vmax, aortic valve Vmean, aortic valve PGmax, aortic valve PGmean, aortic valve VTI, left ventricular outflow tract (LVOT)-Vmax, LVOT-Vmean were measured. All the sheep in this study were healthy and had no signs of heart disease. In this study, the parameters of M-mode and spectral Doppler echocardiographic were assessed and recognized in Iranian Shall sheep. The results demonstrated the parameters of echocardiographic could be dependably determined in Shall sheep which, established normal reference values for these parameters and left ventricular function indices in healthy Shall sheep. These results can be beneficial in appropriate imagination, recognition and measuring cardiac structures. This study can be exerted as a reference for the assessment and diagnosis of heart diseases in sheep medicine and human cardiovascular research in sheep experimental models.

Analysis of hemodynamic parameters on two-layered blood flow in a curved artery

Arterial stenosis is the thickening of the arterial wall due to the growth of aberrant tissues that prevent adequate blood flow in the human circulatory system and induces cardiovascular diseases. Mild stenosis, may lead to serious or permanent damage if remains uncured. There are differences in the curvature response and material composition between the outer layers and the core. There are several locations in blood vessels where they are curved, which affects the blood flow and shear stress. The Navier-Stokes equation in the cylindrical polar coordinate system has been extended by incorporating curvature term in two-layered blood flow along the axial direction with appropriate boundary conditions. Mathematical expressions for hemodynamic parameters such as velocity profile, volumetric flow rate, pressure drop, and shear stress have been calculated analytically in the case of a curve artery with stenosis. Moreover, we have analyzed the effect of stenosis on different hemodynamic parameters with the variation of core and peripheral-layer viscosity and curvature. Flow quantities are affected by the habitancy of stenosis and stipulate different blood flow behavior in both layers in the case of curved artery. This modeling technique may help researchers in medicine, mathematical biology, and bio-engineering.

A question of trust for AI research in medicine

A question of trust for AI research in medicine

Evaluation of Pediatric Patients Admitted to the Hospital for Drug Intoxication

Abstract Objective: Drug poisoning is the most common form of poisoning in children, and it is a situation that can lead to fatal consequences, but can be prevented if appropriate precautions are taken. Children are the future of a society, so drug poisoning poses an important public health problem. Factors such as high-dose drug combinations, misuse, poor storage conditions, and children's access to drugs can all contribute to drug intoxication. The aim of this study is to understand the effects of drug poisoning on children, to identify the characteristics of these children and to raise awareness about the measures that can be taken to prevent this problem. Material and Methods: This study was conducted retrospectively on 100 patients who applied to the pediatric emergency department of Karabuk University Faculty of Medicine Education and Research Hospital with the complaints of drug use and drug exposure. Results: It was observed that the mean age of the patients was 7.65±6.51 years, 58% of them were girls and 71% of them accidentally drank drugs. When the drugs consumed by the patients were examined, it was determined that the analgesic-anti-inflammatory (Paracetemol) group was the highest with 18%. When the hospitalization status of the patients was examined, it was seen that 22% of them were not hospitalized. It was observed that 56% of the patients experienced symptoms, and the most common symptom was nausea and vomiting with 33%. No mortality was observed in any of the patients. Conclusion: Study results show that children often take drugs accidentally. The fact that analgesic-antipyretic group drugs are mostly encountered suggests that it is a predictable result of their widespread use in the community. In addition, the high hospitalization rate with 78% unfortunately leads to an extra expenditure of our limited resources for a condition that could have been prevented. For this reason, establishing an effective public health policy and taking preventive measures for commonly used drugs can reduce the frequency of poisonings. We think that our findings will guide clinicians. Keywords: Drug poisoning, intoxication, drugs, pediatric patients

A self-assessment maturity matrix to support large-scale change using collaborative networks in the New Zealand health system

BackgroundA maturity matrix can be a useful tool for organisations implementing large-system transformation (LST) initiatives in complex systems. Insights from implementation of a local LST initiative using collaborative networks, known as Alliances, highlighted a tool was needed to help health system leaders prompt discussions on how and where to focus their change efforts. In the New Zealand (NZ) health system, Alliances were introduced to integrate the planning and delivery of health care between primary and hospital care.MethodsThe aim of this research was to use insights from Alliance members to develop a learning tool that collaborative networks could use to assess and improve their readiness for change. We constructed a maturity matrix using the knowledge of senior NZ health system leaders, in a workshop setting. The maturity matrix was empirically tested and refined with three Alliances and with feedback from the NZ Ministry of Health Māori Health Strategy and Policy team.ResultsThe maturity matrix described the 10 key elements that had been found to support successful implementation of LST initiatives in the NZ health system, along with success indicators and different stages of maturity from beginning to excellence. Testing of the maturity matrix with three Alliances suggested that it functioned as a learning tool and stimulated collective thinking and reflection. The Māori Health Strategy and Policy team commented on the importance of such a tool to increase health system leaders’ responsiveness to improving Māori health outcomes. Comparisons with similar international matrices revealed common elements with ours. A strength of our maturity matrix is that it is specific to the NZ context and is the first practical tool to implement large-scale change in the health system that incorporates principles of the Government’s treaty with Māori, the indigenous people of NZ.ConclusionsThrough a regular self-assessment process, use of the maturity matrix may create feedback loops to support deliberate learning and knowledge sharing for senior health system leaders and collaborative networks. The maturity matrix fills an important gap in the NZ health system and contributes to implementation science literature internationally.OtherThis study was approved by the Victoria University of Wellington Human Ethics Committee (Ethics Approval Number 27,356). The research was supported by the Victoria University of Wellington research grant (222,809) and from the University of Auckland Department of Medicine research fund (H10779).

Utilizing Multi-Class Classification Methods for Automated Sleep Disorder Prediction

Even from infancy, a human’s day-life alternates from a period of wakefulness to a period of sleep at night, during the 24-hour cycle. Sleep is a normal process necessary for human physical and mental health. A lack of sleep makes it difficult to control emotions and behaviour, reduces productivity at work, and can even increase stress or depression. In addition, poor sleep affects health; when sleep is insufficient, the chances of developing serious diseases greatly increase. Researchers in sleep medicine have identified an extensive list of sleep disorders, and thus leveraged Artificial Intelligence (AI) to automate their analysis and gain a deeper understanding of sleep patterns and related disorders. In this research, we seek a Machine Learning (ML) solution that will allow for efficient classification of unlabeled instances as being Sleep Apnea, Insomnia or Normal (subjects without a specific sleep disorder) by assessing the performance of two well-established strategies for multi-class classification tasks: the One-Vs-All (OVA) and One-Vs-One (OVO). In the context of the specific strategies, two well-known binary classification models were assumed, Logistic Regression (LR) and Support Vector Machines (SVMs). Both strategies’ validity was verified upon a dataset of diverse information related to the profiles (anthropometric data, sleep metrics, lifestyle and cardiovascular health factors) of potential patients or individuals not exhibiting any specific sleep disorder. Performance evaluation was carried out by comparing the weighted average results in all involved classes that represent these two specific sleep disorders and no-disorder occurrence; accuracy, kappa score, precision, recall, f-measure, and Area Under the ROC curve (AUC) were recorded and compared to identify an effective and robust model and strategy, both class-wise and on average. The experimental evaluation unveiled that after feature selection, 2-degree polynomial SVM under both strategies was the least complex and most efficient, recording an accuracy of 91.44%, a kappa score of 84.97%, precision, recall and f-measure equal to 0.914, and an AUC of 0.927.

Comparison of Polysaccharide Profiles of Different Seaweeds Based on Ion Chromatography and Ultrahigh‐Performance Liquid Chromatography

ABSTRACTIn traditional Chinese medicine research, seaweeds used for drug and health food development mainly refer to Sargassum pallidum (Turn.) C. Ag. (SP) and Sargassum fusiforme (Harv.) Setch. (SF). In the Chinese Pharmacopoeia, polysaccharides are the main quality control indicators. The total sugar content is determined by the anthrone–sulfuric acid method to evaluate the quality of seaweeds. However, this method cannot reflect the structural characteristics of seaweed polysaccharides and cannot distinguish among different seaweed varieties. Given this, to comprehensively evaluate the quality of different seaweeds, this study conducted a thorough analysis of the primary structure of polysaccharides in 11 batches of SF and 7 batches of SP. The neutral sugar content was determined by the anthrone–sulfuric acid colorimetric method, weight average molecular weight (Mw) by high‐performance size exclusion chromatography coupled with multi‐angle laser light scattering and refractive index detector method, sulfate content by ion chromatography and monosaccharide composition by ultrahigh‐performance liquid chromatography method, while also using professional software for statistical and similarity analysis. The results showed significant differences (p < 0.05) in neutral sugar content and Mw between S. fusiforme polysaccharides and S. pallidum polysaccharides, which can be used to distinguish SF and SP. The monosaccharide composition fingerprint was analyzed using chemometric methods, and it was found that fucose and glucose could serve as differential markers to distinguish SF and SP. This study further deepens the understanding of polysaccharides in seaweeds and more comprehensively evaluates the quality of different seaweeds.

A Computational Approach of Anti-diabetic Potential Evaluation of Flower and Seed of Nyctanthes arbor tristis Linn

Exploring the medicinal significance of bioactive compounds through computational methods is an increasingly practiced approach in contemporary medicinal research. This study aims to assess the antidiabetic potential of compounds extracted from the plant Nyctanthes arbor tristis by evaluating their ability to inhibit the carbohydrate metabolic enzyme α-glucosidase. The research work was conducted through molecular docking calculation, molecular dynamics simulation (MDS), and ADMET prediction techniques. Among the compounds, arbortistoside-C (NAS03), and arbortristoside-D (NAS04) found in the seed of the plant were identified as hit inhibitors of the target protein with docking scores, -9.9 and -9.4 kcal/mol, respectively. The compounds showed a comparable docking score with the drug of diabetes acarbose (-8.6 kcal/mol). Geometrical parameters like radius of gyration, solvent accessibility surface, root mean square deviation, and root mean square fluctuation from MDS supported the stability of the protein-ligand complex. MMPBSA calculations demonstrated the stability and feasibility of the complex with binding free energy changes of -29.06±6.06 and -23.58±8.80 kcal/mol for compounds NAS03 and NAS04, respectively. The ADMET prediction suggested the drug-likeness of the compounds compared with that of the standard drugs. The results could be used in proposing the antidiabetic potential of the two compounds from the plant as a potential inhibitors of α-glucosidase enzyme. Further, in vitro and in vivo experiments on such compounds could be a more reliable path to validate the output of this computational research.

Fermentation of Polygonati Rhizoma aqueous extract using Lactiplantibacillus plantarum under the condition of eutrophication.

In this experiment, the eutrophication system was established by adding sucrose and yeast powder, and the pH and dissolved oxygen were measured in a bioreactor in real time to study the effect of aerobic environment on the fermentation process of Polygonati Rhizoma extract by Lactiplantibacillus plantarum. To further analyze metabolic changes, UPLC-Q-Exactive MS was used for metabolomic analysis and metabolic profiling. Multivariate analysis was performed using principal component analysis and Orthogonal projections to latent structures discriminant analysis. Finally, 313 differential metabolites were selected, 196 of which were annotated through database matching. After fermentation, the content of short-chain fatty acids, lactic acid, and their derivatives increased significantly, and there were 13 kinds and 4 kinds, respectively. Both compounds and their derivatives are beneficial to the intestinal flora. Consequently, incorporating L. plantarum into the aerobic fermentation process of Polygonati Rhizoma extract within the eutrophic system is potentially advantageous in enhancing the impact of its fermentation solution on the gut microbiota and its effects on human health. Our findings for this kind of edible and medicinal material research and development offer useful insights.