This research paper presents a novel approach for discriminating patients with chronic obstructive pulmonary disease (COPD) from smokers and healthy controls using a self-made electronic nose device. This study aims to develop a portable and user-friendly system that accurately identifies patients with COPD based on volatile organic compound (VOC) profiles present in their breath. Breath samples were collected from 25 patients with COPD, 32 smokers, and 36 healthy controls. The MOS-based electronic nose device incorporated a sensor array consisting of TGS 2600, TGS 2610, TGS 2620, TGS 822, and TGS 826 sensors. Advanced signal processing techniques, including independent component analysis (ICA), were employed to analyze the breath samples and extract relevant features. Three classification models, namely the Support Vector Machine (SVM), Naive Bayes, and Decision Tree, were utilized to discriminate between patients with COPD, smokers, and healthy controls based on the extracted features. The results demonstrate the efficacy of the self-made MOS-based electronic nose device in accurately discriminating between patients with COPD, smokers, and healthy controls. The SVM model achieved a remarkable accuracy of 85.25% and an area under the curve (AUC) of 87%. This study highlights the potential of breath analysis to be used as a non-invasive and cost-effective approach for the diagnosis and differentiation of COPD. These findings provide a solid foundation for further research and the development of non-invasive breath analysis techniques in the field of respiratory disease diagnosis and monitoring.

This research demonstrates the synthesis of silica nanoparticles (Si-NPs) via the sol-gel method, followed by tetra-ethyl-orthosilicate and mercaptopropyl tri-methoxy-silane-mediated thiolation to promote the covalent binding of Aspergillus oryzae β-galactosidase. A higher enzyme immobilization yield of 89% was achieved on the developed nanobiocatalyst. Soluble and immobilized enzyme exhibited similar pH and temperature optima at pH 4.5 and 50 °C, respectively. However, β-galactosidase bound to thiolated Si-NPs (IβG) exhibited a significant enhancement in activity under extreme temperatures and pH variations, as compared to the soluble β-galactosidase (SβG), by improving its tolerance towards harsh pH ranges and limiting the thermal movement of the enzyme at higher temperatures. It was further observed that the immobilized enzyme retained 58% activity at a 5% galactose concentration even after 1 hour. However, under similar experimental conditions, SβG showed 23% activity. The reusability of the immobilized enzyme revealed that it retained 63% activity even after the sixth repeated use and hence could be recovered easily by centrifugation for repeated use in biotechnological applications. The batch reactor experiment indicated that the immobilized enzyme displayed 86% and 79% lactose hydrolysis at 50^oC and 60^oC, respectively, as compared to 71% and 60% lactose hydrolysis of the soluble enzyme under identical conditions after 8 h. Future research of the developed nanobiocatalyst is required to analyze its stability in producing lactose-free dairy in continuous reactors products and in the production of galacto-oligosaccharides.

Chitinases, enzymes produced by diverse organisms like bacteria, fungi, insects, plants, and humans, play a crucial role in degrading the biopolymer chitin. They have wide-ranging applications, including abilities to isolate protoplasts from fungi, control pathogenic fungi, treat chitinous waste, and manage disease transmission viinsects due to their chitin-degrading ability. This study focused on determining optimal conditions for chitinase production using the fungus Beauveria bassiana, acknowledging the enzyme's significant importance. The strain employed was B. bassiana 487 from Embrapa, registered in the ARSEF database. Three media (Hill, Adams, and Medium 2) were assessed with or without shrimp exoskeletons as an inducer over a 10-day period. Initial fermentation conditions included a pH of 5.5, a temperature of 28 °C, stirring at 120 rpm, and an inoculum size of 107 cells/mL. Production and enzymatic activity were evaluated, monitored for 7 days, with the tenth day dedicated to identifying optimal production conditions. Medium 2 demonstrated superior production when supplemented with the inducer, reaching its peak on the seventh day. Following the medium selection, chitinase enzymatic activity in Medium 2 with the inducer was assessed. Until the eighth day, B. bassiana 487 showed low enzyme production, with an enzymatic activity of 6.08 nmol/mL.min. A significant increase occurred on the ninth day, reaching 348.94 nmol/mL.min. High activity persisted on the tenth and eleventh days, with values of 302.45 and 264.59 nmol/mL.min, respectively. In conclusion, for enhanced chitinase production by B. bassiana 487, we recommend using Medium 2 over a 10-day fermentation period under suitable conditions.

Chitosan is a biopolymer synthesized through the deacetylation of chitin, a polysaccharide that can be obtained from various renewable resources, mainly waste from marine food production.

Its excellent properties, including antimicrobial activity, non-toxicity, biocompatibility, and biodegradability, have made chitosan a successful material in food packaging technology.

The objective of this study is to provide a patent landscape of the use of chitosan in food packaging applications.

The reference database used was Espacenet (https://worldwide.espacenet.com), a free patent database provided by the European Patent Office (EPO).

The final patent results were obtained using both classification symbols [IPC (International Patent Classification) and CPC (Cooperative Patent Classification)] and keywords in the full text, title, abstract, and claims search fields.

A total of 2737 patent documents were obtained.

After filtering the data by the earliest priority date (2003-2023), 2556 results were retrieved.

China had the highest number of patents with 2154, followed by the USA with 261 and Europe with 173.

The International Patent System (PCT) was frequently used by applicants and ranked second with 288 patent applications.

A total of 2316 patents/patent applications were filed between 2012 and 2022.

Upon analysis of the data, it was observed that many of the applications were based on chitosan blends. The most commonly claimed biopolymer blends were starch and cellulose, while the most commonly claimed synthetic polymer blends were polylactic acid (PLA) and polyvinyl alcohol (PVA).

The data analysis indicates that the following materials were used: polyhydroxy alcohols, nanostructured additives, quaternary ammonium chitosan, TiO₂ and oxides/hydroxides of zinc as compounding ingredients, heterocyclic compounds with a six-membered ring containing one oxygen atom in the ring, and phenolic acids, mainly gallic, ferulic, and salicylic acid.

The intestinal microbiome is important for synthesising nutrients, breaking down polysaccharides, protecting against foreign microbes, and aiding immune system development by producing short-chain fatty acids (SCFAs). SCFAs are formed through the interaction between the gut microbiota and the diet in the gut lumen. This study aims to extract exopolysaccharide (EPS) from the gut isolate Bacillus spizizenni DMTMMR-17, a probiotic species which was optimised to improvise the yield of EPS through one-factor-at-a-time (OFAT) and response surface methodology. The central composite design (CCD) increased the yield up to 2.32 ± 0.4 g/l, abd characterization was performed to study the structural and functional moieties of EPS by Fourier transform infrared spectroscopy (FTIR) and nuclear magnetic resonance (NMR) for proton and carbon (¹H and C¹³-NMR). The EPS was subjected to artificial simulated gastrointestinal digestion by mimicking the gut conditions of healthy humans. These data reveal the higher concentrations of SCFA derivatives such as propionate, acetate, and other bioactive metabolites. The in vitro experiments in IBD (irritable bowel syndrome) patients' gut homogenates were treated with EPS digest with SCFA, revealing that dysbiosis is reinstated, by improvising the colonisation of probiotic and gut symbionts by inhibiting the growth of pathogenic bacteria, whcih was studied by the metagenomic sequencing (V₃-V₄) region of the 16S rRNA gene. The EPS digest with SCFA was subjected to biological activities such as scavenging and reducing power, which showed 32.03 ± 0.21 and 13.04 ± 0.3 µg/ml. The anti-diabetic activity, like α-amylase, α-glucosidase and DPP-IV, was studied, expressing reduced IC₅₀ values at (9.21 ± 0.3, 4.43 ± 0.4, 21.4 ± 0.33) µg/ml. Anti-inflammatory activity was higher up to 60-75%, and the anti-lipidemic inhibition property expressed inhibition up to 40 % in cholesterol esterase and pancreatic lipase. These results indicate that EPS digest with SCFA is a beneficial substrate and can be administered for combinational IBD therapies.

The retrogradation of starch during storage was attributed to the high amylose content of corn-based food, resulting in economic losses and restricting the development of the food industry. The unique molecular capsule structure of cyclodextrins has been widely developed and applied in food fields in recent years.

β-cyclodextrin(β-CD) and hydroxypropyl-β-cyclodextrin(HP-β-CD) are natural cyclic annular oligosaccharides, with less studies on the application of inhibiting the retrogradation of corn starch. Our research showed that β-CDs could affect the rheological and gelatinization properties of corn starch gel and enhance the thermal stability of starch granules. Meanwhile, the addition of β-CDs during storage can promote the texture characteristics of gel. This was due to the improvement of the gel's internal structure using β-CDs, which was also supported by SEM observations. In addition, XRD and FTIR results illustrated that β-CDs could inhibit the formation of the ordered starch crystal structure. These results were represented more significantly with the addition of HP-β-CD, which may be due to the intense competition for intermolecular water molecules between HP-β-CD and amylose. The experimental results proved the application prospect of β -CDs in corn-based food. Consequently, the addition of β-CDs could delay the retrogradation of CS gel, and the introduction of hydroxypropyl groups was more effective, which provided a theoretical basis and new insights for the production of starch-based food industrial products.

This study focuses on the comprehensive analysis of machine learning algorithms for the classification of breast cancer into benign and malignant categories using the Wisconsin breast cancer dataset. Two distinct approaches, supervised and unsupervised, were employed to evaluate the effectiveness of various algorithms in discerning the nature of cancerous growths based on diverse physical properties.

In the supervised learning realm, the study employed three powerful algorithms: Support Vector Machines (SVMs), Random Forests, and XGBoost. Additionally, unsupervised learning techniques, specifically Linear Discriminant Analysis and the Gaussian Finite Mixture Model for classification, were investigated. Notably, the XGBoost algorithm emerged as the most promising candidate in the supervised category, exhibiting superior classification performance when applied to the testing dataset (20% of the total data). The results indicated that XGBoost achieved an impressive precision of 98.23%, outperforming both the Gaussian Finite Mixture Model for classification (97.5%) and the Linear Discriminant Analysis (96.48%). The XGBoost algorithm, implemented on a subset of the data, demonstrated its efficacy in accurately identifying the nature of breast cancer, highlighting its potential as a robust tool for predicting malignancy based on distinct physical properties.

This study underscores the significance of supervised and unsupervised learning, particularly the XGBoost algorithm and the Gaussian Finite Mixture Model for classification, in optimizing breast cancer classification. The findings contribute valuable insights into the selection of appropriate machine learning techniques for the accurate and efficient identification of benign and malignant breast cancer, thereby facilitating improved diagnostic practices.

Introduction: Diabetes, a global health issue, can cause diabetic nephropathy in one third of its sufferers. Recently, β-amyrin, a natural pentacyclic triterpene, has garnered interest for its potential to combat diabetes and treat chronic kidney disease resulting from the condition. In this study, we investigate the antihyperglycemic and renoprotective effects of β-amyrin, both individually and in combination with metformin, through the use of NRK-52E cell lines. Methods: We conducted an investigation into the impact of β-amyrin and metformin, both separately and in combination, on NRK-52E cell lines under normoglycemic and hyperglycemic conditions. High glucose-cotreated NRK-52E cells were exposed to these compounds, and their effects were evaluated through several parameters, including cell viability assessed using the cell counting kit-8 assay, apoptosis via flow cytometry, reactive oxygen species (ROS) levels using H2DCFDA expression, and gene expression studies via RT-qPCR to examine endoplasmic reticulum (ER) stress, apoptotic markers, and inflammatory markers. Results: Under normoglycemic conditions, the test compounds did not exhibit a significant impact on the cell lines. However, in the presence of high glucose, β-amyrin, metformin, and their combination demonstrated a noteworthy improvement in cell viability, with the combined treatment yielding superior results compared to individual treatments. The flow cytometry analysis revealed a substantial reduction in apoptotic cells, particularly with the combination treatment (p<0.05). Moreover, the test compounds effectively inhibited high glucose-induced ROS production, with the combination treatment displaying the most significant reduction. Gene expression studies demonstrated a downregulation of ER stress, apoptotic markers, and inflammatory markers, with the combination treatment consistently yielding the greatest reductions. Conclusions: β-amyrin and metformin exhibit renoprotective effects in high glucose-induced renal cells, suggesting a promising therapeutic approach for mitigating hyperglycemia's adverse effects on renal function. Further research in diabetic patients is needed to validate these findings.

Enhancing immunity is essential for the maintenance and restoration of body homeostasis, facing the pandemic of coronavirus disease 2019 (COVID-19), and combatting the effects of an unbalanced lifestyle^[1]. Previous research has proven that dietary fibers have multiple bioactivities, indicating their great potential in functional food development^[2,3].

In this study, the immunomodulatory activity of three dietary fibers on cyclophosphamide (CTX)-induced immunosuppression are investigated from the perspective of humoral immunity. We compared the changes in mouse body weight, thymus or spleen index, IgM secretion and metabolism in serum, splenic cytokine TNF-α secretion, splenic mRNA expression of GATA-3 and T-bet detected by quantitative real-time PCR (RT-PCR), and the percentage of CD3⁺ cells in splenic lymphocytes using flow cytometry. The results show that all three dietary fibers improved the status of immunosuppressed mice by recovering body weight and relative organ weight as well as increasing the secretion of serum IgM and splenic cytokine TNF-α. Among the three dietary fibers, apple pectin mostly enhanced T-bet levels, regulating the balance of Th1/Th2 cells^[3]. In addition, the percentage of CD3⁺ cells in splenic lymphocytes improved significantly after treatment with inulin and guar gum. Our research compared the immunomodulatory bioactivity of three different dietary fibers in a CTX-induced immunosuppressed mice model, providing evidence for the bioactivity potential of dietary fibers and a view of integrated immunometabolic responses.

Alcoholic liver disease (ALD) is an ignored global issue of public health. It is urgent for searching bioactive foods to prevent ALD. Zhenjiang aromatic
vinegar (ZAV) contained antioxidant compounds, including polyphenols, flavonoids, and melanoidins. The mechanism of ZAV on preventing acute
liver injury was evaluated in alcohol‐treated mice. Our results showed that ZAV ameliorated morphological damage by hematoxylin and eosin and
Oil Red O staining in alcohol‐treated liver. ZAV relieved symptoms of ALD, which presented as decreased serum triacylglycerol, total cholesterol, alanine
transaminase, and aspartate aminotransferase levels. In addition, ZAV treatment inhibited hepatic oxidative stress levels by downregulating reactive
oxygen species generation, and the oxidative products (malonaldehyde, 4‐hydroxynonenal, and 8‐hydroxydeoxyguanosine), and upregulating catalase,
superoxide dismutase, glutathione, and glutathione peroxidase. ZAV further reduced production of tumor necrosis factor‐α and monocyte chemoattractant protein‐1, and elevated levels of interleukin‐4 and transforming growth factor‐β indicating the inhibition of alcohol‐induced inflammation. Furthermore, ZAV treatment increased expression levels of autophagy‐associated proteins in ALD mice by western blot, which participated in anti‐ALD effect of ZAV. These findings demonstrate that ZAV could be an alternative for ALD intervention by regulating oxidative stress and autophagy. In this study, the mice model of ALD was used to investigate the mechanism of ZAV against liver injury. The data provided novel insights of ZAV on the prevention of acute alcoholic liver injury.