Current Pharmaceutical Biotechnology - Online First

This review aims to systematically investigate the existing research on the effects of anthocyanins on cognitive functions and their underlying mechanisms involved. It provides detailed insights into their development and potential applications.

An extensive review and analysis of various animal experiments and human studies were performed using databases, such as Web of Science, Sci-Hub, EI, ScienceDirect, and PubMed. The keywords, titles, or abstracts searched included, but were not limited to, 'Anthocyanin', 'Cognition', 'Anti-inflammatory', 'Antioxidation', 'Autophagy', and 'Insulin resistance'. The search was conducted covering the period from January 2017 to November 2025. Our aim was to summarize the evidence concerning the impact of anthocyanins on cognitive functions and to explore their underlying mechanisms. We analyzed these mechanisms in terms of antioxidant activity, reduction of neuroinflammation, regulation of autophagy-related pathways, and central insulin sensitivity.

A substantial body of research has indicated that anthocyanins exert beneficial effects on cognitive function. In models exhibiting cognitive impairment, supplementation with anthocyanins has been shown to significantly improve cognitive capabilities. The underlying mechanisms of action are primarily attributed to the following factors: the strong antioxidant properties of anthocyanins, which effectively neutralize free radicals in the brain, thereby diminishing oxidative stress and protecting neuronal integrity and functionality; the inhibition of neuroinflammatory responses, which alleviates the detrimental impact of inflammatory agents on neural tissues and contributes to the maintenance of the brain's homeostatic environment; and the regulation of autophagy-related pathways and central insulin sensitivity, which collectively reduce damage to proteins linked to cognitive function and enhance learning and memory processes.

As the global population ages rapidly and the prevalence of cognitive decline-related diseases, like Alzheimer's, increases, there is a pressing need to create medications that can improve cognitive abilities. Researchers are paying close attention to anthocyanins, natural substances found in plants such as blueberries and purple grapes, due to their significant potential to influence cognitive functions. Nonetheless, further clinical trials are necessary to validate the appropriate dosage and bioavailability of anthocyanins, and certain limitations must be acknowledged.

In the present study, it was found that anthocyanins can improve cognitive impairment in both humans and animals. Their mechanisms of action primarily involve anti-inflammatory effects, antioxidant activity, modulation of autophagy, and the reduction of central insulin resistance. This research lays the groundwork for future studies on the role of anthocyanins in cognitive function.

The Internet of Medical Things (IoMT) has made it possible to create advanced health monitoring systems. It allows the system to detect problems early, thereby mitigating long-term effects. This development will likely enhance the quality of healthcare professionals by reducing their workload and healthcare costs. The IoT in medical technology offers a wide range of information technology capabilities, including intelligent and collaborative healthcare solutions. Aggregating health data in a single repository raises security, copyright, and compliance issues when building a complex machine-learning model.

Federated learning overcomes the above challenges by dispersing a global learning model through a central aggregate server. It retains mastery of patient data in a local participant who ensures data privacy and integrity. This research aims to develop an advanced healthcare monitoring system utilizing federated learning techniques. The system is designed to enable healthcare providers to effectively track patient health through medical sensors and respond promptly when necessary.

The federated learning-based XGBoost model achieved a predictive accuracy of 97.2% in diagnosing Parkinson’s disease. Additionally, the system demonstrated improved privacy preservation, significantly reducing sensitive data exposure with minimal computational overhead, confirming its practical effectiveness in clinical scenarios.

By leveraging federated learning, the proposed approach seeks to enhance the efficiency and effectiveness of health monitoring in clinical settings. To achieve accurate classification and early detection of Parkinson's disease, the study employs two key machine learning algorithms: Support Vector Machine (SVM) and Extreme Gradient Boosting (XGBoost). These methods were selected for their statistical robustness and suitability for the task at hand.

The combination of federated learning, SVM, and XGBoost enhances healthcare monitoring and ensures patient data privacy and integrity.

Primary Sjögren's Syndrome (pSS) is a chronic autoimmune condition affecting lacrimal and salivary glands. While previous studies suggest potential associations between dyslipidemia and autoimmune diseases, the causal relationship between lipid-lowering medications and pSS remains unclear.

This study employed drug-targeted Mendelian randomization (MR) analysis to assess the impact of lipid-lowering drugs on pSS risk, focusing on genetic targets including HMGCR, PCSK9, NPC1L1, APOB, CETP, and LDLR. Data were sourced from the Global Lipids Genetics Consortium and UK Biobank. Significant single-nucleotide polymorphisms linked to LDL cholesterol were utilized as instrumental variables. Causal effects were estimated using Inverse Variance Weighted, Weighted Median, MR Egger, Simple Mode, and Weighted Mode methods. Robustness was ensured through heterogeneity and sensitivity analyses.

The inhibition of HMGCR and CETP genes was found to be significantly associated with an increased risk of developing pSS (HMGCR: OR = 3.602, 95% CI [1.051, 12.344], p = 0.041; CETP: OR = 12.251, 95% CI [2.599, 57.743], p = 0.002).

HMGCR and CETP may affect pSS risk via non-lipid pathways, suggesting distinct mechanisms among different lipid-lowering drug targets.

This study provides compelling evidence suggesting that lipid-lowering drugs may contribute to the risk of pSS, thus offering new insights for clinical intervention strategies.

The most prevalent kind of cancer among women is breast cancer. Consequently, the development of novel, potent medications with fewer adverse effects is required to treat it. Breast cancer is frequently treated clinically with chemotherapy and surgery. However, there are still significant challenges to be addressed in the treatment of breast cancer, including inadequate therapeutic results, inevitable side effects, and the surgical excision of breast tissue. The objective of the study is to develop broccoli extract-based Hydrogel to overcome the challenges in breast cancer treatment.

The developed Hydrogel was characterized by certain techniques to check its stability and drug release abilities. Swelling studies and drug release behavior were checked; the porosity of Hydrogel was checked by SEM EDX Analysis. Furthermore, in vitro studies were done to check the anti-breast cancer activity of the developed Hydrogel.

The hydrogel was a highly porous structure with and compressive modulus, which makes it good for biological use in drug delivery. The in vitro studies showed that, developed Hydrogel inhibits the growth of breast cancer cells (MCF-7) at different concentrations and time intervals of 24 and 48 Hrs and was compatible with the non-cancerous cell line 3T3-L1. The results indicate the tolerability of Hydrogel at the level of cells.

Numerous investigations have demonstrated the anticancer effects of SFN by influencing the various biological processes that tumor cells engage in. In breast cancer cell lines, SFN functions as an HDAC inhibitor and reduces the expression of ER, EGFR, & HER-2 proteins. SFN also triggers apoptosis and cell cycle halt. Both Hydrogel and SFN inhibit the cells growth in MCF-7 breast cancer cells and agree with the previous studies.

In conclusion, we synthesized a hydrogel using broccoli extract to treat breast cancer with better stability, tolerance, and effectiveness through sustained local drug delivery. It was determined that this new hydrogel was a simple and affordable way to accomplish the continuous gene release feature, which would enhance the therapeutic efficacy in anti-cancer treatment while reducing the likelihood of potentially fatal side effects.

Parkinson’s disease (PD) is a prevalent neurodegenerative disorder characterized by the progressive loss of dopaminergic neuron. Although the role of immunity in PD has been increasingly recognized, the immunogenetic mechanisms underpinning its progression remain largely unresolved.

We employed an integrative approach combining Mendelian randomization (MR), expression quantitative trait loci analysis, and single-cell RNA sequencing to investigate immune cell infiltration and transcriptional regulation in PD. Immune cell composition, pathway activation, and gene regulatory networks were assessed through single-cell gene set enrichment analysis and transcriptional correlation analyses.

Immune profiling revealed significant increases in naive B cells (1.22-fold), plasma cells (3.00-fold), switched memory B cells (2.85-fold), and unswitched memory B cells (6.70-fold) in PD patients compared to controls (p < 0.001). MR analysis identified five causal genes- CYTH4, FGR, LRRK2, RIN3, and SAT1- associated with monocyte, neutrophil, and B cell infiltration. SAT1 (OR: 1.529; 95% CI: 1.018–2.297) and RIN3 (OR: 1.222; 95% CI: 1.039–1.437) showed strong associations with PD risk (p < 0.01). SAT1 positively correlated with PARK7 and regulated reactive oxygen species signaling, while FGR negatively correlated with ABCA4, influencing lipid metabolism and immune responses.

These findings highlight distinct immunogenetic mechanisms driving PD progression. The SAT1-PARK7 axis appears to modulate oxidative stress and neuroinflammation, whereas the FGR-ABCA4 interaction may affect metabolic and immune pathways. While the study is limited by population heterogeneity and the challenges of inferring causality, it provides mechanistic insights into immune contributions to PD.

Our integrative genomic analysis identified novel regulatory networks involving immune-related genes in PD, offering potential targets for mechanistic understanding and therapeutic development.

To optimize the culture process of Mesenchymal Stem Cells (MSCs) and enhance their biological functions.

MSCs have shown great potential in treating various diseases due to their low immunogenicity and potent paracrine effects. However, the inherent heterogeneity of MSC populations, which can vary depending on the culture conditions, may challenge large-scale clinical application.

This study investigates the inconsistency of MSCs cultured in different media, from the transcriptional level to biological functions.

RNA sequencing was used to identify different expressed genes of MSCs separated and expanded in three media, which were then validated with qPCR. In vitro assays, including proliferation, tube formation, wound healing, multilineage differentiation, paracrine secretome and injured hepatocyte protection assay, were performed to verify the potential differences among three groups.

MSCs cultured in platelet lysate-containing medium exhibited high expression of genes involved in extracellular matrix regulation, collagen metabolic processes, and angiogenesis, whereas those cultured in serum-free medium demonstrated high expression of genes associated with DNA replication and chromosome segregation. MSCs cultured under serum-containing medium indicated high levels of genes associated with extracellular matrix regulation, cartilage development, and chemotaxis. The results of functional comparative experiments were consistent with the differences in their gene expression patterns. Notably, MSCs cultured in the serum-containing system exhibited greater protective effect against hepatocyte activity.

Different culture conditions affect the biological functions of MSCs. Optimal conditions should be investigated for applications. Next, an in vivo model should be established to evaluate differences in MSC tissue repair function under various culture conditions.