Exosomes from umbilical cord mesenchymal stromal cells promote the collagen production of fibroblasts from pelvic organ prolapse.

BACKGROUND: Pelvic organ prolapse (POP) involves pelvic organ herniation into the vagina due to pelvic floor tissue laxity, and vaginal structure is an essential factor. In POP, the vaginal walls exhibit abnormal collagen distribution and decreased fibroblast levels and functions. The intricate etiology of POP and the prohibition of transvaginal meshes in pelvic reconstruction surgery present challenges in targeted therapy development. Human umbilical cord mesenchymal stromal cells (hucMSCs) present limitations, but their exosomes (hucMSC-Exo) are promising therapeutic tools for promoting fibroblast proliferation and extracellular matrix remodeling. AIM: To investigate the effects of hucMSC-Exo on the functions of primary vaginal fibroblasts and to elucidate the underlying mechanism involved. METHODS: Human vaginal wall collagen content was assessed by Masson's trichrome and Sirius blue staining. Gene expression differences in fibroblasts from patients with and without POP were assessed via RNA sequencing (RNA-seq). The effects of hucMSC-Exo on fibroblasts were determined via functional experiments in vitro. RNA-seq data from fibroblasts exposed to hucMSC-Exo and microRNA (miRNA) sequencing data from hucMSC-Exo were jointly analyzed to identify effective molecules. RESULTS: In POP, the vaginal wall exhibited abnormal collagen distribution and reduced fibroblast 1 quality and quantity. Treatment with 4 or 6 µg/mL hucMSC-Exo suppressed inflammation in POP group fibroblasts, stimulated primary fibroblast growth, and elevated collagen I (Col1) production in vitro. High-throughput RNA-seq of fibroblasts treated with hucMSC-Exo and miRNA sequencing of hucMSC-Exo revealed that abundant exosomal miRNAs downregulated matrix metalloproteinase 11 (MMP11) expression. CONCLUSION: HucMSC-Exo normalized the growth and function of primary fibroblasts from patients with POP by promoting cell growth and Col1 expression in vitro. Abundant miRNAs in hucMSC-Exo targeted and downregulated MMP11 expression. HucMSC-Exo-based therapy may be ideal for safely and effectively treating POP.

Enhancing heterogeneous Fenton-like catalysis through pyrrolidine modification of Fe2O3-CuO composites with oxygen-vacancy defects.

Enhancing the generation of reactive hydroxyl radicals (•OH) is crucial for overcoming the limitations of the low reactivity of heterogeneous Fenton Fe-based catalysts. Researchers have explored various methods to modify catalyst structures to enhance reactivity, yet often at the expense of stability. Herein, suitable carbon and nitrogen-codoped Fe2O3-CuO composites were synthesized via pyrolysis method, demonstrating high Fenton reaction activity and remarkable stability. Experimental findings and density functional theory calculations (DFT) revealed that the presence of oxygen vacancies on the catalyst surface facilitated an increase in exposed FeNC active sites, promoting electron transfer and the accelerating the rate of •OH generation. Moreover, carbon and nitrogen, particularly in the form of pyrrole nitrogen bonded to Fe imparted exceptional stability to the FeNC active sites, mitigating their dissolution. Additionally, the Fe-based catalysts exhibited strong magnetism, enabling easy separation from the reaction solution while maintaining a high degradation efficiency for various organic pollutants, even in the presence of multiple anions. Furthermore, a comprehensive mechanism for methylene blue (MB) degradation was identified, enhancing the potential practical applications of these catalysts.

Vinyl-bearing sp2 carbon-conjugated covalent organic framework composites for enhanced electrochemical performance in hydrogen evolution reaction and lithium-sulfur batteries.

Vinyl-bearing triazine-functionalized covalent organic frameworks (COFs) have emerged as promising materials for electrocatalysis and energy storage. Guided by density functional theory calculations, a vinyl-enriched COF (VCOF-1) featuring a donor-acceptor structure was synthesized based on the Knoevenagel reaction. Moreover, the VCOF-1@Ru without pyrolysis was obtained through chemical coordination interactions between VCOF-1 and RuCl3, exhibiting enhanced electrocatalytic performance in the hydrogen evolution reaction when exposed to 0.5 M H2SO4. The results demonstrated that the protonation of VCOF-1@Ru enhanced the electrical conductivity and accelerated the generation of H2 on the catalytically active site Ru. Additionally, VCOF-1@CNT with a tubular structure was prepared by uniformly wrapping VCOF-1 onto carbon nanotubes (CNTs) and using it as a cathode for lithium-sulfur batteries by chemically and physically encapsulating S. The enhanced performance of VCOF-1@CNT was attributed to the effective suppression of lithium polysulfide migration. This suppression was achieved through several mechanisms, including the inverse vulcanization of vinyl on VCOF-1@CNT, the enhancement of material conductivity, and the interaction between N in the materials and Li ions. This study demonstrated a strategy for enhancing material performance by precisely modulating the COF structure at the molecular level.

Evaluation of transmission-blocking potential of PvPSOP25 using transgenic murine malaria parasite and clinical isolates.

BACKGROUND: Malaria transmission-blocking vaccines (TBVs) aim to inhibit malaria parasite development in mosquitoes and prevent further transmission to the human host. The putative-secreted ookinete protein 25 (PSOP25), highly conserved in Plasmodium spp., is a promising TBV target. Here, we investigated PvPSOP25 from P. vivax as a TBV candidate using transgenic murine parasite P. berghei and clinical P. vivax isolates. METHODS AND FINDINGS: A transgenic P. berghei line expressing PvPSOP25 (TrPvPSOP25Pb) was generated. Full-length PvPSOP25 was expressed in the yeast Pichia pastoris and used to immunize mice to obtain anti-rPvPSOP25 sera. The transmission-blocking activity of the anti-rPvPSOP25 sera was evaluated through in vitro assays and mosquito-feeding experiments. The antisera generated by immunization with rPvPSOP25 specifically recognized the native PvPSOP25 antigen expressed in TrPvPSOP25Pb ookinetes. In vitro assays showed that the immune sera significantly inhibited exflagellation and ookinete formation of the TrPvPSOP25Pb parasite. Mosquitoes feeding on mice infected with the transgenic parasite and passively transferred with the anti-rPvPSOP25 sera showed a 70.7% reduction in oocyst density compared to the control group. In a direct membrane feeding assay conducted with five clinical P. vivax isolates, the mouse anti-rPvPSOP25 antibodies significantly reduced the oocyst density while showing a negligible influence on mosquito infection prevalence. CONCLUSIONS: This study supported the feasibility of transgenic murine malaria parasites expressing P. vivax antigens as a useful tool for evaluating P. vivax TBV candidates. Meanwhile, the moderate transmission-reducing activity of the generated anti-rPvPSOP25 sera necessitates further research to optimize its efficacy.

Photo-Stimulated Zn-based Batteries: Progress, Challenges, and Perspectives.

Solar energy, as a renewable energy source, dominates the vast majority of human energy, which can be harvested and converted by photovoltaic solar cells. However, the intermittent availability of solar energy restricts the actual utilization circumstances of solar cells. Integrating photo-responsive electrodes into an energy storage device emerges as a dependable and executable strategy, fostering the creation of photo-stimulated batteries that seamlessly amalgamate the process of solar energy collection, conversion, and storage in one system. Endowed by virtues such as cost-effectiveness, facile manufacturing, safety, and environmental friendliness, photo-stimulated Zn-based batteries have attracted considerable attention. The progress report furnishes a brief overview, summarizing various photo-stimulated Zn-based batteries. Their configurations, operational principles, advancements, and the intricate engineering of photoelectrode designs are introduced, respectively. Through rigorous architectural design, photo-stimulated Zn-based batteries exhibit the ability to initiate charging by saving electricity usage, and in certain instances, even without the need for external electrical grids under illumination. Furthermore, the compensation of solar energy can be explored to improve the output electric energy. At last, opportunities and challenges toward photo-stimulated Zn-based batteries in the process of development are proposed and discussed in the hope of expanding their application scenarios and accelerating the commercialization progress.

Doping with KBr to Achieve High-Performance CsPbBr3 Semitransparent Perovskite Solar Cells.

Wide-bandgap semitransparent perovskite photovoltaics are emerging as one of the ideal candidates for building-integrated photovoltaics (BIPV). However, surface defects in inorganic CsPbBr3 perovskite prepared by vapor deposition severely limit the optoelectronic performance of perovskite solar cells. To address this issue, a strategy of doping a trace amount of KBr into perovskite by vapor deposition is adopted, effectively improving the quality of the film, reducing surface defect concentration, and enhancing the transportation and extraction of charge carriers. Simultaneously, fully physical vapor deposition technology is employed to fabricate perovskite solar cells with an average visible light transmittance of 44%. These devices exhibited an ultrahigh open-circuit voltage of 1.55 V and a superior power conversion efficiency (PCE) of 7.28%, demonstrating excellent moisture and heat resistance. Moreover, the corresponding 5 cm × 5 cm modules achieve a PCE of 5.35% with great thermal insulation capability. This work provides an approach for fabricating highly efficient all-inorganic perovskite solar cells with high average visible light transmittance, demonstrating new insights into their application in building-integrated photovoltaics.

Sijunzi decoction alleviates inflammation and intestinal epithelial barrier damage and modulates the gut microbiota in ulcerative colitis mice.

Ethnopharmacological relevance: As a representative classical prescription, Sijunzi decoction has powerful therapeutic effects on spleen-stomach qi insufficiency. Ulcerative colitis (UC) is a chronic, diffuse, and non-specifically inflammatory disorder, the etiology of which still remains unclear. In the traditional Chinese medicine (TCM) perspective, splenic asthenia is the primary cause of UC. Based on this, Sijunzi decoction has been extensively used in TCM clinical practice to alleviate UC in recent years. However, the pharmacological mechanism of Sijunzi decoction in modern medicine is still not completely clear, which limits its clinical application. Aim of the study: The purpose of this study was to investigate the Sijunzi decoction's curative effect on acute UC mice and probe into its potential pharmacological mechanism. Materials and methods: The UC mouse model was set up by freely ingesting a 3% dextran sulfate sodium (DSS) solution. The relieving role of Sijunzi decoction on UC in mice was analyzed by evaluating the changes in clinical parameters, colon morphology, histopathology, inflammatory factor content, intestinal epithelial barrier protein expression level, and gut microbiota balance state. Finally, multivariate statistical analysis was conducted to elucidate the relationship between inflammatory factors, intestinal epithelial barrier proteins, and gut microbiota. Results: First, the research findings revealed that Sijunzi decoction could visibly ease the clinical manifestation of UC, lower the DAI score, and attenuate colonic damage. Moreover, Sijunzi decoction could also significantly inhibit IL-6, IL-1ß, and TNF-α while increasing occludin and ZO-1 expression levels. Subsequently, further studies showed that Sijunzi decoction could remodel gut microbiota homeostasis. Sijunzi decoction was beneficial in regulating the levels of Alistipes, Akkermansia, Lachnospiraceae_NK4A136_group, and other bacteria. Finally, multivariate statistical analysis demonstrated that key gut microbes were closely associated with inflammatory factors and intestinal epithelial barrier proteins. Conclusion: Sijunzi decoction can significantly prevent and treat UC. Its mechanism is strongly associated with the improvement of inflammation and intestinal epithelial barrier damage by regulating the gut microbiota.

Strong Interaction between Titanium Carbonitride Embedded in Mesoporous Carbon Nanofibers and Pt Enables Durable Oxygen Reduction.

Platinum (Pt) supported on high surface area carbon has been the most widely used electrocatalyst in proton exchange membrane fuel cell (PEMFC). However, conventional carbon supports are susceptible to corrosion at high potentials, leading to severe degradation of electrochemical performance. In this work, titanium carbonitride embedded in mesoporous carbon nanofibers (m-TiCN NFs) are reported as a promising alternative to address this issue. Benefiting from the interpenetrating conductive pathways inside the one-dimensional (1D) nanostructures and the embedded TiCN nanoparticles (NPs), m-TiCN NFs exhibit excellent stability at high potentials and interact strongly with Pt NPs. Subsequently, m-TiCN NFs-supported Pt NPs deliver remarkably enhanced oxygen reduction reaction (ORR) activity and durability, with negligible activity decay and less than 5% loss of electrochemical surface area（ECSA） after 50 000 cycles. Moreover, the fuel cell assembled by this catalyst delivers a maximum power density of 1.22 W cm-2 and merely 3% loss after 30 000 cycles of accelerated durability tests under U.S. Department of Energy (DOE) protocols. The improved ORR activity and durability are attributed to the superior corrosion resistance of the m-TiCN NF support and the strong interaction between Pt and m-TiCN NFs.

Ferroptosis: An important mechanism of disease mediated by the gut-liver-brain axis.

AIMS: As a unique iron-dependent non-apoptotic cell death, Ferroptosis is involved in the pathogenesis and development of many human diseases and has become a research hotspot in recent years. However, the regulatory role of ferroptosis in the gut-liver-brain axis has not been elucidated. This paper summarizes the regulatory role of ferroptosis and provides theoretical basis for related research. MATERIALS AND METHODS: We searched PubMed, CNKI and Wed of Science databases on ferroptosis mediated gut-liver-brain axis diseases, summarized the regulatory role of ferroptosis on organ axis, and explained the adverse effects of related regulatory effects on various diseases. KEY FINDINGS: According to our summary, the main way in which ferroptosis mediates the gut-liver-brain axis is oxidative stress, and the key cross-talk of ferroptosis affecting signaling pathway network is Nrf2/HO-1. However, there were no specific marker between different organ axes mediate by ferroptosis. SIGNIFICANCE: Our study illustrates the main ways and key cross-talk of ferroptosis mediating the gut-liver-brain axis, providing a basis for future research.

Evaluation of different types of adjuvants in a malaria transmission-blocking vaccine.

Adjuvants are critical components for vaccines, which enhance the strength and longevity of the antibody response and influence the types of immune response. Limited research has been conducted on the immunogenicity and protective efficacy of various adjuvants in malaria transmission-blocking vaccines (TBVs). In this study, we formulated a promising TBV candidate antigen, the P. berghei ookinete surface antigen PSOP25, with different types of adjuvants, including the TLR4 agonist monophosphoryl lipid A (MPLA), the TLR9 agonist cytosine phosphoguanosine oligodeoxynucleotides (CpG ODN 1826) (CpG), a saponin adjuvant QS-21, aluminum hydroxide (Alum), and two combination adjuvants MPLA + QS-21 and QS-21 + CpG. We demonstrated that adjuvanted vaccines results in elevated elicited antibody levels, increased proliferation of plasma cells, and efficient formation of germinal centers (GCs), leading to enhanced long-term protective immune responses. Furthermore, CpG group exhibited the most potent inhibition of ookinete formation and transmission-blocking activity. We found that the rPSOP25 with CpG adjuvant was more effective than MPLA, QS-21, MPLA + QS-21, QS-21 + CpG adjuvants in dendritic cells (DCs) activation and differentiation. Additionally, the CpG adjuvant elicited more rubust immune memory response than Alum adjuvant. CpG and QS-21 adjuvants could activate the Th1 response and promote the secretion of IFN-γ and TNF-α. PSOP25 induced a higher number of Tfh cells in splenocytes when combined with MPLA, CpG, and QS-21 + CpG; and there was no increase in these cell populations when PSOP25 was administered with Alum. In conclusion, CpG may confer enhanced efficacy for the rPSOP25 vaccine, as evidenced by the ability of the elicited antisera to induce protective immune responses and improved transmission-blocking activity.

In silico prediction of ocular toxicity of compounds using explainable machine learning and deep learning approaches.

The accurate identification of chemicals with ocular toxicity is of paramount importance in health hazard assessment. In contemporary chemical toxicology, there is a growing emphasis on refining, reducing, and replacing animal testing in safety evaluations. Therefore, the development of robust computational tools is crucial for regulatory applications. The performance of predictive models is heavily reliant on the quality and quantity of data. In this investigation, we amalgamated the most extensive dataset (4901 compounds) sourced from governmental GHS-compliant databases and literature to develop binary classification models of chemical ocular toxicity. We employed 12 molecular representations in conjunction with six machine learning algorithms and two deep learning algorithms to create a series of binary classification models. The findings indicated that the deep learning method GCN outperformed the machine learning models in cross-validation, achieving an impressive AUC of 0.915. However, the top-performing machine learning model (RF-Descriptor) demonstrated excellent performance with an AUC of 0.869 on the test set and was therefore selected as the best model. To enhance model interpretability, we conducted the SHAP method and attention weights analysis. The two approaches offered visual depictions of the relevance of key descriptors and substructures in predicting ocular toxicity of chemicals. Thus, we successfully struck a delicate balance between data quality and model interpretability, rendering our model valuable for predicting and comprehending potential ocular-toxic compounds in the early stages of drug discovery.

A thematic review on therapeutic toys and games for the elderly with Alzheimer's disease.

PURPOSE: Alzheimer's disease (AD) is a common and devastating neurological ailment that affects millions of the elderly worldwide. Therapeutic toys and games have emerged as potential non-pharmacological interventions for AD. However, despite a growing number of documents on the subject, research on the future direction of therapeutic toys and games for AD remains scarce. To address this gap, this study aims to (1) map the future trends of therapeutic toys and games for AD and (2) identify the categories and design characteristics. MATERIALS AND METHODS: Using a thematic review framework, a systematic literature search was conducted in two electronic databases (Scopus and WoS) using established criteria. Thematic analysis was done using ATLAS.ti 23 to identify prominent themes, patterns and trends. RESULTS: A total of 180 documents were found. Twenty-five articles met the inclusion criteria. A thematic review of these 25 articles identified 13 initial codes, which were been clustered into four themes: detection and evaluation; intervention; toy/game category; and design characteristics. The word "Cognitive" appears most frequently in documents according to word cloud. CONCLUSIONS: Therapeutic toys and games are used to detect and as an intervention for AD. Most of the current studies focused on specific cognitive functions. More research is needed about play therapy for neuropsychiatric symptoms. This thematic review also proposed a conceptual framework for designing toys and games tailored to the needs of the elderly with AD, offering valuable insights to future researchers focusing on this domain.

Most studies focused on cognitive function among Alzheimer's patients.More research is needed about the rehabilitation of neuropsychiatric symptoms among Alzheimer's patients.Games and toys have been evaluated as beneficial for detecting and as an intervention for Alzheimer's disease (AD). More research is needed about how to design games or toys tailored to the needs of the elderly with AD.

Multi-functional carbon nanotube encapsulated by covalent organic frameworks for lithium-sulfur chemistry and photothermal electrocatalysis.

It is significant to tailor multifunctional electrode materials for storing sustainable energy in lithium-sulfur (Li-S) batteries and converting intermittent solar energy into H2, facilitated by electricity. In this context, COF-1@CNT obtained through interfacial interaction fulfilled both requisites via post-functionalization. Upon integrating COF-1@CNT with S as the cathode for Li-S batteries, the system exhibited an initial discharge capacity of 1360 mAh g-1. Subsequently, it maintained a sustained actual capacity even after undergoing 200 charge-discharge cycles at 0.5C. The performance improvement was attributed to the optimized conductivity due to the addition of carbon nanotubes (CNTs). Furthermore, the synergistic interaction between the nitrogen of COF-1 and lithium mitigated the shuttle effect in Li-S batteries. In the modified three-electrode electrolytic cell system, COF-1@CNT-Ru produced by COF-1@CNT with RuCl3 showed better electrochemical reactivity for photothermal-assisted hydrogen evolution reaction (HER). This effect was demonstrated by reducing the overpotential to 140 mV relative to the no-photothermal condition (180 mV) at a current density of 10 mA cm-2. This study marked the first simultaneous application of covalent organic frameworks (COFs) based materials in Li-S batteries and photothermal-assisted electrocatalysts. The modified electrocatalytic system held promise as a novel avenue for exploring solar thermal energy utilization.

NiFeP nanosheets for efficient and durable hydrazine-assisted electrolytic hydrogen production.

Hydrazine-assisted electrochemical water splitting is an important avenue toward low cost and sustainable hydrogen production, which can significantly reduce the voltage of electrochemical water splitting. Herein, we took a simple approach to fabricate NiFeP nanosheet arrays on nickel foam (NiFeP/NF), which exhibit superior electrocatalytic activity for the hydrogen evolution reaction (HER) and the hydrazine oxidation reaction (HzOR). Our investigations revealed that the excellent electrocatalytic activity of NiFeP/NF mainly arises from the bimetallic synergistic effect, abundant electrocatalytically active sites facilitated by the porous nanosheet morphology, high intrinsic conductivity of NiFeP/NF and strong NiFeP-NF adhesion. We assembled a hydrazine-boosted electrochemical water splitting cell using NiFeP/NF as a bifunctional catalyst for both electrodes, and the overall hydrazine splitting (OHzS) exhibits a considerably low overpotential (100 mV at 10 mA cm-2), and is stable for 40 h continuous electrolysis in a 1 M KOH + 0.5 M N2H4 electrolyte. When it is applied to hydrogen production by seawater electrolysis, its catalytic activity shows strong tolerance. This work provides a promising approach for low cost, high-efficiency and stable hydrogen production based on hydrazine-assisted electrolytic seawater splitting for future applications.

Strong and tough polysaccharide organohydrogels for strain, humidity and temperature sensors.

To avoid the potential toxicity of monomer residues in synthetic polymer based organohydrogels, natural polysaccharide-based organohydrogels are expected to be used in multi-functional wearable sensory systems, but most of them have unsatisfactory stiffness, strength and fracture toughness. Herein, a cooking and soaking strategy is proposed to prepare novel natural polysaccharide-based organohydrogels possessing outstanding stiffness, strength, toughness, freezing resistance, heating resistance and long-term durability. The agar organohydrogel exhibits a fracture stress of 3.3 MPa, a Young's modulus of 2.26 MPa and a fracture toughness of 14.8 kJ m-2, the κ-carrageenan organohydrogel exhibits a fracture stress of 3.3 MPa, a Young's modulus of 4.34 MPa and a fracture toughness of 11.0 kJ m-2, and the gellan organohydrogel exhibits a fracture stress of 1.2 MPa, a Young's modulus of 2.81 MPa and a fracture toughness of 5.4 kJ m-2. Furthermore, the agar organohydrogels are assembled into multi-functional wearable sensors by introducing NaCl as a conducting agent exhibiting responses to strain (5-150%), temperature (-15 to 60 °C) and humidity (11-97%), and possessing exceptional multi-sensory capabilities. Therefore, the developed strategy has shown a new pathway towards strengthening polysaccharide-based organohydrogels with potential for application in wearable sensory systems.

AptaDB: a comprehensive database integrating aptamer-target interactions.

Aptamers have emerged as research hotspots of the next generation due to excellent performance benefits and application potentials in pharmacology, medicine, and analytical chemistry. Despite the numerous aptamer investigations, the lack of comprehensive data integration has hindered the development of computational methods for aptamers and the reuse of aptamers. A public access database named AptaDB, derived from experimentally validated data manually collected from the literature, was hence developed, integrating comprehensive aptamer-related data, which include six key components: (i) experimentally validated aptamer-target interaction information, (ii) aptamer property information, (iii) structure information of aptamer, (iv) target information, (v) experimental activity information, and (vi) algorithmically calculated similar aptamers. AptaDB currently contains 1350 experimentally validated aptamer-target interactions, 1230 binding affinity constants, 1293 aptamer sequences, and more. Compared to other aptamer databases, it contains twice the number of entries found in available databases. The collection and integration of the above information categories is unique among available aptamer databases and provides a user-friendly interface. AptaDB will also be continuously updated as aptamer research evolves. We expect that AptaDB will become a powerful source for aptamer rational design and a valuable tool for aptamer screening in the future. For access to AptaDB, please visit http://lmmd.ecust.edu.cn/aptadb/.

State Estimation for Recurrent Neural Networks With Intermittent Transmission.

This work addresses the state estimation problem for recurrent neural networks over capacity-constrained communication channels. The intermittent transmission protocol is used to reduce the communication load, where a stochastic variable with a given distribution is used to describe the transmission interval. A corresponding transmission interval-dependent estimator is designed, and an estimation error system based on it is also derived, whose mean-square stability is proved by constructing an interval-dependent function. By analyzing the performance in each transmission interval, sufficient conditions of the mean-square stability and the strict (Q,S,R) - γ -dissipativity are established for the estimation error system. Finally, the correctness and the superiority of the developed result are illustrated by a numerical example.

GIPR Agonism Enhances TZD-Induced Insulin Sensitivity in Obese IR Mice.

Recent studies have found that glucose-dependent insulinotropic polypeptide receptor (GIPR) agonism can enhance the metabolic efficacy of glucagon-like peptide-1 receptor agonist treatment by promoting both weight-dependent and -independent improvements on systemic insulin sensitivity. These findings have prompted new investigations aimed at better understanding the broad metabolic benefit of GIPR activation. Herein, we determined whether GIPR agonism favorably influenced the pharmacologic efficacy of the insulin-sensitizing thiazolidinedione (TZD) rosiglitazone in obese insulin-resistant (IR) mice. Genetic and pharmacological approaches were used to examine the role of GIPR signaling on rosiglitazone-induced weight gain, hyperphagia, and glycemic control. RNA sequencing was conducted to uncover potential mechanisms by which GIPR activation influences energy balance and insulin sensitivity. In line with previous findings, treatment with rosiglitazone induced the mRNA expression of the GIPR in white and brown fat. However, obese GIPR-null mice dosed with rosiglitazone had equivalent weight gain to that of wild-type (WT) animals. Strikingly, chronic treatment of obese IR WT animals with a long-acting GIPR agonist prevented rosiglitazone-induced weight-gain and hyperphagia, and it enhanced the insulin-sensitivity effect of this TZD. The systemic insulin sensitization was accompanied by increased glucose disposal in brown adipose tissue, which was underlined by the recruitment of metabolic and thermogenic genes. These findings suggest that GIPR agonism can counter the negative consequences of rosiglitazone treatment on body weight and adiposity, while improving its insulin-sensitizing efficacy at the same time.

XGraphCDS: An explainable deep learning model for predicting drug sensitivity from gene pathways and chemical structures.

Cancer is a highly complex disease characterized by genetic and phenotypic heterogeneity among individuals. In the era of precision medicine, understanding the genetic basis of these individual differences is crucial for developing new drugs and achieving personalized treatment. Despite the increasing abundance of cancer genomics data, predicting the relationship between cancer samples and drug sensitivity remains challenging. In this study, we developed an explainable graph neural network framework for predicting cancer drug sensitivity (XGraphCDS) based on comparative learning by integrating cancer gene expression information and drug chemical structure knowledge. Specifically, XGraphCDS consists of a unified heterogeneous network and multiple sub-networks, with molecular graphs representing drugs and gene enrichment scores representing cell lines. Experimental results showed that XGraphCDS consistently outperformed most state-of-the-art baselines (R2 = 0.863, AUC = 0.858). We also constructed a separate in vivo prediction model by using transfer learning strategies with in vitro experimental data and achieved good predictive power (AUC = 0.808). Simultaneously, our framework is interpretable, providing insights into resistance mechanisms alongside accurate predictions. The excellent performance of XGraphCDS highlights its immense potential in aiding the development of selective anti-tumor drugs and personalized dosing strategies in the field of precision medicine.