Innovative Strategies Research Articles

Are Good Deeds Rewarded?—The Impact of Traditional Morality and Modern Responsibility on Green Innovation

The essence of intergenerational sustainability emphasizes the necessity of incorporating altruistic thinking and culture. While prior studies primarily examined corporate innovation strategies from a self-interested lens, this paper aims to investigate the drivers of corporate green innovation from an altruistic perspective. Analyzing a sample of Chinese A-share listed companies from 2011 to 2019, we employ both the OLS model and the mediation effect model to explore how traditional morality and modern responsibility impact corporate green innovation, as well as the mechanisms underlying this relationship. Our findings reveal that both traditional morality and modern responsibility significantly enhance corporate green management innovation, with social trust serving as a key mediating factor. Furthermore, traditional morality and modern responsibility play distinctive roles depending on the stage of economic development: traditional morality primarily influences green innovation in the early stages of economic development, whereas modern responsibility becomes more influential as development progresses. This study provides meaningful insights for research and practice in corporate sustainability, business ethics, and innovation strategy.

IMMU-35. TARGETING THE AHR IMMUNOMETABOLIC HUB DURING VIROIMMUNOTHERAPY OF GLIOMAS

Abstract Glioblastoma (GBM) poses a significant therapeutic challenge in oncology. Recent clinical trials have shown the feasibility of virotherapy to treat patients with GBM. Our laboratory developed an oncolytic adenovirus termed Delta-24-RGD that has been tested in clinical trials for recurrent GBM patients with encouraging results (NCT00805376, NCT02798406). These clinical studies, together with preclinical data, showed that the efficacy of Delta-24-RGD was due to direct tumor cell oncolysis and indirect activation of anti-tumor immune response. To further leverage this immune component, our group generated Delta-24-RGDOX, an armed version of Delta-24-RGD expressing the T-cell activator OX40-L, which exhibits a superior anti-cancer effect. In this project, we aim to further boost the effectiveness of Delta-24-RGDOX by targeting factors that maintain the immunosuppressive characteristic of gliomas. Specifically, we identified the environmental sensor and transcription factor Aryl Hydrocarbon Receptor (AhR) as one of the immunosuppressive factors. We show that AhR is overexpressed in GBM surgical specimens compared to healthy brain tissue, and high AhR expression correlates with poorer survival in glioma patients. Immunofluorescence staining of glioma cells treated with Delta-24-RGDOX demonstrated that AhR translocates to the nucleus, and qPCR showed that translocation resulted in the enhanced transcription of AhR-responsive elements. Additionally, bulk RNA-seq reveals that in vivo glioma models treated with Delta-24-RGDOX exhibit activation of the AhR pathway network. This unexpected and paradoxical activation may be responsible for immune suppression mechanisms, which might hinder the effect of Delta-24-RGDOX. Based on these data, we combined two innovative strategies, the oncolytic virus Delta-24-RGDOX and AhR inhibitors. Survival analysis in immunocompetent models of gliomas treated with this combined therapy showed the greatest therapeutic benefit compared to monotherapy controls. These findings highlight the critical role of AhR activation triggered by Delta-24-RGDOX and position AhR as a potential therapeutic target for enhancing the efficacy of oncolytic adenovirus therapy in GBM.

Gene Therapy in Cardiovascular Disease: Recent Advances and Future Directions in Science: A Science Advisory From the American Heart Association.

Cardiovascular disease remains the foremost cause of morbidity and mortality globally, affecting millions of individuals. Recent discoveries illuminate the substantial role of genetics in cardiovascular disease pathogenesis, encompassing both monogenic and polygenic mechanisms and identifying tangible targets for gene therapies. Innovative strategies have emerged to rectify pathogenic variants that cause monogenic disorders such as hypertrophic, dilated, and arrhythmogenic cardiomyopathies and hypercholesterolemia. These include delivery of exogenous genes to supplement insufficient protein levels caused by pathogenic variants or genome editing to correct, delete, or modify mutant sequences to restore protein function. However, effective delivery of gene therapy to specified cells presents formidable challenges. Viral vectors, notably adeno-associated viruses and nonviral vectors such as lipid and engineered nanoparticles, offer distinct advantages and limitations. Additional risks and obstacles remain, including treatment durability, tissue-specific targeting, vector-associated adverse events, and off-target effects. Addressing these challenges is an ongoing imperative; several clinical gene therapy trials are underway, and many more first-in-human studies are anticipated. This science advisory reviews core concepts of gene therapy, key obstacles, patient risks, and ongoing research endeavors to enable clinicians to understand the complex landscape of this emerging therapy and its remarkable therapeutic potential to benefit cardiovascular disease.

Room for Change: Rural Low-Barrier Housing Policy and Program Models for People with Substance Use and Mental Health Comorbidities

Rural North American communities experience disproportionate burdens of housing instability and toxic drug poisonings. These regions face complex intersections of homelessness, substance use, and mental health issues, and innovative strategies are required to effectively address these crises. In British Columbia, Canada, new funding opportunities to address rural homelessness for complex populations have come after a lag in available resources. Complex Care Housing is a model aimed at filling gaps in the current housing and care continuum for people with mental health and substance use challenges. Due to rural-specific social characteristics, new housing models require ongoing evaluation to ensure programs meet the quality and fidelity of gold standard Housing First programs that upload the tenets of harm reduction and person-centeredness.

Leveraging TikTok and Technology-Enhanced Peer Assessment

Technology-enhanced learning (TEL) is a crucial element of contemporary higher education. This Pecha Kucha explores innovative TEL strategies to enhance student engagement and self-directed learning. This abstract outlines a technologically innovative education design in an Australian university’s commerce course. Within this course, students created TikTok videos to promote awareness of the United Nations Sustainable Development Goals (UN SDGs). The selection of TikTok as the social media tool of choice was informed by its demographic alignment, with 36.7% of its users aged 18 to 24 (Statista Search Department, 2024). The efficacy of short-form video content in fostering engagement, particularly among higher education students, is well-documented (Wong, 2023; Perez et al., 2023). Moreover, Khechine et al.’s (2020) research shows that the adoption of social media tools in education promotes the value of enjoyment and interest in performing an activity, thereby fostering intrinsic motivation - a critical determinant of effective learning (Ryan & Deci, 2000). Students also engaged in peer assessment of their TikTok videos, which centred on the creation of TikTok content tailored for first-year students. Given that the assessors themselves belonged to the first-year cohort, they were deemed to possess an inherent understanding of the target audience. Thus, they were best positioned to evaluate whether TikTok videos communicate the information clearly and stimulate audience’s interest and engagement. Peer assessment is reflexive and allows students to apply learning by assessing in the current context (Bloxham & West, 2004). Li et al. (2020) suggest peer review of assessment leads to significantly improved assessment performance. It also promotes ownership and accountability, encouraging self-directed learning (Ryan & Deci, 2020). Qualtrics, a technology platform, was employed to collect and collate evaluation scores to facilitate the peer assessment process. The peer assessment used Qualtrics with rubric sliders, thereby emulating the evaluative framework typically employed by instructors. This approach adhered to best practices in TEL (Chernikova et al., 2020). Qualtrics also provides additional advantages, including streamlining score collection from large student groups and efficiently generate descriptive statistics to examine whether students give higher scores to their own groups compared to others, and whether there's more variability in scores for their own group versus peer groups (Bloxham & West, 2020). Promoting UN SDGs using TikTok successfully supported TEL and enhanced self-directed learning. The course engagement score has increased by 9 basis points from the previous teaching period. Some examples of student feedback included: “Rehearsing for the video and interviewing students was fun and insightful.” “I was genuinely curious about the university’s sustainability approaches.” “TikTok makes learning about real-life UN SDG efforts approachable.” “Watching other students' TikTok videos was interesting.” Feedback from the teaching team also suggests the quality of the videos were well-reflected in the peer assessment scores. This Pecha Kucha presents an innovative education design that leverages TikTok and peer assessment to boost engagement. It provides a valuable model for academics seeking to integrate TEL strategies within their disciplines, like performing arts and medicine (Nicolaou et al., 2019; Cheston et al., 2013).

CNSC-01. PEDIATRIC GLIOMAS EXPRESS CIRCADIAN GENES AND DEMONSTRATE CIRCADIAN REGULATION OF TEMOZOLOMIDE SENSITIVITY

Abstract INTRODUCTION Pediatric high-grade gliomas (pHGG) are highly invasive brain tumors with dismal survival rates, prompting the need for innovative therapeutic strategies. Previous research in adult glioblastoma patients revealed a correlation between the timing of Temozolomide administration and patient survival. There has, however, been limited exploration into circadian gene expression in pediatric gliomas. In this study, we investigate whether pHGGs exhibit rhythmic expression of circadian genes and whether the timing of drug administration influences Temozolomide sensitivity. METHODS A bioinformatics approach, immunocytochemistry and immunoblotting were used to assess key circadian genes in low- and high-grade gliomas. We then used timed qPCR to assess rhythmic expression in BMAL1 and REV-ERBα, two key circadian genes, across 48 hours in our pHGG cells following dexamethasone cell synchronization. Lastly, we used CyQuant Proliferation Assays to examine the effects of Temozolomide applied at peaks versus troughs in BMAL1 expression. RESULTS Using data from PedcBioPortal, we found significantly higher expression of BMAL1 in pHGGs compared to pLGGs (0.349 + 1.05 vs 0.0545 + 0.666, p < 0.001). We identified cellular localization of BMAL1 and REV-ERBα in pHGGs along with rhythmic expression of BMAL1 and REV-ERBα in our three pHGGs primary cell cultures across 48 hours (JTK_CYCLE, p < 0.005). Lastly, we demonstrated a chronotherapeutic response to Temozolomide in two of our pHGG cell lines, with significantly decreased proliferation when treatment occurred at trough versus peak BMAL1 expression (p < 0.01). CONCLUSION In this study, we found that circadian genes BMAL1 and REV-ERBα are expressed in pHGGs and expression patterns differ between pHGGs versus pLGGs. Circadian gene expression is rhythmic in pHGGs, and pHGGs can have differential Temozolomide-sensitivity based on circadian cycles. These findings suggest that circadian timing of chemotherapy may influence the efficacy of treatment, and next steps will be to explore the mechanisms underlying circadian regulation of Temozolomide sensitivity.

An Innovative Attention-based Triplet Deep Hashing Approach to Retrieve Histopathology Images.

Content-based histopathology image retrieval (CBHIR) can assist in the diagnosis of different diseases. The retrieval procedure can be complex and time-consuming if high-dimensional features are required. Thus, hashing techniques are employed to address these issues by mapping the feature space into binary values of varying lengths. The performance of deep hashing approaches in image retrieval is often superior to that of traditional hashing methods. Among deep hashing approaches, triplet-based models are typically more effective than pairwise ones. Recent studies have demonstrated that incorporating the attention mechanism into a deep hashing approach can improve its effectiveness in retrieving images. This paper presents an innovative triplet deep hashing strategy based on the attention mechanism for retrieving histopathology images, called histopathology attention triplet deep hashing (HATDH). Three deep attention-based hashing models with identical architectures and weights are employed to produce binary values. The proposed attention module can aid the models in extracting features more efficiently. Moreover, we introduce an improved triplet loss function considering pair inputs separately in addition to triplet inputs for increasing efficiency during the training and retrieval steps. Based on experiments conducted on two public histopathology datasets, BreakHis and Kather, HATDH significantly outperforms state-of-the-art hashing algorithms.

MiR-630 as a therapeutic target in pancreatic cancer stem cells: modulation of the PRKCI-Hedgehog signaling axis.

MicroRNAs (miRNAs) are critical regulators of cancer progression, prompting our investigation into the specific function of miR-630 in pancreatic cancer stem cells (PCSCs). Analysis of miRNA and mRNA expression data in PCSCs revealed downregulation of miR-630 and upregulation of PRKCI, implying a potential role for miR-630 in PCSC function and tumorigenicity. Functional assays confirmed that miR-630 directly targets PRKCI, leading to the suppression of the Hedgehog signaling pathway and consequent inhibition of PCSC self-renewal and tumorigenicity in murine models. This study unveiled the modulation of the PRKCI-Hedgehog signaling axis by miR-630, highlighting its promising therapeutic potential for pancreatic cancer (PC) treatment. MiR-630 emerges as a pivotal regulator in PCSC biology, opening up new avenues for targeted interventions in PC. The inhibitory effect of miR-630 on PCSC behavior underscores its potential as a valuable therapeutic target, offering insights into innovative treatment strategies for this challenging disease.

RepID as a potential biomarker and therapeutic target for lung neuroendocrine tumor

Neuroendocrine tumor (NET) is a rare malignant tumor, notably small cell lung cancer (SCLC), a type of lung neuroendocrine tumor, which has a survival rate of less than 7%. Although various biomarkers including CHGA (Chromogranin A), INSM1 (Insulinoma-associated protein 1), and SYP (Synaptophysin) are extensively used for the diagnostic testing of NET, their diverse specificities and sensitivities are acknowledged as limitations. Here, we demonstrate that RepID (Replication initiation determinant protein), a component of CRL4 (Cullin-RING ubiquitin E3 ligase 4), holds promise as a biomarker for identifying NET and SCLC. Analysis of the Cancer Cell Line Encyclopedia (CCLE) via the CellMinerCDB portal reveals a high correlation between RepID transcript levels and mRNA expression of NE signature genes. Additionally, RepID protein is highly expressed in SCLC patient tissues and a subset of SCLC cell lines. Viability analysis following treatment with pevonedistat and SZL-P1-41 in SCLC cell lines and human SCLC-organoid models indicates that RepID expression determines the sensitivity to CRL-targeting anti-cancer drugs. These findings suggest that RepID represents a novel biomarker for NET and SCLC, and insights from RepID research in these cancers could lead to innovative therapeutic strategies.

TMIC-85. THE MECHANISM OF COMBINED HYDROGEN-CHEMICAL THERAPY BASED ON ACTIVE MAGNESIUM MICROMOTORS FOR INHIBITING GLIOBLASTOMA RECURRENCE BY MODULATING TUMOR MICROENVIRONMENT

Abstract OBJECTIVE This study aims to develop an innovative therapeutic strategy to prevent postoperative recurrence of Glioblastoma (GBM), a condition with poor prognosis and high recurrence rates. The focus is on exploring the efficacy of synergistic hydrogen-chemical therapy in inhibiting GBM recurrence, especially by reducing surgery-induced inflammation and enhancing the sensitivity of GBM cells to chemotherapy. METHODS The study employed the fabrication of Mg-Motor-DOX using a biodegradable polylactic acid-glycolic acid copolymer (PLGA) and gelatin containing Doxorubicin (DOX). The reaction of Mg with water produces hydrogen (H2), which aids in scavenging reactive oxygen species (ROS) and inflammation, alongside the specific release of chemotherapy drugs at the tumor site. A thermosensitive hydrogel was developed for in situ delivery of Mg-Motor-DOX to the tumor residual cavity. Additionally, RNA sequencing was used to study the transcriptional changes in the GBM tumor microenvironment (TME) induced by this therapy. RESULTS The study presents initial evidence of the in vivo efficacy of synergistic hydrogen-chemical therapy against GBM. The Mg-Motor-DOX mediated therapy not only scavenged ROS and reduced inflammation but also specifically released chemotherapy drugs at the tumor site, enhancing their effectiveness. RNA-Seq technology elucidated the molecular mechanisms underlying the therapy’s efficacy, revealing significant transcriptional changes in the GBM TME. CONCLUSION Synergistic hydrogen-chemical therapy, facilitated by Mg-Motor-DOX, shows promising potential in preventing the postoperative recurrence of GBM. This innovative approach effectively combines anti-inflammatory benefits and enhanced chemosensitivity, offering new strategies for GBM treatment. The molecular insights provided by RNA-Seq technology contribute to a deeper understanding of tumor treatment mechanisms, paving the way for future clinical applications.

Understanding American tegumentary leishmaniasis in urban Montes Claros, Brazil: insights from clinical, immunological and therapeutic investigations.

The challenge of American tegumentary leishmaniasis (ATL) continues in Brazil, presenting a persistent public health issue despite initiatives aimed at public outreach, vector control and health education. To gain a deeper understanding of this disease, a study was conducted in an endemic region located in the northern region of the state of Minas Gerais, Brazil. The study monitored 30 resident patients diagnosed with ATL, using serum samples from 6 healthy individuals as controls. The localized cutaneous form of the disease was found to be predominant, with lesions appearing on various parts of the body and the majority of the affected individuals being male. The study found significantly higher levels of IgG anti-α-Gal antibodies in ATL-infected patients compared to healthy individuals. Treatment of 19 patients with meglumine antimoniate resulted in limited improvement in symptoms for most. Nonetheless, the study found that 12 patients who completed treatment with epithelialization of the lesions showed a significant decrease in IgG anti-α-Gal antibodies, indicating potential applications of this antibody in the diagnosis and monitoring of the disease. The study also identified Leishmania species in 7 analysed patients, revealing 6 cases infected by Leishmania braziliensis and 1 by L. infantum, with a significant difference in the anti-α-Gal responses. The findings of the study emphasize the urgent need for the development of human vaccines and innovative treatment strategies adapted to the diversity of Leishmania species causing cutaneous leishmaniasis and individual patient responses to improve the clinical management of ATL in Brazil and similar endemic regions.

Harnessing Artificial Intelligence for Wildlife Conservation

The rapid decline in global biodiversity demands innovative conservation strategies. This paper examines the use of artificial intelligence (AI) in wildlife conservation, focusing on the Conservation AI platform. Leveraging machine learning and computer vision, Conservation AI detects and classifies animals, humans, and poaching-related objects using visual spectrum and thermal infrared cameras. The platform processes these data with convolutional neural networks (CNNs) and transformer architectures to monitor species, including those that are critically endangered. Real-time detection provides the immediate responses required for time-critical situations (e.g., poaching), while non-real-time analysis supports long-term wildlife monitoring and habitat health assessment. Case studies from Europe, North America, Africa, and Southeast Asia highlight the platform’s success in species identification, biodiversity monitoring, and poaching prevention. The paper also discusses challenges related to data quality, model accuracy, and logistical constraints while outlining future directions involving technological advancements, expansion into new geographical regions, and deeper collaboration with local communities and policymakers. Conservation AI represents a significant step forward in addressing the urgent challenges of wildlife conservation, offering a scalable and adaptable solution that can be implemented globally.

Enriching Educational Landscapes

As an arts educator, I spent a month in Bhutan engaging Bachelor of Education students in project-based learning activities aimed at enhancing creativity, critical thinking, and problem-solving skills. These activities served as a dynamic capstone to their theoretical literacy unit. I documented students' collaborative efforts and creativity through photos and videos, which have been transformed into eBooks. These resources are now integrated into courses at my Australian university, enriching learning experiences for our culturally diverse student body with authentic examples of cross-cultural project-based learning. The eBooks showcase student outcomes and offer reflective analyses to inform future teaching practices, inspiring innovative and collaborative learning strategies globally. Moreover, these resources contribute to the university's commitment to global education and cultural diversity, demonstrating how experiential learning can transcend geographical boundaries and enrich the educational journey of students promoting global citizenship. To address a broader audience within Bhutan, and globally, the lesson plans and resources I developed to deliver the project-based learning activities, are now available on the Artist in Residence Education Program website. This provides an opportunity for any educator to access and adapt these materials to their own contexts. Teaching in Bhutan highlighted how factors like collectivist culture, religious beliefs, and the Gross National Happiness Index support traditional teaching practices and how complex it is to break down traditional teaching practises and encourage valid creative ways learning. The students greatly enjoyed the new activities and even requested additional lessons. It was rewarding to see them realise their potential for creativity and innovation in teaching, enhancing their approach to learning and self-perception as future educators. In conclusion, understanding sociocultural norms in Bhutan offers a wealth of insights that can inspire and inform academic approaches to teaching in countries with traditional forms of education and limited access to resources.

State-of-the-art therapy and innovative treatment strategies in esophageal squamous cell cancer

SummaryRecent advances in the development of new therapeutic agents and the execution of numerous randomized controlled trials have changed the landscape of systemic therapy approaches in patients with esophageal squamous cell cancer (ESCC). Particularly the inclusion of immunotherapy permits clinicians to improve patient management in multiple settings. This review gives an overview of standard-of-care treatment and sheds light on new therapeutic options, recently approved treatments, and ongoing trials.

Prophylactic and therapeutic vaccine development: advancements and challenges.

Biomedical research is fundamental in developing preventive and therapeutic vaccines, serving as a cornerstone of global public health. This review explores the key concepts, methodologies, tools, and challenges in the vaccine development landscape, focusing on transitioning from basic biomedical sciences to clinical applications. Foundational disciplines such as virology, immunology, and molecular biology lay the groundwork for vaccine creation, while recent innovations like messenger RNA (mRNA) technology and reverse vaccinology have transformed the field. Additionally, it highlights the role of pharmaceutical advancements in translating lab discoveries into clinical solutions. Techniques like CRISPR-Cas9, genome sequencing, monoclonal antibodies, and computational modeling have significantly enhanced vaccine precision and efficacy, expediting the development of vaccines against infectious diseases. The review also discusses challenges that continue to hinder progress, including stringent regulatory pathways, vaccine hesitancy, and the rapid emergence of new pathogens. These obstacles underscore the need for interdisciplinary collaboration and the adoption of innovative strategies. Integrating personalized medicine, nanotechnology, and artificial intelligence is expected to revolutionize vaccine science further. By embracing these advancements, biomedical research has the potential to overcome existing challenges and usher in a new era of therapeutic and prophylactic vaccines, ultimately improving global health outcomes. This review emphasizes the critical role of vaccines in combating current and future health threats, advocating for continued investment in biomedical science and technology.

Effects of a Virtual Trauma Clinic on admissions and length of stay for minor to moderate trauma.

To investigate the feasibility of a Virtual Trauma Clinic (VTC) for patients with minor to moderate trauma, and evaluate patient satisfaction and outcomes. One hundred VTC patients were matched 1:1 with historical patients from the hospital trauma registry who received conventional care. Matching was based on age ± 5 years, sex, mechanism of injury, Injury Severity Score ± 2, trauma team activation and day of week of presentation. VTC patients were sent surveys on experience and outcome measures. VTC was associated with reduced average hospital length of stay for admitted patients by 1.81 days (95% CI = -2.82, -0.79; P = 0.001) and reduced hospital admissions (odds ratio 0.26; 95% CI = 0.14, 0.48; P < 0.001). There was an avoidance of 199 inpatient bed days in total, with no trauma-related readmissions within 30 days post-hospital discharge. 92% of respondents (n = 22) rated the care they received from VTC as excellent or good. Patient-reported outcome surveys showed overall improvement in functional domains but evidence of ongoing disability, with persistent issues of pain and psychological distress at 1 month post-injury. Patients with minor to moderate trauma have ongoing care needs with high rates of pain, psychological distress and disability remaining prevalent long after discharge. VTC provided an innovative strategy for hospital avoidance with high levels of patient satisfaction and no adverse effects on safety. The overall quality of care for these patients was enhanced through the provision of standardised, patient-centred and multidisciplinary follow-up.

L-aspartate ameliorates diet-induced obesity by increasing adipocyte energy expenditure.

Obesity always leads to profound perturbation of metabolome. Metabolome studies enrich the knowledge on associations between endogenous metabolites and obesity, potentially providing innovative strategies for the development of novel anti-obesity pharmacotherapy. This study aims to identify an endogenous metabolite that regulates energy expenditure and to explore its application for obesity treatment. C57BL/6 mice were fed with a high-fat and high-cholesterol (HFC) diet, comprising 60% fat and 1.2% cholesterol, for 12 weeks to induce obesity. Significant metabolites were identified in the livers of both health and obese mice through comparative hepatic metabolomics analysis. Correlation between serum or adipose L-aspartate level and body weight in obese mice, as well as human body mass index (BMI), was evaluated. In addition, saline or 200 mg/kg L-aspartate was orally administrated to HFC diet mice and HFC diet-induced obese mice for 6-7 weeks. Body weight, adipose tissue weight, glucose tolerance and liver damage were assessed to evaluate the effect on obesity prevention and treatment. Comprehensive lab animal monitoring system (CLAMS) and seahorse assay were employed to investigate the regulatory effect of L-aspartate on energy metabolism in vivo and in vitro, respectively. 3T3-L1 preadipocytes and murine white adipose tissue (WAT) were utilized to examine the impact of L-aspartate on adipocyte adipogenesis and lipogenesis and cellular signalling pathway in vitro and in vivo. L-aspartate, an approved drug for liver injury and chronic fatigue, was identified as an endogenous inducer of energy expenditure. Serum or adipose L-aspartate levels were found to be negatively correlated with the severity of obesity in both humans and mice. Administration of L-aspartate to HFC diet mice led to a significant reduction in body weight, with decreases of 14.5% in HFC diet mice and 8.5% in HFC diet-induced obese mice, respectively. In addition, the treatment improved related metabolic syndrome (Figure 2 and Figure S3). These therapeutics were associated with enhancements in whole-body energy expenditure and suppression of adipocyte adipogenesis along with activation of Adenosine 5'-monophosphate-activated protein kinase (AMPK) signalling pathway. L-aspartate may serve as a novel endogenous inducer of energy expenditure and suppressor of adipogenesis and lipogenesis along with activation of AMPK, thereby offering a promising therapeutic strategy for obesity prevention and treatment.

Microbiome-producing SCFAs are associated with preterm birth via trophoblast function modulation.

Preterm birth (PTB) is a leading cause of infant mortality and long-term health issues, affecting millions of families worldwide. Despite its prevalence, the exact causes of PTB remain unclear. Our study reveals that certain bacteria and their metabolic byproducts in the cervicovaginal environment, specifically short-chain fatty acids (SCFAs), are linked to the risk of preterm birth. By analyzing samples from pregnant women, we found that an imbalance in the vaginal microbiota and increased levels of SCFAs are associated with changes in cells that can lead to early labor. This research provides new insights into how the microbiome influences pregnancy outcomes and highlights potential biomarkers for predicting preterm birth. Understanding these microbial influences could lead to innovative strategies for early diagnosis and prevention, ultimately improving maternal and infant health.

DDDR-36. LOOKING AROUND THE CORNER: PREDICTING SYNERGY OR FUTILITY TO COMBINATION OF ARSENIC TRIOXIDE PLUS MNK1 INHIBITORS IN GLIOBLASTOMA

Abstract Glioblastoma (GBM) is the most prevalent type of malignant tumor within the central nervous system. The five-year survival rate of 6.8% highlights the challenges inherent to exceptionally heterogeneous tumors that grow behind the blood brain barrier. The protracted dearth in new agents approved for GBM begs innovative strategies by which to approach clinical trials. Arsenic trioxide (ATO) is the standard of care for myelodysplasia and relapsed or refractory acute promyelocytic leukemia. ATO has an idiopathic mechanism of action, but has shown beneficial effects in other solid tumors. Across six GBM PDX models a 10-fold difference in sensitivity manifests, indicative of underlying innate sensitivity or resistance to ATO. This resistance has been previously shown to correlate with MNK1 expression. In order to sensitize PDX models innately resistant to ATO we utilized combination therapy with the MNK1 inhibitor AUM001 (AUM Biosciences, Singapore; NCT05462236). In high MNK1 expressing PDX models the combination of ATO + AUM001 induces cytotoxic synergy. Additionally, when narrowly measuring effects on the glioma stem cell population (ELDA), strong synergy was observed in models, including those failing to show such using bulk cell population viability assay. GSEA analysis revealed differential high enrichment in gene sets related to oxidative phosphorylation in the models failing to show synergy. Such criteria could act as exclusionary criteria (futility) for clinical trials by excluding such putative non-responder patients from the treatment population. Synergistic models showed enrichment in gene sets related to epithelial/mesenchymal transition, skeletal and sensory organ development, and regionalization. These signatures could serve to prioritize patient inclusion in clinical trials of ATO in combination with AUM001, enriching the fraction of responsive glioma patients. Such molecular signatures may bring precision medicine in early-stage clinical trials to advance promising new agents and combinations of agents to full FDA approval.

Federated Learning : A Paradigm Shift in Collaborative Machine Learning

Federated learning (FL) has emerged as an exceptionally promising method within the realm of machine learning, enabling multiple entities to jointly train a global model while maintaining decentralized data. This paper presents a comprehensive review of federated learning methodologies, applications, and challenges. We begin by elucidating the fundamental concepts underlying FL, including federated optimization algorithms, communication protocols, and privacy-preserving techniques. Subsequently, we delve into various domains where FL has found significant traction, examples include healthcare, finance, and the Internet of Things (IoT), showcasing successful deployments and innovative strategies. Furthermore, we discuss the inherent challenges associated with federated learning, such as communication overhead, heterogeneity of data sources, and privacy concerns, and explore state- of-the-art solutions proposed in literature. Finally, we outline future research directions in federated learning, including advancements in privacy-preserving techniques, scalability improvements, and extension of FL to emerging domains. This thorough examination provides a valuable asset for researchers, practitioners, and policymakers keen on grasping the panorama of federated learning and its ramifications for collaborative machine learning in dispersed settings.