Landscape Analysis Research Articles

Genomic landscape of hepatocellular carcinoma in Egyptian patients by whole exome sequencing

BackgroundHepatocellular carcinoma (HCC) is the most common primary liver cancer. Chronic hepatitis and liver cirrhosis lead to accumulation of genetic alterations driving HCC pathogenesis. This study is designed to explore genomic landscape of HCC in Egyptian patients by whole exome sequencing.MethodsWhole exome sequencing using Ion Torrent was done on 13 HCC patients, who underwent surgical intervention (7 patients underwent living donor liver transplantation (LDLT) and 6 patients had surgical resection}.ResultsMutational signature was mostly S1, S5, S6, and S12 in HCC. Analysis of highly mutated genes in both HCC and Non-HCC revealed the presence of highly mutated genes in HCC (AHNAK2, MUC6, MUC16, TTN, ZNF17, FLG, MUC12, OBSCN, PDE4DIP, MUC5b, and HYDIN). Among the 26 significantly mutated HCC genes—identified across 10 genome sequencing studies—in addition to TCGA, APOB and RP1L1 showed the highest number of mutations in both HCC and Non-HCC tissues. Tier 1, Tier 2 variants in TCGA SMGs in HCC and Non-HCC (TP53, PIK3CA, CDKN2A, and BAP1). Cancer Genome Landscape analysis revealed Tier 1 and Tier 2 variants in HCC (MSH2) and in Non-HCC (KMT2D and ATM). For KEGG analysis, the significantly annotated clusters in HCC were Notch signaling, Wnt signaling, PI3K-AKT pathway, Hippo signaling, Apelin signaling, Hedgehog (Hh) signaling, and MAPK signaling, in addition to ECM-receptor interaction, focal adhesion, and calcium signaling. Tier 1 and Tier 2 variants KIT, KMT2D, NOTCH1, KMT2C, PIK3CA, KIT, SMARCA4, ATM, PTEN, MSH2, and PTCH1 were low frequency variants in both HCC and Non-HCC.ConclusionOur results are in accordance with previous studies in HCC regarding highly mutated genes, TCGA and specifically enriched pathways in HCC. Analysis for clinical interpretation of variants revealed the presence of Tier 1 and Tier 2 variants that represent potential clinically actionable targets. The use of sequencing techniques to detect structural variants and novel techniques as single cell sequencing together with multiomics transcriptomics, metagenomics will integrate the molecular pathogenesis of HCC in Egyptian patients.

Integrated Transportation Case: Planning of Future Transport Infrastructure/Connectivity In Dar es Salaam

Urbanization poses significant challenges to transportation systems in rapidly growing cities like Dar es Salaam. This paper examines the potential of Bus Rapid Transit (BRT) and Intelligent Transport Systems (ITS) to address transportation issues in the Ilala municipality. Despite ongoing infrastructure projects, the city lacks a comprehensive master plan to support its projected growth. The research underscores the importance of integrating infrastructure improvements and ITS to optimize the BRT system in Ilala. The study begins with an analysis of the current transportation landscape, highlighting deficiencies in road networks and public transportation that lead to severe congestion and unreliable commutes. Key stakeholders are identified, and the necessity of their involvement in transportation planning is emphasized. The research questions focus on enhancing stakeholder engagement, integrating ITS, and improving road infrastructure design. A mixed-methods approach is employed, including literature reviews, case studies of successful BRT implementations worldwide, and primary data collection through interviews, surveys, and focus groups with various stakeholders. This comprehensive approach provides actionable insights for enhancing urban mobility in Ilala. Future recommendations include upgrading the BRT system to a Level 3 configuration, incorporating elevated BRT sections to separate bus lanes from other traffic, and optimizing the design of lanes, stations, and vehicles to improve efficiency. Additionally, the paper discusses the potential benefits of a well-implemented ITS, providing real-time information to commuters and enhancing overall transportation experience. By addressing these challenges, the research aims to improve the quality of life for Dar es Salaam residents, stimulate economic growth, and contribute to a more sustainable urban environment. The findings and recommendations offer a strategic framework for future transportation planning in Ilala and beyond

Development of prognostic model incorporating a ferroptosis/cuproptosis-related signature and mutational landscape analysis in muscle-invasive bladder cancer

BackgroundMuscle-invasive bladder cancer (MIBC) is a prevalent and aggressive malignancy. Ferroptosis and cuproptosis are recently discovered forms of programmed cell death (PCD) that have attracted much attention. However, their interactions and impacts on MIBC overall survival (OS) and treatment outcomes remain unclear.MethodsData from the TCGA-BLCA project (as the training set), cBioPortal database, and GEO datasets (GSE13507 and GSE32894, as the test sets) were utilized to identify hub ferroptosis/cuproptosis-related genes (FRGs and CRGs) and develop a prognostic signature. Differential expression analysis (DEA) was conducted, followed by univariate and multivariate Cox’s regression analyses and multiple machine learning (ML) techniques to select genetic features. The performance of the ferroptosis/cuproptosis-related signature was evaluated using Kaplan–Meier (K–M) survival analysis and receiver-operating characteristics (ROC) curves. Mutational and tumour immune microenvironment landscapes were also explored. Real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) experiments confirmed the expression patterns of the hub genes, and functional assays assessed the effects of SCD knockdown on cell viability, proliferation, and migration.ResultsDEA revealed dysregulated FRGs and CRGs in the TCGA MIBC cohort. SCD, DDR2, and MT1A were identified as hub genes. A prognostic signature based on the sum of the weighted expression of these genes demonstrated strong predictive efficacy in the training and test sets. Nomogram incorporating this signature accurately predicted 1-, 3-, and 5-year survival probabilities in the TCGA cohort and GSE13507 dataset. Copy number variation (CNV) and tumour immune microenvironment analysis revealed that high risk score level groups were associated with immunosuppression and lower tumour purity. The associations of risk scores with immunotherapy and chemical drugs were also explored, indicating their potential for guiding treatment for MIBC patients. The dysregulated expression patterns of three hub genes were validated by RT-qPCR experiments.ConclusionsTargeting hub FRGs and CRGs could be a promising therapeutic approach for MIBC. Our prognostic model offers a new framework for MIBC subtyping and can inform personalized therapeutic strategies.

High-Level Isolation: A Landscape Analysis of Global Capabilities and Opportunities to Advance the Field.

High-level isolation units (HLIUs) have been established by countries to provide safe and optimal medical care for patients with high-consequence infectious diseases. We aimed to identify global high-level isolation capabilities and determine gaps and priorities of global HLIUs, using a multiple method approach that included a systematic review of published and gray literature and a review of Joint External Evaluations and Global Health Security Index reports from 112 countries. A follow-up electronic survey was distributed to identified HLIUs. The landscape analysis found 44 previously designated/self-described HLIUs in 19 countries. An additional 33 countries had potential HLIUs; however, there were not enough details on capabilities to determine if they fit the HLIU definition. An electronic survey was distributed to 36 HLIUs to validate landscape analysis findings and to understand challenges, best practices, and priorities for increased networking with a global HLIU cohort; 31 (86%) HLIUs responded. Responses revealed an additional 30 confirmed HLIUs that were not identified in the landscape analysis. To our knowledge, this was the first mapping and the largest ever survey of global HLIUs. Survey findings identified major gaps in visibility of HLIUs: while our landscape analysis initially identified 44 units, the survey unveiled an additional 30 HLIUs that had not been previously identified or confirmed. The lack of formalized regional or global coordinating organizations exacerbates these visibility gaps. The unique characteristics and capabilities of these facilities, coupled with the likelihood these units serve as core components of national health security plans, provides an opportunity for increased connection and networking to advance the field of high-level isolation and address identified gaps in coordination, build an evidence base for HLIU approaches, and inform HLIU definitions and key components.

A Multimodal Analysis of the Linguistic Landscape of Guilin: City as a World-Class Tourism

The study of language landscape has always been the focus of linguistic research, but there are few studies on the world-class tourism language landscape in minority areas. Guilin has always been one of the hottest world-class tourism destinations, with its unique minority character. From the perspectives of multimodal analysis and tourism language landscape construction, this paper discussed the language landscape characteristics of Longyin Road and East-West Lane scenic spots with different orientations and investigated the local people's attitudes towards multilingual signs. The study found that the majority of signs are monolingual and bilingual, predominantly in Chinese and English. Non-textual elements significantly complemented the linguistic landscape, highlighting the need for accurate and diverse multilingual signage to enhance Guilin's world-class tourism image.

Estimating the vulnerability of industrial network infrastructure in Central and Eastern Europe

Industrial infrastructure has suffered an unprecedented number of attacks in Central and Eastern Europe (CEE). This situation can be attributed to many geopolitical factors, including hybrid military conflicts and criminal activity. Industrial networks belonging to the countries that were once under Soviet influence suffer from an elevated risk of cyberattacks. The goal of this work is to propose an easy way to estimate the vulnerabilities of industrial networks to cyber threats on a national level. Since analysis of the industrial vulnerability landscape is difficult, this study proposes an assessment based on the popularity of vulnerable technologies—VPc. This metric is composed of search volume data on keywords related to industrial network technologies and reported security vulnerabilities associated with these words. Data on 116 keywords was analysed and a country-specific VPc index was calculated for twenty states in CEE. The analysis of the popularity of industrial technologies and vendors in CEE reveals interesting information about the industrial security and vulnerability landscape. The results show that some countries (e.g. Estonia) have more resilient industrial infrastructure than others (e.g. Belarus). The results presented in this study are not in conflict with other data and estimation attempts, including the National Cyber Security Index (NCSI). As new vulnerabilities are noted every day, the industrial security landscape changes rapidly. Therefore, a new easy-to-use metric (VPc) can be successfully used for general estimations. This work shows that the VPc score agrees with other estimates and analyses, but as with any other general estimation tool, it must be used with caution.

Suppressing Mycobacterium tuberculosis virulence and drug resistance by targeting Eis protein through computational drug discovery.

Tuberculosis (TB) remains a critical health threat, particularly with the emergence of multidrug-resistant strains. This demands attention from scientific communities and healthcare professionals worldwide to develop effective treatments. The enhanced intracellular survival (Eis) protein is an acetyltransferase enzyme of Mycobacterium tuberculosis that functions by adding acetyl groups to aminoglycoside antibiotics, which interferes with their ability to bind to the bacterial ribosome, thereby preventing them from inhibiting protein synthesis and killing the bacterium. Therefore, targeting this protein accelerates the chance of restoring the aminoglycoside drug activity, thereby reducing the emergence of drug-resistant TB. For this, we have screened 406,747 natural compounds from the Coconut database against Eis protein. Based on MM/GBSA rescoring binding energy, the top 5 most prominent natural compounds, viz. CNP0187003 (-96.14kcal/mol), CNP0176690 (-93.79kcal/mol), CNP0136537 (-92.31kcal/mol), CNP0398701 (-91.96kcal/mol), and CNP0043390 (-91.60kcal/mol) were selected. These compounds exhibited the presence of a substantial number of hydrogen bonds and other significant interactions confirming their strong binding affinity with the Eis protein during the docking process. Subsequently, the MD simulation of these compounds exhibited that the Eis-CNP0043390 complex was the most stable, followed by Eis-CNP0187003 and Eis-CNP0176690 complex, further verified by binding free energy calculation, principal component analysis (PCA), and Free energy landscape analysis. These compounds demonstrated the most favourable results in all parameters utilised for this investigation and may have the potential to inhibit the Eis protein. There these findings will leverage computational techniques to identify and develop a natural compound inhibitor as an alternative for drug-resistant TB.

Determinants of carbon dioxide emissions in Technology Revolution 5.0: New insights from Singapore

Technology Revolution 5.0, characterized by the integration of cutting-edge technologies (CET) like artificial intelligence (AI), internet of things (IoT), and blockchain into various facets of life, has brought remarkable advancements and conveniences. However, this era has also raised significant concerns regarding its environmental impact. The paper applies the ARDL (autoregressive distributed lag approach). The manuscript applied the World Bank data from 2000 to 2022. This paper aims to delve into the determinants contributing to carbon dioxide emissions in the context of industrial revolution 5.0, focusing on Singapore as a case study. The article combines a review of the existing literature, an analysis of the Singaporean environmental landscape, and empirical findings to shed light on this critical issue. The empirical study shows that electricity consumption and foreign direct investment significantly negatively affect environmental pollution in Singapore; fossil fuel and import positively influence ecological pollution. This article helps policymakers have policy implications for Singaporeans in the future.

Landscape analysis of the Kenyan policy on the treatment and prevention of diarrheal disease among under-5 children

ObjectiveDiarrhoea remains a leading cause of morbidity and death among under-5 children in Kenya, despite multipronged policy and programme initiatives to increase access to treatment. This study interrogates the comprehensiveness...

Microalgae- and cyanobacteria-derived phytostimulants for mitigation of salt stress and improved agriculture

Soil salinization poses severe abiotic stress that adversely affects plant growth and development, ultimately threatening global food security by inducing physiological abnormalities. In response to escalating nutrient demands, with global requirements quantified at 76 % for nitrogen and 87 % for phosphorus, modern agriculture is increasingly adopting sustainable practices to enhance nutrient recycling and reduce reliance on external inputs. Emerging sources of plant phytostimulants, such as microalgal and cyanobacterial biomass, show promise in augmenting crop yields and bolstering plant resistance to various abiotic factors, including salt stress. The efficacy of these microorganisms stems from their simplistic cellular structure, superior photosynthetic efficiency, capacity for heterotrophic growth, adaptability to varying environmental conditions, potential for metabolic engineering, and the abundance of valuable biomolecules (such as soluble amino acids, micronutrients, polysaccharides, and phytohormones) within their biomass. This review provides an analysis of the current research landscape concerning microalgae- and cyanobacteria-derived phytostimulants, highlighting their promise as an innovative and sustainable alternative to synthetic fertilizers in the agricultural sector. Moreover, it identifies various adaptive responses of plants to salinity stress and assesses the potential and challenges associated with the use of microalgae and cyanobacteria-based metabolites for developing new sustainable strategies to enhance crop tolerance to salinity stress.

Clinical Trials in Gastroesophageal Cancers: An Analysis of the Global Landscape of Interventional Trials From ClinicalTrials.gov.

To describe the global landscape of clinical research into interventions for gastroesophageal cancers (GECs), with examination of trial characteristics, geographic distribution of trial sites, and factors associated with trial termination. We queried ClinicalTrials.gov to identify all completed or terminated phase III interventional studies investigating GECs (esophageal squamous cell carcinoma [ESCC], esophageal adenocarcinoma [EAC], gastroesophageal junctional [GEJ], and gastric adenocarcinoma). Data on all reported trial characteristics were extracted. Pearson's chi-square and Fisher's exact tests were used to compare differences in completed and terminated trials. Multivariate logistic regression evaluated predictors of termination. A total of 179 trials were identified; of these, 90% were therapeutic. Most included sites in Asia (61%) and Europe (32%); few included sites in Africa (4%). Thirty percent included sites in low- and middle-income countries (LMICs). Most (70%) focused on gastric or GEJ adenocarcinoma, 13% on EAC and ESCC, and 9% on ESCC alone. Sixteen percent (n = 29) of trials terminated prematurely. In multivariate analysis, study site number, location of recruitment sites, and patient population emerged as predictors of termination. Trials recruiting from US-based sites were more likely to terminate (odds ratio [OR], 7.22 [95% CI, 1.59 to 32.69]). Trials conducted exclusively in LMICs were less likely to terminate (OR, 0.04 [95% CI, 0.01 to 0.59] v conducted in high-income countries [HICs] alone). Studies on ESCC were more likely to terminate (OR, 17.74 [95% CI, 1.49 to 210.69]). Although 80% of GECs occur in LMICs, trial activity disproportionately occurs in HICs. Few trials focus on EAC/ESCC despite being highly fatal, highlighting an unmet need. Overall, this study highlights (1) a missed opportunity to recruit patients from high-incidence regions globally; and (2) a pressing need for increasing funding, infrastructure, and support for GEC trials in LMICs.

A bibliometric analysis of global research on microbial immune microenvironment in melanoma from 2012 to 2022.

Melanoma is an aggressive malignancy primarily impacting the skin, mucous membranes, and pigment epithelium. The tumor microbial microenvironment encompasses both the microorganisms inhabiting the tumor vicinity and the environmental factors influencing their interactions. Emerging evidence highlights the pivotal role of the microbial immune microenvironment in melanoma. We conducted an extensive review of scholarly works published from 2012 to 2022, utilizing The Web of Science Core Collection. Subsequently, we employed analytical tools such as VOSviewer, CiteSpace, and the R programming language to scrutinize prevailing research patterns within this domain. A sum of 513 articles were pinpointed, with notable input coming from the United States and China. Harvard University stood out as the top-contributing institution, while the journal Science received the most citations. Current research within this sphere chiefly focuses on two principal domains: the gut microbiota and the PD-L1 pathway concerning melanoma treatment. The study offers an extensive analysis and overview of the worldwide research landscape concerning the immune microenvironment with a focus on microbes in melanoma. It underscores the promising prospects for harnessing the microbial immune microenvironment's potential in melanoma. These findings furnish valuable insights and guidance for advancing scientific inquiry and refining clinical approaches within this dynamic field.

MZT2A serves as a prognostic biomarker and promotes the progression of kidney renal clear cell carcinoma

MZT2A is a novel core component in the γ-tubulin ring complex and aberrantly expressed in some types of tumors. However, MZT2A expression pattern across different cancers and its role in kidney renal clear cell carcinoma have not been sufficiently investigated. A thorough analysis of MZT2A expression landscape across 33 cancer types was conducted, utilizing 712 normal samples and 9807 tumor samples from TCGA (version 37.0), as well as 5112 normal samples from the GTEx databases. MZT2A's impact on KIRC cell viability and proliferation were evaluated through BrdU assays and monitored by cell imaging readers in MZT2A-expressing plasmid or siRNA-transfected cells. Additionally, the effects of MZT2A on cell apoptosis and cell cycle were detected using flow cytometry and Western blot. WGCNA analysis was employed to construct a co-expression gene network associated with MZT2A expression in KIRC, and Pearson correlation coefficient was utilized to examine the relationships between pairs of genes. MZT2A is overexpressed in 25 out of 33 types of cancer, including KIRC. In KIRC, high level of MZT2A was associated with higher clinical stage progression and poorer patients' survival. Downregulation of MZT2A decreased KIRC cell proliferation, retarded cell cycle and promoted apoptosis, while upregulation of MZT2A produced the opposite effects. WGCNA analysis and in vitro experiments revealed that MZT2A activated PI3K/AKT signaling pathway in KIRC. In all, MZT2A was overexpressed in most types of tumors. MZT2A served as an oncogene in KIRC and might be a potential target for guiding future treatments.

Bird Nuisance at an Oil Gathering Station: A Landscape and Site Analysis

Abstract Barn swallow (Hirundo rustica) is a migratory bird. In Petapahan Gas Station (GS), Riau, this bird roost in a big number and create some nuisance due to their faeces. The objective of this paper was to analyse the possible causes of swallow’s roost behaviour at the landscape and site level, and formulate some recommendations. Migratory bird route was studied, the surrounding areas was analysed using, and characteristics of the GS was observed. Petapahan happened to be located at the known bird migratory route. The land-use of surrounded areas was a vast area of oil-palm plantation mixed with agricultural-area, open-area, and housing, create an excellent habitat for insects as the bird’s food. There was no other alternative for roost-site in the 5km radius. At the GS there are many large pipes, small pipes, handrails, I-beams, C-beams, valves, flares, big tanks, pits, office, and many other instruments that can function as the barn swallow’s roost site. Warm temperature, sufficient lighting, and safety from predator also provided good support. Basically, the GS has to accept the occurrence of the birds, while employing some management actions: (1) setting zonation for bird-free and bird-tolerance areas, and (2) put netting and other bird deterrent sensitive sites.

Target regimen profiles for tuberculosis treatment.

Simpler, shorter, safer and more effective treatments for tuberculosis that are easily accessible to all people with tuberculosis are desperately needed. In 2016, the World Health Organization (WHO) developed target regimen profiles for the treatment of tuberculosis to make drug developers aware of both the important features of treatment regimens, and patient and programmatic needs at the country level. In view of recent ground-breaking advances in tuberculosis treatment, WHO has revised and updated these regimen profiles. We used a similar process as for the 2016 profiles, including a baseline treatment landscape analysis, an initial stakeholder survey, modelling studies estimating the impact and cost-effectiveness of novel tuberculosis treatment regimens, and an extensive stakeholder consultation. We developed target regimen profiles for the treatment of rifampicin-susceptible and rifampicin-resistant tuberculosis, as well as a pan-tuberculosis regimen that would be appropriate for patients with any type of tuberculosis. We describe the revised target regimen profile characteristics, with specific minimal and optimal targets to be met, rationale and justification, and aspects relevant to all target regimen profiles (drug susceptibility testing, adherence and forgiveness, treatment strategies, post-tuberculosis lung disease, and cost and access considerations). We discuss the trade-offs of proposed characteristics for decision-making at developmental or operational levels. We expect that, following these target regimen profile revisions, tuberculosis treatment developers will produce regimens that are quality-assured, affordable and widely available, and that meet the needs of affected populations.

Geomorphological landscape analysis for the study of surface and groundwater in a carbonate rock environment in northern Minas Gerais, Brazil

Geomorphological landscape analysis for the study of surface and groundwater in a carbonate rock environment in northern Minas Gerais, Brazil

Landscape analysis of environmental data sources for linkage with SEER cancer patients database.

One of the challenges associated with understanding environmental impacts on cancer risk and outcomes is estimating potential exposures of individuals diagnosed with cancer to adverse environmental conditions over the life course. Historically, this has been partly due to the lack of reliable measures of cancer patients' potential environmental exposures before a cancer diagnosis. The emerging sources of cancer-related spatiotemporal environmental data and residential history information, coupled with novel technologies for data extraction and linkage, present an opportunity to integrate these data into the existing cancer surveillance data infrastructure, thereby facilitating more comprehensive assessment of cancer risk and outcomes. In this paper, we performed a landscape analysis of the available environmental data sources that could be linked to historical residential address information of cancer patients' records collected by the National Cancer Institute's Surveillance, Epidemiology, and End Results Program. The objective is to enable researchers to use these data to assess potential exposures at the time of cancer initiation through the time of diagnosis and even after diagnosis. The paper addresses the challenges associated with data collection and completeness at various spatial and temporal scales, as well as opportunities and directions for future research.

A large-scale audit of dataset licensing and attribution in AI

The race to train language models on vast, diverse and inconsistently documented datasets raises pressing legal and ethical concerns. To improve data transparency and understanding, we convene a multi-disciplinary effort between legal and machine learning experts to systematically audit and trace more than 1,800 text datasets. We develop tools and standards to trace the lineage of these datasets, including their source, creators, licences and subsequent use. Our landscape analysis highlights sharp divides in the composition and focus of data licenced for commercial use. Important categories including low-resource languages, creative tasks and new synthetic data all tend to be restrictively licenced. We observe frequent miscategorization of licences on popular dataset hosting sites, with licence omission rates of more than 70% and error rates of more than 50%. This highlights a crisis in misattribution and informed use of popular datasets driving many recent breakthroughs. Our analysis of data sources also explains the application of copyright law and fair use to finetuning data. As a contribution to continuing improvements in dataset transparency and responsible use, we release our audit, with an interactive user interface, the Data Provenance Explorer, to enable practitioners to trace and filter on data provenance for the most popular finetuning data collections: www.dataprovenance.org.

Prediction of clear cell renal cell carcinoma prognosis based on an immunogenomic landscape analysis

Immune cell infiltration and tumor-related immune molecules play key roles in tumorigenesis and tumor progression. The influence of immune interactions on the molecular characteristics and prognosis of clear cell renal cell carcinoma (ccRCC) remains unclear. A machine learning algorithm was applied to the transcriptome data from The Cancer Genome Atlas database to determine the immunophenotypic and immunological characteristics of ccRCC patients. These algorithms included single-sample gene set enrichment analyses and cell type identification. Using bioinformatics techniques, we examined the prognostic potential and regulatory networks of immune-related genes (IRGs) involved in ccRCC immune interactions. Fifteen IRGs (CCL7, CHGA, CMA1, CRABP2, IFNE, ISG15, NPR3, PDIA2, PGLYRP2, PLA2G2A, SAA1, TEK, TGFA, TNFSF14, and UCN2) were identified as prognostic IRGs associated with overall survival and were used to construct a prognostic model. The area under the receiver operating characteristic curve at 1 year was 0.927; 3 years, 0.822; and 5 years, 0.717, indicating good predictive accuracy. Molecular regulatory networks were found to govern immune interactions in ccRCC. Additionally, we developed a nomogram containing the model and clinical characteristics with high prognostic potential. By systematically examining the sophisticated regulatory mechanisms, molecular characteristics, and prognostic potential of ccRCC immune interactions, we provided an important framework for understanding the molecular mechanisms of ccRCC and identifying new prognostic markers and therapeutic targets for future research.

The first global landscape analysis of multiple sclerosis research funding

Introduction: Multiple sclerosis (MS) is an immune-mediated central nervous system disorder and a growing global health challenge affecting nearly 3 million people worldwide. Incidence and prevalence continue to increase with no known cause or cure. Globally governments and non-profit organizations fund research toward better understanding of and treatments for multiple sclerosis. Methods: This study identified MS research projects funded between 2021 and 2023 by government and non-profit organization sources. Projects were described by type of scientific approach, Pathways to Cure research category (i.e. Stop, Restore, End), and other key characteristics. Results: Over 2,300 MS research projects were identified through 16 non-profit MS organizations and 18 government databases. The overall global portfolio of these projects is valued at nearly one and a half billion Euros. The majority of projects were classified in the Stop category (60%). Research collaboration occurs in many forms among the research community; around 272 projects were reported to be co-funded. Conclusion: Global MS research collaboration will accelerate progress toward increased knowledge, effective treatments, improved health outcomes, and ultimately cures for MS. This landscape analysis highlights the current distribution of MS research investment between topics and begins to suggest where the MS community should focus to increase potential impact for current and future endeavors.