Search Results (926)

Background/Objectives: Inflammation-based markers have emerged as potential prognostic tools in hepatocellular carcinoma (HCC), but comparative data with classical prognostic factors in untreated HCC are limited. This study aimed to evaluate and compare the prognostic performance of inflammatory and conventional markers using Harrell’s concordance index (C-index). Methods: This retrospective study included 250 patients with untreated HCC. Prognostic variables included age, BCLC stage, Child–Pugh classification, Milan criteria, MELD score, AFP, albumin, Charlson comorbidity index, and the inflammation-based markers neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), Systemic Inflammation Response Index (SIRI), and Systemic Immune-inflammation Index (SIII). Survival was analyzed using Cox regression. Predictive performance was assessed using the C-index, Akaike Information Criterion (AIC), and likelihood ratio tests. Results: Among the classical markers, BCLC showed the highest predictive performance (C-index: 0.717), while NLR ranked highest among the inflammatory markers (C-index: 0.640), above the MELD score and Milan criteria. In multivariate analysis, NLR ≥ 2.3 remained an independent predictor of overall survival (HR: 1.787; 95% CI: 1.264–2.527; p < 0.001), along with BCLC stage, albumin, Charlson index, and Milan criteria. Including NLR in the model modestly improved the C-index (from 0.781 to 0.794) but significantly improved model fit (Δ–2LL = 10.75; p = 0.001; lower AIC). Conclusions: NLR is an accessible, cost-effective, and independent prognostic marker for overall survival in untreated HCC. It shows discriminative power comparable to or greater than most conventional predictors and may complement classical stratification tools for HCC. Full article

As an integral component of humanity’s cultural heritage, traditional villages universally confront challenges such as population loss and cultural discontinuity amid rapid urbanization. Cluster-based protection models have increasingly become the international consensus for addressing the survival crisis of such settlements. This study selects the Central Yunnan region of Southwest China—characterized by its complex geography and multi-ethnic habitation—as the research area. Employing ArcGIS spatial analysis techniques alongside clustering algorithms, we examine the spatial distribution characteristics and clustering patterns of 251 traditional villages within this region. The findings are as follows. In terms of spatial distribution, traditional villages in Central Yunnan are unevenly dispersed, predominantly aggregating on mid-elevation gentle slopes; their locations are chiefly influenced by rivers and historical courier routes, albeit with only indirect dependence on waterways. Regarding single-cluster attributes, the spatial and geomorphological features exhibit a composite “band-and-group” pattern shaped by river valleys; culturally, two dominant modes emerge—“ancient-route-dependent” and “ethnic-symbiosis”—reflecting an economy-driven cultural mechanism alongside latent marginalization risks. Concerning construction characteristics, the “Qionglong-Ganlan” and Han-style “One-seal” residential features stand out, illustrating both adaptation to mountainous environments and the cumulative effects of historical culture. Based on these insights, we propose a three-tiered clustering classification framework—“comprehensive-element coordination”, “feature-led”, and “potential-cultivation”—to inform the development of contiguous and typological protection strategies for traditional villages in highland, multi-ethnic regions. Full article

Prognostic markers such as overall survival (OS) and tertiary lymphoid structure (TLS) ratios, alongside diagnostic signatures like primary cancer-type classification, provide critical information for treatment selection, risk stratification, and longitudinal care planning across the oncology continuum. However, extracting these signals solely from sparse, high-dimensional multi-omics data remains a major challenge due to heterogeneity and frequent missingness in patient profiles. To address this challenge, we present SeNMo, a self-normalizing deep neural network trained on five heterogeneous omics layers—gene expression, DNA methylation, miRNA abundance, somatic mutations, and protein expression—along with the clinical variables, that learns a unified representation robust to missing modalities. Trained on more than 10,000 patient profiles across 32 tumor types from The Cancer Genome Atlas (TCGA), SeNMo provides a baseline that can be readily fine-tuned for diverse downstream tasks. On a held-out TCGA test set, the model achieved a concordance index of 0.758 for OS prediction, while external evaluation yielded 0.73 on the CPTAC lung squamous cell carcinoma cohort and 0.66 on an independent 108-patient Moffitt Cancer Center cohort. Furthermore, on Moffitt’s cohort, baseline SeNMo fine-tuned for TLS ratio prediction aligned with expert annotations (p < 0.05) and sharply separated high- versus low-TLS groups, reflecting distinct survival outcomes. Without altering the backbone, a single linear head classified primary cancer type with 99.8% accuracy across the 33 classes. By unifying diagnostic and prognostic predictions in a modality-robust architecture, SeNMo demonstrated strong performance across multiple clinically relevant tasks, including survival estimation, cancer classification, and TLS ratio prediction, highlighting its translational potential for multi-omics oncology applications. Full article

The Vesical Imaging Reporting and Data System (VI-RADS) is used to detect muscle-invasive bladder cancer, with emerging prognostic implications. Integrating imaging parameters with molecular biomarkers may improve risk stratification in bladder cancer. This study evaluated whether combining VI-RADS scores with serum cytokeratin fragment 19 (CYFRA 21-1) levels—a clinically relevant biomarker for bladder cancer—could improve overall survival (OS) prediction. We retrospectively analyzed 134 patients who underwent transurethral resection of bladder tumors, magnetic resonance imaging, and postoperative serum CYFRA 21-1 measurements. In total, 15 cancer-specific deaths were observed during follow-up. Receiver operating characteristic curve analysis identified optimal prognostic cut-off values: VI-RADS score ≥ 4 and CYFRA 21-1 level ≥ 1.8 ng/mL. The 1-, 2-, and 3-year OS in patients with both high VI-RADS scores and CYFRA 21-1 levels were 42.9%, 16.7%, and 8.3%, respectively, significantly lower than those in other groups (p < 0.001, 0.002, and 0.003, respectively). Multivariate Cox proportional hazards analysis demonstrated that such patients had the poorest OS (hazard ratio: 7.51; p = 0.002). This suggests that combining VI-RADS and CYFRA 21-1 improves prognostic accuracy in bladder cancer, demonstrating potential clinical utility by informing individualized treatment strategies; however, limitations include the retrospective study design and absence of external validation. Full article

Viruses use a range of sophisticated strategies to evade detection by cytotoxic T-lymphocytes (CTLs) within host cells. Beyond elaborating dedicated viral proteins that disrupt the MHC class I antigen-presentation machinery, some viruses possess intrinsic, cis-acting genome-encoded elements that interfere with antigen processing and display. These protein features, including G-quadruplex motifs, repetitive peptide sequences, and rare-codon usage, counterintuitively limit production of proteins critical to virus survival, particularly during latency. By slowing viral protein synthesis, these features reduce antigen production and proteosomal degradation, ultimately limiting the generation of peptides for MHC I presentation. These built-in evasion tactics enable viruses to remain “invisible” to CTLs during latency. While these primary sequence intrinsic immune evasion (PSI) mechanisms are well-described in select herpesviruses, emerging evidence suggests that they may also play a critical role in RNA viruses. How these proteins are made, rather than what they functionally target, determines their immune evasion properties. Understanding PSI mechanisms could rationally inform the design of engineered viral antigens with altered or removed evasion elements to restore antigen CTL priming and activation. Such vaccine strategies have the potential to enhance immune recognition, improve clearance of chronically infected cells, and contribute to the treatment of persistent viral infections and virus-associated cancers. Full article

Moringa (Moringa oleifera Lam.) is widely recognised as a multipurpose crop suitable for human and animal consumption, medicinal, and industrial purposes, making it attractive for introduction into new ranges. Its extracts have been found to have beneficial impacts on various crop species and biological activity against multiple weeds, making their use in agriculture promising. However, concerns have also been raised about moringa’s potential to negatively impact the growth and development of other cultivated and non-cultivated plant species, especially in areas where it has been introduced outside its native range. To understand the positive and negative interactions between moringa and other plants, it is essential to investigate its allelopathic potential. Allelopathy is a biological activity by which one plant species produces and releases chemical compounds that influence the reproduction, growth, survival, or behaviour of other plants with either beneficial or detrimental effects on the receiver. Plants produce and release allelochemicals by leaching, volatilisation, or through root exudation. These biochemical compounds can affect critical biological processes such as seed germination, root and shoot elongation, photosynthesis, enzymatic activities, and hormonal balance in neighboring plants. Therefore, allelopathy is an important driver of plant composition and ecological interactions in an ecosystem. This review explores the positive and negative allelopathic effects of moringa extracts on other plant species, which may help to inform decisions regarding its introduction into new biogeographical regions and incorporation into existing farming systems, as well as the use of moringa plant extracts in agriculture. Full article

Phosphatidylinositol 3-kinase alpha (PI3Kα) is frequently mutated in head and neck squamous cell carcinoma (HNSCC), leading to the constitutive activation of the PI3K/Akt pathway, which promotes tumor cell proliferation, survival, and metastasis. PI3Kα allosteric inhibitors demonstrate therapeutic potential as both monotherapy and combination therapy, particularly in patients with PIK3CA mutations or resistance to immunotherapy, through the precise targeting of mutant PI3Kα. Compared to ATP-competitive PI3Kα inhibitors such as Alpelisib, the allosteric inhibitor RLY-2608 exhibits enhanced selectivity for mutant PI3Kα while minimizing the inhibition of wild-type PI3Kα, thereby reducing side effects such as hyperglycemia. To date, no allosteric PI3Kα inhibitors have been approved for clinical use. To develop novel PI3Kα inhibitors with improved safety and efficacy, we employed a scaffold hopping approach to structurally modify RLY-2608 and constructed a compound library. Based on the structural information of the PI3Kα allosteric site, we conducted the systematic virtual screening of 11,550 molecules from databases to identify lead compounds. Through integrated approaches, including molecular docking studies, target validation, druggability evaluation, molecular dynamics simulations, and metabolic pathway and metabolite analyses, we successfully identified a promising novel allosteric PI3Kα inhibitor, H-18 (3-(2-chloro-5-fluorophenyl)isoindolin-1-one). H-18 has not been previously reported as a PI3Kα inhibitor, and provides an excellent foundation for subsequent lead optimization, offering a significant starting point for the development of more potent PI3Kα allosteric inhibitors. Full article

Malignant pleural effusion (MPE) can lead to pleural organization with loculation and impaired drainage. This condition is becoming increasingly more common due to advancements in cancer therapy and extended patient survival. Factors such as repeated thoracentesis through an indwelling pleural catheter (IPC), intrapleural bleeding, and tumor progression contribute to MPE organization. Loculated MPE causes breathlessness and reduced quality of life, and current therapies, including intrapleural fibrinolytic or enzymatic therapy (IPFT/IET), have limitations in efficacy and safety. Identifying new therapeutic targets is crucial for improving treatment outcomes. Research is needed to understand the role of profibrogenic factors in pleural neoplasia, their regulation, and their impact on different stages of pleural organization. The development of a rabbit model of organizing MPE could provide insights into underlying mechanisms and novel interventions. Comparative studies of pleural tissues and effusions from MPE patients and other forms of pleural organization may reveal valuable information. Cellular and molecular profiling, assessment of biomarkers, and personalized IPFT dosing are potential areas of investigation. Suppression of PAI-1 activity and the role of hyaluronic acid in malignant mesothelioma are also important research directions. Understanding the profibrogenic capacity of pleural mesothelial cells undergoing mesenchymal transition (MesoMT) and identifying key contributors and effectors involved in this process are essential for developing effective treatments for loculated MPE. Full article

Background/Objectives: The clinical value of KRAS mutations in lung adenocarcinoma, alone or in combination with other mutations, has been assessed especially in advanced stages. This study evaluates how KRAS and the presence of co-mutations could affect survival in early-stage lung. Methods: We analyzed a real-world cohort including all staged NSCLC patients diagnosed and treated from 2018 to 2022 at our Institute with availability of NGS molecular data. Statistical analyses were made using log-rank test, the two-tailed Fisher’s exact test and Kaplan-Meier survival curves. Results: KRAS mutations were observed in 179/464 cases (38.6%). The majority of KRAS co-mutations were in TP53 (74%) and STK11 (14.3%) genes. KRAS+TP53 co-mutations were more frequent compared to KRAS-only tumors in stage IV NSCLC (p = 0.01). In early stage and locally advanced cases (stage I-III), better prognosis was associated to KRAS-only mutated NSCLC and to KRAS+STK11 mutated cases compared to KRAS+TP53 (p = 0.008). In particular, patients carrying KRAS+TP53 in stage I and II displayed a shorter survival, similar to patients diagnosed at stage III. Conclusions: Routine NGS provides important information for potential actionable mutations but also for the prognostic and predictive role of the presence of co-occurring mutations. In particular, the presence of KRAS+TP53 in stage I and II NSCLC may be considered an unfavorable prognostic marker possibly leading to adapt the perioperative chemo-immunotherapy. Full article

The last stop on the Muslim pilgrimage is the Kaʻba. Like all other holy and religious places, the Kaʻba has survived due to the repairs it has undergone since its construction. However, the Kaʻba has been rebuilt at times when it was destroyed for various reasons. Since the interruption of the pilgrimage would undermine the legitimacy of the caliph, Muslims attached great importance to rebuilding the Kaʻba in such cases. The Kaʻba was last rebuilt by the Ottoman Sulṭān Murād IV after the flood of 1039/1630. However, the rebuilding process has not been without its controversies. Although the Ottoman Empire attempted to rebuild the Kaʻba out of necessity, some scholars objected to this initiative. Ibn ʻAllān, one of the leading Shafiʻi muftis of Mecca, followed the rebuilding work day by day and did not hesitate to intervene when necessary. Riḍwān Agha, who carried out the rebuilding of the Kaʻba, was able to overcome Ibn ʻAllān’s objections with fatwas from the muftis of the four sects (four Sunni schools of law) and thus completed the building work. After the Kaʻba was rebuilt, Turkish works on its history began to be produced. In this way, the public was informed that the Kaʻba could be rebuilt if necessary, and attempts were made to anticipate and prevent any potential reactions. This study aims to contribute to the history of the Kaʻba by analysing its rebuilding after the flood of 1039/1630 through debates between scholars (ʻulamāʼ) and administrators (umarāʼ) during this period. Access to the details of this issue from the works of the ʻulamāʼ who witnessed the rebuilding makes this paper unique. Full article

Background/Objectives: The tumor microenvironment (TME) plays a critical role in cancer progression by shaping immune responses and influencing patient outcomes. We hypothesized that the relative proximity of specific immune cell pairs to cancer cells within the TME could help predict their pro- or anti-tumor functions and reflect clinically relevant immune dynamics. Methods: We analyzed imaging mass cytometry (IMC) data from lung adenocarcinoma (LUAD) and triple-negative breast cancer (TNBC) cohorts. For each immune cell pair, we calculated a relative distance (RD) score, which quantifies the spatial difference in proximity to cancer cells. We assessed the prognostic and predictive significance of these RD-scores by comparing them with conventional features such as cell fractions, densities, and individual cell distances. To account for variations in cell abundance, we also derived normalized RD-scores (NRD-scores). Results: RD-scores were more strongly associated with overall patient survival than standard immunological metrics. Among all immune cell pairs, the RD-score comparing the proximity of B cells to that of intermediate monocytes showed the most significant association with improved survival. In TNBC, RD-scores also improved the distinction between responders and non-responders to immunochemotherapy and chemotherapy. Normalized RD-scores reinforced these findings by minimizing the influence of cell density and further highlighting the importance of immune cell spatial relationships. Conclusions: RD-scores offer a spatially informed biomarker that outperforms traditional metrics in predicting survival and treatment response. This approach provides a new perspective on immune cell behavior in the TME and has potential utility in guiding personalized cancer therapies and patient stratification. Full article

Background: Pneumocystis jirovecii pneumonia (PJP) remains a serious threat to non-HIV immunocompromised patients, who often experience rapid disease progression, delayed diagnosis, and higher mortality. Standard treatment with high-dose trimethoprim-sulfamethoxazole (TMP-SMX) is based primarily on data from HIV-positive populations, despite differences in immune response and drug tolerability. Objective: This narrative review critically synthesizes the available evidence on lower-dose TMP-SMX strategies for PJP in non-HIV patients and explores the potential role of individualized dosing approaches to improve outcomes. Findings: Emerging retrospective data suggest that lower-dose regimens (<15 mg/kg/day) may provide similar survival outcomes with fewer adverse effects. The intense inflammatory response observed after treatment initiation in non-HIV patients, potentially exacerbated by high-dose therapy, may contribute to clinical deterioration. This raises the possibility that TMP-SMX dosing itself could influence immune-mediated lung injury. While adjunctive corticosteroids are frequently used to temper inflammation, their benefit remains uncertain. Conclusions: Existing data suggest that lower-dose TMP-SMX may be effective and better tolerated in some non-HIV patients with PJP. A personalized approach to dosing, informed by clinical and host-specific factors, represents a promising strategy to optimize outcomes and minimize harm. Future research should prioritize precision medicine frameworks and prospective evaluation of individualized dosing protocols. Full article

Background: Many patients harbor minimal residual disease (MRD)—small clusters of residual tumor cells that survive therapy and evade conventional detection but drive recurrence. Although advances in molecular and computational methods have improved circulating tumor DNA (ctDNA)-based MRD detection, these approaches face challenges: ctDNA shedding fluctuates widely across tumor types, disease stages, and histological features. Additionally, low levels of driver mutations originating from healthy tissues can create background noise, complicating the accurate identification of bona fide tumor-specific signals. These limitations underscore the need for refined technologies to further enhance MRD detection beyond DNA sequences in solid malignancies. Methods: Profiling circulating cell-free mRNA (cfmRNA), which is hyperactive in tumor and non-tumor microenvironments, could address these limitations to inform postoperative surveillance and treatment strategies. This study reported the development of OncoMRD BREAST, a customized, gene signature-informed cfmRNA assay for residual disease monitoring in breast cancer. OncoMRD BREAST introduces several advanced technologies that distinguish it from the existing ctDNA-MRD tests. It builds on the patient-derived gene signature for capturing tumor activities while introducing significant upgrades to its liquid biopsy transcriptomic profiling, digital scoring systems, and tracking capabilities. Results: The OncoMRD BREAST test processes inputs from multiple cutting-edge biomarkers—tumor and non-tumor microenvironment—to provide enhanced awareness of tumor activities in real time. By fusing data from these diverse intra- and inter-cellular networks, OncoMRD BREAST significantly improves the sensitivity and reliability of MRD detection and prognosis analysis, even under challenging and complex conditions. In a proof-of-concept real-world pilot trial, OncoMRD BREAST’s rapid quantification of potential tumor activity helped reduce the risk of incorrect treatment strategies, while advanced predictive analytics contributed to the overall benefits and improved outcomes of patients. Conclusions: By tailoring the assay to individual tumor profiles, we aimed to enhance early identification of residual disease and optimize therapeutic decision-making. OncoMRD BREAST is the world’s first and only gene signature-powered test for monitoring residual disease in solid tumors. Full article

The expansion of human activities can degrade natural habitats, thereby increasing threats to wildlife conservation. The wild populations of many species have declined due to the modification of natural habitats by humans. The Arabian wolf (Canis lupus arabs) is a subspecies of the gray wolf that is of conservation concern across its distribution range. The Arabian wolf is understudied in certain habitats (e.g., mountainous areas), which limits understanding of its overall ecology. Given its vulnerable conservation status, this study aimed to collect relevant data and information on incidents and potential threats facing this predator in the rugged mountainous habitats of western Tabuk province, Saudi Arabia, and how the effects of these threats can be minimized. In these mountain habitats Arabian wolves encounter various severe threats that challenge relevant conservation efforts. Observations of such threats—some of which result in wolf mortality—represent serious challenges to the survival of wild Arabian wolves. Conflicts with humans and livestock represent considerable threats that must be appropriately managed. Additionally, the potential association between Arabian wolves and free-ranging dogs requires further investigation. Various conservation scenarios and mitigation approaches can be applied to help reduce negative impacts on Arabian wolf populations and maximize their likelihood of survival. Overall, ensuring the persistence of such a unique desert-adapted apex predator in this ecosystem must become a conservation priority. Full article

Background/Objectives: Laryngeal squamous cell carcinoma (LSCC) is a common malignancy with unsatisfactory survival rates, highlighting the need for reliable biomarkers to improve its diagnosis and prognosis. Growth differentiation factor 15 (GDF15), a protein implicated in various cancers, has not been thoroughly investigated in LSCC. This study aimed to evaluate the significance of GDF15 expression in LSCC by integrating immunohistochemical analysis of archival tissue samples with RNA sequencing data from public databases (TCGA and GEO) to provide comprehensive clinical insights. Methods: We analyzed archival tissue samples from 65 patients with LSCC using immunohistochemistry and evaluated GDF15 expression profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Statistical analyses included Kaplan–Meier survival analysis and Cox proportional hazards regression to assess the correlation between GDF15 expression, clinicopathological variables, and survival outcomes. Results: GDF15 expression did not significantly differ between tumor and adjacent normal tissues. However, in the tissue macroarray (TMA) cohort, high GDF15 expression was significantly associated with a lower TNM stage and less advanced pT status. Kaplan–Meier analysis revealed that high GDF15 expression correlated with reduced overall survival in the TMA cohort, suggesting its utility in risk stratification. Multivariate analysis identified GDF15 as an independent prognostic factor for disease-free survival in LSCC. Conclusions: Our findings suggest that GDF15 may serve as a prognostic biomarker for LSCC, particularly in early-stage disease. Elevated GDF15 levels, which are associated with poorer overall survival, could be integrated into diagnostic panels to enhance risk stratification and inform treatment decisions. Furthermore, GDF15 may be a promising target for therapeutic intervention. Further research is warranted to validate these results and explore their potential in clinical practice. Full article