Search Results (1,569)

Background: Colorectal liver metastasis (CRLM) represents a major clinical challenge in oncology, affecting 25–50% of colorectal cancer patients and significantly impacting survival. While multimodal therapies—including surgical resection, systemic chemotherapy, and local ablative techniques—have improved outcomes, prognosis remains heterogeneous due to variations in tumor biology, patient factors, and institutional practices. Methods: This review synthesizes current evidence on prognostic factors influencing CRLM management, encompassing clinical (e.g., tumor burden, anatomic distribution, timing of metastases), biological (e.g., CEA levels, inflammatory markers), and molecular (e.g., RAS/BRAF mutations, MSI status, HER2 alterations) determinants. Results: Key findings highlight the critical role of molecular profiling in guiding therapeutic decisions, with RAS/BRAF mutations predicting resistance to anti-EGFR therapies and MSI-H status indicating potential responsiveness to immunotherapy. Emerging tools like circulating tumor DNA (ctDNA) and radiomics offer promise for dynamic risk stratification and early recurrence detection, while the gut microbiome is increasingly recognized as a modulator of treatment response. Conclusions: Despite advancements, challenges persist in standardizing resectability criteria and integrating multidisciplinary approaches. Current guidelines (NCCN, ESMO, ASCO) emphasize personalized strategies but lack granularity in terms of incorporating novel biomarkers. This exhaustive review underscores the imperative for the development of a unified, biomarker-integrated framework to refine CRLM management and improve long-term outcomes. Full article

Accounting for 15–30% of colorectal cancer cases, the serrated pathway remains poorly characterized compared to the adenoma–carcinoma sequence. It involves sessile serrated lesions as precursors and is characterized by BRAF mutations (BRAF^V600E), CpG island hypermethylation, and microsatellite instability (MSI). Using label-free proteomics, we compared normal tissue margins from patients with diverticular disease, sessile serrated lesions, low-grade adenomas, and high-grade adenomas. We identified S100A14 as significantly overexpressed in sessile serrated lesions compared to low-grade adenomas, high-grade adenomas, and normal tissues. This overexpression was confirmed by immunohistochemical scoring in an independent cohort. Gene expression analyses of public datasets showed higher S100A14 expression in BRAF^V600E-mutated and MSI-H colorectal cancers compared to microsatellite stable BRAF^wt tumors. This finding was confirmed by immunohistochemical scoring in an independent colorectal cancer cohort. Furthermore, single-cell RNA sequencing analysis from the Human Colon Cancer Atlas revealed that S100A14 expression in tumor cells positively correlated with the abundance of tumoral CD8⁺ cytotoxic T cells, particularly the CD8⁺ CXCL13⁺ subset, known for its association with a favorable response to immunotherapy. Collectively, our results demonstrate for the first time that S100A14 is a potential biomarker of serrated neoplasia and further suggests its potential role in predicting immunotherapy responses in colorectal cancer. Full article

Background/Objectives: Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest solid tumors, with a five-year overall survival rate below 10%. While the introduction of multi-agent chemotherapy regimens has improved outcomes marginally, most patients with advanced disease continue to have limited therapeutic options. Molecular profiling has uncovered actionable genomic alterations in select subgroups of PDAC, yet the clinical impact of targeted therapies remains modest. This review aims to provide a clinically oriented synthesis of emerging molecular targets in PDAC, their therapeutic relevance, and practical considerations for biomarker testing, including current FDA and EMA indications. Methods: A narrative review was conducted using data from PubMed, Embase, Scopus, and international guidelines (NCCN, ESMO, ASCO). The selection focused on evidence published between 2020 and 2025, highlighting molecularly defined PDAC subsets and the current status of targeted therapies. Results: Actionable genomic alterations in PDAC include KRAS G12C mutations, BRCA1/2 and PALB2-associated homologous recombination deficiency, MSI-H/dMMR status, and rare gene fusions involving NTRK, RET, and NRG1. While only a minority of patients are eligible for targeted treatments, early-phase trials and real-world data have shown promising results in these subgroups. Testing molecular profiling is increasingly standard in advanced PDAC. Conclusions: Despite the rarity of targetable mutations, systematic molecular profiling is critical in advanced PDAC to guide off-label therapy or clinical trial enrollment. A practical framework for identifying and acting on molecular targets is essential to bridge the gap between precision oncology and clinical management. Full article

Leaf loss caused by pest infestations poses a serious threat to forest health. The leaf loss rate (LLR) refers to the percentage of the overall tree-crown leaf loss per unit area and is an important indicator for evaluating forest health. Therefore, rapid and accurate acquisition of the LLR via remote sensing monitoring is crucial. This study is based on drone hyperspectral and LiDAR data as well as ground survey data, calculating hyperspectral indices (HSI), multispectral indices (MSI), and LiDAR indices (LI). It employs Savitzky–Golay (S–G) smoothing with different window sizes (W) and polynomial orders (P) combined with recursive feature elimination (RFE) to select sensitive features. Using Random Forest Regression (RFR) and Convolutional Neural Network Regression (CNNR) to construct a multidimensional (horizontal and vertical) estimation model for LLR, combined with LiDAR point cloud data, achieved a three-dimensional visualization of the leaf loss rate of trees. The results of the study showed: (1) The optimal combination of HSI and MSI was determined to be W11P3, and the LI was W5P2. (2) The optimal combination of the number of sensitive features extracted by the RFE algorithm was 13 HSI, 16 MSI, and hierarchical LI (2 in layer I, 9 in layer II, and 11 in layer III). (3) In terms of the horizontal estimation of the defoliation rate, the model performance index of the CNNR_HSI model (MPI = 0.9383) was significantly better than that of RFR_MSI (MPI = 0.8817), indicating that the continuous bands of hyperspectral could better monitor the subtle changes of LLR. (4) The I-CNNR_HSI+LI, II-CNNR_HSI+LI, and III-CNNR_HSI+LI vertical estimation models were constructed by combining the CNNR_HSI model with the best accuracy and the LI sensitive to different vertical levels, respectively, and their MPIs reached more than 0.8, indicating that the LLR estimation of different vertical levels had high accuracy. According to the model, the pixel-level LLR of the sample tree was estimated, and the three-dimensional display of the LLR for forest trees under the pest stress of larch caterpillars was generated, providing a high-precision research scheme for LLR estimation under pest stress. Full article

Ultrahigh resolution fine particulate matter (PM_2.5) mass concentration remote sensing products are crucial for atmospheric environmental monitoring, pollution source verification, health exposure risk assessment, and other fine-scale applications in urban environments. This study developed an ultrahigh resolution retrieval algorithm to estimate 30 m resolution PM_2.5 mass concentrations over urban areas from Landsat-8 and Sentinel-2A/B satellite measurements. The algorithm utilized aerosol optical depth (AOD) products retrieved from the Landsat-8 OLI and Sentinel-2 MSI measurements from 2017 to 2020, combined with multi-source auxiliary data to establish a PM_2.5-AOD relationship model across China. The results showed an overall high coefficient of determination (R²) of 0.82 and 0.76 for the model training accuracy based on samples and stations, respectively. The model prediction accuracy in Beijing and Wuhan reached R² values of 0.86 and 0.85. Applications in both cities demonstrated that ultrahigh resolution PM_2.5 has significant advantages in resolving fine-scale spatial patterns of urban air pollution and pinpointing pollution hotspots. Furthermore, an analysis of point source pollution at a typical heavy pollution emission enterprise confirmed that ultrahigh spatial resolution PM_2.5 can accurately identify the diffusion trend of point source pollution, providing fundamental data support for refined monitoring of urban air pollution and air pollution prevention and control. Full article

Microsatellite instability (MSI) is a clinically important biomarker for predicting responses to immune checkpoint inhibitors and identifying individuals with Lynch syndrome. Although MSI detection has been incorporated into Illumina’s next-generation tumor sequencing workflows, interpretation of the results remains challenging due to the absence of standardized thresholds and reporting criteria. In this retrospective study, we assessed the performance of MSI detection using Illumina’s targeted NGS panels—TruSight Tumor 170 and TruSight Oncology 500. The NGS-based MSI results were compared to those obtained by the reference method, MSI-PCR, across multiple tumor types in a real-world cohort of 331 cancer patients. The NGS method demonstrated high concordance overall (AUC = 0.922), though sensitivity was lower in colorectal cancers (AUC = 0.867) due to broader score variability and overlapping distributions. Our findings support the clinical utility of Illumina’s NGS-derived MSI scores for identifying MSI-H tumors, with a recommended MSI score cut-off value of ≥13.8%. Additionally, a borderline group was introduced, defined by an MSI score ranging from ≥8.7% to <13.8%. Within this range, the integration of TMB into the MSI classification workflow significantly improves diagnostic accuracy. For samples that remain inconclusive, orthogonal confirmation using MSI-PCR is advised to ensure accurate MSI classification. Full article

Lake Chinchaycocha, Peru’s second-largest high-altitude lake and a Ramsar-designated wetland of international importance, is increasingly threatened by anthropogenic pollution and hydroclimatic shifts. This study integrates Sentinel-2 multispectral imagery with in situ water quality data from Peru’s National Water Observatory to assess spatiotemporal dynamics in 31 physicochemical parameters between 2018 and 2024. We evaluated 40 empirical algorithms developed globally for Sentinel-2 and tested their transferability to this ultraoligotrophic Andean system. The results revealed limited predictive accuracy, underscoring the need for localized calibration. Subsequently, we developed and validated site-specific models for ammoniacal nitrogen, electrical conductivity, major ions, and trace metals, achieving high predictive performance during the rainy season (R² up to 0.95). Notably, the study identifies consistent seasonal correlations—such as between total copper and ammoniacal nitrogen—and strong spectral responses in Band 1, linked to runoff dynamics. These findings highlight the potential of combining public monitoring data with remote sensing to enable scalable, cost-effective assessment of water quality in optically complex, high-Andean lakes. The study provides a replicable framework for integrating national datasets into operational monitoring and environmental policy. Full article

Endometrial carcinoma (EC) is the most common gynaecological malignancy in developed nations, exhibiting significant molecular heterogeneity that impacts prognosis and treatment response, particularly in advanced or recurrent settings. Traditional classification is increasingly supplemented by molecular subtyping (POLE-ultramutated, MSI-high/dMMR, NSMP, p53-mutated/CNH), which provides crucial prognostic information and predicts benefit from immunotherapy. This review summarizes the landscape of predictive biomarkers for immune checkpoint inhibitor (ICI) therapy in EC, emphasizing a new therapeutic scenario for advanced and recurrent EC. Mismatch repair deficiency (dMMR) or high microsatellite instability (MSI-H), leading to high tumor mutational burden (TMB) and increased neoantigen production, is the most established predictor, resulting in FDA approvals for pembrolizumab and dostarlimab in this subgroup. POLE mutations also confer hypermutation and high immunogenicity, predicting a favorable ICI response. Other biomarkers, including PD-L1 expression and TMB, show variable correlation with response and require further standardization. The tumor immune microenvironment, including tumor-infiltrating lymphocytes (TILs), also influences treatment outcomes. Clinical trials have demonstrated significant survival benefits for ICIs combined with chemotherapy (e.g., dostarlimab/pembrolizumab + carboplatin/paclitaxel) in first-line settings, especially for dMMR/MSI-H EC, and for ICI combinations with targeted agents (e.g., lenvatinib + pembrolizumab) in previously treated patients. Integrating molecular classification and validated biomarkers is essential for optimizing patient selection and developing personalized immunotherapy strategies for EC. Full article

Alkaline earth elements have emerged as crucial electronic modifiers for regulating active sites in catalytic systems, yet the influence of metal–support interactions (MSIs) between alkaline earth compounds and active metals remains insufficiently understood. This study systematically investigated Pt nanoparticles supported on alkaline earth carbonates (Pt/MCO₃, M = Mg, Ca, Ba) for low-temperature propylene combustion. The Pt/BaCO₃ catalyst exhibited outstanding performance, achieving complete propylene conversion at 192 °C, significantly lower than Pt/MgCO₃ (247 °C) and Pt/CaCO₃ (282 °C). The enhanced activity stemmed from distinct MSI effects among the supports, with Pt/BaCO₃ showing the poorest electron enrichment and lowest propylene adsorption energy. Through kinetic analyses, ¹⁸O₂ isotope labeling, and comprehensive characterization, the reaction was confirmed to follow the Mars–van Krevelen (MvK) mechanism. Pt/BaCO₃ achieves an optimal balance between propylene and oxygen adsorption, a critical factor underlying its superior activity. Full article

Background: Cognitive impairment (CI) is a common and disabling symptom in patients with relapsing–remitting multiple sclerosis (RRMS), potentially emerging at any stage, including preclinical phases. Despite its impact on quality of life, CI often goes unrecognized, as clinical follow-up typically focuses on motor and sensory symptoms. Validated tools, such as the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) and patient-reported outcomes (PROs), should be integrated into routine evaluations beyond the Expanded Disability Status Scale (EDSS). Objective: The objective of this study was to evaluate cognitive impairment and quality of life in patients with RRMS using the BICAMS and PROs. Methods: This cross-sectional, descriptive study included patients with RRMS under follow-up at a tertiary hospital in San Luis Potosí, Mexico. Participants underwent cognitive screening with the BICAMS battery and completed the MSQoL-54 (quality of life), FSMC (fatigue), and MSIS-29 (functional impact) scales. Statistical analyses included ANOVA, the Kruskal–Wallis test, and Pearson correlations. Results: Nineteen patients were evaluated (73.7% female, mean age 36.5 ± 8.9 years). BICAMS results showed variable cognitive performance, with no significant differences across treatment groups for processing speed (p = 0.222), verbal memory (p = 0.082), or visuospatial memory (p = 0.311). A significant correlation was found between verbal and visuospatial memory (r = 0.668, p = 0.002). Total quality of life differed significantly across treatments (F = 8.007, p = 0.029), with a strong correlation between overall quality of life and general health perception (r = 0.793, p < 0.001). Fatigue and MSIS scores showed no association with treatment. Conclusions: Cognitive impairment is common in RRMS and can be detected using brief assessment tools, such as the BICAMS. Incorporating cognitive screening and PROs into clinical practice is essential to guide comprehensive management. Full article

Campus climate research has long been a focus of higher education scholarship; however, studies show that inequalities and a pervasive sense of not belonging continue to negatively affect students. This paper presents the results of a campus-wide survey conducted at a Minority-Serving Institution (MSI), with a sample of 820 undergraduate, master’s, Ph.D., and non-degree students. The authors explore students’ experiences on campus in relation to their identities as well as students’ perceptions of campus climate. Specifically, the paper examines students’ intergroup relations and how these influence their sense of belonging. The survey instrument developed in the frame of this project also included questions designed to assess opportunities students have to develop key values, attitudes, skills, knowledge, and critical understanding related to intercultural and democratic competences necessary for life and work in multicultural societies. This study identifies the areas students perceive as important for development, highlighting which values, attitudes, skills, knowledge, and critical understanding they have had the opportunity to cultivate during their time at the university and those they would like to develop further. The authors hope these findings will inform efforts to strengthen institutional support for more inclusive practices on culturally diverse university campuses and provide evidence-based guidance for designing effective pedagogical interventions. Full article

Objectives: There is a scarcity of studies on multisite infections (MSIs) caused by carbapenem-resistant Klebsiella pneumoniae (CRKP). The primary objectives of this research were to determine the clinical characteristics of CRKP MSI, and the risk factors of infection and mortality. Methods: Patients with a CRKP bloodstream infection (BSI) were enrolled retrospectively between January 2017 and December 2021 in Xijing Hospital, China. The risk factors for CRKP MSI and mortality were evaluated. The demographic data, clinical and microbiological characteristics, therapy and outcomes were analyzed. Results: Among 101 patients, 74.3% (75/101) had a diagnosis of CRKP MSI, while 25.7% (26/101) of CRKP non-MSI. The overall case fatality rate was 42.6% (43/101). Multivariate analysis indicated that previous surgery (OR 3.971, 95% CI 1.504–10.480, p = 0.005) and ICU admission (OR 3.322, 95% CI 1.252–8.816, p = 0.016) were independent risk factors for CRKP MSI. ICU admission (OR 4.765, 95% CI 1.192–19.054, p = 0.027), a Pitt bacteremia score (PBS) > 4 (OR 3.820, 95% CI 1.218–11.983, p = 0.022) and thrombocytopenia (OR 8.650, 95% CI 2.573–29.007, p < 0.001) were independent risk factors for mortality due to CRKP MSI. Conclusions: Our findings confirmed that CRKP MSIs were associated with poorer outcomes. To improve prognosis, early screening of individuals at the highest risk is vital. Full article

Mangroves form the dominant coastal plant community of low-energy tropical intertidal habitats and provide critical ecosystem services to humans and the environment. However, more frequent and increasingly powerful hurricanes and storm surges are creating additional pressure on the natural resilience of these threatened coastal ecosystems. Advances in remote sensing techniques and approaches are critical to providing robust quantitative monitoring of post-storm mangrove forest recovery to better prioritize the often-limited resources available for the restoration of these storm-damaged habitats. Here, we build on previously utilized spatial and temporal ranges of European Space Agency (ESA) Sentinel satellite imagery to monitor and map the recovery of the mangrove forests of the British Virgin Islands (BVI) since the occurrence of back-to-back category 5 hurricanes, Irma and Maria, on September 6 and 19 of 2017, respectively. Pre- to post-storm changes in coastal mangrove forest health were assessed annually using the normalized difference vegetation index (NDVI) and moisture stress index (MSI) from 2016 to 2023 using Google Earth Engine. Results reveal a steady trajectory towards forest health recovery on many of the Territory’s islands since the storms’ impacts in 2017. However, some mangrove patches are slower to recover, such as those on the islands of Virgin Gorda and Jost Van Dyke, and, in some cases, have shown a continued decline (e.g., Prickly Pear Island). Our work also uses a linear ANCOVA model to assess a variety of geospatial, environmental, and anthropogenic drivers for mangrove recovery as a function of NDVI pre-storm and post-storm conditions. The model suggests that roughly 58% of the variability in the 7-year difference (2016 to 2023) in NDVI may be related by a positive linear relationship with the variable of population within 0.5 km and a negative linear relationship with the variables of northwest aspect vs. southwest aspect, island size, temperature, and slope. Full article

Objective: This study aimed to assess the feasibility and acceptability of a Culinary Medicine and Wellness (CMW) class among undergraduate college students attending a U.S. Minority-Serving Institution (MSI), as well as their food security, mental health status, and eating behaviors. Methods: This pre- and post-intervention study was conducted at an MSI in a Southeastern U.S. University, where students enrolled in a 15-week, three-credit CMW class equivalent to 2.5 h per week and received instruction on cooking and preparing healthy meals on a budget. The primary outcomes were acceptability and feasibility of the CMW class. Participants’ food security status, mental health status, and fruit and vegetable intake were also assessed. Program evaluation utilized thematic analysis and descriptive statistics, and trend analyses of outcomes were performed. Results: Eleven participants completed both surveys. The average age was 24 years, with 73% identifying as Black/African American. All participants were female and experienced low or very low food insecurity, and most reported moderate stress levels. All participants reported they would recommend the CMW class to others, with 73% rating it as excellent. Additionally, 82% felt they had learned valuable cooking and budgeting skills. Conclusions: The acceptability and feasibility of a CMW class among college students at an MSI suggests a promising approach to improving cooking skills, enhancing nutrition knowledge, increasing fruit and vegetable intake, and reducing stress. Full article

Pine wilt disease (PWD), caused by Bursaphelenchus xylophilus Steiner & Buhrer (pine wood nematodes, PWN), impacts forest carbon sequestration and climate change. However, satellite-based PWD monitoring is challenging due to the limited spatial resolution of Sentinel’s MSI sensor, which reduces its sensitivity to subtle biochemical alterations in foliage. We have, therefore, developed a slope product index (SPI) for effective detection of PWD using single-date satellite imagery based on spectral gradients in the visible and near-infrared (VNIR) range. The SPI was compared against 15 widely used vegetation indices and demonstrated superior robustness across diverse test sites. Results show that the SPI is more sensitive to changes in chlorophyll content in the PWD detection, even under potentially confounding conditions such as drought. When integrated into Random Forest (RF) and Back-Propagation Neural Network (BPNN) models, SPI significantly improved classification accuracy, with the multivariate RF model achieving the highest performance and univariate with SPI in BPNN. The generalizability of SPI was validated across test sites in distinct climate zones, including Zhejiang (accuracyZ_Mean = 88.14%) and Shandong (accuracyS_Mean = 78.45%) provinces in China, as well as Portugal. Notably, SPI derived from Sentinel-2 imagery in October enables more accurate and timely PWD detection while reducing field investigation complexity and cost. Full article