Search Results (710)

Background: Tongue squamous cell carcinoma (TSCC) is an aggressive oral malignancy characterized by early submucosal invasion and a high risk of cervical lymph node metastasis. Accurate and timely diagnosis is essential, but it remains challenging when relying solely on conventional imaging and histopathology. This systematic review aimed to evaluate studies applying artificial intelligence (AI) in the diagnostic imaging of TSCC. Methods: This review was conducted under PRISMA 2020 guidelines and included studies from January 2020 to December 2024 that utilized AI in TSCC imaging. A total of 13 studies were included, employing AI models such as Convolutional Neural Networks (CNNs), Support Vector Machines (SVMs), and Random Forest (RF). Imaging modalities analyzed included MRI, CT, PET, ultrasound, histopathological whole-slide images (WSI), and endoscopic photographs. Results: Diagnostic performance was generally high, with area under the curve (AUC) values ranging from 0.717 to 0.991, sensitivity from 63.3% to 100%, and specificity from 70.0% to 96.7%. Several models demonstrated superior performance compared to expert clinicians, particularly in delineating tumor margins and estimating the depth of invasion (DOI). However, only one study conducted external validation, and most exhibited moderate risk of bias in patient selection or index test interpretation. Conclusions: AI-based diagnostic tools hold strong potential for enhancing TSCC detection, but future research must address external validation, standardization, and clinical integration to ensure their reliable and widespread adoption. Full article

Snow serves as a crucial water source for vegetation growth on the Mongolian Plateau, and its temporal and spatial variations exert profound influences on terrestrial vegetation phenology. In recent years, global climate change has led to significant changes in snow and vegetation start of growing season (SOS). Therefore, it is necessary to study the mechanism of snow cover on vegetation growth and changes on the Mongolian Plateau. The study found that the spatial snow cover fraction (SCF) of the Mongolian Plateau ranged from 50% to 60%, and the snow melt date (SMD) ranged from day of the year (DOY) 88 to 220, mainly concentrated on the northwest Mongolian Plateau mountainous areas. Using different SOS methods to calculate the vegetation SOS distribution map. Vegetation SOS occurs earlier in the eastern part compared to the western part of the Mongolian Plateau. In this study, we assessed spatiotemporal distribution characteristics of snow on the Mongolian Plateau over the period from 2001 to 2023. The results showed that the SOS of the Mongolian Plateau was mainly concentrated on DOY 71-186. The Cox survival analysis model system established SCF and SMD on vegetation SOS. The SCF standard coefficient is 0.06, and the SMD standard coefficient is 0.02. The SOS_NDVI coefficient is −0.15, and the SOS_NDGI coefficient is −0.096. The results showed that the vegetation SOS process exhibited differential response characteristics to snow driving factors. These research results also highlight the important role of snow in vegetation phenology and emphasize the importance of incorporating the unique effects of vegetation SOS on the Mongolian Plateau. Full article

This study investigates the genetic diversity and population structure of Castanopsis tribuloides, a vital tree species in Asian forest ecosystems. Understanding the genetic patterns of keystone forest species provides critical insights into forest resilience and ecosystem function and informs conservation strategies. We analyzed population samples collected from three distinct locations within Doi Suthep Mountain in northern Thailand using Short Tandem Repeat (STR) markers to assess both intra- and inter-population genetic relationships. DNA was extracted from leaf samples and analyzed using a panel of polymorphic microsatellite loci specifically optimized for Castanopsis species. Statistical analyses included the assessment of forensic parameters (number of alleles, observed and expected heterozygosity, gene diversity, polymorphic information content), population differentiation metrics (G_ST), inbreeding coefficients (F_IS), and gene flow estimates (N_m). We further examined population history through bottleneck analysis using three models (IAM, SMM, and TPM) and visualized genetic relationships through principal coordinate analysis and cluster analysis. Our results revealed significant patterns of genetic structuring across the sampled populations, with genetic distance metrics showing statistically significant differentiation between certain population pairs. The PCA and cluster analyses confirmed distinct population groupings that correspond to geographic distribution patterns. These findings provide the first comprehensive assessment of C. tribuloides population genetics in this region, establishing baseline data for monitoring genetic diversity and informing conservation strategies. This research contributes to our understanding of how landscape features and ecological factors shape genetic diversity patterns in essential forest tree species, with implications for managing forest genetic resources in the face of environmental change. Full article

When people overextend their step length, it leads to an increase in vertical movement and braking force. The overextension elevates landing impacts, which may increase pain in the knees or lower back. The objective of this study was to examine the effects of soft-landing walking techniques in a 90 min, instructor-led group class for older adults. To evaluate a landing impact, an accelerometer measurement system (Descente LTD., Tokyo, Japan) was used to measure a participant 10 meter (m) of walking. Assessment outcomes included the average number of steps, step length, upward acceleration which reflects the landing impact, and survey questions. A total of 223 older adults (31 men, 192 women, mean age 74.4 ± 5.7 years) completed the walking lesson. Following the lesson, participants decreased their step lengths and reduced upward acceleration, along with an increased step count. The number of steps increased, and a positive correlation (r = 0.73, p < 0.01) was observed between the rate of change in step length and upward acceleration. Over 95% of participants gave high marks for practicality and understanding the accelerometer measurements. The information derived from this study will provide valuable insight into the effectiveness of soft-landing techniques as a promotion of a healthy walking program for older adults. Full article

Histopathological grading of oral squamous cell carcinoma is currently based on differentiation of cells, while additional histological parameters, such as the tumor–stroma ratio (TSR), tumor budding (TB), or the combined TSR/tumor budding model could better assess tumor biological behavior and monitoring of patients. Background/Objectives: To integrate risk factors associated with tumor progression: the TSR, TB and TSR/tumor budding model, whose prognostic significance in oral cancer has not yet been evaluated. Methods: An observational cohort retrospective study assembled according to STROBE guidelines on histological materials from 196 patients with invasive squamous cell carcinoma of the oral cavity. The goal of the analysis was to evaluate the association between the tumor stroma ratio, tumor budding, and the combined model of TSR/TB with the clinical and pathologic features of patients with squamous cell carcinoma of the oral cavity and to determine the prognostic value of this model in relation to disease-free survival (DFS) Results: The analysis did not show that the tumor stroma ratio (TSR), tumor budding, and the combined model of TSR/tumor budding were statistically significantly associated with the occurrence of metastatic disease at the start of treatment or during postoperative follow-up, but confirmed the value of depth-of-invasion (DOI) as a negative prognostic factor (HR 15.3, p < 0.001). Conclusions: The TSR, TB, and the combined TSR/TB model were not found to be statistically significant predictors for the disease progression in the Cox regression survival analysis but were found to have a significant correlation with known negative prognostic factors: DOI, neural invasion, and T category. Full article

Understanding how flowering phenology varies across spatial scales is essential for assessing plant responses to environmental heterogeneity under climate change. In this study, we investigated the flowering phenology of the plant species Taraxacum officinale across five sites in an agricultural region of Wanju, Republic of Korea. Each site contained five 1 m × 1 m quadrats, where the number of flowering heads was recorded at 1- to 2-day intervals during the spring flowering period (February to May). We applied the nlstimedist package in R to model flowering distributions and to estimate key phenological metrics including flowering onset (5%), peak (50%), and end (95%). The results revealed substantial variation in flowering timing and duration at both the intra-site (quadrat-level) and inter-site (site-level) scales. Across all sites, the mean onset, peak, end, and duration of flowering were day of year (DOY) 89.6, 101.5, 117.6, and 28.0, respectively. Although flowering onset showed relatively small variation across sites (DOY 88 to 92), flowering peak (DOY 97 to 108) and end dates (DOY 105 to 128) exhibited larger differences at the site level. Sites with dry soils and regularly mowed Zoysia japonica vegetation with minimal understory exhibited shorter flowering durations, while those with moist soils, complex microtopography, and diverse slope orientations showed delayed and prolonged flowering. These findings suggest that microhabitat variability—including landform type, slope direction, soil water content, and soil temperature—plays a key role in shaping local flowering dynamics. Recognizing this fine-scale heterogeneity is essential for improving phenological models and informing site-specific climate adaptation strategies. Full article

This study aimed to predict the potential habitats of Luciola unmunsana using a species distribution model (SDM). Luciola unmunsana is an endemic species that lives only in South Korea, and because its females do not have genus wings and are less fluid, it is difficult to collect, so research related to its distribution and restoration is relatively understudied. Therefore, this study predicted the potential habitats of Luciola unmunsana across South Korea using the single model Maximum Entropy (MaxEnt) and a multi-model ensemble model to prepare basic data necessary for a conservation and habitat restoration plan for the species. A total of 39 points of occurrence were built based on public data and prior research from the Jeonbuk Green Environment Support Center (JGESC), the Global Biodiversity Information Facility (GBIF), and the National Institute of Biological Resources (NIBR). Among the input variables, climate variables were based on the shared socioeconomic pathway (SSP) scenario-based ecological climate index, while nonclimate variables were based on topography, land cover maps, and the Enhanced Vegetation Index (EVI). The main findings of this study are summarized below. First, in predicting Luciola unmunsana potential habitats, the EVI, water network analysis, land cover, and annual precipitation (Bio12) were identified as good predictors in both models. Accordingly, areas with high vegetation activity in their forests, adjacent to water resources, and stable humidity were predicted as potential habitats. Second, by overlaying the predicted potential habitats and highly significant variables, we found that areas with high vegetation vigor within their forests, proximity to water systems, and relatively high annual precipitation, which can maintain stable humidity, are potential habitats for Luciola unmunsana. Third, literature surveys used to predict potential habitat sites, including Geumsan-gun, Chungcheongnam-do, Yeongam-gun, Jeollabuk-do, Mudeungsan Mountain, Gwangju-si, Korea, and Gijang-gun, Busan-si, Korea, confirmed the occurrence of Luciola unmunsana. This study is significant in that it is the first to develop a regional SDM for Luciola unmunsana, whose population is declining due to urbanization. In addition, by applying various environmental variables that reflect ecological characteristics, it contributes to more accurate predictions of the potential habitats of this species. The predicted results can be used as basic data for the future conservation of Luciola unmunsana and the establishment of habitat restoration strategies. Full article

Rubber Tree (Hevea brasiliensis) phenology critically influences tropical plantation productivity and carbon cycling, yet topography and climate impacts remain unclear. By integrating multi-sensor remote sensing (2001–2020) and Google Earth Engine, this study analyzed spatiotemporal dynamics in Hainan Island, China. Results reveal that both the start (SOS occurred between early and late March: day of year, DOY 60–81) and end (EOS occurred late January to early February: DOY 392–406, counted from the previous year) of the growing season exhibit progressive delays from the southeast to northwest, yielding a 10–11 month growing season length (LOS). Significantly, LOS extended by 4.9 days per decade (p < 0.01), despite no significant trends in SOS advancement (−1.1 days per decade) or EOS delay (+3.7 days per decade). Topographic modulation was evident: the SOS was delayed by 0.27 days per 100 m elevation rise (p < 0.01), while the EOS was delayed by 0.07 days per 1° slope increase (p < 0.01). Climatically, a 100 mm precipitation increase advanced SOS/EOS by approximately 1.0 day (p < 0.05), preseasonally, a 1 °C February temperature rise advanced the SOS and EOS by 0.49 and 0.53 days, respectively, and a 100 mm January precipitation increase accelerated EOS by 2.7 days (p < 0.01). These findings advance our mechanistic understanding of rubber phenological responses to climate and topographic gradients, providing actionable insights for sustainable plantation management and tropical forest ecosystem adaptation under changing climatic conditions. Full article

Objectives: In the animal model, we aim to evaluate the bone behavior in two innovative and different laser-treated (L1–L2) titanium implants compared to sandblasted and acid-etched (SBAE) used as control. Materials and Methods: A total of twenty-seven dental implants (8.5 × 3.3 mm) used for the study (Sweden & Martina, Due Carraie Padova-Italy) were placed in three Pelibuey female sheep. Implant surface profilometric, contact angle and EDX analysis were detected. After 15, 30 and 90 days, histological, histomorphometric, SEM-EDX analysis and Bone-to-implant Contact (BIC), Dynamic Osseointegration Index (DOI) and Bone Quality Index (BQI) (as Calcium and Phosphorous atomic percentages ratio) were performed. Results: All surfaces showed relevant profilometric and wettability differences. After 15 days, BIC₁₅ showed great differences in L2 (42.1 ± 2.6) compared to L1 (5.2 ± 3.1) and SBAE (23.3 ± 3.9) as well as after 30 days (L2 (82.4 ± 2.2), L1 (56.2 ± 1.3) and SBAE (77.3 ± 0.4)). After 90 days, relevant lower BIC₉₀ values were detected in L1 (68.4 ± 0.2) compared to L2 (86.4 ± 0.1) and SBAE (86.2 ± 0.6). The DOI showed higher rates of bone growth in L2 after 15 (DOI₁₅ = 2.81) and 30 days (DOI₃₀ = 2.83), compared to L1 (DOI₁₅ = 0.38, DOI₃₀ = 3.40) and SBAE (DOI₁₅ = 1.55, DOI₃₀ = 2.58). The DOI₉₀ drastic slowdown in SBAE (0.96), L1 (0.76), and L2 (0.95) confirmed the Early Osseointegration (EO) as a crucial phase. Moreover, before loading, the lower global BQI in L1 (Ca 44.43 ± 0.08–P 46.14 ± 5.15) and SBAE (Ca 45.31 ± 2.08–P 48.28 ± 1.12) compared to L2 (Ca 79.81 ± 2.08–P 81.85 ± 3.14) allows to assert that osseointegration process and bone healing could not be considered complete if compared to the native bone. Conclusions: The BIC, DOI, and BQI results showed that osseointegration is a dynamic process, confirming the crucial role of surface characteristics able to influence it, especially the early osseointegration (EO) phase. The short-time L2 implants’ higher bone quantity and quality results, compared to L1 and SBAE, suggested the fundamental role of this innovative laser-obtained surface in “secondary stability” and predictable long-term clinical outcomes. Full article

This study investigates the attributes influencing the adoption of fintech services for sustainable investment within the blue economy. Specifically, it integrates the Diffusion of Innovations (DOI) theory and the Technology Acceptance Model (TAM) to examine how the perceived relative advantages, compatibility, complexity, trialability, and observability of fintech services influence their perceived ease of use and perceived usefulness, and it explores their impact on the intention to adopt fintech services. Finally, the study assesses how the intention to adopt fintech services affects sustainable investment decisions in the blue economy. Data were collected from 224 stakeholders in the blue economy sectors in India during the summer of 2024 and analyzed using structural equation modeling with partial least squares (SEM-PLS). The results reveal which attributes significantly influence perceived ease of use and perceived usefulness. Additionally, perceived ease of use and perceived usefulness significantly influence the intention to adopt fintech services. The intention to adopt fintech services positively impacts sustainable investment decisions in the blue economy. This study provides a comprehensive framework for advancing fintech services that support sustainable investment decisions, thereby contributing to the growth of the blue economy. Full article

Background and Objectives: Calcium is an essential mineral that plays a vital role in fetal development and maternal health during pregnancy. The World Health Organization recommends a daily calcium intake of 1.5–2 g for pregnant adult women. Calcium deficiency during gestation may lead to complications, such as gestational hypertension, preeclampsia, loss of bone mineral density, impaired fetal development, and other adverse pregnancy outcomes. The aim of the present review is to evaluate the current clinical evidence on calcium intake during pregnancy. Methods: The present systematic review was conducted according to the PRISMA 2020 statement by searching two major databases, PubMed and Mendeley. The study protocol was registered in the Open Science Framework (DOI: osf.io/rvj7z). Inclusion criteria were clinical trials on calcium supplementation during pregnancy. Exclusion criteria were clinical guidelines, reviews, case reports, case series, letters, and commentaries. The Newcastle–Ottawa Scale was used to assess the risk of bias in the included studies. Results: Initially, 451 publications were identified, and after removal of duplicates and screening of titles and/or abstracts and/or full texts, 34 studies were included. The number of participants ranged between 30 and 22,000 women. Calcium supplementation was associated with lower incidence of and less severe gestational hypertension and preeclampsia, lower risk of preterm birth, longer pregnancy duration and higher neonatal birth weight, and improved maternal bone mineral density postpartum. When the doses were split up into smaller doses, the benefits were strongest with high-dose regimens (1.5–2 g/day). Conclusions: Calcium supplementation during pregnancy has beneficial effects on maternal and neonatal health, especially in populations with insufficient dietary daily calcium intake and women at high risk of hypertensive disorders. Daily dose may vary according to individual needs, daily dietary calcium intake, and general health status. Further large-scale randomized controlled trials (RCTs) are necessary to confirm these findings. Full article

Background: A number of factors might affect survival in oral squamous cell carcinoma. Nodal status is one of the most important prognosticators affecting survival. Studies have shown that pattern of invasion is an important aspect related to survival. Study design: retrospective single-center study (original article). Objectives: Our study aimed at evaluating the factors affecting mandibular invasion, lymph node metastasis, and extracapsular spread in oral squamous cell carcinoma and the survival factors associated with it. Methods: Patient records were evaluated to identify factors influencing primary outcome and survival. Cox regression analysis and Kaplan Meir were applied to evaluate the outcomes. Youden’s index was used to determine a cut-off value for depth of invasion and lymph node size affecting outcome. A p value of <0.05 was considered statistically significant. Results: The study evaluated 162 patients with oral cancer. The cut-off value for DOI was 6.5 mm, significantly affecting mandibular invasion and cervical metastasis. The cut-off value for lymph node size was 2.95 cm, significantly affecting extracapsular spread and overall survival. An aggressive pattern of invasion significantly affects mandibular invasion, cervical metastasis, and survival. Conclusion: An aggressive pattern of invasion and depth of invasion are independent risk factors for cervical lymph node metastasis and mandibular invasion. The independent risk factor for extracapsular spread is lymph node size. Lymph node metastasis and nodal size, pattern of invasion, mandibular invasion, and extracapsular spread are independent risk factors affecting overall survival. Full article

Unlike traditional yield mapping, which is conducted using costly yield sensors mounted on combine harvesters to collect post-harvest data, yield potential prediction using remote sensing data is considered a low-cost alternative. In this study, an effort was made to address the research gap concerning the effectiveness of phenological modeling in crop yield potential prediction using machine learning. Combinations of seven vegetation indices from Sentinel-2 imagery and seven phenology metrics were evaluated for the prediction of maize and soybean yield potential. Ground truth yield data were provided by the Quantile Loss Domain Adversarial Neural Network (QDANN) database, with 1000 samples randomly selected per year from 2019 to 2022 for Iowa and Illinois. Four machine learning algorithms were tested: random forest (RF), support vector machine regression (SVM), multivariate adaptive regression splines (MARS), and Bayesian regularized neural networks (BRNNs). Across all evaluations, RF was found to outperform the other models in both cross-validation and final model accuracy metrics. Vegetation index values at peak of season (POS) and phenological timing, expressed as the day of year (DOY) of phenological events, were identified as the most influential covariates for predicting yield potential in particular years for both maize and soybean. Full article

Background/Objectives: This study describes multiple trials demonstrating the safety and efficacy of a tri-valent vaccine against diseases caused by Porcine Circovirus Types 2a and 2d (PCV2a, PCV2d), Mycoplasma hyopneumoniae, and Lawsonia intracellularis. Methods: For each of the PCV2a and PCV2d onset of immunity (OOIs) and duration of immunity (DOI) studies, 25 pigs were vaccinated with a tri-valent vaccine and 25 with placebo. After dual challenge with PCV2a and porcine reproductive and respiratory virus (PRRSV) (OOI) or single challenge with PCV2d (OOI and DOI), respectively, viremia and lymphoid depletion data were collected. For each of the M. hyopneumoniae OOI and DOI studies, 35 to 70 pigs were vaccinated with the tri-valent vaccine and 35 to 70 with placebo. After M. hyopneumoniae challenge, the lungs were scored for disease. For the L. intracellularis OOI study, 40 to 50 pigs were vaccinated with the tri-valent and 40 to 50 with placebo. After L. intracellularis challenge, the intestines were scored for disease. All pigs were vaccinated at approximately 3 weeks of age, and all placebo vaccines were product matched. Results: Vaccinating pigs with a tri-valent vaccine reduced viremia and lymphoid depletion due to PCV2a and PCV2d, reduced lung lesions due to M. hyopneumoniae and reduced ileum and colonization scores due to L. intracellularis. Conclusions: The trials reported here demonstrated the safety and efficacy of the first ready-to-use PCV2, M. hyopneumoniae, and L. intracellularis vaccine for pigs. Full article

The electrocardiogram (ECG) remains a cornerstone of modern cardiology, providing rapid, non-invasive, and widely accessible diagnostic insights. While ECG interpretation is an essential skill for clinicians, certain patterns can be subtle or atypical, posing diagnostic challenges. In our previous review (doi.org/10.3390/jpm12111754), we explored several uncommon ECG syndromes with significant clinical implications. However, the spectrum of electrocardiographic abnormalities extends far beyond those initially discussed. In this second installment, we expand our discussion of rare and underrecognized ECG syndromes, including Long QT, Jervell and Lange-Nielsen, Romano–Ward, Andersen–Tawil, Timothy, Short QT, and Twiddler’s syndromes, as well as Noonan, Barlow’s, Bundgaard, BRASH, Carvajal, Naxos, and Danon disease. We highlight their clinical context, characteristic findings, and implications for diagnosis and management. These conditions range from acute, life-threatening emergencies requiring immediate intervention to chronic electrical disorders necessitating long-term monitoring and risk stratification. By broadening our focus, we aim to enhance awareness and recognition of these entities, ultimately improving patient outcomes through timely and accurate diagnosis. Full article