Search Results (4,198)

Artificial Intelligence (AI)-based crack detection in buildings uses computer vision and deep learning to automatically identify structural cracks from inspection images. In recent years, many studies have explored this topic, but the overall development of the field, its methodological practices, and the remaining challenges are still not fully clear. Unlike most previous reviews that focus mainly on technical methods, this study combines a large-scale scientometric mapping of the research field with a focused technical analysis of recent AI-based crack detection methods specifically applied to building structures. This study therefore provides a dual-layer review covering research published between 2015 and 2025. A total of 146 Scopus-indexed publications were analysed using Visualization of Similarities viewer (VOSviewer) to examine publication growth, thematic evolution, collaboration patterns, and citation structures. In addition, a focused technical review of 36 highly relevant studies was carried out to analyse task formulations, model families, datasets, evaluation protocols, and methodological practices. The results show a rapid increase in research activity after 2020, largely driven by advances in deep-learning and Unmanned Aerial Vehicle (UAV)-based inspections. At the same time, collaboration networks remain uneven, and citation influence is concentrated in a limited number of research communities. The technical review further shows that most studies focus on detection-level tasks, particularly You Only Look Once (YOLO)-based models, while predictive diagnostics, automated inspection reporting, and decision-oriented Structural Health Monitoring (SHM) are still rarely addressed. Current datasets and evaluation protocols also remain mostly perception-oriented, which makes it difficult to assess robustness, generalisability and long-term predictive capability. Full article

Invasive candidiasis (IC) remains a significant cause of morbidity and mortality among critically ill, hematologic, and neonatal patients worldwide. Rapid and accurate diagnosis is essential to guide timely antifungal therapy and improve outcomes. Among available diagnostic tools, 1,3-β-D-glucan (BDG), a polysaccharide component of the fungal cell wall, has emerged as a key biomarker. BDG assays allow for early detection of probable IC, often preceding positive blood cultures, and offer prognostic information based on serial measurements. Species-specific differences in Candida cell wall composition influence BDG release and diagnostic sensitivity. Candida albicans generally correlates with high BDG levels, whereas Nakaseomyces glabrata, Candida parapsilosis, and Candida auris exhibit variable or lower glucan exposure, limiting assay sensitivity. BDG performance is affected by patient-specific factors, such as prior surgery, transfusions, or coexisting bacterial infections, which may lead to false-positive results. Molecular techniques, including PCR-based assays, provide complementary diagnostic accuracy and species identification, and their combination with BDG testing enhances sensitivity up to 90%. Serial BDG monitoring supports risk stratification and treatment response assessment, with persistent elevations predicting worse outcomes. In neonatal and pediatric populations, optimal cut-off values remain under investigation, highlighting the need for integration with clinical and microbiological data. Overall, BDG represents a valuable adjunct in a multimodal diagnostic workflow, providing both diagnostic and prognostic insights in invasive candidiasis management. Full article

Ultrasound (US) imaging is a widely used diagnostic method in clinics. Real-time-generated US images are used for rapid diagnosis without harm to patients. The quality of US imaging highly depends on the skill of the physician due to the differences among physicians. Techniques for autonomous robotic ultrasound (AU-RUS) acquisitions are expected to become an effective means to improve the level of US diagnosis, reduce the workload of physicians, and improve the standardization of US imaging quality. This paper aims to summarize the current research status of techniques for AU-RUS acquisitions, and to discuss the research trends and challenges regarding related technologies. Firstly, the techniques for AU-RUS acquisitions and systems are outlined. The techniques for teleoperated or autonomous US acquisitions are briefly discussed. Representative RUS acquisition systems are introduced. Then, the current research status of AU-RUS acquisitions is reviewed from four research directions: force sensitivity and control, scanning path-planning and positioning, US treatment guidance, and US image processing technology and quality assessment optimization. This review provides a decision-oriented autonomy perspective by mapping typical methods to workflow components across the stages of perception, decision-making, and execution. We identify major deployment bottlenecks, including safety-verifiable autonomy and failure recovery, motion compensation under deformation, and the lack of standardized, clinically meaningful US image quality metrics. Finally, the shortcomings of current research are summarized and analyzed, and the research trends and challenges for AU-RUS acquisitions are prospected. Full article

Chitooligosaccharides (COS) are short-chain chitosan derivatives with a wide range of biomedical, agricultural, and environmental applications, including antimicrobial therapy, wound healing, and pollutant removal. Reliable quantification of COS is essential but currently relies on high-performance liquid chromatography, mass spectrometry, or capillary electrophoresis, which require costly equipment, complex sample preparation, and are unsuitable for routine or on-site applications. This study reports a rapid, solvent-free, colorimetric assay for COS based on the reaction of 5% aqueous ninhydrin with free amino groups in McIlvaine buffer. The assay was optimized using glucosamine as a model analyte, yielding maximal sensitivity at pH 7.0. The chromophore generated (Ruhemann’s purple) remained stable for over 120 min after reaction, allowing measurements to be taken without strict time constraints. Calibration was linear from 0.4 to 2.2 mM (R² = 0.9926), with low limits of detection (0.006 mM) and quantification (0.018 mM). Increasing absorbance with COS polymerization degree (DP1–DP6) demonstrates specificity for free amino groups, while N-acetyl glucosamine showed a negligible response. Furthermore, the assay was successfully adapted for solid-phase detection on ninhydrin-pretreated filter paper and nitrocellulose, with enhanced sensitivity. This simple, efficient, and low-cost method provides an accessible alternative to instrumental techniques, supporting COS monitoring in laboratory workflows and enabling portable applications in biomedicine, agriculture, and environmental diagnostics. Full article

Escherichia coli, Streptococcus equi subsp. zooepidemicus, Klebsiella oxytoca, and Enterococcus durans are microorganisms capable of causing severe infections, particularly in patients with underlying comorbidities or immune dysfunction. We report a rare clinical case of a 65-year-old man with advanced cardiac and hepatic disease who developed severe diarrheal syndrome followed by septic shock, rapid clinical deterioration, and death. Microbiological examination of autopsy specimens from the intestinal wall and spleen identified Escherichia coli O128 with an enterotoxigenic profile (lt+, st+, eae−), together with Streptococcus equi subsp. zooepidemicus, Klebsiella oxytoca, and Enterococcus durans. Histopathological analysis demonstrated catarrhal enteritis with fibrinous deposits, mucosal edema, vascular congestion, and inflammatory infiltration. Although the microbiological findings were partly derived from autopsy material and postmortem bacterial translocation cannot be completely excluded, the concordance between clinical presentation, laboratory findings, and morphological changes supports the presence of a clinically significant infectious process. To our knowledge, this is the first reported human case of fatal polymicrobial infection involving these four pathogens. The case highlights the potential severity of polymicrobial infections in patients with cirrhosis-associated immune dysfunction and underscores the importance of integrated microbiological and molecular diagnostics for accurate etiological assessment. Full article

Background: Sub-Saharan Africa is undergoing a rapid epidemiological transition marked by a growing burden of non-communicable diseases, including breast, cervical, ovarian, and uterine cancers, which constitute major causes of morbidity and mortality among women in the region; however, comprehensive assessments of long-term trends and regional heterogeneity remain limited. This study examines the burden and temporal trends of breast, cervical, ovarian, and uterine cancers across sub-Saharan Africa from 1990 to 2023. Methods: A retrospective ecological analysis was conducted using data from the latest Global Burden of Disease 2023 study. Age-standardised incidence rates, mortality rates, and disability-adjusted life year rates were estimated for breast, cervical, ovarian, and uterine cancers across 48 sub-Saharan African countries and four sub-regions. Temporal trends were assessed from 1990 to 2023, with percentage changes calculated to characterise epidemiological transitions. Geographic variation and age-specific patterns were examined to identify high-burden settings and priority populations. Results: Between 1990 and 2023, the burden of all four cancers increased substantially across sub-Saharan Africa, with significant regional and country-level heterogeneity. Breast cancer exhibited the largest absolute burden, with incidence increasing by over 120 percent and mortality by more than 80 percent, particularly in Central and Western Africa. Cervical cancer remained the leading cause of cancer-related mortality among women in Eastern and Southern Africa, despite evidence of stabilisation or decline in selected countries. Ovarian and uterine cancers demonstrated sustained upward trends, especially in Central Africa, with high mortality-to-incidence ratios indicating late diagnosis and limited treatment access. Across all cancer types, Central and Eastern sub-Saharan Africa consistently experienced the highest disability-adjusted life year burdens. Conclusions: The burden of the selected cancers in sub-Saharan Africa has increased markedly over the past three decades, with persistent regional inequities reflecting gaps in prevention, early detection, and treatment capacity. Strengthening cancer surveillance systems, expanding equitable access to screening and vaccination programmes, and improving diagnostic and treatment infrastructure are critical to reversing current trends. These findings provide region-specific evidence to guide cancer control priorities and resource allocation across sub-Saharan Africa. Full article

Background/Objectives: Group A Streptococcus (GAS) pharyngitis is a frequent cause of morbidity in pediatric populations, which requires timely identification to prevent complications such as acute rheumatic fever. Rapid antigen detection tests (RADTs) are practical alternatives to throat culture. This study evaluates the diagnostic performance of the RapidFor™ Strep A test. Methods: This prospective clinical study enrolled 389 pediatric patients aged < 18 years with symptoms suggestive of streptococcal pharyngitis. Two throat swabs were collected from each patient: one for rapid antigen testing with RapidFor™ Strep A and one for culture. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Results: Throat culture was positive in 95 of 389 patients (24.4%). The RapidFor™ Strep A test demonstrated a sensitivity of 98.95% (95% confidence interval [CI]: 94.28–99.81%) and a specificity of 96.26% (95% CI: 93.43–97.90%). The PPV was 89.52%, and the NPV was 99.65%. Agreement with culture was excellent (κ = 0.919); in particular, false-positive results accounted for 2.8% and false-negative results accounted for 1.05%. Fever was the strongest clinical indicator associated with positive results. Conclusions: The RapidFor™ Strep A test showed very high diagnostic accuracy compared with throat culture, including an excellent NPV (99.6%), which supports its reliability for ruling out GAS pharyngitis in pediatric settings. The test is an effective screening tool that facilitates timely antibiotic therapy. Full article

C-reactive protein (CRP) level, platelet-to-lymphocyte ratio (PLR), and neutrophil-to-lymphocyte ratio (NLR) have been proposed as biomarkers that reflect disease severity in canine chronic enteropathies. Their correlation with the Canine Chronic Enteropathy Clinical Activity Index (CCECAI) remains unclear. The objective of the present meta-analysis was to assess the correlation between CCECAI and hematological and immunological markers in dogs with CIE. A meta-analysis was conducted to evaluate the correlation of CRP, PLR, and NLR with CCECAI as a diagnostic marker. The PRISMA guidelines were followed to accomplish this procedure. Pooled correlation coefficients were calculated using Fisher’s Z-transformation under random effects models. Heterogeneity and publication bias were examined using standard procedures for the meta-analysis. Eleven studies were found to be fit: five for CRP, four for NLR, and four for PLR. The pooled correlation for CRP level was 0.229 (95% CI: 0.143–0.311, p < 0.001), with consistent findings across studies (I² = 0%). PLR demonstrated a moderate correlation (pooled r = 0.381, 95% CI: 0.238–0.508, p < 0.001; I² = 41%), while NLR showed a slightly stronger correlation (pooled r = 0.410, 95% CI: 0.286–0.521, p < 0.001) but with substantial heterogeneity (I² = 68%). Publication bias analyses indicated modest asymmetry for CRP and PLR, with Egger’s regression significant for both, whereas the NLR showed no clear evidence of bias. Trim-and-fill adjustments slightly attenuated the pooled estimates but did not alter the statistical significance. In conclusion, the correlation between CCECAI and NLR is the most promising biomarker, followed closely by PLR, whereas CRP has a weaker predictive value. The correlation between CCECAI and each of NLR and PLR may provide rapid and reliable diagnostic information about CIE in dogs. Full article

Field-effect transistor (FET) biosensors using graphene have become one of the most promising biosensing platforms for the early diagnosis of diseases with features such as high sensitivity, label-free detection and application compatibility with point-of-care systems. Herein, we critically discuss recent advances in graphene FET (GFET) biosensor development toward clinically relevant biomarkers associated with representative diseases including cancer, neurodegenerative disease, infectious disease, and inflammatory conditions. Recent progress was reviewed to evaluate GFET architectures, surface functionalization methods, and detection quality. The biomarkers explored were clusterin in Alzheimer’s disease, thrombin in coagulopathy, estrogen receptor α (ER-α) in breast cancer, Carcinoembryonic antigen in lung cancer, microRNAs for malignant tumors, exosomes derived from HepG2 for the hepatocellular carcinoma (HCC) cell line, interleukin-6 (IL-6) for chronic obstructive pulmonary disease (COPD), Polyclonal antibodies and antigens (P24) for HIV and prostate-specific antigen for prostate cancer. The developed devices demonstrate ultralow detection limits at femtomolar to attomolar concentrations with the aid of designed antibodies, aptamers and nanomaterials. Herein, this review presents the sensing mechanisms and biomedical application of various GFET platforms, focusing on their emerging potential as next-generation platforms for rapid, non-invasive and point-of-care diagnostics. Full article

Background/Objectives: To quantify end-to-end timeliness of the blood culture (BC) diagnostic workflow over one month using operational key performance indicators (KPIs)—transportation time (TT), time to detection (TTD), time to preliminary report (TTPR), and time to antimicrobial susceptibility testing (AST; TTAST)—and to identify actionable bottlenecks. Methods: This retrospective observational analysis included BC bottles processed between 29 September and 29 October 2023 at a large tertiary-care hospital in Italy. KPIs were computed from laboratory information system (LIS) timestamps and structured observations and were summarized as medians (interquartile range [IQR]). Results: 44.7% (2290/5121) of bottles reached the laboratory within 2 h (median 2.2 h, IQR 1.3–3.7), suggesting pre-analytical delays. Among adult bottles (n = 4995), 68.9% were underfilled (<8 mL), 12.9% met the 8–10 mL target, and 18.2% were overfilled (>10 mL). There were 932 positive bottles (18.2%), with a nocturnal peak in instrument flags despite reduced staffing. Median TTD was 12.6 h (IQR 8.9–18.4), with earlier detection for Gram-negatives than Gram-positives and yeasts (11.9, 14.5, and 30.9 h). In bacterial-positive bottles with complete timestamps (n = 294), median TTPR was 3.8 h (IQR 1.7–8.8); median TTAST was 19.2 h (IQR 14.3–27.8). From collection, median times were 17.9 h (IQR 14.2–23.1) to the preliminary report and 36.0 h (IQR 28.8–48.7) to the AST result. Conclusions: Within-laboratory steps were generally rapid, whereas transport planning and collection volumes emerged as major bottlenecks. Targeted interventions—enforcing ≤2 h TT and training to achieve an 8–10 mL fill—should further improve BC turnaround time. Full article

The Korteweg–de Vries (KdV) equation is a foundational model in geophysical fluid dynamics (GFD), governing the propagation of long internal and surface gravity waves in stratified and shallow ocean environments where the interplay between nonlinear steepening and frequency-dependent dispersion gives rise to solitons. Although the analytical tractability of the KdV equation through inverse scattering is well established, systematic numerical exploration of multi-soliton interactions remains valuable for benchmarking solvers, probing conservation properties under varied oceanic initial conditions, and building intuition for more complex ocean wave phenomena. This article presents sangkuriang, an open-source Python library that solves the KdV equation using Fourier pseudo-spectral spatial discretization and adaptive eighth-order Runge–Kutta time integration. The implementation leverages just-in-time (JIT) compilation to achieve research-grade computational efficiency on standard hardware, making it readily accessible for coastal and ocean engineering applications, including idealized modeling of internal solitary waves on continental shelves, rapid parameter studies for solitary wave propagation in stratified basins, and pedagogical investigations of nonlinear dispersive wave dynamics. The solver is validated through four progressively complex idealized scenarios motivated by oceanic wave dynamics: isolated soliton propagation, symmetric interactions, overtaking collisions, and three-body interactions. High-fidelity conservation of mass, momentum, and energy is demonstrated, with relative errors remaining below $\mathcal{O}\left({10}^{-4}\right)$ across all test cases. Measured soliton velocities align with theoretical predictions within 5%, confirming the capture of the amplitude-dependent dispersion characteristic of oceanic solitary waves. Complementary diagnostics, including spectral entropy and recurrence quantification analysis (RQA), verify that the numerical solutions preserve the regular phase-space structure characteristic of integrable Hamiltonian systems. These results establish sangkuriang as a robust, lightweight platform for reproducible numerical investigation of idealized nonlinear dispersive wave dynamics relevant to coastal and ocean engineering applications. Full article

Rapid urbanization in the Global South has intensified the formation of mega-urban regions, where conventional urban–rural classifications often fail to capture the complexity of peri-urban systems. In the Jakarta–Bandung Mega-Urban Region (JBMUR), rapid land-use change and socio-economic transformation have produced hybrid landscapes that challenge binary zoning approaches. This study aims to delineate urban, peri-urban, and rural spatial structures using a spatially constrained clustering framework and to evaluate the performance of the Rustiadi Quantitative Zoning Method-2 (RQZM-2) compared with conventional non-spatial clustering (Non-RQZM). Built-environment, accessibility, environmental, and socio-economic indicators derived from remote sensing and spatially disaggregated statistical data were analyzed using grid-based K-Means clustering. Comparative validation using internal metrics, stability analysis, spatial coherence diagnostics, and statistical differentiation tests indicates that RQZM-2 produces more stable, spatially coherent, and interpretable clusters than conventional clustering. The validated four-cluster solution identifies compact urban cores, extensive peri-urban transition belts, and two distinct rural sub-types, revealing a functionally differentiated regional structure across the JBMUR. These findings demonstrate that incorporating spatial contextualization into clustering improves the empirical representation of peri-urban spatial continuity and provides a robust analytical basis for spatial zoning and regional planning in rapidly urbanizing mega-urban regions. Full article

Abies georgei var. smithii (Viguie & Gaussen) is a dominant conifer along the southeastern margin of the Qinghai–Tibet Plateau, where heart rot often develops covertly, complicating forest health monitoring and disease management. Fomitopsis subpinicola B.K. Cui, M.L. Han & Shun Liu is an important causal agent of heart rot affecting A. georgei var. smithii in this region, yet rapid, field-deployable molecular diagnostics of this pathogen remain limited. Here, we developed and evaluated two TEF1α-based isothermal platforms for specific detection of F. subpinicola: RAA and LAMP. To reduce potential cross-reactivity, TEF1α sequences from representative taxa within the F. pinicola species complex and closely related non-complex species were aligned for primer/probe design. Candidate RAA primers were screened by gel electrophoresis to select an optimal pair, and two LAMP primer sets were compared by specificity testing to identify the best-performing set. Both assays specifically detected F. subpinicola with no cross-amplification in the tested non-target fungi. Limits of detection were 9.97 copies/μL for fluorescent RAA (25 min), 9.97 × 10² copies/μL for RAA-LFD (15 min), and 9.97 × 10³ copies/μL for LAMP (35 min). In 30 increment core samples from A. georgei var. smithii, all methods consistently detected samples with obvious decay, while fluorescent RAA additionally yielded positives in some apparently asymptomatic samples, indicating promise for early or low-abundance screening. Together, these assays constitute a tiered and application-oriented detection system, enabling flexible selection of diagnostic approaches according to sensitivity requirements, operational conditions, and field surveillance needs for heart rot of A. georgei var. smithii. Full article

The unchecked and uncontrolled global spread of multidrug-resistant (MDR) bacteria is a serious challenge to healthcare and modern medicine, and demands diagnostic approaches that are rapid, sensitive, multiplexed, and reliable in point-of-care (POC) settings. At the interface of nanomaterials and aptamer-based biosensing, significant advances have been reported. The convergence of portable electrochemical sensing technologies, smartphone-based readout systems, and artificial intelligence (AI)- and machine learning (ML)-based data analysis is also playing a significant role in advancing this area. This perspective reflects on the most recent breakthroughs and translational developments in electrochemical nano-aptasensors for MDR bacterial detection, covering diagnostic targets and translation trends, nanomaterials advancements, aptamer engineering-integration, POC strategies and microfluidics platforms, and novel multimodal strategies that enhance accuracy, reliability, and efficiency in POC testing. Moreover, limitations and knowledge gaps in this area, as well as key considerations for sustainable development, large-scale manufacturing, and deployment of integrated electrochemical nano-aptasensors, are also highlighted. Electrochemical nano-aptasensors can pave the way for the transformation of MDR bacterial diagnosis, but need coordinated translational efforts for POC diagnostic advancements towards real-world applications. Full article

Background: Glioblastoma (GBM) remains the most aggressive primary brain tumor, and intraoperative frozen section analysis is the current standard for rapid histopathological assessment. However, this approach is time-consuming and resource-intensive. Stimulated Raman scattering (SRS) imaging has emerged as a label-free technique enabling near real-time microscopic evaluation of fresh tissue. This study compares the visualization of selected histopathological features in a newly developed intraoperative SRS system with conventional hematoxylin–eosin (HE) staining in confirmed GBM. Methods: Tumor samples from 30 patients with neuropathologically confirmed GBM were analyzed. For each case, both HE-stained frozen sections and SRS-generated virtual HE-like images were prepared from separate portions of the specimen. Twelve neuropathologists with varying levels of experience assessed 60 images according to seven predefined GBM criteria, resulting in 720 image evaluations. Feature detection was analyzed using cluster-adjusted generalized estimating equation models, and interobserver agreement was assessed using Fleiss’ κ. Results: Descriptively, hypercellularity and hypervascularization were identified at similar frequencies in both modalities, whereas pleomorphism, endothelial proliferation, mitotic activity, and necrosis were more often recognized in HE images. In cluster-adjusted analyses, SRS showed significantly lower detection rates for hypercellularity, pleomorphism, endothelial proliferation, and mitotic activity, while no significant difference was observed for hypervascularization, necrosis, or pseudopalisading after false discovery rate correction. Interobserver agreement was feature-dependent and generally higher for HE than SRS, particularly for hypercellularity. Conclusions: In this feature-level analysis of neuropathologically confirmed GBM, SRS imaging provided rapid, label-free morphological information and showed comparable visualization of selected histopathological features, particularly hypervascularization. While conventional HE-stained frozen sections remained superior for certain WHO-defining features, SRS represents a promising intraoperative adjunct that may complement established neuropathological workflows. Further studies including non-tumor tissue and a broader range of glioma grades are needed to determine the full diagnostic accuracy and clinical applicability of this technique. Full article