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Archives of Dermatological Research Jun 2024High-frequency ultrasound has been used to visualize depth and vascularization of cutaneous neoplasms, but little has been synthesized as a review for a robust level of... (Review)
Review
High-frequency ultrasound has been used to visualize depth and vascularization of cutaneous neoplasms, but little has been synthesized as a review for a robust level of evidence about the diagnostic accuracy of high-frequency ultrasound in dermatology. A narrative review of the PubMed database was performed to establish the correlation between ultrasound findings and histopathologic/dermoscopic findings for cutaneous neoplasms. Articles were divided into the following four categories: melanocytic, keratinocytic/epidermal, appendageal, and soft tissue/neural neoplasms. Review of the literature revealed that ultrasound findings and histopathology findings were strongly correlated regarding the depth of a cutaneous neoplasm. Morphological characteristics were correlated primarily in soft tissue/neural neoplasms. Overall, there is a paucity of literature on the correlation between high-frequency ultrasound and histopathology of cutaneous neoplasms. Further studies are needed to investigate this correlation in various dermatologic conditions.
Topics: Humans; Skin Neoplasms; Ultrasonography; Skin; Dermoscopy; Melanoma
PubMed: 38904763
DOI: 10.1007/s00403-024-03179-7 -
Pest Management Science Jan 2024Californian thistle (Cirisum arvense) is a troublesome weed in pastures and cropping systems. The fungal biocontrol agent Puccinia punctiformis, commonly referred to as... (Review)
Review
Californian thistle (Cirisum arvense) is a troublesome weed in pastures and cropping systems. The fungal biocontrol agent Puccinia punctiformis, commonly referred to as thistle rust, performs inconsistently on C. arvense. Problems with P. punctiformis establishment and control of C. arvense may be attributable to differing plant endophytic populations in various environments. This article provides an overview of the relationships between endophytes and their host, but also between endophytes and pathogens with a focus on rust pathogens. This review provides insights into reasons why P. punctiformis performs inconsistently and identifies gaps in our knowledge. Filling these gaps may help to improve performance of this classical fungal biocontrol agent. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
Topics: Endophytes; Cirsium; Puccinia
PubMed: 36710281
DOI: 10.1002/ps.7387 -
Histopathology Mar 2024Mucormycosis is a fast-progressing disease with a high mortality rate. The most important factor determining survival of patients is early and accurate diagnosis....
AIMS
Mucormycosis is a fast-progressing disease with a high mortality rate. The most important factor determining survival of patients is early and accurate diagnosis. Although histopathology often recognises invasive mould infections at first, histomorphology alone is insufficient in providing an accurate diagnosis. Unbiased molecular methods to detect and identify fungi are promising, yet their role in complementing routine histopathological workflows has not been studied sufficiently.
METHODS AND RESULTS
We performed a retrospective single-centre study examining the clinical value of complementing histopathology with internal transcribed spacer (ITS) sequencing of fungal DNA in the routine diagnosis of mucormycosis. At our academic centre, we identified 14 consecutive mucormycosis cases diagnosed by histopathology and subsequent ITS sequencing. Using histomorphological examination, fungal hyphae could be detected in all cases; however, morphological features were unreliable regarding specifying the taxa. Subsequent ITS sequencing identified a remarkable phylogenetic diversity among Mucorales: the most common species was Rhizopus microsporus (six of 14; 42.9%), followed by Lichtheimia corymbifera (three of 14, 21.4%) and single detections of Rhizopus oryzae, Actinomucor elegans, Mucor circinelloides, Rhizomucor pusillus and Rhizomucor miehei (one of 14; 7.1%, respectively). In one case, we additionally detected Pneumocystis jirovecii in the same lung tissue specimen, suggesting a clinically relevant co-infection. Fungal culture was performed in 10 cases but yielded positive results in only two of 10 (20%), revealing its limited value in the diagnosis of mucormycosis.
CONCLUSIONS
Our study demonstrates that a combination of histopathology and ITS sequencing is a practically feasible approach that outperforms fungal culture in detecting Mucorales in tissue-associated infections. Therefore, pathologists might adapt diagnostic workflows accordingly when mucormycosis is suspected.
Topics: Humans; Mucormycosis; Retrospective Studies; Phylogeny
PubMed: 38192085
DOI: 10.1111/his.15131 -
ACS Applied Bio Materials Oct 2023Sensitive, rapid, and portable molecular diagnostics is the future of disease surveillance, containment, and therapy. The recent SARS-CoV-2 pandemic has reminded us of... (Review)
Review
Sensitive, rapid, and portable molecular diagnostics is the future of disease surveillance, containment, and therapy. The recent SARS-CoV-2 pandemic has reminded us of the vulnerability of lives from ever-evolving pathogens. At the same time, it has provided opportunities to bridge the gap by translating basic molecular biology into therapeutic tools. One such molecular biology technique is CRISPR (clustered regularly interspaced short palindromic repeat) which has revolutionized the field of molecular diagnostics at the need of the hour. The use of CRISPR-Cas systems has been widespread in biology research due to the ease of performing genetic manipulations. In 2012, CRISPR-Cas systems were, for the first time, shown to be reprogrammable, i.e., capable of performing sequence-specific gene editing. This discovery catapulted the field of CRISPR-Cas research and opened many unexplored avenues in the field of gene editing, from basic research to therapeutics. One such field that benefitted greatly from this discovery was molecular diagnostics, as using CRISPR-Cas technologies enabled existing diagnostic methods to become more sensitive, accurate, and portable, a necessity in disease control. This Review aims to capture some of the trajectories and advances made in this arena and provides a comprehensive understanding of the methods and their potential use as point-of-care diagnostics.
Topics: Pathology, Molecular; Gene Editing; CRISPR-Cas Systems; Genetic Therapy; Point-of-Care Testing
PubMed: 37788375
DOI: 10.1021/acsabm.3c00439 -
European Radiology Dec 2023Accurate prediction of preoperative occult peritoneal metastasis (OPM) is critical to selecting appropriate therapeutic regimen for gastric cancer (GC). Considering the...
OBJECTIVE
Accurate prediction of preoperative occult peritoneal metastasis (OPM) is critical to selecting appropriate therapeutic regimen for gastric cancer (GC). Considering the clinical practicability, we develop and validate a visible nomogram that integrates the CT images and clinicopathological parameters for the individual preoperative prediction of OPM in GC.
METHODS
This retrospective study included 520 patients who underwent staged laparoscopic exploration or peritoneal lavage cytology (PLC) examination. Univariate and multivariate logistic regression results were used to screen model predictors and construct nomograms of OPM risk. The performance of the model was detected by using ROC, accuracy, and C-index. The bootstrap resampling method was considered internal validation of the model. The Delong test was used to evaluate the difference in AUC between the two models.
RESULTS
Grade 2 mural stratification, tumor thickness, and the Lauren classification diffuse were significant predictors of OPM (p < 0.05). The nomogram of these three factors (compared with the original model) showed a higher predictive effect (p < 0.001). The area under the curve (AUC) of the model was 0.830 (95% CI 0.788-0.873), and the internally validated AUC of 1000 bootstrap samples was 0.826 (95% CI 0.756-0.870). The sensitivity, specificity, and accuracy were 76.0%, 78.8%, and 78.3%, respectively.
CONCLUSIONS
CT phenotype-based nomogram demonstrates favorable discrimination and calibration, and it can be conveniently used for preoperative individual risk rating of OPM in GC.
CLINICAL RELEVANCE STATEMENT
In this study, the preoperative OPM prediction model based on CT images (mural stratification, tumor thickness) combined with pathological parameters (the Lauren classification) showed excellent predictive ability in GC, and it is also suitable for clinicians to use rather than limited to professional radiologists.
KEY POINTS
• Nomogram based on CT image analysis can effectively predict occult peritoneal metastasis in gastric cancer (training area under the curve (AUC) = 0.830 and bootstrap AUC = 0.826). • Nomogram model combined with CT features performed better than the original model (established using only clinicopathological parameters) in differentiating occult peritoneal metastasis of gastric cancer.
Topics: Humans; Stomach Neoplasms; Retrospective Studies; Peritoneal Neoplasms; Cytology; Nomograms; Tomography, X-Ray Computed
PubMed: 37414883
DOI: 10.1007/s00330-023-09854-z -
La Radiologia Medica Aug 2023To determine diagnostic performance of MRI radiomics-based machine learning for classification of deep-seated lipoma and atypical lipomatous tumor (ALT) of the...
PURPOSE
To determine diagnostic performance of MRI radiomics-based machine learning for classification of deep-seated lipoma and atypical lipomatous tumor (ALT) of the extremities.
MATERIAL AND METHODS
This retrospective study was performed at three tertiary sarcoma centers and included 150 patients with surgically treated and histology-proven lesions. The training-validation cohort consisted of 114 patients from centers 1 and 2 (n = 64 lipoma, n = 50 ALT). The external test cohort consisted of 36 patients from center 3 (n = 24 lipoma, n = 12 ALT). 3D segmentation was manually performed on T1- and T2-weighted MRI. After extraction and selection of radiomic features, three machine learning classifiers were trained and validated using nested fivefold cross-validation. The best-performing classifier according to previous analysis was evaluated and compared to an experienced musculoskeletal radiologist in the external test cohort.
RESULTS
Eight features passed feature selection and were incorporated into the machine learning models. After training and validation (74% ROC-AUC), the best-performing classifier (Random Forest) showed 92% sensitivity and 33% specificity in the external test cohort with no statistical difference compared to the radiologist (p = 0.474).
CONCLUSION
MRI radiomics-based machine learning may classify deep-seated lipoma and ALT of the extremities with high sensitivity and negative predictive value, thus potentially serving as a non-invasive screening tool to reduce unnecessary referral to tertiary tumor centers.
Topics: Humans; Retrospective Studies; Magnetic Resonance Imaging; Liposarcoma; Lipoma; Extremities; Machine Learning
PubMed: 37335422
DOI: 10.1007/s11547-023-01657-y -
Alzheimer's & Dementia : the Journal of... Jul 2023Post-mortem analysis provides definitive diagnoses of neurodegenerative diseases; however, only a few can be diagnosed during life.
INTRODUCTION
Post-mortem analysis provides definitive diagnoses of neurodegenerative diseases; however, only a few can be diagnosed during life.
METHODS
This study employed statistical tools and machine learning to predict 17 neuropathologic lesions from a cohort of 6518 individuals using 381 clinical features (Table S1). The multisite data allowed validation of the model's robustness by splitting train/test sets by clinical sites. A similar study was performed for predicting Alzheimer's disease (AD) neuropathologic change without specific comorbidities.
RESULTS
Prediction results show high performance for certain lesions that match or exceed that of research annotation. Neurodegenerative comorbidities in addition to AD neuropathologic change resulted in compounded, but disproportionate, effects across cognitive domains as the comorbidity number increased.
DISCUSSION
Certain clinical features could be strongly associated with multiple neurodegenerative diseases, others were lesion-specific, and some were divergent between lesions. Our approach could benefit clinical research, and genetic and biomarker research by enriching cohorts for desired lesions.
Topics: Humans; Alzheimer Disease; Comorbidity; Neuropathology; Biomarkers
PubMed: 36681388
DOI: 10.1002/alz.12921 -
Computers in Biology and Medicine Oct 2023Large-scale labeled datasets are crucial for the success of supervised learning in medical imaging. However, annotating histopathological images is a time-consuming and...
Large-scale labeled datasets are crucial for the success of supervised learning in medical imaging. However, annotating histopathological images is a time-consuming and labor-intensive task that requires highly trained professionals. To address this challenge, self-supervised learning (SSL) can be utilized to pre-train models on large amounts of unsupervised data and transfer the learned representations to various downstream tasks. In this study, we propose a self-supervised Pyramid-based Local Wavelet Transformer (PLWT) model for effectively extracting rich image representations. The PLWT model extracts both local and global features to pre-train a large number of unlabeled histopathology images in a self-supervised manner. Wavelet is used to replace average pooling in the downsampling of the multi-head attention, achieving a significant reduction in information loss during the transmission of image features. Additionally, we introduce a Local Squeeze-and-Excitation (Local SE) module in the feedforward network in combination with the inverse residual to capture local image information. We evaluate PLWT's performance on three histopathological images and demonstrate the impact of pre-training. Our experiment results indicate that PLWT with self-supervised learning performs highly competitive when compared with other SSL methods, and the transferability of visual representations generated by SSL on domain-relevant histopathological images exceeds that of the supervised baseline trained on ImageNet.
Topics: Pregnancy; Female; Humans; Labor, Obstetric; Supervised Machine Learning
PubMed: 37708715
DOI: 10.1016/j.compbiomed.2023.107336 -
European Journal of Gastroenterology &... Mar 2024Gastric juice analysis may be useful for clinical purposes, including the detection of H. pylori infection and diffuse atrophic gastritis on gastric mucosa. EndoFaster... (Review)
Review
Gastric juice analysis may be useful for clinical purposes, including the detection of H. pylori infection and diffuse atrophic gastritis on gastric mucosa. EndoFaster is a novel device which performs real-time analysis of gastric juice revealing the infection and hypochlorhydria by measuring ammonium concentrations and pH levels. This review aimed to evaluate the clinical applications of such a tool. By considering data from overall 11 studies, the values of sensitivity, specificity, positive predictive value, negative predictive value, accuracy, positive likelihood ratio, and negative likelihood ratio were 90%, 86%, 67%, 96%, 87%, 8.5, and 0.13, respectively, for H. pylori diagnosis, and 83%, 92%, 58%, 97%, 91%, 9.9 and 0.2, respectively, for suspecting diffuse atrophic gastritis. The very high value of negative predictive values for both H. pylori and mucosal atrophy would allow avoiding to perform useless negative gastric biopsies when the results of the test are negative. Some promising data suggest that gastric juice analysis may be useful also to diagnose H. pylori infection in patients with chronic active gastritis without evidence of bacteria at histology, as well as in predicting persistent acid reflux in patients on proton pump inhibitor therapy for reflux disease.
Topics: Humans; Gastritis, Atrophic; Gastric Juice; Gastric Mucosa; Gastritis; Helicobacter pylori; Gastroesophageal Reflux; Helicobacter Infections
PubMed: 38179876
DOI: 10.1097/MEG.0000000000002704 -
Neuro-oncology Nov 2023The international, multicenter registry LOGGIC Core BioClinical Data Bank aims to enhance the understanding of tumor biology in pediatric low-grade glioma (pLGG) and...
BACKGROUND
The international, multicenter registry LOGGIC Core BioClinical Data Bank aims to enhance the understanding of tumor biology in pediatric low-grade glioma (pLGG) and provide clinical and molecular data to support treatment decisions and interventional trial participation. Hence, the question arises whether implementation of RNA sequencing (RNA-Seq) using fresh frozen (FrFr) tumor tissue in addition to gene panel and DNA methylation analysis improves diagnostic accuracy and provides additional clinical benefit.
METHODS
Analysis of patients aged 0 to 21 years, enrolled in Germany between April 2019 and February 2021, and for whom FrFr tissue was available. Central reference histopathology, immunohistochemistry, 850k DNA methylation analysis, gene panel sequencing, and RNA-Seq were performed.
RESULTS
FrFr tissue was available in 178/379 enrolled cases. RNA-Seq was performed on 125 of these samples. We confirmed KIAA1549::BRAF-fusion (n = 71), BRAF V600E-mutation (n = 12), and alterations in FGFR1 (n = 14) as the most frequent alterations, among other common molecular drivers (n = 12). N = 16 cases (13%) presented rare gene fusions (eg, TPM3::NTRK1, EWSR1::VGLL1, SH3PXD2A::HTRA1, PDGFB::LRP1, GOPC::ROS1). In n = 27 cases (22%), RNA-Seq detected a driver alteration not otherwise identified (22/27 actionable). The rate of driver alteration detection was hereby increased from 75% to 97%. Furthermore, FGFR1 internal tandem duplications (n = 6) were only detected by RNA-Seq using current bioinformatics pipelines, leading to a change in analysis protocols.
CONCLUSIONS
The addition of RNA-Seq to current diagnostic methods improves diagnostic accuracy, making precision oncology treatments (MEKi/RAFi/ERKi/NTRKi/FGFRi/ROSi) more accessible. We propose to include RNA-Seq as part of routine diagnostics for all pLGG patients, especially when no common pLGG alteration was identified.
Topics: Child; Humans; Proto-Oncogene Proteins B-raf; Pathology, Molecular; Protein-Tyrosine Kinases; RNA-Seq; Proto-Oncogene Proteins; Precision Medicine; Glioma; DNA-Binding Proteins; Transcription Factors
PubMed: 37075810
DOI: 10.1093/neuonc/noad078