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Dentin hypersensitivity (DH) is a common medical condition with underreported prevalence and it is difficult to quantify. This study aimed to investigate whether assessing dental pulp vascular micro-dynamics by laser-Doppler flowmetry (LDF) would be functional for therapeutic evaluation, in contrast to a verbal rating scale (VRS). A split-mouth single-blind randomized study was conducted on seven patients and a total of 36 teeth. Two DH therapeutic methods were employed: (i) fluoride gel; (ii) Nd:YAG radiation combined with fluoride gel. For each tooth, five consecutive LDF determinations of pulp blood flow were made (before and immediately after desensitizing treatment, then after 24 h, 7 days, and 1 month), and the VRS was applied each time. Spearman’s correlation was applied for concurrent validation. Two-way (treatment and patient) repeated measures ANOVA full factorial was applied, followed by Tukey’s post-hoc comparisons and Pillai’s trace multivariate statistic. While VRS scores had moderate reliability, LDF could objectively estimate treatment effects. Based on partial eta-squared values, treatment and patient characteristics were estimated to explain about 84% and 50% of the variability, respectively. In conclusion, LDF is an objective technique that can quantitatively assess DH evolution, and it is effective in reliably monitoring oral health therapeutic interventions.

Purpose The aim of this study is to determine the diagnostic performances of pleural procedures in undiagnosed exudative pleural effusions and to evaluate factors suggestive of benign or malignant pleural effusions in tertiary care centers. Methods This was a multicenter prospective observational study conducted between January 1 and December 31, 2018. A total of 777 patients with undiagnosed exudative pleural effusion after the initial work-up were evaluated. The results of diagnostic procedures and the patients' diagnoses were prospectively recorded. Sensitivity, specificity, and accuracy estimates with 95% confidence intervals were used to examine the performance of pleural procedures to detect malignancy. Results The mean age ± SD of the 777 patients was 62.0 ± 16.0 years, and 68.3% of them were male. The most common cause was malignancy (38.3%). Lung cancer was the leading cause of malignant pleural effusions (20.2%). The diagnostic sensitivity and accuracy of cytology were 59.5% and 84.3%, respectively. The diagnostic sensitivity of image-guided pleural biopsy was 86.4%. The addition of image-guided pleural biopsy to cytology increased diagnostic sensitivity to more than 90%. Thoracoscopic biopsy provided the highest diagnostic sensitivity (94.3%). The highest diagnostic sensitivity of cytology was determined in metastatic pleural effusion from breast cancer (86.7%). Conclusion The diagnostic performance increases considerably when cytology is combined with image-guided pleural biopsy in malignant pleural effusions. However, to avoid unnecessary interventions and complications, the development of criteria to distinguish patients with benign pleural effusions is as important as the identification of patients with malignant pleural effusions.

A versatile portfolio of diagnostic tests is essential for the containment of the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) pandemic. Besides nucleic acid-based test systems and point-of-care (POCT) antigen (Ag) tests, quantitative, laboratory-based nucleocapsid Ag tests for SARS-CoV-2 have recently been launched. Here, we evaluated four commercial Ag tests on automated platforms and one POCT to detect SARS-CoV-2. We evaluated PCR-positive ( n  = 107) and PCR-negative ( n  = 303) respiratory swabs from asymptomatic and symptomatic patients at the end of the second pandemic wave in Germany (February–March 2021) as well as clinical isolates EU1 (B.1.117), variant of concern (VOC) Alpha (B.1.1.7) or Beta (B.1.351), which had been expanded in a biosafety level 3 laboratory. The specificities of automated SARS-CoV-2 Ag tests ranged between 97.0 and 99.7% (Lumipulse G SARS-CoV-2 Ag (Fujirebio): 97.03%, Elecsys SARS-CoV-2 Ag (Roche Diagnostics): 97.69%; LIAISON ® SARS-CoV-2 Ag (Diasorin) and SARS-CoV-2 Ag ELISA (Euroimmun): 99.67%). In this study cohort of hospitalized patients, the clinical sensitivities of tests were low, ranging from 17.76 to 52.34%, and analytical sensitivities ranged from 420,000 to 25,000,000 Geq/ml. In comparison, the detection limit of the Roche Rapid Ag Test (RAT) was 9,300,000 Geq/ml, detecting 23.58% of respiratory samples. Receiver-operating-characteristics (ROCs) and Youden’s index analyses were performed to further characterize the assays’ overall performance and determine optimal assay cutoffs for sensitivity and specificity. VOCs carrying up to four amino acid mutations in nucleocapsid were detected by all five assays with characteristics comparable to non-VOCs. In summary, automated, quantitative SARS-CoV-2 Ag tests show variable performance and are not necessarily superior to a standard POCT. The efficacy of any alternative testing strategies to complement nucleic acid-based assays must be carefully evaluated by independent laboratories prior to widespread implementation.

Fast, definitive diagnosis of Creutzfeldt-Jakob disease (CJD) is important in assessing patient care options and transmission risks. Real-time quaking-induced conversion (RT-QuIC) assays of cerebrospinal fluid (CSF) and nasal-brushing specimens are valuable in distinguishing CJD from non-CJD conditions but have required 2.5 to 5 days. Here, an improved RT-QuIC assay is described which identified positive CSF samples within 4 to 14 h with better analytical sensitivity. Moreover, analysis of 11 CJD patients demonstrated that while 7 were RT-QuIC positive using the previous conditions, 10 were positive using the new assay. In these and further analyses, a total of 46 of 48 CSF samples from sporadic CJD patients were positive, while all 39 non-CJD patients were negative, giving 95.8% diagnostic sensitivity and 100% specificity. This second-generation RT-QuIC assay markedly improved the speed and sensitivity of detecting prion seeds in CSF specimens from CJD patients. This should enhance prospects for rapid and accurate ante mortem CJD diagnosis. IMPORTANCE A long-standing problem in dealing with various neurodegenerative protein misfolding diseases is early and accurate diagnosis. This issue is particularly important with human prion diseases, such as CJD, because prions are deadly, transmissible, and unusually resistant to decontamination. The recently developed RT-QuIC test allows for highly sensitive and specific detection of CJD in human cerebrospinal fluid and is being broadly implemented as a key diagnostic tool. However, as currently applied, RT-QuIC takes 2.5 to 5 days and misses 11 to 23% of CJD cases. Now, we have markedly improved RT-QuIC analysis of human CSF such that CJD and non-CJD patients can be discriminated in a matter of hours rather than days with enhanced sensitivity. These improvements should allow for much faster, more accurate, and practical testing for CJD. In broader terms, our study provides a prototype for tests for misfolded protein aggregates that cause many important amyloid diseases, such as Alzheimer’s, Parkinson’s, and tauopathies. A long-standing problem in dealing with various neurodegenerative protein misfolding diseases is early and accurate diagnosis. This issue is particularly important with human prion diseases, such as CJD, because prions are deadly, transmissible, and unusually resistant to decontamination. The recently developed RT-QuIC test allows for highly sensitive and specific detection of CJD in human cerebrospinal fluid and is being broadly implemented as a key diagnostic tool. However, as currently applied, RT-QuIC takes 2.5 to 5 days and misses 11 to 23% of CJD cases. Now, we have markedly improved RT-QuIC analysis of human CSF such that CJD and non-CJD patients can be discriminated in a matter of hours rather than days with enhanced sensitivity. These improvements should allow for much faster, more accurate, and practical testing for CJD. In broader terms, our study provides a prototype for tests for misfolded protein aggregates that cause many important amyloid diseases, such as Alzheimer’s, Parkinson’s, and tauopathies.

Purpose Papillary thyroid carcinoma (PTC) with metastatic lymph nodes (LNs) is closely associated with disease recurrence. This study accessed the value of superb microvascular imaging (SMI) in the diagnosis and prediction of metastatic cervical LNs in patients with PTC. Methods A total of 183 cervical LNs (103 metastatic and 80 reactive) from 116 patients with PTC were analysed. Metastatic cervical LNs were confirmed by pathology or/and cytology; reactive cervical LNs were confirmed by pathology or clinical features. The characteristic of conventional ultrasound (US) was extracted using univariate and multivariate analyses. The diagnostic performance of US and SMI were compared using the area under the receiver operating curve (AUC) with corresponding sensitivity and specificity. A nomogram was developed to predict metastatic LNs in patients with PTC, based on multivariate analyses. Results L/S < 2, ill-defined border, absence of hilum, isoechoic or hyperechoic, heterogeneous internal echo, peripheral or mixed vascular pattern on color Doppler flow imaging (CDFI) and SMI, and a larger SMI vascular index appeared more frequently in metastatic LNs in the training datasets than in reactive LNs ( P  < 0.05). The diagnostic sensitivity, specificity and accuracy of SMI vs US are 94.4% and 87.3%, 79.3% and 69.3%, and 87.6% and 79.1%, respectively; SMI combined with US exhibited a higher AUC [0.926 (0.877–0.975)] than US only [0.829 (0.759–0.900)]. L/S < 2, peripheral or mixed vascular type on CDFI, and peripheral or mixed vascular types on SMI were independent predictors of metastatic LNs with PTC. The nomogram based on these three parameters exhibited excellent discrimination, with an AUC of 0.926. Conclusion SMI was superior to US in diagnosing metastatic LNs in PTC. US combined with SMI significantly improved the diagnostic accuracy of metastatic cervical LNs with PTC. SMI is efficacious for differentiating and predicting metastatic cervical LNs.

Since 2009, we built up a database which presently includes more than 2000 electrohypersensitivity (EHS) and/or multiple chemical sensitivity (MCS) self-reported cases. This database shows that EHS is associated in 30% of the cases with MCS, and that MCS precedes the occurrence of EHS in 37% of these EHS/MCS-associated cases. EHS and MCS can be characterized clinically by a similar symptomatic picture, and biologically by low-grade inflammation and an autoimmune response involving autoantibodies against O-myelin. Moreover, 80% of the patients with EHS present with one, two, or three detectable oxidative stress biomarkers in their peripheral blood, meaning that overall these patients present with a true objective somatic disorder. Moreover, by using ultrasonic cerebral tomosphygmography and transcranial Doppler ultrasonography, we showed that cases have a defect in the middle cerebral artery hemodynamics, and we localized a tissue pulsometric index deficiency in the capsulo-thalamic area of the temporal lobes, suggesting the involvement of the limbic system and the thalamus. Altogether, these data strongly suggest that EHS is a neurologic pathological disorder which can be diagnosed, treated, and prevented. Because EHS is becoming a new insidious worldwide plague involving millions of people, we ask the World Health Organization (WHO) to include EHS as a neurologic disorder in the international classification of diseases.

Background Various methods exist for statistical inference about a prevalence that consider misclassifications due to an imperfect diagnostic test. However, traditional methods are known to suffer from truncation of the prevalence estimate and the confidence intervals constructed around the point estimate, as well as from under-performance of the confidence intervals’ coverage. Methods In this study, we used simulated data sets to validate a Bayesian prevalence estimation method and compare its performance to frequentist methods, i.e. the Rogan-Gladen estimate for prevalence, RGE , in combination with several methods of confidence interval construction. Our performance measures are (i) error distribution of the point estimate against the simulated true prevalence and (ii) coverage and length of the confidence interval, or credible interval in the case of the Bayesian method. Results Across all data sets, the Bayesian point estimate and the RGE produced similar error distributions with slight advantages of the former over the latter. In addition, the Bayesian estimate did not suffer from the RGE ’s truncation problem at zero or unity. With respect to coverage performance of the confidence and credible intervals, all of the traditional frequentist methods exhibited strong under-coverage, whereas the Bayesian credible interval as well as a newly developed frequentist method by Lang and Reiczigel performed as desired, with the Bayesian method having a very slight advantage in terms of interval length. Conclusion The Bayesian prevalence estimation method should be prefered over traditional frequentist methods. An acceptable alternative is to combine the Rogan-Gladen point estimate with the Lang-Reiczigel confidence interval.

Outbreaks of emerging diseases, like Mpox in 2022, pose unprecedented challenges to global healthcare systems. Although Mpox cases globally decreased since the end of 2022, numbers are still significant in the African Region, European Region, Region of the Americas, and Western Pacific Region. Rapid and efficient detection of infected individuals by precise screening assays is crucial for successful containment. In these assays, analytical and clinical performance must be assessed to ensure high quality. However, clinical studies evaluating Mpox virus (MPXV) detection kits using patient-derived samples are scarce. This study evaluated the analytical and clinical performance of a new diagnostic MPXV real-time PCR detection kit (Sansure Monkeypox Virus Nucleic Acid Diagnostic Kit) using patient-derived samples collected in Germany during the MPXV clade IIb outbreak in 2022. Our experimental approach determined the Limit of Detection (LoD) to less than 200 cp/mL using whole blood samples and samples derived from vesicles or pustules. Furthermore, we tested potentially inhibiting substances and pathogens with homologous nucleic acid sequences or similar clinical presentation and detected no cross-reactivity or interference. Following this, the assay was compared to a CE-marked test in a clinical performance study and achieved a diagnostic sensitivity of 100.00% and diagnostic specificity of 96.97%. In summary, the investigated real-time PCR assay demonstrates high analytical performance and concurs with the competitor device with high specificity and sensitivity.

The African swine fever virus (ASFV) has the ability to infect pigs and cause a highly contagious acute fever that can result in a mortality rate as high as 100%. Due to the viral epidemic, the pig industry worldwide has suffered significant financial setbacks. The absence of a proven vaccine for ASFV necessitates the development of a sensitive and reliable serological diagnostic method, enabling laboratories to effectively and expeditiously detect ASFV infection. In this study, four strains of monoclonal antibodies (mAbs) against p72, namely, 5A1, 4C4, 8A9, and 5E10, were generated through recombinant expression of p72, the main capsid protein of ASFV, and immunized mice with it. Epitope localization was performed by truncated overlapping polypeptides. The results indicate that 5A1 and 4C4 recognized the amino acid 20–39 aa, 8A9 and 5E10 are recognized at 263–282 aa, which is consistent with the reported 265–280 aa epitopes. Conserved analysis revealed 20–39 aa is a high conservation of the epitopes in the ASFV genotypes. Moreover, a blocking ELISA assay for detection ASFV antibody based on 4C4 monoclonal antibody was developed and assessed. The receiver-operating characteristic (ROC) was performed to identify the best threshold value using 87 negative and 67 positive samples. The established test exhibited an area under the curve (AUC) of 0.9997, with a 95% confidence interval ranging from 99.87 to 100%. Furthermore, the test achieved a diagnostic sensitivity of 100% (with a 95% confidence interval of 95.72 to 100%) and a specificity of 98.51% (with a 95% confidence interval of 92.02 to 99.92%) when the threshold was set at 41.97%. The inter- and intra-batch coefficient of variation were below 10%, demonstrating the exceptional repeatability of the method. This method can detect the positive standard serum at a dilution as high as 1:512. Subsequently, an exceptional blocking ELISA assay was established with high diagnostic sensitivity and specificity, providing a novel tool for detecting ASFV antibodies. Key points • Four strains of ASFV monoclonal antibodies against p72 were prepared and their epitopes were identified. • Blocking ELISA method was established based on monoclonal antibody 4C4 with an identified conservative epitope. • The established blocking ELISA method has a good effect on the detection of ASFV antibody.

Background Current methods for obtaining fecal egg counts in horses are often inaccurate and variable depending on the analyst’s skill and experience. Automated digital scanning of fecal sample slides integrated with analysis by an artificial intelligence (AI) algorithm is a viable, emerging alternative that can mitigate operator variation compared to conventional methods in companion animal fecal parasite diagnostics. Vetscan Imagyst is a novel fecal parasite detection system that uploads the scanned image to the cloud where proprietary software analyzes captured images for diagnostic recognition by a deep learning, object detection AI algorithm. The study describes the use and validation of Vetscan Imagyst in equine parasitology. Methods The primary objective of the study was to evaluate the performance of the Vetscan Imagyst system in terms of diagnostic sensitivity and specificity in testing equine fecal samples ( n  = 108) for ova from two parasites that commonly infect horses, strongyles and Parascaris spp., compared to reference assays performed by expert parasitologists using a Mini-FLOTAC technique. Two different fecal flotation solutions were used to prepare the sample slides, NaNO 3 and Sheather’s sugar solution. Results Diagnostic sensitivity of the Vetscan Imagyst algorithm for strongyles versus the manual reference test was 99.2% for samples prepared with NaNO 3 solution and 100.0% for samples prepared with Sheather’s sugar solution. Sensitivity for Parascaris spp. was 88.9% and 99.9%, respectively, for samples prepared with NaNO 3 and Sheather’s sugar solutions. Diagnostic specificity for strongyles was 91.4% and 99.9%, respectively, for samples prepared with NaNO 3 and Sheather’s sugar solutions. Specificity for Parascaris spp. was 93.6% and 99.9%, respectively, for samples prepared with NaNO 3 and Sheather’s sugar solutions. Lin’s concordance correlation coefficients for VETSCAN IMAGYST eggs per gram counts versus those determined by the expert parasitologist were 0.924–0.978 for strongyles and 0.944–0.955 for Parascaris spp., depending on the flotation solution. Conclusions Sensitivity and specificity results for detecting strongyles and Parascaris spp. in equine fecal samples showed that Vetscan Imagyst can consistently provide diagnostic accuracy equivalent to manual evaluations by skilled parasitologists. As an automated method driven by a deep learning AI algorithm, VETSCAN IMAGYST has the potential to avoid variations in analyst characteristics, thus providing more consistent results in a timely manner, in either clinical or laboratory settings. Graphical Abstract