Search

Hirschsprung's disease (HSCR) is characterized by congenital absence of ganglion cells in the gastrointestinal tract, which leads to impaired defecation, constipation and intestinal obstruction. The current diagnosis of HSCR is based on Rectal Suction Biopsies (RSBs), which could be complex in newborns. Occasionally, there is a delay in diagnosis that can increase the risk of clinical complications. Consequently, there is room for new non-invasive diagnostic methods that are objective, more logistically feasible and also deliver a far earlier base for a potential surgical intervention. In recent years, microRNA (miRNA) has come into the focus as a relevant early marker that could provide more insights into the etiology and progression of diseases. Therefore, in the search of a non-invasive HSCR biomarker, we analyzed miRNA expression in urine samples of HSCR patients. Results from 5 HSCR patients using microarrays, revealed hsa-miR-378 h, hsa-miR-210-5p, hsa-miR-6876-3p, hsa-miR-634 and hsa-miR-6883-3p as the most upregulated miRNAs; while hsa-miR-4443, hsa-miR-22-3p, hsa-miR-4732-5p, hsa-miR-3187-5p, and hsa-miR-371b-5p where the most downregulated miRNAs. Further search in miRNAwalk and miRDB databases showed that certainly most of these dysregulated miRNAs identified target HSCR associated genes, such as RET, GDNF, BDNF, EDN3, EDNRB, ERBB, NRG1, SOX10; and other genes implied in neuronal migration and neurogenesis. Finally, we could also validate some of these miRNA changes in HSCR urine by RT-qPCR. Altogether, our analyzed HSCR cohort presents a dysregulated miRNA expression presents that can be detected in urine. Our findings open the possibility of using specific urine miRNA signatures as non-invasive HSCR diagnosis method in the future. [ABSTRACT FROM AUTHOR]

Introduction: The non-invasive assessment of disease severity remains pivotal in patients with chronic liver disease (CLD) as it has wide implications in predicting liver-related complications or death. Shear-wave elastography (SWE) is an emerging ultrasound-based method to non-invasively measure liver stiffness. The aim of our study was to evaluate two-dimensional (2D) and point (p) SWE to predict the presence of esophageal varices (EV) or clinically significant portal hypertension (CSPH). Methods: This was a retrospective analysis of a prospectively performed cohort study of patients with CLD treated in the outpatient clinic of the Frankfurt University Hospital. PSWE using the Hitachi HI Vision ASCENDUS system and the Siemens ACUSON S2000TM system or 2D-SWE using the Toshiba APLIO500 system were analyzed at baseline and during follow-up to predict EV or surrogate parameters of CSPH. ROC curves were calculated for pooled liver stiffness measurements (LSMs) using a bootstrap approach. A combined model of SWE and platelet count was created and a mixed-effect logistic regression analysis using log-transformed values was performed. Results: Overall, 511 patients with CLD and 919 consecutive LSMs were included and 315 patients (61.6%) had signs of CSPH. 2D-SWE performed best to predict EV and CSPH, and the addition of platelet count to the predictive model significantly increased test results for EV (AUC 0.83, 95%-CI: 0.76–0.89; difference in AUC 0.11, 95%-CI: 0.03–0.19, p = 0.004), but only marginally for CSPH (AUC 0.75, 95%-CI: 0.64–0.85; difference in AUC 0.06, 95%-CI: 0.02–0.14, p = 0.150). LSM > 18.5 and >20 kPa were indicative of CSPH and EV, while LSM < 10 kPa and <11 kPa ruled out CSPH and EV, respectively. Conclusions: Our study found that 2D-SWE in combination with platelet count performed best (in comparison to the other SWE methods) to predict EV or CSPH in patients with CLD. Future prospective trials are needed to validate our results. [ABSTRACT FROM AUTHOR]

Background: The gut microbiome compositions of osteoarthritis (OA) and rheumatoid arthritis (RA) patients have been revealed; however, the functional genomics, particularly antibiotic resistance genes (ARGs) and virulence factor genes (VFGs), have not yet been explored. Methods: We used gut metagenomic data to elucidate the distribution of ARGs and VFGs. Building on these differences in gut microbiome, we developed a diagnostic model using a random forest classifier based on ARG and VFG abundances. Results: Our results indicated that both OA and RA patients exhibit significantly higher alpha diversity in ARGs, as measured by observed genes, the Shannon index, and the Simpson index, compared to healthy controls. However, this increased diversity is not significantly different between OA and RA patients. In contrast, VFGs showed higher diversity in RA patients than in healthy individuals, which was not as pronounced in OA patients. An analysis of the top 20 ARGs and VFGs revealed a largely similar composition between the three groups, with notable exceptions of certain genes that were uniquely enriched in either OA or RA patients. This suggests unique microbial patterns associated with each condition. Our beta diversity analysis further demonstrated distinct distributions of ARG and VFG profiles across the three groups, with several genes significantly enriched in both OA and RA patients, indicating potential markers for these diseases. The model achieved high accuracy (74.7–83.6%) when distinguishing both OA and RA from healthy controls using ARG profiles and substantial accuracy using VFG profiles. Conclusion: These results support the potential of ARGs and VFGs as reliable biomarkers for diagnosing OA and RA. [ABSTRACT FROM AUTHOR]

The identification of diseases caused by changes in ion concentration is quite difficult and yet plays a decisive role in the success of clinical care, diagnosis and treatment. The clinically proven approach to diagnosing electrolyte concentration imbalance is blood tests. There is a need to provide a non-invasive diagnostic method that is not of a temporary nature. Bio-signals such as the electrocardiogram (ECG) can be used to meet this demand and become diagnostic tools that facilitate home monitoring of electrolyte concentration on a permanent basis. This study investigates the feasibility and efficiency of methods based on machine learning (ML) and ECG recordings in monitoring critical levels of existing potassium and calcium concentration. Morphological, frequency and frequency-time domain features were extracted to automatically estimate calcium and potassium levels. Furthermore, the potential of estimates based on modeling approaches will be demonstrated to gain insights into relevant clinical findings and improve the performance of monitoring approaches. Using the hold-out validation method, the best results in terms of mean square error (MSE) and R for estimating the calcium value are 0.7157 and 0.57347, using fuzzy inference systems (FIS). Here, R represents the proportion of the variance in the calcium value that is explained by the model.

Hirschsprung’s disease (HSCR) is characterized by congenital absence of ganglion cells in the gastrointestinal tract, which leads to impaired defecation, constipation and intestinal obstruction. The current diagnosis of HSCR is based on Rectal Suction Biopsies (RSBs), which could be complex in newborns. Occasionally, there is a delay in diagnosis that can increase the risk of clinical complications. Consequently, there is room for new non-invasive diagnostic methods that are objective, more logistically feasible and also deliver a far earlier base for a potential surgical intervention. In recent years, microRNA (miRNA) has come into the focus as a relevant early marker that could provide more insights into the etiology and progression of diseases. Therefore, in the search of a non-invasive HSCR biomarker, we analyzed miRNA expression in urine samples of HSCR patients. Results from 5 HSCR patients using microarrays, revealed hsa-miR-378 h, hsa-miR-210-5p, hsa-miR-6876-3p, hsa-miR-634 and hsa-miR-6883-3p as the most upregulated miRNAs; while hsa-miR-4443, hsa-miR-22-3p, hsa-miR-4732-5p, hsa-miR-3187-5p, and hsa-miR-371b-5p where the most downregulated miRNAs. Further search in miRNAwalk and miRDB databases showed that certainly most of these dysregulated miRNAs identified target HSCR associated genes, such as RET, GDNF, BDNF, EDN3, EDNRB, ERBB, NRG1, SOX10; and other genes implied in neuronal migration and neurogenesis. Finally, we could also validate some of these miRNA changes in HSCR urine by RT-qPCR. Altogether, our analyzed HSCR cohort presents a dysregulated miRNA expression presents that can be detected in urine. Our findings open the possibility of using specific urine miRNA signatures as non-invasive HSCR diagnosis method in the future.

Abstract This study aimed to construct a non-invasive diagnostic nomogram based on high-frequency ultrasound and magnetic resonance imaging results for early liver cirrhosis patients with chronic hepatitis B (CHB) which cannot be detected by conventional non-invasive examination methods but can only be diagnosed through invasive liver puncture for pathological examination. 72 patients with CHB were enrolled in this prospective study, and divided into S4 stage of liver cirrhosis and S0-S3 stage of non-liver cirrhosis according to pathological findings. Binary logistic regression analysis was performed to identify independent predictors, and a diagnostic nomogram was constructed for CHB-related early cirrhosis. It was validated and calibrated by bootstrap self-extraction. Binary logistic regression analysis showed that age (OR 1.14, 95% CI (1.04–1.27)), right hepatic vein diameter (OR 0.43, 95% CI 0.23–0.82), presence or absence of nodules (OR 31.98, 95% CI 3.84–266.08), and hepatic parenchymal echogenicity grading (OR 12.82, 95% CI 2.12–77.51) were identified as independent predictive indicators. The nomogram based on the 4 factors above showed good performance, with a sensitivity and specificity of 90.70% and 89.66%, respectively. The area under the curve (AUC) of the prediction model was 0.96, and the predictive model showed better predictive performance than APRI score (AUC 0.57), FIB-4 score (AUC 0.64), INPR score (AUC 0.63), and LSM score (AUC 0.67). The calibration curve of the prediction model fit well with the ideal curve, and the decision curve analysis showed that the net benefit of the model was significant. The nomogram in this study can detect liver cirrhosis in most CHB patients without liver biopsy, providing a direct, fast, and accurate practical diagnostic tool for clinical doctors.

This study aimed to construct a non-invasive diagnostic nomogram based on high-frequency ultrasound and magnetic resonance imaging results for early liver cirrhosis patients with chronic hepatitis B (CHB) which cannot be detected by conventional non-invasive examination methods but can only be diagnosed through invasive liver puncture for pathological examination. 72 patients with CHB were enrolled in this prospective study, and divided into S4 stage of liver cirrhosis and S0-S3 stage of non-liver cirrhosis according to pathological findings. Binary logistic regression analysis was performed to identify independent predictors, and a diagnostic nomogram was constructed for CHB-related early cirrhosis. It was validated and calibrated by bootstrap self-extraction. Binary logistic regression analysis showed that age (OR 1.14, 95% CI (1.04–1.27)), right hepatic vein diameter (OR 0.43, 95% CI 0.23–0.82), presence or absence of nodules (OR 31.98, 95% CI 3.84–266.08), and hepatic parenchymal echogenicity grading (OR 12.82, 95% CI 2.12–77.51) were identified as independent predictive indicators. The nomogram based on the 4 factors above showed good performance, with a sensitivity and specificity of 90.70% and 89.66%, respectively. The area under the curve (AUC) of the prediction model was 0.96, and the predictive model showed better predictive performance than APRI score (AUC 0.57), FIB-4 score (AUC 0.64), INPR score (AUC 0.63), and LSM score (AUC 0.67). The calibration curve of the prediction model fit well with the ideal curve, and the decision curve analysis showed that the net benefit of the model was significant. The nomogram in this study can detect liver cirrhosis in most CHB patients without liver biopsy, providing a direct, fast, and accurate practical diagnostic tool for clinical doctors. [ABSTRACT FROM AUTHOR]

BackgroundThe gut microbiome compositions of osteoarthritis (OA) and rheumatoid arthritis (RA) patients have been revealed; however, the functional genomics, particularly antibiotic resistance genes (ARGs) and virulence factor genes (VFGs), have not yet been explored.MethodsWe used gut metagenomic data to elucidate the distribution of ARGs and VFGs. Building on these differences in gut microbiome, we developed a diagnostic model using a random forest classifier based on ARG and VFG abundances.ResultsOur results indicated that both OA and RA patients exhibit significantly higher alpha diversity in ARGs, as measured by observed genes, the Shannon index, and the Simpson index, compared to healthy controls. However, this increased diversity is not significantly different between OA and RA patients. In contrast, VFGs showed higher diversity in RA patients than in healthy individuals, which was not as pronounced in OA patients. An analysis of the top 20 ARGs and VFGs revealed a largely similar composition between the three groups, with notable exceptions of certain genes that were uniquely enriched in either OA or RA patients. This suggests unique microbial patterns associated with each condition. Our beta diversity analysis further demonstrated distinct distributions of ARG and VFG profiles across the three groups, with several genes significantly enriched in both OA and RA patients, indicating potential markers for these diseases. The model achieved high accuracy (74.7–83.6%) when distinguishing both OA and RA from healthy controls using ARG profiles and substantial accuracy using VFG profiles.ConclusionThese results support the potential of ARGs and VFGs as reliable biomarkers for diagnosing OA and RA.

The popularity of tattoos has led to an increase in associated skin reactions, including complications such as infection, allergic reactions and rare conditions such as tattoo‐induced cutaneous lymphoid hyperplasia (CLH). CLH is a benign lymphoproliferative reaction with clinical features resembling malignant cutaneous lymphomas. Non‐invasive diagnostic tools like reflectance confocal microscopy (RCM) and the new line‐field confocal optical coherence tomography (LC‐OCT) are being studied in dermatology better to understand the morphological patterns of many dermatological diseases. Between September 2021 and May 2023, patients with suspicious lesions for tattoo‐related CLH were analysed using RCM and LC‐OCT before confirming the diagnosis of CLH through skin biopsy and histopathological examination. The study included five cases of CLH. It focused on the analysis of high‐quality LC‐OCT images/videos and RCM images to investigate the features of CLH in tattooed individuals. Most (80%) cases exhibited a mixed T and B lymphocyte infiltration subtype, while 20% showed a predominant T infiltration subtype. RCM and LC‐OCT revealed characteristic features, including architectural disarray, fibrosis, lymphoid infiltrates, and pigment deposits in the epidermis and dermis. Non‐invasive tools such as RCM and LC‐OCT are valuable in diagnosing tattoo‐related CLH. While skin biopsy remains the current standard for diagnosis, RCM and LC‐OCT can serve as helpful adjuncts in identifying the most representative area for biopsy. They may potentially become alternative diagnostic options in the future, offering benefits in terms of cost, diagnostic efficiency, aesthetics and patient satisfaction as the prevalence of tattoo‐related adverse reactions continues to rise. [ABSTRACT FROM AUTHOR]

Urinary tract infections (UTIs) are a common health issue affecting individuals worldwide. Recurrent urinary tract infections (rUTI) pose a significant clinical challenge, with limited understanding of the underlying mechanisms. Recent research suggests that the urobiome, the microbial community residing in the urinary tract, may play a crucial role in the development and recurrence of urinary tract infections. However, the specific virulence factor genes (VFGs) driven by urobiome contributing to infection recurrence remain poorly understood. Our study aimed to investigate the relationship between urobiome driven VFGs and recurrent urinary tract infections. By analyzing the VFGs composition of the urinary microbiome in patients with rUTI compared to a control group, we found higher alpha diversity in rUTI patients compared with healthy control. And then, we sought to identify specific VFGs features associated with infection recurrence. Specifically, we observed an increased abundance of certain VGFs in the recurrent infection group. We also associated VFGs and clinical data. We then developed a diagnostic model based on the levels of these VFGs using random forest and support vector machine analysis to distinguish healthy control and rUIT, rUTI relapse and rUTI remission. The diagnostic accuracy of the model was assessed using receiver operating characteristic curve analysis, and the area under the ROC curve were 0.83 and 0.75. These findings provide valuable insights into the complex interplay between the VFGs of urobiome and recurrent urinary tract infections, highlighting potential targets for therapeutic interventions to prevent infection recurrence.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy, often associated with a poor prognosis for patients. One of the major challenges in managing PDAC is the difficulty in early diagnosis, owing to the limited and invasive nature of current diagnostic methods. Recent studies have identified the oral microbiome as a potential source of non-invasive biomarkers for diseases, including PDAC. In this study, we focused on leveraging the differential expression of virulence factors (VFs) encoded by the oral microbiome to create a diagnostic tool for PDAC. We observed a higher alpha diversity in VF categories among PDAC patients compared to healthy controls. We then identified a panel of VF categories that were significantly upregulated in PDAC patients, these being associated with bacterial adherence, exoenzyme production, and nutritional/metabolic processes. Moreover, Streptococcus-derived VFs were notably enriched in PDAC patients. We developed a diagnostic model using random forest analysis based on the levels of these VFs. The model's diagnostic accuracy was evaluated using receiver operating characteristic (ROC) curve analysis, with an area under the curve (AUC) of 0.88, indicating high accuracy in differentiating PDAC patients from healthy controls. Our findings suggest that VFs encoded by the oral microbiome hold potential as diagnostic tools for PDAC, offering a non-invasive approach that could significantly enhance early detection and prognosis, ultimately leading to improved patient outcomes.

In the food industry, there is a growing demand for cost-effective methods for the inline inspection of food items able to non-invasively detect small foreign bodies that may have contaminated the product during the production process. Microwave imaging may be a valid alternative to the existing technologies, thanks to its inherently low-cost and its capability of sensing low-density contaminants. In this paper, a simple microwave imaging system specifically designed to enable the inspection of a large variety of food products is presented. The system consists of two circularly loaded antipodal Vivaldi antennas with a very large operative band, from 1 to 15 GHz, thus allowing a suitable spatial resolution for different food products, from mostly fatty to high water-content foods. The antennas are arranged in such a way as to collect a signal that can be used to exploit a recently proposed real-time microwave imaging strategy, leveraging the inherent symmetries that usually characterize food items. The system is experimentally characterized, and the achieved results compare favorably with the design specifications and numerical simulations. Relying on these positive results, the first experimental proof of the effectiveness of the entire system is presented confirming its efficacy.

Traditional high‐frequency ultrasound (HFUS; 20 MHz) is a non‐invasive method used to study skin in vivo but is not able to measure skin thickness accurately and to identify the dermal‐epidermal junction (DEJ). Ultra‐high frequency ultrasound (UHFUS; 70–100 MHz) has sub‐millimetre resolution comparable to histology. The aim of this study was to identify, by UHFUS, the DEJ and to describe skin differences in healthy individuals by providing a measure of skin thickness, based on age and gender. We also described the bullous pemphigoid lesion. We enrolled 42 patients divided into 2 groups: A and B. Group A included 32 healthy volunteers aged 22–74 years. Group B consisted of 10 patients with bullous pemphigoid. For each patient in group A, 8 ultrasound (US) clips by 70 MHz probe were performed at forehead, cheek, nose, forearm, abdomen, chest, back and leg. For each patient in group B, 5 US images were acquired at blisters roofs and edges. In each US image, we measured thickness of stratum corneum (α‐β), epidermis (α‐γ) and epidermis plus dermis (α‐δ). In both groups, we found the presence of 4 lines delimiting: the stratum corneum (the layer between α‐line and β‐line), the epidermis (distance between α‐ and γ‐line), and the boundary between dermis and subcutis (δ‐line). The γ‐line corresponds to the point of detachment of the bullae. The abdominal α‐β layer was thicker in males (p = 0.019) and α‐δ thickness at cheeks (p < 0.001), chest (p = 0.007), back (p = 0.025) and forearm (p < 0.001). In females, α‐γ thickness of the back was greater (p = 0.005). In old people compared to young, we noticed an increase of α‐β layer at forehead and chest (p = 0.014), an increase of α‐γ layer at forearm (p = 0.001), back (p = 0.024) and leg (p = 0.010) and an increase of α‐δ layer at forehead (p = 0.001) and nose (p = 0.049). UHFUS is an advanced imaging technique that can detect both the DEJ and the boundary between dermis and subcutaneous tissue so that epidermal and dermal thickness can be measured with good accuracy. Regarding gender and age, skin differences obtained with UHFUS were comparable to other non‐invasive methods. [ABSTRACT FROM AUTHOR]

In the framework of built heritage monitoring techniques, a prominent position is occupied by thermography, which represents an efficient and non-invasive solution for these kinds of investigations, allowing the identification of phenomena detectable only in the non-visible range of the electromagnetic spectrum. This is of extreme interest, especially considering the possibility of integrating the radiometric information with the 3D models achievable from laser scanning or photogrammetric techniques, characterised by a high spatial resolution. This paper aims to illustrate how combining different geomatics techniques (in particular, by merging thermal images, laser scanning point clouds, and traditional visible colour photogrammetric data) can efficiently support historical analyses for studying heritage buildings. Additionally, a strategy for generating HBIM models starting from the integration of 3D thermal investigations and historical sources is proposed, concerning both the multi-temporal modification of the volumes of the building and the individual architectural elements. The case study analysed for the current research was the Palacio de Colomina in Valencia, Spain, a noble palace—now the headquarters of a university—that, during the last few centuries, has been subjected to considerable transformations in terms of rehabilitation works and modification of its volume. [ABSTRACT FROM AUTHOR]

At present, a search for promising ways to diagnose infection caused by SARS-CoV-2 is quite relevant. Oral fluid is not commonly used for assessment of COVID-19 risk. Its molecular profile reflects both local state of the oral cavity, and individual organs and systems, thus suggesting a reliable diagnostic platform. Systemic inflammatory response is known to play a crucial role in development of the coronavirus infection; the “cytokine storm” determines severity of the disease. The saliva-based diagnostics of clinical course in COVID-19 patients includes determination of IL-6, IL-8, C-reactive protein in oral fluid, in order to assess severity of the inflammatory process. The present study was carried out at the Department of Fundamental and Clinical Biochemistry with Laboratory Diagnostics, and Department of Pediatric Infections at the Samara State Medical University. The study involved 122 persons: 67 clinically healthy individuals comprised the control group, and the group of comparison included 55 inpatients with moderate or severe coronavirus infection (COVID-19) caused by SARS-CoV-2 virus as confirmed by PCR and/or ELISA testing. Development of the disease was accompanied by drastically increased contents of IL-6 and IL-8 in oral fluid of the patients relative to the indexes in healthy persons, i.e., several-fold for IL-6 (+ 650%) and even higher elevation of IL-8 levels (+ 26513%), as well as a 2-fold increase of C-reactive protein (+115%). When comparing the immune indexes of oral fluid in presence versus absence of respiratory insufficiency, a significant difference was found for salivary IL-6 (+173%) in the patients with grade 1-2 respiratory insufficiency as compared with patients free of respiratory disorders. Determination of these proinflammatory markers in patients with COVID-19 is of important prognostic significance when assessing development of the disease and its severity. Direct detection of their content in the oral fluid makes this method relevant, and potentially demanded for the outpatient diagnostics, being highly important during pandemics of coronavirus infection and limited medical resources. Examination of oral fluid at the pre-hospital stage is a resource-saving technology, since it does not require additional medical staff to take biomaterial, is non-invasive to the patient, and suggesting a wide range of research items, it can resolve a number of diagnostic issues, e.c., presence of specific genetic material or antibodies to SARS-CoV-2, severity of the inflammatory process and the risk of respiratory failure in the patient.

Malignant melanoma poses a clinical diagnostic problem, since a large number of benign lesions are excised to find a single melanoma. This study assessed the accuracy of a novel non-invasive diagnostic technology, hyperspectral imaging, for melanoma detection. Lesions were imaged prior to excision and histopathological analysis. A deep neural network algorithm was trained twice to distinguish between histopathologically verified malignant and benign melanocytic lesions and to classify the separate subgroups. Furthermore, 2 different approaches were used: a majority vote classification and a pixel-wise classification. The study included 325 lesions from 285 patients. Of these, 74 were invasive melanoma, 88 melanoma in situ, 115 dysplastic naevi, and 48 non-dysplastic naevi. The study included a training set of 358,800 pixels and a validation set of 7,313 pixels, which was then tested with a training set of 24,375 pixels. The majority vote classification achieved high overall sensitivity of 95% and a specificity of 92% (95% confidence interval (95% CI) 0.024–0.029) in differentiating malignant from benign lesions. In the pixel-wise classification, the overall sensitivity and specificity were both 82% (95% CI 0.005–0.005). When divided into 4 subgroups, the diagnostic accuracy was lower. Hyperspectral imaging provides high sensitivity and specificity in distinguishing between naevi and melanoma. This novel method still needs further validation.

• Diagnostic of ancient paper by completely non-invasive diagnostic approach. • UV–Vis-NIR imaging, FORS and fluorescence spectroscopies performed in-situ. • HPLC and FTIR analyses on extracts obtained by a smart sampling method. • A complete characterization of two letters of St. Francis de Sales (1567–1622) was obtained. We report a non-invasive and multi-analytical physico-chemical method for the characterization of paper artworks, able to identify sizing, inks, and glues and to quantify oxidative degradation by-products. The proposed methodology is mostly carried out in situ by using easy-to-use and cheap portable instrumentation for the acquisition of multispectral images, punctual ultraviolet-visible-near infrared fiber-optics reflectance spectroscopy (FORS) and punctual fiber optics fluorescence spectroscopy. Further analytical information is provided by non-invasive in-situ sampling of paper surface by using soft latex sponges, making possible laboratory chromatographic and infrared spectroscopic analyses on the aqueous sponge extracts. The proposed diagnostics method was applied to two 17th century letters written by St Francis of Sales (1567–1622), collected at the Chigi Palace in the town of Ariccia (Italy). Results show an intense oxidative degradation of the letters, also localized in water spots, and the presence of carboxylic acids by-products. Analysis of FORS spectra provided the concentration of chromophores in the paper substrate. The diagnostic method allowed the identification of gelatin sizing, the presence of starch glue in specific areas of the letters and the type of ink used in the text. Our diagnostic approach aims to offer to conservator-restorer a characterization of a paper artwork, that can be applied to other, for a correct planning of conservation interventions. [ABSTRACT FROM AUTHOR]

Cystic fibrosis (CF) is the most common autosomal recessive disease in the Caucasian population. Cystic fibrosis-related liver disease (CFLD) is defined as the pathogenesis related to the underlying CFTR defect in biliary epithelial cells. CFLD needs to be distinguished from other liver manifestations that may not have any pathological significance. The clinical/histological presentation and severity of CFLD vary. The main histological presentation of CFLD is focal biliary fibrosis, which is usually asymptomatic. Portal hypertension develops in a minority of cases (about 10%) and may require specific management including liver transplantation for end-stage liver disease. Portal hypertension is usually the result of the progression of focal biliary fibrosis to multilobular cirrhosis during childhood. Nevertheless, non-cirrhotic portal hypertension as a result of porto-sinusoidal vascular disease is now identified increasingly more frequently, mainly in young adults. To evaluate the effect of new CFTR modulator therapies on the liver, the spectrum of hepatobiliary involvement must first be precisely classified. This paper discusses the phenotypic features of CFLD, its underlying physiopathology and relevant diagnostic and follow-up approaches, with a special focus on imaging. [ABSTRACT FROM AUTHOR]

Aim: Formation of goals of the rehabilitation process of patients with the post-covid syndrome in accordance with the needs of the patient, and the results of sufficient diagnosis. Materials and Methods: A total of 132 people were examined. In 48 patients diagnosed with COVID-19 coronavirus (PCR test). Diagnosis of study participants occurred after 8-12 weeks of the acute period. None of the patients after the acute period of the disease underwent a course of rehabilitation treatment. The diagnosis was performed using a non-invasive blood formula analyzer AMP. Before the measurement, the respiratory rate, heart rate, and the patient`s weight, age, and sex were recorded. Statistical data processing was performed using the statistical package MedStat. Results: The values of such indicators as the Tiffno test, dopamine-β-hydrolase, skeletal muscle circulation, the complex factor regulating cell mitosis were out of the norm in the group of participants who suffered from covid-19, but compared with the control group, was not found a statistically significant difference between the above indicators (p>0.05). Such values are a consequence of the disease and are the basis for describing the main long-term consequences that correspond to the post-covid syndrome. Conclusions: The goals of the rehabilitation process of patients with the post-covid syndrome should be formed in accordance with the positions of evidence-based medicine. The non-invasive blood formula analyzer allows determining the direction of rehabilitation treatment taking into account concomitant chronic diseases and taking into account the patient`s ability to carry out the correction of rehabilitation programs in real-time. [ABSTRACT FROM AUTHOR]

The paper presents an intelligent module to control dynamic two-phase gas–liquid mixtures pipelines flow processes. The module is intelligent because it uses the algorithm based on AI methods, namely, fuzzy logic inference, to build the fuzzy regulator concept. The developed modification has allowed to design and implement the black-box type regulator. Therefore, it is not required to determine any of the complicated computer models of the flow rig, which is unfortunately necessary when using the classic regulators. The inputs of the regulator are four linguistic variables that are decomposed into two classes and two methods of fuzzification. The first input class describes the current values of gas and liquid pipe flows, which at the same time are the controlled values manipulated to generate desired flow type. The second class of the input signals contains a current flow state, namely, its name and the name preferred by the operator flow type. This approach improves the control accuracy since the given flow type can be generated with different gas and liquid volume fractions. Those values can be optimized by knowing the current flow type. Moreover, the fuzzification algorithm used for the input signals included in the first-class covers the current crisp signal value and its trend making the inference more accurate and resistant to slight measurement system inaccuracy. This approach of defined input signals in such environments is used for the first time. Considering all mentioned methods, it is possible to generate the desired flow type by manipulating the system input signals by minimum required values. Furthermore, a flow type can be changed by adjusting only one of the input signals. As an output of the inference process, two linguistic values are received, which are fuzzified adjustment values of the liquid pump and gas flow meter. The regulator looks to be universal, and it can be adopted by multiple test and production rigs. Moreover, once configured with a dedicated rig, it can be easily operated by the non (domain) technical staff. The usage of fuzzy terms makes understanding both the control strategy working principles and the obtained results easy. [ABSTRACT FROM AUTHOR]

Malignant melanoma poses a clinical diagnostic problem, since a large number of benign lesions are excised to find a single melanoma. This study assessed the accuracy of a novel non-invasive diagnostic technology, hyperspectral imaging, for melanoma detection. Lesions were imaged prior to excision and histopathological analysis. A deep neural network algorithm was trained twice to distinguish between histopathologically verified malignant and benign melanocytic lesions and to classify the separate subgroups. Furthermore, 2 different approaches were used: a majority vote classification and a pixel-wise classification. The study included 325 lesions from 285 patients. Of these, 74 were invasive melanoma, 88 melanoma in situ, 115 dysplastic naevi, and 48 non-dysplastic naevi. The study included a training set of 358,800 pixels and a validation set of 7,313 pixels, which was then tested with a training set of 24,375 pixels. The majority vote classification achieved high overall sensitivity of 95% and a specificity of 92% (95% confidence interval (95% CI) 0.024-0.029) in differentiating malignant from benign lesions. In the pixel-wise classification, the overall sensitivity and specificity were both 82% (95% CI 0.005-0.005). When divided into 4 subgroups, the diagnostic accuracy was lower. Hyperspectral imaging provides high sensitivity and specificity in distinguishing between naevi and melanoma. This novel method still needs further validation. [ABSTRACT FROM AUTHOR]

Study Question: Does natural variation exist in the endometrial stem/progenitor cell and protein composition of menstrual fluid across menstrual cycles in women?Summary Answer: Limited variation exists in the percentage of some endometrial stem/progenitor cell types and abundance of selected proteins in menstrual fluid within and between a cohort of women.What Is Known Already: Menstrual fluid is a readily available biofluid that can represent the endometrial environment, containing endometrial stem/progenitor cells and protein factors. It is unknown whether there is natural variation in the cellular and protein content across menstrual cycles of individual women, which has significant implications for the use of menstrual fluid in research and clinical applications.Study Design, Size, Duration: Menstrual fluid was collected from 11 non-pregnant females with regular menstrual cycles. Participants had not used hormonal medications in the previous 3 months. Participants collected menstrual fluid samples from up to five cycles using a silicone menstrual cup worn on Day 2 of menstrual bleeding.Participants/materials, Setting, Methods: Menstrual fluid samples were centrifuged to separate soluble proteins and cells. Cells were depleted of red blood cells and CD45+ leucocytes. Menstrual fluid-derived endometrial stem/progenitor cells were characterized using multicolour flow cytometry including markers for endometrial stem/progenitor cells N-cadherin (NCAD) and stage-specific embryonic antigen-1 (SSEA-1) (for endometrial epithelial progenitor cells; eEPC), and sushi domain containing-2 (SUSD2) (for endometrial mesenchymal stem cells; eMSC). The clonogenicity of menstrual fluid-derived endometrial cells was assessed using colony forming unit assays. Menstrual fluid supernatant was analyzed using a custom magnetic Luminex assay.Main Results and the Role Of Chance: Endometrial stem/progenitor cells are shed in menstrual fluid and demonstrate clonogenic properties. The intraparticipant agreement for SUSD2+ menstrual fluid-derived eMSC (MF-eMSC), SSEA-1+ and NCAD+SSEA-1+ MF-eEPC, and stromal clonogenicity were moderate-good (intraclass correlation; ICC: 0.75, 0.56, 0.54 and 0.52, respectively), indicating limited variability across menstrual cycles. Endometrial inflammatory and repair proteins were detectable in menstrual fluid supernatant, with five of eight (63%) factors demonstrating moderate intraparticipant agreement (secretory leukocyte protein inhibitor (SLPI), lipocalin-2 (NGAL), lactoferrin, follistatin-like 1 (FSTL1), human epididymis protein-4 (HE4); ICC ranges: 0.57-0.69). Interparticipant variation was limited for healthy participants, with the exception of key outliers of which some had self-reported menstrual pathologies.Large Scale Data: N/A. There are no OMICS or other data sets relevant to this study.Limitations, Reasons For Caution: The main limitations to this research relate to the difficulty of obtaining menstrual fluid samples across multiple menstrual cycles in a consistent manner. Several participants could only donate across <3 cycles and the duration of wearing the menstrual cup varied between 4 and 6 h within and between women. Due to the limited sample size used in this study, wider studies involving multiple consecutive menstrual cycles and a larger cohort of women will be required to fully determine the normal range of endometrial stem/progenitor cell and supernatant protein content of menstrual fluid. Possibility for selection bias and true representation of the population of women should also be considered.Wider Implications Of the Findings: Menstrual fluid is a reliable source of endometrial stem/progenitor cells and related endometrial proteins with diagnostic potential. The present study indicates that a single menstrual sample may be sufficient in characterizing a variety of cellular and protein parameters across women's menstrual cycles. The results also demonstrate the potential of menstrual fluid for identifying endometrial and menstrual abnormalities in both research and clinical settings as a non-invasive method for assessing endometrial health.Study Funding/competing Interest(s): This study was supported by grants from the Australian National Health and Medical Research Council to C.E.G. (Senior Research Fellowship 1024298 and Investigator Fellowship 1173882) and to J.E. (project grant 1047756), the Monash IVF Research Foundation to C.E.G. and the Victorian Government's Operational Infrastructure Support Program. K.A.W., M.L.D.-T., S.G.S. and J.E. declare no conflicts of interest. C.E.G. reports grants from NHMRC, during the conduct of the study; grants from EndoFound USA, grants from Ferring Research Innovation, grants from United States Department of Defence, grants from Clue-Utopia Research Foundation, outside the submitted work. CEF reports grants from EndoFound USA, grants from Clue-Utopia Research Foundation, outside the submitted work. [ABSTRACT FROM AUTHOR]

The paper presents an intelligent module to control dynamic two-phase gas–liquid mixtures pipelines flow processes. The module is intelligent because it uses the algorithm based on AI methods, namely, fuzzy logic inference, to build the fuzzy regulator concept. The developed modification has allowed to design and implement the black-box type regulator. Therefore, it is not required to determine any of the complicated computer models of the flow rig, which is unfortunately necessary when using the classic regulators. The inputs of the regulator are four linguistic variables that are decomposed into two classes and two methods of fuzzification. The first input class describes the current values of gas and liquid pipe flows, which at the same time are the controlled values manipulated to generate desired flow type. The second class of the input signals contains a current flow state, namely, its name and the name preferred by the operator flow type. This approach improves the control accuracy since the given flow type can be generated with different gas and liquid volume fractions. Those values can be optimized by knowing the current flow type. Moreover, the fuzzification algorithm used for the input signals included in the first-class covers the current crisp signal value and its trend making the inference more accurate and resistant to slight measurement system inaccuracy. This approach of defined input signals in such environments is used for the first time. Considering all mentioned methods, it is possible to generate the desired flow type by manipulating the system input signals by minimum required values. Furthermore, a flow type can be changed by adjusting only one of the input signals. As an output of the inference process, two linguistic values are received, which are fuzzified adjustment values of the liquid pump and gas flow meter. The regulator looks to be universal, and it can be adopted by multiple test and production rigs. Moreover, once configured with a dedicated rig, it can be easily operated by the non (domain) technical staff. The usage of fuzzy terms makes understanding both the control strategy working principles and the obtained results easy.

The results of the study of air-ions in 310 patients with combined pathology of digestive organs are considered in this article. The data about a new non-invasive method of the diagnostics and individual integrated treatment choice, particularly diet are represented. The selection of food according to the main electrochemically characteristics is grounded. Prospects of using the method of air-ionic testing in clinical practice as non-invasive technology of primary screening and control of treatment results are estimated.

Although detection of urothelial cell carcinoma (or bladder cancer, BC) can be performed via cytological, molecular and genetic marker tests on urine, cystoscopy, an invasive technique, still remains as the gold methodology in clinical practice. It is presented a non-invasive method for detecting BC recurrence consisting of a direct electrochemical test in urine combining voltammetric data at gold and glassy carbon electrodes. The diagnosis is based on the ratio between characteristic voltammetric features recorded for tryptophan, serotonin and melatonin and other related metabolites. The method was tested by means of a clinical trial with 30 patients diagnosed of bladder cancer and a two control groups: 17 healthy volunteers and 15 patients diagnosed of other urinary pathologies and permitted detection of non-muscle invasive stages (pTa, pT1) and muscle-invasive stages (pT2 cancers) of BC. [ABSTRACT FROM AUTHOR]

Abstract: A new technique of diagnosing data for broken rotor bars in induction motors derived from two of the three stator currents, the Beirut diagnostic procedure (BDP) is presented in this paper. The theoretical principles directly related to the application of this diagnostic technique are described, emphasizing the use of a severity factor in order to evaluate the extension of the fault. Defining the severity factor as the normalized amplitude of the fault characteristic frequency enables us to draw up a table of comparison of several usual electric diagnostic methods. Besides the traditional one-phase current spectrum analysis, values of the severity factor related to electrical signals like the instantaneous powers, the current space vector modulus and finally related to the new Beirut diagnostic method are analyzed with respect to the variation of the power factor angle and of the sum of the two current side-band angular displacement. The BDP offers several advantages over the usual motor current signature analyses (MCSA) methods: it is shown how the proposed severity factor applied to the new diagnostic technique is not dependent on motor parameters such as the power factor angle and the fault type which is not the case of the instantaneous powers. In addition, the BDP has the advantage of detecting easily fault characteristic frequencies, which is not possible via diagnostic methods that use the detection of two side-band components as in the simple current spectrum. By theoretical analysis, computer simulations, and laboratory experiments, it is shown that the new method enhances the reliability of diagnostics of broken rotor bars in induction motor. [Copyright &y& Elsevier]

This article presents a comparative investigation of various media for non-invasive diagnosis of mechanical abnormalities in induction motors. Stator voltages and stator currents as well as noises on these signals are simulated first for a fault-free motor then for a motor with mechanical abnormalities. These signals are subsequently employed to compute the instantaneous powers Pab, Pcb, Pabc and last the current Park vector modulus known as the extended Park vector approach (EPVA) method. Waveforms of these simulated signals were analyzed using the power spectral density transformation. Commercially available diagnostics systems use the fact that the amplitude of some components known as fault characteristic frequencies in these electrical signals increase when mechanical abnormalities occur. The amplitude increase of these characteristic frequencies is employed as a criterion in order to investigate noise immunity of the five diagnosis methods, thus making possible their classification. Simulation and experimental results show that the EPVA reveals the highest noise immunity. Utilization of the EPVA is thus enhancing the reliability of diagnostics of induction motor drives. [ABSTRACT FROM AUTHOR]

Copyright of Der Internist is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• Here we describe a strategy to detect PD-L1 exosomes through graphene modified gold chip using a multifunctional peptide as a recognition supermolecules. • Graphene assembly domains in the M-Pep enhanced the inclusion affinities between the graphene and supermolecules. • Antifouling chain makes the sensors surface prevent unnecessary non-specific adsorption, thus increasing the detection accuracy. • The detection limit of 20 particles·mL−1 was reached without signal amplification. Exosomes are lipid-bilayer-enclosed extracellular vehicles (EVs) derived from all cells and circulating in the blood. Identification of cancer specific exosomes in body fluids has shown great potential for cancer diagnostics. The low concentration in blood and likely to deplete their native character on the solid surface makes it difficult to measure it in real time sensitively. Here we describe a strategy to detect PD-L1 exosomes through graphene modified gold chip using a multifunctional peptide (M-Pep, SS-IMVTESSDYSSY-KK-FHYQRDTPKSYN) as a recognition supermolecule. Graphene assembly, antifouling and PD-L1 specific binding domains in the M-Pep enhanced the inclusion affinities between the graphene and supermolecules and ensure keeping its recognition properties efficiently. The fabricated direct-real-time SPR sensor based on M-Pep shows a good sensitivity for the detection of PD-L1 exosomes. Own to its simple, convenient and effective, this M-Pep based SPR sensor provides a useful platform to facilitate clinical investigations of exosomes for noninvasive disease diagnoses. This approach may serve as a potential non-invasive diagnostic and screening tool to detect cancer biomarker and facilitate possible curative therapy. [ABSTRACT FROM AUTHOR]

Endometriosis is a chronic inflammatory disorder characterized by the presence of endometrial-like tissue growing outside of the uterus. Although the cause is unknown, retrograde menstruation leads to deposition of endometrial cells into the peritoneal cavity. Lack of disease recognition and long diagnostic delays (6-10 years) lead to substantial personal, social and financial burdens, as well as delayed treatment. A non-invasive diagnostic for endometriosis is a major unmet clinical need. Here, we assessed whether differences in menstrual effluent-derived stromal fibroblast cells (ME-SFCs) from women with and without endometriosis provide the basis for a non-invasive diagnostic for endometriosis. In addition, we investigated whether treatment of control ME-SFCs with inflammatory cytokines (TNF and IL-1β) could induce an endometriosis-like phenotype. ME-SFCs from laparoscopically diagnosed endometriosis patients exhibit reduced decidualization capacity, measured by IGFBP1 production after exposure to cAMP. A receiver operating characteristic (ROC) curve developed using decidualization data from controls and endometriosis subjects yielded an area under the curve of 0.92. In addition, a significant reduction in ALDH1A1 gene expression and increased podoplanin surface expression were also observed in endometriosis ME-SFCs when compared to control ME-SFCs. These endometriosis-like phenotypes can be reproduced in control ME-SFCs by exposure to inflammatory cytokines (TNF and IL-1β) and are associated with increased cell migration. These results are consistent with the hypothesis that chronic intrauterine inflammation influences the development of endometriosis lesions following retrograde menstruation. In conclusion, the analysis of ME-SFCs can provide an accurate, rapid, and non-invasive diagnostic for endometriosis and insight into disease pathogenesis., (Copyright © 2020 Nayyar, Saleem, Yilmaz, DeFranco, Klein, Elmaliki, Kowalsky, Chatterjee, Xue, Viswanathan, Shih, Gregersen and Metz.)

Background: Decision-making in treatment of an acute compartment syndrome is based on clinical assessment, supported by invasive monitoring. Thus, evolving compartment syndrome may require repeated pressure measurements. In suspected cases of potential compartment syndromes clinical assessment alone seems to be unreliable. The objective of this study was to investigate the feasibility of a non-invasive application estimating whole compartmental elasticity by ultrasound, which may improve accuracy of diagnostics., Methods: In an in vitro model, using an artificial container simulating dimensions of the human anterior tibial compartment, intra-compartmental pressures (p) were raised subsequently up to 80 mmHg by infusion of saline solution. The compartmental depth (mm) in the cross-section view was measured before and after manual probe compression (100 mmHg) upon the surface resulting in a linear compartmental displacement (∆d). This was repeated at rising compartmental pressures. The resulting displacements were related to the corresponding intra-compartmental pressures simulated in our model. A hypothesized relationship between pressures related compartmental displacement and the elasticity at elevated compartment pressures was investigated., Results: With rising compartmental pressures, a non-linear, reciprocal proportional relation between the displacement (mm) and the intra-compartmental pressure (mmHg) occurred. The Pearson coefficient showed a high correlation (r(2) = -0.960). The intra-observer reliability value kappa resulted in a statistically high reliability (κ = 0.840). The inter-observer value indicated a fair reliability (κ = 0.640)., Conclusions: Our model reveals that a strong correlation between compartmental strain displacements assessed by ultrasound and the intra-compartmental pressure changes occurs. Further studies are required to prove whether this assessment is transferable to human muscle tissue. Determining the complete compartmental elasticity by ultrasound enhancement, this application may improve detection of early signs of potential compartment syndrome.