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Melanocytic nevi, commonly known as moles, are benign skin lesions that often occur in children and adolescents. Overall, they are less common in children compared to adults. Understanding the diagnosis and management of melanocytic nevi and risk factors for melanoma development is crucial for their early detection and appropriate treatment. This paper presents children's most common melanocytic nevi, including their epidemiology, morphology, diagnostic methods, and treatment. [ABSTRACT FROM AUTHOR]

The early detection and classification of lung cancer is crucial for improving a patient's outcome. However, the traditional classification methods are based on single machine learning models. Hence, this is limited by the availability and quality of data at the centralized computing server. In this paper, we propose an ensemble Federated Learning-based approach for multi-order lung cancer classification. This approach combines multiple machine learning models trained on different datasets allowing for improvising accuracy and generalization. Moreover, the Federated Learning approach enables the use of distributed data while ensuring data privacy and security. We evaluate the approach on a Kaggle cancer dataset and compare the results with traditional machine learning models. The results demonstrate an accuracy of 89.63% with lung cancer classification. [ABSTRACT FROM AUTHOR]

Quick and reliable mass testing of infected people is an effective tool for the contingency of SARS-CoV-2. During the COVID-19 pandemic, Point-of-Care (POC) tests using Loop-Mediated Isothermal Amplification (LAMP) arose as a useful diagnostic tool. LAMP tests are a robust and fast alternative to Polymerase Chain Reaction (PCR), and their isothermal property allows easy incorporation into POC platforms. The main drawback of using colorimetric LAMP is the reported short-term stability of the pre-mixed reagents, as well as the relatively high rate of false-positive results. Also, low-magnitude amplification can produce a subtle color change, making it difficult to discern a positive reaction. This paper presents Hilab Molecular, a portable device that uses the Internet of Things and Artificial Intelligence to pre-analyze colorimetric data. In addition, we established manufacturing procedures to increase the stability of colorimetric RT-LAMP tests. We show that ready-to-use reactions can be stored for up to 120 days at −20 °C. Furthermore, we validated both the Hilab Molecular device and the Hilab RT-LAMP test for SARS-CoV-2 using 581 patient samples without any purification steps. We achieved a sensitivity of 92.93% and specificity of 99.42% (samples with CT ≤ 30) when compared to RT-qPCR. [ABSTRACT FROM AUTHOR]

(1) Introduction: Wilson's disease (WND) is an autosomal recessive disorder of copper metabolism. The WND gene is ATP7B, located on chromosome 13. WND is characterized by high clinical variability, which causes diagnostic difficulties. (2) Methods: The PubMed, Science Direct, and Wiley Online Library medical databases were reviewed using the following phrases: "Wilson's disease", "ATP7B genotype", "genotype-phenotype", "epigenetics", "genetic modifiers", and their combinations. Publications presenting the results of experimental and clinical studies, as well as review papers, were selected, which concerned: (i) the diversity of genetic strategies and tests used in WND diagnosis; (ii) the difficulties of genetic diagnosis, including uncertainty as to the pathogenicity of variants; (iii) genetic counseling; (iv) phenotypic effects of ATP7B variants in patients with WND and in heterozygous carriers (HzcWND); (v) genetic and epigenetics factors modifying the clinical picture of the disease. (3) Results and conclusions: The genetic diagnosis of WND is carried out using a variety of strategies and tests. Due to the large number of known variants in the ATP7B gene (>900), the usefulness of genetic tests in routine diagnostics is still relatively small and even analyses performed using the most advanced technologies, including next-generation sequencing, require additional tests, including biochemical evidence of abnormal copper metabolism, to confirm the diagnosis of WND. Pseudodominant inheritance, the presence of three various pathogenic variants in the same patient, genotypes indicating the possibility of segmental uniparental disomy, have been reported. Genotype–phenotype relationships in WND are complex. The ATP7B genotype, to some extent, determines the clinical picture of the disease, but other genetic and epigenetic modifiers are also relevant. [ABSTRACT FROM AUTHOR]

Cervical cancer ranks third among all new cancer cases and causes of cancer deaths in females. The paper provides an overview of cervical cancer prevention strategies employed in different regions, with incidence and mortality rates ranging from high to low. It assesses the effectiveness of approaches proposed by national healthcare systems by analysing data published in the National Library of Medicine (Pubmed) since 2018 featuring the following keywords: "cervical cancer prevention", "cervical cancer screening", "barriers to cervical cancer prevention", "premalignant cervical lesions" and "current strategies". WHO's 90-70-90 global strategy for cervical cancer prevention and early screening has proven effective in different countries in both mathematical models and clinical practice. The data analysis carried out within this study identified promising approaches to cervical cancer screening and prevention, which can further enhance the effectiveness of the existing WHO strategy and national healthcare systems. One such approach is the application of AI technologies for detecting precancerous cervical lesions and choosing treatment strategies. As such studies show, the use of AI can not only increase detection accuracy but also ease the burden on primary care. [ABSTRACT FROM AUTHOR]

Autoimmune diseases of the liver and biliary tract require timely and accurate diagnosis. This study evaluates the D-tek panel (D-Tek, Mons, Belgium) of 10 immunodot antigens for its effectiveness in diagnosing autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC). We retrospectively analysed serum samples from 111 patients who had undergone routine testing, including indirect immunofluorescence (IIF) and enzyme-linked immunosorbent assays (ELISA), to confirm or exclude autoimmune liver or biliary tract disease. The panel tested for M2/nPDC, M2/OGDC-E2, M2/BCOADC-E2, M2/PDC-E2, gp210, sp100, LKM1, LC1, SLA, and F-actin antigens. Results showed that all positive IIF+ELISA results were confirmed by the immunodot panel, except for two samples from patients who had never been diagnosed with AIH. The immunodot test identified over 20 additional autoantibodies in samples initially negative by IIF, corroborated by laboratory imaging and medical history. The immunodot technique proved to be a quick, sensitive, and specific method with high overall accuracy. This study suggests that the immunodot technique may be an effective screening and confirmatory method for autoimmune liver diseases, potentially improving diagnostic efficiency and accuracy in clinical practice. [ABSTRACT FROM AUTHOR]

Postpartum hypertension (PPHT) is hypertension that persists or develops after delivery and is a frequent cause of readmission, affecting 10% of pregnancies. This interim analysis aims to describe the cohort and to determine the feasibility and acceptance of a home-based telemonitoring management strategy (HBTMS) in PPHT patients. Enrollment at the University Hospital Basel began during the 2020 SARS-CoV-2 pandemic. Maternity-ward patients were screened for preexisting hypertension, hypertensive disorders of pregnancy, and de novo PPHT. In this pragmatic non-randomized prospective trial, the participants chose the HBTMS or standard of care (SOC), which consisted of outpatient hypertension clinic appointments. The HBTMS was a smartphone application or a programmed spreadsheet to report blood pressure (BP), followed by telephone consultations. Three months postpartum, the participants underwent a 24 h BP measurement and a blood, biomarker, and urine analysis. A total of 311 participants were enrolled between 06/20 and 08/23. The mean age was 34 (±5.3) years. The current pregnancy history demonstrated the following (≥1 diagnosis possible): 10% had preexisting hypertension, 27.3% gestational hypertension, 53% preeclampsia (PE), 0.3% eclampsia, 6% HELLP (hemolysis, elevated liver enzymes, and low platelets), and 18.3% de novo PPHT. A family history of cardiovascular disease and PE was reported in 49.5% and 7.5%, respectively. In total, 23.3% were high-risk for PE. A total of 68.5% delivered via c-section, the mean hospitalization was 6.3 days (±3.9), and newborn intrauterine growth restriction occurred in 21%. A total of 99% of the participants chose the HBTMS. This analysis demonstrated that the HBTMS was accepted. This is vital in the immediate postpartum period and pertinent when the exposure of hospital visits should be avoided. [ABSTRACT FROM AUTHOR]

Background: This study evaluates the potential of ChatGPT and Google Bard as educational tools for patients in orthopedics, focusing on sports medicine and pediatric orthopedics. The aim is to compare the quality of responses provided by these natural language processing (NLP) models, addressing concerns about the potential dissemination of incorrect medical information. Methods: Ten ACL- and flat foot-related questions from a Google search were presented to ChatGPT-3.5 and Google Bard. Expert orthopedic surgeons rated the responses using the Global Quality Score (GQS). The study minimized bias by clearing chat history before each question, maintaining respondent anonymity and employing statistical analysis to compare response quality. Results: ChatGPT-3.5 and Google Bard yielded good-quality responses, with average scores of 4.1 ± 0.7 and 4 ± 0.78, respectively, for sports medicine. For pediatric orthopedics, Google Bard scored 3.5 ± 1, while the average score for responses generated by ChatGPT was 3.8 ± 0.83. In both cases, no statistically significant difference was found between the platforms (p = 0.6787, p = 0.3092). Despite ChatGPT's responses being considered more readable, both platforms showed promise for AI-driven patient education, with no reported misinformation. Conclusions: ChatGPT and Google Bard demonstrate significant potential as supplementary patient education resources in orthopedics. However, improvements are needed for increased reliability. The study underscores the evolving role of AI in orthopedics and calls for continued research to ensure a conscientious integration of AI in healthcare education. [ABSTRACT FROM AUTHOR]

The detection and monitoring of biomarkers in body fluids has been used to improve human healthcare activities for decades. In recent years, researchers have focused their attention on applying the point-of-care (POC) strategies into biomarker detection. The evolution of mobile technologies has allowed researchers to develop numerous portable medical devices that aim to deliver comparable results to clinical measurements. Among these, optical-based detection methods have been considered as one of the common and efficient ways to detect and monitor the presence of biomarkers in bodily fluids, and emerging aggregation-induced emission luminogens (AIEgens) with their distinct features are merging with portable medical devices. In this review, the detection methodologies that use optical measurements in the POC systems for the detection and monitoring of biomarkers in bodily fluids are compared, including colorimetry, fluorescence and chemiluminescence measurements. The current portable technologies, with or without the use of smartphones in device development, that are combined with optical biosensors for the detection and monitoring of biomarkers in body fluids, are also investigated. The review also discusses novel AIEgens used in the portable systems for the detection and monitoring of biomarkers in body fluid. Finally, the potential of future developments and the use of optical detection-based portable devices in healthcare activities are explored. [ABSTRACT FROM AUTHOR]

This review briefly introduces readers to an area where glycomics meets modern oncodiagnostics with a focus on the analysis of sialic acid (Neu5Ac)-terminated structures. We present the biochemical perspective of aberrant sialylation during tumourigenesis and its significance, as well as an analytical perspective on the detection of these structures using different approaches for diagnostic and therapeutic purposes. We also provide a comparison to other established liquid biopsy approaches, and we mathematically define an early-stage cancer based on the overall prognosis and effect of these approaches on the patient's quality of life. Finally, some barriers including regulations and quality of clinical validations data are discussed, and a perspective and major challenges in this area are summarised. [ABSTRACT FROM AUTHOR]

Intracranial chondroid tumors are a heterogeneous group of neoplasms characterized by the presence of a cartilage matrix. These tumors exhibit overlapping clinical and histological features. Mutations in IDH1/2 genes serve as important diagnostic markers of tumor type, particularly chondrosarcoma. To improve the accuracy of IDH1/2 diagnostics, we compared three methods: biochip assay, real-time PCR with DNA melting analysis using TaqMan probes and sequencing (qPCR-DMA-Sanger), and immunohistochemistry (IHC). Tumor samples from 96 patients were investigated. The IDH1 mutations were detected in 34/64 (53%) chondrosarcomas; IHC detected 27/56 (48.2%) mutations, the qPCR-DMA-Sanger method 27/59 (46%) mutations, and the biochip assay revealed 29/60 (48.3%) mutations. The detection of IDH1 mutations in chordoma (2/15) and osteosarcoma (2/7) suggested the need for a revised diagnosis. In benign tumors, IDH1 mutations were present in chondroma (4/6), but absent in chondromyxoid fibroma (0/4). The most frequent IDH1 mutations were R132C (60%), R132L, and R132G (13.5% each), R132H (8%), and R132S (5%). The concordance between the biochip assay and IHC was 90%, between IHC and PCR-DMA-Sanger 83%, and between biochip assay and qPCR-DMA-Sanger was 98%, respectively. No IDH2 mutations were found. The use of independent diagnostic methods may improve the detection of IDH-mutant specimens in chondroid tumors. [ABSTRACT FROM AUTHOR]

The lack of accurate and feasible diagnostic tests poses a significant challenge to visceral leishmaniasis (VL) healthcare services in endemic areas. To date, various VL diagnostic tests have been or are being developed, and their diagnostic performances need to be assessed. In the present study, the diagnostic performances of rk39 RDT, the direct agglutination test (DAT), microscopy, loop-mediated isothermal amplification (LAMP), and miniature direct-on-blood polymerase chain reaction–nucleic acid lateral flow immunoassay (mini-dbPCR-NALFIA) were assessed using quantitative polymerase chain reaction (qPCR) as the reference test in an endemic region of Ethiopia. In this study, 235 suspected VL cases and 104 non-endemic healthy controls (NEHCs) were recruited. Among the suspected VL cases, 144 (61.28%) tested positive with qPCR. The sensitivities for rk39 RDT, DAT, microscopy, LAMP assay, and mini-dbPCR-NALFIA were 88.11%, 96.50%, 76.58%, 94.33%, and 95.80%, respectively. The specificities were 83.33%, 97.96%, 100%, 97.38%, and 98.92% for rk39 RDT, DAT, microscopy, LAMP assay, and mini-dbPCR-NALFIA, respectively. In conclusion, rk39 RDT and microscopy exhibited lower sensitivities, while DAT demonstrated excellent performance. LAMP and mini-dbPCR-NALFIA showed excellent performances with feasibility for implementation in remote endemic areas, although the latter requires further evaluation in such regions. [ABSTRACT FROM AUTHOR]

Accurate preoperative localization is crucial for successful minimally invasive parathyroidectomy in primary hyperparathyroidism (PHPT). Preoperative localization can be challenging in patients with recurrent and/or multigland disease (MGD). This has led clinicians to investigate multiple imaging techniques, most of which are associated with radiation exposure. Magnetic resonance imaging (MRI) offers ionizing radiation-free and accurate imaging, making it an attractive alternative imaging modality. The objective of this systematic review is to provide an overview of the diagnostic performance of MRI in the localization of PHPT. PubMed and Embase libraries were searched from 1 January 2000 to 31 March 2023. Studies were included that investigated MRI techniques for the localization of PHPT. The exclusion criteria were (1) secondary/tertiary hyperparathyroidism, (2) studies that provided no diagnostic performance values, (3) studies published before 2000, and (4) studies using 0.5 Tesla MRI scanners. Twenty-four articles were included in the systematic review, with a total of 1127 patients with PHPT. In 14 studies investigating conventional MRI for PHPT localization, sensitivities varied between 39.1% and 94.3%. When employing more advanced MRI protocols like 4D MRI for PHPT localization in 11 studies, sensitivities ranged from 55.6% to 100%. The combination of MR imaging with functional techniques such as 18F-FCH-PET/MRI yielded the highest diagnostic accuracy, with sensitivities ranging from 84.2% to 100% in five studies. Despite the limitations of the available evidence, the results of this review indicate that the combination of MR imaging with functional imaging techniques such as 18F-FCH-PET/MRI yielded the highest diagnostic accuracy. Further research on emerging MR imaging modalities, such as 4D MRI and PET/MRI, is warranted, as MRI exposes patients to minimal or no ionizing radiation compared to other imaging modalities. [ABSTRACT FROM AUTHOR]

For women achieving clinical remission after the completion of initial treatment for epithelial ovarian cancer, 80% with advanced-stage disease will develop recurrence. However, the standard treatment of women with recurrent platinum-sensitive diseases remains poorly defined. Secondary (SCS), tertiary (TCS) or quaternary (QCS) cytoreduction surgery for recurrence has been suggested to be associated with increased overall survival (OS). We searched five databases for studies reporting death rate, OS, cytoreduction rates, post-operative morbidity/mortality and diagnostic models predicting complete cytoreduction in a platinum-sensitive disease recurrence setting. Death rates calculated from raw data were pooled based on a random-effects model. Meta-regression/linear regression was performed to explore the role of complete or optimal cytoreduction as a moderator. Pooled death rates were 45%, 51%, 66% for SCS, TCS and QCS, respectively. Median OS for optimal cytoreduction ranged from 16–91, 24–99 and 39–135 months for SCS, TCS and QCS, respectively. Every 10% increase in complete cytoreduction rates at SCS corresponds to a 7% increase in median OS. Complete cytoreduction rates ranged from 9–100%, 35–90% and 33–100% for SCS, TCS and QCS, respectively. Major post-operative thirty-day morbidity was reported to range from 0–47%, 13–33% and 15–29% for SCS, TCS and QCS, respectively. Thirty-day post-operative mortality was 0–6%, 0–3% and 0–2% for SCS, TCS and QCS, respectively. There were two externally validated diagnostic models predicting complete cytoreduction at SCS, but none for TCS and QCS. In conclusion, our data confirm that maximal effort higher order cytoreductive surgery resulting in complete cytoreduction can improve survival. [ABSTRACT FROM AUTHOR]

In this paper, we study ways and methods to diagnose the emotional state of individuals using external audiovisual stimuli and heart telemetry tools. We apply a mathematical model of neurocognitive brain activity developed specifically for this study to interpret the experimental scheme and its results. This experimental technique is based on monitoring and analyzing the dynamics of heart rate variability (HRV), taking into account the particular context and events occurring around the subject of the study. In addition, we provide a brief description of the theory of information images/representations used for the paradigm and interpretation of the experiment. For this study, we viewed the human mind as a one-dimensional potential hole with finite walls of different sizes and an internal potential barrier modeling the border between consciousness and subconsciousness. We also provided the foundations of the mathematical apparatus for this particular view. This experiment allowed us to identify the characteristic markers of influencing external stimuli, which form a foundation for diagnosing the emotional state of an individual. [ABSTRACT FROM AUTHOR]

Taenia solium diagnosis is challenging as trained personnel, good diagnostic tools, and infrastructure is lacking in resource-poor areas. This paper aims to describe the study trial design adopted to evaluate a newly developed rapid point-of-care test that simultaneously detects taeniosis and neurocysticercosis (TS POC) in three district hospitals in Tanzania. The two-stage design included three types of patients: patients with specific neurological signs and symptoms (group 1); patients with complaints compatible with intestinal worm infections (group 2); patients with other symptom(s) (group 3). For group 1, all patients were tested using the TS POC test (stage 1), after which all positive, and a subset of negative, patients were selected for laboratory reference tests, clinical examination, and a brain computed tomography (CT) scan (stage 2). For groups 2 and 3, a similar design was adopted, but clinical examination and a brain CT scan (stage 2) were only performed in patients who were TS POC test-positive for cysticercosis. Due to the lack of a gold standard, a Bayesian approach was used to determine test accuracy for taeniosis and cysticercosis. For neurocysticercosis, a composite case definition was used as the reference standard. If successful, this study will help the future developments (commercialization and implementation) of the rapid test and improve patient management and disease prevention. [ABSTRACT FROM AUTHOR]

Cardiotocography (CTG), which measures the fetal heart rate (FHR) and maternal uterine contractions (UC) simultaneously, is used for monitoring fetal well-being during delivery or antenatally at the third trimester. Baseline FHR and its response to uterine contractions can be used to diagnose fetal distress, which may necessitate therapeutic intervention. In this study, a machine learning model based on feature extraction (autoencoder), feature selection (recursive feature elimination), and Bayesian optimization, was proposed to diagnose and classify the different conditions of fetuses (Normal, Suspect, Pathologic) along with the CTG morphological patterns. The model was evaluated on a publicly available CTG dataset. This research also addressed the imbalance nature of the CTG dataset. The proposed model has a potential application as a decision support tool to manage pregnancies. The proposed model resulted in good performance analysis metrics. Using this model with Random Forest resulted in a model accuracy of 96.62% for fetal status classification and 94.96% for CTG morphological pattern classification. In rational terms, the model was able to accurately predict 98% Suspect cases and 98.6% Pathologic cases in the dataset. The combination of predicting and classifying fetal status as well as the CTG morphological patterns shows potential in monitoring high-risk pregnancies. [ABSTRACT FROM AUTHOR]

(1) Introduction: Wilson's disease (WND) is an autosomal recessive disorder of copper (Cu) metabolism. Many tools are available to diagnose and monitor the clinical course of WND. Laboratory tests to determine disorders of Cu metabolism are of significant diagnostic importance. (2) Methods: A systematic review of the literature in the PubMed, Science Direct, and Wiley Online Library databases was conducted. (Results): For many years, Cu metabolism in WND was assessed with serum ceruloplasmin (CP) concentration, radioactive Cu test, total serum Cu concentration, urinary copper excretion, and Cu content in the liver. The results of these studies are not always unambiguous and easy to interpret. New methods have been developed to calculate non-CP Cu (NCC) directly. New parameters, such as relative Cu exchange (REC), reflecting the ratio of CuEXC to total serum Cu, as well as relative Cu exchange (REC), reflecting the ratio of CuEXC to total serum Cu, have been shown to be an accurate tool for the diagnosis of WND. Recently, a direct and fast LC-ICP-MS method for the study of CuEXC was presented. A new method to assess Cu metabolism during treatment with ALXN1840 (bis-choline tetrathiomolybdate [TTM]) has been developed. The assay enables the bioanalysis of CP and different types of Cu, including CP-Cu, direct NCC (dNCC), and labile bound copper (LBC) in human plasma. Conclusions: A few diagnostic and monitoring tools are available for patients with WND. While many patients are diagnosed and adequately assessed with currently available methods, diagnosis and monitoring is a real challenge in a group of patients who are stuck with borderline results, ambiguous genetic findings, and unclear clinical phenotypes. Technological progress and the characterization of new diagnostic parameters, including those related to Cu metabolism, may provide confidence in the more accurate diagnosis of WND in the future. [ABSTRACT FROM AUTHOR]

When it comes to skin tumors and cancers, melanoma ranks among the most prevalent and deadly. With the advancement of deep learning and computer vision, it is now possible to quickly and accurately determine whether or not a patient has malignancy. This is significant since a prompt identification greatly decreases the likelihood of a fatal outcome. Artificial intelligence has the potential to improve healthcare in many ways, including melanoma diagnosis. In a nutshell, this research employed an Inception-V3 and InceptionResnet-V2 strategy for melanoma recognition. The feature extraction layers that were previously frozen were fine-tuned after the newly added top layers were trained. This study used data from the HAM10000 dataset, which included an unrepresentative sample of seven different forms of skin cancer. To fix the discrepancy, we utilized data augmentation. The proposed models outperformed the results of the previous investigation with an effectiveness of 0.89 for Inception-V3 and 0.91 for InceptionResnet-V2. [ABSTRACT FROM AUTHOR]

Globally, the emergence of the coronavirus disease (COVID-19) has had a significant impact on life. The need for ongoing SARS-CoV-2 screening employing inexpensive and quick diagnostic approaches is undeniable, given the ongoing pandemic and variations in vaccine administration in resource-constrained regions. This study presents results as proof of concept to use hybridization chain reaction (HCR) and clustered regularly interspaced short palindromic repeats (CRISPR)/Cas12a complex for detecting SARS-CoV-2. HCR hairpin probes were designed using the NUPACK web-based program and further used to amplify the SARS-CoV-2 N gene in archived nasopharyngeal samples. The results were visualized using agarose gels and CRISPR Cas12a-based lateral flow strips. The assay was evaluated using the gold standard, real-time polymerase chain reaction (RT-PCR), as recommended by the World Health Organization (WHO). The results show the comparative efficiency of HCR to RT-PCR. This study shows that HCR and CRISPR are viable alternatives for diagnosing SARS-CoV-2 in samples. [ABSTRACT FROM AUTHOR]

Zika virus (ZIKV) diagnostics are crucial for proper antenatal and postnatal care and also for surveillance and serosurvey studies. Since the viremia during ZIKV infection is fleeting, serological testing is highly valuable to inform diagnosis. However, current serology tests using whole virus antigens frequently suffer from cross reactivity issues, delays, and technical complexity, especially in low and middle income countries (LMICs) and endemic countries. Here, we describe an indirect ELISA to detect specific IgG antibodies using the ZIKV envelope domain III (EDIII) protein expressed in Drosophila S2 cells as an immunogen. Using a total of 367 clinical samples, we showed that the EDIII-ELISA was able to detect IgG antibodies against ZIKV with high sensitivity of 100.0% and specificity of 94.7% when compared to plaque reduction neutralization tests (PRNTs) as the gold standard and using 0.208 as the cut-off OD value. These results show the usefulness of the recombinant envelope domain III as an alternative to standard whole virus proteins for ZIKV diagnostics as it improves the sensitivity and specificity of IgG ELISA assay when used as an immunogen. This method should, therefore, be extended to serological diagnostic techniques for other members of the flavivirus genus and for use in IgM diagnostic testing. [ABSTRACT FROM AUTHOR]

Long-range correlations are often used as diagnostic markers in physiological research. Due to the limitations of conventional techniques, their characterizations are typically carried out with alternative approaches, such as the detrended fluctuation analysis (DFA). In our previous works, we found EEG-related markers of the blood–brain barrier (BBB), which limits the penetration of major drugs into the brain. However, anesthetics can penetrate the BBB, affecting its function in a dose-related manner. Here, we study two types of anesthesia widely used in experiments on animals, including zoletil/xylazine and isoflurane in optimal doses not associated with changes in the BBB. Based on DFA, we reveal informative characteristics of the electrical activity of the brain during such doses that are important for controlling the depth of anesthesia in long-term experiments using magnetic resonance imaging, multiphoton microscopy, etc., which are crucial for the interpretation of experimental results. These findings provide an important informative platform for the enhancement and refinement of surgery, since the EEG-based DFA analysis of BBB can easily be used during surgery as a tool for characterizing normal BBB functions under anesthesia. [ABSTRACT FROM AUTHOR]

Dermatoscopy, high-frequency ultrasonography (HFUS) and spectrophotometry are promising quantitative imaging techniques for the investigation and diagnostics of cutaneous melanocytic tumors. In this paper, we propose the hybrid technique and automatic prognostic models by combining the quantitative image parameters of ultrasonic B-scan images, dermatoscopic and spectrophotometric images (melanin, blood and collagen) to increase accuracy in the diagnostics of cutaneous melanoma. The extracted sets of various quantitative parameters and features of dermatoscopic, ultrasonic and spectrometric images were used to develop the four different classification models: logistic regression (LR), linear discriminant analysis (LDA), support vector machine (SVM) and Naive Bayes. The results were compared to the combination of only two techniques out of three. The reliable differentiation between melanocytic naevus and melanoma were achieved by the proposed technique. The accuracy of more than 90% was estimated in the case of LR, LDA and SVM by the proposed method. [ABSTRACT FROM AUTHOR]

In 2020, colorectal cancer was the third most common type of cancer worldwide with a clearly visible increase in the number of cases each year. With relatively high mortality rates and an uncertain prognosis, colorectal cancer is a serious health problem. There is an urgent need to investigate its specific mechanism of carcinogenesis and progression in order to develop new strategies of action against this cancer. Nectins and Nectin-like molecules are cell adhesion molecules that take part in a plethora of essential processes in healthy tissues as well as mediating substantial actions for tumor initiation and evolution. Our understanding of their role and a viable application of this in anti-cancer therapy has rapidly improved in recent years. This review summarizes the current data on the role nectins and Nectin-like molecules play in colorectal cancer. [ABSTRACT FROM AUTHOR]

Varicella-zoster virus (VZV) is the etiological agent of varicella (chickenpox) and herpes zoster (shingles). VZV infections are ubiquitous and highly contagious, and diagnosis is mostly based on the assessment of signs and symptoms. However, monkeypox, an emerging infectious disease caused by the monkeypox virus (MPXV), has clinical manifestations that are similar to those of VZV infections. With the recent monkeypox outbreak in non-endemic regions, VZV infections are likely to be misdiagnosed in the absence of laboratory testing. Considering the lack of accessible diagnostic tests that discriminate VZV from MPXV or other poxviruses, a handy and affordable detection system for VZV is crucial for rapid differential diagnosis. Here, we developed a new detection method for VZV using recombinase-aided amplification technology, combined with the lateral flow system (RAA-LF). Given the prevalence of VZV worldwide, this method can be applied not only to distinguish VZV from other viruses causing rash, but also to foster early detection, contributing substantially to disease control. [ABSTRACT FROM AUTHOR]

The aim of this systematic review is to provide an overview of the use of Dynamic Contrast-enhanced Computed Tomography (DCE-CT) in patients with pancreatic cancer. This study was composed according to the PRISMA guidelines 2009. The literature search was conducted in PubMed, Cochrane Library, EMBASE, and Web of Science databases to identify all relevant publications. The QUADAS-2 tool was implemented to assess the risk of bias and applicability concerns of each included study. The initial literature search yielded 483 publications. Thirteen articles were included. Articles were categorized into three groups: nine articles concerning primary diagnosis or staging, one article about tumor response to treatment, and three articles regarding scan techniques. In exocrine pancreatic tumors, measurements of blood flow in eight studies and blood volume in seven studies were significantly lower in tumor tissue, compared with measurements in pancreatic tissue outside of tumor, or normal pancreatic tissue in control groups of healthy volunteers. The studies were heterogeneous in the number of patients enrolled and scan protocols. Perfusion parameters measured and analyzed by DCE-CT might be useful in the investigation of characteristic vascular patterns of exocrine pancreatic tumors. Further clinical studies are desired for investigating the potential of DCE-CT in pancreatic tumors. [ABSTRACT FROM AUTHOR]

Diagnostic devices, methodological approaches, and traditional constructs of clinical pathology practice, cultivated throughout centuries, have transformed radically in the wake of explosive technological growth and other, e.g., environmental, catalysts of change. Ushered into the fray of modern laboratory medicine are digital imaging devices and machine-learning (ML) software fashioned to mitigate challenges, e.g., practitioner shortage while preparing clinicians for emerging interconnectivity of environments and diagnostic information in the era of big data. As computer vision shapes new constructs for the modern world and intertwines with clinical medicine, cultivating clarity of our new terrain through examining the trajectory and current scope of computational pathology and its pertinence to clinical practice is vital. Through review of numerous studies, we find developmental efforts for ML migrating from research to standardized clinical frameworks while overcoming obstacles that have formerly curtailed adoption of these tools, e.g., generalizability, data availability, and user-friendly accessibility. Groundbreaking validatory efforts have facilitated the clinical deployment of ML tools demonstrating the capacity to effectively aid in distinguishing tumor subtype and grade, classify early vs. advanced cancer stages, and assist in quality control and primary diagnosis applications. Case studies have demonstrated the benefits of streamlined, digitized workflows for practitioners alleviated by decreased burdens. [ABSTRACT FROM AUTHOR]

Germline mutations in the tumor suppressor gene BRCA1-associated protein-1 (BAP1) lead to BAP1 tumor predisposition syndrome (BAP1-TPDS), characterized by high susceptibility to several tumor types, chiefly melanoma, mesothelioma, renal cell carcinoma, and basal cell carcinoma. Here, we present the results of our ten-year experience in the molecular diagnosis of BAP1-TPDS, along with a clinical update and cascade genetic testing of previously reported BAP1-TPDS patients and their relatives. Specifically, we sequenced germline DNA samples from 101 individuals with suspected BAP1-TPDS and validated pathogenic variants (PVs) by assessing BAP1 somatic loss in matching tumor specimens. Overall, we identified seven patients (7/101, 6.9%) carrying six different germline BAP1 PVs, including one novel variant. Consistently, cascade testing revealed a total of seven BAP1 PV carriers. In addition, we explored the mutational burden of BAP1-TPDS tumors by targeted next-generation sequencing. Lastly, we found that certain tumors present in PV carriers retain a wild-type BAP1 allele, suggesting a sporadic origin of these tumors or a functional role of heterozygous BAP1 in neoplastic development. Altogether, our findings have important clinical implications for therapeutic response of BAP1-TPDS patients. [ABSTRACT FROM AUTHOR]

Aging is an irreversible and natural phenomenon that occurs as a person ages. Anti-aging medicine applies advanced science and medical technology to early detection, prevention, treatment, and reversal of age-related dysfunctions, disorders, and diseases. Therefore, anti-aging diagnostic medicine and healthcare are important factors in helping the elderly population lead healthy and active lives. However, it is challenging to diagnose various aging and related diseases accurately through various forms of anti-aging diagnostic medicine and health management. It may not be treated appropriately, so many older people are making various efforts to prevent aging themselves in advance. Therefore, anti-aging medicine and health care have been developed in various forms, from health checkups to alternative medicine and biophysical technology beyond simple clinical medicine, and are being applied to demand the needs of the elderly. This review intends to explore and characterize various applications related to anti-aging medicine and healthcare in the elderly. In addition, economic, medical, and ethical considerations arising from the relationship between the increase in the elderly population and the continuous development of anti-aging medicine can be considered. [ABSTRACT FROM AUTHOR]

Infectious diseases caused by bacteria and viruses are highly contagious and can easily be transmitted via air, water, body fluids, etc. Throughout human civilization, there have been several pandemic outbreaks, such as the Plague, Spanish Flu, Swine-Flu, and, recently, COVID-19, amongst many others. Early diagnosis not only increases the chance of quick recovery but also helps prevent the spread of infections. Conventional diagnostic techniques can provide reliable results but have several drawbacks, including costly devices, lengthy wait time, and requirement of trained professionals to operate the devices, making them inaccessible in low-resource settings. Thus, a significant effort has been directed towards point-of-care (POC) devices that enable rapid diagnosis of bacterial and viral infections. A majority of the POC devices are based on plasmonics and/or microfluidics-based platforms integrated with mobile readers and imaging systems. These techniques have been shown to provide rapid, sensitive detection of pathogens. The advantages of POC devices include low-cost, rapid results, and portability, which enables on-site testing anywhere across the globe. Here we aim to review the recent advances in novel POC technologies in detecting bacteria and viruses that led to a breakthrough in the modern healthcare industry. [ABSTRACT FROM AUTHOR]

Rising SARS-CoV-2 cases, testing delays, and the risk of pre-symptomatic and asymptomatic transmission provided the impetus for an in-house rapid testing program. Employees and their household contacts were encouraged to self-collect saliva samples that were pooled for routine testing using an established colorimetric reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay. In brief, individual or a maximum of four saliva samples were pooled and heat-inactivated to render microorganisms, especially SARS-CoV-2, non-infectious prior to being added to RT-LAMP assay tubes containing either the human sample control gene, RNase P, or a region of the SARS-CoV-2 gene, ORF1ab. During the second wave of SARS-CoV-2 infections in November 2020, two samples from an employee and a member of their household tested positive via RT-LAMP within two days of each other. A delayed clinical qRT-PCR test confirmation of both individuals 5 days later underscored the power of routine rapid testing with within-the-hour turnaround times. Workplace rapid testing programs using RT-LAMP are flexible in their design, have a reduced cost compared to qRT-PCR, may involve non-invasive self-saliva collection for increased safety for the testing personnel, and can be performed with minimal training. [ABSTRACT FROM AUTHOR]

The application of absolute quantification in SPECT/CT has seen increased interest in the context of radionuclide therapies where patient-specific dosimetry is a requirement within the European Union (EU) legislation. However, the translation of this technique to diagnostic nuclear medicine outside this setting is rather slow. Clinical research has, in some examples, already shown an association between imaging metrics and clinical diagnosis, but the applications, in general, lack proper validation because of the absence of a ground truth measurement. Meanwhile, additive manufacturing or 3D printing has seen rapid improvements, increasing its uptake in medical imaging. Three-dimensional printed phantoms have already made a significant impact on quantitative imaging, a trend that is likely to increase in the future. In this review, we summarize the data of recent literature to underpin our premise that the validation of diagnostic applications in nuclear medicine using application-specific phantoms is within reach given the current state-of-the-art in additive manufacturing or 3D printing. [ABSTRACT FROM AUTHOR]

von Willebrand disease (VWD) is reportedly the most common inherited bleeding disorder. This disorder develops as a result of defects and/or deficiency of the plasma protein von Willebrand factor (VWF). Laboratory testing for VWF-related disorders requires the assessment of both VWF level and VWF activity, the latter requiring multiple assays. As an additional step, an evaluation of VWF structural features by multimer analysis is useful in selective investigations. Multimer analysis is also important for the selection of a suitable VWF therapy preparation (desmopressin, VWF/FVIII concentrate, recombinant VWF) and the determination of the correct dose for the patient. Based on clinical and laboratory findings, including the analysis of VWF multimers, we classified our patients into individual types of VWD. Our study group included 58 patients. The study group consisted of 66% (38 patients) with VWD type 1, 5% (3 patients) with VWD type 2, 7% (4 patients) with VWD type 3, 5% (3 patients) with mixed type 1/2A VWD, and 17% (10 patients) comprising an unclassified group. In this article, we provide an overview of our practical experience using a new complementary method—the analysis of von Willebrand factor multimers with a semi-automatic analyzer Hydrasys 2 scan. We explain the principle, procedure, advantages, and pitfalls associated with the introduction of the VWF multimer analysis methodology into standard VWD diagnostics. [ABSTRACT FROM AUTHOR]

The design and development of biosensors, analytical devices used to detect various analytes in different matrices, has emerged. Biosensors indicate a biorecognition element with a physicochemical analyzer or detector, i.e., a transducer. In the present scenario, various types of biosensors have been deployed in healthcare and clinical research, for instance, biosensors for blood glucose monitoring. Pathogenic microbes are contributing mediators of numerous infectious diseases that are becoming extremely serious worldwide. The recent outbreak of COVID-19 is one of the most recent examples of such communal and deadly diseases. In efforts to work towards the efficacious treatment of pathogenic viral contagions, a fast and precise detection method is of the utmost importance in biomedical and healthcare sectors for early diagnostics and timely countermeasures. Among various available sensor systems, optical biosensors offer easy-to-use, fast, portable, handy, multiplexed, direct, real-time, and inexpensive diagnosis with the added advantages of specificity and sensitivity. Many progressive concepts and extremely multidisciplinary approaches, including microelectronics, microelectromechanical systems (MEMSs), nanotechnologies, molecular biology, and biotechnology with chemistry, are used to operate optical biosensors. A portable and handheld optical biosensing device would provide fast and reliable results for the identification and quantitation of pathogenic virus particles in each sample. In the modern day, the integration of intelligent nanomaterials in the developed devices provides much more sensitive and highly advanced sensors that may produce the results in no time and eventually help clinicians and doctors enormously. This review accentuates the existing challenges engaged in converting laboratory research to real-world device applications and optical diagnostics methods for virus infections. The review's background and progress are expected to be insightful to the researchers in the sensor field and facilitate the design and fabrication of optical sensors for life-threatening viruses with broader applicability to any desired pathogens. [ABSTRACT FROM AUTHOR]

The COVID-19 epidemic has been going on continuously for more than 1.5 years. Fast and reliable diagnosis is a key component of an outbreak response strategy. Our goal is to present the statistics from one of the diagnostic points of a large city in Poland. Swabs of the throat or nasopharynx of people reporting for molecular diagnostics of SARS-CoV-2 presence were taken. CE-IVD-certified RNA isolation and RT-PCR assays were used. According to our data, the prevalence of SARS-CoV-2 infection in the examined population equaled 14.7%; however, large differences were observed depending on where the sampling point was located: as much as 50.3% of positive results for samples collected at a stationary point, 36.2% for samples from inpatients and hospital staff, and only 8.9% for samples from patients whose test was paid by their employer. The age structure of the infected population was fairly even, with a slightly higher number of people over 50 years of age. Men were examined more often, but it was among women that a higher percentage of infection was recorded. Every fifth test was performed for a foreigner, but compared to Poles, a much lower incidence of infection was found in these samples. We conclude that due to the high prevalence of infection in patients from social care centers and in those referred to hospitals, it is recommended that a special sanitary regime is followed in those settings. We will evaluate the effectiveness of vaccinations, expecting that the coming months bring positive changes in the statistics on prevalence. [ABSTRACT FROM AUTHOR]

The accurate diagnosis of keratoconus, especially in its early stages of development, allows one to utilise timely and proper treatment strategies for slowing the progression of the disease and provide visual rehabilitation. Various keratometry indices and classifications for quantifying the severity of keratoconus have been developed. Today, many of them involve the use of the latest methods of computer processing and data analysis. The main purpose of this work was to develop a machine-learning-based algorithm to precisely determine the stage of keratoconus, allowing optimal management of patients with this disease. A multicentre retrospective study was carried out to obtain a database of patients with keratoconus and to use machine-learning techniques such as principal component analysis and clustering. The created program allows for us to distinguish between a normal state; preclinical keratoconus; and stages 1, 2, 3 and 4 of the disease, with an accuracy in terms of the AUC of 0.95 to 1.00 based on keratotopographer readings, relative to the adapted Amsler–Krumeich algorithm. The predicted stage and additional diagnostic criteria were then used to create a standardised keratoconus management algorithm. We also developed a web-based interface for the algorithm, providing us the opportunity to use the software in a clinical environment. [ABSTRACT FROM AUTHOR]

The transmission of Tuberculosis (TB) is very rapid and the burden it places on health care systems is felt globally. The effective management and prevention of this disease requires that it is detected early. Current TB diagnostic approaches, such as the culture, sputum smear, skin tuberculin, and molecular tests are time-consuming, and some are unaffordable for low-income countries. Rapid tests for disease biomarker detection are mostly based on immunological assays that use antibodies which are costly to produce, have low sensitivity and stability. Aptamers can replace antibodies in these diagnostic tests for the development of new rapid tests that are more cost effective; more stable at high temperatures and therefore have a better shelf life; do not have batch-to-batch variations, and thus more consistently bind to a specific target with similar or higher specificity and selectivity and are therefore more reliable. Advancements in TB research, in particular the application of proteomics to identify TB specific biomarkers, led to the identification of a number of biomarker proteins, that can be used to develop aptamer-based diagnostic assays able to screen individuals at the point-of-care (POC) more efficiently in resource-limited settings. [ABSTRACT FROM AUTHOR]

Infectious diseases are an existential health threat, potentiated by emerging and re-emerging viruses and increasing bacterial antibiotic resistance. Targeted treatment of infectious diseases requires precision diagnostics, especially in cases where broad-range therapeutics such as antibiotics fail. There is thus an increasing need for new approaches to develop sensitive and specific in vitro diagnostic (IVD) tests. Basic science and translational research are needed to identify key microbial molecules as diagnostic targets, to identify relevant host counterparts, and to use this knowledge in developing or improving IVD. In this regard, an overlooked feature is the capacity of pathogens to adhere specifically to host cells and tissues. The molecular entities relevant for pathogen–surface interaction are the so-called adhesins. Adhesins vary from protein compounds to (poly-)saccharides or lipid structures that interact with eukaryotic host cell matrix molecules and receptors. Such interactions co-define the specificity and sensitivity of a diagnostic test. Currently, adhesin-receptor binding is typically used in the pre-analytical phase of IVD tests, focusing on pathogen enrichment. Further exploration of adhesin–ligand interaction, supported by present high-throughput "omics" technologies, might stimulate a new generation of broadly applicable pathogen detection and characterization tools. This review describes recent results of novel structure-defining technologies allowing for detailed molecular analysis of adhesins, their receptors and complexes. Since the host ligands evolve slowly, the corresponding adhesin interaction is under selective pressure to maintain a constant receptor binding domain. IVD should exploit such conserved binding sites and, in particular, use the human ligand to enrich the pathogen. We provide an inventory of methods based on adhesion factors and pathogen attachment mechanisms, which can also be of relevance to currently emerging pathogens, including SARS-CoV-2, the causative agent of COVID-19. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) are a class of small RNA molecules that have an important regulatory role in multiple physiological and pathological processes. Their disease-specific profiles and presence in biofluids are properties that enable miRNAs to be employed as non-invasive biomarkers. In the past decades, several methods have been developed for miRNA analysis, including small RNA sequencing (RNA-seq). Small RNA-seq enables genome-wide profiling and analysis of known, as well as novel, miRNA variants. Moreover, its high sensitivity allows for profiling of low input samples such as liquid biopsies, which have now found applications in diagnostics and prognostics. Still, due to technical bias and the limited ability to capture the true miRNA representation, its potential remains unfulfilled. The introduction of many new small RNA-seq approaches that tried to minimize this bias, has led to the existence of the many small RNA-seq protocols seen today. Here, we review all current approaches to cDNA library construction used during the small RNA-seq workflow, with particular focus on their implementation in commercially available protocols. We provide an overview of each protocol and discuss their applicability. We also review recent benchmarking studies comparing each protocol's performance and summarize the major conclusions that can be gathered from their usage. The result documents variable performance of the protocols and highlights their different applications in miRNA research. Taken together, our review provides a comprehensive overview of all the current small RNA-seq approaches, summarizes their strengths and weaknesses, and provides guidelines for their applications in miRNA research. [ABSTRACT FROM AUTHOR]

Efficient segmentation of Magnetic Resonance (MR) brain tumor images is of the utmost value for the diagnosis of tumor region. In recent years, advancement in the field of neural networks has been used to refine the segmentation performance of brain tumor sub-regions. The brain tumor segmentation has proven to be a complicated task even for neural networks, due to the small-scale tumor regions. These small-scale tumor regions are unable to be identified, the reason being their tiny size and the huge difference between area occupancy by different tumor classes. In previous state-of-the-art neural network models, the biggest problem was that the location information along with spatial details gets lost in deeper layers. To address these problems, we have proposed an encoder–decoder based model named BrainSeg-Net. The Feature Enhancer (FE) block is incorporated into the BrainSeg-Net architecture which extracts the middle-level features from low-level features from the shallow layers and shares them with the dense layers. This feature aggregation helps to achieve better performance of tumor identification. To address the problem associated with imbalance class, we have used a custom-designed loss function. For evaluation of BrainSeg-Net architecture, three benchmark datasets are utilized: BraTS2017, BraTS 2018, and BraTS 2019. Segmentation of Enhancing Core (EC), Whole Tumor (WT), and Tumor Core (TC) is carried out. The proposed architecture have exhibited good improvement when compared with existing baseline and state-of-the-art techniques. The MR brain tumor segmentation by BrainSeg-Net uses enhanced location and spatial features, which performs better than the existing plethora of brain MR image segmentation approaches. [ABSTRACT FROM AUTHOR]

Stroke is a top leading cause of death, which occurs due to interference in the blood flow of the brain. Ischemic stroke (blockage) accounts for most cases (87%) and is further subtyped into cardioembolic, atherosclerosis, lacunar, other causes, and cryptogenic strokes. The main value of subtyping ischemic stroke patients is for a better therapeutic decision-making process. The current classification methods are complex and time-consuming (hours to days). Specific blood-based biomarker measurements have promising potential to improve ischemic stroke mechanism classification. Over the past decades, the hypothesis that different blood-based biomarkers are associated with different ischemic stroke mechanisms is increasingly investigated. This review presents the recent studies that investigated blood-based biomarker characteristics differentiation between ischemic stroke mechanisms. Different blood-based biomarkers are specifically discussed (b-type natriuretic peptide, d-dimer, c-reactive protein, tumor necrosis factor-α, interleukin-6, interleukin-1β, neutrophil–lymphocyte ratio, total cholesterol, triglycerides, low-density lipoprotein, high-density lipoprotein and apolipoprotein A), as well as the different cut-off values that may be useful in specific classifications for cardioembolic and atherosclerosis etiologies. Lastly, the structure of a point-of-care biosensor device is presented, as a measuring tool on-site. The information presented in this review will hopefully contribute to the major efforts to improve the care for stroke patients. [ABSTRACT FROM AUTHOR]

A laboratory-developed test (LDT) is a type of in vitro diagnostic test that is designed, manufactured and used in the same laboratory (i.e., an in-house test). In this study, a metabolomics-based LDT was developed. This test involves a blood plasma preparation, direct-infusion mass spectrometry analysis with a high-resolution mass spectrometer, alignment and normalization of mass peaks using original algorithms, metabolite annotation by a biochemical context-driven algorithm, detection of overrepresented metabolic pathways and results in a visualization in the form of a pathway names cloud. The LDT was applied to detect early stage Parkinson's disease (PD)—the diagnosis of which currently requires great effort due to the lack of available laboratory tests. In a case–control study (n = 56), the LDT revealed a statistically sound pattern in the PD-relevant pathways. Usage of the LDT for individuals confirmed its ability to reveal this pattern and thus diagnose PD at the early-stage (1–2.5 stages, according to Hoehn and Yahr scale). The detection of this pattern by LDT could diagnose PD with a specificity of 64%, sensitivity of 86% and an accuracy of 75%. Thus, this LDT can be used for further widespread testing. [ABSTRACT FROM AUTHOR]

The aim of the work is to study the metabolic characteristics of saliva in lung cancer for use in early diagnosis and determining the prognosis of the disease. The patient group included 425 lung cancer patients, 168 patients with non-cancerous lung diseases, and 550 healthy volunteers. Saliva samples were collected from all participants in the experiment before treatment and 34 biochemical saliva parameters were determined. Participants were monitored for six years to assess survival rates. The statistical analysis was performed by means of Statistica 10.0 (StatSoft) program and R package (version 3.2.3). To construct the classifier, the Random Forest method was used; the classification quality was assessed using the cross-validation method. Prognostic factors were analyzed by multivariate analysis using Cox's proportional hazard model in a backward step-wise fashion to adjust for potential confounding factors. A complex of metabolic changes occurring in saliva in lung cancer is described. Seven biochemical parameters were identified (catalase, triene conjugates, Schiff bases, pH, sialic acids, alkaline phosphatase, chlorides), which were used to construct the classifier. The sensitivity and specificity of the method were 69.5% and 87.5%, which is practically not inferior to the diagnostic characteristics of markers routinely used in the diagnosis of lung cancer. Significant independent factors in the poor prognosis of lung cancer are imidazole compounds (ICs) above 0.478 mmol/L and salivary lactate dehydrogenase activity below 545 U/L. Saliva has been shown to have great potential for the development of diagnostic and prognostic tests for lung cancer. [ABSTRACT FROM AUTHOR]

Demonstrating clinical utility for diagnostic tests and securing coverage and reimbursement requires high quality and, ideally, randomized controlled trial (RCT) data. Traditional RCTs are often too costly, slow, and cumbersome for diagnostic firms. Alternative data options are needed. We evaluated four RCTs using virtual patients to demonstrate clinical utility. Each study used a similar pre-post intervention, two round design to facilitate comparison. Representative samples of physicians were recruited and randomized into control and intervention arms. All physicians were asked to care for their virtual patients during two assessment rounds, separated by a multi-week time interval. Between rounds, intervention physicians reviewed educational materials on the diagnostic test. All physician responses were scored against evidence-based care criteria. RCTs using virtual patients can demonstrate clinical utility for a variety of diagnostic test types, including: (1) an advanced multi-biomarker blood test, (2) a chromosomal microarray, (3) a proteomic assay analysis, and (4) a multiplex immunofluorescence imaging platform. In two studies, utility was demonstrated for all targeted patient populations, while in the other two studies, utility was only demonstrated for a select sub-segment of the intended patient population. Of these four tests, two received positive coverage decisions from Palmetto, one utilized the study results to support commercial payer adjudications, and the fourth company went out of business. RCTs using virtual patients are a cost-effective approach to demonstrate the presence or absence of clinical utility. [ABSTRACT FROM AUTHOR]

Cancer is the cause of death for one in seven individuals worldwide. It is widely acknowledged that screening and early diagnosis are of vital importance for improving the likelihood of recovery. However, given the costly, time-consuming, and invasive nature of the many methods currently in use, patients often do not take advantage of the services available to them. Consequently, many researchers are exploring the possibility of developing fast, reliable, and non-invasive diagnostic tools that can be used directly or by local physicians at the point-of-care. Herein, we look at the use of established biomarkers in cancer therapy and investigate emerging biomarkers exhibiting future potential. The incorporation of these biomarkers into point-of-care devices could potentially reduce the strain currently experienced by screening programs in hospitals and healthcare systems. Results derived from point-of-care tests should be accurate, sensitive, and generated rapidly to assist in the selection of the best course of treatment for optimal patient care. Essentially, point-of-care diagnostics should enhance the well-being of patients and lead to a reduction in cancer-related deaths. [ABSTRACT FROM AUTHOR]