Conventional Laboratory Tests Research Articles

Prediction of Resilient Modulus Value of Cohesive and Non-Cohesive Soils Using Artificial Neural Network.

This paper investigates the application of Artificial Neural Networks (ANNs) for predicting the resilient modulus (Mr) of subgrade and subbase soils, which is a critical parameter in pavement design. Utilizing a dataset of 1683 Mr observations, the ANN model incorporates eight input variables, including soil gradation, plasticity, and stress conditions. The model was optimized using a quasi-Newton method, achieving high predictive accuracy, with a coefficient of determination (R2) of 0.9613 and low error rates for both selection and testing datasets. To further enhance model interpretability, SHAP (SHapley Additive exPlanations) analysis was conducted, revealing the significant influence of specific input parameters, such as saturation ratio, plasticity index and soil gradation, on Mr predictions. This study underscores the potential of ANNs as a practical tool for estimating resilient modulus, offering a reliable alternative to conventional laboratory testing methods. The findings suggest that integrating ANNs into pavement design processes can lead to more accurate predictions of pavement performance, ultimately supporting the development of more efficient and durable road structures.

Improvement of biodegradability prediction QSAR system through optimal combination of algorithms

Abstract This paper introduces a novel quantitative structure-activity relationship (QSAR) system for predicting the biodegradability of chemicals. The system focuses on evaluating the ratio of biochemical oxygen demand (BOD) to theoretical oxygen demand (ThOD) (%BOD/ThOD) and the presence of degradation products to categorize chemicals as “readily biodegradable” (RB) or “not readily biodegradable” (NB). The conventional laboratory testing method for biodegradability assessment is time-consuming and expensive, thus highlighting the need for a quantitative structure-activity relationship (QSAR) system that can predict biodegradability without the need for extensive testing. The authors acquired a dataset of 3948 chemicals from the National Institute of Technology and Evaluation (NITE) database, which included information on molecular structure, %BOD/ThOD values, and the presence of degradation products. The QSAR system consists of two prediction models: a %BOD/ThOD prediction model and a discrimination prediction model. Multiple algorithms were employed in each model to enhance prediction accuracy. The %BOD/ThOD prediction model utilizes eight algorithms, including linear, nonlinear, and tree-structured models. The discrimination prediction model employs ten algorithms, and the outcomes are combined using majority voting. Explanatory variables for both models include molecular descriptors and spatial structure derived from the chemical’s molecular representation. The performance of the QSAR system was evaluated based on training and validation datasets. Results showed that the combination of three %BOD/ThOD prediction algorithms improved the average correction rate compared to using all algorithms. Similarly, selecting the discrimination prediction algorithm further enhanced the average correction rate.

Phenotypic and genotypic evaluation of bleeding diagnostic dilemmas: Two case studies

Inherited platelet disorders (IPDs) are a heterogeneous group of conditions that present significant challenges in diagnosis and management. Here, we report two cases of patients presenting with clinically significant bleeding but with unclear etiologies by conventional clinical laboratory testing. Further evaluation, utilizing a combination of high-dimensional multiplexed mass cytometry and genetic sequencing, revealed the underlying causes of bleeding in both cases, leading to definitive diagnoses. These cases underscore the potential utility of combined multimodal approaches in evaluating patients with bleeding disorders. Moreover, these high-parameter methods can offer substantial mechanistic insights and can enhance our understanding of the molecular pathogenesis of IPDs. Future studies involving larger patient cohorts are needed to further validate this strategy, directly comparing its diagnostic yield and accuracy with current clinical laboratory testing approaches, which can ultimately improve patient care.

Tocilizumab reduces hypercoagulation in COVID-19 – Perspectives from the coagulation and immunomodulation Covid assessment (Coag-ImmCovA) clinical trial

BackgroundDespite medical interventions, COVID-19 continues to persist at pandemic proportions. A hypercoagulation state was rapidly observed in the severely ill, and the incidence of thromboembolic events remains elevated. Interleukin inhibitors have demonstrated positive effects on the hyperactivation of the immune system in COVID-19, with the interleukin-6 inhibitor tocilizumab showing promising results in reducing mortality. Nevertheless, the impact of interleukin inhibitors on the coagulation system remains incompletely understood. MethodsIn this clinical trial conducted in Stockholm, Sweden, interleukin inhibitors, namely anakinra (ANA) or tocilizumab (TOCI), were randomly administered in addition to standard care (SC) to hospitalized patients with COVID-19. A control group received only SC. The primary outcome sought to measure effects on global hemostasis, as indicated by changes in functional coagulation tests, specifically Rotational Thromboelastometry (ROTEM) or Overall Hemostatic Potential (OHP), visualized through scanning electron microscopy images. Secondary outcomes included effects on conventional coagulation laboratory tests. ResultsThe study enrolled 74 patients who were randomized to receive either ANA or TOCI in addition to SC, or SC alone. In the TOCI group, ROTEM variables exhibited less hypercoagulation after 29 days compared with ANA or SC treatment groups, characterized by prolonged clot formation time and decreased clot firmness. OHP decreased, but there were no significant differences among the three treatment groups. Plasma fibrinogen levels, initially elevated, decreased significantly in TOCI recipients over time. ConclusionTocilizumab treatment demonstrated a significant reduction of hypercoagulation in hospitalized COVID-19 patients, by improvements in both global coagulation tests and conventional laboratory tests, in comparison with anakinra or SC alone. This finding underscores the significance of tocilizumab as a viable treatment option in severe COVID-19 cases, with the potential to decrease thrombosis incidence.

Utility of Global Hemostatic Assays in Patients with Bleeding Disorders of Unknown Cause.

Bleeding disorder of unknown cause (BDUC) is a diagnosis of exclusion after exhaustive evaluation of plasmatic coagulation and platelet function. This review explores the utility of global hemostatic assays as confirmatory tests and in elucidating the pathophysiology of BDUC. Unlike traditional hemostatic tests that focus on coagulation factors, global assays are conducted both in plasma and also whole blood. These assays provide a more comprehensive understanding of the cell-based model of coagulation, aid in the identification of plasmatic factor abnormalities that may reduce hemostatic capacity, and allow for the assessment of impaired platelet-endothelial interactions under shear stress, as well as hyperfibrinolytic states. While clinical tests such as skin bleeding time and global assays such as PFA-100 exhibit limited diagnostic capacity, the role of viscoelastic testing in identifying hemostatic dysfunction in patients with BDUC remains unclear. Thrombin generation assays have shown variable results in BDUC patients; some studies demonstrate differences compared with healthy controls or reference values, whereas others question its clinical utility. Fibrinolysis assessment in vitro remains challenging, with studies employing euglobulin clot lysis time, plasma clot lysis time, and fluorogenic plasmin generation yielding inconclusive or conflicting results. Notably, recent studies suggest that microfluidic analysis unveils shear-dependent platelet function defects in BDUC patients, undetected by conventional platelet function assays. Overall, global assays might be helpful for exploring underlying hemostatic impairments, when conventional hemostatic laboratory tests yield no results. However, due to limited data and/or discrepant results, further research is needed to evaluate the utility of global assays as screening tools.

General Applicability of Existing College of American Pathologists Accreditation Requirements to Clinical Implementation of Machine Learning-Based Methods in Molecular Oncology Testing.

The College of American Pathologists (CAP) accreditation requirements for clinical laboratory testing help ensure laboratories implement and maintain systems and processes that are associated with quality. Machine learning (ML)-based models share some features of conventional laboratory testing methods. Accreditation requirements that specifically address clinical laboratories' use of ML remain in the early stages of development. To identify relevant CAP accreditation requirements that may be applied to the clinical adoption of ML-based molecular oncology assays, and to provide examples of current and emerging ML applications in molecular oncology testing. CAP accreditation checklists related to molecular pathology and general laboratory practices (Molecular Pathology, All Common and Laboratory General) were reviewed. Examples of checklist requirements that are generally applicable to validation, revalidation, quality management, infrastructure, and analytical procedures of ML-based molecular oncology assays were summarized. Instances of ML use in molecular oncology testing were assessed from literature review. Components of the general CAP accreditation framework that exist for traditional molecular oncology assay validation and maintenance are also relevant for implementing ML-based tests in a clinical laboratory. Current and emerging applications of ML in molecular oncology testing include DNA methylation profiling for central nervous system tumor classification, variant calling, microsatellite instability testing, mutational signature analysis, and variant prediction from histopathology images. Currently, much of the ML activity in molecular oncology is within early clinical implementation. Despite specific considerations that apply to the adoption of ML-based methods, existing CAP requirements can serve as general guidelines for the clinical implementation of ML-based assays in molecular oncology testing.

Application of non-destructive testing methods for assessing fracture resistance in dental ceramics: the sound harvesting test

IntroductionEvaluating the fracture resistance of dental ceramics such as monolithic zirconia crowns is crucial for assessing their durability. Conventional destructive laboratory tests often fail to accurately evaluate the timing and failing crack formation of these brittle materials. Non-destructive testing methods, such as acoustic emission testing (AET), offers an alternative by providing valuable data on material properties without causing damage to the samples.The in vitro study aimed to evaluate the sensitivity of a sound harvesting modified acoustic emission testing by comparing the fracture resistance of posterior monolithic zirconia crowns (MZCs) measured via the modified set up with that of a conventional fracture toughness test.Material and methodsA modified acoustic emission set up, the sound harvesting test (SHT), featuring a condenser microphone, an amplifier, a custom audio chipset and a cut-off switch integrated into a universal testing machine, was compared to a conventional fracture toughness test to measure fracture loads on 50 posterior monolithic zirconia crowns divided in two groups.ResultsThe sound harvesting test recorded a mean fracture load of 1,108.99 N, significantly less than the 1,292.52 N measured with the conventional test, indicating a more sensitive detection of fractures. Statistically significant differences (p < 0.05) were observed between the two groups.ConclusionDespite its limitations, the study suggests considering sound harvesting testing as an potential alternative for fracture load testing of dental brittle materials due to its ability to identify failures at lower loads enhancing therefore a more accurate evaluation of the behavior of dental materials. However, further testing on a broader range of dental materials is warranted to improve result accuracy and applicability.

Regression–Based Diagnostic Models for Early Lung Cancer Integrating Conventional Indicators with Tumor Markers

The aim of this research was to develop a lung cancer diagnostic and predictive model that integrates traditional laboratory indicators with tumor markers. This model is intended to facilitate early screening and assist in the process of identifying or detecting lung cancer through a cost-effective, rapid, and convenient approach, ultimately enhancing the early detection rate of lung cancer. A retrospective study was conducted on 66 patients diagnosed with lung cancer and 159 patients with benign pulmonary conditions. Data including general clinical information, conventional laboratory test results, and tumor marker levels were collected. Data analysis was conducted using SPSS 26.0 (Statistical Product and Service Solutions 26.0). The lung cancer diagnosis and prediction model is created using a composite index established through binary logistic regression. The combined diagnostic prediction models, incorporating both traditional indicators and tumor markers, demonstrated a greater area under the curve (AUC) when compared to the diagnostic prediction model based solely on tumor markers and their combination testing. The values of cut-off point, AUC, accuracy, sensitivity, specificity, positive and negative detection rate and accuracy rate are 0.1805, 0.959, 86.67%, 0.955, 0.830, 95.45%, 83.02% and 89.33 respectively and it is shown that the combined diagnostic model display notable efficacy and clinical relevance in aiding the early diagnosis of lung cancer.

A framework for estimating the matric suction in unsaturated soils using multiple artificial intelligence techniques

AbstractImplementation of the state‐of‐the‐art understanding of the mechanics of unsaturated soils into geotechnical engineering practice is partly limited due to the lack of quick, reliable, and economical techniques for matric suction measurement. Matric suction is one of the key stress state variables that significantly influences the hydro‐mechanical behavior of unsaturated soils. In this paper, to address this objective, two artificial intelligence (AI) models were developed for estimating matric suction in unsaturated soils based on the particle swarm optimization support vector regression (PSO‐SVR) and multivariate adaptive regression spline (MARS) algorithms. The results suggest that both these models can reasonably estimate matric suction. Compared to the MARS model, the PSO‐SVR model can achieve higher accuracy. Nonetheless, the MARS model facilitates the sensitivity analysis and the selection of essential inputs. A novel integrated framework is proposed and validated, leveraging the strengths, and alleviating the limitations of the PSO‐SVR and MARS algorithms for reliable and rapid estimation of matric suction in the range of 0–1500 kPa for low plastic soils (0 < Ip ≤ 7). Six inputs are required to use this model successfully; some can be measured using conventional laboratory tests, and others can be calculated from mass‐volume relationships.

Variant mapping using mass spectrometry–based proteotyping as a diagnostic tool in von Willebrand disease

Backgroundvon Willebrand disease (VWD) is the most common inherited bleeding disorder, characterized by either partial or complete von Willebrand factor (VWF) deficiency or by the occurrence of VWF proteoforms of altered functionality. The gene encoding VWF is highly polymorphic, giving rise to a variety of proteoforms with varying plasma concentrations and clinical significance. ObjectivesTo address this complexity, we translated genomic variation in VWF to corresponding VWF proteoforms circulating in blood. MethodsVWF was characterized in VWD patients (n = 64) participating in the Willebrand in the Netherlands study by conventional laboratory testing, DNA sequencing and complementary discovery, and targeted mass spectrometry–based plasma proteomic strategies. ResultsUnbiased plasma profiling combined with immune enrichment of VWF verified VWF and its binding partner factor VIII as key determinants of VWD and revealed a remarkable heterogeneity in VWF amino acid sequence coverage among patients. Subsequent VWF proteotyping enabled identification of both polymorphisms (eg, p.Thr789Ala, p.Gln852Arg, and p.Thr1381Ala), as well as pathogenic variants (n = 16) along with their corresponding canonical sequences. Targeted proteomics using stable isotope–labeled peptides confirmed unbiased proteotyping for 5 selected variants and suggested differential proteoform quantities in plasma. The variant-to-wild-type peptide ratio was determined in 6 type 2B patients heterozygous for p.Arg1306Trp, confirming the relatively low proteoform concentration of the pathogenic variant. The elevated VWF propeptide/VWF ratio indicated increased clearance of specific VWF proteoforms. ConclusionThis study highlights how VWF proteotyping from plasma could be the first step to bridge the gap between genotyping and functional testing in VWD.

Diagnostic accuracy of DPP Fever Panel II Asia tests for tropical fever diagnosis.

Fever is the most frequent symptom in patients seeking care in South and Southeast Asia. The introduction of rapid diagnostic tests (RDTs) for malaria continues to drive patient management and care. Malaria-negative cases are commonly treated with antibiotics without confirmation of bacteraemia. Conventional laboratory tests for differential diagnosis require skilled staff and appropriate access to healthcare facilities. In addition, introducing single-disease RDTs instead of conventional laboratory tests remains costly. To overcome some of the delivery challenges of multiple separate tests, a multiplexed RDT with the capacity to diagnose a diverse range of tropical fevers would be a cost-effective solution. In this study, a multiplex lateral flow immunoassay (DPP Fever Panel II Assay) that can detect serum immunoglobulin M (IgM) and specific microbial antigens of common fever agents in Asia (Orientia tsutsugamushi, Rickettsia typhi, Leptospira spp., Burkholderia pseudomallei, Dengue virus, Chikungunya virus, and Zika virus), was evaluated. Whole blood (WB) and serum samples from 300 patients with undefined febrile illness (UFI) recruited in Vientiane, Laos PDR were tested using the DPP Fever Panel II, which consists of an Antibody panel and Antigen panel. To compare reader performance, results were recorded using two DPP readers, DPP Micro Reader (Micro Reader 1) and DPP Micro Reader Next Generation (Micro Reader 2). WB and serum samples were run on the same fever panel and read on both micro readers in order to compare results. ROC analysis and equal variance analysis were performed to inform the diagnostic validity of the test compared against the respective reference standards of each fever agent (S1 Table). Overall better AUC values were observed in whole blood results. No significant difference in AUC performance was observed when comparing whole blood and serum sample testing, except for when testing for R. typhi IgM (p = 0.04), Leptospira IgM (p = 0.02), and Dengue IgG (p = 0.03). Linear regression depicted R2 values had ~70% agreement across WB and serum samples, except when testing for leptospirosis and Zika, where the R2 values were 0.37 and 0.47, respectively. No significant difference was observed between the performance of Micro Reader 1 and Micro Reader 2, except when testing for the following pathogens: Zika IgM, Zika IgG, and B pseudomallei CPS Ag. These results demonstrate that the diagnostic accuracy of the DPP Fever Panel II is comparable to that of commonly used RDTs. The optimal cut-off would depend on the use of the test and the desired sensitivity and specificity. Further studies are required to authenticate the use of these cut-offs in other endemic regions. This multiplex RDT offers diagnostic benefits in areas with limited access to healthcare and has the potential to improve field testing capacities. This could improve tropical fever management and reduce the public health burden in endemic low-resource areas.

Identification of the molecular etiology in rare congenital hemolytic anemias using next-generation sequencing with exome-based copy number variant analysis.

In congenital hemolytic anemias (CHA), it is not always possible to determine the specific diagnosis by evaluating clinical findings and conventional laboratory tests. The aim of this study is to evaluate the utility of next-generation sequencing (NGS) and clinical-exome-based copy number variant (CNV) analysis in patients with CHA. One hundred and forty-three CHA cases from 115 unrelated families referred for molecular analysis were enrolled in the study. Molecular analysis was performed using two different clinical exome panels in 130 patients, and whole-exome sequencing in nine patients. Exome-based CNV calling was incorporated into the traditional single-nucleotide variant and small insertion/deletion analysis pipeline for NGS data in 92 cases. In four patients from the same family, the PK Gypsy variant was investigated using long-range polymerase chain reaction. Molecular diagnosis was established in 86% of the study group. The most frequently mutated genes were SPTB (31.7%) and PKLR (28.5%). CNV analysis of 92 cases revealed that three patients had different sizes of large deletions in the SPTB and six patients had a deletion in the PKLR. In this study, NGS provided a high molecular diagnostic rate in cases with rare CHA. Analysis of the CNVs contributed to the diagnostic success.

Diagnostic yield of the Kveim test in sarcoidosis patients.

Sarcoidosis is a granulomatous disorder of unknown etiology characterized by the existence of non-caseating granulomatous inflammation. Diagnosis can be challenging due to the presence of comprehensive clinical, laboratory, and radiologic manifestations. We have evaluated the diagnostic yield of the Kveim test and compared this test with the other conventional laboratory modalities. Our aim was to reach the highest level of diagnostic confidence acknowledging the absolute uncertainty in diagnosis with the current diagnostic enterprises. Medical records of 300 sarcoidosis patients were reviewed. Patients were classified into two categories as the conventional laboratory and the Kveim test group to compare the diagnostic yield. Sensitivity of the Kveim test was 76.4% while the conventional laboratory tests provided a 64% diagnostic yield. The conventional tests had a low diagnostic rate in the early disease stages. Kveim test revealed a high yield diagnosis for all stages of sarcoidosis. Integrated assessment of the two modalities reached a 96.8% sensitivity and a 94,6% specificity. Conventional laboratory modalities were useful for the assessment of disease activity and identification of organ involvement. Kveim test revealed a significant diagnostic yield for all stages of sarcoidosis. The lowest output was achieved in stage IV patients due to the waning of active granulomatous inflammation. The highest diagnostic sensitivity was obtained by an integrated analysis of the conventional laboratory and the Kveim test results for all aspects of sarcoidosis.

A Connectivity Metrics-Based Approach for the Prediction of Stress-Dependent Fracture Permeability

Rapid and accurate assessment of fracture permeability is critical for subsurface resource and energy development as well as rock engineering stability. Fracture permeability deviates from the classical cubic law under the effect of roughness, geological stress, as well as mining-induced stress. Conventional laboratory tests and numerical simulations are commonly costly and time-consuming, whereas the use of a connectivity metric based on percolation theory can quickly predict fracture permeability, but with relatively low accuracy. For this reason, we selected two static connectivity metrics with the highest and lowest prediction accuracy in previous studies, respectively, and proposed to revise and use them for fracture permeability estimation, considering the effect of isolated large-aperture regions within the fractures under increasing normal stress. Several hundred fractures with different fractal dimensions and mismatch lengths were numerically generated and deformed, and their permeability was calculated by the local cubic law (LCL). Based on the dataset, the connectivity metrics were counted using the revised approach, and the results show that, regardless of the connectivity metrics, the new model greatly improves the accuracy of permeability prediction compared to the pre-improved model, by at least 8% for different cutoff aperture thresholds.

Evaluation of radiological capacity and usage in paediatric TB diagnosis: A mixed-method protocol of a comparative study in Mozambique, South Africa and Spain.

Tuberculosis remains one of the top ten causes of mortality globally. Children accounted for 12% of all TB cases and 18% of all TB deaths in 2022. Paediatric TB is difficult to diagnose with conventional laboratory tests, and chest radiographs remain crucial. However, in low-and middle-income countries with high TB burden, the capacity for radiological diagnosis of paediatric TB is rarely documented and data on the associated radiation exposure limited. A multicentre, mixed-methods study is proposed in three countries, Mozambique, South Africa and Spain. At the national level, official registry databases will be utilised to retrospectively compile an inventory of licensed imaging resources (mainly X-ray and Computed Tomography (CT) scan equipment) for the year 2021. At the selected health facility level, three descriptive cross-sectional standardised surveys will be conducted to assess radiology capacity, radiological imaging diagnostic use for paediatric TB diagnosis, and radiation protection optimization: a site survey, a clinician-targeted survey, and a radiology staff-targeted survey, respectively. At the patient level, potential dose optimisation will be assessed for children under 16 years of age who were diagnosed and treated for TB in selected sites in each country. For this component, a retrospective analysis of dosimetry will be performed on TB and radiology data routinely collected at the respective sites. National inventory data will be presented as the number of units per million people by modality, region and country. Descriptive analyses will be conducted on survey data, including the demographic, clinical and programmatic characteristics of children treated for TB who had imaging examinations (chest X-ray (CXR) and/or CT scan). Dose exposure analysis will be performed by children's age, gender and disease spectrum. As far as we know, this is the first multicentre and multi-national study to compare radiological capacity, radiation protection optimization and practices between high and low TB burden settings in the context of childhood TB management. The planned comparative analyses will inform policy-makers of existing radiological capacity and deficiencies, allowing better resource prioritisation. It will inform clinicians and radiologists on best practices and means to optimise the use of radiological technology in paediatric TB management.

Application of geophysical techniques based on multi-attribute inversion in predicting high-quality source rocks

Total organic carbon (TOC) content is an important indicator for evaluating the quality of source rocks. Conventional laboratory analysis and testing, single well interpretation, and other methods are limited by sample data or the number of well locations, and cannot comprehensively and accurately predict the planar distribution of TOC content in source rocks. Based on this, a method for predicting TOC content using seismic inversion with multiple attributes is proposed. The basis for applying seismic attributes to study TOC of source rocks is the inherent relationship between seismic and logging data. By using logging data to calculate TOC, the correlation between seismic attributes of well side seismic traces and logging is established, and seismic attributes are converted into TOC of source rocks. The results show that the TOC content in the third section of the Shahejie Formation of the Liaohe Depression is relatively high, distributed in the range of 1% to 5%. The trend of planar variation is manifested as a gradual decrease from the centre of the depression to both sides, and the centre is concentrated in the Panshan and Qingshui area. The overall prediction effect is good, proving the strong feasibility of this method.

Comparison of Fecal Calprotectin with Different Endoscopic Scores in the Assessment of Ulcerative Colitis (UC) Activity and Its Utility in Differentiating IBS from IBD.

Ulcerative colitis (UC), a chronic inflammatory disease of gastrointestinal tract, can have initial presentation which is clinically difficult to differentiate from functional bowel disorders [irritable bowel syndrome (IBS) and irritable bowel disease (IBD)]. Conventional laboratory tests, such as erythrocyte sedimentation rate (ESR), C-reactive protein, and albumin express systemic patient responses instead of intestinal inflammation. In the last decade, fecal calprotectin, a calcium-binding protein, has been suggested as a sensitive marker of intestinal inflammation. However, only few studies have investigated its role in relation with the extent of the disease. To evaluate the usefulness of fecal calprotectin as a biomarker for disease activity in UC, its correlation with disease extent and its utility in differentiating IBS from IBD. A total of 75 patients (50 cases with colonoscopic evidence of inflammation and 25 cases with normal colonoscopic examination) were included in the study. Fecal calprotectin test was done on the day of colonoscopy. Severity of the disease was assessed by modified Mayo's endoscopy score (MMES). Age and baseline parameters were comparable in both the groups (UC and IBS). Patients in the ulcerative group had tachycardia (95 vs 74), high ESR (26 vs 20), high leukocytes count (9198 vs 8852), high fecal calprotectin (594 vs 29), low albumin (3.00 vs 3.80) and low hemoglobin (11 vs 13.40). Minimum and maximum MMES were 2 and 13.2. A significant correlation was observed between fecal calprotectin and MMES (p-value < 0.001). Fecal calprotectin is a simple, noninvasive, cost-effective marker that is strongly associated with colorectal inflammation; moreover, it has better role in the differentiation of IBD (UC) from IBS. Acharya K, Bhardwaj V, Chuahan I, et al. Comparison of Fecal Calprotectin with Different Endoscopic Scores in the Assessment of Ulcerative Colitis (UC) Activity and Its Utility in Differentiating IBS from IBD. Euroasian J Hepato-Gastroenterol 2023;13(2):120-123.

Pegivirus Detection in Cerebrospinal Fluid from Patients with Central Nervous System Infections of Unknown Etiology in Brazil by Viral Metagenomics.

Metagenomic next-generation sequencing (mNGS) methodology serves as an excellent supplement in cases where diagnosis is challenging to establish through conventional laboratory tests, and its usage is increasingly prevalent. Examining the causes of infectious diseases in the central nervous system (CNS) is vital for understanding their spread, managing outbreaks, and effective patient care. In a study conducted in the state of São Paulo, Brazil, cerebrospinal fluid (CSF) samples from 500 patients with CNS diseases of indeterminate etiology, collected between 2017 and 2021, were analyzed. Employing a mNGS approach, we obtained the complete coding sequence of Pegivirus hominis (HPgV) genotype 2 in a sample from a patient with encephalitis (named IAL-425/BRA/SP/2019); no other pathogen was detected. Subsequently, to determine the extent of this virus's presence, both polymerase chain reaction (PCR) and/or real-time PCR assays were utilized on the entire collection. The presence of the virus was identified in 4.0% of the samples analyzed. This research constitutes the first report of HPgV detection in CSF samples in South America. Analysis of the IAL-425 genome (9107 nt) revealed a 90% nucleotide identity with HPgV strains from various countries. Evolutionary analyses suggest that HPgV is both endemic and extensively distributed. The direct involvement of HPgV in CNS infections in these patients remains uncertain.

Impact of HBcrAg levels on HBsAg seroconversion after HBV rebound: a case report

BackgroundNucleoside analogues (NAs) such as entecavir are required for at least 12 months when patients with resolved hepatitis B virus (HBV) infection develop HBV reactivation. Entecavir treatment does not always achieve hepatitis B surface antigen (HBsAg) seroconversion. The cessation of NA for HBV reactivation sometimes causes HBV rebound. The impact of hepatitis B core-related antigen (HBcrAg) on predicting HBV rebound is controversial.Case presentationA 67-year-old woman with resolved HBV infection received rituximab for post-transplant lymphoproliferative disorder after peripheral blood stem cell transplantation. Since she tested positive for HBV-DNA after the first rituximab therapy (day 0), entecavir treatment was started. Because the HBV-DNA test became negative and her liver function had been normal, entecavir was terminated on day 376. According to the retrospective measurements, HBcrAg remained positive while the HBV-DNA level was undetectable. One hundred forty-one days after entecavir cessation, the HBV-DNA turned positive again, suggesting HBV rebound (day 517). Her liver function deteriorated and HBV infection worsened, even though entecavir treatment was resumed on day 615. On the contrary, hepatitis B surface antibody levels increased after the rebound, resulting in HBsAg seroconversion with HBcrAg and HBV-DNA levels undetectable. HBV reactivation has not been detected after the second entecavir cessation, and both HBcrAg and HBV-DNA levels remained undetectable.Discussion and conclusionsThis case suggests that NA cessation induced-HBV rebound achieved HBsAg seroconversion under the guidance of a hepatologist. Since HBcrAg had been detectable while HBV-DNA was undetectable, HBcrAg may be an index for predicting HBV rebound resulting in HBsAg seroconversion as well as other conventional laboratory tests. Prospective measuring HBcrAg is required to confirm this case report.

Hydromechanical tensile strength modelling at particle size level for non cohesive granular materials

The aim of this paper is to propose a robust yet simple model to predict the variation of the tensile strength of granular materials with the degree of saturation. Because capillary phenomenon and air–water surface tension govern interparticle bonding in granular materials, they are explicitly taken into consideration. These vary with the degree of saturation as with all geotechnical structures that are subjected to wetting–drying processes. To predict the influence of capillary and air–water surface tension effects, mathematical equations are derived to simulate a porous model. The model is used to predict the drainage process in the porous network of the material and thus determine the relationship between interparticle bonding and the degree of saturation of the granular material. These hydraulic processes are expressed in mechanical terms using the effective stress concept thus providing the key for hydromechanical coupling. The parameters for the resulting equations can be obtained from conventional well-known laboratory tests: the water retention curve, the grain-size distribution of the material and its void ratio. The numerical results are confronted to laboratory tests showing that this approach predicts accurately the tensile strength of granular materials.