Prevalência de Influenza A, vírus sincicial respiratório eSARS-CoV-2 em pacientes com síndrome respiratóriaaguda grave em Passo Fundo, Rio Grande do Sul / Prevalence of Influenza A, respiratory syncytial virus andSARS-CoV-2 in patients with severe acute respiratorysyndrome in Passo Fundo, Rio Grande do Sul

A síndrome respiratória aguda grave (SRAG) é caracterizada por sintomas de febre alta, tosse e dispneia, e, na maioria dos casos, relacionada a uma quantidade reduzida de agentes infecciosos. O objetivo foi avaliar a prevalência dos vírus respiratórios Influenza A (FluA), vírus sincicial respiratório (RSV) e do novo coronavírus (SARS-CoV-2) em pacientes com internação hospitalar por SRAG. Estudo transversal, com pacientes em internação hospitalar com SRAG entre novembro de 2021 e maio de 2022. Dados sociodemográficos e clínicos e amostras da nasofaringe foram coletados/as, as quais foram submetidas à extração de RNA e testadas quanto à positividade para Influenza A, RSV e SARS-CoV-2 por meio da técnica de PCR em tempo real pelo método SYBR Green. Foram incluídos 42 pacientes, sendo 59,5% do sexo feminino, 57,1% idosos, 54,8% com ensino fundamental. A maior parte dos pacientes reportou hábito tabagista prévio ou atual (54,8%), não etilista (73,8%) e 83,3% deles apresentavam alguma comorbidade, sendo hipertensão arterial sistêmica e diabetes mellitus tipo 2 as mais prevalentes. Um total de 10,5% dos pacientes testou positivo para FluA, nenhuma amostra positiva para RSV e 76,3% positivos para SARS-CoV-2. Na população estudada, SRAG com agravo hospitalar foi observado em maior proporção, em mulheres, idosos e pessoas com comorbidades, embora sem significância estatística, sendo o novo coronavírus o agente etiológico mais relacionado, o que evidencia a patogenicidade desse agente e suas consequências ainda são evidentes após quase 2 anos de período pandêmico.

Severe acute respiratory syndrome (SARS) is characterized by symptoms of high fever, cough and dyspnea, and is in most cases related to a reduced amount of infectious agents. The objective was to assess the prevalence of respiratory viruses Influenza A (FluA), respiratory syncytial virus (RSV) and the new coronavirus (SARS-CoV-2) in patients hospitalized for SARS. Cross-sectional study, with patients hospitalized with SARS between November 2021 and May 2022. Sociodemographic and clinical data and nasopharyngeal samples were collected, which were subjected to RNA extraction and tested for positivity for Influenza A, RSV and SARS-CoV-2 using the real-time PCR technique using the SYBR Green method. 42 patients were included, 59.5% female, 57.1% elderly, 54.8% with primary education. Most patients reported previous or current smoking habits (54.8%), non-drinkers (73.8) and 83.3% of them had some comorbidity, with systemic arterial hypertension and type 2 diabetes mellitus being the most prevalent. A total of 10.5% of patients tested positive for FluA, no samples positive for RSV, and 76.3% positive for SARS-CoV-2. In the studied population, SARS with hospital injury was observed more frequently in women and the elderly, with associated comorbidities, with the new coronavirus being the most related etiological agent, which shows, although not statistically significant, that the pathogenicity of this agent and its consequences are still evident after almost 2 years of period pandemic.

Establishing Reference Values for Vaginal Vestibule Elastography in Healthy Postmenopausal Women.

Objective This study aims to establish normative elastography values for the vaginal vestibule in healthy postmenopausal women and assess the variability of these values with age and measurement time during the day. Methods The study included 111 women aged 40-90, excluding those with medical histories or treatments affecting vaginal health. Elastography measurements were taken twice daily, between 9-10 AM and 3-4 PM, using real-time tissue elastography technology. Statistical analysis evaluated the effects of age, body mass index (BMI), and diurnal variation on vaginal vestibule elasticity. Results A significant positive correlation between age and elastography values was found (p=8.36×10⁻7), with elastography values increasing by approximately 0.0040 units per year. The mean elastography value was 28.32% (SD=5.87%) in the morning and 28.10% (SD=5.90%) in the afternoon, with a statistically significant difference (p=0.016). BMI showed a weak negative correlation with elastography values (r=-0.2021, p=0.0334). Conclusion Establishing reference values for vaginal vestibule elastography provides a foundation for improved diagnostic accuracy and early detection of gynecological conditions. The findings support the use of elastography as a non-invasive, reliable diagnostic tool in clinical practice. Future research should validate these results across different age groups and in women with specific gynecological conditions to further solidify the clinical applicability of vaginal vestibule elastography.

Evaluating the quantitative performance of environmental DNA metabarcoding for freshwater zooplankton community: a case study in Lake Biwa, Japan.

Zooplankton monitoring is important for understanding their population dynamics and life history, ecosystem health, and environmental changes. Compared with traditional morphological identification, environmental DNA (eDNA) analysis allows for more sensitive and efficient monitoring of zooplankton diversity. Previous eDNA studies have primarily used metabarcoding approaches to reveal their richness and composition, whereas its performance in predicting zooplankton abundance remains understudied. We conducted water and bulk sampling in Lake Biwa, Japan, showing that the number of sequence reads by metabarcoding moderately correlated with eDNA concentrations estimated by quantitative real-time PCR (qPCR). In addition, the eDNA read number was significantly related to cladoceran and copepod abundance estimated by microscopy sorting, although there remained too much uncertainty in the read-abundance relationship. Moreover, there was a significant difference in species composition between eDNA metabarcoding and sorting. Although our results indicated the potential applicability of eDNA metabarcoding for quantifying multiple zooplankton abundance, several methodological validations in eDNA metabarcoding would also be required to optimize its performance in the future.

Non-invasive and real-time monitoring of polyhydroxyalkanoates production using two-dimensional fluorescence spectroscopy.

Bioplastics are a sustainable and environmental-friendly alternative to the conventional petroleum-based plastics, namely due to their source (biobased) and due to their biodegradability or both. Polyhydroxyalkanoates (PHA) stand out among the bioplastics group by being intracellular biobased, biodegradable and biocompatible polymers. PHA production has been highly investigated during the last decades. However, to date, PHA production has been monitored through offline and time-consuming tools, involving hazardous solvents, not allowing a timely control of the bioprocesses, which often results in a loss of process productivity and hinders its implementation at full scale. Therefore, two-dimensional (2D) fluorescence spectroscopy was assessed for monitoring the PHA content at real-time, as it is a non-destructive, solvent-free and non-invasive technique. The complex information of the biological broth was captured within fluorescence excitation-emission matrices (EEMs), which were deconvoluted through projection to latent structures (PLS) modelling to estimate PHA production by an enriched PHA microbial culture, using fermented brewer's spent grain as feedstock. A good correlation for PHA prediction was achieved, with an average error of ca. 4.0% gPHA/gTS for new predictions. This work demonstrates the great potential of using 2D fluorescence spectroscopy to assess the intracellular PHA content without requiring staining agents. Moreover, it unlocks the possibility of an online and real-time monitoring of the biopolymer production processes, which will contribute towards the improvement of the PHA process productivity and, consequently, its implementation at full scale.

Identification and Validation of an Invasion-Related Disease-Free Survival Prognostic Model for Tongue Squamous Cell Carcinoma.

INTRODUCTION: Tongue squamous cell carcinoma (TSCC) is a common malignant tumour type with aggressive invasion and a poor prognosis. To date, invasion-related gene expression signatures for the prognostic stratification of TSCC patients are unavailable in clinical practice. This study aimed to assess the impact of invasion-related genes on the prognosis of TSCC patients. METHODS: We obtained mRNA profiles and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases (TCGA-TSCC and GSE41116, respectively). The TSCC samples from the TCGA-TSCC cohort were randomly divided into TCGA training and TCGA test datasets at a 7:3 ratio. Next, a disease-free survival (DFS) prognostic risk model was established on the basis of univariate and stepwise multivariate Cox regression analyses of the TCGA training cohort. Moreover, prognostic genes were screened. The model was subsequently evaluated and validated using the TCGA test and GSE41116 datasets. In addition, the prognostic genes were validated in the human TSCC cell line UM1 and the human oral keratinocyte (HOK) cell line using quantitative real-time polymerase chain reaction (qRT-PCR) analysis. RESULTS: A total of 70 candidate genes related to invasion were identified in the TCGA-TSCC cohort. DFS data were subsequently constructed, and 6 prognostic genes, HMGN2, MYL12B, ACTB, PPP1CA, PSMB9, and IFITM3, were identified. The TSCC samples were divided into high- and low-risk groups in the TCGA training, TCGA test, and GSE41116 cohorts, respectively. In particular, patients with TSCC in the low-risk group had longer DFS than those in the high-risk group. Furthermore, qRT-PCR analysis confirmed that the expression levels of the 6 prognostic genes were significantly greater in the TSCC cell line UM1 than in the HOK cell line. CONCLUSION: This study identified new invasion-related target genes related to poor prognosis in TSCC patients, providing new insights into the underlying mechanisms of TSCC invasion.

A droplet digital PCR assay to detect Chinese rice-field eels rhabdovirus.

Chinese rice-field eels rhabdovirus (CrERV) causes haemorrhagic disease in Chinese rice-field eels (Monopterus albus), leading to significant mortality and economic losses. Sensitive detection of CrERV nucleic acids is essential to control the spread of this pathogen and to treat infected individuals. Herein, we developed an efficient and sensitive droplet digital PCR (ddPCR) method to rapidly detect and quantify CrERV. The ddPCR assay optimal conditions were an annealing temperature of 53°C, and primer and probe concentrations of 0.5 and 0.25 µM, respectively. The assay had a diagnostic sensitivity of 0.23 copies/µL, and was highly specific, showing no cross reactivity with other viruses (infectious haematopoietic necrosis virus, grass carp reovirus, spring viremia of carp virus, largemouth bass ranavirus, carp edema virus, Chinese giant salamander iridovirus, and white spot syndrome virus). Real-time quantitative PCR testing of 30 Chinese rice-field eels samples detected CrERV in 7 samples (23.3%), whereas ddPCR detected CrERV in 12 samples (40%), demonstrating its higher sensitivity. Thus, ddPCR represents an advanced method to absolutely quantify CrERV in infected fish with low virus concentrations, providing a valuable tool to manage the spread and impact of CrERV.

Methodological assessment for efficient collection of Schistosoma mansoni environmental DNA and improved schistosomiasis surveillance in tropical wetlands.

Schistosomiasis, caused by trematodes of genus Schistosoma, is among the most seriously neglected tropical diseases. Although rapid surveillance of risk areas for Schistosoma transmission is vital to control schistosomiasis, the habitat and infection status of this parasite are difficult to assess. Environmental DNA (eDNA) analysis, involving the detection of extra-organismal DNA in water samples, facilitates cost-efficient and sensitive biomonitoring of aquatic environments and is a promising tool to identify Schistosoma habitat and infection risk areas. However, in tropical wetlands, highly turbid water causes filter clogging, thereby decreasing the filtration volume and increasing the risk of false negatives. Therefore, in this study, we aimed to conduct laboratory experiments and field surveys in Lake Victoria, Mbita, to determine the appropriate filter pore size for S. mansoni eDNA collection in terms of particle size and filtration volume. In the laboratory experiment, aquarium water was sequentially filtered using different pore size filters. Targeting >3 µm size fraction was found to be sufficient to capture S. mansoni eDNA particles, regardless of their life cycle stage (egg, miracidia, and cercaria). In the field surveys, GF/D (2.7 µm nominal pore size) filter yielded 2.5-times the filtration volume obtained with a smaller pore size filter and pre-filtration methods under the same time constraints. Moreover, a site-occupancy model was applied to the field detection results to estimate S. mansoni eDNA occurrence and detection probabilities and assess the number of water samples and PCR replicates necessary for efficient eDNA detection. Overall, this study reveals an effective method for S. mansoni eDNA detection in turbid water, facilitating the rapid and sensitive monitoring of its distribution and cost-effective identification of schistosomiasis transmission risk areas.

Training individuals with schizophrenia to gain volitional control of the theory of mind network with real-time fMRI: A pilot study.

Individuals diagnosed with schizophrenia spectrum disorders (SSDs) often demonstrate alterations in the Theory of Mind Network (ToM-N). Here, in this proof-of-concept, single-arm pilot study, we investigate whether participants with an SSD (N = 7) were able to learn to volitionally control regions of the ToM-N (dorso/middle/ventromedial prefrontal cortex [D/M/VMPFC], left temporoparietal junction [LTPJ], precuneus [PC], right superior temporal sulcus [RSTS], and right temporoparietal junction [RTPJ]) using real-time fMRI neurofeedback (rtfMRI-NF). Region-of-interest analyses demonstrate that after neurofeedback training, participants were able to gain volitional control in the following ToM-N brain regions during the transfer task, where no active feedback was given: right temporoparietal junction, precuneus, and dorso/ventromedial prefrontal cortex (neurofeedback effect Fs > 6.17, ps < .05). These findings suggest that trained volitional control over the ToM-N is tentatively feasible with rtfMRI neurofeedback in SSD, although findings need to be replicated with more robust designs that include a control group and larger samples.

The real-time shadow detection of the PV module by computer vision based on histogram matching and gamma transformation method.

Solar energy plays an important role in renewable energy generation, with the advantages of low pollution, easy installation, and relatively easy access. However, photovoltaic (PV) modules are susceptible to cause localized shading from external factors such as leaves in the canopy, surrounding buildings, etc., which would affect power generation efficiency and even pose safety risks. Existing methods cannot perform well in real-time conditions. This paper proposes a real-time shading monitoring method for the PV module based on computer vision. The gamma transform and histogram matching were adopted to enhance key features and adjust the global gamut strength distribution in the image of the PV module; then the gray-level slicing method finished the segmentation to detect the shadow from the video. All processing can be realized in the real-time monitor camera and the detection results can be displayed on the HMI in PC with high efficiency and low cost. According to tests in the practical complex environment, the method can have enough detection performance and high real-time performance with an accuracy of 0.98, and the F0.5 and F2 values are 0.87 and 0.85, respectively. The metrics of the proposed method are higher than those of the existing Canny detection method, the Random Forest detection method, and the CNN detection method. In addition, the average time required by the proposed method to process a frame is 0.721 s. In addition, the average time required by the method to process an image frame is 0.721 s, which has good real-time performance.

Longitudinal associations between depressive symptoms and cell deformability: do glucocorticoids play a role?

Cell deformability of all major blood cell types is increased in depressive disorders (DD). Furthermore, impaired glucocorticoid secretion is associated with DD, as well as depressive symptoms in general and known to alter cell mechanical properties. Nevertheless, there are no longitudinal studies examining accumulated glucocorticoid output and depressive symptoms regarding cell deformability. The aim of the present study was to investigate, whether depressive symptoms predict cell deformability one year later and whether accumulated hair glucocorticoids mediate this relationship. In 136 individuals (nfemale = 100; Mage = 46.72, SD = 11.28; age range = 20-65), depressive symptoms (PHQ-9) and hair glucocorticoids (cortisol and cortisone) were measured at time point one (T1), while one year later (T2) both depressive symptoms and hair glucocorticoids were reassessed. Additionally, cell deformability of peripheral blood cells was assessed at T2. Depression severity at T1 predicted higher cell deformability in monocytes and lymphocytes at T2. Accumulated hair cortisol and cortisone concentrations from T1 and T2 were not associated with higher cell deformability and further did not mediate the relationship between depressive symptoms and cell deformability. Elevated depressive symptomatology in a population based sample is longitudinally associated with higher immune cell deformability, while long-term integrated glucocorticoid levels seem not to be implicated in the underlying mechanism.

A Comparative Performance Evaluation of YOLO-Type Detectors on a New Open Fire and Smoke Dataset.

The paper introduces a new FireAndSmoke open dataset comprising over 22,000 images and 93,000 distinct instances compiled from 1200 YouTube videos and public Internet resources. The scenes include separate and combined fire and smoke scenarios and a curated set of difficult cases representing real-life circumstances when specific image patches may be erroneously detected as fire/smoke presence. The dataset has been constructed using both static pictures and video sequences, covering day/night, indoor/outdoor, urban/industrial/forest, low/high resolution, and single/multiple instance cases. A rigorous selection, preprocessing, and labeling procedure has been applied, adhering to the findability, accessibility, interoperability, and reusability specifications described in the literature. The performances of the YOLO-type family of object detectors have been compared in terms of class-wise Precision, Recall, Mean Average Precision (mAP), and speed. Experimental results indicate the recently introduced YOLO10 model as the top performer, with 89% accuracy and a mAP@50 larger than 91%.

Releaf: An Efficient Method for Real-Time Occlusion Handling by Game Theory.

Receiving uninterrupted videos from a scene with multiple cameras is a challenging task. One of the issues that significantly affects this task is called occlusion. In this paper, we propose an algorithm for occlusion handling in multi-camera systems. The proposed algorithm, which is called Real-time leader finder (Releaf), leverages mechanism design to assign leader and follower roles to each of the cameras in a multi-camera setup. We assign leader and follower roles to the cameras and lead the motion by the camera with the least occluded view using the Stackelberg equilibrium. The proposed approach is evaluated on our previously open-sourced tendon-driven 3D-printed robotic eye that tracks the face of a human subject. Experimental results demonstrate the superiority of the proposed algorithm over the Q-leaning and Deep Q Networks (DQN) baselines, achieving an improvement of 20% and 18% for horizontal errors and an enhancement of 81% for vertical errors, as measured by the root mean squared error metric. Furthermore, Releaf has the superiority of real-time performance, which removes the need for training and makes it a promising approach for occlusion handling in multi-camera systems.

Enhanced Harmonic Partitioned Scheduling of Periodic Real-Time Tasks Based on Slack Analysis.

The adoption of multiprocessor platforms is growing commonplace in Internet of Things (IoT) applications to handle large volumes of sensor data while maintaining real-time performance at a reasonable cost and with low power consumption. Partitioned scheduling is a competitive approach to ensure the temporal constraints of real-time sensor data processing tasks on multiprocessor platforms. However, the problem of partitioning real-time sensor data processing tasks to individual processors is strongly NP-hard, making it crucial to develop efficient partitioning heuristics to achieve high real-time performance. This paper presents an enhanced harmonic partitioned multiprocessor scheduling method for periodic real-time sensor data processing tasks to improve system utilization over the state of the art. Specifically, we introduce a general harmonic index to effectively quantify the harmonicity of a periodic real-time task set. This index is derived by analyzing the variance between the worst-case slack time and the best-case slack time for the lowest-priority task in the task set. Leveraging this harmonic index, we propose two efficient partitioned scheduling methods to optimize the system utilization via strategically allocating the workload among processors by leveraging the task harmonic relationship. Experiments with randomly synthesized task sets demonstrate that our methods significantly surpass existing approaches in terms of schedulability.

High-intensity focused ultrasound ablation combined with hysteroscopy for the treatment of uterine arteriovenous fistula associated with retained products of conception: a prospective cohort study.

OBJECTIVE: To evaluate the efficacy of combining high-intensity focused ultrasound (HIFU) ablation with hysteroscopic removal of retained products of conception in the presence of a uterine arteriovenous fistula (UAVF). DESIGN: Prospective cohort study SETTING: Tertiary hospital. PARTICIPANTS: 17 patients with UAVF and retained products of conception. INTERVENTIONS: HIFU ablation combined with hysteroscopic removal of retained products of conception RESULTS: All patients presented with irregular vaginal bleeding following pregnancy termination and not responsive to medical treatment. Patients were confirmed to have a UAVF along with concurrent intrauterine residue using three-dimensional color Doppler ultrasonography, uterine angiography, or pelvic-enhanced magnetic resonance imaging; and demonstrated a poor response to medical treatment. Under real-time ultrasound guidance, HIFU was used to ablate the arteriovenous malformation region. Patients underwent hysteroscopic removal of retained products of conception; the removed tissue was subjected to pathological examination. All patients underwent monthly uterine color Doppler ultrasound examinations and menstrual status follow-up within 3 months postoperatively and showed normal menstrual recovery without signs of arteriovenous malformations on ultrasonography. Pathological examination of the tissues removed during hysteroscopic clearance revealed characteristics consistent with pregnancy, with abnormal blood vessels in some tissues. All patients experienced normal menstrual recovery postoperatively, without intrauterine adhesions. CONCLUSION: Combining HIFU ablation with postoperative hysteroscopic surgery effectively treats pregnancy related UAVF with minimal complications, preserves fertility; it offers an additional treatment option for patients wanting future fertility.

Surface tracking integrated extended depth-of-field microscopy for rapid non-contact examination of conjunctival goblet cells in humans.

Conjunctival goblet cells (CGCs) are specialized epithelial cells playing key roles for ocular surface homeostasis, and their examination is important for diagnosing ocular surface diseases. Despite recent advancements in high-contrast CGC imaging for non-invasive examination, significant challenges remain for human applications. High-speed large-area imaging over the curved ocular surface is needed to assess statistically meaningful CGCs in the extensive human conjunctiva. To address this challenge, we developed a novel surface detection method and an integrated microscopy system for human use. With both a long detection range of 2 mm and a high update rate of 50 Hz, the surface detection method enabled real-time surface tracking during large-area imaging. The integrated microscopy could complete 5 × 2 patch imaging in approximately 10 s. CGC density analysis showed significantly reduced uncertainties with large-area imaging. This is the first demonstration of non-contact large-area cellular examination in humans, and this new development holds promise for non-invasive CGC examination and accurate diagnosis of ocular surface diseases.

A Comparative Evaluation of Real-Time Guided Dynamic Navigation and Conventional Techniques for Post Space Preparation During Post Endodontic Management: An In Vitro Study.

INTRODUCTION:  The three-dimensional (3D) dynamic navigation system (DNS; Navident, ClaroNav Technology, Toronto, ON) is a revolutionary technique in endodontics that offers superior precision and efficiency compared to existing techniques for post space preparation. AIM: The aim is to evaluate and contrast the efficacy and efficiency of the DNS with conventional post space preparation techniques. This assessment considers several parameters, notably canal deviation (global coronal and apical deviation and angular deflection), duration of the procedure, and total volumetric loss of instrumented root canal and volumetric loss of instrumented root canal above 4 mm from the apex. MATERIALS AND METHODS: Freshly extracted maxillary central incisors were chosen for this study. A total sample size of 60 (n) was included. The extracted teeth samples were divided into two groups: 3D DNS (group I; n = 30) and conventional techniques (group II; n = 30). The samples were taken, and 50% of the crown structure was reduced for post space preparation to ensure standardization between the two groups. The samples were root canal-treated and mounted in a 3D-printed maxillary cast. Preoperative micro-computed tomography (micro-CT) and cone-beam computed tomography (CBCT) were taken for both groups. For group I, post space preparation was conducted with the DNS, which provided comprehensive guidance. The procedure was stopped when post space preparation was 4 mm short of the apex, as indicated in the system display. For group II, post space preparation was done without the guidance of DNS. Time taken for the procedure was assessed using a timer; canal deviation was evaluated using CBCT analysis, and volumetric loss was estimated using micro-CT analysis. RESULTS: The dynamic navigation group achieves significantly more precise outcomes in post space preparation than the conventional technique. The DNS group has significantly lesser global coronal and apical deviation and angular deflection compared to the conventional group (p < 0.05). The DNS group has reduced the volumetric loss of instrumented root canals compared to the conventional group (p < 0.05). Furthermore, the DNS group requires significantly less time than the conventional method, with a mean difference of about 10.567 minutes (p < 0.05). CONCLUSION: Implementing dynamic navigation improves precision in post space preparation, with a notable reduction in canal deviation and volumetric loss and a decrease in procedure time compared to the conventional method.

Real-time acid production and extracellular matrix formation in mature biofilms of three Streptococcus mutans strains with special reference to xylitol.

Background: Acidogenicity and production of an extracellular matrix (ECM) are important virulence factors for the dental caries-associated bacteria, such as Streptococcus mutans, that live in biofilms on tooth surface. The ECM protects the bacteria from the flushing and buffering effects of saliva resulting in highly acidic microenvironments inside the biofilm. Materials and methods: In this in vitro study, we applied real-time assays to follow biofilm formation and pH decrease in a growth medium and saliva by three S. mutans strains, as well as acid neutralization inside the mature biofilm. Results were compared with the biofilm composition. Effects of a non-fermentable polyol, xylitol, on acid production and acid neutralization in mature biofilms were evaluated by real-time pH measurements and confocal microscopy. Results: Combination of real-time pH measurements with biofilm accumulation assays revealed growth media dependent differences in the pH decrease and biofilm accumulation, as well as strain differences in acid production and biofilm formation but not in the buffer diffusion through ECM. The presence of xylitol reduced the pH drop during biofilm formation of all strains. In addition, with strain Ingbritt xylitol reduced the amount of ECM in biofilm, which increased the rate of acid neutralization inside the biofilm after buffer exposure. Conclusion: Our results stress the importance of biofilm matrix in creating the acidic environment inside a S. mutans biofilm, especially in the presence of saliva. In addition, our results suggest a novel mechanism of xylitol action. The observed increase in the permeability of the S. mutans ECM after xylitol exposure may allow acid-neutralizing saliva to reach deeper layer of the biofilms and thus, in part, explain previous clinical observations of reduced plaque acidogenicity after frequent xylitol use.

Real-time artificial intelligence-based texture analysis of muscle ultrasound data for neuromuscular disorder assessment.

Objective: Many artificial intelligence approaches to muscle ultrasound image analysis have not been implemented on usable devices in clinical neuromuscular medicine practice, owing to high computational demands and lack of standardised testing protocols. This study evaluated the feasibility of using real-time texture analysis to differentiate between various pathological conditions. Methods: We analysed 17,021 cross-sectional ultrasound images of the biceps brachii of 75 participants, including 25 each with neurogenic disorders, myogenic disorders, and healthy controls. The size and location of the regions of interest were randomly selected to minimise bias. A random forest classifier utilising texture features such as Dissimilarity and Homogeneity was developed and deployed on a mobile PC, enabling real-time analysis. Results: The classifier distinguished patients with an accuracy of 81 %. Echogenicity and Contrast from the Co-Occurrence Matrix were significant predictive features. Validation on 15 patients achieved accuracies of 78 %/93 % per image/patient over 15-second videos, respectively. The use of a mobile PC facilitated real-time estimation of the underlying pathology during ultrasound examination, without influencing procedures. Conclusions: Real-time automatic texture analysis is feasible as an adjunct for the diagnosis of neuromuscular disorders. Significance: Artificial intelligence using texture analysis with a light computational load supports the semi-quantitative evaluation of neuromuscular ultrasound.

Promoting molecular diagnostic equity: assessing in-house real-time PCR for Neisseria gonorrhoeae in anal samples from MSM recruited in an outpatient setting in Morocco.

Objectives: Gonorrhea is a prevalent sexually transmitted infection among men who have sex with men (MSM). In Morocco, the basic laboratory diagnosis of Neisseria gonorrhoeae (NG) is based on microscopy and, in some settings, on culture. However, no nucleic acid amplification test (NAAT) has been implemented for routine diagnosis of gonorrhoeae.The aim of this study is to assess the effectiveness of an in-house real-time PCR test for detecting N. gonorrhoeae DNA in anal swabs samples collected during an Integrated Behavioral and Biological survey. Patients and methods: Samples from 245 MSM, recruited using a Respondent Driven Sampling, were collected and tested for NG infection using GeneXpert CT/NG assay (Cepheid, USA). An In-House real-time PCR technique targeting the pseudo gene porA was developed and used for a parallel investigation of the same infection. The reliability of the in-house RT-PCR was validated through tests of reproducibility, repeatability, limit of detection, and cross-reactivity with other bacteria. The intrinsic performance characteristics of the qRT-PCR were assessed, namely, the sensitivity, the specificity, the positive predictive value (PPV), and the negative predictive value (NPV). The GeneXpert CT/NG assay was adopted as a reference method. Results: For N. gonorrhoeae detection, the in-house real-time PCR assay showed a sensitivity and specificity of 80% and 100%, respectively. The PPV of the assay was 100% and the NPV was 97.3%. Conclusion: The in-house real-time PCR assay has high specificity and sensitivity, and it emerges as a promising approach for detecting N. gonorrhoeae in clinical specimens, particularly in decentralized settings such as regional laboratories.

Real-time identification of noise type contaminated in surface electromyogram signals using efficient statistical features.

Different types of noise contaminating the surface electromyogram (EMG) signal may degrade the recognition performance. For noise removal, the type of noise has to first be identified. In this paper, we propose a real-time efficient system for identifying a clean EMG signal and noisy EMG signals contaminated with any one of the following three types of noise: electrocardiogram interference, spike noise, and power line interference. Two statistical descriptors, kurtosis and skewness, are used as input features for the cascading quadratic discriminant analysis classifier. An efficient simplification of kurtosis and skewness calculations that can reduce computation time and memory storage is proposed. The experimental results from the real-time system based on an ATmega 2560 microcontroller demonstrate that the kurtosis and skewness values show root mean square errors between the traditional and proposed efficient techniques of 0.08 and 0.09, respectively. The identification accuracy with five-fold cross-validation resulting from the quadratic discriminant analysis classifier is 96.00%.