Conventional Tests Research Articles

Occurrence of Salmonella Species in Local and Commercial Chickens Slaughtered at Samaru and Sabongari Live Bird Markets, Kaduna State

Salmonellosis is a bacterial infection caused by members of the genus Salmonella. It is one of the most common and important zoonotic diseases. The route of infection from animals to humans is usually through contaminated food, water and environment. Bacteriological investigation on 303 cloacal swab samples collected from local (139) and commercial (164) chickens slaughtered at Samaru and Sabon-gari live bird markets, Kaduna State was carried out to determine the occurrence of Salmonella species. Cultural isolation and identification using conventional biochemical tests, microgen test kit™ and Polymerase Chain Reaction (PCR) amplification of invA gene of the Salmonella isolates was carried out. Isolates were subjected to antimicrobial susceptibility tests, phenotypic detection of Extended Spectrum Beta Lactamases (ESBLs) producing Salmonella isolates using the modified Clinical and Laboratory Standards Institute (CLSI) ESBL confirmatory test. The occurrence of Salmonella species based on cultural and biochemical tests was found to be 13 (4.29%), microgen kit identified 7 (53.8%) of the 13 Salmonella species while PCR based on invA gene confirmed 9 (69.2%) as the overall occurrence rate of Salmonella species. Meanwhile, the study also revealed rate of occurrence of Salmonella species in local chickens 8 (61.5%) which was higher compared to commercial chickens 1 (7.69%) with a statistical significant association (χ2 = 8.775, P = 0.003) between the occurrence of Salmonella species in local and commercial chickens. Antimicrobial susceptibility testing was carried out using panel of 12 antibiotics from 8 different antibiotic classes. Highest rate of sensitivity of the isolates to antibiotics was observed for Ofloxacin with 90%, while all the isolates (100%) were resistant to Nalidixic Acid, Cefazolin, Amoxicillin + Clavulanic Acid, Oxacillin and Penicillin. This study revealed multidrug-resistance (MDR) profile of Salmonella with a total of (25%) of Salmonella isolates being resistant to 5 antibiotics belonging to 4 different classes of antimicrobials with the highest multiple antibiotic-resistant (MAR) indices ranging from 0.58 to 0.91. All the nine (9) isolates of Salmonella tested were found to be negative for ESBLs production. Therefore, it is concluded that Salmonella species are present in local and commercial chickens slaughtered at Samaru and Sabon-gari live bird markets, Kaduna State and could pose serious public health risks to handlers and to consumers of poultry meat and its products.

Assessment of Serum Cortisol Levels in Hypothyroidism Patients: A Cross-Sectional Study.

Hypothyroidism, characterized by insufficient thyroid hormone production, affects a significant global population, particularly women and the elderly. Recent research has emphasized the interaction between hypothyroidism and the hypothalamic-pituitary-adrenal (HPA) axis, highlighting cortisol's crucial role in the disease's physiological manifestations. This study aims to evaluate serum cortisol levels in hypothyroid patients, examining the intricate relationship between these two endocrine systems. By exploring the potential impact of altered cortisol levels on hypothyroidism's clinical presentation and progression, the study seeks to contribute valuable insights to enhance diagnostic approaches and develop more effective treatment strategies. A cross-sectional observational study was conducted at the Indira Gandhi Institute of Medical Sciences, assessing 65 hypothyroid cases and 65 age-matched euthyroid controls. Demographic data, medical history, and blood samples were collected, and serum cortisol, thyroid-stimulating hormone (TSH), triiodothyronine (T3), and thyroxine (T4) levels were measured. The study adhered to ethical considerations and received institutional approval. The study included 65 hypothyroid cases (56 females, 9 males) and 65 euthyroid controls. Serum cortisol showed a significant correlation with TSH and T4 levels. Linear regression revealed a negative correlation between serum T4 and T3 levels and serum cortisol in hypothyroidism. A positive correlation was observed between TSH and cortisol. These findings align with previous studies, suggesting potential regulatory mechanisms and compensatory responses in hypothyroid patients. The study's results emphasize the complex interaction between cortisol and thyroid function, suggesting a direct relationship between serum cortisol and TSH levels in hypothyroidism. Patients with severe hypothyroidism exhibited elevated cortisol concentrations, indicating a potential compensatory mechanism initiated by the HPA axis. Integrating serum cortisol assessment with conventional thyroid function tests could offer comprehensive insights into hypothyroidism severity and progression, providing a more holistic approach to patient care. This study contributes to understanding the complex relationship between serum cortisol levels and hypothyroidism, emphasizing the need for further research to uncover underlying mechanisms and therapeutic implications. A comprehensive understanding holds the potential for more tailored and effective treatment strategies for individuals with hypothyroidism.

Imaging of voids beyond boring depth with 3D SPT-seismic full-waveform tomography

Identification of voids in bedrock is important for the design of deep foundations. Driven piles are often socketed near the top of bedrock due to driving refusal, thus it is crucial to image voids below the pile tips for the reliability of foundations. This study investigates the capabilities of a new SPT-seismic testing method in imaging voids beyond the boring depth. The method utilizes a 3D full-waveform inversion (3D FWI) of wavefields induced by the standard penetration test (SPT) blows at depths (in-depth source) to characterize subsurface material properties. After being verified on synthetic data, the method is applied to field data recorded by 72 vertical geophones placed in a 36 × 18 m array on the ground surface during a SPT. Using the seismic data from a single SPT to 11-m depth, subsurface soil/rock properties were characterized in a large 3D domain of 24 × 36 × 18 m (depth × length × width), or up to 18 m away from the SPT location. A deep void at 13 to 17-m depth is successfully imaged, showing the capability of the method to detect a void beyond the depth of an SPT boring. The results suggest the SPT-seismic method is a powerful tool for site investigation particularly for imaging of voids in weathered and karst rock that are difficult to identify by conventional geophysical methods or invasive tests.

A precision overview of genomic resistance screening in Ecuadorian isolates of Mycobacterium tuberculosis using web-based bioinformatics tools.

Tuberculosis (TB) is among the deadliest diseases worldwide, and its impact is mainly due to the continuous emergence of resistant isolates during treatment due to the laborious process of resistance diagnosis, nonadherence to treatment and circulation of previously resistant isolates of Mycobacterium tuberculosis. In this study, we evaluated the performance and functionalities of web-based tools, including Mykrobe, TB-profiler, PhyResSE, KvarQ, and SAM-TB, for detecting resistance in 88 Ecuadorian isolates of Mycobacterium tuberculosis drug susceptibility tested previously. Statistical analysis was used to determine the correlation between genomic and phenotypic analysis. Our results showed that with the exception of KvarQ, all tools had the highest correlation with the conventional drug susceptibility test (DST) for global resistance detection (98% agreement and 0.941 Cohen's kappa), while SAM-TB, PhyResSE, TB-profiler and Mykrobe had better correlations with DST for first-line drug analysis individually. We also identified that in our study, only 50% of mutations characterized by the web-based tools in the rpoB, katG, embB, pncA, gyrA and rrs regions were canonical and included in the World Health Organization (WHO) catalogue. Our findings suggest that SAM-TB, PhyResSE, TB-profiler and Mykrobe were efficient in determining canonical resistance-related mutations, but more analysis is needed to improve second-line detection. Improving surveillance programs using whole-genome sequencing tools for first-line drugs, MDR-TB and XDR-TB is essential to understand the molecular epidemiology of TB in Ecuador. Tuberculosis, an infectious disease caused by Mycobacterium tuberculosis, most commonly affects the lungs and is often spread through the air when infected people cough, sneeze, or spit. However, despite the existence of effective drug treatment, patient adherence, long duration of treatment, and late diagnosis have reduced the effectiveness of therapy and increased drug resistance. The increase in resistant cases, added to the impact of the COVID-19 pandemic, has highlighted the importance of implementing efficient and timely diagnostic methodologies worldwide. The significance of our research is in evaluating and identifying a more efficient and user-friendly web-based tool to characterize resistance in Mycobacterium tuberculosis by whole-genome sequencing, which will allow more routine application to improve TB strain surveillance programs locally.

Robust testing for explosive behavior with strongly dependent errors

A heteroskedasticity-autocorrelation robust (HAR) test statistic is proposed to test for the presence of explosive roots in financial or real asset prices when the equation errors are strongly dependent. Limit theory for the test statistic is developed and extended to heteroskedastic models. The new test has stable size properties unlike conventional test statistics that typically lead to size distortion and inconsistency in the presence of strongly dependent equation errors. The new procedure can be used to consistently time-stamp the origination and termination of an explosive episode under similar conditions of long memory errors. Simulations are conducted to assess the finite sample performance of the proposed test and estimators. An empirical application to the S&P 500 index highlights the usefulness of the proposed procedures in practical work.

Wideband frequency impedance for diagnosis of ossicular chain abnormality

Background The accurate estimation of the ossicular chain abnormalities using existing functional examinations has been difficult. Aims/Objectives This study aimed to verify the accuracy of preoperative diagnosis of ossicular chain abnormalities using a wideband frequency impedance (WFI) meter, which can measure the dynamic characteristics of the middle ear. Material and Methods Retrospective cohort study. Fourteen ears of patients with ossicular chain abnormalities that were definitively diagnosed surgically were included in this study. The following data were collected for each participant: sound pressure level (SPL) curve measured using the WFI meter and a sweep frequency impedance (SFI) meter, WFI measurements plotted on the resonance frequency (RF)-ΔSPL plane, distribution map of the dynamic characteristics of the middle ear, preoperative audiometry results, and the definitive surgical diagnosis. Results The SPL curve obtained using the WFI meter had lesser noise than that obtained using the SFI meter. The distribution map revealed that the ossicular chain separation range and ossicular chain fixation range were completely separated. The hearing data tended to be poor in cases with small ΔSPL. Conclusions and Significance WFI can potentially enhance the accuracy of SFI. In addition, it can also be used for the classification of ossicular chain separation and fixation as well as the quantification of fixation in cases of ossicular chain anomalies that cannot be diagnosed using conventional tests.

Benzodiazepine Delorazepam Induces Locomotory Hyperactivity and Alterations in Pedal Mucus Texture in the Freshwater Gastropod Planorbarius corneus

Benzodiazepines, psychotropic drugs, are ubiquitous in the aquatic environment due to over-consumption and inefficient removal by sewage treatment plants. Bioaccumulation with consequent behavioral and physiological effects has been reported in many aquatic species. However, the responses are species-specific and still poorly understood. To improve the knowledge, we exposed the freshwater snail Planorbarius corneus to 1, 5, or 10 µg/L of delorazepam, the most widely consumed benzodiazepine in Italy. Conventional behavioral tests were used to assess the effects on locomotor and feeding behavior. Histological and biochemical analyses were also performed to detect possible changes in the structure and composition of the foot mucus and glands. The results show a paradoxical response with reduced feeding activity and locomotor hyperactivity. Pedal mucus was altered in texture but not in composition, becoming particularly rich in fibrous collagen-like material, and a significant change in the protein composition was highlighted in the foot. In conclusion, exposure to delorazepam induces disinhibited behavior in Planorbarius corneus, potentially increasing the risk of predation, and an increase in mucus protein production, which, together with reduced feeding activity, would severely compromise energy resources.

Evaluation of perioperative routine coagulation testing versus thromboelastography for major liver resection - A single-arm, prospective, interventional trial (PORTAL trial).

The International Normalised Ratio (INR), which assesses the loss of procoagulant factors in the extrinsic pathway, fails to evaluate the coagulation abnormalities comprehensively after a major liver resection, which often leads to reduced synthesis of procoagulant and anticoagulant-factors. This study was conducted with an aim to study the trend and compare the results of routine coagulation tests and thromboelastography (TEG) during the perioperative period in patients undergoing major liver resections (≥3 segments). Twenty-five patients who underwent a major liver resection were enrolled. This prospective, single-arm, interventional study was performed with the primary objective of determining the serial changes in conventional coagulation tests and TEG during the perioperative period in patients undergoing major liver resections, at the preincision period, intraoperative period, postoperatively, at 48 h and on the fifth postoperative day. Transfusion requirements of blood components were also assessed with a TEG-guided replacement strategy. Spearman rank-order correlation was used to study the relationships of coagulation tests (both TEG and conventional tests) at each time point. The prothrombin time (PT)-INR was elevated in 14 patients (56%) at the intraoperative, immediate postoperative and 48-h time points in contrast to the TEG parameters, which remained normal in all patients. Blood component transfusion was avoided in 4, 11 and 10 patients at the intraoperative, immediate postoperative and 48-h time points, respectively. International Normalised Ratio overestimates the coagulopathy in patients undergoing major liver resection, and a thromboelastography-guided transfusion strategy reduces overall transfusion requirements.

The Application of Immersive Virtual Reality and Machine Learning for the Assessment of Unilateral Spatial Neglect

Abstract Even subtle forms of hemispatial neglect after stroke negatively affect the performance of daily life tasks, increase the risk of injury, and are associated with poor rehabilitation outcomes. Conventional paper-and-pencil tests, however, often underestimate the symptoms. We aimed to identify relevant neglect-specific measures and clinical decision rules based on machine learning techniques on behavioral data generated in a new Virtual Reality (VR) application, the immersive virtual road-crossing task. In total, 59 participants were included in our study: two right-hemispheric stroke groups with left neglect (N = 20) or no neglect (N = 19), classified based on conventional tests and medical diagnosis, and healthy controls (N = 20). A neuropsychological test battery and the VR task were administered to all participants. We applied decision trees and random forest models to predict the respective groups based on the results of the VR task. Our feature selection procedure yielded six features as suitable predictors, most of which involved lateral time-related measures, particularly reaction times, and head movements. Our model achieved a high training accuracy of 96.6% and estimated test accuracy of 76.8%. These results confirm previous reports that temporal behavioral patterns are key to detecting subtle neglect in patients with chronic stroke. Our results indicate that VR combined with machine learning has the potential to achieve higher test accuracies while being highly applicable to clinical practice.

EE188 A Retrospective Cohort Comparing the Tuberculosis Diagnosis Related Costs and Health Resource Use (HRU) Using a Rapid Nucleic Acid Amplification (NAA) Test Vs. Conventional Tests in China, Followed By a Budget Impact Model

EE188 A Retrospective Cohort Comparing the Tuberculosis Diagnosis Related Costs and Health Resource Use (HRU) Using a Rapid Nucleic Acid Amplification (NAA) Test Vs. Conventional Tests in China, Followed By a Budget Impact Model

Performance of clinical metagenomics in France: a prospective observational study

Metagenomic next-generation sequencing (mNGS) allows untargeted identification of a broad range of pathogens, including rare or novel microorganisms. Despite the recognition of mNGS as a valuable diagnostic tool for infections, the most relevant indications for this innovative strategy remain poorly defined. We aimed to assess the determinants of positivity and clinical utility of mNGS. In this observational study, we prospectively performed short-read shotgun metagenomics analysis as a second-line test (in cases of negative first-line test or when the symptoms were not fully explained by initial positive results) or as a first-line test in life-threatening situations requiring urgent non-targeted pathogen identification at the Necker-Enfants Malades Hospital (Paris, France). All sample types, clinical indications, and patient populations were included. Samples were accompanied by a mandatory form completed by the senior clinician or pathologist, on which the clinical level of suspected infection (defined as high or low) was indicated. We assessed the variables (gender, age, immune status, initial suspicion of infection, indication, and sample type) associated with mNGS pathogen detection using odds ratios (ORs) from multivariate logistic regression. Additional investigations were carried out using specific PCR or culture techniques, to confirm positive mNGS results, or when infectious suspicion was particularly high despite a negative mNGS result. Between Oct 29, 2019, and Nov 7, 2022, we analysed 742 samples collected from 523 patients. The initial suspicion of infection was either high (n=470, 63%) or low (n=272, 37%). Causative or possibly causative pathogens were detected in 117 (25%) samples from patients with high initial suspicion of infection, versus nine (3%) samples analysed to rule out infection (OR 9·1, 95% CI 4·6-20·4; p<0·0001). We showed that mNGS had higher odds of detecting a causative or possibly causative pathogenic virus on CNS biopsies than CSF samples (4·1, 1·7-10·7; p=0·0025) and in samples from immunodeficient compared with immunocompetent individuals (2·4, 1·4-4·1; p=0·0013). Concordance with conventional confirmatory tests results was 103 (97%) of 106, when mNGS detected causative or possibly causative pathogens. Altogether, among 231 samples investigated by both mNGS and subsequent specific tests, discordant results were found in 69 (30%) samples, of which 58 (84%) were mNGS positive and specific tests negative, and 11 (16%) mNGS negative and specific tests positive. Major determinants of pathogen detection by mNGS are immune status and initial level of suspicion of infection. These findings will contribute, along with future studies, to refining the positioning of mNGS in diagnostic and treatment decision-making algorithms. Necker-Enfants Malades Hospital and Institut Pasteur. For the French translation of the abstract see Supplementary Materials section.

Brittleness index evaluation of gas-bearing sandstone under triaxial compression conditions

Brittleness is a critical property in gas-bearing rock excavation and reservoir fracturing. This paper analyzes the three types of brittleness indices in detail, proposes new indices, and conducts relevant conventional triaxial tests for analysis. A stress–strain curve-based brittleness index would be appropriate for the evaluation of brittleness if the parameters represented unique and certain stress–strain curves. Therefore, a new brittleness index is proposed. It consists of two components: the stress variation index and the strain variation index, which reflects the strain ratio of the stress drop and the relationship between elastic and post-peak strains, combining the stress variation and strain variation in the pre- and post-peak phases. Triaxial compression tests of sandstone under different confining pressures and gas pressures were conducted, and specific stress and strain parameters were collected. Based on the comparison and analysis of various brittleness indices, it is found that the newly proposed brittleness index can be a good measure of the brittle evolution of sandstones under different confining pressures and gas pressures, and it can provide a more accurate estimate of rock brittleness than the existing indices. The index is also used to further investigate the relationship between rock brittleness and confining and gas pressures. This has important implications for the assessment of rock brittleness in practical engineering.

DETECT‐AD (Digital Evaluations and Technologies Enabling Clinical Translation for Alzheimer’s Disease): A simulated anti‐amyloid clinical trial using digital biomarkers as primary outcome measures

AbstractBackgroundEarly detection and precise monitoring of cognitive and functional decline in persons with Alzheimer’s Disease (AD) in clinical trials is a high priority. Unfortunately, early detection and monitoring of the subtle and slow changes of disease with conventional cognitive testing and self‐report questionnaires has been fraught with poor sensitivity and lack ecological validity. Digital biomarkers using ambient sensing technologies may afford a more effective approach to conducting trials. Remaining to be established is the ability of this approach to fundamentally improve early AD treatment response readout in a formal clinical trial setting. A simulated clinical trial (DETECT‐AD: ClinicalTrials.gov, NCT05385913) is being conducted to determine how well continuously assessed, home‐based digital biomarkers may detect clinically meaningful changes in individuals with changing amyloid (Aß) burdens in pre‐symptomatic AD.MethodClinically prodromal AD patients with estimable rates of AD progression based on Aß Florbetapir‐PET status are enrolled divided n = 50:n = 50 into Aß “positive” (higher amyloid burden) patients who predictably progress (as if they were receiving placebo) and Aß “negative” patients progressing more slowly (representing the treatment group). A study‐provided multivitamin mimics RCT conditions and study drug adherence behavior. Baseline standard clinical and biomarker measures are obtained along with digital biomarkers (DB) captured with passive and active sensors (actigraphy, bed mats, IR sensing, e‐pillbox, computing/phone device use, weekly online reporting/cognitive assessment). Primary outcome is the change in a composite DB composed of measures in 4 domains: mobility, cognition, sleep, and socialization. Secondary measures are the relationship of DB to fluid biomarkers (plasma ptau181/217, amyloid, NfL) and MRI/PET measures.ResultTo date (01/16/2023), 46/100 have been enrolled with mean(SD): follow‐up = 27.0(7.9) weeks (no dropout); age = 78(6.6); 63% women; MoCA = 25.5(2.3); PET SUVR = 1.09(0.20), range: 0.850‐2.07. Exemplary baseline digital biomarker metrics are presented in the Table. Preliminary data shows an inverse Aß‐SUVR correlation with mean steps/day (r = ‐.41, p = .012) and a positive correlation of MoCA with computer use (r = .61; p = .036).ConclusionHome‐based continuous capture of multi‐domain DBs is feasible in a clinical trial setting and may yield early meaningful indicators of clinically relevant changes in older adults with pre‐AD dementia. Further evidence will evolve as sample sizes and longitudinal follow‐up increases.

The Interpretation of Standard Cardiopulmonary Exercise Test Indices of Cardiac Function in Chronic Kidney Disease

Background and Aims: As there is growing interest in the application of cardiopulmonary exercise test (CPX) in chronic kidney disease (CKD), it is important to understand the utility of conventional exercise test parameters in quantifying the cardiopulmonary fitness of patients with CKD. Merely extrapolating information from heart failure (HF) patients would not suffice. In the present study, we evaluated the utility of CPX parameters such as the peak O2-pulse and the estimated stroke volume (SV) in assessing the peak SV by comparing with the actual measured values. Furthermore, we compared the anaerobic threshold (AT), peak circulatory power, and ventilatory power with that of the measured values of the peak cardiac power (CPOpeak) in representing the cardiac functional reserve in CKD. We also performed such analyses in patients with HF for comparison. Method: A cross sectional study of 70 asymptomatic male CKD patients [CKD stages 2–5 (pre-dialysis)] without primary cardiac disease or diabetes mellitus and 25 HF patients. A specialized CPX with a CO2 rebreathing technique was utilized to measure the peak cardiac output and peak cardiac power output. The peak O2 consumption (VO2peak) and AT were also measured during the test. Parameters such as the O2-pulse, stroke volume, arteriovenous difference in O2 concentration [C(a-v)O2], peak circulatory power, and peak ventilatory power were all calculated. Pearson’s correlation, univariate, and multivariate analyses were applied. Results: Whereas there was a strong correlation between the peak O2-pulse and measured peak SV in HF, the correlation was less robust in CKD. Similarly, the correlation between the estimated SV and the measured SV was less robust in CKD compared to HF. The AT only showed a modest correlation with the CPOpeak in HF and only a weak correlation in CKD. A stronger correlation was demonstrated between the peak circulatory power and CPOpeak, and the ventilatory power and CPOpeak. In HF, the central cardiac factor was the predominant determinant of the standard CPX-derived surrogate indices of cardiac performance. By contrast, in CKD both central and peripheral factors played an equally important role, making such indices less reliable markers of cardiac performance per se in CKD. Conclusion: The results highlight that the standard CPX-derived surrogate markers of cardiac performance may be less reliable in CKD, and that further prospective studies comparing such surrogate markers with directly measured cardiac hemodynamics are required before adopting such markers into clinical practice or research in CKD.

Forest resilience research using remote sensing and GIS – A systematic literature review

Forest resilience assessment is increasingly important given the current global environmental change. However, attributes and indicators to quantify forest resilience still need to be explored. Remote sensing (RS) and Geographical Information System (GIS) techniques are widely applied for forest resilience modeling. A bibliometric analysis was conducted to obtain insights concerning methods for quantifying forest resilience using RS/GIS. VosViewer and Bibliometrix R software were applied to analyze 117 articles from the Web of Science global database covering a period of 2011-2021. Using inclusion-exclusion criteria, 31 studies were examined, covering local, regional, and transnational ecosystem types. Satellite devices were used in 28 studies, whilst GIS dataset frameworks were used in the remaining studies. Multiple satellites and sensors were preferable to maximize results for modeling forest resilience. To estimate resilience, ecological attributes (above-ground biomass, tree-ring, and basal area increments) and remote-sensing derived indicators (vegetation indices, forest cover changes, deforestation rates, and forest productivity) were analyzed using conventional statistical tests or machine learning techniques. Studies combined experiments, observations, and process-based models demonstrated better results. Scale and resolution, indicator uncertainty, and data availability were among the constraints reported using RS/GIS. Therefore, a standardized framework for forest resilience assessment incorporating field observation with RS/GIS is needed.

DETECT‐AD (Digital Evaluations and Technologies Enabling Clinical Translation for Alzheimer’s Disease): A simulated anti‐amyloid clinical trial using digital biomarkers as primary outcome measures

AbstractBackgroundEarly detection and precise monitoring of cognitive and functional decline in persons with Alzheimer’s Disease (AD) in clinical trials is a high priority. Unfortunately, early detection and monitoring of the subtle and slow changes of disease with conventional cognitive testing and self‐report questionnaires has been fraught with poor sensitivity and lack ecological validity. Digital biomarkers using ambient sensing technologies may afford a more effective approach to conducting trials. Remaining to be established is the ability of this approach to fundamentally improve early AD treatment response readout in a formal clinical trial setting. A simulated clinical trial (DETECT‐AD: ClinicalTrials.gov, NCT05385913) is being conducted to determine how well continuously assessed, home‐based digital biomarkers may detect clinically meaningful changes in individuals with changing amyloid (Aβ) burdens in pre‐symptomatic AD.MethodClinically prodromal AD patients with estimable rates of AD progression based on Aβ Florbetapir‐PET status are enrolled divided n = 50:n = 50 into Aβ “positive” (higher amyloid burden) patients who predictably progress (as if they were receiving placebo) and Aβ “negative” patients progressing more slowly (representing the treatment group). A study‐provided multivitamin mimics RCT conditions and study drug adherence behavior. Baseline standard clinical and biomarker measures are obtained along with digital biomarkers (DB) captured with passive and active sensors (actigraphy, bed mats, IR sensing, e‐pillbox, computing/phone device use, weekly online reporting/cognitive assessment). Primary outcome is the change in a composite DB composed of measures in 4 domains: mobility, cognition, sleep, and socialization. Secondary measures are the relationship of DB to fluid biomarkers (plasma ptau181/217, amyloid, NfL) and MRI/PET measures.ResultTo date (01/16/2023), 46/100 have been enrolled with mean(SD): follow‐up = 27.0(7.9) weeks (no dropout); age = 78(6.6); 63% women; MoCA = 25.5(2.3); PET SUVR = 1.09(0.20), range: 0.850‐2.07. Exemplary baseline digital biomarker metrics are presented in the Table. Preliminary data shows an inverse Aβ‐SUVR correlation with mean steps/day (r = ‐.41, p = .012) and a positive correlation of MoCA with computer use (r = .61; p = .036).ConclusionHome‐based continuous capture of multi‐domain DBs is feasible in a clinical trial setting and may yield early meaningful indicators of clinically relevant changes in older adults with pre‐AD dementia. Further evidence will evolve as sample sizes and longitudinal follow‐up increases.

Evaluation of Metabarcoding Methods for Plant Disease Surveillance

Metabarcoding holds great potential for general plant pathogen surveillance by providing an untargeted profile of the host microbiome. However, the standard marker utilized for microbiome analysis of prokaryotes, the 16 rRNA gene, offers limited diagnostic utility as it provides phylogenetic resolution primarily at the genus level, and universal primers often co-amplify plant DNA. Here, we evaluated two recently published universal primer sets targeting the DNA gyrase and RNA polymerase ß subunit genes ( gyrB and rpoB, respectively), relative to a plant discriminating 16S primer set (799F/1115R), as disease surveillance tools. Comparative analysis of a mock bacterial community, as well as naturally infected citrus variegated chlorosis samples, indicated that the gyrB method displayed optimal performance in the amplification of DNA across a broad taxonomic spectrum of plant-pathogenic bacteria, providing resolution at the species and, in some cases, subspecies levels. It also generated high-quality datasets with minimal to no co-amplification of plant DNA, outperforming the rpoB and 16S assays in these regards. Further evaluation revealed that the gyrB method displayed an overall linear trend in the detection of several diverse bacterial pathogens; however, it was at least an order of magnitude less sensitive than a standard real-time PCR assay. Finally, we demonstrate the potential of this method to disentangle a mixed population of Pantoea spp. associated with a rice-bacterial blight outbreak and identify putative novel pathogens that would otherwise be overlooked with conventional PCR-based tests. This work represents steps toward establishing a robust, untargeted metabarcoding method for general plant disease surveillance. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Digitized Biomarkers Utilizing Human‐Computer Interaction Sensing Technology for Early Auxiliary Diagnosis of Alzheimer’s Disease

AbstractBackgroundAlzheimer’s disease (AD) is a progressive and debilitating neurological disorder that impacts millions of individuals globally. Prompt and accurate detection and diagnosis of Alzheimer’s disease are pivotal for providing effective care and management to patients. However, early identification of the disease remains challenging due to the complexity of diagnostic procedures and the similarity of symptoms with age‐related cognitive decline. With the world transitioning towards a more digital‐focused environment, there is an increasing potential to utilize human‐computer interaction technologies to aid in the early detection of Alzheimer’s disease.MethodWe recruited 40 healthy individuals, 40 patients with mild cognitive impairment (MCI), and 40 patients with early AD. By incorporating fusion perception‐enhancing technologies into intelligent identification devices, such as eye‐tracking and body motion detection, peripheral modal biometric information can be gathered from subjects.ResultThe study found that in human‐computer interaction experiments using eye‐tracking, the patients with early AD showed significantly longer completion times and free rates of eye motion and movement trajectory than the normal group and those with MCI. The correlation between eye motion trajectory and movement trajectory was notably lower as compared to the normal group and the MCI group. During the human‐computer interaction physical movement experiment, the AD group recorded lower target accuracy rate and screen click rate as compared to the normal group and patients with MCI. Similarly, in the human‐computer interaction clock drawing experiment, the AD group demonstrated longer completion time and pen‐up thinking time, as well as lower clock drawing scores. Furthermore, the total completion time of human‐computer interaction tasks was notably shorter as compared to conventional cognitive screening tests. In conclusion, peripheral biomarkers obtained from the aforementioned human‐computer interaction task were analyzed using machine learning techniques, resulting in the identification of early‐stage Alzheimer’s disease with a classification accuracy of 91.1%.ConclusionHence, this non‐invasive and accurate technique may prove instrumental in identifying potential cognitive deficits associated with this disease while also being widely applicable for screening early AD.

Analysis Of Determinant Factors Employee Performance Of Directorate General Of Intellectual Property Rights Republic Of Indonesia

Examining the effects of leadership style, work motivation, work discipline, and job happiness on employees' performance is the goal of this study. The study's population, which totaled 100 people, was made up of workers. The required sample is gathered using a convenience sampling technique. Facts gathered directly from survey respondents are considered primary data. It is here retrieved directly by responding to a questionnaire. The scale that is widely used in the construction of questionnaires is the Likert scale. The data analysis methods employed in this study are hypothesis testing, conventional assumption testing, and data quality testing (validity and reliability testing). Workplace discipline has a significant impact on how well people perform, according to research findings. Work motivation has a big impact on employee performance. A leader's style does not significantly affect employee performance. Job satisfaction has a substantial impact on employee performance. Work ethics, work motivation, leadership style, and job satisfaction all have a big impact on employee performance. An analysis of the adjusted coefficient of determination (Adjusted R Square) shows that the competence, work discipline, remuneration, organizational culture, and organizational commitment variables may all be utilized to explain the performance variable. Meanwhile, the other difference is influenced by or explained by additional elements outside the purview of this research.

Pathogenic Profile Characteristics and Clinical Risk Factor Analysis of Patients Who Died from Sepsis Combined with Pulmonary Infection by Metagenomic Next-Generation Sequencing.

Sepsis is one of the major diseases that seriously threatens human health, and its incidence and in-hospital morbidity and mortality rates remain high. Applying metagenomic next-generation sequencing (mNGS) technology to analyze the differences in pathogenic profiles and clinical factors in patients surviving and dying from sepsis combined with pulmonary infections provides diagnostic value and application for clinical purposes. Sixty-three BALF samples from patients with sepsis combined with pulmonary infection from Fuqing Hospital Affiliated to Fujian Medical University were collected, and all of them were tested by simultaneous mNGS and conventional microbial combined test (CMT) to compare the pathogenic profiles and clinical indices of patients who survived and died of sepsis combined with pulmonary infection and to further compare the diagnostic differences between mNGS and CMT in patients who survived and died of sepsis combined with pulmonary infection. We analyzed the diagnostic value of mNGS for sepsis combined with pulmonary infection. A total of 141 strains of pathogens were isolated from 63 samples of patients with sepsis combined with pneumonia at suspected infection sites, Klebsiella pneumoniae, Acinetobacter baumannii, and Stenotrophomonas maltophilia are predominant, and higher ApacheII, LAC, P and PT are all risk factors affecting the death of septic patients. Applying the mNGS method to patients with sepsis combined with pneumonia can improve the positive detection rate of pathogenic microorganisms and focus on death-related risk factors such as pathogenic bacteria species as well as clinical laboratory indices, which can guide clinicians to take appropriate measures to treat patients with sepsis and reduce the occurrence of death.