Subjective Threshold Research Articles

Genetics, age, and diet influence gut bacterial communities and performance of black soldier fly larvae (Hermetia illucens)

BackgroundThe gut microbiota of black soldier fly larvae (BSFL, Hermetia illucens) play a crucial role in recycling various organic waste streams. This capability is linked to the presence of a potential common core microbiota in BSFL. However, subjective thresholds for defining core taxa and the difficulty of separating genetic and environmental influences have prevented a clear consensus in the literature. We analysed the gut bacterial communities of two genetically distinct BSF lines (wild type (WT) and lab-adapted line (LD)) raised on ten different diets based on common agricultural by-products and food waste in Southeast Asia.ResultsHigh-throughput 16S rRNA gene sequencing revealed that gut bacterial communities were significantly influenced by genetics (p = 0.001), diet (plant/meat-dominated; p = 0.001), larval age (p = 0.001), and the interactions between all three (p = 0.002). This led us to investigate both common core taxa and lineage-specific core taxa. At a strict > 97% prevalence threshold, four core taxa were identified: Providencia_A_732258, an unclassified genus within the family Enterococcaceae, Morganella, and Enterococcus_H_360604. A relaxed threshold (> 80% prevalence) extended the core to include other potential common core taxa such as Klebsiella, Proteus, and Scrofimicrobium. Our data suggest that Proteus, Scrofimicrobium, Corynebacterium, Vagococcus_B, Lysinibacillus_304693 (all LD), and Paenibacillus_J_366884 (WT) are lineage-specific rather than members of a common core (> 90% prevalence in either LD or WT, with prevalence significantly different between lines (p ≤ 0.05)). Positive correlations were observed between several core genera and larval performance in LD, typical of a highly optimized lab-adapted line. Interestingly, only members of the genus Providencia appeared to play a crucial role in most aspects of larval performance in both genetic lineages.ConclusionOur study demonstrates that the gut microbiota of BSFL is influenced by genetic factors, diet composition, larval age, and their interactions. We identified a distinct lineage-specific core microbiota, emphasizing genetic background’s role. Future studies should apply a standardized high prevalence threshold of at least > 90% unless there is a valid reason for relaxation or sample exclusion. The consistent association of Providencia spp. with larval performance across both genetic lines highlights their crucial role in the BSFL gut ecosystem.

Historical Cohort Differences in Views on Aging in the US: A Trend Toward Longer Midlife but Older Felt Age.

This study compared equal age groups from two cohorts from the Midlife in the United States (MIDUS) study surveyed at different times to characterize societal changes in measures of subjective age and age threshold. Two successive MIDUS cohorts were utilized (1995-1996 and 2011-2014; age range 25-74). Outcomes included subjective age (felt age and desired age) and age threshold. Following multiple imputations of missing data and balancing methods, weighted linear regression measured associations between subjective age outcomes and cohort, sex, and chronological age. Individuals of the later MIDUS cohort reported older felt age and younger desired age in middle age groups (35-64 years old). An increase in age threshold was observed only in older age groups (65+). Possible underlying historical changes in health and societal age stereotypes are explored to explain the observed trend toward older felt age and age threshold, but a younger desired age.

Detrended fluctuation analysis to determine physiologic thresholds, investigation and evidence from incremental cycling test.

Training zones are generally assessed by gas-exchange thresholds (GET). Several mathematical analyses of heart rate variability (HRV) are proposed for indirect GET determination. Our study aimed to investigate the accordance of the detrend fluctuation analysis (DFA α1) for determining GET with first (VT1) and second ventilatory (VT2) thresholds in well-trained subjects. Eighteen female and 38 male sub-elite cyclists performed a maximal incremental cycling test of 2-min stage duration with continuous gas exchange and HR measurements. Power output (PO), Oxygen uptake ( O2) and HR at VT1 and VT2 were compared with DFA α1 0.75 (HRVT1) and 0.50 (HRVT2). Agreements between PO, O2 and HR values were analyzed using Bland-Altman analysis. Large limits of agreement between VT1 and HRVT1 were observed for measures of O2 expressed in mL.min-1.kg-1 [-21.3; + 14.1], HR [39.2; + 26.9] bpm and PO [-118; + 83] watts. Indeed, agreements were also low between VT2 and HRVT2 for measures of O2 [-26.7; + 4.3] mL.min-1.kg-1, HR [-45.5; + 10.6] bpm and PO [-157; + 35] watts. Our results also showed a sex effect: women obtained worst predictions based on DFA α1 than men for HR (p = 0.014), PO (p = 0.044) at VT1 and (p = 0.045), HR (p = 0.003) and PO (p = 0.004) at VT2. There was unsatisfactory agreement between the GET and DFA α1 methods for VT1 and VT2 determination in both sex well-trained cyclists. Trial registrationnumber 2233534 on 2024/03/05 retrospectively registered.

Evaluation of safety and effectiveness of the LISTENT LCI-20PI cochlear implant in prelingually deafened children

ObjectivesThis prospective multicenter clinical trial was to evaluate the safety and effectiveness of a novel cochlear implant (CI) system, the LISTENT LCI-20PI device in prelingually deafened children (<6 years old). DesignThe LCI-20PI CI system was implanted in 70 prelingually deafened children (<6 years old). The median age (interquartile range) at implantation was 3 years old (2–4 years old). The status of the LCI-20PI devices was evaluated through CI device testing and fitting including measurement of electrically evoked compound action potential (ECAP), electrode impedances, subjective thresholds (T levels), and subjective comfort levels (C levels). The safety and effectiveness of the devices were evaluated during 1-year follow-up. The clinical trial registration number is ChiCTR2200067092. ResultsECAPs were successfully measured in 92.8% (64/70) recipients intraoperatively and in 94.3% (66/70) recipients during device activation. Most of the impedances (99.7%) were within normal limits of 0.7–20 kOhm. The median (interquartile ranges) Meaningful Auditory Integration Scale/Infant-Toddler Meaningful Auditory Integration Scale (MAIS/IT-MAIS) was 95% (85%–97.5%) at 12-month post-activation testing. Median (interquartile range) close-set monosyllabic-word recognition score (MRS) and disyllabic-word recognition score (DRS) in children 3–6 years old at 12-month post-activation testing were 86% (77%–97%) and 90% (70%–100%), respectively. ConclusionsThe new developed LCI-20PI CI device proved safe and effective in prelingually deafened children (<6 years old) in the clinical trial. This CI system could be a cost-effective alternative for prelingually deafened children.

The combined effect of transcutaneous electrical nerve stimulation and transcutaneous auricular vagus nerve stimulation on pressure and heat pain thresholds in pain-free subjects: a randomized cross-over trial

BackgroundTranscutaneous electrical nerve stimulation (TENS) is a non-invasive modality that utilizes electrical currents to modulate pain in populations with acute and chronic pain. TENS has been demonstrated to produce hypoalgesic effects in postoperative pain, fibromyalgia, knee osteoarthritis, and healthy subjects. Transcutaneous auricular vagus nerve stimulation (TaVNS) is a non-invasive modality that modulates the vagus nerve by stimulating its auricular branches. The effects of the combination of TENS and TaVNS on producing an analgesic response have not been studied. Considering that TENS and TaVNS both stimulate similar analgesic pathways but through different means of activation, we can hypothesize that a combination of both methods can produce a more pronounced analgesic response. Therefore, the objective of this study is to assess the hypoalgesic effect of a combination of TENS and TaVNS in pain-free subjects.Methods/designThe study will be a simple crossover design conducted at the University of Hartford. Subjects will be recruited from the University of Hartford population via oral communication, digital flyers, and posters on campus. Thirty participants will undergo two sessions in a crossover manner with one week in between. During one session, the participants will receive TENS with active TaVNS and the other session will be a placebo procedure (TENS with placebo TaVNS). The order of these sessions will be randomized. Importantly, the pressure pain threshold (PPT) and heat pain threshold (HPT) assessors will be blinded to the treatment category. For active TaVNS, a frequency of 25 Hz will be applied with a pulse duration of 200 µs. For placebo TaVNS, the intensity will be increased to a sensory level and then decreased to 0 mA. High-frequency TENS of 100 Hz will be applied in both sessions, with a pulse duration of 200 µsec, asymmetrical biphasic square waveform, and intensity of maximal tolerance without pain. TENS and TaVNS will be turned on for 30 min after a baseline measurement of outcomes. TENS and TaVNS will then be turned off, but the electrodes will remain on until completion of post-treatment assessment. Pressure pain threshold, heat pain threshold, blood pressure, oxygen saturation, and heart rate will be tested 4 times: Once pre-intervention, once during intervention, once immediately after the intervention, and once 15 min post-intervention. Statistical analysis of the data obtained will consider a significance level of p < 0.05.DiscussionThis study will provide evidence concerning the combined effects of TENS and TaVNS on pain threshold in pain-free participants. Based on the outcomes, a greater understanding of how TENS and TaVNS, when used in conjunction, can modulate pain pathways.Trial registrationClinicalTrials.gov NCT06361381. Registered on 09 April 2024.

CT Quantification of Interstitial Lung Abnormality and Interstitial Lung Disease: From Technical Challenges to Future Directions.

Interstitial lung disease (ILD) encompasses a variety of lung disorders with varying degrees of inflammation or fibrosis, requiring a combination of clinical, imaging, and pathologic data for evaluation. Imaging is essential for the noninvasive diagnosis of the disease, as well as for assessing disease severity, monitoring its progression, and evaluating treatment response. However, traditional visual assessments of ILD with computed tomography (CT) suffer from reader variability. Automated quantitative CT offers a more objective approach by using computer-based analysis to consistently evaluate and measure ILD. Advancements in technology have significantly improved the accuracy and reliability of these measurements. Recently, interstitial lung abnormalities (ILAs), which represent potential preclinical ILD incidentally found on CT scans and are characterized by abnormalities in over 5% of any lung zone, have gained attention and clinical importance. The challenge lies in the accurate and consistent identification of ILA, given that its definition relies on a subjective threshold, making quantitative tools crucial for precise ILA evaluation. This review highlights the state of CT quantification of ILD and ILA, addressing clinical and research disparities while emphasizing how machine learning or deep learning in quantitative imaging can improve diagnosis and management by providing more accurate assessments, and finally, suggests the future directions of quantitative CT in this area.

Application of Machine Learning Algorithms to Analyze the Clinical Characteristics of NIHL Caused by Impulse Noise and Steady Noise.

Occupational hearing loss of workers exposed to impulse noise and workers exposed to steady noise for a long time may have different clinical characteristics. As of May 2019, all 92 servicemen working in a weapon experimental field exposed to impulse noise for over 1 year were collected as the impulse noise group. As of Dec 2019, all 78 servicemen working in an engine working experimental field exposed to steady noise for over 1 year were collected as the steady noise group. The propensity score matching (PSM) model was used to eliminate the imbalance of age and working time between the two groups of subjects. After propensity score matching, 51 subjects in each group were finally included in the study. The machine learning model is constructed according to pure tone auditory threshold, and the performance of the machine learning model is evaluated by accuracy, sensitivity, specificity, and AUC. Subjects in the impulse noise group and the steady noise group had significant hearing loss at high frequencies. The hearing of the steady noise group was worse than that of the impulse noise group at speech frequency especially at the frequency of 1 kHz. Among machine learning models, XGBoost has the best prediction and classification performance. The pure tone auditory threshold of subjects in both groups decreased and at high frequency. The hearing of the steady noise group at 1 kHz was significantly worse than that of the impulse noise group. XGBoost is the best model to predict the classification of our two groups. Our research can guide the prevention of damage caused by different types of noises.

A Study on the Measurement of Relative Poverty in Developing Countries with Large Populations

Under the goal of global poverty eradication, it has become a forward-looking research aim to establish relative poverty criteria and identify people experiencing relative poverty in countries with different demographic characteristics. This paper introduces a new method to measure the relative poverty standard, which is to use the fuzzy decision tree algorithm to objectively estimate the relative poverty standard. The advantage of this algorithm lies in (1) it not only maintaining the regression idea of measuring absolute poverty, but also emphasizing the nonlinearity when the demand is increasing, which can reflect the change in human needs. (2) It overcomes the division of the traditional method which clearly distinguishes between those experiencing poverty and those who are not by means of a subjective threshold, and it also avoids the subjectivity of the selection of multidimensional indicators. (3) It overcomes the problems of data skewness and extreme value issues that traditional methods have, and can exhibit multi-dimensional characteristics. (4) Most importantly, this method can overcome the gap problem caused by the complex population structure in developing countries with huge populations, and is more adaptable under big data conditions than traditional methods. Taking China as an example, using data from the China Household Finance Survey for validation, the validation results show that the relative poverty standard in China in 2019 can be approximately delineated as 5288.5 RMB; this result is higher than the absolute poverty standard line delineated in China in that year, lower than the relative poverty standard line measured using the proportion method, and it can satisfy the average per capita food, tobacco, and alcohol consumption expenditure of Chinese residents in that year. Thus, compared with other methods, the fuzzy decision tree algorithm can better match the identification of relative poverty in developing countries with large populations.

Metabolic changes assessed by 1H MR spectroscopy in the corpus callosum of post-COVID patients

ObjectiveMany patients with long COVID experience neurological and psychological symptoms. Signal abnormalities on MR images in the corpus callosum have been reported. Knowledge about the metabolic profile in the splenium of the corpus callosum (CCS) may contribute to a better understanding of the pathophysiology of long COVID.Materials and methodsEighty-one subjects underwent proton MR spectroscopy examination. The metabolic concentrations of total N-acetylaspartate (NAA), choline-containing compounds (Cho), total creatine (Cr), myo-inositol (mI), and NAA/Cho in the CCS were statistically compared in the group of patients containing 58 subjects with positive IgG COVID-19 antibodies or positive SARS-CoV-2 qPCR test at least two months before the MR and the group of healthy controls containing 23 subjects with negative IgG antibodies.ResultsAn age-dependent effect of SARS-CoV-2 on Cho concentrations in the CCS has been observed. Considering the subjective threshold of age = 40 years, older patients showed significantly increased Cho concentrations in the CCS than older healthy controls (p = 0.02). NAA, Cr, and mI were unchanged. All metabolite concentrations in the CCS of younger post-COVID-19 patients remained unaffected by SARS-CoV-2. Cho did not show any difference between symptomatic and asymptomatic patients (p = 0.91).DiscussionOur results suggest that SARS-CoV-2 disproportionately increases Cho concentration in the CCS among older post-COVID-19 patients compared to younger ones. The observed changes in Cho may be related to the microstructural reorganization in the CCS also reported in diffusion measurements rather than increased membrane turnover. These changes do not seem to be related to neuropsychological problems of the post-COVID-19 patients. Further metabolic studies are recommended to confirm these observations.

Correlation between neural response telemetry measurements and fitting levels

IntroductionThe neural response telemetry (NRT) is a standard procedure in cochlear implantation mostly used to determine the functionality of implanted device and to check auditory nerve responds to the stimulus. Correlation between NRT measurements and subjective threshold (T) and maximum comfort (C) levels has been reported but results are inconsistent, and it is still not clear which of the NRT measurements could be the most useful in predicting fitting levels. PurposeIn our study we aimed to investigate which NRT measurement corresponds better to fitting levels. Impedance (IMP), Evoked Action Potential (ECAP) threshold and amplitude growth function (AGF) slope values were included in the study. Also, we tried to identify cochlear area at which the connection between NRT measurements and fitting levels would be the most pronounced. Materials and methodsThirty-one children implanted with Cochlear device were included in this retrospective study.IMP, ECAP thresholds and AGF were obtained intra-operatively and 12 months after surgery at electrodes 5, 11 and 19 as representative for each part of cochlea. Subjective T and C levels were obtained 12 months after the surgery during cochlear fitting. ResultsECAP thresholds obtained 12 months after surgery showed statistically significant correlation to both T and C levels at all 3 selected electrodes. IMP correlated with C levels while AGF showed tendency to correlate with T levels. However, these correlations were not statistically significant for all electrodes. ConclusionECAP threshold measurements correlated to T and C values better than AGF slope and IMP. Measurements obtained twelve months after surgery seems to be more predictive of T and C values compared to intra-operative measurements.The best correlation between ECAP threshold and T and C values was found at electrode 11 suggesting NRT measurements at mid-portion cochlear region to be the most useful in predicting fitting levels.

Subjective versus Psychophysical Measures of Chemosensory Alterations following COVID-19

Introduction: Olfactory dysfunction is a common symptom of COVID-19. However, subjective perception of olfactory function does not always correlate well with more objective measures. This study seeks to clarify associations between subjective and psychophysical measures of olfaction and gustation in patients with subjective chemosensory dysfunction following COVID-19. Methods: Adults with persistent COVID-19-associated chemosensory disturbance were recruited for a prospective, longitudinal cohort study at a tertiary care institution. Participants provided subjective measures of olfactory and gustatory function and underwent psychophysical assessment using Sniffin’ Sticks olfactory and Monell gustatory tests. Results: Data analysis (n = 65) showed a statistically significant association between subjective and psychophysical measures of olfaction (p < 0.001). For each one-point increase in subjectively-reported olfactory ability, there is, on average, a 0.11 (95% CI: 0.06, 0.16; p < 0.001) point increase in TDI score while adjusting for age at baseline assessment, sex, and follow-up time. For each one-point increase in subjectively-reported olfactory ability, there is, on average, a 0.04 (95% CI: 0.02, 0.06; p < 0.001) point and 0.05 (95% CI: 0.03, 0.07; p < 0.001) point increase in discrimination and identification scores, respectively, when adjusting for age at baseline assessment, sex, and follow-up time. Conclusion: Subjective olfaction shows a mild to moderate association with psychophysical measures, but it fails to comprehensively assess persistent COVID-19-associated chemosensory deficits. The lack of significant association between subjective olfaction and threshold limits the utility of subjective olfaction in tracking recovery. These findings support the push for more widespread psychophysical chemosensory testing.

Psychometrics of inertial heading perception.

Inertial self-motion perception is thought to depend primarily on otolith cues. Recent evidence demonstrated that vestibular perceptual thresholds (including inertial heading) are adaptable, suggesting novel clinical approaches for treating perceptual impairments resulting from vestibular disease. Little is known about the psychometric properties of perceptual estimates of inertial heading like test-retest reliability. Here we investigate the psychometric properties of a passive inertial heading perceptual test. Forty-seven healthy subjects participated across two visits, performing in an inertial heading discrimination task. The point of subjective equality (PSE) and thresholds for heading discrimination were identified for the same day and across day tests. Paired t-tests determined if the PSE or thresholds significantly changed and a mixed interclass correlation coefficient (ICC) model examined test-retest reliability. Minimum detectable change (MDC) was calculated for PSE and threshold for heading discrimination. Within a testing session, the heading discrimination PSE score test-retest reliability was good (ICC = 0. 80) and did not change (t(1,36) = -1.23, p = 0.23). Heading discrimination thresholds were moderately reliable (ICC = 0.67) and also stable (t(1,36) = 0.10, p = 0.92). Across testing sessions, heading direction PSE scores were moderately correlated (ICC = 0.59) and stable (t(1,46) = -0.44, p = 0.66). Heading direction thresholds had poor reliability (ICC = 0.03) and were significantly smaller at the second visit (t(1,46) = 2.8, p = 0.008). MDC for heading direction PSE ranged from 6-9 degrees across tests. The current results indicate moderate reliability for heading perception PSE and provide clinical context for interpreting change in inertial vestibular self-motion perception over time or after an intervention.

Causal structure learning for high-dimensional non-stationary time series

Learning the causal structure of high-dimensional non-stationary time series can help in understanding the data generation mechanism, which is a crucial task in machine learning. However, current causal discovery methods for high-dimensional non-stationary time series face several challenges, including the inability to effectively capture non-stationarity, failure to ensure acyclicity of causal graphs, and reliance on subjective threshold definitions, leading to suboptimal algorithm performance. To address these challenges, we introduce a novel Causal Structure Learning model for High-dimensional Non-stationary Time Series (CSL-HNTS). Firstly, this model presents a graph neural network to model the non-stationarity of time series. Secondly, it introduces a novel Directed Acyclic Graph (DAG) sampling method that transforms the space of DAGs into a continuous space, enabling the search for causal graphs within this continuous space to ensure acyclicity. Finally, the model proposes an automatic threshold definition method, without prior knowledge, to convert the weighted adjacency matrix into the Boolean adjacency matrix of the causal graph, thereby avoiding time-consuming postprocessing steps. The proposed approach is validated using simulation datasets and two real datasets, and is benchmarked against current state-of-the-art methods and ablation experiments. The results demonstrate a significant improvement over existing methods, highlighting the efficacy of the proposed model.

Composite Plot for Visualizing Aminotransferase and Bilirubin Changes in Clinical Trials of Subjects with Abnormal Baseline Values.

On-treatment excursions of liver laboratory test values in clinical trials involving subjects with underlying liver disease are relevant for the efficacy and safety assessment of drug products and biologics. Existing visualization and analysis tools do not efficiently provide an integrated view of these excursions when baseline liver tests are abnormal. The aim of this study was to develop a composite plot that enables visualization of on-treatment changes in liver test results both as multiples of the upper limit of normal defined by each laboratory's reference population (×ULN) and multiples of the subjects' baseline (×BLN) values. The composite plot approach combines biochemical evaluation for drug-induced severe hepatotoxicity (eDISH) plots sequentially applied to subjects' baseline and peak on-treatment liver test results normalized by ULN and integrates them into a four-panel shift plot of peak on-treatment values normalized by BLN. The composite plot enabled efficient assessment of improvement in liver test values during treatment compared with pretreatment in subjects treated with the investigational drug (or the natural history of placebo-treated subjects) and identified outlier subjects for potential drug-induced liver injury. For studies in subjects with abnormal baseline values, the composite plot has potential application in the assessment of beneficial and concerning on-treatment modifications in liver test values in reference to the individual subject's baseline and population threshold values.

An intraoperative accelerometry and real-time analysis tool for magnetic resonance-guided focused ultrasound thalamotomy.

Magnetic resonance-guided focused ultrasound (MRgFUS) is one of the newest surgical treatments for essential tremor (ET). During this procedure, a lesion is created within the thalamus to mitigate tremor. Targeting is done using a combination of stereotaxy, MR tractography, and sublesional heating, with tremor assessed during the procedure to gauge therapeutic effectiveness. Currently, tremor assessments are done qualitatively, but this approach requires the tremor change to be above a subjective threshold and provides no objective record of surgical tremor progression. Here, the authors present and demonstrate an MR-compatible accelerometer with custom MATLAB analysis code and graphical user interface to record, visualize, and quantify tremor in near real-time. Results can be exported and saved for future review. This method was used in 20 surgeries, with patients experiencing a 50.7% (95% CI -64.1% to -37.3%) improvement in the treated limb per the Clinical Rating Scale for Tremor. This method does not interrupt the surgery and is quantitative. As research on optimizing MRgFUS treatment for ET continues-for example, the refinement of targeting during sublesional sonications-such quantifying and recording of tremor changes will provide rapid and objective feedback.

Mapping winter fallow arable lands in Southern China by using a multi-temporal overlapped area minimization threshold method

ABSTRACT In China, a nation facing farmland scarcity, accurate mapping of winter fallow arable lands is crucial for enhancing crop rotation and land use efficiency. The Dynamic Threshold (DT) method commonly used in phenology and winter fallow land studies often employs empirically set subjective thresholds. This approach tends to uniformly apply a single threshold across diverse vegetation types and geographical regions, neglecting the variations in physiological traits and spatial heterogeneity. This study developed a multitemporal overlapping area minimization threshold method (MOAMT). This approach constructed Normalized difference vegetation index (NDVI) probability density functions for both winter fallow and non-winter fallow arable land across a time series to attain a statistically significant threshold. We use MOAMT and DT methods for winter fallow arable land extraction in southern China, respectively. And then, comparison of identification accuracy between MOAMT and DT has been implemented by using confusion matrix method. Compared to the DT method, MOAMT exhibits better performance. The mapping of winter fallow arable lands highlighted their predominant distribution in the middle and lower reaches of the Yangtze River (MLR-YR) Basin, covering approximately 20.8 million hectares, with potential for development. This study will provide information support for the optimization of planting layouts in China, offering new opportunities for further increasing grain production. While in the sense of research approach, this study indicates the superiority of threshold obtained through statistical probability calibration over empirical universal thresholds for classification accuracy. We advocate for prioritizing threshold calibration in future applications of threshold classification methods.

Endoscopic 5-Aminolevulinic Acid–Induced Fluorescence-Guided Intraparenchymal Brain Tumor Resection—Can the Endoscope Detect More Fluorescence Than the Microscope?

ObjectivesUsing a laboratory-based optical setup we show that 5ALA fluorescence is better detected using the endoscope than the microscope. Furthermore, we present our case series of fully-endoscopic 5ALA guided resection of intraparenchymal tumors. MethodsA Zeiss Pentero® microscope was compared to the Karl Storz Hopkins® endoscope. The spectra and intensity of each blue light source were measured. Quantitative fluorescence detection thresholds were measured using a spectrometer. Subjective fluorescence detection thresholds were measured by 6 blinded neuro-oncology surgeons. Clinical data were prospectively collected for all consecutive cases of fully-endoscopic 5ALA guided resection of intraparenchymal tumors between 2012-2023. ResultsThe intensity of blue light on the sample was greater for the endoscope than the microscope at working distances below 20mm. The quantitative fluorescence detection thresholds were lower for the endoscope than the microscope at both 30/10mm working distances. Fluorescence detection threshold was 0.65-0.80% relative DCM concentration (3.20x10-7 to 3.94x10-7mol/dm-3) for the microscope, 0.40-0.55 % relative concentrations (1.97x10-7 to 2.71x10-7mol/dm-3) for the endoscope at 30mm and 0.15-0.30% relative concentrations (7.40x10-8 to 1.48x10-7mol/dm-3) for the endoscope at 10mm.49 5ALA endoscope-assisted brain tumor resections were carried out on 45 patients (mean age=41, male=28). Greater than 95% resection was achieved in 80% of cases and gross total resection (GTR) in 42%. GTR was achieved in 100% of tumors in non-eloquent locations. There was 1 new neurological deficit. ConclusionThe endoscope provides enhanced visualization/detection of 5ALA-induced fluorescence compared to the microscope. 5ALA endoscopic-assisted resection of intraparenchymal tumors is safe and feasible.

Maximization delays decision-making in acute care nursing

The maximization personality trait refers to the tendency to face decision-making situations along a continuum from exhaustively analysing all the options (maximize) to choosing the one that exceeds a subjective threshold of acceptability (satisfy). Research has revealed the influence of maximizing on decision making, although little is known about its possible role in high risk and high uncertainty situations. A sample of 153 active Spanish nurses, with an average experience of 11 years, completed a maximization questionnaire and responded to written vignettes depicting time-demanding decision making in which three options were offered, representing delayed action, non-action, and immediate action. Two vignettes presented critical situations related to acute care during the COVID-19 pandemic, whilst two vignettes presented non-nursing scenarios. People high in maximization took longer to choose and were more likely to choose non-action. No relationship was found between maximization score and the subjective experience of the person making the choice. Maximization had no significant correlation with years of experience nor perceived expertise. Greater perceived expertise was associated with lower indecision and greater confidence. When participants answered nursing vignettes, they took longer to respond, but chose less delayed action and more immediate action. Our results suggest that maximization plays only a relative role in acute care decision-making in nursing, as compared to contextual variables and expertise. They also support a domain general approach to this personality trait. Findings are consistent with Nibbelink and Reed's Practice-Primed Decision Model for nursing.

Performance Analysis and Clinical Evaluation of an Automated Tool for Plantar Threshold Sensitivity Assessment in a Non-Diabetic Control Population

Abstract Neuropathy is associated with sensation loss in the extremities. Semmes–Weinstein monofilaments are common tools used to assess an individuals' sensation perception. It has long been characterized using hand-applied Semmes–Weinstein monofilaments, however they are subjected to clinician biases and material deviations, and other factors that affect the reproducibility to administer a consistent amount of contact force on the plantar surface. A tool was developed to automate this testing protocol and to more accurately determine an individual's threshold sensitivity at various locations on the plantar surface. Individuals without type 2 diabetes mellitus (DM2) were classed as control subjects. They were evaluated using a hand applied monofilament and the automated tool. The device accuracy of the automated tool was first determined, followed by subject's threshold sensitivity at each location. Twenty-six locations were evaluated per person between 0.35 and 10.0 grams-force. A threshold sensitivity index norm was calculated based on the threshold sensitivity at each location per individual and was plotted against age, body mass index, ankle brachial index, fasting blood sugars, and HbA1c. The device demonstrated accuracy with an absolute error less than or equal to 0.4 grams-force at most locations. Age showed the strongest relationships to sensation loss. As age increased sensitivity to touch decreased. The automated tool was shown to be effective in determining an individual's threshold sensitivity in individuals without DM2. The calculation of the threshold sensitivity index norm was useful to classify sensation loss. The automated tool has the potential to effectively diagnosis neuropathy and document disease progression.

Application of a Combinatorial Vortex Detection Algorithm on 2 Component 2 Dimensional Particle Image Velocimetry Data to Characterize the Wake of an Oscillating Wing

To investigate the vortical wake pattern generated by water flow past an oscillating symmetric airfoil, using experimental velocity fields from particle image velocimetry (PIV), a novel combinatorial vortex detection (CVD) algorithm is developed. The primary goal is to identify and characterize vortices within the wake. Experimental flows introduce complexities not present in numerical simulations, posing challenges for vortex detection. The proposed CVD approach offers a more robust alternative, excelling in both vortex detection and quantification of essential parameters, unlike widely-used methods such as Q-criterion, λ2-criterion, and Δ-criterion, which rely on subjective and arbitrary thresholds resulting in uncertainty. The CVD algorithm effectively characterizes the airfoil wake, identifying and analyzing vortices aligning with the Burgers model. This research enhances understanding of wake phenomena and showcases the algorithm’s potential as a valuable tool for vortex detection and characterization, particularly for experimental fluid dynamics. It provides a comprehensive, robust, and non-arbitrary approach, overcoming limitations of traditional methods and opening new avenues for studying complex flows.