Detection Threshold Research Articles

IDENTIFICATION OF WHITE WINE ADULTERATION WITH APPLE JUICE AND APPLE CIDER USING CYCLIC VOLTAMMETRY ON A SCREEN-PRINTED ELECTRODE AIDED BY CHEMOMETRIC ANALYSIS

An electroanalytical approach has been developed for the identification and quantification of adulteration of white wine with apple juice and apple cider. After addition of LiClO4 as electrolyte and deoxygenation, the sample was analysed via cyclic voltammetry conducted on a screen-printed carbon electrode modified with gold nanoparticles. Cyclic voltammograms (CVs) of white wine samples displayed consistency regardless of their grape variety, mono-, bi- or multi-varietal status as well as geographical origin. In contrast, CVs of apple juice and apple cider exhibited similarities but were distinct from those of white wine. They were particularly characterized by the presence of a cathodic peak at about -0.50V, attributed to sugars and organic acids, predominantly malic acid. Subsequently, cyclic voltammograms were exported into data points and they were subjected to chemometric analysis. Principal Component Analysis effectively grouped samples into two clusters: white wine and apple juice/ apple cider. Class-modelling demonstrated the ability to detect adulteration in white wine samples, with a detection threshold of 5% v/v or lower, contingent upon the adulterant type (apple juice or apple cider). Partial Least Squares regression facilitated quantification of the adulteration level with acceptable accuracy. This approach is both cost-effective and straightforward, necessitating minimal sample preparation.

Pain and small fiber pathology in men with fibromyalgia syndrome.

Small fiber pathology may be involved in the pathophysiology of pain in women with fibromyalgia syndrome (FMS). This prospective single-center case-control study provides detailed pain phenotyping and small fiber pathology data in a cohort of men with FMS on a morphological and functional level. Forty-two men with FMS underwent a comprehensive pain-related interview and neurological examination, a questionnaire and neurophysiological assessment, and specialized small fiber tests: skin punch biopsy, quantitative sensory testing including C-tactile afferents, and corneal confocal microscopy. Data were compared with those of healthy male controls. Men with FMS reported generalized and permanent pain with additional pain attacks and a mostly pressing pain character. Intraepidermal nerve fiber density was reduced at ≥1 biopsy site in 35 of 42 (83%) men with FMS (controls: 32/65, 49%). Compared with male controls, men with FMS had elevated cold (P < 0.05) and warm detection thresholds (P < 0.001) and an increased mechanical pain threshold (P < 0.05) as well as an impairment of C-tactile afferents (P < 0.05). Corneal nerve fiber density was lower in male patients with FMS vs healthy men (P < 0.01). Male FMS patients with pathological skin innervation at ≥1 biopsy site compared with those with normal skin innervation had a higher clinical Widespread Pain Index (P < 0.05) indicating an association between the severity of cutaneous denervation and symptom load. We show a distinct pain phenotype and small nerve fiber dysfunction and pathology in male patients with FMS. These findings may have implications for the diagnosis and management of men with FMS.

Role of intra-individual variation in the detection of thresholds for DFI and for misclassification rates: A retrospective analysis of 14,775 SCSA® tests.

Sperm DNA damage is associated with reduced male fertility after natural conception and intrauterine insemination. However, the impact on in vitro fertilization (IVF) and especially intracytoplasmic sperm injection (ICSI) treatments is still unclear. Few studies have focused on the intra-individual variation in DFI even though it may have an important role to play in terms of detection of thresholds and for misclassification rates. Results for Sperm Chromatin Structure Assay (SCSA®) tests performed for 70 European fertility clinics between January 1st, 2008 and December 31st, 2022 were examined. A small retrospective study included 406 couples receiving their first treatment with IVF or ICSI. These results were then used for a mathematical simulation to investigate the role of intra-individual variation. The large retrospective study included a total of 14,138 diagnostic tests and 637 tests from an IUI study. The distribution of DFI was assessed for the IUI cohort and cohorts of patients attending Sims IVF and Fertility Center Hamburg (FCH). Descriptive analysis of the data was performed regarding time of year, male age, and year. When DFI was above the thresholds of 15 and 25, a significant reduction in ongoing pregnancies after 12weeks of gestation was observed for IVF and ICSI treatments, respectively. For IVF treatments, the pregnancy rate was reduced from 45.1% to 24.6%, odds ratio=2.58 (p=0.004). For ICSI treatments, the pregnancy rate was reduced from 48.6% to 29.6%, odds ratio=2.00 (p=0.032). Intra-individual variation was significantly related to the misclassification rate and the sample size required to identify a threshold. The percentage of patients with a DFI below 15 was 64.8% for the IUI cohort and 51.7% and 41.6% for cohorts of patients attending Sims IVF and FCH, respectively. The median DFI for these cohorts differed significantly and was 11.6, 15.0 and 17.2, respectively. DFI shows a seasonal variation, and increases with male age. During the past 15 years, the median DFI has increased by 0.05% per year (p=0.02). Ongoing pregnancy rates are reduced significantly for both IVF and ICSI treatments when DFI is above the thresholds of 15 and 25, respectively. The misclassification rate and the required sample size increase with increasing intra-individual variation. Couples with a DFI above 15 are more likely to experience failed assisted reproductive technology(ART) cycles. DFI appears to have increased during the past 15 years.

Investigating Defect Detection in Advanced Ceramic Additive Manufacturing Using Active Thermography

Additive manufacturing of advanced materials has become widespread, encompassing a range of materials including thermoplastics, metals, and ceramics. For the ceramics, the complete production process typically involves indirect additive manufacturing, where the green ceramic part undergoes debinding and sintering to achieve its final mechanical and thermal properties. To avoid unnecessary energy-intensive steps, it is crucial to assess the internal integrity of the ceramic in its green stage. This study aims to investigate the use of active thermography for defect detection. The approach is to examine detectability using two benchmarks: the first focuses on the detectability threshold, and the second on typical defects encountered in 3D printing. For the first benchmark, reflection and transmission modes are tested with and without a camera angle to minimize reflection. The second benchmark will then be assessed using the most effective configurations identified. All defects larger than 1.2 mm were detectable across the benchmarks. The method can successfully detect defects, with transmission mode being more suitable since it does not require a camera angle adjustment to avoid reflections. However, the method struggles to detect typical 3D-printing defects because the minimum defect size is 0.6 mm, which is the size of the nozzle.

Effects of Er:YAG laser debonding on changes in the properties of dental zirconia.

To investigate changes in the optical and mechanical properties of novel zirconia ceramics applied in dentistry after Er:YAG laser debonding and to evaluate the feasibility and value of reusing zirconia restorations debonded by an Er:YAG laser. Four types of zirconia ceramics were investigated: self-glazed zirconia (SGZ), 3Y-TZP, 4Y-PSZ and 5Y-PSZ. Forty rectangular (25 mm*8 mm*1.5 mm) specimens were fabricated for each zirconia type, and a total of 160 specimens were manufactured. The zirconia specimens were divided into four subgroups according to the applied Er:YAG laser debonding process: the control group, 4 W laser group, 5 W laser group, and 6 W laser group. For each subgroup, 10 specimens were subjected to color tests (color difference (△E) and transparency parameter (TP) tests) and subsequent mechanical tests (flexural strength (FS), elastic modulus (EM), Vickers hardness (VH) and surface roughness (Ra) tests). The △E, TP, FS, EM, VH and Ra values were measured and calculated. One random sample from each subgroup was observed by SEM. Statistical analyses were performed by one-way ANOVA followed by post hoc comparisons (α = 0.05). The △E and TP values after Er:YAG laser debonding were not significantly different among the subgroups (P > 0.05). However, the 6 W laser group had the highest △E and lowest TP. The ranges of changes in △E and TP were below the clinically detectable threshold (△E = 1.2, △TP = 1.33). In terms of the mechanical properties, there were no significant differences in the FS, EM, VH or Ra among the subgroups. No obvious microcracks were detected on the surfaces of the zirconia specimens during SEM. Er:YAG laser debonding does not obviously affect the optical or mechanical properties of novel zirconia ceramics in dentistry. Moreover, it is potentially feasible and valuable to reuse zirconia restorations after Er:YAG laser debonding.

CRISPR-Cas13a-Based Lateral Flow Assay for Detection of Bovine Leukemia Virus

Bovine leukemia virus (BLV) is the causative agent of enzootic bovine leukosis (EBL), which presents worldwide prevalence. BLV caused substantial economic loss in China around the 1980s; then, it could not be detected for some time, until recently. Due to its latent and chronic characteristics, the efficient and accurate detection of BLV is of utmost significance to the timely implementation of control measures. Therefore, this study harnessed the recombinase-aided amplification (RAA), clustered regularly interspaced short palindromic repeats (CRISPR)-associated protein 13a (Cas13a) technology, and lateral flow (LF) strips to develop an efficient method for detection of BLV. In this method, isothermal amplification of the targeted pol gene is performed at 37 °C with a detection threshold of 1 copy/µL, and the procedure is completed in 100 min. This assay demonstrated high selectivity for BLV, as indicated by the absence of a cross-reaction with six common bovine pathogens. Remarkably, 100 blood samples from dairy cows were tested in parallel with a conventional quantitative polymerase chain reaction (qPCR) and this method and the results showed 100% agreement. Furthermore, this method exhibited good repeatability. In conclusion, in this study, we established a sensitive and specific method for BLV detection, which shows promise for application in BLV surveillance.

Abstract B006: Qualitative research study on the use of minimal residual disease as an intermediate endpoint in multiple myeloma clinical trials in Saudi Arabia

Abstract Introduction: The U.S. Food and Drug Administration has recently considered minimal residual disease (MRD) as an acceptable accelerated approval endpoint in multiple myeloma (MM). Meta-analysis studies have shown the clinical benefit of MRD negativity in certain hematological cancers such as MM. Objectives: This qualitative research study, with a unique focus on the Saudi context, aims to assess the opinions and experiences of hematology and oncology specialists and consultants in Saudi Arabia. The study is particularly interested in their views on the use of MRD as an intermediate endpoint in early-phase clinical trials for fast-track drug approval by the Saudi Food and Drug Authority in the context of multiple myeloma. This includes assessing the use of MRD in both newly diagnosed and relapsed/refractory MM. The secondary objective is to gather information about the feasibility and availability of sensitive MRD detection methods in real-world medical practice and clinical trials in Saudi Arabia. Study Design: The study will involve interviewing 30 registered male or female physicians specialized in hematology and oncology in Saudi Arabia. The physicians will be included in the study using purposive sampling methods. The study will collect the physicians’ opinions and experiences about MRD. The interviews will be conducted through a single focus group and several face-to- face interviews or performed online, using ZOOM. Participants should have more than one year of experience post-residency or post-fellowship training. The predetermined set of semi- structured questions will cover topics such as the definition of MRD, its clinical and research significance, MRD detection thresholds, duration of MRD negativity, and its correlation with other clinical endpoints, such as progression-free survival and overall survival. The interviews will be conducted by scientific oncology and hematology evaluation experts at the Saudi Food and Drug Authority, who play a crucial role in this study. The study will consist of 5–10 semi- structured one-to-one interviews and focused group discussions of as few as four participants. Before starting any interview, participants will complete consent forms, including the study’s goals and who will conduct the study. Qualitative data will be prepared and analyzed by an expert in data analysis, ensuring the highest research standards. The results will be presented using descriptive and interpretive methods. Citation Format: Albandari A Alnasser, Tariq H Alqurayshah. Qualitative research study on the use of minimal residual disease as an intermediate endpoint in multiple myeloma clinical trials in Saudi Arabia [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B006.

Abstract B007: A qualitative research study on hematology and oncology consultants’ experiences and opinions on using minimal residual disease (MRD) as a fast-track approval endpoint in early-phase clinical trials in multiple myeloma in Saudi Arabia

Abstract Introduction: The U.S. Food and Drug Administration recently considered the minimal residual disease (MRD) as an acceptable accelerated approval endpoint in multiple myeloma (MM). The data from the meta-analysis studies established the clinical benefit of MRD negativity in certain hematological cancers such as MM. Objectives: The primary objective of this qualitative research study is to assess hematology and oncology consultants’ opinions and experiences on the adequacy of using minimal residual disease (MRD) as an intermediate endpoint in early- phase clinical trials in multiple myeloma (MM) for fast-track approval of drugs and biological products in the Saudi Food and Drug Authority. That may include using MRD in MM in both settings: newly diagnosed and relapsed/refractory MM. The secondary objective is to gather information about the feasibility and availability of sensitive methods for detecting MRD in the context of real-world medical practice and clinical trials in Saudi Arabia. Study Design: The study design is a qualitative approach to interviewing 30 registered male, or female physicians specialized in hematology and oncology in Saudi Arabia. The interviews will be conducted in two ways: a single focus group and several face-to-face interviews. The participants should have more than 1 year of experience post-fellowship training. The participants will be invited for an interview via email or phone. A predetermined set of semi-structured questions is to be asked in the same order to each participant. The topic of questions will include the definition of MRD, clinical and research significance of MRD, MRD detection thresholds (e.g., 10^-5 vs. 10^-6), duration of MRD negativity at the complete response, correlation with other clinical endpoints such as progression-free survival (PFS) and overall survival (OS). The interviews will be conducted by scientific oncology and hematology evaluation experts at the Saudi Food and Drug Authority who have considerable experience in engaging in personal discussion. This qualitative study has about 5–10 semi-structured one-to-one interviews of hematology and oncology consultants performed at a convenient time for each doctor. Moreover, the discussions in focus groups can be as small as four participants. Qualitative data will be prepared and analyzed by an expert in data analysis. Citation Format: Tariq Hassan Alqurayshah, Albandari Alnasser, Tariq Alqurayshah. A qualitative research study on hematology and oncology consultants’ experiences and opinions on using minimal residual disease (MRD) as a fast-track approval endpoint in early-phase clinical trials in multiple myeloma in Saudi Arabia [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B007.

Spatiotemporal Evolution of Marine Heatwaves Globally

Abstract The spatiotemporal evolution of marine heatwaves (MHWs) is explored using a tracking algorithm called Ocetrac that provides objective characterization of MHW spatiotemporal evolution. Candidate MHW grid points are defined in detrended gridded sea temperature data using a seasonally varying temperature threshold. Identified MHW points are collected into spatially distinct objects using edge detection with weak sensitivity to edge detection and size percentile threshold criteria at each timestep. Ocetrac then uses 3D connectivity to determine if these objects are part of the same event, but Ocetrac only defines the full MHW event after all timesteps have been processed, limiting its use in predictability studies. Here Ocetrac is applied to monthly satellite sea surface temperature data from September 1981 through January 2021. The resulting MHWs are characterized by their intensity, duration, and total area covered. The global analysis shows that MHWs in the Gulf of Maine and Mediterranean Sea are spatially isolated, while major MHWs in the Pacific and Indian Oceans are connected in space and time. The largest and most long lasting MHW using this method lasts for 60 months from November 2013 to October 2018, encompassing previously identified MHW events including those in the Northeast Pacific (2014-2015), the Tasman Sea (2015-2016, 2017-2018), and the Great Barrier Reef (2016).

Distributed Passive Positioning and Sorting Method for Multi-Network Frequency-Hopping Time Division Multiple Access Signals

When there are time division multiple access (TDMA) signals with large bandwidth, waveform aliasing, and fast frequency-hopping in space, current methods have difficulty achieving the accurate localization of radiation sources and signal-sorting from multiple network stations. To solve the above problems, a distributed passive positioning and network stations sorting method for broadband frequency-hopping signals based on two-level parameter estimation and joint clustering is proposed in this paper. Firstly, a two-stage filtering structure is designed to achieve control filtering for each frequency point. After narrowing down the parameter estimation range through adaptive threshold detection, the time difference of arrival (TDOA) and the velocity difference of arrival (VDOA) can be obtained via coherent accumulating based on the cross ambiguity function (CAF). Then, a multi-station positioning method based on the TDOA/VDOA is used to estimate the position of the target. Finally, the distributed joint eigenvectors of the multi-stations are constructed, and the signals belonging to different network stations are effectively classified using the improved K-means method. Numerical simulations indicate that the proposed method has a better positioning and sorting effect in low signal-to-noise (SNR) and low snapshot conditions compared with current methods.

DETER-RT: The new INPE-TropiSCO deforestation monitoring system in the Amazon biome

Abstract. The Amazon biome, undergoing significant deforestation, requires robust monitoring systems for effective management and conservation. This study introduces DETER-RT, a novel deforestation detection system that combines the Synthetic Aperture Radar (SAR)-based DETER-R and the TropiSCO systems to enhance detection capabilities using Sentinel-1 satellite data. DETER-RT utilizes a double-threshold technique to optimize the detection of deforestation by balancing detection accuracy and minimizing false positives across different forest types and conditions in the Amazon. The new system modulates detection thresholds based on the proximity of new disturbances to previously detected deforestation, incorporating a dynamic, regionalized threshold adjustment to cater to the variable characteristics of the Amazon’s diverse forest cover. Initial results indicate that DETER-RT provides more timely and accurate warnings compared to existing methods, especially during the fire season, where its performance is less impacted by smoke and haze that typically hinder optical sensors. This approach exemplifies the integration of advanced remote sensing technologies and analytical techniques in environmental monitoring.

Inhomogeneity detection within a head-sized phantom using tracking of charged nuclear fragments in ion beam therapy

Objective.The highly conformal carbon-ion radiotherapy is associated with an increased sensitivity of the dose distributions to internal changes in the patient during the treatment course. Hence, monitoring methodologies capable of detecting such changes are of vital importance. We established experimental setup conditions to address the sensitivity of a monitoring approach based on secondary-fragment tracking for detecting clinically motivated air cavity dimensions in a homogeneous head-sized PMMA phantom in 40 mm depth.Approach.The air cavities were positioned within the entrance channel of a treatment field of 50 mm diameter at three lateral positions. The measured secondary-fragment emission profiles were compared to a reference measurement without cavities. The experiments were conducted at the Heidelberg Ion-Beam Therapy Center in Germany at typical doses and dose rates.Main results.Significances above a detectability threshold of 2σfor the larger cavities (20 mm diameter and 4 mm thickness, and 20 mm diameter and 2 mm thickness) across the entire treatment field. The smallest cavity of 10 mm diameter and 2 mm thickness, which is on the lower limit of clinical interest, could not be detected at any position. We also demonstrated that it is feasible to reconstruct the lateral position of the cavity on average within 2.8 mm, once the cavity is detected. This is sufficient for the clinicians to estimate medical effects of such a cavity and to decide about the need for a control imaging CT.Significance.This investigation defines well-controlled reference conditions for the evaluation of the performance of any kind of treatment monitoring method and its capability to detect internal changes within head-sized objects. Four air cavities with volumes between 0.31 cm3and 1.26 cm3were narrowed down around the detectability threshold of this secondary-fragment-based monitoring method.

Effect of Lingual Nerve Block and Localised Somatosensory Abnormalities in Patients With Burning Mouth Syndrome-A Randomised Crossover Double-Blind Trial.

To investigate the effect of a lingual nerve block on spontaneous pain in patients with burning mouth syndrome (BMS) and to estimate associated somatosensory abnormalities by quantitative sensory testing (QST). A standardised QST battery including cold detection threshold (CDT), warmth detection threshold (WDT), thermal sensory limen (TSL), paradoxical heat sensation (PHS), cold pain threshold (CPT), heat pain threshold (HPT), mechanical pain threshold (MPT), wind-up ratio (WUR) and pressure pain threshold (PPT) was performed at the oral mucosa of the most painful site and intraoral control site in 20 BMS patients, and at the tongue and cheek mucosa in 22 age- and gender-matched healthy controls. The effect of a lingual nerve block on spontaneous burning pain reported by the BMS patients on a 0-10 cm visual analogue scale (VAS) was investigated in a randomised double-blind crossover design using (1 mL) lidocaine (lido) or saline (sal) with an interval of 1 week. The BMS patients were grouped into 'central' and 'peripheral' mechanisms based on the effect of the lingual nerve injections. For each BMS patient, Z-scores and Loss/Gain scores were computed. Differences among groups and sites were analysed using a two-way ANOVA. Differences within group were assessed by paired t-test. The 20 BMS patients were characterised on the basis of VAS changes (ΔLido-ΔSal) as a peripheral BMS subgroup (n = 9) with pain relief more than 1 cm on the VAS and a central BMS subgroup (n = 11) with pain relief less than 1 cm. BMS patients (n = 20) had lower sensitivity to thermal stimuli (i.e., CDT, WDT, TSL, CPT, HPT and PPT) and higher sensitivity to mechanical stimuli (i.e., PPT) compared with controls (p ≤ 0.007). Based on Loss/Gain coding, L1G0 (loss of thermal somatosensory function with no somatosensory gain, 55.0%) was the most frequent coding in the BMS group, which was higher than 11.4% in the control group (p < 0.001). Surprisingly, there was no significant difference between the peripheral and central BMS subgroups with regard to the Z-scores of any of the nine QST parameters (p > 0.097). The results of the lingual nerve blocks demonstrated two distinct phenotypes with either peripheral or central mechanisms but no direct impact on somatosensory function. Overall, somatosensory function in BMS patients seems abnormal in the painful areas compared to matched controls with a conspicuous loss of thermosensory function.

SOHUPDS+: An Efficient One-phase Algorithm for Mining High Utility Patterns over a Data Stream

Existing algorithms for mining high utility patterns over a data stream are two-phase algorithms that are not scalable due to the large number of candidates generation in the first phase, particularly when the minimum utility threshold is low. Moreover, in the second phase, the algorithm needs to scan the database again to find out actual utility for candidates. In this paper, we propose one-phase algorithm SOHUPDS+ to mine high utility itemsets in the current sliding window of the data stream with respect to absolute or relative minimum utility threshold. To facilitate SOHUPDS+, we propose a data structure IUDataListSW+ , which stores and maintains utility and upper-bound values of the items in the current sliding window when sliding window advances. In addition, we propose a transaction merging strategy, called BitmapTransactionMerging , which saves execution time for utility and upper-bound values computations in denser datasets. Moreover, we propose update strategies to utilize mined high utility patterns from the previous sliding window to update high utility patterns in the current sliding window. The results of experiments illustrate that SOHUPDS+ is more efficient than the state-of-the-art algorithms in terms of execution time as well as memory usage in most of the experiments on various datasets.

FaceFinder: A Machine Learning Tool for Identification of Facial Images from Heterogenous Datasets

PurposeTo develop an algorithm to automate the organization of large photo databases using the Haar cascade algorithm for face and eye detection using machine learning tools in Python. DesignRetrospective study for the purposes of clinical tool development. MethodsWe developed an algorithm, termed FaceFinder, to identify front facing images in a large dataset of facial, orthodontal and miscellaneous images. FaceFinder works by detecting the presence of faces and at least two eyes using the Haar cascade. Execution time was recorded using different-sized datasets. A total of 895 images were analyzed by FaceFinder using various thresholds for face and eye detection. Precision, recall, specificity, accuracy, and F1 score were computed by comparison to ground truth labels of the images as determined by a human grader. ResultsUsing medium thresholds for face and eye detection, FaceFinder reached recall, accuracy, and F1 score of 89.3%, 91.6%, and 92.9%, respectively with an execution time per image was 0.91 seconds. Using the highest threshold for face and eye detection, FaceFinder achieved precision and specificity values of 98.3% and 99.2% respectively. ConclusionsFaceFinder is capable of sorting through a heterogenous dataset of photos of patients with craniofacial disease and identifying high-quality front-facing facial images. This capability allows for automated sorting of large databases that can facilitate and expedite data preparation for further downstream analyses involving artificial intelligence and facial landmarking.

Changes in Donor-Derived Cell-Free DNA Before and After Rejection and De Novo DSA Detection in Primary and Repeat Kidney Transplant Recipients.

Serial monitoring of dd-cfDNA and change from baseline can provide meaningful information beyond absolute thresholds. We describe dd-cfDNA trajectories from the baseline before and after acute rejection (AR) and de novo donor-specific antibodies (dnDSA) detection in kidney transplant recipients (KTRs). We included KTR from 02/2019 to 03/2022 with serial dd-cfDNA. The primary analysis compared the time-varying change in dd-cfDNA from baseline in KTR first AR on biopsy [AR] to patients with no-AR on biopsy [no-AR]. 151 KTR were analyzed (AR=56 KTR, no-AR=95 KTRs). In the AR group, dd-cfDNA rose ahead of diagnosis: median rise from baseline was 75% at -3 months, 32% at -2 months, and 325% at -1 month before biopsy. At the time of biopsy, the median rise in dd-cfDNA from baseline was 291% (IQR [interquartile range] 88%-1081%) in AR and 17% (IQR 0%- 194%) in no-AR (p<0.0001). Following treatment, dd-cfDNA values fell in the AR group with a median change from baseline of 94.7% at +1 month, 10.5% at +2 months, and 0% at +3 months. These trajectories were not observed in the no-AR group. Similarly, there were no significant differences in eGFR (estimated glomerular filtration rate) trajectories between the two groups. The median change from baseline to dnDSA detection was 141% (IQR 112%-574%). In KTRs with persistent rejection, median dd-cfDNA was 0.95% (IQR 0.44-1.8) compared to 0.19% (IQR 0.12-0.31) in subjects with no rejection on follow-up (p<0.001). The significant changes from baseline observed before and after AR show how serial monitoring enhances dd-cfDNA utility and allows for earlier identification of evolving injury and monitoring treatment response.

Automatic detection of landslide impact areas using Google Earth Engine

This research introduces an effective framework for automatically detecting landslide impact areas using Google Earth Engine (GEE). The Asia–Pacific region frequently experiences earthquakes and heavy rainfall, leading to frequent landslides that cause loss of life and property. Focusing on landslide catalogues from Taiwan and Japan, the study proposes an automatic landslide detection process using a new method termed multi-bitemporal images (MBTIs), which involves the collection of accumulated changes over time. First, set the event date and collect all images before and after the event. Second, analyse the change pixels in bi-temporal images. Third, review all change pixels to determine the total amount of accumulated changes. This method includes all bi-temporal image sets in the analysis, unlike traditional methods that only use single pairs of bi-temporal images. Clouds are filtered using a pixel-based approach and machine learning techniques. The landslide areas are analysed statistically, and appropriate thresholds for automatic landslide detection are suggested. Using reproducibility, which indicates the percentage of bi-temporal images that detect vegetation loss in mountainous areas, the proposed method achieves a 99% reduction in false positives with a reproducibility requirement of 24.21%, while maintaining true positives at 66.89%. This study analyzed 28–720 bi-temporal image sets from various regions using Sentinel-2 data, revealing that subsequent landslides can be 7–293 times larger than co-seismic landslides. In comparison, subsequent landslides were found to be 3–12 times larger than rainfall-induced landslides. Additionally, the impact of earthquake event on subsequent landslides is 2.3–24.4 times greater than that of rainfall-induced event. By using GEE, the accumulation of hundreds of satellite images can be completed within 15 min, depending on the processing requirements.

Clinical Cues for the Early Diagnosis of Transthyretin-Related Polyneuropathy.

The estimated prevalence of hereditary transthyretin-related familial amyloid polyneuropathy (TTR-FAP) and the small number of known patients in Germany indicate that many patients with TTR-FAP remain undiagnosed, and may instead be classified as "idiopathic." The aim of this study was to identify biomarkers for detecting TTR-FAP among a cohort of patients with idiopathic polyneuropathy (PNP). Clinical evaluations (including the Neuropathy Impairment Score and Neuropathy Disability Score), nerve conduction studies (NCSs), quantitative sensory testing, and autonomic function tests were performed on 23 patients with TTR-FAP and 89 with idiopathic PNP. Discriminant analysis was then performed to identify variables useful for predicting TTR-FAP. Patients with TTR-FAP had paresis of the finger and thumb muscles, and reduced vibration perception and increased pressure pain in the upper and lower extremities. The NCSs showed that action potentials were smaller in the median, ulnar (both motor and sensory), and sural nerves in TTR-FAP. The sensory nerve conduction velocity was also reduced in the ulnar nerve. Autonomic neuropathy was confirmed by reduced sympathetic skin responses in the hands and feet in TTR-FAP. Multivariate discriminant analysis revealed that finger abduction strength, sensory ulnar nerve action potential amplitude, and vibration detection and pressure pain thresholds in the upper extremities were sufficient to correctly identify TTR-FAP in 81.3% of cases. Detailed clinical and neurophysiological investigations of standard parameters in the upper limb may help to identify the otherwise-rare TTR-FAP.

Evaluation of Image Segmentation Methods for In Situ Quality Assessment in Additive Manufacturing

Additive manufacturing (AM), or 3D printing, has revolutionized the fabrication of complex parts, but assessing their quality remains a challenge. Quality assessment, especially for the interior part geometry, relies on post-print inspection techniques unsuitable for real-time in situ analysis. Vision-based approaches could be employed to capture images of any layer during fabrication, and then segmentation methods could be used to identify in-layer features in order to establish dimensional conformity and detect defects for in situ evaluation of the overall part quality. This research evaluated five image segmentation methods (simple thresholding, adaptive thresholding, Sobel edge detector, Canny edge detector, and watershed transform) on the same platform for their effectiveness in isolating and identifying features in 3D-printed layers under different contrast conditions for in situ quality assessment. The performance metrics used are accuracy, precision, recall, and the Jaccard index. The experimental set-up is based on an open-frame fused filament fabrication printer augmented with a vision system. The control system software for printing and imaging (acquisition and processing) was custom developed in Python running on a Raspberry Pi. Most of the segmentation methods reliably segmented the external geometry and high-contrast internal features. The simple thresholding, Canny edge detector, and watershed transform methods did not perform well with low-contrast parts and could not reliably segment internal features when the previous layer was visible. The adaptive thresholding and Sobel edge detector methods segmented high- and low-contrast features. However, the segmentation outputs were heavily affected by textural and image noise. The research identified factors affecting the performance and limitations of these segmentation methods and contributing to the broader effort of improving in situ quality assessment in AM, such as automatic dimensional analysis of internal and external features and the overall geometry.

All-solid-state electrochemical marine sensors based on Na3V2(PO4)3@Na4Zr2Si3O12 solid-state reference electrodes

In this study, Na4Zr2Si3O12 (NZS) solid electrolyte was prepared using an elevated-temperature solid-state method. After heating under supercritical conditions (i.e., 400 °C and 40 MPa), the structure and performance stability of the as-fabricated NZS solid electrolyte were evaluated applying scanning electron microscopy (SEM), X-ray diffraction (XRD), and electrochemical impedance spectroscopy (EIS). A new all-solid-state reference electrode, combining Na3V2(PO4)3(NVP) with NZS (NVP@NZS), was developed, and its electrochemical properties were investigated. The prepared reference electrode demonstrated steady potential in both simulated seawater and buffer solutions across a range of pH values and different salt solutions. The reference electrode, integrated with an Ir/IrO2 working electrode, was used to construct an all-solid-state potentiometric pH sensor. This sensor demonstrated a strong linear related response when measuring the pH of both aqueous solutions and simulated seawater samples. Additionally, an ion sensor based on anodic stripping voltammetry, constructed with the assembled solid-state reference electrode, a platinum counter electrode, and a gold-mercury working electrode, was utilized to measure Cu2+ and S2− ions in both aqueous solutions and simulated seawater samples. These all-solid-state electrochemical sensors, incorporating the NVP@NZS solid-state reference electrode, demonstrated a small detection threshold, excellent linear correlation (R2 > 0.99), and a broad detection range, making them well-suited for chemical analysis in challenging marine environments.