High Sensitivity Research Articles

SpWRKY71 is required for drought tolerance in tomato

ABSTRACT Drought has a profound impact on the growth, development and quality yield of crops. It has been demonstrated that WRKY transcription factors (TFs) play an important role in abiotic stress responses. Previously, numerous studies have documented the functional role of these TFs in a range of plant species. In this study, the SpWRKY71 gene from the wild tomato specie, Solanum. pennellii, was identified and its role in drought stress tolerance was investigated. Subcellular localisation showed that SpWRKY71 is predominantly nuclear in localisation and exhibited elevated transcript levels following PEG6000 and abscisic acid (ABA) treatments. Furthermore, we employed virus-induced gene silencing (VIGS) technology to examine the function of SpWRKY71 in tomato under stress conditions. The plants in which SpWRKY71 had been silenced demonstrated a high sensitivity to drought conditions, exhibiting accelerated and more severe stem and leaf wilting compared to the control plants. The results indicated that SpWRKY71 silencing resulted in a significant exacerbation of drought-induced oxidative damage, as evidenced by an increase in the accumulation of hydrogen peroxide (H₂O₂), superoxide anion (O₂–) and malondialdehyde (MDA) and reduction in the antioxidant enzyme activities and stress-related genes compared to the control. These results indicate that SpWRKY71 plays a significant role in the mechanism of drought stress tolerance in tomato, thereby providing theoretical foundation for the study of the SpWRKY71-mediated drought tolerance in plants.

An isotope dilution-liquid chromatography-tandem mass spectrometry-based candidate reference measurement procedure for the quantification of cortisol in human serum and plasma.

Accurate measurement of serum cortisol is crucial for the diagnosis and management of adrenal disorders. Thus, we have developed a novel isotope dilution-liquid chromatography-tandem mass spectrometry (ID-LC MS/MS)-based candidate reference measurement procedure (RMP) to quantify cortisol in human serum/plasma, offering higher sensitivity and reliability compared to existing RMPs. Quantitative Nuclear Magnetic Resonance spectroscopic (qNMR) methodology has been utilized to assign the absolute content (g/g) and SI-traceability to the reference materials. A novel two-dimensional heart-cut liquid chromatography (LC) approach was implemented for the LC-MS/MS, combined with a supported liquid extraction (SLE) sample preparation protocol. A multi-day validation experiment assessed precision and accuracy. Reproducibility was assessed by comparing procedure results between two independent laboratories, and measurement uncertainty (MU) was evaluated in compliance with current guidelines. The established RMP exhibited high sensitivity, with a quantification range of 0.800-600 ng/mL (2.21-1,655 nmol/L), exceeding the ranges of existing JCTLM-listed RMPs. Intermediate precision was≤2.6 %, and repeatability ranged from 0.9 to 1.9 % across all concentration levels. The relative mean bias ranged from-1.3 to 1.4 % for all matrices and concentration levels. Measurement uncertainties (MU) for cortisol in single measurements were≤2.8 % regardless of the concentration level and sample type. Using the certified International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) reference panel, the equivalence between the candidate RMP and the Joint Committee on Traceability in Laboratory Medicine (JCTLM) listed RMPs (NRMeth 57 and NRMeth 8) was assessed, revealing excellent agreement. This RMP allows for highly sensitive and reproducible determination of cortisol. The performance of the RMP facilitates the standardization of routine assays and ensures traceability in the measurement of individual patient samples.

Diagnostic performance of Mindray CL1200i high sensitivity cardiac troponin I assay compared to Abbott Alinity cardiac troponin I assay for the diagnosis of type 1 and 2 acute myocardial infarction in females and males: MERITnI study.

We examined the 0- and 2-h diagnostic performance of the Mindray high-sensitivity cardiac troponin I (hs-cTnI) assay using two predefined sex-specific 99th percentile upper reference limits (URL) in patients with normal electrocardiograms to aid in the diagnosis of myocardial infarction (MI). Consecutive emergency department patients undergoing serial high-sensitivity cardiac troponin I (hs-cTnI) testing on clinical indication were studied in the 'Mindray hs-cTnI Assay Analytical and Clinical Evaluation for the Diagnosis and RIsk Assessment of Myocardial InfarctIon' (MERITnI) trial (NCT05853042). Plasma hs-cTnI testing was performed using Mindray CL1200i (investigational) and Abbott Alinity (clinical) assays. In 1,556 patients (60.7 % male, 43.3 % White, 45.8 % Black, 34.8 % chest pain), 2.7 % had type 1 MI, 2.7 % type 2 MI, and 21.5 % non-MI myocardial injury. At 0 h for all MIs (n=86), using package insert URLs and Universal Sample Bank (USB) URLs, sensitivities were 83.7 and 93.0 %. At 0/2 h for all MIs with package insert and USB URLs, sensitivities were higher with serial testing, at 95.3 and 97.7 %. Negative predictive value (NPVs) were excellent and similar for both URLs, ranging from 98 to 100 %. Substantial hs-cTnI concentration differences were observed between sex and injury types. Alinity hs-cTnI diagnostic observations were similar for both package insert and USB URLs. The Mindray CL1200i hs-cTnI assay provides the relevant clinical diagnostic information to enable clinicians to deliver cost-effective care for patients to aid in the diagnosis of MI predicated on 0- and 2-h serial testing based on sex-specific 99th percentiles. Novel observations were observed for findings based on different URLs and for females and MI types.

Real-time detection of loosening torque in bolted joints using piezoresistive pressure-sensitive layer based on multi-walled carbon nanotubes reinforced epoxy nanocomposites

Abstract Bolted connections are extensively used in construction and machine design, playing critical roles in various industrial applications. Bolts and screws are, however, prone to loosening or separating due to factors such as shock, vibration, and temperature fluctuations. This self-loosening phenomenon poses a considerable challenge to the reliability of bolted connections, necessitating regular inspections to ensure their safety. In this study, we report a cost-effective technique for monitoring bolted joint loosening torque: BoltWISE (Bolt loosening detection with innovative sensors). BoltWISE employs an innovative sensor element consisting of a piezoresistive, pressure-sensitive layer made from multi-walled carbon nanotube/epoxy nanocomposites coated onto an FR4 substrate, functioning as a washer. Our approach provides high sensitivity, durability, linearity, and fast response times, with minimal hysteresis during both the tightening and loosening processes. Finite-element method simulations were conducted to determine the optimal sensor positions, ensuring fast response during bolt tightening and loosening. Our findings highlight BoltWISE as a promising, low-cost solution for efficiently detecting bolt loosening in industrial environments. Its ease of implementation and fabrication make it a valuable tool for improving safety and maintenance practices across various industries.

Assisting significance of lncRNA ASB16-AS1 in the early detection and prognosis prediction of patients with deep venous thrombosis

BackgroundDeep venous thrombosis (DVT) is a kind of vascular obstruction, that commonly and widely occurs in lower limbs. Due to the lack of obvious symptoms in the early stage, the rate of misdiagnosis and missed diagnosis is high. This study evaluated the expression and significance of lncRNA ASB16-AS1 (ASB16-AS1) in DVT aiming to identify a novel biomarker for its screening and monitoring.MethodsThere were 77 DVT patients and 62 healthy individuals included in this study. Plasma ASB16-AS1 level was evaluated using PCR and compared between DVT and healthy groups. The diagnostic and prognostic values of ASB16-AS1 were assessed with ROC and Cox analyses. The correlation of ASB16-AS1 with patients’ conditions, inflammation, and oxidative stress was evaluated by Spearman correlation analysis.ResultsASB16-AS1 was significantly upregulated in DVT (P < 0.001), which could discriminate DVT patients from healthy individuals with high sensitivity and specificity (AUC of ROC = 0.858). Increased ASB16-AS1 was associated with the incidence of complications (P = 0.033) and especially for pulmonary embolism in patients (P = 0.029). ASB16-AS1 was negatively correlated with prothrombin time (PT, r = -0.763), antithrombin level (AT, r = -0.711), and international normalized ratio (INR, r = -0.764), and showed positive correlation with fibrinogen (FIB, r = 0.793) and D-dimer (D-D, r = 0.731). Additionally, ASB16-AS1 was positively correlated with pro-inflammation cytokines (rIL−6 = 0.853, rIL−10 = -0.836, rhsCRP = 0.787) and pro-oxidative stress factors (rSOD = -0.751, rMDA = 0.842, r8-isoPGF2α = 0.840).ConclusionUpregulated ASB16-AS1 was identified as a diagnostic and prognostic biomarker of DVT and was closely associated with inflammation and oxidative stress during DVT.

Duplex Ultrasound in Evaluating Transplanted Renal Artery In-Stent Restenosis.

To evaluate the diagnosis performance of duplex ultrasound (DUS) in predicting transplanted renal artery (TRA) in-stent restenosis (ISR). In this retrospective study, 112 consecutive patients underwent stenting due to TRA stenosis. DUS were performed within 1 week after stenting for baseline value, and after ≥3 months follow-up for surveillance of ISR. The DUS measurements included peak systolic velocity (PSV) and PSV ratio of renal artery stent to iliac artery (RIR). Receiver operating characteristic (ROC) curves were applied to evaluate the diagnosis performance of DUS parameters in predicting ISR. There were 69 patients (28 men; age, 38.3 ± 15.1 years) who obtained 92 adequate paired DUS and CTA after stenting, which were classified as ISR group (26 TRAs) and non-ISR group (66 TRAs). There was no difference between the two groups for baseline DUS features, including PSVB and RIRB. The late DUS features including stent PSVL (475.5 vs 261.9 cm/s), RIRL (4.10 vs 2.18), and stent PSVL/PSVB (2.72 vs 1.14) were significantly higher in the ISR group than the non-ISR group (all P < .0001). Stent PSVL, RIRL, and PSVL/PSVB demonstrated comparable AUCs in predicting ISR. However, the sensitivity and specificity of PSVL/PSVB in predicting ISR were 92.3 and 93.5%, respectively, demonstrating higher specificity with equivalent sensitivity than PSVL and higher sensitivity with equivalent specificity than RIRL. DUS is an accurate technique to identify TRA-ISR. We suggest all patients should undergo DUS immediately after stenting to establish baseline value and aid in evaluating ISR at late follow-up.

Application of PMS2 and MSH6 double-antibody detection in screening of mismatch repair deficient tumors

Objective: To investigate whether the immunohistochemical results of two markers PMS2 and MSH6 (2-MMR) could replace the four markers MLH1, PMS2, MSH2 and MSH6 (4-MMR) to detect mismatch repair deficient (dMMR) cancers. Methods: A retrospective analysis was conducted with summary of immunohistochemical data from 7 867 cases of gastric cancer, colorectal cancer, endometrial cancer, and other diseases in the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China, from March 2018 to March 2023. The consistency of 2-MMR and 4-MMR results was examined. Microsatellite instability (MSI) and next-generation sequencing (NGS) were performed in patients with specific phenotypes. Results: The Cohen κ values of 2-MMR and 4-MMR in gastric cancer, colorectal cancer, endometrial cancer and other diseases were 0.88, 0.99, 0.88 and 1.00, respectively. The overall consistency, sensitivity and specificity were 0.97, 99.6%, and 100.0%, respectively. Both 2-MMR and 4-MMR could detect the difference between various clinicopathological features. 24 (0.3%) of the 7 867 patients were found to have a special phenotype of MMR, and 6 of them were selected for MSI and NGS molecular testing. MSI analysis showed MSI-H in all cases, while NGS found that 5 of them had MMR-related gene mutations and 1 had POLE p.S297F mutation. Conclusions: Compared with 4-MMR, 2-MMR has high consistency, specificity and sensitivity. The cases with special phenotype only account for extremely low proportion. Therefore, 4-MMR may be replaced with 2-MMR in dMMR screening.

An updated overview of Juvenile systemic sclerosis in a French cohort

BackgroundSystemic sclerosis encompasses a range of disorders characterized by vascular and connective tissue abnormalities. Although rare in pediatrics, juvenile systemic sclerosis (jSSc) is a severe and life-threatening condition that significantly impacts children’s development. This study aimed to provide an overview of JSSc in France over the past decade.MethodsPatients with disease onset before the age of 16 were included following a request for observations sent via email to member practitioners of the SOFREMIP (French pediatric Rheumatology society).ResultsOur study included 18 patients from 8 different French centers. While our cohort exhibited a balanced distribution between limited and diffuse subsets of the disease, we observed a higher prevalence of the diffuse subset in children above the age of 10. Skin induration was the most reported symptom, while Raynaud’s phenomenon was present in 61% of the children at initial clinical evaluation. All children tested positive for antinuclear antibodies, with anti-Scl70 being the most common specificity, even among children with limited cutaneous subsets. Interestingly, we found a high sensitivity of the ACR / EULAR criteria for diagnosing jSSc in our cohort with 83% of patients meeting these criteria, except for 3 children who presented with overlap syndromes. Despite the frequent use of corticosteroids at the onset, no deaths or renal crises were reported. Three patients received treatment with biological agents, specifically Rituximab and Tocilizumab.ConclusionJSSc is a rare but severe disease requiring rapid, specialized, and multidisciplinary care. Further studies are needed to validate proper diagnosis criteria including overlap syndromes and evaluate the use of biotherapies in children.

Voice analysis and deep learning for detecting mental disorders in pregnant women: a cross-sectional study

IntroductionPerinatal mental disorders are prevalent, affecting 10–20% of pregnant women, and can negatively impact both maternal and neonatal outcomes. Traditional screening tools, such as the Edinburgh Postnatal Depression Scale (EPDS), present limitations due to subjectivity and time constraints in clinical settings. Recent advances in voice analysis and machine learning have shown potential for providing more objective screening methods. This study aimed to develop a deep learning model that analyzes the voices of pregnant women to screen for mental disorders, thereby offering an alternative to the traditional tools.MethodsA cross-sectional study was conducted among 204 pregnant women, from whom voice samples were collected during their one-month postpartum checkup. The audio data were preprocessed into 5000 ms intervals, converted into mel-spectrograms, and augmented using TrivialAugment and context-rich minority oversampling. The EfficientFormer V2-L model, pretrained on ImageNet, was employed with transfer learning for classification. The hyperparameters were optimized using Optuna, and an ensemble learning approach was used for the final predictions. The model’s performance was compared to that of the EPDS in terms of sensitivity, specificity, and other diagnostic metrics.ResultsOf the 172 participants analyzed (149 without mental disorders and 23 with mental disorders), the voice-based model demonstrated a sensitivity of 1.00 and a recall of 0.82, outperforming the EPDS in these areas. However, the EPDS exhibited higher specificity (0.97) and precision (0.84). No significant difference was observed in the area under the receiver operating characteristic curve between the two methods (p = 0.759).DiscussionThe voice-based model showed higher sensitivity and recall, suggesting that it may be more effective in identifying at-risk individuals than the EPDS. Machine learning and voice analysis are promising objective screening methods for mental disorders during pregnancy, potentially improving early detection.ConclusionWe developed a lightweight machine learning model to analyze pregnant women's voices for screening various mental disorders, achieving high sensitivity and demonstrating the potential of voice analysis as an effective and objective tool in perinatal mental health care.

Wearable Photonic Artificial Throat for Silent Communication and Speech Recognition.

Advocating for the voices of the disabled, particularly through wearable artificial throats, has garnered significant attention recently. Such devices necessitate sensors with stretchability, high sensitivity, and excellent skin conformability. In this study, an intelligent photonic artificial throat has been developed. It features a sandwich-structured optical fiber sensor encapsulated in Dragon Skin 20, which has an elastic modulus similar to human tissue and is integrated with sensitivity-enhancing rings and fabric for enhanced wearability. With ultrafast response (response time: 10 ms, recovery time: 32 ms) and high sensitivity (1.92 μW/mN), it detects throat area vibrations and muscle contractions, accurately identifying tones in Mandarin, vowels, words, and sentences in English, achieving accurate bilingual detection. It also distinguishes animal sounds (horse neighing and cuckoo's call) and pop songs when mounted on speakers. Furthermore, the artificial throat can accurately detect subtle movements of the head and neck, and by combining nodding actions with the MORSE code, silent communication between individuals has been successfully achieved. Integrated with an advanced artificial intelligence (AI) algorithm, it recognizes tones (97.50%), vowel letters (97.00%), common words (98.00%) and sentences (96.52%), opening prospects for biomedical applications, language education, speech recognition, motion monitoring, and more.

Adapting a Mobile Health App for Smoking Cessation in Black Adults With Anxiety Through an Analysis of the Mobile Anxiety Sensitivity Program Proof-of-Concept Trial: Qualitative Study.

At least half of smokers make a serious quit attempt each year, but Black adults who smoke are less likely than White adults who smoke to quit smoking successfully. Black adults who smoke and have high anxiety sensitivity (an individual difference factor implicated in smoking relapse and culturally relevant to Black adults) are even less successful. The Mobile Anxiety Sensitivity Program for Smoking (MASP) is a smoking cessation smartphone app culturally tailored to Black adults who smoke to increase smoking cessation rates by targeting anxiety sensitivity. This study examined the acceptability and feasibility of the MASP smartphone app following a 6-week pilot test through postintervention qualitative interviews. The MASP smoking cessation app was adapted from an evidence-based app by adding culturally tailored narration and images specific to the Black community, educational content on tobacco use in the Black community and the role of menthol, culturally tailored messages, and addressing tobacco use and racial discrimination. The MASP app was piloted with 24 adults with high anxiety sensitivity who identified as Black, smoked daily, and were not currently using medications or psychotherapy for smoking cessation. At the end of the 6-week pilot test, 21/24 participants (67% female; 95.2% non-Hispanic; mean age=47.3 years; 43% college educated; 86% single or separated) completed an audio-recorded semistructured interview assessing the acceptability and utility of the app, individual experiences, barriers to use, the cultural fit for Black adults who wanted to quit smoking, and identified areas for improvement. Transcribed interviews were coded using NVivo (Lumivero), and then analyzed for themes using an inductive, use-focused process. Most participants (17/21, 81%) had smoked for more than 20 years and 29% (6/21) of them smoked more than 20 cigarettes daily. Participants felt the MASP app was helpful in quitting smoking (20/21, 95%) and made them more aware of smoking thoughts, feelings, and behaviors (16/19, 84%). Half of the participants (11/21, 52%) thought the combination of medication and smartphone app gave them the best chance of quitting smoking. Themes related to participant experiences using the app included establishing trust and credibility through the recruitment experience, providing personally tailored content linked to evidence-based stress reduction techniques, and self-reflection through daily surveys. The culturally tailored material increased app relevance, engagement, and acceptability. Suggested improvements included opportunities to engage with other participants, more control over app functions, and additional self-monitoring functions. Adding culturally tailored material to an evidence-based mobile health (mHealth) intervention could increase the use of smoking cessation interventions among Black adults who want to quit smoking. Qualitative interviews provide mHealth app developers important insights into how apps can be improved before full study implementation and emphasize the importance of getting feedback from the target population throughout the development process of mHealth interventions. ClinicalTrials.gov NCT04838236; https://clinicaltrials.gov/ct2/show/NCT04838236.

Accuracy of Single-dose Transcatheter Aortic Valve Replacement Planning CT Angiography for the Detection of Coronary Artery Disease.

To assess the accuracy of transaortic valve replacement (TAVR) planning CT examinations with a broad detector and a single dose of contrast media to diagnose CAD in a large patient cohort. In this retrospective study, consecutive patients who underwent a dedicated TAVR planning CT examination with a single contrast media dose and a 320-detector row between November 2017 and March 2021 were screened for inclusion. Inclusion criteria were a complete and correctly performed CT exam as well as an invasive coronary angiography (ICA). The scan consisted of 3 series: (1) ECG-triggered calcium score series over the heart. (2) ECG triggered i.v. CM scanning over the heart covering the entire cardiac cycle (0% to 100%). (3) non-ECG triggered scanning over the thoracic-abdominal area including subclavian and femoral arteries. For 2 and 3, a single i.v. CM bolus was used (300mg iodine per kg total body weight of iodixanol, minimum 47mL, maximum 75mL at 100kVp; 90mL at 120kVp). CT-derived CAD was defined as either free of obstructive CAD (<50%) or showing obstructive disease (>50%), further subclassified in moderate stenosis (50%-70%), or severe stenosis (>70%) for each vessel. ICA data were used as standard of reference. We studied 599 patients (78.6±7.5y, 358 men). In ICA, 428 of 2396 coronary vessels (17.8%) demonstrated stenosis of 50% or more. In a per-patient analysis, CTA had a sensitivity of 97.6% and specificity of 84.3% for the detection of patients with at least one vessel with stenosis of 50% or more as well as a NPV and PPV of 97.8% and 82.2%, respectively. In a per-vessel analysis, CTA had 80.8% sensitivity and 88.1% specificity for the detection of stenosis of 50% or more, as well as an NPV and PPV of 95.5% and 59.6%, respectively. Single-dose TAVR planning CT imaging with a wide detector has high sensitivity and NPV to exclude at least moderate CAD in TAVR candidates.

The relationship between oxLDL, sLOX-1, PCSK9 and carotid intima-media thickness in patients with prediabetes and type 2 diabetes

Affection of vascular structures is a known complication in diabetes and prediabetes. Subclinical atherosclerosis begins to develop years before both cardiovascular and cerebrovascular diseases become symptomatic. The aim of this study was to evaluate the relationship between circulating oxidized LDL (oxLDL), soluble lectin-like oxidized LDL (sLOX)-1 and proprotein convertase subtilisin/kexin type 9 (PCSK9) levels and carotid intima-media thickness (CIMT) in patients with prediabetes and T2DM. We recruited 50 T2DM patients with macrovascular complications, 50 T2DM patients with uncomplicated, 50 prediabetes patients, and 50 healthy participants. The common carotid arteries were visualized by high-resolution B-mode carotid artery ultrasonography. Measurement of serum oxLDL, sLOX-1 and PCSK9 levels were assessed by using a commercially available human enzyme-linked immunosorbent assay (ELISA) method. Homeostasis model assessment for insulin resistance (HOMA-IR) was also calculated. Circulating LDL-C, oxLDL, sLOX-1 and PCSK9 levels were significantly higher in T2DM patients with macrovascular complications compared to control group, prediabetes and uncomplicated diabetes. There was significant difference, especially between the controls and the T2DM patients with macrovascular complications. The CIMT increased progressively from control through to T2DM. Both right and left CIMT also showed significant differences between the groups of prediabetes versus uncomplicated diabetes at p < 0.001 showing progressive increase in vascular involvement with progression of disease. There was a positive correlation between PCSK9 levels with LDL-C, oxLDL, sLOX-1, and CIMT. ROC curve analyses showed that PCSK9, as well as oxLDL and LOX-1, was a strong predictor of T2DM with high sensitivity and specificity. In this study, we found that oxLDL, sLOX-1 and PCSK9 levels were significantly associated with carotid intima-media thickness. Our findings suggest that these biomarkers may be used as potential markers for the assessment of cardiovascular risk in patients with prediabetes and type 2 diabetes.

Wearable Self-Powered Pressure Sensors Based on alk-Ti3C2Tx Regulating Contact Barrier Difference for Noncontact Motion Object Recognition.

Wearable self-powered pressure sensors present tremendous potential for object recognition. However, the fluctuated approach speed and distance may compromise the device output, thus affecting the recognition accuracy. Herein, a wearable self-powered pressure sensor with high sensitivity (1.48 VkPa-1), high output (130.5V), and high permeability (259.98 mms-1) are developed where the contact barrier difference and triboelectric charge density of the triboelectric layer surface are dynamically regulated by modulating the surface groups resulting in a lower dielectric loss and higher output. The sensor leverages the polarity difference between the target object and the sensitive material to generate electrical signals at different speeds and distances through an electrostatic induction mechanism. With the assistance of the Transformer model with a self-attention mechanism, an average recognition accuracy of 94.3% is achieved by acquiring sensing signals at different speeds and distances. Simulating the ability of human vision, enables visually impaired people to acclimate to their surroundings more easily and independently and provides a critical advancement in the assistance of the blind with daily life.

High-sensitive MXene and GST-based tunable refractive index sensor for the infrared and visible spectrum from multipurpose sensing applications

In this paper, a sensor with a multi-layered structure based on MXene and chalcogenide which is based on germanium (Ge)-antimony (Sb) telluride (Te) (GST) as an active plasmonic material is designed. The design is simulated in 2D. The design is a general sensor to detect refractive index from 1 to 1.15. Here, the design structure is arranged by placing the analyte on top. The middle metal layer is considered Ag/Au/Al/Cu to identify the effect of the metal layer on overall absorption and reflector. The GST layer is modeled with two distinct states: aGST and cGST, allowing for the analysis of the structure's tunable behavior based on the varying properties of these states. Optimisation and validation for parameters like height, width, and other metals, such as Ag/Au/Cu/Al processes, were conducted to ensure optimal device performance. The proposed refractive index sensor offers a high sensitivity variation ranging from 80 deg RIU−1 to 770 deg/RIU. The bandwidth and resonant area show significant variation between the two states of GST material. In other words, the proposed refractive index sensor can be used as a lab-on-chip biosensor. This proposed sensor provides potential application in the research of biomolecular detection and chemical testing.

Evaluation of deep learning-based scatter correction on a long-axial field-of-view PET scanner.

Long-axial field-of-view (LAFOV) positron emission tomography (PET) systems allow higher sensitivity, with an increased number of detected lines of response induced by a larger angle of acceptance. However this extended angle increases the number of multiple scatters and the scatter contribution within oblique planes. As scattering affects both quality and quantification of the reconstructed image, it is crucial to correct this effect with more accurate methods than the state-of-the-art single scatter simulation (SSS) that can reach its limits with such an extended field-of-view (FOV). In this work, which is an extension of our previous assessment of deep learning-based scatter estimation (DLSE) carried out on a conventional PET system, we aim to evaluate the DLSE method performance on LAFOV total-body PET. The proposed DLSE method based on an convolutional neural network (CNN) U-Net architecture uses emission and attenuation sinograms to estimate scatter sinogram. The network was trained from Monte-Carlo (MC) simulations of XCAT phantoms [ F]-FDG PET acquisitions using a Siemens Biograph Vision Quadra scanner model, with multiple morphologies and dose distributions. We firstly evaluated the method performance on simulated data in both sinogram and image domain by comparing it to the MC ground truth and SSS scatter sinograms. We then tested the method on seven [ F]-FDG and [ F]-PSMA clinical datasets, and compare it to SSS estimations. DLSE showed superior accuracy on phantom data, greater robustness to patient size and dose variations compared to SSS, and better lesion contrast recovery. It also yielded promising clinical results, improving lesion contrasts in [ F]-FDG datasets and performing consistently with [ F]-PSMA datasets despite no training with [ F]-PSMA. LAFOV PET scatter can be accurately estimated from raw data using the proposed DLSE method.

Mutant glycosidases for labeling sialoglycans with high specificity and affinity

Affinity labeling of biomacromolecules is vital for bioimaging and functional studies. However, affinity probes recognizing glycans with high specificity remain scarce. Here we report the development of glycan recombinant affinity binders (GRABs) based on mutant bacterial sialidases, which are enzymatically inactive but preserve stringent specificity for sialoglycan substrates. By mutating a key catalytic residue of Streptococcus pneumoniae neuraminidase A (SpNanA) and Ruminococcus gnavus neuraminidase H (RgNanH), we develop GRAB-Sia and GRAB-Sia3 recognizing total sialoglycans and α2,3-sialosides, respectively. The GRABs exhibit strict substrate and linkage specificity, and tetramerization with streptavidin substantially increases their avidity. The GRABs and tetrameric GRABs (tetra-GRABs) are effective tools for probing sialoglycans in immunoblotting, flow cytometry, immunoprecipitation, and fluorescence imaging. Furthermore, multiplex analysis with tetra-GRABs uncovers spatially distinct sialoglycans in the various mouse organs. This work provides a versatile toolkit for labeling and analyzing sialoglycans with high specificity, sensitivity, and convenience.

Parents’ use of coercive and indulgent feeding practices for children with avid eating behaviour: an Ecological Momentary Assessment study

BackgroundChildren with avid eating behaviour display high food responsiveness, high emotional overeating and low sensitivity to fullness; behaviours which may increase the risk of obesity and are challenging for parents to manage. This study explores the situational predictors of coercive or indulgent feeding practices among parents of children with avid eating behaviours using Ecological Momentary Assessment (EMA).MethodsThe study involved 109 parents of 3-5-year-old children exhibiting avid eating behaviour. Over 10 days, participants completed EMA surveys via a mobile app to report on their mood, stress, feeding goals, and feeding practices during eating occasions. Multilevel modelling was used to assess how parental mood, goals, and the eating context (e.g., meal versus snack, public versus private setting) influenced feeding practices.ResultsParents were more likely to use specific coercive or indulgent feeding practices when experiencing higher stress, when aiming to avoid mealtime conflict, and during meals versus snacks. A negative meal atmosphere and a public setting also increased the likelihood of certain indulgent practices. Notably, parents were more likely to report giving their child food to calm them down or help manage their behaviour when the meal atmosphere was perceived as negative and if they aimed to reduce conflict at the meal. The findings highlight that the context of feeding occasions significantly drives the use of coercive or indulgent feeding practices.ConclusionsParental stress, goals, and the eating context are key determinants of coercive or indulgent feeding practices with children exhibiting avid eating behaviours. Interventions to support parents should consider these dynamic factors, promoting healthier feeding strategies tailored to real-life contexts.

Multi-task AI models in dermatology: Overcoming critical clinical translation challenges for enhanced skin lesion diagnosis.

The surge in AI models for diagnosing skin lesions through image analysis is notable, yet their clinical implementation faces challenges. Common limitations include an over reliance on dermoscopy, lack of real-world applicability when only binary output (e.g. benign/malignant) is offered and low accuracy when faced with rare skin conditions. To address these common constraints associated with limited diagnostic output, and applicability to real-world settings. We developed an All-In-One Hierarchical-Out of Distribution-Clinical Triage (HOT) AI model for skin lesion analysis. Trained on a large dataset of ~208,000 lesion images, our HOT AI model generates three outputs: a hierarchical three-level prediction, an alert for out-of-distribution (OOD) images and a recommendation for dermoscopy to improve diagnostic prediction. Our hierarchical prediction output provides a binary level 1 prediction (benign/malignant), Level 2 prediction of eight possible categories (e.g. melanocytic and keratinocytic) and a more definitive Level 3 prediction from 44 lesion categories. The model produced high sensitivity for Level 1 prediction (88.14% CI: 87.42-88.51); however, significantly lower for Level 3 prediction (63.90%, CI: 62.27-65.61). By relying on all three prediction levels for consensus, Level 1 false-positives were reduced by 20-25%, and false-negatives were decreased by 11-13% of cases. OOD detection was benchmarked against previous landmark models and outperformed comparative models. Lastly, 44% of images were recommended for dermoscopy, and with additional image input, Level 3 sensitivity increased from 48.13% (CI:45.08-49.57) to 52.54% (CI:50.25-55.04). Our HOT-AI model attempts to address common challenges in existing models by combining three tasks in one model to increase accuracy and clinical utility. By providing a more nuanced prediction, and alert for OOD, the model output provides greater explainability of the AI decision process. Prospective clinical testing is required to measure how this additional output impacts user trust, and how the model performs in a real-world setting.

Vibration-based structural damage detection using FRF and modal constant curvature

ABSTRACT This paper presents a new method for locating and quantifying damage in beam-like structures based on the modal constant curvatures and natural frequency extracted from the measurements of the Frequency Response Function (FRF). The modal constant curvature is very effective for localising the damage due to the discontinuity created near the damaged zone. However, in classical vibrational measurement techniques, the discontinuity is confounded by measurement noise. To overcome these limitations, a new index is developed by normalising the curvature of the first fourth vibration mode. The new index gives a value of 1 in the damage location with the elimination of all the values that can distort the results. In order to make the index sensitive for damage depth, quantification charts are developed based on natural frequency ratios. Numerical simulations on a cantilever beam demonstrated the high sensitivity of the proposed method, with errors of under 0.4%. Experimental tests on a cantilever beam confirmed its reliability, with errors of under 3.6%. The method’s low sensitivity to disturbance makes it a robust method for locating and quantifying damage in mechanical structures.