Quantification of Pectobacterium carotovorum subsp. carotovorum in kimchi cabbage using a surface-enhanced Raman scattering platform with silver nanostructures.

Pectobacterium carotovorum subsp. carotovorum (PCC) is a notorious plant pathogen responsible for severe soft rot in kimchi cabbage, which results in significant economic losses. To detect PCC rapidly and accurately in kimchi cabbage, we developed a surface-enhanced Raman scattering (SERS) substrate on which silver nanospheres (AgNSs), nanowires (AgNWs), and nanoseeds are combined on a polydimethylsiloxane (PDMS) platform. The incorporation of Ag nanoseeds creates a higher density of hotspots, which ensures a low detection limit of 1.001 CFU/mL. Electron microscopy and spectroscopic analyses confirmed the successful fabrication of the substrate and its enhanced sensitivity. The SERS substrate exhibits excellent selectivity by effectively distinguishing PCC from other bacteria commonly found in kimchi cabbage. The substrate gives rise to strong Raman signals across PCC concentrations ranging from 101 to 106 CFU/mL. Additionally, a predictive model was developed for accurately detecting PCC in real kimchi cabbage samples, and the results were validated by polymerase chain reaction measurements. A sensitive, selective, and rapid approach for PCC detection in kimchi cabbage that offers a promising improvement over existing methodologies is presented.

Effects of dietary powdered Ficus deltoidea on the growth and health performance of African catfish, Clarias gariepinus production.

Intensive aquaculture causes a decline in the health status of fish, resulting in an increased disease incidence. To counteract this, feed additives have been utilized to improve the growth performance and health of aquaculture species. This work specifically investigates the impact of powdered Ficus deltoidea (FD) on various parameters related to growth, blood parameters, liver and intestine morphology, body proximate analysis, digestive enzymes, antioxidant capacity, and disease resistance to motile Aeromonad Septicemia (MAS) caused by Aeromonas hydrophila infection in African catfish, Clarias gariepinus. Four formulated diets were prepared: T1 (0% FD), T2 (0.5% FD), T3 (0.75% FD), and T4 (1% FD). After 8 weeks, the African catfish's growth performance fed with the T2 diet exhibited a substantial improvement (p < 0.05), along with a remarkably lower (p < 0.05) feed conversion ratio (FCR) when compared to the other treatment groups. Blood parameter analysis revealed notably higher (p < 0.05) levels of white blood cell (WBC), lymphocytosis (LYM), hemoglobin (HGB), albumin (ALB), globulin (GLOB), as well as total protein (TP) in the T2 diet group. While all treatment groups displayed normal intestinal morphology, liver deterioration was observed in groups supplemented with higher FD. The T2 diet group recorded the highest villus length, width, and crypt depth. Protease and lipase levels were also notably improved in the T2 diet group compared to other treatment groups. Additionally, catalase (CAT), glutathione peroxidase (GPx), and superoxide dismutase (SOD) were remarkably elevated in all FD diet groups than in the control group. The expression of immune-related genes, including transforming growth factor beta 1, heat shock protein 90, nuclear factor kappa-B gene, and lysozyme G, was upregulated in all treatments. Overall, the results of this study indicate that incorporating dietary FD at 0.5% concentration in the diet of African catfish may enhance their productivity in intensive farming.

EAV: EEG-Audio-Video Dataset for Emotion Recognition in Conversational Contexts.

Understanding emotional states is pivotal for the development of next-generation human-machine interfaces. Human behaviors in social interactions have resulted in psycho-physiological processes influenced by perceptual inputs. Therefore, efforts to comprehend brain functions and human behavior could potentially catalyze the development of AI models with human-like attributes. In this study, we introduce a multimodal emotion dataset comprising data from 30-channel electroencephalography (EEG), audio, and video recordings from 42 participants. Each participant engaged in a cue-based conversation scenario, eliciting five distinct emotions: neutral, anger, happiness, sadness, and calmness. Throughout the experiment, each participant contributed 200 interactions, which encompassed both listening and speaking. This resulted in a cumulative total of 8,400 interactions across all participants. We evaluated the baseline performance of emotion recognition for each modality using established deep neural network (DNN) methods. The Emotion in EEG-Audio-Visual (EAV) dataset represents the first public dataset to incorporate three primary modalities for emotion recognition within a conversational context. We anticipate that this dataset will make significant contributions to the modeling of the human emotional process, encompassing both fundamental neuroscience and machine learning viewpoints.

Design of fully synthetic signal peptide library and its use for enhanced secretory production of recombinant proteins in Corynebacterium glutamicum.

BACKGROUND: Corynebacterium glutamicum is an attractive host for secretory production of recombinant proteins, including high-value industrial enzymes and therapeutic proteins. The choice of an appropriate signaling peptide is crucial for efficient protein secretion. However, due to the limited availability of signal peptides in C. glutamicum, establishing an optimal secretion system is challenging. RESULT: We constructed a signal peptide library for the isolation of target-specific signal peptides and developed a highly efficient secretory production system in C. glutamicum. Based on the sequence information of the signal peptides of the general secretion-dependent pathway in C. glutamicum, a synthetic signal peptide library was designed, and validated with three protein models. First, we examined endoxylanase (XynA) and one potential signal peptide (C1) was successfully isolated by library screening on xylan-containing agar plates. With this C1 signal peptide, secretory production of XynA as high as 3.2 g/L could be achieved with high purity (> 80%). Next, the signal peptide for ⍺-amylase (AmyA) was screened on a starch-containing agar plate. The production titer of the isolated signal peptide (HS06) reached 1.48 g/L which was 2-fold higher than that of the well-known Cg1514 signal peptide. Finally, we isolated the signal peptide for the M18 single-chain variable fragment (scFv). As an enzyme-independent screening tool, we developed a fluorescence-dependent screening tool using Fluorescence-Activating and Absorption-Shifting Tag (FAST) fusion, and successfully isolated the optimal signal peptide (18F11) for M18 scFv. With 18F11, secretory production as high as 228 mg/L was achieved, which was 3.4-fold higher than previous results. CONCLUSIONS: By screening a fully synthetic signal peptide library, we achieved improved production of target proteins compared to previous results using well-known signal peptides. Our synthetic library provides a useful resource for the development of an optimal secretion system for various recombinant proteins in C. glutamicum, and we believe this bacterium to be a more promising workhorse for the bioindustry.

Effects of Rheum palmatum Root on In Vitro and In Vivo Methane Production and Rumen Fermentation Characteristics.

This study investigated the impact of Rheum palmatum root (RP) for reducing methane and its impact on rumen fermentation and blood metabolites in cattle. Rumen fluid was collected from three cannulated steers (736 ± 15 kg) and mixed with buffer (1:3 ratio) for the in vitro trial. Treatments were divided into control and RP supplement groups (1%, 3%, and 5% of substrates), with each sample incubated at 39 °C for 24 and 48 hours. Methane was measured after incubation, showing a dose-dependent linear decrease after 48 hours. Quadratic changes were observed in total volatile fatty acids, acetate, and butyrate. Additionally, in vitro dry matter digestibility decreased linearly with RP inclusion. In vivo trials involved four Korean steers in a 2 × 2 crossover design over 3 weeks, with treatments including a control group and a group with 3% RP addition. Dry matter intake (DMI) tended to decrease in the RP group compared to the control. Methane emissions (g/kg DMI) were not affected by RP addition. Blood metabolites indicated higher lipase concentrations in the RP group. In conclusion, RP reduced methane production in the in vitro trial but had no effect in the in vivo trial, likely due to adaptation of ruminal bacteria to RP.

Which Dermal Filler is Better for Penile Augmentation for Aesthetic Purposes? A Prospective, Single-Surgeon Study Based on Real-World Experience.

PURPOSE: Several types of dermal fillers have been recently introduced and used for penile augmentation (PA). However, few studies have compared outcomes after the injection of different fillers. This study aimed to compare the clinical outcomes of hyaluronic acid (HLA), polylactic acid (PLA), and polymethyl methacrylate (PMA) filler injections, which are the most commonly used for aesthetic purposes. MATERIALS AND METHODS: This prospective study was conducted for 24 weeks after a filler injection by a surgeon between March 2017 and December 2021. Healthy adult men complaining of small penis were enrolled. Penile girth, satisfaction, and injection-associated adverse events (AEs) were assessed at baseline and 4, 12, and 24 weeks after injection. RESULTS: Of the 301 men who received filler injections, 125, 134, and 42 received HLA, PLA, and PMA fillers, respectively. The augmentation effect was in the order of PMA, HLA, and PLA, respectively, at 24 weeks (PMA vs. HLA, p<0.001; HLA vs. PLA, p=0.006). Satisfaction levels increased significantly at 24 weeks in all groups (each with p<0.001). However, the increase in satisfaction levels was smaller in the PMA group (PMA vs. HLA or PLA, p<0.05, for both penile appearance and sexual life). No serious or systemic AEs were recorded. Filler injection-associated local AEs in the HLA, PLA, and PMA groups occurred in 9 (7.2%), 16 (11.9%), and 6 (14.3%) men, respectively. There was no significant difference in AEs among the groups (p=0.299). CONCLUSIONS: The augmentative effect was greater in the PMA group than in the HLA and PLA groups, whereas the increase in satisfaction levels was smaller in the PMA group. Our study demonstrated the clinical course of different types of fillers and suggests that the filler type should be selected after detailed counseling considering individual characteristics and preferences.

In Vitro Self-Circularization Methods Based on Self-Splicing Ribozyme.

In vitro circular RNA (circRNA) preparation methods have been gaining a lot of attention recently as several reports suggest that circRNAs are more stable, with better performances in cells and in vivo, than linear RNAs in various biomedical applications. Self-splicing ribozymes are considered a major in vitro circRNA generation method for biomedical applications due to their simplicity and efficiency in the circularization of the gene of interest. This review summarizes, updates, and discusses the recently developed self-circularization methods based on the self-splicing ribozyme, such as group I and II intron ribozymes, and the pros and cons of each method in preparing circRNA in vitro.

Efficient Polycrystalline Single-Cation Perovskite Light-Emitting Diodes by Simultaneous Intracrystal and Interfacial Defect Passivation.

Polycrystalline perovskite light-emitting diodes (PeLEDs) have shown great promise with high efficiency and easy processability. However, PeLEDs using single-cation polycrystalline perovskite emitters have demonstrated low efficiency due to defects within the grains and at the interfaces between the perovskite layer and the charge injection contact. Thus, simultaneous defect engineering of perovskites to suppress exciton loss within the grains and at the interfaces is crucial for achieving high efficiency in PeLEDs. Here, 1,8-octanedithiol which is a strong nucleophile, is used to increase the luminescence efficiency of a single-cation perovskite by suppressing non-radiative recombination within the grains of their polycrystalline emitter film as well as at their interface with an anode. The dithiol additive performs a multifunctional role in defect passivation, spatial confinement of excitons, and prevention of exciton quenching at the interface between the perovskite layer and the underlying hole-injection layer. Photoluminescence studies demonstrate that incorporating the dithiol additive significantly enhances the charge carrier dynamics in perovskites, resulting in an external quantum efficiency (EQE) of up to 23.46% even in a simplified PeLED that does not use a hole-injection layer. This represents the highest level of EQE achieved among devices utilizing polycrystalline single-cation perovskites.

In vivo contribution of Cyp24a1 promoter vitamin D response elements.

CYP24A1 is a multifunctional, P450 mitochondrial 24-hydroxylase enzyme that is responsible for catabolism of the most active vitamin D hormone (calcitriol, 1,25(OH)2D3), its precursor (calcifediol, 25(OH)D3), and numerous other vitamin D metabolites at the 23- and 24-carbon positions. In the kidney, Cyp24a1 is induced by 1,25(OH)2D3, induced by FGF23, and potently suppressed by PTH to tightly control the circulating blood levels of 1,25(OH)2D3. This gene is believed to be under the control of a pair of classic promoter proximal (PRO) vitamin D response elements (VDREs) that are aided by distal, downstream (DS) containing enhancers that we identified more recently. The DS1 enhancer cluster was found to respond to PTH and FGF23 actions in a kidney-specific manner. The DS2 enhancer cluster was found to assist in the response of 1,25(OH)2D3 in kidney, as well as other target tissues. Despite this knowledge, the in vivo contribution of the PRO VDREs to gene expression, what drives Cyp24a1 basal expression in the kidney, how FGF23 activates Cyp24a1, and importantly, how PTH suppresses Cyp24a1, all remain unknown. Here in this study, we utilize homology directed CRISPR to mutate one or both VDREs in the PRO region of the Cyp24a1 gene in vivo in the mouse to address these questions. We found that the VDRE (VDRE1) more proximal to the to the transcriptional start site (TSS) is the dominant VDRE of the pair and mutation of both VDREs leads to a dramatic loss of VDR, a reduction of Cyp24a1 gene expression in the kidney, and a near elimination of 1,25(OH)2D3 induction in the intestine. FGF23 induction of Cyp24a1 was reduced with mutation of the PRO VDREs, however, co-treatment of 1,25(OH)2D3 and FGF23 synergistically increased Cyp24a1 expression even with the loss of the PRO VDREs. PTH suppression of Cyp24a1 gene expression was unchanged with PRO VDRE mutations, despite a minor reduction in total pCREB occupancy. Finally, VDR occupancy was dramatically reduced across the DS enhancers in the Cyp24a1 locus after the PRO VDREs mutation. Taken together, our data suggest a cooperative relationship between the DS and PRO enhancers in the regulation of Cyp24a1 by 1,25(OH)2D3 and FGF23, and despite the overall reduction of CREB on the genome it appeared that suppression either does not rely on CREB or that the PRO VDREs are unconnected to PTH suppression altogether. These studies point to the DS1 region as a basal switch for Cyp24a1 expression and help further define the interconnected genomic control of these hormones on vitamin D catabolism.

Development of a Fit-For-Purpose Multi-Marker Panel for Early Diagnosis of Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) suffers from a lack of an effective diagnostic method, which hampers improvement in patient survival. Carbohydrate antigen 19-9 (CA19-9) is the only FDA-approved blood biomarker for PDAC, yet its clinical utility is limited due to suboptimal performance. Liquid chromatography-mass spectrometry (LC-MS) has emerged as a burgeoning technology in clinical proteomics for the discovery, verification, and validation of novel biomarkers. A plethora of protein biomarker candidates for PDAC have been identified using LC-MS, yet few has successfully transitioned into clinical practice. This translational standstill is owed partly to insufficient considerations of practical needs and perspectives of clinical implementation during biomarker development pipelines, such as demonstrating the analytical robustness of proposed biomarkers which is critical for transitioning from research-grade to clinical-grade assays. Moreover, the throughput and cost-effectiveness of proposed assays ought to be considered concomitantly from the early phases of the biomarker pipelines for enhancing widespread adoption in clinical settings. Here, we developed a fit-for-purpose multi-marker panel for PDAC diagnosis by consolidating analytically robust biomarkers as well as employing a relatively simple LC-MS protocol. In the discovery phase, we comprehensively surveyed putative PDAC biomarkers from both in-house data and prior studies. In the verification phase, we developed a multiple-reaction monitoring (MRM)-MS-based proteomic assay using surrogate peptides that passed stringent analytical validation tests. We adopted a high-throughput protocol including a short gradient (<10 min) and simple sample preparation (no depletion or enrichment steps). Additionally, we developed our assay using serum samples, which are usually the preferred biospecimen in clinical settings. We developed predictive models based on our final panel of 12 protein biomarkers combined with CA19-9, which showed improved diagnostic performance compared to using CA19-9 alone in discriminating PDAC from non-PDAC controls including healthy individuals and patients with benign pancreatic diseases. A large-scale clinical validation is underway to demonstrate the clinical validity of our novel panel.

RIPK3 causes mitochondrial dysfunction and albuminuria in diabetic podocytopathy through PGAM5-Drp1 signaling.

BACKGROUND: Receptor-interacting protein kinase (RIPK)3 is an essential molecule for necroptosis and its role in kidney fibrosis has been investigated using various kidney injury models. However, the relevance and the underlying mechanisms of RIPK3 to podocyte injury in albuminuric diabetic kidney disease (DKD) remain unclear. Here, we investigated the role of RIPK3 in glomerular injury of DKD. METHODS: We analyzed RIPK3 expression levels in the kidneys of patients with biopsy-proven DKD and animal models of DKD. Additionally, to confirm the clinical significance of circulating RIPK3, RIPK3 was measured by ELISA in plasma obtained from a prospective observational cohort of patients with type 2 diabetes, and estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio (UACR), which are indicators of renal function, were followed up during the observation period. To investigate the role of RIPK3 in glomerular damage in DKD, we induced a DKD model using a high-fat diet in Ripk3 knockout and wild-type mice. To assess whether mitochondrial dysfunction and albuminuria in DKD take a Ripk3-dependent pathway, we used single-cell RNA sequencing of kidney cortex and immortalized podocytes treated with high glucose or overexpressing RIPK3. RESULTS: RIPK3 expression was increased in podocytes of diabetic glomeruli with increased albuminuria and decreased podocyte numbers. Plasma RIPK3 levels were significantly elevated in albuminuric diabetic patients than in non-diabetic controls (p = 0.002) and non-albuminuric diabetic patients (p = 0.046). The participants in the highest tertile of plasma RIPK3 had a higher incidence of renal progression (hazard ratio [HR] 2.29 [1.05-4.98]) and incident chronic kidney disease (HR 4.08 [1.10-15.13]). Ripk3 knockout improved albuminuria, podocyte loss, and renal ultrastructure in DKD mice. Increased mitochondrial fragmentation, upregulated mitochondrial fission-related proteins such as phosphoglycerate mutase family member 5 (PGAM5) and dynamin-related protein 1 (Drp1), and mitochondrial ROS were decreased in podocytes of Ripk3 knockout DKD mice. In cultured podocytes, RIPK3 inhibition attenuated mitochondrial fission and mitochondrial dysfunction by decreasing p-mixed lineage kinase domain-like protein (MLKL), PGAM5, and p-Drp1 S616 and mitochondrial translocation of Drp1. CONCLUSIONS: The study demonstrates that RIPK3 reflects deterioration of renal function of DKD. In addition, RIPK3 induces diabetic podocytopathy by regulating mitochondrial fission via PGAM5-Drp1 signaling through MLKL. Inhibition of RIPK3 might be a promising therapeutic option for treating DKD.

Improving monitoring network design to detect leaks at hazardous facilities: Lessons from a CO2 storage site.

Exploring the challenges posed by uncertainties in numerical modeling for hazardous material storage, this study introduces methodologies to improve monitoring networks for detecting subsurface leakages. The proposed approaches were applied to the Korea CO2 Storage Environmental Management (K-COSEM) test site, undergoing calibration, validation and uncertainty analysis through hydraulic and controlled-CO2 release tests. The calibration phase involved inter-well tracer and multi-well pumping tests, leveraging the Parameter ESTimation (PEST) model to determine the aquifer flow and solute transport properties of the K-COSEM site. To tackle uncertainties with limited observation data, we adopted Latin Hypercube simulation. Our uncertainty analysis confirmed model accuracy in simulating observed CO2 breakthrough curves. We also explored a probabilistic method to identify the environmental change point (EnCP) through correlation analysis with the distance from the CO2 injection well, revealing a linear trend and pinpointed potential preferential flow pathways by assessing detection probabilities. Evaluating CO2 detection capabilities was crucial for optimizing monitoring well placement, highlighting strategic well selection based on detection probabilities. This study advances managing uncertainties in hydrogeological modeling, underscoring the importance of sophisticated models in designing monitoring networks for hazardous leak detection in complex subsurface conditions.

Influence of preoperative embolisation on resection of brain arteriovenous malformations: cohort study.

PURPOSE: Preoperative endovascular embolisation is a widely used adjunct for the surgical treatment of brain arteriovenous malformations (AVMs). However, whether this improves completeness of AVM resection is unknown, as previous analyses have not adjusted for potential confounding factors. We aimed to determine if preoperative endovascular embolisation was associated with increased rate of complete AVM resection at first surgery, following adjustment for Spetzler-Martin grade items. METHODS: We identified a cohort of all patients undergoing first ever AVM resection in a specialist neurosciences unit in the NHS Lothian Health Board region of Scotland between June 2004 and June 2022. Data was prospectively extracted from medical records. Our primary outcome was completeness of AVM resection. We determined the odds of complete AVM resection using binomial logistic regression with adjustment for Spetzler-Martin grading system items: maximum nidus diameter, eloquence of adjacent brain and the presence of deep venous drainage. RESULTS: 88 patients (median age 40y [IQR 19-53], 55% male) underwent AVM resection. 34/88 (39%) patients underwent preoperative embolisation and complete resection was achieved at first surgery in 74/88 (84%). Preoperative embolisation was associated with increased adjusted odds of complete AVM resection (adjusted odds ratio [aOR] 8.6 [95% confidence interval (95% CI) 1.7-67.7]; p = 0.017). The presence of deep venous drainage was associated with reduced chance of complete AVM resection (aOR 0.18 [95% CI 0.04-0.63]; p = 0.009). CONCLUSIONS: Preoperative embolisation is associated with improved chances of complete AVM resection following adjustment for Spetzler-Martin grade, and should therefore be considered when planning surgical resection of AVMs.

Long-term (10-year) monitoring of transposon-mediated transgenic cattle.

The production of transgenic animals using non-viral methods has raised questions regarding their long-term health and genomic stability. In this study, we evaluated these aspects in transgenic cattle over ten years, using transposon-mediated gene transfer. Our longitudinal analysis included a comprehensive health assessment and whole-genome DNA resequencing. We found no significant alterations in physiological parameters or health complications in transposon-mediated transgenic cattle that exceeded 10 years of age. Genomic analysis revealed that the rates of somatic mutations and copy number variations in transgenic cattle were comparable to those in non-transgenic cattle. Furthermore, structural variants were infrequent, suggesting that transposon-mediated gene insertion did not compromise genomic integrity. These findings highlight the viability of transposon systems for generating transgenic livestock, potentially expanding their applications in agriculture and biotechnology. This study contributes significantly to our understanding of the long-term implications of transgenesis in large animals and supports the safety and stability of this method.

Diagnostic value of a deep learning-based hyoid bone tracking model for aspiration in patients with post-stroke dysphagia.

Objective: Hyoid bone movement is potentially related to aspiration risk in post-stroke dysphagia (PSD) patients but is difficult to assess quantitatively. This study aimed to measure the distance of hyoid bone movement more efficiently and accurately using a deep learning model and determine the clinical usefulness of the model in PSD patients. Methods: This study included 85 patients with PSD within 6 months from onset. Patients were grouped into an aspiration group (n = 35) and a non-aspiration group (n = 50) according to the results of a videofluoroscopic swallowing study. Hyoid bone movement was tracked using a deep learning model constructed with the BiFPN-U-Net(T) architecture. The maximum distance of hyoid bone movement was measured horizontally (H max), vertically (V max), and diagonally (D max). Results: Compared with the non-aspiration group, the aspiration group showed significant decreases in hyoid bone movement in all directions. The area under the curve of V max was highest at 0.715 with a sensitivity of 0.680 and specificity of 0.743. The V max cutoff value for predicting aspiration risk was 1.61 cm. The success of oral feeding at the time of discharge was significantly more frequent when hyoid movement was equal to or larger than the cutoff value although no significant relationship was found between hyoid movement and other clinical characteristics. Conclusion: Hyoid bone movement of PSD patients can be measured quantitatively and efficiently using a deep learning model. Deep learning model-based analysis of hyoid bone movement seems to be useful for predicting aspiration risk and the possibility of resuming oral feeding.

Ambient printing of native oxides for ultrathin transparent flexible circuit boards.

Metal oxide films are essential in most electronic devices, yet they are typically deposited at elevated temperatures by using slow, vacuum-based processes. We printed native oxide films over large areas at ambient conditions by moving a molten metal meniscus across a target substrate. The oxide gently separates from the metal through fluid instabilities that occur in the meniscus, leading to uniform films free of liquid residue. The printed oxide has a metallic interlayer that renders the films highly conductive. The metallic character of the printed films promotes wetting of trace amounts of evaporated gold that would otherwise form disconnected islands on conventional oxide surfaces. The resulting ultrathin (<10 nanometers) conductors can be patterned into flexible circuits that are transparent, mechanically robust, and electrically stable, even at elevated temperatures.

Adaptive ambiguity-aware weighting for multi-label recognition with limited annotations.

In multi-label recognition, effectively addressing the challenge of partial labels is crucial for reducing annotation costs and enhancing model generalization. Existing methods exhibit limitations by relying on unrealistic simulations with uniformly dropped labels, overlooking how ambiguous instances and instance-level factors impacts label ambiguity in real-world datasets. To address this deficiency, our paper introduces a realistic partial label setting grounded in instance ambiguity, complemented by Reliable Ambiguity-Aware Instance Weighting (R-AAIW)-a strategy that utilizes importance weighting to adapt dynamically to the inherent ambiguity of multi-label instances. The strategy leverages an ambiguity score to prioritize learning from clearer instances. As proficiency of the model improves, the weights are dynamically modulated to gradually shift focus towards more ambiguous instances. By employing an adaptive re-weighting method that adjusts to the complexity of each instance, our approach not only enhances the model's capability to detect subtle variations among labels but also ensures comprehensive learning without excluding difficult instances. Extensive experimentation across various benchmarks highlights our approach's superiority over existing methods, showcasing its ability to provide a more accurate and adaptable framework for multi-label recognition tasks.

A phase 4 randomized active-controlled clinical study to compare the efficacy and safety of sustained-release pregabalin with immediate-release pregabalin in type 2 diabetic patients with peripheral neuropathic pain.

AIMS: The objective of this study was to demonstrate that sustained-release (SR) pregabalin is non-inferior to immediate-release (IR) pregabalin in attenuating diabetic peripheral neuropathic (DPN) pain along with patient satisfaction and compliance. METHODS: This was an 8-week, randomized, active-controlled, open-label, phase 4 study. Eligible subjects who had been on IR pregabalin for 4 weeks were randomized to 1:1 ratio to either continue with twice-daily IR pregabalin (75 mg), or to switch to once-daily SR pregabalin (150 mg). Primary efficacy endpoint was the change in visual analogue scale (VAS) scores after 8 weeks of treatment compared to baseline in both SR and IR pregabalin groups. RESULTS: Among 130 randomized subjects, 125 patients were included in full analysis set. For the change in VAS pain score, the least squares (LS) mean were -17.95 (SR pregabalin) and -18.74 (IR pregabalin) and the LS mean difference between both groups was 0.79, with the upper limit of the 95 % confidence interval [-5.99, 7.58] below the pre-specified non-inferiority margin of 9.2 mm. CONCLUSIONS: This study demonstrates that the new once-daily SR pregabalin formulation is not different to the twice-daily IR pregabalin in alleviating DPN pain, indicating its potential as a promising treatment for DPN pain with a comparable safety profile. TRIAL REGISTRATION: ClinicalTrials.gov, NCT05624853.

Iteratively Calibratable Network for Reliable EEG-Based Robotic Arm Control.

Robotic arms are increasingly being utilized in shared workspaces, which necessitates the accurate interpretation of human intentions for both efficiency and safety. Electroencephalogram (EEG) signals, commonly employed to measure brain activity, offer a direct communication channel between humans and robotic arms. However, the ambiguous and unstable characteristics of EEG signals, coupled with their widespread distribution, make it challenging to collect sufficient data and hinder the calibration performance for new signals, thereby reducing the reliability of EEG-based applications. To address these issues, this study proposes an iteratively calibratable network aimed at enhancing the reliability and efficiency of EEG-based robotic arm control systems. The proposed method integrates feature inputs with network expansion techniques. This integration allows a network trained on an extensive initial dataset to adapt effectively to new users during calibration. Additionally, our approach combines motor imagery and speech imagery datasets to increase not only its intuitiveness but also the number of command classes. The evaluation is conducted in a pseudo-online manner, with a robotic arm operating in real-time to collect data, which is then analyzed offline. The evaluation results demonstrated that the proposed method outperformed the comparison group in 10 sessions and demonstrated competitive results when the two paradigms were combined. Therefore, it was confirmed that the network can be calibrated and personalized using only the new data from new users.