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Effect of surface polishing on roughness, biofilm formation, and biocompatibility of LCD-printed denture base polymer
A longitudinal evaluation of the community-based rehabilitation support programme for Post-COVID-19 condition in Hong Kong
Abstract Eight non-governmental organisations (NGOs) in Hong Kong participated in a one-year pilot programme delivering community-based multidisciplinary rehabilitation services for individuals with Post-COVID-19 Condition (PCC). This study evaluated the programme’s performance across three NGOs, focusing on improvements in patient-reported outcomes and recovery trajectories, and exploring associations with sociodemographic characteristics and service utilisation. A prospective longitudinal survey was conducted between November 2022 and July 2023. Health outcomes were assessed using the Modified COVID-19 Yorkshire Rehabilitation Scale (C19-YRSm) at baseline, immediately post-service, and three months post-service. Sociodemographic and service utilisation data were also collected. Univariate and multivariate logistic regression analyses were performed to identify the potential predictors for significant clinical improvements. Of the 1,655 recruited participants, 623 completed all three assessments. Statistically significant improvements were observed in 16 out of 17 outcome measures regarding symptom severity, functional disability, and overall health scores. Despite these improvements, participants did not fully return to their self-reported pre-COVID-19 health status. Regression analyses revealed that younger participants and those with more severe symptoms prior to service were more likely to exhibit substantial clinical improvements across multiple domains immediately and three months after service utilisation. This community-based PCC multidisciplinary rehabilitation programme in Hong Kong yielded significant improvements in health outcomes, though complete recovery was not achieved. Despite the lack of a control group, our findings underscored the potential effectiveness of person-centred, case-managed, and multidisciplinary rehabilitation packages.
Exploring the link between sensory habituation in everyday life and attentional control abilities
Low-dose chronic exposure to hemin and kynurenine enhances metabolic adaptation in a colorectal cancer cell model
Endophytic Trichoderma and Bacillus isolates suppress Lasiodiplodia theobromae-associated dieback in blueberry under arid coastal conditions
Abstract Blueberry ( Vaccinium corymbosum L.) production represents one of the main pillars of Peruvian agro-exports; however, its sustainability is increasingly threatened by wood-infecting fungal diseases such as dieback. This study was conducted in the Nuevo Proyecto–Olmos area (Lambayeque, Peru), covering a total cultivated area of 176 ha. The objectives were to molecularly identify the fungal pathogens associated with blueberry dieback to perform a preliminary evaluation of the antagonistic potential of endophytic microorganisms. Pathogens were isolated and characterized using morphological and molecular approaches, followed by pathogenicity tests and in vitro efficacy assays of beneficial microorganisms. Disease incidence was dominated by Lasiodiplodia spp., followed by Neopestalotiopsis , Fusarium , and Diaporthe . Lasiodiplodia theobromae was the most prevalent and aggressive species, confirming its association with the observed disease symptoms. For the genus Lasiodiplodia , temperatures between 25 and 30 °C favored mycelial growth, whereas 20 °C and 35 °C limited development. Endophytic isolates of Trichoderma spp. and Bacillus spp. inhibited pathogen mycelial growth by more than 60% under in vitro conditions. These findings highlight the potential of beneficial microorganisms as preliminary candidates for the biological control of wood-infecting fungi in blueberry production systems.
Multimodal contrastive prognostication framework for early neurological outcome prediction in post-cardiac arrest patients
Engineering novel ceramic metal oxides with residual carbon for efficient sequestration of Auramine O from wastewater
Structural and functional dissection of a higher-order oligomerization interface in yeast ceramide synthase
Data mining-based lung cancer diagnostic models and high-risk warning for occupational group
Lymphodepleting preconditioning impairs host antitumor immunity induced by adoptive T cell therapy in mouse models
Abstract Adoptive T cell therapy (ACT) is effective against hematologic cancers, but the mechanisms underlying durable responses in solid tumors remain unclear. We show that adoptively transferred CD8 + T cells that eradicate established murine tumors promote expansion of host CD8 + T cells exhibiting tumor-reactive and tissue-resident phenotypes that contribute to tumor elimination. Mechanistically, tumor necrosis factor (TNF) from transferred cells induces dendritic cell (DC)-dependent expansion of host CD8 + T cells, conferring protection against ACT-resistant tumor cells lacking the targeted antigen. Lymphodepleting preconditioning promotes expansion of transferred cells and primary tumor eradication but impairs host antitumor immunity and abrogates protection against ACT-resistant tumors. In human tumors, increased TNF/DC/CD8 + T cell profiles correlate with favorable ACT responses and improved survival. These findings reveal a TNF-dependent interplay between transferred and host CD8 + T cells underlying durable antitumor immunity that is impaired by lymphodepleting preconditioning in mouse models, suggesting an underappreciated mechanism of ACT resistance.
Retraction Note: An intelligent learning system based on electronic health records for unbiased stroke prediction
A pathogenic Tau mutation drives autophagy-lysosome dysfunction that limits Tau degradation in a model of frontotemporal dementia
Calibrating deep classifiers with dynamic confidence propagation and adaptive normalization
Single-breath-hold 3D abdominal metabolic MRI enables label-free diagnosis of liver cancer
Abstract Chemical exchange saturation transfer (CEST) MRI could detect proteins/peptides, creatine, glucose, and glycogen by labeling their exchangeable amide, amine, and hydroxyl groups respectively, via frequency-selective RF pulses. Without the need for contrast agents or specialized hardware, CEST can be conveniently integrated into existing clinical MR protocols. However, its abdominal application is limited by long scan time (> 5 min) and susceptibility to respiratory motion (60–70% successful scan rate). We develop an ultra-fast 3D CEST MRI approach using spatial-spectral encoding (SSE), enabling a full spectral scan of whole-liver 3D images within a single breath-hold. SSE-CEST employs an efficient z-ω encoding pattern by applying a saturation gradient, followed by a data-driven spatial spectral reconstruction based on the low-rankness of CEST spectra. SSE-CEST is comprehensively evaluated in glycogen phantoms, ex vivo porcine liver, healthy volunteers and patients. Single breath-hold SSE-CEST largely improves successful rate, with a correlation of 0.95 between two repeated scans. SSE-CEST enables the detection of multi-metabolite changes in the liver and pancreas after an overnight fasting, and the dynamic mapping of hepatic glucose metabolism during an oral glucose test. For liver cancer patients, SSE could differentiate active lesions from post-treatment necrosis, featuring superior in-slice spatial resolution and motion-stabilized images. SSE-CEST MRI potentially could facilitate the diagnosis and patient management for liver and other abdominal diseases.
Cloning, expression and characterisation of short-chain dehydrogenase/reductase SDR12 (A0A7I5E7J1) from a parasitic nematode Haemonchus contortus
Advanced physiological maturation of human iPSC-derived cardiomyocytes using an algorithm-directed optimization of defined media components
Wavelet neural network based reduced-ripple DITC of switched reluctance motors in electric vehicles
Abstract Switched Reluctance Motors (SRMs) are potential candidates for high-performance and cost-effective electric drives owing to their simple structure, robustness, fault-tolerant control, high-reliability, and high-efficiency. However, their highly nonlinear magnetic characteristics and doubly salient structure inherently generate considerable torque ripples, which limit their widespread adoption across various industrial applications. This paper introduces an enhanced Direct Instantaneous Torque Control (DITC) scheme augmented with a Wavelet Neural Network (WNN) to minimize torque ripples. The proposed WNN is employed to dynamically compensate for the torque error, hence adjusting the reference torque signal and providing an optimal input for the hysteresis torque controller. This nonlinear mechanism can significantly mitigate the torque ripples, enhance the quality of torque profiles, and maintain the required average torque. A fixed-gain, 3 layers, 2 Neurons, 7 parameters, single WNN is implemented for compensating the torque error, considering the different operating conditions; the Equilibrium Optimizer (EO) algorithm is utilized to train and optimize the network parameters (weights, translation, and dilation of wavelet functions). The simulation and experimental results confirm the superior performance of the proposed DITC-WNN compared to conventional schemes. The proposed DITC-WNN shows experimental reductions in torque ripples of about 28.8% for heavy loads and 16% for light loads over a wide speed range, confirming its suitability for high-performance and reduced ripple SRM drives.