Beyond conventional bounds: Surpassing system limits for stereotactic ablative (SAbR) lung radiotherapy using CBCT-based adaptive planning system.

PURPOSE: Online adaptive radiotherapy relies on a high degree of automation to enable rapid planning procedures. The Varian Ethos intelligent optimization engine (IOE) was originally designed for conventional treatments so it is crucial to provide clear guidance for lung SAbR plans. This study investigates using the Ethos IOE together with adaptive-specific optimization tuning structures we designed and templated within Ethos to mitigate inter-planner variability in meeting RTOG metrics for both online-adaptive and offline SAbR plans. METHODS: We developed a planning strategy to automate the generation of tuning structures and optimization. This was validated by retrospective analysis of 35 lung SAbR cases (total 105 fractions) treated on Ethos. The effectiveness of our planning strategy was evaluated by comparing plan quality with-and-without auto-generated tuning structures. Internal target volume (ITV) contour was compared between that drawn from CT simulation and from cone-beam CT (CBCT) at time of treatment to verify CBCT image quality and treatment effectiveness. Planning strategy robustness for lung SAbR was quantified by frequency of plans meeting reference plan RTOG constraints. RESULTS: Our planning strategy creates a gradient within the ITV with maximum dose in the core and improves intermediate dose conformality on average by 2%. ITV size showed no significant difference between those contoured from CT simulation and first fraction, and also trended towards decreasing over course of treatment. Compared to non-adaptive plans, adaptive plans better meet reference plan goals (37% vs. 100% PTV coverage compliance, for scheduled and adapted plans) while improving plan quality (improved GI (gradient index) by 3.8%, CI (conformity index) by 1.7%). CONCLUSION: We developed a robust and readily shareable planning strategy for the treatment of adaptive lung SAbR on the Ethos system. We validated that automatic online plan re-optimization along with the formulated adaptive tuning structures can ensure consistent plan quality. With the proposed planning strategy, highly ablative treatments are feasible on Ethos.

Uncovering the shared neuro-immune-related regulatory mechanisms between spinal cord injury and osteoarthritis.

Adults with spinal cord injury (SCI), a destructive neurological injury, have a significantly higher incidence of osteoarthritis (OA), a highly prevalent chronic joint disorder. This study aimed to dissect the neuroimmune-related regulatory mechanisms of SCI and OA using bioinformatics analysis. Using microarray data from the Gene Expression Omnibus database, differentially expressed genes (DEGs) were screened between SCI and sham samples and between OA and control samples. Common DEGs were used to construct a protein-protein interaction (PPI) network. Weighted gene co-expression network analysis (WGCNA) was used to mine SCI- and OA-related modules. Shared miRNAs were identified, and target genes were predicted using the Human MicroRNA Disease Database (HMDD) database. A miRNA-gene-pathway regulatory network was constructed with overlapping genes, miRNAs, and significantly enriched pathways. Finally, the expression of the identified genes and miRNAs was verified using RT-qPCR. In both the SCI and OA groups, 185 common DEGs were identified, and three hub clusters were obtained from the PPI network. WGCNA revealed three SCI-related modules and two OA-related modules. There were 43 overlapping genes between the PPI network clusters and the WGCNA network modules. Seventeen miRNAs shared between patients with SCI and OA were identified. A regulatory network consisting of five genes, six miRNAs, and six signaling pathways was constructed. Upregulation of CD44, TGFBR1, CCR5, and IGF1, while lower levels of miR-125b-5p, miR-130a-3p, miR-16-5p, miR-204-5p, and miR-204-3p in both SCI and OA were successfully verified using RT-qPCR. Our study suggests that a miRNA-gene-pathway network is implicated in the neuroimmune-related regulatory mechanisms of SCI and OA. CD44, TGFBR1, CCR5, and IGF1, and their related miRNAs (miR-125b-5p, miR-130a-3p, miR-16-5p, miR-204-5p, and miR-204-3p) may serve as promising biomarkers and candidate therapeutic targets for SCI and OA.

Sustainable reprocessing of lithium iron phosphate batteries: A recovery approach using liquid-phase method at reduced temperature.

Lithium iron phosphate batteries, known for their durability, safety, and cost-efficiency, have become essential in new energy applications. However, their widespread use has highlighted the urgency of battery recycling. Inadequate management could lead to resource waste and environmental harm. Traditional recycling methods, like hydrometallurgy and pyrometallurgy, are complex and energy-intensive, resulting in high costs. To address these challenges, this study introduces a novel low-temperature liquid-phase method for regenerating lithium iron phosphate positive electrode materials. By using N2H4·H2O as a reducing agent, missing Li+ ions are replenished, and anti-site defects are reduced through annealing. This process restores nearly all missing Li+ ions at 80 °C/6h. After high-temperature sintering at 700 °C/2h, the regenerated LiFePO4 matches commercial LiFePO4 in terms of anti-site defects and exhibits excellent performance with a 97 % capacity retention rate after 100 cycles at 1C. Compared to high-temperature techniques, this low-temperature liquid-phase method is simpler, safer, and more energy-efficient, offering a blueprint for reclaiming discarded LiFePO4 and similar materials.

Boosting Photocatalytic CO2 Methanation through Interface Fusion over CdS Quantum Dot Aerogels.

In the field of photocatalytic CO2 reduction, quantum dot (QD) assemblies have emerged as promising candidate photocatalysts due to their superior light absorption and better substrate adsorption. However, the poor contacts within QD assemblies lead to low interfacial charge transfer efficiency, making QD assemblies suffer from unsatisfactory photocatalytic performance. Herein, a novel approach is presented involving the construction of strongly interfacial fused CdS QD assemblies (CdS QD gel) for CO2 reduction. The novel CdS QD gel demonstrates outstanding photocatalytic performance for CO2 methanation, achieving a CH4 generation rate of ≈296 µmol g-1 h-1, with a selectivity surpassing 76% and an apparent quantum yield (AQY) of 1.4%. Further investigations reveal that the robust interfacial fusion in these CdS QDs not only boosts their ability to absorb visible light but also significantly promotes charge separation. The present work paves the way for utilizing QD gel photocatalysts in realizing efficient CO2 reduction and highlights the critical role of interfacial engineering in photocatalysts.

Spin Effect to Regulate the Electronic Structure of Ir─Fe Aerogels for Efficient Acidic Water Oxidation.

"Spin" has been recently reported as an important degree of electronic freedom to promote catalysis, yet how it influences electronic structure remains unexplored. This work reports the spin-induced orbital hybridization in Ir─Fe bimetallic aerogels, where the electronic structure of Ir sites is effectively regulated by tuning the spin property of Fe atoms. The spin-optimized electronic structure boosts oxygen evolution reaction (OER) electrocatalysis in acidic media, resulting in a largely improved catalytic performance with an overpotential of as low as 236 mV at 10 mA cm-2. Furthermore, the gelation kinetics for the aerogel synthesis is improved by an order of magnitude based on the introduction of a magnetic field. Density functional theory calculation reveals that the increased magnetic moment of Fe (3d orbital) changes the d-band structure (i.e., the d-band center and bandwidth) of Ir (5d orbital) via orbital hybridization, resulting in optimized binding of reaction intermediates. This strategy builds the bridge between the electron spin theory with the d-band theory and provides a new way for the design of high-performance electrocatalysts by using spin-induced orbital interaction.

Embedding biocatalysts in a redox polymer enhances the performance of dye-sensitized photocathodes in bias-free photoelectrochemical water splitting.

Dye-sensitized photoelectrodes consisting of photosensitizers and molecular catalysts with tunable structures and adjustable energy levels are attractive for low-cost and eco-friendly solar-assisted synthesis of energy rich products. Despite these advantages, dye-sensitized NiO photocathodes suffer from severe electron-hole recombination and facile molecule detachment, limiting photocurrent and stability in photoelectrochemical water-splitting devices. In this work, we develop an efficient and robust biohybrid dye-sensitized NiO photocathode, in which the intermolecular charge transfer is enhanced by a redox polymer. Owing to efficient assisted electron transfer from the dye to the catalyst, the biohybrid NiO photocathode showed a satisfactory photocurrent of 141±17 µA·cm-2 at neutral pH at 0 V versus reversible hydrogen electrode and a stable continuous output within 5 h. This photocathode is capable of driving overall water splitting in combination with a bismuth vanadate photoanode, showing distinguished solar-to-hydrogen efficiency among all reported water-splitting devices based on dye-sensitized photocathodes. These findings demonstrate the opportunity of building green biohybrid systems for artificial synthesis of solar fuels.

Adapt-On-Demand: A Novel Strategy for Personalized Adaptive Radiation Therapy for Locally Advanced Lung Cancer.

PURPOSE: Real-time adaptation of thoracic radiation plans is compelling because offline adaptive experiences show that tumor volumes and lung anatomy can change during therapy. We present and analyze a novel adaptive-on-demand (AOD) workflow combining online adaptive radiation therapy (o-ART) on the ETHOS system with image guided radiation therapy delivery on a Halcyon unit for conventional fractionated radiation therapy of locally advanced lung cancer (LALC). METHODS AND MATERIALS: We analyzed 26 patients with LALC treated with the AOD workflow, adapting weekly. We timed segments of the workflow to evaluate efficiency in a real-world clinic. Target coverage and organ at risk (OAR) doses were compared between adaptive plans (ADP) and nonadaptive scheduled plans (SCH). Planning robustness was evaluated by the frequency of preplanning goals achieved in ADP plans, stratified by tumor volume change. RESULTS: The AOD workflow was achievable within 30 minutes for most radiation fractions. Over the course of therapy, we observed an average 26.6% ± 23.3% reduction in internal target volume (ITV). Despite these changes, with o-ART, ITV and planning target volume (PTV) coverage (V100%) was 99.2% and 93.9% for all members of the cohort, respectively. This represented a 2.9% and 6.8% improvement over nonadaptive plans (P < .05), respectively. For tumors that grew >10%, V100% was 93.1% for o-ART and 76.4% for nonadaptive plans, representing a median 17.2% improvement in the PTV coverage (P < .05). In these plans, critical OAR constraints were met 94.1% of the time, whereas in nonadaptive plans, this figure was 81.9%. This represented reductions of 1.32 Gy, 1.34 Gy, or 1.75 Gy in the heart, esophagus, and lung, respectively. The effect was larger when tumors had shrunk more than 10%. Regardless of tumor volume alterations, the PTV/ITV coverage was achieved for all adaptive plans. Exceptional cases, where dose constraints were not met, were due to large initial tumor volumes or tumor growth. CONCLUSIONS: The AOD workflow is efficient and robust in responding to anatomic changes in LALC patients, providing dosimetric advantages over standard therapy. Weekly adaptation was adequate to keep pace with changes. This approach is a feasible alternative to conventional offline replanning workflows for managing anatomy changes in LALC radiation therapy.

Higher Dietary Inflammatory Index and Increased Mortality Rate of Adults With Hyperuricemia: Findings From the National Health and Nutritional Examination Survey (2001-2018).

OBJECTIVE: This study aimed to assess the association between Dietary Inflammatory Index (DII) score and death among adults with hyperuricemia. METHODS: We collected data from the 2001 to 2018 cohorts of the National Health and Nutritional Examination Survey. Death information was obtained based on death certificate records from the National Death Index through December 31, 2019. The associations between DII score and all-cause, cardiovascular disease (CVD), and cancer death were investigated by using Cox proportional hazards regression models. RESULTS: We enrolled 7,786 participants with hyperuricemia in this study. The DII score ranged from -4.42 to 4.61. Higher DII score was significantly associated with higher levels of body mass index, glycohemoglobin, glucose, low-density lipoprotein-cholesterol, and C-reactive protein (all P < 0.05). During 67,851 person-years of follow-up, deaths of 1,456 participants were identified, including 532 CVD deaths and 246 cancer deaths. After adjusting for potential variables, significant higher risk of all-cause (hazard ratio [HR] 1.18, 95% confidence interval [95% CI] 1.03-1.36, P = 0.01) and CVD (HR 1.30, 95% CI 1.03-1.63, P = 0.02) death was observed for individuals with higher DII scores. Considering the DII score as a continuous variable, the risk of all-cause and CVD death increases 5% (HR 1.05, 95% CI 1.01-1.08) and 8% (HR 1.08, 95% CI 1.02-1.15) with each one-unit increment in DII score, respectively. Subgroup analysis indicated that the association between DII score and all-cause death among participants with hyperuricemia was more significant in males. CONCLUSION: DII score is found to be positively associated with all-cause and CVD death of adults with hyperuricemia. Controlling the intake of proinflammatory food might be a potential strategy to reduce the mortality rate.

Performance validation of the 2023 American College of Rheumatology/European League Against Rheumatism antiphospholipid syndrome classification criteria in an antiphospholipid syndrome cohort.

BACKGROUND: The 2023 American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) antiphospholipid syndrome (APS) classification criteria were developed with higher specificity but lower sensitivity compared with the 2006 Sydney revised classification criteria. OBJECTIVES: To validate the performance of the 2023 ACR/EULAR APS classification criteria in a large Chinese APS cohort. METHODS: This was a single-center cohort study. Inclusion criteria aligned with the entry criteria of 2023 criteria. APS classification by "expert consensus panel" served as the gold standard. Sensitivity and specificity were compared between the 2023 and 2006 criteria. RESULTS: A total of 526 patients with a mean age of 38.55 ± 12.67 years were enrolled, of whom 366 (69.58%) were female and 182 (34.60%) had systemic lupus erythematosus (SLE). Among them, 407 (77.38%) patients were classified as APS by experts. The 2023 criteria demonstrated higher overall specificity than the 2006 criteria (0.983 vs 0.950), while sensitivity was relatively lower (0.818 vs 0.853). The sensitivity of the 2023 criteria improved for patients with SLE (0.860 vs 0.825), microvascular manifestations (0.867 vs 0.786), cardiac valve disease (0.903 vs 0.774), and thrombocytopenia (0.811 vs 0.790). Reduced sensitivity of the 2023 criteria was linked to the omission of certain microvascular manifestations, a stricter definition of pregnancy morbidity, and the exclusion of isolated thrombocytopenia and isolated IgM isotype antiphospholipid antibodies from meeting clinical and laboratory criteria, respectively. CONCLUSION: The 2023 criteria offer higher overall specificity and improved sensitivity in specific patient subsets, such as those with SLE, microvascular manifestations, cardiac valve disease, and thrombocytopenia when compared with the 2006 criteria.

Corrigendum: Influence of body composition assessment with bioelectrical impedance vector analysis in cancer patients undergoing surgery.

[This corrects the article DOI: 10.3389/fonc.2023.1132972.].

Adaptive Radiotherapy: Next-Generation Radiotherapy.

Radiotherapy, a crucial technique in cancer therapy, has traditionally relied on the premise of largely unchanging patient anatomy during the treatment course and encompassing uncertainties by target margins. This review introduces adaptive radiotherapy (ART), a notable innovation that addresses anatomy changes and optimizes the therapeutic ratio. ART utilizes advanced imaging techniques such as CT, MRI, and PET to modify the treatment plan based on observed anatomical changes and even biological changes during the course of treatment. The narrative review provides a comprehensive guide on ART for healthcare professionals and trainees in radiation oncology and anyone else interested in the topic. The incorporation of artificial intelligence in ART has played a crucial role in improving effectiveness, particularly in contour segmentation, treatment planning, and quality assurance. This has expedited the process to render online ART feasible, lowered the burden for radiation oncology practitioners, and enhanced the precision of dynamically personalized treatment. Current technical and clinical progress on ART is discussed in this review, highlighting the ongoing development of imaging technologies and AI and emphasizing their contribution to enhancing the applicability and effectiveness of ART.

Recyclable and Stable Porphyrin-Based Self-Assemblies by Electrostatic Force for Efficient Photocatalytic Organic Transformation.

Development of efficient, stable, and recyclable photocatalysts for organic synthesis is vital for transformation of traditional thermal organic chemistry into green sustainable organic chemistry. In this work, the study reports an electrostatic approach to assemble meso-tetra (4-sulfonate phenyl) porphyrin (TPPS)tetra (4-sulfonate phenyl) porphyrin (TPPS) as a donor and benzyl viologen (BV) as an acceptor into stable and recyclable photocatalyst for an efficient organic transformation reaction - aryl sulfide oxidation. By use of the electrostatic TPPS-BV photocatalysts, 0.1 mmol aryl sulfide with electron-donating group can be completely transformed into aryl sulfoxide in 60 min without overoxidation into sulfone, rendering near 100% yield and selectivity. The photocatalyst can be recycled up to 95% when 10 mg amount is used. Mechanistic study reveals that efficient charge separation between TPPS and BV results in sufficient formation of superoxide which further reacts with the oxidized sulfide by the photocatalyst to produce the sulfoxide. This mechanistic pathway differs significantly from the previously proposed singlet oxygen-dominated process in homogeneous TPPS photocatalysis.

Artificial intelligence driven malnutrition diagnostic model for patients with acute abdomen based on GLIM criteria: a cross-sectional research protocol.

BACKGROUND: Patients with acute abdomen often experience reduced voluntary intake and a hypermetabolic process, leading to a high occurrence of malnutrition. The Global Leadership Initiative on Malnutrition (GLIM) criteria have rapidly developed into a principal methodological tool for nutritional diagnosis. Additionally, machine learning is emerging to establish artificial intelligent-enabled diagnostic models, but the accuracy and robustness need to be verified. We aimed to establish an intelligence-enabled malnutrition diagnosis model based on GLIM for patients with acute abdomen. METHOD: This study is a single-centre, cross-sectional observational investigation into the prevalence of malnutrition in patients with acute abdomen using the GLIM criteria. Data collection occurs on the day of admission, at 3 and 7 days post-admission, including biochemical analysis, body composition indicators, disease severity scoring, nutritional risk screening, malnutrition diagnosis and nutritional support information. The occurrence rate of malnutrition in patients with acute abdomen is analysed with the GLIM criteria based on the Nutritional Risk Screening 2002 and the Mini Nutritional Assessment Short-Form to investigate the sensitivity and accuracy of the GLIM criteria. After data cleansing and preprocessing, a machine learning approach is employed to establish a predictive model for malnutrition diagnosis in patients with acute abdomen based on the GLIM criteria. ETHICS AND DISSEMINATION: This study has obtained ethical approval from the Ethics Committee of the Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital on 28 November 2022 (Yan-2022-442). The results of this study will be disseminated in peer-reviewed journals, at scientific conferences and directly to study participants. TRIAL REGISTRATION NUMBER: ChiCTR2200067044.

Recent advances in photoelectrochemical platforms based on porous materials for environmental pollutant detection.

Human health and ecology are seriously threatened by harmful environmental contaminants. It is essential to develop efficient and simple methods for their detection. Environmental pollutants can be detected using photoelectrochemical (PEC) detection technologies. The key ingredient in the PEC sensing system is the photoactive material. Due to the unique characteristics, such as a large surface area, enhanced exposure of active sites, and effective mass capture and diffusion, porous materials have been regarded as ideal sensing materials for the construction of PEC sensors. Extensive efforts have been devoted to the development and modification of PEC sensors based on porous materials. However, a review of the relationship between detection performance and the structure of porous materials is still lacking. In this work, we present an overview of PEC sensors based on porous materials. A number of typical porous materials are introduced separately, and their applications in PEC detection of different types of environmental pollutants are also discussed. More importantly, special attention has been paid to how the porous material's structure affects aspects like sensitivity, selectivity, and detection limits of the associated PEC sensor. In addition, future research perspectives in the area of PEC sensors based on porous materials are presented.

Inter-fractional portability of deep learning models for lung target tracking on cine imaging acquired in MRI-guided radiotherapy.

MRI-guided radiotherapy systems enable beam gating by tracking the target on planar, two-dimensional cine images acquired during treatment. This study aims to evaluate how deep-learning (DL) models for target tracking that are trained on data from one fraction can be translated to subsequent fractions. Cine images were acquired for six patients treated on an MRI-guided radiotherapy platform (MRIdian, Viewray Inc.) with an onboard 0.35 T MRI scanner. Three DL models (U-net, attention U-net and nested U-net) for target tracking were trained using two training strategies: (1) uniform training using data obtained only from the first fraction with testing performed on data from subsequent fractions and (2) adaptive training in which training was updated each fraction by adding 20 samples from the current fraction with testing performed on the remaining images from that fraction. Tracking performance was compared between algorithms, models and training strategies by evaluating the Dice similarity coefficient (DSC) and 95% Hausdorff Distance (HD95) between automatically generated and manually specified contours. The mean DSC for all six patients in comparing manual contours and contours generated by the onboard algorithm (OBT) were 0.68 ± 0.16. Compared to OBT, the DSC values improved 17.0 - 19.3% for the three DL models with uniform training, and 24.7 - 25.7% for the models based on adaptive training. The HD95 values improved 50.6 - 54.5% for the models based on adaptive training. DL-based techniques achieved better tracking performance than the onboard, registration-based tracking approach. DL-based tracking performance improved when implementing an adaptive strategy that augments training data fraction-by-fraction.

Aptamer-functionalized gold nanoparticles for mercury ion detection in a colorimetric assay based on color change time as signal readout.

A universal strategy for a rapid colorimetric method for Hg2+ in an aqueous solution is described. The specific binding of Hg2+ (thymine-Hg2+-thymine) with thiolated DNA-functionalized gold nanoparticles (AuNPs) via Au-S bonds increases the spatial hindrance of the AuNP surface, resulting in a weakened catalytic ability of AuNPs to catalyze the reaction between p-nitrophenol and NaBH4. Therefore, the color change time (CCT) of the solution from yellow to colorless becomes longer. Based on the kinetic curve of absorbance over time measured by a UV spectrometer, the level of Hg2+ in aqueous solutions can be easily quantified. A linear relationship between CCT and Hg2+ concentration was obtained in the 10-600-nM range with a detection limit of 0.20 nM, which is much lower than the limit value (10 nM) defined by the US Environmental Protection Agency for Hg2+ in drinking water. The excellent sensitivity comes from CCT as the signal output of the probe, rather than the absorbance or wavelength change used in traditional colorimetric probes as the signal output.

Simulation and pre-planning omitted radiotherapy (SPORT): a feasibility study for prostate cancer.

This study explored the feasibility of on-couch intensity modulated radiotherapy (IMRT) planning for prostate cancer (PCa) on a cone-beam CT (CBCT)-based online adaptive RT platform without an individualized pre-treatment plan and contours. Ten patients with PCa previously treated with image-guided IMRT (60 Gy/20 fractions) were selected. In contrast to the routine online adaptive RT workflow, a novel approach was employed in which the same preplan that was optimized on one reference patient was adapted to generate individual on-couch/initial plans for the other nine test patients using Ethos emulator. Simulation CTs of the test patients were used as simulated online CBCT (sCBCT) for emulation. Quality assessments were conducted on synthetic CTs (sCT). Dosimetric comparisons were performed between on-couch plans, on-couch plans recomputed on the sCBCT and individually optimized plans for test patients. The median value of mean absolute difference between sCT and sCBCT was 74.7 HU (range 69.5-91.5 HU). The average CTV/PTV coverage by prescription dose was 100.0%/94.7%, and normal tissue constraints were met for the nine test patients in on-couch plans on sCT. Recalculating on-couch plans on the sCBCT showed about 0.7% reduction of PTV coverage and a 0.6% increasing of hotspot, and the dose difference of the OARs was negligible (<0.5 Gy). Hence, initial IMRT plans for new patients can be generated by adapting a reference patient's preplan with online contours, which had similar qualities to the conventional approach of individually optimized plan on the simulation CT. Further study is needed to identify selection criteria for patient anatomy most amenable to this workflow.

Strain Effects in Ru-Au Bimetallic Aerogels Boost Electrocatalytic Hydrogen Evolution.

To improve the sluggish kinetics of the hydrogen evolution reaction (HER), a key component in water-splitting applications, there is an urgent desire to develop efficient, cost-effective, and stable electrocatalysts. Strain engineering is proving an efficient strategy for increasing the catalytic activity of electrocatalysts. This work presents the development of Ru-Au bimetallic aerogels by a simple one-step in situ reduction-gelation approach, which exhibits strain effects and electron transfer to create a remarkable HER activity and stability in an alkaline environment. The surface strain induced by the bimetallic segregated structure shifts the d-band center downward, enhancing catalysis by balancing the processes of water dissociation, OH* adsorption, and H* adsorption. Specifically, the optimized catalyst shows low overpotentials of only 24.1 mV at a current density of 10 mA cm-2 in alkaline electrolytes, surpassing commercial Pt/C. This study can contribute to the understanding of strain engineering in bimetallic electrocatalysts for HER at the atomic scale.

Dual-band terahertz chiral metasurface absorber with enhanced circular dichroism based on temperature-tunable InSb for sensing applications.

Circular dichroism (CD) in terahertz (THz) regions has been widely used in biomonitoring, analytical chemistry, communication sensing, and other fields. Herein, we present a simple design for a dual-band THz chiral metasurface absorber (CMA) with a stronger CD effect based on temperature-tunable InSb for enhanced sensing applications. The proposed dual-band CMA consisted of a periodic array of the evolved C-shaped InSb adhered to a copper substrate. The designed CMA at 305 K achieved a right-handed circular polarization (RCP)-selective absorbance of 98.86% and 97.43% at 1.65 THz and 1.89 THz, respectively, and left-handed circular polarization (LCP) absorbance of 9.98% and 22.46%, respectively, and exhibited stronger CD values of 0.89 and 0.75. In addition, the CD properties of the designed CMA can be adjusted by changing the geometrical parameters of the unit-cell structure. The simulated electric field and power follow distributions indicate that this dual-band chiral-selective absorption of the designed CMA is due to the different plasma resonance mode excitations for the incident circular polarization (CP) wave. In addition, the CD properties of the designed CMA can be adjusted by changing the geometrical parameters of the unit-cell structure. Furthermore, CD spectra can be dynamically adjusted by varying the outside temperature and refraction index (RI) of the filled analytes. The designed dual-band CMA can function as a high-performance temperature sensor with sensitivities of 4.68 GHz K-1 and 5.52 GHz K-1 and also as an RI sensor with sensitivities of 1080 GHz RIU-1 and 860 GHz RIU-1, respectively. Our proposed tunable dual-band CMA with its exquisite performance has the potential to be widely applied in diverse areas such as detection, sensing, and other related optoelectronic fields.

piRNA mmu_piR_037459 suppression alleviated the degeneration of chondrocyte and cartilage.

OBJECTIVE: Osteoarthritis (OA) is a prevalent chronic degenerative joint ailment. Its primary pathological characteristics encompass degeneration of articular cartilage, inflammation of the synovium, and alterations in the subchondral bone proximate to the cartilage. Chondrocytes, as the sole cell type within articular cartilage, assume a crucial role in upholding the dynamic equilibrium between anabolic and catabolic processes within the extracellular matrix of articular cartilage. IL-1ß stands as a pivotal inflammatory factor that instigates cartilage degeneration. piRNA, categorized as a subset of brief non-coding RNAs spanning nucleotide lengths of 26-31nt, assumes a significant regulatory role in cellular function. METHODS: Small RNA sequencing and quantitative PCR (qPCR) were employed to investigate the impact of the inflammatory factor IL-1ß on piRNA expression within chondrocytes. The regulation of mmu_piR_037459 expression in chondrocytes was achieved using piRNA mimics and inhibitors. Additionally, collagen II expression was assessed through both qPCR and Western blot analysis. Chondrocyte apoptosis was evaluated via flow cytometry and clonogenesis assays. To assess the influence of mmu_piR_037459 on osteoarthritis, a mouse model of anterior cruciate ligament transection (ACLT) was established. Furthermore, the regulatory effect of mmu_piR_037459 on USP7 was investigated using bioinformatics and a luciferase reporter gene assay. RESULTS: mmu_piR_037459 inhibited the expression of collagen II in chondrocytes, inhibited the proliferation of chondrocytes, and promoted the apoptosis of chondrocytes. mmu_piR_037459 affected the function of chondrocytes by regulating the expression of USP7. Inhibition of mmu_piR_037459 expression could promote chondrocyte proliferation, inhibit chondrocyte apoptosis, and alleviate the degeneration of OA cartilage. CONCLUSIONS: This study suggests that mmu_piR_037459 maybe a new therapeutic targets and strategies for the treatment of OA.