Search Results (50)

Cool-climate maize fields are characterized by low soil temperatures, strong seasonal hydrothermal fluctuations, and peat-influenced soil profiles, which may lead to patterns of nitrogen (N) cycling distinct from those in conventional agricultural soils. During maize growth, soils from three depths were characterized using physicochemical measurements, N-transformation and enzyme-activity assays, metagenomic sequencing, Mantel tests, variation partitioning analysis, and partial least squares path modeling (PLS-PM). Soil environmental factors varied significantly over time and with depth; soil organic matter (SOM) and total nitrogen (TN) increased with depth, while ammonium nitrogen (NH₄⁺-N) predominated early and nitrate nitrogen (NO₃⁻-N) predominated during the middle and late growth stages. The nitrogen fixation rate (NFR), nitrification rate (NitR), and denitrification rate (DNR) all peaked in August and showed a spatial pattern characterized by nitrogen fixation in the deepest layer and denitrification in the upper and middle layers. Bacterial communities varied less spatiotemporally than fungal communities. The genes nifK, hao, nirS/nirK, NR, nrfC, and hzsA/hzsC were identified as key nitrogen-cycling functional genes. Mantel tests and PLS-PM further characterized these relationships, with PLS-PM showing that soil physicochemical properties were positively associated with bacterial community composition (β = 0.87, p < 0.01), which, in turn, was negatively associated with N-cycling functional genes (β = −0.97, p < 0.001). Together, these pathways were associated with variation in N-cycling processes. Overall, this study advances an integrated understanding of N-cycling patterns and their potential controls in cool-climate maize fields and provides a scientific basis for optimizing N management strategies. Full article

As part of the ACTRIS research infrastructure, a six-month study (May–October 2024) was conducted at the CNR-IMAA Atmospheric Observatory (CIAO, Southern Italy) to characterize non-refractory submicron aerosol (NR-PM₁). Measurements were conducted in real time using a time-of-flight aerosol chemical speciation monitor (ToF-ACSM) and highlighted the predominant presence of organic aerosol (OA), with values reaching 49.5 µg m⁻³. During the study period, nitrate and ammonium concentrations remained below 2 µg m⁻³ on average, while sulfate concentrations showed normal variation during the analysis period (maximum value of 11.70 µg m⁻³). The daily variability of concentrations was influenced by both boundary layer dynamics and local emission variations. The calculated charge and mass balances allowed us to study the good neutralization of PM₁ in the atmosphere. The composition of the organic aerosol was dominated by oxygenated species, with a small contribution from biomass combustion. Ultimately, these results provide an excellent starting point for understanding the aerosol chemical composition and seasonal variability at the site, ahead of future analyses and comparisons within the ACTRIS of which the observatory is part. Full article

The advancement of microelectromechanical systems (MEMS) drives the demand for multifunctional ferroelectrics that synergistically combine substantial strain with competitive energy storage capabilities. In this work, the simultaneous enhancement of electromechanical strain and energy storage properties is achieved in (1−x)(Bi_0.5Na_0.5)_0.94Ba_0.06(Ti_0.98Mn_0.02)O₃-xSrTiO₃ (0 ≤ x ≤ 0.3) ceramics by synergistically employing A-site defect engineering and the nonergodic/ergodic relaxor (NR/ER) phase boundary design. The incorporation of Sr²⁺ plays a dual role: it induces cationic disorder that expands the polarization difference (ΔP = P_max − P_r), thereby effectively boosting the recoverable energy density (W_rec). Concurrently, it stabilizes a critical NR/ER phase ratio near room temperature, which maximizes the strain while minimizing the strain hysteresis. Consequently, when x = 0.15, the optimized system delivers a large strain of 0.45% (d₃₃* = 562 pm/V) with low hysteresis (H = 10.8%). In addition, the x = 0.25 composition exhibits an enhanced W_rec of 1.06 J/cm³, a competitive energy-storage potential (W_rec/E) of 0.013 mC/cm², and a high efficiency (η) of 81% under 80 kV/cm. This work provides an effective strategy for developing multifunctional lead-free materials for integrated actuators and energy storage devices. Full article

Background: Care for knee osteoarthritis (KOA) is frequently fragmented, and pathway-level decisions within Physical Medicine and Rehabilitation (PM&R) are influenced by local organizations. The objective of this study was to identify areas of agreement and disagreement among PM&R experts and to translate these into a clinically interpretable, function-oriented care pathway for knee osteoarthritis (KOA) within rehabilitation services. Methods: A two-round Real-Time Delphi study was conducted using the SmartDelphi web platform. A steering committee of five PM&R physicians developed a 37-item questionnaire covering referral/access, functional and outcome assessment, conservative management, escalation/referral thresholds, and follow-up/discharge. Round 1 was online (SERMEF osteoarthritis working group; 46 invited, 40 completed; 87.0%) with responses collected until 30 April 2025. Round 2 was an in-person, facilitated validation round on 30 May 2025 at the SERMEF Congress (A Coruña; 85 invited, 70 completed; 82.4%). Items were rated on a 6-point Likert scale; consensus strength was defined by interquartile range (IQR): strong (0–1) vs. weak (≥2). No patient-level data were collected; participant characteristics were comparable across rounds, suggesting consensus refinement reflected deliberation rather than panel shifts over time. Results: Consensus supported a longitudinal, function-first pathway that was structured into five phases: entry/referral to PM&R; comprehensive functional assessment using a minimum outcomes dataset (pain VAS/NRS, WOMAC function, quality-of-life scale); multimodal conservative rehabilitation combining exercise/physiotherapy, education/self-management support, and indicated oral/topical therapies; reassessment-guided escalation in non-responders, reserving interventional PM&R techniques, multidisciplinary musculoskeletal pain-unit management, or orthopedic evaluation for persistent pain and/or functional limitation; and longitudinal monitoring with defined discharge criteria. Conclusions: SERMEF PM&R experts converged on an implementation-oriented, outcomes-driven KOA itinerary centred on functioning, conservative multimodal care, structured reassessment, and explicit discharge planning. Full article

Aquaponics is a water-reusing, circular form of controlled-environment agriculture, but its sustainability benefits depend on reliable, constraint-aware nutrient dosing under delayed inflow effects. Aquaponics involves coupling hydroponics with aquaculture but is difficult to control because the greenhouse/crop state at the current time step ($t$) must anticipate water-quality changes that arrive at the next time step ($t+1$), under hard EC–pH and dose constraints. We propose the Analysis System for Nutrient Requirements in Hydroponics (ASNRH), a two-module, constraint-aware framework that directly regresses next-step elemental supplementation (N, P, K; mg·L⁻¹). First, the Fish-farm By-product Prediction Module (FBPM) uses a lightweight GRU forecaster to predict inflow chemistry at $t+1$ (e.g., NH₄⁺/NO₂⁻/NO₃⁻, alkalinity) from standard aquaculture sensors. Second, the Nutrient Requirement Prediction Module (NRPM) encodes the current hydroponic and crop state at t in parallel with the FBPM inflow at $t+1$ via a dual-branch architecture and fuses both representations to produce non-negative dose recommendations while penalizing forecasted EC/pH violations and excessive actuation volatility. The data pipeline assumes low-cost greenhouse and aquaculture sensors with chronological, leakage-free splits. A protocol-first simulation evaluates ASNRH against time-series and rule-based baselines using accuracy metrics (MAE/RMSE/R²), EC/pH violation rates, and robustness under missingness/noise; ablations isolate the contributions of the inflow branch, constraint-aware losses, and lightweight physics priors. The framework targets deployability in decoupled or coupled aquaponics by structurally resolving $t$ vs. $t+1$ asynchrony and internalizing domain constraints during learning; procedures are specified to support reproducibility and subsequent field trials. By operationalizing anticipatory dosing from reused aquaculture byproducts under EC/pH feasibility constraints, ASNRH is designed to support sustainability goals such as reduced nutrient wastage and fewer corrective water exchanges in coupled or decoupled aquaponics. Full article

In this work, we report the development of a highly sensitive optical sensor for the detection of cardiac troponin I (cTnI), a key biomarker for early-stage myocardial infarction diagnosis. The sensor combines castor oil-derived biomimetic receptors, called GreenNanoMIPs and prepared via the molecular imprinting technology using as a template an epitope of cTnI (i.e., the NR10 peptide), with a portable multimode plastic optical fiber surface plasmon resonance (POF-SPR) transducer. For sensing, gold SPR chips were functionalized with GreenNanoMIPs as proven by refractive index changes and confirmed by means of XPS. Binding experiments demonstrated the cTnI_nanoMIP-SPR sensor’s ability to detect both the NR10 peptide epitope and the full-length cTnI protein within minutes (t = 10 min), with high sensitivity and selectivity in buffer and serum matrices. The cTnI_nanoMIP-SPR showed an LOD of 3.53 × 10⁻¹⁵ M, with a linearity range of 1 pM–100 pM, outperforming previously reported sensor platforms and making it a promising tool for early-stage myocardial infarction detection. Full article

Pediatric obesity is rising globally, and emerging evidence suggests that sleep timing may influence metabolic health through epigenetic mechanisms. This study investigated epigenome-wide DNA methylation patterns associated with bedtime in children and explored their biological relevance. Children aged 6–10 years were classified as early (≤8:30 PM) or late (>8:30 PM) bedtime groups. Saliva-derived DNA was analyzed using the Illumina Infinium MethylationEPIC BeadChip Array, and the Sparse Wrapper Algorithm (SWAG) was applied to identify differentially methylated loci. A total of 1006 CpG sites, representing 571 unique genes, were significantly associated with bedtime (p < 0.001). Significant methylation differences were observed between early and late bedtime groups, with ABCG2, ABHD4, MOBKL1A, AK3, SDE2, PRAMEF4, CREM, CDH4, BRAT1, and SDK1 showing the most consistent variation. Functional enrichment analyses (Gene Ontology, KEGG, and DisGeNET) conducted on the SWAG-identified gene set revealed enrichment in biological processes including peptidyl-lysin demethylation, regulation of sodium ion transport, DNA repair, and lipo-protein particle assembly. Key KEGG pathways included circadian entrainment, neurotransmission (GABAergic, dopaminergic, and glutamatergic), growth hormone synthesis, and insulin secretion. DisGeNET analysis identified associations with neurodevelopmental disorders and cognitive impairment. Cross-comparison with established sleep and obesity gene sets identified ten overlapping genes(CDH4, NR3C2, ACTG1, COG5, CAT, HDAC4, FTO, DOK7, OCLN, and ATXN1). These findings suggest that variations in bedtime during childhood may epigenetically modify genes regulating circadian rhythm, metabolism, neuronal connectivity, and stress response, potentially predisposing to later-life developmental, and metabolic challenges. Full article

Background: Multimodal analgesia, combining adductor canal block (ACB) and local infiltration analgesia (LIA), is commonly used for pain control after total knee arthroplasty (TKA). However, ACB alone may not fully cover the anteromedial knee, a region extensively disrupted by TKA. Recent studies suggest that blocking branches of the anterior femoral cutaneous nerve (AFCN) could enhance analgesia, but targeted AFCN blocks are technically challenging. We evaluated supra-sartorial subcutaneous infiltration (SSSI) at the femoral triangle apex as a simpler alternative to AFCN blocks. Methods: We retrospectively reviewed 19 patients undergoing TKA with a standardized multimodal analgesic protocol, including intraoperative LIA limited to posterior capsule (PC-LIA), postoperative SSSI, and delayed intermittent ACB via catheter. SSSI involved infiltrating 20 mL of 0.3% ropivacaine into the subcutaneous plane above the sartorius muscle at the level of femoral triangle apex. Pain was assessed using Numerical Rating Scale (NRS) scores at rest and during movement at 9:00 PM on postoperative day 0 (POD 0) and 9:00 AM on POD 1, with scheduled ACB doses administered at the time of NRS pain score assessments. Rescue ACB boluses were given for intolerable pain before the first scheduled dose. Results: Eleven patients (58%) required no rescue analgesia before the first scheduled ACB, maintaining NRS scores ≤ 4 at rest and with movement for a minimum of 575–785 min post-spinal anesthesia. Eight patients needed rescue ACB, with variable pain relief. Conclusions: SSSI, when combined with PC-LIA, provided clinically meaningful analgesia in 58% of our patient cohort following TKA, though the variability observed suggests limited consistency. As a practical alternative to targeted AFCN blocks, SSSI could potentially complement ACB in multimodal pain management, but its efficacy remains uncertain due to the retrospective, non-controlled study design without a comparator group. Further investigation through prospective randomized controlled trials is warranted to validate these preliminary findings. Full article

This paper presents a highly linear two-stage InGaP/GaAs power amplifier integrated circuit (PAIC) using a dynamic predistorter for 5G small-cell applications. The proposed predistorter, based on a diode-connected transistor, utilizes a supply voltage to accurately control the linearization characteristics by adjusting its dc current. It is connected in parallel with an inter-stage of the two-stage PAIC through a series configuration of a resistor and an inductor, and features a shunt capacitor at the base of the transistor. These passive components have been optimized to enhance the linearization performance by managing the RF signal’s coupling to the diode. Using these optimized components, the AM−AM and AM−PM nonlinearities arising from the nonlinear resistance and capacitance in the diode can be effectively used to significantly flatten the AM−AM and AM−PM characteristics of the PAIC. The proposed predistorter was applied to the 2.6 GHz two-stage InGaP/GaAs HBT PAIC. The IC was tested using a 5 × 5 mm² module package based on a four-layer laminate. The load network was implemented off-chip on the laminate. By employing a continuous-wave (CW) signal, the AM−AM and AM−PM characteristics at 2.55–2.65 GHz were improved by approximately 0.05 dB and 3°, respectively. When utilizing the new radio (NR) signal, based on OFDM cyclic prefix (CP) with a signal bandwidth of 100 MHz and a peak-to-average power ratio (PAPR) of 9.7 dB, the power-added efficiency (PAE) reached at least 11.8%, and the average output power was no less than 24 dBm, achieving an adjacent channel leakage power ratio (ACLR) of −40.0 dBc. Full article

The responses of soil nitrogen component dynamics and enzyme activities to vegetation degradation in wet meadows ecosystems remain unclear. This study employed a combination of field surveys and laboratory experiments to investigate soil nitrogen components and nitrogen cycling enzyme activities under different intensities of vegetation degradation and during the vegetation growth season in a wet meadow on the Qinghai–Tibetan Plateau. The aim was to explore the responses of soil nitrogen components and nitrogen cycling enzyme activities to vegetation degradation and their interrelationships. The results showed that vegetation degradation significantly reduced TN, NH₄⁺-N, MBN, PRO, and NiR, and increased NO₃⁻-N, URE, and NR. Soil nitrogen components and enzyme activities exhibited seasonal fluctuations across different degradation levels during the growing season. The Pearson correlation analysis revealed a significant positive correlation between temperature, moisture, nitrogen fractions, and nitrogen cycle-related enzyme activities, as well as between the nitrogen fractions and the enzyme activities themselves. Partial Least Squares Path Modeling (PLS-PM) elucidated the relationships between soil properties and nitrogen components under different degradation levels, explaining 78% of the variance in nitrogen components. Degradation level, growth season, and soil physical properties had indirect associations with nitrogen components, whereas soil enzyme activities exerted a direct positive influence on nitrogen components. Our research revealed the universal impact mechanism of environmental factors, soil characteristics, and vegetation degradation on nitrogen cycling in a wet meadow, thereby making a significant contribution to the restoration and maintenance of functional integrity in alpine wetland ecosystems. Full article

Abnormal expression of miRNAs is associated with the occurrence and progression of cancer and other diseases, making miRNAs essential biomarkers for disease diagnosis and prognosis. However, the intrinsic properties of miRNAs, such as short length, low abundance, and high sequence homology, represent great challenges for fast and accurate miRNA detection in clinics. Herein, we developed a novel hybridization chain reaction (HCR)-based electrochemical miRNAs chip (e-miRchip), featured with gold nanostructured electrodes (GNEs) and silver nanoparticle reporters (AgNRs), for sensitive and multiplexed miRNA detection. AgNRs were synthesized and applied on the e-miRchip to generate strong redox signals in the presence of miRNA. The stem–loop capture probe was covalently immobilized on the GNEs, and was opened upon miRNA hybridization to consequently trigger the HCR for signal amplification. The multiple long-repeated DNA helix generated by HCR provides the binding sites for the AgNRs, contributing to the amplification of the electrochemical signals of miRNA hybridization. To optimize the detection sensitivity, GNEs with three distinct structures were electroplated, in which flower-like GNEs were found to be the best electrode morphology for miRNAs analysis. Under optimal conditions, the HCR-based e-miRchip showed an excellent detection performance with an LOD of 0.9 fM and a linear detection range from 1 fM to 10 pM. Moreover, this HCR-based e-miRchip platform was able to effectively distinguish miRNAs from the one- or two-base mismatches. This HCR-based e-miRchip holds great potential as a highly efficient and promising miRNA detection platform for the diagnosis and prognosis of cancer and other diseases in the future. Full article

Nitric oxide (NO) functions as a signaling molecule in plant adaptation to changing environmental conditions. NO levels were found to increase in plants in response to low temperatures (LTs). However, knowledge of the pathways involved in enhanced NO production under cold stress is still limited. For this reason, we aimed to determine the role of different NO sources in NO generation in cucumber roots exposed to 10 °C for short (1 d) and long (6 d) periods. The short-term treatment of seedlings with LT markedly increased plasma membrane-bound nitrate reductase (PM-NR) activity and induced the expression of three genes encoding NR in cucumber (CsNR1-3). On the other hand, long-term exposure was related to both increased cytoplasmic NR (cNR) activity and induced expression of the CsARC gene, encoding the amidoxime-reducing component (ARC) protein. The decrease in nitrite reductase (NiR) activity and the higher NO₂⁻/NO₃⁻ ratio in the roots of plants exposed to LTs for 1 d suggest that tissue conditions may favor NR-dependent NO production. Regardless of NR stimulation, a significant increase in NOS-like activity was observed in the roots, especially during the long-term treatment of plants with LT. These results indicate that diverse NO-producing routes, both reductive and oxidative, are activated in cucumber tissues at different stages of cold stress. Full article

Natural resources (NRs) are important for the operation of any economy and are crucial for preserving environmental quality. However, the persistent utilization of NRs has led to a severe deterioration of environmental quality. This presents a vulnerability to the steadiness of the ecosystem, emphasizing the urgent requirement to achieve a harmonious equilibrium concerning the utilization of NRs and the conservation of environmental quality. Environmental taxes (ETs), green finance (GF), and the cultivation of a proficient workforce dedicated to achieving sustainable development are essential for attaining equilibrium and advancing the Sustainable Development Goals (SDGs). We aim to investigate the impact of NR, ET, GF, and the human capital index (HCI) on environmental pollution (PM_2.5, CH₄, CO₂, and N₂O) in the G20 countries from 2000 to 2022. This study employs a novel and cutting-edge MMQR methodology, offering distinct perspectives that diverge from the conclusions of previous research. The study’s findings suggest that excessive use of NRs contributes to the degradation of environmental quality. ET, GF, and economic growth help to improve environmental quality, but HCI has a harmful impact. The paper proposes that the establishment and enforcement of environmental regulations are crucial for attaining ecological integrity and meeting SDGs 7, 12, and 13. Full article

Background: N6-methyladenosine (m⁶A) modification plays a crucial role in the regulation of diverse cellular processes influenced by environmental factors. Nevertheless, the involvement of m⁶A-modified long noncoding RNAs (lncRNAs) in the pathogenesis of lung injury induced by particulate matter (PM) remains largely unexplored. Methods: Here, we establish a mouse model of PM-induced lung injury. We utilized m6A-modified RNA immunoprecipitation sequencing (MeRIP-seq) to identify differentially expressed m6A peaks on long non-coding RNAs (lncRNAs). Concurrently, we performed lncRNA sequencing (lncRNA-seq) to determine the differentially expressed lncRNAs. The candidate m6A-modified lncRNAs in the lung tissues of mice were identified through the intersection of the data obtained from these two sequencing approaches. Results: A total of 664 hypermethylated m⁶A peaks on 644 lncRNAs and 367 hypomethylated m⁶A peaks on 358 lncRNAs are confirmed. We use bioinformatic tools to analyze the potential functions and pathways of these m⁶A-modified lncRNAs, revealing their involvement in regulating inflammation, immune response, and metabolism-related pathways. Three key m⁶A-modified lncRNAs (lncRNA NR_003508, lncRNA uc008scb.1, and lncRNA ENSMUST00000159072) are identified through a joint analysis of the MeRIP-seq and lncRNA-seq data, and their validation is carried out using MeRIP-PCR and qRT-PCR. Analysis of the coding-non-coding gene co-expression network reveals that m⁶A-modified lncRNAs NR_003508 and uc008scb.1 participate in regulating pathways associated with inflammation and immune response. Conclusions: This study first provides a comprehensive transcriptome-wide analysis of m⁶A methylation profiling in lncRNAs associated with PM-induced lung injury and identifies three pivotal candidate m⁶A-modified lncRNAs. These findings shed light on a novel regulatory mechanism underlying PM-induced lung injury. Full article

Aerosols and their chemical composition exert an influence on the atmospheric environment, global climate, and human health. However, obtaining the chemical composition of aerosols with high spatial and temporal resolution remains a challenging issue. In this study, using the NR-PM1 collected in the Beijing area from 2012 to 2013, we found that the annual average concentration was 41.32 μg·m⁻³, with the largest percentage of organics accounting for 49.3% of NR-PM1, followed by nitrates, sulfates, and ammonium. We then established models of aerosol chemical composition based on a machine learning algorithm. By comparing the inversion accuracies of single models—namely MLR (Multivariable Linear Regression) model, SVR (Support Vector Regression) model, RF (Random Forest) model, KNN (K-Nearest Neighbor) model, and LightGBM (Light Gradient Boosting Machine)—with that of the combined model (CM) after selecting the optimal model, we found that although the accuracy of the KNN model was the highest among the other single models, the accuracy of the CM model was higher. By employing the CM model to the spatially and temporally matched AOD (aerosol optical depth) data and meteorological data of the Beijing–Tianjin–Hebei region, the spatial distribution of the annual average concentrations of the four components was obtained. The areas with higher concentrations are mainly situated in the southwest of Beijing, and the annual average concentrations of the four components in Beijing’s southwest are 28 μg·m⁻³, 7 μg·m⁻³, 8 μg·m⁻³, and 15 μg·m⁻³ for organics, sulfates, ammonium, and nitrates, respectively. This study not only provides new methodological ideas for obtaining aerosol chemical composition concentrations based on satellite remote sensing data but also provides a data foundation and theoretical support for the formulation of atmospheric pollution prevention and control policies. Full article