Background: Metabolic changes in donkey meat during the early postmortem period have not been previously reported. Methods: The LC–MS-based metabolomics technique was conducted to understand the metabolic profiles and identify the key metabolites of donkey meat in the first 48 h postmortem. Results: The pH values showed a decreasing trend followed by an increasing trend. Shear force was the lowest at 4 h and the highest at 24 h (p < 0.05). For the metabolome, some candidate biomarker metabolites were identified, such as adenine, inosine, n-acetylhistidine, citric acid, isocitrate, and malic acid. Predominant metabolic pathways, such as citrate cycle (TCA cycle), alanine, aspartate and glutamate metabolism, and purine metabolism, were affected by aging time. Overabundant n-acetylhistidine was identified in LT, declined at 12 h postmortem aging, and then increased. This may explain the significantly lower pH at 12 h postmortem. Adenine was higher at 4 h postmortem, then declined. Decreased ADP may indicate a fast consumption of ATP and subsequent purine metabolism in donkey meat. Conclusions: The results of this study provided new insights into early postmortem aging of donkey meat quality. Full article

One of the limitations of the dung beetle optimization (DBO) is its susceptibility to local optima and its relatively low search accuracy. Several strategies have been utilized to improve the diversity, search precision, and outcomes of the DBO. However, the equilibrium between exploration and exploitation has not been achieved optimally. This paper presents a novel algorithm called the ODBO, which incorporates cat map and an opposition-based learning strategy, which is based on symmetry theory. In addition, in order to enhance the performance of the dung ball rolling phase, this paper combines the global search strategy of the osprey optimization algorithm with the position update strategy of the DBO. Additionally, we enhance the population’s diversity during the foraging phase of the DBO by incorporating vertical and horizontal crossover of individuals. This introduction of asymmetry in the crossover operation increases the exploration capability of the algorithm, allowing it to effectively escape local optima and facilitate global search. Full article

Objective: Burning mouth syndrome (BMS) is a chronic pain disorder characterized by intraoral burning or dysaesthetic sensation, with the absence of any identifiable lesions. Numerous treatments for BMS have been investigated, though without conclusive results. An analysis was conducted of the efficacy of treatment with a low-level diode laser and clonazepam in patients with BMS, and a study was carried out on the levels of different salivary biomarkers before and after treatment. Material and methods: A randomized, single-blind clinical trial was carried out involving 89 patients divided into the following groups: group 1 (laser, The Helbo^® Theralite Laser 3D Pocket Probe + clonazepam) (n = 20), group 2 (sham laser placebo) (n = 19), group 3 (laser) (n = 21) and group 4 (clonazepam) (n = 18). Symptom intensity was scored based on a visual analogue scale (VAS). Sialometry was performed before and after treatment, and the Xerostomia Inventory, Oral Health Impact Profile-14 (OHIP-14) and Mini-Nutritional Assessment (MNA) questionnaires were administered. The following markers were measured in saliva samples: interleukins (IL2, IL4, IL5, IL6, IL7, IL8, IL1β, IL10, IL12, IL13, IL17, IL21 and IL23), proteins (MIP-3α, MIP-1α and MIP-1β), GM-CSF, interferon gamma (IFNγ), interferon-inducible T-cell alpha chemoattractant (ITAC), fractalkine and tumor necrosis factor α (TNFα). Results: A significant decrease in the VAS scores was observed after treatment in group 1 (laser + clonazepam) (p = 0.029) and group 3 (laser) (p = 0.005). In turn, group 3 (laser) showed a decrease in the salivary concentration of fractalkine (p = 0.025); interleukins IL12 (p = 0.048), IL17 (p = 0.020), IL21 (p = 0.008), IL7 (p = 0.001) and IL8 (p = 0.007); proteins MIP1α (p = 0.048) and MIP1β (p = 0.047); and TNFα (p = 0.047) versus baseline. Following treatment, group 1 (laser + clonazepam) showed significant differences in IL21 (p = 0.045) and IL7 (p = 0.009) versus baseline, while group 4 (clonazepam) showed significant differences in IL13 (p = 0.036), IL2 (p = 0.020) and IL4 (p = 0.001). No significant differences were recorded in group 2 (sham laser placebo). Conclusions: The low-level diode laser is a good treatment option in BMS, resulting in a decrease in patient symptoms and in salivary biomarkers. However, standardization of the intervention protocols and laser intensity parameters is needed in order to draw more firm conclusions. Full article

Pinus thunbergii Parl. is an economically and medicinally important plant, as well as a world-renowned horticultural species of the Pinus genus. Pine wilt disease is a dangerous condition that affects P. thunbergii. However, understanding of the genetics underlying resistance to this disease is poor. Our findings reveal that P. thunbergii’s resistance mechanism is based on differential transcriptome responses generated by the early presence of the pathogen Bursaphelenchus xylophilus, also known as the pine wood nematode. A transcriptome analysis (RNA-seq) was performed to examine gene expression in shoot tissues from resistant and susceptible P. thunbergii trees. RNA samples were collected from the shoots of inoculated pines throughout the infection phases by the virulent Bursaphelenchus xylophilus AMA3 strain. The photosynthesis and plant–pathogen interaction pathways were significantly enriched in the first and third days after infection. Flavonoid biosynthesis was induced in response to late infestation (7 and 14 days post-infestation). Calmodulin, RBOH, HLC protein, RPS, PR1, and genes implicated in phytohormone crosstalk (e.g., SGT1, MYC2, PP2C, and ERF1) showed significant alterations between resistant and susceptible trees. Furthermore, salicylic acid was found to aid pine wood nematodes tolerate adverse conditions and boost reproduction, which may be significant for pine wood nematode colonization within pines. These findings provide new insights into how host defenses overcame pine wood nematode infection in the early stage, which could potentially contribute to the development of novel strategies for the control of pine wilt disease. Full article

The current study aims to utilize the homotopy perturbation method (HPM) to solve nonlinear dynamical models, with a particular focus on models related to predicting and controlling pandemics, such as the SIR model. Specifically, we apply this method to solve a six-compartment model for the novel coronavirus (COVID-19), which includes susceptible, exposed, asymptomatic infected, symptomatic infected, and recovered individuals, and the concentration of COVID-19 in the environment is indicated by $S(t)$, $E(t)$, $A(t)$, $I(t)$, $R(t)$, and $B(t)$, respectively. We present the series solution of this model by varying the controlling parameters and representing them graphically. Additionally, we verify the accuracy of the series solution (up to the $(n-1)th$-degree polynomial) that satisfies both the initial conditions and the model, with all coefficients correct at 18 decimal places. Furthermore, we have compared our results with the Runge–Kutta fourth-order method. Based on our findings, we conclude that the homotopy perturbation method is a promising approach to solve nonlinear dynamical models, particularly those associated with pandemics. This method provides valuable insight into how the control of various parameters can affect the model. We suggest that future studies can expand on our work by exploring additional models and assessing the applicability of other analytical methods. Full article

MXenes, as emerging 2D sensing materials for next-generation electronics, have attracted tremendous attention owing to their extraordinary electrical conductivity, mechanical strength, and flexibility. However, challenges remain due to the weak stability in the oxygen environment and nonnegligible aggregation of layered MXenes, which severely affect the durability and sensing performances of the corresponding MXene-based pressure sensors, respectively. Here, in this work, we propose an easy-to-fabricate self-assembly strategy to prepare multilayered MXene composite films, where the first layer MXene is hydrogen-bond self-assembled on the electrospun thermoplastic urethane (TPU) fibers surface and the anti-oxidized functionalized-MXene (f-MXene) is subsequently adhered on the MXene layer by spontaneous electrostatic attraction. Remarkably, the f-MXene surface is functionalized with silanization reagents to form a hydrophobic protective layer, thus preventing the oxidation of the MXene-based pressure sensor during service. Simultaneously, the electrostatic self-assembled MXene and f-MXene successfully avoid the invalid stacking of MXene, leading to an improved pressure sensitivity. Moreover, the adopted electrospinning method can facilitate cyclic self-assembly and the formation of a hierarchical micro-nano porous structure of the multilayered f-MXene/MXene/TPU (M-fM²T) composite. The gradient pores can generate changes in the conductive pathways within a wide loading range, broadening the pressure detection range of the as-proposed multilayered f-MXene/MXene/TPU piezoresistive sensor (M-fM²TPS). Experimentally, these novel features endow our M-fM²TPS with an outstanding maximum sensitivity of 40.31 kPa⁻¹ and an extensive sensing range of up to 120 kPa. Additionally, our M-fM²TPS exhibits excellent anti-oxidized properties for environmental stability and mechanical reliability for long-term use, which shows only ~0.8% fractional resistance changes after being placed in a natural environment for over 30 days and provides a reproducible loading–unloading pressure measurement for more than 1000 cycles. As a proof of concept, the M-fM²TPS is deployed to monitor human movements and radial artery pulse. Our anti-oxidized self-assembly strategy of multilayered MXene is expected to guide the future investigation of MXene-based advanced sensors with commercial values. Full article

Memristive structures are among the most promising options to be components of neuromorphic devices. However, the formation of HfO₂-based devices in crossbar arrays requires considerable time since electroforming is a single stochastic operation. In this study, we investigate how Ar⁺ plasma immersion ion implantation (PI) affects the Pt/HfO₂ (4 nm)/${\mathrm{HfO}}_X{\mathrm{N}}_Y$ (3 nm)/TaN electroforming voltage. The advantage of PI is the simultaneous and uniform processing of the entire wafer. It is thought that Ar⁺ implantation causes defects to the oxide matrix, with the majority of the oxygen anions being shifted in the direction of the TaN electrode. We demonstrate that it is feasible to reduce the electroforming voltages from 7.1 V to values less than 3 V by carefully selecting the implantation energy. A considerable decrease in the electroforming voltage was achievable at an implantation energy that provided the dispersion of recoils over the whole thickness of the oxide without significantly affecting the ${\mathrm{HfO}}_X{\mathrm{N}}_Y$/TaN interface. At the same time, Ar⁺ PI at higher and lower energies did not produce the same significant decrease in the electroforming voltage. It is also possible to obtain self-compliance of current in the structure during electroforming after PI with energy less than 2 keV. Full article

The influence of bovine serum albumin (BSA) on collapsing poly(N-isopropylacrylamide) (PNIPAM) chains was studied with turbidimetry and spin probe and spin label electron paramagnetic resonance spectroscopy. An increased ratio of collapsed chains in aqueous solutions in the narrow temperature region near the LCST appeared in the presence of 2.5–10 wt% BSA. The spin probe EPR data indicate that the inner cavities of the BSA dimers are probably responsive to the capture of small hydrophobic or amphiphilic molecules, such as TEMPO nitroxyl radical. The observed features of the structure and dynamics of inhomogeneities of aqueous PNIPAM-BSA solutions, including their mutual influence on the behavior of the polymer and protein below the LCST, should be considered when developing and investigating PNIPAM-based drug delivery systems. Full article

Food waste is considered to be a social, environmental, administrative, and economic problem. Given the large-scale production and distribution of food, food waste in food services has been widely discussed by experts, professors, and scientists in the field. This systematic review aimed to understand which food service has the highest percentage of plate food waste. A systematic review and meta-analysis were conducted until January 2024 in ten electronic databases: MEDLINE, Embase, IBECS, BINACIS, BDENF, CUMED, BDNPAR, ARGMSAL, Cochrane Library, Sustainable Development Goals, and the gray literature. The protocol was previously registered with PROSPERO under the code CRD42024501971. Studies that have assessed plate food waste in food services were included. There were no restrictions on language, publication location, or date. The risk of bias analysis was carried out using the JBI instrument. A proportion meta-analysis was carried out using R software (version 4.2.1). This systematic review with meta-analysis showed that the type of distribution and the food service are the factors that have the greatest impact on the percentage and per capita of plate food waste. In the face of increased waste, interventions should be targeted by type and distribution system, diners, and meals in order to lessen the impact of these factors. Full article

Background: Various nutritional strategies are increasingly used in sports to reduce oxidative stress and promote recovery. Chokeberry is rich in polyphenols and can reduce oxidative stress. Consequently, chokeberry juices and mixed juices with chokeberry content are increasingly used in sports. However, the data are very limited. Therefore, this study investigates the effects of the short-term supplementation of a red fruit juice drink with chokeberry content or a placebo on muscle damage, oxidative status, and leg strength during a six-day intense endurance protocol. Methods: Eighteen recreational endurance athletes participated in a cross-over high intensity interval training (HIIT) design, receiving either juice or a placebo. Baseline and post-exercise assessments included blood samples, anthropometric data, and leg strength measurements. Results: A significant increase was measured in muscle damage following the endurance protocol in all participants (∆ CK juice: 117.12 ± 191.75 U/L, ∆ CK placebo: 164.35 ± 267.00 U/L; p = 0.001, η² = 0.17). No group effects were detected in exercise-induced muscle damage (p = 0.371, η² = 0.010) and oxidative status (p = 0.632, η² = 0.000). The reduction in strength was stronger in the placebo group, but group effects are missing statistical significance (∆ e1RM juice: 1.34 ± 9.26 kg, ∆ e1RM placebo: −3.33 ± 11.49 kg; p = 0.988, η² = 0.000). Conclusion: Although a reduction in strength can be interpreted for the placebo treatment, no statistically significant influence of chokeberry could be determined. It appears that potential effects may only occur with prolonged application and a higher content of polyphenols, but further research is needed to confirm this. Full article

The reachable set of controlled dynamical systems is the set of all reachable states from an initial condition over a certain time horizon, subject to operational constraints and exogenous disturbances. In astrodynamics, rapid approximation of reachable sets is invaluable for trajectory planning, collision avoidance, and ensuring safe and optimal performance in complex dynamics. Leveraging the connection between minimum-time trajectories and the boundary of reachable sets, we propose a sampling-based method for rapid and efficient approximation of reachable sets for finite- and low-thrust spacecraft. The proposed method combines a minimum-time multi-stage indirect formulation with the celebrated primer vector theory. Reachable sets are generated under two-body and circular restricted three-body (CR3B) dynamics. For the two-body dynamics, reachable sets are generated for (1) the heliocentric phase of a benchmark Earth-to-Mars problem, (2) two scenarios with uncertainties in the initial position and velocity of the spacecraft at the time of departure from Earth, and (3) a scenario with a bounded single impulse at the time of departure from Earth. For the CR3B dynamics, several cislunar applications are considered, including L1 Halo orbit, L2 Halo orbit, and Lunar Gateway 9:2 NRHO. The results indicate that low-thrust spacecraft reachable sets coincide with invariant manifolds existing in multi-body dynamical environments. The proposed method serves as a valuable tool for qualitatively analyzing the evolution of reachable sets under complex dynamics, which would otherwise be either incoherent with existing grid-based reachability approaches or computationally intractable with a complete Hamilton–Jacobi–Bellman method. Full article

Inertial signals are the most widely used signals in human activity recognition (HAR) applications, and extensive research has been performed on developing HAR classifiers using accelerometer and gyroscope data. This study aimed to investigate the potential enhancement of HAR models through the fusion of biological signals with inertial signals. The classification of eight common low-, medium-, and high-intensity activities was assessed using machine learning (ML) algorithms, trained on accelerometer (ACC), blood volume pulse (BVP), and electrodermal activity (EDA) data obtained from a wrist-worn sensor. Two types of ML algorithms were employed: a random forest (RF) trained on features; and a pre-trained deep learning (DL) network (ResNet-18) trained on spectrogram images. Evaluation was conducted on both individual activities and more generalized activity groups, based on similar intensity. Results indicated that RF classifiers outperformed corresponding DL classifiers at both individual and grouped levels. However, the fusion of EDA and BVP signals with ACC data improved DL classifier performance compared to a baseline DL model with ACC-only data. The best performance was achieved by a classifier trained on a combination of ACC, EDA, and BVP images, yielding F1-scores of 69 and 87 for individual and grouped activity classifications, respectively. For DL models trained with additional biological signals, almost all individual activity classifications showed improvement (p-value < 0.05). In grouped activity classifications, DL model performance was enhanced for low- and medium-intensity activities. Exploring the classification of two specific activities, ascending/descending stairs and cycling, revealed significantly improved results using a DL model trained on combined ACC, BVP, and EDA spectrogram images (p-value < 0.05). Full article

In this paper, a matching method for altimeter and transponder signals in Sub-optimal Maximum Likelihood Estimate (SMLE) tracking mode is proposed. In the in-orbit calibration of the altimeter in SMLE tracking mode using the reconstructive transponder, it is necessary to separate the forwarding signal from the ground echo signal. At the same time, the fluctuations in the received signal of the altimeter, which are caused by the forwarding signal of the transponder, can be eliminated. The transponder generates a bias when measuring the arrival time of the transmitting signal from the altimeter and embeds this bias in both the transponder-recorded data and the altimeter-recorded data. Therefore, the two sets of data have one-to-one correspondence, and they are superimposed using the sliding sum method. Moreover, the distance between the altimeter and the transponder is a parabolic geometric relationship, and the outliers are eliminated by the fitting error minimization decision, and the transponder signal is separated from the ground echo. The final altimeter transmitting–receiving signal path is obtained. Furthermore, the principles underlying this method can be used for any transponder that can adjust the response signal delay during calibration. Full article

Sketched drawings sometimes include non-solid lines drawn as sets of consecutive strokes. They represent dashed lines, which are useful for various purposes. Recognizing such dashed lines while parsing drawings is reasonably straightforward if they are outlined with a ruler and compass but becomes challenging when they are hand-drawn. The problem is manageable if the strokes are drawn consecutively so we can leverage the entire sequence. However, it becomes more challenging if they are drawn unordered, and/or we do not have access to the sequence (like in batch vectorization). In this paper, we describe a new approach to identify groups of strokes as depicting single hand-drawn dashed lines. The approach does not use sequence information and is tolerant with irregularities and imprecisions of the strokes. Our goal is to identify hidden lines of sketched engineering line-drawings, which would enable the interpretation of line-drawings with hidden edges, which currently cannot be efficiently vectorized. We speculate that other fields like hand-drawn graph interpretation may also benefit from our approach. Full article

Multiport converters (MCs) are widely adopted in many applications, from renewable energy sources and storage integration to automotive applications and distribution systems. They are used in order to interface different energy sources, storage devices and loads with one single, simple converter topology in contrast to the traditional approach, which can require different solutions made by two-port converters. MCs allow for a reduction in the number of components and cascaded conversion stages with respect to an equivalent system of two-port converters, resulting in reduced complexity, dimensions and costs, as well as in improved reliability and enhanced efficiency. Nevertheless, some aspects related to the design of MCs are still worth further discussion when MCs are applied to hybrid AC/DC distribution systems. First, most converters are developed for one specific application and are not modular in structure. Furthermore, many of the proposed solutions are not equally suitable for AC and DC applications and they can introduce significant issues in hybrid distribution systems, with earthing management being particularly critical. Even though most available solutions offer satisfying steady-state and dynamic performances, fault behavior is often not considered and the possibility of maintaining controllability during faults is overlooked. Building on these three aspects, in this paper, a new MC for hybrid distribution systems is presented. An innovative circuit topology integrating three-phase AC ports and three-wire DC ports and characterized by a unique connection between the AC neutral wire and the DC midpoint neutral wire is presented. Its control principles and properties during external faults are highlighted, and extensive numerical simulations support the presented discussion. Full article

This study introduces a novel framework that leverages artificial intelligence (AI), specifically deep learning and reinforcement learning, to enhance energy efficiency in architectural design. The goal is to identify architectural arrangements that maximize energy efficiency. The complexity of these models is acknowledged, and an in-depth analysis of model selection, their inherent complexity, and the hyperparameters that govern their operation is conducted. This study validates the scalability of these models by comparing them with traditional optimization techniques like genetic algorithms and simulated annealing. The proposed system exhibits superior scalability, adaptability, and computational efficiency. This research study also explores the ethical and societal implications of integrating AI with architectural design, including potential impacts on human creativity, public welfare, and personal privacy. This study acknowledges it is in its preliminary stage and identifies its potential limitations, setting the stage for future research to enhance and expand the effectiveness of the proposed methodology. The findings indicate that the model can steer the architectural field towards sustainability, with a demonstrated reduction in energy usage of up to 20%. This study also conducts a thorough analysis of the ethical implications of AI in architecture, emphasizing the balance between technological advancement and human creativity. In summary, this research study presents a groundbreaking approach to energy-efficient architectural design using AI, with promising results and wide-ranging applicability. It also thoughtfully addresses the ethical considerations and potential societal impacts of this technological integration. Full article

The key to whether elderly individuals in the community can enjoy their later years peacefully lies in the service capabilities of community comprehensive elderly care service facilities (CCECSF) under the Public-Private Partnership (PPP) mode. To maintain a high level of service capability in community comprehensive elderly care service facilities under PPP mode, scientific evaluation of the effectiveness of these facilities is equally crucial. This article first constructs a post-occupancy evaluation index system of community comprehensive elderly care service facilities under PPP mode that includes three evaluation attributes and fifteen evaluation criteria based on the Chinese culture and lifestyle habits. Regarding the issue of direct users being unable to directly participate in evaluations, the uncertainty in evaluation information, and the volatility of evaluation results, a multi-stage post-occupancy evaluation model is constructed based on probabilistic linguistic term set, TOPSIS model and multi-stage decision theory. The above post-occupancy evaluation index system and evaluation model together constitute a multi-stage post-occupancy evaluation framework for community comprehensive elderly care service facilities under PPP mode. The outcomes of the case study indicate that the post-occupancy evaluation index system can offer a scientifically guided approach for evaluating the service level of community comprehensive elderly care service facilities under the PPP mode; meanwhile, the multi-stage evaluation model can enable direct user participation in the post-evaluation of facility usage and improve the robustness and reduce the fluctuation of the evaluation results, so as to improve the scientificity of the evaluation results. Full article

Improving measurement accuracy is the core issue with surface acoustic wave (SAW) micro-force sensors. An electrode transducer can stimulate not only the SAW but also the bulk acoustic wave (BAW). A portion of the BAW can be picked up by the receiving transducer, leading to an unwanted or spurious signal. This can harm the device’s frequency response characteristics, thereby potentially reducing the precision of the micro-force sensor’s measurements. This paper examines the influence of anisotropy on wave propagation, and it also performs a phase-matching analysis between interdigital transducers (IDTs) and bulk waves. Two solutions are shown to reduce the influence of BAW for SAW micro sensors, which are arranged with acoustic absorbers at the ends of the substrate and in grooving in the piezoelectric substrate. Three different types of sensors were manufactured, and the test results showed that the sidelobes of the SAW micro-force sensor could be effectively inhibited (3.32 dB), thereby enhancing the sensitivity and performance of sensor detection. The SAW micro-force sensor manufactured using the new process was tested and the following results were obtained: the center frequency was 59.83 MHz, the fractional bandwidth was 1.33%, the range was 0–1000 mN, the linearity was 1.02%, the hysteresis was 0.59%, the repeatability was 1.11%, and the accuracy was 1.34%. Full article

As blockchain becomes more widely used, a growing number of application fields are becoming interested in blockchain to benefit from its decentralised nature, invariability, security, transparency, quick transaction capabilities, and cost-effectiveness. Blockchain has a wide range of applications and uses in healthcare. Distributed ledger technology facilitates the secure transfer of patient medical records, manages the medicine supply chain, and creates an efficient, transparent, safe, and effective way of communicating data across global healthcare. The organ transplantation process (OTP) is one of the healthcare areas that benefit from the use of such technology to make its process more secure and transparent. In this article, we put forward a systematic literature review analysis on the application of blockchain to the OTP. Additionally, we address and highlight the barriers and challenges that arise while using blockchain technology for the OTP. We also offer some suggestions for future developments that would enhance blockchain’s implementation in the OTP domain. Full article

Synchronous motors have extended their presence in different applications, specifically in high-demand environments such as agronomy. These uses need advanced and better control strategies to improve energy efficiency. Within this context, sliding mode control has demonstrated effectiveness in electric machine control due to its advantages in robustness and quick adaptation to uncertain dynamic system disturbances. Nevertheless, this control technique presents the undesirable chattering phenomenon due to the discontinuous control action. This paper introduces a novel speed integral control scheme based on sliding modes for synchronous motors. This approach is designed to track smooth speed profiles and is evaluated through several numeric simulations to verify its robustness against variable torque loads. This approach addresses using electric motors for different applications such as irrigation systems, greenhouses, pumps, and others. Moreover, to address the chattering problem, different sign function approximations are evaluated in the control scheme. Then, the most effective functions for suppressing the chattering phenomenon through extensive comparative analysis are identified. Integral compensation in this technique demonstrates improvement in motor performance, while sign function approximations show a chattering reduction. Different study cases prove the robustness of this control scheme for large-scale synchronous motors. The simulation results validate the proposed control scheme based on sliding modes with integral compensation, by achieving chattering reduction and obtaining an efficient control scheme against uncertain disturbances in synchronous motors for agronomy applications. Full article

The potential of aerogels as catalysts for the synthesis of a relevant class of bis-heterocyclic compounds such as bis(indolyl)methanes was investigated. In particular, the studied catalyst was a nanocomposite aerogel based on nanocrystalline nickel ferrite (NiFe₂O₄) dispersed on amorphous porous silica aerogel obtained by two-step sol–gel synthesis followed by gel drying under supercritical conditions and calcination treatments. It was found that the NiFe₂O₄/SiO₂ aerogel is an active catalyst for the selected reaction, enabling high conversions at room temperature, and it proved to be active for three repeated runs. The catalytic activity can be ascribed to both the textural and acidic features of the silica matrix and of the nanocrystalline ferrite. In addition, ferrite nanocrystals provide functionality for magnetic recovery of the catalyst from the crude mixture, enabling time-effective separation from the reaction environment. Evidence of the retention of species involved in the reaction into the catalyst is also pointed out, likely due to the porosity of the aerogel together with the affinity of some species towards the silica matrix. Our work contributes to the study of aerogels as catalysts for organic reactions by demonstrating their potential as well as limitations for the room-temperature synthesis of bis(indolyl)methanes. Full article

Background: Burns represent a serious health problem, associated with multiple-organ failure, prolonged hospitalization, septic complications, and increased rate of mortality. The main aim of our study was to evaluate the levels of various circulating molecules in children with severe burns (more than 25% TBSA), in three different moments: 48 h, day 10, and day 21 post-burn. Materials and Methods: This study included 32 children with burns produced by flame, hot liquid, and electric arc and 21 controls. Serum plasminogen activator inhibitor-1 (PAI-1), α 1-acid glycoprotein (AGP), C-reactive protein (CRP), and platelet factor 4 (PF4) were detected using the Multiplex technique. Several parameters, such as fibrinogen, leucocyte count, thrombocyte count, triiodothyronine, thyroxine, and thyroid-stimulating hormone were also determined for each patient during hospitalization. Results: Significant statistical differences were obtained for CRP, AGP, and PF4 compared to the control group, in different moments of measurements. Negative correlations between CRP, AGP, and PF4 serum levels and burned body surface, and also the hospitalization period, were observed. Discussions: CRP levels increased in the first 10 days after burn trauma and then decreased after day 21. Serum PAI-1 levels were higher immediately after the burn and started decreasing only after day 10 post-burn. AGP had elevated levels 48 h after the burn, then decreased at 7–10 days afterwards, and once again increased levels after 21 days. PF4 serum levels increased after day 10 since the burning event. Conclusions: Serum CRP, AGP, PAI-1, and PF4 seem to be promising molecules in monitoring patients with a burn within the first 21 days. Full article