The 2017–2024 period has been prolific in the area of the algorithms for deep-based survival analysis. We have searched the answers to the following three questions. (1) Is there a new “gold standard” already in clinical data analysis? (2) Does the DL component lead to a notably improved performance? (3) Are there tangible benefits of deep-based survival that are not directly attainable with non-deep methods? We have analyzed and compared the selected influential algorithms devised for two types of input: clinicopathological (a small set of numeric, binary and categorical) and omics data (numeric and extremely high dimensional with a pronounced p >> n complication). Full article

Aerial photoelectric imaging payloads have become an important means of reconnaissance and surveillance in recent years. However, aerial images are easily affected by external conditions and have unclear edges, which greatly reduces the accuracy of imaging target recognition. This paper proposes the M-YOLOv5 model, which uses a shallow feature layer. The RFBs module is introduced to improve the receptive field and detection effect of small targets. In the neck network part, the BiFPN structure is used to reuse the underlying features to integrate more features, and a CBAM attention mechanism is added to improve detection accuracy. The experimental results show that the detection effect of this method on the DroneVehicle dataset is better than that of the original network, with the precision rate increased by 2.8%, the recall rate increased by 16%, and the average precision increased by 2.3%. Considering the real-time problem of target detection, based on the improved model, the Clight-YOLOv5 model is proposed, by lightweighting the network structure and using the depth-separable convolution optimization module. After lightweighting, the number of model parameters is decreased by 71.3%, which provides a new idea for lightweight target detection and proves the model’s effectiveness in aviation scenarios. Full article

Fire engineering endeavours to mitigate injury or the loss of life in the event of a fire. This is achieved primarily through fire prevention, containment, and extinguishment measures. Should prevention fail, the structural integrity of buildings, coupled with effective evacuation strategies, becomes paramount. While glass fibre-reinforced polymer (GFRP) materials have demonstrated efficacy in reinforcing concrete elements, their performance under fire conditions, notably in comparison to steel, necessitates a deeper understanding for structural applications. This study experimentally and numerically investigates the fire performance of GFRP-reinforced concrete (RC) columns subjected to only fire load without additional external loads. The research aims to ascertain the fire resistance based on the thickness of the concrete coating and the ultimate tensile strength of GFRP rebars after 90 min of fire exposure. Four GFRP-RC columns were subjected to a standardized fire curve on all sides in the experimental program. In the analytical program, a theoretical model was developed using the heat transfer module of the COMSOL software. The results of both analyses were very close, indicating the reliability of the procedure used. Based on the findings, recommendations regarding the fire resistance of GFRP-RC columns were formulated for structural applications. Results from this research provide the civil engineering community with data that will help them continue using FRP materials as internal reinforcement for concrete. Full article

Supporting refugee and migrant health has become a critical focus of healthcare policy. Developing and designing health literacy interventions that meet the needs of refugees and migrants is core to achieving this objective. This literature review sought to identify antecedents and consequences of health literacy among refugees and migrants during the first two years of the COVID-19 pandemic. We systematically searched nine electronic databases and numerous grey literature sources to identify studies published between December 2019 and March 2022. The antecedents (societal and environmental determinants, situational determinants, and personal determinants) and consequences of health literacy among refugees and migrants were mapped to a validated integrated health literacy model. Social and environmental determinants (n = 35) were the most reported antecedent influencing health literacy among refugees and migrants during the first two years of COVID-19. Language (n = 26) and culture (n = 16) were these determinants’ most frequently reported aspects. Situational determinants (n = 24) and personal determinants (n = 26) were less frequently identified factors influencing health literacy among refugees and migrants. Literacy (n = 11) and socioeconomic status (n = 8) were the most frequently reported aspects of personal determinants. Media use (n = 9) and family and peer influence (n = 7) were the most cited situational determinants reported. Refugees and migrants with higher levels of health literacy were more likely to use healthcare services, resulting in better health outcomes. The findings of this review reveal personal and situational factors that impacted health literacy among refugees and migrants during COVID-19 that require attention. However, the inadequate adaptation of health literacy interventions for linguistic and cultural diversity was a greater problem. Attention to this well-known aspect of public health preparedness and tailoring health literacy interventions to the needs of refugees and migrants during pandemics and other public health emergencies are paramount. Full article

In this article, a comparison of ionization techniques is provided and discussed. Conventional liquid chromatography with an electrospray ionization source shows higher robustness and repeatability in comparison with liquid chromatography coupled with a coordination ion spray (CIS-MS) source using silver nitrate as the dopant. However, the higher sensitivity and possibility to collect more data in untargeted applications mean CIS-MS is emerging as an instrument used in specific applications. During this research, the limit of detection (LOD) for GHRP-2 and GHRP-6 was established at 0.2 ng/mL, and the lower limit of quantification (LLOQ) was 0.5 ng/mL for CIS-MS. For conventional ESI-MS combined with solid-phase extraction on weak cation exchange columns, the limit of detection was found to be 1 ng/mL, and the lower limit of quantification was 2 ng/mL. Full article

Time series forecasting has been a challenging area in the field of Artificial Intelligence. Various approaches such as linear neural networks, recurrent linear neural networks, Convolutional Neural Networks, and recently transformers have been attempted for the time series forecasting domain. Although transformer-based architectures have been outstanding in the Natural Language Processing domain, especially in autoregressive language modeling, the initial attempts to use transformers in the time series arena have met mixed success. A recent important work indicating simple linear networks outperform transformer-based designs. We investigate this paradox in detail comparing the linear neural network- and transformer-based designs, providing insights into why a certain approach may be better for a particular type of problem. We also improve upon the recently proposed simple linear neural network-based architecture by using dual pipelines with batch normalization and reversible instance normalization. Our enhanced architecture outperforms all existing architectures for time series forecasting on a majority of the popular benchmarks. Full article

Biochar (Bc) and liquid vermicompost extracts (LVEs) are increasingly being used as biofertilizers in agriculture to promote soil-microbe-crop interactions. However, although both these products can potentially act synergistically due to their complementary characteristics, their co-application in different soils has not yet been investigated. Therefore, firstly, an LVE-activated biochar (B_LVE) was experimentally formulated and the persistence of LVE bacteria over a 60-day storage period was determined. The total number of LVE bacteria increased by 10-fold after 7 days and was stable throughout the entire biochar storage period. In addition, changes in the composition of the bacterial community were observed after 30 days of storage, indicating that taxa less represented in pure LVE may be advantaged upon biochar colonization. Secondly, a microcosm experiment was performed to evaluate whether the biological fertility and enzyme activities of two soils, differing in organic matter content, could be enhanced by the addition of LVE-activated biochar. In this experiment, three different doses of Bc, LVE, and B_LVE against the carbon-related biological fertility index (i.e., biological fertility index, BFI) and three enzyme activities over a 21-day incubation period were tested. The B_LVE treatment yielded the best results (i.e., BFI +32%, enzyme activities +38%). This indicates that Bc and LVEs can act synergistically to promote soil fertility, quality, and microbial activity. By integrating LVE-activated biochar into their soil management practices, farmers could achieve higher crop yields and healthier products. Full article

Due to the prevalent challenges of inadequate accuracy, unstandardized parameters, and suboptimal efficiency with regard to icing prediction, this study introduces an innovative online method for icing prediction based on Robust STL–BTSF and IBWO–LSSVR. Firstly, this study adopts the Robust Seasonal Decomposition of Time Series and Bilinear Temporal–Spectral Fusion (Robust STL–BTSF) approach, which is demonstrably effective for short-term and limited sample data preprocessing. Subsequently, injecting a multi-faceted enhancement approach to the Beluga Whale Optimization algorithm (BWO), which integrates a nonlinear balancing factor, a population optimization strategy, a whale fall mechanism, and an ascendant elite learning scheme. Then, using the Improved BWO (IBWO) above to optimize the key hyperparameters of Least Squares Support Vector Regression (LSSVR), a superior offline predictive part is constructed based on this approach. In addition, an Incremental Online Learning algorithm (IOL) is imported. Integrating the two parts, the advanced online icing prediction model for transmission lines is built. Finally, simulations based on actual icing data unequivocally demonstrate that the proposed method markedly enhances both the accuracy and speed of predictions, thereby presenting a sophisticated solution for the icing prediction on the transmission lines. Full article

Random polypropylene is considered an alternative material to regular polypropylene for applications where improved impact and creep resistance, as well as stiffness, are required. Random polypropylene nanocomposites reinforced with dimethyldichlorosilane-treated silica particles were prepared using meltmixing. The effect of varying the nanoparticles’ content on the structural, mechanical, damping and thermal behavior of the nanocomposites was investigated. The results indicated the improved deformation potential, fracture toughness, and energy storage capacity of the matrix with increasing the filler content. It was observed that the use of high filler fractions limited the reinforcing efficiency of the SiO₂ nanoparticles due to the formation of large agglomerates. The nanoparticles’ segregation was initially advised by modeling Young’s modulus but was also confirmed by electron imaging. Examination of the thermal properties of the nanocomposites indicated the limited effect of the nanoparticles on the melting behavior along with the thermal stability of the matrix. These results confirmed the usage of silica nanoparticles as a way of further improving the mechanical and thermomechanical properties of random polypropylene. Full article

Biogas is a renewable energy source generated through the anaerobic digestion (AD) of organic feedstocks. This study aims to quantify the biogas production potential (BPP) of fruit wastes via semi-continuous lab-scale mesophilic AD over a total of 100 days. The feed was composed of 80% banana peelings and 20% pineapple residues, mimicking the waste composition of a Costa Rican fruit processing facility used as a test case. The average loading rate of volatile suspended solids (VSS) corresponded to 3.6 kg VSS·m⁻³·d⁻¹. Biogas yield and composition were monitored, along with the concentration of ammonium, volatile fatty acids, and pH. Discounting the start-up phase, the BPP averaged to 526 L_N (kg VSS)⁻¹ with a methane concentration of around 54%, suggesting suitability of the substrate for AD. We calculated that if upscaled to the Costa Rican test case facility, these values translate into a gross average heat and electricity production via AD of around 5100 MWh_el·a⁻¹ and 5100 MWh_th·a⁻¹, respectively. Deducting self-consumption of the AD treatment, this is equivalent to 73% of the facility’s electricity demand, and could save about 450,000 L of heavy oil per year for heat generation. To circumvent nitrogen shortage, the addition of a co-substrate such as dry manure seems advisable. Full article

Water scarcity is a critical abiotic stress factor for plants in arid and semi-arid regions, impacting crop development and production yield and quality. Monitoring water stress at finer scales (e.g., farm and plant), requires multispectral imagery with thermal capabilities at centimeter resolution. This study investigates drought stress in pistachio trees in a farm located in Yazd province, Iran, by using Unmanned Aerial Vehicle (UAV) images to quantify evapotranspiration and assess drought stress in individual trees. Images were captured on 10 July 2022, using a Matrix 300 UAV with a MicaSense Altum multispectral sensor. By employing the Surface Energy Balance Algorithm for Land (SEBAL), actual field evapotranspiration was accurately calculated (10 cm spatial resolution). Maps of the optimum crop coefficient (K_c) were developed from the Normalized Difference Vegetation Index (NDVI) based on standard evapotranspiration using the Food and Agriculture Organization (FAO) 56 methodology. The comparison between actual and standard evapotranspiration allowed us to identify drought-stressed trees. Results showed an average and maximum daily evaporation of 4.3 and 8.0 mm/day, respectively, in pistachio trees. The real crop coefficient (K_c) for pistachio was 0.66, contrasting with the FAO 56 standard of 1.17 due to the stress factor (K_s). A significant correlation was found between K_c and NDVI (R² = 0.67, p < 0.01). The regression model produced a crop coefficient map, valuable to support precise irrigation management and drought prevention, considering the heterogeneity at the farm scale. Full article

Calmodulin (Calm), a crucial Ca²⁺ sensor, plays an important role in calcium-dependent signal transduction cascades. However, the expression and the relevance of Calm in stress and immune response have not been characterized in Megalobrama amblycephala. In this study, we identified the full-length cDNA of Calm (termed MaCalm) in blunt snout bream M. amblycephala, and analyzed MaCalm expression patterns in response to cadmium and Aeromonas hydrophila challenges. MaCalm was 1603 bp long, including a 5′-terminal untranslated region (UTR) of 97 bp, a 3′-terminal UTR of 1056 bp and an open reading frame (ORF) of 450 bp encoding a polypeptide of 149 amino acids with a calculated molecular weight (MW) of 16.84 kDa and an isoelectric point (pI) of 4.09. Usually, MaCalm contains four conservative EF hand motifs. The phylogenetic tree analysis indicated that the nucleotide sequence of MaCalm specifically clustered with Ctenopharyngodon idella with high identity (98.33%). Tissue distribution analysis demonstrated that the ubiquitous expression of MaCalm mRNA was found in all tested tissues, with the highest expression in the brain and the lowest expression in muscle. MaCalm showed significant upregulation at 14 d and 28 d post exposure to varying concentrations of cadmium in the liver; HSP70 transcripts in the liver significantly upregulated at 14 d post exposure to different concentrations of cadmium. Moreover, in response to the A. hydrophila challenge in vivo, MaCalm transcripts in the liver first increased and then decreased, but MaCalm transcripts in the kidney declined gradually with prolonged infection. After the A. hydrophila challenge, the expression level of HSP70 was significantly downregulated at 24 h in the liver and its expression level was notably downregulated at 12 h and at 24 h in the kidney. Collectively, our results suggest that MaCalm possesses vital roles in stress and immune response in M. amblycephala. Full article

Climate change poses significant challenges to agricultural productivity, making the efficient management of water resources essential for sustainable crop production. The assessment of plant water status is crucial for understanding plant physiological responses to water stress and optimizing water management practices in agriculture. Proximal and remote sensing techniques have emerged as powerful tools for the non-destructive, efficient, and spatially extensive monitoring of plant water status. This review aims to examine the recent advancements in proximal and remote sensing methodologies utilized for assessing the water status, consumption, and irrigation needs of fruit tree crops. Several proximal sensing tools have proved useful in the continuous estimation of tree water status but have strong limitations in terms of spatial variability. On the contrary, remote sensing technologies, although less precise in terms of water status estimates, can easily cover from medium to large areas with drone or satellite images. The integration of proximal and remote sensing would definitely improve plant water status assessment, resulting in higher accuracy by integrating temporal and spatial scales. This paper consists of three parts: the first part covers current plant-based proximal sensing tools, the second part covers remote sensing techniques, and the third part includes an update on the on the combined use of the two methodologies. Full article

As water temperatures rise in streams due to global temperature variations, dams, and increased water usage, native fish species face uncertain futures. Our study defines the thermal limits of flannelmouth sucker larvae. By raising sucker eggs at three acclimation temperatures (11 °C, 16 °C, and 22 °C), we defined ideal conditions for larval survival and the temperature tolerance range using critical thermal maximum (CTMax) and minimum (CTMin) trials. Larvae survived best at 16 °C. Within our three acclimation temperatures, our data suggest that larvae can survive static temperatures between 6.9 °C and 26.4 °C. Beyond an upper temperature of 34.8 °C and a lower temperature of 6.3 °C, these fish may fail to adapt. While flannelmouth suckers withstand high temperatures, even small temperature decreases prove detrimental. By defining the temperature limits of the flannelmouth sucker, we can make informed management decisions to preserve the populations of this desert fish. Full article

Hansenula polymorpha is a non-conventional and thermo-tolerant yeast that is well-known for its use in the industrial production of recombinant proteins. However, research to evaluate this yeast’s potential for the high-temperature fermentation of sugar to produce alcohols for biofuel applications is limited. The present work investigated a wild-type H. polymorpha strain (DSM 70277) for the production of ethanol at a temperature of 40 °C under limited oxygen presence by using a batch fermentation reactor. Fermentation experiments were performed using three types of sugar (glucose, fructose, xylose) as substrates with two initial inoculum concentrations (1.1 g·L⁻¹ and 5.0 g·L⁻¹). The maximum specific growth rates of H. polymorpha yeast were 0.121–0.159 h⁻¹ for fructose, 0.140–0.175 h⁻¹ for glucose, and 0.003–0.009 h⁻¹ for xylose. The biomass volumetric productivity was 0.270–0.473 g·L⁻¹h⁻¹ (fructose), 0.185–0.483 g·L⁻¹h⁻¹ (glucose), and 0.001–0.069 g·L⁻¹h⁻¹ (xylose). The overall yield of ethanol from glucose (0.470 g·g⁻¹) was higher than that from fructose (0.434 g·g⁻¹) and xylose (0.071 g·g⁻¹). The H. polymorpha yeast exhibited different behavior and efficacy regarding the use of glucose, fructose, and xylose as substrates for producing ethanol. The present knowledge could be applied to improve the fermentation process for valorization of waste biomass to produce bioethanol. Full article

Hydrolyzed royal jelly peptide (RJP) has garnered attention for its health-promoting functions. However, the potential applications of RJP in skincare have not been fully explored. In this study, we prepared RJP through the enzymatic hydrolysis of royal jelly protein with trypsin and investigated its antioxidant and anti-inflammatory properties on primary human dermal fibroblasts (HDFs). Our results demonstrate that RJP effectively inhibits oxidative damage induced by H₂O₂ and lipid peroxidation triggered by AAPH and t-BuOOH in HDFs. This effect may be attributed to the ability of RJP to enhance the level of glutathione and the activities of catalase and glutathione peroxidase 4, as well as its excellent iron chelating capacity. Furthermore, RJP modulates the NLRP3 inflammasome-mediated inflammatory response in HDFs, suppressing the mRNA expressions of NLRP3 and IL-1β in the primer stage induced by LPS and the release of mature IL-1β induced by ATP, monosodium urate, or nigericin in the activation stage. RJP also represses the expressions of COX2 and iNOS induced by LPS. Finally, we reveal that RJP exhibits superior antioxidant and anti-inflammatory properties over unhydrolyzed royal jelly protein. These findings suggest that RJP exerts protective effects on skin cells through antioxidative and anti-inflammatory mechanisms, indicating its promise for potential therapeutic avenues for managing oxidative stress and inflammation-related skin disorders. Full article

To determine the evolution of microbial community and microbial shift under anaerobic processes, this study investigates the use of denaturing gradient gel electrophoresis (DGGE). In the DGGE, short- and medium-sized DNA fragments are separated based on their melting characteristics, and this technique is used in this study to understand the dominant bacterial community in mesophilic and thermophilic anaerobic digestion processes. Dairy manure is known for emitting greenhouse gases (GHGs) such as methane, and GHG emissions from manure is a biological process that is largely dependent on the manure conditions, microbial community presence in manure, and their functions. Additional efforts are needed to understand the GHG emissions from manure and develop control strategies to minimize the biological GHG emissions from manure. To study the microbial shift during anaerobic processes responsible for GHG emission, we conducted a series of manure anaerobic digestion experiments, and these experiments were conducted in lab-scale reactors operated under various temperature conditions (28 °C, 36 °C, 44 °C, and 52 °C). We examined the third variable region (V3) of the 16S rRNA gene fingerprints of bacterial presence in anaerobic environment by PCR amplification and DGGE separation. Results showed that bacterial community was affected by the temperature conditions and anaerobic incubation time of manure. The microbial community structure of the original manure changed over time during anaerobic processes, and the community composition changed substantially with the temperature of the anaerobic process. At Day 0, the sequence similarity confirmed that most of the bacteria were similar (>95%) to Acinetobacter sp. (strain: ATCC 31012), a Gram-negative bacteria, regardless of temperature conditions. At day 7, the sequence similarity of DNA fragments of reactors (28 °C) was similar to Acinetobacter sp.; however, the DNA fragments of effluent of reactors at 44 °C and 52 °C were similar to Coprothermobacter proteolyticus (strain: DSM 5265) (similarity: 97%) and Tepidimicrobium ferriphilum (strain: DSM 16624) (similarity: 100%), respectively. At day 60, the analysis showed that DNA fragments of effluent of 28 °C reactor were similar to Galbibacter mesophilus (strain: NBRC 10162) (similarity: 87%), and DNA fragments of effluent of 36 °C reactors were similar to Syntrophomonas curvata (strain: GB8-1) (similarity: 91%). In reactors with a relatively higher temperature, the DNA fragments of effluent of 44 °C reactor were similar to Dielma fastidiosa (strain: JC13) (similarity: 86%), and the DNA fragments of effluent of 52 °C reactor were similar to Coprothermobacter proteolyticus (strain: DSM 5265) (similarity: 99%). To authors’ knowledge, this is one of the few studies where DGGE-based approach is utilized to study and compare microbial shifts under mesophilic and thermophilic anaerobic digestions of manure simultaneously. While there were challenges in identifying the bands during gradient gel electrophoresis, the joint use of DGGE and sequencing tool can be potentially useful for illustrating and comparing the change in microbial community structure under complex anaerobic processes and functionality of microbes for understanding the consequential GHG emissions from manure. Full article

The reliable transfer of bioprocesses from single-use bioreactors (SUBs) of different scales to conventional stainless steel stirred-tank bioreactors is of steadily growing interest. In this publication, a scale-up study for SUBs with volumes of 200 L and 2000 L and the transfer to an industrial-scale conventional stainless steel stirred-tank bioreactor with a volume of 15,000 L is presented. The scale-up and transfer are based on a comparison of mixing times and the modeling of volumetric mass transfer coefficients k_La, measured in all three reactors in aqueous PBS/Kolliphor solution. The mass transfer coefficients are compared with the widely used correlation of van’t Riet at constant stirrer tip speeds. It can be shown that a van’t Riet correlation enables a robust and reliable prediction of mass transfer coefficients on each scale for a wide range of stirrer tip speeds and aeration rates. The process transfer from single-use bioreactors to conventional stainless steel stirred-tank bioreactors is proven to be uncritical concerning mass transfer performance. This provides higher flexibility with respect to bioreactor equipment considered for specific processes. Full article

Although fully automated volumetric approaches for monitoring brain tumor response have many advantages, most available deep learning models are optimized for highly curated, multi-contrast MRI from newly diagnosed gliomas, which are not representative of post-treatment cases in the clinic. Improving segmentation for treated patients is critical to accurately tracking changes in response to therapy. We investigated mixing data from newly diagnosed (n = 208) and treated (n = 221) gliomas in training, applying transfer learning (TL) from pre- to post-treatment imaging domains, and incorporating spatial regularization for T2-lesion segmentation using only T2 FLAIR images as input to improve generalization post-treatment. These approaches were evaluated on 24 patients suspected of progression who had received prior treatment. Including 26% of treated patients in training improved performance by 13.9%, and including more treated and untreated patients resulted in minimal changes. Fine-tuning with treated glioma improved sensitivity compared to data mixing by 2.5% (p < 0.05), and spatial regularization further improved performance when used with TL by 95th HD, Dice, and sensitivity (6.8%, 0.8%, 2.2%; p < 0.05). While training with ≥60 treated patients yielded the majority of performance gain, TL and spatial regularization further improved T2-lesion segmentation to treated gliomas using a single MR contrast and minimal processing, demonstrating clinical utility in response assessment. Full article

In order to improve the plugging performance of high-temperature and high-salt oil reservoir plugging agents, this paper utilizes a copolymer composed of acrylamide and 2-acrylamide-2-methylpropanesulfonic acid (AM/AMPS) as the polymer, polyethyleneimine as the cross-linking agent, and nylon fiber as the stabilizer to develop a high-temperature- and high-salt-resistant gel system. This study analyzed and evaluated the temperature resistance, salt resistance and blocking performance of the gel system. The evaluation results show that the gel-forming strength of this gel system can reach an H level, and it has good thermal stability at the high temperature of 130 °C. At the high salinity of 240,720 mg/L, the syneresis rate remains below 2.5%, and the gel-forming time is greater than 15 h; the higher the temperature, the shorter the gelling time. The results of our sand-filled pipe-plugging experiment show that the gel system can adapt to sand-filled pipes with different levels of permeability, and reaching a plugging rate of 94%. Full article

Hydraulic fracturing is vital in recovering hydrocarbons from oil and gas reservoirs. It involves injecting a fluid under high pressure into reservoir rock. A significant part of fracturing fluids is the addition of polymers that become gels or gel-like under reservoir conditions. Polymers are employed as viscosifiers and friction reducers to provide proppants in fracturing fluids as a transport medium. There are numerous systems for fracturing fluids based on macromolecules. The employment of natural and man-made linear polymers, and also, to a lesser extent, synthetic hyperbranched polymers, as additives in fracturing fluids in the past one to two decades has shown great promise in enhancing the stability of fracturing fluids under various challenging reservoir conditions. Modern innovations demonstrate the importance of developing chemical structures and properties to improve performance. Key challenges include maintaining viscosity under reservoir conditions and achieving suitable shear-thinning behavior. The physical architecture of macromolecules and novel crosslinking processes are essential in addressing these issues. The effect of macromolecule interactions on reservoir conditions is very critical in regard to efficient fluid qualities and successful fracturing operations. In future, there is the potential for ongoing studies to produce specialized macromolecular solutions for increased efficiency and sustainability in oil and gas applications. Full article

The escalating utilization of titanium dioxide nanoparticles (TiO₂ NPs) in everyday products has sparked concerns regarding their potential hazards to pregnant females and their offspring. To address these concerns and shed light on their undetermined adverse effects and mechanisms, we established a pregnant rat model to investigate the impacts of TiO₂ NPs on both maternal and offspring health and to explore the underlying mechanisms of those impacts. Pregnant rats were orally administered TiO₂ NPs at a dose of 5 mg/kg body weight per day from GD5 to GD18 during pregnancy. Maternal body weight, organ weight, and birth outcomes were monitored and recorded. Maternal pathological changes were examined by HE staining and TEM observation. Maternal blood pressure was assessed using a non-invasive blood analyzer, and the urinary protein level was determined using spot urine samples. Our findings revealed that TiO₂ NPs triggered various pathological alterations in maternal liver, kidney, and spleen, and induced maternal preeclampsia-like syndrome, as well as leading to growth restriction in the offspring. Further examination unveiled that TiO₂ NPs hindered trophoblastic cell invasion into the endometrium via the promotion of autophagy. Consistent hypertension and proteinuria resulted from the destroyed the kidney GBM. In total, an exposure to TiO₂ NPs during pregnancy might increase the risk of human preeclampsia through increased maternal arterial pressure and urinary albumin levels, as well as causing fetal growth restriction in the offspring. Full article