Eczema (atopic dermatitis, AD) is a skin disease characterized by skin barrier dysfunction due to various factors, including genetics, immune system abnormalities, and environmental triggers. Application of emollients and topical drugs such as corticosteroids and calcineurin inhibitors form the mainstay of treatments for this challenging condition. This review aims to summarize the recent advances made in phytochemical-based topical applications to treat AD and the different carriers that are being used. In this review, the clinical efficacy of several plant extracts and bioactive phytochemical compounds in treating AD are discussed. The anti-atopic effects of the herbs are evident through improvements in the Scoring Atopic Dermatitis (SCORAD) index, reduced epidermal thickness, decreased transepidermal water loss, and alleviated itching and dryness in individuals affected by AD as well as in AD mouse models. Histopathological studies and serum analyses conducted in AD mouse models demonstrated a reduction in key inflammatory factors, including thymic stromal lymphopoietin (TSLP), serum immunoglobulin E (IgE), and interleukins (IL). Additionally, there was an observed upregulation of the filaggrin (FLG) gene, which regulates the proteins constituting the stratum corneum, the outermost layer of the epidermis. Carriers play a crucial role in topical drug applications, influencing dose delivery, retention, and bioavailability. This discussion delves into the efficacy of various nanocarriers, including liposomes, ethosomes, nanoemulsions, micelles, nanocrystals, solid-lipid nanoparticles, and polymeric nanoparticles. Consequently, the potential long-term side effects such as atrophy, eruptions, lymphoma, pain, and allergic reactions that are associated with current topical treatments, including emollients, topical corticosteroids, topical calcineurin inhibitors, and crisaborole, can potentially be mitigated through the use of phytochemical-based natural topical treatments. Full article

The use of artificial water points for wildlife in African savannah ecosystems has been widely criticised for affecting the distribution of wildlife and initiating changes in the heterogeneity of natural landscapes. We examined the spatiotemporal variations in the landscape before and after the installation of an artificial water point by integrating the analysis of vegetation and soil spectral response patterns with a supervised learning random forest model between 2002 and 2022 in Chobe Enclave, Northern Botswana. Our results revealed that the study area is characterised by animal species such as Equus quagga, Aepyceros melampus, and Loxodonta africana. The findings also showed that the main vegetation species in the study area landscape include Combretum elaeagnoides, Vachellia luederitzii, and Combretum hereroense. The artificial water point induced disturbances on a drought-vulnerable landscape which affected vegetation heterogeneity by degrading the historically dominant vegetation cover types such as Colophospermum mopane, Dichrostachys cinerea, and Cynodon dactylon. The immediate years following the artificial water point installation demonstrated the highest spectral response patterns by vegetation and soil features attributed to intense landscape disturbances due to abrupt high-density aggregation of wildlife around the water point. Landscapes were strongly homogenised in later years (2022), as shown by overly overlapping spectral patterns owing to an increase in dead plant-based material and senescent foliage due to vegetation toppling and trampling. The landscape disturbances disproportionately affected mopane-dominated woodlands compared to other vegetation species as indicated by statistically significant land cover change obtained from a random forest classification. The woodlands declined significantly (p < 0.05) within 0–0.5 km, 0.5–1 km, 1–5 km, and 5–10 km distances after the installation of the water point. The results of this study indicate that continuous nonstrategic and uninformed use of artificial water points for wildlife will trigger ecological alterations in savannah ecosystems. Full article

Traditional collaborative filtering (CF)-based recommendation systems are often challenged by data sparsity. The recent research has recognized the potential of integrating new information sources, such as knowledge graphs, to address this issue. However, a common drawback is the neglect of the interplay between user–item interaction data and knowledge graph information, resulting in insufficient model performance due to coarse-grained feature fusion. To bridge this gap, in this paper, we propose a novel graph neural network (GNN) model called KGCFRec, which leverages both Knowledge Graph and user–item Collaborative Filtering information for an enhanced Recommender system. KGCFRec employs a dual-channel information propagation and aggregation mechanism to generate distinct representations for the collaborative knowledge graph and the user–item interaction graph. This is followed by an attention mechanism that adaptively fuses the knowledge graph with collaborative information, thereby refining the representations and narrowing the gap between them. The experiments conducted on three real-world datasets demonstrate that KGCFRec outperforms state-of-the-art methods. These promising results underscore the capability of KGCFRec to enhance recommendation accuracy by integrating knowledge graph information. Full article

Background: This study investigated in vivo regulation and levels of active matrix metalloproteinase-8 (aMMP-8), a major collagenolytic protease, in periodontitis. Methods: Twenty-seven adults with chronic periodontitis (CP) and 30 periodontally healthy controls (HC) were enrolled in immunohistochemistry and transcriptomics analytics in order to assess Treponema denticola (Td) dentilisin and MMP-8 immunoexpression, mRNA expression of MMP-8 and its regulators (IL-1β, MMP-2, MMP-7, TIMP-1). Furthermore, the periodontal anti-infective treatment effect was monitored by four different MMP-8 assays (aMMP-8-IFMA, aMMP-8-Oralyzer, MMP-8-activity [RFU/minute], and total MMP-8 by ELISA) among 12 CP (compared to 25 HC). Results: Immunohistochemistry revealed significantly more Td-dentilisin and MMP-8 immunoreactivities in CP vs. HC. Transcriptomics revealed significantly elevated IL-1β and MMP-7 RNA expressions, and MMP-2 RNA was slightly reduced. No significant differences were recorded in the relatively low or barely detectable levels of MMP-8 mRNAs. Periodontal treatment significantly decreased all MMP-8 assay levels accompanied by the assessed clinical indices (periodontal probing depths, bleeding-on-probing, and visual plaque levels). However, active but not total MMP-8 levels persisted higher in CP than in periodontally healthy controls. Conclusion: In periodontal health, there are low aMMP-8 levels. The presence of Td-dentilisin in CP gingivae is associated with elevated aMMP-8 levels, potentially contributing to a higher risk of active periodontal tissue collagenolysis and progression of periodontitis. This can be detected by aMMP-8-specific assays and online/real-time aMMP-8 chair-side testing. Full article

In order to reduce the toxicological impact on healthy cells and to improve the therapeutic response, many drug delivery systems have been fabricated and analysed, involving the use of different natural and synthetic materials at macro-, micro- and nanoscales. Among the natural materials which have demonstrated a huge potential for the development of effective drug delivery systems, silk fibroin has emerged for its excellent biological properties and for the possibility to be processed in a wide range of forms, which can be compliant with multiple active molecules and pharmaceutical ingredients for the treatment of various diseases. This review aims at presenting silk fibroin as an interesting biopolymer for applications in drug delivery systems, exploring the results obtained in recent works in terms of technological progress and effectiveness in vitro and in vivo. Full article

The transition from batch to continuous production in the catalytic hydrogenation of nitrile butadiene rubber (NBR) into hydrogenated NBR (HNBR) marks a significant advance for applications under demanding conditions. This study introduces a continuous process utilizing a static mixer (SM) reactor, which notably achieves a hydrogenation conversion rate exceeding 97%. We thoroughly review a mechanistic model of the SM reactor to elucidate the internal dynamics governing the hydrogenation process and address the inherent uncertainties in key parameters such as the Peclet number (Pe), dimensionless time (θτ), reaction coefficient (R), and flow rate coefficient (q). A comprehensive dataset generated from varied parameter values serves as the basis for training an artificial neural network (ANN), which is then compared against traditional models including linear regression, decision tree, and random forest in terms of efficacy. Our results clearly demonstrate the ANN’s superiority in predicting the degree of hydrogenation, achieving the lowest root mean squared error (RMSE) of 3.69 compared to 21.90 for linear regression, 4.94 for decision tree, and 7.51 for random forest. The ANN’s robust capability for modeling complex nonlinear relationships and dynamics significantly enhances decision-making, planning, and optimization of the reactor, reducing computational demands and operational costs. In other words, this approach allows users to rely on a single ML-based model instead of multiple mechanistic models for reflecting the effects of possible uncertainties. Additionally, a feature importance study validates the critical impact of time and element number on the hydrogenation process, further supporting the ANN’s predictive accuracy. These findings underscore the potential of ML-based models in streamlining and enhancing the efficiency of chemical production processes. Full article

For future large-scale CubeSat applications in orbit, the deployer must accommodate a greater number of CubeSats and facilitate cluster releases. This paper introduces an improved A* algorithm tailored for CubeSat in-orbit transfer path planning. Unlike the traditional A* algorithm, this enhanced version incorporates a path coordination strategy to manage congestion caused by the simultaneous transfer of many CubeSats, ensuring they reach their designated release positions smoothly and thus significantly boosting the efficiency of CubeSat transfers. Additionally, the algorithm develops a cost model for attitude disturbances on the electromagnetic conveying platform and crafts an improved cost function. It strategically balances the reduction in attitude disturbances caused by CubeSat transfers with the efficiency of these transfers. The primary goal is to minimize platform disturbances while optimizing the number of steps CubeSats need to reach their intended positions. The effectiveness of this algorithm is demonstrated through detailed case studies, which confirm that during the CubeSat transfer process, the platform’s attitude remains stable, and the transfer efficiency is well-managed, achieving efficient path planning for the in-orbit transfer of numerous CubeSats. Full article

Recent findings indicate that air pollution contributes to the onset and advancement of chronic obstructive pulmonary disease (COPD). Nevertheless, there is insufficient research indicating that air pollution is linked to COPD in the region of inland northwest China. Daily hospital admission records for COPD, air pollutant levels, and meteorological factor information were collected in Jiuquan for this study between 1 January 2018 and 31 December 2019. We employed a distributed lag non-linear model (DLNM) integrated with the generalized additive model (GAM) to assess the association between air pollution and hospital admissions for COPD with single lag days from lag0 to lag7 and multiday moving average lag days from lag01 to lag07. For example, the pollutant concentration on the current day was lag0, and on the prior 7th day was lag7. The present and previous 7-day moving average pollutant concentration was lag07. Gender, age, and season-specific stratified analyses were also carried out. It is noteworthy that the delayed days exhibited a different pattern, and the magnitude of associations varied. For NO₂ and CO, obvious associations with hospitalizations for COPD were found at lag1, lag01–lag07, and lag03–lag07, with the biggest associations at lag05 and lag06 [RR = 1.015 (95%CI: 1.008, 1.023) for NO₂, RR = 2.049 (95%CI: 1.416, 2.966) for CO], while only SO₂ at lag02 was appreciably linked to hospitalizations for COPD [1.167 (95%CI: 1.009, 1.348)]. In contrast, short-term encounters with PM_2.5, PM₁₀, and O₃ were found to have no significant effects on COPD morbidity. The lag effects of NO₂ and CO were stronger than those of PM_2.5 and PM₁₀. Males and those aged 65 years or older were more vulnerable to air pollution. When it came to the seasons, the impacts appeared to be more pronounced in the cold season. In conclusion, short-term encounters with NO₂ and CO were significantly correlated with COPD hospitalization in males and the elderly (≥65). Full article

Tectona grandis L. f. (teak) is highly valued in the international market, but its volume and properties vary depending on its genetic material and planting site. Evaluating these factors is crucial for promoting new plantations. Therefore, this study aimed to assess the impact of genetic material (clones TG1 and TG3 and seminal material) and planting site (Nova Maringá and Água Boa, Mato Grosso, Brazil) on morphological parameters (heartwood, sapwood, bark, pith proportions, and pith eccentricity), physical properties (shrinkage and air-dry density), and mechanical properties (static bending strength—fm, compressive strength—fc0, Janka hardness—fH90, and shear strength—fv0). For this purpose, we sampled five trees aged 13 years per genetic material from commercial plantations. In Nova Maringá, trees exhibited, on average, 56.07% heartwood, while in Água Boa, this value was less than 50%. Seminal material showed the lowest percentage of heartwood (49.2%). The pith percentage was significantly greater in Água Boa than in Nova Maringá, regardless of the genetic material. We observed the highest standard deviation (5.61) in pith eccentricity for the seminal material. Both the planting site and genetic material influenced the air-dry density (~12% moisture content), which ranged from 0.535 to 0.618 g·cm⁻³. Trees grown in Nova Maringá produced wood with higher dimensional stability than those from Água Boa, exhibiting a 14% lower radial shrinkage and a 6% lower volumetric variation. In Nova Maringá, the wood from the seminal material exhibited greater resistance. On the other hand, in Água Boa, that material showed lower resistance (fv0, fm, and fc0), or there was no significant difference (fH90) compared to the clonal materials. When comparing the clonal materials (TG1 and TG3) at each planting site, they demonstrated similar mechanical properties. The variability in physical and mechanical properties among different genetic materials and planting locations highlights the need to select appropriate teak genetic materials for each region. We concluded that more productive teak clones can be selected without compromising the physical and mechanical properties of the wood. Full article

Since the 16th century, Western countries have conducted extensive plant collections in Asia, particularly in China, driven by the need to collect botanical resources and foster academic development. These activities have not only significantly enriched the Western botanical specimen collections but have also had a profound impact on the development of related disciplines such as botany, ecology, and horticulture. During this process, a large number of renowned plant hunters emerged, whose discoveries and contributions are still remembered today. George Forrest (1873–1932) was one of these distinguished plant hunters. From 1904 to 1932, he visited China seven times to collect plants and became famous for the regional distinctiveness of the species he collected. However, due to the lack of systematic collection, organization, and analysis of specimens collected by Forrest, only a few species, such as the species Rhododendron, are well-known among the many species he introduced to the West. Furthermore, the personal collecting characteristics and the characteristic species collected by Forrest are also not clear. This limits a comprehensive understanding of the specimen collection history and impact of Forrest in China. Therefore, systematic organization and analysis of Forrest’s plant specimens collected in China are crucial to understanding his impact on botanical classification, Rhododendrons introduction, global horticulture, and plant propagation. This study aims to systematically organize and analyze the plant specimens collected by George Forrest in China to investigate the family, genus, and species composition of the collected specimens and the seven collection expeditions of Forrest in China, as well as the time and altitude of these collections. Furthermore, it seeks to discuss Forrest’s scientific contributions to the global spread of plants, the widespread application of the Rhododendron, and his impact on the development of modern gardens, providing a theoretical basis and data reference for related research and professional development. To this end, we extensively consulted important historical literature related to Forrest and systematically collected data from online specimen databases. The conclusions drawn from the available data include 38,603 specimens, with 26,079 collection numbers, belonging to 233 families, 1395 genera, and 5426 species, which account for 48.24%, 32.63%, and 14.17% of the plant families, genera, and species in China, respectively. Rhododendron specimens made up 17.20% of the specimens collected in this study. The collection locations cover three provinces or autonomous regions, 11 prefecture-level cities, and 25 counties. Furthermore, we found that Forrest’s collections were concentrated in spring and summer, mainly in high-altitude areas, with 135 species found below 1500 m and 3754 species at 1500 m and above. Rhododendron specimens were mostly found above 3000 m. Full article

Papillary thyroid carcinoma (PTC) presents a significant health concern, particularly among Hispanic women in the United States, who exhibit a disproportionately higher chance of developing an advanced disease when compared to the non-Hispanic population. Emerging evidence suggests coagulation factor X, encoded by the F10 gene, has a potential role in inhibiting cancer cell migration. However, comprehensive investigations into the differential expression patterns of F10 in Hispanic versus non-Hispanic females remain limited. RNA-sequencing data were acquired from the TCGA database for white female patients, 166 non-Hispanic and 25 Hispanic. A statistically significant (p < 0.05) 2.06-fold increase in F10 expression levels was detected in disease-free tumors compared to recurrent PTC tumors. Furthermore, an increase in F10 gene expression levels was also observed, corresponding to approximately a 1.74-fold increase in non-Hispanic patients compared to Hispanic patients. The probability of tumor recurrence was 1.82 times higher in the cohort with low expression of F10 compared to the high-expression cohort, correlating with the lower disease-free rates observed in the Hispanic patient cohort when compared to non-Hispanics. This finding underscores the relevance of ethnic disparities in molecular profiles for understanding cancer susceptibility. Identifying F10 as a potential prognostic biomarker highlights avenues for targeted interventions and contributes to improving diagnostic and treatment strategies for diverse patient populations. Full article

Unidirectional porous hydroxyapatite (UDPHAp) was developed as a remarkable scaffold characterized by a distinct structure with unidirectional pores oriented in the horizontal direction and connected through interposes. We evaluated the radiographic changes, clinical outcomes, and complications following UDPHAp implantation for the treatment of bone tumors. Excellent bone formation within and around the implant was observed in all patients treated with intralesional resection and UDPHAp implantation for benign bone tumors. The absorption of UDPHAp and remodeling of the bone marrow space was observed in 45% of the patients at a mean of 17 months postoperatively and was significantly more common in younger patients. Preoperative cortical thinning was completely regenerated in 84% of patients at a mean of 10 months postoperatively. No complications related to the implanted UDPHAp were observed. In a pediatric patient with bone sarcoma, when the defect after fibular resection was filled with UDPHAp implants, radiography showed complete resorption of the implant and clear formation of cortex and marrow in the resected part of the fibula. The patient could walk well without crutches and participate in sports activities. UDPHAp is a useful bone graft substitute for the treatment of benign bone tumors, and the use of this material has a low complication rate. We also review and discuss the potential of UDPHAp as a bone graft substitute in the clinical setting of orthopedic surgery. Full article

Whilst study abroad (SA) periods hold much promise for foreign language development, increasing research suggests sojourners’ experiences are unique, and language development does not always follow a linear trajectory. For some learners, SA has little impact on their language performance despite the affordances of L2 immersion (the Survivors). Other learners maximise the potential of SA, and this has a positive impact on their language development (the Thrivers). This paper examines the selected cases of four Japanese learners of English and their request language performance during a 10-month SA in the UK. Changes in pragmatic knowledge (based on appropriateness ratings) were documented at three equidistant time points. Language contact profile data also provided quantitative insights into the learners’ extracurricular language use and qualitative personal reflections. The selected cases illustrate two learners surviving the SA experience, showing minimal change in their request performance. The other two learners thrived during SA, showing accelerated performance in terms of lexical variation at the production level. This paper reports on the case histories of these learners to better understand these unique experiences and pragmatic discrepancies. Suggestions for how learners might be more pragmatically successful during SA are also offered. Full article

This study explores trust dynamics within online social networks, blending social science theories with advanced machine-learning (ML) techniques. We examine trust’s multifaceted nature—definitions, types, and mechanisms for its establishment and maintenance—and analyze social network structures through graph theory. Employing a diverse array of ML models (e.g., KNN, SVM, Naive Bayes, Gradient Boosting, and Neural Networks), we predict connection strengths on Facebook, focusing on model performance metrics such as accuracy, precision, recall, and F1-score. Our methodology, executed in Python using the Anaconda distribution, unveils insights into trust formation and sustainability on social media, highlighting the potent application of ML in understanding these dynamics. Challenges, including the complexity of modeling social behaviors and ethical data use concerns, are discussed, emphasizing the need for continued innovation. Our findings contribute to the discourse on trust in social networks and suggest future research directions, including the application of our methodologies to other platforms and the study of online trust over time. This work not only advances the academic understanding of digital social interactions but also offers practical implications for developers, policymakers, and online communities. Full article

As a space camera works in orbit, the stress rebound caused by gravity inevitably results in the deformation of its optomechanical structure, and the relative position change between different optical components will affect the Line-Of-Sight pointing of the camera. In this paper, the optical sensitivity calculation of a space camera’s Line-Of-Sight pointing is realized based on the optomechanical constraint equations, and the Line-Of-Sight equations are constructed using the second type of response (DRESP2) method to realize an optomechanical integrated analysis of the camera’s Line-Of-Sight stability at the structural finite element solver level. The verification results show that the Line-Of-Sight stability error is 6.38%, meaning that this method can identify the sensitive optical elements of the optical system efficiently and quickly. Thus, the method in this paper has important significance as a reference for the analysis of the Line-Of-Sight stability of complex optical systems. Full article

Offshore wind turbines operating in frigid and humid climates may encounter icing on the blade surface. This phenomenon adversely impacts the aerodynamic efficiency of the turbine, consequently diminishing power generation efficacy. Investigating the distribution characteristics of icing on the blade surface is imperative. Hence, this study undertook icing wind tunnel tests on segments of DU25 airfoil, a prevalent type for offshore wind turbines, to examine such characteristics as different chord lengths and angles of attack. The results show a simultaneous increase in the blade icing area and growth rate of the net icing area with augmenting the chord length and angles of attack. The total icing area rate decreases by a factor of two when the chord length is doubled. The relative positioning of icing and the average icing thickness remain consistent across the airfoil blades with varying chord lengths. Comparing the icing shapes on blades of varying scales shows a similarity ranging from 84.06% to 88.72%. The results of this study provide insight into the icing characteristics of offshore wind turbines. Full article

Background: Left ventricular hypertrophy (LVH) is a powerful predictor of future cardiovascular events. Objectives: The objectives of this study were to conduct a systematic review of machine learning (ML) algorithms for the identification of LVH and compare them with respect to the classical features of test sensitivity, specificity, accuracy, ROC and the traditional ECG criteria for LVH. Methods: A search string was constructed with the operators “left ventricular hypertrophy, electrocardiogram” AND machine learning; then, Medline and PubMed were systematically searched. Results: There were 14 studies that examined the detection of LVH utilizing the ECG and utilized at least one ML approach. ML approaches encompassed support vector machines, logistic regression, Random Forest, GLMNet, Gradient Boosting Machine, XGBoost, AdaBoost, ensemble neural networks, convolutional neural networks, deep neural networks and a back-propagation neural network. Sensitivity ranged from 0.29 to 0.966 and specificity ranged from 0.53 to 0.99. A comparison with the classical ECG criteria for LVH was performed in nine studies. ML algorithms were universally more sensitive than the Cornell voltage, Cornell product, Sokolow-Lyons or Romhilt-Estes criteria. However, none of the ML algorithms had meaningfully better specificity, and four were worse. Many of the ML algorithms included a large number of clinical (age, sex, height, weight), laboratory and detailed ECG waveform data (P, QRS and T wave), making them difficult to utilize in a clinical screening situation. Conclusions: There are over a dozen different ML algorithms for the detection of LVH on a 12-lead ECG that use various ECG signal analyses and/or the inclusion of clinical and laboratory variables. Most improved in terms of sensitivity, but most also failed to outperform specificity compared to the classic ECG criteria. ML algorithms should be compared or tested on the same (standard) database. Full article

The United Arab Emirates has very little data on the incidence or prevalence of fungal diseases. Using total and underlying disease risk populations and likely affected proportions, we have modelled the burden of fungal disease for the first time. The most prevalent serious fungal conditions are recurrent vulvovaginitis (~190,000 affected) and fungal asthma (~34,000 affected). Given the UAE’s low prevalence of HIV, we estimate an at-risk population of 204 with respect to serious fungal infections with cryptococcal meningitis estimated at 2 cases annually, 15 cases of Pneumocystis pneumonia (PCP) annually, and 20 cases of esophageal candidiasis in the HIV population. PCP incidence in non-HIV patients is estimated at 150 cases annually. Likewise, with the same low prevalence of tuberculosis in the country, we estimate a total chronic pulmonary aspergillosis prevalence of 1002 cases. The estimated annual incidence of invasive aspergillosis is 505 patients, based on local data on rates of malignancy, solid organ transplantation, and chronic obstructive pulmonary disease (5.9 per 100,000). Based on the 2022 annual report of the UAE’s national surveillance database, candidaemia annual incidence is 1090 (11.8/100,000), of which 49.2% occurs in intensive care. Fungal diseases affect ~228,695 (2.46%) of the population in the UAE. Full article

Bacterial biofilms are hardy, adaptable colonies, evading immune recognition while triggering and sustaining inflammation. The goals for this study were to present a method for testing the immunogenicity of secreted metabolites from pathogenic biofilm and to document whether biofilm treated with a nutraceutical enzyme and botanical blend (NEBB) showed evidence of reprogrammed bacterial metabolism, potentially becoming more recognizable to the immune system. We screened immune-modulating properties of metabolites from established biofilm from Pseudomonas aeruginosa (Pa), Stapholycoccus simulans (Ss), and Borrelia burgdorferi (Bb). Secreted metabolites significantly increased the cytokine production by human peripheral blood mononuclear cells, including Interleukin-1-beta (IL-1β), Interleukin-6 (IL-6), macrophage inflammatory protein-1-alpha (MIP-1α), tumor necrosis factor-alpha (TNF-α), interleukin-1 receptor antagonist (IL-1ra), and interleukin-10 (IL-10). Pa metabolites triggered the most robust increase in IL-1β, whereas Bb metabolites triggered the most robust increase in IL-10. NEBB-disrupted biofilm produced metabolites triggering altered immune modulation compared to metabolites from untreated biofilm. Metabolites from NEBB-disrupted biofilm triggered increased MIP-1α levels and reduced IL-10 levels, suggesting a reduced ability to suppress the recruitment of phagocytes compared to untreated biofilm. The results suggest that nutraceutical biofilm disruption offers strategies for inflammation management in chronic infectious illnesses. Further clinical studies are warranted to evaluate clinical correlations in infected human hosts. Full article

The tomato is a fruit vegetable rich in nutritional and medicinal value grown in greenhouses and fields worldwide. It is severely sensitive to heat stress, which frequently occurs with rising global warming. Predictions indicate a 0.2 °C increase in average surface temperatures per decade for the next three decades, which underlines the threat of austere heat stress in the future. Previous studies have reported that heat stress adversely affects tomato growth, limits nutrient availability, hammers photosynthesis, disrupts reproduction, denatures proteins, upsets signaling pathways, and damages cell membranes. The overproduction of reactive oxygen species in response to heat stress is toxic to tomato plants. The negative consequences of heat stress on the tomato have been the focus of much investigation, resulting in the emergence of several therapeutic interventions. However, a considerable distance remains to be covered to develop tomato varieties that are tolerant to current heat stress and durable in the perspective of increasing global warming. This current review provides a critical analysis of the heat stress consequences on the tomato in the context of global warming, its innate response to heat stress, and the elucidation of domains characterized by a scarcity of knowledge, along with potential avenues for enhancing sustainable tolerance against heat stress through the involvement of diverse advanced technologies. The particular mechanism underlying thermotolerance remains indeterminate and requires further elucidatory investigation. The precise roles and interplay of signaling pathways in response to heat stress remain unresolved. The etiology of tomato plants’ physiological and molecular responses against heat stress remains unexplained. Utilizing modern functional genomics techniques, including transcriptomics, proteomics, and metabolomics, can assist in identifying potential candidate proteins, metabolites, genes, gene networks, and signaling pathways contributing to tomato stress tolerance. Improving tomato tolerance against heat stress urges a comprehensive and combined strategy including modern techniques, the latest apparatuses, speedy breeding, physiology, and molecular markers to regulate their physiological, molecular, and biochemical reactions. Full article

Talaromyces sp. DC2 is an endophytic fungus that was isolated from the stem of Catharanthus roseus (L.) G. Don in Hanoi, Vietnam and is capable of producing vinca alkaloids. This study utilizes the PacBio Sequel technology to completely sequence the whole genome of Talaromyces sp. DC2The genome study revealed that DC2 contains a total of 34.58 Mb spanned by 156 contigs, with a GC content of 46.5%. The identification and prediction of functional protein-coding genes, tRNA, and rRNA were comprehensively predicted and highly annotated using various BLAST databases, including non-redundant (Nr) protein sequence, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Clusters of Orthologous Groups (COG), and Carbohydrate-Active Enzymes (CAZy) databases. The genome of DC2 has a total of 149, 227, 65, 153, 53, and 6 genes responsible for cellulose, hemicellulose, lignin, pectin, chitin, starch, and inulin degradation, respectively. The Antibiotics and Secondary Metabolites Analysis Shell (AntiSMASH) analyses revealed that strain DC2 possesses 20 biosynthetic gene clusters responsible for producing secondary metabolites. The strain DC2 has also been found to harbor the DDC gene encoding aromatic L-amino acid decarboxylase enzyme. Conclusively, this study has provided a comprehensive understanding of the processes involved in secondary metabolites and the ability of the Talaromyces sp. DC2 strain to degrade plant cell walls. Full article

This study explores the multifaceted influence of litter size, maternal care, exercise, and aging on rats’ neurobehavioral plasticity and dentate gyrus microglia dynamics. Body weight evolution revealed a progressive increase until maturity, followed by a decline during aging, with larger litters exhibiting lower weights initially. Notably, exercised rats from smaller litters displayed higher body weights during the mature and aged stages. The dentate gyrus volumes showed no significant differences among groups, except for aged sedentary rats from smaller litters, which exhibited a reduction. Maternal care varied significantly based on litter size, with large litter dams showing lower frequencies of caregiving behaviors. Behavioral assays highlighted the detrimental impact of a sedentary lifestyle and reduced maternal care/large litters on spatial memory, mitigated by exercise in aged rats from smaller litters. The microglial dynamics in the layers of dentate gyrus revealed age-related changes modulated by litter size and exercise. Exercise interventions mitigated microgliosis associated with aging, particularly in aged rats. These findings underscore the complex interplay between early-life experiences, exercise, microglial dynamics, and neurobehavioral outcomes during aging. Full article