To solve the problem of urban freight demand and build an efficient, practical, intelligent, green, and sustainable new logistics system, this paper considers the application of the subway network to urban freight transportation and studies the location problem of subway transit stations in the urban freight network. According to the differences between different subway stations, the nodal degree, medial centrality, proximity centrality, and regional accessibility are proposed as the evaluation indexes, and the improved fuzzy analytic hierarchy method and entropy weight method are used to calculate the index weight. The TOPSIS evaluation method is used to evaluate the importance of each subway station, and the importance evaluation model of subway stations is constructed. Combined with the distribution location and transportation demand of urban express delivery outlets, a two-tier planning model for the location of subway transfer stations was constructed with total cost and customer satisfaction as the objective functions, and the case studies were carried out by taking Jiangning District, Lishui District, and Gaochun District of Nanjing as the research objects. The results show that Hohai University Focheng West Road, Zhengfang Middle Road, Qunli, and Gaochun can be transformed into subway transfer stations and used as transshipment centers of the urban cargo transportation network. Compared with the original ground transportation network, 52.87% of the ground transportation distance in the optimized transportation network is replaced by subway transportation, and the total cost of logistics transportation is reduced by 8.73%, which verifies the feasibility of subway for urban cargo transportation, reduces logistics transportation costs, and relieves the pressure of ground transportation, which is of great significance for the sustainable development of urban logistics. Full article

Financial inclusion (FI) relates to the access and availability of financial services to society, especially in low-income groups. FI is pivotal in achieving 7 of the 17 Sustainable Development Goals (SDGs). This paper explores the level of FI in the rural areas of Maharashtra and measures the impact of FI on the social conditions of Self-Help Groups (SHGs) prevalent in these areas. The study is based on a 424 SHGs survey conducted in the Pune, Thane, and Palghar districts of Maharashtra, India. The impact of FI on SHGs is evaluated using a Structural Equation Model (SEM). The results of the study show that physical banking services, Business Facilitators (BFs), and Business Correspondents (BCs) improve the social conditions of rural SHGs. Additionally, BCs and BFs mediate the relationship between physical banking services and social conditions. The study also reveals an insignificant association between BCs and BFs and insurance services. The present study highlights the importance of increasing the awareness of insurance policies through financial literacy programs and making timely availability and accessibility of BCs and BFs to enhance financial inclusion in rural areas. Full article

Road safety is a serious concern worldwide, and traffic signs play a critical role in confirming road safety, particularly in the context of AVs. Therefore, there is a need for ongoing advancements in traffic sign evaluation methodologies. This paper comprehensively analyzes the relationship between traffic sign retroreflectivity and LiDAR intensity to enhance visibility and communication on road networks. Using Python 3.10 programming and statistical techniques, we thoroughly analyzed handheld retroreflectivity coefficients alongside LiDAR intensity data from two LiDAR configurations: 2LRLiDAR and 1CLiDAR systems. The study focused specifically on RA1 and RA2 traffic sign classes, exploring correlations between retroreflectivity and intensity and identifying factors that may impact their performance. Our findings reveal variations in retroreflectivity compliance rates among different sign categories and color compositions, emphasizing the necessity for targeted interventions in sign design and production processes. Additionally, we observed distinct patterns in LiDAR intensity distributions, indicating the potential of LiDAR technology for assessing sign visibility. However, the limited correlations between retroreflectivity and LiDAR intensity underscore the need for further investigation and standardization efforts. This study provides valuable insights into optimizing traffic sign effectiveness, ultimately contributing to improved road safety conditions. Full article

Cochlear implants are crucial for addressing severe-to-profound hearing loss, with the success of the procedure requiring careful electrode placement. This scoping review synthesizes the findings from 125 studies examining the factors influencing insertion forces (IFs) and intracochlear pressure (IP), which are crucial for optimizing implantation techniques and enhancing patient outcomes. The review highlights the impact of variables, including insertion depth, speed, and the use of robotic assistance on IFs and IP. Results indicate that higher insertion speeds generally increase IFs and IP in artificial models, a pattern not consistently observed in cadaveric studies due to variations in methodology and sample size. The study also explores the observed minimal impact of robotic assistance on reducing IFs compared to manual methods. Importantly, this review underscores the need for a standardized approach in cochlear implant research to address inconsistencies and improve clinical practices aimed at preserving hearing during implantation. Full article

Finite Control Set Model Predictive Control (FCS-MPC) has the ability to achieve multi-objective optimization, but there are still many challenges. The key to realizing multi-objective optimization in FCS-MPC lies in the design of the cost function. However, the different dimensions of penalty terms in the cost function often lead to difficulties in designing weighting coefficients. Incorrect weighting coefficients may result in truncation errors in calculations of DSPs and FPGAs, thereby affecting the algorithm’s control performance. Therefore, this article focuses on a system driving an induction motor with a three-level Neutral Point Clamped (NPC) inverter, and selects stator current and switching frequency as penalty terms in the cost function. An improved method is proposed to unify the dimensions of both penalty terms in the cost function. By unifying the dimensions of the penalty terms, a simple design of weighting coefficients can be achieved. Subsequently, to balance the inverter’s switching frequency and the dynamic response performance of the motor, a composite cost function is further proposed. Finally, the rationality of the proposed method is validated through simulation and experimental platforms. Full article

This paper explores the intricate interplay between perceived challenge and narrative immersion within role-playing game (RPG) video games, motivated by the escalating influence of game difficulty on player choices. A quantitative methodology was employed, utilizing three specific questionnaires for data collection on player habits and experiences, perceived challenge, and narrative immersion. The study consisted of two interconnected stages: an initial research phase to identify and understand player habits, followed by an in-person intervention involving the playing of three distinct RPG video games. During this intervention, selected players engaged with the chosen RPG video games separately, and after each session, responded to two surveys assessing narrative immersion and perceived challenge. The study concludes that a meticulous adjustment of perceived challenge by video game studios moderately influences narrative immersion, reinforcing the enduring prominence of the RPG genre as a distinctive choice in narrative. Full article

In this review we examine the functionally diverse ATPase associated with various cellular activities (AAA-ATPase), valosin-containing protein (VCP/p97), its molecular functions, the mutational landscape of VCP and the phenotypic manifestation of VCP disease. VCP is crucial to a multitude of cellular functions including protein quality control, endoplasmic reticulum-associated degradation (ERAD), autophagy, mitophagy, lysophagy, stress granule formation and clearance, DNA replication and mitosis, DNA damage response including nucleotide excision repair, ATM- and ATR-mediated damage response, homologous repair and non-homologous end joining. VCP variants cause multisystem proteinopathy, and pathology can arise in several tissue types such as skeletal muscle, bone, brain, motor neurons, sensory neurons and possibly cardiac muscle, with the disease course being challenging to predict. Full article

Amyotrophic lateral sclerosis (ALS) is an incurable rare neurodegenerative condition, with 45% of cases showing the symptom of dysphagia; its clinical signs are atrophy, weakness, and fasciculations of the facial muscles, tongue, and pharynx. Furthermore, dysphagia is the main cause of aspiration pneumonia. The traditional treatment for dysphagia varies based on the patient’s difficulty of swallowing. The initial phase consists of dietary consistency adjustments, progressing to alternatives like nasogastric tubes or percutaneous endoscopic gastrostomy (PEG) in advanced stages. Osteopathic manipulative treatment (OMT) is a complementary ‘hands-on’ approach that has already shown positive results as an add-on therapy in various health conditions. This study is a case report of a man diagnosed with ALS with initial dysphagia, managed with a protocol that extraordinarily included OMT. The patient showed somatic dysfunctions in the mediastinal region, upper cervical region, and occipital area which are all anatomically related to the nervous system, especially the glossopharyngeal reflex. At the end of the rehabilitation protocol, there was a reduction in the swallowing problems measured with Strand Scale and swallowing tests, and the patient reported an improved psycho-physical well-being assessed with the Amyotrophic Lateral Sclerosis Assessment Questionnaire (ALSAQ-40). Instead, the neurological function measured with ALSFRS-S remained stable. Although the nature of this study design prevents any causal assumption, the positive results should lead to future randomized controlled trials to assess the effectiveness of OMT as an adjunctive therapeutic proposal to improve the health of ALS patients. Full article

CAR-T cell therapy is at the forefront of next-generation multiple myeloma (MM) management, with two B-cell maturation antigen (BCMA)-targeted products recently approved. However, these products are incapable of breaking the infamous pattern of patient relapse. Two contributing factors are the use of BCMA as a target molecule and the artificial scFv format that is responsible for antigen recognition. Tackling both points of improvement in the present study, we used previously characterized VHHs that specifically target the idiotype of murine 5T33 MM cells. This idiotype represents one of the most promising yet challenging MM target antigens, as it is highly cancer- but also patient-specific. These VHHs were incorporated into VHH-based CAR modules, the format of which has advantages compared to scFv-based CARs. This allowed a side-by-side comparison of the influence of the targeting domain on T cell activation. Surprisingly, VHHs previously selected as lead compounds for targeted MM radiotherapy are not the best (CAR-) T cell activators. Moreover, the majority of the evaluated VHHs are incapable of inducing any T cell activation. As such, we highlight the importance of specific VHH selection, depending on its intended use, and thereby raise an important shortcoming of current common CAR development approaches. Full article

Bolts have the advantages of simple installation and easy removal. They are widely applied in aerospace and high-speed railway traffic. However, the loosening of bolts under mixed loads can lead to nonlinear decreases in pre-loading. This affects the safety performance of the structure and may lead to catastrophic consequences. Existing techniques cannot be used to monitor the bolt performance status in time. This has caused significant problems with the safety and reliability of equipment. In order to study the relaxation law of bolt pre-loading, this paper carries out an experimental analysis for 8.8-grade hexagonal bolts and calibrates the torque coefficient. We also studied different loading waveforms, nickel steel plate surface roughnesses, tangential displacement frequencies, four different strengths and bolt head contact areas of the bolt, the initial pre-loading, and the effects of tangential cyclic displacement on pre-loading relaxation. This was done in order to accurately predict the degree of bolt pre-loading loosening under external loads. The laws are described using the allometric model function and the nine-stage polynomial function. The least squares method is used to identify the parameters in the function. The results show that bolts with a smooth surface of the connected structure nickel steel flat plate, high-frequency working conditions, half-sine wave, and a high-strength have better anti-loosening properties. Taking 5–10 cycles of cyclic loading as a boundary, the pre-loading relaxation is divided into two stages. The first stage is a stage of rapid decrease in bolt pre-loading, and the second stage is the slow decrease process. The performance prediction study shows that the allometric model function is the worst fitted, at 71.7% for the small displacement condition. Other than that, the allometric model function and the nine-stage polynomial function can predict more than 85.5% and 90.4%, which require the use of least squares to identify two and ten unknown parameters, respectively. The complexity of the two is different, but both can by better indicators than the pre-loading relaxation law under specific conditions. It helps to improve the monitoring of bolt loosening and the system use cycle, and it can provide theoretical support for complex equipment working for a long time. Full article

A hub motor is integrated into an electric wheel. The external excitation is complex and the heat dissipation conditions are poor. The working temperature of the hub motor easily becomes too high, resulting in large fluctuations in the output torque, which affect its service life. Taking a four-wheel hub-driven electric vehicle as the research object and aiming to resolve the issue of inaccurate prediction of the output torque of the hub motor in the real operating environment of the vehicle, a method for analyzing the temperature rise and torque characteristics of the hub motor considering multisource excitation and magnetic–thermal bidirectional coupling is proposed. First, the multisource excitation transmission path of the hub motor and the coupling principle of the road-electric wheel-vehicle body suspension system are analyzed from three aspects: the electromagnetic effect of the hub motor itself, the tire-ground effect, and the interaction between suspension (body) and electric wheel. We concluded that the load torque and air gap change in the motor are the key factors of its torque characteristics. On this basis, a dynamic model of the road-electric wheel-suspension-vehicle body system, an electromagnetic field model of the hub motor, and a temperature field model are established, and the influence of load torque and air gap change on the loss of in-wheel motor under multisource excitation is analyzed. Furthermore, based on the magnetic–thermal bidirectional coupling method, the motor loss under the combined action of load torque and air gap change is introduced into the temperature field model, and combined with the electromagnetic field model of the hub motor, the temperature distribution law and torque characteristics of the hub motor are accurately predicted. Finally, the accuracy and effectiveness of the calculation results of the temperature and torque characteristics of the hub motor are verified via an electric wheel bench test. Full article

Background: Ovarian cancer (OC) is the most lethal gynecological cancer in the United States. Among the different types of OC, serous ovarian cancer (SOC) stands out as the most prevalent. Transcriptomics techniques generate extensive gene expression data, yet only a few of these genes are relevant to clinical diagnosis. Methods: Methods for feature selection (FS) address the challenges of high dimensionality in extensive datasets. This study proposes a computational framework that applies FS techniques to identify genes highly associated with platinum-based chemotherapy response on SOC patients. Using SOC datasets from the Gene Expression Omnibus (GEO) database, LASSO and varSelRF FS methods were employed. Machine learning classification algorithms such as random forest (RF) and support vector machine (SVM) were also used to evaluate the performance of the models. Results: The proposed framework has identified biomarkers panels with 9 and 10 genes that are highly correlated with platinum–paclitaxel and platinum-only response in SOC patients, respectively. The predictive models have been trained using the identified gene signatures and accuracy of above 90% was achieved. Conclusions: In this study, we propose that applying multiple feature selection methods not only effectively reduces the number of identified biomarkers, enhancing their biological relevance, but also corroborates the efficacy of drug response prediction models in cancer treatment. Full article

Given the increasing competition and the impact of digital media in the automobile industry, dealerships need to understand the antecedents of customer happiness and brand love. The goals of the study are to analyse the combined influence of the cognitive and affective drivers of brand love for high-involvement products and its effects on behavioural intentions, paying special attention to the moderating role of susceptibility to information posted on social media. Using a sample of 317 Jordanian car buyers, a structural model is tested that confirms that the sales consultant’s empathy is a strong predictor of customer happiness during a car purchase and a stronger predictor of his/her trust in the car dealership. Happiness and trust translate into greater brand love, which in turn can generate resistance towards negative information posted on social media; positive electronic word-of-mouth; and willingness to pay more. Happiness fully mediated the relationship between empathy and car brand love. The effect of the impact of the perceived empathy of salespeople on customer happiness was stronger for consumers with low susceptibility to information posted on social media. This work expands the academic knowledge of the direct mediating and moderating effects of brand love. Full article

Ablative composites serve as sacrificial materials, protecting underlying materials from high-temperature environments by endothermic reactions. These materials undergo various phenomena, including thermal degradation, pyrolysis, gas generation, char formation, erosion, gas flow, and different modes of heat transfer (such as conduction, convection, and radiation), all stemming from these endothermic reactions. These phenomena synergize to form a protective layer over the underlying materials. Carbon, with its superb mechanical properties and various available forms, is highlighted, alongside phenolics known for good adhesion and fabric ability and elastomers valued for flexibility and resilience. This study focuses on recent advancements in carbon-and-phenolic and carbon-and-elastomeric composites, considering factors such as erosion speed; high-temperature resistance; tensile, bending, and compressive strength; fiber–matrix interaction; and char formation. Various authors’ calculations regarding the percentage reduction in linear ablation rate (LAR) and mass ablation rate (MAR) are discussed. These analyses inform potential advancements in the field of carbon/phenolic and carbon/elastomeric ablative composites. Full article

mRNA vaccines have emerged as an optimistic technological platform for vaccine innovation in this new scientific era. mRNA vaccines have dramatically altered the domain of vaccinology by offering a versatile and rapid approach to combating infectious diseases and virus-induced cancers. Clinical trials have demonstrated efficacy rates of 94–95% in preventing COVID-19, and mRNA vaccines have been increasingly recognized as a powerful vaccine platform. Although mRNA vaccines have played an essential role in the COVID-19 pandemic, they still have several limitations; their instability and degradation affect their storage, delivery, and over-all efficiency. mRNA is typically enclosed in a transport mechanism to facilitate its entry into the target cell because it is an unstable and negatively charged molecule. For instance, mRNA that is given using lipid-nanoparticle-based vaccine delivery systems (LNPs) solely enters cells through endocytosis, establishing an endosome without damaging the cell membrane. The COVID-19 pandemic has accelerated the development of mRNA vaccine platforms used to treat and prevent several infectious diseases. This technology has the potential to change the future course of the disease by providing a safe and effective way to combat infectious diseases and cancer. A single-stranded genetic sequence found in mRNA vaccines instructs host cells to produce proteins inside ribosomes to elicit immunological responses and prepare the immune system to fight infections or cancer cells. The potential applications of mRNA vaccine technology are vast and can lead to the development of a preferred vaccine pattern. As a result, a new generation of vaccinations has gradually gained popularity and access to the general population. To adapt the design of an antigen, and even combine sequences from different variations in response to new changes in the viral genome, mRNA vaccines may be used. Current mRNA vaccines provide adequate safety and protection, but the duration of that protection can only be determined if further clinical research is conducted. Full article

The strategic objective of world climate policy is the decarbonization of industries, aiming to achieve “net-zero” emissions by 2050, as outlined in the European Green Deal and the Paris Agreement. This transition entails increasing the utilization of renewable energy sources (RES) in industrial energy consumption, thereby transforming economies from reliance on fossil fuels to sustainable alternatives. However, this shift poses a significant challenge for many EU countries, with varying degrees of success in adaptation. This paper investigates the process of decarbonizing industries by analyzing trends in the adoption of RES in EU countries and evaluating their progress toward climate targets. Utilizing time series analysis of production, total energy usage, and the proportion of renewables in industrial energy consumption, the study compares two groups of countries: longstanding EU members and newer additions. The aim is to forecast the trajectory of RES integration in industry and assess the feasibility of meeting the targets outlined in the European Green Deal. The findings reveal a considerable gap between the set targets and projected outcomes, with only a few countries expected to meet the EU’s 2030 goals. This is highlighted by disparities in RES shares across member states, ranging from 0.0% to 53.8% in 2022. Despite notable increases in the absolute use of renewable energy, particularly in central and eastern European nations, substantial challenges persist in aligning industrial sectors with EU decarbonization objectives. Full article

The purpose of the present cross-sectional study was to examine the relationship between heart rate variability (HRV) and the range of cervical motion, disability, pain intensity, pain catastrophizing, and quality of life in patients with chronic, non-specific neck pain. Thirty-five patients, aged 20–48 years, with chronic non-specific neck pain, completed validated questionnaires regarding neck pain intensity, pain-associated disability, catastrophic thoughts, and quality of life. The range of cervical motion was assessed using a digital goniometer. HRV indices were recorded in three positions (supine, sitting, and standing) through a smartphone application. Several significant correlations were observed between HRV indices and neck pain disability, the helplessness factor of catastrophizing, neck rotation, and quality of life. These correlations were only observed in the standing position. Pain catastrophizing was positively correlated with disability and pain intensity during active neck movement (Pearson r = 0.544, p < 0.01; Pearson r = 0.605, p < 0.01, respectively). Quality of life was negatively correlated with pain intensity during active movement (Pearson r = −0.347, p < 0.05). HRV indices were correlated with the psychological and physical domains of neck pain. These cardiac indices have been related to neck pain variables in some previous studies. Further research is needed to confirm this relationship in different daily conditions. Full article

Aquatic ecosystems can suffer inadvertent contamination from widely used herbicides. This study delves into the relative toxicity of 36 herbicides on green algae, exploring 11 distinct modes of action and 25 chemical structure classes. Through a 72-h algal growth inhibition test, it was found that herbicides targeting acetolactate synthase (ALS), photosystem II (PSII inhibitors), microtubule assembly, very-long-chain fatty acid (VLCFA) synthesis, and lipid synthesis exhibited high toxicity, with 72-h EC50 (half-maximal effective concentration) values ranging from 0.003 mg/L to 24.6 mg/L. Other pesticide types showed moderate to low toxicity, with EC50 values ranging from 0.59 mg/L to 143 mg/L. Interestingly, herbicides sharing the same mode of action but differing in chemical composition displayed significantly varied toxicity. For instance, penoxsulam and pyribenzoxim, both ALS inhibitors, demonstrated distinct toxicity levels. Similarly, terbuthylazine and bentazone, both PSII inhibitors, also exhibited differing toxicities. Notably, herbicides approved for rice cultivation showed lower toxicity to green algae compared to those intended for terrestrial plants. These data offer valuable insights for assessing the potential risks posed by these chemicals to aquatic organisms. Additionally, to prevent or minimize herbicide residual effects, modern management practices were reviewed to offer practical guidance. Full article

In this study, we report on the development of hydroxyapatite (HAp) and samarium-doped hydroxyapatite (SmHAp) nanoparticles using a cost-effective method and their biological effects on a bone-derived cell line MC3T3-E1. The physicochemical and biological features of HAp and SmHAp nanoparticles are explored. The X-ray diffraction (XRD) studies revealed that no additional peaks were observed after the integration of samarium (Sm) ions into the HAp structure. Valuable information regarding the molecular structure and morphological features of nanoparticles were obtained by using Fourier-transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS). The elemental composition obtained by using energy-dispersive X-ray spectroscopy (EDS) confirmed the presence of the HAp constituent elements, Ca, O, and P, as well as the presence and uniform distribution of Sm³⁺ ions. Both HAp and SmHAp nanoparticles demonstrated biocompatibility at concentrations below 25 μg/mL and 50 μg/mL, respectively, for up to 72 h of exposure. Cell membrane integrity was preserved following treatment with concentrations up to 100 μg/mL HAp and 400 μg/mL SmHAp, confirming the role of Sm³⁺ ions in enhancing the cytocompatibility of HAp. Furthermore, our findings reveal a positive, albeit limited, effect of SmHAp nanoparticles on the actin dynamics, osteogenesis, and cell migration compared to HAp nanoparticles. Importantly, the biological results highlight the potential role of Sm³⁺ ions in maintaining cellular balance by mitigating disruptions in Ca²⁺ homeostasis induced by HAp nanoparticles. Therefore, our study represents a significant contribution to the safety assessment of both HAp and SmHAp nanoparticles for biomedical applications focused on bone regeneration. Full article

The recurrent load shedding crisis in South Africa has highlighted the need to accurately predict electricity consumption for residential buildings. This has significant ramifications for daily life and economic productivity. To address this challenge, this study leverages machine learning models to predict the hourly energy consumption of residential buildings in South Africa. This study evaluates the performance of various regression techniques, including Random Forest (RF), Decision Tree (DT), Extreme Gradient Boosting (XGBoost), and Adaptive Boosting (AdaBoost) machine learning models, using a national residential dataset that contains measurements collected every hour. The objective is to determine the most effective models for predicting next-hour residential building consumption. These models use historical patterns of energy usage to capture temporal details such as seasonal variations and rolling averages. Feature engineering methods are further employed to enhance their predictive capabilities. The performance of each individual model was evaluated using criteria such as the mean squared error (MSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and coefficient of determination (R²). The results show that both RF and DT achieve the best accuracy for the prediction of residential electricity consumption (because the MSE, MAE, and MAPE for RF and DT are very close to 0). These findings offer actionable insights for households, businesses, and policymakers. By enabling more accurate and granular energy consumption forecasts, this can mitigate the effects of load shedding. This study contributes to the discourse on sustainable energy management by combining advanced machine learning models with real-world energy challenges. Full article

Diabetes mellitus (DM) is a global health concern characterized by a deficiency in insulin production. Considering the systemic toxicity and limited efficacy associated with current antidiabetic medications, there is the utmost need for natural, plant-based alternatives. Herbal medicines have experienced exponential growth in popularity globally in recent years for their natural origins and minimal side effects. Ecuador has a rich cultural history in ethnobotany that plays a crucial role in its people’s lives. This study identifies 27 Ecuadorian medicinal plants that are traditionally used for diabetes treatment and are prepared through infusion, decoction, or juice, or are ingested in their raw forms. Among them, 22 plants have demonstrated hypoglycemic or anti-hyperglycemic properties that are rich with bioactive phytochemicals, which was confirmed in several in vitro and in vivo studies. However, Bryophyllum gastonis-bonnieri, Costus villosissimus, Juglans neotropica, Pithecellobium excelsum, and Myroxylon peruiferum, which were extensively used in traditional medicine preparation in Ecuador for many decades to treat diabetes, are lacking in pharmacological elucidation. The Ecuadorian medicinal plants used to treat diabetes have been found to have several bioactive compounds such as flavonoids, phenolics, fatty acids, aldehydes, and terpenoids that are mainly responsible for reducing blood sugar levels and oxidative stress, regulating intestinal function, improving insulin resistance, inhibiting α-amylase and α-glucosidase, lowering gluconeogenic enzymes, stimulating glucose uptake mechanisms, and playing an important role in glucose and lipid metabolism. However, there is a substantial lack of integrated approaches between the existing ethnomedicinal practices and pharmacological research. Therefore, this review aims to discuss and explore the traditional medicinal plants used in Ecuador for treating DM and their bioactive phytochemicals, which are mainly responsible for their antidiabetic properties. We believe that the use of Ecuadorian herbal medicine in a scientifically sound way can substantially benefit the local economy and industries seeking natural products. Full article

The need for the increasing geographical spread of fire blight (FB) affecting fruit crops to be addressed led to large-scale chemicalization of the environmental matrices and reduction of plant productivity. The current study aimed to assess the effects of novel biopreparations at different exposure durations on photosynthetic pigment content and antioxidant enzyme activity in leaves of apple and pear varieties with varying levels of resistance to FB. Biopreparations were formulated from a cultural broth containing Lacticaseibacillus paracasei M12 or Bacillus amyloliquefaciens MB40 isolated from apple trees’ phyllosphere. Aseptic leaves from blight-resistant (endemic Malus sieversii cv. KG10), moderately resistant (Pyrus pyraster cv. Wild), and susceptible (endangered Malus domestica cv. Aport and Pyrus communis cv. Shygys) varieties were employed. The impact of biopreparations on fruit crop antioxidant systems and photosynthetic apparatuses was investigated in vitro. Study results indicated that FB-resistant varieties exhibit enhanced adaptability and oxidative stress resistance compared to susceptible ones. Plant response to biopreparations varied based on the plant’s initial FB sensitivity and exposure duration. Indeed, biopreparations improved the adaptive response of the assimilation apparatus, protein synthesis, and catalase and superoxide dismutase activity in susceptible varieties, suggesting that biopreparations have the potential for future commercialization to manage FB in fruit crops. Full article