Energy efficiency is a principle of architectural design that reduces environmental impact. Generative design can offer alternative options to improve energy efficiency in buildings, but significant gaps exist in the application due to accessing complex knowledge. This study aimed to explore publications on generative design and energy efficiency in buildings and identify generative methods for energy efficiency topics. This study conducted a systematic review using the PRISMA methodology in December 2023 by searching publications from databases including Scopus, Google Scholar, and Thai Journals Online. Descriptive analysis examined 34 articles, showing the publication year, source, and citations. Comparative qualitative and descriptive analysis identified generative methods. Publications are increasing over time, and further growth is expected related to the accessibility of computational design and practical applications. Tools and frameworks demonstrated reduced energy usage compared to prototypes or traditional design approaches. The most studied is thermal performance, which was reduced by 28%. Energy performance achieved up to a 23.30% reduction, followed by others and daylighting. In addition to single-topic studies, there are also studies with multiple topics. Evolutionary algorithms are standard. Parametric search strategies have increased. Exploration reveals rule-based and mixed methods. Machine learning and AI garner attention. Full article

To effectively reduce building energy consumption, a novel full fresh air system with a heat source tower (HST) and a borehole heat exchanger (BHE) was proposed for space cooling and dehumidification in this paper. The cooling system only adopts geothermal energy to produce dry and cold fresh air for space cooling and dehumidification through the BHE and HST, which has the advantage of non-condensate water compared to BHE systems integrated with a fan coil or chilled beam. Based on the established mathematical model of the cooling system, this paper analyzed the system characteristics, feasibility, operation strategy, energy performance, and cost-effectiveness of the proposed model in detail. The results show that the mathematical model has less than 10% error in estimating the system performance compared to the practical HST−BHE experimental set up. Under the specific boundary conditions, the cooling and dehumidification capacity of this system increases with the decrease in the air temperature, air moisture content, and inlet water temperature of the HST. The optimal cooling capacity and the system COP can be achieved when the air–water flow ratio is at 4:3. A case study was conducted in a residential building in Shenyang with an area of about 1800 m². It was found that this system can fully meet the cooling and dehumidification demand in such a residential building. The operation strategy of the cooling system can be optimized by adjusting the air–water flow ratio from 4:3 to 3:2 during the early cooling season (7 June–1 July) and end cooling season (3 August–1 September). As a result, the average COP of the cooling system during the whole cooling season can be improved from 6.1 to 8.7. Compared with the air source heat pump (ASHP) and the ground source heat pump (GSHP) for space cooling, the proposed cooling system can achieve an energy saving rate of 123% and 26%, respectively. Considering that the BHE of the GSHP can be part of the proposed HST−BHE cooling system, the integration of the HST and GHSP for space cooling (and heating) is strongly recommended in actual applications. Full article

Concerns over sustainability have recently drawn more attention in a post-COVID-19 environment, particularly from developing countries. This heightened global awareness of sustainability highlights the importance of comprehending consumer behavior in purchasing green products. This study utilized an extended theory of planned behavior (TPB) called the sustainability theory of planned behavior (STPB) to holistically assess the behavioral intention among green consumers in a particular developing country: the Philippines. Convenience sampling was used with 500 participants, and 54 modified questions were distributed online. Different factors, such as perceived environmental concern, perceived economic concern, perceived authority support, subjective norm, attitude, perceived behavioral control, customer perceived value, and purchasing intention, were assessed concurrently through the structural equation modeling (SEM) approach. Through this, it was discovered that all the STPB predictors were significant drivers affecting the consumers’ purchasing intention, with customer perceived value having the highest direct effect. Moreover, it was found that the relationship between perceived economic concern on subjective norms and perceived behavioral control was insignificant. Further implications and comparisons were made based on the results of the study. The study’s findings can be utilized to help policymakers and marketers devise strategies that will effectively encourage sustainability through targeted interventions and increased product awareness. The study has validated the integration of new constructs into the TPB, enhancing the predictive power of the proposed model for assessing the behavioral intention to purchase green products. Thus, the model construct can be applied and utilized to investigate other topics regarding sustainability. Full article

This study addresses the field of X-ray security screening and focuses on synthesising realistic X-ray images using advanced generative models. Insufficient training data in this area pose a major challenge, which we address through innovative data augmentation techniques. We utilise the power of generative adversarial networks (GANs) and conditional GANs (cGANs), in particular the Pix2Pix and Pix2PixHD models, to investigate the generation of X-ray images from various inputs such as masks and edges. Our experiments conducted on a Korean dataset containing dangerous objects relevant to security screening show the effectiveness of these models in improving the quality and realism of image synthesis. Quantitative evaluations based on metrics such as PSNR, SSIM, LPIPS, FID, and FSIM, with scores of 19.93, 0.71, 0.12, 29.36, and 0.54, respectively, show the superiority of our strategy, especially when integrated with hybrid inputs containing both edges and masks. Overall, our results highlight the potential of advanced generative models to overcome the challenges of data scarcity in X-ray security screening and pave the way for more efficient and accurate inspection systems. Full article

Machines operate under increasingly harsher contact conditions, causing significant wear and contact fatigue. Sub-surface stresses are responsible for the premature contact fatigue of rolling element bearings, meshing gears, and cam–follower pairs. Surface protection measures include hard, wear-resistant coatings. Traditionally, contact integrity has been predicted using classical Hertzian contact mechanics. However, the theory is only applicable when the contact between a pair of ellipsoidal solids of revolution may be considered as a rigid indenter penetrating a semi-infinite elastic half-space. Many coatings act as thin bonded elastic layers that undergo considerably higher pressures than those predicted by the classical theory. Furthermore, inelastic deformation of bonded solids can cause plastic flow, work-hardening, and elastoplastic behaviour. This paper presents a comprehensive, integrated contact mechanics analysis that includes induced sub-surface stresses in concentrated counterformal finite line contacts for all the aforementioned cases. Generated pressures and deformation are predicted for hard coated surfaces, for which there is a dearth of relevant analysis. The contact characteristics, which are of particular practical significance, of many hard, wear-resistant advanced coatings are also studied. The paper clearly demonstrates the importance of using efficient semi-analytical, detailed holistic contact mechanics rather than the classical idealised methods or empirical numerical ones such as FEA. The novel approach presented for the finite line contact of thin-layered bonded solids has not hitherto been reported in the open literature. Full article

The post-harvest phase of potato tuber dormancy and sprouting are essential in determining the economic value. The intricate transition from dormancy to active growth is influenced by multiple factors, including environmental factors, carbohydrate metabolism, and hormonal regulation. Well-established environmental factors such as temperature, humidity, and light play pivotal roles in these processes. However, recent research has expanded our understanding to encompass other novel influences such as magnetic fields, cold plasma treatment, and UV-C irradiation. Hormones like abscisic acid (ABA), gibberellic acid (GA), cytokinins (CK), auxin, and ethylene (ETH) act as crucial messengers, while brassinosteroids (BRs) have emerged as key modulators of potato tuber sprouting. In addition, jasmonates (JAs), strigolactones (SLs), and salicylic acid (SA) also regulate potato dormancy and sprouting. This review article delves into the intricate study of potato dormancy and sprouting, emphasizing the impact of environmental conditions, carbohydrate metabolism, and hormonal regulation. It explores how various environmental factors affect dormancy and sprouting processes. Additionally, it highlights the role of carbohydrates in potato tuber sprouting and the intricate hormonal interplay, particularly the role of BRs. This review underscores the complexity of these interactions and their importance in optimizing potato dormancy and sprouting for agricultural practices. Full article

One of the key driving factors for achieving the goal of sustainable economic development is to ensure decent employment opportunities. This article explores the relationship between industrial intelligence and sustainable development in China from the perspective of employment. Based on interprovincial panel data from 2006 to 2019, using the fixed-effect regression model and mediating-effect regression model, this study empirically tests the impact of industrial intelligence on sustainable employment in China. The following conclusions are drawn: (1) Industrial intelligence has a significant positive impact on the overall scale of employment. Industrial intelligence has promoted the optimization and upgrading of employment skill structure and industrial structure. Industrial intelligence will reduce the employment proportion of low-skilled labor and increase the employment proportion of medium-skilled labor and high-skilled labor. Industrial intelligence significantly reduces the employment share of the manufacturing sector and increases the employment share of the service sector. (2) Industrial intelligence reduces employment levels through capital deepening effects. Industrial intelligence has significantly improved regional labor productivity and significantly improved employment levels through productivity effects. (3) The results of regional heterogeneity show that industrial intelligence has promoted the improvement of employment level and the upgrading of employment structure in the eastern region but has not had a significant positive impact on other regions. Full article

Improving agricultural production relies on the decisions and actions of farmers and land managers, highlighting the importance of efficient soil monitoring techniques for better resource management and reduced environmental impacts. Despite considerable advancements in soil sensors, their traditional bulky counterparts cause difficulty in widespread adoption and large-scale deployment. Printed electronics emerge as a promising technology, offering flexibility in device design, cost-effectiveness for mass production, and a compact footprint suitable for versatile deployment platforms. This review overviews how printed sensors are used in monitoring soil parameters through electrochemical sensing mechanisms, enabling direct measurement of nutrients, moisture content, pH value, and others. Notably, printed sensors address scalability and cost concerns in fabrication, making them suitable for deployment across large crop fields. Additionally, seamlessly integrating printed sensors with printed antenna units or traditional integrated circuits can facilitate comprehensive functionality for real-time data collection and communication. This real-time information empowers informed decision-making, optimizes resource management, and enhances crop yield. This review aims to provide a comprehensive overview of recent work related to printed electrochemical soil sensors, ultimately providing insight into future research directions that can enable widespread adoption of precision agriculture technologies. Full article

SARS-CoV-2 is the pathogen responsible for the most recent global pandemic, which has claimed hundreds of thousands of victims worldwide. Despite remarkable efforts to develop an effective vaccine, concerns have been raised about the actual protection against novel variants. Thus, researchers are eager to identify alternative strategies to fight against this pathogen. Like other opportunistic entities, a key step in the SARS-CoV-2 lifecycle is the maturation of the envelope glycoprotein at the RARR685↓ motif by the cellular enzyme Furin. Inhibition of this cleavage greatly affects viral propagation, thus representing an ideal drug target to contain infection. Importantly, no Furin-escape variants have ever been detected, suggesting that the pathogen cannot replace this protease by any means. Here, we designed a novel fluorogenic SARS-CoV-2-derived substrate to screen commercially available and custom-made libraries of small molecules for the identification of new Furin inhibitors. We found that a peptide substrate mimicking the cleavage site of the envelope glycoprotein of the Omicron variant (QTQTKSHRRAR-AMC) is a superior tool for screening Furin activity when compared to the commercially available Pyr-RTKR-AMC substrate. Using this setting, we identified promising novel compounds able to modulate Furin activity in vitro and suitable for interfering with SARS-CoV-2 maturation. In particular, we showed that 3-((5-((5-bromothiophen-2-yl)methylene)-4-oxo-4,5 dihydrothiazol-2-yl)(3-chloro-4-methylphenyl)amino)propanoic acid (P3, IC₅₀ = 35 μM) may represent an attractive chemical scaffold for the development of more effective antiviral drugs via a mechanism of action that possibly implies the targeting of Furin secondary sites (exosites) rather than its canonical catalytic pocket. Overall, a SARS-CoV-2-derived peptide was investigated as a new substrate for in vitro high-throughput screening (HTS) of Furin inhibitors and allowed the identification of compound P3 as a promising hit with an innovative chemical scaffold. Given the key role of Furin in infection and the lack of any Food and Drug Administration (FDA)-approved Furin inhibitor, P3 represents an interesting antiviral candidate Full article

Accurately segmenting cancer lesions is essential for effective personalized treatment and enhanced patient outcomes. We propose a multi-resolution selective segmentation (MurSS) model to accurately segment breast cancer lesions from hematoxylin and eosin (H&E) stained whole-slide images (WSIs). We used The Cancer Genome Atlas breast invasive carcinoma (BRCA) public dataset for training and validation. We used the Korea University Medical Center, Guro Hospital, BRCA dataset for the final test evaluation. MurSS utilizes both low- and high-resolution patches to leverage multi-resolution features using adaptive instance normalization. This enhances segmentation performance while employing a selective segmentation method to automatically reject ambiguous tissue regions, ensuring stable training. MurSS rejects 5% of WSI regions and achieves a pixel-level accuracy of 96.88% (95% confidence interval (CI): 95.97–97.62%) and mean Intersection over Union of 0.7283 (95% CI: 0.6865–0.7640). In our study, MurSS exhibits superior performance over other deep learning models, showcasing its ability to reject ambiguous areas identified by expert annotations while using multi-resolution inputs. Full article

Amoxicillin and sulbactam are widely used in animal food compounding. Amoxicillin–sulbactam hybrid molecules are bicester compounds made by linking amoxicillin and sulbactam with methylene groups and have good application prospects. However, the residual elimination pattern of these hybrid molecules in animals needs to be explored. In the present study, the amoxicillin–sulbactam hybrid molecule (AS group) and a mixture of amoxicillin and sulbactam (mixture group) were administered to rats by gavage, and the levels of the major metabolites of amoxicillin, amoxicilloic acid, amoxicillin diketopiperazine, and sulbactam were determined by UPLC‒MS/MS. The residue elimination patterns of the major metabolites in the liver, kidney, urine, and feces of rats in the AS group and the mixture group were compared. The results showed that the total amount of amoxicillin, amoxicilloic acid, amoxicillin diketopiperazine, and the highest concentration of sulbactam in the liver and kidney samples of the AS group and the mixture group appeared at 1 h after drug withdrawal. Between 1 h and 12 h post discontinuation, the total amount of amoxicillin, amoxicilloic acid, and amoxicillin diketopiperazine in the two tissues decreased rapidly, and the elimination half-life of the AS group was significantly higher than that in the mixture group (p < 0.05); the residual amount of sulbactam also decreased rapidly, and the elimination half-life was not significantly different (p > 0.05). In 72 h urine samples, the total excretion rates were 60.61 ± 2.13% and 62.62 ± 1.73% in the AS group and mixture group, respectively. The total excretion rates of fecal samples (at 72 h) for the AS group and mixture group were 9.54 ± 0.26% and 10.60 ± 0.24%, respectively. These results showed that the total quantity of amoxicillin, amoxicilloic acid, and amoxicillin diketopiperazine was eliminated more slowly in the liver and kidney of the AS group than those of the mixture group and that the excretion rate through urine and feces was essentially the same for both groups. The residual elimination pattern of the hybrid molecule in rats determined in this study provides a theoretical basis for the in-depth development and application of hybrid molecules, as well as guidelines for the development of similar drugs. Full article

Even though morphological signs of differentiation have a minimal impact on survival after intensive cytotoxic therapy for acute myeloid leukemia (AML), monocytic AML cell differentiation (i.e., classified as French/American/British (FAB) subtypes M4/M5) is associated with a different responsiveness both to Bcl-2 inhibition (decreased responsiveness) and possibly also bromodomain inhibition (increased responsiveness). FAB-M4/M5 patients are heterogeneous with regard to genetic abnormalities, even though monocytic differentiation is common for patients with Nucleophosmin 1 (NPM1) insertions/mutations; to further study the heterogeneity of FAB-M4/M5 patients we did a proteomic and phosphoproteomic comparison of FAB-M4/M5 patients with (n = 13) and without (n = 12) NPM1 mutations. The proteomic profile of NPM1-mutated FAB-M4/M5 patients was characterized by increased levels of proteins involved in the regulation of endocytosis/vesicle trafficking/organellar communication. In contrast, AML cells without NPM1 mutations were characterized by increased levels of several proteins involved in the regulation of cytoplasmic translation, including a large number of ribosomal proteins. The phosphoproteomic differences between the two groups were less extensive but reflected similar differences. To conclude, even though FAB classification/monocytic differentiation are associated with differences in responsiveness to new targeted therapies (e.g., Bcl-2 inhibition), our results shows that FAB-M4/M5 patients are heterogeneous with regard to important biological characteristics of the leukemic cells. Full article

In advancing the transition of the energy sector toward heightened sustainability and environmental friendliness, biopolymers have emerged as key elements in the construction of triboelectric nanogenerators (TENGs) due to their renewable sources and excellent biodegradability. The development of these TENG devices is of significant importance to the next generation of renewable and sustainable energy technologies based on carbon-neutral materials. This paper introduces the working principles, material sources, and wide-ranging applications of biopolymer-based triboelectric nanogenerators (BP-TENGs). It focuses on the various categories of biopolymers, ranging from natural sources to microbial and chemical synthesis, showcasing their significant potential in enhancing TENG performance and expanding their application scope, while emphasizing their notable advantages in biocompatibility and environmental sustainability. To gain deeper insights into future trends, we discuss the practical applications of BP-TENG in different fields, categorizing them into energy harvesting, healthcare, and environmental monitoring. Finally, the paper reveals the shortcomings, challenges, and possible solutions of BP-TENG, aiming to promote the advancement and application of biopolymer-based TENG technology. We hope this review will inspire the further development of BP-TENG towards more efficient energy conversion and broader applications. Full article

In this study, the effect of different cooking techniques on broccoli moisture, total phenolic, total flavonoid, and radical scavenging capacity results, polyphenol contents, and their quantitative values was investigated. The total phenolic quantities of fresh and cooked broccoli samples were assessed to be between 36.32 (conventional boiling) and 423.39 mg GAE/100 g (microwave heating). The radical scavenging activities of the broccoli samples were reported between 2.55 (conventional boiling) and 4.99 mmol/kg (microwave heating). In addition, catechin and rutin quantities of the fresh and cooked broccoli samples were measured to be between 2.24 (conventional boiling) and 54.48 mg/100 g (microwave heating), and between 0.55 (conventional boiling) and 16.33 mg/100 g (microwave heating), respectively. The most abundant elements in fresh and cooked broccoli samples were K, Ca, P, S, and Mg. The results showed some changes depending on cooking techniques compared to the control. The bioactive properties of broccoli samples cooked by means of conventional boiling, boiling in vacuum bag, and high-pressure boiling were established to be lower compared to the fresh sample. Catechin, 3,4-dihydroxybenzoic acid, rutin, and gallic acid were the key phenolic compounds of fresh and cooked broccoli samples. The phenolic components of broccoli were significantly affected by the applied cooking techniques. The highest protein in broccoli samples was determined in the broccoli sample cooked by boiling in a vacuum bag. There were statistically significant changes among the mineral results of broccoli cooked with different cooking methods. Full article

Let $K_v^{(3)}=(V,E)$ be the complete 3-uniform hypergraph, where the vertex set is $V=\{x_1,x_2,\cdots ,x_v\}$, in which the edge set $E$ is of all triples. Let $ST$ denote the special tetrahedron with four edges, where each edge contains three vertices of degree 2. In this paper, we consider the decomposition and packing of a complete 3-uniform hypergraph of an $\lambda -$fold special tetrahedron. Firstly, the necessary conditions for the existence of the $\lambda -$fold $ST-$decomposition are discussed in four distinct cases. Secondly, according to the recursive constructions, the required designs of small orders are found. For hypergraphs with large orders, they can be recursively generated using some designs of small orders. Then, it is proven that the above necessary conditions are sufficient. Finally, we prove that a maximum $ST-$packing of a complete 3-uniform hypergraph $K_v^{(3)}$ exists for all $v\ge 6$ and $\lambda \ge 1$ Full article

Muscular temporomandibular joint disorders (M-TMDs) encompass a wide range of painful muscular conditions, which can provoke functional limitation and severely affect quality of life. The aim of the present study was to assess the treatment outcomes in patients affected by M-TMDs in terms of pain scores assessed with pressure pain threshold (PPT). The levels of depression, anxiety, and the Oral Health Impact Profile were also assessed and compared to healthy controls. Patients with a clinical diagnosis of M-TMDs and a control group of healthy subjects were enrolled. At baseline, OHIP-14, PHQ-9, and GAD-7 were administered. PPT was registered at the level of masseter and temporalis muscles. The patients affected by M-TMDs were then treated with oral splints and physio-kinesiotherapy following a standardized treatment protocol. At the 6-month follow-up of M-TMD-affected patients, PPT was registered, and the questionnaires were re-administered to evaluate treatment outcomes. In total, sixty patients and sixty controls were enrolled. The treatment of M-TMDs produced a significant improvement in PPT at the level of the masseter muscle. OHIP-14 at baseline in the M-TMD group was significantly higher compared to the control group (p < 0.05). At the 6-month follow-up, a significant reduction in OHIP-14 scores was registered, although with higher scores compared to the control group (p < 0.05). PHQ-9 was significantly higher at baseline in the M-TMD group (p < 0.05) and decreased to values comparable to the control group after treatment. GAD-7 presented statistically significant differences between the control group and M-TMD patients at baseline (p < 0.05) and between pre- and post-treatment in the M-TMD group. Following treatment, the GAD-7 scores were comparable to the control group. The symptom burden associated with M-TMDs negatively affects quality of life, with higher oral health impairment and a tendency towards depression and anxiety compared to healthy subjects. Following treatment, an improvement in both PPT and quality of life was observed. Full article

A major limitation of most metabolomics datasets is the sparsity of pathway annotations for detected metabolites. It is common for less than half of the identified metabolites in these datasets to have a known metabolic pathway involvement. Trying to address this limitation, machine learning models have been developed to predict the association of a metabolite with a “pathway category”, as defined by a metabolic knowledge base like KEGG. Past models were implemented as a single binary classifier specific to a single pathway category, requiring a set of binary classifiers for generating the predictions for multiple pathway categories. This past approach multiplied the computational resources necessary for training while diluting the positive entries in the gold standard datasets needed for training. To address these limitations, we propose a generalization of the metabolic pathway prediction problem using a single binary classifier that accepts the features both representing a metabolite and representing a pathway category and then predicts whether the given metabolite is involved in the corresponding pathway category. We demonstrate that this metabolite–pathway features pair approach not only outperforms the combined performance of training separate binary classifiers but demonstrates an order of magnitude improvement in robustness: a Matthews correlation coefficient of 0.784 ± 0.013 versus 0.768 ± 0.154. Full article

The q-rung orthopair fuzzy sets (q-ROFSs), a novel concept for processing vague information, offer a more potent and all-encompassing method compared to traditional fuzzy sets, intuitionistic fuzzy sets, and Pythagorean fuzzy sets. The inclusion of the parameter q allows for the q-rung orthopair fuzzy sets to capture a broader range of uncertainty of information. In this paper, we present two novel distance measures for q-ROFSs inspired by the Jensen–Shannon divergence, called $D_{JS\_2D}$ and $D_{JS\_3D}$, and we analyze some properties they satisfy, such as non-degeneracy, symmetry, boundedness, and triangular inequality. Then, the normalized distance measures, called $D_{\widetilde{JS\_2D}}$ and $D_{\widetilde{JS\_3D}}$, are proposed and we verify their rationality through numerical experiments. Finally, we apply the proposed distance measures to practical scenarios, including pattern recognition and multicriteria decision-making, and the results demonstrate the effectiveness of the proposed distance measures. Full article

Metal and metal oxide nanostructured materials have been chemically and physically characterized and tested concerning methylene blue (MB) photoremoval and UV antibacterial activity against Escherichia coli and Staphylococcus aureus. In detail, silver nanoparticles and commercial BaTiO₃ nanoparticles were modified to obtain nanocomposites through sonicated sol–gel TiO₂ synthesis and the photodeposition of Ag nanoparticles, respectively. The characterization results of pristine nanomaterials and synthetized photocatalysts revealed significant differences in specific surface area (SSA), the presence of impurities in commercial Ag nanoparticles, an anatase phase with brookite traces for TiO₂-based nanomaterials, and a mixed cubic–tetragonal phase for BaTiO₃. Silver nanoparticles exhibited superior antibacterial activity at different dosages; however, they were inactive in the photoremoval of the dye. The silver–TiO_x nanocomposite demonstrated an activity in the UV photodegradation of MB and UV inhibition of bacterial growth. Specifically, TiO₂/AgNP (30–50 nm) reduced growth by 487.5 and 1.1 × 10³ times for Escherichia coli and Staphylococcus aureus, respectively, at a dose of 500 ug/mL under UV irradiation. Full article

This paper examines the communication difficulties encountered in cross-media wireless optical transmission through simulated research on the utilization of orthogonal time and frequency space (OTFS) modulation technology. Our analysis and comparison demonstrate that OTFS significantly improves the reliability and throughput of data transmission in intricate multipath channel settings. In contrast to conventional orthogonal frequency division multiplexing (OFDM) technology, OTFS displays better resilience and transmission effectiveness. We foresee additional enhancements and progress in OTFS technology to present a sturdier and more efficient resolution for wireless communication, thereby providing valuable perspectives and encouragement for associated research initiatives. Our results underscore the capability of OTFS technology to transform wireless communication systems in demanding multipath channel conditions. Full article

Antimicrobial resistance (AMR) is one of the biggest threats in modern times. It was estimated that in 2019, 1.27 million deaths occurred around the globe due to AMR. Methicillin-resistant Staphylococcus aureus (MRSA) strains, a pathogen considered of high priority by the World Health Organization, have proven to be resistant to most of the actual antimicrobial treatments. Therefore, new treatments are required to be able to manage this increasing threat. Under this perspective, an important metabolic pathway for MRSA survival, and absent in mammals, is the shikimate pathway, which is involved in the biosynthesis of chorismate, an intermediate for the synthesis of aromatic amino acids, folates, and ubiquinone. Therefore, the enzymes of this route have been considered good targets to design novel antibiotics. The fifth step of the route is performed by shikimate kinase (SK). In this study, an in-house chemical library of 170 benzimidazole derivatives was screened against MRSA shikimate kinase (SaSK). This effort led to the identification of the first SaSK inhibitors, and the two inhibitors with the greatest inhibition activity (C1 and C2) were characterized. Kinetic studies showed that both compounds were competitive inhibitors with respect to ATP and non-competitive for shikimate. Structural analysis through molecular docking and molecular dynamics simulations indicated that both inhibitors interacted with ARG113, an important residue involved in ATP binding, and formed stable complexes during the simulation period. Biological activity evaluation showed that both compounds were able to inhibit the growth of a MRSA strain. Mitochondrial assays showed that both compounds modify the activity of electron transport chain complexes. Finally, ADMETox predictions suggested that, in general, C1 and C2 can be considered as potential drug candidates. Therefore, the benzimidazole derivatives reported here are the first SaSK inhibitors, representing a promising scaffold and a guide to design new drugs against MRSA. Full article

We present a classical treatment of the ionization and electron-capture processes in the interaction of protons with neutral noble-gas atoms, namely, Ne, Ar, Kr, and Xe. We used a three-body classical-trajectory Monte Carlo (CTMC) method to calculate the total (TCS) and differential (DCS) cross sections of single-electron processes. The Garvey-type model potential was employed in the CTMC model to describe the collision between the projectile and the target, accounting for the screening effect of the inactive electrons. The TCSs are evaluated for impact energies in the energy range between 0.2 keV and 50 MeV for a number of sub-shells of the targets. The ionization DCS are evaluated for an impact energy of 35 keV, focusing on the outer sub-shells only. We found that our ionization and electron-capture TCSs are in very good agreement with the previous theoretical and experimental data for all targets. Moreover, we presented single (SDCS)- and double (DDCS)-differential cross sections as a function of the energy and ejection angle of the ionized electron for all collision systems. Full article