Sci, Volume 6, Issue 4 (December 2024) – 30 articles

Cloud computing has revolutionized the digital era by providing a more efficient, scalable, and cost-effective infrastructure. Secure systems that encrypt and protect data before it is transmitted over a network and stored in the cloud benefit the entire transmission process. Transmission data can be encrypted and protected with a secure dynamic substitution box (S-box). In this paper, we propose the QuantumGS-box, which is a dynamic S-box for high-speed cloud-based storage encryption generated by bit shuffling with a genetic algorithm and a quantum random number generator (QRNG). The proposed work generates the S-box optimized values in a dynamic way, and an experimental evaluation of the proposed S-box method has been conducted using several cryptographic criteria, including bit independence criteria, speed, non-linearity, differential and linear approximation probabilities, strict avalanche criteria and balanced output. The results demonstrate that the QuantumGS-box can enhance robustness, is resilient to differential and provide improved linear cryptoanalysis compared to other research works while assuring non-linearity. The characteristics of the proposed S-box are compared with other state of the art S-boxes to validate its performance. These characteristics indicate that the QuantumGS-box is a promising candidate for cloud-based storage encryption applications. Full article

The work is dedicated to the investigation of the possibility of producing and studying the properties of the thin-walled elements of Diamond-type lattice structures, manufactured from the aluminum alloy AlSi10Mg using the selective laser melting method. The accuracy of fabricating the thin-walled elements was assessed depending on the specified model thickness, power, and scanning strategy. It was demonstrated that the minimum wall thickness with minimal porosity was achieved at a laser power of 260 W and a laser scanning speed of 1500 mm/s. Based on the selected SLM parameters, Diamond-type lattice structures with a wall thickness of 200 µm were produced. Tomographic methods confirmed minimal deviation in the thickness and shape of the lattice structure from the model. Mechanical compression tests were conducted to determine the deformation characteristics, as well as the Young’s modulus, yield strength, and ultimate tensile strength. It was shown that the chosen parameters allow for the production of functional lattice structures. Full article

The identification of dynamical systems from data is essential in control theory, enabling the creation of mathematical models that accurately represent the behavior of complex systems. However, real-world applications often present challenges such as the unknown dimensionality of the system and limited access to measurements, particularly in partially observed systems. The Hankel alternative view of Koopman (HAVOK) method offers a data-driven approach to identify linear representations of nonlinear systems, but it often overlooks the influence of external control signals (inputs) and disturbances. This paper introduces a novel input-aware modeling method for unstable linear systems using data-driven Koopman analysis. By explicitly incorporating the impact of inputs and disturbances, our method enhances the accuracy and robustness of system identification, even in the face of incomplete observations. The proposed approach leverages Koopman operator theory on augmented state-input data to capture both the intrinsic dynamics and the system’s sensitivity to external control. Through extensive numerical examples, we demonstrate the effectiveness of our method in accurately identifying and predicting the behavior of various dynamical systems, including real-world nonlinear systems and simulated unstable linear systems with and without disturbances. The results highlight the potential of our approach to advance the field of system identification and control, offering a powerful tool for modeling and analyzing complex systems in diverse applications. Full article

This study presents the synthesis of metal nanoparticles (NPs) with antimicrobial properties from cyanobacterial biomass. Silver (AgNP), copper (CuNP), and zinc (ZnNP) nanoparticles were prepared from exopolysaccharides (EPSs) obtained from isolated cyanobacterial strains. The antimicrobial activity of AgNPs against Escherichia coli and Staphylococcus aureus was evaluated, and compared with CuNPs and ZnNPs, AgNPs were found to have a greater capacity to inhibit bacterial growth. The main factors influencing antimicrobial activity are the concentration and type of metal used. Using an optimized experimental design, specific conditions were established to maximize the antimicrobial efficacy of the synthesized NPs. The characterization of the nanoparticles included UV–VIS, FTIR, and EDX techniques, which confirmed the formation and purity of the AgNPs. This study highlights the effectiveness of cyanobacterial EPS as a reducing and stabilizing agent and provides a sustainable and efficient alternative for producing nanoparticles with biomedical applications. Full article

This paper presents research on the effects of the addition of various contents of graphene oxide and sintering temperature on the mechanical, tribological, and electrical characteristics of WC-ZrO₂ composites. Wet processing and spark plasma sintering provided dense samples with simultaneous reduction of graphene oxide (rGO) during sintering. The obtained results showed that the best mechanical properties were observed at a sintering temperature of 1700 °C in samples with 0.5 vol.% rGO content; namely, indentation fracture toughness (5.8 ± 0.4 MPa·m^1/2) and flexural strength (872 ± 43 MPa) increased by 9% and 24.3% compared with the sample without rGO. In addition to improved mechanical performance, rGO-reinforced composites exhibited lower wear rates and friction coefficients than non-rGO composites, due to the formation of a graphitic lubricating tribolayer on worn surfaces and counterbodies in a friction pair, which provided sufficient lubrication to reduce the coefficient of friction and wear rate. The resulting composites also showed low electrical resistivity, suggesting the possibility of using electrical discharge machining to manufacture ceramic products of complex shapes from them. Full article

Hepatitis C virus (HCV) infection affects over 71 million people worldwide, leading to severe liver diseases, including cirrhosis and hepatocellular carcinoma. The virus’s high mutation rate complicates current antiviral therapies by promoting drug resistance, emphasizing the need for novel therapeutics. Traditional high-throughput screening (HTS) methods are costly, time-consuming, and prone to false positives, underscoring the necessity for more efficient alternatives. Machine learning (ML), particularly quantitative structure–activity relationship (QSAR) modeling, offers a promising solution by predicting compounds’ biological activity based on chemical structures. However, the “black-box” nature of many ML models raises concerns about interpretability, which is critical for understanding drug action mechanisms. To address this, we propose an explainable multi-model stacked classifier (MMSC) for predicting hepatitis C drug candidates. Our approach combines random forests (RF), support vector machines (SVM), gradient boosting machines (GBM), and k-nearest neighbors (KNN) using a logistic regression meta-learner. Trained and tested on a dataset of 495 compounds targeting HCV NS3 protease, the model achieved 94.95% accuracy, 97.40% precision, and a 96.77% F1-score. Using SHAP values, we provided interpretability by identifying key molecular descriptors influencing the model’s predictions. This explainable MMSC approach improves hepatitis C drug discovery, bridging the gap between predictive performance and interpretability while offering actionable insights for researchers. Full article

This paper presents a pH sensor with a Mach–Zehnder Interferometer (MZI) that operates in solutions of 4.0, 7.0, and 10.0. The sensor device consists of two tapered sections with dimensions of 1 mm/1 mm/1 mm for down-taper, waist-length, and up-taper, respectively, with a separation of 10 mm. The diameter of the waist is 40 $\mathsf{\mu }$m. This work includes the experimental evaluation of an MZI fiber optic pH sensor at 1559 nm, where 1559 nm represents a specific wavelength chosen for its optimal sensitivity in evaluating the sensor pH detection performance. It is not the central wavelength of the optical fiber, but one of the minimal values selected to enhance the interaction between the evanescent field and the sample, ensuring the reliable detection of pH variations. These sensor dimensions and the functionalized solution of multi-walled carbon nanotubes (MWCNTs) increase the detection of pH in dyes used in the textile industry. Alizarin is a strong anionic red dye that is part of the anthraquinone dye group. The experimental results demonstrated effective detection of pH levels in water contamination involving dye. This development could resolve the problem with Alizarin. The simple fabrication, low cost, and stability of the optical response make this sensor relevant for pH measurements in water contamination. Full article

Osseodensification is an innovative surgical instrumentation technique based on additive (non-cutting) drilling using special burs. It is known from the literature, that the osseodensification burs should operate in a clockwise direction to drill holes and in a counterclockwise direction to compact the osteotomy walls. For these purposes, the burs have special design features, like conical contour shape, increased number of helical flutes, and negative rake angle on the peripheral part. However, although other parameters and features of the burs define their overall performance, they are not described sufficiently, and their influence on surgical quality is almost unknown both for clinicians and tool manufacturers. The purpose of the present research is to identify the key design features of burs for osseodensification and their functional relationship with the qualitative indices of the procedure based on an analytical review of research papers and patent documents. It will help to further improve the design of osseodensification burs and thereby enhance the surgical quality and, ultimately, patient satisfaction. Results: The most important design features and parameters of osseodensification burs are identified. Thereon, the structural model of osseodensification bur is first represented as a hypergraph. Based on the analysis of previous research, functional relationships between design parameters of osseodensification burs, osseodensification procedure conditions, and procedure performance data were established and, for the first time, described in the comprehensive form of a hypergraph. Conclusions: This study provides formal models that form the basis of database structure and its control interface, which will be used in the later developed computer-aided design module to create advanced types of burs under consideration. These models will also help to make good experimental designs used in studies aimed at improving the efficiency of the osseodensification procedure. Full article

Over 10% of patients undergoing aortic endograft implantation experience endoleaks within a few years. In the case of type 1a endoleaks, a crack forms between the aorta and the prosthesis collar, allowing blood to pass. This blood fills the aneurysmal sac and can lead to its rupture. None of the strategies, such as prostheses with barbs and hooks or ad hoc pharmacological therapies, can prevent the phenomenon. An alternative approach is to reduce diameter oscillations due to pulsating pressure to improve the endoprosthesis adhesion to the internal vessel walls during the initial post-implantation phases. To reach this objective, we propose to use a passive intra-aortic balloon pump (PIABP) inserted and then maintained inside the vessel immediately after the surgical procedure. We tested our hypothesis in a mechanical mock of the cardiovascular system. A silicon aorta with physiological behavior was created for this purpose. The PIABP was inflated to increasing pressures between systolic and diastolic values (120/80 mmHg). For each aorta and each condition, the variations in aortic diameter between systole and diastole, and the pressure variations, were measured. For the normal aorta, with a PIABP pressure of 110 mmHg, the variations in diameter were reduced by 38%. Assuming an endoprosthesis with a diameter of 30 mm (oversized by 5% compared to the diastolic diameter), the time the oscillations are higher than 30 mm is also reduced by 36%. The results are positive and suggest the usefulness of a biomechanical approach to the problem of type 1a endoleaks. Further in silico and clinical trials are necessary to validate the method. Full article

Metallographic analyses of nodular iron casting methods are based on visual comparisons according to measuring standards. In fact, iron foundry workers have a poster that describes several characterizations of the metallographies and, showing the real metal in a microscope, they try to subjectively check the similarity between those examples and the real one. Currently, there are new approaches related to the application of machine vision and deep learning classifications. Although these aforementioned methods are more precise and accurate, they are more resource consuming, difficult to manage, and less scalable than other simpler methods that do not use the classical way of working with images. Moreover, for day-by-day work, this kind of precision is not needed, and this task must be carried out as fast as possible. Hence, this research work presents a novel approach to apply the same kind of comparisons carried out by human beings, but with the precision of a computer. Specifically, we construct a well-characterized vector database, populated with several metallographies analysed using accurate methods. Then, all images are represented by an embedding that tries to transform them into a vector representation to, finally, create the final classification and characterization of a specific metallography when applied a similarity search method in our learnt knowledge database. Full article

Inappropriate antimicrobial use in food animal farming propels antimicrobial resistance (AMR) that affects all health domains. Colistin is a ‘Reserve’ antibiotic for human treatment to be conserved for multidrug-resistant pathogens; however, it is being used as an animal growth promoter in many developing countries. The evolution of mobilized colistin resistance (mcr) gene-mediated colistin resistance has been reported to be associated with rampant colistin use. This study investigated the current variants of the mcr gene in chicken gut contents in Bangladesh. A cross-sectional study was designed to assess the mcr-1 to mcr-5 genes in 80 fresh poultry droppings from commercial poultry farms and 40 poultry droppings from household farms. DNA was extracted from each poultry dropping using commercial kits (Qiagen GmbH, Hilden, Germany). Real-time quantitative polymerase chain reaction (RT-qPCR) was employed using the qTOWER3 thermal cycler (Analytik Jena GmbH, Jena, Germany) to analyze the mcr gene variants in the extracted DNA. This study observed that 47.5% (57/120) of the samples exhibited the presence of at least one mcr gene out of the five variants investigated. The individual detection rates of the mcr-1, mcr-2, mcr-3, mcr-4, and mcr-5 genes were 42.5% (51/120), 2.5% (3/120), 1.7% (2/120), 5% (6/120), and 9.2% (11/120), respectively. The co-carriage of two or more genes was found in over 10% (10/57) of the samples. The triple occurrence of mcr genes was identified in three samples with the combination of mcr-1+mcr-2+mcr-4, mcr-1+mcr-3+mcr-5, and mcr-1+mcr-4+mcr-5. Overall, a significantly higher number of mcr genes were identified in the commercial farm chicken droppings compared to the household chicken droppings (p = 0.007). The existence of mcr genes in poultry feces in Bangladesh emphasizes the importance of proper poultry waste disposal and good hygiene practices in poultry livestock and its value chain. The potential impact of environmental ARGs should be considered in national and global policy documents. An integrated and combined approach to the One Health concept should be applied in all domains to understand and control the environment’s role in the evolution and transmission of AMR. Full article

(1) Background: Microbiota could be related to tumorigenesis through the persistence of an inflammatory state, also at the endometrial level. Inflammation, in fact, is involved in the promotion of genetic instability and in a favorable microenvironment for tumor growth. One pathway could be the disruption of the epithelial/mucosal barrier, with the activation of cytokines. The microbiota also seem to favor other involved patterns, such as insulin resistance and increased adipose tissue. (2) Methods: The online search for this review was based on keywords such as “endometrial cancer” and “microbiota” on the main online scientific database. Our objective is a narrative up-to-date review of the current literature on gynecological microbiota; we analyze the possible correlations with known modifying and promoting oncological factors (i.e., Body Mass Index- BMI, menopause, pH), with particular attention to vaginal and uterine microorganisms respective to the development of endometrial cancer in comparison to healthy women. (3) Results: Various species and distributions of bacteria could be related to tumorigenesis and induce alterations in cell signaling and cycle pathways, including those in the gynecological field. (4) Conclusions: In the literature, the different composition of uterine and vaginal microbiota has been analyzed in the past years, and their diversity and actions seem to correlate with possible oncological effects. Full article

Operational risk (OR) is usually caused by losses due to human errors, inadequate or defective internal processes, system failures, or external events that affect an organization. According to the Basel II agreement, OR is defined by seven risk events: internal fraud, external fraud, labor relations, clients, damage to fixed assets, technical failures and failures in the execution and administration of processes. However, the low frequency with which a loss event occurs creates a technological challenge for insurers in estimating the operational value at risk (OpVar) for the protection derived from an organization’s business activities. Following the above, this paper develops and analyzes a Deep Fuzzy Credibility Surface model (DFCS), which allows the integration in a single structure of different loss event databases for the estimation of an operational value at risk (OpVar), overcoming the limitations imposed by the low frequency with which a risk event occurs within an organization (sparse data). For the estimation of OpVar, the DFCS model incorporates a novel activation function based on the generalized log-logistic function to model random variables of frequency and severity that define a loss event (linguistic random variables), as well as a credibility surface to integrate the magnitude and heterogeneity of losses in a single structure as a result of the integration of databases. The stability provided by the DFCS model could be evidenced through the structure exhibited by the aggregate loss distributions (ALDs), which are obtained as a result of the convolution process between frequency and severity random variables for each database and which are expected to achieve similar structures to the probability distributions suggested by Basel II agreements (lean, long tail, positive skewness) against the OR modeling. These features make the DFCS model a reference for estimating the OpVar to protect the risk arising from an organization’s business operations by integrating internal and external loss event databases. Full article

Previous research has shown that higher glycosylated haemoglobin (HbA1c) levels are related to poorer quality of life. The objective was to analyse the moderating role of emotional intelligence (EI) in the relationship between HbA1c levels and quality of life through both positive (PA) and negative affect (NA) in individuals with Type 1 diabetes (T1D). A total of 72 participants with T1D (mean age = 41.10, SD = 10.73) were assessed on HbA1c. Psychological constructs were measured through the following questionnaires: MSCEIT (EI), PANAS (affect), and EsDQOL (quality of life). Higher levels of HbA1c and NA were related to a worse quality of life. In contrast, higher PA was related to a better quality of life. In addition, higher EI was associated with lower NA and worries about diabetes. In individuals with low EI scores, EI had a positive moderating effect on the relationship between HbA1c and NA. The moderated mediation analysis revealed a significant positive indirect effect of HbA1c on quality of life through NA moderated by EI for these individuals with low EI scores. This study shows how higher HbA1c levels have a negative impact on the quality of life of individuals with T1D and low EI levels by increasing their NA. Full article

The study site, a major teaching hospital in Dublin, Ireland, addressed significant challenges within its dermatology service through a comprehensive improvement initiative using a person-centred Lean Six Sigma methodology. Initially, the hospital’s dermatology department faced excessive outpatient waiting times, with 3736 patients awaiting appointments, and 1615 waiting over 12 months. The person-centred Lean Six Sigma approach, which combines Lean techniques to reduce non-value add and Six Sigma methods to eliminate variation through a person-centred lens, was applied to overhaul the referral, triage, and scheduling processes. Key interventions included standardising triage categories, centralising the triage process, and redistributing referrals equitably among consultants. A new centralised triage system was established, leading to a more efficient allocation of appointments and better management of urgent cases. Post-implementation data showed a 40% reduction in the overall waiting list and a 60% reduction in the number of patients waiting over 12 months. The initiative significantly decreased the wait times across all urgency categories, with the most notable improvements in soon and urgent referrals. These changes were also the impetus for a follow-up design-led innovation phase, where the team worked with partners across the educational and healthcare system to enable disruptive change. The success of this project provides a scalable model for improvements in similar healthcare settings. Full article

The concept of the centaur, symbolizing the fusion of human and machine intelligence, has intrigued visionaries for decades. Recent advancements in artificial intelligence have made this concept not only realizable but also actionable. This synergistic partnership between natural and artificial intelligence promises superior outcomes by leveraging the strengths of both entities. Tracing its origins back to early pioneers of human–computer interaction in the 1960s, such as J.C.R. Licklider and Douglas Engelbart, the idea initially manifested in centaur chess but faced challenges as technological advances began to overshadow human contributions. However, the resurgence of generative AI in the late 2010s, exemplified by conversational agents and text-to-image chatbots, has rekindled interest in the profound potential of human–AI collaboration. This article formalizes the centaurian model, detailing properties associated with various centaurian designs, evaluating their feasibility, and proposing a design methodology that integrates human creativity with artificial intelligence. Additionally, it compares this model with other integrative theories, such as the Theory of Extended Mind and Intellectology, providing a comprehensive analysis of its place in the landscape of human–machine interaction. Full article

Pancreatic lipase is an enzyme crucial for breaking down fats through hydrolysis, and inhibiting it is important for managing obesity. This study evaluated the lipase inhibitory profile of the leaf (SALE) and vine (SAVE) of Secamone afzelii, explored the modes of inhibition, identified the primary compounds responsible for this effect, and examined their molecular interactions with lipase using in vitro and in silico techniques. SALE (IC50: 0.41 ± 0.02 mg/mL) exhibited higher lipase inhibitory activity compared to SAVE (IC50: 0.95 ± 0.05 mg/mL), although it was significantly lower than orlistat (IC50: 0.07 ± 0.00 mg/mL) across all concentrations. S. afzelii extracts inhibited lipase activity through an uncompetitive mode of inhibition. Gas chromatography-mas spectroscopy identified 54 and 47 compounds in SALE and SAVE, respectively, with 9,12-octadecadienoic acid (Z, Z)-, n-hexadecanoic acid and 4S,6R-dimethyl-7R-hydroxynonan-3-one identified as the most abundant compounds in both extracts. The binding energy of the top five ligands from S. afzelii ranged from −7.7 to −6.6 kcal/mol, outperforming that of orlistat (−4.4 kcal/mol). The ligands and orlistat had similar binding poses stabilised by hydrogen and π interactions with CYS299, SER301, CYS304, ASN425 and VAL426. These compounds were predicted to possess promising pharmacokinetic, lipophilic and hydrophilic properties. These results offer insights into the traditional use of S. afzelii for treating obesity and valuable information on potential drug candidates that can be optimised for combating this disease. Full article

Curcumin, a bioactive compound derived from turmeric, possesses numerous pharmaceutical properties; however, its poor aqueous solubility and permeability result in low bioavailability. This study aims to develop a solid self-nanoemulsifying drug delivery system (S-SNEDDS) using different lactose types as solid carriers for the oral administration of curcumin to enhance its solubility. The system comprised curcumin, an oil phase, and a surfactant. Jasmine oil, as the oil phase, and Cremophor^® RH40, as the surfactant, were selected due to their superior ability to solubilize curcumin. A microemulsion was then prepared using a ternary phase diagram. The liquid SNEDDSs were converted into S-SNEDDSs by employing three solid carriers: Tablettose^® 80, FlowLac^® 100, and GranuLac^® 200. Dissolution studies conducted in simulated gastric fluid demonstrated a significant improvement in curcumin solubility in the S-SNEDDS formulations compared to curcumin powder. Differential scanning calorimetry (DSC) and X-ray diffraction (XRD) analyses confirmed the appearance of curcumin in the S-SNEDDS, while Fourier-transform infrared (FTIR) spectroscopy indicated compatibility between the excipients and curcumin. Additionally, an accelerated stability study conducted over four weeks at 40 °C and 75% relative humidity showed no significant changes in the physical appearance of the S-SNEDDS formulations. These findings suggest that the S-SNEDDS formulation effectively enhances curcumin’s solubility, potentially improving its bioavailability for oral administration. Full article

With approximately 18 million people affected by cancer in 2020 globally, scientists are exploring innovative approaches to develop effective treatments for various types of cancer. Traditional chemotherapy drugs, although effective against cancer cells, often lead to significant side effects on healthy tissues, such as hair loss, anemia, and nausea. To discover safer alternatives, researchers are investigating natural bioactive compounds found abundantly in plants. Luteolin, a flavonoid found in celery and artichokes, stands out due to its diverse anti-carcinogenic properties, including inhibiting proliferation, inducing apoptosis, activating autophagy, and inhibiting angiogenesis and metastasis. However, the therapeutic potential of luteolin is hindered by challenges related to its bioavailability and solubility. This critical review explores the specific anti-carcinogenic properties of luteolin while analyzing the impact of its limited bioavailability and solubility on effectiveness. Additionally, it investigates the outcomes of encapsulating luteolin in nanoformulations, providing insights into potential strategies for enhancing its anti-carcinogenic effects. Finally, the review compares the efficacy of luteolin with and without nanoformulations. This review provides valuable insights into the potential of utilizing luteolin-loaded nanoformulations as a safer and more effective method for treating cancer, contributing to the ongoing efforts in improving cancer care and outcomes worldwide. Full article

This study examines the relationship between inspiratory muscle performance (IMP) using the Test of Incremental Respiratory Endurance (TIRE), knee extension (EXT) and flexion (FLEX) acceleration (ACCEL) and deceleration (DECEL) times on an isokinetic dynamometer (ID), and performance of the Yo-Yo Intermittent Recovery Test Level 1 (YYIRT1) among thirteen Division I collegiate women soccer players (D1CWSP). Knee EXT and FLEX were tested at three velocities (60°/s, 180°/s, and 300°/s) using ID, while IMP was measured using maximal inspiratory pressure (MIP) and sustained maximal inspiratory pressure (SMIP). Significant negative correlations were found between MIP and the ACCEL time of FLEX at 60°/s and 300°/s, as well as between MIP and the DECEL time of EXT at 180°/s. Additionally, SMIP was negatively correlated with ACCEL times of FLEX at 180°/s and 300°/s and with DECEL times for both EXT and FLEX at 300°/s. These results suggest that greater IMP is linked to faster ACCEL and DECEL times in knee EXT and FLEX, indicating a role of IMP in enhancing muscle recruitment and performance. The only significant correlation with the YYIRT1 performance was observed between the YYIRT accumulated distance and the ACCEL time of FLEX at 180°/s. These findings highlight a physiological mechanism whereby IMP may contribute to improved dynamic muscle performance, though further research is needed to explore its implications for overall athletic performance. Full article

The rise of antimicrobial resistance (AMR) has become a critical health challenge. This, plus the antimicrobial discovery void, had led scientists to search for an effective alternative to antimicrobials. In this context, nanomaterials, such as graphene oxide (GO), a two-dimensional (2D) carbon molecule with oxidized functional groups, have been shown to interact physically and chemically with bacteria. Moreover, the addition of polyethylene glycol (PEG) to its surface enhances GO’s biocompatibility and water solubility, making it a promising candidate for biomedical applications. This study evaluates the antimicrobial efficacy of GO and its polyethylene glycol-modified form (GO-PEG) against Staphylococcus aureus, a bacterium responsible for numerous hospital-acquired and multidrug-resistant infections. After their production, both nanomaterials were characterized using various techniques to provide insight into their morphology, stability, and functional group composition. Then, the antimicrobial activity of GO and GO-PEG was assessed using the Müeller–Hinton broth microdilution method, determining the minimum inhibitory concentration (MIC) for S. aureus among ten different concentrations of both nanomaterials (from 0.0625 to 32 mg/mL). The results demonstrate the potential of GO as an effective antimicrobial agent at 16 and 32 mg/mL, offering new strategies in the fight against AMR. Further research could establish its role in future therapeutic applications. Full article

The umbilical cord, comprising three vital blood vessels, serves as the lifeline between mother and fetus. Prenatal care emphasizes detailed ultrasound examinations of the umbilical cord and postnatal inspections of the placenta and cord to preemptively address potential complications. Studies have consistently shown a significant link between a single umbilical artery and unfavorable perinatal consequences, such as mortality and congenital abnormalities. Conversely, the impact of additional vessels remains uncertain. This review is dedicated to enhancing our understanding and refining diagnostic and therapeutic approaches in prenatal healthcare. The objective is to identify knowledge gaps and propose evidence-based solutions to improve care for pregnant women and their unborn babies. The presence of a single umbilical artery in prenatal diagnosis may signify potential risks for fetal anomalies and adverse pregnancy outcomes such as hemodynamic instability, ischemia, and an increased likelihood of intrauterine growth restriction. Additionally, even the presence of supernumerary vessels may be associated with fetal malformations. Serial fetal evaluations are recommended for detecting anomalies and monitoring fetal growth throughout pregnancy. Despite the generally benign nature of isolated SUA and supernumerary vessels, close monitoring and comprehensive prenatal care are essential to ensuring optimal outcomes for both mother and baby. Full article

Background: Acute ischemic stroke (AIS) is one of the leading causes of death in the industrialized world and causes a heavy personal and economic burden. Thrombus perviousness, measured with pre-interventional computed tomography (CT), is a relatively new imaging biomarker with the potential to estimate clinical outcome in AIS and optimize therapy. However, reported findings on the relationship between thrombus perviousness and clinical parameters in AIS are conflicting. In this study, we investigated the characteristics of the time-resolved contrast agent uptake in thrombi and the predictive potential for clinical outcomes. Methods: We analyzed 55 AIS patients who underwent pre-interventional CT perfusion and recanalization with mechanical thrombectomy. A thrombus with a visible hyperdense artery sign was segmented in 2D. Thrombus standard perviousness was measured as the mean thrombus attenuation increase (TAI) between CT angiography (CTA) and NCCT. For dynamic perviousness, the time-resolved contrast agent uptake curve (CAU) was derived from a 30-phase CT perfusion (CTP) measurement. The rise time (t_rise) and the TAI increase rate per second (∆d), as well as the time window for the 10th (tW₁₀), 20th (tW₂₀), and 30th (tW₃₀) percentiles of the CAU peak, were calculated. The standard and dynamic perviousness (t_rise, ∆d, tW₁₀, tW₂₀, and tW₃₀₎ were analyzed for their associations with clinical outcomes (3-month mRS) with the Wilcoxon signed rank test. Results: Dynamic perviousness was associated with the clinical outcome. The group mean t_rise and ∆d for thrombi with good clinical outcomes (mRS ≤ 2) were approximately 20% lower (p = 0.04) and 36% higher (p = 0.02) than those for thrombi with poor outcomes (mRS > 2). The time windows for the 10, 20, and 30% maximum contrast agent concentrations in the thrombus were approximately 40% (p = 0.004), 18% (p = 0.02) and 33% (p = 0.004) lower in thrombi with good outcomes than in thrombi with poor outcomes, respectively. Standard perviousness showed no association with clinical outcome. Conclusion: Dynamic perviousness from perfusion imaging retrieves the CAU characteristics of thrombi with greater resolution detail than standard perviousness. Thrombi with relatively fast contrast agent uptake dynamics are more prone to good clinical outcomes than thrombi with slow uptake dynamics. Full article

Lead sulfide (PbS) on the nanoscale was synthesized via a chemical route at room temperature using lead nitrate {Pb(NO₃)₂} and sodium sulfide (Na₂S). The Na₂S was prepared at ~105 °C using sodium hydroxide (NaOH) and sulfur (S) powder. The produced PbS, denoted as Lab-PbS, was compared with a high-concentration PbS phase of galena. The produced Na₂S and Lab-PbS were examined using scanning electron microscopy and energy dispersive X-ray spectroscopy for microstructural and chemical analysis. The results confirmed a high-purity PbS compound (>99%) with a nanoscale particle size. The results showed that ultrasonic agitation was vital for obtaining the nanoparticle size of the Lab-PbS. Furthermore, thin films from the synthesized Lab-PbS and galena were successfully thermally evaporated on glass, quartz, and silicon substrates. The formation of nanometric grains was confirmed by scanning electron microscopy (SEM). XRD and FTIR spectroscopy were carried out for the Lab-PbS, galena fine powders, and galena thin films. The average crystal diameter was calculated for the galena thin films and was found to be approximately 26.6 nm. Moreover, the UV–Visible transmission curve was measured for the thin films in the wavelength range of 200–1100 nm in order to calculate the bandgap energy (E_g) for the thin films. The values of E_g were approximately 2.65 eV and 2.85 eV for the galena and Lab-PbS thin films, respectively. Finally, the sintering of the Lab-PbS and galena powders was carried out at ~700 °C for 1 h under vacuum, achieving relative densities of ~98.1% and ~99.2% for the Lab-PbS and galena, respectively. Full article

This study explores the evolution and impact of research on the challenges and opportunities in the implementation of artificial intelligence (AI) in manufacturing between 2019 and August 2024. By addressing the growing integration of AI technologies in the manufacturing sector, the research seeks to provide a comprehensive view of how AI applications are transforming production processes, improving efficiency, and opening new business opportunities. A bibliometric analysis was conducted, examining global scientific production, influential authors, key sources, and thematic trends. Data were collected from Scopus, and a detailed review of key publications was carried out to identify knowledge gaps and unresolved research questions. The results reveal a steady increase in research related to AI in manufacturing, with a strong focus on automation, predictive maintenance, and supply chain optimization. The study also highlights the dominance of certain institutions and key authors driving this field of research. Despite the progress, significant challenges remain, particularly regarding the scalability of AI solutions and ethical considerations. The findings suggest that while AI holds considerable potential for the manufacturing industry, more interdisciplinary research is needed to address existing gaps and maximize its benefits. Full article

Background and aim: Metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as non-alcoholic fatty liver disease (NAFLD) affects up to 25% of the population and causes significant morbidity and mortality. Sarcopenia, the loss of muscle strength and quantity/quality, shares multiple pathways with MASLD, pointing to their possible association. In this systematic review, we aimed to describe the association between low muscle mass and/or strength and/or performance and the presence, development, or severity of MASLD/NAFLD. Methods: A search was performed in PubMed, Web of Science, Scopus, and LILACS, on 16 October 2020, for relevant studies, using a comprehensive search query and following PRISMA guidelines for systematic review conduction and reporting. Results: The search yielded 1042 results, of which 42 full papers and 11 poster abstracts were included. NAFLD was determined by imaging (n = 27), non-invasive tests (n = 13), liver biopsy (n = 11), or transient elastography (n = 2), and its severity by liver biopsy (n = 10), non-invasive tests (n = 7), transient elastography (n = 7), or imaging (n = 4). Muscle mass was, in most cases, adjusted for weight (n = 25), body mass index (BMI; n = 13), or height (n = 10). Most studies showed an association of low muscle mass and low strength with NAFLD presence and severity. However, the association of muscle mass with NAFLD was present when muscle mass was adjusted for weight or BMI but not when it was adjusted for height. A meta-analysis was not possible due to high heterogeneity in the methods of assessment of muscle parameters and NAFLD. Conclusions: This systematic review suggests the need for standardization of methods in this discipline. The issuing of specific guidance regarding sarcopenia in NAFLD would be of importance. Full article

This study explores the effects of offshoring and backshoring on value creation per employee within the manufacturing sector by investigating the difference between firms that did and those that did not engage in corresponding relocation activities. Historically, offshoring has been a strategy to reduce costs and increase efficiency. However, the rise of advanced digital technologies and changing market dynamics have sparked a countertrend toward backshoring. Using data from the European Manufacturing Survey, this research examines how these strategies impact value creation, also taking into account the roles of sales growth and export intensity as potential moderators. The results of hierarchical regression analysis indicate that neither firms that have engaged in offshoring of production nor firms that have engaged in offshoring of R&D have significantly higher or lower value creation per employee than those that did not. In contrast, firms that have engaged in backshoring of production realize higher value creation when coupled with high sales growth. Firms that have engaged in backshoring of R&D, on the other hand, realize higher value creation when combined with high export intensity. These findings highlight the importance of aligning strategic decisions with both technological capabilities and market conditions to enhance productivity. The study suggests that a balanced and holistic approach, integrating both offshoring and backshoring strategies tailored to specific business contexts, can optimize value creation and maintain competitiveness in a rapidly evolving global landscape. Full article

Periodontitis is characterized by gingival regression, alveolar bone resorption and the development of deep periodontal pockets that, if left untreated, can lead to tooth loss. Currently, specific biomarkers are needed for the early, objective diagnosis, monitoring, and management of periodontal patients. In this proteomic study, periodontal pocket tissues from patients with severe periodontitis were analyzed in comparison to periodontally healthy sites with the aim of discovering distinctive protein targets. Gingival tissues were fragmented using a motorized mechanical method and mixture protein was separated via mono-dimensional gel electrophoresis. The examination of protein bands using definite 1D image analysis software allowed for the detection of 22 differentially expressed proteins between pathological and healthy samples that were identified through mass spectrometry. A comparative assessment of these proteins with those previously reported in other studies conducted on periodontal diseases in various types of oral specimens, such as gingival crevicular fluid, dentin, tooth pulp, root canal content, salivary gland secretions, saliva, periodontal ligament cells, and dental stem cells, highlighted a great number of significant common matches. The discovery of a selective cluster of periodontitis-related biomarkers could become particularly important before the clinical manifestation of the disease to promptly stop its progression for a timely preventive diagnosis. Full article