Abstract: In this work, we inspected the friendship network on Twitter (recently rebranded as X), concentrating on individuals and organizations intertwined with the energy field. We particularly focus on seasoned professionals, corporate entities, and domain specialists, all connected through `following’ relationships. By meticulously examining these ties, we uncover several distinct groupings within the network, each defined by the unique roles its members occupy. Our analysis demonstrates that the natural emergence of such clusters on social platforms exerts a profound influence on public discourse regarding energy and other critical matters, including climate change. Furthermore, we reveal that the ever-changing interplay of misleading information catalyzes the formation of ideologically divided factions, which often leads to reduced engagement in online conversations. These emergent clusters, characterized by their shared communication styles, form relatively compact communities where the exchange of information is infrequent compared to larger networks and is usually confined to accounts created for specific commercial objectives. Additionally, by leveraging a machine learning approach, we are able to pinpoint pivotal actors within these niche segments and elucidate the mechanisms that sustain their connectivity. This method provides novel insights into how corporate communication unfolds on social media, offering a refreshed perspective on professional networking. Ultimately, our findings highlight the ways in which companies within the energy sector take advantage of Twitter to coordinate their initiatives, with key institutions serving as central nodes in maintaining the organization of these networks.

Abstract: Background/Objectives Light-assisted in-office whitening procedures are widely used in clinical practice; however, comparative clinical data remain limited, particularly when evaluated using objective outcome measures. This exploratory pilot randomized clinical trial aimed to assess the immediate objective performance of two light-assisted in-office whitening protocols using standardized digital spectrophotometry. Materials and Methods Twelve healthy adult participants (18–45 years) presenting extrinsic or mixed-type tooth discoloration (baseline shade VITA A3 or darker) were randomly allocated into two parallel groups (n = 6 each). One group received whitening with a 35% hydrogen peroxide gel activated by a diode laser device, while the other group underwent whitening with a 25% hydrogen peroxide gel activated by an LED-based device. Tooth color was measured before and immediately after treatment using a digital spectrophotometer (VITA Easyshade V, VITA Zahnfabrik, Bad Säckingen, Germany), and color differences (ΔE) were calculated based on CIE L*a*b* coordinates. Statistical analysis was performed using the Mann–Whitney U test. Results: Both light-assisted interventions resulted in clinically perceptible whitening outcomes (ΔE > 3.3). The LED-assisted group showed a slightly higher mean ΔE value (11.62 ± 5.93) compared with the laser-assisted group (10.96 ± 3.27); however, the difference was not statistically significant (p = 0.818). Given the limited sample size, the study was not powered for definitive comparative inference. No adverse events were recorded. Conclusions: Within the limitations of this exploratory pilot randomized clinical trial, both light-assisted in-office whitening protocols produced immediate clinically perceptible color changes. Although no statistically significant difference was detected, the limited sample size precludes definitive conclusions regarding relative efficacy. Larger, adequately powered randomized studies incorporating longitudinal follow-up and patient-reported outcomes are required to confirm these preliminary findings.

Abstract: Seasonal influenza in children is usually recognized as acute febrile respiratory syndrome. This commentary highlights recent clinical observations in which influenza-like illness was accompanied by conjunctivitis and sleep-related breathing abnormalities (new snoring and brief apnea-like events), sometimes accompanied by oxygen desaturation. Because these features are not classic manifestations of seasonal influenza, they are best framed as associated findings that may reflect upper-airway inflammation, post-nasal drip, or concomitant lower-respiratory involvement. The commentary discusses the Egyptian/African approach using Kelleni’s protocol in its outpatient management and calls for independent monitoring by pediatric and ENT/sleep clinicians to determine whether a reproducible pattern is emerging across settings.

Abstract: This study presents an innovative approach for the selective extraction of Co(II) and its separation from Ni(II) using ethyl ester glycine-betaine derivatives, specifically tri(n-pentyl)[2-ethoxy-2-oxoethyl]ammonium dicyanamide, as extractants in combi-nation with continuous-mode liquid–liquid contact. Semi-pilot-scale implementation requires non-equilibrium conditions, characterized by short contact times between ef-fluent and extractant phases. To address this, we propose dissolving analog of gly-cine-betaine ionic liquid (AGB-IL) in low-viscosity MIBK solvents to enhance mass transfer while reducing dependence on fossil-based solvents. Liquid–liquid extraction and continuous-flow stripping experiments were designed based on prior batch results and conducted in a saline environment, employing a chaotropic electrolyte for extrac-tion and a kosmotropic electrolyte for stripping. Both open and closed systems were tested to compare extractive performance with batch conditions and with scenarios representative of industrial operations. Results indicate that continuous-flow systems achieve performance comparable to batch systems in terms of extraction efficiency, Co/Ni separation coefficients, and recyclability. These findings provide proof of con-cept for the development of semi-pilot and pilot-scale processes for efficient cobalt re-covery.

Abstract: Background/Objectives: In the United States alone, new prostate cancer (PCa) cases for 2023 are estimated at 288,300 and deaths at 34,13700 [1]. Prostate imaging is increasingly evaluated by artificial intelligence and computer-assisted targeting which opens new opportunities in biopsy and the focal therapy of visualized lesions [2]. Our objective was to investigate the safety and feasibility of using MR-guided focal laser (light amplification by the stimulated emission of radiation) therapy for these visible cancers using a transrectal approach for both laser applicator placement and therapy delivery in an outpatient setting. Methods: We used a 1.5 Tesla MRI scanner (Philips Healthcare, Best, The Netherlands) for both image acquisition and real-time thermometry. In addition, we used a commercially available CAD system and targeting hardware (Philips, Best, The Netherlands) for image analysis and interventional planning. Laser focal therapy of biopsy-proven lesions was delivered using a U.S. Food and Drug Administration (FDA) 510(k) cleared laser emitter, laser fiber and thermal mapping visualization software (Medtronic, Minneapolis, MN, USA) introduced transrectally under MRI-guidance. Results: 112 cancer foci were treated in 81 men, from Gleason Grade 1 (GG1) to GG3 for treatment-naïve patients and all Gleason Grades for salvage patients. With pre-treatment lesion volumes ranging from 0.03 cc to 6.6 cc, with a mean of 1.1 cc and a median of 0.49 cc (25% and 75% quartiles of 0.25 cc and 1.4 cc respectively). The mean MRI volume of coagulation necrosis was 7.1cc and ranged from 0.6cc to 22.9cc. No serious adverse events or morbidity were reported. At six-month MR-guided in-bore biopsy 25 treatment regions were positive for clinically significant disease (GG>1), consistent with in-field residual or recurrent cancer rate of 22% of regions and 23% of subjects. We observed a 40% decrease in mean PSA at 1 year post therapy in the entire cohort. Conclusions: Our data indicate that transrectally delivered MRI-guided laser focal therapy for prostate cancer is both safe and feasible in an outpatient setting and results in a significant biochemical response and acceptable cancer control rate at 6 months.

Abstract: Background: Spirituality and religious diversity are increasingly recognized as essen-tial components of holistic nursing care in global healthcare systems. However, their integration into undergraduate nursing education remains heterogeneous and often insufficiently structured, creating a gap between professional values and students’ preparedness to address spiritual needs in culturally diverse clinical environments. This study aimed to explore nursing students’ perceptions, attitudes, and perceived skills regarding spirituality, religion, and spiritual care, and the factors associated with these dimensions. Methods: A descriptive exploratory survey was conducted on a sample of 69 third-year students of the Degree Course in Nursing belonging to two Roman universities. Data were collected between May and July 2025 using the Nursing Care and Religious Diversity Scale (NCRDS), consisting of 31 items. Statistical analyses included descriptive statistics, internal reliability analyses, group comparisons, and multivariate regression models. Results: Students showed moderate levels of attention to patients' spiritual needs and integration of spirituality into care practice, while high importance was given to spiritual care skills. University education was perceived as only partially adequate. Multivariate analyses showed that students' personal spiritu-ality is positively associated with the assessment of spiritual needs and the perception of competence, while exposure to contexts characterized by greater religious diversity is associated with a lower perception of preparedness. Conclusions: The results high-light a discrepancy between professional values and perceived operational skills, sug-gesting the need to systematically integrate spirituality and religious diversity into nursing curricula. A structured training approach could strengthen transferable pro-fessional skills and promote truly holistic and person-centred care.

Abstract: Background: Tuberculosis (TB) remains a major public health challenge in many low- and middle-income countries, where socio-economic inequalities continue to undermine treatment success. Structural barriers such as poverty, unemployment, and limited access to healthcare services can disrupt treatment adherence and contribute to poor outcomes. While biomedical interventions remain central to TB control, there is growing recognition that community engagement strategies may strengthen TB management. This study examined the influence of socio-economic determinants on TB treatment outcomes and explored the potential contribution of community engagement interventions to improving TB care in rural settings. Methods: A retrospective quantitative analysis was conducted using a dataset of 512 patient records with documented TB treatment outcomes. Descriptive statistics were used to summarise patient characteristics. Multivariable logistic regression was applied to identify socio-economic determinants associated with unsuccessful treatment outcomes. Scenario-based predictive modelling and marginal effects analysis were then used to estimate the potential impact of integrating community engagement mechanisms, including community health worker outreach, peer support networks, and community-based health education. Results: Overall, 79.1% of patients achieved successful treatment outcomes, while 17.0% experienced unsuccessful outcomes. Social vulnerability was strongly associated with poor treatment outcomes (AOR = 1.8; 95% CI: 1.2–2.6). Unemployment (AOR = 1.6; 95% CI: 1.1–2.3) and unstable income sources (AOR = 1.5; 95% CI: 1.0–2.2) were also significant predictors of unsuccessful outcomes. Predictive modelling suggested that integrating community engagement interventions could reduce the predicted probability of unsuccessful treatment outcomes from 17% to approximately 10%. Interaction analysis further indicated that the greatest improvements occurred among patients with high socio-economic risk. Conclusion: Socio-economic vulnerability remains a critical determinant of TB treatment outcomes. Integrating community engagement strategies, particularly community-based health education and patient support mechanisms, may improve treatment adherence and reduce unsuccessful outcomes, especially among socially disadvantaged populations. Strengthening community participation in TB programmes may therefore represent an important pathway toward more equitable and effective TB control. Keywords: tuberculosis; community engagement; socio-economic determinants; treatment outcomes; health education; rural health; predictive modelling.

Abstract: Functional information measures how rare functional configurations are. Wong and colleagues argue that selection should drive a law of increasing functional information. This is often read as a claim that complexity must increase. Here I give a different interpretation, which is that survivors tend to be the systems that did not overcommit. I model a system as a policy π, meaning a bundle of commitments expressed in a finite embodied vocabulary. New selection pressures arrive as a set of future requirements drawn from the unobserved outcome set U. A currently viable policy leaves an unobserved buffer B_π ⊆ U of outcomes it still permits. Under a maximally ignorant novelty model, the survival probability of π is exactly 2^{|B_π| − |U|}. Under any exchangeable novelty prior, survival remains monotone in B_π. So persistence under novelty favours weak policies, where weakness counts the compatible completions left open. I define degree of future function as survival probability and functional information as Hazen and Szostak rarity within the currently viable set. Conditioning on persistence reweights the viable set toward larger buffers and therefore toward higher functional information. This yields a mathematical analogue of the proposed law under explicit assumptions. Supplementary analysis quantifies how much structured novelty is needed before that buffer size ordering can reverse. In fully enumerated toy worlds, weakness maximisation improves mean log survival probability relative to random choice. Weakness and simplicity are not the same thing. Weakness helps a system persist under novelty, because it keeps more futures compatible. Simplicity helps a system persist because there is less to break, which obviates the need for repair. Complexity requires self-repair to persist, increasing weakness. Life is persistent complexity. In between complex life and simple nonlife is the void of the unviable: complexity which is not alive.

Abstract: Open-pit mining relies heavily on visual inspection to identify indicators of slope instability such as surface cracks. Early identification of these geotechnical hazards allows for the implementation of safety interventions to protect both workers and assets in the event of slope failures or landslides. While computer vision (CV) approaches offer a promising avenue for autonomous crack detection, their effectiveness remains constrained by the scarcity of labelled geotechnical datasets. Deep learning (DL) models require large amounts of representative training data to generalize to unseen conditions; however, collecting such data from operational mine sites is limited by safety, cost, and data confidentiality constraints. To address this challenge, we propose a hybrid game engine—generative artificial intelligence (AI) framework for large-scale dataset synthesis. Leveraging a parameterized virtual environment developed in Unreal Engine 5 (UE5), the framework captures realistic images of open-pit surface cracks and enriches their visual diversity using StyleGAN2-ADA. The resulting datasets were used to train the YOLOv11 real-time object detection model and evaluated on a real-world dataset of open-pit slope imagery to assess the effectiveness of the proposed framework in improving CV model generalizability under extreme data scarcity. Experimental results demonstrated that models trained on the proposed framework substantially outperformed the UE5 baseline, with average precision (AP) at intersection over union (IoU) thresholds of 0.5 and [0.5:0.95] increasing from 0.403 to 0.922 and 0.223 to 0.722 respectively, accompanied by a reduction in missed detections from 95 to eight for the best-performing configurations. These findings demonstrate the potential of hybrid generative AI frameworks to mitigate data scarcity in CV applications and support the development of scalable automated slope monitoring systems for improved worker safety and operational efficiency in open-pit mining.

Abstract: Background/Objectives: Heart rate variability (HRV) and ventricular repolarization parameters are non-invasive markers of cardiac autonomic regulation and electrical stability. Although these parameters un-dergo significant maturational changes during childhood, normative data and their physiological interac-tions in healthy pediatric populations remain insufficiently explored. This study aimed to evaluate the rela-tionship between HRV and ventricular repolarization indices (QT, QTc, QTd, QTcd) in healthy children and to establish age-stratified normative reference values for HRV parameters across four distinct age groups. Methods: This cross-sectional study included 254 healthy children (145 males, 57.1%; mean age 12.51 ± 3.55 years, range 5–18 years). All participants underwent 24-hour ambulatory electrocardiographic (Holter) monitoring. HRV parameters (SDNN, SDANN, RMSSD, pNN50, LF, HF, and LF/HF ratio) and ventricular repolarization indices (QT, QTc, QTd, QTcd) were derived. Participants were stratified into four age groups: 5–8, 9–12, 13–15, and 16–18 years. Normative percentile distributions (5th–95th) were generated for all HRV parameters. Results: Significant maturational increases were observed in all time- and frequency-domain HRV parame-ters across the four age groups (p < 0.001), accompanied by a decline in heart rate (r = -0.471, p < 0.001). The uncorrected QT interval showed strong positive correlations with all HRV indices, particularly SDNN (r = 0.434, p < 0.001) and RMSSD (r = 0.426, p < 0.001), while heart rate correction (QTc) attenuated these associations. Repolarization heterogeneity (QTd) correlated significantly with SDNN (r = 0.269, p < 0.001) and HF (r = 0.186, p = 0.004). Females exhibited significantly higher QTc values (r = 0.294, p < 0.001) and lower mean HRV values compared to males. Multivariate regression identified sex as the only significant independent predictor of QTc (β = 0.294, p < 0.001). Conclusion: Cardiac autonomic modulation, as reflected by HRV, significantly influences ventricular re-polarization dynamics in healthy children. The age-specific normative percentile charts established in this study provide a robust physiological reference for pediatric cardiac autonomic and electrophysiological assessment, facilitating improved clinical interpretation and arrhythmic risk stratification in children and adolescents.

Abstract: Certain integer transformations exhibit unexpected forms of stability that resemble attractors in dynamical systems. Two classical examples are the Kaprekar transformation leading to the constant 6174 and the arithmetic structure of perfect numbers. Although traditionally studied in separate areas of number theory, both phenomena reveal a common feature: the emergence of stable configurations under discrete informational constraints. In this work, we propose a unified framework based on Viscous Time Theory (VTT) and its informational geometry perspective, in which these two structures are interpreted as complementary forms of arithmetic stabilization. The Kaprekar transformation defines a discrete dynamical system whose iterations rapidly converge to a unique attractor (6174) for almost all four-digit inputs. Perfect numbers, on the other hand, arise as equilibrium points of the divisor-sum operator, where the informational deviation between a number and the sum of its proper divisors vanishes. We formalize both mechanisms using a common representation based on discrete informational tension functions defined over the integers. Within this framework, Kaprekar collapse appears as a dynamic attractor produced by iterative dissipation of digit-configuration tension, while perfect numbers correspond to static coherence wells generated by structural balance in the divisor field. Numerical exploration further suggests the presence of near-equilibrium zones—arithmetic configurations where informational gradients become locally minimal. These structures provide a natural bridge between iterative attractors and divisor-based equilibria, suggesting that stability phenomena in number theory may be understood through a broader lens of informational relaxation processes. The results do not claim new proofs regarding perfect numbers, but instead propose a conceptual and computational framework that unifies dynamic and structural stability in arithmetic systems. This perspective may provide new tools for exploring discrete attractors, divisor dynamics, and informational structures within number theory.

Abstract:

Background and Objectives: Postoperative pain and intra-abdominal adhesions are common complications following surgery. Pain delays early mobilization, whereas adhesions can lead to bowel obstruction, chronic pain, or infertility. Current treatments, including systemic analgesics and physical barrier methods, are only partially effective. We hypothesized that combining these modalities would yield superior outcomes. Accordingly, we investigated whether a lidocaine-loaded alginate–carboxymethyl cellulose–polyethylene oxide (ACPE) electrospun film could more effectively reduce both postoperative pain and adhesion formation than either component alone. Materials and Methods: An electrospun nanofiber film composed of ACPE containing lidocaine was prepared. Its effects were evaluated in rats using an incisional pain and a peritoneal adhesion model. Four groups were compared: saline control, free lidocaine, drug-free ACPE film, and lidocaine-loaded ACPE film. Fifteen rats were allocated to each group. The primary outcome was the mechanical withdrawal threshold (MWT) after plantar incision, while secondary outcomes included histological changes and adhesion scores assessed by the Moreno system. Results: The lidocaine–ACPE film significantly increased MWT compared with all other groups, demonstrating a stronger and longer-lasting analgesic effect than free lidocaine. Adhesion scores were also lowest in the film group. Histological analysis confirmed a reduction in inflammatory cell infiltration and collagen deposition. Conclusion: A lidocaine-loaded ACPE nanofiber film effectively reduced both postoperative pain and adhesion formation in a rodent model. The combination of sustained local drug release and physical barrier function provides a promising strategy to address two major postoperative complications. Further preclinical studies are warranted before clinical application.

Abstract: Newborn screening for Congenital adrenal hyperplasia (CAH) is effective in identifying patients with severe forms before a potentially lethal crisis but has a relatively high false positive rate. The aim of this study was to improve the national neonatal screening program in Sweden, and the positive predictive value by implementing a LC-MS/MS second-tier testing. A combination of two independent parameters, the steroid hormone ratio (androstenedione+17-hydroxyprogesterone)/cortisol and the concentration of 21-deoxycortisol and adjustment of cut-off levels resulted in an increase of the positive predictive value (PPV) from 14 % to 84 % for full-term infants. In total the false positive screening cases decreased by 88 %. CYP21A2 genotyping was used to determine the severity of CAH in identified cases. We report on the stepwise approach that was used to optimize the cut-off levels for full-term and preterm infants in order not to miss any true cases in the process.

Abstract: This study examines whether the effects of fiscal revenue and expenditure on grain production in China are nonlinear. Using a balanced panel of 31 provinces from 2007 to 2021, we analyze major revenue-side and expenditure-side fiscal instruments, including the cultivated land occupation tax, value-added tax, agricultural insurance subsidies, agricultural loan interest subsidies, rural minimum living security subsidies, education expenditure, and transportation infrastructure expenditure. To identify regime-dependent marginal effects, we employ panel kink and double-kink regression models with endogenously estimated kink points. The results show that fiscal effects are intensity-dependent rather than constant. The cultivated land occupation tax exhibits a kinked relationship with grain production, with a stronger land-protection effect beyond a certain policy intensity. Agricultural insurance subsidies display a double-kink pattern, with the strongest positive effect concentrated in an intermediate subsidy range. Rural minimum living security subsidies are positively associated with grain production at lower levels, but their marginal effect weakens and may become negative after the kink point. Overall, the findings suggest that fiscal policy effectiveness depends not only on policy direction but also on policy intensity, implying that grain-support policies should be calibrated with attention to nonlinear threshold effects.

Abstract: The origin of uranium-series imbalance and radiogenic lead excess has long been a subject of debate. Here, based on a novel theory of neutrino oscillation-induced radioactive decay and magma formation, a unified mechanism is proposed to explain uranium-series imbalance, radiogenic lead excess, and excess argon formation. This mechanism indicates that magma originates from the upper mantle, formed by the melting of its constituent materials due to accelerated radioactive decay induced by atmospheric neutrino oscillations. During magma formation, radioactive decay rates typically increase due to Mikheyev-Smirnov-Wolfenstein (MSW) resonance perturbations from neutrino oscillations. This effect causes radioactive isotopes to decay over a shorter period than their normal half-lives would suggest, resulting in overestimated ages based on decay laws. Consequently, radioactive daughter isotopes and radiogenic isotopes become enriched relative to their parent isotopes. The accelerated melting of radioactive materials due to increased decay rates means that both the excess of radioactive daughter isotopes and radiogenic isotopes accompany the magma formation process. When using radiometric dating, careful consideration of the mineral's formation environment is essential. Generally, minerals formed in the crust or at the Earth's surface exhibit relatively normal radiometric ages, whereas minerals formed in the mantle or glassy materials solidified from magma tend to show radiometric ages that are older to varying degrees.

Abstract: Jet anomaly detection in a high-energy physics is a non-stationary task that is fuelled by shifts in the domain due to pile-up and predominantly by background noise, and dynamically changing relationships between jet constituents in such a scenario, where a conventional graph neural network architecture is frequently inadequate in terms of robustness and interpretability. Physics-Self-Adaptive Multi-Agent System (PhySA-MAS) is a physics-directed, self-adaptive multi-agent architecture that proposes jet analysis as a decentralized and dynamically reconfigurable reasoning scheme. It does not use one monolithic model but instead integrates specialist agents dealing with meta-learning, relational reasoning, communication and topology control which can vary their interactions depending on event-level physics. The energy conservation constraints are incorporated in graph message passing to provide physical consistency, and a reinforcement driven topology controller rewires inter-agent communication dynamically to forces according to anomalous patterns. An additional communication strategy, anchor-peer communication, ensures the further stabilization of learning through the reduction of gradient conflict and the amplification of the signals related to anomalies, which, in combination, offers a powerful and structurally understandable alternative to fixed deep learning models.

Abstract: Background/Objectives: To develop and preliminarily evaluate a practical Python‑based program for universal dynamic intracardiac blood flow visualization and the extraction of new quantitative parameters, serving as an initial step toward future flow‑based cardiac evaluation. Methods: The method was applied across five imaging modalities (angiography, MRI, ICE, TEE, TTE) using standard diagnostic hardware. Preliminary testing used ECG‑gated ICE DICOM images from sixteen patients undergoing first‑time AF ablation. Results: The program produced straightforward, easily adoptable flow visualizations and automatically computed the *Turbulence Index (TI)* and *Blood Mobility Fraction (BMF)* across cardiac cycles. Distinct preliminary flow patterns were observed between sinus rhythm and atrial fibrillation. Outputs are exportable for AI analysis. Conclusions: This approach demonstrates preliminary feasibility for simple, broadly applicable intracardiac flow assessment and introduces TI and BMF as promising flow‑based biomarkers for future prognostic use.

Abstract: Objective: This study aims to investigate how overlapping developmental transcription factors and signaling pathways between small intestinal neuroendocrine cells and hepatocytes govern liver-specific metastasis in carcinoid tumors, and to assess the clinical implications of these shared cell-type specific programs for early detection, risk-adapted surveillance, and targeted therapeutic strategies aimed at improving patient outcomes. Background: Small intestinal carcinoid tumors preferentially metastasize to the liver, driving morbidity and mortality, yet traditional explanations like vascular patterns inadequately account for this specificity. Overlapping transcription factors and signaling pathways between SI-NECs and hepatocytes such as FOXA, GATA, SOX, NOTCH, Wnt/β-catenin, Hippo, FGF/HGF, TGF-β, and Dll1/4, may confer “liver-compatible” programs that facilitate adhesion, survival, and proliferation. Understanding these overlaps could enable early detection, targeted surveillance, and therapeutics, redefining organ-specific metastasis mechanisms. Methods: Databases, including PubMed, MEDLINE, Scopus, and Web of Science were searched through March 2026, to investigate overlapping genes/tfs/signaling pathways (FOXA1/2, GATA4/6, SOX4/9, HES1/NOTCH, Wnt/ beta catenin, Hippo/YAP-TAZ, FGF/HGF, TGF-β, and Dll1/4) between SI-NECs and hepatocytes that may have role in governing liver tropism for metastasis of Carcinoid Tumor. Studies meeting the criteria outlined in the methods section were systematically reviewed to address the research question. This study adheres to the relevant PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Results: Key findings indicate that small intestinal carcinoid tumors exhibit a high propensity for liver metastasis due to overlapping developmental transcription factors and signaling pathways with hepatocytes, including FOXA1/2, GATA4/6, SOX4/9, HES1/NOTCH, Wnt/ beta catenin, Hippo/YAP-TAZ, FGF/HGF, TGF-β, and Dll1/4. These shared programs preserve progenitor-like plasticity, enable responsiveness to hepatic microenvironmental cues, and facilitate adhesion, survival, proliferation, and extracellular matrix remodeling. This compatibility due to overlap explains organ-specific tropism and highlights opportunities for early metastasis detection, risk-adapted surveillance, and targeted therapeutics, providing a framework for understanding liver-directed metastasis in carcinoid tumor patients. Conclusion: Small intestinal carcinoid tumors preferentially metastasize to the liver due to overlapping transcriptional and signaling programs shared with hepatocytes. Factors such as FOXA1/2, GATA4/6, SOX4/9, HES1/NOTCH, Wnt/beta catenin, Hippo/YAP-TAZ, FGF/HGF, TGF-β, and Dll1/4 enable tumor cells to maintain progenitor-like plasticity, respond to hepatic cues, and integrate into the liver microenvironment. The high propensity of small intestinal carcinoid tumors to metastasize to the liver can be explained by overlaps in transcription factors, signaling pathways, and progenitor-like features between SI-NECs and hepatocytes. This creates a microenvironment and functional compatibility, making the liver a preferential metastatic site.

Abstract: Most of the technological processes in modern industrial production are realized with the help of mechanical energy, which is most conveniently obtained by means of an electric drive. In the metallurgical, machine-tool and other industries, it is advisable to use a multi-motor asynchronous electric drive for general industrial mechanisms such as overhead cranes (trolley movement mechanism), conveyors, rolling mills, taking into account technological requirements and operating modes. This requires the use of more sophisticated control methods for electromechanical systems, since two or more electric motors must work in concert for a single load. This, in turn, entails the use of a new element base, power and control, which makes it possible to implement these technological work cycles. The constant development of technology places increased demands on the electric drive regarding the accuracy of movement, both in statics and dynamics, speed and reliability. At the present stage, all these requirements can be achieved using specialized high-speed microprocessors as the basis of a control system for a twin-motor asynchronous electric drive, which opens up wide opportunities for creating technically advanced adjustable drives. At the same time, due to the intensive development of electronics and semiconductor technology, it is necessary to reduce the cost of electric drive control systems.

Abstract: The traditional assumption that formal journalism education is a prerequisite for practicing journalism has increasingly been challenged in the contemporary media environment. Historically, many influential journalists entered the profession without formal academic training in journalism, relying instead on diverse intellectual backgrounds, experiential learning, and multidisciplinary knowledge. This study explores the argument that journalism is fundamentally a knowledge-driven profession rather than a degree-dependent one. Drawing upon historical analysis, professional case studies, and theoretical insights from communication studies, knowledge sociology, and media professionalization theory, the article examines whether journalism education is essential for journalistic practice or whether multidimensional knowledge—including political, economic, technological, cultural, and ethical literacy—is the more critical requirement.The article situates journalism within broader debates about professionalization, epistemic authority, and the transformation of media institutions in the digital era. It argues that journalism education contributes valuable methodological and ethical frameworks; however, the profession itself historically evolved from individuals possessing wide-ranging knowledge rather than narrow vocational training. In the digital age, journalists increasingly operate at the intersection of multiple disciplines such as data science, international relations, sociology, environmental studies, and digital technologies. Consequently, multidimensional knowledge and intellectual curiosity may provide stronger foundations for journalistic excellence than formal training alone.Using qualitative historical review and comparative analysis of global media systems, the study evaluates the career trajectories of prominent journalists and analyzes how interdisciplinary knowledge shapes journalistic credibility, investigative capacity, and interpretive reporting. The findings suggest that journalism education should not be viewed as a gatekeeping requirement but rather as one of several pathways into the profession. The article proposes a reconceptualization of journalism education that prioritizes interdisciplinary knowledge acquisition, critical thinking, and epistemic diversity rather than purely technical training.This research contributes to ongoing debates on journalism professionalization, media education reform, and the evolving epistemology of news production. The study concludes that the future of journalism lies not in strict academic credentialism but in the cultivation of multidimensional knowledge ecosystems capable of addressing complex global realities.