This paper explores the multifaceted impact of biofilms, bacterial communities enveloped in extracellular polymeric substance (EPS). Biofilms play a dual role, acting as environmental champions and health threats. They interact with heavy metals, either causing pollution or aiding environmental remediation. Beneficial biofilms generate electricity and repair concrete cracks, offering sustainable solutions. Conversely, they contribute to infections, posing health risks. The study emphasizes the need for in-depth research, utilizing bibliographic methods to analyze global biofilm research. By identifying keywords, core countries, and pivotal organizations, the paper informs future investigations, offering insights into biofilm research evolution and practical applications.

The fifth Industrial revolution (I5.0) prioritizes resilience and sustainability, integrating cognitive cyber-physical systems and advanced technologies to enhance machining processes. Numerous research studies have been conducted to optimize machining operations by identifying and reducing the sources of uncertainty and estimating the optimal cutting parameters. Virtual modeling and Tool Condition Monitoring (TCM) methodologies have been developed to assess the cutting states during machining processes. With a precise estimation of cutting states, the safety margin necessary to deal with the uncertainties can be reduced, resulting in improved process productivity. This paper reviews the recent advances in high-performance machining systems with a focus on the cyber-physical models developed for the cutting operation of difficult-to-cut materials using cemented carbide tools. An overview of the literature and background on the advances in the offline and online process optimization approaches have been presented. Process optimization objectives such as tool life utilization, dynamic stability, enhanced productivity, improved machined part quality, and reduced energy consumption and carbon emissions are independently investigated for the offline and online optimization methods. Addressing the critical objectives and constraints prevalent in industrial applications, the paper explores the challenges and opportunities inherent in developing a robust cyber-physical optimization system

FacioScapuloHumeral Dystrophy (FSHD) is one of the most prevalent inherited muscle disorders, and is linked to the inappropriate expression of the DUX4 transcription factor in adult muscles. The deregulated molecular network causing FSHD skeletal muscle dysfunction and pathology is still not well understood. It has been shown that the hypoxia response factor HIF1α is critically disturbed in FSHD and has a major role in DUX4 induced cell death. In this study, we further explore the relationship between DUX4 and HIF1α. We found that the DUX4 and HIF1α link differed according to the stage of myogenic differentiation and was conserved between human and mouse muscle. Furthermore, we found that HIF1α knock-down in a mouse model of DUX4 local expression exacerbated DUX4-mediated muscle fibrosis. Our data indicate that the suggested role of HIF1α in DUX4 toxicity is complex and that targeting HIF1α might be challenging in the context of FSHD therapeutic approaches.

Dynamic crossflow filtration (DCF) is the state-of-the-art technology for solid-liquid separation from viscous and sensitive feed streams in the food and biopharma industry. Up to now, the potential of industrial processes is often not fully exploited because fixed recipes are usually applied to run the processes. Therefore, a digital twin has been developed to optimize an industrial brownfield DCF plant. The core of the digital twin is a mechanistic-empirical process model combining fundamental filtration laws with process expert knowledge. The effect of variation of selected process and model parameters on plant productivity has been assessed using a model-based design-of-experiments approach and a regression metamodel has been trained with the data. A cyclic program that bidirectionally communicates with the DCF asset serves as frame of the digital twin. It monitors the process dynamics membrane torque and transmembrane pressure and feeds back the optimum permeate flow rate setpoint to the physical asset in almost real-time during process runs. The presented digital twin framework is a simple example how an industrial established process can be controlled by a hybrid model-based algorithm. With a digital process dynamics model at hand, the presented metamodel optimization approach can be easily transferred to other (bio)chemical processes.

The removal of sulfur from fossil fuels is one of the most important processes in modern refineries. It is accomplished via hydrodesulfurization (HDS) of the sulfur organic compounds in presence of heterogeneous catalysts. In the current work, heterogeneous catalysts containing cobalt and mo-lybdenum supported on mesoporous materials type SBA-15 and AlSBA-15 were synthesized for application in the HDS reactions of thiophene in n-heptane stream. The mesoporous materials were synthesized by hydrothermal method starting from TEOS, pseudobohemite, hydrochloric ac-id and water. Pluronic P123 was used as template. The best calcination conditions for removal of the organic template were optimized by thermogravimetry analysis (TG/DTG). The calcined SBA-15 and AlSBA-15 supports were submitted to co-impregnation with solutions of cobalt nitrate and ammonium heptamolybdate, aiming the production of 15% in mass of metal loading with atomic ratio of [Co/(Co+Mo)]=0.45. The obtained materials were dried and calcined for obtaining the mesoporous catalysts in the form of CoMo/SBA-15 and CoMo/AlSBA-15. The catalysts were char-acterized by XRD, TG/DTG, SEM and nitrogen adsorption. From XRD analysis, it was verified that after decomposition of the cobalt and molybdenun salts, were formed MoO3, Co3O4 and Co-MoO4 oxides on the supports, being attributed to these chemical species the activity for the HDS reactions. The activity of the obtained catalysts was evaluated in a continuously flowing tubular fixed-bed microreactor coupled on-line to a gas chromatograph, using n-heptane stream contain-ing 12070 ppm of thiophene (ca. 5100 ppm of sulfur) as a model compound. From the catalytic tests it was verified that the synthesized catalysts presented good activity for the reaction, and the main obtained products were cis- and trans-2-butene, 1-butene, n-butane and low amounts of iso-butane. The presence of 1,3-butadiene and tetrahydrothiophene (THT) were not detected. A mechanism of the primary and secondary reactions and subsequent formation of the olefins and paraffins, in the CoMo/SBA-15 and CoMo/AlSBA-15 mesoporous catalysts were proposed, con-sidering steps of desulfurization, hydrogenation, dehydrogenation, THT decyclization and isomerization.

Due to the ongoing global warming on the Earth, permafrost degradation has been extensively taking place, which poses a substantial threat to civil and industrial facilities and infrastructure elements, as well as to the utilization of natural resources in the Arctic and high-latitude regions. In order to prevent the negative consequences of permafrost thawing under the foundations of constructions, various geophysical techniques for monitoring permafrost have been proposed and applied so far: temperature, electrical, seismic and many others. At the same time, non-stationary electromagnetic methods seem to have significant potential and a number of important practical advantages. We propose a cross-borehole exploration system for the highest localization of target objects in the cryolithozone. A novel mathematical apparatus for three-dimensional modeling of transient electromagnetic (TEM) signals by the vector finite element method has been developed. The original combination of the latter, the Sumudu integral transform and artificial neural networks makes it possible to examine spatially heterogeneous objects of the cryolithozone with a high contrast of geoelectric parameters, significantly reducing computational costs. We have studied the sensitivity of the TEM signals to the boundary between thawed and frozen rocks depending on the inter-borehole distance and spatial orientations of the transmitters and receivers. Numerical simulation results of the TEM monitoring of industrial facilities located on permafrost are considered. The formation of a talik has been shown to significantly manifest itself in the measured electromagnetic responses, which enables timely prevention of industrial disasters and environmental catastrophes.

This study analyzes the relationship between economic policy uncertainty (hereinafter EPU) and corporate value, and verifies the differential effects of EPU on corporate value according to corporate social responsibility (hereinafter CSR) activities. The study period was from 2010 to 2020, and the EPU indexes measured by Baker et al. (2016)'s method and Hexun's CSR scores for companies listed on the Chinese stock market were used. Hexun is one of the three major evaluation agencies in China, and the CSR scores evaluated by this agency have been widely used in previous studies as a representative indicator of Chinese companies' CSR performance. The results of this study are as follows. First, EPU and corporate value were found to have a negative (-) relationship. Second, active CSR activities relieved the negative (-) relationship between EPU and corporate value. Finally, companies were divided into groups according to CSR activity scores to analyze the relationship and according to the result, the negative (-) relationship between EPU and corporate value was greater in the groups with low CSR activity scores than in the groups with high CSR activity scores. A lag model was applied to control endogeneity, and the results were consistent with the main results above. Previous studies have mainly focused on microscopic factors to investigate factors affecting corporate value. This study focused on macroeconomic policies and paid attention to the effects of changes in the macroenvironment caused by economic policy uncertainty on corporate value. In addition, this study is meaningful in that it expanded previous studies related to CSR activities by confirming that active CSR activities can be an advantageous tool for overcoming EPU.

The flow properties of pellets or granules are crucial for further processing the drug dosage forms. Optimal compression or filling the multiparticulate dosage forms into capsules is influenced by forces between discrete particles, which could be partially characterized by flow properties. Several techniques were developed for the examination of flowability, including static and dynamic methods applying empirical studies and the up-to-date chaos theory; however newest methods seem only to be powerful with the supplement of empirical principles. Our experiments try to refine both the technique of analysis and the methods by finding new, alternative ways. Our approach to the flowability measurements was to set up a dynamic time-dependent model which combines empirical observations and the chaos theory on a geometrical basis, thus find new aspects regarding flow properties of pellets and granules that could be relevant for drug developers.

Background: Neuromuscular electrical stimulation (NMES) has beneficial effects on physical functions in Multiple Sclerosis (MS) patients. However, the neurophysiological mechanisms underlying these functional improvements are still unclear. This study aims at comparing acute responses in spinal excitability, as measured by soleus Hoffmann reflex (H-reflex), between MS patients and healthy individuals, following three experimental conditions involving the ankle planta flexor muscles: 1) passive NMES (pNMES); 2) NMES superimposed to isometric voluntary contraction (NMES+); and 3) isometric voluntary contraction (ISO). Methods: 20 MS patients (MSp) and 20 healthy individuals as control group (CG) took part in a single experimental session. During each condition, participants performed 15 repetitions of 6 seconds at 20% of maximal voluntary isometric contraction, with 6 seconds of recovery between repetitions. Before and after each condition, H-reflex amplitudes were recorded. Results: In MSp, H-reflex amplitude did not change following any experimental condition (ISO: p = 0.506; pNMES: p = 0.068; NMES+: p = 0.126). In CG, H-reflex amplitude significantly increased following NMES+ (p = 0.01), decreased after pNMES (p = 0.000) and was unaltered following ISO (p = 0.829). Conclusion: the different H-reflex responses between MS and CG might reflect a reduced ability of MS patients in modulating spinal excitability.

Background: Delivery of quality family planning services depends on availability of skilled health care providers, which is often a challenge in Low- and middle-income countries. This study evaluates the effects of a targeted training program on family planning services delivered by the Lady Health Workers (LHWs) in six districts of Punjab, Pakistan. The primary goal was to enhance the quality and accessibility of family planning services, recognizing the pivotal role of LHWs in community health. Methods: Using a robust panel data difference-in-differences (DiD) approach, we analyzed the electronic medical records (EMR) of 1,410 LHWs over a nine-month period. This timeframe in-cluded both pre-training (July to December 2022) and post-training (April to June 2023) phases. Our assessment focused on the impact of training on five outcome variables: the number of follow-up clients, the number of Intrauterine Contraceptive Device (IUCD) clients, the number of condom clients, the number of modern method clients, and the number of injection clients. We also con-sidered control variables such as LHW age, LHW education, the number of eligible couples in each LHW's catchment area, and a categorical variable for the districts. Results: The positive and statistically significant (p<0.05) coefficients across various service cat-egories – Follow Up Clients [Coeff: 1.00, CI: (0.30 - 1.70)], IUCD Clients [Coeff: 0.23, CI: (-0.01 - 0.46)], Condom Clients [Coeff: 1.41, CI: (0.97 – 1.86)], Modern Method Clients [Coeff: 1.82, CI: (0.96 – 2.68)], and Injection Clients [Coeff: 0.32, CI: (0.14 – 0.50)]. These findings indicate enhanced productivity among LHWs who have received training, with results significant at the 95% con-fidence interval (CI). Conclusion: The study highlights the effectiveness of targeted training programs in boosting family planning services at the community level and offers insightful implications for policy-makers and health practitioners. While focused on six districts in Punjab, these promising results emphasize the need for ongoing training and support for frontline health workers to bolster family planning initiatives.

Immune checkpoint receptors play a crucial role in steering tumor progression, prompting a focused investigation into the role of TIM3 in breast cancer. Analysis of TCGA BRCA data unveiled diverse correlations between TIM-3 expression and immune cell infiltration across subtypes. In our in-house cohort studied through IHC, significant changes in TIM3 expression with tumor grades were observed. Higher TIM3 expression correlated with increased disease-free survival in pan breast cancer, marking the first revelation of TIM3's positive role in pan BC prognosis. The study indicates that alluring TIM3 response, rather than suppression, may enhance breast cancer prognosis.

Acute kidney infection (AKI) occurred by tubular necrosis and glomerular dysfunction caused by many factors. SARS CoV-2 infection identified to cause fatal AKI. This paper aims to review the effect of covid-19 infection on the failure of the kidney and its mechanism. It identified that the SARS-CoV-2 received by the targeted cell by Angiotensin-converting enzyme 2 (ACE2). After the virus received by the target cells, it induces the production of pro-inflammatory cytokines such as tumor necrosis factor (TNF), interleukin (IL)-1, and interferons (IFN) by immune cells and causes cytokine storm. The pro-inflammatory cytokines are again responsible to induce the secretion of cyclooxygenase‑2 (COX‑2), which causes inflammation and pain as well it stimulates the iNOS enzyme to produce NO which allows the vasodilation of renal arteries. The increased production of NO by iNO enhanced the vasodilation of arteries, and allows the adhesion of neutrophils to the artery, and causes damage to glomerulus and tubules. Hence, the most likely sustainable intervention could be the application of angiotensin-converting enzyme 2 (ACE2) inhibition by the receptors of the target cells in these vital organs to reduce sever destruction during treatment at the early stage of infection.

This paper aims to study the performance of solar collectors with various sizes under different weather conditions of different Japanese cities, i.e. Kofu city, Nagoya city and Yamagata city. The heat generated from the solar collector was used to conduct a biogas dry reforming reactor in order to produce H2 to feed a solid oxide fuel cell (SOFC). This study has revealed that the output temperature of solar collector, Tfb in April and July was higher than that in January and October irrespective of city. The optimum length of absorber (dx) of the collector was 4 m irrespective of city. It was clarified that Tfb in Yamagata city in January and October, i.e. winter and autumn is lower than that in Kofu city and Nagoya city especially, which is influenced by the tendency of a solar intensity (I) strongly, not velocity of surrounding air (ua). On the other hand, Tfb is almost the same in April and July, i.e. spring and summer, irrespective of city. The amount of produced H2 from the biogas dry reforming reactor and the power generated by SOFC using H2 in spring and summer were higher compared to the other seasons irrespective of city. This study has revealed that the highest available households number per month was 4.7 according to the investigation in this study.

Stem cells can be used to treat diabetic mellitus and complications. ω3-docosahexaenoic acid (DHA) derived lipid mediators are inflammation-resolving and protective. This study found novel DHA-derived 7S,14R-dihydroxy-4Z,8E,10Z,12E,16Z,19Z-docosahexaenoic acid (7S,14R-diHDHA), a maresin-1 stereoisomer biosynthesized by leukocytes and related enzymes. Moreover, 7S,14R-diHDHA can enhance mesenchymal stem cell (MSC) functions in the amelioration of diabetic mellitus and retinal pericyte loss in diabetic db/db mice. MSCs treated with 7S,14R-diHDHA were delivered into db/db mice i.v. every 5 days for 35 days. Blood glucose levels in diabetic mice were lowered by 7S,14R-diHDHA-treated MSCs compared to control and untreated MSC groups, accompanied by improved glucose tolerance and higher blood insulin levels. 7S,14R-diHDHA-treated MSCs increased insulin+ β-cell ratio and decreased glucogan+ α-cell ratio in islets, as well as reduced macrophages in pancreas. 7S,14R-diHDHA induced MSC functions in promoting MIN6 β-cell viability and insulin secretion. 7S,14R-diHDHA induced MSC paracrine functions by increasing the generation of hepatocyte growth factor and vascular endothelial growth factor. Furthermore, 7S,14R-diHDHA enhanced MSC functions to ameliorate diabetes-caused pericyte loss in diabetic retinopathy by increasing their density in retina in db/db mice. Our findings provide a novel strategy for improving therapy for diabetes and diabetic retinopathy using 7S,14R-diHDHA-primed MSCs.

Electrochemotherapy (ECT) is one of the newest therapeutic strategies employed as medical procedure for skin neoplasms’ treatment, especially for Classic Kaposi’s Sarcoma (CKS). The aim of this study was to demonstrate ECT clinical response and local control of CKS disease. Primary endpoint was to value the worth and efficacy of this local therapy in CKS skin lesions’ treatment. Nineteen CKS patients were enrolled, 14 males and 5 females with median age at diagnosis of 72. Complete response (CR) has been gained in 12 patients after first ECT attempt, meanwhile 3 and 4 out of 19 patients obtained a Partial response (PR), so that they underwent to a second and a third ECT treatment, each other. Clinical response was evaluated during all the time of the follow-up, which ranged between 3 months and 4 years with a median of 18 months. CKS skin lesions control still represents a challenge for surgeons and oncologists. Nevertheless, according to this and other authors’ recent experiences, ECT could be considered the gold standard strategy for early-stage patients, but at the same time it could be considered as a valid option in controlling Kaposi’s Sarcoma locally advanced lesions.

The expansion of copper mining on the hyper-arid pacific slope of southern Peru has precipitated growing concern for scarce water resources in the region. Located in the headwaters of the Torata river, in the department of Moquegua, the Cuajone mine, owned by Southern Copper, provides a unique opportunity, in a little-studied region, to examine the relative impact of the landscape-scale mining on water resources in the region. Principal component analysis and cluster analysis of the water chemistry data from 16 sites, collected over three seasons during 2017 and 2018, show distinct statistical groupings indicating that, above the settlement of Torata, water geochemistry is a function of chemical weathering processes acting upon underlying geological units, and confirming that the Cuajone mine does not significantly affect water quality in the Torata river. Impact mitigation strategies that firstly divert channel flow around the mine and secondly divert mine waste to the Toquepala river and tailings dam at Quebrada Honda, below the Toquepala mine, in the department of Tacna, secure water quality in the Torata river for the foreseeable future. In the greater Moquegua river catchment, our results further suggest that water quality has been more significantly impacted by urban effluents and agricultural runoff than the Cuajone mine. The increase in total dissolved solids in the waters of the lower catchment reflects the cumulative addition of dissolved ions through chemical weathering of the underlying geological units, supplemented by rapid recharge of surface waters contaminated by residues associated with agricultural and urban runoff through the porous alluvial aquifer. Concentrations in some of the major ions exceeded internationally recommended maxima for agricultural use, especially in the coastal region. Occasionally, arsenic and manganese contamination also reached unsafe levels for domestic consumption. In the lower catchment, below the Cuajone mine, data and multivariate analyses point to urban effluents and agricultural run-off rather than weathering of exposed rock units, natural or otherwise, as the main cause of contamination.

Punica granatum L., commonly known as pomegranate, is a typical fruit of Asia, Mediterranean countries, Middle East and USA areas. While in the ancient time pomegranate was considered an ornamental plant, nowadays numerous scientific studies have highlighted its antioxidant and anti-radical activities, up to consider pomegranate as a “superfood”. Pomegranate presents a high content of natural bioactive compounds (NBCs) and its consumption appears to exert numerous healthy beneficial effects, in particular, in several pathological conditions, namely in patients affected by metabolic syndrome, cancer, nephrolithiasis, urinary tract infections and neurodegenerative diseases. Moreover, recent studies pointed out the possible beneficial action of pomegranate on oral health. For these reasons, the utility of pomegranate in internal medicine and in dentistry represents a promising field, as it could permit the development of innovative natural adjuvant therapies, able to empower the standard pharmaceutical therapies.

The Kanchenjunga Conservation Area (KCA) is a high mountain protected area in eastern Nepal undergoing socio-economic and environmental changes that are unprecedented in the region’s history. In the following paper, we discuss recent changes involving new road construction, climate change, adventure tourism, and the wildlife/forest cover/medicinal plant sectors. Our assessments are based on the collective results of past and recent field research, remote sensing analysis, oral histories, and literature reviews. While similar changes are occurring in mountain protected areas (MPA) throughout Nepal, it is suggested that the KCA differs from other regions in that it still retains the option of conducting detailed feasibility, environmental, and impact assessments prior to the implementation of major change-associated projects, particularly the construction of roads. In turn, the KCA might avoid many of the environmental, social, and economic problems experienced elsewhere in Nepal, while enhancing its status, income-generating capacities, and sustainability as a global destination for adventure, nature, and cultural tourism.

Amidst the recent energy crisis, the pivotal role of resource efficiency and renewable energy sources (RES) for sustainable development has become apparent. Transition to sustainability involves decentralized energy solutions empowering local communities to generate, store, and utilize their energy, diminishing reliance on centralized systems and potentially transforming them into power flexibility resources. This is particularly crucial in non-interconnected island systems that primarily rely on imported oil for electricity generation. Such reliance not only implies high production costs but also threatens energy security and adds to the environmental footprint of local economic activities. Addressing the above necessitates, amongst other elements, the adoption of advanced energy management with sophisticated forecasting and demand-side management (DSM) strategies. In response, we introduce a versatile algorithm investigating the impact of DSM at the community scale, designed to maximize the utilization of renewable energy produced from local installations. Integrated as an ancillary module in an advanced energy management platform, the algorithm undergoes testing using datasets collected from end-consumers and a small-scale RES installation on the island of Tilos, Greece. This study not only offers insights for energy stakeholders but also establishes theoretical parameters that can inform subsequent decision-making processes.

Homochirality is an obvious feature of life on Earth. On the other hand, extraterrestrial samples contain largely racemic compounds. The same is true for any common organic synthesis. Therefore, it has been a perplexing puzzle for decades how these racemates could have formed enantiomerically enriched fractions as a basis for the origin of homochiral life forms. Numerous hypotheses have been put forward as to how preferentially homochiral molecules could have formed and accumulated on Earth. In this article, it is shown that homochirality of the abiotic organic pool at the time of formation of the first self-replicating molecules is not necessary and not even probable. It is proposed to abandon the notion of a molecular ensemble and to focus on the level of individual molecules. Although the formation of the first self-replicating, most likely homochiral molecule is a seemingly improbable event, on a closer look, it is almost inevitable that homochiral molecules have formed simply on a statistical basis. In this case, the non-selective leap to homochirality would be one of the first steps in chemical evolution directly out of a racemic “ocean”. Moreover, most studies focus on the chirality of the primordial monomers with respect to an asymmetric carbon atom. However, any polymer with a minimal size that allows folding to a secondary structure, would spontaneously lead to asymmetric higher structures (conformations). Most of the functions of these polymers would be influenced by this inherently asymmetric folding. To summarize, simple and universal mechanisms may have led to homochiral self-replicating systems in the context of chemical evolution. A homochiral monomer pool is deemed unnecessary and probably never existed on primordial Earth.

The therapeutic management of acquired thrombotic thrombocytopenic purpura (aTTP) has recently benefited from the introduction of caplacizumab, an agent directed to inhibition of platelet aggregation. This real-world analysis investigated the epidemiology, the demographic and clinical characteristics of aTTP patients in Italy before and after caplacizumab introduction in 2020. Hospitalized adults with aTTP were included using the administrative databases of healthcare entities covering 17 million residents. Epidemiological estimates of aTTP considered the 3-year period before and after caplacizumab introduction. After stratification by treatment or not with caplacizumab, aTTP patients were characterized for their demographic and clinical features. The annual incidence before and after 2020 was estimated in the range 4.3-5.8 cases/million and 3.6-4.6/million, respectively. From 2018 to 2022, 393 patients with aTTP were included, 42 of them treated with caplacizumab. Caplacizumab-treated patients were aged on average 46.8 years, 31% were males, and showed tendentially better clinical outcomes: no treated patients died at either 1 month or 3 months after caplacizumab treatment initiation, compared to 10.5% (1 month) and 11.1% (3 months) mortality among the untreated. Caplacizumab treatment was associated with a trend towards shorter hospital stays. These findings suggest that caplacizumab advent provided clinical and survival benefits for patients with aTTP.

Several epidemiological studies have demonstrated that particulate matter (PM) in air pollution can be involved in the genesis or aggravation of different cardiovascular, respiratory, perinatal, and cancer diseases. This study assessed the in vitro effects of PM &lt;10 μm in aerodynamic diameter (PM10) on the secretion of cytokines by a human monocytic cell line (THP-1). We compared the chemotactic, pro-inflammatory, and anti-inflammatory cytokines induced by PM10 collected for two years during three different seasons in five different Mexico City locations. MIP-1α, IP-10, MCP-1, TNF-α, and VEGF were the main secretion products after stimulation with 80 μg/mL of PM10 for 24 hours. The THP-1 cells showed a differential response to PM10 obtained in the different sites of Mexico City. The PM10 from the north and the central city areas induced a higher pro-inflammatory cytokine response than those from the south. Seasonal pro-inflammatory cytokine secretion always exceeded the anti-inflammatory one. The rainy season-derived particles caused the lowest pro-inflammatory effects. We concluded that toxicological assessment of airborne particles provides evidence supporting their potential role in chronic exacerbation of local or systemic inflammatory responses that may worsen the evolution of some chronic diseases.

we describe an atypical case of Whipple disease involving exclusively the spinal cord in an adolescent receiving immunosuppressive therapy for systemic lupus erythematosus. The diagnosis was particularly difficult since lupus and Whipple disease can present similar clinical features and the patient’s prolonged contact with sewage was initially not mentioned. A literature review of the clinical, imaging, diagnostic, and therapeutic challenges of Whipple disease is also performed.

Under the extreme shortage of water resources in the Yellow River Basin, it is of great signifi-cance to analyze the spatial distribution relationship between rural settlement and water re-sources for the coordinated development of human and water resources in the Yellow River Ba-sin. However, the water allocation scheme depended on statistical data in the previous work, not on rural settlements in space. Furthermore, previous researches seldom focus on the evaluation of surface water resources accessibility according to the spatial distribution characteristics of ru-ral settlements and water resources, especially, in the Yellow River Basin and using rural set-tlement as unit. Therefore, a quantitative evaluation model of surface water resources accessibil-ity is constructed by using the GIS network analysis method, taking rural settlement as the re-search unit, based on three dimensions of topography, distance, and surface water resources, at the Yellow River basin scale. The results show that: (1) The surface runoff of rural settlement in the Yellow River basin is mostly less than 0.05 km/m2, reaching 99.83%. In other words, the Yel-low River Basin is extremely short of water resources. The surface water resources accessibility is affected by distance, topography, and surface water resources. The evaluation results show that the range of surface water resources accessibility is 0.13~0.88, with an average value of 0.47 and a standard deviation of 0.05. The High surface water resources accessibility value in the Yel-low River Basin is in the east and west, and the low value is mainly distributed in the middle. (2) The range from low to high of surface water resources accessibility in 12 catchments is Sanmen-xia station, Lanzhou station, Shizuishan station, Longmen station, Tongguan station, Toudaoguai station, Xiaolangdi station, Huayuankou station, Lijin station, Gaocun station, Ai Shan station and Tangnaihai station. (3) The value of surface water resources accessibility at the city scale is higher in the east of 10 cities and in the west of 1 city. However, it is lower in the west of 9 cities. And the values of the other cities are at a medium level. The correlation coefficient with primary industry GDP and surface water resources accessibility is 0.271 (N=56, Sig=0.043, in 0.05 level, the correlation is significant), which verifies the rationality of surface water resources accessibility model to some extent.

Diamond-like carbon (DLC) layers are known for their high corrosion and wear resistance, low friction, and high biocompatibility. However, it is often necessary to dope DLC layers with additional chemical elements to strengthen their adhesion to the substrate. Ti-DLC layers (doped with 0.4, 2.1, 3.7, 6.6, 12.8 at.% of Ti) were prepared by dual pulsed laser deposition, and pure DLC, glass, and polystyrene (PS) were used as controls. In vitro cell-material interactions were investigated with an emphasis on cell adhesion, proliferation, and osteogenic differentiation. We observed slightly increasing roughness and contact angle and decreasing surface free energy on Ti-DLC layers with increasing Ti content. Three-week biological experiments were performed using adipose tissue-derived stem cells (ADSCs) and bone marrow mesenchymal stem cells (bmM-SCs) in vitro. The cell proliferation activity was similar or slightly higher on the Ti-doped materials than on glass and PS. Osteogenic cell differentiation on all materials was proved by collagen and osteocalcin production, ALP activity, and Ca deposition. The bmMSCs exhibited greater initial proliferation potential and an earlier onset of osteogenic differentiation than the ADSCs. The ADSCs showed a slightly higher formation of focal adhesions, higher metabolic activity, and Ca deposition with increasing Ti content.

The impact of the crystalline or amorphous structure of a solid on the solubility and pharmacokinetic properties of a drug candidate is always considered by the pharmaceutical industry during the development of a new drug, however, it is not so frequently considered during the early discovery process by organic and medicinal chemists, particularly working at the academia. We want to share, as an example case, the false negative obtained in the biological testing of a solid sample of a tyrosine kinase inhibitor due to an unexpected crystallinity with respect to a solid amorphous batch of the same compound and the experimentation carried out to establish the origin of such inconsistency.

PitNETs, although typically benign, comprise a small percentage of therapy-resistant aggressive, occasionally metastatic tumors, underpinning a need to identify novel therapeutic targets. PitNETs carry few mutations but associate with conditions that promote alternative splicing as an oncogenic alternative and express the TrkA neurotrophin receptor, which exhibits oncogenic alternative TrkAIII splicing in other tumors. Alternative TrkAIII splicing was assessed by RT-PCR in 53 PitNETs and compared to HIF1a, HIF2a, SF3B1, SRSF2, U2AF1 and JCPyV large T antigen mRNA expression, unconventional Xbp1 splicing, SF3B1 mutation, and TrkA isoform(s) immunoreactivity by confocal immunofluorescence (IF). Alternative TrkAIII mRNA splicing was detected in all invasive PitNET phenotypes, was significantly elevated in invasive compared to non-invasive PIT1 PitNETs, relatively high in invasive and non-invasive SF1 and TPIT PitNETs, and was associated with IF consistent with intracellular TrkAIII activation but not with hotspot SF3B1 mutations, altered SF3B1, SRSF2 and U2AF1 splice factor mRNA expression, JCPyV large T antigen expression or unconventional Xbp1 splicing. A potential role for hypoxia in TrkAIII mRNA splicing was supported by significant elevation of HIF2a mRNA expression in invasive PIT1 PitNETs. These data demonstrate that alternative TrkAIII splicing, potentially promoted by hypoxia, occurs frequently in PitNETs and may associate with IF consistent with intracellular TrkAIII activation, supporting a potential role for TrkAIII in PitNET pathogenesis and progression, identifying TrkAIII as a novel potential target in refractory PitNETs.

Existing studies often lack a systematic solution for Unmanned Aerial Vehicles (UAV) inspection system, which hinders their widespread application in crack detection. To enhance its practicality, this study proposes a formal and systematic framework for UAV inspection systems, specifically designed for automatic crack detection and pavement distress evaluation. The framework integrates UAV data acquisition, deep learning based crack identification, and road damage assessment in a comprehensive and orderly manner. Firstly, the flight control strategy is presented, and road crack data is collected using the DJI Mini 2 UAV imagery, establishing a high-quality UAV crack image datasets with ground truth information. Secondly, a validation and comparison study is conducted to enhance the automatic crack detection capability and provide an appropriate deployment scheme for UAV inspection systems. This study develops automatic crack detection models based on mainstream deep learning algorithms(namely, Faster-RCNN, YOLOv5s, YOLOv7-tiny, and YOLOv8s) in urban road scenarios. The results demonstrate that the Faster-RCNN algorithm achieves the highest accuracy and is suitable for online data collection of UAV and offline inspection at work stations. Meanwhile, the YOLO models, while slightly lower in accuracy, are the fastest algorithm and are suitable for lightweight deployment of UAV with online collection and real-time inspection. Quantitative measurement methods for road cracks are presented to assess road damage, which will enhance the application of UAV inspection systems and provide factual evidence for maintenance decisions made by road authorities.

We construct hypergraphs to analyze functional brain connectivity, leveraging event-related coherence in magnetoencephalography (MEG) data during the visual perception of a flickering image. Principal network characteristics are computed for delta, theta, alpha, beta, and gamma frequency ranges. Employing a coherence measure, a statistical estimate of correlation between signal pairs across frequencies, we generate edge time series, depicting how an edge evolves over time. This forms the basis for constructing an edge-to-edge functional connectivity network. Emphasizing hyperedges as connected components in an absolute-valued functional connectivity network, we focus on exploring these hyperedges in the context of individual variability. Our coherence-based hypergraph construction specifically addresses functional connectivity among four brain lobes: frontal, parietal, temporal, and occipital. This approach enables a nuanced exploration of individual differences within diverse frequency bands, providing insights into the dynamical nature of brain connectivity during visual perception tasks. The results furnish compelling evidence supporting the hypothesis of cortico-cortical interactions occurring across varying scales. The derived hypergraph illustrates robust activation patterns in specific brain regions, indicative of their engagement across diverse cognitive contexts and different frequency bands. Our findings suggest potential integration or multifunctionality within the examined lobes, contributing valuable perspectives to our understanding of brain dynamics during visual perception.

Articular cartilage healing and repair is one of the biggest clinical challenges in trauma and orthopaedic medicine, leading to high economic loss due to athletic impairment in sport horses. Multipotent Mesenchymal stem/stromal cells are part of novel therapeutic arsenal aimed at tissue regeneration and restoring organ function. These cells release biomolecules and factors in the culture media, producing the so called conditioned medium, which have a pro-regenerative effect through paracrine mechanisms. Considering this, a therapeutic product combining equine synovial membrane derived Mesenchymal stem/stromal cells and equine umbilical cord stroma-derived Mesenchymal stem/stromal cells conditioned medium was employed. In this work the treatment of two articular defects, in the first phalanx and third metacarpus of the left front limb of a five-year-old horse, is described. Following surgical debridement of the lesions, the treatment comprised two intra-articular administrations of the above-mentioned therapeutic combination, 15 days apart. This was followed by a thorough rehabilitation program. A second-round treatment was performed 6 months later. Diagnostic imaging demonstrated significant improvement of the articular defects. The clinical outcome allowed a full return to the athletic performance demonstrating the safety and potential advantages of this approach when compared with other therapeutic options.

There are different ways to analyse energy absorbance (EA) in the human auditory system. In previous research, we developed a complete finite element model (FEM) of the human auditory system. In this mentioned work, the external auditory canal (EAC), middle ear, and inner ear (spiral cochlea, vestibule, and semi-circular canals) were modelled based on human temporal bone histological sections. Multiple acoustic, structure and fluid-coupled analyses were conducted using the FEM to perform harmonic analyses in the 0.1–10 kHz range. Once the FEM had been validated with published experimental data, the FEM numerical results were used to calculate the EA or energy reflected (ER) by the tympanic membrane. This EA was also measured in clinical audiology tests which were used as a diagnostic parameter. A mathematical approach was developed to calculate the EA and ER, with numerical and experimental results showing adequate correlation up to 1 kHz. Another published FEM had adapted its boundary conditions to replicate experimental results. Here, we recalculated those numerical results by applying the natural boundary conditions of human hearing and found that the results almost totally agreed with our FEM. This boundary problem is frequent and problematic in experimental hearing test protocols: the more invasive they are, the more the results are affected. One of the main objectives of using FEMs is to explore how the experimental test conditions influence the results. Further work will still be required to uncover the relationship between the middle ear structure and EA to clarify how to best use FEMs. Moreover, the FEM boundary conditions must be more representative in future work to ensure their adequate interpretation.

Background: Early detection of atrial fibrillation (AF) is essential to prevent stroke and other cardiac and embolic complications. We compared the diagnostic properties for AF detection of the percentage of successive RR interval differences greater than or equal to 30 ms or 3.25% of the previous RR interval (pRR30 and pRR3.25%, respectively), and asymmetric entropy descriptors of RR intervals. Previously, both pRR30 and pRR3.25% outperformed many other heart rate variability (HRV) parameters in distinguishing AF from sinus rhythm (SR) in 60-second electrocardiograms (ECGs). Methods: The 60-s segments with RR intervals were extracted from the publicly available Physionet Long-Term Atrial Fibrillation Database (84 recording, 24-hour Holter ECG). There were 31753 60-s segments of AF and 32073 60-s segments of SR. The diagnostic properties of all parameters were analysed with the receiver operator curve analysis, confusion matrix and logistic regression. The best model with pRR30, pRR3.25% and total entropic features (H) had the largest area under the curve (AUC) – 0.98 compared to 0.959 for pRR30 - and 0.972 for pRR3.25%. However, the differences in AUC between pRR30, pRR3.25% alone and the combined model were negligible from a practical point of view. Moreover, combining pRR30, pRR3.25% with H significantly increased the number of false-negative cases by more than threefold. Conclusions: Asymmetric entropy has some potential in differentiating AF from SR in the 60-s RR interval time series, but the addition of these parameters does not seem to make a relevant difference compared to pRR30 and especially pRR3.25%.

Secondary acute myeloid leukemia (sAML) is a heterogeneous malignant hematopoietic disease that arises either from an antecedent hematologic disorder (AHD) including myelodysplastic syndromes (MDS), myeloproliferative neoplasms (MPN), aplastic anemia (AA), or as a result of exposure to genotoxic chemotherapeutic agents or radiotherapy (therapy related AML, tAML). sAML is diagnosed when the number of blasts is ≥20% in the bone marrow or peripheral blood, and it is characterized by poor prognosis, resistance to therapy and low overall survival rate. With the recent advances in next generation sequencing technologies, our understanding of the molecular events associated with sAML evolution has significantly increased and opened new perspectives for the development of novel therapies. The genetic aberrations that are associated with sAML affect genes involved in processes such as splicing, chromatin modification and genome integrity. Moreover, non-coding RNAs’ emerged as an important contributing factor to leukemogenesis. For decades, the standard treatment for secondary AML has been the 7 + 3 regimen of cytarabine and daunorubicin which prolongs survival for several months, but modifications in either dosage or delivery has significantly extended that time. Apart from traditional chemotherapy, hematopoietic stem cell transplantation, CAR-T cell therapy and small molecule inhibitors have also emerged to treat sAML.

Host immunological pathways have been proposed including TH1, TH2, TH3, TH9, TH17, TH22, TH1-like, and THαβ immune reactions. Besides TH2 and TH9 immune responses which are against multicellular parasites, host immunological pathways against viruses, intracellular micro-organisms (bacteria, protozoa, and fungi), and extracellular micro-organisms can use programmed cell death pathways to trigger immune reactions or to execute effective strategies to eliminate these pathogens. These programmed cell deaths include apoptosis, autophagic death, pyroptosis, ferroptosis, necroptosis, and NETosis. Apoptosis is related to host anti-virus eradicable THαβ immunity. Autophagic death is related to host anti-virus tolerable TH3 immunity. Pyroptosis is related to host anti-intracellular micro-organism eradicable TH1 immunity. Ferroptosis is related to host anti-intracellular micro-organism tolerable TH1-like immunity. Necroptosis is related to host anti-extracellular micro-organism eradicable TH22 immunity. NETosis is related to host anti-extracellular micro-organism tolerable TH17 immunity.

This study aimed to identify changes in visitor behavior and visitor interest in healing forests before and after the COVID-19 pandemic. The study used text mining analysis techniques to identify changes in visitation behavior over time, divided into three periods: pre-COVID-19 (January 1 to December 31, 2019), during the COVID-19 pandemic (November 1, 2020 to October 31, 2022), and post-COVID-19 (November 1, 2022 to October 31, 2023 ). After the COVID-19 outbreak, healing forest use behavior did not regress to pre-COVID-19 levels. Activity-based keywords such as "hiking," "trekking," and "walking" stood out as the main drivers of this change in behavior. Therefore, related authorities must examine the scalability of the functions, services, and programs of healing forests from a general healing space to a space for leisure and tourism. These findings will contribute to the development of future marketing strategies and programs for healing forests.

The microbiota in the oral cavity has a strict connection to its host. Its unbalance may determine oral diseases and can also have an impact on the systemic health. Probiotic strains may help in the restoration of a balanced condition. For this purpose, we screened the antibacterial and antiadhesive activities of many viable probiotic strains (Lactobacillus acidophilus PBS066, Lactobacillus crispatus LCR030, Lactobacillus gasseri LG050, Lactiplantibacillus plantarum PBS067, Limosilactobacillus reuteri PBS072, Lacticaseibacillus rhamnosus LRH020, Bifidobacterium animalis subsp. lactis BL050, Lacticaseibacillus paracasei LPC 1101, L. paracasei LPC 1082, and L. paracasei LPC 1114) against two main oral pathogens, Streptococcus mutans and Aggregatibacter actinomycetemcomitans, involved in dental caries and periodontal disease development and progression. Our results, obtained through agar overlay assay, plate count method, and scanning electron microscope imaging, indicate that the tested probiotics prevent the growth and adhesion of oral pathogens in a strain-specific manner, improving oral health. L. plantarum PBS067, L. rhamnosus LRH020, L. paracasei LPC 1101, L. paracasei LPC 1082, and L. paracasei LPC 1114 performed in a significant way against both pathogens in all the tests used. They can be considered as an effective adjuvant to guarantee oral and systemic well-being.

The microglia, displaying diverse phenotypes, play a significant regulatory role in the development, progression, and prognosis of Parkinson's disease. Research has established that glycolytic reprogramming serves as a critical regulator of inflammation initiation in pro-inflammatory macrophages. Furthermore, the modulation of glycolytic reprogramming has the potential to reverse the polarized state of these macrophages. Previous studies have shown that levetistilide A (LA), a phthalide component derived from Angelica sinensis, possesses a range of pharmacological effects, including anti-inflammatory, antioxidant, and neuroprotective properties. In our study, we have examined the impact of LA on inflammatory cytokines and glucose metabolism in microglia induced by lipopolysaccharide (LPS). Furthermore, we explored the effects of LA on the AMPK/mTOR pathway and assessed its neuroprotective potential both in vitro and in vivo. The findings revealed that LA notably diminished the expression of M1 pro-inflammatory factors induced by LPS in microglia, while leaving M2 anti-inflammatory factor expression unaltered. Additionally, it reduced ROS production and suppressed IκB-α phosphorylation levels as well as NF-κB p65 nuclear translocation. Notably, LA exhibited the ability to reverse microglial glucose metabolism reprogramming and modulate the phosphorylation levels of AMPK/mTOR. In vivo experiments further corroborated these findings, demonstrating that LA mitigated the death of TH-positive dopaminergic neurons and reduced microglia activation in the ventral SNpc brain region of the midbrain and the striatum. In summary, LA exhibited neuroprotective benefits by modulating the polarization state of microglia and altering glucose metabolism, highlighting its therapeutic potential.

The possibility of using Si-based anodes in lithium-ion batteries is actively investigated due to the increased lithium capacity of silicon. The paper reports the preparation of submicron silicon fibers on glassy carbon in the KI–KF–KCl–K2SiF6 melt at 720°C. For this purpose, the parameters of silicon electrodeposition in the form of fibers were determined by cyclic voltammetry, and ex-perimental samples of ordered silicon fibers with an average diameter from 0.1 to 0.3 μm were obtained under galvanostatic electrolysis conditions. Using the obtained silicon fibers, anode half-cells of lithium-ion battery was fabricated, and its electrochemical performance under mul-tiple lithiation and delithiation was studied. By means of voltametric studies, it is observed that charging and discharging of the anode based on the obtained silicon fibers occurs at potentials from 0.2 to 0.05 V and from 0.2 to 0.5 V, respectively. A change in discharge capacity from 520 to 200 mAh g-1 during the first 50 charge/discharge cycles at a charge current of 0.1C and a Coulomb ef-ficiency of 98-100% was shown. The possibility of charging silicon-based anode samples at charging currents up to 2C was also noted; the discharge capacity ranged from 25 to 250 mAh g-1.

The integration of Artificial Intelligence (AI) with the Internet of Things (IoT) has propelled technological innovation across various industries. This systematic literature review explores the current state and future trajectories of AI in IoT, with a particular focus on emerging trends in intelligent data analysis and privacy protection. The proliferation of IoT devices, marked by voluminous data generation, has reshaped data processing methods, providing actionable insights for informed decision-making. While previous reviews have offered valuable insights, they often fall short of comprehensively addressing the multifaceted dimensions within the AI-driven IoT landscape. This review aims to bridge this gap by systematically examining existing literature and acknowledging the limitations of past studies. To achieve this aim, the study uses a meticulous approach guided by established methodologies. The chosen methodology ensures the rigor and validity of the review, aligning with PRISMA guidelines for systematic reviews. This systematic literature review serves as a comprehensive guide for researchers, practitioners, and policymakers, offering insights into the current landscape and paving the way for future research directions. The identified trends and challenges provide a valuable resource for navigating the evolving domain of AI in IoT, fostering a balanced, secure, and sustainable advancement in this dynamic field.

This study focuses on predicting traffic speed using the simple Multilayer Perceptron (MLP) model, despite the availability of various models for traffic prediction, with artificial intelligence demonstrating superior predictive capabilities. Emphasizing that the quality of the data holds greater significance than the model itself, the research underscores the challenges posed by data containing significant errors and fluctuations. Unlike relying solely on criteria such as Mean Absolute Deviation (MAD) or coefficient of determination (r2), this study advocates for the use of MAD/range as a more robust metric for prediction accuracy, especially when dealing with data exhibiting substantial order.The study sets the speed limit and traffic value at 0.65 and 0.88, respectively. Notably, both criteria yield identical accuracy results of 13% for MAD/R in predicting speed and 14% for traffic. This parity suggests that the artificial intelligence model performs equally well for both variables, highlighting the importance of considering alternative evaluation metrics in the face of data complexities.

The objective of this study was to investigate the liquefaction resistance of chemically improved sandy soils in a straightforward and accurate manner. Using only the existing experimental databases and artificial intelligence, the goal was to make predictions without conducting physical experiments. Emphasis was placed on the significance of data from 20 loading cycles of cyclic undrained triaxial tests to determine the liquefaction resistance and the contribution of each explanatory variable. Different combinations of explanatory variables were considered. Regarding the predictive model, it was observed that a case with the liquefaction resistance ratio as the dependent variable and other parameters as explanatory variables yielded favorable results. In terms of exploring combinations of explanatory variables, it was found advantageous to include all variables as doing so consistently resulted in a high coefficient of determination. The inclusion of the liquefaction resistance ratio in the training data was found to improve the predictive accuracy. In addition, the results obtained when using a linear model for the prediction suggested the potential to accurately predict the liquefaction resistance using historical data.

This study comprehensively investigates Al2O3's mechanical properties, focusing on fracture toughness, surface energy, Young's modulus, and crack propagation. The density functional theory (DFT) is employed to model the vacancies in Al2O3, providing essential insights into this material’s structural stability and defect formation. The DFT simulations reveal a deep understanding of vacancy-related properties and their impact on mechanical behavior. In conjunction with molecular dynamics (MD) simulations, the fracture toughness and crack propagation in Al2O3 are explored, offering valuable information on material strength and durability. The surface energy of Al2O3 is also assessed using DFT, shedding light on its interactions with the surrounding environment. The combination of DFT and MD simulations provides a robust framework for a comprehensive understanding of Al2O3's mechanical properties, with implications for material science and engineering applications.

Obesity is one of the most prevalent chronic diseases and has become a global epidemic. Obesity leads to a greater risk of breast cancer (BC), metastases, recurrence, and decreased survival. For sustained weight loss, bariatric surgery is effective as a long-term solution. Bariatric surgery is associated with improved outcomes of several cancers including BC, although the mechanisms mediating this protection are unknown. We hypothesized that elevated bile acid pools detected after bariatric surgery may be factors that contribute to improved BC outcomes. Indeed, patients with greater expression of the bile acid receptor FXR displayed improved survival in specific BC subtypes. Patients with tumors that are estrogen receptor negative (ER-) displayed significantly elevated survival with higher FXR (NR1H4) expression compared to lower expression. FXR is a nuclear hormone receptor activated by bile acids. Therefore, we posited that activating FXR using an established FDA-approved agonist would display anticancer effects. Indeed, FXR agonism by the bile acid mimetic known commercially as OCALIVA (“OCA”), or Obeticholic acid (INT-747), significantly reduced BC progression and overall tumor burden in a pre-clinical model. In human and murine BC analyses in vitro, agonism of FXR significantly and dose-dependently inhibited proliferation, migration, and viability. In contrast, synthetic agonism of another common bile acid receptor, the G protein-coupled bile acid receptor (GPBAR1, TGR5) which is mainly activated by secondary bile acids, failed to significantly alter cancer cell dynamics. In conclusion, agonism of FXR by primary bile acid memetic OCA yields potent anti-tumor effects potentially through inhibition of proliferation and migration and reduced cell viability. Findings suggest that FXR is a tumor suppressor gene with high potential for personalized therapeutic strategies for individuals with BC.

Background: Skin substitutes play a crucial role in wound care by actively modulating the wound healing process, promoting angiogenesis, and protecting the integrity of the native extracellular matrix. Consequently, surgeons have increasingly recognized these resources as excellent complements to improve reconstructive outcomes. This review focuses on the author's experience using these biomaterials in complex cases, highlighting the benefits they bring to patient care. Methods: A literature review was conducted to evaluate the regenerative properties of skin substitutes and their applicability in head and neck, upper and lower extremities, and trunk reconstruction. Results: The reviewed literature, along with the authors' experience, supports the adjunct use of skin substitutes in various reconstructive situations. Combining them with skin grafts improves resulting skin quality and may also enhance donor site healing. They have proven effective in addressing chronic venous ulcers, traumatic wounds with limited donor tissues for coverage, extensive burns, diabetic foot ulcers, and oncologic resections in the face and scalp. Furthermore, combining them with autologous tissue shows promising results in achieving stable closure. Conclusions: Incorporating skin substitutes in complex reconstructive scenarios offers multiple benefits. Their regenerative properties and ability to modulate the healing process contribute to enhanced outcomes and reduced overall costs.

Yellow nanorod Mg-MOF-74 was obtained by solvothermal synthesis method. XRD、N2 adsorption-desorption isotherms、SEM and TGA results suggest that the particle size of Mg-MOF-74 reaches 400 nm after the introduction of sodium acetate in the precursor of Mg-MOF-74. Besides, the morphology of Mg-MOF-74 was changed from cauliflower to rod particles. At the same time, the BET specific surface area and pore volume of Mg-MOF-74 were also increased a lot. Then the CO2 dynamic adsorption capacity of Mg-MOF-74 was measured by self-made fix bed under 30 ℃、0.1 bar CO2 partial pressure. The results show that the CO2 adsorption capacity of Mg-MOF-74-N2 reaches 3.67 mmol/g and its CO2 adsorption capacity remains unchanged after 10 times CO2 adsorption-desorption cycles.

This comprehensive review delves into gold market business management, covering historical perspectives, market dynamics, mining models, investment strategies, technology, regulations, global trends, and sustainability. Starting with a historical overview, it traces the gold market's evolution and analyzes supply-demand dynamics, price fluctuations, and geopolitical influences. The article scrutinizes gold mining models, evaluating environmental and social responsibilities, and explores financial management strategies, emphasizing risk and gold's role in portfolios. Examining technology's role, it highlights innovations in exploration, mining, and processing for improved efficiency and sustainability. The regulatory landscape analysis encompasses compliance challenges, environmental regulations, and ethical considerations, emphasizing global impacts. Global market trends are explored, identifying potential opportunities and challenges, offering strategic insights. The review concludes by evaluating sustainability practices, emphasizing environmental conservation, community engagement, and ethical sourcing.

The aberrant glycosylation is a hallmark of cancer progression and chemoresistance. It is also an immune therapeutic target for various cancers. Tunicamycin (TM) is one of the potent nucleo-side antibiotics and an inhibitor of aberrant glycosylation in various cancer cells, including breast cancer, gastric cancer, and pancreatic cancer, parallel with inhibition of cancer cell growth and progression of tumors. Thus, TM can be considered a potent antitumor drug in various cancers and may promote chemosensitivity. Mechanistically, TM impedes the role of the UDP-HexNAc enzyme in the biosynthesis of oligosaccharides, specialized macromolecules instrumental in N-linked glycosylation. Further, like chemotherapies such as doxorubicin (DOX), 5'fluorouracil, etoposide, and Cisplatin, TM induces the unfolded protein response (UPR) by blocking aberrant glycosylation. Despite TM's antitumor effectiveness, its lack of cell-type specific cytotoxicity impedes its anticancer efficacy. Thus, various nanoencapsulation techniques and materials have been considered for use in experiments to reduce TM's cytotoxicity and improve efficacy as a targeted therapy. The current review is a profound audit of the benefits and pitfalls of TM in various cancers, focusing on breast, colon, and pancreatic cancers. Additional progressive studies have also discussed the use of TM in immune checkpoints and other unique pathways. Cytotoxicity and other possibly adverse effects of TM are highlighted based on the data from in vitro and in vivo assays. In addition, the recent advances in nano-based drug delivery systems regarding TM have been emphasized. However, the potential of this nucleoside inhibitor re-quires thorough investigation and research to determine its likeliness as a viable chemotherapeutic.

In drilling small holes with diameters of 1 mm or less, minute clogging and twining of chips or adhesion of the workpiece material can become factors in causing breakages of the drill bit; moreover, it can be difficult to identify the machining state. Acoustic emission (AE) sensing is a nondestructive inspection technique that measures the elastic-stress waves that are generated when a material is deformed and fractured. AE sensing permits highly sensitive measurements to be made without changing the rigidity of the experimental system, unlike force sensing of cutting resistance, etc. In the present study, attempts were made to identify the machining state and tool wear, and to predict abnormalities in small-diameter drilling by using the change in the frequency of AE signal waveforms arising from deformation and fracture. It was shown that it is possible to predict the breakage of the drill bit by detecting the high-frequency AE signals caused by adhesion. In addition, a correlation map of the AE frequency spectrum for identifying the machining state in a drilling operation is suggested.

The present study aimed to characterize the microstructure of a temporary 3D printing resin (Resilab Temp), evaluating the optical properties and mechanical behavior according to different post-processing curing times. For the analysis of the surface microstructure and establishment of the best printing pattern, samples in bar format following ISO 4049 (25 x 10 x 3 mm) were designed in CAD software (Rhinoceros 6.0), printed on the W3D printer (Wilcos), and light-cured in Anycubic Photon at different times (without curing, 16 minutes, 32 minutes, and 1 hour). For the structural characterization, analyses were carried out in FTIR (Fourier Transform Infrared Spectroscopy) and Scanning Electron Microscopy (SEM). The mechanical behavior of the resin was based on flexural strength tests and Knoop microhardness. Color and translucency analysis were performed with a spectrophotometer (VITA Easy Shade Advanced 4.0), which was evaluated following CIELab, using gray, black, and white backgrounds. All analyses were performed immediately after making the samples and repeated after thermal aging with 2 thousand cycles (5-55 °C). The results obtained were statistically analyzed with a significance level of 5%. FT-IR analysis showed about a 46% degree of conversion on the surface and 37% in the center of the resin sample. The flexural strength was higher for the groups polymerized for 32 min and 1h, while the Knoop microhardness did not show a statistical difference between the groups. Color and translucency analysis also did not show statistical differences between groups. According to all the analyses carried out in this study, for the evaluated material, the post-polymerization time of 1 hour can be suggested to improve the mechanical performance of 3D-printed devices.

The architecture, organization and functioning of biocatalytic reaction networks, which are coded in the cell specific genome and which work together in the small space of biological cells, are a fascinating feature of life evolved over more than 3 billion years. The knowledge about the diversity of biocatalytic functions and metabolic pathways sustaining life on our planet is highly important, especially as the currently occurring loss of biodiversity is considered a planetary boundary which is at high risk, and knowledge about the life of current biological organisms should be gained before they become extinct. In addition to the well-known enzymatic reactions involved in biochemical pathways, the enzyme universe offers numerous opportunities for discovering novel functions and pathways. Maintaining thousands of molecules and reactions functioning properly within biological cells, which may be exposed to various kinds of external hazards, environmental stress, enzymatic side reactions or non-enzymatic chemical reactions, is key for keeping cellular life healthy. This review aims at outlining advances in assigning enzyme functions to protein sequences and the discovery of novel biocatalytic functions and pathways.

A facile and environmentally benign method for a single-phase barium titanate synthesis in water vapor medium was studied to reveal the mechanism of phase transformation of the initial simple oxides mixture and estimate the capability of the product to be used as a raw material for low-frequency dielectric ceramics. The composition and structure of the reaction mixture treated in vapor at 130…150 °C as well as 230 °C for various time were investigated by means of XRD, SEM, HRTEM, EDX, and FTIR methods. The kinetics of the occurring phase transformation was described by Johnson-Mehl-Avrami-Erofeev equation. The reaction between the initial oxides was considered as a topochemical process with an apparent activation energy of 74…80 kJ mol^-1. A crucial role in this process belonged to the water vapor medium, which facilitated the generation of the reaction zone and its spreading inward the solid particles. The synthesized tetragonal barium titanate powder (mean particle size of 135 ± 24 nm) was sintered by a conventional technique at 1250 °C to obtain ceramics with grains of about 2 μm. Capacitance measurements performed a dielectric constant and loss tangent of ceramics, which reached 3879 and 6.7 10^-3, respectively, at 1 kHz and room temperature.

Reproductive abnormalities have been observed in fallow deer populations in Hungary. We supposed mycotoxin contamination to be one of the possible causes because multi-mycotoxin contamination is known to be dangerous even at low toxin levels, especially for young animals. We investigated the spatial pattern of mycotoxin occurrences and the relation of maternal and foetal mycotoxin levels. 72 fallow deer embryos and their mothers were sampled in seven forested regions in Hungary in the 2020/2021 hunting season. We analyzed Aflatoxin (AF), Zearalenone (ZEA), Fumonizin B1 (FB1), DON, T2-toxin concentrations in maternal and foetal liver by ELISA. AF was present in 70% and 82%, ZEA in 41% and 96%, DON in 90% and 98%, T2 in 96% and 85%, FB1 in 84% and 3% of hind and foetus livers, respectively. All mycotoxins passed into the foetus, but Fumonizin B1 only rarely. The individual variability of mycotoxin levels was extremely high, but the spatial differences were moderate. We could not prove a relation between the maternal and foetal mycotoxin concentrations, but we found accumulation of ZEA and DON in the foetuses. These results reflect the possible threats of mycotoxins to the population dynamics and reproduction of wild fallow deer.

Background: Survival and outcome of extremely preterm (EP) infants have improved due to changes in the management of stabilization at birth and respiratory distress syndrome. Methods: In a retrospective study conducted at an academic perinatal level III center in Romania, we compared the effects of different protocols on the early outcomes of EP infants of two different periods (2008-2012 vs. 2018 vs. 2022). Two subgroups were studied in each period, based on gestational age (GA), 22-25 weeks, and 26-28 weeks, excluding those with significant congenital anomalies or missing data. Results: 270 EP infants were included in the study (121/149), with a mean GA 26.1±1.6/26.7±1.1 weeks. Significant improvements were found during period II regarding initial FiO2 (40% vs. 100%; &lt;0.001), nCPAP (55.7% vs. 19.0%; p&lt;0.001) at birth, early rescue surfactant administration (65.8% vs. 34.7%; p&lt;0.001), need of mechanical ventilation (58.4% vs. 98.3%; p&lt;0.001). Survival rates of EP infants significantly improved from 41.3% to 72.5%, particularly in the 26-28 weeks subgroup (63.8% to 83%). The frequency of severe IVH decreased in period II from 30.6% to 14.1%, while the rates of BPD were lower in period II (23.4% vs. 36.6%; p=0.045), in the 26-28 weeks subgroup. We found improvements but no significant differences in NEC, sepsis, PVL, ROP, or PDA frequencies. Conclusions: Using updated guidelines and protocols is crucial for improving outcomes.

BKW is a highly efficient Storage Function-type rainfall-runoff model that utilizes the steady-state storage (S) and outflow (Q) of a catchment at different rainfall intensities as the S-Q relation of the catchment. For the inundation nowcasting of urban areas under high-intensity, short-duration rainfall, a Storage Function-type model is a judicious choice. However, S-Q hysteresis exists in the catchment S-Q relation, and BKW is unable to exhibit hysteresis due to assuming that the S-Q relation of a catchment is a nonlinear relation. The S-Q hysteresis can influence the outflow estimation of BKW, reducing the model's accuracy. Through the evaluation of analytical solutions, we found that the change in rainfall intensity dominates the S-Q relation of a catchment. The S-Q relation during a rainfall event is a dynamic process rather than a monotonic nonlinear relation. By applying the dynamic S-Q relation in BKW, we improved BKW to become a highly efficient and accurate rainfall-runoff model for small urban catchments.

The classification of tumors in subtypes, characterized by phenotypes determined by specific differentiation pathways, aids diagnosis and directs therapy towards targeted approaches. However, with the advent and explosion of next-generation sequencing, cancer phenotypes are turning out to be far more heterogenous than initially thought, and the classification is continually being updated to include more subtypes. Tumors are indeed highly dynamic and they can evolve and undergo various changes in their characteristics during disease progression. The picture becomes even more complex when tumor responds to a therapy. In all these cases, cancer cells acquire the ability to trans-differentiate, changing subtype, and adapt to changing microenvironments. These modifications affect the tumor's growth rate, invasiveness, response to treatment, and overall clinical behavior. Studying tumor subtype transitions is crucial for understanding tumor evolution, predicting disease outcomes, and developing personalized treatment strategies. We discuss this emerging hallmark of cancer and the molecular mechanisms involved at the crossroads between tumor cells and their microenvironment, focusing on four different human cancers in which tissue plasticity causes a subtype switch: breast cancer, prostate cancer, glioblastoma and pancreatic adenocarcinoma.

Diabetic retinopathy (DR), a prevalent complication of diabetes mellitus affecting a significant portion of the global population, has long been viewed primarily as a microvascular disorder. However, emerging evidence suggests that it should be redefined as a neurovascular disease with multifaceted pathogenesis rooted in oxidative stress and advanced glycation end products. The transforming growth factor-β (TGF-β) signaling family has emerged as a major contributor to DR pathogenesis due to its pivotal role in retinal vascular homeostasis, endothelial cell barrier function, and pericyte differentiation. However, the precise roles of TGF-β signaling in DR remain incompletely understood, with conflicting reports on its impact in different stages of the disease. Additionally, the BMP subfamily within the TGF-β superfamily introduces further complexity, with BMPs exhibiting both pro- and anti-angiogenic properties. Furthermore, TGF-β signaling extends beyond the vascular realm, encompassing immune regulation, neuronal survival, and maintenance. The intricate interactions between TGF-β and reactive oxygen species (ROS), non-coding RNAs, and inflammatory mediators have been implicated in the pathogenesis of DR. This review delves into the complex web of signaling pathways orchestrated by the TGF-β superfamily and their involvement in DR. A comprehensive understanding of these pathways may hold the key to developing targeted therapies to halt or mitigate the progression of DR and its devastating consequences.

Breast cancer brain metastasis (BCBM) is a challenging condition with limited treatment options and poor prognosis. Understanding the interactions between tumor cells and the blood-brain barrier (BBB) is critical for developing novel therapeutic strategies. One promising target is estrogen receptor β (ERβ), which promotes the expression of key tight junction proteins, sealing the BBB and reducing its permeability. In this study, we investigated the effects of 17β-estradiol (E2) and the selective ERβ agonist diarylpropionitrile (DPN) on endothelial and cancer cells. Western blot analysis revealed the expression patterns of ERs in these cell lines, and estrogen treatment upregulated claudin-5 expression in brain endothelial cells. Using in vitro models of the BBB, we found that DPN treatment significantly increased BBB tightness about suppressed BBB transmigration activity of representative HER2-positive (BT-474) and triple-negative (MDA-MB-231) breast cancer cell lines. However, the efficacy of DPN treatment decreased when cancer cells were pre-differentiated in the presence of E2. Our results support ERβ as a potential target for the prevention and treatment of BCBM and suggest that targeted vector-based approaches may be effective for future preventive and therapeutic implications.

It has been reported that Sclerotium nivale Elenev causes winter damage (Sclerotium disease) to winter rye and turfgrass in the European part of Russia, Ukraine, and Estonia. This fungal name is invalid, and their biological characteristics are limited. Since all reports on this fungus and their disease are written in Russian and Estonian without our recent review (Tkachenko 2013), few phytopathologists outside the former Union of Soviet Socialist Republics know about this fungus. We found symptoms of Sclerotium disease in Moscow, Russia, and we obtained asexual spore-forming ascomycetous (absent clamp connections) and basidiomycetous (had clamp connections) isolates from their white sclerotia. “S. nivale” was composed of several fungal species of ascomycetes and basidiomycetes. The ascomycetous isolate had the ability to grow under the snow cover, and phylogenic analysis suggested that the ascomycetous isolate had high homology (98–99%) with genera of Karstenula and Paraphaeosphaeria. We previously reported sclerotia of Typhula sp. were formed ca. 2 weeks to 1 month after the snow melt, remained immature as mycelial aggregations after snow melt, and matured without snow. In addition, Paraphaeosphaeria included sclerotium parasites such as P. minitans. Several cold-adapted fungi infected basidiomycetous sclerotia of Typhula spp. and others. These findings suggested that ascomycetous S. nivale was the possibility of the mycoparasite under the snow.

This paper aims to explore how climate change affects electricity generation (fossil-fueled power plants, hydroelectric stations, wind systems and photovoltaics) and energy demand in residential buildings in Greece for the period up to 2050. In both cases RCP scenarios results are considered in the appropriate spatial and temporal dimension. Energy supply technologies were examined through statistical regression models and/or mathematical equations correlating climatic parameters with energy productivity. With respect to energy demand, bottom-up models were developed that integrate behavioral and policy aspects. The analysis showed that climate change is expected to mainly affect electricity generation from hydro and thermal power plants, while the impacts on solar and wind energy are significantly lower. The range of impacts on hydro potential and electricity generation depends on the geographical location of the power plants and shows significant uncertainty due to the corresponding uncertainty in climate models estimates regarding precipitation and runoff changes while showing significant geographical variations. With respect to energy demand, climate change is expected to affect energy consumption, but the expected range of effects depends on both the implementation and the characteristics (deep vs. shallow renovation) of measures for upgrading the thermal performance of the building stock and the intensity of climate change.

Primary spontaneous pneumothorax (PSP) is a pleural disease that abruptly affects healthy adolescents and young adults, representing a common thoracic disorder in this age group. This study aimed to investigate the necessity of preoperative chest tube insertion in patients with PSP and to re-evaluate current clinical treatment approaches. A retrospective review of medical records was conducted for children and young adults aged 14–30 years, diagnosed with PSP and who underwent Video-assisted thoracoscopic surgery (VATS) between January 2016 and December 2022 at Wonju Severance Christian Hospital. Patients were retrospectively divided into two groups based on their initial treatment: chest tube insertion and non-chest tube insertion. Clinical data including demographics, treatment details, and outcomes were collected and compared. Total 128 cases of PSP were included in the study. The total length of hospital stay was significantly shorter in the non-chest tube group (p=0.000), which was attributed to the omission of pre-operative chest tube insertions. No significant differences were observed between the two groups in terms of postoperative complications or recurrence rates. In cases of young patients with PSP, omitting pre-operative chest tube insertion may be a viable option if the patient is scheduled for VATS.

Hydrodechlorination reaction of 3-(benzo-1,3-dioxol-5-yl)-3-chloro-2-methylacrylaldehyde in the presence of different low metal content heterogeneous mono- or bi-metallic catalysts was tested for the synthesis of the fragrance Helional® (3-[3,4-methylendioxyphenyl]-2-methyl-propionaldehyde). In particular, mono Pd/Al2O3, Rh/Al2O3 or bi-metallic Pd-Cu/Al2O3, Rh-Cu/Al2O3 catalysts were tested in different reaction conditions from which it emerged that mono-Rh/Al2O3 was the best performing catalyst allowing to achieve 100% substrate conversion and 99% selectivity towards Helional® in 24h at 80°C, p(H2) 1.0 MPa in the presence of a base. To establish correlations between atomic structure and catalytic activity, catalysts were characterized by Cu, Rh and Pd K-edge XANES, EXAFS analysis. These characterizations allowed to verify that the formation of Pd-Cu alloys and the presence of Cu oxide/hydroxide species on the surface of the Al2O3 support, are responsible for the very low catalytic efficiency of bimetallic species tested.

Neuroblastoma is an embryonal tumor arising from the sympathetic central nervous system. The epidermal growth factor (EGF) plays a role in neuroblastoma growth and metastatic behavior. Recently, we have demonstrated that cathepsin D (CD) contrasts EGF-induced neuroblastoma cell growth in 2D by downregulating EGFR/MAPK signaling. Aggressive NB is highly metastatic to the bone and the brain. In the metastatic process, adherent cells detach to form clusters of suspended cells that once reached the metastatic site adhere and form secondary colonies. Whether CD involves in survival of metastatic NB clones is not known. Therefore, in this study we addressed how CD differentially affects cell growth in suspension versus adherent condition. To mimic tumor heterogeneity, we co-cultured transgenic clones silenced for or overexpressing CD. We compared the growth kinetics of such mixed clones in 2D and 3D models in response to EGF, and we found that Over CD clone was advantaged for the growth in suspension, while the CD knocked-down clone was favored for the adherent growth as 2D. The fact that CD plays a dual role in cancer cell growth in 2D and 3D conditions indicates that during clonal evolution subclones expressing different level of CD may arise, which confers survival and growth advantages depending on the metastatic step. Whether CD involves in survival of metastatic NB clones is not known. We propose that epigenetic regulation of CD expression could be an additional strategy to prevent NB metastases.

In our increasingly urbanized world, precise and up-to-date maps of human settlements are essential for sustainable urban development policies. The availability of open-access Sentinel-2 data from the Copernicus program presents an opportunity to create a comprehensive global map of human settlements, offering a detailed view of built areas on a large scale. This study estimates large-scale built-up fractions using encoder-decoder deep learning architectures like U-net, Res-U-net, and Attention-U-net in the large and complex urban area of Delhi, India. Openly available datasets like Open Street Map (OSM) and Microsoft building footprint datasets are used to derive built-up fractions at 10×10m resolution cells for over 34,000 km2. Our results show that Attention-U-net with the Huber loss function performs the best in different built-up densities (i.e., urban, semi-urban or rural) with an R2 score of 0.631, while Res-U-net and U-net obtained an R2 score of 0.623 and 0.612, respectively. The investigated networks significantly improve the accuracy over the latest Global Human Settlement Layer product (GHSL-S2), which uses a deep-CNN and reaches an R2 of 0.387 in our case study area. The result of this study yields a valuable spatial layer for examining the spatial distribution of human settlements across the entire spectrum from rural to urban areas.

As the world increasingly becomes more interconnected, the demand for safety and security is ever-increasing, particularly for industrial networks. This has prompted numerous researchers to investigate different methodologies and techniques suitable for intrusion detection systems (IDS) requirements. Over the years, many studies have proposed various solutions in this regard including signature-based and machine-learning (ML) based systems. More recently, researchers are considering deep learning (DL) based anomaly detection approaches. Most proposed works in this research field aimed to achieve either one or a combination of high accuracy, considerably low false alarm rates (FARs), high classification specificity and detection sensitivity, achieving lightweight DL models, or other ML and DL-related performance measurement metrics. In this study, we propose a novel method to convert a raw dataset to an image dataset to magnify patterns. Based on this we devise an anomaly detection for IDS using a lightweight convolutional neural network (CNN) that classifies denial of service and distributed denial of service. The proposed methods were evaluated using a modern dataset, CSE-CIC-IDS2018, and a legacy dataset, NSL-KDD. We have also applied a combined dataset to assess the generalization of the proposed model across various datasets. Our experimental results have demonstrated that the proposed methods achieved high accuracy and considerably low FARs with high specificity and sensitivity. The resulting loss and accuracy curves have also demonstrated the excellent generalization of the proposed lightweight CNN model, effectively avoiding overfitting. This holds for both the modern and legacy datasets, including their mixed version.

In this paper, we consider an epidemiological Susceptible-Infected-Susceptible (SIS) model in which the individuals cured from the infection return back into the group of people endangered by the infection. Delay differential equations were introduced to create more realistic models since many processes depend on past history. Many different mathematical methods, including the Susceptible-Infected-Recovered (SIR) model as well as derivatives thereof, can be used to prognose the spread of many various infectious diseases, including Covid-19.We use a nonlinear differential system with time delay as a mathematical formulation of this model. It is examined by the existence of a positive solution which is bounded by two functions $k_1, k_2\in C([t_0,\infty),(0,\infty))$ with constants $\lambda_1 > 0,\,\lambda_2 > 0$ where $0<\lambda_1\leq \lambda_2$. The conditions are put in place for existence of a positive solution that approaches zero in infinity, if $t\to\infty$. Infectious diseases accompany a person throughout their entire life, and in the history of mankind often appeared in frequent epidemics caused high mortality. The occurrence of infectious diseases in the population represents a serious health, social and economic problem. There is a lot of ambiguity concerning the time span and final spread of the epidemic thus making it very demanding for the governing bodies, healthcare institutions, and economic sector to precisely judge the future development.Several examples are shown at the end of this paper.

Background The distinctive feature of liver fibrosis is the progressive replacement of healthy hepatic cells by extracellular matrix protein, which is abundant in collagen I and III with impaired matrix remodelling. The activation of myofibroblastic cells enhances a fibrogenic response of complex interactions of hepatic stellate cells, fibroblasts and inflammatory cells to produce excessive deposition of extracellular protein matrix. This process is activated by multiple fibrogenic mediators and cytokines such as TNF-α and IL-1ß with decrease in the anti-fibrogenic factor NF-ҡß. Mesenchymal stem cells (MSCs) represent a promising therapy for liver fibrosis giving more advanced regenerative influence when cultured with extrinsic or intrinsic proliferative factors, cytokines, anti-oxidants, growth factors, and hormones such as Melatonin (MT). However, previous studies showed conflicted findings concerning the therapeutic effects of adipose (AD) and bone marrow (BM)-MSCs, therefore, the present work aimed to accomplish a comparative and comprehensive study investigating the impact of MT pre-treatment on the immunomodulatory, anti-inflammatory and anti-apoptotic effects of AD and BM-MSCs and to critically analyse whether MT pre-treated both AD-MSCs and BM-MSCs reveal equal or different therapeutic and regenerative potentials in CCl4-injured liver of experimental rat models. Materials and methods Six groups of experimental rats were used with ten rats in each group; group I (control group), group II (CCl4-treated group), group III (CCl4 and BM-MSCs treated group), group IV (CCl4 and MT pre-treated BM-MSCs group), group V (CCl4 and AD-MSCs treated group) and group VI (CCl4 and MT pre-treated AD-MSCs group). Liver function tests, gene expression of inflammatory, fibrogenic, apoptotic and proliferative factors were analysed. Histological and immunohistochemical changes were assessed. Results The present study compared the capability of AD and BM-MSCs, with and without the pre-treatment of MT, to reduce hepatic fibrosis. Both types of MSCs improved hepatocyte function by reducing the serum levels of (ALT), aspartate aminotransferase (AST), alkaline phosphatase (AKP), and total bilirubin (TBIL). In addition, the changes in the hepatocellular architecture including the hepatocytes, liver sinusoids, central veins, portal veins, biliary ducts and hepatic arteries showed decrease hepatocyte injury and cholestasis with reduction of inflammation, apoptosis and necrosis of the hepatic cells together with inhibition of liver tissue fibrosis. These results were augmented by the analysis of the expression of the anti-inflammatory cytokines TNFα and IL-1β, the anti-fibrogenic factor NF-ҡß, the apoptotic factor caspase-3 and the proliferative indicators antigen Ki-67 and proliferating cell nuclear antigen (PCNA). These findings were found statistically significant, with the best results in the rats received AD-MSCs pre-treated with MT, denoting better regenerative and therapeutic effects. Conclusion AD-MSCs, pre-treated with MT, are superior to BM-MSCs due to their better efficacy in improving hepatic fibrosis and promoting the therapeutic and regenerative capability of liver tissue. They represent a very significant tool for future stem cell use in tissue regeneration strategy for the treatment of liver diseases.

In this paper, a class of coupled competitive neural networks, which subject to disturbance and discontinuous activation functions, is concerned. To realize the fixed-time quasi-bipartite synchronization, an aperiodic intermittent controller is initially designed. Subsequently, by combining the fixed-time stability theory and nonsmooth analysis, several criteria are established to ensure the bipartite synchronization in fixed time. Moreover, synchronization error bounds and settling time estimates are provided. Finally, numerical simulations are presented to verify the main results.

Flood forecasting helps anticipate floods and evacuate people, but due to the access of a large number of iot data acquisition devices, the explosive growth of multidimensional data and the increasingly demanding prediction accuracy, classical parameter models and traditional machine learning algorithms are unable to meet the high efficiency and high precision requirements of prediction tasks. In recent years, deep learning algorithms represented by convolutional neural networks, recurrent neural networks and Informer models have achieved fruitful results in time series prediction tasks. The Informer model is used to predict the flood flow of the reservoir. At the same time, the prediction results are compared with the prediction results of the traditional method and the LSTM model, and how to apply the Informer model in the field of flood prediction to improve the accuracy of flood prediction is studied. The data of 28 floods in the Wan 'an Reservoir control basin from May 2014 to June 2020 were used, with areal rainfall in five subzones and outflow from two reservoirs as inputs and flood processes with different sequence lengths as outputs. The results show that the Informer model has good accuracy and applicability in flood forecasting. In the flood forecasting with sequence length of 4, 5 and 6, Informer has higher prediction accuracy, and the prediction accuracy is better than other models under the same sequence length, but the prediction accuracy will decline to a certain extent with the increase of sequence length. The Informer model stably predicts the flood peak better, and its average flood peak difference and average maximum flood peak difference are the smallest. As the length of the sequence increases, the number of fields with a maximum flood peak difference less than 15% increases, and the maximum flood peak difference decreases. Therefore, the Informer model can be used as one of the better flood forecasting methods, and it provides a new forecasting method and scientific decision-making basis for reservoir flood control.

The study of dog point following has been increasingly popular, at least partially due to the initial claims that dogs outperform apes and the suggestion that our domestication process caused dogs to have a biological capacity to communicate with humans. We take the view that dog pointing is more complicated than was initially reported, and in this study, we explore several potential variables that may make a difference. Our variables include point type (ipsilateral (same-side) vs contralateral (cross-body) points), position (standing vs seated), and distance (proximal vs distal). We find that most dogs follow ipsilateral points while less than half of the dogs in our sample follow contralateral points, and that position and distance also affect dogs’ success. We suggest that dogs acquire ipsilateral points via associative mechanisms, but that contralateral points require the dogs to understand the humans’ communicative intent.

Glioblastoma multiforme (GBM), the most prevalent primary malignant brain tumor in adults, exhibits a dismal 6.9% five-year survival rate post-diagnosis. Thymoquinone (TQ), the most abundant bioactive compound in Nigella Sativa, has been extensively researched for its anti-cancer properties across various human cancers. Yet, its specific anticancer mechanisms and pathways in glioblastoma remain to be elucidated. In this study, we assessed the impact of different TQ concentrations on the viability of A172 cells using WST-8 and Toluidine blue assays, followed by RNA sequencing (RNA-seq) to identify differentially expressed genes (DEGs). We confirmed their expression levels through quantitative RT-PCR and performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses for these DEGs. RNA-seq revealed no significant gene expression changes at 2.5 µM and 5 µM TQ concentrations. However, at 25 µM and 50 µM, TQ significantly reduced cell viability in a dose-dependent manner. We identified 1548 DEGs at 25 µM TQ (684 upregulated, 864 downregulated) and 2797 DEGs at 50 µM TQ (1528 upregulated, 1269 downregulated), with 1202 DEGs common to both concentrations. TQ inhibited key pathways such as PI3K-Akt signaling, calcium signaling, focal adhesion, and ECM-receptor interaction in A172 cells. It downregulated several potential oncogenes (e.g., AEBP1, MIAT) and genes linked to GBM proliferation and migration (e.g., SOCS2, HCP5), while modulating Wnt signaling and upregulating tumor suppressor genes (e.g., SPRY4, BEX2). TQ also affected p53 downstream targets, maintaining p53 levels. This study elucidates the anticancer mechanisms of TQ in A172 GBM cells, underscoring its effects on multiple signaling pathways and positioning TQ as a promising candidate for innovative glioblastoma treatment strategies.

In this study, the temporal variation in soil salinity dynamics was monitored and analyzed using Electromagnetic Induction (EMI) in an agricultural area in Port Said, Egypt, which is at risk of soil salinization. To assess soil salinity, repeated CMD2 soil apparent electrical conductivity (ECa) measurements were taken and inverted to generate electromagnetic conductivity imaging (EMCI), representing soil electrical conductivity (σ) distribution through time-lapse inversion. This process involved converting EMCI data into salinity cross sections using a site-specific calibration equation that correlates σ with the electrical conductivity of saturated soil paste extract (ECe) for the collected soil samples. The study was performed from August 2021 to April 2023, involving six surveys during two agriculture seasons. The results demonstrated the accurate prediction ability of soil salinity with R2 value of 0.81. The soil salinity cross sections generated on different dates observed changes in the soil salinity distribution. These changes can be attributed to shifts in irrigation water salinity resulting from canal lining, winter rainfall events, and variations in groundwater salinity. This approach is effective for evaluating agricultural management strategies in irrigated areas where it is necessary to continuously track soil salinity to avoid soil fertility degradation and a decrease in agricultural production and farmer’s income.

The C-C motif chemokine receptor 8 (CCR8) is highly and selectively expressed in regulatory T (Treg) cells and is associated with tumor progression. The massive accumulation of Treg cells into tumors suppresses the effector function of CD8⁺ cells against tumor cells. Therefore, selective depletion of Treg cells using anti-CCR8 monoclonal antibodies (mAbs) reinvigorates antitumor immune responses and improves responses to cancer immunotherapy. Previously, we developed an anti-mouse CCR8 (mCCR8) mAb, C₈Mab-2, using the Cell-Based Immunization and Screening (CBIS) method. In this study, the binding epitope of C₈Mab-2 was investigated using flow cytometry. The mCCR8 extracellular domain-substituted mutant analysis showed that C₈Mab-2 recognizes the N-terminal region (1–33 amino acids) of mCCR8. Next, 1×alanine (or glycine) scanning and 2×alanine (or glycine) scanning were conducted in the N-terminal region. The results revealed that the _17-DFFTAP_-22 sequence is important for the recognition by C₈Mab-2, and Thr20 is a central amino acid of the epitope. These results revealed the involvement of the N-terminus of mCCR8 in the recognition by C₈Mab-2.

Video gamers can play to negate the psychological impact of stress (Pine et al., 2020), which may become problematic when users over-rely on the stress-relief potential of gaming. This study used a repeated-measures experimental design to investigate the relationships between stress, video gaming, and problematic video gaming behaviours in a convenience sample of 40 students at a UK university. Results indicated that positive affect increased and negative affect decreased, whilst a biological stress measure (Instantaneous Pulse Rate) also decreased after a short video gaming session (t(36) = 4.82, p < .001, d = 0.79). Results also suggest that video gaming can act as a short-term buffer against the physiological impact of stress. Further research should focus on testing individuals who have been tested for Gaming Disorder as opposed to a general population. Research could also utilise variations of the methodological framework used in this study to examine the intensity of a stress-relief effect under different social situations. The study’s findings in relation to published work are also discussed.

Ribosomal proteins (r-proteins) are abundant, highly conserved, and multifaceted cellular proteins in all domains of life. Most r-proteins have RNA-binding properties and are able to form protein-protein contacts. Bacterial r-proteins govern the co-transcriptional rRNA folding during ribosome assembly and participate in formation of the ribosome functional sites such as the mRNA binding site, tRNA binding sites, the peptidyl- transferase center, and the protein exit tunnel. In addition to their primary role in a cell as integral components of the protein synthesis machinery, many of r-proteins can function beyond the ribosome (the phenomenon known as moonlighting), acting either as individual regulatory proteins or in complexes with various cellular components. Extraribosomal activities of r-proteins have been intensively studied over decades (reviewed in [1]). The past decade brought significant advancement in our knowledge of r-protein functions due to expanding studies on ribosomes and gene expression mechanisms not only in model bacteria like Escherichia coli or Bacillus subtilis, but also in previously little-explored bacterial species from various phyla. This review is aimed to update the information on multiple functions of r-proteins in bacteria.

A healthy 47-year-old woman consulted the Oral Surgery and Implantology Unit of the University Hospitals of Geneva with a request to treat her painful tooth 11 and replace the missing tooth 21. The dental history revealed that the patient had lost teeth 21 and 22 due to advanced caries. On clinical examination, tooth 11 showed an ill-fitting prosthetic crown with overhanging margins, an increased localized probing depth of 8 mm in the disto-vestibular area and sensitivity to percussion. The edentulous site 21 showed horizontal bone atrophy. Radiological examination revealed a well-defined unilocular radiotransparent lesion surrounded by a thin radiolucent border, located at the apex of tooth 11 and measuring 10 x 8 mm. The treatment consisted of extraction of 11, enucleation of the apical lesion, insertion of implants at sites 11 and 21 with simultaneous bone augmentation in a single surgical procedure with aesthetic and functional results at 3-year follow-up without any complications. Our case highlights that immediate implant placement in case of cystic periapical lesion represents a good valid alternative to standard treatment.

Clostridioides (Clostridium) difficile is an enteric pathogen of neonatal pigs with zoonotic transmission remaining a significant problem in humans, including nosocomial resurgence, following oral administration of broad-spectrum antibiotics. To date, the immune response to C. difficile has mostly focused on neutrophils and cytokine/chemokines, particularly in human infection. We show that porcine monocytes respond to C. difficile differently compared with many other bacterial infections. Infection of porcine monocytes with human C. difficile strains CD630 (Ribotype 078) or R20291 (Ribotype 027) for 3 or 24h post-infection (pi) resulted in a lack of oxidative burst or nitrite ion production when compared to uninfected controls (P >0.05). The survival dynamics of both CD630 and R20291 in monocytes were similar with intracellular bacterial numbers being similar at 3h pi and 24h pi (P >0.05). However, we show that porcine monocytes entrap C. difficile via extracellular DNA traps. This process began as early as 3h pi and at 24h pi the nuclei appeared to be depleted of DNA, although extracellular DNA was associated with the cell membrane. Our preliminary study also suggests that entrapment of C. difficile by extracellular DNA may occur via a process of monocyte etosis.

Artificial intelligence (AI) is revolutionizing approaches in plant disease management and phy-topathological research. This review analyzes current applications and future directions of AI in addressing evolving agricultural challenges. Plant diseases annually cause 10-16% yield losses in major crops, prompting urgent innovations. Artificial intelligence (AI) shows aptitude for auto-mated disease detection and diagnosis utilizing image recognition techniques, with reported accuracies exceeding 95% and surpassing human visual assessment. Forecasting models inte-grating weather, soil, and crop data enable preemptive interventions by predicting spa-tial-temporal outbreak risks weeks in advance at 81-95% precision, minimizing pesticide usage. Precision agriculture powered by AI optimizes data-driven, tailored crop protection strategies boosting resilience. Real-time monitoring leveraging AI discerns pre-symptomatic anomalies from plant and environmental data for early alerts. These applications highlight AI's proficiency in il-luminating opaque disease patterns within increasingly complex agricultural data. Machine learning techniques overcome human cognitive constraints by discovering multivariate correla-tions unnoticed before. AI is poised to transform in-field decision making around disease pre-vention and precision management. Overall, AI constitutes a strategic innovation pathway to strengthen ecological plant health management amidst climate change, globalization, and agri-cultural intensification pressures. With prudent and ethical implementation, AI-enabled tools promise to enable next-generation phytopathology, enhancing crop resilience worldwide.Artificial Intelligence, Phytopathology, Emerging Disease, Climate Change, Control diseases.

The aim of the study was to determine the effect of the application of different organic matter, UGmax soil conditioner and simplifications in potato cultivation on the content of dry matter, starch, sugars in tubers of the medium-early edible cultivar 'Satina' after harvest and after long-term storage. The highest dry matter (173.4 g kg-1) and starch (124.6 g kg-1 f. m.) content was ob-tained with the simultaneous application of a manure with soil conditioner at 100% mineral fer-tilization. In the case of sugars, the withdrawal of the soil conditioner from the crop proved most beneficial, for total sugars on the stubble intercrop (5.06 g kg-1 f. m.) and for reducing sug-ars (1.99 g kg-1 f. m.) on the straw. Each protection reduction applied resulted in a significant re-duction in starch content. In this regard, the withdrawal of herbicides with simultaneous appli-cation of manure and UGmax proved most beneficial. Long-term storage of tubers caused a sig-nificant reduction in their quality in terms of dry matter and starch content (average by -3.6 and -2.3%, respectively) and an increase in total and reducing sugars (average by 11.8 and 9.6%, re-spectively). The decrease in dry matter and starch content was significantly influenced by the 50% reduction in NPK fertilization applied during the growing season, while the application of soil conditioner with full protection contributed to the increase in reducing sugars after storage at 28.9 pts%. Our research is in line with current trends of used potato cultivation technologies focused mainly on environmental protection, so the results of this study can provide a basis for validation for researchers currently engaged in such evaluation.

The use of the Google Scholar produces about 278 hits on the term ‘‘inertial propulsion.’’ If patents are also included, the number of hits increases to 536. This paper discusses, in a critical way, some characteristic aspects of this controversial topic. The review starts with the halteres of athletes in the Olympic games of ancient times and then continues with some typical devices which were developed or/and patented from the second fourth of the twentieth century till today.

Multilineage-differentiating stress-enduring (Muse) cells, a cell subgroup from mesenchymal stem cells (MSCs), are pluripotent cells with unique characteristics such as non-tumorigenic and pluripotent differentiation ability. After homing, Muse cells spontaneously differentiate into tissue component cells and supplement damaged/lost cells to participate in tissue repair. Importantly, Muse cells can survive in injured tissue for an extended period, stabilizing and promoting tissue repair. In addition, it has been confirmed that injection of exogenous Muse cells exerts anti-inflammatory, anti-apoptosis, anti-fibrosis, immunomodulatory, and paracrine protective effects in vivo. The discovery of Muse cells is an important breakthrough in regenerative medicine. The article provides a comprehensive review of the characteristics, sources, and potential mechanisms of Muse cells for tissue repair and regeneration. This review serves as a foundation for the further utilization of Muse cells as a key clinical tool in regenerative medicine.

Lathyrane-type diterpenes have a wide range of biological activities. Among them, euphoboetirane A (1) exerts neurogenesis-promoting activity. In order to increase the structural diversity of this type of lathyranes to explore their potential use in neurodegenerative disorders, the biotransformation of 1 by Streptomyces puniceus BC-5GB.11 has been investigated. The strain BC-5GB.11, isolated from surface sediments collected from the intertidal zone of the inner Bay of Cadiz, was identified as Streptomyces puniceus, as determined by phylogenetic analysis using 16S rRNA gene sequence. Biotransformation of 1 by BC-5GB.11 afforded five products (3-7), all of them reported here for the first time. The main biotransformation pathways involved regioselective oxidation at non-activated carbons (3-5) and isomerization of the D^12,13 double bond (6). In addition, a cyclopropane-rearranged compound was found (7). The structures of all compounds were elucidated on the basis of extensive NMR and HRESIMS spectroscopic studies.

Glioblastoma is a central nervous system cancer type with a poor prognosis. One of its main features is the constant change of metabolism phenotype to support its development and progression. Mitochondria play a critical role in cellular metabolism. Acetylation on lysine residues of mitochondrial enzymes is a mechanism for regulating protein function. This modification negatively affects the mitochondrial proteome function and is counteracted by the enzyme sirtuin 3 (SIRT3). To better understand how SIRT3 regulates mitochondrial metabolism, we inhibited SIRT3 and examined by high-resolution mass spectrometry analysis the proteome and acetylome of two glioblastoma cell lines with different metabolic preferences. Our results indicate that protein synthesis machinery is regulated by lysine acetylation and plays a role in the metabolic phenotype. We also identified new SIRT3 targets not previously associated with specific functions, highlighting their potential as future targets for further study. This study shed light on the role of SIRT3 in mitochondria and its implication for cellular metabolism. We have generated knowledge at the proteome and acetylome levels on the dynamics between two glioblastoma cell lines with opposing metabolic phenotypes. Our results might guide in searching for biomarkers at both proteome and acetylome levels in glioblastoma.

(1) Background: The research on the potential of regional food products, known for their rich bio-active compound content, could enhance human health in local populations. This is especially pertinent amid the Covid-19 pandemic and global trade disruptions; (2) Methods: The current study evaluated the physico-chemical composition using standard methods, antioxidant activity via DPPH, ABTS, FRAP, and CUPRAC methods, sorption capacity (at 10°C, 25°C, and 40°C with water activity ranging from 0.1 to 0.9) through the static-gravimetric method, and monolayer moisture content (MMC) calculated using the BET model; (3) Results: The approximate physi-co-chemical composition of laboratory-produced quince powder is as follows: proteins - 1.27g, carbohydrates - 75.80g, fats - 0.49g, fibers - 21.50g, ash – 2.31g, and nutritional value – 355.65kcal. Antioxidant activity is confirmed by all methods. The Modified Halsey model is recommended to describe the sorption isotherms with an S-shaped form. The MMC for the adsorption process ranges from 14.41% d.b. to 7.09% d.b., and for the desorption process, it ranges from 13.11% d.b. to 7.80% d.b.; (4) Conclusions: Seasonal and regional foods boast the best nutritional profiles, as they are cultivated and harvested at optimal ripeness in natural sunlight, preserving the essential vitamins and minerals in the food.

This work targets the development of a mobility control system for high-speed series hybrid electric tracked vehicles, which operate with independent traction motors for each track. The scope of the research encompasses the modeling of the series hybrid powertrain specific to military tracked vehicles, as well as an in-depth analysis of their dynamic behavior. Subsequently, the study conducts a critical review of the mobility control approaches sourced from literature, identifying key techniques relevant to high-inertia vehicular applications. Building on the foundational models, the study puts forward a robust closed-loop mobility control system aimed at ensuring precise and stable off-road vehicle operations. The system's resilience and adaptability to a variety of driving conditions are emphasized, with a particular focus on handling maneuvers such as steering and pivoting, which are challenging operations for tracked vehicle agility. The performance of the proposed mobility control system is tested through a series of simulations, covering a spectrum of operational scenarios. These tests are carried out in both offline simulation settings, which permit meticulous fine-tuning of system parameters, and real-time environments that replicate actual field conditions. The simulation results demonstrate the system's capacity to improve vehicular response and highlight its potential impact on the future designs of mobility control systems for the heavy-duty vehicle sector, particularly in defense applications.

The creation of protonated water nanoclusters from amorphous water-ice under laboratory conditions suggests the possible ejection of such nanoclusters from ubiquitous amorphous water-ice-covered cosmic dust to interstellar space. The quantum properties of these quintessential water entities introduce a tantalizing prospect that bridges the origins of dark matter, dark energy, and life in the universe. The quantum-entangled diffuse Rydberg electronic states inherent to cosmic water nanoclusters make them plausible candidates for baryonic dark matter. Moreover, they exhibit the capacity to absorb, through the microscopic dynamical Casimir effect, virtual photons originating from zero-point-energy vacuum fluctuations occurring above the water-nanocluster vibrational frequency cutoff. This selective interaction leaves only vacuum fluctuations below these frequencies with gravitational significance, cancelling the vacuum-energy catastrophe and yielding a shared genesis for dark matter and dark energy. Moreover, this theory extends its implications to the origins of life itself, proposing that RNA protocells on Earth and habitable exoplanets may have emerged from the interactions between cosmic water nanoclusters and prebiotic organic molecules, thus yielding an anthropic narrative. Collectively, these findings coalesce into a cosmological framework depicting a cyclic universe, with cosmic water nanoclusters constituting a quintessence scalar field, instead of adhering to the multiverse concept based on cosmic inflation theory. Recent observations of CMB birefringence support this quintessence.

This study sought to improve the nutritional, functional and biochemical properties of pearl millet through malting and fermentation. Moringa oleifera leaf powder (MLP) was used as a fortificant. Mixture design was used to find optimal proportions for each of the components that yield a high protein and or low saturated fat content. Twelve mixtures with varying ratios of fermented, and malted pearl millet flour ranging between 30–65%, and MLP between 5–15% were generated through I-Optimal mixture design. The mixtures were wet-cooked, freeze-dried and analyzed for protein and fat content. The data obtained were fitted to a linear mixture model and the search for the optimum was done using Numerical Optimization for maximising protein and minimising saturated fat. The linear model was suitable for explaining variation for total protein and saturated fat with r2 of 0.50 and 0.51, respectively. Increasing MLP increased protein content. Two final formulations were generated through the optimization process. Pearl millet’s protein content increased by up to 22% while saturated fat decreased by up to 13%. Ash content increased by 75%. Polyphenol content and oxygen radical absorbance capacity increased by 80% and 25%, respectively. Final and peak viscosity were reduced by 90% and 95%, respectively.

Smoker’s paradox usually refers to the common observation of a favourable outcome of smoker patients in acute myocardial infarction. The interpretation of this phenomenon is still controversial and not fully explained. We aimed at assessing whether smoking could be associated with mortality in a large cohort of prospectively enrolled patients with ST segment elevation myocardial infarction (STEMI) referred to primary percutaneous coronary intervention (pPCI). From April 2006 to December 2018 a population of 2456 STEMI patients treated with primary PCI were prospectively enrolled in the MATRIX registry. Ischemic time, clinical, demographics, angiographic data and 1-year follow-up were collected. Among 2546 patients admitted with STEMI 1007 (41%) were current smokers. Smokers were 10 years younger and had lower crude in-hospital and 1-year mortality (1.5% vs 6%, p&lt;0.0001 and 5% vs 11%, p&lt;0.0001), shorter ischemic time (203 [147-299] vs 220 [154-334] minutes, p=0.002) and shorter decision time (60 [30-135] vs 70 [36-170] minutes, p=0.0063). After propensity-matching, age, cardiogenic shock and low TIMI score were associated with in-hospital mortality, while smoking habit was still associated with reduced mortality. Smoking was also associated with reduced death rate at 1-year follow-up (HR 0.54, 95% CI [0.37 - 0.78]; p&lt;0.001). Our data show a protective link between smoking status and mortality in patients with STEMI, the so called “smoker’s paradox”. This could be explained not only by the shorter ischemic time and younger age of the smoking population but also by a specific pathogenetic effect of smoking underlying the onset of STEMI and response to therapies.

Cracks on concrete surfaces are vital factors affecting construction safety. Accurate and efficient crack detection can prevent safety accidents. Using drones to photograph cracks on a concrete surface and detect them through computer vision technology has the advantages of accurate target recognition, simple practical operation, and low cost. To solve this problem, an improved CenterNet concrete crack-detection model is proposed. First, a channel-space attention mechanism is added to the original model to enhance the ability of the convolution neural network to pay attention to the image. Second, a feature selection module is introduced to scale the feature map in the downsampling stage to a uniform size and combine it in the channel dimension. In the upsampling stage, the feature selection module adaptively selects the combined features and fuses them with the output features of the upsampling. Finally, the target size loss is optimised from a Smooth L1 Loss to IoU Loss to improve its inability to adapt to targets of different sizes. The experimental results show that the improved CenterNet model reduces the FPS by 123.7, increases the GPU memory by 62MB, increases the FLOPs by 3.81, and increases the AP by 0.154 compared with the original model. The GPU memory occupancy remained stable during the training process and exhibited good real-time performance and robustness.

Chive (Allium schoenoprasum L.) has a strong antioxidant property as it contains abundant phenolic compounds and ascorbic acid (AsA). In the present study, we investigated the metabolism of phenolic compounds and the change in antioxidant activity in different tissue parts of post-harvest chive. The results showed that compared with the bottom white part (BW), the round green part (RG) exhibited significantly higher content of phenolic compounds, increased enzyme activities and antioxidant activities, indicating that phenolic compounds were mainly synthesized in RG. The expression levels of genes (phenylalanine ammonia lyase (PAL), cinnamate 4-hydroxylase (C4H) and 4-coumaroyl-CoA ligase (4CL)) and their corresponding enzymes activities rapidly decreased in RG, whereas they were maintained in BW, suggesting that senescence occurred more rapidly in RG compared with that in BW. Our study provides a theoretical foundation for further research and development of different parts of Allium plants and offers a basis for consumers' nutritional considerations.

A crucial aspect in developing machine learning algorithms (or any type of predictive models) is the comparison of different algorithmic candidates based on evaluation criteria that measure their accuracy and practical value in terms of successfully capturing the complexity of the underlying problem and generalizing in a wide range of real-world scenarios. In the domain of diabetes mellitus machine learning techniques are widely employed in the prediction of future values of glucose concentration in the blood in order to assist the patient in avoiding deviations from the normo-glycemic value range and the consequences of hyper- and hypoglycemia. In the relative literature there is an apparent lack of a uniformly adopted evaluation metric which could combine the clarity and direct comparative nature of statistical mathematical formulas dealing with prediction error residuals (e.g., the RMSE) with the clinical insights and the visual-qualitative approach of clinical evaluation tools (e.g., Clarke's EGA). Mean Adjusted Exponent (MADEX) error metric, proposed in this paper, attempts to address this need by providing a validation tool based on an easy to implement mathematical formula, that incorporates adjustable parameters of clinical significance.

This article theoretically derives the magnetic field and vector potential produced by a steady current I flowing in an arbitrary plane loop at an arbitrary point r. Numerical examples are presented to demonstrate the behavior of the magnetic field produced by loops of various shapes such as polygons, circles, ellipses, and p-norm balls. Taking the limit as the loop shrinks to a point and the current I grows to infinity so that the magnetic dipole moment m of the loop (defined as the current I times the vector area of the loop) is kept constant, the magnetic field and vector potential are theoretically shown to converge to those of an ideal point magnetic dipole m.

The Ca Mau Peninsula situated in the Mekong Delta of Vietnam, features a low-lying terrain. Over recent years, the region has encountered the adverse impacts of climate change, leading to both land subsidence and rising sea levels. In this study, we assessed the land subsidence susceptibility in the Ca Mau peninsula utilizing three Boosting machine learning models: AdaBoost, Gradient Boosting, and Extremely Gradient Boosting (XGB). Eight key factors were identified as the most influential in land subsidence within Ca Mau: land cover (LULC), Groundwater levels, distance to roads, Digital Terrain Model (DTM), normalized vegetation index (NDVI), geology, soil composition, and proximity to rivers and streams. A dataset comprising 1950 subsidence sample points was employed for the model, with 1910 points obtained from the PSInSAR Radar method, and the remaining points derived from leveling measurements. The sample points were split, with 70% allocated to the training set and 30% to the testing set. Following computation and execution, the three models underwent evaluation for accuracy using statistical metrics such as the ROC curve, Area under the curve (AUC), Specificity, Sensitivity, and Overall Accuracy. The research findings revealed that the XGB model exhibited the highest accuracy, achieving an AUC above 0.9 for both the training and test sets. Consequently, XGB was chosen to construct a land subsidence susceptibility map for the Ca Mau peninsula.

Cryptococcus neoformans is a fungus that mainly affects the respiratory system and the central nervous system. One of the main virulence factors is the capsule, constituted by the polysaccharides glucuronoxylomannan (GXM) and glucuronoxylomanogalactan (GXMGal). Polysaccharides are immunomodulators. One of the target cell populations for modulation are macrophages, part of the first line of defense, important for innate and adaptive immunity. It has been reported that macrophages can be modulated to act as a "Trojan horse" taking phagocytosed yeasts to strategic sites or having their machinery activation compromised. The scarcity of information on canine cryptococcosis led us to assess whether the purified capsular polysaccharides from C. neoformans would be able to modulate the microbicidal action of macrophages. In the present study, we observed that the capsular polysaccharides, GXM, GXMGal or capsule total did not present toxic effects for the DH82 macrophage cell line. However, it was possible to demonstrate that phagocytic activity was decreased after treatment with polysaccharides. In addition, yeasts recovered from macrophages treated with the polysaccharides, after phagocytosis, could be cultured, showing that their viability was not altered. The polysaccharides led to a reduction in ROS production and the expression of IL-12 and IL-6. We observed that GXMGal inhibits MHC class II expression and GXM reduces ERK phosphorylation. In contrast, GXMGal and GXM were able to increase the PPAR- expression. Furthermore, our data suggests that capsular polysaccharides can reduce the microbicidal activity of canine macrophages DH82.

Early-onset colorectal cancer (EOCRC) is defined as a diagnosis of colorectal cancer (CRC) in individuals younger than 50 years of age. While overall CRC rates in the United States (US) decreased between 2001 and 2018, EOCRC rates have increased. This research project aims to evaluate the feasibility and acceptability of Time-Restricted Eating (TRE), Mindfulness, or TRE combined with Mindfulness among young to middle-aged adults at risk of EOCRC. Forty-eight participants will be randomly assigned to one of four groups: TRE, Mindfulness, TRE &amp; Mindfulness, or Control. Data on feasibility, adherence, and acceptability will be collected. Measures assessed at baseline and post-intervention will include body weight, body composition, dietary intake, physical activity, sleep behavior, circulating biomarkers, hair cortisol, and gut microbiome. Effects of the intervention on the following will be examined: 1) acceptability and feasibility; 2) body weight, body composition, and adherence to TRE; 3) circulating metabolic, inflammation, and oxidative stress biomarkers; 4) intestinal inflammation; and 5) the gut microbiome. TRE combined with Mindfulness holds promise for stress reduction and weight management among individuals at risk of EOCRC. The results of this pilot study will inform the design and development of larger trials aimed at preventing risk factors associated with EOCRC.

Green economy has emerged as a significant pillar of sustainable development in the current global context, and the unpredictability of economic policy has progressively garnered the interest of businesses and government officials as one of the obstacles they must confront. This paper examines how uncertainty in the green economy impacts the green economy's efficacy. The research concentrates on how changes in a particular region can result in geospatial diffusion (spatial spillover), which is a form of spatial spillover wherein the uncertainty of the green economy can impact its efficacy. This paper examines the policy formulation and current state of the green economy across various regions, as well as the diffusion of economic policy uncertainty across geographical areas and the subsequent impact on the green economy's status quo. There is a negative correlation between economic policy uncertainty and green economy efficacy, according to research. There is a spatial spillover effect between economic policy uncertainty and the efficacy of the green economy. Regional variations exist in the impact of economic policy uncertainty on the efficacy of the green economy. The findings indicate that the implementation of AI has a more substantial beneficial effect on carbon emissions. An increase in carbon dioxide emissions poses a growing challenge for the industrial sector in its pursuit of carbon neutrality.

In this review paper, we discuss the use of BERT, one of the most well-liked deep learning-based language models. The model's operation mechanism, key areas of applicability to text analytics tasks, comparisons with related models for each activity, and a description of certain proprietary models are all covered in this work. The data from several dozen original scientific studies that have been published in the last few years and have garnered the greatest interest from the scientific community were systematized in order to prepare this review. All researchers and students who wish to learn about the most recent developments in the field of natural language text analysis may find this survey helpful. Bidirectional Encoder Representations from Transformers, or BERT for short, is the subject of a thorough investigation that we present. The area of natural language processing holds significant importance in the creation of intelligent systems. To do a variety of activities, one must comprehend the sentence's correct meaning in order to produce the desired result. Computers have a hard time understanding languages because of how context constantly changes. The main challenge in natural language processing tasks is getting computers to understand text context, and BERT is seen as a revolution in this regard. It picks up the language and its meaning in a manner that is quite similar to how the human brain processes meaning from sentences. Its capacity to identify a word from both the left and right contexts of a sentence makes it special. A new era in the perception and comprehension of natural languages has been ushered in with the development of BERT, which could help computers understand natural languages more fully. This study aims to provide readers with a deeper knowledge of the BERT language model and how it is applied to different NLP tasks.

: Background: Vaccination against COVID-19 has been the main strategy used by most countries to limit the spread of the virus. However, vaccine uptake has been low in Africa, leading to the implementation of several interventions in order to improve vaccine coverage. This study was conducted due to the lack of information about COVID-19 vaccine coverage and the factors associated with vaccine hesitancy. Methods: This cross-sectional study was carried out in Kinshasa city using multi-stage random sampling. A total of 2160 households were included in the study. The data were analyzed using Stata 15 software. The means and standard deviations were calculated for normally distributed continuous variables, while proportions with their 95% confidence intervals (CIs) were calculated for categorical variables. Pearson’s chi-square test or Fisher’s exact test was used to test the associations between dependent variables and each independent variable. Logistic regression was used to identify the factors associated with hesitancy receiving the COVID-19 vaccination. Results: The majority of respondents were aged between 25 and 34 and 35 and 49 (28.9%). During this study, 15% (95% CI [13.25–17.9]) of respondents had received at least one dose of the COVID-19 vaccine. Among the reasons given for refusing to be vaccinated, most respondents cited concerns about the vaccine being unsafe or causing adverse reactions (45%). Among the reasons given for accepting the vaccine, 26% thought that the vaccine prevented superinfection. The factors associated with hesitancy toward the COVID-19 vaccine were female gender, an age of less than 35 years, and living in non-slum households. Conclusions: Despite the interventions implemented across the country, the reluctance to be vaccinated remains a problem; this could lead to poor health outcomes, especially among the elderly and those with pre-existing conditions. It is important to step up awareness-raising campaigns in the community in order to increase the uptake of vaccination.

Machine learning has become more prevalent as a tool used for biogeochemical analysis in agricultural management. However, a common drawback of machine learning models is the lack of interpretability, as they are black boxes that provide little insight into agricultural management. To overcome this limitation, we compared three tree-based models (decision tree, random forest, and gradient boosting) to explain soil organic matter content through Shapley additive explanations (SHAP). Here, we used nationwide data on field crops, soil, terrain, and climate across South Korea (n = 9,584). Using the SHAP method, we identified common primary controls of the models, for example, regions with precipitation levels above 1400 mm and exchangeable potassium levels exceeding 1 cmol+ kg-1, which favor enhanced organic matter in the soil. Different models identified different impacts of nutrients on the organic matter level in the soil. The SHAP method is practical for assessing whether different machine learning models yield consistent findings in addressing these inquiries. Increasing the explainability of these models means determining essential variables related to soil organic matter management and understanding their associations for specific instances.

Neuroinflammation and brain oxidative stress are recognized as significant contributors to hypertension including salt sensitive hypertension. Extracellular vesicles (EVs) play an essential role in intercellular communication in various situations, including physiological and pathological ones. Based on this evidence, we hypothesized that EVs derived from the brains of hypertensive rats with salt sensitivity could trigger neuroinflammation and oxidative stress during hypertension development. To test this hypothesis, we compared the impact of EVs isolated from the brains of hypertensive Dahl Salt Sensitive rats (DSS) and normotensive Sprague Dawley (SD) rats on inflammatory factors and mitochondrial reactive oxygen species (mtROS) production in primary neuronal cultures and brain cardiovascular relevant regions, including the hypothalamic paraventricular nucleus (PVN) and lamina terminalis (LT). We found that brain-derived DSS-EVs significantly increased mRNA levels of proinflammatory cytokines (PICs) and chemokines, including TNFα, IL1β, CCL2, CCL5, and CCL12, as well as the transcriptional factor NF-κB in neuronal cultures. DSS-EVs also induced oxidative stress in neuronal cultures, as evidenced by elevated NADPH oxidase subunit CYBA coding gene mRNA levels and persistent mtROS elevation. When DSS-EVs were injected into the brains of normal SD rats, mRNA levels of PICs, chemokines, and the chronic neuronal activity marker FOSL1 were significantly increased in the PVN and LT. Furthermore, DSS-EVs caused mtROS elevation in brain PVN and LT, particularly in neurons. Our study reveals a novel role for brain-derived EVs from hypertensive rats in triggering neuroinflammation, upregulating chemokine expression, and inducing excessive ROS production. These findings provide insight into the complex interactions between EVs and hypertension-associated processes, offering potential therapeutic targets for hypertension-linked neurological complications.

An exposition is undertaken to reveal the significant impact of the time-dependent root parameter, on the stability of Pointwise Stationary Fluid Flow Approximation (PSFFA) model of the non-stationary queueing system. This opens new grounds to stability analysis of non-stationary queueing systems. Potential PSFFA applications of IoT are highlighted.