Emerging autologous cellular therapies that utilize platelet-rich plasma (PRP) applications have the potential to play adjunctive roles in a variety of regenerative medicine treatment plans. There is a global unmet need for tissue repair strategies to treat musculoskeletal (MSK) and spinal disorders, osteoarthritis (OA), and patients with chronic complex and recalcitrant wounds. PRP therapy is based on the fact that platelet growth factors (PGFs) support the three phases of wound healing and repair cascade (inflammation, proliferation, remodeling). Many different PRP formulations have been evaluated, originating from human, in vitro, and animal studies. However, recommendations from in vitro and animal research often lead to different clinical outcomes because it is difficult to translate non-clinical study outcomes and methodology recommendations to human clinical treatment protocols. In recent years, progress has been made in understanding PRP technology and the concepts for bioformulation, and new research directives and new indications have been suggested. In this review, we will discuss recent developments regarding PRP preparation and composition regarding platelet dosing, leukocyte activities concerning innate and adaptive immunomodulation, serotonin (5-HT) effects and pain killing. Furthermore, we discuss PRP mechanisms related to inflammation and angiogenesis in tissue repair and regenerative processes. Lastly, we will review the effect of certain drugs on PRP activity, and the combination of PRP and rehabilitation protocols.

Carotenoid and carotenoid esters profiles of peel, pulp and whole fruit tissues of astringent persimmon (Diospyrus kaki Thunb., var. Rojo Brillante) have been characterized in detail and quantified for the first time. Carotenoids were determined by HPLC-PDA-MS/MS (APCI+), using a reverse phase C30 column. A total of 38 carotenoids were identified and quantified, corresponding to 21 free carotenoids (13 xanthophylls and 8 hydrocarbon carotenes) and a total of 17 carotenoid esters. The qualitative profiles are very similar among tissues, differing only in the carotenoids concentration. The most important identified free xanthophylls were (all-E)-β-cryptoxanthin, (all-E)-antheraxanthin, (all-E)-lutein, (all-E)-zeaxanthin and (all-E)-violaxanthin . Hydrocarbon carotenoids found were (all-E)-β-carotene, (all-E)-α-carotene, (9Z)-β-carotene, (13Z)-β-carotene, (9Z)-α-carotene, and lycopene. The most abundant carotenoid esters were (all-E)-lutein-3-O-palmitate, (all-E)-zeaxanthin myristate, (all-E)-zeaxanthin palmitate and (all-E)-cryptoxanthin laurate. Processing by high pressures produced no regular effect on persimmon carotenoids and pasteurization affected negatively the content of all carotenoids from all studied persimmon tissues. This work will contribute to the development of scientific research about the bioaccessibity and bioavailabity of each individual free or esterified persimmon carotenoids in order to a better understanding of the carotenoid compounds impact in human health.

Time-series analysis is a widely used technique across various fields and industries, as it helps in understanding, predicting, and forecasting the behavior of data points over time. These fields include but are not limited to finance, economics, healthcare, transportation, etc. In the case of this paper, we have focused on finance. Predicting future values of financial time series offers several benefits. Accurate forecasts can help investors make better decisions about their investments. To predict future values, deep learning algorithms are commonly used since it is an effective method with complex data. In this study, we conduct a study that investigates the use of different data pre-processing techniques on deep learning algorithms in predicting the time series values. To conduct this experimental study, we utilize an open source software, which using long short-term memory technique as the representative deep learning technique, published in github software code repository platform. With this study, we investigate the effects of autoencoder and discrete wavelet transform data pre-processing techniques in time-series prediction. We discuss the details of the experimental study and report our results. The results show that time series prediction (using backtesting methodology) without any data pre-processing leads to 12.6% for mean absolute percentage error. The results also show that, time series prediction with the data preprocessing techniques (Wavelet Transform and Stacked Autoencoder) lead to 3.4%

This paper designs and fabricates a small-type permanent-magnet linear motor and driver for automation applications. It covers structural design, magnetic circuit analysis, control strategies, and hardware development. Magnetic circuit analysis software JMAG is used for flux density distribution, back electromotive force(back-EMF), and electromagnetic force analysis. To address end effects and cogging force, auxiliary core structures and control strategies are proposed. The motor has a three-phase, six-coil, seven-pole configuration, achieving a peak phase voltage of 3.621 V at 1.0 m/s with a total harmonic distortion(THD) of 0.49 % and the voltages of each phase are balancing a phase voltage error of -0.002 V. The average electromagnetic force is 5.46 N/A. The driver uses a three-phase inverter with voltage space vector pulse width modulation(VSVPWM), dq-axes current closed-loop control, electromagnetic force control, and S-curve motion trajectory control. Simulations with JMAG-RT models in MATLAB/Simulink verify the control strategies. A microcontroller (TMS320F280045) serves as the control core, and a magnetic encoder with a 488 nm resolution provides position feedback. Each phase winding has an equivalent resistance of approximately 3.0 Ω and an inductance of approximately 1.98 mH. The S-curve motion trajectory control achieves a maximum position error of approximately 5.0 μm and a speed ripple of approximately 0.03 m/s at steady speed. With cogging force improvement, the maximum electromagnetic force is 4.90 N, and the q-axis current compensates around 1.05 A based on mover position. S-curve motion trajectory control results in highly stable and responsive performance. Practical tests show that the designed small-type permanent-magnet linear motor and its driver provide efficient, stable, and high-precision solutions for automation applications.

Transient conjugate heat transfer measurements under varying temperature and velocity inlet boundary conditions at incompressible flow conditions were performed for flat plate and ribbed channel geometries. Therefrom local adiabatic wall temperatures and heat transfer coefficients are determined. Those data are analyzed using typical heat transfer correlations, e.g. Nu=CRe^mPr^n determining the local distribution of C and m. It is shown that they are closely linked. A relationship lnC=A−mB is observed with A and B as modeling parameters. They could be related to parameters in log law or power law representations for turbulent boundary layer flows. The parameter m is shown to have a close link to local pressure gradients and therewith near wall streamlines as well as friction factor distributions. A normalization of the C parameter allows to derive a Reynolds analogy factor and therefrom local wall shear stresses.

Many anti-tumor effects of group-specific component-derived macrophage-activating factors (GcMAFs) have been reported; however, the specific mechanisms remain unclear. Controlling tumor-associated macrophages (TAMs) in the tumor microenvironment is essential for cancer treatment. This study assessed the role of GcMAF in macrophage activation, elucidated the mechanisms by which it exerts its anti-tumor effects, and determined its effects on TAMs in the tumor microenvironment. GcMAF-stimulated RAW264.7 macrophages and EMT6 breast tumor cells were co-cultured in a 0.4-µm pore cell culture insert, and gene and protein expression and cell viability were evaluated. DNA microarray analysis of GcMAF-stimulated RAW264.7 cells was conducted. The induction of M2 RAW264.7 cells by interleukin (IL)-4 and IL-13 was analyzed. GcMAF stimulation increased the tumor necrosis factor-α and inducible nitric oxide synthase mRNA and protein levels in RAW264.7 cells but decreased the viability of co-cultured EMT6 cells. These results were confirmed in the M2 RAW264M2.7 cells, suggesting that GcMAF exerts anti-tumor effects by inducing the differentiation of macrophages into the M1 type and reprogramming M2 macrophages to the M1 type. The anti-tumor activity of GcMAF via M2-to-M1 macrophage reprogramming could aid in developing novel cancer immunotherapies.

Laportea bulbifera (Sieb. et Zucc.) Wedd. (L. bulbifera) is a significant plant belonging to the Laportea genus. It has been traditionally used in ethnomedicine to treat various conditions such as rheumatic arthralgia, fractures, falling injuries, nephritis dropsy, limb numbness, pruritus, fatigue-induced internal imbalances, and irregular menstruation. Modern pharmacological studies have confirmed its therapeutic potential, as it exhibits anti-inflammatory, immunosuppressive, analgesic, and anti-rheumatoid arthritis properties. In order to gather in-depth information on L. bulbifera, a comprehensive literature search was conducted using databases such as Web of Science, PubMed, ProQuest, and CNKI. This review aims to provide a comprehensive understanding of L. bulbifera by covering various aspects, including ethnomedicinal uses, geographical distribution, botanical description, phytochemistry, pharmacology, and quality control. By doing so, this review intends to lay a strong foundation and propose new research avenues for the exploration and development of potential applications of L. bulbifera. Thus far, a total of 189 compounds have been isolated and identified from L. bulbifera. These compounds include flavonoids, phenolics, nitrogen compounds, steroids, terpenoids, coumarins, phenylpropanoids, fatty acids and their derivatives, and other compounds. Notably, flavonoids and fatty acids in L. bulbifera have demonstrated remarkable antioxidant and anti-inflammatory properties. Furthermore, these compounds show promising potential in activities such as analgesia, hypoglycemia, and hypolipidemia, as well as toxicity. Despite the extensive fundamental studies conducted on L. bulbifera, further research is still needed to enhance our understanding of its credible mechanism of action and improve its quality control. This necessitates more comprehensive investigations to explore the specific material basis, uncover new mechanisms of action, and refine the quality control methods related to L. bulbifera. By doing so, we could contribute to the further development and utilization of this plant.

The model internal year-to-year variability (hereafter, internal variability) is a significant source of uncertainty when estimating anthropogenic aerosol effective radiative forcing (ERF). In this study, we investigate the impact of internal variability using large ensemble simulations (600 years in total) with the same climate model under prescribed anthropogenic aerosol forcings. A comparison of the magnitudes (i.e., standard deviation, Std) of these influences confirms that internal variability has negligible impacts on the instantaneous radiative forcing (RF) diagnosed by double radiation calls but has considerable impacts on estimating ERF through rapid adjustments (ADJ). Approximately half of the model grids exhibit strong internal variability influence on ERF (Std > 5 W m−2). These strong internal variabilities lead to a 50% probability that 30-year linear change can reach 2 W m−2, and 10-year linear change can reach 4 W m−2. A 50-year simulation can provide a relatively stable annual mean map of ERF (ERF = ADJ + RF), but it fails for ADJ. The statistically significant areas in the annual mean maps of both ERF and ADJ from a 10-year simulation exhibit instability with evident chaotic features. These analyses contribute to the setup of comparative experiments and a more comprehensive understanding of the modeled anthropogenic aerosol ERF.

Cryptosporidiosis is a major human health concern globally. Despite well-established methods, misdiagnosis remains common. Our understanding of the cryptosporidiosis biochemical mechanism remains limited, compounding the difficulty of clinical diagnosis. Here, we used a systems biology approach to investigate the underlying biochemical interactions in C57BL/6J mice infected with Cryptosporidium parvum. Faecal samples were collected daily following infection. Blood, liver tissues and luminal contents were collected 10 days post infection (dpi). High-resolution liquid chromatography and low-resolution gas chromatography coupled with mass spectrometry were used to analyse the proteomes and metabolomes of these samples. Faeces and luminal contents were additionally subjected to 16S rRNA gene sequencing. Univariate and multivariate statistical analysis of the acquired data illustrated altered host and microbial energy pathways during infection. Glycolysis/citrate cycle metabolites were depleted, while short-chain fatty acids and D-amino acids accumulated. An increased abundance of bacteria associated with a stressed gut environment was seen. Host proteins involved in energy pathways and Lactobacillus glyceraldehyde-3-phosphate dehydrogenase were upregulated during cryptosporidiosis. Liver oxalate also increased during infection. Microbiome-parasite relationships were observed to be more influential than the host-parasite association in mediating major biochemical changes in the mouse gut during cryptosporidiosis. Defining this parasite-microbiome interaction is the first step towards building a comprehensive cryptosporidiosis model towards biomarker discovery, and rapid and accurate diagnostics.

COVID-19 has created anxiety not only in individuals but also in health organizations, and countries worldwide. Not a single industry is left un-influenced and loss is being estimated in billions of dollars. The widespread of this pandemic disease has challenged researchers all over the world. Some of the researchers are working to invent its cure while, others are applying computing technologies to stop its spread, by analyzing and identifying patterns for prediction and forecasting. This is by no doubt the hottest area of research for the last 100 years. This survey has targeted the research published in computing sub-domains to combat the pandemic. The survey has clustered the scientific efforts into logical groups: surveillance, metrological effects, social media analytics, image processing and business and economy, analysis and modeling. It will serve as a leading source for the followings: researchers who want to identify what has been achieved in different computing sub-domains, those who need fresh authenticated datasets openly accessible for different research contexts and what are future directions in this area of research. The findings of analysis and modeling can be also useful for government agencies who want to set priorities and formulate policies.

This study presents a new form of velocity distribution in laminar liquid flow in rectangular microchannels using the eigenfunction expansion technique. Darcy friction factor and Poiseuille number are also obtained analytically. Due to the symmetry of the solutions, the effects of changing the aspect ratio from 0 to ∞ are also discussed. Using finite element method (FEM), the obtained analytical results are further compared with the 3D numerical simulations for the rectangular microchannels with different range of aspect ratio and pressure gradient, and excellent agreements were found. These findings provide additional insights in interpreting the results of the pressure-driven flows in finite aspect ratio microchannels, in which very precise comparison with the macroscale theory is crucial.

STUDY QUESTION: Which are the main research interests among patients of assisted reproductive technologies (ART)? SUMMARY ANSWER: Patients identified as research priorities that deserve further investigation: success rates and risks of ART, side-effects of treatments, resources to cope with infertility, effectiveness of alternative therapies, lifestyle habits to protect fertility, oocyte quality and ovarian reserve, and causes of genetic or hereditary infertility. WHAT IS KNOWN ALREADY: The involvement of patients and caregivers in setting research agendas in medicine has gathered significant momentum in the last decade. Patients’ involvement in setting research priorities offers several benefits: improved patient knowledge and awareness of their condition; greater understanding of the medical professionals of the impact of the condition on patients’ quality of life; reduced costs associated with redundant research activities. This is may be also applicable to research in infertility and ART, where patients’ interests have never been explored before. STUDY DESIGN, SIZE, DURATION: This is a cross-sectional study that consists of an anonymous online survey, which was sent up to three times to 2112 patients from 11 fertility centers in 5 countries between January-December 2018. The study design was based on the James Lind Alliance priority setting partnership model, which comprises the identification of patients groups, the exploration of the research agenda, the analysis of collected data and identification of priorities. PARTICIPANTS/MATERIALS, SETTING, METHODS: Overall, 2112 patients were contacted, and 945 surveys were answered (RR: 44.7%). Patients were asked to identify research questions relevant to them in the areas of infertility causes and prevention, fertility treatments (medication and ART), and the emotional aspects of infertility. Answers were categorized in topics and ranked by frequency. A long list of the top-30 research topics was extracted from the aggregate results, from which, a short list of the top-10 research topics was created. At the end, 10 research questions related to each of the 10 research topics were constructed, based on the answers given by patients. MAIN RESULTS AND THE ROLE OF CHANCE: Female (845, 89.4%) and male (100, 10.6%) patients were included. The mean age of patients was 37.8 (SD 1.74). Most of the patients did not have children at the time of the survey (523, 59%), while 51 (5.7%) were pregnant. Sixty (6.3%) patients did not start treatment, 579 (61.3%) were performing a treatment with their own gametes and 304 (32.2%) were treated through gamete donation. Patients were mainly interested in the effectiveness of ART -especially per clinical profile-, side effects of drugs, protection of fertility and prevention of infertility –especially through diet and exercise-, and psychological aspects of the infertility journey. The top-10 research questions (and weight) obtained were: 1) What are the side-effects of ART treatments? (41.6%); 2) What are the most effective methods to cope with infertility from the psychological point of view? (37.2%); 3) What effects could diet have on fertility? (25.9%); 4) What are ART success rates per clinical profile? (25.9%); 5) Are there habits and lifestyle factors that could prevent infertility? (20.0%); 6) What are the long-term risks associated to ART? (18.5%); 7) Are alternative therapies such as acupuncture, yoga, and meditation effective to treat/prevent infertility? (18.5%); 8) What is the impact of exercise on fertility? (15.4%); 9) How does oocytes quantity and quality affect fertility? (9.5%); 10) What are the genetic patterns or hereditary conditions causing/related to infertility? (9.5%). LIMITATIONS, REASONS FOR CAUTION: Although all respondents had attended a fertility center, not all of them were diagnosed as infertile (i.e. single women) and had started treatment at the time of response, while a few were pregnant; their priorities for research might have been influenced by their infertility journey. Also, all participants attended private fertility centers: areas of interest may be different in public settings. WIDER IMPLICATIONS FOR THE FINDINGS: Researchers and clinicians should keep in mind that, in addition to improvement of treatments’ success rates and side-effects, patients greatly value research on causes, prevention and emotional aspects of infertility. As their views might differ from those of medical professionals, patients’ voices should be incorporated in setting infertility research priorities.

Food allergies are common worldwide and have become a major public health concern; more than 220 million people are estimated to suffer from food allergies worldwide. On the other hand, polyphenols, phenolic substances found in plants, have attracted attention for their health-promoting functions, including their anti-allergic effects. In this study, we examined the potential inhibitory effects of 80% ethanol extracts from 22 different vegetables on the degranulation process in RBL-2H3 cells. Our aim was to identify vegetables that could prevent and treat type I allergic diseases. We found strong inhibition of degranulation by the extracts of perilla and chives. Furthermore, we verified the respective efficacy via animal experiments, which revealed that the anaphylactic symptoms caused by ovalbumin (OVA) load were alleviated in OVA allergy model mice that ingested vegetable extracts of perilla and chives. These phenomena were suggested to be caused by induction of suppression in the expression of subunits that constitute the high-affinity IgE receptor, particularly the α-chain of FcεR I. Notably, the anti-allergic effects of vegetables that can be consumed daily are expected to result in the discovery of new anti-immediate allergenic drugs based on the components of these vegetables.

Movement disorders can be associated with various drugs and systemic diseases, posing diagnostic challenges for clinicians. This review explores the spectrum of movement disorders associated with pharmacological agents and medical conditions. Drug-induced movement disorders encompass a broad range of conditions resulting from exposure to medications that affect several neurotransmitters. Neuroleptic medications can lead to tardive dyskinesia, characterized by involuntary, repetitive movements. Antipsychotics and antiemetics, including metoclopramide, may induce acute dystonic reactions. Other drugs, such as dopamine receptor-blocking agents, can contribute to drug-induced parkinsonism. Beyond medications, movement disorders can also arise secondary to systemic diseases. Metabolic disorders like Wilson's disease, characterized by copper accumulation, may manifest as chorea or dystonia. Inflammatory conditions such as rheumatoid arthritis and systemic lupus erythematosus can result in secondary movement disorders due to autoimmune-mediated processes affecting the central nervous system. Movement disorders linked to drugs or systemic diseases often necessitate a thorough clinical evaluation, including detailed medication histories and comprehensive systemic assessments. Neuroimaging, laboratory investigations, and, in some cases, cerebrospinal fluid analyses and electrodiagnostic studies help in establishing accurate diagnoses. Management involves addressing the underlying cause, modifying medications, and employing symptomatic treatments.

Artificial Intelligence (AI) in healthcare has ushered in a revolutionary era by transforming the way we provide care and reduce adverse consequences. This paper explores the field of AI applications in healthcare, including side effect management, streamlined administrative procedures, and customized treatment programs.

This cross-country four-year longitudinal study investigated the development of processing speed throughout primary school education. The analyses were conducted on data collected from 441 schoolchildren in Grades 1, 2, 3 and 4 (aged 6.42 to 11.85 years) in the Kyrgyzstan and Russia. Mixed effects growth modeling was applied to estimate average and individual growth trajectories for processing speed at two cross-country samples. Latent class growth modeling was conducted to identify different types of growth trajectories for processing speed and to compare the distribution of the types within the analyzed samples. According to the results, processing speed significantly increases across primary school years. The trajectory is characterized by nonlinear changes with more intensive growth between Grades 1 and 2, which later slows down until Grade 4. There were no significant cross-country differences in the initial score of processing speed or developmental changes in processing speed across primary school years. The development of processing speed is described by a model with three quadratic growth types but minimally differs. It is concluded that in both samples, the development of processing speed may be characterized by homogeneity, with the most intensive growth from Grade 1 to Grade 2 and subsequent linear improvement until Grade 4.

Vaccination is one of the most effective methods for preventing morbidity and mortality from COVID-19. Vaccine hesitancy has led to a decrease in vaccine uptake; driven by misinformation, fear, and perceptions of vaccine safety. Whole inactivated vaccines have been used in one-fifth of the vaccine recipients in Africa, however there is limited real-world data on their safety. We evaluated the reported side effects and factors associated with reported side effects following vaccination with whole inactivated COVID-19 vaccines - BBiBP-CorV (Sinopharm) and CoronaVac (Sinovac). A quantitative survey evaluating attitudes and side effects from vaccination was administered to 1016 adults presenting at vaccination centers. Two follow-up telephone interviews were conducted to determine side effects after the first and second vaccination dose. Overall, the vaccine was well tolerated; 26.0% and 14.4% reported side effects after the first and second dose respectively. The most frequent local and systemic side effects were pain at the injection site and headaches respectively. Most symptoms were mild, and no participants re-quired hospitalization. Participants who perceived COVID-19 vaccines as safe or had a personal COVID-19 experience were significantly less likely to report side effects. Our findings provide data on the safety and tolerability of whole inactivated COVID-19 vaccines in an African population, providing the necessary data to create effective strategies to increase vaccination and support vaccination campaigns.

Hyper-radiosensitivity (HRS) is the increased sensitivity to low doses of ionizing radiation observed in most cell lines. We previously demonstrated that HRS is permanently abolished in cells irradiated at a low dose rate (LDR), in a mechanism dependent on transforming growth factor β3 (TGF-β3). In this study, we aimed to elucidate the activation and receptor binding of TGF-β3 in this mechanism. T-47D cells were pre-treated with inhibitors of potential receptors and activators of TGF-β3, along with addition of small extracellular vesicles (sEVs) from LDR primed cells, before their radiosensitivity was assessed by the clonogenic assay. The protein content of sEVs from LDR primed cells was analyzed with mass spectrometry. Our results show that sEVs contain TGF-β3 regardless of priming status, but only sEVs from LDR primed cells remove HRS in reporter cells. Inhibition of the matrix metalloproteinase (MMP) family prevents removal of HRS, suggesting an MMP-dependent activation of TGF-β3 in the LDR primed cells. We demonstrate a functional interaction between TGF-β3 and activin receptor like kinase 1 (ALK1), by showing that TGF-β3 removes HRS through ALK1 binding, independent of ALK5 and TGF-βRII. These results are an important contribution to a more comprehensive understanding of the mechanism behind TGF-β3 mediated removal of HRS.

Direct laser writing three-dimensional nano-lithography is an established technique for manufacturing functional 3D micro- and nano-objects via non-linear absorption induced polymerization process. In this Chapter an underlying physical mechanisms taking place during nano-confined polymerization reaction, induced by tightly focused ultra-short laser pulses, are reviewed and discussed. The special attention is paid on the effects that directly impact structuring resolution and minimum achievable feature size. Analysis of possible photo-initiation mechanisms as contributing multi-photon absorption and avalanche ionization in pre-polymers under diverse exposure conditions (wavelength, pulse duration) is presented. Feasible structuring of pure (non-photosensitized) and functional nanoparticles doped polymer precursors is justified and benefits of such materials/structures for microoptics, photonics and cell scaffolds are highlighted. The influence of temperature effects (induced by writing process itself or determined by ambient conditions) on polymerization process, observed in different pre-polymers under diverse exposure regimes is outlined. The further adjustment of the structuring resolution is possible via precise control of light polarization and diffusion assisted radical quenching. The work is concluded with a brief outlook on future challenges and perspectives related to refinement of 3D ultra-fast laser lithography fabrication process in the means of application of diverse post-processing methods and research into novel photo-curable materials including inorganic ones.

Wave energy converter (WEC) arrays deployed in coastal regions may create physical disturbances potentially resulting in environmental stresses. Presently, limited information is available on the nature of these physical disturbance or the resultant effects. A quantitative Spatial Environmental Assessment Tool (SEAT) for evaluating potential effects of wave energy converter (WEC) arrays on nearshore hydrodynamics and sediment transport is presented for the central Oregon coast (USA) through coupled numerical model simulations of an array of WECs. Derived climatological wave conditions were used as inputs to the model to allow for the calculation of risk metrics associated with various hydrodynamic and sediment transport variables such as maximum shear stress, bottom velocity, and change in bed elevation. The risk maps provided simple, quantitative, and spatially-resolved means of evaluating physical changes in the vicinity of a hypothetical WEC array in response to varying wave conditions. Near-field risk of sediment mobility was determined to be moderate in the lee of the densely spaced array, where the potential for increased sediment deposition could result in benthic habitat alteration. Modifications to the nearshore sediment deposition and erosion patterns were observed near headlands and topographic features, which could have implications for littoral sediment transport. The results illustrate the benefits of a risk evaluation tool for facilitating coastal resource management at early market marine renewable energy sites.

Harms of combustible cigarette (CC) use in pregnancy for fetal development are well-studied. Less understood is potential impacts of newer non-combustible cigarette alternatives, including electronic cigarettes (EC). Our goal was to examine whether EC use during pregnancy predicts increased risk of adverse birth outcomes. This retrospective cohort study used data from the Obstetrics Initiative (OBI), a statewide collaborative of 70 maternity hospitals. OBI’s clinical registry of data on nulliparous, term, singleton, vertex fetal presentation pregnancies were from medical records. Three groups of pregnancy cigarette users (Controls (n=26,394), CC (n=2,216), EC (n=493) were compared on birth outcomes, controlling for background differences. Compared to controls, the EC group had significantly lower birth weight, while CC had reduced birthweight and greater rates of arterial cord pH < 7.1. Compared to EC, CC users had higher rates of neonates requiring antibiotics and NICU admission. Growing evidence suggests EC are not safer alternatives to CC, and use during pregnancy should be discouraged. Additional research is needed, as non-significant trends for increased risk of several adverse neonatal outcomes following EC use were found, potentially significant in larger studies with average-risk for adverse pregnancy outcomes and when frequency and timing of EC exposure are considered.

This review paper provides an overview of recent advances in computational fluid dynamics (CFD) simulations of ejector pumps for vacuum generation. It examines various turbulence models, multiphase flow approaches, and numerical techniques employed to capture complex flow phenomena like shock waves, mixing, phase transitions, and heat/mass transfer. Emphasis is placed on comprehensive assessment of flow characteristics within ejectors, including condensation effects such as nucleation, droplet growth, and non-equilibrium conditions. The review highlights efforts in optimizing ejector geometries and operating parameters to enhance the entrainment ratio, a crucial performance metric for ejectors. The studies reviewed encompass diverse working fluids, flow regimes, and geometric configurations, underscoring the significance of ejector technology across various industries. While substantial progress has been made in developing advanced simulation techniques, several challenges persist, including accurate modeling of real gas behavior, phase change kinetics, and coupled heat/mass transfer phenomena. Future research efforts should focus on developing robust multiphase models, implementing advanced turbulence modeling techniques, integrating machine learning based optimization methods, and exploring novel ejector configurations for emerging applications.

Despite being small and simple structured in comparison to their victims, virus particles have the potential to harm severly and even kill highly developed species such as humans. To face upcoming virus pandemics, detailed quantitative biophysical understanding of intracellular virus replication mechanisms is inevitable. Unveiling the relationship of form and function might allow to determine putative attack points relevant for the systematic development of direct antiviral agents (DAA) and potent vaccines. Biophysical investigations of spatio-temporal dynamics of intracellular virus replication so far are rare. We are developing a framework to allow for fully spatio-temporal resolved virus replication dynamics simulations based on partial differential equations models (PDE) and evaluated with advanced numerical mathematical methods on leading supercomputers. This study presents an advanced highly nonlinear model of the genome replication cycle of a specific RNA virus, the Hepatitis C virus (HCV). The diffusion-reaction model mimics the interplay of the major components of the viral RNA (vRNA) cycle, namely non structural viral proteins (NSP), vRNA and a generic host factor. Technically, we couple surface PDEs (sufPDEs) on the 3D embedded 2D Endoplasmatic Reticulum (ER) manifold with PDEs in the 3D membranous web (MW) and cytosol volume. (The MWs are the replication factories growing on the ER induced by NSPs.) The sufPDE/PDE model is evaluated at realistic reconstructed cell geometries which are based on experimental data. The simulations couple the effects of NSPs which are restricted to the ER surface with effects appearing in the volume. The volume effects include the host factor supply from the cytosol and the MW dynamics. Special emphasis is put to the exchange of components between ER surface, MWs and cytosol volume. As the vRNA spatial properties are not fully understood so far in experiment, the model allows for vRNA both restricted to the ER and moving in the cytosol. The visualization of the simulation resembles a look into some sort of fully 3D resolved “in silico microscopes” to mirror and complement in vitro / in vivo experiments for the intracellular vRNA cycle dynamics. The output data are quantitatively consistent with experimental data and provoke advanced experimental studies to validate the model.

This manuscript employs a surface stress-driven nonlocal model to explore the combined effects of long-range interaction and surface energy on higher vibration modes of functionally graded nanobeams. The nanobeam theory, based on Bernoulli-Euler kinematics, incorporates surface effects such as surface elasticity, surface residual stresses, surface density, and rotary inertia. Hamilton's principle is applied to derive the governing equation with size-dependent considerations. The main outcomes of a parametric investigation, considering four different kinematic boundary conditions (Cantilever, Simply-Supported, Clamped-Pinned, and Doubly-Clamped) while varying the nonlocal parameter and material gradient index, are presented and discussed. Additionally, the normalized natural frequencies for the second, third, fourth and fifth modes of vibrations are provided and analyzed for each case under study. The results underscore the model's effectiveness in capturing surface energy effects on the overall dynamic behavior of functionally graded Bernoulli-Euler nanobeams, offering a cost-effective approach for designing and optimizing nano-scaled structures.

All vaccines exhibit specific and nonspecific effects. Specific effects are shown by the efficacy against the target pathogen, while nonspecific effects can be detected by the change in all-cause mortality. The real-world non-COVID-19 all-cause mortality (NCACM) data for the population of England between January 2021 and May 2023 was assessed. All vaccines administered were based on the original Wuhan antigen. Each gender and age group, along with COVID-19 variant shows its own unique NCACM vaccination benefit/disbenefit time profile. The efficacy of COVID-19 vaccination against COVID-19 disease/death per se is undisputed, however, the nonspecific outcomes of COVID–19 vaccination is far more nuanced than have been widely appreciated. This confirms an earlier study on the unanticipated nonspecific effects of influenza vaccination against all-cause winter mortality. Interestingly, a high proportion of NCACM beneficial effects occurred during the first 21 days following COVID-19 vaccination, while the worst example of increased NCACM occurred during the fourth dose of COVID-19 vaccination in 19–40-year-olds for the interval &gt;21 days post vaccination which led to NCACM 3- to 10-times higher than in the unvaccinated. By the time of the Omicron variant, NCACM outcomes in those aged 90+ are mostly adverse. The beneficial nonspecific effects of COVID-19 vaccination increase with age and reach their maximum effect during the second week post vaccination for age groups below 50 years, rising to during the third week for those aged 70+. Finally, we discuss the mechanisms by which COVID-19 vaccination could induce wider nonspecific effects. Most of these mechanisms seem to depend on gene regulation by noncoding RNAs which also interact with mRNAs. We suggest that further international studies are required to discern the nonspecific NCACM effects of the different COVID-19 variants other than the three variants prevalent in the UK, and different types/manufacturer of COVID-19 vaccines which have been employed around the world. We can only speculate regarding the nonspecific effects of the COVID-19 vaccines administered to persons with an asymptomatic infection, and during vaccine waning. Vaccines not only need to be effective against the target pathogen, as primarily determined by antibody production, but need to minimize any unanticipated adverse nonspecific effects against all-cause mortality.

Recently, Mulroney,et.al., demonstrated that Pfizer’s ModRNA Covid vaccine, but not AstraZeneca Covid vaccine, produce aberrant foreign proteins in vivo due to reading frame shift in ribosomes. This phenomenon could elucidate the notable surge in autoimmune diseases following the administration of ModRNA vaccines compared to Influenza vaccines between 2020 and 2023, as found in the VAERS database. These findings bear significant implications for the future application of mRNA technology, emphasizing the necessity of modifying the design of the mRNA sequence to mitigate these defects. Remarkably, Mulroney and collaborators achieved a reduction in frame shift proteins by introducing additional edits to the mRNA sequences. This adjustment is pivotal for rectifying the flawed design of the ModRNA employed by Pfizer. In light of these findings, many advocate for the immediate recall and further investigation of these products. The notion of a "future mRNA-based therapy" should be postponed indefinitely.

The purpose of this article is to present the COVID-19 pandemic disruptions occurring in the supply chain of automotive companies, taking into account the type of business. The specific objectives are: to identify and characterise the types of enterprises operating in automotive supply chains, to identify changes during the pandemic in automotive enterprises, depending on the type of activity, to show disruptions in automotive supply chains and ways to counteract these disadvantages depending on the type of activity. Automotive enterprises operating in Poland were selected for the study purposefully. A random selection method was used to select 500 automotive companies for the study. The data sources were surveys conducted in June 2023 among 500 enterprises in the form of a face-to-face telephone interview. Automotive companies experienced supply chain disruptions, regardless of the type of business. Most often, these were caused by lockdowns and official closures, low stocks of materials and products, and problems with employees. There was no difference by type of business. Disruptions were most often short-lived, up to 1 year. Companies countered disruptions by using mostly operational measures, which were short-lived. Only a small percentage of operators made strategic decisions and countered disruptions over a longer period. The scale of these actions was greater among manufacturers than among dealers and car service companies.

Energy efficiency is, in principle, a simple idea: an output of human value, for example, vehicle-km traveled, divided by the needed input energy. Efficiency improvements are regarded by many as an important means of mitigating not only climate change, but also other environmental problems. Accordingly, many countries have efficiency ratings for appliances and efficiency standards for road vehicles. Despite the vast number of articles published on energy efficiency, few question whether it is a useful or accurate measure in its present form. This review addresses this lack, by a critical review of the literature, not only in energy efficiency, but in other areas of research, such as ‘energy services’, that can help broaden the scope of this idea, both geographically and conceptually. These shortcomings are illustrated in case studies of road passenger transport and buildings. The main findings are that energy efficiency inevitably has an ethical dimension, that feedbacks are more widespread than generally considered, and that conventional efficiency measures omit important energy input items, particularly those concerned with mining of the materials needed for renewable energy plants. Finally, the key results of this review are summarized, and its limitations are discussed, as is the future research needed to overcome these shortcomings.

More than 600 Healthcare workers died due to COVID-19 infection until January 2022 in Ecuador. Even though the COVID-19 vaccines are safe, local, and systemic reactions were reported among physicians. This study aims to analyze the Adverse events (AEs) of COVID-19 vaccines with an emphasis on homologous and heterologous booster doses. An electronic survey was performed in Quito- Ecuador, directed to physicians who were vaccinated with the three doses of COVID-19 vaccines. 210 participants were analyzed after administering any doses of the vaccines. At least one AE was identified in 60.0% (126/210) of the sample after the first dose, 52.40% (110/210) after the second dose, and 75.2% (158/210) after the booster dose. The most frequent AEs were localized pain, myalgia, headache, and fever. At least one drug was used in 44.3% of the population after the first dose, 37.1% after the second dose, and 63.8% in the booster dose. Heterol-ogous booster produces more AEs compared with homologous booster (80.1% vs. 53.8%), and 77.3% of participants reported that interfered with daily activities. Similar studies agree that reactogenicity occurs mainly with heterologous vaccination compared to ho-mologous vaccination. This situation affected physicians’ performance in daily activities and led them to use medication for the symptoms

Bayesian nonlinear mixed effects models for data in the form of continuous, repeated measurements from a population, also known as Bayesian hierarchical nonlinear models, are a popular platform for analysis when interest focuses on individual specific characteristics and relevant uncertainty quantification. Due to the limitation of computational power, this framework was relatively dormant until the late 1980s, but in recent years, the statistical research community saw vigorous development of new methodological and computational techniques for these models, the emergence of software, and wide application of the models in numerous industrial and academic fields. This article presents an overview of the formulation, interpretation, and implementation of Bayesian nonlinear mixed effects models and surveys recent advances and applications.

The X-ray induced spin crossover transition of an Fe(II) molecular thin film in the presence and absence of a magnetic field has been investigated. The thermal activation energy barrier in the soft X-ray activation of the spin crossover transition for [Fe{H2B(pz)2}2(bipy)] molecular thin films is reduced in the presence of an applied magnetic field, as measured through X-ray absorption spectroscopy at various temperatures. The influence of a 1.8 T magnetic field is sufficient to cause deviations from the expected exponential spin state transition behavior that is measured in the field free case. We find that orbital moment diminishes with increasing temperature, relative to the spin moment in the vicinity of room temperature.

(1) Background: To investigate the dynamic issues behind international variation in EWM. (2) A rolling EWM calculation is used to reveal seasonal changes in the EWM calculation and is especially relevant nearer to the equator. (3) Results: In addition to latitude country specific factors determine EWM. Females generally show higher EWM mainly due to respiratory conditions. The EWM for respiratory conditions in England and Wales ranges from 44% to 83% which is about double the all-cause mortality equivalent. Age has a profound effect on EWM with a peak in puberty and then increasing EWM at old age. The gap between male and female EWM seems to act as a diagnostic tool reflecting the infectious/metrological mix in each winter. Additional difference due to ethnicity are also observed. An EWM equivalent calculation for sickness absence demonstrates how additional health-related variables can be linked to EWM. (4) Conclusions: EWM does not reach a peak at the same time each year, especially so in the tropics. Countries midway between the equator and the poles show highest EWM. Differences between the genders are highly significant and seem to vary according to the mix of variables active each winter. Pandemic influenza does not elevate EWM, although seasonal influenza plays a part each winter.

The objective of the study was to examine the effects of perceived stress on depression and subsequently to examine the effects of depression on alcohol use disorders. The data were obtained by an electronic questionnaire survey during the coronavirus disease 2019 (COVID-19) pandemic (n=1523 Slovak college students). Descriptive, regression and correlation analysis were used in the analytical processing, while the analyses included students' scores in three diagnostic tools (Perceived Stress Scale (PSS), Patient Health Questionnaire for depression (PHQ 9) and Alcohol Use Disorders Identification Test (AUDIT)), as well as gender and income characteristics. The PSS identified an increased level of perceived stress in female students, in contrast, the AUDIT showed an increased level of alcohol use disorders in male students. Differences in mental and behavioural disorders between the gender and income categories were significant in most of the analysed cases. In terms of gender-income characteristics, it was possible to confirm a significant positive effect of the PSS score on the PHQ 9 score, as well as a significant positive effect of the PHQ 9 score on the AUDIT score. As a result, efforts to reduce stress will be reflected in a reduction of depressive disorders as well as a reduction of excessive alcohol consumption among students.

Magnetic nanoparticles are met across many biological species ranging from magnetosensitive bacteria, fishes, bees, bats, rats, birds, to humans. They can be both of biogenetic origin and due to environmental contamination, being either in paramagnetic or ferromagnetic state. The energy of such naturally occurring single-domain magnetic nanoparticles can reach up to 10-20 room k_BT in the magnetic field of the Earth, which naturally led to supposition that they can serve as sensory elements in various animals. This work explores within a stochastic modeling framework a fascinating hypothesis of magnetosensitive ion channels with magnetic nanoparticles serving as sensory elements, especially, how realistic it is given a highly dissipative viscoelastic interior of living cells and typical sizes of nanoparticles possibly involved.

Cardiotonic steroids (CTS) are a group of steroid compounds derived from certain plants and animals. CTS are selective inhibitors of Na,K-ATPase, so for a long time they were widely used for medical purposes to treat heart failure and some other diseases. However, over time, doctors gradually began to refuse this group of drugs due to their narrow therapeutic range and a number of serious side effects. However, in parallel with the rise and fall of interest in CTS as a drug, interest in them as a single class of high-affinity Na,K-ATPase inhibitors has only increased. Numerous data on the effect of CTS on signaling cascades and cell viability made impelling a search for a rationale for the existence of such a subtle biological regulator. A large number of studies devoted to the potential use of CTS in the treatment of neurodegenerative, oncological, immune and other diseases "revitalized" the already "written off" group of the drugs. If initially the role of exogenous (mainly plant origin) CTS was studied, then by the 90s of the XX century the study of the role of endogenous CTS and their regulatory effects became a popular trend in biology and physiology. The role of endogenous CTS was studied in details in the pathogenesis of cardiovascular diseases [1]. A large number of researchers have unanimously stated that endogenous CTS are very complex regulators of the development of pathological processes; however, the exact cause-and-effect relationship that would unambiguously explain the processes of synthesis, utilization, and the role of endogenous CTS has not yet been established. The effects of CTS in the frame of various regulatory schemes have been described, but the predominant number of studies was devoted to arterial hypertension, heart and renal failure, cancer [2–4], aging [5,6], and neuroinflammation. The effects of both endo- and exogenous CTS on blood cells and have been studied to a much lesser extent.

Spin-orbit coupling and nonparaxiality effects during propagation of vortex vector light beams in a cylindrical graded-index waveguide are investigated by solving the full three-component field Maxwell’s equations. Symmetry breaking effects for left- and right-handed circularly polarized vortex light beams propagating in a rotationally symmetric graded-index optical fiber are considered. The mode-group delay in a graded-index fiber due to spin-orbit interaction is demonstrated. It is shown that the relative delay times between vortex pulses of opposite circular polarizations of the order of 10 ps/km can be observed in graded-index fibers for high-order topological charges.

The DEP force is usually calculated from the object’s point of view using the interaction of the object’s induced dipole moment with the inducing field. Recently, we described the DEP behavior of high- and low-conductive 200-µm 2D spheres in a square 1x1mm chamber with a plane-versus-plane electrode configuration from the system’s point of view. Here we extend our previous considerations to the plane-versus-plane and pointed-versus-pointed electrode configurations. The trajectories of the sphere center and the corresponding DEP forces were calculated from the gradient of the system’s overall energy dissipation for given starting points. The dissipation’s dependence on the sphere’s position in the chamber is described by the numerical “conductance field”, which is the DC equivalent of the capacitive charge-work field. While the plane-versus-plane electrode configuration is field-gradient free without an object, the presence of the highly or low-conductive spheres generates structures in the conductance fields, which result in very similar DEP trajectories. For both electrode configurations, the model describes trajectories with multiple endpoints, watersheds, and saddle points, very high attractive and repulsive forces in front of pointed electrodes, and the effect of mirror charges. Because the model accounts for inhomogeneous polarization within the objects, the approach allows the modeling of the complicated interplay of attractive and repulsive forces near electrode surfaces and chamber edges. Non-reversible DEP forces or asymmetric magnitudes for the highly and low-conductive spheres in large areas of the chamber indicate the presence of higher-order moments, mirror charges, etc.

Thyroid hormones, their metabolites and synthetic analogues are potential anti-steatotic drug candidates considering that subclinical and manifest hypothyroidism is associated with hepatic lipid accumulation, non-alcoholic fatty liver disease, and its pandemic sequelae. Thyromimetically active compounds stimulate hepatic lipogenesis, fatty acid beta-oxidation, cholesterol metabolism and metabolic pathways of glucose homeostasis. Many of these effects are mediated by T3 receptor β1-dependent modulation of transcription. However, rapid non-canonical mitochondrial effects have also been reported, especially for the metabolite 3,5-diiodothyronine (3,5-T2), which does not elicit the full spectrum of “thyromimetic” actions inherent to T3. Most preclinical studies in rodent models of obesity and first human clinical trials are promising with respect to the antisteatotic hepatic effects, but potent agents exhibit unwanted thyromimetic effects on the heart and/or suppress feedback regulation of the hypothalamus-pituitary-thyroid-periphery axis and the fine-tuned thyroid hormone system. This review focusses on 3,5-T2 effects on hepatic lipid and glucose metabolism and (non-)canonical mechanisms of action including its mitochondrial targets. Various high fat diet animal models with distinct thyroid hormone status indicate species- and dose-dependent efficiency of 3,5-T2 and its synthetic analogue TRC150094. No convincing evidence has been presented for their clinical use in prevention or treatment of obesity and related metabolic conditions.

A practical wind farm controller for production maximisation based on coordinated control is presented. The farm controller emphasises computational efficiency without compromising accuracy. The controller combines Particle Swarm Optimisation (PSO) with a turbulence intensity based Jensen wake model (TI-JM) for exploiting the benefits of either curtailing upstream turbines using coefficient of power ($C_P$) or deflecting wakes by applying yaw-offsets for maximising net farm production. First, TI-JM is evaluated using convention control benchmarking WindPRO and real time SCADA data from three operating wind farms. Then the optimized strategies are evaluated using simulations based on TI-JM and PSO. The innovative control strategies can optimise a medium size wind farm, Lillgrund consisting of 48 wind turbines, requiring less than 50 seconds for a single simulation, increasing farm efficiency up to a maximum of 6% in full wake conditions.

The recent Zika virus (ZIKV) outbreak in Americas surprised all of us because of its rapid spread and association with neurologic disorders including fetal microcephaly, brain and ocular anomalies and Guillain-Barré syndrome. In responding to this global health outcry, unprecedented and world-wide efforts are taking place to study the ZIKV etiology. Much have been learned about this virus in the areas of epidemiology, clinical manifestation, viral sequences and protein structures, as well as effects of ZIKV infection on fetal brain development and microcephaly. However, the molecular mechanism underlying ZIKV-mediated neurologic disorders remains elusive. Some critical questions include: 1) what type of virologic changes has taken place that increased the viral virulence? 2) which ZIKV protein(s) is responsible for the enhanced viral pathogenicity? And 3) how the newly adapted and pathogenic ZIKV strains alter their interactions with host cells leading to neurologic disorders? The goal of this review is to explore the molecular insights into the ZIKV-host interactions with special focuses on host cell receptor usage for viral entry, host cellular and immune antiviral responses, ZIKV counteraction and ZIKV-induced cytopathic effects. Our hope with this literature review is to inspire additional studies focusing on molecular studies of ZIKV-host Interactions.

The cause of sarcoidosis is unknown, and vitamin D is contraindicated to treat the condition. We therefore ask what causes sarcoidosis and why vitamin D can be dangerous for those so afflicted. We propose a contrary hypothesis: sarcoidosis is a physiological process of defense against cancer that requires the substrate vitamin D. We tested this hypothesis, finding many case reports involving sarcoidosis and cancer—further cases of cancer mimicry by sarcoidosis. Several reports describe spontaneous healing of cancer in the presence of sarcoidosis. In the context of the granulomas of sarcoidosis, monocytes are the site of vitamin D release. Furthermore, active vitamin D can control cancer cells by using the vitamin D receptors of the nucleus. That granulomas consistently do not caseate is explained as a confrontation with human molecules and the cancer cells’ complete absorption. The striking fact that granulomas of sarcoidosis mostly lack cancerous cells is interpreted as a result of a well-functioning sarcoidosis process. We view the typical sarcoidosis monocytic synthesis of active vitamin D as a successful defense against cancer: a theory we call the “endogenous program organizing cancer apoptosis” (EPOCA).

Constructing an innovation system centered on new-quality productivity is key to achieving China's technological independence and high-quality development, especially against the backdrop of rapid advancements in artificial intelligence. This article utilizes provincial panel data from China spanning 2010 to 2022 and applies kernel density estimation and the Moran's I index to study the spatiotemporal evolution of artificial intelligence and new-quality productivity. The findings indicate a clustering trend in the development of both factors across regions. Causal empirical analysis using a two-way fixed-effects model reveals that artificial intelligence positively influences new-quality productivity, with conclusions validated by robustness and endogeneity tests.

Self-sustained learning (SSL) is considered a crucial factor in promoting students’ long-term learning and development in a sustainable society. To deepen the understanding of SSL, especially in the context of learning English as a second language, the current study examined the influence of intercultural communicative skills, language mindset, and positive L2 self on SSL in English learning among 1,238 college students in China. The results showed that students not only had a strong language mindset, positive L2 self, and intercultural communicative skills but also scored higher in long-term self-sustained English learning. Findings from the Structural Equation Modeling indicated that both language mindset and intercultural communicative skills positively predicted positive L2 self and self-sustained English learning. Furthermore, language mindset and intercultural communicative skills had an indirect impact on self-sustained English learning through positive L2 self. These findings suggest that to promote English learners’ SSL, instructors should help facilitate students’ intercultural communicative skills and foster a growth language mindset, as well as positive language learning beliefs.

Pituitary adenylate cyclase-activating polypeptide receptor 1 (PAC1-R) has a higher affinity for pituitary adenylate cyclase- activating polypeptide (PACAP) than for vasoactive intestinal peptide (VIP). PACAP exerts its neuroprotective effects through PAC1-R. PAC1-R has become a target for drug development, and we targeted PAC1-R to screen small positive allosteric modulator 1 (SPAM1). SPAM1 has a neuroprotective effects, and in the D-galactose (D-gal) mouse model, SPAM1 improved the structure of the hippocampal dentate gyrus and restored the number of neurons. Compared with D-gal model mice, SPAM1 treatment upregulated the expression of Sirtuin 6 (SIRT6) and Lamin B1, and downregulated the expression of YinYang 1 (YY1) and p16. Consistent with this, the same results were obtained in senescent RGC-5 cells. Meanwhile, SPAM1 was also found to up-regulate SIRT6 and down-regulate YY1 expression in normal RGC-5 cells. Then, we further explored the mechanism of SPAM1 neuroprotection by whole transcriptome sequencing and proteomic analysis, and found that SPAM is involved in the longevity regulating pathway, and confirmed the up-regulation of neurofilament light polypeptide and neurofilament medium polypeptide by western blot, thus laying a pharmacological foundation for SPAM1 as a therapeutic agent for neurodegenerative diseases. polypeptide and neurofilament medium polypeptide. Thus, it lays a pharmacological foundation for SPAM1 as a therapeutic drug for neurodegenerative diseases.

We investigated and quantified bacterial accumulation in facemasks used by the general population, using 16S rRNA (Sanger Sequencing), culture and biochemical analysis along with Rose Bengal staining. Additionally, a systematic overview of the literature on face mask contamination was undertaken. We found an average bacterial load of 4.24 × 10⁴ CFU recovered/mask, with a maximum load of 2.85 × 10⁵ CFU. This maximum is 310 times higher than the limit value for contamination of ventilation system outlet surfaces specified by the German standard VDI 6022. Biochemical and molecular identification predominantly found Staphylococcus species (80%), including Staphylococcus aureus, along with endospore-forming Bacillus spp. Literature reports also indicate contamination of masks by bacterial and fungal opportunists of the genera Acinetobacter, Aspergillus, Alternaria, Bacillus, Cadosporium, Candida, Escherichia, Enterobacter, Enterococcus, Klebsiella (including K. pneumoniae), Micrococcus, Microsporum, Mucor, Pseudomonas, Staphylococcus and Streptococcus. Bacterial counts increase linearly with wearing duration, and prolonged use may affect the skin and respiratory microbiomes, promoting consequential eye, skin, oral and airway conditions. These aspects underscore the urgent need for further research and a risk-benefit analysis in respect of mask use, particularly given their unproven efficacy in disrupting the transmission of respiratory viruses and their adverse social consequences.

Background: This study retrospective evaluates patients with stage IV melanoma treated with Nivolumab and Ipilimumab combination therapy from two regional oncology centers from Romania between the years of 2019 up to the end of 2022. Methods: The data were analyzed in SAS for Windows, V9.4. The survival curves were estimated using the Kaplan-Meier method, and survival distributions were compared with log-rank test. The effects of the main clinical and pathological variables on OS and PFS were investigated with Cox regression. Results: Kaplan-Meier curve of OS in all evaluable patients enrolled in the study resulted in a median OS of 346 days (95% CI: 150-NA) and a median PFS of 211 days (95% CI: 113-430). 45.3% of the patients experienced adverse events during the Nivolumab + Ipilimumab treatment with some of them having multiple organ systems involved. Discussion: The OS values were lower than that reported in approval clinical trials, but the results show a marked improvement when comparing to results obtained by chemotherapy regimens previously used in these scenarios. Conclusion: This study provides real-world insights into the survival data and safety profiles of combination therapy with anti-PD-1 antibodies and anti-CTLA-4 antibodies.

This work presents results of property researches of fabricated samples of silica few-mode optical fiber (FMF) with induced chirality under twisting 10 and 66 revolutions per meter, core diameter 11 µm, typical “telecommunication” cladding diameter 125 µm and improved height of quasi-step refractive index profile. Proposed FMF supports 4 guided modes over “C”-band. We represent results of computed characteristics, as well as experimentally measured spectral responses of laser-excited optical signals, including researches and analysis of few-mode effects, occurring after fiber Bragg grating writing.

The assessment of welfare and disease progression in animal models is critical. Most tools rely on evaluating individual subjects, whereas social behaviors, also sensitive to acute illness, chronic diseases, or mental health, are scarcely monitored because of their complexity, are invasive, and time-consuming. We propose the evaluation of social nesting, a species-typical behavior naturally occurring in standard housing conditions, for such behavioral monitoring. We provide an example of its use to evaluate social deficits and the long-term effects of neonatal sensorial stimulation in male and female adult 3xTg-AD mice for Alzheimer's disease compared to sex- and age-matched NTg counterparts with normal aging. Social nesting was sensitive to genotype (worse in 3xTg-AD mice), sex (worse in males), profile, and treatment (distinct temporal patterns, time to observe the maximum score and incidence of the perfect nest). Since social nesting can be easily included in housing routines, this neuroethological approach can be useful for animal's welfare, monitoring the disease's progress, and evaluating potential risk factors and effects of preventive/therapeutical strategies. Finally, the non-invasive, painless, simple, short time and low-cost features of this home-cage monitoring are advantages that make social nesting feasible to be successfully implemented in most animal department settings.

Based on the minimum conduction band edge caused by the minimum channel potential resulting from the quasi-3D scaling theory and the 3D density of state (DOS) accompanied by the Fermi-Dirac distribution function on the source and drain sides, a unified semiconductor-device-physics-based ballistic model is developed for the threshold voltage of modern multiple-gate (MG) transistors, including FinFET, W-gate MOSFET, and Nanosheet (NS) MOSFET. It is shown that the thin silicon, thin gate oxide, and high work function will alleviate the ballistic effects and resist the threshold voltage degradation. Besides, as the device dimension is further reduced to give rise to the 2D/1D DOS, the lowest conduction band edge is hence increased to resist the threshold voltage degradation. The nanosheet MOSFET exhibits the largest threshold voltage among the three transistors due to the smallest minimum conduction band edge caused by the quasi-3D minimum channel potential. Compared to P-type MOSFET (P-FET), the N-FET shows more threshold voltage because the electron has a more effective mass than the hole

Biological control, a well-established plant protection method, has garnered substantial attention in recent decades. Various approaches, including biological control agents (BCA), catch crops, biofumigation, sticky traps, and pheromones, have been extensively explored. While the effectiveness of these methods varies depending on specific circumstances, their collective significance has grown amid mounting pressures to curtail or eliminate conventional synthetic plant protection products. Previous review articles have highlighted the synergistic benefits of using two or more BCAs simultaneously, yet limited information exists regarding the concurrent use of diverse biological control methods. This comprehensive review incorporates a thorough literature search to assess the synergistic potential of concurrently employing two or more of these methods, followed by a discussion on perspectives of holistic management and mimicking of complex natural systems, shedding light on the vast potential and need for further research in this domain.

Many studies have demonstrated hydrogen's therapeutic and preventive effects on various diseases. Its selective antioxidant properties against hydroxyl radicals, which are responsible for the indirect effects of ionizing radiation, may make it worthy of attention as a new radio-protector. We recently developed new hydrogen water that is more stable and has higher antioxidant activity by using ultra-fine bubbles. In this study, female C57BL/6J mice given ad libitum access to ultra-fine bubble hydrogen water (UBHW) were subjected to whole-body irradiation (WBI) with X-rays, and the radio-protective effect of UBHW was evaluated. Sub-lethal WBI resulted in a 30-day survival rate of 100% in UBHW-fed mice, compared with 37% in control mice. In the case of lethal WBI, while the control mice died out in about 3 weeks, the 30-day survival rate improved to 40% by UBHW due to the high scavenging activity of hydroxy radicals. Twenty-six serum proteins involved in inflammatory and immune responses were significantly identified in UBHW-fed mice by proteomics, and UBHW may enhance and regulate these functions, resulting in reduced damage in mice exposed to WBI. We conclude that UBHW has good potential in radio-protection, with evidence that warrants further research efforts in this field.

This study investigates the application of deep residual networks for predicting the dynamics of interacting three-dimensional rigid bodies. We present a framework combining a 3D physics simulator implemented in C++ with a deep learning model constructed using PyTorch. The simulator generates training data encompassing linear and angular motion, elastic collisions, fluid friction, gravitational effects, and damping. Our deep residual network, consisting of an input layer, multiple residual blocks, and an output layer, is designed to handle the complexities of 3D dynamics. We evaluate the network's performance using a dataset of 10,000 simulated scenarios, each involving 3-5 interacting rigid bodies. The model achieves a mean squared error of 0.015 for position predictions and 0.022 for orientation predictions, representing a 25% improvement over baseline methods. Our results demonstrate the network's ability to capture intricate physical interactions, with particular success in predicting elastic collisions and rotational dynamics. This work significantly contributes to physics-informed machine learning by showcasing the immense potential of deep residual networks in modeling complex 3D physical systems. We discuss our approach's limitations and propose future directions for improving generalization to more diverse object shapes and materials.

Following the coronavirus disease 2019 (COVID-19) pandemic, several studies have examined the possibility of correlating the virulence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19, to the climatic conditions of the involved sites; however, inconclusive results have been generally obtained. Although either air temperature or humidity cannot be independently correlated with virus viability, a strong relationship between SARS-CoV-2 virulence and the specific enthalpy of moist air appears to exist, as confirmed by extensive data analysis. Given this framework, the present study involves a detailed investigation based on the first 20–30 days of the epidemic before public health interventions in 30 selected Italian provinces with rather different climates, here assumed as being representative of what happened in the country from North to South, of the relationship between COVID-19 distributions and the climatic conditions recorded at each site before the pandemic outbreak. Accordingly, a correlating equation between the incidence rate of the pandemic and the average specific enthalpy of atmospheric air was developed, and an enthalpy-based seasonal virulence risk scale was proposed as a tool to predict the potential danger of COVID-19 spread due to the persistence of weather conditions favorable to SARS-CoV-2 viability. For practical applications, a conclusive risk chart expressed in terms of coupled temperatures and relative humidity (RH) values was provided, showing that safer conditions occur in case of higher RH at the highest temperatures, and of lower RH at the lowest temperatures. The proposed risk scale was in agreement with the available infectivity data in the literature for a number of cities around the world.

In the context of intelligent and integrative lighting, in addition to the need for color quality and brightness, the non-visual effect is essential. This refers to the retinal ganglion cells (ipRGCs) and their function, first proposed in 1927. The melanopsin action spectrum has been published in CIE S 026/E: 2018 with the corresponding melanopic equivalent daylight (D65) illuminance (mEDI), melanopic daylight (D65) efficacy ratio (mDER) and 4 other parameters. Due to the importance of mEDI and mDER, this work synthesizes a simple computational model of mDER as the main research objective, based on a database of 4214 practical spectral power distributions (SPDs) of daylight, conventional, LED, and mixed light sources. In addition to the high correlation coefficient R2 of 0.96795 and the 97% confidence offset of 0.0067802, the feasibility of the mDER model in intelligent and integrated lighting applications has been extensively tested and validated. The uncertainty between the mEDI calculated directly from the spectra and that obtained by processing the RGB sensor and applying the mDER model has reached ± 3.3% after an appropriate matrixing process and proper illumination characterization combined with the successful mDER calculation model. This result opens the potential of low-cost RGB sensors for applications in intelligent and integrative lighting systems to optimize and compensate the non-visual effective parameter mEDI using daylight and artificial light in indoor spaces. The goal of the research on RGB sensors and the corresponding processing method are also presented and their feasibility is methodically demonstrated. A comprehensive investigation with a huge amount of color sensor sensitivities is necessary in a future work of other researches.

The Bacillus Calmette-Guérin (BCG) vaccine has been used for over one hundred years to protect against the most lethal infectious agent in human history, tuberculosis. Over four billion BCG doses have been given and, worldwide, most newborns receive BCG. A few countries, including the United States, did not adopt the WHO recommendation for routine use of BCG. Moreover, within the past several decades, most of Western Europe and Australia, having originally employed routine BCG, have discontinued its use. This review article articulates the impacts of those decisions. The associated consequences include increased tuberculosis, increased infections caused by non-tuberculous mycobacteria (NTM), increased autoimmune disease (autoimmune diabetes and multiple sclerosis) and increased neurodegenerative disease (Parkinson’s disease and Alzheimer’s disease). This review also offers an emerged zoonotic pathogen, Mycobacterium avium ss. paratuberculosis (MAP) as a mostly unrecognized NTM that may have a causal role in some, if not all, of these diseases. Current clinical trials with BCG for varied infectious, autoimmune and neurodegenerative diseases have brought this century-old vaccine to the fore due to its presumed immuno-modulating capacity. With its historic success and strong safety profile, the new and novel applications for BCG may lead to its universal use –putting the Western World back onto the road not taken.

This paper explores the Wilsonian renormalization group of probe-D-branes, focusing on the Dirac-Born-Infeld (DBI) action. The analysis involves deriving the constant of motion and formulating the Wilsonian renormalization group equation. The study extends to the infrared regime, considering both zero and non-zero temperatures. Additionally, thermodynamic aspects related to the functional form of the grand potential are discussed. The investigation provides insights into the renormalization of probe-D-branes and their thermodynamic properties.

Gilbert's syndrome (GS) is a common hereditary condition characterized by mild increases in serum bilirubin levels due to inherited defects in bilirubin metabolism. This review, based on data from peer-reviewed articles and journals spanning from 1977 to January 2024, provides a comprehensive overview of over four decades of research on GS. Early studies primarily focused on defining the clinical and genetic characteristics of the syndrome, laying the foundation for subsequent investigations. More recent research has delved into the genetic mechanisms underlying the reduced expression of bilirubin UDP-glucuronosyltransferase, which has significantly enhanced our understanding of the pathogenesis of GS. Furthermore, recent studies have shed light on the clinical implications of GS, including its association with non-alcoholic fatty liver disease and mortality risk, highlighting the complex interplay between genetic factors, bilirubin metabolism, and clinical outcomes. Despite its generally benign nature, thorough research is essential to fully understand the impact of GS on patients' lives. This review emphasizes the importance of ongoing research to deepen our understanding of GS and its broader implications.

This paper introduces an innovative nanotechnology-based approach that provides a pathway to enhance the energy release efficiency of nanoenergetic materials (nEMs) by harnessing self-synchronized collective atomic vibrations and phonon wave resonance within the transition domains between nanocomponents, without altering the material composition. The key innovation involves incorporating finely-tuned 2D-ordered linear-chain carbon-based multilayer nano-enhanced interfaces as programmable nanodevices into the transition domains using advanced multistage processing and assembly techniques. These programmable nanodevices enable precise control over self-synchronized collective atomic vibrations and phonon wave propagation, leading to synergistic effects. To activate and optimize these effects, a combination of various methods is employed, including energy-driven initiation of allotropic phase transformations, surface acoustic wave-assisted micro/nano-manipulation, heteroatom doping, directed self-assembly using high-frequency electromagnetic fields, and data-driven inverse design approaches. By leveraging a data-driven inverse design strategy and uncovering hidden structure-property relationships, we maximize energy release efficiency using the carbon nano-materials genome approach derived from multifactorial neural network-based predictive models. This approach not only unlocks new functionalities in nEMs but also improves environmental performance and safety levels. By pioneering transformative pathways for nEMs through harnessing phonon wave resonance in low-dimensional nanocarbon transition interfaces, this research brings significant advancements in the field.

Power sources that can consistently deliver high levels of energy over extended periods are crucial for various space applications. Among the many methods of energy generation, direct heat-to-electricity conversion without intermediate steps or moving components shows particular promise but also presents significant challenges. The aim of this research is to address these challenges by enhancing the energy efficiency of thermionic conversion, which transforms thermal energy into electrical energy, through the development and utilization of a novel class of emission nanomaterials known as multilayer carbyne-enriched 3D-shaped nano-interfaces. By manipulating the topological, physicochemical, and functional characteristics of these interfaces, we seek to optimize their thermionic conversion capabilities. Building on the recent discovery of collective atomic vibrations called phonon waves within transition domains of multilayer nanostructures, we have devised a new approach to enhance the efficiency of thermionic energy converters. This involves unlocking the predictive functionality of 2D-ordered linear-chain carbon-based multilayer emitters through the excitation and fine-tuning of collective atomic vibrations and nanoarchitecture. To achieve this, we propose employing a combination of techniques that leverage interface effects, enable phonon wave propagation, facilitate energy exchange, and capitalize on synergistic effects offered by the multilayer nano-enhanced interfaces. The resulting devices for thermionic energy conversion have the potential to significantly surpass the efficiency of existing plasma thermionic converters by several orders of magnitude. Moreover, these electricity-generating sources based on thermionic conversion represent fundamental options for the advancement of Lunar and Martian research missions, opening up possibilities for sustainable energy production in extraterrestrial environments.

We delve into nonrelativistic quantum electrodynamics within a background magnetic field, ensuring gauge invariance via a vector potential. Our exploration extends to the Lagrangian, which incorporates electron self-interactions and electromagnetic field interactions. Through the path integral formalism, we elucidate the effective action, with a specific focus on the photon propagator and screening effects. Examining density and current components reveals Laurent expansions in the hydrodynamic limit. The equations of motion in real space are derived, leading to discussions on phenomena such as Poiseuille-like flow and the Navier-Stokes equation. To ground our theoretical framework at practical contexts, we consider applications such as the fluid dynamics at binary star systems. Depending on the velocity of the expelled fluid, our analysis allows for both nonrelativistic and relativistic treatments, providing a versatile tool for understanding the intricacies of fluid behavior at astrophysical scenarios. Additionally, we recognize that at the presence of a magnetic field, magnetohydrodynamics becomes crucial. While our current focus is at nonrelativistic quantum electrodynamics, the insights gained here contribute to a broader understanding, offering a comprehensive foundation for quantum electrodynamics analysis at diverse physical systems.