Smart farm is a technology that greatly helps improve the productivity and quality of crops and is being actively introduced into indoor environments such as green houses. However, it has not yet been distributed to field-grown crops. The main reason is that, unlike indoor environments, it is very difficult to collect sensor data for monitoring the growth environment of crops in open fields where weather conditions change significantly and power supply is difficult. Additionally, because various sensors are used, the data formats of the devices are different, making it difficult to process. This paper presents a field crop growth environment monitoring and big data analysis system. The proposed system first solves power supply and data communication problems using solar power generation and LPWA technology. Additionally, based on the oneM2M architecture, data from various sensors is transmitted to the server using standardized technology. The transmitted data is stored and managed on the server as big data, and can be used to predict the production and quality of field-grown crops and take appropriate measures. The proposed system is expected to create an environment optimized for the growth of field crops and help prevent and manage diseases.

We offered the circuit of a discrete analog filter (DAF) low frequencies of second-order on switchable capacitors, which differs from the known ones in that three capacitors with one terminal are connected to a common bus, and the frequency of the DAF pole depends not only on the ratio of the capacitances of the frequency-setting capacitors, but also on the ratio of resistances two additional resistors in the feedback. This allows at constant values ​​of the capacitances and a fixed switching frequency of electronic switches, control the pole frequency by changing the resistance ratio of additional resistors. Computer simulation of the developed circuit was performed in the Micro-Cap environment. It has been established that the DAF has a transmission coefficient close to minus one at very low frequencies and a transmission coefficient close to zero at higher frequencies.

For many years, energy monitoring at the most disaggregate level has been mainly sought through the idea of Non-Intrusive Load Monitoring (NILM). Nevertheless, a practical application of this concept in the residential sector should address the underlying concerns raised by the technical specifications of case studies. From one side, such an operation must handle common matters related to the essence of any NILM system. Although this aspect has been thoroughly investigated by basic research, it is limited to the properties of public datasets. On the other side, it must deal with specific concerns corresponding to uncommon situations. These circumstances impose further restrictions on existent NILM schemes, however, they have been overlooked due to the lack of pertinent databases to scrutinize. Accordingly, this paper presents applied research on a potential solution to NILM for Quebec residences. It carries out a relevant investigation into the multi-faceted nature of this problem in order to reveal barriers to feasible implementations in the context of Quebec. This work commences with a concise discussion about the NILM idea to highlight its essential requirements for a fruitful practice. Afterward, it provides a comparative statistical analysis to represent the specificity and potential challenges of the case study in accordance with NILM necessities. For this purpose, the examination exploits data from real-world measurement systems in the same and European regions. Subsequently, this study focuses on a load identification exercise by proposing a combinatory approach that utilizes the promise of sub-meter smart technologies to integrate the intrusive aspect of load monitoring with the non-intrusive one. The former is aimed at extracting overall heating demand from the aggregate one by a supervised procedure based on Deep Learning (DL) models while the latter is designed for disaggregating the residual load through an unsupervised process on the basis of clustering techniques. The results demonstrate that geographically-dependent cases create electricity consumption scenarios under which existing NILM methods can be questioned. From a realistic standpoint, this research elaborates on critical remarks to realize viable NILM systems, particularly, in Quebec houses.

Low-sodium salt substitute (LSSS) has the potential in regulating sodium and potassium intake and has been available in China market for years. However, its real-world use and impact to sodium\potassium intake is unclear. Baseline data of 4000 adult participants who participated in three similar-designed randomized controlled trails were pooled together for this study. Self-reported awareness and use of LSSS were collected using the uniform questionnaire, and the 24-h urinary sodium and potassium excretion was used to estimate their dietary intake. Mixed-effects models were developed to assess the relationship between LSSS and 24-h urinary sodium and potassium excretion. 32.0% of the participants reported awareness of LSSS and 11.7% reported its current use. After adjusting location, sex, age, and education, compared with the group of participants unaware of LSSS, participants who were aware but not using LSSS and those who were using LSSS had a lower 24-h urinary sodium excretion by –356.1(95% CI: –503.9, –205.9) mg/d and –490.6(95% CI: –679.2, –293.7), respectively (p<0.001). No significant difference was found for 24-h urinary potassium excretion and sodium-to-potassium ratio among the three groups (p>0.05). In conclusion, although associated with lower sodium intake, the awareness and real-world use of LSSS are still very low in China.

An inter- and transdisciplinary concept has been developed, focusing on the scaling of industrial circular construction using innovative compacted mineral mixtures (CMM) derived from various soil types (sand, silt, clay) and recycled mineral waste. The concept aims to accelerate the systemic transformation of the construction industry towards carbon neutrality by promoting the large-scale adoption and automation of CMM-based construction materials, which incorporate natural mineral components and recycled aggregates or industrial by-products. In close collaboration with international and domestic stakeholders in the construction sector, the concept explores the integration of various CMM-based construction methods for producing wall elements in conventional building construction. Leveraging a digital urban mining platform, the concept aims to standardize the production process and enable mass-scale production. The ultimate goal is to fully harness the potential of automated CMM-based wall elements as a fast, competitive, emission-free, and recyclable alternative to traditional masonry and concrete construction techniques. To achieve this objective, the concept draws upon the latest advances in soil mechanics, rheology, and automation and incorporates open-source digital platform technologies to enhance data accessibility, processing, and knowledge acquisition. This will bolster confidence in CMM-based technologies and facilitate their widespread adoption. The extraordinary transfer potential of this approach necessitates both basic and applied research. As such, the proposed transformative, inter- and transdisciplinary concept will be conducted and synthesized using a comprehensive, holistic, and transfer-oriented methodology.

Urinary incontinence (UI) is a common geriatric syndrome affecting bladder health and is especially prevalent in nursing homes (NHs). The aim of the study was to determine the prevalence of UI and its associated factors in 5 Spanish NHs. UI (measured with Minimum Data Set 3.0.), sociodemographic and health-related variables were collected. Chi- square (or Fisher’s) or Student’s t-test (or Mann Whitney U) for bivariate analysis were used, with Prevalence Ratio (PR) as an association measure. The prevalence of UI was 66.1% (CI:95%, 53.6–77.2) and was significantly associated with frailty (PR 1.84; 95%CI 0.96–3.53), faecal incontinence (FI) (PR 1.65; 95%CI 1.02–2.65), anxiety (PR 1.64; 95%CI 1.01–2.66), physical performance (PR 1.77; 95%CI 1.00–3.11) and cognitive state (PR 1.95; 95%CI 1.05–3.60). Statistically significant differences between incontinent-continent groups were found for activities of daily living (ADL) limitations, mobility, quality of life, sedentary behaviour (SB) and handgrip strength. It can be concluded that 2/3 of the residents experienced UI, and its significant associated factors were mainly physical (SB, frailty, physical performance, ADL limitations, mobility, FI and handgrip strength) followed by psycho-cognitive factors (cognition, anxiety and quality of life).

Today, more disciplines are intercepting each other, giving rise to “cross-disciplinary” research. Technological advancements in material science and device structure and production have paved the way towards development of new classes of multi-purpose sensory devices. Organic phototransistors (OPTs) are photo-activated sensors based on organic field-effect transistors that convert incident light signals into electrical signals. The organic semiconductor (OSC) layer and three-electrode structure of an OPT offer great advantages for light detection compared to conventional photodetectors and photodiodes, due to their signal amplification and noise reduction characteristics. Solution processing of the active layer enables mass production of OPT devices at significantly reduced cost. The chemical structure of OSCs can be modified accordingly to fulfil detection at various wavelengths for different purposes. Organic phototransistors have attracted substantial interest in a variety of fields, namely biomedical, medical diagnostics, healthcare, energy, security, and environmental monitoring. Lightweight and mechanically flexible and wearable OPTs are suitable alternatives not only at clinical levels but also for point-of-care and home-assisted usage. In this review, we aim to explain different types, working mechanism and figures of merit of organic phototransistors and highlight the recent advances from the literature on development and implementation of OPTs for a broad range of research and real-life applications.

Insulin-like growth factor binding proteins (IGFBPs) are critical modulators of the metabolism. In adults, IGFBPs are associated with obesity and insulin resistance but the association of IGFBPs with metabolic homeostasis in children and adolescents is not fully characterized. In this study we investigated the association of plasma IGFBPs (IGFBP-1, 3 and 7) with weight status, central adiposity and cardiovascular disease markers Hs-CRP and Ox-LDL. A total of 420 adolescents (age 11-14 years) were randomly recruited from public middle schools in Kuwait. IGFBPs were measured using bead-based multiplexing while Hs-CRP and Ox-LDL were measured using ELISA. IGFBP-1 levels were significantly lower in obese and overweight participants compared to normal weight children. Only IGFBP-1 was negatively associated with waist circumference to height (WC/Ht) ratio. IGFBP-1 was negatively correlated with Hs-CRP while IGFBP-3 and IGFBP-7 were negatively correlated with Ox-LDL. These data demonstrate a robust negative association of IGFBP-1, but not IGFBP-3 or -7, with overweight and obesity, and the inflammation marker Hs-CRP. Central adiposity (WC/Ht ratio) was a stronger predictor of IGFBP-1 than BMI-for-age z-score. IGFBP-1 could thus be used as a sensitive predictive diagnostic tool for obesity and its subsequent effects in screening and monitoring of obesity-related metabolic complications in adolescents.

The slate aggregate has long been perceived as a substandard, low quality waste material with its physical and chemical properties not being competitive with those of the primary aggregates. It is assumed that the slate aggregate particles are not strong, that is not durable and will not compact. This research aims to address those claims and review the available literature on the performance of the slate aggregate. The review inaugurates by analysing the physical, chemical and mechanical properties of slate, before expanding into a literature review of laboratory testing’s on the effect of moisture content on density, compaction and layer thickness of slate aggregate.The paper reviews case studies of construction projects in North Wales, where the slate aggregate has been used for general fill and road building for many years. Some of the case studies include the A55 coastal road and duelling of the A5 in Anglesey (WRAP, 2004), where slate aggregate was successfully used as sub-base. The paper also investigates why many civil engineers are reluctant to use the slate aggregate and regard the material as sub-standard, flaky aggregate. The research paper reviews the potential usages and various products the slate aggregate is suitable for and satisfies the requested standards. The final topic reviewed is the cost of transporting slate aggregate compared with the cost of transport for primary aggregate and the introduction of the Primary Aggregates Tax (Parliament of the United Kingdom, 2011). The last topic includes a critical analyses of the claims that the slate aggregate a commercially viable construction material despite its remote location (Woodward et al, 2004). The transportation cost and the supply chain complexities must be evaluated prior to considering the long-term sustainability of the product (Radanliev et al^1-6, 2014, 2015, 2016).

Brain plasticity is the ability of the brain to change and adapt in response to experience or learning. Its hallmarks are developmental flexibility, complex interactions of genetic and environmental influences, and structure-functional changes comprising neurogenesis, axonal sprouting, and synaptic remodeling. Herein, we review brain plasticity association with non-coding RNAs (ncRNAs). Studies on brain plasticity have important practical implications. Numerous cerebral ncRNAs are linked with neurological disorders, which makes them putative targets for RNA-based diagnostics and therapeutics since molecular characteristics of brain plastic change may reveal disease course and rehabilitative potential of the patient. A new insight into the concept of brain plasticity will provide perspectives on functional recovery following brain damage. The knowledge of this phenomenon will enable physicians to exploit cerebral plastic potential and regulate eloquent networks with timely interventions. Future studies will provide pathophysiologic mechanisms of brain plasticity at macro- and microscopic levels to advance rehabilitation strategies and improve the quality of life in neurological disorders.

Mutation of a single amino acid residue may significantly affect the structure and function of an entire protein. The effect of single amino acid substitutions can be assessed by examining the physicochemical environment surrounding the amino acid of interest, an emerging form of quantification of which is multidimensional tensors. However, the effect with respect to a protein variant’s inherent dynamics in tensor space is rarely assessed despite the potential importance of this form of analysis in revealing local physicochemical properties of the protein and response to mutation. Using the wild-type and 936 mutant structures of the protein domain 1pga, the present research evaluated the effects of local protein context and single amino acid substitutions on molecular dynamics simulation-derived structural distributions via the use of tensors capturing a range of biochemical properties. It was observed that the extent of simulated physicochemical variation local to a substituted amino acid is positively associated with local mechanical stiffness, loss of protein thermostability and decreased local hydrophobicity. In addition, it was observed that the largest tensor variation occurs in densely-packed, hydrophobic core-associated regions of protein structures. In summary, the pattern of tensor change aligns with prior knowledge about protein stability and physicochemical properties.

Coronaviruses (CoVs) have recently emerged as significant causes of respiratory disease outbreaks. The novel coronavirus pneumonia of 2019, known as COVID-19, are highly infectious and triggered by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Understanding virus-host interactions and molecular targets in host cell death signalling is crucial for treatment development. Small natural compounds like celastrol and curcumin, acting as proteasome inhibitors, can potentially modify NF-κB signalling for treating SARS-CoV-2 infections. Various natural constituents, including alkaloids, flavonoids, terpenoids, diarylheptanoids, and anthraquinones, inhibit viral infection, progression, and amplification of coronaviruses. Derived from medicinal herbs, these compounds possess anti-inflammatory and antiviral properties, impacting the viral life cycle, including entry, replication, assembly, and release of COVID-19 virions. This review focuses on the development of small molecules of non-covalent inhibitors targeting the Main Protease (Mpro, also called 3CLpro) enzyme of SARS-CoV-2. It highlights the design using molecular dynamics (MD) studies and computational methods for further improvements in Mpro inhibitor design. The in-silico approach, which is pivotal in this process, provides an accelerated virtual avenue for exploring and developing potential inhibitors, representing the latest advancements in drug design.

The advancement of computational drug discovery and design necessitates continuous innovation to enhance the accuracy and scope of predictive models for early-stage drug research and development. This article introduces a novel workflow for in silico generation of structural and intermolecular binding affinity data with reasonable accuracy, combining two computational tools: Modeller and Prodigy. By leveraging synthetic structural and biophysical data, this approach addresses the limitations of existing experimental datasets, generating extensive, high-quantity binding affinity data with reasonable accuracy for biomolecular binding pairs, which broadens the horizon of computational biomolecule design and discovery by enabling extensive exploration of the sequence space of biomolecular binding pairs, and narrows the gap between experimental binding affinity data and its unexplored territories. Overall, this article presents a methodological advance to enhance the accuracy and scope of computational biomolecule discovery and design, paves the way for the development of preclinical candidates with improved efficacy and specificity, and holds transformative potential for further advancements in artificial intelligence-enabled biomolecule discovery and design in the future.

Exploiting the van der Waals model of liquids, it is possible to derive analytical formulas for the thermodynamic functions governing solvation, the transfer of a solute molecule from a fixed position in the ideal gas phase to a fixed position in the liquid phase. The solvation Gibbs free energy change consists of two contributions: (a) the high number density of all liquids and the repulsive interactions due to the basic fact that each molecule has its own body lead to the need of spending free energy to create a cavity suitable to host the solute molecule; (b) the ubiquitous intermolecular attractive interactions lead to a gain in free energy for turning on attractions between the solute molecule and surrounding liquid molecules. Also the solvation entropy change consists of two contributions: (a) there is an entropy loss in all liquids because the cavity presence limits the space accessible to liquid molecules during their continuous translations; (b) there is an entropy gain in all liquids, at room temperature, due to the liquid structural reorganization as a response to the perturbation represented by solute insertion. The latter entropy contribution proves to be balanced by a corresponding enthalpy term. This scenario emerged from the van der Waals model is in qualitative agreement with experimental results.

Gestational trophoblastic diseases (GTDs) encompass a spectrum of conditions characterized by abnormal trophoblastic cell growth, ranging from benign molar pregnancies to malignant trophoblastic neoplasms. This systematic review explores the molecular underpinnings of GTDs, focusing on genetic and epigenetic factors that influence disease progression and clinical outcomes. Based on 65 studies identified through systematic search and selection criteria, key findings include dysregulations in tumor suppressor genes such as p53, aberrant apoptotic pathways involving BCL-2, and altered expression of growth factor receptors and microRNAs. These molecular alterations not only differentiate molar pregnancies from normal placental development but also contribute to their clinical behavior, from benign moles to potentially malignant forms. The review synthesizes insights from immunohistochemical studies and molecular analyses to provide a comprehensive understanding of GTD pathogenesis and implications for personalized care strategies.

Keywords: Chronic Obstructive Pulmonary Disease (COPD), Long Non-Coding RNAs (lncRNAs), Molecular Pathogenesis, Inflammation, Lung Cancer, Diagnostic Biomarkers

Amyloid self-assembled from amyloid peptides βΑ40 or βΑ42 is notorious for its neurotoxic effects in plaque and neurofibrillary tangle formations leading to neuron dysfunction and diseases of cognitive decline (e.g. Alzheimer’s, Parkinson’s and Huntington's disease). This contrasts with so-called functional amyloids which are non-toxic ordered template structures amenable to applications in tissue engineering. Amyloid fibrils of variable morphology including long and hollow fibres and flattened tube and spiral ribbon-like structures have been used in engineering applications in nano-biology. Protein assemblies based on amyloid core structures display diverse biological functionalities could be applied in futuristic self-assembling biomaterials in nano-electronics. These possibilities have revolutionized the development of next generation computers and biosensors, ultracapacitors, memristors, actuators, molecular switches and could also be used to develop artificial synapses. Amyloid fibril assemblies have also been used in photoelectric and photon capture light harvesting technologies and been applied in innovative nano-photoelectronics and photovoltaics. Hybrid Aβ(16–22)-α-synuclein amyloid fibrils also exhibit light-harvesting and electron-transfer properties. Engineered amyloid assemblies are thus facilitating innovative futuristic advances in nano-technology. Furthermore, with a better understanding of amyloid fibril assembly processes it may be possible to develop therapeutic methods that prevent the toxic build up of this polymer in brain tissues that leads to diseases of cognitive decline. With the ever-expanding prevalence of these diseases in the ageing general global population, there certainly is a clear and present need to find a remedy for these debilitating conditions.

fibrillation (AF) and heart failure with preserved ejection fraction (HFpEF). Join us on a journey that unravels the mysteries of molecular intricacies, delves into advanced imaging techniques, and sheds light on therapeutic pathways. Unveiling the role of cardiac amyloidosis, particularly sub-clinical isolated cardiac amyloidosis (ICA), the narrative unfolds the heightened risk of AF in the elderly. State-of-the-art imaging techniques like cardiac magnetic resonance (CMR) and molecular imaging step into the spotlight, unraveling diagnostic and prognostic nuances of AF and HFpEF. Embarking on the molecular voyage, the article navigates through next-generation sequencing and comprehensive genomic profiling, shedding light on genetic alterations shaping the AF-HFpEF landscape. This molecular compass lays the groundwork for personalized medicine, illuminating pathways to identify therapeutic bullseyes and biomarkers. In the realm of medical strategies, the discussion homes in on the promising notes struck by SGLT2 inhibitors, particularly dapagliflozin, orchestrating a reduction in AF burden. Characters like spironolactone and dronedarone make appearances, each weaving a distinct tale, revealing their potential roles in steering the ship for AF- HFpEF patients. The subplot involving obesity in HFpEF unfolds, with the LEGACY study portraying the benefits of weight reduction. The pivotal intervention of catheter ablation emerges as the hero, boasting positive outcomes in reducing hospitalization rates and overall mortality for AF-HFpEF patients. However, cautionary tales echo about its impact on left atrial function, adding layers of complexity that beckon careful consideration and monitoring. Amidst the narrative, critical discussions unfold about the limitations of current research, echoing the need to define acute heart failure, refine imaging techniques, and tailor management strategies. The narrative passionately advocates for a personalized touch in addressing AF-HFpEF, recognizing the unique blend of clinical and molecular personas. In essence, this review paints a vivid mural of AF-HFpEF, skillfully bridging the realms of molecular intricacies and the artistry of clinical management.

Sustainable development of our society demands recycling of metallic wastes which may contain a variety of metallic impurities. Thus, it is desirable to develop a ‘universal’ structure, such as an amorphous alloy tolerating high concentrations of metallic pollutants. We performed ab initio molecular dynamics simulations to manufacture a novel multicomponent amorphous alloy of twenty elements (20e-HEAA). Analysis reveals both topological and chemical compositional short-range ordering in the obtained 20e-HEAA and formation of B-B clusters. Electronic structure calculations reveal the metallic nature of the amorphous alloy with its Fermi level falling in a valley in the density of states. Moreover, the Zn 3d and Cd 4d electrons exhibit a localized nature and thus, should be excluded from the valence electron concentration (VEC) analysis in the study of high-entropy alloys. The information obtained here is helpful to get insight into multicomponent high entropy materials, especially multicomponent high-entropy amorphous alloys as potential circular metals.

Peptide/Histidine Transporter PHT1 (SLC15A4) is expressed in lysosomal membranes of immune cells where it plays an important role in metabolic and inflammatory signaling. PHT1 is an H+-coupled/histidine symporter that can transport a broad range of oligopeptides, including a variety of bacterial-derived peptides. Moreover, it enables the scaffolding of various metabolic signaling molecules and interacts with key regulatory elements of the immune response. Therefore, it is not surprising that PHT1 is associated with the development of autoimmune diseases, such as systemic lupus erythematosus (SLE). Unfortunately, the pharmacological development of PHT1 has been hampered by the lack of appropriate transport assays. With the aim to address this shortcoming, a novel transport assay based on solid supported membrane-based electrophysiology (SSME) is presented. Key findings of the present SSME studies include the first recordings of electrophysiological properties, a pH dependence analysis, an assessment of PHT1 substrate selectivity, as well as the transport kinetics of the identified substrates. In contrast to previous works, PHT1 is studied its native lysosomal environment. Moreover, observed substrate selectivity is validated by molecular docking. Overall, this new SSME-based assay is expected to contribute to unlock the pharmacological potential of PHT1 and to deepen the understanding of its functional properties.

The synthesis and characterization of the multicomponent crystals formed by 2,2’-thiodiacetic acid (H2tda) and 2,6-diaminopurine (Hdap) or N9-(2-hydroxyethyl)adenine (9heade) are reported. The crystals are in the salt rather than cocrystal form, as witnessed by single crystal X-ray diffractometry where a structural analysis revealed their ionic nature, confirming the proton transfer from the 2,2’-thiodiacetic acid to the basic groups of the coformers. The new multicomponent crystals have molecular formulas [(H9heade+)(Htda)] (1) and [(H2dap+)2(tda2)]·2H2O (2), and were also characterized by FTIR, elemental analysis as well as thermogravimetric/differential scanning calorimetry (TG/DSC) analyses. In the crystal packing the ions interact with each other via O–H···N, O–H···O. N–H···O and N–H···N hydrogen bonds generating cyclic hydrogen bonded motifs with graph-set notation of R22(16), R22(10), R32(10), R33(10), R22(9), R32(8) and R42(8), to form different supramolecular homo- and hetero-synthons. In addition, in the crystal packing of 2, pairs of diaminopurinium ions display an strong anti-parallel ,-stacking interaction, with short inter-centroids and interplanar distances (3.39 and 3.24 Å respectively) and fairly tight angle (17.5°). These assemblies have been further analyzed energetically by using DFT calculations, MEP surface analysis and QTAIM characterization.

The human body contains 60-70% of water, depending on age. As a body fluid, it is not only a medium in which physical and chemical processes take place, but it is also one of the active mediators. Water is the richest substance with non-covalent hydrogen bonds. Water molecules, by themselves (in vacuum), are diamagnetic, but when organized into clusters, become diamagnetic or paramagnetic. Also, biomolecules (DNA, collagen, clathrin, and other proteins) have non-covalent hydrogen bonds in their structure. The interaction, as well as signal transmission, between water and biomolecules is achieved through the vibrations of covalent and non-covalent hydrogen bonds, which determine the state and dynamics of conformational changes of biomolecules. Disruptive conformational changes of biomolecules, cells, and tissues lead to their dysfunctionality, so they are a frequent cause of many disorders and diseases. For example, the rearrangement of hydrogen bonding due to mitochondrial disease mutation in cytochrome bc1 disturbs heme bH redox potential and spin state. In order to prevent and repair the dysfunctional conformational changes, a liquid substance was developed based on the second derivative of the C₆₀ molecule (SD-C₆₀), which has classical and quantum properties. Characterization of SD-C₆₀ by UV-VIS-NIR, FTIR, TEM, and AFM/MFM was done and it is shown that SD-C₆₀ water layers generate vibrations with near-zero phase dispersion which are transmitted through the Fibonacci’s water chains to biomolecules. In comparison to previously published SD-C₆₀ derivate (3HFWC, size until 10 nm, and 1-5 water layers), improved formulation (3HFWC-W, size 10-25 nm, and 6-9 water layers) showed multiplied cytotoxic activity against melanoma cell lines of different aggressiveness. Apart from this, the mode of action was preserved and based on induction of senescence rather than cell death. Importantly, high selectivity toward malignant phenotype was detected. Observed effects can be ascribed to a machinery of hydrogen bonds, which are generated in SD-C₆₀ and transmitted through water to biomolecules. This approach may open a new field in science and healthcare - a “water-based nanomedicine”.

This paper presents the concept of a novel adaptable sensing solution currently being developed under the EU Commission founded PHOTONGATE project. This concept will allow to quantify multiple analytes of the same or different nature (chemicals, metals, bacteria, etc.) in a single test with levels of sensitivity and selectivity at/or over those offered by current solutions. PHOTONGATE relies on two core technologies: a bio-chemical technology (molecular gates) which will confer the specificity and, therefore, the capability to be adaptable to the analyte of interest, and which combined with porous substrates will increase the sensitivity, and a photonic technology based on Local Surface Plasmonic Resonance (LSPR) structures serves as transducer for light interaction. Both technologies are in the micron range, facilitating the integration of multiple sensors within a small area (mm²). The concept will be developed for its application in health diagnosis and food safety sectors. It is thought as an easy-to-use modular concept, which will consist of the sensing module, mainly of a microfluidics cartridge that will house the photonic sensor, and a platform for fluidic handling, optical interrogation, and signal processing. The platform will include a new optical concept, fully Europe Union Made, avoiding optical fibers and expensive optical components.

Lucky bamboo (Dracaena sanderiana hort. ex Mast. = Dracaena braunii) is a domestic species widely cultivated for ornamental purposes in China. In March 2022, a severe occurrence of anthracnose disease was observed on the stems of lucky bamboo plants in a greenery retail store located in Nanjing, Jiangsu Province, China. The morphological characteristics of isolates obtained from diseased stem tissues were identical with those described for Colletotrichum species. Based on multilocus phylogenetic analysis with the internal transcribed spacer (ITS), actin (ACT) gene, and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) gene, the pathogen was identified as Colleto-trichum gloeosporioides (Penz.) Penz. & Sacc. Pathogenicity was verified by mycelial plug-inoculating stem cuttings of one-year-old lucky bamboo plants and spray-inoculating whole one-year-old lucky bamboo plants, respectively. Koch’s postulates were fulfilled by the re-isolation of C. gloeosporioides from symptomatic tissues. To the best of our knowledge, this report describes the first time that C. gloeosporioides was observed to cause anthracnose on lucky bamboo in China.

Intrinsic disorder accounts for the flexibility of protein loops, molecular building blocks that are largely responsible for the processes and molecular functions of the living world. While loops likely represent early structural forms that served as intermediates in the emergence of protein structural domains, their origin and evolution remains poorly understood. Here, we conduct a phylogenomic survey of disorder in loop prototypes sourced from the ArchDB classification. Tracing prototypes associated with protein fold families along an evolutionary chronology revealed ancient prototypes tended to be more disordered than their derived counterparts, with ordered prototypes developing later in evolution. This highlights the central evolutionary role of disorder and flexibility. While mean disorder increased with time, a minority of ordered prototypes exist that emerged early in evolutionary history, possibly driven by the need to preserve specific molecular functions. We also revealed percolation of evolutionary constraints from higher to lower levels of organization. Percolation resulted in trade-offs between flexibility and rigidity that impacted prototype structure and geometry. Our findings provide a deep evolutionary view of the link between structure, disorder, flexibility and function, as well as insights into the evolutionary role of intrinsic disorder in loops and their contribution to protein structure and function.

Pyrochlore oxides (A2B2O7) are potential nuclear waste substrate material due to their superior radiation resistance properties. We performed molecular dynamics simulations to study the structural properties and displacement cascades in ytterbium titanate pyrochlore (Yb2Ti2O7). We computed threshold displacement energy ( Ed ) and lattice constant ( ao) of Yb2Ti2O7. The effect of displacement cascades in Yb2Ti2O7 of recoils of energies 1 keV, 2 keV, 5 keV, 10 keV in different crystallographic directions ([100], [110], [111]) were studied. The number of defects is found to be proportional to the energy of incident PKA. Additionally, the Ed of pyrochlore is computed and it exhibits anisotropy. Furthermore, radiation damage in high-entropy pyrochlore (HEPy) i.e., YbYTiZrO7, YbGdTiZrO7 , Yb0.5Y0.5Eu0.5Gd0.5TiZrO7 were investigated and compared with Yb2Ti2O7. It was found that HEPy have a larger Ed as compared with Yb2Ti2O7 which exhibits characteristic of lower radiation damage resistance than HEPy. Our simulation proposed that HEPy alloys are more radiation resistant than individual pyrochlore constituents . This work will provide atomic insights in developing substrate materials for nuclear waste applications.

Cervical cancer is a significant global health concern, with human papillomavirus (HPV) infection being a crucial risk factor. Photodynamic therapy (PDT) is an attractive, minimally invasive treatment for HPV-related cervical lesions, which uses photosensitizers and light to selectively de-stroy abnormal cells. We aim to provide an overview of the various sorts of dyes that are utilized in PDT for decreasing the incidence and mortality of cervical cancer. Besides, the article discusses ongoing clinical trials for PDT in low-grade squamous intraepithelial neoplasia (LSIL) and high-grade squamous intraepithelial lesions (HSIL), as well as preclinical approaches for PDT in cervical cancer using various dyes. Moreover, it highlights potential dyes for PDT, examine them in in-silico condition, their pros and cons and also the solutions for enhancing their anticancer com-patibility. We also display that PDT is a promising therapeutic strategy for the diagnosis and treatment of HPV-associated cervical lesions. Moreover, it shows that using different classes of dyes improves the anticancer effects of PDT. Finally, among all dyes which are used in PDT, Fullerene demonstrated high tendency to over expressed receptors in cervical cancer cells and seems to be a proper candidate for be used in PDT more than before, but further research is necessary to assess its long-term efficacy and safety.

The compilation summarizes results so far gathered in a project that investigates the atom with classical (Newtonian) physics. It posits that the atom’s wave-particle dual nature is real, objective and intrinsic; the wave gives rise to the cosmic vacuum field while the particle, of course, manifests condensed matter. Light’s π radians oscillation manifests, on molar scale, significant radial tension in the vacuum field, the effect, amongst others, causes molecular matter to precipitate out of the vacuum – so-called ‘molecular outflow’. Cosmic vacuum field radial tension relates to molecular mass, in other words, a mass-radius (M-R) relationship is uncovered. It is argued that using the M-R relation it is possible to perform a valid simulation of the cosmic physical reality. The three states of matter are meaningfully accounted for using the atom’s e-m radiation wavelength. It is explained that force, be it of any kind whatsoever, originates in the atomic waveform, i.e., the cosmic vacuum field.

ORF7b-2 is an accessory protein of the SARS-CoV-2 virus of only 43 amino acids. It has been implicated in various functional hypotheses, some of which predict its involvement as a trans-membrane protein. In this study, ORF7b-2 has often been compared to ORF7b-1 of the SARS virus to highlight differences and similarities with a protein that should have a similar biological role. Structural analysis of ORF7b-2 and its electrostatic characteristics show a polypeptide with both ends negatively charged and a diffuse negative charge over the entire structure. Therefore, its behavior in solution is like that of a weak negative polyelectrolyte, more precisely a polyanion with a net charge of – 4 at neutral pH. Its structure was modeled with two different modeling systems, one of which was ab initio. The two best models are similar, as confirmed by the Ramachandran plot, and show a central alpha-helical structure with two disordered and mobile ends. A normal mode analysis characterized the low-frequency dynamic aspects of the protein. The analysis of the structural shows a rigid central segment with mobile and fluctuating extremities, involved in a conformational equilibrium of the helix ↔ coil type. The calculation of the dipole moment shows its vector is not aligned with the main axis of the structure with an outward tilt of 24°. Molecular dynamics simulations were also conducted and the one in water is in good agreement with the previous results. While, the simulation performed by inserting a pre-oriented dimer (OMP) into a solvated lipid showed the low tendency of the protein to solvate in the apolar environment of the membrane. ORF7b-2 also shows a widespread distribution of negative surfaces that dynamically adjust to changes in structural organization. The BioGrid platform's [Biological General Repository for Interaction Datasets] through the BioGrid COVID-19 Coronavirus Curation Project shows a very large number of experimentally proven physical interactions unique to ORF7b-2, some of them with cytoplasmic proteins. These features of ORF7b-2, evaluated together, suggest a remarkable propensity of ORF7b-2 to interact with multiple molecular partners on both an electrostatic and hydrophobic basis. All this makes it unreasonable that the only biological function of this protein should be that exerted as an intramembrane protein.

Atopic dermatitis (AD) is a common chronic inflammatory skin disease with high prevalence worldwide, including countries from Asia, Africa and Latin America, and in different ethnic groups. In recent years, more attention on AD heterogeneity associated on multiple factors, including patient’s ethnic background, has been posed, resulting in an increasing body of clinical, genetic, epidemiologic, and immune-phenotypic evidence that delineate differences among racial groups with AD. Filaggrin (FLG) mutations, the strongest genetic risk factor for the development of AD, are detected in up to 50% of European and 27% of Asian AD patients, while very rarely in Africans. The Th2 activation is a common attribute of all ethnic groups, though the Asian endotype of AD is also characterized by an increased Th17-mediated signal whereas African Americans own a strong Th2/Th22 signature and the absence of Th1/Th17 skewing. In addition, the ethnic heterogeneity may own important therapeutic implications as the genetic predisposition may affect treatment response and, thereby, a tailored strategy that better targets the dominant immunologic pathways in each ethnic subgroup may be envisaged. Nevertheless, white patients with AD represent the largest ethnicity enrolled and tested in clinical trials and the most treated in a real-world setting, limiting the investigation about safety and efficacy across different ethnicities. The purpose of this review is to describe the heterogeneity of pathophysiology across ethnicities and its potential therapeutic implications.

This work communicates cavity ring-down spectroscopy (CRDS) of methylidyne (CH) in a chemiluminescent plasma that is produced in a microwave cavity. Of interest are the rotational lines of the 0-0 vibrational transition for the A-X band and the 1-0 vibrational transition for the B-X band. The reported investigations originate from CH-radical research in 1996 that constituted the first case of applying CRDS to the CH radical. The report also includes recent analysis that shows excellent agreement of measured and computed data, and it communicates CH line strength data.

Shale gas and coalbed methane are energy sources that partly or even mainly consist of methane stored in an adsorbed state in the pores of the organic-rich rock and coal seams. In this study, the graphene nanoslit model is employed to model the nanometer slit pores in shale and coal. The Grand Canonical Monte Carlo (GCMC) and Molecular Dynamics (MD) modelling methods are used to investigate the mechanisms of adsorption and displacement of methane in the slit pore. It was found that the CVFF forcefield resulted in the largest adsorption amount, while the PCFF forcefield resulted in the least. The COMPASS and COMPASS II force fields led to similar results. As the width of the slit pore increases, the adsorption amount of gas molecules increases, and the number density profile of adsorbed methane molecules alters from a single adsorption layer to multi-adsorption layers. The minimum slit pore width at which methane molecules can penetrate the slit pore was found to be 0.7 nm. Moreover, it is demonstrated that by lowering the temperature, the adsorption rate of the methane increases since the adsorption is an exothermic process. Enhancing methane recovery was investigated by the injection of gases such as CO2 and N2 to displace the adsorbed methane. The comparison of adsorption isotherms of gas molecules provided the following order in terms of the amount of adsorption: CO2>CH4>N2.

G protein-coupled receptors (GPCRs) are amongst the most pharmaceutically relevant and well-studied protein targets, yet unanswered questions in the field leave significant gaps in our understanding of their nuanced structure and function. 3D pharmacophore models are powerful computational tools in silico drug discovery, presenting myriad opportunities for the integration of GPCR structural biology and cheminformatics. This review highlights success stories in the application of 3D pharmacophore modeling to de novo drug design, discovery of biased and allosteric ligands, scaffold hopping, QSAR analysis, hit-to-lead optimization, GPCR de-orphanization, mechanistic understanding of GPCR pharmacology and elucidation of ligand-receptor interactions. Furthermore, advances in the incorporation of dynamics and machine learning will be highlighted. The review will analyze challenges in the field of GPCR drug discovery, detailing how 3D pharmacophore modeling can be used to address them. Finally, we will present opportunities afforded by 3D pharmacophore modeling in the advancement of our understanding and targeting of GPCRs.

Principal component analysis (PCA) is used to reduce the dimensionalities of high dimensional datasets in a variety of research areas. For example, biological macromolecules, such as proteins, exhibit many degrees of freedom, allowing them to adopt intricate structures and exhibit complex functions by undergoing large conformational changes. Therefore, molecular simulations of and experiments on proteins generate a large number of structure variations in high dimensional space. PCA and many PCA-related methods have been developed to extract key features from such structural data, and these approaches have been widely applied for over 30 years to elucidate macromolecular dynamics. This review mainly focuses on the methodological aspects of PCA and related methods, and their applications for investigating protein dynamics.

The cardiac sodium ion channel (NaV1.5) is a protein with four domains (DI-DIV), each with six transmembrane segments. Its opening and subsequent inactivation results in the brief rapid influx of Na+ ions resulting in the depolarization of cardiomyocytes. The neurotoxin veratridine (VTD) inhibits NaV1.5 inactivation resulting in longer channel opening times, and potentially fatal action potential prolongation. VTD is predicted to bind at the channel pore, but alternative binding sites have not been ruled out. To determine the binding site of VTD on NaV1.5, we performed docking calculations and high-throughput electrophysiology experiments. The docking calculations identified two distinct binding regions. The first site was in the pore, close to the binding site of NaV1.4 and NaV1.5 blocking drugs in experimental structures. The second site was at the “mouth” of the pore at the cytosolic side, partly solvent-exposed. Mutations at this site (L409, E417, and I1466) had large effects on VTD binding, while residues deeper in the pore had no effect, consistent with VTD binding at the mouth site. Overall, our results suggest a VTD binding site close to the cytoplasmic mouth of the channel pore. Binding at this alternative site might indicate an allosteric inactivation mechanism for VTD at NaV1.5.

Avian sex chromosomes evolved after the divergence birds and crocodilians from their common ancestor, so they are much younger than the better-studied chromosomes of mammals. It has long been recognized that there may have been several stages to the evolution of avian sex chromosomes. For example, the CHD1 undergoes recombination in paleognaths but not neognaths. Genome assemblies have suggested there may be variation in the timing of barriers to recombination among Neognathae, but there remains little understanding of the extent of this variability. Here, we look at partial sequences of ATP5F1A, which is on the avian Z and W chromosomes. It is known that recombination of this gene has independently ceased in Galliformes, Anseriformes, and at least five neoavian orders, but whether there are other independent cessations of recombination among Neoaves is not understood. We used a combination of data extracted from published chromosomal-level genomes with data collected using PCR and cloning to identify Z and W copies in 22 orders. Our results suggest there may be at least 19 independent cessations of recombination within Neognathae, and 3 clades that may still be undergoing recombination (or have only recently ceased recombination). Analyses of ATP5F1A protein sequences revealed an increased amino acid substitution rate for W chromosome gametologs, suggesting relaxed purifying selection on the W chromosome. Supporting this hypothesis, we found that the increased substitution rate was particularly pronounced for buried residues, which are expected to be more strongly constrained by purifying selection. This highlights the dynamic nature of avian sex chromosomes, and that this level of variation among clades means they should be a good system to understand sex chromosome evolution.

The accurate prediction of molecular properties such as lipophilicity and aqueous solubility are of great importance and pose challenges in several stages of the drug discovery pipeline. Machine learning methods like graph-based neural networks (GNNs) have shown exceptionally good performance in predicting these properties. In this work, we introduce a novel GNN architecture, called directed edge graph isomorphism network (D-GIN). It is composed of two distinct sub-architectures (D-MPNN, GIN) and achieves an improvement in accuracy over its sub-architectures employing various learning, and featurization strategies. We argue that combining models with different key aspects help make graph neural networks deeper and simultaneously increase their predictive power. Furthermore, we address current limitations in assessment of deep-learning models, namely, comparison of single training run performance metrics, and offer a more robust solution.

This study focused on the characterization of lactic acid bacteria (LAB) in a renowned traditional Italian cheese, Pecorino di Farindola, to select an autochthonous culture and investigate its po-tential for the improvement of safety and functional properties. Two hundred and six LAB isolated throughout production and maturation from nine cheese lots of three farms were identified by 16S rRNA gene sequencing and tested for the presence of genes encoding virulence factors, vancomycin resistance (for enterococci), biogenic amines (BAs) and bacteriocin production, for antimicrobial activity, and for the capacity to survive in the gastro-intestinal tract (GIT) based on tolerance to low pH and bile salts and adhesion to CaCo-2 cells. A Lacticaseibacillus paracasei isolate was used in cheese making and determined a decline of spiked Listeria monocytogenes and Escherichia coli O157 faster than in control cheese. The autochthonous bacterial groups were numerically unaffected, apart from lactobacilli that were recovered in higher numbers in the cheese with added L. paracasei. Based on Repetitive Extragenic Palyndrome (Rep) PCR profiles, the added strain possibly dominated until day 88 in cheese. Results encourage further trials with autochthonous cultures to efficiently inhibit hazardous bacteria and enrich a functional microbiota in Pecorino di Farindola and similar cheeses.

There is a need to search for new antifungals, especially for the treatment of the invasive Candida infections, caused mainly by C. albicans. These infections are steadily increasing at an alarming rate, mostly among immunocompromised patients. The newly synthesized compounds (3a-3k) were characterized by physico-chemical parameters and investigated for antimicrobial activity using the microdilution broth method to estimate minimal inhibitory concentration (MIC). Additionally, their antibiofilm activity and mode of action together with the effect on the membrane permeability in C. albicans were investigated. Biofilm biomass and its metabolic activity were quantitatively measured using crystal violet (CV) staining and tetrazolium salt (XTT) reduction assay. The cytotoxic effect on normal human lung fibroblasts and hemolytic effect were also evaluated. The results showed differential activity of the compounds against yeasts (MIC = 0.24-500 µg/mL) and bacteria (MIC = 125-1000 µg/mL). Most compounds possessed strong antifungal activity (MIC = 0.24-7.81 µg/mL). The compounds 3b, 3c, and 3e, showed no inhibitory (at 1/2 MIC) and eradication (at 8 x MIC) effect on C. albicans biofilm. Only slight decrease in the biofilm metabolic activity was observed for compound 3b. Moreover, the studied compounds increased the permeability of the membrane/cell wall of C. albicans and their mode of action may be related to action within the fungal cell wall structure and/or within the cell membrane. It is worth noting that the compounds had no cytotoxicity effect on pulmonary fibroblasts and erythrocytes at concentrations showing anticandidal activity. The present studies in vitro confirm that these derivatives appear to be a very promising group of antifungals for further preclinical studies.

Background: Real-world data on the molecular epidemiology of EGFR resistance mutations at or after progression with first- or second-generation EGFR-TKIs in patients with advanced NSCLC are lacking. Methods: This ongoing observational study was carried out by 23 hospital-based physicians in Greece. The decision to perform Cobas® EGFR Mutation Test v2 in tissue and/or plasma at disease progression was made before enrollment. For patients with negative/inconclusive T790M plasma-based results, tissue re-biopsy could be performed. Results: Ninety-six (96) eligible patients were consecutively enrolled (median age: 67.8 years) between July-2017 and September-2019. Of the patients, 98% were tested upon progression using plasma and 2% using tissue/cytology biopsy. The T790M mutation was detected in 16.0% of liquid biopsies. Tissue re-biopsy was performed in 22.8% of patients with a T790M-negative plasma result. In total, the T790M positivity rate was 21.9%, not differing between patients on first- or second-generation EGFR-TKI. Higher (≥2) ECOG performance status and longer (≥10 months) time to disease progression following EGFR-TKI treatment initiation were associated with T790M positivity. Conclusions: Results from plasma/tissue-cytology samples in a real-world setting, yielded a T790M positivity rate lower than previous reports. Fewer than one in four patients with negative plasma-based testing underwent tissue re-biopsy, indicating the challenges in routine care settings.

Drug repurposing, the practice of utilizing existing drugs for novel clinical indications, has tremendous potential for improving human health outcomes and increasing therapeutic development efficiency. The goal of multidisease multitarget drug repurposing, also known as shotgun drug repurposing, is to develop platforms that assess the therapeutic potential of each existing drug for every clinical indication. Our Computational Analysis of Novel Drug Opportunities (CANDO) platform for shotgun multitarget repurposing implements several pipelines via large scale modelling and simulation of interactions between comprehensive libraries of drugs/compounds and protein structures. In these pipelines, each drug is described by an interaction signature that is then compared to all other signatures that are then sorted and ranked based on similarity. Pipelines within the platform are benchmarked based on their ability to recover known drugs for all indications in our library, and predictions are generated based on the hypothesis that (novel) drugs with similar signatures may be repurposed for the same indication(s). The drug-protein interactions in the platform used to create the drug-proteome signatures may be determined by any screening or docking method but the primary approach used thus far has been an in house similarity docking protocol. In this study, we calculated drug-proteome interaction signatures using the publicly available molecular docking method Autodock Vina and created hybrid decision tree pipelines that combined our original bio- and cheminformatic approach with the goal of assessing and benchmarking their drug repurposing capabilities and performance. The hybrid decision tree pipeline outperformed the corresponding two docking-based pipelines it was synthesized from, yielding an average indication accuracy of 13.3% at the top10 cutoff (the most stringent), relative to 10.9% and 7.1% for its constituent pipelines, and a random control accuracy of 2.2%. We demonstrate that docking based virtual screening pipelines have unique performance characteristics and that the CANDO shotgun repurposing paradigm is not dependent on a specific docking method. Our results also provide further evidence that multiple CANDO pipelines can be synthesized to enhance drug repurposing predictive capability relative to their constituent pipelines. Overall, this study indicates that pipelines consisting of varied docking based signature generation methods can capture unique and useful signal for accurate comparison of drug-proteome interaction signatures, leading to improvements in the benchmarking and predictive performance of the CANDO shotgun drug repurposing platform.

The influence of distant London dispersion forces on the docking preference of alcohols of different size between the two lone electron pairs of the carbonyl group in pinacolone is explored by infrared spectroscopy of the OH stretching fundamental in supersonic jet expansions of 1:1 solvate complexes. Experimentally, no pronounced tendency of the alcohol to switch from the methyl to the bulkier tert-butyl side with increasing size is found. In all cases, methyl docking dominates by at least a factor of two, whereas DFT-optimized structures suggest a very close balance for the larger alcohols, once corrected by CCSD(T) relative electronic energies. Together with inconsistencies when switching from a C4 to a C5 alcohol, this points at deficiencies of the investigated B3LYP and in particular TPSS functionals even after dispersion correction, which cannot be blamed on zero point energy effects. The search for density functionals which describe the harmonic frequency shift, the structural change and the energy difference between the docking isomers of larger alcohols to unsymmetric ketones in a satisfactory way is open.

Accurate diagnosis at an early stage of infection is essential for the successful management of any contagious disease. The COVID-19, caused by the SARS-CoV-2 virus is a pandemic that has affected 214 countries affecting more than 30.8 million people causing 0.957 million deaths as of third week of September, 2020. The primary diagnosis of the infection is done either by the molecular technique of RT-qPCR by detecting portions of the RNA of the viral genome or through immunodiagnostic tests by detecting the viral proteins or the antibodies produced by the host. As the demand for the test increased rapidly many naive manufacturers entered the market with novel kits and more and more laboratories also entered the diagnostic arena making the test result more error-prone. There are serious debates globally and regionally on the sensitivity and specificity of these tests and about the overall accuracy and reliability of the tests for decision making on control strategies. The significance of the test is also complexed by the presence of asymptomatic carriers, re-occurrence of infection in cured patients as well as by the varied incubation periods of the infection and shifting of the viral location in the host tissues. In this paper, we review the techniques available for SARS-CoV-2 diagnosis and probable factors that can reduce the sensitivity and specificity of the different test methods currently in vogue. We also provide a check-list of factors to be taken care to avoid fallacious practices to reduce false positive and false negative results by the clinical laboratories

Spatially resolved, line-of-sight measurements of aluminum monoxide emission spectra in laser ablation plasma are used with Abel inversion techniques to extract radial plasma temperatures. Contour mapping of the radially deconvolved signal intensity shows a ring of AlO formation near the plasma boundary with the ambient atmosphere. Simulations of the molecular spectra were coupled with the line profile fitting routines. Temperature results are presented with simultaneous inferences from lateral, asymmetric radial, and symmetric radial AlO spectral intensity profiles. This analysis indicates that we measured shockwave phenomena in the radial profiles, including a temperature drop behind the blast wave created during plasma initiation.

This study deals with computational analysis of dominant fatty acid ethyl esters characterized from the biodiesel produced from waste beef tallow by means of KOH catalyzed ethanol based transesterification. Ethyl palmitate, Ethyl Oleate, Ethyl Stearate and Ethyl Myristate were identified as dominant fatty acid esters and were computed for molecular analysis in Gaussian 09 software using Density Functional Theory (B3LYP method) with 6-31G* as basis set. Geometric parameters were in accordance with existing experimental values and population analysis exhibited negative charge for oxygen atoms, both positive & negative charge for carbon atoms in all ester molecules. The molecular dipole moment was higher for unsaturated ester molecule and quadruple moment proposed electronic dislocation in X+Y direction. Also, energy gap decreased slightly with increasing carbon chain but reduced drastically with increase in unsaturation. Electrostatic potential mapping displayed negative electrostatic potential for oxygen atoms in ester linkage of all ester molecules.

Chlorotoxin (CTX) is a 36–amino acid peptide with 8 Cys residues that forms four Cys-Cys bonds. It has high affinity for the glioma-specific chloride channel and matrix metalloprotease-2. Structural and binding properties of CTX analogs with various Cys residue substitutions with L-a-aminobutyric acid (Abu) have been previously reported. Using 4.2 ìs molecular dynamics, we compared the conformational and essential space sampling of CTX and analogs [Abu/Ser^2,19]CTX, [Abu/Ser^5,28]CTX, [Abu/Ser^16,33]CTX, [Abu/Ser^20,35]CTX, and [Abu/Ser^{2,5,16,19,20,28,33,35}]CTX. The native and substituted peptides maintained a high degree of a-helix propensity from residues 8 through 21, with the exception of [Ser^5,28]CTX and [Abu^16,33]CTX. In agreement with previous circular dichroism spectropolarimetry results, the C-terminal b-sheet content varied less from residues 25 through 29 and 32 through 36 and was well conserved in all analogs, except: [Abu^16,33]CTX, [Ser^20,35]CTX, [Abu^{2,5,16,19,20,28,33,35}]CTX, and [Ser^{2,5,16,19,20,28,33,35}]CTX. The Cys¹⁶-Cys³³ and Cys²⁰-Cys³⁵ Cys-Cys bonds appear to be required to maintain the ab-motif of CTX. Their selective substitution with Ser^16,33 however, may mitigate the destabilizing effect of Cys¹⁶-Cys³³ substitution by the formation of an inter residue H-bond from OgH of Ser¹⁶ to OgH of Ser³³ bridged by a water molecule. All peptides shared considerable sampled conformational space, which explains the retained receptor binding of the nonnative analogs.

Combined awareness about the power and limitations of bioinformatics and molecular biology enables advanced research based on high-throughput data. Despite an increasing demand for scientists with a combined background in both fields, the education in dry lab and wet lab is often separated. This work describes an example of integrated education with focus on genomics and transcriptomics. Participants learn computational and molecular biology methods in the same practical course. Peer-review is applied as a teaching method to foster cooperative learning of students with heterogeneous backgrounds. Evaluation results indicate acceptance and appreciation of this approach.

To understand functions of biomolecules such as proteins, not only structures but their conformational change and kinetics are important to be characterized but its atomistic details are hard to obtain both experimentally and computationally. We review our recent computational studies using novel enhanced sampling techniques for conformational sampling of biomolecules and calculations of their kinetics. For efficiently characterizing the free energy landscape of a biomolecule, we introduce the multiscale enhanced sampling method, which uses a combined system of atomistic and coarse-grained models. Based on the idea of Hamiltonian replica exchange, we can recover the statistical properties of the atomistic model without any biases. We next introduce the string method as a path search method to calculate the minimum free energy pathways along a multidimensional curve in high dimensional space. Finally we introduce novel methods to calculate kinetics of biomolecules based on the ideas of path sampling: One is the Onsager-Machlup action method, and the other is the weighted ensemble method. Some applications of above methods to biomolecular systems are also discussed and illustrated.

Arylamine N-acetyltransferases (NATs) are cytosolic enzymes, highly polymorphic, present in both eukaryotes and prokaryotes. These enzymes play an important role in the detoxification and activation of xenobiotics as well as in the synthesis of endogenous compounds. Specific NATs have been pointed out in the literature as possible therapeutic targets. In particular, the human NAT1, for the treatment of certain cancers, and the NAT from M. tuberculosis (TBNAT), for the treatment of tuberculosis. This paper describes an in silico approach to prospect and select potentially inhibitors of NAT1 and TBNAT from the Traditional Chinese Medicine (TCM) using free available tools. A library with ligands from TCM was previously screened in order to select only compounds with optimal pharmacological properties. The affinity of the selected ligands with respect to NAT enzymes was then evaluated by virtual screening (VS). Subsequently, the complexes with the best ligands were submitted to molecular dynamics (MD) simulations aiming to obtain better quality information on affinity and selectivity. The results for one specific ligand, ZINC14690579, indicated its potential for affinity and selectivity. ZINC14690579 structure may represent the discovery of a new scaffold for future development of NAT inhibitors.

Paving blocks are concrete pieces placed in exposed places to the weather, which are sub-jected to loads and wear. Hence, quality control in the manufacture of paving blocks is es-sential to guarantee the properties and durability of the product in construction projects. In Ecuador, the requirements are described in the Ecuadorian technical standard "NTE INEN 3040", and tensile splitting strength is a fundamental requirement to guarantee product quality. It is analyzed using quality control measurements such as dimensions, the weight of the fresh paving block in the vibro-compacted process, and the percentage of water absorption in order to know how the variables influence and manage to predict the tensile splitting strength to avoid product non-conformity in advance, having a timely and better control of the manufacturing process. The data was obtained from a company that can produce 30 000 units per day of rectangular paving blocks with 6 cm thickness. Mul-tivariate models such as multiple linear regression, regression trees, random forests and neural networks are performed to predict the tensile splitting strength variable through two groups of predictors; the first group is the thickness mm, width mm, length mm, mass of fresh paving block g and percentage of water absorption %. The second group of pre-dictor variables is the density of the fresh paving block kg/m3 and the percentage of water absorption %. It is concluded that the multiple linear regression method performs better in predicting the first group of predictor variables with a mean square error (MSE) of 0.110086, followed by the neural network without hidden layers resulting in an MSE of 0.112198. The best method for the second set of predictors was the neural network with-out hidden layers with a mean square error ( MSE ) of 0.112402, closely followed by the multiple linear regression model with an MSE of 0.115044.

The results of physico-chemical studies of individual fruit parts, including crusts, partitions, juice and seeds themselves, extracted from immature (green), unripe and mature fruits of three harvest periods are presented: 20.VII, 01.IX and 15.X. The analyses were carried out in 2019-20 during the period of active growth and ripening of fruits in the varieties Spring, Iridanaly, Guleisha pink and wild pomegranate from the Geokchay region (Azerbaijan) using standard and generally accepted physico-chemical methods. The ripe fruit (130-288 g) consisted of 60-113% of the peel (peel together with partitions), 53-140% of the juice and 17-85% of the seeds themselves. The edible part of the ripened fruits (53.85-73.2 of the total weight of the fruit) consisted of 58.54-78.65% juice and 21.35 -41.46% seeds, fresh juice contained 15.7-17.7% solids, including 12.04-13.84% sugar, 0.17-0.30% protein, 0.15—0.23% pectin, 0.30-0.40% ash and 0.26-0.57% total polyphenols. The concentrations of solids, protein, ash and total polyphenols in the seeds themselves, remaining after the extraction of juice from the grains of ripe fruits, were 50.0-58.2, 4.13-5.75, 0.60-1.0 and 0.08-0.32%, respectively. There were fewer total polyphenols, flavonoids, chlorogenic acids, catechins and leucoanthocyanins in ripe fruits, and more ascorbic acid, anthocyanins and proanthocyanidins than in unripe ones. The period from the second half of July to the beginning of September is the time of a real “boom” of common polyphenols.

Emerging evidence suggests that low socioeconomic status (SES) home environments may play a role by promoting excess energy intake through a lack of access to non-food reinforcers. Because of the deleterious effects of SES related disparities on child health and development, feasible and culturally acceptable interventions are urgently needed. Community-based music enrichment programs may be an ideal intervention strategy. In collaboration with a local non-profit organization and music studio, we conducted a pilot randomized controlled trial to assess the effects of a music enrichment program versus playdate control in a group of 9-24-month-old healthy infants (N = 16). Overall, we found some intervention effects on relative reinforcing value of food (RRVfood) and the home environmental enrichment measures (i.e., increased music use at home and home language environment). Our intervention demonstrated large effects on an increased use of music at home. We did not find significant group differences on the RRVfood and home language environment, but some of the effect sizes were medium-to-large. Results also suggest that our intervention is feasible and acceptable. Parent feedback indicated the intervention was well-liked and steps we took to help reduce barriers worked. Music enrichment programs maybe a high-impact, low-cost strategy to address socioeconomic disparities.

Gas-water relative permeability curve is the foundation of gas reservoir dynamic analysis and numerical simulation. It is generally obtained through gas displacing water experiment. Referring to the existing national standards, gas-water relative permeability test is carried out for low-permeability and tight sandstone. The flow is discontinuous and the curve smoothness is poor, which affects the application of gas-water relative permeability curve. Based on the comparative analysis of a large number of mercury injection and NMR experimental results of low-permeability and tight sandstone, a method to characterize the throat radius distribution of low-permeability tight sandstone based on NMR T2 spectrum is explored. Combined with high-speed centrifugal experiment, the calculation formulas of core water saturation, phase relative permeability of gas-water under different centrifugal force are established. A new method of "nuclear magnetic resonance + high-speed centrifugation" for gas-water relative permeability curve test of low-permeability and tight sandstone is formed, and the test is carried out on Sulige low-permeability tight sandstone core. The results show that: (1) The shape of cumulative distribution curve of throat radius by mercury injection method is basically consistent with that of T2 relaxation time by NMR, and there is a good corresponding relationship between them. (2) The centrifugation process is similar to the gas displacing water process. With the decrease of water saturation, water centrifugation in rock core becomes more and more difficult until it become irreducible. (3) The test process of the new method is unified and standard and up to 6 cores can be tested at the same time. The calculation results of water saturation and relative permeability curve are reliable and the integral curve is smooth, which greatly improves the test efficiency of gas-water relative permeability curve in low-permeability and tight sandstone. The new method can be widely used to study the gas-water two-phase seepage law in low-permeability and tight sandstone gas reservoir.

A model for enabling the production of lower carbon cement paste is proposed in this research. The model is based on predicting the strength of cement pastes with partial replacement of wheat straw ash (WSA) and silica fume (SF), two major wastes of agricultural and industrial production. The model is set up based on response surface methodology and Box-Behnken design, and included a suite of mechanical tests with distinct replacements following a micro an meso characterization. The model shows capability for predicting strength of any cement paste, including partial substitution of WSA and/or SF at any combination level with excellent accuracy, which is verified with three validation mixtures demonstrating maximum errors of less than 6% at the three ages. The analysis of the response surface evidences that any cement replacement in the range of 0-20% WSA and above 5% SF allows the reduction of the carbon footprint by maximizing the incorporation of both wastes. The proposed model can be used by setting the required strength of cement paste and calculating the maximum possible replacement, which should contribute to making the construction industry more sustainable by utilizing local waste.

A new clothing resistance model is described and applied to characterize the human thermal and moisture climates. The climate was described by the thermal (rcl,t) and evap-orative (rcl,e) resistances of comfortable, imaginary clothing. The key input variable of the model is the rate of sweating (λEsw). Since sweating is an individual-specific process, the model applies to the individual. The observations were carried out by a single individual in Martonvásár (Hungarian lowland, Central Europe) in the summer of 2023 and the winter of 2024. During the observations, the observer walked at a speed of 1.1-1.7 ms-1 in weather-appropriate clothing. Among the results, we would highlight the following: Dur-ing large environmental heat surpluses, the rcl,t values were found to be between 0.1-0.5 clo-t (clo-t = 0.155 m2·℃·W-1), while the rcl,e values fell between 0.4-0.8 clo-e (clo-e = 0.155 m2·hPa·W-1). The values of the parameters close to 0 were caused by intense sweating (λEsw > 200 Wm-2). The applicability of the model is limited and largely depends on the rela-tionship between λEsw and the metabolic heat flux density.

The paper describes an application of machine learning approach for parameter optimization. The method is demonstrated for the elasto-viscoplastic model with both isotropic and kinematic hardening. It is shown that the proposed method based on long-short term memory networks enabled to obtain reasonable agreement of stress-strain curves for cyclic deformation in low-cycle fatigue regime. The main advantage of the proposed approach over traditional optimization schemes lies in the possibility to get parameters for a new material without the necessity to conduct any further optimizations. As the power and robustness of the developed method was demonstrated on the very challenging problem (cyclic deformation, crystal plasticity, self-consistent model, isotropic and kinematic hardening), it is directly applicable to other experiments and models.

Abstract—The static and fatigue analysis of plates with holes, made of 2D woven roving composites, is conducted. The parametrization of convex holes is proposed. Experimental results of specimens without holes and with different shapes of notches are discussed. The fatigue behaviour is considered with the use of the low cycle fatigue method. The analysis is supplemented by the numerical finite element modeling. The present work is an extension of the results discussed in the literature. The finite element modeling of plates with holes is presented in details in Ref [1-3] including also the problems of the accuracy. The experimental results and the form of specimens are shown in Ref [4]. Two parametrical description of static and fatigue behaviour of plates with holes characterizes the goal and the novelty of the paper. The fuzzy approach is employed to reduce the number of experimental data [5].

While providing safe water for the rural poor is considered a basic human right, there are numerous issues associated with existing technologies with shortcomings. Performance issues have continued to fail to meet the needs of impoverished families due to issues including high cost, difficulties with performance, and continuing needs for maintenance. These issues have severely interfered the safe water accessibility. Key aspects of the Guelph Water Filter (GWF) system can avoid/minimize many of these issues. The GWF as described herein enables delivery of low cost, long-term performance at 3Log removal of E.coli and can deliver 1 to 3 L of treated water per hour. The GWF is simple to operate, has an ability to provide sufficient water for a family, maintains longevity of performance, is easy to maintain and has protection against breakage during the cleaning process, is repairable at village level, and operates using a sizable reservoir of water to supply raw water, meaning the technology does not need to be refilled frequently. Hence, the capability of the novel GWF technology is shown to bypass many of the troublesome features of alternative low-tech water treatment technologies. The potential for the GWF to function for 2 days continuously avoids the need for young girls to fetch raw water frequently during a day, thereby enabling them to attend school. Hence, the GWF enhances the potential to result in ‘safe water and full schools’, providing the opportunity for girls to receive education and capture socio-economic benefits for the community.

: Low-temperature growth of diamond films by chemical vapor deposition (CVD) method is not so widely reported and especially its initial periods of nucleation and growth phenomenon are of particular interest to the researchers. Four sets of substrates were selected for growing diamond films by linear antenna microwave plasma enhanced CVD (LA-MPCVD). Among them, silicon and sapphire substrates were pre-treated with detonation nanodiamond (DND) seeds before diamond growth for enhancement of its nucleation. On the other hand, carbon nanotube (CNT) films on Si substrates were also used as another template for LA-MPCVD diamond growth. In order to enhance the diamond nucleation during CVD growth, some of the CNT films were again pre-treated by electrophoretic deposition (EPD) of diamond nanoparticles. All these substrates were then put inside the LA-MPCVD chamber for growing diamond films under variable processing conditions. Microwave input powers (1100 – 2800 W), input power modes (pulse or continuous), antenna to stage distances (5 - 6.5 cm), process gas recipes (with or without CO2), methane gas percentages (3 - 5%), deposition times (11 – 120 minutes) were altered to investigate their effect on the growth of diamond film on the pre-treated substrates. The substrate temperatures were found to vary from as low as 170oC to a maximum of 307oC during the alteration of the different processing parameters. Contrary to the conventional MPCVD, it was observed that during the first hour of LA-MPCVD diamond growth, DND seeds or the nucleating structures, do not coalesce together to make a continuous film. Deposition time was the most critical factor in fully covering the substrate surfaces with diamond film, since the substrate temperature could not become stable during the first hour of LA-MPCVD. CNT was found to be oxidised rapidly under LA-MPCVD plasma conditions; therefore, a CO2-free process gas recipe was used to reduce CNT burning. Moreover, EPD-coated CNT was found to be less oxidised by the LACVD plasma during diamond growth.

Human epidermal growth factor receptor 2 (HER2) belongs to the ErbB family, a group of four transmembrane glycoproteins with tyrosine kinase activity, all structurally related to the epidermal growth factor receptor (EGFR). These tyrosine kinases are involved in the transmission of cellular signals controlling normal cell growth and differentiation. If this transmission goes awry, it can lead to dysregulated growth of the cell. HER2 specifically can be implicated in the pathogenesis of at least eight malignancies. HER2 positivity quickly became a well characterized indicator of aggressiveness and poor prognosis, with high rates of disease progression and mortality. After realizing the implication of HER2, it first became investigated as a target for treatment in breast cancer, and later expanded to areas of research in other cancers types. To this day, the most therapeutic advancements of anti-HER2 therapy have been in breast cancer, however, there have been strong advancements made in the incorporation of anti HER2 therapy in other cancer types as well. This comprehensive review dissects HER2 to its core incorporating the most up to date information. The topics touched upon are discussed in detail and up to 200 published sources from the most highly recognized journals have been integrated. The importance of knowing about HER2 is exemplified by the groundbreaking advancements that have been made, and the change in treatment plans it has brought to the oncological world in the last twenty years. Since, its ground breaking discovery there has been significant breakthroughs in knowledge regarding the actual receptor, the receptors biology, its mechanism of action, advancements in tests to detect HER2 and significant strides on how to best incorporate targeted treatment. Due to the success of this field thus far, the review concludes by discussing the future of novel anti-HER2 therapy currently in development that everyone should be aware of.

Iterative Stochastic decoding is an alternative to standard fixed-point decoding of Low-density parity check codes (LDPC) to reduce inter-node routing. In this paper, we propose a Flexible Field-Programmable Gate Array (FPGA)-Based Stochastic decoding (SD) hardware architecture for LDPC codes in the Fifth-Generation (5G) New Radio (NR) Standard that supports decoding of set of various code rates. This decoder’s runtime flexibility is desirable to switch a better performing code rate automatically based on the channel conditions without the extra time needed for reprogramming of FPGA. An offline design method is implemented to generate the hardware description language (HDL) code description of the decoder for the required code-rate set, which is further synthesized and integrated into the Xilinx Kintex-7 series FPGA board to determine the hardware resource utilisation and processing throughput. The Synopsys design tools were employed during both the simulation and synthesis stages, in combination with TSMC 65-nm CMOS standard cell technology, to facilitate comparative analysis. Compared with state-of-the-art designs, the proposed architecture reduces hardware utilization by up to 26% and achieved energy efficiency by 52%.

Our objective was to evaluate whether pregnancy is prolonged by use of a proteomics-based maternal serum screening test followed by treatment interventions. This is a secondary analysis of the PREVENT-PTB randomized trial comparing screening with the PreTRM test versus no screening. The primary trial analysis found no significant between-group difference in preterm birth rate. Rather than considering a dichotomous outcome (preterm vs term), we treated gestational age at birth as a continuous variable using survival analysis. We also evaluated between-group difference in NICU length of stay and duration of respiratory support. Results indicated that pregnancy was significantly prolonged in subjects screened with PreTRM test compared to controls (adjusted hazard ratio 0.53, 95% confidence interval 0.36-0.78, P <0.01). Newborns of screened subjects had significantly shorter NICU stay but no significant decrease in duration of respiratory support. In the PreTRM screen-positive group, interventions that were associated with pregnancy prolongation included care management and low-dose aspirin but not 17-hydroxyprogesterone caproate. We concluded that screening with the PreTRM test followed by interventions for screen-positive pregnancies can prolong pregnancy and reduce NICU-LOS.

Applications for Wireless Sensor Networks (WSNs) range from monitoring the environment to automating factories. However, sustained and effective functioning is made more difficult by Sensor Nodes (SNs) limited energy supplies in which optimization is the main issue. So with the aim of increasing the lifespan by decreasing the energy consumption of WSN, Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol with Deep Learning (DL) algorithm is analyzed in this paper. LEACH is a hierarchical mechanism that elects Cluster Heads (CHs) and regularly rotates their positions in order to allocate energy use effectively by using the same amount of energy. However, Deep Learning (DL) method is used to further improve energy optimization. In many applications, the types of Deep Learning methods like Artificial Neural Networks (ANNs) have shown to be very useful. Using this method, WSNs may make more efficient decisions that reduce energy consumption. Data aggregation, duty cycling, and transmission protocols may all be optimized by Deep Learning model's ability to recognize patterns and forecast network behavior. This results in lower energy consumption, a longer lifespan for the network, and better overall performance.

Powerful emitters of the ultraviolet C (UVC) light in the wavelength range of 230-280nm are necessary for the development of effective and safe optical disinfection technologies, high-sensitive optical spectroscopy and non-line-of-sight optical communication. This review considers such UVC-emitters with electron-beam pumping of heterostructures with quantum wells in the (Al,Ga)N material system. The important advantages of these emitters include the absence of the critical problem of p-type doping and the possibility of achieving record (up to several tens of watts for peak values) output optical power values in the UVC range. The review consistently considers about a decade of world experience in the implementation of various UV emitters with various types of thermionic, field-emission, and plasma-cathode electron guns (sources) used to excite various designs of active (light-emitting) regions in heterostructures with quantum wells AlxGa1-xN/AlyGa1-yN (x = 0 − 0.5, y = 0.6 − 1) fabricated either by metal-organic chemical vapor deposition or by plasma-activated molecular beam epitaxy. Special attention is paid to the production of heterostructures with multiple quantum wells/two-dimensional(2D) quantum disks GaN/AlN with a monolayer (1ML ~ 0.25nm) thickness, which ensures a high internal quantum efficiency of radiative recombination in the UVC range, low elastic stresses in heterostructures, and a high output UVC-optical powers.

The DNS of film boiling requires strong computational resources that are difficult to obtain for a daily CFD use by the practitioners of the industrial R&D experts. On the other hand, the film boiling experiments are associated with the usage of the expensive and highly sophisticated apparatus, and the research to this end is found to be relatively difficult due to high heat flow rates that are present in the process itself. When combined with a transient heat conduction in a solid, the problem becomes significantly difficult. Therefore, a novel method in computation of conjugate heat transfer during film boiling in a quiescent liquid has been proposed in this paper. The method relies on the solution of mass, momentum and energy conservation equations in a two-fluid framework, supplemented with the appropriate closures. Furthermore, the turbulent flow has been found as an important parameter in obtaining the accurate solution of the temperature field evolution in a solid specimen, via the proper modeling of turbulent kinetic energy (TKE) value, that has been imposed as a constant value, i.e., the frozen turbulence approach. It was found, in addition, that the appropriate TKE value can be obtained by use of Kelvin-Helmholtz instability theory in conjunction with the boundary layer theory. The obtained results show excellent agreement with the experimental data within the first 15 s of the experiment, i.e., the first ca. 10 % of the total duration of the film boiling mode of heat transfer. Furthermore, the heat transfer coefficient has matched the error bands prescribed by the authors of the paper that has presented the correlations, whilst the averaged values are far beyond this band, i.e., are slightly more than 30 % higher. The further inspection has revealed a measure of similarity between the computational result of the volume fraction field distribution and the experiment, thus confirming the capability of the method to obtain realistic interface evolution in time. The method has shown full capability for further pursuing the industrial-scale film boiling problems that involve turbulent flow and the conjugate heat transfer approach.

In many developing countries, plastic waste management is left to citizens. This usually results in hazardous landfilling or open-air burning, leading to emissions that are harmful to human health and the environment. An easy, profitable, and clean method of processing and transforming the waste into value is required. In this context, this study provides an open-source methodology to transform low-density polyethylene drinking water sachets, into pavement blocks by using a streamlined do-it-yourself approach that requires only modest capital. Two different materials, sand, and ashes are evaluated as additives in plastic composites and the mechanical strength of the resulting blocks are tested for different proportion mix of plastic, sand, and ash. The best composite had an elastic modulus of 169MPa, a compressive strength of 29MPa, and a water absorptivity of 2.2%. The composite pavers can be sold at 100% profit while employing workers at 1.5X the minimum wage. In the West African region, this technology has the potential to produce 19 million pavement tiles from 28,000 tons of plastic water sachets annually in Ghana, Nigeria, and Liberia. This can contribute to waste management in the region while generating a gross revenue of 2.85 billion XOF (4.33 million USD).

There is a systematic exclusion of gender-based violence, safe abortion, reproductive cancers, infertility services, comprehensive sexuality education, sexuality services, and STI’s other than HIV in essential health packages in LMICs. To accelerate progress on sexual reproductive health (SRH), the Guttmacher–Lancet Commission proposed the adoption of these interventions into an essential health package of SRH services that should be universally available. In this commentary, we use a healthcare priority-setting processes lens to review the importance of these services for universal health coverage. We isolate inherent challenges in social value judgments for terminal, process and content evidence for their healthcare priority-setting. We then advance promising emerging practical examples from low to middle-income countries on evidence-informed decision-making processes. We recommend capacity development through regional support, generating equity and efficiency evidence and strengthening political and publicly acceptable processes to institutionalise and operationalise evidence-informed decision-making.

This paper is a mini literature review about electromagnetic field’s effects on cells, tissues and new treatment modalities. We have reviewed a papers which have been published in high quality journals in the last 5 years as two authors. This review’s aim is to be a resource for experimental studies about electricity’s effects on cell biology and pathophysiology. As a result of this literature review, we found that especially extremely low electric frequency and intermediate frequency fields have very important pathophysiological effects. We have mentioned four important expressions on this subject; electroporation, electrofusion, electrochemotherapy, gene electrotransference. Two different new treatment approaches have been developed by use of these two important electrical waves. First is tumor treating fields and the other is pulsed electric fields. Most studies in literature have been done with extremely low frequency and pulsed electric fields. In terms of diseases, most studies are about glioblastoma multiforme and malign melanoma.Most studies in literature have been done with extremely low frequency and pulsed electric fields. In terms of diseases, most studies are about glioblastoma and melanoma.

Selenium-rich Au-Ag mineralization has been discovered in the Kremnica ore district, central Slovakia. The mineralization is hosted by a single quartz-dolomite vein hosted by Neogene propyllitized andesites of the Kremnica stratovolcano. Ore mineralogy and crystal chemistry of individual ore minerals have been studied here. The early base-metal ore mineralization composed of pyrite, sphalerite and chalcopyrite lacks selenium, whereas the superimposed Au-Ag paragenesis is Se-enriched. The Au-Ag alloys, uytenbogaardtite, minerals of the galena-clausthalite series, acanthite-naumannite series, diaphorite, miargyrite, pyrargyrite-proustite, polybasite group, minerals of the tetrahedrite group and andorite branch (andorite IV, andorite VI, Ag-excess fizélyite), freislebenite, and rare Pb-Sb sulphosalts (scaiinite, robinsonite, plagionite) have been identified here. Besides selenides, the most Se-enriched phases are miargyrite, proustite-pyrargyrite, and polybasite-pearceite, whose Se contents are among the highest reported worldwide. In addition, one new phase has been found, corresponding to a Se-analogue of pearceite containing 2.08 - 3.54 apfu Se. The style of mineralization, paragenetic situation, and chemical trends observed in individual minerals are comparable to those of Au-Ag low-sulphidation epithermal Au-Ag mineralizations of the Kremnica and neighboring Štiavnica and Hodruša-Hámre Ore Districts, however, the pronounced enrichment in selenium is a specific feature of the studied vein only.

The application of the sensors optical fiber in the areas of scientific instrumentation and industrial instrumentation is very attractive due to its numerous advantages. In the industry of civil engineering for example, quasi-distributed sensors made with optical fiber are used for reliable strain and temperature measurements. Here, a quasi-distributed sensor in the frequency domain is discussed. The sensor consists of a series of low-finesse Fabry-Perot interferometers where each Fabry-Perot interferometer acts as a local sensor. Fabry-Perot interferometers are formed by pairs of identical low reflective Bragg gratings imprinted in a single mode fiber. All interferometer sensors have different cavity length, provoking the frequency-domain multiplexing. The optical signal represents the superposition of all interference patterns which can be decomposed using the Fourier transform. The frequency spectrum is analyzed and sensor´s properties were defined. Following, a quasi-distributed sensor was numerically simulated. Our sensor simulation considers sensor properties, signal processing, noise system and instrumentation. The numerical results show the behavior of resolution vs. signal-to-noise ratio. From our results, the Fabry-Perot sensor has high resolution and low resolutions. Both resolutions are conceivable because the FDPA algorithm elaborates two evaluations of Bragg wavelength shift

Severe acute respiratory infection (SARI) is mainly caused by viral pathogens, with a high prevalence in high-risk populations such as infants and older adults. Co-infections by different viruses are frequent and, in some cases, associated with severe disease outcomes. Purpose: The main purpose of this study was to identify respiratory viruses circulating in Barranquilla during the COVID-19 pandemic peaks and estimate the prevalence of viral co-infections in samples from individuals with different degrees of respiratory infection. Methods: Between August and October 2021, 101 samples were collected from individuals with influenza-like illness (ILI) by the District Health Laboratory of Barranquilla and four local health care institutions and analyzed at Universidad Simón Bolívar. Eighteen respiratory viruses, including SARS-CoV-2, were analyzed via qRT-PCR using nasal swabs or nasopharyngeal aspirate samples. Results: Of the 101 study individuals, 56 were male and 45 were female (55.5% and 44.5%, respectively); 25.7% of individuals were infected with at least one of the evaluated viruses. Respiratory syncytial virus (RSV) and human rhinovirus (HRV) were the two most frequently detected viruses (30.7% and 15.4% of total positives, respectively). Co-infections with two or more respiratory viruses accounted for 42% of the total positive cases. Conclusion: Our findings indicate the presence of different respiratory viruses in swab or nasopharyngeal aspirate samples from individuals with ILI, including coinfection. These results reveal the circulation of several respiratory viruses in the city of Barranquilla, confirming their importance as potential causes of SARI in Colombia and the need for their active surveillance.

The present article describes the synthesis of an isonicotinate-derived meso-arylporphyrin, that has been fully characterized by spectroscopic methods (including fluorescence spectroscopy), as well as by elemental analysis and by HR-MS. The structure of a n-hexane monosolvate has been determined by single crystal X-ray diffraction analysis. The radical scavenging activity of this new porphyrin against the 2,2-diphenyl-1-picrylhydrazyl (DDPH) radical has been measured. Its antifungal activity against three yeast strains (C. albicans ATCC 90028, C. glabrata ATCC 64677 and C. tropicalis ATCC 64677) has been tested, using the disk diffusion and the microdilution methods. Whereas the measured antioxidant activity was low, the porphyrin showed moderate but encouraging antifungal activity. Finally, a study of its effect on the germination of lentil seeds revealed interesting allelopathic properties.

We hereby describe an efficient method for the preparation of a series of new 1-substituted 1,2,3-triazole-based acetaminophen derivatives through a clean, good-yielding, simple, and expeditious procedure based on the O-propargylation reaction of the acetaminophen (APAP) obtained from expired commercial tablets and the CuBr(PPh3)3-catalyzed Huisgen reaction be-tween O-propargylated APAP and diverse organoazides prepared from commercially available anilines as available starting reagents. An interesting nitric oxide-releasing 1,2,3-triazole hybrid of APAP was also obtained easily using the developed method. The structures of the designed hybrid compounds, which are expected to be pharmacologically active, were fully characterized by FT-IR, 1H- and 13C-NMR and are reported for the first time. According to the in-silico studies performed in this work and literature analysis, these hybrids are interesting models in search of new pharmacological nontoxic agents endowed with anti-inflammatory and anticancer properties.

In this article, the biocatalytic oxidation of ethanol into acetaldehyde was studied using a catalase entrapped within monolithic polyampholyte cryogel, p(APTAC-co-AMPS), derived from an anionic monomer, 2-acrylamido-2-methyl-1-propanesulfonic acid sodium salt (AMPS), and a cationic monomer, (3-acrylamidopropyl) trimethylammonium chloride (APTAC) as catalyst. Macroporous polyampholyte cryogels containing various amounts of catalase were synthesized in situ under cryo-polymerization conditions at a molar ratio of monomers [APTAC]:[AMPS] = 75:25 mol.% in the presence of 10 mol.% cross-linking agent, N,N-methylenebisacrylamide (MBAA). The conversion of ethanol into acetaldehyde in good-to-high yields was observed in flow-through and batch type reactors under optimal conditions: at T = 10-20 C, pH = 7.1, [C2H5OH]:[H2O2] = 50:50 vol.%. According to SEM image the pore sizes of p(AMPS-co-APTAC) cryogel vary from 15 to 55 μm. The catalytic activity of catalase entrapped within monolithic polyampholyte cryogel in the conversion of ethanol into acetaldehyde was evaluated through the determination of such kinetic parameters as Michaelis constant (Km), the maximum enzymatic rate (Vmax), activation energy (Ea), turnover number (TON) and turnover frequency (TOF). The catalase encapsulated within monolithic polyampholyte cryogel exhibits a high conversion of ethanol into acetaldehyde. The advantages and disadvantages of flow-through and batch type reactors were highlighted.

During COVID-19 pandemic, drug repurposing represented an effective strategy to obtain quick answers to medical emergencies. Basing on previous data on Methotrexate (MTX), we evaluated the anti-viral activity of several DHFR inhibitors in two cell lines. We observed that this class of compounds showed a significant influence on the virus-induced cytopathic effect (CPE) partly associated to the intrinsic antimetabolic activity of these drugs, but also to a specific antiviral function. To elucidate the molecular mechanisms, we took advantage of our EXSCALATE platform for in-silico molecular modelling and further validated the influence of these inhibitors on nsp13 and viral entry. Interestingly, Pralatrexate and Trimetrexate showed superior effects in counteracting the viral infection compared to other DHFR inhibitors. Our results indicate that their higher activity is due to their polypharmacological and pleiotropic profile. These compounds can thus potentially give a clinical advantage in the management of SARS-CoV-2 infection in patients already treated with this class of drugs.

In this work we study the recently developed parametrized partition function formulation and show how we can infer the thermodynamic properties of fermions based on numerical simulation of bosons and distinguishable particles at various temperatures. In particular, we show that in the three dimensional space defined by energy, temperature and the parameter characterizing parametrized partition function, we can map the energies of bosons and distinguishable particles to fermionic energies through constant-energy contours. We apply this idea to both noninteracting and interacting Fermi systems and show it is possible to infer the fermionic energies at all temperatures, thus providing a practical and efficient approach to obtain thermodynamic properties of large fermion systems with numerical simulation. As an example, we present energies for up to 50 noninteracting fermions and up to 20 interacting fermions at all temperatures and show good agreement with the analytical result for noninteracting case.

The main regulatory factors during the adaptation of cancer cells to hypoxic stress are the hypoxia-inducible factors (HIFs), which are being increasingly recognized as an interesting and challenging target for the design of new chemotherapeutic molecules. HIF2A was found to have an large internal hydrophilic cavity within its PAS-B domain, unique to this sub-unit and is suggested to be a possible ligand-binding site. Regulation of HIF2A by cellular molecules is still greatly unknown. In This paper we have employed in-silico techniques, such as molecular docking and dynamic simulation, to design new direct inhibitors against HIF-2A subunit via targeting one of its critical domains and the final top screened molecules have been tested on hypoxic cancer cells for further validation of their inhibitory potential. we targeted the hydrophilic cavity inside the PAS-B domain of the HIF2A to identify novel molecules with a high binding capacity. Virtual Screening methodology was used for molecular docking of NSC library against the target domain inside the HIF2A PAS-B domain with the top 5% compounds with significant MolDock and Re-rank scores were selected for further analysis. The NSC 106416, NSC 217021, NSC 217026, and NSC 215639 compounds were selected based on their docking scores. NSC 215639 had the minimum polar solvation energy and also had a relative strong binding energy. NSC 217026 had the strongest binding energy among other compounds.

Phylogenomic analyses have revolutionized the study of biodiversity, but they have revealed that estimated tree topologies can depend, at least in part, on the subset of the genome that is analyzed. For example, estimates of trees for avian orders differ if protein coding or non-coding data are analyzed. The bird tree is a good study system because the historical signal for relationships among orders is very weak, which should permit subtle non-historical signals to be identified, while monophyly of orders is strongly corroborated, allowing identification of strong non-historical signals. Hydrophobic amino acids in mitochondrially-encoded proteins, which are expected to be found in transmembrane helices, have been hypothesized to be associated with non-historical signals. We tested this hypothesis by comparing the evolution of transmembrane helices and extramembrane segments of mitochondrial proteins from 420 bird species, sampled from most avian orders. We estimated amino acids exchangeabilities for both structural environments and assessed the performance of phylogenetic analysis using each data type. We compared those relative exchangeabilities with values calculated using a substitution dataset for transmembrane helices from a variety of sampled set of nuclear- and mitochondrially-encoded proteins, allowing us to compare the bird-specific mitochondrial models with a general model of transmembrane protein evolution. To complement our amino acid analyses, we examined the impact of protein structure on patterns of nucleotide evolution. Models of transmembrane and extramembrane sequence evolution for amino acids and nucleotides exhibited striking differences, but there was no evidence for strong topological data type effects. However, incorporating protein structure into analyses of mitochondrially-encoded proteins improved model fit. Thus, we believe that considering protein structure will improve analyses of mitogenomic data, both in birds and in other taxa.

Under the oxidative stress condition, the small RNA (sRNA) Oxys that acts as essential post-transcriptional regulators of gene expression is produced and plays a regulatory function with the assistance of the RNA chaperone Hfq protein. Interestingly, experimental studies found that the N48A mutation of Hfq protein could enhance the binding affinity with OxyS while resulting in defection of gene regulation. But, how the Hfq protein interacts with sRNA Oxys and the origin of the stronger affinity of N48A mutation are both unclear. In this paper, molecular dynamics (MD) simulations were performed on the complex structure of Hfq and OxyS to explore their binding mechanism. The molecular mechanics generalized Born surface area (MM/GBSA) and interaction entropy (IE) method were combined to calculate the binding free energy between Hfq and OxyS sRNA, and the computational result is in excellent correlation with the experimental result. Per-residue decomposition of the binding free energy revealed that the enhanced binding ability of the N48A mutation mainly comes from the increased van der Waals interactions (vdW). This research explores the binding mechanism between Oxys and chaperone protein Hfq, and revealed the origin of the strong binding affinity of N48A mutation. The results provided important insights on the mechanism of gene expression regulation affected by protein mutations.

Course-based Undergraduate Research Experiences (CUREs) in high-enrollment, introductory classes are a 37 potentially transformative approach to retaining more students in STEM majors. We developed and piloted a CURE 38 in the introductory biology courses at the University of Washington. This CURE focuses on analyzing experimental 39 evolution of antibiotic resistance in Escherichia coli and generates data on two topics relevant to clinical practice: 40 compensatory mutations and cross-drug effects. By studying mutations in central cellular machinery that confer drug 41 resistance, students not only gain insight into fundamental cellular phenomena, but also recognize the molecular 42 basis of a medically important form of evolutionary change, connecting genetics, microbiology, and evolution.

ND1 subunit possesses the majority of the inhibitor binding domain of the human MRC-I. This is an attractive target for the search for new inhibitors that seek mitochondrial dysfunction. It is known, from in vitro experiments, some metabolites from Annona muricata called acetogenins have important biological activities such as anticancer, antiparasitic, and insecticide. Previous studies propose an inhibitory activity of bovine MRC-I by bis-THF acetogenins such as annocatacin B, however, there are few studies on its inhibitory effect on human MRC-I. In this work, we evaluate the molecular and energetic affinity of the annocatacin B molecule with the human ND1 subunit in order to elucidate its potential capacity to be a good inhibitor of this subunit. For this purpose, QM optimizations, MD simulations and MM/PBSA analysis were performed. As a control to compare our outcomes, the molecule rotenone, which is a known MRC-I inhibitor, was chosen. Our results show that annocatacin B has a greater affinity for the ND1 structure, its size and folding were probably the main characteristics that contributed to stabilize the molecular complex. Furthermore, the MM/PBSA calculations showed a 35% stronger BFE compared to the rotenone complex. Detailed analysis of the BFE shows that the aliphatic chains of annocatacin B play a key role in molecular coupling by distributing favorable interactions throughout the major part of the ND1 structure. These results are consistent with experimental studies that mention that acetogenins may be good inhibitors of MRC-I.

Molecular modeling is widely utilized in subjects including but not limited to physics, chemistry, biology, materials science and engineering. Impressive progress has been made in development of theories, algorithms and software packages. To divide and conquer, and to cache intermediate results have been long standing principles in development of algorithms. Not surprisingly, Most of important methodological advancements in more than half century of molecule modeling are various implementations of these two fundamental principles. In the mainstream classical computational molecular science based on force fields parameterization by coarse graining, tremendous efforts have been invested on two lines of algorithm development. The first is coarse graining, which is to represent multiple basic particles in higher resolution modeling as a single larger and softer particle in lower resolution counterpart, with resulting force fields of partial transferability at the expense of some information loss. The second is enhanced sampling, which realizes "dividing and conquering" and/or "caching" in configurational space with focus either on reaction coordinates and collective variables as in metadynamics and related algorithms, or on the transition matrix and state discretization as in Markov state models. For this line of algorithms, spatial resolution is maintained but no transferability is available. Deep learning has been utilized to realize more efficient and accurate ways of "dividing and conquering" and "caching" along these two lines of algorithmic research. We proposed and demonstrated the local free energy landscape approach, a new framework for classical computational molecular science and a third class of algorithm that facilitates molecular modeling through partially transferable in resolution "caching" of distributions for local clusters of molecular degrees of freedom. Differences, connections and potential interactions among these three algorithmic directions are discussed, with the hope to stimulate development of more elegant, efficient and reliable formulations and algorithms for "dividing and conquering" and "caching" in complex molecular systems.

Starting from December 2019, coronavirus disease 2019 (COVID-19) has emerged as a once-in-a-century pandemic with deadly consequences, which urgently calls for new treatments, cures and supporting apparatuses. Remdesivir was reported by World Health Organization (WHO) as the most promising drug currently available for the treatment of COVID-19. Here, we use molecular dynamics simulations and free energy perturbation methods to study the inhibition mechanism of remdesivir to its target SARS-CoV-2 virus RNA-dependent RNA polymerase (RdRp). In the absence of a crystal structure of the SARS-CoV-2 RdRp, we first construct the homology model of this polymerase based on a previously available structure of SARS-CoV NSP12 RdRp (with a sequence identify of 95.8%). We then build the putative binding mode by aligning the remdesivir + RdRp complex to the ATP bound poliovirus RdRp. The putative binding structure is further optimized with molecular dynamics simulations and demonstrated to be stable, indicating a reasonable binding mode for remdesivir. The relative binding free energy of remdesivir is calculated to be -8.28 ± 0.65 kcal/mol, much stronger than the natural substrate ATP (-4.14 ± 0.89 kcal/mol) which is needed for the polymerization. The ~800-fold improvement in the K_d from remdesivir over ATP indicates an effective replacement of APT in blocking of the RdRp binding pocket. Key residues D618, S549 and R555 are found to be the contributors to the binding affinity of remdesivir. These findings demonstrate that remdesivir can potentially act as a SARS-CoV-2 RNA-chain terminator, effectively stopping its RNA reproduction, with key residues also identified for future lead optimization and/or drug resistance studies.

Alpha-fetoprotein (AFP) is a major embryo- and tumor-associated protein capable of binding and transporting variety of hydrophobic ligands including estrogens. AFP has been shown to inhibit estrogen receptor (ER)-positive tumor growth and this can be attributed to its estrogen-binding ability. Despite AFP has long been investigated, its three-dimensional (3D) structure has not been experimentally resolved and molecular mechanisms underlying AFP-ligand interaction remain obscure. In our study we constructed homology-based 3D model of human AFP (HAFP) with the purpose to perform docking of ERα ligands, three agonists (17β-estradiol, estrone and diethylstilbestrol) and three antagonists (tamoxifen, afimoxifene and endoxifen) into the obtained structure. Based on ligand docked scoring function, we identified three putative estrogen- and antiestrogen-binding sites with different ligand binding affinities. Two high-affinity sites were located in (i) a tunnel formed within HAFP subdomains IB and IIA and (ii) opposite side of the molecule in a groove originating from cavity formed between domains I and III, while (iii) the third low-affinity site was found at the bottom of the cavity. 100 ns MD simulation allowed studying their geometries and showed that HAFP-estrogen interactions occur due to van der Waals forces, while both hydrophobic and electrostatic interactions were almost equally involved in HAFP-antiestrogen binding. MM/GBSA rescoring method estimated binding free energies (ΔG_bind) and showed that antiestrogens have higher affinities to HAFP as compared to estrogens. We performed in silico point substitutions of amino acid residues to confirm their roles in HAFP-ligand interactions and showed that Thr132, Leu138, His170, Phe172, Ser217, Gln221, His266, His316, Lys453, and Asp478 residues along two disulfide bonds, Cys224-Cys270 and Cys269-Cys277 have key roles in both HAFP-estrogen and HAFP-antiestrogen binding. Data obtained in our study contribute to understanding mechanisms underlying protein-ligand interactions and anti-cancer therapy strategies based on ER-binding ligands.

In order to clarify the nature of the halogen bond (XB), we considered the prototype noble gas – dihalogen molecule (Ng-X2) systems, focusing on the nature, range and strength of the interaction. We exploited data gained from molecular beam scattering experiments with the measure of interference effects to obtain a suitable formulation of the interaction potential, with the support of high-level ab initio calculations, and charge displacement analysis. The essential interaction components involved in the Ng-X2 adducts have been characterized, pointing at their critical balance in the definition of the XB. Particular emphasis is devoted to the energy stability of the orientational Ng-X2 isomers, the barrier for the X2 hindered rotation, and the influence of the X2 electronic state. The present integrated study returns reliable force fields for molecular dynamics simulations in Ng-X2 complexes that can be extended to systems with increasing complexity and whose properties depend on the selective formation of XB.

Naturally occurring small molecules include a large variety of natural products from different sources that have confirmed activity against epigenetic targets. In this work we review chemoinformatic, molecular modeling and other computational approaches that have been used to uncover natural products as inhibitors of DNA metiltransferases, a major family of epigenetic targets with significant potential for the treatment of cancer and several other diseases. Examples of these computational approaches include docking, similarity-based virtual screening, and pharmacophore modeling. It is also commented the chemoinformatic-based exploration of the chemical space of naturally occurring compounds as epigenetic modulators which may have significant implications in epigenetic drug discovery and nutriepigenetics.

Quantum mechanics could be studied through polynomial algebra, as has been demonstrated by a work (“An approach to first-principles electronic structure calculation by symbolic-numeric computation” by A. Kikuchi). We carry forward the algebraic method of quantum mechanics through algebraic number theory; the basic equations are represented by the multivariate polynomial ideals; the symbolic computations process the ideal and disentangle the eigenstates as the algebraic variety; upon which one canbuild the Galois extension of the number field, in analogy with the univariate polynomial case, to investigate the hierarchy of solutions; the Galois extension is accompanied with the group operations, which permute the eigenstates from one to another, and furnish the quantum system with a non-apparent symmetry. Besides, this sort of algebraic quantum mechanics is an embodiment of the class field theory; some of the important consequences of the latter emerge in quantum mechanics. We shall demonstrate these points through simple models; we will see the use of computational algebra facilitates such sort of analysis, which might often be complicated if we try to solve them manually.

Neck circumference (NC), neck circumference to height ratio (NHtR) and neck circumference to weight ratio (NWtR) appear to be good candidates for the non-invasive management of non-alcoholic fatty liver disease (NAFLD). This study aimed to evaluate the ability of routine variables to assess and manage NAFLD in participants with obesity and NAFLD included in a 2-year nutritional intervention program. Anthropometric measurements, biochemical variables and imaging techniques were performed at different study time-points (baseline, 6, 12 and 24 months). The nutritional intervention significantly improved all anthropometric measurements as well as the glucose profile and the hepatic enzymes. NC and neck ratios combined with ALT levels and HOMA-IR showed good prediction ability for the hepatic fat content and hepatic steatosis at all the study time-points in a ROC analysis. The prediction ability of the combination panels improved when the weight loss variable was also considered. NC and neck ratios are easy anthropometric measurements that in combination with routine biochemical variables (ALT and HOMA-IR) showed good prediction ability of NAFLD. More research studies are necessary to validate the utility of these simple and easy variables as surrogate markers of NAFLD since their application could improve the prevention and management of this prevalent disease.

Northern Nigeria has had historically low antenatal care (ANC) utilization rates with poor health outcomes. Group antenatal care (gANC) improves ANC behavior and pregnancy outcomes. The gANC has been adopted in Kaduna and Kano states, Nigeria. This paper presents baseline findings from the evaluation of the implementation of the gANC program to support scaling in real-world setting. Baseline data were collected from a cohort of 1,269 and 1,200 pregnant women enrolled in gANC at health facilities in Kaduna and Kano states respectively from March to April 2024. Analyses of socio-demographic and pregnancy behavior data were done. Participants were mostly between ages 19-31 years, married or living with a partner, with over 50% having their own businesses. Over 62% and 34% had completed secondary or higher-level education with 60% and 80% living in urban areas in Kaduna and Kano States, respectively. In Kano State, >60% of the women had their last delivery at home with 41.6% not assisted by a skilled birth attendant. In Kaduna, >63% delivered in the hospital and >50% had skilled attendance during labor. Almost half had not used contraceptives previously. Subsequent longitudinal data will examine the impact of gANC utilization on perinatal outcomes.

Results-Based Financing (RBF) in pediatrics, in regions with scarce resources like Northern Uganda, provides an innovative approach to enhancing healthcare delivery. RBF aligns financial incentives with desired health outcomes, boosting service quality, efficiency, and effectiveness by tying compensation to achieving specific, measurable health targets. Lacor and Kalongo hospitals, before the introduction of RBF, faced numerous challenges, including limited resources, staffing shortages, and inconsistent quality of care. RBF adoption requires critical health outcomes to target, such as lowering child mortality rates, enhancing vaccination coverage, and increasing the frequency of timely prenatal care visits. The empirical application of RBF in pediatric services at Lacor and Kalongo Hospital from 2018 to 2024 shows improved healthcare quality and outcomes. Healthcare systems can identify ways to implement RBF models better, ensuring that financial incentives effectively contribute to attaining superior health outcomes.

In this study, the fundamentals of electroencephalography signals, their categorization into frequency sub-bands, the circuitry used for their acquisition, and the impact of noise interference on signal acquisition are examined. Additionally, design specifications for medical-grade and research-grade EEG circuits and a comprehensive analysis of various analog front-end architectures for electroencephalograph (EEG) circuit design are presented. Three distinct selected case studies are examined in terms of comparative evaluation with generic EEG circuit design templates. Moreover, a novel one-channel battery-supplied EEG analog front-end circuit designed to address the requirements of usage protocols containing strong com-pound muscle movements is introduced. Furthermore, a realistic input signal generator circuit is proposed that models the human body and the Electromagnetic Interference from its surroundings. Experimental simulations are conducted in 50 Hz and 60 Hz electrical grid environments to evaluate the performance of the novel design. The results demonstrate the efficacy of the proposed system, particularly in terms of bandwidth, portability, common mode rejection ratio , gain, suppression of muscle movement artifacts, electrostatic discharge and leakage current protection. Conclusively, the novel design is cost-effective and suitable for both commercial and research single-channel EEG applications. It can be easily incorporated in Brain Computer Interfaces and neurofeedback training systems.

In this work, an analog front-end (AFE) circuit for Electrocardiogram (ECG) detection system has been designed, implemented, and investigated in an industry-standard Cadence simulation framework using advanced technology node of 45 nm. The AFE consists of an instrumentation amplifier, a Butterworth band-pass filter (with fifth-order low-pass and second-order high-pass sections), and a second-order notch filter- all are based on two-stage, Miller-compensated operational transconductance amplifiers (OTA). The OTAs have been designed employing the $g_m/I_D$ methodology. Both the pre-layout and post-layout simulation were carried out. The layout consumes an area of 0.0058 mm$^2$ without the resistors and capacitors. Analysis of various simulation results were carried out for the proposed AFE. The circuit demonstrates a post-layout bandwidth of 239 Hz with a variable gain between 44 to 58 dB, a notch depth of -56.4 dB at 50.1 Hz, a total harmonic distortion (THD) of -59.65 dB (less than 1\%), an input referred noise spectral density of $

It’s well known that existing horizontal well drilling and hydraulic fracturing technology that is used to achieve large-scale cost-effective production from immature to low-moderate maturity continental shale in China, where the organic matter mainly exists in the solid form is fairly ineffective. To overcome the obstacles, in-situ conversion technology seems feasible, while implementing it in the target layer along with estimating the amount of expected recoverable hydrocarbon in such shale formations seems difficult. This is because there is no guideline to choose the most appropriate method and select relevant key parameters for this purpose. Hence, based on thermal simulation experiments during the in-situ conversion of crude oil from the Triassic Chang 73 Formation in the Ordos Basin and the Cretaceous Nenjiang Formation in the Songliao Basin, this deficiency in knowledge was addressed. First, relationships between the in-situ converted total organic carbon (TOC) content and the vitrinite reflectance (Ro) of the shales and between the residual oil volume and the hydrocarbon yield was established. Second, the yields of residual oil and in-situ converted hydrocarbon were measured, revealing their sensitivity to fluid pressure and crude oil density. In addition, a model was proposed to estimate the amount of in-situ converted hydrocarbon based on the TOC, hydrocarbon generation potential, Ro, residual oil volume, fluid pressure, and crude oil density. Finally, a method was established to determine key parameters on the final hydrocarbon yield from immature to low-moderate maturity organic material during in-situ conversion in shales. Following the procedure outlined in this paper, estimated recoverable in-situ converted oil in the shales of the Nenjiang Formation in the Songliao Basin was estimated to be approximately 292×108 tons, along with 18.5×1012 cubic meters of natural gas, in an area of approximately 8×104 square kilometers. Collectively, the method developed in this study is independent from the organic matter type and other geological and/or petrophysical properties of the formation and can be applied to other areas globally where there isn’t any available in-situ conversion thermal simulation experimental data.

In space application, hybrid pixel detectors of the Timepix family have been considered mainly for measurement of radiation levels and radiation dosimetry in low earth orbits. By the example of the Space Application of Timepix Radiation Monitor (SATRAM), we demonstrate the unique capabilities of Timepix-based miniaturized radiation detectors for particle separation. Using a novel method for proton spectrum reconstruction, we were able to measure the spectrum of protons trapped in the inner Van-Allen radiation belt, for the first time with a single-layer detector. We assess the measurement stability and the resiliency of the detector to the space environment demonstrating that, even though degradation is observed, data quality has not been affected significantly over more than 10 years. Based on the SATRAM heritage and the capabilities of the latest-generation Timepix-series chips, we discuss their applicability for use in a compact magnetic spectrometer for deep-space mission or in the high radiation environment of the Jupiter radiation belts, and their capability for use as single-layer X- and γ-ray polarimeter. The latter was supported by measurement of the polarization of scattered radiation in a laboratory experiment, where a modulation of 80% was found.

This study aimed to evaluate the proliferation and migration of fibroblast cells derived from chronic wounds and investigate the impact of low-level laser therapy (LLLT) on their growth and migration. A total of 60 dermal samples were obtained from three sites of chronic pressure ulcers and diabetic ulcers in 20 patients. Following collection in the operating room, the dermal samples were isolated using the procedure described by Freshney RI. Fibroblasts from the wound base (Site 1) exhibited a slow proliferation rate and a decrease in proliferative capacity. Fibroblasts from wound margins (Site 2) and adjacent healing skin (Site 3) could be successfully isolated and maintained for multiple generations without any morphological changes. Fibroblasts from chronic wounds at Sites 2 and 3 showed slower proliferation rates and reduced migration capabilities compared to normal dermal fibroblasts (control samples). The fibroblast cells were exposed to LLLT at different energy levels (2.5, 3, and 3.5 J/cm2). The laser-treated groups demonstrated a significantly higher increase in cell count compared to the control sample, with the highest increase observed at an energy level of 3 J/cm2. These findings suggest that LLLT at an energy level of 3 J/cm2 could effectively enhance fibroblast migration, indicating its potential as a therapeutic intervention for chronic wounds.

Machine Learning can be used for social good. In this paper, we discuss how it can be used to combat climate change and facilitate land management and farming in developing countries and in particular in Côte d’Ivoire. This paper explores models that improve land and water management and agricultural farming cultivation to contrast climate change. Côte d’Ivoire is the largest producer of cocoa beans (43%) in the world, but deforestation, lack of rainfall, drought, and climate change threaten crops and the already fragile economy of Ivorian farmers. It is important to combat climate change with methods and techniques that are affordable to the local farmers and also induce positive effects in production. We discuss the use of low-cost sensors to collect data on the soil and open data and open source software to develop AI tools. We show that using deep neural networks (YOLOv5m) is effective for detecting healthy plants and pods of cocoa from damaged ones only using mobile phone images. Focusing on a single land is not enough to combat climate change, which has different causes and involves also knowledge at a higher scale. We propose a new method of forecasting for the analysis of remote sensors. Remote sensor data come from GRACE NASA Mission and ERA5 produced by the Copernicus Climate Change Service at ECMWF. We implement a new deep neural network architecture named CIWA-net. It is based on a Fully Convolutional Neural Network (FCN) [ 1] and it is a U-net like architecture [2]. The aim of CIWA-net is to forecast Total Water Storage Anomalies (TWSA). We show the quality of our model with a comparison to a vanilla Convolutional Neural Network. CIWA-net could be used also for the detection of lands that interfere with agricultural work and yields, such as deserted areas, water-soaking soil areas, zones at risk of desertification, and poor land use. The employment of AI at the service of agriculture can decrease crop losses and waste, lower the inputs onto the soil of fertilizers, responsible for the increase of Greenhouse Gases. It could be useful to help the small farmers (at a local scale) and also the policy-makers and farmers’ cooperatives (at the regional scale) to take valid and coordinated countermeasures to improve the correct use of the lands, helping to contrast and adapt to climate change.

Osteoporotic spinal fractures represent an increasingly widespread health problem in our aging society. We aimed to investigate the treatment options for low-energy spinal fractures in the el-derly and their impact on mortality, focusing on surgical stabilization using minimally invasive and open techniques. We evaluated 1356 patients over 50 years of age with compression frac-tures sustained due to low energy trauma treated at a single trauma center. We compared the mortality of patients following stable and operated/non-operated unstable compression frac-tures and the eligibility to surgery using the open and minimally invasive approach. The pa-tients received surgical or conservative care according to severity and eligibility to surgery. The mortality hazard ratio of patients who underwent screw fixation was 1.02 (P > .91), of patients who refused surgery was 1.68 (P < .001) and that of patients with anesthesiological contraindica-tion was 1.57 (P = .08), compared to conservatively treated patients with stable fractures. The dif-ference in mortality between open and minimally invasive surgeries was not significant, but the number of patients eligible for surgery with the minimally invasive procedure was significantly higher (OR: 0.25; P < .001). Spinal stability after fractures may be an important predictor of sur-vival in patients with low-impact fractures.

Functional gastrointestinal disorders (FGIDs) are common in children and adolescents. In recent years, interest in the role of diet in the treatment of FGIDs has increased. Currently, interest focus-es on the low-FODMAP diet (LFD), the fructose- or lactose-restricted diet (FRD or LRD), the glu-ten-free diet (GFD), and the Mediterranean diet (MD). In this review, we focus on the role of these dietary patterns in the FGIDs most commonly diagnosed in clinical practice, namely irritable bowel syndrome (IBS), functional abdominal pain (FAP), functional dyspepsia (FD), and func-tional constipation (FC). Fifteen clinical trials were systematically reviewed (both RCTs and sin-gle arm clinical trials). We demonstrated the lack of high-quality intervention trials. Based on current evidence, low-FODMAP diet, LRD, FRD, or GFD have no place in daily practice for the management of children and adolescents with FGIDs. Nevertheless, some patients with IBS or RAP may have some benefit from the use of a low-FODMAP diet or FRD/LRD. Limited data sug-gest that MD may be promising in the management of FGIDs, especially in IBS patients, but more data are required to investigate the mechanisms of its protective effects.

Background: In regenerative dentistry the graft material influences the success. It should act as an osteoconductive scaffold, providing a mineral substrate during resorption and inducing the activity of osteoinductive cells capable of producing new bone, platelet growth factors, and cell differentiation factors inducing the differentiation of undifferentiated mesenchymal cells into. Given that dentin shares many biochemical characteristics with bone tissue, it has recently attracted considerable interest as a biomaterial for bone repair. The aim of this study is to compare two grinder types in order to determine the optimal method for producing dentinal particles using a mechanical grinder. Materials and methods: A sample of 40 natural human teeth without restorations, prostheses or root canal treatments was used and divided into two groups subjected to two different grinder speeds (high-speed and low-speed). The high-speed showed a greater dispersion (53.5+-9.89% of the tooth) due to the pulverisation (highly thin granules) of part of the tooth. The low-speed grinder does not pulverize the dentin and the percentage of tooth loss is 9.16+/-2.34%. Conclusion: The low-speed gringer allows to save a major part of the tooth and to have a maximum quantity of graft material but requires more time. Further studies must be promoted to optimise the grinding procedures.

This research proposes a roof-mounted auxiliary power supply (APS) system for 600VDC low-floor light rail vehicle (LRV). The proposed APS system consists of five parallel-connected dc-ac inverter modules (modules 1-5). The inverter modules 1 and 2 are three-phase dc-ac inverters for compressor motors of the cooling system, and the inverter modules 3 and 4 are three-phase dc-ac inverters for air pump motors of the braking system. The inverter module 5 is single-phase dc-ac inverter for 220VAC power supply for onboard electric loads. Simulations and experiments were carried out under variable load torque and output frequency for modules 1 – 4; and under full and no resistive loads for the inverter module 5. The measured total input current and total input power of the proposed APS system under full load condition are 118.76A and 71.25kW. Essentially, the proposed APS system is operationally applicable to the 600VDC low-floor RLV. Besides, the novelty of this research lies in the use of five parallel-connected inverter modules, unlike in the conventional APS systems which require three-phase output transformer or isolated dc-dc converter. Specifically, the proposed APS system requires neither three-phase output transformer nor isolated dc-dc converter.