bluuebunny/crossref_metadata_2025 huggingface dataset:
A Review of the Characteristics of Light Pollution: Assessment Technique, Policy, and Legislation
Authors: Hao Ying , Wang Peiyao , Zhang Zhongyao , Xu Zhiming , Jia Dagong
Published: June 2024

Light pollution from the use of artificial lighting poses significant impacts on human health, traffic safety, ecological environment, astronomy, and energy use. The advancement of characteristics of light pollution assessment technology has played a significant role in shaping prevention and control policies, thereby enabling measures, such as environmental standards and legislation and product procurement guidelines, but considerable variation in the definition, control strategies, and regulatory frameworks remains. Therefore, there is a need to review the characteristics of light pollution, including the assessment technique, policy, and legislation. Through the literature review, it can be found that technical standards are required to prevent light pollution. For example, light pollution is decreased by 6% in France through the legislation of artificial light. Key approaches are suggested to control global light pollution, including implementing ambient brightness zoning, regulating lighting product usage, and establishing dark sky reserves. Technology and policy should be integrated. The precise data coming from satellite imagery, drones, and balloons could provide guidance when making the policies.
Improving Outcomes for Regional Families in the Early Years: Increasing Access to Child and Family Health Services for Regional Australia
Authors: Appleton Jessica , Stockton Deborah A. , Dickinson Marie , Debono Deborah
Published: June 2024

Providing child and family health (CFH) services that meet the needs of young children and their families is important for a child’s early experiences, development and lifelong health and well-being. In Australia, families living in regional and rural areas have historically had limited access to specialist CFH services. In 2019, five new specialist CFH services were established in regional areas of New South Wales, Australia. The purpose of this study is to understand the regional families’ perceptions and experiences of these new CFH services. A convergent mixed-methods design involving a survey and semi-structured interviews with parents who had used the service was used for this study. Data collected include demographics, reasons for engaging with the service, perception, and experience of the service, including if the service provided was family centred. Triangulation of the quantitative and qualitative analysis uncovered three main findings: (i) The regional location of the service reduced the burden on families to access support for their needs; (ii) providing a service that is family-centred is important to achieve positive outcomes; and (iii) providing a service that is family-centred advances the local reputation of the service, enabling a greater reach into the community. Providing local specialist CFH services reduces the burden on families and has positive outcomes; however, providing services that are family-centred is key.
DNA-PKcs Inhibition Sensitizes Human Chondrosarcoma Cells to Carbon Ion Irradiation via Cell Cycle Arrest and Telomere Capping Disruption
Authors: Lohberger Birgit , Barna Sandra , Glänzer Dietmar , Eck Nicole , Leithner Andreas , Georg Dietmar
Published: June 2024

In order to overcome the resistance to radiotherapy in human chondrosarcoma cells, the prevention from efficient DNA repair with a combined treatment with the DNA-dependent protein kinase catalytic subunit (DNA-PKcs) inhibitor AZD7648 was explored for carbon ion (C-ion) as well as reference photon (X-ray) irradiation (IR) using gene expression analysis, flow cytometry, protein phosphorylation, and telomere length shortening. Proliferation markers and cell cycle distribution changed significantly after combined treatment, revealing a prominent G2/M arrest. The expression of the G2/M checkpoint genes cyclin B, CDK1, and WEE1 was significantly reduced by IR alone and the combined treatment. While IR alone showed no effects, additional AZD7648 treatment resulted in a dose-dependent reduction in AKT phosphorylation and an increase in Chk2 phosphorylation. Twenty-four hours after IR, the key genes of DNA repair mechanisms were reduced by the combined treatment, which led to impaired DNA repair and increased radiosensitivity. A time-dependent shortening of telomere length was observed in both cell lines after combined treatment with AZD7648 and 8 Gy X-ray/C-ion IR. Our data suggest that the inhibition of DNA-PKcs may increase sensitivity to X-rays and C-ion IR by impairing its functional role in DNA repair mechanisms and telomere end protection.
Endothelial-to-Mesenchymal Transition in Cardiovascular Pathophysiology
Authors: Singh Aman , Bhatt Kriti S. , Nguyen Hien C. , Frisbee Jefferson C. , Singh Krishna K.
Published: June 2024

Under different pathophysiological conditions, endothelial cells lose endothelial phenotype and gain mesenchymal cell-like phenotype via a process known as endothelial-to-mesenchymal transition (EndMT). At the molecular level, endothelial cells lose the expression of endothelial cell-specific markers such as CD31/platelet-endothelial cell adhesion molecule, von Willebrand factor, and vascular-endothelial cadherin and gain the expression of mesenchymal cell markers such as α-smooth muscle actin, N-cadherin, vimentin, fibroblast specific protein-1, and collagens. EndMT is induced by numerous different pathways triggered and modulated by multiple different and often redundant mechanisms in a context-dependent manner depending on the pathophysiological status of the cell. EndMT plays an essential role in embryonic development, particularly in atrioventricular valve development; however, EndMT is also implicated in the pathogenesis of several genetically determined and acquired diseases, including malignant, cardiovascular, inflammatory, and fibrotic disorders. Among cardiovascular diseases, aberrant EndMT is reported in atherosclerosis, pulmonary hypertension, valvular disease, fibroelastosis, and cardiac fibrosis. Accordingly, understanding the mechanisms behind the cause and/or effect of EndMT to eventually target EndMT appears to be a promising strategy for treating aberrant EndMT-associated diseases. However, this approach is limited by a lack of precise functional and molecular pathways, causes and/or effects, and a lack of robust animal models and human data about EndMT in different diseases. Here, we review different mechanisms in EndMT and the role of EndMT in various cardiovascular diseases.
STAT3 Pathways Contribute to β-HCH Interference with Anticancer Tyrosine Kinase Inhibitors
Authors: Fiorini Sara , Rubini Elisabetta , Perugini Monia , Altieri Fabio , Chichiarelli Silvia , Meschiari Giorgia , Arrighetti Giulia , Vijgen John , Natali Pier Giorgio , Minacori Marco , Eufemi Margherita
Published: June 2024

Organochlorine pesticides (OCPs) are a class of environmentally persistent and bioaccumulative pollutants. Among these, β-hexachlorocyclohexane (β-HCH) is a byproduct of lindane synthesis, one of the most worldwide widespread pesticides. β-HCH cellular mechanisms inducing chemical carcinogenesis correspond to many of those inducing chemoresistance, in particular, by the activation of signal transducer and activator of transcription 3 (STAT3) signaling pathways. For this purpose, four cell lines, representative of breast, lung, prostate, and hepatocellular cancers, were treated with β-HCH, specific tyrosine kinase inhibitors (TKIs), and a STAT3 inhibitor. All cell samples were analyzed by a viability assay, immunoblotting analysis, a wound-healing assay, and a colony formation assay. The results show that β-HCH reduces the efficacy of TKIs. The STAT3 protein, in this context, plays a central role. In fact, by inhibiting its activity, the efficacy of the anticancer drug is restored. Furthermore, this manuscript aimed to draw the attention of the scientific and socio-healthcare community to the issue of prolonged exposure to contaminants and their impact on drug efficacy.
Semaglutide May Ameliorate Fibrosis and Inhibit Epithelial–Mesenchymal Transition in Intrauterine Adhesion Models
Authors: Wu Luming , Zhan Yue , Wang Yiqing
Published: June 2024

The purpose of this study was to explore the effect of Semaglutide on intrauterine adhesions and discover new drugs for such adhesions. In this study, the cell model was simulated by TGF-β1-induced human endometrial epithelial cells, and the animal model was established through mechanical curettage and inflammatory stimulation. After co-culturing with TGF-β1 with or without different concentrations of Semaglutide for 48 h, cells were collected for RT-qPCR and Western blotting analyses. Three doses were subcutaneously injected into experimental mice once a day for two weeks, while the control group received sterile ddH2O. The serum and uterine tissues of the mice were collected. HE and Masson staining were used for the uterine histomorphological and pathological analyses. RT-qPCR and Western blotting were used for mRNA and protein expression analyses. Serum indicators were detected using ELISA kits. The results showed that Semaglutide significantly reduced the mRNA levels of fibrosis indicators ACTA2, COL1A1, and FN and inflammatory indicators TNF-α, IL-6, and NF-κB in the two models. Semaglutide improved endometrium morphology, increased the number of endometrial glands, and reduced collagen deposition in IUA mice. The results also showed that Semaglutide could inhibit vimentin, E-Cadherin, and N-Cadherin in the two models. In summary, Semaglutide can ameliorate fibrosis and inflammation of intrauterine adhesions as well as inhibit epithelial–mesenchymal transition in IUA models.
The Impact of Ulmus macrocarpa Extracts on a Model of Sarcopenia-Induced C57BL/6 Mice
Authors: Lee Chan Ho , Kwon Yeeun , Park Sunmin , Kim TaeHee , Kim Min Seok , Kim Eun Ji , Jung Jae In , Min Sangil , Park Kwang-Hyun , Jeong Jae Hun , Choi Sun Eun
Published: June 2024

Aging leads to tissue and cellular changes, often driven by oxidative stress and inflammation, which contribute to age-related diseases. Our research focuses on harnessing the potent anti-inflammatory and antioxidant properties of Korean Ulmus macrocarpa Hance, a traditional herbal remedy, to address muscle loss and atrophy. We evaluated the effects of Ulmus extract on various parameters in a muscle atrophy model, including weight, exercise performance, grip strength, body composition, muscle mass, and fiber characteristics. Additionally, we conducted Western blot and RT-PCR analyses to examine muscle protein regulation, apoptosis factors, inflammation, and antioxidants. In a dexamethasone-induced muscle atrophy model, Ulmus extract administration promoted genes related to muscle formation while reducing those associated with muscle atrophy. It also mitigated inflammation and boosted muscle antioxidants, indicating a potential improvement in muscle atrophy. These findings highlight the promise of Ulmus extract for developing pharmaceuticals and supplements to combat muscle loss and atrophy, paving the way for clinical applications.
The Skin–Brain Axis: From UV and Pigmentation to Behaviour Modulation
Authors: Ascsillán Anna A. , Kemény Lajos V.
Published: June 2024

The skin–brain axis has been suggested to play a role in several pathophysiological conditions, including opioid addiction, Parkinson’s disease and many others. Recent evidence suggests that pathways regulating skin pigmentation may directly and indirectly regulate behaviour. Conversely, CNS-driven neural and hormonal responses have been demonstrated to regulate pigmentation, e.g., under stress. Additionally, due to the shared neuroectodermal origins of the melanocytes and neurons in the CNS, certain CNS diseases may be linked to pigmentation-related changes due to common regulators, e.g., MC1R variations. Furthermore, the HPA analogue of the skin connects skin pigmentation to the endocrine system, thereby allowing the skin to index possible hormonal abnormalities visibly. In this review, insight is provided into skin pigment production and neuromelanin synthesis in the brain and recent findings are summarised on how signalling pathways in the skin, with a particular focus on pigmentation, are interconnected with the central nervous system. Thus, this review may supply a better understanding of the mechanism of several skin–brain associations in health and disease.
Involvement of Endolysosomes and Aurora Kinase A in the Regulation of Amyloid β Protein Levels in Neurons
Authors: Afghah Zahra , Khan Nabab , Datta Gaurav , Halcrow Peter W. , Geiger Jonathan D. , Chen Xuesong
Published: June 2024

Aurora kinase A (AURKA) is a serine/threonine-protein kinase that regulates microtubule organization during neuron migration and neurite formation. Decreased activity of AURKA was found in Alzheimer’s disease (AD) brain samples, but little is known about the role of AURKA in AD pathogenesis. Here, we demonstrate that AURKA is expressed in primary cultured rat neurons, neurons from adult mouse brains, and neurons in postmortem human AD brains. AURKA phosphorylation, which positively correlates with its activity, is reduced in human AD brains. In SH-SY5Y cells, pharmacological activation of AURKA increased AURKA phosphorylation, acidified endolysosomes, decreased the activity of amyloid beta protein (Aβ) generating enzyme β-site amyloid precursor protein cleaving enzyme (BACE-1), increased the activity of the Aβ degrading enzyme cathepsin D, and decreased the intracellular and secreted levels of Aβ. Conversely, pharmacological inhibition of AURKA decreased AURKA phosphorylation, de-acidified endolysosomes, decreased the activity of cathepsin D, and increased intracellular and secreted levels of Aβ. Thus, reduced AURKA activity in AD may contribute to the development of intraneuronal accumulations of Aβ and extracellular amyloid plaque formation.
Targeting SHP2 Cryptic Allosteric Sites for Effective Cancer Therapy
Authors: Rehman Ashfaq Ur , Zhao Cizhang , Wu Yongxian , Zhu Qiang , Luo Ray
Published: June 2024

SHP2, a pivotal component downstream of both receptor and non-receptor tyrosine kinases, has been underscored in the progression of various human cancers and neurodevelopmental disorders. Allosteric inhibitors have been proposed to regulate its autoinhibition. However, oncogenic mutations, such as E76K, convert SHP2 into its open state, wherein the catalytic cleft becomes fully exposed to its ligands. This study elucidates the dynamic properties of SHP2 structures across different states, with a focus on the effects of oncogenic mutation on two known binding sites of allosteric inhibitors. Through extensive modeling and simulations, we further identified an alternative allosteric binding pocket in solution structures. Additional analysis provides insights into the dynamics and stability of the potential site. In addition, multi-tier screening was deployed to identify potential binders targeting the potential site. Our efforts to identify a new allosteric site contribute to community-wide initiatives developing therapies using multiple allosteric inhibitors to target distinct pockets on SHP2, in the hope of potentially inhibiting or slowing tumor growth associated with SHP2.
Introducing Bis(5-(Trifluoromethyl)pyridin-2-yl)amine Chelating Unit via Pd-Catalyzed Amination
Authors: Korinskiy Nikolay A. , Abel Anton S. , Ionova Violetta A. , Bezzubov Stanislav I. , Averin Alexei D. , Beletskaya Irina P.
Published: June 2024

We report a one-step synthesis of trifluoromethyl-substituted di(pyridin-2-yl)amine-based ligands. N-(hetero)aryl-substituted bis(5-(trifluoromethyl)pyridin-2-yl)amines were obtained from 2-bromo-5-(trifluoromethyl)pyridine and corresponding aromatic amines via Pd-catalyzed amination reaction in the presence of a Pd(dba)2/BINAP catalytic system. Four new ligands were prepared in good to high yields and characterized by NMR, IR spectroscopies and mass spectrometry. The structure of one of the products was additionally supported by X-ray analysis.
Prediction of the Cohesion Energy, Shear Modulus and Hardness of Single-Phase Metals and High-Entropy Alloys
Authors: Temesi Ottó K. , Varga Lajos K. , Chinh Nguyen Q. , Vitos Levente
Published: June 2024

In order to facilitate the prediction of some physical properties, we propose several simple formulas based on two parameters only, the metallic valence and metallic atomic radii. Knowing the composition, for single-phase alloys, the average parameters can be calculated by the rule of mixture. The input parameters can be obtained from tabulated databases. Adopting from the literature the results of Coulomb crystal model for metals and single-phase high-entropy alloys, we have derived formulas for the shear modulus (G) and the cohesion energy (Ecoh). Based on these parameters separately, we set up two formulas to estimate the hardness in the case of pure metals. For single-phase (solid-solution) HEAs, by simplifying the Maresca and Curtin model, we obtained a formula for estimating the hardness, which takes into account the atomic misfit in addition to G. The maximal hardness for single-phase HEA is approximately 600 kg/mm2 and is obtained for a composition with a valence electron concentration of approximately 6 ÷ 7.
The Influence of Rhenium Content on Helium Desorption Behavior in Tungsten–Rhenium Alloy
Authors: Liu Yongli , Song Yamin , Dong Ye , Zhu Te , Zhang Peng , Wu Lu , Cao Xingzhong , Wang Baoyi
Published: June 2024

To investigate the influence of different rhenium contents on the helium desorption behavior in tungsten–rhenium alloys, pure tungsten and tungsten–rhenium alloys were irradiated with helium under the same conditions. All irradiated samples were characterized using TDS and DBS techniques. The results indicate that the addition of rhenium can reduce the total helium desorption quantity in tungsten–rhenium alloys and slightly accelerate the reduction in the concentration of vacancy-type defects accompanying helium dissociation. The desorption activation energy of helium is approximately 2 eV at the low-temperature peak (~785 K) and about 4 eV at the high-temperature peak (~1475 K). An increase in rhenium content causes the desorption peak to shift towards higher temperatures (>1473 K), which is attributed to the formation of the stable complex structures between rhenium and vacancies. Besides, the migration of He-vacancy complexes towards traps and dynamic annealing processes both lead to the recovery of vacancy-type defects, resulting in a decrease in the positron annihilation S parameters.
Combined Experimental and Numerical Modelling of the Electrical Behaviour of Laser-Soldered Steel Sheets
Authors: Körmöczi Andor , Horváth Gábor , Szörényi Tamás , Geretovszky Zsolt
Published: June 2024

The electric vehicle (EV) industry challenges battery joining technologies by requiring higher energy density both by mass and volume. Improving the energy density via new battery chemistry would be the holy grail but is seriously hindered and progresses slowly. In the meantime, alternative ways, such as implementing more efficient cell packaging by minimising the electrical resistance of joints, are of primary focus. In this paper, we discuss the challenges associated with the electrical characterisation of laser-soldered joints in general, and the minimisation of their resistive losses, in particular. In order to assess the impact of joint resistance on the overall resistance of the sample, the alteration in resistance was monitored as a function of voltage probe distance and modelled by finite element simulation. The experimental measurements showed two different regimes: one far from the joint area and another in its vicinity and within the joint cross-section. The presented results confirm the importance of the thickness of the filler material, the effective and total soldered area, and the area and position of the voids within the total soldered area in determining the electrical resistance of joints.
Crosslinked Polydiallyldimethylammonium Chloride Adsorbent for the Selective Separation of Rhenium Ions from Pregnant Leach Solutions
Authors: Fathi Mohammadbagher , Mahmoudian Mehdi , Alorro Richard Diaz , Chegini Mostafa
Published: June 2024

The depletion of valuable mineral reserves has rendered effluents generated from mining and industrial processing activities a promising resource for the production of precious elements. The synthesis and improvement of new adsorbents to extract valuable compounds from industrial wastes and pregnant leach solutions, besides increasing wealth, can play a significant role in reducing environmental concerns. In this work, a new and low-cost adsorbent for the selective extraction of rhenium (perrhenate ions, ReO4−) was synthesized by the free-radical polymerization (FRP) of a diallyl dimethylammonium chloride monomer (quaternary amine) in the presence of a crosslinker. Various methods were employed to characterize the polymeric adsorbent. The results revealed that the designed polymeric adsorbent had a high surface area and pores with nano-metric dimensions and a pore volume of 6.4 × 10−3 cm3/g. Four environments—single, binary, multicomponent, and real solutions—were applied to evaluate the adsorbent’s performance in the selective separation of Re. Additionally, these environments were used to understand the behavior of molybdenum ions, the primary competitors of perrhenate ions in the ion exchange process. In competitive conditions, using variations in qe,mix/qe, an antagonism phenomenon (qe,mix/qe < 1) occurred due to the inhibitory effect of surface-adsorbed molybdenum ions on the binding of the perrhenate ions. However, across all conditions, the separation values for Re were higher than those for the other studied elements (Mo, Cu, Fe).
Analytical Determination of Nusselt Numbers for Convective Heat Transfer Coefficients in Channel Macroporous Absorbers
Authors: Cheilytko Andrii , Schwarzbözl Peter , Broeske Robin Tim
Published: June 2024

This article introduces a novel analytical equation for computing the Nusselt number within the macroporous structures of channel absorbers utilized in high-temperature solar receivers. The equation incorporates heat and mass transfer processes occurring within boundary layers as fluid flows through complex-shaped macroporous absorber channels. The importance of accounting for the length of the thermodynamic boundary layer within channel-type macroporous media when calculating heat transfer coefficients using the Nusselt equation is demonstrated. By incorporating proposed indicators of porosity and flow characteristics, this method significantly enhances the accuracy of heat transfer coefficient calculations for such media. Discrepancies observed in existing calculation relationships and experiments are attributed to the omission of certain proposed values in the Nusselt number for macroporous media. To address this, empirical coefficients for the Nusselt number are derived using statistical methods. The resulting semi-empirical equation is applied to macroporous absorbers in solar receivers. The findings enable more accurate predictions of future absorber characteristics, enhancing their efficiency. The derived equation is successfully validated against numerical data across various geometric structures of absorbers in concentrated solar power plants.
A Comprehensive Approach for Designing Low Carbon Wood Bio-Concretes
Authors: da Gloria M’hamed Y. R. , Caldas Lucas R. , Barros Joaquim A. O. , Toledo Filho Romildo D.
Published: June 2024

This paper presents a method for designing low carbon bio-based building materials, also named bio-concretes, produced with wood wastes in shavings form (WS) and cementitious pastes. As the aggregates phase of bio-concretes is composed of plant-based particles, known as porous and high water-absorbing materials, the bio-concretes cannot be designed by using the traditional design rules used for conventional mortar or concrete. Then, the method used in the current paper is an adaptation of a previous one that has been developed in a recent paper where bio-concretes were produced with a cement matrix, three types of bio-aggregates, and a proposal of a design abacus. However, when that abacus is used for designing WBC with low cement content in the matrix, the target compressive strength is not reached. In the present paper, the method is extended to low cement content matrix (up to 70% of cement substitution) and also considering the greenhouse gas (GHG) emission of the WBC. To obtain data for proposing a new design abacus, an experimental program was carried out by producing nine workable WBCs, varying wood volumetric fractions (40–45–50%), and water-to-binder ratios. The bio-concretes produced presented adequate consistency, lightness (density between 715 and 1207 kg/m3), and compressive strength ranging from 0.64 to 12.27 MPa. In addition, the GHG emissions of the WBC were analysed through the Life Cycle Assessment methodology. From the relationships obtained between density, compressive strength, water-to-binder ratio, cement consumption, and GHG emissions of the WBC, calibration constants were proposed for developing the updated and more complete abacus regarding an integrated mix design methodology.
Development and Calibration of a Microfluidic, Chip-Based Sensor System for Monitoring the Physical Properties of Water Samples in Aquacultures
Authors: Aliazizi Fereshteh , Özsoylu Dua , Bakhshi Sichani Soroush , Khorshid Mehran , Glorieux Christ , Robbens Johan , Schöning Michael J. , Wagner Patrick
Published: June 2024

In this work, we present a compact, bifunctional chip-based sensor setup that measures the temperature and electrical conductivity of water samples, including specimens from rivers and channels, aquaculture, and the Atlantic Ocean. For conductivity measurements, we utilize the impedance amplitude recorded via interdigitated electrode structures at a single triggering frequency. The results are well in line with data obtained using a calibrated reference instrument. The new setup holds for conductivity values spanning almost two orders of magnitude (river versus ocean water) without the need for equivalent circuit modelling. Temperature measurements were performed in four-point geometry with an on-chip platinum RTD (resistance temperature detector) in the temperature range between 2 °C and 40 °C, showing no hysteresis effects between warming and cooling cycles. Although the meander was not shielded against the liquid, the temperature calibration provided equivalent results to low conductive Milli-Q and highly conductive ocean water. The sensor is therefore suitable for inline and online monitoring purposes in recirculating aquaculture systems.
Potential of Cell-Penetrating Peptide-Conjugated Antisense Oligonucleotides for the Treatment of SMA
Authors: Leckie Jamie , Yokota Toshifumi
Published: June 2024

Spinal muscular atrophy (SMA) is a severe neuromuscular disorder that is caused by mutations in the survival motor neuron 1 (SMN1) gene, hindering the production of functional survival motor neuron (SMN) proteins. Antisense oligonucleotides (ASOs), a versatile DNA-like drug, are adept at binding to target RNA to prevent translation or promote alternative splicing. Nusinersen is an FDA-approved ASO for the treatment of SMA. It effectively promotes alternative splicing in pre-mRNA transcribed from the SMN2 gene, an analog of the SMN1 gene, to produce a greater amount of full-length SMN protein, to compensate for the loss of functional protein translated from SMN1. Despite its efficacy in ameliorating SMA symptoms, the cellular uptake of these ASOs is suboptimal, and their inability to penetrate the CNS necessitates invasive lumbar punctures. Cell-penetrating peptides (CPPs), which can be conjugated to ASOs, represent a promising approach to improve the efficiency of these treatments for SMA and have the potential to transverse the blood–brain barrier to circumvent the need for intrusive intrathecal injections and their associated adverse effects. This review provides a comprehensive analysis of ASO therapies, their application for the treatment of SMA, and the encouraging potential of CPPs as delivery systems to improve ASO uptake and overall efficiency.
Highly Efficient and Selective Extraction of Gold from Thiosulfate Leaching Solution Using Functionalized Dicationic Ionic Liquids
Authors: Zhou Qiang , Fan Yunchang , Zhang Sheli
Published: June 2024

Thiosulfate leaching has been regarded as a promising alternative to cyanidation, but it still faces the challenge of the recovery of low content of gold from high concentrations of thiosulfate solutions. Liquid–liquid extraction is a method to address this issue but is still limited by the use of volatile and toxic organic solvents. To overcome this limitation, this work synthesized some functionalized dicationic ionic liquids (DILs) to serve as extraction solvents for the recovery of the gold–thiosulfate complex, [Au(S2O3)2]3−, from thiosulfate solutions. Experimental results indicated that the DILs showed higher extraction rates toward [Au(S2O3)2]3− compared with their monocationic-based counterparts, likely due to the stronger electrostatic interaction between the dications of the ILs and [Au(S2O3)2]3−. The transfer of [Au(S2O3)2]3− from the water phase to the IL phase was identified as an anion exchange and endothermic process. The rate of extraction was limited by the anion exchange process occurring at the IL–water interface. The extraction ability of ILs highly depended on the type of anion; specifically, the ILs with anions that had strong hydrogen-bonding ability exhibited high extraction ability toward [Au(S2O3)2]3−. Finally, DILs proved effective in the recovery of [Au(S2O3)2]3− from an actual gold leaching solution and exhibited high selectivity toward coexisting ions, indicating their potential as environmentally friendly solvents for gold recovery.
Nusinersen Treatment for Spinal Muscular Atrophy: Retrospective Multicenter Study of Pediatric and Adult Patients in Kuwait
Authors: AlTawari Asma , Zakaria Mohammad , Kamel Walaa , Shaalan Nayera , Elghazawi Gamal , Ali Mohamed , Salota Dalia , Attia Amr , Elanany Ehab , Shalaby Osama , Alqallaf Fatema , Mitic Vesna , Bastaki Laila
Published: June 2024

Spinal muscular atrophy is a neuromuscular genetic condition associated with progressive muscle weakness and atrophy. Nusinersen is an antisense oligonucleotide therapy approved for the treatment of 5q spinal muscular atrophy in pediatric and adult patients. The objective of this clinical case series is to describe the efficacy and safety of nusinersen in treating spinal muscular atrophy in 20 pediatric and 18 adult patients across six treatment centers in Kuwait. Functional motor assessments (Children’s Hospital of Philadelphia Infant Test of Neuromuscular Disorders, Hammersmith Functional Motor Scale Expanded, and Revised Upper Limb Module) were used to assess changes in motor function following nusinersen treatment. The safety assessment involved clinical monitoring of adverse events. The results demonstrate clinically meaningful or considerable improvement in motor performance for nearly all patients, lasting over 4 years in some cases. A total of 70% of patients in the pediatric cohort and 72% of patients in the adult cohort achieved a clinically meaningful improvement in motor function following nusinersen treatment. Additionally, nusinersen was well-tolerated in both cohorts. These findings add to the growing body of evidence relating to the clinical efficacy and safety of nusinersen.
QbD-Based Development and Evaluation of Pazopanib Hydrochloride Extrudates Prepared by Hot-Melt Extrusion Technique: In Vitro and In Vivo Evaluation
Authors: Gupta Amit , Dahima Rashmi , Panda Sunil K. , Gupta Annie , Singh Gaurav Deep , Wani Tanveer A. , Hussain Afzal , Rathore Devashish
Published: June 2024

Background: Pazopanib hydrochloride (PZB) is a protein kinase inhibitor approved by the United States Food and Drug Administration and European agencies for the treatment of renal cell carcinoma and other renal malignancies. However, it exhibits poor aqueous solubility and inconsistent oral drug absorption. In this regard, the current research work entails the development and evaluation of the extrudates of pazopanib hydrochloride by the hot-melt extrusion (HME) technique for solubility enhancement and augmenting oral bioavailability. Results: Solid dispersion of the drug was prepared using polymers such as Kollidon VA64, hydroxypropylmethylcellulose (HPMC), Eudragit EPO, and Affinisol 15LV in a 1:2 ratio by the HME process through a lab-scale 18 mm extruder. Systematic optimization of the formulation variables was carried out with the help of custom screening design (JMP Software by SAS, Version 14.0) to study the impact of polymer type and plasticizer level on the quality of extrudate processability by measuring the torque value, appearance, and disintegration time as the responses. The polymer blends containing Kollidon VA64 and Affinisol 15LV resulted in respective clear transparent extrudates, while Eudragit EPO and HPMC extrudates were found to be opaque white and brownish, respectively. Furthermore, evaluation of the impact of process parameters such as screw rpm and barrel temperature was measured using a definitive screening design on the extrude appearance, torque, disintegration time, and dissolution profile. Based on the statistical outcomes, it can be concluded that barrel temperature has a significant impact on torque, disintegration time, and dissolution at 30 min, while screw speed has an insignificant impact on the response variables. Affinisol extrudates showed less moisture uptake and faster dissolution in comparison to Kollidon VA64 extrudates. Affinisol extrudates were evaluated for polymorphic stability up to a 3-month accelerated condition and found no recrystallization. PZB–Extrudates using the Affinisol polymer (Test formulation A) revealed significantly higher bioavailability (AUC) in comparison to the free Pazopanib drug and marketed formulation.
Nanoliposomes Permeability in a Microfluidic Drug Delivery Platform across a 3D Hydrogel
Authors: Peyret Corentin , Manousaki Aleka , Bouguet-Bonnet Sabine , Stratakis Emmanuel , Sanchez-Gonzalez Laura , Kahn Cyril J.F. , Arab-Tehrany Elmira
Published: June 2024

Nanoliposomes are nano-sized vesicles that can be used as drug delivery carriers with the ability to encapsulate both hydrophobic and hydrophilic compounds. Moreover, their lipid compositions facilitate their internalization by cells. However, the interaction between nanoliposomes and the membrane barrier of the human body is not well-known. If cellular tests and animal testing offer a solution, their lack of physiological relevance and ethical concerns make them unsuitable to properly mimic human body complexity. Microfluidics, which allows the environment of the human body to be imitated in a controlled way, can fulfil this role. However, existing models are missing the presence of something that would mimic a basal membrane, often consisting of a simple cell layer on a polymer membrane. In this study, we investigated the diffusion of nanoliposomes in a microfluidic system and found the optimal parameters to maximize their diffusion. Then, we incorporated a custom made GelMA with a controlled degree of substitution and studied the passage of fluorescently labeled nanoliposomes through this barrier. Our results show that highly substituted GelMA was more porous than lower substitution GelMA. Overall, our work lays the foundation for the incorporation of a hydrogel mimicking a basal membrane on a drug delivery microfluidic platform.
Correction: Del Valle-Moreno et al. Model-Informed Precision Dosing Software Tools for Dosage Regimen Individualization: A Scoping Review. Pharmaceutics 2023, 15, 1859
Authors: Del Valle-Moreno Paula , Suarez-Casillas Paloma , Mejías-Trueba Marta , Ciudad-Gutiérrez Pablo , Guisado-Gil Ana Belén , Gil-Navarro María Victoria , Herrera-Hidalgo Laura
Published: June 2024

There was an error in the original publication [...]
Ultrafast Polymerization of a Self-Adhesive and Strain Sensitive Hydrogel-Based Flexible Sensor for Human Motion Monitoring and Handwriting Recognition
Authors: Du Bin , Yin Mengwei , Yang Kenan , Wang Sainan , Pei Yiting , Luo Rubai , Zhou Shisheng , Li Huailin
Published: June 2024

Hydrogel-based flexible electronic devices have great potential in human motion monitoring, electronic skins, and human-computer interaction applications; hence, the efficient preparation of highly sensitive hydrogel-based flexible sensors is important. In the present work, the ultrafast polymerization of a hydrogel (1–3 min) was achieved by constructing a tannic acid (TA)-Fe3+ dynamic redox system, which endowed the hydrogel with good adhesion performance (the adhesion strength in wood was 17.646 kPa). In addition, the uniform dispersal ensured by incorporating polydopamine-decorated polypyrrole (PPy@PDA) into the hydrogel matrix significantly improved the hydrogel’s stretching ability (575.082%). The as-prepared PAM/CS/PPy@PDA/TA hydrogel-based flexible sensor had a high-fidelity low detection limit (strain = 1%), high sensitivity at small strains (GF = 5.311 at strain = 0–8%), and fast response time (0.33 s) and recovery time (0.25 s), and it was reliably applied to accurate human motion monitoring and handwriting recognition. The PAM/CS/PPy@PDA/TA hydrogel opens new horizons for wearable electronic devices, electronic skins, and human-computer interaction applications.
Higher-Order Convolutional Neural Networks for Essential Climate Variables Forecasting
Authors: Giannopoulos Michalis , Tsagkatakis Grigorios , Tsakalides Panagiotis
Published: June 2024

Earth observation imaging technologies, particularly multispectral sensors, produce extensive high-dimensional data over time, thus offering a wealth of information on global dynamics. These data encapsulate crucial information in essential climate variables, such as varying levels of soil moisture and temperature. However, current cutting-edge machine learning models, including deep learning ones, often overlook the treasure trove of multidimensional data, thus analyzing each variable in isolation and losing critical interconnected information. In our study, we enhance conventional convolutional neural network models, specifically those based on the embedded temporal convolutional network framework, thus transforming them into models that inherently understand and interpret multidimensional correlations and dependencies. This transformation involves recasting the existing problem as a generalized case of N-dimensional observation analysis, which is followed by deriving essential forward and backward pass equations through tensor decompositions and compounded convolutions. Consequently, we adapt integral components of established embedded temporal convolutional network models, like encoder and decoder networks, thus enabling them to process 4D spatial time series data that encompass all essential climate variables concurrently. Through the rigorous exploration of diverse model architectures and an extensive evaluation of their forecasting prowess against top-tier methods, we utilize two new, long-term essential climate variables datasets with monthly intervals extending over four decades. Our empirical scrutiny, particularly focusing on soil temperature data, unveils that the innovative high-dimensional embedded temporal convolutional network model-centric approaches markedly excel in forecasting, thus surpassing their low-dimensional counterparts, even under the most challenging conditions characterized by a notable paucity of training data.
A New Grid Zenith Tropospheric Delay Model Considering Time-Varying Vertical Adjustment and Diurnal Variation over China
Authors: Zhang Jihong , Zuo Xiaoqing , Guo Shipeng , Xie Shaofeng , Yang Xu , Li Yongning , Yue Xuefu
Published: June 2024

Improving the accuracy of zenith tropospheric delay (ZTD) models is an important task. However, the existing ZTD models still have limitations, such as a lack of appropriate vertical adjustment function and being unsuitable for China, which has a complex climate and great undulating terrain. A new approach that considers the time-varying vertical adjustment and delicate diurnal variations of ZTD was introduced to develop a new grid ZTD model (NGZTD). The NGZTD model employed the Gaussian function and considered the seasonal variations of Gaussian coefficients to express the vertical variations of ZTD. The effectiveness of vertical interpolation for the vertical adjustment model (NGZTD-H) was validated. The root mean squared errors (RMSE) of the NGZTD-H model improved by 58% and 22% compared to the global pressure and temperature 3 (GPT3) model using ERA5 and radiosonde data, respectively. The NGZTD model’s effectiveness for directly estimating the ZTD was validated. The NGZTD model improved by 22% and 31% compared to the GPT3 model using GNSS-derived ZTD and layered ZTD at radiosonde stations, respectively. Seasonal variations in Gaussian coefficients need to be considered. Using constant Gaussian coefficients will generate large errors. The NGZTD model exhibited outstanding advantages in capturing diurnal variations and adapting to undulating terrain. We analyzed and discussed the main error sources of the NGZTD model using validation of spatial interpolation accuracy. This new ZTD model has potential applications in enhancing the reliability of navigation, positioning, and interferometric synthetic aperture radar (InSAR) measurements and is recommended to promote the development of space geodesy techniques.
Utilizing Deep Learning for Defect Inspection in Hand Tool Assembly
Authors: Lin Hong-Dar , Jheng Cheng-Kai , Lin Chou-Hsien , Chang Hung-Tso
Published: June 2024

The integrity of product assembly in the precision assembly industry significantly influences the quality of the final products. During the assembly process, products may acquire assembly defects due to personnel oversight. A severe assembly defect could impair the product’s normal function and potentially cause loss of life or property for the user. For workpiece defect inspection, there is limited discussion on the simultaneous detection of the primary kinds of assembly anomaly (missing parts, misplaced parts, foreign objects, and extra parts). However, these assembly anomalies account for most customer complaints in the traditional hand tool industry. This is because no equipment can comprehensively inspect major assembly defects, and inspections rely solely on professionals using simple tools and their own experience. Thus, this study proposes an automated visual inspection system to achieve defect inspection in hand tool assembly. This study samples the work-in-process from three assembly stations in the ratchet wrench assembly process; an investigation of 28 common assembly defect types is presented, covering the 4 kinds of assembly anomaly in the assembly operation; also, this study captures sample images of various assembly defects for the experiments. First, the captured images are filtered to eliminate surface reflection noise from the workpiece; then, a circular mask is given at the assembly position to extract the ROI area; next, the filtered ROI images are used to create a defect-type label set using manual annotation; after this, the R-CNN series network models are applied to object feature extraction and classification; finally, they are compared with other object detection models to identify which inspection model has the better performance. The experimental results show that, if each station uses the best model for defect inspection, it can effectively detect and classify defects. The average defect detection rate (1-β) of each station is 92.64%, the average misjudgment rate (α) is 6.68%, and the average correct classification rate (CR) is 88.03%.
Streamline Intelligent Crowd Monitoring with IoT Cloud Computing Middleware
Authors: Gazis Alexandros , Katsiri Eleftheria
Published: June 2024

This article introduces a novel middleware that utilizes cost-effective, low-power computing devices like Raspberry Pi to analyze data from wireless sensor networks (WSNs). It is designed for indoor settings like historical buildings and museums, tracking visitors and identifying points of interest. It serves as an evacuation aid by monitoring occupancy and gauging the popularity of specific areas, subjects, or art exhibitions. The middleware employs a basic form of the MapReduce algorithm to gather WSN data and distribute it across available computer nodes. Data collected by RFID sensors on visitor badges is stored on mini-computers placed in exhibition rooms and then transmitted to a remote database after a preset time frame. Utilizing MapReduce for data analysis and a leader election algorithm for fault tolerance, this middleware showcases its viability through metrics, demonstrating applications like swift prototyping and accurate validation of findings. Despite using simpler hardware, its performance matches resource-intensive methods involving audiovisual and AI techniques. This design’s innovation lies in its fault-tolerant, distributed setup using budget-friendly, low-power devices rather than resource-heavy hardware or methods. Successfully tested at a historical building in Greece (M. Hatzidakis’ residence), it is tailored for indoor spaces. This paper compares its algorithmic application layer with other implementations, highlighting its technical strengths and advantages. Particularly relevant in the wake of the COVID-19 pandemic and general monitoring middleware for indoor locations, this middleware holds promise in tracking visitor counts and overall building occupancy.
Comparison of Machine Learning Algorithms Fed with Mobility-Related and Baropodometric Measurements to Identify Temporomandibular Disorders
Authors: Taborri Juri , Molinaro Luca , Russo Luca , Palmerini Valerio , Larion Alin , Rossi Stefano
Published: June 2024

Temporomandibular disorders (TMDs) refer to a group of conditions that affect the temporomandibular joint, causing pain and dysfunction in the jaw joint and related muscles. The diagnosis of TMDs typically involves clinical assessment through operator-based physical examination, a self-reported questionnaire and imaging studies. To objectivize the measurement of TMD, this study aims at investigating the feasibility of using machine-learning algorithms fed with data gathered from low-cost and portable instruments to identify the presence of TMD in adult subjects. Through this aim, the experimental protocol involved fifty participants, equally distributed between TMD and healthy subjects, acting as a control group. The diagnosis of TMD was performed by a skilled operator through the typical clinical scale. Participants underwent a baropodometric analysis by using a pressure matrix and the evaluation of the cervical mobility through inertial sensors. Nine machine-learning algorithms belonging to support vector machine, k-nearest neighbours and decision tree algorithms were compared. The k-nearest neighbours algorithm based on cosine distance was found to be the best performing, achieving performances of 0.94, 0.94 and 0.08 for the accuracy, F1-score and G-index, respectively. These findings open the possibility of using such methodology to support the diagnosis of TMDs in clinical environments.