Combined Treatment of Ketogenic Diet and Propagermanium Reduces Neuroinflammation in Tay-Sachs Disease Mouse Model

Tay-Sachs disease is a rare lysosomal storage disorder caused by beta-Hexosaminidase A enzyme deficiency causing abnormal GM2 ganglioside accumulation in the central nervous system. GM2 accumulation triggers chronic neuroinflammation due to neurodegeneration-based astrogliosis and macrophage activity with the increased expression level of Ccl2 in the cortex of a recently generated Tay-Sachs disease mouse model Hexa-/-Neu3-/-. Propagermanium blocks the neuroinflammatory response induced by Ccl2, which is highly expressed in astrocytes and microglia. The ketogenic diet has broad potential usage in neurological disorders, but the knowledge of the impact on Tay-Sach disease is limited. This study aimed to display the effect of combining the ketogenic diet and propagermanium treatment on chronic neuroinflammation in the Tay-Sachs disease mouse model. Hexa-/-Neu3-/- mice were placed into the following groups: (i) standard diet, (ii) ketogenic diet, (iii) standard diet with propagermanium, and (iv) ketogenic diet with propagermanium. RT-PCR and immunohistochemistry analyzed neuroinflammation markers. Behavioral analyses were also applied to assess phenotypic improvement. Notably, the expression levels of neuroinflammation-related genes were reduced in the cortex of 140-day-old Hexa-/-Neu3-/- mice compared to beta-Hexosaminidase A deficient mice (Hexa-/-) after combined treatment. Immunohistochemical analysis displayed correlated results with the RT-PCR. Our data suggest the potential to implement combined treatment to reduce chronic inflammation in Tay-Sachs and other lysosomal storage diseases

Evaluation of Hydro-Geochemical Processes Controlling Groundwater Quality in Balkh Center (Mazar-E Northern Afghanistan)

Background: Groundwater in Afghanistan stands as the predominant water source employed for potable consumption, household utilization, irrigation, and industrial applications. Major cities of Afghanistan are largely dependent on groundwater resources. However, the groundwater quality of major cities in Afghanistan, including Mazar-e-Sharif city was not investigated in detail. Objective: This study aims to conduct a comprehensive analysis of the hydrochemical characteristics of the Mazar-e-Sharif groundwater, identify the factors influencing groundwater quality, and evaluate the groundwater contamination sources. Methods: A total of 18 groundwater samples were collected during the dry season (June 2020) and analyzed for various physico-chemical parameters. Methods such as multivariate statistical analyses, geochemical modeling, water quality index (WQI), and spatial distribution of groundwater quality were employed to evaluate the hydro-geochemistry of the study area. Results: The results reveal that 1) The prevailing groundwater within the study area is predominantly characterized by Na-(Ca)-HCO3 and Ca-(Mg)-SO4 water types. 2) Physicochemical variables such as NO3−, F−, TDS, and SO42− exceeded the World Health Organization (WHO) safe limits in many wells. 3) Hydro-geochemical processes such as silicate weathering, cation exchange, and gypsum dissolution controls the groundwater chemistry. 4) Cl/Br ratios reveal, that high salinity may originate from evaporitic lacustrine and evaporite deposits and found to be localized in nature. 5) The Water Quality Index (WQI) classification suggests that approximately 60 % of the groundwater samples fall into poor to very poor water quality categories, highlighting substantial public health concerns. Major contaminants like nitrate and fluoride were found to be higher than the safe limit in nearly half of the samples. Conclusion: The findings of this study hold value for decision-makers in formulating a proficient strategy for the management of groundwater resources in Mazar-e-Sharif City in achieving the UN sustainable goal (SDG) of providing sustainable water for all. Furthermore, new advanced techniques like environmental isotopes should be analyzed to evaluate groundwater hydro-chemical evolution in the future to enhance our understanding. © 202

Rings Whose Mininjective Modules Are Injective

The main goal of this paper is to characterize rings over which the mininjective modules are injective, so that the classes of mininjective modules and injective modules coincide. We show that these rings are precisely those Noetherian rings for which every min-flat module is projective and we study this characterization in the cases when the ring is Kasch, commutative and when it is quasi-Frobenius. We also treat the case of nxn upper triangular matrix rings, proving that their mininjective modules are injective if and only if n=2. We use the developed machinery to find a new type of examples of indigent modules (those whose subinjectivity domain contains only the injective modules), whose existence is known, so far, only in some rather restricted situations

Therapeutic and Pharmaceutical Applications of Pegylated Nano-Carriers

The coating of the exterior of nanocarriers with polyethylene glycol (PEG; known as “PEGylation”), has emerged as one of the most widely adopted approaches to impart stealth properties to pharmaceutical nanocarrier systems. The PEGylation tactic offers a stealth barrier towards the adsorption of circulatory proteins owing to its hydrophilicity, elasticity, neutralization, and hydration properties. PEGylation dramatically provides sustained drug release benefits, reduces immune sensitivity, as well as improves the systemic circulation period, Overall, PEGylation effectively improves the therapeutic efficacy of the loaded therapeutic moiety in treating target cells and tissues. This chapter offers discussion on drug delivery nanosystems that are developed based on the principle of PEGylation strategy. Furthermore, a detailed account of the pharmaceutical and biomedical applications of PEGylated nanocarriers has also been presented in detail. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024

Quantum Optics Applications of Hexagonal Boron Nitride Defects

Hexagonal boron nitride (hBN) has emerged as a compelling platform for both classical and quantum technologies. In particular, the past decade has witnessed a surge of novel ideas and developments, which may be overwhelming for newcomers to the field. This review provides an overview of the fundamental concepts and key applications of hBN, including quantum sensing, quantum key distribution, quantum computing, and quantum memory. Additionally, critical experimental and theoretical advances that have expanded the capabilities of hBN are highlighted, in a cohesive and accessible manner. The objective is to equip readers with a comprehensive understanding of the diverse applications of hBN, and provide insights into ongoing research efforts

An Interior Inverse Generalized Impedance Problem for the Modified Helmholtz Equation in Two Dimensions

We consider the inverse interior problem of recovering the surface impedances of the cavity from sources and measurements placed on a curve inside of it. The uniqueness issue is investigated, and a hybrid method is proposed for the numerical solution. The approach takes advantages of both direct and iterative schemes, such as it does not require an initial guess and has an accuracy of a Newton-type method. Presented numerical experiments demonstrate the feasibility and effectiveness of the approach

Comparison of Conventional and Machine Learning Models for Kinetic Modelling of Biomethane Production From Pretreated Tomato Plant Residues

Tomato plant residues (Solanum lycopersicum L.) lack sustainable applications as abundant lignocellulosic biomass after harvest. These residues can be utilized as substrates in anaerobic digestion for biomethane production, generating energy and reducing waste. The purpose of this study was to investigate the sustainable utilization of tomato plant residues for biomethane production at varying conditions and to model biological kinetics. The study aimed to evaluate the effects of varying substrate/inoculum ratios, sulfuric acid pretreatment concentrations, and yeast (Saccharomyces cerevisiae) addition on biogas and biomethane yields under mesophilic conditions (37 degrees C). Maximum biogas and biomethane yields in the studied range were obtained when the substrate/inoculum ratio was 3 (g substrate/g inoculum), the sulfuric acid concentration used for residue pretreatment was 2 %v/v, and the substrate/yeast ratio was 10 (g substrate/g yeast). The yeast ratio of 10 increased the cumulative biogas and biomethane production by 96.5 and 128.9%, respectively. Conventional models (Modified Gompertz, Cone, First-order, Logistic) and Machine Learning models (Support Vector Machine and Neural Network) were compared for biological kinetics. Machine Learning models were also observed to give good fitting results similar to conventional models. Results suggest that Machine Learning models (RMSE: 2.5833-12.0500) are reliable methods like conventional kinetic models (RMSE: 2.1796-13.4880) for forecasting biomethane production in anaerobic digestion processes and Machine Learning models can be applied without needing prior understanding of biomethane production kinetics

High-Temperature Bose-Einstein Condensation of Dark Excitons in Holey Graphyne

We investigated the optical and excitonic properties of holey graphyne (HGY), which is a recently synthesized two-dimensional (2D) carbon allotrope, using first-principles calculations. The potential of HGY for and band-edge wave-function symmetry of HGY lead to strong Coulomb interactions and symmetry-forbidden optical transition, resulting in the formation of long-lived dark excitons. The lowest-energy dark exciton in HGY has a large binding energy of 0.63 eV and can be well described by the screened hydrogenic model. By analyzing the constraints on exciton density and temperature necessary for BEC, a phase diagram for the electron-hole system in HGY is constructed, and a maximum BEC transition temperature of 503 K is predicted. Our findings thus reveal the great possibility of achieving above-room-temperature excitonic BEC in 2D carbon materials

Recent Advances in Hydrogel-Based 3D Disease Modeling and Drug Screening Platforms

Three-dimensional (3D) disease modeling and drug screening systems have become important in tissue engineering, drug screening, and development. The newly developed systems support cell and extracellular matrix (ECM) interactions, which are necessary for the formation of the tissue or an accurate model of a disease. Hydrogels are favorable biomaterials due to their properties: biocompatibility, high swelling capacity, tunable viscosity, mechanical properties, and their ability to biomimic the structure and function of ECM. They have been used to model various diseases such as tumors, cancer diseases, neurodegenerative diseases, cardiac diseases, and cardiovascular diseases. Additive manufacturing approaches, such as 3D printing/bioprinting, stereolithography (SLA), selective laser sintering (SLS), and fused deposition modeling (FDM), enable the design of scaffolds with high precision; thus, increasing the accuracy of the disease models. In addition, the aforementioned methodologies improve the design of the hydrogel-based scaffolds, which resemble the complicated structure and intricate microenvironment of tissues or tumors, further advancing the development of therapeutic agents and strategies. Thus, 3D hydrogel-based disease models fabricated through additive manufacturing approaches provide an enhanced 3D microenvironment that empowers personalized medicine toward targeted therapeutics, in accordance with 3D drug screening platforms. © 2025. The Author(s), under exclusive license to Springer Nature Switzerland AG

Markov Olmayan Ortamlar ile Etkileşimdeki Süperiletken Transmon Kübitlerin Kesirli Dinamiği

In this thesis, we have introduced the Mittag-Leffler (ML) type correlations to the field of both decoherence suppression in a system consisting of a single transmon qubit interacting with a Markovian bath and the characterization of the dynamics of a transmon qubit interacting with a defect in an amorphous medium, respectively. The effect of the characteristic exponent (CE) of the ML correlated noise, being spatially orthogonal to the Markovian noise, on the decoherence time and population have been analyzed. Two types of ML correlated noise, one of which is diffusive, and the other being constructed by fractional generalization of the random telegraph noise, have been considered. It has been observed that the coherence time increases depending on the memory represented by the CE. Lévy type energy fluctuations with heavy tailed correlations, which might give rise to an anomalous diffusion, between the transmon qubit and the neighboring single defect in the non-Markovian bath of an amorphous coating have been analyzed. The heavy tailed correlations might cause a long-term memory in the dynamics of the interacting system. We have characterized the fluctuations by a time dependent CE for the case in which the bath has a time varying power spectral density. Therefore, we have introduced the variable order fractional master equation to model the dynamics of the transmon qubit, the simulation codes which do not exist in the literature of open quantum systems and analyzed the effects of the bath with a time dependent CE on the decoherence times.Bu tezde, literatürde ilk defa olmak üzere, Mittag-Leffler (ML) tipi ilintilerin Markov bir çevre ile etkileşimde olan transmon kübitlerin eşfazlılık sürelerinin iyileştirilmesine olan etkisini irdeledik. Tez kapsamında gerçekleştirdiğimiz ikinci çalışmada, literatürde ilk defa, amorf bir çevre içindeki kusur ile etkileşimde olan transmon kübitin zaman dinamiğini analiz ettik. Markov karakteristiğine sahip gürültü eksenine dik uygulanan ML ilintili gürültüye ait karakteristik üstelin (KÜ), eşfazlılık süresine ve kubit durum dağılımına etkisini analiz ettik. Bu kapsamda yayıngan ve rastsal telegraf gürültüsünün kesirli genelleştirilmesinden inşaa ettiğimiz iki tip ML ilintili gürültü kullandık. Eşfazlılık süresinin KÜ ile ifade edilen hafızaya bağlı olarak arttığını gözlemledik. Transmon kübit ve üzerinde üretim aşamasında oluşan amorf kaplamadaki tek bir kusur arasında Gaussian olmayan karakteristiğe sahip enerji yayılımına sebep olabilecek, aynı zamanda etkileşimdeki sistem dinamiğinde uzun süreli hafızaya sebep olabilecek ağır kuyruklu Lévy tipi enerji salınımlarını irdeledik. Çevrenin güç tayfı yoğunluğunun zaman bağımlı olma durumunu zamana bağlı kesirli üstel ile betimledik. Bu ifadeye bağlı olarak, transmon kübitin zaman dinamiğini değişken mertebeli kesirli ana denklem ile ifade ettik; zamana bağlı KÜ ile betimlenen ortamın, kübit eşfazlılık süresine etkisinin, açık kuantum sistemlerinde ilk olmak üzere, bilgisayar benzetimlerini gerçekleştirdik