Katarína Nemčeková, Patrícia Dudoňová, Tomáš Holka
et al.
Silver nanoparticles (AgNPs) have attracted tremendous attention in recent years due to their unique physicochemical properties, including pronounced surface plasmon resonance, tunable size, and amenability to functionalization. These attributes underpin the growing interest in AgNPs as SMART nanocarriers for targeted drug delivery and as active components in biosensing platforms. In this work, we discuss various synthesis strategies for AgNPs—ranging from conventional chemical methods to green approaches—and highlight their subsequent functionalization with anticancer drugs, notably doxorubicin (DOX). We also examine the potential of AgNPs in biosensor applications, emphasizing electrochemical and optical detection modalities capable of monitoring drug release, oxidative stress, and relevant biomarkers. Our experimental data support the conclusion that AgNPs can effectively improve therapeutic efficacy by exploiting tumor-specific conditions (e.g., lower pH) while also enhancing biosensor sensitivity via surface plasmon resonance and electrochemical signal amplification. We provide a thorough discussion of the results, including mechanistic aspects of reactive oxygen species (ROS) generation, drug release kinetics, and sensor performance metrics. Overall, AgNP-based nanocarriers emerge as a powerful platform to address current challenges in precision oncology and medical diagnostics.
Chintu Sundaresan, Teena Haneef, V. R Anusha
et al.
Background:
Dental anxiety is a prevalent concern in pediatric patients, often leading to compromised oral healthcare outcomes. Effective behavioral management techniques are essential in reducing anxiety and facilitating successful dental treatments.
Materials and Methods:
A randomized clinical trial was conducted involving 90 children aged between 4 and 8 years attending a pediatric dental clinic. The participants were randomly divided into three groups (n = 30 each): Group A (Tell-Show-Do), Group B (audiovisual distraction), and Group C (modeling). Anxiety levels were assessed before and after the intervention using the Facial Image Scale (FIS) and Pulse Rate Monitoring with a pulse oximeter.
Results:
All three techniques led to a significant reduction in anxiety levels post-intervention. The mean FIS score decreased from 4.2 ± 0.6 to 2.1 ± 0.5 in Group A, 4.3 ± 0.5 to 1.9 ± 0.4 in Group B, and 4.1 ± 0.7 to 2.3 ± 0.6 in Group C (P < 0.001). The pulse rate also showed a reduction: Group A (from 105.4 ± 8.2 bpm to 92.1 ± 7.4 bpm), Group B (from 106.8 ± 7.9 bpm to 89.3 ± 6.5 bpm), and Group C (from 104.6 ± 8.6 bpm to 95.8 ± 7.8 bpm). Audiovisual distraction showed the greatest reduction in both subjective and physiological parameters of anxiety compared to the other groups.
Conclusion:
All three behavioral management techniques were effective in reducing dental anxiety among children aged 4–8 years. However, audiovisual distraction proved to be the most effective, followed by Tell-Show-Do and modeling.
Grain-surface chemistry plays a crucial role in the formation of molecules of astrobiological interest, including H$_{2}$S and complex organic molecules (COMs). They are commonly observed in the gas phase toward star-forming regions, but their detection in ices remains limited. Combining gas-phase observations with chemical modeling is therefore essential for advancing our understanding of their chemistry. In this paper we investigate the factors that promote or hinder molecular complexity combining gas-phase observations of CH$_{3}$OH, H$_{2}$S, OCS, N$_{2}$H$^{+}$, and C$^{18}$O with chemical modeling in two dense cores: Barnard-1b and IC348. We observed millimeter emission lines of CH$_{3}$OH, H$_{2}$S, OCS, N$_{2}$H$^{+}$, and C$^{18}$O along strips using the IRAM 30m and Yebes 40m telescopes. We used the gas-grain chemical model \texttt{Nautilus} to reproduce the observed abundance profiles adjusting parameters such as initial sulfur abundances and binding energies. H$_{2}$S, N$_{2}$H$^{+}$ and C$^{18}$O gas-phase abundances vary up to one order of magnitude towards the extinction peak. CH$_{3}$OH abundance remains quite uniform. These abundances can only be reproduced assuming a decreasing sulfur budget, which lowers H$_{2}$S and enhances CH$_{3}$OH abundances. Decreasing binding energies, which are expected in CO-rich apolar ices, are also required. The sulfur depletion required by H$_2$S is generally higher than that required by CH$_3$OH, suggesting unknown sulfur sinks. These findings highlight the intricate relationship between sulfur chemistry and COM formation, driven by the competition between sulfur and CO for hydrogen atoms. Our study emphasizes that the growth of CO ice and the progressive sequestration of hydrogen atoms by sulfur are critical in determining whether chemical complexity can develop, providing key insights into the early stages of star and planet formation.
Quantum computing has the potential to revolutionize quantum chemistry and material science by offering solutions to complex problems unattainable with classical computers. However, the development of efficient quantum algorithms that are efficient under noisy conditions remains a major challenge. This paper introduces the truncated Variational Hamiltonian Ansatz (tVHA), a novel circuit design for conducting quantum calculations on Noisy Intermediate-Scale Quantum (NISQ) devices. tVHA provides a promising approach for a broad range of applications by utilizing principles from the adiabatic theorem in solid state physics. Our proposed ansatz significantly reduces the parameter count and can decrease circuit size substantially, with a trade-off in accuracy. Thus, tVHA facilitates easier convergence within the variational quantum eigensolver framework compared to state-of-the-art ansätze such as Unitary Coupled Cluster (UCC) and Hardware-Efficient Ansatz (HEA). While this paper concentrates on the practical applications of tVHA in quantum chemistry, demonstrating its suitability for both weakly and strongly correlated systems and its compatibility with active space calculations, its underlying principles suggest a wider applicability extending to the broader field of material science computations on quantum computing platforms.
Hybrid quantum-classical algorithms have begun to leverage quantum devices to efficiently represent many-electron wavefunctions, enabling early demonstrations of molecular simulations on real hardware. A key prerequisite for scalable quantum chemistry, however, is size consistency: the energy of non-interacting subsystems must scale linearly with system size. While many algorithms are theoretically size-consistent, noise on quantum devices may couple nominally independent subsystems and degrade this fundamental property. Here, we systematically evaluate size consistency on quantum hardware by simulating systems composed of increasing numbers of non-interacting H$_{2}$ molecules using optimally shallow unitary circuits. We find that molecular energies remain size-consistent within chemical accuracy for an estimated 118 and 71 H$_{2}$ subsystems for one- and two-qubit unitary designs, respectively, demonstrating that current quantum devices preserve size consistency over chemically relevant system sizes and supporting the feasibility of scalable, noise-resilient simulation of strongly correlated molecules and materials.
In solid-state nanopores, achieving reliable control over pore aperture opening and closing (gating) remains a major challenge. Gating can be driven by the applied voltage involving electrically tunable chemical reactions, achieved by selecting appropriate compounds within the nanopore volume. In particular, cyclic precipitation and dissolution of metal phosphates can be triggered by regulating cation transport through an applied transmembrane voltage, thereby enabling reversible pore gating. Under negative bias, metal phosphate precipitates form inside the pore, obstructing ion flow and reducing current. Switching the polarity dissolves the precipitates, restoring ionic conductance. This process effectively produces a nanofluidic diode characterized by a remarkably high rectification ratio. To probe these localized chemical reactions more directly, we employed a plasmonic nanopore that generates strong confined fields, enabling surface-enhanced Raman scattering (SERS) measurements within the nanopore volume during cyclic gating. These measurements not only validate the proposed in-pore chemistry but also highlight the potential of plasmonic nanopores as powerful tools for monitoring nanoscale chemical processes with high spatial resolution.
Bacterial small laccases (SLAC) are promising industrial biocatalysts due to their ability to oxidize a broad range of substrates with exceptional thermostability and tolerance for alkaline pH. Electron transfer between substrate, copper centers, and O2 is one of the key steps in the catalytic turnover of SLAC. However, limited research has been conducted on the electron transfer pathway of SLAC and SLAC-catalyzed reactions, hindering further engineering of SLAC to produce tunable biocatalysts for novel applications. Herein, the combinational use of electron paramagnetic resonance (EPR) and ultraviolet–visible (UV–vis) spectroscopic methods coupled with redox titration were employed to monitor the electron transfer processes and obtain further insights into the electron transfer pathway in SLAC. The reduction potentials for type 1 copper (T1Cu), type 2 copper (T2Cu) and type 3 copper (T3Cu) were determined to be 367 ± 2 mV, 378 ± 5 mV and 403 ± 2 mV, respectively. Moreover, the reduction potential of a selected substrate of SLAC, hydroquinone (HQ), was determined to be 288 mV using cyclic voltammetry (CV). In this way, an electron transfer pathway was identified based on the reduction potentials. Specifically, electrons are transferred from HQ to T1Cu, then to T2Cu and T3Cu, and finally to O2. Furthermore, superhyperfine splitting observed via EPR during redox titration indicated a modification in the covalency of T2Cu upon electron uptake, suggesting a conformational alteration in the protein environment surrounding the copper sites, which could potentially influence the reduction potential of the copper sites during catalytic processes. The results presented here not only provide a comprehensive method for analyzing the electron transfer pathway in metalloenzymes through reduction potential measurements, but also offer valuable insights for further engineering and directed evolution studies of SLAC in the aim for biotechnological and industrial applications.
Physical and theoretical chemistry, Analytical chemistry
Alicia Thiel, Franziska Drews, Marcello Pirritano
et al.
Cobalt (Co) and Nickel (Ni) are used nowadays in various industrial applications like lithium-ion batteries, raising concerns about their environmental release and public health threats. Both metals are potentially carcinogenic and may cause neurological and cardiovascular dysfunctions, though underlying toxicity mechanisms have to be further elucidated. This study employs untargeted transcriptomics to analyze downstream cellular effects of individual and combined Co and Ni toxicity in human liver carcinoma cells (HepG2). The results reveal a synergistic effect of Co and Ni, leading to significantly higher number of differentially expressed genes (DEGs) compared to individual exposure. There was a clear enrichment of Nrf2 regulated genes linked to pathways such as glycolysis, iron and glutathione metabolism, and sphingolipid metabolism, confirmed by targeted analysis. Co and Ni exposure alone and combined caused nuclear Nrf2 translocation, while only combined exposure significantly affects iron and glutathione metabolism, evidenced by upregulation of HMOX-1 and iron storage protein FTL. Both metals impact sphingolipid metabolism, increasing dihydroceramide levels and decreasing ceramides, sphingosine and lactosylceramides, along with diacylglycerol accumulation. By combining transcriptomics and analytical methods, this study provides valuable insights into molecular mechanisms of Co and Ni toxicity, paving the way for further understanding of metal stress.
Deepshikha Singh, Shruti Gupta, Arpita Goswami
et al.
Aim:
The purpose of this research is to determine the relationship between periodontal disease severity, cigarette smoking, gutka chewing, and type 2 diabetes mellitus by estimating, correlating, and comparing blood levels of vitamin B12, folic acid, and erythrocyte sedimentation rate (ESR) in patients with chronic periodontitis.
Methodology:
A cross-sectional research study conducted at Rama Dental College Hospital and Research Centre in Kanpur involved 240 patients with chronic periodontitis, who also exhibited additional risk factors including smoking, gutkha chewing, and type-2 diabetes mellitus. Divided into four groups of 60 individuals each, the study aimed to estimate and correlate blood levels of vitamin B12, folic acid, and ESR. Group I served as the control with chronic periodontitis patients, while Group II comprised chronic periodontitis patients who were smokers, Group III included those who chewed gutkha, and Group IV consisted of patients with type-2 diabetes mellitus. Clinical parameters were assessed, and patients were followed up to track any changes or correlations.
Result:
This research confirmed that low levels of vitamin B12 and folic acid are linked to inflammatory diseases such chronic periodontitis.
Conclusion:
The study revealed that type-2 diabetic and gutka chewer groups exhibited statistically higher periodontal disease severity, vitamin B12, and folic acid deficiencies and elevated ESR compared to smokers and control groups.
Riddhi Chawla, Abhishek Jahagirdar, Happy Riba
et al.
Background:
A common sleep problem linked to poor cardiovascular outcomes and death is “sleep apnea (SL).” Nevertheless, little is known about how SL affects cardiovascular health in the long run. The purpose of this research was to investigate the relationship between a tertiary care center’s long-term cohort’s cardiovascular morbidity and mortality and the severity of their SL.
Methods:
Between January 1, 2010, and December 31, 2020, 500 individuals at a tertiary care facility who had been diagnosed with SL participated in this retrospective cohort research. Electronic medical records were used to collect patient data, which were then examined for cardiovascular outcomes, treatment methods, comorbidities, sleep research findings, and demographics. Heart failure, myocardial infarction, stroke, and cardiovascular-related mortality were among the cardiovascular events that were noted throughout the follow-up period, and the severity of SL was classified using the “apnea–hypopnea index.”
Findings:
Of the 500 patients in the cohort, 60% were men and the mean age was 55.7 years. Fifty percent of people had one or more cardiovascular risk factors, including diabetes, high blood pressure, and smoking. During the course of the follow-up, 100 cardiovascular-related fatalities were reported, and 40% of patients had at least one cardiovascular event. The severity of SL was shown to be positively correlated with the occurrence of cardiovascular events (16.7% in mild, 25% in moderate, and 40% in severe SL, P < 0.05).
Conclusion:
In a cohort of patients receiving tertiary care, this research shows a substantial correlation between the severity of SL and cardiovascular morbidity and death. It is crucial to identify and treat SL early on to reduce cardiovascular risks and enhance patient outcomes. To further understand the underlying processes and develop treatment approaches for people with cardiovascular comorbidities and SL, more research is necessary.
Prachi Khatri, Cristiano Porciani, Emilio Romano-Díaz
et al.
Aims. We present a new sub-grid model, HYACINTH -- HYdrogen And Carbon chemistry in the INTerstellar medium in Hydro simulations -- for computing the non-equilibrium abundances of ${\rm H_2}$ and its carbon-based tracers, namely ${\rm CO}$, ${\rm C}$, and ${\rm C^+}$, in cosmological simulations of galaxy formation. Methods. The model accounts for the unresolved density structure in simulations using a variable probability distribution function of sub-grid densities and a temperature-density relation. Included is a simplified chemical network that has been tailored for hydrogen and carbon chemistry within molecular clouds and easily integrated into large-scale simulations with minimal computational overhead. As an example, we applied HYACINTH to a simulated galaxy at redshift $z \sim 2.5$ in post-processing and compared the resulting abundances with observations. Results. The chemical predictions from HYACINTH are in reasonable agreement with high-resolution molecular-cloud simulations at different metallicities. By post-processing a galaxy simulation with HYACINTH, we reproduced the $\rm H\,I-{\rm H_2}$ transition as a function of the hydrogen column density $N_{\rm H}$ for both Milky-Way-like and Large-Magellanic-Cloud-like conditions. Column density maps reveal that ${\rm CO}$ is concentrated in the peaks of the ${\rm H_2}$ distribution, while atomic carbon more broadly traces the bulk of ${\rm H_2}$ in our post-processed galaxy. Based on both the column density maps and the surface density profiles of the different gas species in the post-processed galaxy, we find that ${\rm C^+}$ maintains a substantially high surface density out to $\sim 10 \, \rm kpc$ as opposed to other components that exhibit a higher central concentration. This is similar to the extended $[\rm C\,II]$ emission found in some recent observations at high redshifts.
Uncertainty quantification enables users to assess the reliability of responses generated by large language models (LLMs). We present a novel Question Rephrasing technique to evaluate the input uncertainty of LLMs, which refers to the uncertainty arising from equivalent variations of the inputs provided to LLMs. This technique is integrated with sampling methods that measure the output uncertainty of LLMs, thereby offering a more comprehensive uncertainty assessment. We validated our approach on property prediction and reaction prediction for molecular chemistry tasks.
In the present work, potentiometric sensors with polymer membranes used for chlorhexidine (CHXD) determination were developed. The polymer membranes were plasticized with bis(2-ethylheksyl)sebacate (DOS) or 2-nitrophenyloctyl ether (<i>o</i>-NPOE). The active compounds used in the membrane were cyclodextrins, crown ethers, and ion exchangers. The best-constructed electrode was based on neutral heptakis(2,3,6-tri-O-benzoyl)-<i>β</i>-cyclodextrin with lipophilic salt (KTpClBP)—potassium tetrakis(4-chlorophenyl) borate—dissolved in plasticizer, DOS. The presented electrode is characterized by an average cationic slope of 30.9 ± 2.9 mV decade<sup>−1</sup> within a linear range of 1 × 10<sup>−6</sup> to 1 × 10<sup>−3</sup> mol × L<sup>−1</sup>, while the value of the correlation coefficient is 0.9970 ± 0.0026. The response time was about 5 s when increasing the sample concentration and about 10 s when diluting the sample. The electrode potential is independent of the pH within a range of 4.0–9.5. The polymeric membrane sensor was successfully applied for assays of chlorhexidine digluconate in pure samples and pharmaceutical samples. The relative error from three replicate measurements was determined to be 1.1%. and the accuracy was RSD = 0.3–1.1%.
Eliška Jiroušková, Radomír Čabala, Romana Sokolová
Abstract Electrochemical oxidation of the new psychoactive substance 3‐fluorophenmetrazine (FPM) was studied in phosphate buffers by cyclic voltammetry and differential pulse voltammetry (DPV) on a glassy carbon electrode. The redox potential of FPM in buffered solution strongly depends on pH. Cyclic voltammetry behavior shows the partial influence of adsorption on the electrode process not allowing detailed analysis of the individual steps of the reaction scheme, it means the involvement of electron transfer (E) and chemical reaction (C). Nevertheless, the irreversible shape of the cyclic voltammogram is explained by the participation of hydroxylation nucleophilic addition of water (hydroxylation) after two‐electron/two‐proton oxidation of molecule at the tetrahydro‐1,4‐oxazine ring. The suggested mechanism leading to hydroxylated derivative 2‐(3‐fluorophenyl)‐3‐methyl‐5‐hydroxymorfolin is supported by the calculated highest occupied molecular orbital spatial distribution and atomic charges calculations for electrochemically formed radical cation. Infrared spectroelectrochemistry performed during oxidation in acetonitrile/water also supported the formation of this product. The analytical method of FPM determination on glassy carbon electrode was developed using DPV with an attained limit of detection = 4.7 μmol/L in phosphate buffer of pH 9. The linear range of the calibration curve is from 7.0 to 107.00 μmol/L, correlation coefficient (r) = 0.9988.
Hybrid quantum-classical approaches offer potential solutions to quantum chemistry problems, yet they often manifest as constrained optimization problems. Here, we explore the interconnection between constrained optimization and generalized eigenvalue problems through the Unitary Coupled Cluster (UCC) excitation generators. Inspired by the generator coordinate method, we employ these UCC excitation generators to construct non-orthogonal, overcomplete many-body bases, projecting the system Hamiltonian into an effective Hamiltonian, which bypasses issues such as barren plateaus that heuristic numerical minimizers often encountered in standard variational quantum eigensolver (VQE). Diverging from conventional quantum subspace expansion methods, we introduce an adaptive scheme that robustly constructs the many-body basis sets from a pool of the UCC excitation generators. This scheme supports the development of a hierarchical ADAPT quantum-classical strategy, enabling a balanced interplay between subspace expansion and ansatz optimization to address complex, strongly correlated quantum chemical systems cost-effectively, setting the stage for more advanced quantum simulations in chemistry.
M. Shahidul Islam, Kei Nakagawa, M. Abdullah-Al-Mamun
et al.
Pond water is used in everyday life by many people in Bangladesh, however, without sufficient and reliable information regarding water quality and pollution status. For this reason, geospatial analysis and mapping of water quality indices such as metal (MI), contamination (Cd), and physicochemical water quality index (WQI) were assessed to improve the understanding of potential pollution sources. Samples were collected from twenty randomly selected ponds situated in Jashore Sadar Upazila, Bangladesh. Nineteen (19) water quality parameters were measured, including pH, temperature, EC, TDS, total suspended solids (TSS), chloride, alkalinity, total hardness, salinity, Fe, Mn, Pb, Cr, Cd, Co, Zn, Ag, Ni, and Cu. The average concentration of Fe, Mn, Pb, Cd, and Ag was much higher than recommended standards. The WQI ranged from 1.59-5.27, Cd from -0.19-18.28, and MI from 7.81-26.28. The spatial distribution of MI indicates that the south-western and south-eastern region of the study area are stands out with a very high pollution pressure. The spatial distribution of Cd, follows the same trend as for MI. A multitude of different types of pollution sources contributes to the high pollution load such as, municipal wastewater, leachate from landfills, small industry wastewater and stormwater, and agricultural runoff. The studied pond water is highly polluted and not suitable for household use and fish consumption.