Browse Articles

Microstructural geometry revealed by NMR line shape analysis

We introduce a technique for extracting microstructural geometry from NMR line shape analysis in porous materials at angstrom-scale resolution with the use of weak magnetic field gradients. Diverging from the generally held view of FID signals undergoing simple exponential decay, we show that a detailed analysis of the line shape can unravel structural geometry on much smaller scales than previously thought. While the original q-space PFG NMR relies on strong magnetic field gradients in order to achieve high spatial resolution, our current approach reaches comparable or higher resolution using much weaker gradients. As a model system, we simulated gas diffusion for xenon confined within carbon nanotubes over a range of temperatures and nanotube diameters in order to unveil manifestations of confinement in the diffusion behavior. We report a multiscale scheme that couples the above-mentioned MD simulations with the generalized Langevin equation to estimate the transport properties of interest for this problem, such as diffusivity coefficients and NMR line shapes, using the Green–Kubo correlation function to correctly evaluate time-dependent diffusion. Our results highlight how NMR methodologies can be adapted as effective means toward structural investigation at very small scales when dealing with complicated geometries. This method is expected to find applications in materials science, catalysis, biomedicine, and other areas.

Nanoencapsulation of amitriptyline enhances the potency of antidepressant-like effects and exhibits anxiolytic-like effects in Wistar rats

Depression poses a significant global health challenge, affecting an estimated 300 million people worldwide. While amitriptyline (Ami) remains one of the most effective antidepressants, its numerous side-effects contribute to a high dropout rate among patients. Addressing this issue requires exploring methods to enhance its bioavailability and reduce dosage. In this study, we describe a technique for producing amitriptyline nanoparticles (Ami-NPs) to improve the drug’s efficiency. The effectiveness was assessed by comparing the dose-response curves of Ami-NPs and non-encapsulated Ami in male and female Wistar rats subjected to the forced swimming test (FST). Ami-NPs were fabricated using nanoprecipitation, with a copolymer of poly (methyl vinyl ether/maleic acid) as the encapsulant, and a 3% solution of poloxamer F-127 as surfactant stabilizer. A Box-Behnken design was used to optimize the production of Ami-NPs, resulting in nanoparticles with the following optimal characteristics: a size of 198.6 ±  38.1 nm, a polydispersity index of 0.005 ±  0.03 nm, a zeta potential of -32 ±  6 mV, and encapsulation efficiency of 79.1 ±  7.4%. Ami-NPs showed higher potency and efficacy in reducing immobility during the FST (ED50 =  7.06 mg/kg, Emax =  41.1%), compared to amitriptyline in solution (Ami-S) (ED50 =  11.89 mg/kg, Emax =  33.2%). The Emax of Ami-NPs occurred at 12 mg/kg, while Ami-S peaked at 15.8 mg/kg. In the open field test, only treatment with Ami-NPs (12 mg/kg) and the empty nanoparticles increased immobility. In the elevated plus-maze, treatment with Ami-NPs (12 mg/kg) significantly reduced closed-arm entries (2.1 ±  0.6), compared to control solution (9.5 ±  1.8), control nanoparticles (8 ±  1.0) and Ami-S (11.5 ±  2). In the marble burying test, Ami-NPs (12 mg/kg) significantly reduced buried marbles (2.4 ±  0.4) compared to control nanoparticles (8.7 ±  1.2). These findings suggest that Ami-NPs could be a promising approach to enhance Ami bioavailability, thereby increasing its potency and antidepressant efficacy, while improving anxiolytic-like effects.

HFNC Oxygen Therapy vs COT in Prolonged Upper Gastrointestinal Endoscopy Inside the ICU: A Prospective, Randomized, Controlled Clinical Study

Secure and flexible image watermarking using IWT, SVD, and chaos models for robustness and imperceptibility

Reproducing the thermal effects induced by aging in La-based amorphous alloy

Physical aging intrinsically exists in amorphous materials and refers to the evolution of the nonequilibrium structure toward an equilibrium state. The aging process can significantly affect the thermomechanical properties of the amorphous materials, thereby influencing their macroscopic responses. Aging models not only help in understanding the underlying physical mechanisms of the relaxation behavior but also may provide an effective tool for predicting the physical and mechanical properties of metastable nonequilibrium materials in practical applications. In the current work, based on the measurement of calorimetric data and shear modulus during the heating process of amorphous metallic alloys, we obtained the mechanical and thermal property changes caused by physical aging. By incorporating the characteristic time of their α relaxation into a first-order kinetic equation and considering the coupled evolution between the characteristic time and the structural order parameter, we derived an aging kinetics model based on the hierarchically constrained atomic dynamics theory. This model effectively reproduces the thermal effects in the aging region and the supercooled liquid region observed in the calorimetric data.

Machine learning delta-T noise for temperature bias estimation

Delta-T shot noise is activated in temperature-biased electronic junctions, down to the atomic scale. It is characterized by a quadratic dependence on the temperature difference and a nonlinear relationship with the transmission coefficients of partially opened conduction channels. In this work, we demonstrate that delta-T noise, measured across an ensemble of atomic-scale junctions, can be utilized to estimate the temperature bias in these systems. Our approach employs a supervised machine learning algorithm to train a neural network, with input features being the scaled electrical conductance, the delta-T noise, and the mean temperature. Due to limited experimental data, we generate synthetic datasets, designed to mimic experiments. The neural network, trained on these synthetic data, was subsequently applied to predict temperature biases from experimental datasets. Using performance metrics, we demonstrate that the mean bias—the deviation of predicted temperature differences from their true value—is less than 1 K for junctions with conductance up to 4G0. Our study highlights that, while a single delta-T noise measurement is insufficient for accurately estimating the applied temperature bias due to noise contributions from other sources, averaging over an ensemble of junctions enables predictions within experimental uncertainties. This suggests that machine learning approaches can be utilized for estimation of temperature biases and similarly other stimuli in electronic junctions.

Impact of COVID-19 on In-Patient and Out-Patient services in Bangladesh

Introduction The global Coronavirus disease (COVID-19) pandemic disrupted healthcare systems, reducing access to medical services. In Bangladesh, strict lockdowns, healthcare worker shortages, and resource diversion further strained the system. Despite these challenges, the impact on inpatient and outpatient service utilisation in Bangladesh remains unaddressed. This study explored the levels of inpatient admissions and outpatient visits in public healthcare facilities before and during COVID-19 pandemic in Bangladesh. Methods We conducted a cross-sectional secondary analysis of inpatient and outpatient data from all public hospitals collected via District Health Information System, version 2 (DHIS2) from January 2017 to June 2021. Using 2017-2019 as the baseline, we analysed healthcare utilisation indicators (outpatient visits and inpatient admissions) with descriptive and segmented Poisson regression to assess the impact of COVID-19 in 2020 and 2021. Results In 2020, outpatient visits and inpatient admissions significantly declined to 34.1 million and 37.5 million, respectively, from 47.6 million and 56.2 million in 2019. Segmented regression analysis confirmed these drops, especially in Dhaka (IRR =  0.62, p < 0.001) and Barisal (IRR =  0.69, p < 0.002) for outpatient visits, and in Dhaka (IRR =  0.64, p < 0.000) and Khulna (IRR =  0.70, p < 0.000) for inpatient admissions. In 2021, most divisions saw an increase in outpatient visit and inpatient admission numbers, with the lowest rebound in Sylhet. Conclusion The COVID-19 pandemic significantly reduced Outpatient Department (OPD) visits and Inpatient Department (IPD) admissions in Bangladesh in 2020, with partial recovery in 2021. To ensure sustained access to care, it is crucial to strengthen healthcare facilities and equip healthcare providers to be prepared for future pandemics or emergencies.

Beyond Sound Sleep: The Wake-up Call on Benzodiazepine Overdose

Circulating biomarkers and neuroanatomical brain structures differ in older adults with and without post-traumatic stress disorder

Anomalous coercive field enhancement and phase transitions in 30Pb(In1/2Nb1/2)O3–40Pb(Mg1/3Nb2/3)O3–30PbTiO3 ferroelectrics under pressure

We investigated the spectroscopy and ferroelectric properties of 30Pb(In1/2Nb1/2)O3–40Pb(Mg1/3Nb2/3)O3–30PbTiO3 (30PIN-40PMN-30PT) single crystal as a function of pressure up to about 5 GPa. The hysteresis loops indicate that the ferroelectric properties of 30PIN-40PMN-30PT remain relatively stable below 1.4 GPa. Beyond this threshold, polarization experiences a sharp decline from 1.4 to 2.4 GPa, accompanied by an anomalous increase in coercive field (Ec) in this pressure range. The maintenance of polarization before 1.4 GPa is due to the slight suppression of lattice distortion in the ambient phase and strong suppression after that is from a phase transition and coexistence of multiphases, the latter of which also leads to the enhancement of Ec. When the phase transfers to a pure tetragonal phase after 2.4 GPa, polarization stabilizes at a plateau once more. At 4.0 GPa, current loop measurements reveal a complete loss of ferroelectric properties, signifying a structural phase transition to a paraelectric phase, evidenced by a new Raman peak at 370 cm−1. Further compression results in an absence of ferroelectricity altogether. These findings demonstrate that the material composition of 30PIN-40PMN-30PT is capable of enduring certain high pressure while maintaining commendable ferroelectric properties—providing crucial support for applications in deep-sea transducers.

Two-component relativistic equation-of-motion coupled cluster for electron ionization

We present an implementation of the relativistic ionization-potential (IP) equation-of-motion coupled-cluster (EOMCC) with up to 3-hole–2-particle (3h2p) excitations that makes use of the molecular mean-field exact two-component framework and the full Dirac–Coulomb–Breit Hamiltonian. The closed-shell nature of the reference state in an X2C-IP-EOMCC calculation allows for accurate predictions of spin–orbit splittings in open-shell molecules without breaking degeneracies, as would occur in an excitation-energy EOMCC calculation carried out directly on an unrestricted open-shell reference. We apply X2C-IP-EOMCC to the ground and first excited states of the HCCX+ (X = Cl, Br, I) cations, where it is demonstrated that a large basis set (i.e., quadruple-zeta quality) and 3h2p correlation effects are necessary for accurate absolute energetics. The maximum error in calculated adiabatic IPs is on the order of 0.1 eV, whereas spin–orbit splittings themselves are accurate to ≈0.01 eV, as compared to experimentally obtained values.

Effects of cochlear implantation on gait performance in adults with hearing impairment: A systematic review

Background Previous systematic reviews evaluated the effect of hearing interventions on static and dynamic stability and found several positive effects of hearing interventions. Despite numerous reviews on hearing interventions and balance, the impact of cochlear implantation on gait and fall risk remains unclear. Objective This systematic review examines the effects of cochlear implantation on gait performance in adults with hearing loss. Methods A comprehensive literature search was conducted in PubMed, Web of Science, and Scopus, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The PEDro scale assessed the methodological quality, risk of bias, and study design of included articles. Results Seven studies met the inclusion criteria. Five focused solely on cochlear implantation, while two included both cochlear implants (CIs) and hearing aids. Methodological inconsistencies were evident in measurement approaches and follow-up durations, leading to variable outcomes. Short-term follow-up post-implantation showed no improvement or even worsened gait outcomes. However, a longer follow-up of three months post-implantation indicated partial improvements in specific gait measures like Tandem Walk speed, though not in comfortable walking speed. Cross-sectional studies comparing on-off CI conditions revealed no significant differences in gait outcomes. Conclusions Improvements in gait due to cochlear implantation require at least three months to manifest. The variability in study methodologies complicates understanding the full impact of cochlear implantation on gait. Given that only seven, methodologically inconsistent articles were found, it is necessary to conduct additional research to understand the relationship between hearing, gait and fall risk and to specifically include longer post-CI monitoring periods.

The Range of Nonpharmacological Measures to Prevent Delirium in ICUs is Broader than Assumed

Repurposing of apoptotic inducer drugs against Mycobacterium tuberculosis

Analytical models for the thermal properties of n-type porous silicon layers: Dependence of porosity

Several reports in the literature concern the thermal properties of porous silicon samples considering the porous layer plus the silicon substrate, but not so of the porous layer in particular. This work uses the frequency domain photoacoustic technique in a heat transmission configuration together with an analysis based on a composite two-layer model of thermal resistances on n-type porous silicon and the porosity concept to develop a non-separative (and hence non-destructive) methodology for determining the thermal properties of the porous layer of n-type porous silicon and provide analytical models to obtain such properties as a function of its porosity. The porous silicon samples were elaborated by anodization, with anodization times from 10 to 100 min on (100)-oriented n-type crystalline silicon wafers and using a 48% hydrofluoric acid water solution. These wafers were non-degenerated, phosphorous doped, 500 μm roughly thick, and had 1.72 Ω cm electrical resistivity. In each sample, gravimetry determined porosity ranging from 0.279 to 0.702, and the porous layer's thickness was determined by electron microscopy. An analytical expression was obtained for the effective thermal diffusivity of the n-type porous silicon as a whole. After fitting it to the data obtained by the photoacoustic measurements, a value around 0.076 cm2/s, independent of porosity, was obtained for the thermal diffusivity of the porous layer. In addition, analytical expressions were obtained for the porous layer's thermal conductivity, volumetric heat capacity, and thermal effusivity, all showed a decreasing linear dependence on the porosity.

The XPS of pyridine: A combined theoretical and experimental analysis

A detailed analysis of the N(1s) and C(1s) X-Ray Photoelectron Spectroscopy (XPS) is made, where the measured XPS is compared with theoretical Sudden Approximation (SA) intensities and theoretical XPS Binding Energies (BEs). There is remarkably good agreement between the theoretical predictions and the measured XPS; in particular, the different full width at half maximum values for the C(1s) and N(1s) BEs are explained in terms of unresolved C(1s) BEs for the different C atoms in pyridine. This work demonstrates that the combination of theory and XPS measurements can extract analysis of the XPS relevant to the molecular electronic structure. The theory used is based on fully relativistic self-consistent field solutions of the Dirac–Coulomb Hamiltonian, and the SA is used to determine relative XPS intensities.

A two-factor scale of perceived power

Power-the capacity to influence outcomes-manifests in two distinct forms: social power, defined as the perceived ability to control others’ behaviors and decisions, and personal power, characterized by the capacity to resist unwanted external influence and maintain autonomy. Theoretically, these dimensions are rooted in different needs, and thus are likely to differentially predict certain behaviors. However, existing measures often conflate these dimensions, limiting insights into their unique behavioral effects. To address this issue, the present research has developed and validated a two-factor scale of perceived power to completely capture both facets of power across twelve studies (N =  2,878). Exploratory and confirmatory factor analyses support the scale’s structure, while reliability and validity tests demonstrate its robustness. Following assessments of the structure of the scale, its validity was demonstrated across multiple studies: Study 1 establishes the orthogonality of personal and social power through experimental manipulation, Study 2 reveals that personal power increases proactive advice-seeking, whereas social power reduces the tendency to solicit advice, and Study 3 demonstrates that social power amplifies negative reactions to service failures, while personal power does not. These divergent outcomes underscore the distinct roles of personal and social power, highlighting the scale’s utility for advancing research.

Utility of Serum Prolactin Levels as a Marker for Disease Severity and Short-term Prognosis in Patients with Cirrhosis: A Prospective Observational Study

Gene expression associated with endocrine therapy resistance in estrogen receptor-positive breast cancer

Pressure-regulated bandgap narrowing and photoelectric activity enhancement in layered halide compound GeI2

Layered semiconductors offer distinct advantages for optoelectronically responsive heterojunction devices due to their strong light–matter interactions and weak interlayer van der Waals interactions, which enable exfoliation into adjustable thicknesses. However, their practical utility is often restricted by excessively wide bandgaps, which limit spectral response within the visible light range and reduce light absorption efficiency, thereby constraining broadband detection capabilities. In this study, pressure was employed as a tuning parameter to modulate the bandgap and optimize the photoelectric performance of the layered semiconductor GeI2. Structural stability under moderate compression (5 GPa) was confirmed through in situ Raman spectra and x-ray diffraction, with no evidence of phase transition. At 5 GPa, a remarkable five-order-of-magnitude enhancement in photoelectric activity was observed. In situ UV-visible absorption spectroscopy, supported by theoretical calculations, revealed that this enhancement is primarily driven by pressure-induced narrowing of the bandgap. These findings offer critical insights for designing two-dimensional broadband photodetectors with tailored bandgap properties and enhanced photoelectric response, contributing to advancing next-generation flexible optoelectronic devices.