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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
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
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
Efficient sampling of free energy landscapes with functions in Sobolev spaces
Molecular simulations of biological and physical phenomena generally involve sampling complicated, rough energy landscapes characterized by multiple local minima. In this work, we introduce a new family of methods for advanced sampling that draw inspiration from functional representations used in machine learning and approximation theory. As shown here, such representations are particularly well suited for learning free energies using artificial neural networks. As a system evolves through phase space, the proposed methods gradually build a model for the free energy as a function of one or more collective variables, from both the frequency of visits to distinct states and generalized force estimates corresponding to such states. Implementation of the methods is relatively simple and, more importantly, for the representative examples considered in this work, they provide computational efficiency gains of up to several orders of magnitude over other widely used simulation techniques.
Ethiopian antimicrobial consumption trends in human health sector: A surveillance report 2020–2022
Background Antimicrobial resistance (AMR) poses a severe global health threat, driven by the overuse and misuse of antimicrobials across the human, agricultural, and veterinary sectors. To combat this, global and national AMR prevention and containment strategies have been implemented, necessitating continuous monitoring of antimicrobial consumption (AMC) as an integral part of antimicrobial stewardship interventions. Objective This study aims to assess and analyze trends in AMC in Ethiopia from 2020 to 2022, with the goal of informing national and sub-national strategies to combat AMR. Methods A three-year AMC surveillance was conducted from 2020 to 2022. Data on locally manufactured and imported antimicrobials were collected from local manufacturers and Ethiopian Food and Drug Authority (EFDA)-regulated ports of entry. AMC was analyzed using the WHO GLASS AMC tool, with antimicrobials categorized using the WHO Anatomical Therapeutic Chemical (ATC) classification system. Consumption was measured in Defined Daily Doses (DDDs) and DDD per 1,000 inhabitants per day (DID), normalized using population estimates from the World Population Prospects for Ethiopia. Results The total AMC in Ethiopia increased from 432 million DDDs in 2020 to 485 million DDDs in 2022. The DID rose from 10.63 in 2020 to 11.34 in 2022. Antibacterials dominated consumption, comprising 98.87% in 2020, 95.96% in 2021, and 99.79% in 2022. Penicillins (J01C) and quinolones (J01M) were the most consumed antimicrobials. As per the Ethiopian AWaRe classification, the majority of antibacterial agents consumed were in the Access group, accounting for 71.14% in 2020, 70.65% in 2021, and 74.2% in 2022. Oral formulations consistently made up over 87% of the total consumption each year. Reliance on imported antimicrobials remained high, with imports comprising 64.76% in 2020 and 74.47% in 2022. Conclusion The increasing trend in AMC in Ethiopia from 2020 to 2022 underscores the urgent need to establish and strengthen national, sub-national, and facility-level surveillance and reporting systems to better monitor and ensure rational antimicrobial use.
FDEM numerical simulation of size effect on mechanical properties of basalts with hidden microcracks
Pulsed discharge jet laser spectroscopy of the stibino (SbH2) free radical: Hyperfine and isotopic structure in the high-resolution electronic spectrum
The Ã2A1–X̃2B1 0-0 bands of the overlapping LIF spectra of 121SbH2 and 123SbH2 have been recorded at high resolution under supersonic expansion conditions. The radicals were made by a pulsed electric discharge through a dilute mixture of SbH3 in high pressure argon at the exit of a pulsed molecular beam valve. The Sb isotopic lines, magnetic hyperfine structure, and large spin-rotation splittings have been assigned in the spectra. The transitions of the two isotopologues were fitted independently, and the rotational constants were used to obtain the following zero-point effective molecular structures: r″ = 1.7203(1) Å, θ″ = 90.370(4)°; r′ = 1.6915(4) Å and θ′ = 120.80(2)°. The fitted molecular constants have been validated using isotope relations and by comparison with theoretical formulas. The T0 antimony isotope splitting of SbH2 is only 0.0098 cm−1.
Molecular screening and dynamics simulation reveal potential phytocompounds in Swertia chirayita targeting the UspA1 protein of Moraxella catarrhalis for COPD therapy
Chronic obstructive pulmonary disease (COPD) is a global health burden, with Moraxella catarrhalis significantly contributing to acute exacerbations and increased healthcare challenges. This study aimed to identify potential drug candidates in Swertia chirayita, a traditional Himalayan medicinal plant, demonstrating efficacy against the ubiquitous surface protein A1 (UspA1) of M. catarrhalis through an in-silico computational approach. The three-dimensional structures of 46 phytocompounds of S. chirayita were retrieved from the IMPPAT 2.0 database. The structures underwent thorough analysis and screening, emphasizing key factors such as binding energy, molecular docking performance, drug-likeness, and toxicity prediction to assess their therapeutic potential. Considering the spectrometry, pharmacokinetic properties, docking results, drug likeliness, and toxicological effects, five phytocompounds such as beta-amyrin, calendol, episwertenol, kairatenol and swertanone were identified as the inhibitors of the UspA1 in M. catarrhalis. UspA1 demonstrated binding affinities of –9.1 kcal/mol for beta-amyrin, –8.9 kcal/mol for calendol, –9.4 kcal/mol for episwertenol, –9.6 kcal/mol for kairatenol, and –9.0 kcal/mol for swertanone. All of these affinities were stronger than that of the control drug ceftobiprole, which had a binding score of –6.6 kcal/mol. The toxicity analysis confirmed that all five compounds are safe potential therapeutic options, showing no toxicity or carcinogenicity. We also performed a 100 ns molecular dynamics simulation of the phytocompounds to analyze their stability and interactions as protein-ligand complexes. Among the five screened phytocompounds, beta-amyrin and episwertenol exhibited favorable characteristics, including stable root mean square deviation values, minimal root mean square fluctuations, and consistent radius of gyration values. Throughout the simulations, intermolecular interactions such as hydrogen bonds and hydrophobic contacts were maintained. Additionally, the compounds demonstrated strong affinity, as indicated by negative binding free energy values. Taken together, findings of this study strongly suggest that beta-amyrin and episwertenol have the potential to act as inhibitors against the UspA1 protein of M. catarrhalis, offering promising prospects for the treatment and management of COPD.
Publisher Correction: Identification of potential biomarkers and pathways involved in high-altitude pulmonary edema using GC-MS and LC-MS metabolomic methods
Bridge connectivity effects on photoinduced ground-state electron spin polarization
Transient electron paramagnetic resonance (TREPR) spectroscopy has been used to probe photoinduced electron spin polarization in the recovered ground states of four radical-elaborated (CAT)Pt(bpy) donor-acceptor complexes (CAT = catechol; bpy = 4,4′-di-tert-butyl-2,2′-bipyridine). These complexes are comprised of one or two S = 1/2 nitronyl nitroxide radicals attached through different phenylethynyl bridges to the 3- or 3,6 positions of the CAT donor. In this study, we demonstrate the effects of substitution patterns on the magnitude of the TREPR signal, thereby guiding future design principles for generating and understanding the origin of photoinduced electron spin polarization in these and related chromophores.
Factors influencing disaster preparedness behaviors of older adults
This study examines the heterogeneity in disaster preparedness behaviors among older adults and the factors that influence them, with the aim of offering policy recommendations to mitigate casualties among older adults during natural disasters. This is a secondary data analysis of cross-sectional data involving 394 participants aged 65 and above, with data sourced from the seventh wave of the Basic Social Change Survey conducted by Academia Sinica. These cross-sectional data were collected through face-to-face interviews, where interviewers conducted one-on-one questioning to gather general information and assess disaster preparedness. Hierarchical regression analysis was employed to explore the relationship between various factors and disaster preparedness behaviors. Descriptive statistics show that among the six disaster preparedness behaviors, 32.5% of the elderly moved vehicles or household items to a safe location, and 27.2% secured cabinets or large appliances. The remaining four disaster preparedness behaviors—including purchasing disaster insurance, preparing a disaster emergency kit, identifying and planning evacuation locations and routes, and participating in disaster response drills—were exhibited by less than 11.9% of the participants. Hierarchical regression showed that younger age, higher education, lower income, better health, community involvement, disaster experience, and higher perceived risk were associated with increased preparedness among older adults. The study found that most older adults do not invest time or money in disaster preparedness. Government agencies should encourage older adults to participate and account for their heterogeneity, such as through targeted interventions in health promotion, disaster response education, and social support. Initiatives like health check-ups, exercise classes to improve physical fitness, and simple, understandable disaster response courses can enhance risk perception. For high-income groups, emphasizing the importance of disaster preparedness through data and real-life examples is crucial. Older adults should also be encouraged to join community organizations and disaster drills, and a platform for sharing disaster experiences should be established to improve overall disaster resilience.