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Prognosis of extracolonic findings on clinical computed tomographic colonography: A single-center experience

Computed tomographic colonography (CTC) is crucial for colorectal cancer screening and secondary examinations, often revealing extracolonic findings with unclear significance. This study retrospectively evaluated the impact of such findings on the prognosis and management of 103 patients (mean observation period [OP]: 2183 days), categorized according to the CT Colonography Reporting and Data System (C-RADS). The distributions were 17% (mean OP: 2,821 days) for E1, 38% for E2 (2,759 days), 6% for E3 (2,150 days), and 39% for E4 (1,338 days). Eighteen patients were further examined, but no treatment-related changes were observed in the E2 or E3 cases. Six of nine E4 patients responded to treatment (mean OP: 1,286 days). Kaplan–Meier analysis revealed worse prognosis for E4 (mean survival: 10.1 years) than for E1–E3 combined (5.6 years) ( p < 0.0001). E4 findings are key in guiding treatment. The concordance rate between the clinical (Past E) and revised (Revised E) categories was high (0.83, 95% confidence interval: 0.77–0.88). The prognoses differed significantly between Revised E1–E3 (mean survival: 10.0 years) and Revised E4 (6.2 years) ( p < 0.0001). Although E4 significantly affects prognosis, E2 and E3 had limited effects on treatment, highlighting the need for further study to improve diagnostic accuracy.

Optimizing Oxygenation during Gastrointestinal Endoscopy: The Rise of HFNC Therapy

cRGD-based MRI imaging-enhanced nanoplatform helps DOX target pancreatic cancer

Tracking spin flip-flop dynamics of surface molecules with quantum dissipation theory

The integration of scanning tunneling microscopy (STM) and electron spin resonance spectroscopy with voltage pulses is an emerging technique to probe the local spin dynamics of surface-adsorbed molecules. However, in experiments, the detection of real-time spin dynamics is severely hampered by the limited temporal resolution of STM electronics, and the associated theoretical investigations are still in their early stages due to various challenges in numerical simulations. In this work, we employ the highly accurate hierarchical equations of motion method to characterize the spin states and track the real-time coherent flip-flop spin dynamics in a surface-adsorbed hydrogenated Ti dimer. Our simulations accurately reproduce the experimental observations and reveal the influences of substrate and pulse duration on the spin decoherence process of the dimer. These achievements provide valuable insights into the coherent spin dynamics of surface-adsorbed molecules and set the stage for the application of surface-adsorbed molecular spins to quantum sensing, quantum information processing, and quantum computing.

Barriers to and facilitators of rehabilitation according to socio-economic status, after acute respiratory distress syndrome due to COVID-19: A qualitative study in the RECOVIDS cohort

Background The COVID-19 pandemic may have compounded social disparities in access to healthcare, with possible deleterious consequences on the functional prognosis of patients after a stay in the intensive care unit (ICU). In the previous RECOVIDS study, we reported that despite comparable pulmonary sequelae and similar access to rehabilitation, socio-economically “vulnerable” patients had lower quality of life at 6 months after an ICU stay. We aimed to describe the barriers to, and facilitators of participation in rehabilitation, among patients from the RECOVIDS study, regardless of their socio-economic situation. Methods Qualitative study using semi-structured interviews with adult patients admitted to ICU for PCR-proven SARS-CoV-2 infection, and who had acute respiratory distress syndrome (ARDS) or had received high flow nasal oxygen. In addition, patients had to have been living at home for the month prior to the interview and had to be proficient in French. Eligible patients were randomly selected, aiming to select the same number of socially deprived and non-socially-deprived patients. Interviews were transcribed for thematic analysis. Results In total, 31 interviews were performed from 10/2021 to 01/2022; 16 with socially deprived, and 15 with non-deprived participants. Average age was 65.2 (±11.6) years. Four themes emerged from the analysis of the interviews, namely: (1) the impact of the patient’s professional and socio-economic situation; (2) the feeling that age and socio-economic situation influence access to rehabilitation; (3) a perception that the healthcare system was saturated, and that inequalities exist in access to rehabilitation resources; (4) perception of previous own health and expectations of post-resuscitation health status. Conclusion A precarious socio-economic situation has a substantial impact on access to rehabilitation after ICU admission for ARDS caused by COVID-19. It represents a barrier to rehabilitation through the combined action of various social determinants that deserve to be detected early, in order to take appropriate action to ensure that the most socially vulnerable individuals can benefit from access to rehabilitation.

The Effect of Perioperative Fluid Therapy on Postoperative Renal Functions in Patients Receiving Liver Transplantation from Living Donors: A Retrospective Observational Study

Enhanced expression of dystrophin, IGF-1, CD44 and MYH3 in plasma and skeletal muscles including diaphragm of mdx mice after oral administration of Neu REFIX beta 1,3-1,6 glucan

Abstract Duchenne muscular dystrophy (DMD) is a rare genetic disease, causing muscle degeneration due to lack of dystrophin with inadequate muscle regeneration culminating in muscle dysfunction. The N-163 strain of Aureobasidium Pullulans produced Beta-1,3 − 1,6-glucan (Neu REFIX) reported to be safe with anti-inflammatory and anti-fibrotic efficacy earlier, herein we evaluated its effects on muscle regeneration in mdx mice. Forty-five mice in three groups ( n  = 15 each): Group 1 (normal), Group 2 ( mdx control), and Group 3 ( mdx fed Neu REFIX) were evaluated for 45 days. IGF-1, Dystrophin, CD44 and MYH3 in diaphragm, plasma and skeletal muscle were evaluated by ELISA and immunohistochemistry. Mean IGF-1 expression was 20.32% and 16.27% higher in plasma ( p  = 0.03) and diaphragm respectively in Neu-REFIX group. Mean dystrophin was higher in Neu-REFIX group by 70.3% and 4.7% in diaphragm and plasma respectively than control. H-score intensity of CD44 + was > 2.0 with an MYH3-positivity 20% higher in Neu-REFIX than control. Oral administration of Neu REFIX was safe. Significantly enhanced plasma IGF-1 beside increased Dystrophin, MYH3 and CD44, proving a restoration of muscle regeneration and differentiation, especially in diaphragm, makes us recommend it as a disease modifying adjuvant in both early and advanced stages of DMD.

Unitary vibrational coupled cluster: General theory and implementation

Along with the surge in interest in quantum computing, interest in the unitary coupled cluster (UCC) Ansatz has reemerged. Although extensively studied within electronic structure theory, the UCC Ansatz remains relatively unexplored for the problem of molecular vibrations. In this contribution, working equations for the unitary vibrational coupled cluster (UVCC) Ansatz are derived, implemented, and benchmarked. Accuracy and convergence of state-specific excitation energies toward the full vibrational configuration interaction (FVCI) limit are observed to be comparable to vibrational coupled cluster theory. In addition, the overlap of a truncated UVCC state with the FVCI state is shown to exhibit some interesting properties from the perspective of fault-tolerant quantum computing.

Needs, rationale, and outcomes of leadership education in neurosurgery

Background Surgeons are expected to lead teams/organizations to achieve optimal patient outcomes; however, few receive formal education in leadership. The goals of the study were to: 1) assess the unmet needs and gaps in leadership education for neurosurgeons and residents/fellows; 2) identify factors associated with availability of leadership education, access to leadership positions and the similarities/differences across geographic regions and institutional type; 3) describe the associations between gender and leadership; 4) determine the impact of leadership education. Methods International survey of 657 neurosurgeons, residents/fellows. A series of univariate analysis and multivariate were conducted to assess the association between specific variables and leadership outcomes. Results Almost half (48%) indicated that leadership education did not exist in their organization. This lack was more notable in non-academic centers (p < 0.001), among neurosurgeons with less than 5 years of work experience (p = 0.03), and respondents from South America (p = 0.02). Nearly two-thirds (61.1%) reported never having leadership training. Significantly fewer respondents in the age range 35–44 years old (p = 0.02), those working in the Middle East (p = 0.02), neurosurgeons with work experience less than 5 years (p = 0.004), working in non-academic center (p = 0.02) attended leadership training. In contrast to the differences seen across geographic regions and types of institutions, overall, the proportions of males and females having access to leadership training and being offered leadership positions were similar. Among participants, 87.1% of those with leadership training were offered leadership roles, compared to 65.5% of those without leadership training (p <  0.001). Additionally, participants with leadership training experienced a burnout rate of 29.2%, whereas those without leadership training had a higher rate of burnout of 40.5% (p =  0.02). Conclusions There is a pressing need to develop educational opportunities for leadership in neurosurgery, especially for younger neurosurgeons, neurosurgeons working in non-academic centers, in countries and non-academic institutions where leadership education is less accessible. Leadership education is associated with increased numbers of neurosurgical leaders at all levels as well as reduced levels of burnout.

Prokineticin-2 and Procalcitonin\'s Diagnostic Accuracy for Sepsis in Critically Ill Patients: A Prospective Observational Study

Up-regulation of MAPK14-related lncRNAs in the circulation of migraineurs

Detection of atomic oxygen and its electronic coherence decays using time-resolved ultrafast coherent Raman scattering

We report the detection of atomic oxygen and quantitative measurements of its electronic Raman coherence decays in flames and low-temperature plasmas using time-resolved hybrid femtosecond/picosecond coherent anti-Stokes Raman scattering (CARS). Atomic oxygen was detected using the Raman transitions between the spin–orbit coupled triplet ground states. Atomic oxygen was generated in an H2/O2/Ar diffusion flame and an O2/Ar pulsed plasma discharge. Single exponential decays were observed for the O(3P2)–O(3P1) Raman transition at 158.3 cm−1 and the O(3P2)–O(3P0) Raman transition at 227 cm−1. From the decay measurements, the atomic O Raman linewidths were obtained from 25 to 150 Torr in non-equilibrium plasma and at 760 Torr in a flame. Enhanced signal-to-noise ratios (SNRs) of atomic oxygen and atomic to molecular oxygen signal contrasts were obtained by taking advantage of electronic triplet coherence beating. Enhancement of up to seven times in the atomic O SNR was observed. We also found that the dephasing rates of O2(v = 0–3, N = 37) were similar, which provides evidence for the assumption that vibrational excitation does not influence the dephasing of diatomic molecular rotational CARS transitions.

Incidence and factors associated with SARS-CoV-2 infection and re-infection among people experiencing homelessness in Toronto, Canada: A prospective cohort study

People experiencing homelessness are at elevated risk of SARS-CoV-2 infection, yet estimates generally exclude re-infections and rely on data sources affected by testing policies or study timing. In this prospective cohort study, we report incidence of SARS-CoV-2 infection and re-infections over time using a combination of community-based and study-administered testing, and assessed individual and housing-related factors associated with new infection. Individuals experiencing homelessness were randomly selected from 62 sites across Toronto, Canada, between June and September 2021. Participants provided detailed surveys and biological samples to test for SARS-CoV-2 (by RT-PCR and ELISA) every three months for one year. Self-reported data were verified and augmented through linkage to health administrative databases. Among 640 participants who completed 2,401 interviews, we identified 613 SARS-CoV-2 infection events, representing an incidence rate of 35.3 infections/100-person years (95% CI 31.6-39.4) prior to the onset of Omicron and 97.2 infections/100 person-years (95% CI 86.8-108.8) after Omicron. Nearly 30% (n = 182) of these events were re-infections. In multivariable models, post-Omicron interviews (adjusted rate ratio [aRR] 3.54 [95% CI 3.12-4.02]), history of prior COVID-19 infection (1 infection aRR 2.55 [95% CI 2.29-2.83]; 2 + infections aRR 2.28 [95% CI 1.80-2.89]) and residing in high- or moderate-exposure risk (congregate and shared) housing settings (high-exposure aRR 1.74 [95% CI 1.43-2.11]; moderate-exposure aRR 1.39 [1.15-1.68]) were most significantly associated with new infection. Our findings highlight that existing reports significantly underestimate SARS-CoV-2 infection burden among people experiencing homelessness, but confirms previously reported factors associated with infection, including congregate and shared housing settings. Reducing reliance on overcrowded emergency housing is necessary to reduce infection incidence in this population as well as associated inequities in downstream acute and chronic complications.

Validity of MACOCHA Score in Predicting First-pass Success of Endotracheal Intubation in Emergency Department: An Observational Study

CGRPβ suppresses the pathogenesis of ulcerative colitis via the immunoproteasome

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

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.