Tag: pubmed

Science. 2023 Oct 27;382(6669):443-447. doi: 10.1126/science.abq6753. Epub 2023 Oct 26.

ABSTRACT

The understanding of nonequilibrium dynamics in many-body quantum systems is a fundamental issue in statistical physics. Experiments that probe universal properties of these systems can address such foundational questions. In this study, we report the measurement of universal dynamics triggered by a quench from the superfluid to normal phase across the Berezinskii-Kosterlitz-Thouless transition in a two-dimensional (2D) Bose gas. We reduced the density by splitting the 2D gas in two, realizing a quench across the critical point. The subsequent relaxation dynamics were probed with matter-wave interferometry to measure the local phase fluctuations. We show that the time evolution of both the phase correlation function and vortex density obeys universal scaling laws. This conclusion is supported by classical-field simulations and interpreted by means of real-time renormalization group theory.

PMID:37883542 | DOI:10.1126/science.abq6753

PLoS One. 2023 Oct 26;18(10):e0293598. doi: 10.1371/journal.pone.0293598. eCollection 2023.

ABSTRACT

Acute myocardial infarction is an acute-stage disease that requires prompt diagnosis and treatment. Primary percutaneous coronary intervention (pPCI) for ST-elevation myocardial infarction (STEMI) is a high-risk factor for post-contrast acute kidney injury (PC-AKI). This retrospective cohort study analyzed the data of 754 patients with STEMI who underwent pPCI and were integrated into the Fast Interrogation Rule for STEMI critical pathway program between 2015 and 2019. We aimed to determine the optimal cutoff baseline eGFR for identifying a high risk of PC-AKI after multivariable adjustment with statistically significant risk factors. We also compared the incidence rates of PC-AKI between the previous and current diagnostic criteria. The probability of PC-AKI increased when the baseline estimated glomerular filtration rate (eGFR) was ≤ 79mL/min/1.73 m2. The optimal cutoff baseline eGFR for high risk of PC-AKI was found to be an eGFR of ≤ 61 mL/min/1.73 m2 after multivariable adjustment. The current diagnostic criteria more accurately identified the patient group with impaired renal function. Our results have clinically significant implications for identifying patients at a high risk of developing PC-AKI, especially before and after the use of contrast agents in patients who require PCI for STEMI in the emergency department.

PMID:37883518 | DOI:10.1371/journal.pone.0293598

PLoS One. 2023 Oct 26;18(10):e0286403. doi: 10.1371/journal.pone.0286403. eCollection 2023.

ABSTRACT

There is a norm in psychology to use causally ambiguous statistical language, rather than straightforward causal language, when describing methods and results of nonexperimental studies. However, causally ambiguous language may inhibit a critical examination of the study’s causal assumptions and lead to a greater acceptance of policy recommendations that rely on causal interpretations of nonexperimental findings. In a preregistered experiment, 142 psychology faculty, postdocs, and doctoral students (54% female), ages 22-67 (M = 33.20, SD = 8.96), rated the design and analysis from hypothetical studies with causally ambiguous statistical language as of higher quality (by .34-.80 SD) and as similarly or more supportive (by .16-.27 SD) of policy recommendations than studies described in straightforward causal language. Thus, using statistical rather than causal language to describe nonexperimental findings did not decrease, and may have increased, perceived support for implicitly causal conclusions.

PMID:37883517 | DOI:10.1371/journal.pone.0286403

PLoS One. 2023 Oct 26;18(10):e0289376. doi: 10.1371/journal.pone.0289376. eCollection 2023.

ABSTRACT

The present field experiment investigated how alibi witnesses react when confronted with camera footage or identification testimony that incriminates an innocent suspect. Under the pretext of a problem-solving study, pairs of participants (N = 109) and confederates worked on an individual task with a dividing wall obstructing their view of each other. When the mobile phone of the experimenter was missing from an adjacent room at the end of the session, all participants confirmed that the confederate had not left the room. After several days, participants returned to the lab for a second session. They were asked to confirm their corroboration, orally and in writing, after learning that the confederate either had been identified from a photograph or was present on camera footage. A control group received no evidence. In this second session, written (but not oral) alibi corroboration was weaker in the incriminating evidence conditions (47%) than the no-evidence condition (81%), as hypothesized. Unexpectedly, corroboration was equally strong in the camera and identification evidence conditions. As expected, alibi corroboration was stronger in session 1 than in session 2 for both camera (89% and 31-46%) and identification evidence conditions (86% and 31-49%). The current findings provide first evidence that camera footage and eyewitness identification testimony can bear on the availability of exculpatory alibi evidence in court and emphasize the need to document incidents of evidence contamination.

PMID:37883512 | DOI:10.1371/journal.pone.0289376

PLoS One. 2023 Oct 26;18(10):e0293665. doi: 10.1371/journal.pone.0293665. eCollection 2023.

ABSTRACT

Oral health might not only act as risk factor for head and neck squamous cell carcinoma (HNSCC), but might also have a predictive value for the patients’ survival. Currently, information on the effect of oral health on survival of patients with different sites of HNSCC is lacking. This single-center retrospective study aimed to compare oral health in patients with different sites of HNSCC and to analyse whether oral health is associated with survival in the different subsets of HNSCC patients. Dental records of HNSCC patients referred for dental assessment prior to radio(chemo)therapy were included. Patient-related parameters (age at time of diagnosis, sex, tobacco exposure, alcohol consumption, HPV status), treatment data (primary treatment, intent), performance status, tumor demographics (anatomical site, TNM staging), and oral health parameters (DMFT, periodontal health, teeth with/without root canal treatment and with/without periodontitis apicalis) were obtained. Oral health parameters were compared between different anatomical sites. Survival of all HNSCC patients and of individual subsets was assessed using Kaplan-Meier statistics, and the effect of tumor demographics, patient-related parameters, and oral health on survival was analysed by cox regression analyses (α = 5%). 371 patients with HNSCC (oral: n = 86, oropharyngeal: n = 174, hypopharyngeal: n = 59, laryngeal: n = 15, other: n = 37) were included. Oral health parameters did not differ between subsets (padj.≥0.199). Five-year cumulative survival of HNSCC patients amounted to 78.6%. Only for HNSCC originating in the oral cavity and oropharynx, survival was associated with the treatment intent (p = 0.015) or performance status (p = 0.007) in the multivariable analyses, respectively. Within the limitations of this study, oral health was not different between different subsets and had no significant effect on survival of HNSCC patients.

PMID:37883511 | DOI:10.1371/journal.pone.0293665

PLoS One. 2023 Oct 26;18(10):e0293003. doi: 10.1371/journal.pone.0293003. eCollection 2023.

ABSTRACT

Individuals usually develop a sense of place through lived experiences or travel. Here we introduce new and innovative tools to measure sense of place for remote, far-away locations, such as Greenland. We apply this methodology within place-based education to study whether we can distinguish a sense of place between those who have visited Greenland or are otherwise strongly connected to the place from those who never visited. Place-based education research indicates that an increased sense of place has a positive effect on learning outcomes. Thus, we hypothesize that vicarious experiences with a place result in a measurably stronger sense of place when compared to the sense of place of those who have not experienced the place directly. We studied two distinct groups; the first are people with a strong Greenland connection (experts, n = 93). The second are students who have never been there (novices, n = 142). Using i) emotional value attribution of words, ii) thematic analysis of phrases and iii) categorization of words, we show significant differences between novice’s and expert’s use of words and phrases to describe Greenland as a proxy of sense of place. Emotional value of words revealed statistically significant differences between experts and novices such as word power (dominance), feeling pleasantness (valence), and degree of arousal evoked by the word. While both groups have an overall positive impression of Greenland, 31% of novices express a neutral view with little to no awareness of Greenland (experts 4% neutral). We found differences between experts and novices along dimensions such as natural features; cultural attributes; people of Greenland; concerns, importance, or interest in and feeling connected to Greenland. Experts exhibit more complex place attributes, frequently using emotional words, while novices present a superficial picture of Greenland. Engaging with virtual environments may shift novice learners to a more expert-like sense of place, for a far-away places like Greenland, thus, we suggest virtual field trips can supplement geoscience teaching of concepts in far-away places like Greenland and beyond.

PMID:37883501 | DOI:10.1371/journal.pone.0293003

PLoS One. 2023 Oct 26;18(10):e0293474. doi: 10.1371/journal.pone.0293474. eCollection 2023.

ABSTRACT

In the context of the rapid development of the global digital economy, it is of great significance to explore the greening transformation of the manufacturing industry from the micro-perspective of enterprise digital development. This paper empirically examines the impact and mechanism of enterprise digital development on the greening transformation of the manufacturing industry using the 2010-2020 data of Chinese A-share listed companies in the manufacturing industry as a sample. The study shows that enterprise digital development can significantly promote the greening transformation of China’s manufacturing industry, and this conclusion still holds after a series of robustness tests. Technological innovation and financing constraints are important mediating mechanisms. Further research found that the impact of enterprise digital development on the greening transformation of China’s manufacturing industry has a positive nonlinear effect, and its marginal effect shows a weakening trend. Heterogeneity analysis shows that, from the perspective of micro characteristics, digital development is more able to promote the green transformation of state-owned and large enterprises. From a macro-regional perspective, digital development can better promote the green transformation of the manufacturing industry in eastern cities, key city clusters, and high-level cities. The findings of this paper can provide corresponding insights for “revitalizing the manufacturing industry”, and also provide decision-making references for countries aiming to make the manufacturing industry bigger and stronger.

PMID:37883494 | DOI:10.1371/journal.pone.0293474

J Glob Health. 2023 Oct 27;13:06050. doi: 10.7189/jogh.13.06050.

ABSTRACT

BACKGROUND: During health emergencies, leading healthcare organisations, such as the World Health Organization (WHO), the European Centre for Disease Control and Prevention (ECDC), and the United States Centers for Disease Control and Prevention (CDC), provide guidance for public health response. Previous studies have evaluated clinical practice guidelines (CPGs) produced in response to epidemics or pandemics, yet few have focused on public health guidelines and recommendations. To address this gap, we assessed health systems guidance (HSG) produced by the WHO, the ECDC, and the CDC for the 2009 H1N1 and COVID-19 pandemics.

METHODS: We extracted HSG for the H1N1 and COVID-19 pandemics from the organisations’ dedicated repositories and websites. After screening the retrieved documents for eligibility, five assessors evaluated them using the Appraisal of Guidelines Research & Evaluation – Health Systems (AGREE-HS) tool to assess the completeness and transparency of reporting according to the five AGREE-HS domains: “Topic”, “Participants”, “Methods”, “Recommendations”, and “Implementability”.

RESULTS: Following the screening process, we included 108 HSG in the analysis. We observed statistically significant differences between the H1N1 and COVID-19 pandemics, with HSG issued during COVID-19 receiving higher AGREE-HS scores. The HSG produced by the CDC had significantly lower overall scores and single-domain scores compared to the WHO and ECDC. However, all HSG scored relatively low, under the median of 40 total points (range = 10-70), indicating incomplete reporting. The HSG produced by all three organisations received a median score <4 (range = 1-7) for the “Participants”, “Methods”, and “Implementability” domains.

CONCLUSIONS: There is still significant progress to be made in the quality and completeness of reporting in HSG issued during pandemics, especially regarding methodological approaches and the composition of the guidance development team. Due to their significant impact and importance for healthcare systems globally, HSG issued during future healthcare crises should adhere to best reporting practices to increase uptake by stakeholders and ensure public trust in healthcare organisations.

PMID:37883198 | DOI:10.7189/jogh.13.06050

J Med Internet Res. 2023 Oct 26;25:e44417. doi: 10.2196/44417.

ABSTRACT

BACKGROUND: Machine learning (ML) methods have shown great potential in predicting colorectal cancer (CRC) survival. However, the ML models introduced thus far have mainly focused on binary outcomes and have not considered the time-to-event nature of this type of modeling.

OBJECTIVE: This study aims to evaluate the performance of ML approaches for modeling time-to-event survival data and develop transparent models for predicting CRC-specific survival.

METHODS: The data set used in this retrospective cohort study contains information on patients who were newly diagnosed with CRC between December 28, 2012, and December 27, 2019, at West China Hospital, Sichuan University. We assessed the performance of 6 representative ML models, including random survival forest (RSF), gradient boosting machine (GBM), DeepSurv, DeepHit, neural net-extended time-dependent Cox (or Cox-Time), and neural multitask logistic regression (N-MTLR) in predicting CRC-specific survival. Multiple imputation by chained equations method was applied to handle missing values in variables. Multivariable analysis and clinical experience were used to select significant features associated with CRC survival. Model performance was evaluated in stratified 5-fold cross-validation repeated 5 times by using the time-dependent concordance index, integrated Brier score, calibration curves, and decision curves. The SHapley Additive exPlanations method was applied to calculate feature importance.

RESULTS: A total of 2157 patients with CRC were included in this study. Among the 6 time-to-event ML models, the DeepHit model exhibited the best discriminative ability (time-dependent concordance index 0.789, 95% CI 0.779-0.799) and the RSF model produced better-calibrated survival estimates (integrated Brier score 0.096, 95% CI 0.094-0.099), but these are not statistically significant. Additionally, the RSF, GBM, DeepSurv, Cox-Time, and N-MTLR models have comparable predictive accuracy to the Cox Proportional Hazards model in terms of discrimination and calibration. The calibration curves showed that all the ML models exhibited good 5-year survival calibration. The decision curves for CRC-specific survival at 5 years showed that all the ML models, especially RSF, had higher net benefits than default strategies of treating all or no patients at a range of clinically reasonable risk thresholds. The SHapley Additive exPlanations method revealed that R0 resection, tumor-node-metastasis staging, and the number of positive lymph nodes were important factors for 5-year CRC-specific survival.

CONCLUSIONS: This study showed the potential of applying time-to-event ML predictive algorithms to help predict CRC-specific survival. The RSF, GBM, Cox-Time, and N-MTLR algorithms could provide nonparametric alternatives to the Cox Proportional Hazards model in estimating the survival probability of patients with CRC. The transparent time-to-event ML models help clinicians to more accurately predict the survival rate for these patients and improve patient outcomes by enabling personalized treatment plans that are informed by explainable ML models.

PMID:37883174 | DOI:10.2196/44417

Elife. 2023 Oct 26;12:e82823. doi: 10.7554/eLife.82823.

ABSTRACT

During perceptual decision-making tasks, centroparietal electroencephalographic (EEG) potentials report an evidence accumulation-to-bound process that is time locked to trial onset. However, decisions in real-world environments are rarely confined to discrete trials; they instead unfold continuously, with accumulation of time-varying evidence being recency-weighted towards its immediate past. The neural mechanisms supporting recency-weighted continuous decision-making remain unclear. Here, we use a novel continuous task design to study how the centroparietal positivity (CPP) adapts to different environments that place different constraints on evidence accumulation. We show that adaptations in evidence weighting to these different environments are reflected in changes in the CPP. The CPP becomes more sensitive to fluctuations in sensory evidence when large shifts in evidence are less frequent, and the potential is primarily sensitive to fluctuations in decision-relevant (not decision-irrelevant) sensory input. A complementary triphasic component over occipito-parietal cortex encodes the sum of recently accumulated sensory evidence, and its magnitude covaries with parameters describing how different individuals integrate sensory evidence over time. A computational model based on leaky evidence accumulation suggests that these findings can be accounted for by a shift in decision threshold between different environments, which is also reflected in the magnitude of pre-decision EEG activity. Our findings reveal how adaptations in EEG responses reflect flexibility in evidence accumulation to the statistics of dynamic sensory environments.

PMID:37883173 | DOI:10.7554/eLife.82823