Specific Time Points Research Articles

Patient-reported outcomes in N1 breast cancer: A phase III trial comparing whole-breast to whole-breast plus regional irradiation after taxane-based chemotherapy (KROG 1701).

577 Background: Recent randomized trials have highlighted the benefits of regional node irradiation (RNI) in high-risk node-positive or pN1 breast cancer, yet its impact in the context of modern taxane-based adjuvant chemotherapy remains unclear. In this multi-center phase III trial, we study to prove the hypothesis that there is no difference in terms of disease-free survival between standard whole-breast irradiation (WBI) with RNI and WBI alone in pN1 breast cancer patients receiving taxane-based adjuvant chemotherapy. Comprehensive patient-reported outcomes (PROs) collected at multiple time points are now reported. Methods: The KROG 17-01 trial (NCT03269981), a prospective, multicenter, non-inferiority study, randomized patients with pN1 breast cancer after breast-conserving surgery and adjuvant taxane-containing chemotherapy to WBI or WBI+RNI. Both conventional and hypofractionated radiotherapy (RT) were allowed. PROs were assessed using the EORTC QLQ-C30 and QLQ-BR23 modules. All data were collected at baseline, during RT, and at follow-up intervals of 3-6 months, 1, 2, 3, 4, and 5 years post-treatment. Linear mixed models were used to compare PROs between treatment arms. Results: From April 2017 to December 2021, 840 patients were enrolled; 777 received intervention as assigned, and 750 completed baseline PRO questionnaires (387 in WBI+RNI, 363 in WBI). Overall, PRO domains improved over time (p<0.001). During RT, the WBI+RNI group experienced more fatigue, nausea, and vomiting (p<0.05), and reported lower global health (p=0.090) and physical functioning (p=0.049) with borderline significance compared to the WBI group. At 3-6 months post-RT, WBI+RNI group also showed higher arm symptom scores (p=0.030). Apart from these specific timepoints, no significant differences were observed in other PRO domain scores, including arm and breast symptoms, between treatment arms. In addition, there was no significant differences in PRO domains according to RT techniques and fractionation, except for breast symptoms during RT, favoring hypofractionation and intensity-modulated RT. Conclusions: In patients with pN1 breast cancer treated with taxane-based adjuvant chemotherapy, adding RNI was associated with minor, transient declines in specific PRO domains. However, these differences were not clinically significant, indicating comparable overall patient experiences between the two treatment arms. Clinical trial information: NCT03269981 .

When to stop immunotherapy for advanced melanoma: Emulation of target trials.

9521 Background: Immune checkpoint inhibitors (ICI) have demonstrated their effectiveness with a 7.5-year overall survival (OS) close to 50% for advanced stages. The design of clinical trials allowed treatment until progression or toxicity, or for a maximum duration of two years. Prolonged follow-up of responders after cessation shows sustained response and a low risk of relapse in the months following cessation. As of yet, the optimal duration of anti-PD-1 therapy for metastatic melanoma remains unestablished. The objective of this work was to evaluate the optimal duration of ICI. Methods: We conducted emulated trials using the cloning, weighting and censoring approach. Each emulated trial aimed at comparing the causal effect of stopping versus continuing ICI at a specific timepoint, in patients still under treatment and with disease control at that time. Results: The study comprised 1017 participants to the MELBASE cohort. Results of the 6-month discontinuation emulated trial showed a significantly lower OS if treatment was discontinued, compared to continuing treatment for at least three months. The 48-month survival difference was 37.8% (95% confidence interval [CI] 19.8 to 60.5), and the corresponding restricted mean survival time difference 8.3 months (95% CI: 4.1 to 12.7). The 12-month and 18-month discontinuation emulated trials both showed no evidence of benefit of either discontinuing or continuing ICI at any of those timepoints. The 24-month discontinuation emulated trial results were more in favor of stopping compared to continuing treatment at that decision point, with an absolute 48-month survival 10.5% higher (95% CI 4.4 to 18.1). Conclusions: These results suggest that a one-year course of immunotherapy is both necessary and sufficient for patients with advanced melanoma. Prolonged treatment beyond 2 years does not appear to be beneficial in terms of survival and could even be detrimental.[Table: see text]

CD19 expression in diffuse large B-cell lymphoma (DLBCL) patient biopsies after treatment with tafasitamab.

e19050 Background: Tafasitamab (tafa) is a CD19-targeting immunotherapy that induces enhanced antibody dependent cellular cytotoxicity and phagocytosis. Tafa received accelerated FDA approval in 2020 for treating relapsed or refractory DLBCL in combination with lenalidomide in patients ineligible for autologous stem cell transplant, based on results from L-MIND, a multicenter, open-label, single-arm, phase 2 trial. FirmMIND (NCT05429268) is an ongoing identical study, further evaluating efficacy and safety of tafa in this setting. Several other CD19 targeting agents are available; however, CD19 antigen loss following treatment with chimeric antigen receptor T-cell therapy targeting CD19 (CART19) has raised concerns over CD19-targeted therapy sequencing. Loss of CD19 has not been observed to date in tafa clinical trials or practice. Methods: To evaluate CD19 expression at screening and after disease progression in firmMIND, we developed an immunohistochemistry (IHC) assay using a mAb that binds to an intracellular epitope of CD19 clone LE-CD19. To validate that CD19 expression is detectable after tafa treatment, we treated cultured SU-DHL-4 or Jurkat cells with tafa at a saturating concentration for 24 hours. After washing out unbound tafa, cells were harvested at specific timepoints. Resulting cell line blocks were assessed for CD19 expression by IHC. We also monitored CD19 trafficking in response to fluorescently labeled tafa by confocal microscopy. Results: By IHC, CD19 expression was comparable between treatment conditions, suggesting the assay can effectively measure CD19 expression in lymphoma biopsy samples post-tafa. Confocal microscopy showed a fraction of tafa-bound CD19 internalized and colocalized with a CD19 intracellular pool labeled with anti-CD19 mAb clone EPR5906; this mAb also detected CD19 that remained localized on the cell surface. The data demonstrated that CD19 persists on tumor cells after tafa treatment at levels that could be bound by other CD19-targeting therapies. As of the January 25, 2024 data cutoff, we received 6 end-of-treatment (EOT) samples from patients in firmMIND. Biopsies were collected 14-26 days after the last tafa dose; 5 of 6 samples were biopsies from lymph nodes or liver and showed ≥80% of tumor cells staining CD19+ on membranes with 3+ intensity by IHC, except 1 that was collected only 6 days after last dose and showed 50% positivity. The sixth biopsy (extranodal subcutaneous lesion) showed no CD19 expression at baseline or EOT. Conclusions: Patient biopsy analysis and preclinical data suggest that following tafa treatment, CD19 antigen is preserved on the surface of tumor cells after short and transient internalization and could be targeted by other CD19 agents, such as CART therapy. This conclusion is supported by sequential treatment with tafa followed by CART in vivo (Sakemura, 2024). Analyses are ongoing to confirm these findings.

Cathepsin K deficiency prevented stress-related thrombosis in a mouse FeCl3 model

BackgroundExposure to chronic psychological stress (CPS) is a risk factor for thrombotic cardiocerebrovascular diseases (CCVDs). The expression and activity of the cysteine cathepsin K (CTSK) are upregulated in stressed cardiovascular tissues, and we investigated whether CTSK is involved in chronic stress-related thrombosis, focusing on stress serum-induced endothelial apoptosis.Methods and resultsEight-week-old wild-type male mice (CTSK+/+) randomly divided to non-stress and 3-week restraint stress groups received a left carotid artery iron chloride3 (FeCl3)-induced thrombosis injury for biological and morphological evaluations at specific timepoints. On day 21 post-stress/injury, the stress had enhanced the arterial thrombi weights and lengths, in addition to harmful alterations of plasma ADAMTS13, von Willebrand factor, and plasminogen activation inhibitor-1, plus injured-artery endothelial loss and CTSK protein/mRNA expression. The stressed CTSK+/+ mice had increased levels of injured arterial cleaved Notch1, Hes1, cleaved caspase8, matrix metalloproteinase-9/-2, angiotensin type 1 receptor, galactin3, p16IN4A, p22phox, gp91phox, intracellular adhesion molecule-1, TNF-α, MCP-1, and TLR-4 proteins and/or genes. Pharmacological and genetic inhibitions of CTSK ameliorated the stress-induced thrombus formation and the observed molecular and morphological changes. In cultured HUVECs, CTSK overexpression and silencing respectively increased and mitigated stressed-serum- and H2O2-induced apoptosis associated with apoptosis-related protein changes. Recombinant human CTSK degraded γ-secretase substrate in a dose-dependent manor and activated Notch1 and Hes1 expression upregulation.ConclusionsCTSK appeared to contribute to stress-related thrombosis in mice subjected to FeCl3 stress, possibly via the modulation of vascular inflammation, oxidative production and apoptosis, suggesting that CTSK could be an effective therapeutic target for CPS-related thrombotic events in patients with CCVDs.

Institutionalizing suspicion: Tracing the decline of the Swedish sickness insurance system in the 2000’s

This article presents an analysis of Swedish sickness insurance in the 2000’s, outlining cultural and structural shifts in political and institutional design. The study is based on analytic dualism and Margaret S. Archer’s morphogenetic model, which is used to create an analytical narrative focusing on political and institutional developments. The narrative identifies two distinct phases: one period of rapid cultural and structural change (morphogenesis), and one of institutionalization of the new structure (morphostasis). The narrative describes how a key element of the Swedish welfare state, sickness insurance, underwent a transition from an encompassing and generous to a strict and suspicious system, and how this was effectively solidified politically and organizationally. This is related both to a broader shift toward neoliberal and workfare policies, and to the specific socio-cultural and social interactions between agents to reform the system. The analysis provides a contribution to the literature by providing an internationally relevant empirical case of how an encompassing system has undergone a period of substantial decline, and by presenting a coherent long-term narrative which temporalizes this development into specific timepoints and phases.

One Territory, Two Worlds

This paper analyzes Kazuo Ishiguro’s When We Were Orphans is a literary work that critiques and examines colonial structures and their consequences: Ishiguro criticizes the colonization of Shanghai by showing the inherent power imbalance between the native population and the colonizers, the chaos and lawlessness outside of the Settlement as opposed to within, and the general understanding of Shanghai and the Settlement held by characters from Britain. As a work of historical fiction, the novel serves to explore a particular society at a particular point in time, and therefore, must be analyzed with close consideration to the historical period and context in which the novel is set. At the same time, this paper concludes, Ishiguro’s observations and critiques are highly relevant in today’s society.

Spatiotemporal Analysis of Particle Spread to Assess the Hybrid Particle-Flow CFD Model of Radioembolization of HCC Tumors.

Computational fluid dynamics (CFD) models can potentially aid in pre-operative planning of transarterial radioactive microparticle injections to treat hepatocellular carcinoma, but these models are computationally very costly. Previously, we introduced the hybrid particle-flow model as a surrogate, less costly modelling approach for the full particle distribution in truncated hepatic arterial trees. We hypothesized that higher cross-sectional particle spread could increase the match between flow and particle distribution. Here, we investigate whether truncation is still reliable for selective injection scenarios, and if spread is an important factor to consider for reliable truncation. Moderate and severe up- and downstream truncation for selective injection served as input for the hybrid model to compare downstream particle distributions with non-truncated models. In each simulation, particle cross-sectional spread was quantified for 5-6 planes. Severe truncation gave maximum differences in particle distribution of ∼4-11% and ∼8-9% for down- and upstream truncation, respectively. For moderate truncation, these differences were only ∼1-1.5% and ∼0.5-2%. Considering all particles, spread increased downstream of the tip to 80-90%. However, spread was found to be much lower at specific timepoints, indicating high time-dependency. Combining domain truncation with hybrid particle-flow modelling is an effective method to reduce computational complexity, but moderate truncation is more reliable than severe truncation. Time-dependent spread measures show where differences might arise between flow and particle modelling. The hybrid particle-flow model cuts down computational time significantly by reducing the physical domain, paving the way towards future clinical applications.

Comparison of the potential toxicity induced by microplastics made of polyethylene terephthalate (PET) and polylactic acid (PLA) on the earthworm Eiseniafoetida

A growing number of studies have demonstrated that microplastic (MP) contamination is widespread in terrestrial ecosystems. A wide array of MPs made of conventional, fossil-based polymers differing in size and shape has been detected in soils worldwide. Recently, also MPs made of bioplastics have been found in soils, but there is a dearth of information concerning their toxicity on soil organisms. This study aimed at exploring the potential toxicity induced by the exposure for 28 days to irregular shaped and differently sized MPs made of a fossil-based (polyethylene terephthalate – PET) and a bioplastic (polylactic acid – PLA) polymer on the earthworm Eisenia foetida. Two amounts (1 g and 10 g/kg of soil, corresponding to 0.1% and 1% of soil weight) of both MP types were administered to the earthworms. A multi-level approach was used to investigate the MP-induced effects at sub-individual and individual level. Changes in the activity of antioxidant and detoxifying enzymes, as well as in lipid peroxidation levels, were investigated at specific time-points (i.e., 7, 14, 21 and 28 days) as sub-individual responses. Histological analyses were performed to assess effects at tissue level, while the change in digging activity was considered as a proxy of behavioral effects. Earthworms ingested MPs made of both the polymers. MPs made of PET did not induce any adverse effect at none of the biological levels. In contrast, MPs made of PLA caused the modulation of earthworms’ oxidative status as showed by a bell-shaped activity of superoxide dismutase coupled with an increase in glutathione peroxidase activity. However, neither oxidative and tissue damage, nor behavioral alteration occurred. These findings suggest that the exposure to bio-based MPs can cause higher toxicity compared to fossil-based MPs.

Evolving Knowledge Graph Representation Learning with Multiple Attention Strategies for Citation Recommendation System

The growing number of publications in the field of artificial intelligence highlights the need for researchers to enhance their efficiency in searching for relevant articles. Most paper recommendation models either rely on simplistic citation relationships among papers or focus on content-based approaches, both of which overlook interactions within academic networks. To address the aforementioned problem, knowledge graph embedding (KGE) methods have been used for citation recommendations because recent research proves that graph representations can effectively improve recommendation model accuracy. However, academic networks are dynamic, leading to changes in the representations of users and items over time. The majority of KGE-based citation recommendations are primarily designed for static graphs, thus failing to capture the evolution of dynamic knowledge graph (DKG) structures. To address these challenges, we introduced the evolving knowledge graph embedding (EKGE) method. In this methodology, evolving knowledge graphs are input into time-series models to learn the patterns of structural evolution. The model has the capability to generate embeddings for each entity at various time points, thereby overcoming limitation of static models that require retraining to acquire embeddings at each specific time point. To enhance the efficiency of feature extraction, we employed a multiple attention strategy. This helped the model find recommendation lists that are closely related to a user’s needs, leading to improved recommendation accuracy. Various experiments conducted on a citation recommendation dataset revealed that the EKGE model exhibits a 1.13% increase in prediction accuracy compared to other KGE methods. Moreover, the model’s accuracy can be further increased by an additional 0.84% through the incorporation of an attention mechanism.

Memory reactivation in slow wave sleep enhances relational learning in humans

Sleep boosts the integration of memories, and can thus facilitate relational learning. This benefit may be due to memory reactivation during non-REM sleep. We set out to test this by explicitly cueing reactivation using a technique called targeted memory reactivation (TMR), in which sounds are paired with learned material in wake and then softly played during subsequent sleep, triggering reactivation of the associated memories. We specifically tested whether TMR in slow wave sleep leads to enhancements in inferential thinking in a transitive inference task. Because the Up-phase of the slow oscillation is more responsive to cues than the Down-phase, we also asked whether Up-phase stimulation is more beneficial for such integration. Our data show that TMR during the Up-Phase boosts the ability to make inferences, but only for the most distant inferential leaps. Up-phase stimulation was also associated with detectable memory reinstatement, whereas Down-phase stimulation led to below-chance performance the next morning. Detection of memory reinstatement after Up-state stimulation was negatively correlated with performance on the most difficult inferences the next morning. These findings demonstrate that cueing memory reactivation at specific time points in sleep can benefit difficult relational learning problems.

Together forever? How customer co‐creation affects the adoption of digital service innovations over time

AbstractThis study delves into the intricate relationship between customers' willingness to co‐create (WCC) and the required level of co‐creation (LCC) for effective service innovation adoption. In response to recent findings suggesting a “co‐creation sweet spot,” beyond which additional co‐creation activities have detrimental effects, this research aims to provide both theoretical and empirical insights into this phenomenon. Unlike previous investigations focusing on either the willingness to co‐create or the level of co‐creation at a particular point in time and overlooking potential interactions, our study considers their interactions over time, acknowledging that revenue for most digital services is generated through ongoing customer usage. Utilizing longitudinal data from 352 participants across four waves and employing structural equation modeling, our analysis reveals a nuanced pattern. Customers' willingness to co‐create predominantly shapes usage intention in the pre‐adoption stage, while the level of co‐creation becomes a critical driver for continuous usage in the post‐adoption stages. Further analysis using response surface analysis with polynomial regression confirms a specific matching logic: customers with low (high) willingness to co‐create expect a low (high) level of co‐creation from a service innovation. From a theoretical perspective, our findings contribute to bridging the research gap concerning an optimal co‐creation level, offering insights into psychological processes underlying the co‐creation sweet spot. Furthermore, we also shed light on temporal aspects of the interplay between willingness to co‐create and the level of co‐creation, offering a more holistic perspective on their joint influence on adoption behavior. From a managerial perspective, our study challenges the traditional assumption that more co‐creation naturally leads to better outcomes. It emphasizes the significance of tailoring the level of co‐creation in digital service innovations based on customers' intrinsic willingness. This strategic customization aligns with the evolving landscape of digital service innovation, offering practical insights for managers striving to optimize their co‐creation strategies.

Detection of nitric oxide-mediated metabolic effects using real-time extracellular flux analysis.

Dendritic cell (DC) activation is marked by key events including: (I) rapid induction and shifting of metabolism favoring glycolysis for generation of biosynthetic metabolic intermediates and (II) large scale changes in gene expression including the upregulation of the antimicrobial enzyme inducible nitric oxide synthase (iNOS) which produces the toxic gas nitric oxide (NO). Historically, acute metabolic reprogramming and NO-mediated effects on cellular metabolism have been studied at specific timepoints during the DC activation process, namely at times before and after NO production. However, no formal method of real time detection of NO-mediated effects on DC metabolism have been fully described. Here, using Real-Time Extracellular Flux Analysis, we experimentally establish the phenomenon of an NO-dependent mitochondrial respiration threshold, which shows how titration of an activating stimulus is inextricably linked to suppression of mitochondrial respiration in an NO-dependent manner. As part of this work, we explore the efficacy of two different iNOS inhibitors in blocking the iNOS reaction kinetically in real time and explore/discuss parameters and considerations for application using Real Time Extracellular Flux Analysis technology. In addition, we show, the temporal relationship between acute metabolic reprogramming and NO-mediated sustained metabolic reprogramming kinetically in single real-time assay. These findings provide a method for detection of NO-mediated metabolic effects in DCs and offer novel insight into the timing of the DC activation process with its associated key metabolic events, revealing a better understanding of the nuances of immune cell biology.

A propensity score-integrated approach for leveraging external data in a randomized controlled trial with time-to-event endpoints.

In a randomized controlled trial with time-to-event endpoint, some commonly used statistical tests to test for various aspects of survival differences, such as survival probability at a fixed time point, survival function up to a specific time point, and restricted mean survival time, may not be directly applicable when external data are leveraged to augment an arm (or both arms) of an RCT. In this paper, we propose a propensity score-integrated approach to extend such tests when external data are leveraged. Simulation studies are conducted to evaluate the operating characteristics of three propensity score-integrated statistical tests, and an illustrative example is given to demonstrate how these proposed procedures can be implemented.

Dynamics of IGF signalling during the ovulatory peak in women undergoing ovarian stimulation.

IGF signalling is known to affect human ovarian follicular function during growth and development. However, the role of the IGF system is unknown during the ovulatory peak, which is characterized by profound changes in granulosa cell (GCs) mitosis and function. How is the IGF system expressed and regulated during the midcycle surge in women? Follicular fluid (FF) and granulosa cells (GCs) were collected during the ovulatory peak from two specific time-points. One sample was obtained before oocyte pick up (OPU): before ovulation trigger (OT) (T = 0 h) or at 12, 17, or 32 h after OT, and one sample was obtained at OPU 36 h after OT. University hospital. Fifty women undergoing ovarian stimulation were included. Gene expression profiles were assessed by microarray analysis of GCs. IGF-related proteins in the FF were assessed by using immunoassays or by determination of activity with a proteinase assay. Expression of proteins promoting IGF activity (i.e., IGF2, PAPPA, and IRS1) together with proliferation markers were downregulated on a transcriptional level in GCs after OT, whereas proteins inhibiting the IGF signal (i.e., IGFBPs, IGF2R, and STC1) were upregulated. STC1 gene expression and protein levels were greatly upregulated after OT with a parallel steep downregulation of PAPP-A proteolytic activity. These data suggest that downregulation of IGF signalling mediated by increased STC1 expression is instrumental for the sudden cessation in GC proliferation and onset of differentiation during the ovulatory peak.

An Intelligent Early Warning System for Harmful Algal Blooms: Harnessing the Power of Big Data and Deep Learning.

Harmful algal blooms (HABs) pose a significant ecological threat and economic detriment to freshwater environments. In order to develop an intelligent early warning system for HABs, big data and deep learning models were harnessed in this study. Data collection was achieved utilizing the vertical aquatic monitoring system (VAMS). Subsequently, the analysis and stratification of the vertical aquatic layer were conducted employing the "DeepDPM-Spectral Clustering" method. This approach drastically reduced the number of predictive models and enhanced the adaptability of the system. The Bloomformer-2 model was developed to conduct both single-step and multistep predictions of Chl-a, integrating the " Alert Level Framework" issued by the World Health Organization to accomplish early warning for HABs. The case study conducted in Taihu Lake revealed that during the winter of 2018, the water column could be partitioned into four clusters (Groups W1-W4), while in the summer of 2019, the water column could be partitioned into five clusters (Groups S1-S5). Moreover, in a subsequent predictive task, Bloomformer-2 exhibited superiority in performance across all clusters for both the winter of 2018 and the summer of 2019 (MAE: 0.175-0.394, MSE: 0.042-0.305, and MAPE: 0.228-2.279 for single-step prediction; MAE: 0.184-0.505, MSE: 0.101-0.378, and MAPE: 0.243-4.011 for multistep prediction). The prediction for the 3 days indicated that Group W1 was in a Level I alert state at all times. Conversely, Group S1 was mainly under an Level I alert, with seven specific time points escalating to a Level II alert. Furthermore, the end-to-end architecture of this system, coupled with the automation of its various processes, minimized human intervention, endowing it with intelligent characteristics. This research highlights the transformative potential of integrating big data and artificial intelligence in environmental management and emphasizes the importance of model interpretability in machine learning applications.

Incidence and factors associated with dysphagia in intensive care unit patients 24 h after extubation.

Post-extubation dysphagia deserves attention because it places patients at risk following extubation, especially critically ill patients in intensive care unit. However, there are limited studies of post-extubation dysphagia in the early stages after extubation. To investigate the incidence and factors associated with post-extubation dysphagia among patients in intensive care unit within 24 h of extubation. A prospective descriptive study was carried out with 173 adult patients in intensive care unit with tracheal extubation at a tertiary hospital in Guangzhou, China. The Gugging Swallowing Screen was used to evaluate the swallowing function of patients 1, 4 and 24 h after extubation. Demographic and clinical data were retrieved from medical records. The incidence of post-extubation dysphagia in patients within 1, 4 and 24 h after extubation was 86.71% (n = 150), 63.01% (n = 109) and 43.35% (n = 75), respectively. The risk factors included older age (OR = 1.057, 95%CI [1.039, 1.072], p < .001), cardiovascular disease (OR = 0.098, 95%CI [0.082, 0.127], p = .012), thyroid dysfunction (OR = 5.042, 95%CI [1.527, 13.684], p < .001), non-post-operative admission (OR = 3.186, 95%CI [1.142, 14.422], p = .036), mechanical ventilation duration >48 h (OR = 3.558, 95%CI [1.217, 10.385], p = .020), intubation duration >24 h (OR = 0.533, 95%CI [0.278, 0.898], p = .048) and intubation model size ≤7 (OR = 0.327, 95%CI [0.158, 0.788], p < .01). This study revealed a high incidence of post-extubation dysphagia in critical patients in the 24 h after extubation, with the incidence decreasing over time. Screening of early post-extubation dysphagia after extubation is needed, but the specific evaluation time point requires further investigation. Patients with older age, cerebrovascular disease, thyroid dysfunction, post-operative admission, longer mechanical ventilation time, thicker intubation models and longer intubation time have a higher risk of the occurrence of post-extubation dysphagia. The incidence of post-extubation dysphagia is very high in the early stage. Within 24 h after extubation, the patient's swallowing function should be actively evaluated, and the occurrence of aspiration should be vigilant. Patients with older age, cerebrovascular disease, thyroid dysfunction, post-operative admission, longer mechanical ventilation time, thicker intubation models and longer intubation time should receive more attention.

함수형 시공간 기법을 활용한 지표면 온도의 변화점 분석

Weather stations collect various meteorological variables such as temperature, precipitation, and humidity. These variables have been measured at the regular and repetitive time points at the specific location in the year. However, ideally, the characteristic of the climate data is that these variables exist in the form of a continuous function regardless of the time points observed. This characteristic is considered to be close to the functional data perspective, which assumes that data are observed in the form of function values at discrete points from a random function that exists as a continuous function in an infinite-dimensional space, and they require statistical techniques that are different from existing approaches. In this study, we aim to analyze land surface temperature data to determine that there is a change point in the spatial average for almost domestic observatories, assuming that they measured over a total of 42 years from 1981 to 2022 at 48 sites is functional data. Specifically, after estimating the spatial and temporal covariances, the weight for integrating spatial information was extracted from the spatial covariance structure, and the eigenfunctions and eigenvalues for integrating temporal information were extracted from the temporal covariance structure. Based on this, we introduce a method of expressing statistics as a partial sum of the mean difference before and after a specific point in time, as well as an approximate distribution.

Sample size determination for time-to-event endpoints in randomized selection trials with generalized exponential distribution

Randomized selection trials are frequently used to compare experimental treatments that have the potential to be beneficial, but they often do not include a control group. While time-to-event endpoints are commonly applied in clinical investigations, methodologies for determining the required sample size for such endpoints, except exponential distribution, are lacking. In recent times, there has been a shift in clinical trials, with a growing emphasis on progression-free survival as a primary endpoint. However, the utilization of this measure has typically been restricted to specific time points for both sample size determination and analysis. This alteration in approach could wield a substantial influence on the clinical trial process, potentially diminishing the capacity to discern variances between treatment groups. In the calculation of sample sizes for randomized trials, this investigation operates under the assumption that the time-to-event endpoint conforms to either an exponential, Weibull, or generalized exponential distribution.

Pharmacokinetics of drugs used to treat drug sensitive-tuberculosis in breastfeeding mother-infant pairs: An observational pharmacokinetic study

Background Globally, more than half of women take medicines whilst breastfeeding. Data concerning the exposure of the breastfed infant to drugs and any related risks are sparce. Lactation studies are only rarely performed close to licensing for medicines anticipated to be widely used in women of childbearing age. Medicines taken by breastfeeding mothers on tuberculosis (TB) treatment can be transferred to the breastfed infant. Potential effects of anti-tuberculosis medicines on nursing infants are not well understood. Similarly, women face mental health challenges whilst taking medications, including postpartum depression, hence the need to assess the psychological behavior of a breastfeeding woman. Potential risks are the development of adverse drug effects in the breastfed infant and selection for resistance, whereas potential benefits might include exposure to potentially prophylactic concentrations of the drug. Pharmacokinetic studies are therefore necessary to understand this situation fully. Methods This study will enroll 20 mothers receiving first-line anti-tuberculosis medicines, together with their breastfed infants, with the aim of characterizing the breastmilk transfer of the medicines from the mother to the infants. Samples of maternal blood, breastmilk and breastfeeding infant’s blood will be obtained at specific time points for bioanalysis of drug concentrations. Pharmacokinetic data will be analyzed using a population pharmacokinetic approach. Additionally, the study will assess the psychological status of breastfeeding women and the well-being of their infants. Maternal depression is linked to long-term negative consequences for the infant’s physiological regulation, poor growth-promoting setting for the infants, and inappropriate interactive conduct, characterized by low compassion, constrained range of emotional expression, and varying provision of the infant’s budding engagement. Conclusions This study will provide the first systematic characterization of mother-to-infant transfer of first-line anti-tuberculosis medicines through breast milk. A mathematical pharmacokinetics model characterizing plasma-to-breastmilk transfer of rifampicin, isoniazid, ethambutol, and pyrazinamide will be developed and used to characterize infant exposure through breast milk. Our findings will contribute towards treatment optimization in breastfeeding and provide a framework to foster other lactation pharmacokinetic studies.

Asymmetric dynamic spillover and time-frequency connectedness in the oil-stock nexus under COVID-19 shock: Evidence from African oil importers and exporters

Amid the profound disruptions triggered by COVID-19 in financial markets, this paper investigates changes in the interconnectedness behavior in terms of mean and volatility contagion between crude oil and stock markets in African oil importers and exporters. To this aim, we employ asymmetric BEKK-Copula-GARCH and Wavelet Coherence methods, and the analyses are evaluated before and during COVID-19. The findings indicate that the interdependence between crude oil and African stock returns is relatively weak before COVID-19, but the strength is amplified during the pandemic. Significant volatility spillover from crude oil to stock markets is exhibited in South Africa, Tunisia, and Tanzania during COVID-19. However, the results are insignificant in all the selected African countries before the pandemic. Furthermore, evidence of asymmetric volatility transmission is uncovered in South Africa and Tunisia during COVID-19. The findings also reveal that the connectedness between crude oil and African stocks is time and frequency dependent, with the strong linkage observed in the mid-term and long-term at specific time points. Overall, this study holds vital contributions as it unveils new insights into how COVID-19 reshaped the traditional behavior regarding the oil-stock nexus in Africa, thus informing policy responses and investment strategies at times of extreme events.