bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of prognosis and immunotherapy response in breast cancer based on neutrophil extracellular traps-related classification
Authors: Zhao Jiajing , Xie Xiaojun
Published: May 2023

Neutrophil extracellular traps (NETs), a network of DNA histone complexes and proteins released by activated neutrophils, have been demonstrated to be associated with inflammation, infection related immune response and tumorigenesis in previous reports. However, the relationship between NETs related genes and breast cancer remains controversial. In the study, we retrieved transcriptome data and clinical information of BRCA patients from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) datasets. The expression matrix of neutrophil extracellular traps (NETs) related genes was generated and consensus clustering was performed by Partitioning Around Medoid (PAM) to classify BRCA patients into two subgroups (NETs high group and NETs low group). Subsequently, we focus on the differentially expressed genes (DEGs) between the two NETs-related subgroups and further explored NETs enrichment related signaling pathways by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. In addition, we constructed a risk signature model by LASSO Cox regression analysis to evaluate the association between riskscore and prognosis. Even more, we explored the landscape of the tumor immune microenvironment and the expression of immune checkpoints related genes as well as HLA genes between two NETs subtypes in breast cancer patients. Moreover, we found and validated the correlation of different immune cells with risk score, as well as the response to immunotherapy in different subgroups of patients was detected by Tumor Immune Dysfunction and Exclusion (TIDE) database. Ultimately, a nomogram prognostic prediction model was established to speculate on the prognosis of breast cancer patients. The results suggest that high riskscore is associated with poor immunotherapy response and adverse clinical outcomes in breast cancer patients. In conclusion, we established a NETs-related stratification system that is beneficial for guiding the clinical treatment and predicting prognosis of BRCA.
Accounting for uncertainty in training data to improve machine learning performance in predicting new disease activity in early multiple sclerosis
Authors: Tayyab Maryam , Metz Luanne M. , Li David K.B. , Kolind Shannon , Carruthers Robert , Traboulsee Anthony , Tam Roger C.
Published: May 2023

Introduction

Machine learning (ML) has great potential for using health data to predict clinical outcomes in individual patients. Missing data are a common challenge in training ML algorithms, such as when subjects withdraw from a clinical study, leaving some samples with missing outcome labels. In this study, we have compared three ML models to determine whether accounting for label uncertainty can improve a model’s predictions.

Methods

We used a dataset from a completed phase-III clinical trial that evaluated the efficacy of minocycline for delaying the conversion from clinically isolated syndrome to multiple sclerosis (MS), using the McDonald 2005 diagnostic criteria. There were a total of 142 participants, and at the 2-year follow-up 81 had converted to MS, 29 remained stable, and 32 had uncertain outcomes. In a stratified 7-fold cross-validation, we trained three random forest (RF) ML models using MRI volumetric features and clinical variables to predict the conversion outcome, which represented new disease activity within 2 years of a first clinical demyelinating event. One RF was trained using subjects with the uncertain labels excluded (RFexclude), another RF was trained using the entire dataset but with assumed labels for the uncertain group (RFnaive), and a third, a probabilistic RF (PRF, a type of RF that can model label uncertainty) was trained on the entire dataset, with probabilistic labels assigned to the uncertain group.

Results

Probabilistic random forest outperformed both the RF models with the highest AUC (0.76, compared to 0.69 for RFexclude and 0.71 for RFnaive) and F1-score (86.6% compared to 82.6% for RFexclude and 76.8% for RFnaive).

Conclusion

Machine learning algorithms capable of modeling label uncertainty can improve predictive performance in datasets in which a substantial number of subjects have unknown outcomes.
Acupuncture with twirling reinforcing and reducing manipulation shows a control of hypertension and regulation of blood pressure-related target brain regions in spontaneously hypertensive rat: a preliminary resting-state functional MRI study
Authors: Li Yin-Yin , Liu Ji-Peng , Shi Shu-Feng , Yang Ke-Zhen , Gong Yu , Sun Jiao , Xie Qi , Wu Xiao-Li , Liu Qing-Guo , Xu Meng
Published: May 2023

Aim

To observe the effects of acupuncture manipulations on blood pressure and brain function in spontaneously hypertensive rats and elucidate the anti-hypertensive effect of the manipulations’ central mechanism.

Methods

This study used acupuncture twirling reinforcing, acupuncture twirling reducing, and acupuncture twirling uniform reinforcing-reducing manipulations to act on the bilateral TaiChong point of rats. The depth of acupuncture was 1.5–2 mm, and twisting was performed at a frequency of 60 times/min within ±360° for 3 min, followed by the needle being retained for 17 min. Functional magnetic resonance imaging was performed at the end of the intervention. Regional homogeneity and amplitude of low-frequency fluctuations were used to assess the differences in brain regions in each group of rats, and the core brain region (left hypothalamus) among the differential brain regions was selected as the seed for functional connectivity analysis.

Results

(1) The anti-hypertensive effect was achieved by acupuncture manipulations, and the anti-hypertensive effect of twirling reducing manipulation on spontaneously hypertensive rats was better than that of twirling uniform reinforcing-reducing and twirling reinforcing manipulations. (2) After regional homogeneity and amplitude of low-frequency fluctuations analyses, the hypothalamus, the brain region related to blood pressure, was activated in the twirling uniform reinforcing-reducing manipulation group; the corpus callosum and cerebellum were activated in the twirling reinforcing manipulation group; and the hypothalamus, olfactory bulb, corpus callosum, brainstem, globus pallidum, and striatum were activated in the twirling reducing manipulation group. (3) According to the functional connectivity analysis, different acupuncture manipulations increased the functional connections between seed points and the brainstem, olfactory bulb, and cerebellum, etc.

Conclusion

These results suggest that acupuncture manipulations achieved the hypotensive effect and the twirling reducing manipulation had a better hypotensive effect on spontaneously hypertensive rats than twirling uniform reinforcing-reducing and twirling reinforcing manipulations; the central mechanism of the anti-hypertensive effect of twirling reinforcing and reducing manipulation may be related to the activation of brain regions associated with blood pressure regulation and the functional connections between them. Furthermore, brain regions involved in motor control, cognition, and hearing were also activated. We hypothesize that activation of these brain regions may help prevent or mitigate the onset and progression of hypertensive brain damage.
Muscle-derived stem cell exosomes with overexpressed miR-214 promote the regeneration and repair of rat sciatic nerve after crush injury to activate the JAK2/STAT3 pathway by targeting PTEN
Authors: Zeng Xiangyu , Bian Wei , Liu Ziwen , Li Jianming , Ren Shuai , Zhang Jian , Zhang Haoran , Tegeleqi Bu , He Guanyi , Guan Mingyan , Gao Zewei , Huang Chi , Liu Jianyu
Published: May 2023

Introduction

This study aimed to investigate the effect of muscle-derived stem cell (MDSC) exosomes with overexpressed miR-214 on the regeneration and repair of rat sciatic nerve after crush injury and its molecular mechanism.

Methods

First, primary MDSCs, Schwann cells (SCs) and dorsal root ganglion (DRG) neurons were isolated and cultured, and the characteristics of MDSCs-derived exosomes were identified by molecular biology and immunohistochemistry. NC mimics and miR-214 mimics were transfected to obtain exo-NC and exo-miR-214. An in vitro co-culture system was established to determine the effect of exo-miR-214 on nerve regeneration. The restoration of sciatic nerve function of rats by exo-miR-214 was evaluated by walking track analysis. Immunofluorescence for NF and S100 was used to detect the regeneration of axon and myelin sheath in injured nerve. The Starbase database was used to analyze the downstream target genes of miR-214. QRT-PCR and dual luciferase reporter assays were used to validate the miR-214 and PTEN interaction relationship. And the expression of the JAK2/STAT3 pathway-related proteins in sciatic nerve tissues were detected by western blot.

Results

The above experiments showed that MDSCs-derived exosomes with overexpressed miR-214 was found to promote the proliferation and migration of SCs, increase the expression of neurotrophic factors, promote axon extension of DRG neurons and positively affect the recovery of nerve structure and function. In addition, PTEN was a target gene of miR-214. Exo-miR-214 can significantly inhibit the expression level of PTEN, increase the protein expression levels of p-JAK2 and p-STAT3 and the ratio of p-JAK2/JAK2 and p-STAT3/STAT3, also MDSCs-derived exosomes with overexpressed miR-214 can reduce the occurrence of denervated muscle atrophy.

Conclusion

In summary, the MDSCs-derived exosomes with overexpressed miR-214 is involved in peripheral nerve regeneration and repair in rats after sciatic nerve crush injury to activate the JAK2/ STAT3 pathway by targeting PTEN.
Improvement of functional characteristics of Hypophthalmichthys molitrix protein by modification with chitosan oligosaccharide
Authors: Cong Haihua , Wu Qiming , Zhang Zhuoran , Kan Juntao
Published: May 2023

In the food processing field, it is very often that fish proteins are denatured affecting the nutritional value of the product which is vital to be solved. By using appropriate sugar donors for glycosylation with protein, improving the stability and emulsification properties of fish proteins can be achieved. This research looks into the impacts of enzymatic chitosan oligosaccharide (CO) at various concentration (0.15%, 0.30%, 0.45%, 0.60%, w/v) upon the molecular makeup and function of silver carp myofibrillar protein (MP) in an attempt to comprehend the impact of electrostatic binding among MP as well as CO on protein conformation. Analysis was done on the impact of various CO concentrations upon MP’s secondary structure, conformational changes, and functional characteristics. Twelve sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) assays were implemented to monitor MP; Fourier transform infrared spectroscopy, endogenous fluorescence spectroscopy, and UV absorption spectra were carried out to investigate the influence of CO on MP; Particle size distribution, emulsifying activity index (EAI), solubility, turbidity, sulfhydryl content, carbonyl content, foaming capacity, surface hydrophobicity, emulsifying stability index (ESI), and foam persistence were all investigated. In addition, we used dynamic light scattering, scanning electron microscope, and atomic force microscope to analyze myosin (MO) and 0.60% CO-MO complex. The results demonstrated that CO and MP form complexes through hydrogen bonding and electrostatic interactions. CO modification not only delayed the oxidation of MP but also promoted MP to show better solubility, foaming, and foaming stability. In addition, CO modified myosin particle size decreased, reducing myosin’s roughness and making myosin’s structure more compact. To sum up, molecular interaction could change functional characteristics, and products with special properties could be developed after modification with chitosan oligosaccharide.
Therapeutic potential of multifunctional myricetin for treatment of type 2 diabetes mellitus
Authors: Niisato Naomi , Marunaka Yoshinori
Published: May 2023

Type 2 diabetes mellitus (T2DM) is a metabolic disorder characterized by chronic hyperglycemia, insulin resistance, and insufficient insulin secretion. It is considered that chronic hyperglycemia causes serious problems due to diabetic complications such as retinopathy, nephropathy, and neuropathy. Primarily, treatment in T2DM is pharmacologically tried by using drugs that are insulin sensitizers, insulin secretagogues, α-glucosidase inhibitors, and glucose transporter inhibitors. However, long-term application of these drugs frequently induces various harmful side effects, suggesting that the importance of taking advantage of natural products like phytochemicals. Accordingly, flavonoids, a group of phytochemicals, have attracted attention as components of natural products which are effective in the treatment of several diseases containing T2DM and are strongly recommended as food supplements to ameliorate T2DM-related complications. Several well-studied flavonoids such as quercetin and catechin are known to have anti-diabetic, anti-obesity, and anti-hypertensive actions, although a huge number of flavonoids are still under investigation and their actions are not fully understood. In this situation, myricetin is being shown to be a multiple bioactive compound to prevent and/or suppress hyperglycemia through inhibiting digestion and uptake of saccharides and enhancing insulin secretion as a possible GLP-1 receptor agonist, and to ameliorate T2DM-related complications by protecting endothelial cells from oxidative stress induced by hyperglycemia. In this review, we summarize the multiple effects of myricetin on the targets of T2DM treatment, comparing with different flavonoids.
Development of ensemble learning models for prognosis of hepatocellular carcinoma patients underwent postoperative adjuvant transarterial chemoembolization
Authors: Liang Yuxin , Wang Zirui , Peng Yujiao , Dai Zonglin , Lai Chunyou , Qiu Yuqin , Yao Yutong , Shi Ying , Shang Jin , Huang Xiaolun
Published: May 2023

Background

Postoperative adjuvant transarterial chemoembolization (PA-TACE) has been increasing widely used to improve the prognosis of hepatocellular carcinoma (HCC) patients. However, clinical outcomes vary from patient to patient, which calls for individualized prognostic prediction and early management.

Methods

A total of 274 HCC patients who underwent PA-TACE were enrolled in this study. The prediction performance of five machine learning models was compared and the prognostic variables of postoperative outcomes were identified.

Results

Compared with other machine learning models, the risk prediction model based on ensemble learning strategies, including Boosting, Bagging, and Stacking algorithms, presented better prediction performance for overall mortality and HCC recurrence. Moreover, the results showed that the Stacking algorithm had relatively low time consumption, good discriminative ability, and the best prediction performance. In addition, according to time-dependent ROC analysis, the ensemble learning strategies were found to perform well in predicting both OS and RFS for the patients. Our study also found that BCLC Stage, hsCRP/ALB and frequency of PA-TACE were relatively important variables in both overall mortality and recurrence, while MVI contributed more to the recurrence of the patients.

Conclusion

Among the five machine learning models, the ensemble learning strategies, especially the Stacking algorithm, could better predict the prognosis of HCC patients following PA-TACE. Machine learning models could also help clinicians identify the important prognostic factors that are clinically useful in individualized patient monitoring and management.
All-oral low-dose chemotherapy TEPIP is effective and well-tolerated in patients with peripheral T-cell lymphoma
Authors: Fante Matthias A. , Harrer Dennis C. , Zartner Barbara , Lüke Florian , Mayer Stephanie , Menhart Karin , Reichle Albrecht , Herr Wolfgang , Vogelhuber Martin , Heudobler Daniel
Published: May 2023

Purpose

Peripheral T-cell lymphoma (PTCL) is a rare and heterogenous hematologic malignancy with poor prognosis especially in elderly and frail patients who are not eligible for intensive treatment. The resulting palliative setting necessitates tolerable but effective schedules for outpatient treatment. TEPIP is a locally developed, all-oral low-dose regimen comprising trofosfamide, etoposide, procarbazine, idarubicin, and prednisolone.

Methods

In this observational retrospective, single-center study, the safety and efficacy of TEPIP was evaluated in 12 patients (pts.) with PTCL treated at the University Medical Center Regensburg between 2010 and 2022. The endpoints were overall response rate (ORR) and overall survival (OS), and adverse events were individually reported according to the Common Terminology Criteria for Adverse Events (CTCAE) criteria.

Results

The enrolled cohort was characterized by advanced age (median 70 years), extensive disease (100% Ann Arbor ≥stage 3), and poor prognosis (75% high/high-intermediate international prognostic index). The most common subtype was angioimmunoblastic T-cell lymphoma (8/12), and 11/12 patients had relapsed or refractory disease at TEPIP onset with a median of 1.5 prior treatment regimens. After a median of 2.5 TEPIP cycles (total of 83 cycles), the ORR was 42% (complete remission 25%), and the OS reached a median of 185 days. Any grade of adverse event (AE) occurred in 8/12 patients, with four patients showing AE ≥CTCAE grade 3 (33%), and the AEs were mainly non-hematological.

Conclusion

TEPIP demonstrated competitive efficacy with a tolerable safety profile in a highly palliative cohort of patients with difficult-to-treat PTCL. The all-oral application, which makes outpatient treatment possible, is particularly noteworthy.
Effect of a BSHP process on clinical work ability of nurses in a children's cardiac intensive care unit
Authors: Ma Fangyan , Shi Aiguo , Bian Lanzheng , Li Mei , Li Mingxiong , Xu Banghong
Published: May 2023

Background

Nurse shift change is the key step to ensuring the integrity, dynamics, and continuity of clinical nursing in intensive care units.

Objectives

To evaluate the effect of a bedside shift handover process (BSHP) on the clinical work ability of first-line clinical nurses in a children's cardiac intensive care unit (CICU).

Methods

This quasi-experimental study was performed on the first-line clinical nurses working in a pediatric CICU at Children's Hospital of Nanjing Medical University between July and December, 2018. Participants were trained by the BSHP. This article is based on the STROBE checklist.

Results

A total of 41 nurses were trained, with 34 women. The nurses in the intensive care unit showed significantly improved clinical work ability, including the ability to assess illness/find problems, master professional knowledge, standardized hands-on ability, ability to express communication, strain handling capacity, and humanistic care and accomplishment (all P < 0.05), after training.

Conclusion

BSHP might improve the clinical work ability for pediatric CICU nurses through a standardization shift handover. The traditional oral shift change in CICU can easily cause an information distortion, and it is difficult or even impossible to arouse the nurses' enthusiasm. This study suggested that BSHP might be an alternative shift change process for pediatric CICU nurses.
The Italian Network for Monitoring Medication Use During Pregnancy (MoM-Net): Experience and Perspectives
Authors: Belleudi Valeria , Fortinguerra Filomena , Poggi Francesca R. , Perna Serena , Bortolus Renata , Donati Serena , Clavenna Antonio , Locatelli Anna , Davoli Marina , Addis Antonio , Trotta Francesco ,   MoM-Net group
Published: May 2023

There is an acute need for research to acquire high-quality information on the use of medicines in pregnancy, both in terms of appropriateness and safety. For this purpose, the Italian Medicines Agency established a Network for Monitoring Medication use in pregnancy (MoM-Net) through the conduction of population-based studies using administrative data available at regional level. This paper aimed to describe the experiences and challenges within the network. MoM-Net currently involves eight regions and several experts from public and academic institutions. The first study conducted aimed to identify drug use before, during and after pregnancy investigating specific therapeutic categories, analysing regional variability and monitoring drug use in specific subpopulations (i.e. foreign women/multiple pregnancies). Aggregated demographic, clinical, and prescription data were analysed using a distributed network approach based on common data model. The study population included all women delivering during 2016–2018 in the participating regions (n = 449,012), and corresponding to 59% of deliveries in Italy. Seventy-three per cent of the cohort had at least one drug prescription during pregnancy, compared to 57% before and 59% after pregnancy. In general, a good adherence to guidelines for pregnant women was found although some drug categories at risk of inappropriateness, such as progestins and antibiotics, were prescribed. A strong variability in the use of drugs among regions and in specific subpopulations was observed. The MoM-Net represents a valuable surveillance system on the use of medicines in pregnancy, available to monitor drug categories at high risk of inappropriateness and to investigate health needs in specific regions or subpopulations.
Antiarthritic potential of the butanol fraction of Sesuvium sesuvioides: An in vitro, in vivo, and in silico evaluation
Authors: Sajid-ur-Rehman Muhammad , Ishtiaq Saiqa , Aati Hanan Y. , Sherif Asmaa E. , Abbas Khan Mohsin , Hussain Mussadique , Sohaib Khan Muhammad , Ahmed Maqsood , Naseem Muhammad Jawad , Khan Kashif-ur-Rehman
Published: May 2023

Sesuvium sesuvioides (Fenzl) Verdc (Aizoaceae) has been traditionally used in the treatment of inflammation, arthritis, and gout. However, its antiarthritic potential has not been evaluated scientifically. The current study was designed to assess the antiarthritic properties of the n-butanol fraction of S. sesuvioides (SsBu) by phytochemical analysis, in vitro and in vivo pharmacological activities, and in silico studies. Phytochemical analysis showed total phenolic contents (90.7 ± 3.02 mg GAE/g) and total flavonoid contents (23.7 ± 0.69 mg RE/g), and further analysis by GC-MS identified possible bioactive phytocompounds belonging to phenols, flavonoids, steroids, and fatty acids. The in vitro antioxidant potential of SsBu was assessed by DPPH (175.5 ± 7.35 mg TE/g), ABTS (391.6 ± 17.1 mg TE/g), FRAP (418.2 ± 10.8 mg TE/g), CUPRAC (884.8 ± 7.97 mg TE/g), phosphomolybdenum (5.7 ± 0.33 mmol TE/g), and metal chelating activity (9.04 ± 0.58 mg EDTAE/g). Moreover, in the in vitro studies, inhibition (%) of egg albumin and bovine serum albumin denaturation assays showed that the anti-inflammatory effect of SsBu at the dose of 800 μg/ml was comparable to that of diclofenac sodium used as a standard drug. The in vivo antiarthritic activity was assessed to determine the curative impact of SsBu against formalin-induced (dose-dependent significant (p < 0.05) effect 72.2% inhibition at 750 mg/kg compared to standard; 69.1% inhibition) and complete Freund’s adjuvant-induced arthritis (40.8%; inhibition compared to standard, 42.3%). SsBu significantly controlled PGE-2 level compared to the control group (p < 0.001) and restored the hematological parameters in rheumatoid arthritis. Treatment with SsBu significantly reduced oxidative stress by reinstating superoxide dismutase, GSH, and malondialdehyde along with pro-inflammatory markers (IL-6 and TNF-α) in arthritic rats. Molecular docking revealed the antiarthritic role of major identified compounds. Kaempferol-3-rutinoside was found to be more potent for COX-1 (−9.2 kcal/mol) and COX-2 inhibition (−9.9 kcal/mol) than diclofenac sodium (COX-1, −8.0 and COX-2, −6.5 kcal/mol). Out of the 12 docked compounds, two for COX-1 and seven for COX-2 inhibition showed more potent binding than the standard drug. The results from the in vitro, in vivo, and in silico approaches finally concluded that the n-butanol fraction of S. sesuvioides had antioxidant and antiarthritic potential, which may be due to the presence of potential bioactive compounds.
Sulfosuccinimidyl oleate ameliorates the high-fat diet-induced obesity syndrome by reducing intestinal and hepatic absorption
Authors: Ma Qiming , Wen Li , Tian Yanxia , Ma Liqin , Wen Zhangsheng , Kun Yang , Xu Mengping , Liu Xiaoping
Published: May 2023

Background: A high-fat Western diet is a risk factor for obesity and steatosis. Reducing intestinal absorption of a high-fat diet (HFD) is a feasible strategy to control obesity. Sulfosuccinimidyl oleate (SSO) inhibits intestinal fatty acid transport. Therefore, the aim of this study was to investigate the effects of SSO on HFD-induced glucose and lipid metabolism in mice and its possible underlying mechanisms.

Methods: Male C57/BL were fed a HFD (60% calories) for 12 weeks and were administered an oral dose of SSO (50 mg/kg/day). The expression of lipid absorption genes (CD36, MTTP, and DGAT1) and the serum levels of triglycerides (TGs), total cholesterol (TC), and free fatty acids (FFAs) were detected. Lipid distribution in the liver was detected by oil red and hematoxylin and eosin staining. In addition, serum levels of inflammatory factors, alanine aminotransferase (ALT), and aspartate aminotransferase (AST) were measured to detect side effects.

Results: SSO was effective in the treatment of obesity and metabolic syndrome induced by HFD in mice. It attenuated the assembly of intestinal epithelial chylomicrons by inhibiting intestinal epithelial transport and absorption of fatty acids, thereby reducing the gene expression levels of MTTP and DGAT1, resulting in decreased plasma TG and FFA levels. At the same time, it inhibited the transport of fatty acids in the liver and improved the steatosis induced by a HFD. The results of oil red staining showed that SSO treatment can reduce lipid accumulation in the liver by 70%, with no drug-induced liver injury detected on the basis of interleukin-6, C-reactive protein, ALT, and AST levels. In addition, SSO treatment significantly improved insulin resistance, decreased fasting blood glucose levels, and improved glucose tolerance in HFD-fed mice.

Conclusion: SSO is effective in the treatment of obesity and metabolic syndrome induced by a HFD in mice. SSO reduces intestinal fatty acid absorption by reducing the inhibition of intestinal CD36 expression, followed by decreased TG and FFA levels, which attenuates HFD-induced fatty liver.
Modelling spatiotemporal dynamics of cerebral blood flow using multiple-timepoint arterial spin labelling MRI
Authors: Pinto Joana , Blockley Nicholas P. , Harkin James W. , Bulte Daniel P.
Published: May 2023

Introduction: Cerebral blood flow (CBF) is an important physiological parameter that can be quantified non-invasively using arterial spin labelling (ASL) imaging. Although most ASL studies are based on single-timepoint strategies, multi-timepoint approaches (multiple-PLD) in combination with appropriate model fitting strategies may be beneficial not only to improve CBF quantification but also to retrieve other physiological information of interest.

Methods: In this work, we tested several kinetic models for the fitting of multiple-PLD pCASL data in a group of 10 healthy subjects. In particular, we extended the standard kinetic model by incorporating dispersion effects and the macrovascular contribution and assessed their individual and combined effect on CBF quantification. These assessments were performed using two pseudo-continuous ASL (pCASL) datasets acquired in the same subjects but during two conditions mimicking different CBF dynamics: normocapnia and hypercapnia (achieved through a CO2 stimulus).

Results: All kinetic models quantified and highlighted the different CBF spatiotemporal dynamics between the two conditions. Hypercapnia led to an increase in CBF whilst decreasing arterial transit time (ATT) and arterial blood volume (aBV). When comparing the different kinetic models, the incorporation of dispersion effects yielded a significant decrease in CBF (∼10–22%) and ATT (∼17–26%), whilst aBV (∼44–74%) increased, and this was observed in both conditions. The extended model that includes dispersion effects and the macrovascular component has been shown to provide the best fit to both datasets.

Conclusion: Our results support the use of extended models that include the macrovascular component and dispersion effects when modelling multiple-PLD pCASL data.
Effects of COVID-19 on cognition and mood after hospitalization and at 2-month follow-up
Authors: Peskar Manca , Šimunič Boštjan , Šlosar Luka , Pišot Saša , Teraž Kaja , Gasparini Mladen , Pišot Rado , Marusic Uros
Published: May 2023

A plethora of evidence links SARS-CoV-2 infection with concomitant cognitive dysfunction, which often persists weeks to months after the acute stages of illness and affects executive function, attention, memory, orientation, and movement control. It remains largely unclear which conditions or factors exacerbate the recovery. In a cohort of N=37 Slovenian patients (5 females, aged M = 58, SD = 10.7 years) that were hospitalized because of COVID-19, the cognitive function and mood states were assessed immediately after discharge and 2-months later to investigate the early post-COVID recovery changes. We assessed the global Montreal Cognitive Assessment (MoCA), Simple and Choice Reaction Times, executive functions (Trail-Making Test – TMT-A and TMT-B), short-term memory (Auditory Verbal Learning Test – AVLT), and visuospatial memory. We monitored depressive and anxiety symptoms and applied general self-efficacy and cognitive complaints questionnaires. Our results showed a global cognitive impairment (MoCA, Z = 332.5; p = 0.012), poorer performance on executive functions (TMT-A, Z = 188; p = 0.014; and TMT-B, Z = 185; p = 0.012), verbal memory (AVLT, F = 33.4; p < 0.001), and delayed recall (AVLT7, F = 17.1; p < 0.001), and higher depressive (Z = 145; p = 0.015) and anxiety (Z = 141; p = 0.003) symptoms after hospital discharge compared to 2-month follow-up, indicating that SARS-CoV-2 may transiently impair cognitive function and adversely affect the mood. No improvement in MoCA was observed in 40.5% of the patients at follow-up, indicating possible long-term effects of COVID-19 on global cognitive performance. Medical comorbidities (p = 0.035) significantly predicted the change in MoCA score over time, while fat mass (FM, p = 0.518), Mediterranean diet index (p = .0.944), and Florida Cognitive Activities Score (p = 0.927) did not. These results suggest that the patients’ medical comorbidities at the time of SARS-CoV-2 infection could importantly contribute to the acute impairment of cognitive function and stress the importance of systemic implementation of countermeasures to limit the negative consequences on public health.
Perceived rhythmic regularity is greater for song than speech: examining acoustic correlates of rhythmic regularity in speech and song
Authors: Yu Chu Yi , Cabildo Anne , Grahn Jessica A. , Vanden Bosch der Nederlanden Christina M.
Published: May 2023

Rhythm is a key feature of music and language, but the way rhythm unfolds within each domain differs. Music induces perception of a beat, a regular repeating pulse spaced by roughly equal durations, whereas speech does not have the same isochronous framework. Although rhythmic regularity is a defining feature of music and language, it is difficult to derive acoustic indices of the differences in rhythmic regularity between domains. The current study examined whether participants could provide subjective ratings of rhythmic regularity for acoustically matched (syllable-, tempo-, and contour-matched) and acoustically unmatched (varying in tempo, syllable number, semantics, and contour) exemplars of speech and song. We used subjective ratings to index the presence or absence of an underlying beat and correlated ratings with stimulus features to identify acoustic metrics of regularity. Experiment 1 highlighted that ratings based on the term “rhythmic regularity” did not result in consistent definitions of regularity across participants, with opposite ratings for participants who adopted a beat-based definition (song greater than speech), a normal-prosody definition (speech greater than song), or an unclear definition (no difference). Experiment 2 defined rhythmic regularity as how easy it would be to tap or clap to the utterances. Participants rated song as easier to clap or tap to than speech for both acoustically matched and unmatched datasets. Subjective regularity ratings from Experiment 2 illustrated that stimuli with longer syllable durations and with less spectral flux were rated as more rhythmically regular across domains. Our findings demonstrate that rhythmic regularity distinguishes speech from song and several key acoustic features can be used to predict listeners’ perception of rhythmic regularity within and across domains as well.
ChatGPT outperforms humans in emotional awareness evaluations
Authors: Elyoseph Zohar , Hadar-Shoval Dorit , Asraf Kfir , Lvovsky Maya
Published: May 2023

The artificial intelligence chatbot, ChatGPT, has gained widespread attention for its ability to perform natural language processing tasks and has the fastest-growing user base in history. Although ChatGPT has successfully generated theoretical information in multiple fields, its ability to identify and describe emotions is still unknown. Emotional awareness (EA), the ability to conceptualize one’s own and others’ emotions, is considered a transdiagnostic mechanism for psychopathology. This study utilized the Levels of Emotional Awareness Scale (LEAS) as an objective, performance-based test to analyze ChatGPT’s responses to twenty scenarios and compared its EA performance with that of the general population norms, as reported by a previous study. A second examination was performed one month later to measure EA improvement over time. Finally, two independent licensed psychologists evaluated the fit-to-context of ChatGPT’s EA responses. In the first examination, ChatGPT demonstrated significantly higher performance than the general population on all the LEAS scales (Z score = 2.84). In the second examination, ChatGPT’s performance significantly improved, almost reaching the maximum possible LEAS score (Z score = 4.26). Its accuracy levels were also extremely high (9.7/10). The study demonstrated that ChatGPT can generate appropriate EA responses, and that its performance may improve significantly over time. The study has theoretical and clinical implications, as ChatGPT can be used as part of cognitive training for clinical populations with EA impairments. In addition, ChatGPT’s EA-like abilities may facilitate psychiatric diagnosis and assessment and be used to enhance emotional language. Further research is warranted to better understand the potential benefits and risks of ChatGPT and refine it to promote mental health.
Trait and state-related characteristics of thalamo-cortical circuit disruption in bipolar disorder: a prospective cross-sectional study
Authors: Zeng Can , Liao SuQun , Pu Weidan
Published: May 2023

Objective

The purpose of this study is to investigate the shared and distinct thalamic-cortical circuit between bipolar depression and remission, as well as to investigate the trait and state-related characteristics of the abnormal thalamic-cortical circuit in bipolar disorder.

Methods

Resting-state functional magnetic resonance imaging was performed on 38 bipolar depression patients, 40 bipolar remission patients, and 39 gender-matched healthy controls (rsfMRI). The thalamic subregions were used as seed points to draw the functional connectivity of the entire brain, and then the shared and distinct thalamic-cortical circuits between bipolar depression and remission were compared.

Results

When compared to the healthy group, both groups of patients had significantly lower functional connectivity between the rostral temporal thalamus and the lingual gyrus, the posterior parietal thalamus, the precuneus/cerebellum, and the occipital thalamus and the precuneus; however, functional connectivity between the premotor thalamus and the superior medial frontal was significantly lower in depression.

Conclusion

This study discovered that both bipolar depression and remission had abnormal sensorimotor-thalamic functional connectivity, implying that it is a trait-related characteristic of bipolar disorder; however, the decline in prefrontal-thalamic connectivity exists specifically in bipolar depression, implying that it is a state-related characteristic of bipolar disorder.
Analysis of COVID-19 outbreak in Hubei province based on Tencent's location big data
Authors: Hua Lei , Ran Rong , Li Tingrou
Published: May 2023

Rapid urbanization has gradually strengthened the spatial links between cities, which greatly aggravates the possibility of the spread of an epidemic. Traditional methods lack the early and accurate detection of epidemics. This study took the Hubei province as the study area and used Tencent's location big data to study the spread of COVID-19. Using ArcGIS as a platform, the urban relation intensity, urban centrality, overlay analysis, and correlation analysis were used to measure and analyze the population mobility data of 17 cities in Hubei province. The results showed that there was high similarity in the spatial distribution of urban relation intensity, urban centrality, and the number of infected people, all indicating the spatial distribution characteristics of “one large and two small” distributions with Wuhan as the core and Huanggang and Xiaogan as the two wings. The urban centrality of Wuhan was four times higher than that of Huanggang and Xiaogan, and the urban relation intensity of Wuhan with Huanggang and Xiaogan was also the second highest in the Hubei province. Meanwhile, in the analysis of the number of infected persons, it was found that the number of infected persons in Wuhan was approximately two times that of these two cities. Through correlation analysis of the urban relation intensity, urban centrality, and the number of infected people, it was found that there was an extremely significant positive correlation among the urban relation intensity, urban centrality, and the number of infected people, with an R2 of 0.976 and 0.938, respectively. Based on Tencent's location big data, this study conducted the epidemic spread research for “epidemic spatial risk classification and prevention and control level selection” to make up for the shortcomings in epidemic risk analysis and judgment. This could provide a reference for city managers to effectively coordinate existing resources, formulate policy, and control the epidemic.
Research on patient-centered design for post-stroke depression patients based on SEM and comprehensive evaluation
Authors: Li Yuxuan , Zhang Qi , Fang Xing
Published: May 2023

Introduction

Since COVID-19, medical resources have been tight, making it inconvenient to go offline for the sequelae of diseases such as post-stroke depression (PSD) that require long-term follow-up. As a new digital therapy, VRTL began to gain popularity.

Method

The research is divided into two parts: pre-test and post-test. In the pre-test, an evaluation method integrating reality-based interaction (RBI), structural equation model (SEM), analytic hierarchy process (AHP), and entropy weight method is proposed. In the post-test the patients’ physiological indicators (Diastolic blood pressure, systolic blood pressure and heart rate) are measured to verify the effectiveness of RBI-SEM model using T-test method.

Results

In the pre-test, using SEM, it was confirmed that Pi physical awareness, Bi body awareness, Ei environmental awareness, and Si social awareness were significantly correlated and positively affected VRTL satisfaction (p >> F 0.217; B >> F 0.130; E >> F 0.243; S >> F 0.122). The comprehensive weight ranking based on RBI-SEM considered light environment (0.665), vegetation diversity (0.667), accessible roaming space (0.550) et al. relatively of importance. And T-tset in the post-test experiment considered that the data of the two measurements before and after the VRTL experience, systolic blood pressure (p < 0.01), diastolic blood pressure (p < 0.01), and blood pressure (p < 0.01) were significantly decreased; one-way ANOVA concluded that there was no significant difference in the changes of blood pressure and heart rate among participants of different ages and genders (p > 0.01).

Conclusion

This research validated the effectiveness of RBI theory for VRTL design guidelines, established an RBI-SEM based VRTL evaluation model, and the output VRTL for PSD in the older adults was confirmed to have significant therapeutic benefits. This lays the foundation for designers to decompose design tasks and integrate VRTL into traditional clinical treatment systems.

Contribution from the public or patients

Four public health department employees helped to improve the research’s content.
The 2022 ParticipACTION Report Card on Physical Activity for Children and Youth: Focus on the COVID-19 pandemic impact and equity-deserving groups
Authors: Kuzik Nicholas , Cameron Christine , Carson Valerie , Chaput Jean-Philippe , Colley Rachel , Doiron Joe , Faulkner Guy , Janssen Ian , Saunders Travis , Spence John C. , Tucker Patricia , Vanderloo Leigh M. , Tremblay Mark S.
Published: May 2023

Introduction

The ParticipACTION Report Card on Physical Activity for Children and Youth is the most comprehensive national assessment of physical activity and related behaviors, characteristics, and opportunities for children and youth. The 2022 Report Card assigned grades based on data gathered during the COVID-19 pandemic to reflect this extraordinary time-period in Canada. Further, while not graded, efforts were made to summarize key findings for early years children and those identifying as: having a disability, Indigenous, 2SLGBTQ+, newcomers to Canada, racialized, or girls. The purpose of this paper is to summarize the 2022 ParticipACTION Report Card on Physical Activity for Children and Youth.

Methods

The best available physical activity data captured during the whole COVID-19 pandemic was synthesized across 14 different indicators in four categories. The 2022 Report Card Research Committee assigned letter grades (i.e., A–F) based on expert consensus of the evidence.

Synthesis

Grades were assigned for: Daily Behaviors (Overall Physical Activity: D; Active Play: D−; Active Transportation: C−; Organized Sport: C+; Physical Education: Incomplete [INC]; Sedentary Behaviors: F; Sleep: B; 24-Hour Movement Behaviors: F), Individual Characteristics (Physical Literacy: INC; Physical Fitness: INC), Spaces and Places (Household: C, School: B−, Community and Environment: B), and Strategies and Investments (Government: B−). Compared to the 2020 Report Card, the COVID-19 specific grades increased for Active Play and Active Transportation; and decreased for Overall Physical Activity, Sedentary Behaviors, Organized Sport, and Community and Environment. There were many data gaps for equity-deserving groups.

Conclusion

During the COVID-19 pandemic, the grade for Overall Physical Activity decreased from a D+ (2020) to a D, coinciding with decreases in grades reflecting fewer opportunities for sport and community/facility-based activities as well as higher levels of sedentary behaviors. Fortunately, improvements in Active Transportation and Active Play during COVID-19 prevented a worse shift in children’s health behaviors. Efforts are needed to improve physical activity for children and youth during and post-pandemic, with a greater emphasis on equity-deserving groups.
Development and validation of a prediction model based on comorbidities to estimate the risk of in-hospital death in patients with COVID-19
Authors: Zhu Yangjie , Yu Boyang , Tang Kang , Liu Tongtong , Niu Dongjun , Zhang Lulu
Published: May 2023

Background

Most existing prognostic models of COVID-19 require imaging manifestations and laboratory results as predictors, which are only available in the post-hospitalization period. Therefore, we aimed to develop and validate a prognostic model to assess the in-hospital death risk in COVID-19 patients using routinely available predictors at hospital admission.

Methods

We conducted a retrospective cohort study of patients with COVID-19 using the Healthcare Cost and Utilization Project State Inpatient Database in 2020. Patients hospitalized in Eastern United States (Florida, Michigan, Kentucky, and Maryland) were included in the training set, and those hospitalized in Western United States (Nevada) were included in the validation set. Discrimination, calibration, and clinical utility were evaluated to assess the model's performance.

Results

A total of 17 954 in-hospital deaths occurred in the training set (n = 168 137), and 1,352 in-hospital deaths occurred in the validation set (n = 12 577). The final prediction model included 15 variables readily available at hospital admission, including age, sex, and 13 comorbidities. This prediction model showed moderate discrimination with an area under the curve (AUC) of 0.726 (95% confidence interval [CI]: 0.722—0.729) and good calibration (Brier score = 0.090, slope = 1, intercept = 0) in the training set; a similar predictive ability was observed in the validation set.

Conclusion

An easy-to-use prognostic model based on predictors readily available at hospital admission was developed and validated for the early identification of COVID-19 patients with a high risk of in-hospital death. This model can be a clinical decision-support tool to triage patients and optimize resource allocation.