Category: Statistics

Adv Exp Med Biol. 2023;1424:255-263. doi: 10.1007/978-3-031-31982-2_29.

ABSTRACT

The brain’s temperature measurements (T_B) in patients with severe brain damage are important, in order to offer the optimal treatment. The purpose of this research is the creation of mathematical models for the T_B‘s prediction, based on the temperatures in the bladder (T_BL), femoral artery (T_FA), ear canal (T_ΕC), and axilla (T_A), without the need for placement of intracranial catheter, contributing significantly to the research of the human thermoregulatory system.The research involved 18 patients (13 men and 5 women), who were hospitalized in the adult intensive care units (ICU) of Larissa’s two hospitals, with severe brain injury. An intracranial catheter with a thermistor was used to continuously measure T_B and other parameters. The T_B‘s measurements, and simultaneously one or more of T_BL, T_FA, T_EC, and T_A, were recorded every 1 h.To create T_B predicting models, the data of each measurement was separated into (a) model sample (measurements’ 80%) and (b) validation sample (measurements’ 20%). Multivariate linear regression analysis demonstrated that it is possible to predict brain’s temperature (PrT_B), using independent variables (R₂ was T_BL = 0.73, T_FA = 0.80, T_EC = 0.27, and T_A = 0.17, p < 0.05). Significant linear associations were found, statistically, and no difference in means between T_B and PrT_B of each prediction model. Also, the 95% limits of agreement and the percent coefficient of variation showed sufficient agreement between the T_B and PrT_B in each prediction model.In conclusion, brain’s temperature prediction models based on T_BL, T_FA, T_EC, and T_A were successful. Its determination contributes to the improvement of clinical decision-making.

PMID:37486502 | DOI:10.1007/978-3-031-31982-2_29

Adv Exp Med Biol. 2023;1424:233-240. doi: 10.1007/978-3-031-31982-2_26.

ABSTRACT

In an attempt to develop therapeutic agents to treat Alzheimer’s disease, a series of flavonoid analogues were collected, which already had established acetylcholinesterase (AChE) enzyme inhibition activity. For each molecule we also collected biological activity data (Ki). Then, 3D-QSAR (quantitative structure-activity relationship model) was developed which showed acceptable predictive and descriptive capability as represented by standard statistical parameters r2 and q2. This SAR data can explain the key descriptors which can be related to AChE inhibitory activity. Using the QSAR model, pharmacophores were developed based on which, virtual screening was done and a dataset was obtained which loaded as a prediction set to fit the developed QSAR model. Top 10 compounds fitting the QSAR model were subjected to molecular docking. CHEMBL1718051 was found to be the lead compound. This study is offering an example of a computationally-driven tool for prioritisation and discovery of probable AChE inhibitors. Further, in vivo and in vitro testing will show its therapeutic potential.

PMID:37486499 | DOI:10.1007/978-3-031-31982-2_26

Adv Exp Med Biol. 2023;1424:201-211. doi: 10.1007/978-3-031-31982-2_22.

ABSTRACT

Amyotrophic lateral sclerosis (ALS) is a late-onset fatal neurodegenerative disease characterized by progressive loss of the upper and lower motor neurons. There are currently limited approved drugs for the disorder, and for this reason the strategy of repositioning already approved therapeutics could exhibit a successful outcome. Herein, we used CMAP and L1000CDS² databases which include gene expression profiles datasets (genomic signatures) to identify potent compounds and classes of compounds which reverse disease’s signature which could in turn reverse its phenotype. ALS signature was obtained by comparing gene expression of muscle biopsy specimens between diseased and healthy individuals. Statistical analysis was conducted to explore differentially transcripts in patients’ samples. Then, the list of upregulated and downregulated genes was used to query both databases in order to determine molecules which downregulate the genes which are upregulated by ALS and vice versa. These compounds, based on their chemical structure along with known treatments, were clustered to reveal drugs with novel and potentially more effective mode of action with most of them predicted to affect pathways heavily involved in ALS. This evidence suggests that these compounds are strong candidates for moving to the next phase of the drug repurposing pipeline which is in vitro and in vivo experimental evaluation.

PMID:37486495 | DOI:10.1007/978-3-031-31982-2_22

Adv Exp Med Biol. 2023;1424:145-155. doi: 10.1007/978-3-031-31982-2_15.

ABSTRACT

Allergic contact dermatitis (ACD) is an inflammatory reaction affecting all age groups and both sexes. ACD is characterized by a delayed-type hypersensitivity reaction IV caused by skin contact with haptens. Chronic exposure typically leads to a decrease in erythema accompanied by lichenification (thickening and hardening of the skin) and persistent itching. The current study aims to investigate the patterns of contact sensitization in the Greek population using patch test data analysis. Patch test data from 240 patients (120 Males/120 Females) with allergic contact dermatitis were collected at the Laboratory for Patch Testing, National Reference Center for Occupational Dermatoses “Andreas Syggros” Hospital in Athens Greece. The contact allergic reactions were caused by ethylenediamine dihydrochloride 1%, thimerosal 0.5%, and methyldibromo-glutaronitrile 0.1% from the European baseline series of allergens; information was also collected for ICDRG evaluation, an extended MOAHLFA index and patient-reported outcomes (daily routine questionnaire). The chi-square test for independence and Spearman’s rank were used to evaluate the association and correlation, respectively, between patient characteristics and ACD-related factors. Multiple correspondence analysis (MCA), which is a data analysis approach, was used to find and depict underlying structures in the data collection for nominal categorical data. Statistically significant associations were found between the following pairs of characteristics: eczema triggers and gender and eczema triggers and hand dermatitis. The results from MCA showed that there is correlation between allergic contact dermatitis onset, allergens, and demographic variables.

PMID:37486488 | DOI:10.1007/978-3-031-31982-2_15

Adv Exp Med Biol. 2023;1424:135-144. doi: 10.1007/978-3-031-31982-2_14.

ABSTRACT

OBJECTIVE: Epilepsy patients could possibly benefit from the remuneration observed in the use of virtual reality (VR) and virtual environments (VEs), especially in cognitive difficulties associated with visuospatial navigation (memory, attention, and processing speed).

AIM: Research questions under consideration in the present systematic review are associated to VEs’ efficiency as a cognitive rehabilitation practice in epilepsy and the particular VR methods indicated for epilepsy patients. To meet criteria, studies included participants suffering from any form of epilepsy and a methodological design with a structured rehabilitation program/model. Data were collected online, using academic databases.

RESULTS: Fourteen studies were included in the literature review and 6 in the statistical analysis. ROBINS-I protocol was implemented to assess the risk of bias. An inverse variance analysis (random effects) of pooled estimates of differences was implemented, in the form of continuous data. Despite the heterogeneity of the studies, all of them agree on the beneficial aspects of VR and VEs in cognitive rehabilitation in relation to visuospatial memory, attention, and information processing speed.

CONCLUSION: We suggest that patients suffering from epilepsy may benefit from the use of VR cognitive rehabilitation interventions, concerning visuospatial memory, attention, and information processing speed. However, further investigation is needed in order to gain a better understanding of the mechanisms involved in cognitive rehabilitation via VEs and establish efficient and dynamic rehabilitation protocols.

PMID:37486487 | DOI:10.1007/978-3-031-31982-2_14

Breast Cancer. 2023 Jul 24. doi: 10.1007/s12282-023-01485-y. Online ahead of print.

ABSTRACT

BACKGROUND: Cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) improve the prognosis of hormone receptor-positive HER2-negative advanced/metastatic breast cancer (HR+/HER2- mBC). However, some cancers show resistance to CDK4/6i and have a poor prognosis. The non-luminal disease score (NOLUS) was developed to predict non-luminal disease using immunohistochemical analysis.

METHODS: The association between the efficacy of CDK4/6i and NOLUS was investigated by evaluating pathological and clinical data, including real-world progression-free survival (rw-PFS) and overall survival (OS). Real-world data of patients with HR+/HER2- mBC who received CDK4/6i therapy [palbociclib or abemaciclib] as first- or second-line endocrine treatments was obtained. NOLUS was calculated using the formula: NOLUS (0-100) = – 0.45 × estrogen receptor (ER) (%) – 0.28 × progesterone receptor (PR) (%) + 0.27 × Ki67(%) + 73, and the patients were divided into two groups: NOLUS-positive (≥ 51.38) and NOLUS-negative (< 51.38).

RESULTS: Of the 300 patients, 28 (9.3%) were NOLUS-positive, and 272 (90.7%) were NOLUS-negative. The expression rates (%) of ER and PgR in NOLUS-positive patients were lower than those in NOLUS-negative patients (p < 0.001). Ki67 expression was higher in NOLUS-positive patients. There were statistically significant differences in prognosis (rw-PFS and OS) between the two groups. Moreover, NOLUS-negative patients showed statistically better rw-PFS with first-line therapy than second-line therapy. However, NOLUS-positive patients showed poor prognoses with both the first and second therapeutic lines, suggesting CDK4/6i inefficacy for NOLUS-positive patients.

CONCLUSIONS: The efficacy and prognosis of CDK4/6i significantly differed between the NOLUS-positive and NOLUS-negative patients. This feasible method can predict patients with HR+/HER2- mBC resistant to CDK4/6i and help select a better therapeutic approach to overcome resistance.

PMID:37486454 | DOI:10.1007/s12282-023-01485-y

Med Biol Eng Comput. 2023 Jul 24. doi: 10.1007/s11517-023-02859-2. Online ahead of print.

ABSTRACT

Accurate diagnosis of autism spectrum disorder (ASD) is crucial for effective treatment and prognosis. Functional brain networks (FBNs) constructed from functional magnetic resonance imaging (fMRI) have become a popular tool for ASD diagnosis. However, existing model-driven approaches used to construct FBNs lack the ability to capture potential non-linear relationships between data and labels. Moreover, most existing studies treat the FBNs construction and disease classification as separate steps, leading to large inter-subject variability in the estimated FBNs and reducing the statistical power of subsequent group comparison. To address these limitations, we propose a new approach to FBNs construction called the deep unrolling-based spatial constraint representation (DUSCR) model and integrate it with a convolutional classifier to create an end-to-end framework for ASD recognition. Specifically, the model spatial constraint representation (SCR) is solved using a proximal gradient descent algorithm, and we unroll it into deep networks using the deep unrolling algorithm. Classification is then performed using a convolutional prototype learning model. We evaluated the effectiveness of the proposed method on the ABIDE I dataset and observed a significant improvement in model performance and classification accuracy. The resting state fMRI images are preprocessed into time series data and 3D coordinates of each region of interest. The data are fed into the DUSCR model, a model for building functional brain networks using deep learning instead of traditional models, that we propose, and then the outputs are fed into the convolutional classifier with prototype learning to determine whether the patient has ASD disease.

PMID:37486440 | DOI:10.1007/s11517-023-02859-2

Neuroradiology. 2023 Jul 24. doi: 10.1007/s00234-023-03201-1. Online ahead of print.

ABSTRACT

PURPOSE: To evaluate the ability of neurite orientation dispersion and density imaging (NODDI) for detecting white matter (WM) microstructural abnormalities in minimal hepatic encephalopathy (MHE).

METHODS: Diffusion-weighted images, enabling the estimation of NODDI and diffusion tensor imaging (DTI) parameters, were acquired from 20 healthy controls (HC), 22 cirrhotic patients without MHE (NHE), and 15 cirrhotic patients with MHE. Tract-based spatial statistics were used to determine differences in DTI (including fractional anisotropy [FA] and mean/axial/radial diffusivity [MD/AD/RD]) and NODDI parameters (including neurite density index [NDI], orientation dispersion index [ODI], and isotropic volume fraction [ISO]). Voxel-wise analyses of correlations between diffusion parameters and neurocognitive performance determined by Psychometric Hepatic Encephalopathy Score (PHES) were completed.

RESULTS: MHE patients had extensive NDI reduction and rare ODI reduction, primarily involving the genu and body of corpus callosum and the bilateral frontal lobe, corona radiata, external capsule, anterior limb of internal capsule, temporal lobe, posterior thalamic radiation, and brainstem. The extent of NDI and ODI reduction expanded from NHE to MHE. In both MHE and NHE groups, the extent of NDI change was quite larger than that of FA change. No significant intergroup difference in ISO/MD/AD/RD was observed. Tissue specificity afforded by NODDI revealed the underpinning of FA reduction in MHE. The NDI in left frontal lobe was significantly correlated with PHES.

CONCLUSION: MHE is characterized by diffuse WM microstructural impairment (especially neurite density reduction). NODDI can improve the detection of WM microstructural impairments in MHE and provides more precise information about MHE-related pathology than DTI.

PMID:37486421 | DOI:10.1007/s00234-023-03201-1

Hum Vaccin Immunother. 2023 Jul 24:2234792. doi: 10.1080/21645515.2023.2234792. Online ahead of print.

ABSTRACT

Immunoprofiling has become a crucial tool for understanding the complex interactions between the immune system and diseases or interventions, such as therapies and vaccinations. Immune response biomarkers are critical for understanding those relationships and potentially developing personalized intervention strategies. Single-cell data have emerged as a promising source for identifying immune response biomarkers. In this review, we discuss the current state-of-the-art methods for immunoprofiling, including those for reducing the dimensionality of high-dimensional single-cell data and methods for clustering, classification, and prediction. We also draw attention to recent developments in data integration.

PMID:37485833 | DOI:10.1080/21645515.2023.2234792

Disaster Med Public Health Prep. 2023 Jul 24;17:e436. doi: 10.1017/dmp.2023.100.

ABSTRACT

OBJECTIVE: In Turkey, which is a land of disasters, it is vital for nurses to be prepared before a disaster, and to exhibit an effective attitude and behavior during it. Having a large number of casualties during a disaster may cause inadequacies in receiving basic health care in the hospital.

METHODS: This study was conducted in a descriptive and cross-sectional style to determine the disaster preparedness and preparedness perceptions of nurses. Data were collected with the Personal Information Form and Nurses’ Perception of Disaster Preparedness Scale (NPDPS).

RESULTS: Nurses’ disaster experience, drill experience, and perusal of the disaster plan positively affected the perception of disaster. The disaster preparedness of the institution positively affected the perception of disaster preparation. A significant difference was determined between the requests for information regarding disaster education and NPDPS. A statistically significant relationship was found between terrorist attacks, earthquake exposure, and the total scale score of NPDPS.

CONCLUSIONS: Consequently, nurses and health institutions, whose responsibilities become graver in disasters, have duties such as providing treatment and medical support. Therefore, it was suggested that disaster nursing and disaster management should have been included in the in-service training of nurses.

PMID:37485823 | DOI:10.1017/dmp.2023.100