Nevin Manimala

BMC Geriatr. 2023 Nov 22;23(1):767. doi: 10.1186/s12877-023-04457-1.

ABSTRACT

BACKGROUND: Delirium is a prevalent neuropsychiatric medical phenomenon that causes serious emergency outcomes, including mortality and morbidity. It also increases the suffering and the economic burden for families and carers. Unfortunately, the pathophysiology of delirium is still unknown, which is a major obstacle to therapeutic development. The modern network-based system biology and multi-omics analysis approach has been widely used to recover the key drug target biomolecules and signaling pathways associated with disease pathophysiology. This study aimed to identify the major drug target hub-proteins associated with delirium, their regulatory molecules with functional pathways, and repurposable drug candidates for delirium treatment.

METHODS: We used a comprehensive proteomic seed dataset derived from a systematic literature review and the Comparative Toxicogenomics Database (CTD). An integrated multi-omics network-based bioinformatics approach was utilized in this study. The STRING database was used to construct the protein-protein interaction (PPI) network. The gene set enrichment and signaling pathways analysis, the regulatory transcription factors and microRNAs were conducted using delirium-associated genes. Finally, hub-proteins associated repurposable drugs were retrieved from CMap database.

RESULTS: We have distinguished 11 drug targeted hub-proteins (MAPK1, MAPK3, TP53, JUN, STAT3, SRC, RELA, AKT1, MAPK14, HSP90AA1 and DLG4), 5 transcription factors (FOXC1, GATA2, YY1, TFAP2A and SREBF1) and 6 microRNA (miR-375, miR-17-5, miR-17-5p, miR-106a-5p, miR-125b-5p, and miR-125a-5p) associated with delirium. The functional enrichment and pathway analysis revealed the cytokines, inflammation, postoperative pain, oxidative stress-associated pathways, developmental biology, shigellosis and cellular senescence which are closely connected with delirium development and the hallmarks of aging. The hub-proteins associated computationally identified repurposable drugs were retrieved from database. The predicted drug molecules including aspirin, irbesartan, ephedrine-(racemic), nedocromil, and guanidine were characterized as anti-inflammatory, stimulating the central nervous system, neuroprotective medication based on the existing literatures. The drug molecules may play an important role for therapeutic development against delirium if they are investigated more extensively through clinical trials and various wet lab experiments.

CONCLUSION: This study could possibly help future research on investigating the delirium-associated therapeutic target biomarker hub-proteins and repurposed drug compounds. These results will also aid understanding of the molecular mechanisms that underlie the pathophysiology of delirium onset and molecular function.

PMID:37993790 | DOI:10.1186/s12877-023-04457-1

BMC Geriatr. 2023 Nov 22;23(1):764. doi: 10.1186/s12877-023-04412-0.

ABSTRACT

BACKGROUND: Aesthetics of everyday life are associated with the physical, mental, and social health of older adults, leading them to experience a successful old age. This study aimed to examine the aesthetics of everyday life and its related factors among older adults in Kashan from 2021 to 2022.

METHODS: This cross-sectional study consisted of 350 older adults who were referred to Urban Comprehensive Health Service Centers (UCHSC) in Kashan. Sampling was done by a two-stage method (cluster, random). The data collection was performed with a background information questionnaire and the Elderly’s Perception of Everyday Aesthetics scale (EPEA-S). Data were analyzed using an independent t-test, analysis of variance, Pearson’s correlation coefficient, and multiple linear regression tests in the SPSS software.

RESULTS: The mean age of the participants was 69.56 ± 6.63 years. The mean score of aesthetics of everyday life in older adults was 133.02 ± 14.73, with the family and others subscale receiving the highest score. The univariate test indicated a statistically significant correlation between age, employment status, education, income, smoking, social activities, physical activities, interest in artistic works, and the aesthetics of everyday life in older adults (P < 0.01). Multivariate linear analysis showed that age, employment status, smoking, income, social activities, physical activities, and interest in artistic works predicted and explained 28% of the variance of life aesthetics in older adults (R2 = 0.28).

CONCLUSIONS: The aesthetics of everyday life of the Iranian older adults were in a good range. Healthcare providers and families of older adults can use this concept to enhance the elderly’s physical, mental, and social health.

PMID:37993782 | DOI:10.1186/s12877-023-04412-0

BMC Bioinformatics. 2023 Nov 22;24(1):443. doi: 10.1186/s12859-023-05560-1.

ABSTRACT

Messenger RNA (mRNA) has an essential role in the protein production process. Predicting mRNA expression levels accurately is crucial for understanding gene regulation, and various models (statistical and neural network-based) have been developed for this purpose. A few models predict mRNA expression levels from the DNA sequence, exploiting the DNA sequence and gene features (e.g., number of exons/introns, gene length). Other models include information about long-range interaction molecules (i.e., enhancers/silencers) and transcriptional regulators as predictive features, such as transcription factors (TFs) and small RNAs (e.g., microRNAs – miRNAs). Recently, a convolutional neural network (CNN) model, called Xpresso, has been proposed for mRNA expression level prediction leveraging the promoter sequence and mRNAs’ half-life features (gene features). To push forward the mRNA level prediction, we present miREx, a CNN-based tool that includes information about miRNA targets and expression levels in the model. Indeed, each miRNA can target specific genes, and the model exploits this information to guide the learning process. In detail, not all miRNAs are included, only a selected subset with the highest impact on the model. MiREx has been evaluated on four cancer primary sites from the genomics data commons (GDC) database: lung, kidney, breast, and corpus uteri. Results show that mRNA level prediction benefits from selected miRNA targets and expression information. Future model developments could include other transcriptional regulators or be trained with proteomics data to infer protein levels.

PMID:37993778 | DOI:10.1186/s12859-023-05560-1

BMC Bioinformatics. 2023 Nov 22;24(1):442. doi: 10.1186/s12859-023-05572-x.

ABSTRACT

Drug repurposing is an exciting field of research toward recognizing a new FDA-approved drug target for the treatment of a specific disease. It has received extensive attention regarding the tedious, time-consuming, and highly expensive procedure with a high risk of failure of new drug discovery. Data-driven approaches are an important class of methods that have been introduced for identifying a candidate drug against a target disease. In the present study, a model is proposed illustrating the integration of drug-disease association data for drug repurposing using a deep neural network. The model, so-called IDDI-DNN, primarily constructs similarity matrices for drug-related properties (three matrices), disease-related properties (two matrices), and drug-disease associations (one matrix). Then, these matrices are integrated into a unique matrix through a two-step procedure benefiting from the similarity network fusion method. The model uses a constructed matrix for the prediction of novel and unknown drug-disease associations through a convolutional neural network. The proposed model was evaluated comparatively using two different datasets including the gold standard dataset and DNdataset. Comparing the results of evaluations indicates that IDDI-DNN outperforms other state-of-the-art methods concerning prediction accuracy.

PMID:37993777 | DOI:10.1186/s12859-023-05572-x

BMC Infect Dis. 2023 Nov 22;23(1):819. doi: 10.1186/s12879-023-08742-7.

ABSTRACT

BACKGROUND: The 2017 World Health Organization (WHO) report has listed extended-spectrum β-lactamase-producing Enterobacterales (ESBL-E) as critical pathogens for public health and requiring urgently new antibiotics. The aim of this study was to characterize phenotypically and genotypically ESBL-E isolated among clinical samples in Dschang, Cameroon.

METHODS: A cross-sectional study was conducted during a four-month periods from February to May 2022 in the two biggest hospitals of Dschang. Clinical samples were collected and cultured on Eosin Methylene Blue agar. Suspected growing colonies were biochemically identified using the Enterosystem Kit 18R. Antimicrobial susceptibility testing (AST) was done using the Kirby Bauer disc diffusion method and interpretated according to the CA-SFM recommendations. ESBL phenotypes were double screened using CHROMagar™ ESBL and double disk synergy test (DDST). The detection of resistance genes was performed using conventional and multiplex PCR methods. Results were analyzed with SPSS (version 21) and a p-value < 0.05 was considered statistically significant.

RESULTS: A total of 152 Enterobacterales were isolated among 597 clinical samples including urine, blood, cervico-vaginal, urethral swabs and wound samples. The overall prevalence of ESBL-Enterobacterales was 29.61% (45/152). The most represented ESBL species were Escherichia coli (n = 23; 51.11%), Klebsiella pneumoniae (n = 8; 17.78%) and Citrobacter freundii (n = 6; 13.33%).

CONCLUSION: This study reveals the high burden of ESBL-E among clinical samples in the regional hospital in Dschang with the most common species being E. coli and K. pneumoniae. It confirmed the high occurrence of bla_CTX-M and bla_TEM among ESBL-E. The study suggests that implementing antimicrobial stewardship program and real-time surveillance of antimicrobial resistance are needed in the Western region of Cameroon. Moreover, the implementation of infection prevention and control measures (IPC) is essential to curb the dissemination of these bacteria from community to hospital settings. Implementation of national action plan to fight against antimicrobial resistance at the local levels is urgently needed.

PMID:37993766 | DOI:10.1186/s12879-023-08742-7

Ann Biomed Eng. 2023 Nov 22. doi: 10.1007/s10439-023-03407-7. Online ahead of print.

ABSTRACT

This study aims to facilitate intracranial simulation of traumatic events by determining the mechanical properties of different anatomical structures of the brain. Our experimental indentation paradigm used fresh, post-operative human tissue, which is highly advantageous in determining mechanical properties without being affected by postmortem time. This study employed an inverse finite element approach coupled with experimental indentation data to characterize mechanical properties of the human hippocampus (CA1, CA3, dentate gyrus), cortex white matter, and cortex grey matter. We determined that an uncoupled viscoelastic Ogden constitutive formulation was most appropriate to represent the mechanical behavior of these different regions of brain. Anatomical regions were significantly different in their mechanical properties. The cortex white matter was stiffer than cortex grey matter, and the CA1 and dentate gyrus were both stiffer than cortex grey matter. Although no sex dependency was observed, there were trends indicating that male brain regions were generally stiffer than corresponding female regions. In addition, there were no statistically significant age dependent differences. This study provides a structure-specific description of fresh human brain tissue mechanical properties, which will be an important step toward explicitly modeling the heterogeneity of brain tissue deformation during TBI through finite element modeling.

PMID:37993751 | DOI:10.1007/s10439-023-03407-7

Lasers Med Sci. 2023 Nov 23;38(1):275. doi: 10.1007/s10103-023-03929-5.

ABSTRACT

The management of skin burns is still challenging. Among the therapeutic methods used, there are topical treatments with pharmacological and herbal agents, low-intensity therapeutic ultrasound, use of biomaterials, reconstructive techniques and photobiomodulation therapy. The aim of this study was to evaluate the effects of photobiomodulation with blue Light Emitting Diode (LED) on burn healing. Fifty Wistar rats were divided into control (CTRL) (n = 25) and blue LED (LED) (n = 25), with subgroups (n = 5) for each time of euthanasia (7, 14, 21, 28 and 32 days). Treated animals were daily irradiated (470 nm, 1W, 0.44 W/cm², 50 J/cm²). Clinical evaluations were performed and the Wound Retraction Index (WRI) was determined. Histological sections were submitted to hematoxylin-eosin, toluidine blue and the immunohistochemical technique, with anti-α-SMA and anti-TGF-β1 antibodies. All data were directly collected by previously calibrated evaluators in a blind manner. The values were included in a statistical program. For all statistical tests used, 5% significance level (p < 0.05) was considered. No statistically significant differences in WRI between groups were observed (p > 0.05). Re-epithelialization was higher using LED at 7 and 14 days (p < 0.05) and greater amount of inflammatory cells was observed at 7 days (p = 0.01). With LED at 21 and 32 days, greater number of mast cells were observed (p < 0.05), as well as smaller number of myofibroblasts at 14, 21, 28 and 32 days (p < 0.05) and lower percentage of TGF-β1 positive cells in the conjunctiva at 7, 14 and 21 days (p < 0.05). Negative correlations were observed in LED between the percentage of TGF-β1 in the epithelium and the mean number of inflammatory cells and number of myofibroblasts (p < 0.05). The results suggest that, depending on the period, blue LED can modulate the healing processes of third-degree skin burns, such as re-epithelialization, inflammatory response, mast cell concentration, myofibroblast differentiation and TGF-β1 immunoexpression. Despite these effects, this therapy does not seem to have significant influence on the retraction of these wounds. Future studies, using different protocols, should be carried out to expand the knowledge about the photobiomodulatory mechanisms of this type of light in the healing process.

PMID:37993749 | DOI:10.1007/s10103-023-03929-5

Neuroradiology. 2023 Nov 23. doi: 10.1007/s00234-023-03243-5. Online ahead of print.

ABSTRACT

PURPOSE: The use of magnetic resonance angiography (MRA) for assessing CNS fetal vasculature has been limited. The aim of this study was to determine the feasibility and added value of 2D time-of-flight (TOF) MRA of the fetal brain vasculature with a 1.5 T scanner.

METHODS: We conducted a prospective study (September 2018 to October 2022) by consecutively selecting pregnant women (≥ 18 years) with clinical indication to fetal brain MRI. On a 1.5 T scanner, a 2D TOF MRA acquisition was obtained at the end of the clinical protocol. Two neuroradiologists independently reviewed all MRIs; a qualitative scale of motion artifacts was applied to MRA images; represented vessels in MRA and T2 images were registered.

RESULTS: Thirty-five fetal brain MRIs. Mean maternal age: 32 years; mean fetal gestational age (GA): 31 weeks. Artifacts were found in 74% of MRA. The number of MRAs performed without artifacts increased with GA. On MRA, the identification of the majority of vessels increased with GA; statistical significance was reached in the identification of torcular Herophili (p = 0.026), vein of Galen (p < 0.001), internal cerebral veins (p = 0.002), basilar artery (p = 0.027), vertebral arteries (p = 0.025), and middle cerebral arteries (p = 0.044). Significantly, MRA depicted the sigmoid sinuses and internal jugular veins more frequently. Vascular pathology was found in 3/35 fetal brain MRIs.

CONCLUSION: Although artifacts were found in 74% of cases, MRA acquisitions were informative and of sufficient diagnostic quality in most studies. This technique may represent a valuable complimentary tool in CNS prenatal vascular studies.

PMID:37993731 | DOI:10.1007/s00234-023-03243-5

Sci Rep. 2023 Nov 22;13(1):20450. doi: 10.1038/s41598-023-47910-2.

ABSTRACT

The evidence base of surgical fracture care is extremely sparse with only few sound RCTs available. It is hypothesized that anthropometric factors relevantly influence mechanical conditions in the fracture gap, thereby interfering with the mechanoinduction of fracture healing. Development of a finite element model of a tibia fracture, which is the basis of an in silico population (n = 300) by systematic variation of anthropometric parameters. Simulations of the stance phase and correlation between anthropometric parameters and the mechanical stimulus in the fracture gap. Analysis of the influence of anthropometric parameters on statistical dispersion between in silico trial cohorts with respect to the probability to generate two, with respect to anthropometric parameters statistically different trial cohorts, given the same power assumptions. The mechanical impact in the fracture gap correlates with anthropometric parameters; confirming the hypothesis that anthropometric factors are a relevant entity. On a cohort level simulation of a fracture trial showed that given an adequate power the principle of randomization successfully levels out the impact of anthropometric factors. From a clinical perspective these group sizes are difficult to achieve, especially when considering that the trials takes advantage of a “laboratory approach “, i.e. the fracture type has not been varied, such that in real world trials the cohort size have to be even larger to level out the different configurations of fractures gaps. Anthropometric parameters have a significant impact on the fracture gap mechanics. The cohort sizes necessary to level out this effect are difficult or unrealistic to achieve in RCTs, which is the reason for sparse evidence in orthotrauma. New approaches to clinical trials taking advantage of modelling and simulation techniques need to be developed and explored.

PMID:37993727 | DOI:10.1038/s41598-023-47910-2

Behav Res Methods. 2023 Nov 22. doi: 10.3758/s13428-023-02290-3. Online ahead of print.

ABSTRACT

How feelings change over time is a central topic in emotion research. To study these affective fluctuations, researchers often ask participants to repeatedly indicate how they feel on a self-report rating scale. Despite widespread recognition that this kind of data is subject to measurement error, the extent of this error remains an open question. Complementing many daily-life studies, this study aimed to investigate this question in an experimental setting. In such a setting, multiple trials follow each other at a fast pace, forcing experimenters to use a limited number of questions to measure affect during each trial. A total of 1398 participants completed a probabilistic reward task in which they were unknowingly presented with the same string of outcomes multiple times throughout the study. This allowed us to assess the test-retest consistency of their affective responses to the rating scales under investigation. We then compared these consistencies across different types of rating scales in hopes of finding out whether a given type of scale led to a greater consistency of affective measurements. Overall, we found moderate to good consistency of the affective measurements. Surprisingly, however, we found no differences in consistency across rating scales, which suggests that the specific rating scale that is used does not influence the measurement consistency.

PMID:37993673 | DOI:10.3758/s13428-023-02290-3