Category: Nevin Manimala

J Neuroeng Rehabil. 2023 Apr 29;20(1):55. doi: 10.1186/s12984-023-01178-9.

ABSTRACT

BACKGROUND: An incomplete spinal cord injury (SCI) refers to remaining sensorimotor function below the injury with the possibility for the patient to regain walking abilities. However, these patients often suffer from diverse gait deficits, which are not objectively assessed in the current clinical routine. Wearable inertial sensors are a promising tool to capture gait patterns objectively and started to gain ground for other neurological disorders such as stroke, multiple sclerosis, and Parkinson’s disease. In this work, we present a data-driven approach to assess walking for SCI patients based on sensor-derived outcome measures. We aimed to (i) characterize their walking pattern in more depth by identifying groups with similar walking characteristics and (ii) use sensor-derived gait parameters as predictors for future walking capacity.

METHODS: The dataset analyzed consisted of 66 SCI patients and 20 healthy controls performing a standardized gait test, namely the 6-min walking test (6MWT), while wearing a sparse sensor setup of one sensor attached to each ankle. A data-driven approach has been followed using statistical methods and machine learning models to identify relevant and non-redundant gait parameters.

RESULTS: Clustering resulted in 4 groups of patients that were compared to each other and to the healthy controls. The clusters did differ in terms of their average walking speed but also in terms of more qualitative gait parameters such as variability or parameters indicating compensatory movements. Further, using longitudinal data from a subset of patients that performed the 6MWT several times during their rehabilitation, a prediction model has been trained to estimate whether the patient’s walking speed will improve significantly in the future. Including sensor-derived gait parameters as inputs for the prediction model resulted in an accuracy of 80%, which is a considerable improvement of 10% compared to using only the days since injury, the present 6MWT distance, and the days until the next 6MWT as predictors.

CONCLUSIONS: In summary, the work presented proves that sensor-derived gait parameters provide additional information on walking characteristics and thus are beneficial to complement clinical walking assessments of SCI patients. This work is a step towards a more deficit-oriented therapy and paves the way for better rehabilitation outcome predictions.

PMID:37120519 | DOI:10.1186/s12984-023-01178-9

Eur Neuropsychopharmacol. 2023 Apr 17;73:24-35. doi: 10.1016/j.euroneuro.2023.04.008. Online ahead of print.

ABSTRACT

The objective of this study is to quantify the impact of the COVID-19 pandemic on attention deficit hyperactivity disorder (ADHD) medication consumption globally and nationally using pharmaceutical sales data from 2014 to 2021 across 47 countries and regions. A seasonal autoregressive integrated moving average model (SARIMA) was applied to the time series until the end of 2019 at country level and used for the prediction of the ADHD medication consumption in 2020 and 2021. The deviations from the actual to the forecasted sales, which simulate the development without the emergence of COVID-19, yield estimates for the pandemic’s impact. In 36 of the 47 countries and regions, the actual sales in 2020 were lower than predicted, with an average relative drop of 6.2% in defined daily doses (DDD) per 1000 inhabitants per day at country-level. In 2021, most countries recorded actually higher ADHD medication use than predicted at the end of 2019. On average, the consumption increased per country by 1.60%. The deviations strongly correlate with the stringency of anti-pandemic government policies. The findings suggest that the pandemic led to a substantially lower consumption of ADHD medication in 2020. However, in 2021 the pandemic had an accelerating effect as the increasing consumption trends are more pronounced than before the pandemic.

PMID:37119560 | DOI:10.1016/j.euroneuro.2023.04.008

J Forensic Leg Med. 2023 Apr 21;96:102525. doi: 10.1016/j.jflm.2023.102525. Online ahead of print.

ABSTRACT

BACKGROUND: Reaction time (RT) is the interval between a stimulus and an appropriate voluntary response in an individual. Alcohol is known to result in delayed RT. In Sri Lanka, an alleged drunken driver is legally subjected to a medico-legal examination to confirm or exclude impairment. The guideline for examining a drunk person in Sri Lanka includes the ruler drop test (RDT) as a test of RT. RDT is a simple test of visual reaction time in which the subject attempts to stop a falling ruler, and the height fallen is used to determine the time taken to react to the event. However, a formal study has yet to be carried out to establish population-specific reference values to interpret RDT results.

METHODS: A cross-sectional descriptive study was conducted using 903 adults ≥18 years. A nonparametric approach was applied for deriving the reference values based on an inter-percentile interval.

RESULTS: The study population consisted of 56.6% females, and the mean age of the participants was 41.6 years. Most (95%) of the study population could catch the ruler at or less than 40.0 cm of average height. The average height on RDT increased from younger to older age groups. However, subgrouping based on other variables, including sex, age, and alcohol consumption, did not show any statistically significant difference.

CONCLUSIONS: The population-specific cut-off limit to identify alcohol intoxication by RDT in a Sri Lankan adult is ‘average height’ >40 cm.

PMID:37119545 | DOI:10.1016/j.jflm.2023.102525

Adv Mind Body Med. 2023 Winter;37(1):4-10.

ABSTRACT

CONTEXT: Type 2 diabetes mellitus (T2DM) patients are at increased risk of cognitive impairment and dementia compared to healthy individuals. Lifestyle practices such as yoga can have a vital role in preventing and managing T2DM. Some studies have found that yoga can positively impact cognitive function in T2DM.

OBJECTIVE: The study aimed to investigate the benefits of short-term yoga practice on heart rate variability (HRV) and cognitive function for T2DM patients, without a matched control group, to address the paucity of data on the effectiveness of yoga practice on cognitive health on T2DM individuals.

DESIGN: Current study is a single group pre post design.

SETTING: The study took place in the Department of Yoga and Life Sciences at Swami Vivekananda Yoga Anusandhana Samsthana (S-VYASA) in Bangalore, India.

PARTICIPANTS: Participants were 21 T2DM patients from various hospitals, clinics and community setups, in different parts of Bengaluru city in India.

INTERVENTION: The participants took part in one month of yoga practice.

OUTCOME MEASURES: The research team used the Madrid card sorting test (MCST) to assess participants’ executive function (EF) at baseline and postintervention. In addition, the team monitored participants’ heart rate variability (HRV) in a resting phase and during task performance.

RESULTS: Between baseline and postintervention: (1) participants’ reaction time for the MCST decreased for overall task performance (P = .01) and during rule shifting (P = .03); (2) a significant reduction occurred in participants’ random errors (REs) and incorrect responses, at P = .02 for both, whereas a significant increase occurred in correct responses and efficient errors (EEs), at P = .03 and P = .01, respectively; (3) the low frequency (LF) and LF/high frequency (HF ) ratio for the HRV decreased; HF increased but the difference wasn’t statistically significant; and (4) a statistically significant decrease occurred in LF and LF/HF and an increase in HF occurred during task performance.

CONCLUSION: Yoga therapy had beneficial effects on cognitive performance for the T2DM participants. The yoga practice also positively affected autonomic functions during task performance and suggesting that it can reduce task-induced stress. It’s important for the future studies to validate the current findings with a randomized controlled trial.

PMID:37119540

Ann Clin Transl Neurol. 2023 Apr 29. doi: 10.1002/acn3.51782. Online ahead of print.

ABSTRACT

OBJECTIVE: Neurodegenerative conditions often manifest radiologically with the appearance of premature aging. Multiple sclerosis (MS) biomarkers related to lesion burden are well developed, but measures of neurodegeneration are less well-developed. The appearance of premature aging quantified by machine learning applied to structural MRI assesses neurodegenerative pathology. We assess the explanatory and predictive power of “brain age” analysis on disability in MS using a large, real-world dataset.

METHODS: Brain age analysis is predicated on the over-estimation of predicted brain age in patients with more advanced pathology. We compared the performance of three brain age algorithms in a large, longitudinal dataset (>13,000 imaging sessions from >6,000 individual MS patients). Effects of MS, MS disease course, disability, lesion burden, and DMT efficacy were assessed using linear mixed effects models.

RESULTS: MS was associated with advanced predicted brain age cross-sectionally and accelerated brain aging longitudinally in all techniques. While MS disease course (relapsing vs. progressive) did contribute to advanced brain age, disability was the primary correlate of advanced brain age. We found that advanced brain age at study enrollment predicted more disability accumulation longitudinally. Lastly, a more youthful appearing brain (predicted brain age less than actual age) was associated with decreased disability.

INTERPRETATION: Brain age is a technically tractable and clinically relevant biomarker of disease pathology that correlates with and predicts increasing disability in MS. Advanced brain age predicts future disability accumulation.

PMID:37119507 | DOI:10.1002/acn3.51782

Environ Sci Pollut Res Int. 2023 Apr 29. doi: 10.1007/s11356-023-27183-y. Online ahead of print.

ABSTRACT

Green finance has become an important reform force to promote the sustainable development of China’s economy. Therefore, it has a great significance for in-depth analysis of the advantages and disadvantages of regional green finance development, to further promote it by clarifying and predicting the regional differences and dynamic evolution trends. Based on this, this paper will select the relevant index from 2001 to 2020 to construct China Green Finance Core Network (CGFCN) in different years by using Space-L method at the first, then analyze its network characteristics and spatial evolution pattern in depth, and finally predict the future development trend of CGFCN by link prediction. The research results show that: firstly, the evolution of CGFCN is mainly divided into three stages: rapid development, stable development and optimal development, and the closeness of CGFCN is constantly improving. Besides, two strong relationship networks are gradually forming, that is Beijing-Tianjin region and the Yangtze River Detla region. Secondly, with the development of green finance, the community division has changed. It is mainly divided into four communities, named the Beijing-Tianjin-Hebei leading community, the eastern provincial community, the Yangtze River Delta community and the central and southern joint community. Different communities will have different integration in different periods. Thirdly, the future development direction of green finance network is mainly Beijing-Tianjin-Hebei region and Yangtze River Delta regions, and their outward radiation are mainly shown in the eastern coastal and central regions, which also have strong development potential. In this regard, it is proposed to coordinate development across provinces to speed up the “urban integration” of green finance services; Establish an efficient community development mechanism and promote the interconnection of green finance markets and infrastructure between different regions; Strengthen the resource flow among regions and coordinate the resource competition of green finance.

PMID:37119493 | DOI:10.1007/s11356-023-27183-y

Mol Biol Rep. 2023 Apr 29. doi: 10.1007/s11033-023-08347-y. Online ahead of print.

ABSTRACT

BACKGROUND: Crop improvement for tolerance to various biotic and abiotic stress factors necessitates understanding the key gene regulatory mechanisms. One such mechanism of gene regulation involves changes in cytosine methylation at the gene body and flanking regulatory sequences. The present study was undertaken to identify genes which might be potential targets of drought-induced DNA methylation in chickpea.

METHODS AND RESULTS: Two chickpea genotypes, which contrast for drought tolerance, were subjected to drought stress conditions and their differential response was studied by analysing different morpho-physiological traits. Utilizing the in-house, high throughput sequencing data, the SQUAMOSA promoter-binding (SBP) protein-like (SPL) transcription factor genes were identified to be differentially methylated and expressed amongst the two genotypes, in response to drought stress. The methylation status of one of these genes was examined and validated through bisulfite PCR (BS-PCR). The identified genes could be possible homologs to known epialleles and can therefore serve as potential epialleles which can be utilized for crop improvement in chickpea.

CONCLUSION: The SPL TF genes are potential targets of epigenetic regulation in response to drought stress in chickpea. Since these are TFs, they might play important roles in controlling the expression of other genes, thus contributing to differential drought response of the two genotypes.

PMID:37119417 | DOI:10.1007/s11033-023-08347-y

Mol Biol Rep. 2023 Apr 29. doi: 10.1007/s11033-023-08448-8. Online ahead of print.

ABSTRACT

BACKGROUND: Coronavirus Disease 2019 (COVID-19) is a global pandemic, and mortality and clinical consequences vary across countries. One of the factors influencing COVID-19 outcomes is genetic polymorphism. Two Kurdish populations, Sorani and Hawrami, live in the Sulaimani province of the Kurdistan Region of Iraq. It seems Hawrami had a milder COVID-19 outcome. According to previous research conducted on various ethnic groups across the globe, single nucleotide polymorphisms (SNPs) in the interferon-induced transmembrane protein 3 (IFITM3) and interluken-6 (IL6) genes were associated with the severity of COVID-19 in those populations.

METHODS AND RESULTS: We hypothesized that Hawrami may have protective SNPs. So, in this study, we used DNA sequencing to genotype three IFITM3 SNPs and nine IL6 SNPs by DNA sequencing to investigate the association of Sorani and Hawrami population polymorphisms. Genotype AA for the rs12252 SNP in IFITM3 was insignificantly more common in the Sorani group (54% vs. 44%). The Hawrami population showed a higher percentage of the CC genotype of the rs34481144 SNP in the IFITM3 gene (62% vs. 44.3%) and a higher proportion of the non-risky GG genotype of the rs1800795 SNP in the IL6 gene (53.4 vs. 43.3); however, the SNPs were insignificantly associated between the two populations.

CONCLUSIONS: IFITM3 and IL6 SNPs have no statistically significant association between the two Kurdish populations. The decreased proportion of non-risk alleles at rs34481144 and rs1800795 in the Hawrami population may partially support the research hypothesis. However, contrary to our hypothesis, the Sorani group had an insignificantly higher protective variant of the rs12252 SNP.

PMID:37119412 | DOI:10.1007/s11033-023-08448-8

Mol Biol Rep. 2023 Apr 29. doi: 10.1007/s11033-023-08433-1. Online ahead of print.

ABSTRACT

BACKGROUND: The dysfunctions in the metabolism of iron have an important role in many pathological conditions, ranging from disease with iron deposition to cancer. Studies on malignant diseases of the breast reported irregular expression in genes associated with iron metabolism. The variations are related to findings that have prognostic significance. This study evaluated the relationship of the expression levels of transferrin receptor 1 (TFRC), iron regulatory protein 1 (IRP1), hepcidin (HAMP), ferroportin 1 (FPN1), hemojuvelin (HFE2), matriptase 2 (TMPRSS6), and miR-122 genes in the normal and malignant tissues of breast cancer patients.

METHODS & RESULTS: The normal and malignant tissues from 75 women with breast malignancies were used in this study. The patients did not receive any treatment previously. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used in figuring the levels of gene expression associated with iron metabolism. When the malignant and normal tissues gene expression levels were analyzed, expression of TFRC increased (1.586-fold); IRP1 (0.594 fold) and miR-122 (0.320 fold) expression decreased; HAMP, FPN1, HFE2, and TMPRSS6 expressions did not change. FPN1 and IRP1 had a positive association, and this association was statistically significant (r = 0.266; p = 0.022). IRP1 and miR-122 had a positive association, and this association had statistical significance (r = 0.231; p = 0.048).

CONCLUSIONS: Our study portrayed the important association between genes involved in iron hemostasis and breast malignancy. The results could be used to establish new diagnostic techniques in the management of breast malignancies. The alterations in the metabolism of malignant breast cells with normal breast cells could be utilized to achieve advantages in treatment.

PMID:37119411 | DOI:10.1007/s11033-023-08433-1

Dig Dis Sci. 2023 Apr 29. doi: 10.1007/s10620-023-07935-z. Online ahead of print.

ABSTRACT

BACKGROUND: Hepatic encephalopathy (HE) is a major cause of mortality and morbidity in patients with cirrhosis. Lactulose non-adherence is one of the most frequently reported precipitants of hospital admission for HE.

AIMS: We aimed to identify which factors contribute most to lactulose non-adherence and propose strategies to promote greater adherence and utilization of lactulose.

METHODS: Participants in this study consisted of patients with cirrhosis who were taking lactulose for prevention of HE. Subjects were administered the Morisky Adherence Scale 8 (MAS-8) and a customized 16-question survey that assessed barriers to lactulose adherence. Results from the MAS-8 were used to stratify subjects into “adherent” and “non-adherent” groups. Survey responses were compared between groups.

RESULTS: We enrolled 129 patients in our study, of whom 45 were categorized as “adherent and 72 were categorized as “non-adherent.” Barriers to adherence included large volumes of lactulose, high frequency of dosing, difficulty remembering to take the medication, unpleasant taste, and medication side-effects. Most patients (97%) expressed understanding of the importance of lactulose, and 71% of patients felt that lactulose was working to manage their HE. Hospital admission rates for HE was higher in non-adherent patients, although this difference was not statistically significant.

CONCLUSION: We identified several factors that contribute to lactulose non-adherence among patients treated for HE. Many of these factors are potentially modifiable. Patient and care-giver education are critical to assure adherence. Pharmacists and nurses are an essential but underutilized aspect of education regarding proper medication use.

PMID:37119376 | DOI:10.1007/s10620-023-07935-z