Category: Nevin Manimala

Commun Med (Lond). 2023 Jul 22;3(1):103. doi: 10.1038/s43856-023-00331-8.

ABSTRACT

BACKGROUND: Maternal HIV infection and antiretroviral drugs (ARVs) are associated with increased risks of adverse perinatal outcomes. The vast majority of pregnant women living with HIV (WLHIV) reside in sub-Saharan Africa. We aimed to determine the burden of adverse perinatal outcomes attributable to HIV and ARVs in sub-Saharan Africa between 1990 and 2020.

METHODS: We conduct a systematic review of studies on the association of pregnant WLHIV with adverse perinatal outcomes in sub-Saharan Africa. We perform random-effects meta-analyses to determine the risk difference (attributable risk, AR) of perinatal outcomes among WLHIV receiving no ARVs, monotherapy, or combination antiretroviral therapy (cART) initiated antenatally or preconception, compared to HIV-negative women. We estimate numbers of perinatal outcomes attributable to HIV and ARVs by combining the AR values with numbers of WLHIV receiving different ARV regimens in each country in sub-Saharan Africa annually between 1990 and 2020.

RESULTS: We find that WLHIV receiving no ARVs or cART initiated antenatally or preconception, but not monotherapy, have an increased risk of preterm birth (PTB), low birthweight (LBW) and small for gestational age (SGA), compared to HIV-negative women. Between 1990 and 2020, 1,921,563 PTBs, 2,119,320 LBWs, and 2,049,434 SGAs are estimated to be attributable to HIV and ARVs in sub-Saharan Africa, mainly among WLHIV receiving no ARVs, while monotherapy and preconception and antenatal cART averted many adverse outcomes. In 2020, 64,585 PTBs, 58,608 LBWs, and 61,112 SGAs were estimated to be attributable to HIV and ARVs, the majority among WLHIV receiving preconception cART.

CONCLUSIONS: As the proportion of WLHIV receiving preconception cART increases, the burden of adverse perinatal outcomes among WLHIV in sub-Saharan Africa is likely to remain high.

SYSTEMATIC REVIEW REGISTRATION NUMBER: CRD42021248987.

PMID:37481594 | DOI:10.1038/s43856-023-00331-8

Sci Rep. 2023 Jul 22;13(1):11852. doi: 10.1038/s41598-023-38719-0.

ABSTRACT

This paper presents a new strategy to generate synthetic samples containing casting defects. Four samples of Inconel 100 containing casting defects such as shrinkages and pores have been characterized using X-ray tomography and are used as reference for this application. Shrinkages are known to be tortuous in shape and more detrimental for the mechanical properties of materials, especially metal fatigue, whereas pores can be of two types: broken shrinkage pores with arbitrary shape and gaseous pores of spherical shape. For the generation of synthetic samples, an integrated module of Spatial Point Pattern (SPP) analysis and deep learning techniques such as Generative Adversarial Networks (GANs) and Convolutional Neural Networks (CNNs) are used. The SPP analysis describes the spatial distributions of casting defects in material space, whereas GANs and CNNs generate a defect of arbitrary morphology very close to real defects. SPP analysis reveals the existence of two different void nucleation mechanisms during metal solidification associated to shrinkages and pores. Our deep learning model successfully generates casting defects with defect size ranging from 100 µm to 1.5 mm and of very realistic shapes. The entire synthetic microstructure generation process respects the global defect statistics of reference samples and the generated samples are validated by statistically comparing with real samples.

PMID:37481577 | DOI:10.1038/s41598-023-38719-0

Alzheimers Res Ther. 2023 Jul 22;15(1):127. doi: 10.1186/s13195-023-01268-9.

ABSTRACT

BACKGROUND: We aimed to quantify the identification of mild cognitive impairment and/or Alzheimer’s disease using olfactory-stimulated functional near-infrared spectroscopy using machine learning through a post hoc analysis of a previous diagnostic trial and an external additional trial.

METHODS: We conducted two independent, patient-level, single-group, diagnostic interventional trials (original and additional trials) involving elderly volunteers (aged > 60 years) with suspected declining cognitive function. All volunteers were assessed by measuring the oxygenation difference in the orbitofrontal cortex using an open-label olfactory-stimulated functional near-infrared spectroscopy approach, medical interview, amyloid positron emission tomography, brain magnetic resonance imaging, Mini-Mental State Examination, and Seoul Neuropsychological Screening Battery.

RESULTS: In total, 97 (original trial) and 36 (additional trial) elderly volunteers with suspected decline in cognitive function met the eligibility criteria. The statistical model reported classification accuracies of 87.3% in patients with mild cognitive impairment and Alzheimer’s disease in internal validation (original trial) but 63.9% in external validation (additional trial). The machine learning algorithm achieved 92.5% accuracy with the internal validation data and 82.5% accuracy with the external validation data. For the diagnosis of mild cognitive impairment, machine learning performed better than statistical methods with internal (86.0% versus 85.2%) and external validation data (85.4% versus 68.8%).

INTERPRETATION: In two independent trials, machine learning models using olfactory-stimulated oxygenation differences in the orbitofrontal cortex were superior in diagnosing mild cognitive impairment and Alzheimer’s disease compared to classic statistical models. Our results suggest that the machine learning algorithm is stable across different patient groups and increases generalization and reproducibility.

TRIAL REGISTRATION: Clinical Research Information Service (CRiS) of Republic of Korea; CRIS numbers, KCT0006197 and KCT0007589.

PMID:37481573 | DOI:10.1186/s13195-023-01268-9

BMC Microbiol. 2023 Jul 22;23(1):196. doi: 10.1186/s12866-023-02933-7.

ABSTRACT

BACKGROUND: Recently, an important relationship between Parkinson’s disease and the gut microbiota, through the brain-gut axis interactions, has been established. Previous studies have declared that alterations in the gut microbiota have a great impact on the pathogenesis and clinical picture of Parkinson’s disease (PD). The present study aimed to identify the gut microbiome that is likely related to Parkinson’s disease as well as their possible relation to clinical phenotypes.

METHODS: Thirty patients with Parkinson’s disease, who presented to the Parkinson’s disease Neurology Clinic of Alexandria University Hospital were enrolled in our study. A cross-matching control group of 35 healthy subjects of similar age and sex were included. Stool specimens were taken from each. Quantitative SYBR Green Real-Time PCR was done for the identification and quantitation of selected bacterial phyla, genera and/or species.

RESULTS: There was a significant increase in Bacteroides and a significant decrease of Firmicutes and Firmicutes / Bacteroidetes ratio and Bifidobacteria in PD patients. Although Prevotella was decreased among PD patients relative to the healthy control, the difference was not statistically significant. Comparing the PD clinical phenotypes with the control group, the Mixed phenotype had significantly higher Bacteroides, Tremors predominant had lower Firmicutes and Firmicutes / Bacteroidetes ratio, and both tremors and postural instability and gait disability (PIGD) phenotypes had lower Bifidobacteria. However, there was no statistically significant difference between these phenotypes. Furthermore, when comparing tremors and non-tremors predominant phenotypes; Lactobacilli showed a significant decrease in non-tremors predominant phenotypes.

CONCLUSIONS: The current study showed evidence of changes in the gut microbiome of Parkinson’s disease patients compared to the healthy controls. These observations may highlight the importance of the identification of microbiome and specific bacterial changes that can be targeted for the treatment of Parkinson’s disease.

PMID:37481569 | DOI:10.1186/s12866-023-02933-7

J Orthop Surg Res. 2023 Jul 22;18(1):524. doi: 10.1186/s13018-023-04006-x.

ABSTRACT

PURPOSE: Bone cement augmentation surgery includes percutaneous vertebroplasty (PVP) and percutaneous kyphoplasty (PKP). In this study, we aimed to investigate the risk of sandwich vertebral fractures in the treatment of osteoporotic vertebral compression fractures via PVP and PKP.

METHODS: We performed a retrospective analytical study and included 61 patients with osteoporotic vertebral compression fractures who underwent PVP and PKP at the Spinal Surgery Department of The Second Hospital of Liaocheng Affiliated with Shandong First Medical University from January 2019 to January 2022. These patients were divided into the following two groups by simple random sampling: group A (N = 30) underwent PVP treatment and group B (N = 31) underwent PKP treatment. The surgical time, fluoroscopy frequency, visual analog scale (VAS) score, amount of bone cement, the leakage rate of bone cement in intervertebral space, Cobb angle, and the incidence of fractures in both groups of sandwich vertebral were recorded after 1 year of follow-up.

RESULTS: No statistically significant difference was found in terms of surgical time, fluoroscopy frequency, and VAS score between the two groups (P > 0.05). However, a statistically significant difference was found in terms of the amount of bone cement, the leakage rate of bone cement intervertebral space, Cobb angle, and the incidence of vertebral body fractures in both groups (P < 0.05). The amount of bone cement, the leakage rate of bone cement in intervertebral space, Cobb angle, and sandwich vertebral fractures were higher in Group A than in Group B.

CONCLUSIONS: When PVP and PKP were performed to treat osteoporotic vertebral compression fractures, the sandwich vertebral exhibited a risk of fracture. PVP exhibited a greater relative risk than PKP, which may be due to the relatively larger amount of bone cement, higher rate of bone cement leakage in the intervertebral space, and larger Cobb angle.

PMID:37481567 | DOI:10.1186/s13018-023-04006-x

Cell Mol Biol Lett. 2023 Jul 22;28(1):58. doi: 10.1186/s11658-023-00476-3.

ABSTRACT

BACKGROUND: One of the factors that affect the progression of melanoma is the tumor microenvironment, which consists of cellular elements, extracellular matrix, acidification, and a hypoxic state. Adipocytes are one of the types of cell present in the niche and are localized in the deepest layer of the skin. However, the relationship between fat cells and melanoma remains unclear.

METHODS: We assessed the influence of melanoma cells on adipocytes using an indirect coculture system. We estimated the level of cancer-associated adipocyte (CAA) markers through quantitative PCR analysis. The fibroblastic phenotype of CAAs was confirmed by cell staining and western blotting analysis. The lipid content was estimated by lipid detection in CAAs using LipidSpot and by quantitative analysis using Oil Red O. The expression of proteins involved in lipid synthesis, delipidation, and metabolic processes were assessed through quantitative PCR or western blotting analysis. Lactate secretion was established using a Lactate-Glo™ assay. Proteins secreted by CAAs were identified in cytokine and angiogenesis arrays. The proliferation of melanoma cells cocultured with CAAs was assessed using an XTT proliferation assay. Statistical analysis was performed using a one-way ANOVA followed by Tukey’s test in GraphPad Prism 7 software.

RESULTS: Obtained CAAs were identified by decreased levels of leptin, adiponectin, resistin, and FABP4. Adipocytes cocultured with melanoma presented fibroblastic features, such as a similar proteolytic pattern to that of 3T3L1 fibroblasts and increased levels of vimentin and TGFβRIII. Melanoma cells led to a reduction of lipid content in CAAs, possibly by downregulation of lipid synthesis pathways (lower FADS, SC4MOL, FASN) or enhancement of lipolysis (higher level of phosphorylation of ERK and STAT3). Adipocytes cocultured with melanoma cells secreted higher IL6 and SerpinE1 levels and produced less CCL2, CXCL1, and angiogenic molecules. CAAs also showed metabolic changes comprising the increased secretion of lactate and enhanced production of glucose, lactate, and ion transporters. In addition, changes in adipocytes observed following melanoma coculture resulted in a higher proliferation rate of cancer cells.

CONCLUSIONS: Melanoma cells led to decreased lipid content in adipocytes, which might be related to enhanced delipidation or reduction of lipid synthesis. Fibroblast-like CAAs showed metabolic changes that may be the reason for accelerated proliferation of melanoma cells.

PMID:37481560 | DOI:10.1186/s11658-023-00476-3

Trials. 2023 Jul 22;24(1):469. doi: 10.1186/s13063-023-07453-3.

ABSTRACT

BACKGROUND: India has made steady progress in improving rates of primary school enrolment but levels of learning achievement remain low. The Support To Rural India’s Public Education System (STRIPES) trial provided evidence that an after-school para-teacher intervention improved numeracy and literacy levels in Telangana, India. The STRIPES2 trial investigates whether such an intervention will have a similar effect on the literacy and numeracy of primary school age children in the Satna District of Madhya Pradesh, India.

METHODS/DESIGN: The STRIPES2 trial forms one part of a cluster-randomised controlled trial with villages (clusters) randomised to receive either a health (CHAMPION2) or education (STRIPES2) intervention. Building on the design of the earlier CHAMPION/STRIPES trial, villages receiving the health intervention are controls for the education intervention and vice versa. The primary outcome is a combined literacy and numeracy score. Secondary outcomes include separate scores for literacy and numeracy; caregivers’ engagement with child’s learning; expenditure on education; enrolment in school; caregiver’s report of school attendance and the cost effectiveness of the intervention. Over 7000 primary school age children have been recruited and randomised in STRIPES2.

DISCUSSION: This update to the published trial protocol gives a detailed plan for the statistical analysis of the STRIPES 2 trial.

TRIAL REGISTRATION: Registry of India: CTRI/2019/05/019296. Registered on 23 May 2019. http://www.ctri.nic.in/Clinicaltrials/pdf_generate.php?trialid=31198&EncHid=&modid=&compid=%27,%2731198det%27.

PMID:37481559 | DOI:10.1186/s13063-023-07453-3

BMC Pregnancy Childbirth. 2023 Jul 22;23(1):532. doi: 10.1186/s12884-023-05851-8.

ABSTRACT

BACKGROUND: A growing body of literature indicates that including male partners in antenatal care can be instrumental to improving women’s health service utilization and maternal and child health outcomes. Despite this, very few studies have documented overall trends in male partner attendance and what factors influence this involvement within the Indian context. In this study, we used nationally representative data to examine levels of male partner attendance in antenatal care and the factors associated with male partner attendance.

METHODS: Data were used from the National Family Health Survey (NFHS-4) conducted in 2015-16. Weighted (probability weights) descriptive statistics were conducted to summarize the level of male partner attendance in antenatal care in India, and multivariable logistic regression models were constructed to estimate the factors associated with male partner attendance in antenatal care.

RESULTS: In 2015, of the women who had attended at least one antenatal care contact during their pregnancy, about 85% reported that their male partners had accompanied them to antenatal care contacts, with variations across regions. Level of education, household wealth, knowledge of pregnancy-related issues, men’s age at marriage, region, and women’s level of autonomy emerged as significant predictors of male partner attendance in antenatal care.

CONCLUSIONS: The results of this study highlight the multiple influences that shape male partners’ attendance in antenatal care. The findings underscore the need for a multi-faceted approach to programs and interventions aimed at encouraging male partner involvement; recognizing men both as individuals, as well as being situated within the family/household and community.

PMID:37481558 | DOI:10.1186/s12884-023-05851-8

BMC Oral Health. 2023 Jul 22;23(1):513. doi: 10.1186/s12903-023-03235-0.

ABSTRACT

BACKGROUND: Psychological stress is a crucial parameter in defining the symptoms of burning mouth syndrome (BMS). We hypothesized that the level of psychological stress in patients with BMS would correlate with severity of clinical symptoms, cortisol levels, and cortisol/ adrenocorticotropic hormone (ACTH) ratio. We aimed to comprehensively investigate the influence of clinical and hematologic parameters on the hypothalamic-pituitary-adrenal axis, particularly concerning the presence or absence of self-perceived psychological stress in patients with BMS. In addition, we aimed to identify parameters predicting psychological stress in these patients.

METHODS: One hundred and forty-one patients with BMS (117 women, 82.98%; 56.21 ± 13.92 years) were divided into psychological stress (n = 68; 55 females, 56.39 ± 12.89 years) and non-psychological stress groups (n = 73; 62 females, 56.03 ± 14.90 years), and inter- and intra-group statistical analyses were conducted. Significant predictors of psychological stress in patients with BMS were investigated through multiple logistic regression analysis.

RESULTS: The prevalence of xerostomia was significantly higher (67.6% vs. 34.2%, p < 0.001), while unstimulated salivary flow rate was lower (0.66 ± 0.59 vs. 0.91 ± 0.53 mL/min, p < 0.01) in the psychological stress group than in the non-psychological stress group. SCL-90R subscale values for somatization, hostility, anxiety, and depression, as well as cortisol and ACTH levels and the cortisol/ACTH ratio, were also higher in the psychological stress group (all p < 0.05). Above-mean values for cortisol (AUC = 0.980, 95%CI: 0.959-1.000) and cortisol/ACTH (AUC = 0.779; 95%CI, 0.701-0.856) were excellent predictors of psychological stress, with cortisol (r = 0.831, p < 0.01) and cortisol/ACTH (r = 0.482, p < 0.01) demonstrating substantial correlations. Above-average values for cortisol (OR = 446.73) and cortisol/ACTH (OR = 6.159) significantly increased incidence of psychological stress in patients with BMS (all p < 0.001).

CONCLUSIONS: Among patients with BMS, xerostomia, decreased salivary flow rate, increased cortisol levels, and cortisol/ACTH ratio were associated with psychological stress, highlighting the psycho-neuro-endocrinological features of this condition. Cortisol and cortisol/ACTH ratio were strong predictors of psychological stress in patients with BMS.

PMID:37481556 | DOI:10.1186/s12903-023-03235-0

BMC Med Res Methodol. 2023 Jul 22;23(1):171. doi: 10.1186/s12874-023-01987-5.

ABSTRACT

BACKGROUND: COVID-19 brought enormous challenges to public health surveillance and underscored the importance of developing and maintaining robust systems for accurate surveillance. As public health data collection efforts expand, there is a critical need for infectious disease modeling researchers to continue to develop prospective surveillance metrics and statistical models to accommodate the modeling of large disease counts and variability. This paper evaluated different likelihoods for the disease count model and various spatiotemporal mean models for prospective surveillance.

METHODS: We evaluated Bayesian spatiotemporal models, which are the foundation for model-based infectious disease surveillance metrics. Bayesian spatiotemporal mean models based on the Poisson and the negative binomial likelihoods were evaluated with the different lengths of past data usage. We compared their goodness of fit and short-term prediction performance with both simulated epidemic data and real data from the COVID-19 pandemic.

RESULTS: The simulation results show that the negative binomial likelihood-based models show better goodness of fit results than Poisson likelihood-based models as deemed by smaller deviance information criteria (DIC) values. However, Poisson models yield smaller mean square error (MSE) and mean absolute one-step prediction error (MAOSPE) results when we use a shorter length of the past data such as 7 and 3 time periods. Real COVID-19 data analysis of New Jersey and South Carolina shows similar results for the goodness of fit and short-term prediction results. Negative binomial-based mean models showed better performance when we used the past data of 52 time periods. Poisson-based mean models showed comparable goodness of fit performance and smaller MSE and MAOSPE results when we used the past data of 7 and 3 time periods.

CONCLUSION: We evaluate these models and provide future infectious disease outbreak modeling guidelines for Bayesian spatiotemporal analysis. Our choice of the likelihood and spatiotemporal mean models was influenced by both historical data length and variability. With a longer length of past data usage and more over-dispersed data, the negative binomial likelihood shows a better model fit than the Poisson likelihood. However, as we use a shorter length of the past data for our surveillance analysis, the difference between the Poisson and the negative binomial models becomes smaller. In this case, the Poisson likelihood shows robust posterior mean estimate and short-term prediction results.

PMID:37481553 | DOI:10.1186/s12874-023-01987-5