Normal Control Subjects Research Articles

Degree of joint risk factor control and incident chronic kidney disease among individuals with obesity.

To investigate the extent to which joint risk factor control might attenuate the excess risk of chronic kidney disease (CKD) in participants with obesity. We included a total of 97 538 participants who were obese at baseline and matched 97 538 normal weight control participants from the UK Biobank in the analysis. The degree of joint risk factor control was assessed based on six major CKD risk factors, including blood pressure, glycated haemoglobin, low-density lipoprotein cholesterol, albuminuria, smoking and physical activity. The Cox proportional hazards models were used to estimate associations between the degree of risk factor control and risk of CKD, following participants from their baseline assessment until the occurrence of CKD, death, or the end of the follow-up period. Among participants with obesity, joint risk factor control showed an association with a stepwise reduction of incident CKD risk. Each additional risk factor control corresponded to an 11% (hazard ratio: 0.89; 95% confidence interval: 0.86-0.91) reduced risk of CKD among participants with obesity, with the optimal controlling of all six risk factors associated with a 49% (hazard ratio: 0.51; 95% confidence interval: 0.43-0.61) decrease in risk of CKD. Furthermore, in individuals with obesity who jointly controlled all six risk factors, the excess risk of CKD associated with obesity was effectively neutralized compared with normal weight control subjects. Notably, the protective correlations between the degree of joint risk factor control and the incidence of CKD were more pronounced in men compared with women, in individuals with a lower healthy food score versus a higher score, and among diabetes medication users as opposed to non-users (pinteraction = 0.017, 0.033 and 0.014, respectively). The joint risk factor control is associated with an inverse association of CKD risk in an accumulative manner among individuals with obesity. Achieving ideal control over risk factors may effectively counterbalance the excessive risk of CKD typically associated with obesity.

18F]FDG PET integrated with structural MRI for accurate brain age prediction.

Brain aging is a complex and heterogeneous process characterized by both structural and functional decline. This study aimed to establish a novel deep learning (DL) method for predicting brain age by utilizing structural and metabolic imaging data. The dataset comprised participants from both the Universal Medical Imaging Diagnostic Center (UMIDC) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). The former recruited 395 normal control (NC) subjects, while the latter included 438 NC subjects, 51 mild cognitive impairment (MCI) subjects, and 56 Alzheimer's disease (AD) subjects. We developed a novel dual-pathway, 3D simple fully convolutional network (Dual-SFCNeXt) to estimate brain age using [18F]fluorodeoxyglucose positron emission tomography ([18F]FDG PET) and structural magnetic resonance imaging (sMRI) images of NC subjects as input. Several prevailing DL models were trained and tested using either MRI or PET data for comparison. Model accuracies were evaluated using mean absolute error (MAE) and Pearson's correlation coefficient (r). Brain age gap (BAG), deviations of brain age from chronologic age, was correlated with cognitive assessments in MCI and AD subjects. Both PET- and MRI-based models achieved high prediction accuracy. The leading model was the SFCNeXt (the single-pathway version) for PET (MAE = 2.92, r = 0.96) and MRI (MAE = 3.23, r = 0.95) on all samples. By integrating both PET and MRI images, the Dual-SFCNeXt demonstrated significantly improved accuracy (MAE = 2.37, r = 0.97) compared to all single-modality models. Significantly higher BAG was observed in both the AD (P < 0.0001) and MCI (P < 0.0001) groups compared to the NC group. BAG correlated significantly with Mini-Mental State Examination (MMSE) scores (r=-0.390 for AD, r=-0.436 for MCI) and the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) scores (r = 0.333 for AD, r = 0.372 for MCI). The integration of [18F]FDG PET with structural MRI enhances the accuracy of brain age prediction, potentially introducing a new avenue for related multimodal brain age prediction studies.

Unravelling Neuroinflammation-Mediated Mitochondrial Dysfunction in Mild Cognitive Impairment: Insights from Targeted Metabolomics

BackgroundThe prevalence of Type 2 Diabetes Mellitus (T2DM) is rising rapidly among the elderly due to age-related metabolic changes. Older adults with T2DM have a 50-65% increased risk of developing cognitive impairment, particularly mild cognitive impairment (MCI), which may progress to neurodegenerative conditions like Alzheimer's disease (AD). Recent studies underscore the significant roles of mitochondrial dysfunction, disrupted glutamate-glutamine cycling, hyperglycemia, and hyperprolinemia in cognitive decline. These interconnected metabolites—glucose, glutamine, glutamate, and proline—are potential targets for understanding the relationship between T2DM and cognitive impairment. Material and MethodThe present targeted NMR based metabolomics study aims to compare the blood plasma/serum metabolic profiles of these four metabolites in age and sex matched MCI (N=27) and T2DM patients (N=38) with respect to normal control (NC, N=23) subjects. The metabolic profiling was performed using 1H NMR spectroscopy. ResultsCompared to NC group, both T2DM and MCI groups exhibited elevated glucose levels. Circulatory glucose and glutamine levels were significantly higher in T2DM subjects than in MCI and NC subjects, while glutamate levels followed a similar trend in both T2DM and MCI groups. However, in MCI patients, circulatory proline and proline-to-glutamine (PQR) and glutamate-to-glutamine was significantly elevated compared to T2DM, while glutamine was significantly reduced. ConclusionThe decreased circulatory levels of glutamine and PQR demonstrated statistically significant correlation with the severity of the cognitive impairment as assessed based on Mini Mental State Examination (MMSE) score suggested augmented utilization of glutamine in MCI patients and accumulation to proline due to active neuro-inflammatory processes and impaired mitochondrial functioning in MCI brain.

Serum thymosin beta 10 level as a potential prognosis prediction of hepatocellular carcinoma and hepatic diseases

Thymosin Beta 10 (TMSB10) is a thymosin family member that has been identified as being overexpressed in a wide variety of human cancers. This study aimed to determine the expression level of TMSB10 in sera of patients with hepatocellular carcinoma (HCC) and liver cirrhosis. And to reveal the association between TMSB10 and different stages in patients with HCC. We also wanted to know how TMSB10 is predictive in HCC patients and its relation to the Barcelona Clinic's staging system. The study included 41 HCC patients, 15 liver cirrhosis patients, and 15 normal control subjects. The enzyme-linked immunosorbent assay was used to determine serum levels of TMSB10 and alpha-fetoprotein (AFP) in serum of normal control individuals and patients with liver cirrhosis and different stages of HCC, and to evaluate the relationship of AFP with TMSB10. The TMSB10 levels in patients with HCC were statistically different than in the control group and in the different stages of HCC. We found a statistically significant difference in the distribution of TMSB10 between the three study groups (p&lt; 0.001). There was an association between TMSB10 concentration and AFP. The level of TMSB10 in the serum of the HCC subgroups was then analyzed. The TMSB10 level increased with the advance of HCC stages. The TMSB10 level in HCC patients did not correlate with levels of liver function tests including aminotransferase, aspartate aminotransferase, albumin, prothrombin, bilirubin, or alkaline phosphatase. In conclusion, serum TMSB10 levels can be used as a potential prognostic marker for clinical stages of HCC.

Radiomic detection of abnormal brain regions in tuberous sclerosis complex.

Radiomics refers to the extraction of quantitative information from medical images and is most commonly utilized in oncology to provide ancillary information for solid tumor diagnosis, prognosis, and treatment response. The traditional radiomic pipeline involves segmentation of volumes of interest with comparison to normal brain. In other neurologic disorders, such as epilepsy, lesion delineation may be difficult or impossible due to poor anatomic definition, small size, and multifocal or diffuse distribution. Tuberous sclerosis complex (TSC) is a rare genetic disease in which brain magnetic resonance imaging (MRI) demonstrates multifocal abnormalities with variable imaging and epileptogenic features. The purpose of this study was to develop a radiomic workflow for identification of abnormal brain regions in TSC, using a whole-brain atlas-based approach with generation of heatmaps based on signal deviation from normal controls. This was a retrospective pilot study utilizing high-resolution whole-brain 3D FLAIR MRI datasets from retrospective enrollment of tuberous sclerosis complex (TSC) patients and normal controls. Subjects underwent MRI including high-resolution 3D FLAIR sequences. Preprocessing included skull stripping, coregistration, and intensity normalization. Using the Brainnetome and Harvard-Oxford atlases, brain regions were parcellated into 318 discrete regions. Expert neuroradiologists spatially labeled all tubers in TSC patients using ITK-SNAP. The pyradiomics toolbox was used to extract 88 radiomic features based on IBSI guidelines, comparing tuber-affected and non-tuber-affected parenchyma in TSC patients, as well as normal brain tissue in control patients. For model training and validation, regions with tubers from 20 TSC patients and 30 normal control subjects were randomly divided into two training sets (80%) and two validation sets (20%). Additional model testing was performed on a separate group of 20 healthy controls. LASSO (least absolute shrinkage and selection operator) was used to perform variable selection and regularization to identify regions containing tubers. Relevant radiomic features selected by LASSO were combined to produce a radiomic score ω, defined as the sum of squared differences from average control group values. Region-specific ω scores were converted to heat maps and spatially coregistered with brain MRI to reflect overall radiomic deviation from normal. The proposed radiomic workflow allows for quantification of deviation from normal in 318 regions of the brain with the use of a summative radiomic score ω. This score can be used to generate spatially registered heatmaps to identify brain regions with radiomic abnormalities. The pilot study of TSC showed radiomic scores ω that were statistically different in regions containing tubers from regions without tubers/normal brain (p<0.0001). Our model exhibits an AUC of 0.81 (95% confidence interval: 0.78-0.84) on the testing set, and the best threshold obtained on the training set, when applied to the testing set, allows us to identify regions with tubers with a specificity of 0.91 and a sensitivity of 0.60. We describe a whole-brain atlas-based radiomic approach to identify abnormal brain regions in TSC patients. This approach may be helpful for identifying specific regions of interest based on relatively greater signal deviation, particularly in clinical scenarios with numerous or poorly defined anatomic lesions.

Osteocalcin: A potential marker to identify and monitor girls with rapidly progressive central precocious puberty.

To evaluate the suitability of serum osteocalcin (OC) as a marker to distinguish between rapidly and non-rapidly progressive central precocious puberty (RP-CPP and NRP-CPP), as well as its potential to assess growth rates following treatment with gonadotropin-releasing hormone agonist (GnRHa). Serum levels of OC were measured using enzyme-linked immunosorbent assays in girls diagnosed with either RP-CPP or NRP-CPP as well as in normal control subjects. Receiver operating characteristic (ROC) curve analysis was performed to determine the cut-off value for OC. Multivariate linear regression analysis was used to analyse the main influencing factors associated with OC. Serum OC levels were higher in the CPP girls when compared to normal controls (110.76 ± 43.69 vs 55.97 ± 20.96 ng/mL, P < 0.001). The level in the RP-CPP group was higher than the NRP-CPP group (153.28 ± 33.89 vs 88.33 ± 29.26 ng/mL, P < 0.001). The cut-off value of OC levels for distinguishing between RP-CPP and NRP-CPP was 107.05 ng/mL, the sensitivity was 94.7% and the specificity was 77.8%, which was superior to using the basal luteinising hormone (B-LH) levels, and the area under ROC curve (AUC) were 0.933 versus 0.695, respectively. Following 1-2 years of treatment with GnRHa for girls with CPP, both OC levels and the growth rates decreased to pre-pubertal values. B-LH levels, bone age and body weight were also significant factors, which affected OC levels. Serum OC levels may be a useful marker for distinguishing RP-CPP from NRP-CPP. In addition, it was also found to be a useful predictor for growth rate during GnRHa treatment.

Asprosin in nonalcoholic fatty liver disease and hypothyroidism: a case-control study

ABSTRACT Purpose The present study aimed to determine the serum level of asprosin, a novel glucogenic and orexigenic hormone, in NAFLD and hypothyroidism patients. Methods This is a case–control study that included three groups of age and sex-matched subjects: hypothyroid patients with NAFLD (n = 26), hypothyroid patients without NAFLD (n = 25) and normal control subjects (n = 27). A detailed clinical history was obtained, and an examination was performed. Laboratory tests included fasting plasma glucose and insulin, lipid profile, TSH, free T4, AST, ALT, albumin, and asprosin. The homeostatic model assessment of insulin resistance (HOMA-IR) score was calculated. Abdominal ultrasonography was performed to calculate the hepatorenal index and define participants with NAFLD. The data were statistically analyzed. Results There was a statistically significant difference between the three groups regarding serum asprosin concentration (p < 0.01). Serum asprosin levels were significantly higher in the patients with hypothyroidism and NAFLD compared to both other groups [2.70 ng/mL (2.17–4.10), 1.26 ng/mL (0.96–2.50), and 1.72 ng/mL (1.41–2.12), respectively]. There was no significant difference between the other two groups. There was a significant positive correlation of moderate strength between asprosin and HOMA-IR, BMI, and waist circumference. Asprosin and HOMA-IR were significantly higher in patients with NAFLD compared to subjects with normal liver (p < 0.001). Conclusion The coexistence of NAFLD and hypothyroidism is more strongly associated with increased asprosin than is the presence of hypothyroidism alone. This could be due to increased insulin resistance as a possible link.

Diagnostic Power and Reproducibility of Objective Perimetry in Glaucoma.

An objective perimetry method provides four 30-2 style reports in 8 minutes. These comprise sensitivity and delay reports for both eyes. A combined report format shows comparable diagnostic power to two forms of automated perimetry. To compare objective perimetry with two forms of standard automated perimetry (SAP) in glaucoma. The study cohort contained 40 persons with glaucoma (PwG) and 94 normal control subjects. The PwG had both perimetric and pre-perimetric eyes. Multifocal pupillographic objective perimetry was performed with the objectiveField Analyser® (OFA®), which independently assesses the visual fields of both eyes concurrently. Its OFA30 test assessed the central ±30°, and the OFA15 test assessed the central ±15°, both providing 30-2 style reports. The OFA tests were repeated two weeks apart to assess test-retest variability (TRV). OFA was compared with Matrix and HFA-SITA fast 24-2 threshold testing. Diagnostic power was quantified as area under receiver operating characteristic curves (AUROC). Test durations, Mean Defects and Pattern Standard Deviations of the 4 tests were compared. At a median of 4.09±0.02 minutes/eye the OFA tests were quicker than SAP (all P≤0.0001), 2 minutes/eye if OFA per-region sensitivities and delays are considered separately. The %AUROCs for OFA, Matrix and HFA were not significantly different, averaging 93±3% (mean±SD) in perimetric eyes, and 73±6% in pre-perimetric eyes. For moderate to severe fields OFA TRV was less than published results for SAP. OFA30 mean defects were significantly correlated between repeats (r=0.91), and with OFA15 (r=0.93, both P<0.0001). OFA provides extra functional measures in the form of per-region delays, and between-eye asymmetries. Both the OFA wide-field and macular tests provided comparable diagnostic power to SAP and better TRV in damaged eyes.

Dynamic degree centrality in stroke-induced Broca's aphasia varies based on first language: A functional MRI study.

This study sought to explore dynamic degree centrality (DC) variability in particular regions of the brain in patients with poststroke Broca aphasia (BA) using a resting-state functional magnetic resonance imaging (rs-fMRI) approach, comparing differences between Uyghur and Chinese BA patients. This study investigated two factors, language and BA status, and divided patients into four groups: Uyghur aphasia patients (UA), Uyghur normal control subjects (UN), Chinese aphasia patients (CA), and Chinese normal subjects (CN) who underwent rs-fMRI analysis. Two-way analysis of variance (ANOVA) was used to calculate the comprehensive differences in dynamic DC among these four groups. Correlations between DC and language behavior were assessed with partial correlation analyses. Two-way ANOVA revealed comparable results for the results of pairwise comparisons of dynamic DC variability among the four groups in the right middle frontal gyrus/orbital part (ORBmid.R), right superior frontal gyrus/dorsolateral, and right precuneus (PCUN.R), with results as follows: UA<UN, CA>CN, UA<CA, and UN>CN (p<.05, with the exception of the p-values for UA and UN in superior frontal gyrus/dorsolateral). In contrast, the opposite results were observed for the right calcarine fissure and surrounding cortex (CAL.R, p<.05). The observed enhancement of dynamic DC variability in ORBmid.R and PCUN.R among Chinese BA patients and in CAL.R in Uyghur BA patients may be attributable to language network restructuring. Overall, these results suggest that BA patients who use different language families may exhibit differences in the network mechanisms that characterize observed impairments of language function.

Hypoperfusion of hypothalamic subunits in medication-overuse headache using a 3D PCASL MRI

Hypothalamus is a crucial deep brain area that is responsible for the integration and coordination of various brain functions. The altered perfusion of hypothalamus during headache caused by medication-overuse headache (MOH) was previously unknown. In the current study, the altered perfusion of hypothalamic subregions in MOH patients was investigated using state-of-the-art 3D pseudo-continuous arterial spin labeling (PCASL) MR imaging. In this study, 29 normal controls subjects (NCs) and 29 MOH patients underwent 3D PCASL and brain structural MR imaging. The hypothalamus was automatically segmented into 10 subunits and the volume of each subunit was automatically determined using Freesurfer software (v7.4.1). All segmented hypothalamic subunits were converted to individual hypothalamic subunit masks. The cerebral blood flow (CBF) images were coregistered with the raw brain structural images and resliced. The CBF value of each hypothalamic subunit was extracted from the warped CBF images. The volume and CBF value of each hypothalamic subunit were analyzed using the independent sample T test and Mann–Whitney U test, receiver operating characteristic (ROC) curve analysis, and Pearson and Spearman correlation analysis. Hypothalamic subunits with significantly decreased perfusion were located in the left posterior, left tubular superior, right anterior–inferior, right tubular inferior, right tubular superior, right posterior subunit and the entire right hypothalamus [CBF value for MOH vs NC (mL/100 g·min): 48.41 ± 6.75 vs 54.08 ± 11.47, 44.44 ± 4.79 vs 48.11 ± 7.73, 41.49 (32.90, 61.46) vs 49.38 ± 10.47, 46.62 ± 7.04 vs 53.90 ± 11.75, 42.12 ± 5.74 vs 47.02 ± 9.99, 42.79 ± 5.15 vs 47.93 ± 10.48 and 43.58 ± 5.06 vs 48.65 ± 9.33, respectively] in MOH compared to NC (P < 0.05). ROC analysis for these positive subunits revealed that area under the curve was 0.658–0.693, and ROC curve for left posterior subunit had the highest specificity of 93.10% while the entire right hypothalamus had the highest sensitivity of 72.41%. Further correlation analysis showed that the CBF value of the left posterior, right anterior–inferior, right tubular superior, whole right hypothalamus presented significantly negative correlation with Hamilton Depression Scale (HAMD) score (P < 0.05). Hypoperfusion of hypothalamic subunits may contribute to the understanding of MOH pathogenesis, and the 3D PCASL could be considered as a potential diagnostic and assessment tool for MOH.

Oligodeoxynucleotides containing CpG motifs (CpG-ODN) restores immune regulatory functions of airway macrophages of patients with asthma.

Allergic asthma is characterized by the polarization of Th2 cells and impaired immune regulation. Macrophages occupy the largest proportion of airway immune cells. This study aims to discover the mechanism that hinders the immune regulatory functions of airway macrophages. In this study, macrophages were isolated from cells in bronchoalveolar lavage fluids (BALF) collected from asthma patients and normal control (NC) subjects. The results indicated that macrophages occupied the largest portion of the cellular components in BALF. The frequency of IL-10+ macrophage was significantly lower in asthma patients than in NC subjects. The expression of IL-10 in macrophages of BALF was associated with the levels of asthma-related parameters. The immune-suppressive functions of BALF M0 cells were defective in asthma patients. The inducibility of IL-10 expression was impaired in BALF macrophages of asthma patients, which could be restored by exposing to CpG. In conclusion, the induction of IL-10 in macrophages of BALF in asthma patients was impaired, and it could be restored by exposure to CpG.

Exploring the effects of matrix metalloproteinase-13 on the malignant biological behavior of tongue squamous cell carcinoma via the TNF signaling pathway based on bioinformatics methods.

Identification of the etiology, molecular mechanisms, and carcinogenic pathways of tongue squamous cell carcinoma (TSCC) is crucial for developing new diagnostic and therapeutic strategies. This study used bioinformatics methods to identify key genes in TSCC and explored the potential functions and pathway mechanisms related to the malignant biological behavior of TSCC. Gene chip data sets (i.e., GSE13601 and GSE34106) containing the data of both TSCC patients and normal control subjects were selected from the Gene Expression Omnibus (GEO) database. Using a gene expression analysis tool (GEO2R) of the GEO database, the differentially expressed genes (DEGs) were identified using the following criteria: |log fold change| >1, and P<0.05. The GEO2R tool was also used to select the upregulated DEGs in the chip candidates based on a P value <0.05. A Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, Gene Ontology (GO) function analysis, and a protein-protein interaction (PPI) network analysis were then conducted. The results were displayed using R language packages, including volcano plots, Venn diagrams, heatmaps, and enriched pathway bubble charts. Genes from the MalaCards database were compared with the candidate genes, and a thorough review of the literature was conducted to determine the clinical significance of these genes. Finally, feature gene-directed chemical drugs or targeted drugs were predicted using the Comparative Toxicogenomics Database (CTD). In total, 767 upregulated DEGs were identified from GSE13601 and 695 from GSE34106. By intersecting the upregulated DEGs from both data sets using a Venn diagram, 100 DEGs related to TSCC were identified. The enrichment analysis of the KEGG signaling pathways identified the majority of the pathways associated with the upregulated DEGs, including the Toll-like receptor signaling pathway, the extracellular matrix-receptor interaction, the tumor necrosis factor (TNF) signaling pathway, cytokine-cytokine receptor interaction, the chemokine signaling pathway, the interlukin-17 signaling pathway, and natural killer cell-mediated cytotoxicity. The PPI network and module analyses of the shared DEGs ultimately resulted in five clusters and 55 candidate genes. A further intersection analysis of the TSCC-related genes in the MalaCards database via a Venn diagram identified three important shared DEGs; that is, matrix metalloproteinase-1 (MMP1), MMP9, and MMP13. In the CTD, seven drugs related to MMP13 were identified for treating tongue tumors. This study identified key genes and signaling pathways involved in TSCC and thus extended understandings of the molecular mechanisms that underlie the development and progression of TSCC. Additionally, this study showed that MMP13 may influence the malignant biological behavior of TSCC through the TNF signaling pathway. This finding could provide a theoretical basis for research into early differential diagnosis and targeted treatment.

Clinical metabolomics investigation of rheumatoid arthritis patients receiving ayurvedic whole system intervention

BackgroundArthritis is a common clinical condition seen in Ayurveda clinics. Clinical trials have reported Ayurvedic interventions to be of benefits in many arthritic conditions including Rheumatoid Arthritis (RA). No mechanistic details however are available about how such interventions on their own or as a combination of whole system Ayurveda might be working. Objective: The study aims to evaluate simultaneously the clinical outcome of Ayurveda whole system (AWS) intervention in RA patients and identifying the serum metabolic signatures which could be useful for diagnosing the disease and monitoring treatment response. Material and methodsRA patients (n = 37) simultaneously diagnosed as Amavata fulfilling the specific inclusion and exclusion criteria were recruited in the study and were given Ayurveda whole system (AWS) intervention comprised of oral medicines, local therapy and dietary recommendation for 3 months. The clinical and serum metabolic changes were investigated for pre-treatment RA patients (baseline RA group, n = 37) and post-treatment RA patients (following treatment of 6-weeks (RA_F, n = 26) and three months (RA_T, n = 36). For comparative serum metabolomics analysis, 57 normal healthy control (HC) subjects were also involved and the serum metabolic profiles were measured at high-field 800 MHz NMR spectrometer. The serum metabolic profiles were compared using multivariate statistical analysis and discriminatory metabolic features were evaluated for diagnostic potential using receiver operating characteristic (ROC) curve analysis. ResultsA significant reduction in DAS-28 ESR, AAM Score, total swollen joints, total tender joints were observed following AWS intervention. The clinical outcomes were concordant with changes in metabolic profiles of RA patients as these were also shifting towards the normal levels following the intervention. Compared to healthy control (HC) subjects, the sera of baseline RA patients were characterised by increased circulatory level of succinate, lysine, mannose, creatine, and 3-Hydroxybutyrate (3-HB) and decreased levels of alanine. The present study also evaluated the serum metabolic ratios for their discriminatory and diagnostic potential and notably, six metabolic ratios (KHR, KThR, KVR, GHR, PTR and SHR) were found significantly altered (elevated) in baseline RA patients. However, in RA patients receiving AWS treatment, these metabolic changes showed marked convergence towards the metabolic signatures of healthy controls. ConclusionThis first of its kind study clearly shows the clinical efficacy of Ayurvedic Whole System (AWS) intervention in the management of Rheumatoid Arthritis (RA), as demonstrated by significant improvements in key clinical parameters. The intervention not only alleviated symptoms but also induced a profound metabolic shifting towards normalization; thus, underscoring the potential of AWS intervention to modulate cellular metabolism in a manner that facilitates a return to homeostasis in RA patients. However, future studies are imperative to confirm these preliminary observations and delineate the underlying mechanisms of action of intervention in cases of RA.

Prevalence, time course, and visual impact of peripapillary hyperreflective ovoid mass-like structures (PHOMS) in pediatric patients with optic nerve pathologies

BackgroundPeripapillary hyperreflective ovoid masslike structures (PHOMS) are a recently defined optical coherence tomography (OCT) finding. The purpose of this study was to characterize the presence of PHOMS and their visual significance in pediatric patients with and without optic nerve pathologies. MethodsThis retrospective study evaluated 400 patients (<18 years of age) including normal control subjects and patients with optic neuritis, papillitis, optic nerve head drusen (ONHD), and papilledema. Information on demographics, visual function, and structural parameters were obtained. ResultsPHOMS were found in 7 of 2,582 of normal control eyes (7%), 9 of 59 eyes with optic neuritis (15.3%), 58 of 76 eyes with ONHD (76.3%), 3 of 11 eyes with papillitis (27.3%), and 180 of 308 eyes with papilledema (58.4%). PHOMS were more prevalent in the papilledema (P < 0.001), ONHD (P < 0.001), and optic neuritis (P = 0.028) eyes than in control eyes. We identified 5 cases where PHOMS developed de novo. This occurred over an average of 2.3 years (range, 0.2-7.4 years). Sixteen cases of PHOMS resolved over an average of 1.1 years (range, 0.3-4.0 years). Cross-sectionally, PHOMS were not associated with visual acuity (P = 0.551), retinal nerve fiber layer thickness (P = 0.068), ganglion cell volume (P = 0.375), or visual field mean deviation (P = 0.795). ConclusionsPHOMS are present in a majority of children with papilledema or ONHD. PHOMS are dynamic and may form de novo over time with optic nerve pathology and may resolve either through treatment or atrophy. There was no relationship between the presence of PHOMS and poor visual function in our study cohort.

A novel, noninvasive, multimodal screening test for the early detection of precancerous lesions and colorectal cancers using an artificial intelligence–based algorithm.

3627 Background: Colorectal cancer (CRC) ranks as the second leading cause of cancer-related mortality worldwide, and its incidence is increasing in younger populations. Detection of early-stage CRC and its precursor lesions, such as advanced adenomas (AA), is crucial for successful treatment and reduces CRC-related mortality. Although non-invasive methods for early detection are available and increase screening compliance, their performance with respect to detection of advanced adenomas and early-stage cancers is limited. Here, we describe a novel and non-invasive stool-based approach combining diagnostic biomarkers with an algorithm generated by machine learning/artificial intelligence (ML/AI) resulting in significantly improved diagnostic performance for the detection of not only CRC, but especially precancerous lesions like AA. Methods: Data were generated from a combined cohort of stool samples collected at 10 clinical sites in Europe (COLOFUTURE study) and 21 clinical sites in the US (eAArly DETECT study). The evaluable study cohort consists of 690 subjects, including 78 CRC, 146 AA, 147 with non-advanced adenoma (AD) and 319 normal colonoscopy negative control (NC) subjects (49% female, 51% male, average age 61.8 years). Results were compared with colonoscopy and pathology findings to determine sensitivity and specificity for detection of early-stage CRC and AA vs. AD and NC. Nucleic acids were extracted from stabilized stool samples using a silica bead-based extraction method. Expression of mRNA biomarkers was analyzed utilizing Real-Time PCR. Human hemoglobin was quantified using FIT. The Emerge Quantitative Evolution ML/AI platform was leveraged to develop classifiers capable of distinguishing CRC and AA from AD and NC. Results: Applying the combined approach of non-invasive diagnostic testing with an AI/ML generated algorithm, the sensitivity for detection of CRC overall was 92.3%. In addition, this method enabled AA detection with a sensitivity of 82.2%. Specificity turned out to be 90.1 % (AD+NC). Conclusions: This innovative, non-invasive, multimodal screening strategy based on self-collected stool samples which combines mRNA expression patterns and FIT analysis with an AI/ML-generated algorithm represents a substantial improvement in the effectiveness of non-invasive CRC screening. Such improvements in usability and performance leading to reliable detection of early-stage CRC and precursor lesions, such as advanced adenomas, are required for wide-spread availability and adaption of non-invasive screening tests to accepted clinically relevant usage and to prevent the development of CRC effectively.

UHPLC-HRMS-based Multiomics to Explore the Potential Mechanisms and Biomarkers for Colorectal Cancer

BackgroundUnderstanding the metabolic changes in colorectal cancer (CRC) and exploring potential diagnostic biomarkers is crucial for elucidating its pathogenesis and reducing mortality. Cancer cells are typically derived from cancer tissues and can be easily obtained and cultured. Systematic studies on CRC cells at different stages are still lacking. Additionally, there is a need to validate our previous findings from human serum.MethodsUltrahigh-performance liquid chromatography tandem high-resolution mass spectrometry (UHPLC-HRMS)-based metabolomics and lipidomics were employed to comprehensively measure metabolites and lipids in CRC cells at four different stages and serum samples from normal control (NR) and CRC subjects. Univariate and multivariate statistical analyses were applied to select the differential metabolites and lipids between groups. Biomarkers with good diagnostic efficacy for CRC that existed in both cells and serum were screened by the receiver operating characteristic curve (ROC) analysis. Furthermore, potential biomarkers were validated using metabolite standards.ResultsMetabolite and lipid profiles differed significantly among CRC cells at stages A, B, C, and D. Dysregulation of glycerophospholipid (GPL), fatty acid (FA), and amino acid (AA) metabolism played a crucial role in the CRC progression, particularly GPL metabolism dominated by phosphatidylcholine (PC). A total of 46 differential metabolites and 29 differential lipids common to the four stages of CRC cells were discovered. Eight metabolites showed the same trends in CRC cells and serum from CRC patients compared to the control groups. Among them, palmitoylcarnitine and sphingosine could serve as potential biomarkers with the values of area under the curve (AUC) more than 0.80 in the serum and cells. Their panel exhibited excellent performance in discriminating CRC cells at different stages from normal cells (AUC = 1.00).ConclusionsTo our knowledge, this is the first research to attempt to validate the results of metabolism studies of serum from CRC patients using cell models. The metabolic disorders of PC, FA, and AA were closely related to the tumorigenesis of CRC, with PC being the more critical factor. The panel composed of palmitoylcarnitine and sphingosine may act as a potential biomarker for the diagnosis of CRC, aiding in its prevention.

EEF1A1 regulates the expression and alternative splicing of genes associated with Parkinson's disease in U251 cells.

Eukaryotic elongation factor 1A1 (eEF1A1) is an RNA-binding protein that is associated with PARK2 activity in cells, suggesting a possible role in Parkinson's disease (PD). To clear whether eEF1A1 plays a role in PD through transcriptional or posttranscriptional regulation. The GSE68719 dataset was downloaded from the GEO database, and the RNA-seq data of all brain tissue autopsies were obtained from 29 PD patients and 44 neurologically normal control subjects. To inhibit eEF1A1 from being expressed in U251 cells, siRNA was transfected into those cells, and RNA-seq high-throughput sequencing was used to determine the differentially expressed genes (DEGs) and differentially alternative splicing events (ASEs) resulting from eEF1A1 knockdown. eEF1A1 was significantly overexpressed in PD brain tissue in the BA9 area. GO and KEGG enrichment analyses revealed that eEF1A1 knockdown significantly upregulated the expression of the genes CXCL10, NGF, PTX3, IL6, ST6GALNAC3, NUPR1, TNFRSF21, and CXCL2 and upregulated the alternative splicing of the genes ACOT7, DDX10, SHMT2, MYEF2, and NDUFAF5. These genes were enriched in pathways related to PD pathogenesis, such as apoptosis, inflammatory response, and mitochondrial dysfunction. The results suggesting that eEF1A1 involved in the development of PD by regulating the differential expression and alternative splicing of genes, providing a theoretical basis for subsequent research.

Diagnostic ability of macular nerve fiber layer thickness measured by swept-source optical coherence tomography in preperimetric glaucoma.

We evaluated the diagnostic ability of macula retinal nerve fiber layer (mRNFL) thickness in preperimetric glaucoma (PPG) patients. This prospective study included 83 patients with PPG and 83 age- and refractive error-matched normal control subjects. PPG was defined as a localized RNFL defect corresponding to glaucomatous optic disc changes with a normal visual field test. We used spectral-domain (SD) optical coherence tomography (OCT) to measure the circumpapillary RNFL (cpRNFL) thickness and macular ganglion cell-inner plexiform layer (GCIPL) thickness. Swept-source (SS) OCT was used to measure cpRNFL thickness, macular ganglion cell layer + inner plexiform layer (IPL) thickness (GCL+), and macular ganglion cell layer + IPL+ mRNFL thickness (GCL++). The mRNFL thickness was defined as GCL++ minus GCL+. To evaluate the diagnostic power of each parameter, the area under the receiver operating characteristics curve (AUROC) was analyzed to differentiate PPG from the normal groups. Using SD-OCT, all GCIPL parameters and most cpRNFL parameters, except at the nasal and temporal quadrant, were significantly lower in PPG versus normal controls. PPG eyes had significantly smaller values than normal controls for all cpRNFL and GCL parameters measured by SS-OCT, except mRNFL at the superonasal area. The inferotemporal GCL++ had the largest AUROC value (0.904), followed by inferotemporal GCL+ (0.882), inferotemporal GCIPL thickness (0.871), inferior GCL++ (0.866), inferior cpRNFL thickness by SS-OCT (0.846), inferior cpRNFL thickness by SD-OCT (0.841), and inferotemporal mRNFL thickness (0.840). The diagnostic performance was comparable between inferotemporal mRNFL thickness and the best measures of GCL (inferotemporal GCL++, p = 0.098) and cpRNFL (inferior cpRNFL thickness by SS-OCT, p = 0.546). The diagnostic ability of mRNFL thickness was comparable to that of the best measures of cpRNFL and GCL analysis for eyes with PPG. Therefore, mRNFL thickness could be a new parameter to detect early structural changes in PPG.

Lipid Profile and Atherogenic Risk Assessment in Nigerian Breast Cancer Patients – A Cross-Sectional Study

Background The lipid profile and atherogenic risk indices in Nigerian breast cancer patients are largely unknown. This study evaluated the lipid profile and atherogenic risk indices of breast cancer patients in Nigeria. Methods This study involved 45 primarily diagnosed breast cancer patients and 50 normal control subjects. Total cholesterol, triglyceride, and High-density lipoprotein cholesterol (HDL-C) were measured. Low-density lipoprotein cholesterol (LDL-C) was calculated according to Friedewald formula. Atherogenic index of plasma (AIP), Atherogenic coefficient (AC), TC/HDL-C (Castelli I) and LDL-C/HDL-C (Castelli II) risk indices were all calculated. The Framingham risk assessment was calculated and categorized. Results The study group had significantly higher triglycerides (TG), and atherogenic indices than the control group (p < 0.001), while HDL-Cholesterol (HDL-C) was significantly lower in the study group (p < 0.001). Total cholesterol and LDL-Cholesterol (LDL-C) had a significant positive correlation with age (r = 0.283, p < 0.018; r = 0.272, p < 0.023); TG was significantly positively correlated with systolic and diastolic blood pressure (r = 0.320. p < 0.007; r = 0.334, p < 0.005); HDL-C had a significant negative correlation with BMI, systolic and diastolic blood pressure (r = −0.252, p < 0.035; r = −0.29, p < 0.015; r = −0.329, p < 0.005). The lipid ratios (TC/HDL-C, LDL-C/HDL-C) were significantly positively correlated with body mass index (BMI), systolic and diastolic blood pressure. The Framingham Risk Score showed that only 2 subjects in the study group (4.4%) were at a high risk of having a cardiovascular event. Conclusion Breast cancer patients have a higher prevalence of dyslipidaemia, and cardiovascular risk than the normal population.

Noninvasive PCA3 detection for screening prostate diseases using a graphene oxide-based method

Prostate Cancer Associated 3 (PCA3) as a promising biomarker to replace serum prostate-specific antigen (PSA) for differential diagnosis of benign and malignant prostate diseases. However, the detection of PCA3 in urine requires the collection of digital rectal examination (DRE) urine, which limits the application of PCA3 in screening prostate diseases. In the present study, a new reverse transcription quantitative real-time polymerase chain reaction (qRT-PCR) method was developed for PCA3 detection in non-DRE urine. The method uses the nanomaterial Graphene oxide (GO) to effectively prevent nonspecific amplification in qRT-PCR. GO-based qRT-PCR produced no nonspecific amplification. Receiver operating characteristic curve (ROC) results showed that the area under curve (AUC) of PCA3 to discriminate normal control subjects from prostate cancer (PCa) was 0.869 (95% confidence interval [CI], 0.689–1.000), and using 2.711 as the cutoff value of PCA3, the sensitivity was 81.8% and the specificity was as high as 88.9%. For prostatitis (PTIS) and PCa, the AUC value of PCA3 to distinguish them was 0.636 (95% CI, 0.396–0.877), with 81.8% sensitivity and 58.3% specificity. Compared with the 8.3% specificity of PAS, the specificity of PCA3 was improved by 50%, which suggested that PCA3, in non-DRE urine, has a significant potential application in the differential diagnosis of prostate diseases.