OBJECTIVE: Autoantibodies against hexokinase 1 (HK1) were recently proposed to be associated with diabetic macular edema (DME). We hypothesized that anti-HK1 autoantibodies can be used as DME markers and to predict DME onset.
METHODS: Serum from patients with 1) DME, 2) diabetes mellitus (DM), 3) allergies or autoimmunities, and 4) control subjects was tested for anti-HK1 and anti-hexokinase 2 (HK2) autoantibodies by immunoblotting. Patients with DM were prospectively followed for up to nine years, and the association of anti-HK1 antibodies with new-onset DME was evaluated. The vitreous humor was also tested for autoantibodies.
RESULTS: Among patients with DME, 32 % were positive for anti-HK1 autoantibodies (42 % of those with underlying type 1 DM and 31 % of those with underlying type 2 DM), and 12 % were positive for anti-HK2 autoantibodies, with only partial overlap of these two groups of patients. Anti-HK1 positive were also 7 % of patients with DM, 6 % of patients with allergies and autoimmunities, and 3 % of control subjects. The latter three groups were anti-HK2 negative. Only one of seven patients with DM who were initially anti-HK1 positive developed DME.
CONCLUSIONS: Anti-HK1 autoantibodies can be used as DME markers but fail to predict DME onset.

Detection of human-generated volatile organic compounds (VOCs) is a new pathway for assessing health. Herein, a polyvinylidene fluoride (PVDF)-based colorimetric sensor array was designed for detecting disease-related VOCs (DVOCs) within 15 min, using a complex of Cu metal-organic framework, graphene aerogel, and dyes as response materials. Fingermaps derived from 28 DVOCs were obtained for further data processing. Pattern recognition was successfully employed in the correct discrimination of 28 DVOCs in low (10 μM), medium (100 μM), and high (300 μM) concentrations. Importantly, the sensor array also presented excellent discrimination ability and application potential when detecting VOCs produced by human cancer and normal cells. In general, VOC acquisition is noninvasive and harmless, and the PVDF-based sensor arrays are simple and visual. Such advantages expand their further application potential.

Perivascular spaces (PVS) visible on brain MRI signal cerebral small vessel disease (CSVD). The coexistence of PVS with other CSVD manifestations likely increases the risk of adverse neurological outcomes. We related PVS to other CSVD manifestations and brain volumes that are markers of vascular brain injury and neurodegeneration. Framingham Heart Study (FHS) participants with CSVD ratings on brain MRI were included. PVS were rated in the basal ganglia (BG) and centrum semiovale (CSO) into grades I-IV and a category reflecting high burden in single or mixed CSO-BG regions. We related PVS to covert brain infarcts (CBI), white matter hyperintensities (WMH), cerebral microbleeds (CMB), total brain, hippocampal, and cortical gray matter volumes using adjusted multivariable regression analyses. In 2454 participants (mean age 54 ± 12 years), we observed that higher PVS burden in both BG and CSO was related to CMB in lobar and deep brain regions and increased WMH. Greater CSO PVS burden was associated with decreased total cortical gray volumes. PVS are associated with ischemic markers of CSVD and neurodegeneration markers. Further studies should elucidate the causality between PVS and other CSVD manifestations.

UNASSIGNED: In this study, we conducted an integrated study of the diagnostic value of MiR-223 in ectopic pregnancy (EP).
UNASSIGNED: We used GSE44731 downloaded from GEO and GEO2R to identify differentially expressed miRNA. The hub genes corresponding to the differential miRNA were then identified by using the Xiantao academic tool, GO (Gene Ontology), and KEGG (Kyoto Encyclopedia of Genes and Genomes). Afterward, we used the miEAA database to perform gene set enrichment analysis (GSEA) of differential miRNA, and used Xiantao academic tools again to conduct the ceRNA network based on the target genes. Protein-protein interaction (PPI) network construction and lncRNA of hub miRNA target genes were then predicted by the starbase database. For validation, the villus tissue from intrauterine pregnancy and tubal pregnancy was collected and assayed by qPCR.
UNASSIGNED: In total 19 differentially expressed miRNAs were screened out, of which MiR-223 had a relatively clear diagnostic significance. Hub genes were enriched and analyzed by GO, KEGG, and GSEA, and the results showed that regulation of NF-κB and other signaling pathways are primarily enriched in ectopic pregnancy. We also obtained 215 key genes from PPI analysis. Our ceRNA analysis indicated that LRRC75A-AS1 and PITPNA-AS1 were associated with MiR-223, and the expression of MiR-223 in qPCR was significantly high in tubal pregnancy group.
UNASSIGNED: We found that MiR-223 can be used in the diagnosis of EP. Our findings provide valuable information and direction for future research into novel targets for EP diagnosis.

Primary fibroblasts from patient\'s skin biopsies are directly isolated without any alteration in the genome, retaining in culture conditions their endogenous cellular characteristics and biochemical properties. The aim of this study was to identify a distinctive cell phenotype for potential drug evaluation in fibroblasts from Huntington\'s Disease (HD) patients, using image-based high content analysis. We show that HD fibroblasts have a distinctive nuclear morphology associated with a nuclear actin cap deficiency. This in turn affects cell motility in a similar manner to fibroblasts from Hutchinson-Gilford progeria syndrome (HGPS) patients used as known actin cap deficient cells. Moreover, treatment of the HD cells with either Latrunculin B, used to disrupt actin cap formation, or the antioxidant agent Mitoquinone, used to improve mitochondrial activity, show expected opposite effects on actin cap associated morphological features and cell motility. Deep data analysis allows strong cluster classification within HD cells according to patients\' disease severity score which is distinct from HGPS and matching controls supporting that actin cap is a biomarker in HD patients\' cells correlated with HD severity status that could be modulated by pharmacological agents as tool for personalized drug evaluation.

In Saudi Arabia, the epidemiology of rheumatoid arthritis (RA) is not well studied and is marked by inconsistencies in clinical diagnosis. Therefore, in this study, we explored the prevalence, clinical characteristics, and diagnostic validity of a prediction score based upon disease markers in orthropedic clinics\' patients in the Madinah region of Saudi Arabia.
The clinical data for this retrospective cross-sectional study were retrieved from the database registry of orthopedic clinics in selected hospitals of the Medinah province of Saudi Arabia. Sociodemographic features, disease markers and the clinical characteristics were collected for a period of 6 months, from December 1, 2020, to May 31, 2021. The prediction score was generated from the sum of disease markers, coded as dichotomous variables.
The total sample size of our study was 401. The prevalence of RA in the study subjects (n = 401) was 14.46% (n = 58). Among RA patients, the majority were females (60.3%). Painful joints (69%) and swollen joints (51.7%) were the most common clinical complaints among RA patients. RA patients suffered from arthritis (51.7%) and experienced fatigue (46.6%), weight loss (44.8%), and loss of appetite (41.4%). Diabetes (55.2%) was the most common comorbidity in the RA patients. The sensitivity and specificity of the prediction score at the criterion score of 2.5 were 67.3% and 63.0%, respectively. The area under the curve was 0.69 (95% CI [0.62-0.76]).
There was a moderately high prevalence of RA in patients visiting the orthropedic clinics of the selected hospitals of Madinah region of Saudi Arabia. The diagnostic validity of the prediction score, though promising, was slightly lower than the acceptable range.

Endometriosis is a common gynecological disorder defined as the presence of endometrial-like tissue (glands and stroma) outside the uterus. The etiopathogenesis of endometriosis is still poorly recognized. It is speculated that stage-specific embryonic antigen 1 (SSEA-1)-positive stem-like glandular epithelial cells may contribute to the development of the disease. The synthesis of SSEA-1 is mediated by fucosyltransferase 4 encoded by the FUT4 gene. Therefore, this study aimed to evaluate the specific expression of FUT4 mRNA in biopsies of the endometrium from women with and without endometriosis. FUT4 mRNA levels were examined in 49 women with laparoscopically confirmed endometriosis and 28 controls by means of quantitative reverse-transcription polymerase chain reaction (qRT-PCR). The expression of FUT4 mRNA was significantly increased in the endometrium of patients with endometriosis when compared to the controls (p < 0.0001). Expression of FUT4 mRNA in the endometrium was correlated with the severity of endometriosis (rs = 0.5579, p < 0.0001); however, there were no differences in endometrial FUT4 mRNA expression when comparing endometriotic lesions from various locations. The discriminatory ability of FUT4 mRNA expression was evaluated by receiver-operating characteristics (ROC), which showed high statistical significance (AUC = 0.90, p < 0.0001), thus indicating that an increased level of endometrial FUT4 mRNA may serve as a specific marker for endometriosis.

Existing data suggest that people with multiple sclerosis (pwMS) are at an elevated risk for experiencing olfactory impairment. We investigated if smell dysfunction can be used as an MS disease marker. This is a cross-sectional, case−control study. All data were collected prospectively from 171 participants, 115 pwMS and 56 controls (age and sex stratified and matched to the patients), who reported smell, taste, and nasal breathing, and completed the Greek-validated questionnaires for nasal obstruction (NOSE), nasal-symptoms QoL (SNOT-22), and olfaction-associated QoL (QOD). The smell was assessed with the “Sniffin’ sticks” (odor threshold (OT), discrimination (OD), identification (OI) test, and total TDI). We recorded the pwMS disease characteristics (Expanded Disability Status Scale-EDSS, the disease type and duration), cognitive function, emotional status, fatigue, and impact of MS in everyday activities. A TDI < 30.75 (hyposmia) was detected in 30.8% of the patients. The patients’ OD and TDI scores were significantly lower than the controls’ (p = 0.005, and 0.015, respectively). The hyposmia correlated with disease severity and duration. The EDSS score correlated negatively with OD (r = −0.299, p = 0.001) and TDI (r = −0.242, p = 0.01). The disease duration correlated negatively with OD (r = −0.305, p = 0.001, OI (r = −0.253, p = 0.008) and TDI (r = −0.3, p = 0.001). The information processing speed (SDMT) correlated with OD, OT, and TDI (r = 0.302, p = 0.002; r = 0.242, p = 0.016; r = 0.326, p = 0.001). The olfactory function is changing in MS in accordance with disease progression.

Cerebral small vessel disease (CSVD) increases with age and is associated with stroke and cognitive decline. Enlarged Perivascular Spaces (ePVS) is an emerging marker of CSVD, but its prevalence over the life span remain unclear. We characterized the age and sex-specific prevalence of ePVS and relation to age-specific risk factors, in a large community-based sample.
We included 3,710 Framingham Heart Study participants with available brain MRI (average age 61.4±14.6, 46% men). ePVS burden was rated in the centrum semiovale (CSO) and basal ganglia (BG) regions. Individual vascular risk factors were related to ePVS burden in the CSO, BG, and mixed CSO-BG regions using multivariable adjusted ordinal logistic regression analysis.
Severe ePVS prevalence increased with age in men and women, and paralleled increase in vascular risk factors, and prevention treatment use. Older age, hypertension (and resulting higher treatment use), higher systolic and diastolic blood pressure, and smoking were associated with higher burden of ePVS in the CSO, BG and mixed regions.
Our observations reinforce the hypothesis that ePVS may be a marker of aging-driven brain vascular pathologies, and its association with vascular risk factors support their role as CSVD imaging biomarker.

The employment of liquid chromatography-mass spectrometry (LC-MS) untargeted and targeted metabolomics has led to the discovery of novel biomarkers and improved the understanding of various disease mechanisms. Numerous strategies have been reported to expand the metabolite coverage in LC-MS-untargeted and targeted metabolomics. To improve the sensitivity of low-abundance or poor-ionized metabolites for reducing the amount of clinical sample, chemical derivatization methods are used to target different functional groups. Proper sample preparation is beneficial for reducing the matrix effect, maintaining the stability of the LC-MS system, and increasing the metabolite coverage. Machine learning has recently been integrated into the workflow of LC-MS metabolomics to accelerate metabolite identification and data-processing automation, and increase the accuracy of disease classification and clinical outcome prediction. Due to the rapidly growing utility of LC-MS metabolomics in discovering disease markers, this review will address the recent advances in the field and offer perspectives on various strategies for expanding metabolite coverage, chemical derivatization, sample preparation, clinical disease markers, and machining learning for disease modeling.