Search Results (192)

Background/Objectives: Diabetic neuropathy (DN) is one of the most common complications of type 2 diabetes mellitus (T2DM), involving complex metabolic, vascular, and epigenetic mechanisms. MicroRNA-210-3p (miR-210-3p), a hypoxia-responsive molecule, has been implicated in various diabetic complications, but its role in DN is not well defined. This study aimed to investigate the relationship between miR-210-3p expression, measured as delta Ct (ΔCt), and the presence and type of diabetic neuropathy, as well as correlations with corneal nerve parameters assessed by corneal confocal microscopy (CCM). Methods: Eighty patients with T2DM were stratified into four groups: no neuropathy, autonomic neuropathy, peripheral neuropathy, and combined neuropathy. Expression of miR-210-3p was quantified using RT-qPCR, and CCM was used to measure corneal nerve fiber density (CNFD), length (CNFL), and branch density (CNBD). Results: ΔCt values were significantly lower in patients with combined neuropathy compared to those without neuropathy, indicating higher miR-210-3p expression. Intermediate values were observed in autonomic and peripheral neuropathy groups. CCM parameters were significantly reduced in patients with DN. ΔCt was inversely correlated with neuropathy severity but positively associated with diabetes duration. Conclusions: These findings suggest that miR-210-3p may serve as a biomarker of nerve damage and cellular stress in diabetes, and that combining gene expression profiling with CCM could improve DN diagnosis and monitoring. Full article

Fig (Ficus carica L.), a deciduous fruit tree that belongs to the Moraceae family, is cultivated worldwide as an important fruit crop for raw and processed foods. Quantitative real-time PCR (RT-qPCR) is a widely used method in F. carica to elucidate expression of genes related to various physiological responses. However, no studies have identified appropriate reference genes for RT-qPCR normalization in F. carica. In this study, 12 genes were selected from the F. carica genome as candidate reference genes for normalizing target gene expression. All candidate genes exhibited high amplification efficiency and specificity in the absence of primer dimers or extra PCR amplicons. The expression levels of the candidate genes were measured in three different plant tissues (fruit, leaf, and stem) under fungal pathogen infection using RT-qPCR. Their expression stabilities were evaluated using four computational algorithms: geNorm, Normfinder, delta-Ct, and BestKeeper. The RefFinder program was also used to calculate the geometric mean of the stability rankings obtained from these algorithms. The comprehensive ranking revealed that FcYLS8, FcPP2A, and FcAP2M were the most stable reference genes under biotic stress in the fruits, leaves, and stems, respectively. In contrast, traditional reference genes such as FcACT2, FcEF-1α, FcGAPDH, FcUBC21, and FcUBQ5 exhibited relatively low expression stability in all tested tissues. This study identified and validated stable reference genes for RT-qPCR normalization in F. carica, thus providing a valuable resource for accurate gene expression studies under biotic stress and highlighting the importance of validating reference genes to ensure reliable and reproducible RT-qPCR analysis. Full article

Reverse transcription quantitative PCR (RT-qPCR) is a powerful and widely used technique for quantifying alterations in gene expression. Cassava bacterial blight caused by Xanthomonas phaseoli pv. manihotis severely constraints cassava growth and yield. Accurate evaluation of the expression levels of genes following infection by X. phaseoli pv. manihotis is crucial for the identification of potential cassava resistance genes. In this study, thirty-two novel potential reference genes were screened from the cassava–X. phaseoli pv. manihotis transcriptome. Their expression, along with that of seven literature-reported cassava reference genes, was evaluated in two susceptible and two resistant cassava varieties at six time points post-inoculation by X. phaseoli pv. manihotis through RT-qPCR analysis. The stability of thirty-nine candidate reference genes was assessed by four algorithms: geNorm, NormFinder, Delta Ct, and RefFinder. The results demonstrated that serving as new reference genes, MehnRNPR and MePRPF38B consistently exhibited superior expression stability over seven established reference genes under X. phaseoli pv. manihotis infection, regardless of the susceptible or resistant cassava varieties. The reliability of the reference genes was validated by assessing the expression pattern of MeNAC35 and MeSWEET10a under X. phaseoli pv. manihotis infection. The findings of this study provide valuable insights for advancing the precision of the quantification of cassava candidate genes associated with disease resistance. Full article

Background/Objectives: To explore the prognostic potential of gross tumor volume (GTV)-based delta-radiomic features from CT simulation scans in patients with locally advanced unresectable vulvar cancer. Methods: A total of 21 patients (between 2019 and 2024) undergoing definitive radiotherapy were included, with baseline and post-phase I (after 25 fractions) CT simulation scans analyzed. Radiomic features (n = 107) were extracted from GTVs using PyRadiomics, and delta features were calculated as the relative change between scans. A multi-step selection pipeline (univariable Cox screening (p < 0.10), correlation filtering, and Lasso–Cox) was applied for each endpoint: local control (LC), regional control, distant metastasis-free survival, progression-free survival, and overall survival (OS). Model discrimination was assessed via 500-iteration bootstrapped concordance index (C-index), and calibration was plotted at 24 months. Results: Median follow-up was 50.0 months. The 2-year LC and OS rates were 56.2% and 55.9%, respectively. Final multivariable models retained a sole texture Δ feature for LC (HR = 2.62, 95% CI = 1.05–6.52, p = 0.039; C-index = 0.748) and six Δ features for OS (C-index = 0.864). No features were retained for other endpoints. For LC, increased run-length non-uniformity after phase I predicted poorer control. For OS, increased texture/shape complexity predicted worse survival, whereas increased uniformity predicted better survival. Conclusions: CT-based delta-radiomic features, particularly shape and texture metrics, may predict LC and OS in unresectable vulvar cancer. Despite the small sample size, these findings highlight the potential for delta-radiomics as a noninvasive biomarker for risk stratification. Validation in larger cohorts and exploring potential in adaptive radiotherapy are warranted. Full article

Accurate normalization of qRT-PCR data in pulmonary tuberculosis (TB) research requires reference genes whose expression is invariant across clinically relevant matrices, yet no studies have addressed this in lesion tissue and blood concurrently. We assessed the expression stability of eight popular housekeeping genes—ACTB, B2M, GAPDH, HPRT1, PPIA, RPL13A, UBC and YWHAZ—in lung tuberculomas and peripheral blood mononuclear cells (PBMCs) from TB patients. Standardized extraction and amplification yielded Cq values that were ranked by geNorm, NormFinder, BestKeeper and comparative Delta CT, with consensus scores generated in RefFinder; and correlation analysis was conducted in order to select the most suitable genes to work collectively for future normalization. The consensus analysis placed PPIA, YWHAZ and HPRT1 at the top, while GAPDH and UBC were the least stable. Our findings endorse a three-gene panel (PPIA, YWHAZ, HPRT1) for robust normalization of host gene-expression studies in both lesion tissue and PBMCs in pulmonary TB and highlight the necessity of context-specific reference-gene validation. Full article

Background: Radiomics enables the extraction of quantitative imaging biomarkers that can non-invasively capture tumor biology and treatment response. Delta-radiomics, by assessing temporal changes in radiomic features, may improve reproducibility and reveal early therapy-induced alterations. This study investigated whether delta-texture features from contrast-enhanced CT could predict progression-free survival (PFS) and overall survival (OS) in patients with metastatic colorectal cancer (mCRC) liver metastases treated with cetuximab rechallenge plus avelumab within the CAVE trial. Methods: This retrospective substudy included 42 patients enrolled in the multicenter CAVE phase II trial with evaluable liver metastases on baseline and first restaging CT. Liver lesions were manually segmented by two readers, and radiomic features were extracted according to IBSI guidelines. Delta-values were calculated as relative changes between baseline and post-treatment scans. Reproducibility (ICC > 0.70), univariate and multivariable analyses, ROC/AUC, bootstrap resampling, cross-validation, and decision curve analysis were performed to evaluate predictive performance and clinical utility. Results: Among reproducible features, delta-GLCM Homogeneity emerged as the most robust predictor. A decrease in homogeneity independently correlated with longer PFS (HR = 0.32, p = 0.003) and OS (HR = 0.41, p = 0.021). The combined clinical–radiomic model achieved good discrimination (AUC 0.94 training, 0.74 validation) and stable performance on internal validation (bootstrap C-index 0.77). Decision curve analysis indicated greater net clinical benefit compared with clinical variables alone. Conclusions: This exploratory study provides preliminary evidence that delta-GLCM Homogeneity may serve as a reproducible imaging biomarker of response and survival in mCRC patients receiving cetuximab plus avelumab rechallenge. If validated in larger, independent cohorts, delta-radiomics could enable early identification of non-responders and support personalized treatment adaptation in immuno-targeted therapy. Given the small sample size, the potential for overfitting should be considered. Future work should prioritize prospective multicenter validation with a pre-registered, locked model and explore multimodal integration (radiogenomics, circulating biomarkers, and AI-driven fusion of imaging with clinical/omic data) to strengthen translational impact. Beyond imaging advances, these findings align with broader trends in personalized oncology, including response-adaptive strategies, multimodal biomarker integration, and AI-enabled decision support. Full article

Background: The Delta variant of SARS-CoV-2 virus, one of the alarming variants of concern (VOC) with a distinct mutation characteristic, was immensely detrimental and a significant cause of the prolonged pandemic waves. This study aimed to analyze the genetic characteristics of the predominant Delta variant in acute febrile illness (AFI) patients in Ethiopia. Method: Nasopharyngeal swab samples were collected from AFI patients in four hospitals from February 2021 to June 2022 and tested for SARS-CoV-2 by using RT-qPCR. Of 101 positive samples, 48 stored specimens were re-tested, and 26 with sufficient RNA quality (Ct < 30) were sequenced using whole-genome sequencing to identify variants of concern, specific virus lineages and mutation features. Result: Delta variants (21J clade) were found predominant among all the sequenced SARS-CoV-2 isolate (80.8%, 21/26). AY.120 (46.2%) and B.1.617.2 (26.9%) were the predominant sub-lineages of the Delta variant. Omicron (21k, Pango BA.1.1/BA.1.17/BA.1) and Alpha (20I, Pango B.1.1.7) variants accounted for 11.5% and 7.7% of the total sequenced samples. Phylogenetic analysis showed evidence of local transmission and possible multiple introductions of SARS-CoV-2 VOCs in Ethiopia. The number of mutations increases dramatically from Alpha (~35 avg) to Delta (~42 avg) to Omicron (~56 avg). The Delta variant revealed a spike mutation on L452R and T478K and P681R, and was characterized by the double deletion E156-F157- in Spike protein. Conclusions: The findings are indicative of a gradual change in the genetic coding of the virus underscoring the importance of ongoing genomic surveillance to track the evolution and spread of SARS-CoV-2 and other emerging virus. Full article

Background/Objectives: Systemic sclerosis-associated interstitial lung disease (SSc-ILD) and chronic obstructive pulmonary disease (COPD) are linked to multi-organ vulnerability involving the lungs, heart, and kidneys. This study aimed to compare the annual changes in pulmonary, cardiac, and renal parameters in patients with SSc-ILD and COPD across three consecutive years, using both individual biomarkers and integrated composite profiles. Methods: This observational longitudinal study included repeated assessments in 2023, 2024, and 2025. Functional, laboratory, and imaging parameters were collected: 6-min walk test (6MWT), SpO₂ (pre-/post-exercise), spirometry/CT lung volumes, gas exchange (pO₂/pCO₂/lactate), echocardiography [left ventricular ejection fraction (LVEF), estimated systolic pulmonary artery pressure (sPAP)], cardiac biomarkers (NT-proBNP, MR-proANP, hsTnT), renal markers [eGFR, creatinine, albuminuria, albumin-to-creatinine ratio (ACR)], heart rate variability (HRV), and renal CT densitometry. All markers were standardized (z-scores, higher values = worse). Subprofiles were generated and aggregated into three integrated profiles (cardiac, renal, pulmonary). Within-group dynamics were analyzed using the Wilcoxon signed-rank test (year-to-year deltas), between-group comparisons with the Mann–Whitney U test, effect sizes via Cliff’s delta, and multiple testing correction with the Benjamini–Hochberg false discovery rate (FDR). Results: Exercise tolerance declined in both groups: by 2025, 6MWT distance decreased by −10 m in SSc-ILD (p = 0.006; q = 0.010) and −20 m in COPD (p = 0.002; q = 0.004); post-exercise SpO₂ fell in both cohorts (both p < 0.001; q < 0.001). MR-proANP remained consistently higher in SSc-ILD across all years (p ≤ 0.005; q ≤ 0.028). sPAP increased in both groups, reaching higher values in COPD by 2025 (p = 0.007; q = 0.033). NT-proBNP and hsTnT increased over time, while eGFR declined, and ACR rose in both cohorts (both p < 0.001; q < 0.001). HRV (HF/total power) decreased by 2025. Composite profiles showed: in 2023, the cardiac profile was worse in SSc-ILD (δ ≈ 0.27; p = 0.011; q = 0.048), but differences diminished by 2025; the renal profile was initially worse in SSc-ILD but later shifted unfavorably in COPD; the pulmonary profile showed no consistent between-group differences. Conclusions: Over three years, patients with SSc-ILD and COPD exhibited concordant deterioration in pulmonary, cardiac, and renal function. Distinct leading markers emerged: desaturation during exercise and neurohormonal activation (MR-proANP) in SSc-ILD, versus reduced 6MWT and higher sPAP in COPD. These findings support the need for integrated monitoring of the cardio–pulmo–renal continuum. Limitations include the observational design, multiple comparisons, and absence of advanced repeated-measures modeling. Full article

Background: Non-smokers and individuals with minimal smoking history represent a significant proportion of lung cancer cases but are often overlooked in current risk assessment models. Pulmonary nodules are commonly detected incidentally—appearing in approximately 24–31% of all chest CT scans regardless of smoking status. However, most established risk models, such as the Brock model, were developed using cohorts heavily enriched with individuals who have substantial smoking histories. This limits their generalizability to non-smoking and light-smoking populations, highlighting the need for more inclusive and tailored risk prediction strategies. Purpose: We aimed to develop a longitudinal radiomics-based approach for lung cancer risk prediction, integrating time-varying radiomic modeling to enhance early detection in USPSTF-ineligible patients. Methods: Unlike conventional models that rely on a single scan, we conducted a longitudinal analysis of 122 patients who were later diagnosed with lung cancer, with a total of 622 CT scans analyzed. Of these patients, 69% were former smokers, while 30% had never smoked. Quantitative radiomic features were extracted from serial chest CT scans to capture temporal changes in nodule evolution. A time-varying survival model was implemented to dynamically assess lung cancer risk. Additionally, we evaluated the integration of handcrafted radiomic features and the deep learning-based Sybil model to determine the added value of combining local nodule characteristics with global lung assessments. Results: Our radiomic analysis identified specific CT patterns associated with malignant transformation, including increased nodule size, voxel intensity, textural entropy, as indicators of tumor heterogeneity and progression. Integrating radiomics, delta-radiomics, and longitudinal imaging features resulted in the optimal predictive performance during cross-validation (concordance index [C-index]: 0.69), surpassing that of models using demographics alone (C-index: 0.50) and Sybil alone (C-index: 0.54). Compared to the Brock model (67% accuracy, 100% sensitivity, 33% specificity), our composite risk model achieved 78% accuracy, 89% sensitivity, and 67% specificity, demonstrating improved early cancer risk stratification. Kaplan–Meier curves and individualized cancer development probability functions further validated the model’s ability to track dynamic risk progression for individual patients. Visual analysis of longitudinal CT scans confirmed alignment between predicted risk and evolving nodule characteristics. Conclusions: Our study demonstrates that integrating radiomics, sybil, and clinical factors enhances future lung cancer risk prediction in USPSTF-ineligible patients, outperforming existing models and supporting personalized screening and early intervention strategies. Full article

The present study aimed to identify genes encoding enzymes involved in the biotransformation of monoterpenoid (–)-isopulegol by Rhodococcus rhodochrous IEGM 1362. This strain is able to transform (–)-isopulegol with formation of two novel metabolites with promising antitumor and analeptic activities. Cell fractions of rhodococci and specific inhibitor of cytochrome P450-dependent oxygenase activity were used to establish the localization and type of biotransformation enzymes. The expression of nine CYP450 genes selected by bioinformatics analysis was analyzed by quantitative real-time PCR (qRT-PCR). Selection of optimal reference genes for normalization of qRT-PCR results was performed using BestKeeper, Normfinder, geNorm, Delta CT, and RefFinder algorithms. As a result of these studies, the role of CYP450 enzyme complexes in the biotransformation of (–)-isopulegol was confirmed, and their cytoplasmic localization was established. The genes encoding DNA gyrase subunit B (gyrB) and protein translocase subunit A (secA) were selected as the most stable reference genes. The induced expression of the gene encoding CYP450 hydroxylase in the presence of (–)-isopulegol was determined. The obtained data allow us to identify the specific CYP450 enzyme involved in (–)-isopulegol biotransformation by R. rhodochrous IEGM 1362 and lay the foundation for further studies of molecular and genetic mechanisms of monoterpenoid biotransformation. Full article

This paper presents a low-power continuous-time delta-sigma (CT-DS) analog-to-digital converter (ADC) for use in high-sensitivity automotive-grade sub-1 GHz receivers in emerging wireless sensors network applications. The proposed ADC employs a third-order Cascade of Integrators FeedForward and Feedback (CIFF-B) loop filter operating at a sampling frequency of 150 MHz to achieve high energy efficiency and robust noise shaping. A low-noise phase-locked loop (PLL) is integrated to provide high-precision clock signals. The loop filter combines active-RC and GmC integrators with the source degeneration technique to optimize power consumption and linearity. To minimize complexity and enhance stability, a 1-bit quantizer with isolation switches and return-to-zero (RZ) digital-to-analog converters (DACs) are used in the modulator. With a 500 kHz bandwidth, the sensitivity of the receiver is −105.5 dBm. Fabricated in a 180 nm standard CMOS process, the prototype achieves a peak signal-to-noise ratio (SNR) of 76.1 dB and a signal-to-noise and distortion ratio (SNDR) of 75.3 dB, resulting in a Schreier figure of merit (FoM) of 160.7 dB based on SNDR, while consuming only 0.8 mA from a 1.8 V supply. Full article

The harsh, cold, and dry winters in northern China necessitate burying wine grapevines (Vitis vinifera) for winter protection. In this study, we screened for stably expressed reference genes in wine grapes (V. vinifera) under low-temperature stress at 4 °C (chilling) and −15 °C (freezing). A cold-resistant line “Hanniang 1301” and its cold-sensitive parent ‘Cabernet Sauvignon’ were treated at 4 °C and −15 °C for varying durations. Nineteen candidate reference genes were selected for qPCR analysis. Gene stability under chilling and freezing stress was evaluated using the following five algorithms: Delta CT (ΔCt), geNorm, NormFinder, BestKeeper, and RefFinder. The optimal reference genes under chilling (4 °C) and freezing (−15 °C) conditions were pairs with dual-reference combinations. However, the genes selected differed between chilling and sub-freezing temperatures. For chilling stress (4 °C), EF1α-1 and EF1α-2 were the most stable. Meanwhile, for freezing stress (−15 °C), GAPDH and Actin were optimal. We identified suitable reference genes for gene expression studies in wine grapes under low-temperature stress; this establishes a theoretical foundation for optimizing reference gene selection in plants under other abiotic stresses. Full article

Background: Severe glenoid bone loss presents a major challenge in both primary and revision reverse shoulder arthroplasty (RSA). Standard implants often fail to achieve reliable fixation in these cases. Custom-made, 3D-printed glenoid components have emerged as a potential solution, offering anatomically tailored fit and fixation. This study evaluates the clinical and radiographic outcomes of custom-made glenoid implants in managing severe glenoid bone loss. Methods: A retrospective, multicenter study was conducted on 23 shoulders (11 primary and 12 revision RSAs) that received a custom-made glenoid component using the Enovis ProMade System (San Daniele del Friuli, Udine, Italy) between 2017 and 2022, with a minimum follow-up of 24 months. Preoperative planning utilized CT-based 3D modeling to design implants with patient-specific instrumentation. Clinical outcomes (ROM, pain, Constant–Murley score) and radiographic results were assessed. Statistical comparisons were made between primary and revision groups. Results: Both groups demonstrated significant improvements in shoulder mobility, pain relief, and Constant–Murley scores (all p < 0.001), with no significant differences between primary and revision groups in delta scores. Radiographically, no loosening was observed, with minimal radiolucent lines and low complication rates. Four cases of instability occurred, all in the revision group, with only one requiring conversion to hemiarthroplasty. No differences in radiographic outcomes were observed between groups. Conclusions: Custom-made glenoid implants provide a reliable solution for severe glenoid bone loss in both primary and revision RSA, yielding consistent functional improvement and implant stability. Further prospective studies with larger cohorts and long-term follow-up are warranted to confirm these findings and assess cost-effectiveness. Full article

Background and Purpose: Stratification based on specific image biomarkers applicable in clinical settings could help optimize treatment outcomes for recurrent non-small cell lung cancer patients. For this purpose, we aimed to determine the clinical impact of positive delta changes (any difference above zero > 0) between baseline [¹⁸F]FDG PET/CT metrics before the first treatment course and reirradiation. Material/Methods: Forty-seven patients who underwent thoracic reirradiation with curative intent at our institute between 2013 and 2021 met the inclusion criteria. All patients had histologically verified NSCLC, ECOG (Eastern Cooperative Oncology Group) ≤ 2, and underwent [¹⁸F]FDG PET/CT for initial staging and re-staging before primary radiotherapy and reirradiation, respectively. The time interval between radiation treatments was at least nine months. Quantitative metabolic volume and intensity parameters were measured before first irradiation and before reirradiation, and the difference above zero (>0; delta change) between them was statistically correlated to locoregional control (LRC), progression-free survival (PFS), and overall survival (OS). Results: Patients were followed for a median time of 33 months after reirradiation. The median OS was 21.8 months (95%-CI: 16.3–27.3), the median PFS was 12 months (95%-CI: 6.7–17.3), and the median LRC was 13 months (95%-CI: 9.0–17.0). Multivariate analysis revealed that the delta changes in SULpeak, SUVmax, and SULmax of the lymph nodes significantly impacted OS (SULpeak p = 0.017; SUVmax p = 0.006; SULmax p = 0.006), PFS (SULpeak p = 0.010; SUVmax p = 0.009; SULmax p = 0.009), and LRC (SULpeak p < 0.001; SUVmax p = 0.003; SULmax p = 0.003). Conclusions: Delta changes in SULpeak, SUVmax, and SULmax of the metastatic lymph nodes significantly impacted all clinical endpoints (OS, PFS and LRC) in recurrent NSCLC patients treated with reirradiation. Hence, these imaging biomarkers could be helpful with regard to patient selection in this challenging clinical situation. Full article

Asia minor bluegrass (Polypogon fugax), a widespread Poaceae weed, exhibits broad tolerance to abiotic stresses. Validated reference genes (RGs) for reliable RT-qPCR normalization in this ecologically and agriculturally significant species remain unidentified. This study identified eight candidate RGs using transcriptome data from seedling tissues. We assessed the expression stability of these eight RGs across various abiotic stresses and developmental stages using Delta Ct, BestKeeper, geNorm, and NormFinder algorithms. A comprehensive stability ranking was generated using RefFinder, with validation performed using the target genes COR413 and P5CS. Results identified EIF4A and TUB as the optimal RG combination for normalizing gene expression during heat stress, cold stress, and growth stages. EIF4A and ACT were most stable under drought stress, EIF4A and 28S under salt stress, and EIF4A and EF-1 under cadmium (Cd) stress. Furthermore, EIF4A and UBQ demonstrated optimal stability under herbicide stress. Additionally, application of validated RGs revealed higher acetyl-CoA carboxylase gene (ACCase) expression in one herbicide-resistant population, suggesting target-site gene overexpression contributes to resistance. This work presents the first systematic evaluation of RGs in P. fugax. The identified stable RGs provide essential tools for future gene expression studies on growth and abiotic stress responses in this species, facilitating deeper insights into the molecular basis of its weediness and adaptability. Full article