Polymer-based antibody mimetics (iBodies) target human PD-L1 and function as a potent immune checkpoint blocker.

Immune checkpoint blockade (ICB) using monoclonal antibodies against programmed cell death protein 1 (PD-1) or programmed death-ligand 1 (PD-L1) is the treatment of choice for cancer immunotherapy. However, low tissue permeability, immunogenicity, immune-related adverse effects, and high cost could be possibly improved using alternative approaches. On the other hand, synthetic low-molecular-weight (LMW) PD-1/PD-L1 blockers have failed to progress beyond in vitro studies, mostly due to low binding affinity or poor pharmacological characteristics resulting from their limited solubility and/or stability. Here, we report the development of polymer-based anti-human PD-L1 antibody mimetics (α-hPD-L1 iBodies) by attaching the macrocyclic peptide WL12 to a N-(2-hydroxypropyl)methacrylamide copolymer. We characterized the binding properties of iBodies using surface plasmon resonance, enzyme-linked immunosorbent assay, flow cytometry, confocal microscopy, and a cellular ICB model. We found that the α-hPD-L1 iBodies specifically target human PD-L1 (hPD-L1) and block the PD-1/PD-L1 interaction in vitro, comparable to the atezolizumab, durvalumab, and avelumab licensed monoclonal antibodies targeting PD-L1. Our findings suggest that iBodies can be used as experimental tools to target hPD-L1 and could serve as a platform to potentiate the therapeutic effect of hPD-L1-targeting small molecules by improving their affinity and pharmacokinetic properties.

Epigenetic modulation of cytokine expression in Mycobacterium tuberculosis-infected monocyte derived-dendritic cells: Implications for tuberculosis diagnosis.

BACKGROUND: To delineate alterations in DNA methylation at high resolution within the genomic profile of monocyte-derived-dendritic cells (mo-DCs) in connection with Mycobacterium tuberculosis (MTB) infection, with particular emphasis on pro/ anti-inflammatory genes. METHODS: In the context of this investigation, mo-DCs were infected by various active strains of MTB (Rifampicin-resistant [RIFR], H37Rv, multidrug-resistant [MDR], and extensively drug-resistant [XDR]). Subsequently, the pro/anti-inflammatory hub gene expression levels within the IL-6, IL-12, IFN-γ, IL-1ß, TNF-α, and IL-10 pathways were evaluated employing real-time reverse transcription-polymerase chain reaction (RT-PCR). Additionally, the effects of MTB infection on mo-DC protein expression were examined through western blot analysis. The methylation status (%) of TNF-α and IL-10 was considered through Methylation Sensitive-High Resolution Melting (MS-HRM). RESULTS: The results revealed an up-regulation of all pro-inflammatory genes among all groups, with TNF-α exhibiting the highest expression level. Conversely, the anti-inflammatory gene (IL-10) showed a down-regulated expression level. Furthermore, the DNA methylation status (%) of TNF-α decreased significantly among all the groups (P < 0.001), although there were no notable distinctions in the DNA methylation status (%) of IL-10 when compared to the control group (P > 0.05). CONCLUSION: MTB infection induces DNA methylation changes in mo-DCs. The hypo-methylation of TNF-α may induce the up-regulation of this gene. This correlation revealed that the more resistant the MTB strain (XDR) is, the lower the methylation status (%) in the TNF-α gene.

Hybrid WT-CNN-GRU-based model for the estimation of reservoir water quality variables considering spatio-temporal features.

Water quality indicators (WQIs), such as chlorophyll-a (Chl-a) and dissolved oxygen (DO), are crucial for understanding and assessing the health of aquatic ecosystems. Precise prediction of these indicators is fundamental for the efficient administration of rivers, lakes, and reservoirs. This research utilized two unique DL algorithms-namely, convolutional neural network (CNNs) and gated recurrent units (GRUs)-alongside their amalgamation, CNN-GRU, to precisely gauge the concentration of these indicators within a reservoir. Moreover, to optimize the outcomes of the developed hybrid model, we considered the impact of a decomposition technique, specifically the wavelet transform (WT). In addition to these efforts, we created two distinct machine learning (ML) algorithms-namely, random forest (RF) and support vector regression (SVR)-to demonstrate the superior performance of deep learning algorithms over individual ML ones. We initially gathered WQIs from diverse locations and varying depths within the reservoir using an AAQ-RINKO device in the study area to achieve this. It is important to highlight that, despite utilizing diverse data-driven models in water quality estimation, a significant gap persists in the existing literature regarding implementing a comprehensive hybrid algorithm. This algorithm integrates the wavelet transform, convolutional neural network (CNN), and gated recurrent unit (GRU) methodologies to estimate WQIs accurately within a spatiotemporal framework. Subsequently, the effectiveness of the models that were developed was assessed utilizing various statistical metrics, encompassing the correlation coefficient (r), root mean square error (RMSE), mean absolute error (MAE), and Nash-Sutcliffe efficiency (NSE) throughout both the training and testing phases. The findings demonstrated that the WT-CNN-GRU model exhibited better performance in comparison with the other algorithms by 13% (SVR), 13% (RF), 9% (CNN), and 8% (GRU) when R-squared and DO were considered as evaluation indices and WQIs, respectively.

Finite element solution of coupled multiphysics reaction-diffusion equations for fracture healing in hard biological tissues.

This study proposes a computational framework to investigate the multi-stage process of fracture healing in hard tissues, e.g., long bone, based on the mathematical Bailon-Plaza and Van der Meulen formulation. The goal is to explore the influence of critical biological factors by employing the finite element method for more realistic configurations. The model integrates a set of variables, including cell densities, growth factors, and extracellular matrix contents, managed by a coupled system of partial differential equations. A weak finite element formulation is introduced to enhance the numerical robustness for coarser mesh grids, complex geometries, and more accurate boundary conditions. This formulation is less sensitive to mesh quality and converges smoothly with mesh refinement, exhibiting superior numerical stability compared to previously available strong-form solutions. The model accurately reproduces various stages of healing, including soft cartilage callus formation, endochondral and intramembranous ossification, and hard bony callus development for various sizes of fracture gap. Model predictions align with the existing research and are logically coherent with the available experimental data. The developed multiphysics simulation clarifies the coordination of cellular dynamics, extracellular matrix alterations, and signaling growth factors during fracture healing.

Methylation Status of miR-34a and miR-126 in Non-Small Cell Lung Cancer (NSCLC) Tumor Tissues.

Background: MiR-34a and miR-126 mainly act as tumor suppressors and are often downregulated in various cancers, including non-small cell lung cancer (NSCLC). We aimed to determine the methylation status of miR-34a and miR-126 in NSCLC patients. Methods: The current study included 63 paraffin-embedded NSCLC and paired adjacent normal tissues. After DNA extraction and bisulfite treatment, the methylation status of miR-34a and miR-126 were evaluated using the MSP method. Results: There was no statistically significant difference between tumor and normal tissues regarding the methylation status of miR-34a and miR-126 (p > 0.05). Moreover, we found no significant correlation between the methylation status of miR-34a and miR-126 with patients' demographic parameters, including gender, age, and pathology subtype (p > 0.05). Conclusion: Considering the low expression of mir-126 and mir-34 in NSCLC, more sensitive methods are recommended to be exploited for detecting the level of methylation or underlying mechanisms other than promoter hypermethylation in silencing these genes in NSCLC.

Tuberculosis and lung cancer: metabolic pathways play a key role.

Despite the fact that some cases of tuberculosis (TB) are undiagnosed and untreated, it remains a serious global public health issue. In the diagnosis, treatment, and control of latent and active TB, there may be a lack of effectiveness. An understanding of metabolic pathways can be fundamental to treat latent TB infection and active TB disease. Rather than targeting Mycobacterium tuberculosis, the control strategies aim to strengthen host responses to infection and reduce chronic inflammation by effectively enhancing host resistance to infection. The pathogenesis and progression of TB are linked to several metabolites and metabolic pathways, and they are potential targets for host-directed therapies. Additionally, metabolic pathways can contribute to the progression of lung cancer in patients with latent or active TB. A comprehensive metabolic pathway analysis is conducted to highlight lung cancer development in latent and active TB. The current study aimed to emphasize the association between metabolic pathways of tumor development in patients with latent and active TB. Health control programs around the world are compromised by TB and lung cancer due to their special epidemiological and clinical characteristics. Therefore, presenting the importance of lung cancer progression through metabolic pathways occurring upon TB infection can open new doors to improving control of TB infection and active TB disease while stressing that further evaluations are required to uncover this correlation.

Meta-analysis: Risk of pancreatic cancer in patients with inflammatory bowel disease.

BACKGROUND: Studies exploring the association between inflammatory bowel disease (IBD) and pancreatic cancer have reported inconsistent results. AIMS: To provide a comprehensive overview of the risk of pancreatic cancer development in patients with IBD. METHODS: We searched Embase, PubMed, Scopus and ProQuest from inception to 31 October 2023. We included population-based cohort studies examining the risk of incident pancreatic cancer in adult patients with IBD compared to the non-IBD population. We also retrieved Mendelian randomisation (MR) studies investigating the relationship of IBD with pancreatic cancer risk. We conducted random-effects meta-analyses and provided pooled relative risks (RRs) with 95% confidence intervals (CIs). RESULTS: We included 13 studies. Among 11 cohort studies, the risk of developing pancreatic cancer increased by 79% in patients with IBD (RR = 1.79 [95% CI: 1.16-2.75]; I2 = 95.7%). Patients either with Crohn's disease (RR = 1.42 [95% CI: 1.24-1.63]) or ulcerative colitis (RR = 1.50 [95% CI: 1.17-1.92]) had increased risk (p for interaction = 0.72). The annual incidence of pancreatic cancer potentially attributable to IBD increased by 55 cases (95% CI: 17-103) per million. Two MR studies demonstrated that genetic liability to IBD was associated with an increased risk of pancreatic cancer. CONCLUSIONS: Our results suggest a moderate increase in the risk of pancreatic cancer in patients with IBD, which may be further heightened by genetic predisposition to IBD. The increased risk of pancreatic cancer is probably similar in Crohn's disease and ulcerative colitis.

Mapping reservoir water quality from Sentinel-2 satellite data based on a new approach of weighted averaging: Application of Bayesian maximum entropy.

In regions like Oman, which are characterized by aridity, enhancing the water quality discharged from reservoirs poses considerable challenges. This predicament is notably pronounced at Wadi Dayqah Dam (WDD), where meeting the demand for ample, superior water downstream proves to be a formidable task. Thus, accurately estimating and mapping water quality indicators (WQIs) is paramount for sustainable planning of inland in the study area. Since traditional procedures to collect water quality data are time-consuming, labor-intensive, and costly, water resources management has shifted from gathering field measurement data to utilizing remote sensing (RS) data. WDD has been threatened by various driving forces in recent years, such as contamination from different sources, sedimentation, nutrient runoff, salinity intrusion, temperature fluctuations, and microbial contamination. Therefore, this study aimed to retrieve and map WQIs, namely dissolved oxygen (DO) and chlorophyll-a (Chl-a) of the Wadi Dayqah Dam (WDD) reservoir from Sentinel-2 (S2) satellite data using a new procedure of weighted averaging, namely Bayesian Maximum Entropy-based Fusion (BMEF). To do so, the outputs of four Machine Learning (ML) algorithms, namely Multilayer Regression (MLR), Random Forest Regression (RFR), Support Vector Regression (SVRs), and XGBoost, were combined using this approach together, considering uncertainty. Water samples from 254 systematic plots were obtained for temperature (T), electrical conductivity (EC), chlorophyll-a (Chl-a), pH, oxidation-reduction potential (ORP), and dissolved oxygen (DO) in WDD. The findings indicated that, throughout both the training and testing phases, the BMEF model outperformed individual machine learning models. Considering Chl-a, as WQI, and R-squared, as evaluation indices, BMEF outperformed MLR, SVR, RFR, and XGBoost by 6%, 9%, 2%, and 7%, respectively. Furthermore, the results were significantly enhanced when the best combination of various spectral bands was considered to estimate specific WQIs instead of using all S2 bands as input variables of the ML algorithms.

Risk of Common Neurological Disorders in Adult Patients with Inflammatory Bowel Disease: A Systematic Review and Meta-analysis.

BACKGROUND: Several studies investigated the risks of neurological conditions in patients with inflammatory bowel disease (IBD), with some variability in findings. We aimed to perform a systematic review and meta-analysis of available evidence to elucidate the association between IBD and the risks of common neurological disorders. METHODS: We conducted a literature search through Embase, PubMed, Scopus, and ProQuest databases from inception to June 30, 2023, to identify cohort studies assessing the risk of developing stroke, all-cause dementia, Parkinson's disease (PD), multiple sclerosis (MS), seizure/epilepsy, and peripheral neuropathy in adult IBD patients compared with non-IBD population. We combined hazard ratios (HRs) with 95% confidence intervals (CIs) to compute pooled estimates using a random-effects model. RESULTS: In total, 22 cohort studies were included, of which 9 studies reported 7074 stroke events in 202 460 IBD patients, 5 studies reported 3783 all-cause dementia diagnoses in 109 602 IBD patients, 7 studies reported 932 PD diagnoses in 354 792 IBD patients, and 1 study reported 6 MS events in 35 581 IBD patients. We observed increased risks of incident stroke (pooled HR = 1.19; 95% CI, 1.06-1.31), all-cause dementia (pooled HR = 1.22; 95% CI, 1.05-1.38), PD (pooled HR = 1.39; 95% CI, 1.20-1.58), and MS (HR = 2.89; 95% CI, 1.02-8.42). No eligible studies were found on peripheral neuropathy and seizure/epilepsy. CONCLUSIONS: Inflammatory bowel disease may be modestly associated with increased risks of stroke, all-cause dementia, and PD. Further longitudinal studies are warranted to investigate potential links with MS, seizure/epilepsy, and peripheral neuropathy, as well as their clinical significance.

This systematic review and meta-analysis of cohort studies aimed to clarify association between inflammatory bowel disease and risks of common neurological disorders. Based on analyses, inflammatory bowel disease may modestly increase risks of stroke, all-cause dementia, and Parkinson's disease vs the healthy population.

Infectious keratitis in pediatric population aged less than two years: a tertiary eye institute experience.

BACKGROUND: Infectious keratitis is a serious ocular condition, which can lead to corneal scarring, vision loss, and even blindness. Pediatric infectious keratitis accounts for about 13% of all cases, although there is a lack of comprehensive data regarding keratitis in less than two years of age population group. This study was aimed to determine predisposing factors, clinical characteristics, microbial profile, and management of infectious keratitis in a population of children aged less than two years. MATERIALS AND METHODS: A retrospective study was carried out in a tertiary eye institute over a period of 18 years from July 2005 to December 2022. Collected data was analyzed for demographics, predisposing factors, clinical features, and treatment methods. RESULTS: Fifty-seven cases of keratitis were identified. Age of the patients ranged from 1 to 24 months (Median: 6, interquartile range: 2-10). Thirty cases were male (52.6%). Predisposing factors were identified in 39 cases (68.4%): consisting of prior ocular trauma (n = 15), previous intraocular surgery (n = 11), ocular surface disease (n = 10), nasolacrimal duct obstruction (n = 4), prematurity (n = 3), developmental delay (n = 2), TORCH infection (n = 1), and contact lens (n = 1). Corneal thinning was observed in 29 eyes (50.9%), which progressed to perforation in 13 eyes (22.8%). Three patients developed endophthalmitis (95% CI, 1.5-13.4%). Most eyes had negative smear (60.4%) and culture (59.6%) results. Pseudomonas aeruginosa was the most common microorganism (11 of 21). Candida albicans was isolated in one case. In vitro susceptibility results showed good coverage of the combined ceftazidime and vancomycin regimen (100%). Surgical procedures were carried out in 35 eyes (61.4%) and 15 eyes required tectonic procedures (26.3%). CONCLUSION: Despite good coverage of medical treatment over cultured isolates, surgical tectonic intervention was required in nearly a quarter of cases to resolve the corneal infection. This finding indicates the necessity of prompt patient referring, corneal sampling and initiation of the treatment.

Does Elderly-Onset Inflammatory Bowel Disease Increase Risk of Colorectal Cancer? A Systematic Review and Meta-Analysis.

BACKGROUND: Although younger adults with inflammatory bowel disease (IBD) are known to have an increased risk of developing colorectal cancer (CRC), the impact of IBD on CRC risk in elderly patients is not yet fully understood. Therefore, we conducted this systematic review and meta-analysis to address this knowledge gap. METHODS: We thoroughly searched Embase, PubMed, and Scopus, covering the literature from inception to 31 August 2023, in any language. We enrolled population-based cohort studies that appraised the risk of CRC development in elderly patients (≥60 years) with IBD as compared to the non-IBD population. Our meta-analysis provided pooled relative risk (RR) with 95% confidence intervals (CIs) using a random-effect model. RESULTS: Out of 3904 citations, 3 eligible cohort studies were ultimately included, reporting 694 CRC events in 35,187 patients with IBD. According to analysis, the risk of developing CRC did not increase in patients with elderly-onset IBD (RR = 1.17 [95% CI: 0.86-1.47]; I2 = 62.6%). This lack of a significant association was observed in both patients with Crohn's disease (RR = 1.28 [95% CI: 0.88-1.69]) and ulcerative colitis (RR = 0.99 [95% CI: 0.90-1.09]) (p for interaction = 0.166). CONCLUSION: Our findings revealed no significant increase in the risk of incident CRC in patients with elderly-onset IBD, suggesting that intense screening of these patients for CRC may not be necessary.

Use of RAPD, enzyme activity staining, and colony size to differentiate phytopathogenic Fuzarium oxysporum isolates from Iran

Fusarium oxysporum is a common soilborn plant pathogen with a worldwide distribution. Fusarium yellows disease of chickpea (Cicer arientinum) caused by F. oxysporum is one of the most destructive soilborn disease which is a major production constraint in chickpea-growing regions of Iran. Three laboratory methods ôamplification of genomic DNA using random primers, enzyme activity staining, and colony size determinationö have been used to discriminate between highly virulent (HV) and weakly virulent (WV) isolates of F. oxysporum. On the basis of colony size (a traditional morphological method) and the ability of isolates to produce pectic enzymes, five HV isolates were differentiated from three WV isolates. The HV isolates formed large colony (ranging from 10.1 to 12.6 mm in diameter) and showed the same enzyme pattern, while the WV isolates produced small colony (ranging from 5.8 to 7.8 mm in diameter) and had not detectable enzyme activity in the stained overlaying gel. Twelve arbitrary 10-mer primers were tested on these 8 isolates of F. oxysporum by Polymerase Chain Reaction (PCR). Cluster analysis of the data from the DNA amplification by Random Amplified Polymorphic DNA (RAPD), differentiated HV from WV isolates. The results obtained from RAPD test confirmed the classification of these eight isolates based on pathogenicity test, colony size, and enzyme activity staining into two groups (HV and WV).