Eur Radiol. 2025 Mar 5. doi: 10.1007/s00330-025-11468-6. Online ahead of print.

ABSTRACT

OBJECTIVES: Incidental airway tumors are rare and can easily be overlooked on chest CT, especially at an early stage. Therefore, we developed and assessed a deep learning-based artificial intelligence (AI) system for detecting and localizing airway nodules.

MATERIALS AND METHODS: At a single academic hospital, we retrospectively analyzed cancer diagnoses and radiology reports from patients who received a chest or chest-abdomen CT scan between 2004 and 2020 to find cases presenting as airway nodules. Primary cancers were verified through bronchoscopy with biopsy or cytologic testing. The malignancy status of other nodules was confirmed with bronchoscopy only or follow-up CT scans if such evidence was unavailable. An AI system was trained and evaluated with a ten-fold cross-validation procedure. The performance of the system was assessed with a free-response receiver operating characteristic curve.

RESULTS: We identified 160 patients with airway nodules (median age of 64 years [IQR: 54-70], 58 women) and added a random sample of 160 patients without airway nodules (median age of 60 years [IQR: 48-69], 80 women). The sensitivity of the AI system was 75.1% (95% CI: 67.6-81.6%) for detecting all nodules with an average number of false positives per scan of 0.25 in negative patients and 0.56 in positive patients. At the same operating point, the sensitivity was 79.0% (95% CI: 70.4-86.6%) for the subset of tumors. A subgroup analysis showed that the system detected the majority of subtle tumors.

CONCLUSION: The AI system detects most airway nodules on chest CT with an acceptable false positive rate.

KEY POINTS: Question Incidental airway tumors are rare and are susceptible to being overlooked on chest CT. Findings An AI system can detect most benign and malignant airway nodules with an acceptable false positive rate, including nodules that have very subtle features. Clinical relevance An AI system shows potential for supporting radiologists in detecting airway tumors.

PMID:40042650 | DOI:10.1007/s00330-025-11468-6

Eur Radiol. 2025 Mar 5. doi: 10.1007/s00330-025-11473-9. Online ahead of print.

ABSTRACT

OBJECTIVES: This study evaluated and compared the effectiveness of various predictive models for forecasting occult lymph node metastasis (LNM) in tongue squamous cell carcinoma (TSCC) patients.

METHODS: In this retrospective diagnostic experiment, 268 patients were recruited from three medical centers. Based on the different hospitals from which the patients were recruited, they were divided into a training set, an internal testing set, and two external testing sets, comprising 107, 53, 63, and 45 patients, respectively. Several predictive models were developed using patients' contrast-enhanced magnetic resonance imaging (CEMRI), including two-dimensional deep learning (2D DL), conventional radiomics (C-radiomics), and intratumoral heterogeneity radiomics (ITH-radiomics). Univariate and multivariate logistic regression analyses were conducted on the clinical data. Finally, two fusion strategies were used to construct the model.

RESULTS: The ITH-radiomics model exhibited superior discriminative power compared to C-radiomics model. The late fusion model had the highest area under the curve (AUC) across all test sets (0.81-0.85). Compared to the late fusion model, the AUC values for the early fusion, 2D DL, C-radiomics, and ITH-radiomics models in the test sets ranged from 0.77 to 0.82, 0.64 to 0.81, 0.66 to 0.77, and 0.77 to 0.80, respectively. Additionally, the late fusion model demonstrated the highest accuracy (76-89%) and specificity (87-100%) across the test sets.

CONCLUSIONS: The evaluation of the models' effectiveness revealed that the decision-based late fusion model, which integrated 2D DL, C-radiomics, ITH-radiomics, and clinical data, achieved the best results. This predictive approach can more accurately assess patients' conditions and aid in selecting surgical plans.

KEY POINTS: Question How well does fusing multiple models work for predicting occult lymph node metastasis in patients with tongue squamous cell carcinoma? Findings The late fusion model, incorporating two-dimensional deep learning, conventional-radiomics, intratumoral heterogeneity-radiomics, and clinical features, achieved the best results compared to each individual model. Clinical relevance Patients with a high intratumoral heterogeneity-radiomics index exhibit an increased risk of occult lymph node metastasis in tongue squamous cell carcinoma patients, which showed that the late fusion model achieves superior predictive performance compared to the early fusion model.

PMID:40042648 | DOI:10.1007/s00330-025-11473-9

Environ Geochem Health. 2025 Mar 5;47(4):101. doi: 10.1007/s10653-025-02413-z.

ABSTRACT

With increasing scholarly focus on the ramifications of land use changes on water quality, although substantial research has been undertaken, the findings demonstrate pronounced spatial variability and the heterogeneity of research methodologies. To address this critical gap, this review offers a rigorous evaluation of the strengths and limitations of current research methodologies, providing targeted recommendations for refinement. It systematically assesses the existing body of literature concerning the influence of land use changes on water quality, with particular emphasis on the spatial heterogeneity of research results and the uniformity of employed methodologies. Despite variations in geographical contexts and research subjects, the methodological paradigms remain largely consistent, typically encompassing the acquisition and analysis of water quality and land use data, the delineation of buffer zones, and the application of correlation and regression analyses. However, these approaches encounter limitations in addressing regional disparities, nonlinear interactions, and real-time monitoring complexities. The review advocates for methodological advancements, such as the integration of automated monitoring systems and IoT technologies, alongside the fusion of deep learning algorithms with remote sensing techniques, to enhance both the precision and efficiency of data collection. Furthermore, it recommends the standardization of buffer zone delineation, the reinforcement of foundational water quality assessments, and the utilization of catchment-scale analyses to more accurately capture the influence of land use changes on water quality. Future inquiries should prioritize the development of interdisciplinary ecological models to elucidate the interaction and feedback mechanisms between land use, water quality, and climate change.

PMID:40042544 | DOI:10.1007/s10653-025-02413-z

Alzheimers Dement. 2025 Mar;21(3):e14601. doi: 10.1002/alz.14601.

ABSTRACT

INTRODUCTION: The utility of retinal photography-derived aging biomarkers for predicting cognitive decline remains under-explored.

METHODS: A memory-clinic cohort in Singapore was followed-up for 5 years. RetiPhenoAge, a retinal aging biomarker, was derived from retinal photographs using deep-learning. Using competing risk analysis, we determined the associations of RetiPhenoAge with cognitive decline and dementia, with the UK Biobank utilized as the replication cohort. The associations of RetiPhenoAge with MRI markers(cerebral small vessel disease [CSVD] and neurodegeneration) and its underlying plasma proteomic profile were evaluated.

RESULTS: Of 510 memory-clinic subjects(N = 155 cognitive decline), RetiPhenoAge associated with incident cognitive decline (subdistribution hazard ratio [SHR] 1.34, 95% confidence interval [CI] 1.10-1.64, p = 0.004), and incident dementia (SHR 1.43, 95% CI 1.02-2.01, p = 0.036). In the UK Biobank (N = 33 495), RetiPhenoAge similarly predicted incident dementia (SHR 1.25, 95% CI 1.09-1.41, p = 0.008). RetiPhenoAge significantly associated with CSVD, brain atrophy, and plasma proteomic signatures related to aging.

DISCUSSION: RetiPhenoAge may provide a non-invasive prognostic screening tool for cognitive decline and dementia.

HIGHLIGHTS: RetiPhenoAge, a retinal aging marker, was studied in an Asian memory clinic cohort. Older RetiPhenoAge predicted future cognitive decline and incident dementia. It also linked to neuropathological markers, and plasma proteomic profiles of aging. UK Biobank replication found that RetiPhenoAge predicted 12-year incident dementia. Future studies should validate RetiPhenoAge as a prognostic biomarker for dementia.

PMID:40042460 | DOI:10.1002/alz.14601

Microb Biotechnol. 2025 Mar;18(3):e70121. doi: 10.1111/1751-7915.70121.

ABSTRACT

Antimicrobial peptides (AMPs) face stability and toxicity challenges in clinical use. Stapled modification enhances their stability and effectiveness, but its application in peptide design is rarely reported. This study built ten prediction models for stapled AMPs using deep and machine learning, tested their accuracy with an independent data set and wet lab experiments, and characterised stapled loop structures using structural, sequence and amino acid descriptors. AlphaFold improved stapled peptide structure prediction. The support vector machine model performed best, while two deep learning models achieved the highest accuracy of 1.0 on an external test set. Designed cysteine- and lysine-stapled peptides inhibited various bacteria with low concentrations and showed good serum stability and low haemolytic activity. This study highlights the potential of the deep learning method in peptide modification and design.

PMID:40042163 | DOI:10.1111/1751-7915.70121

Adv Sci (Weinh). 2025 Mar 5:e2415808. doi: 10.1002/advs.202415808. Online ahead of print.

ABSTRACT

Current imaging technologies are limited in their capability to simultaneously capture intracellular and extracellular dynamics in a spatially and temporally resolved manner. This study presents a multimodal imaging system that integrates nanoplasmonic sensing with multichannel fluorescence imaging to concomitantly analyze intracellular and extracellular processes in space and time at the single-cell level. Utilizing a highly sensitive gold nanohole array biosensor, the system provides label-free and real-time monitoring of extracellular secretion, while implementing nanoplasmonic-compatible multichannel fluorescence microscopy enables to visualize the interconnected intracellular activities. Combined with deep-learning-assisted image processing, this integrated approach allows multiparametric and simultaneous study of various cellular constituents in hundreds of individual cells with subcellular spatial and minute-level temporal resolution over extended periods of up to 20 h. The system's utility is demonstrated by characterizing a range of secreted biomolecules and fluorescence toolkits across three distinct applications: visualization of secretory behaviors along with subcellular organelles and metabolic processes, concurrent monitoring of protein expression and secretion, and assessment of cell cycle phases alongside their corresponding secretory profiles. By offering comprehensive insights, the multifunctional approach is expected to enhance holistic readouts of biological systems, facilitating new discoveries in both fundamental and translational sciences.

PMID:40042114 | DOI:10.1002/advs.202415808

Clin Chem Lab Med. 2025 Mar 6. doi: 10.1515/cclm-2024-1219. Online ahead of print.

NO ABSTRACT

PMID:40042089 | DOI:10.1515/cclm-2024-1219

ACS Sens. 2025 Mar 5. doi: 10.1021/acssensors.4c03472. Online ahead of print.

ABSTRACT

Anterior talofibular ligament (ATFL) sprain is one of the most prevalent sports-related injuries, so proper evaluation of ligament sprains is critical for treatment options. However, existing tests suffer from a lack of standardized quantitative evaluation criteria, interindividual variability, incompatible materials, or risks of infection. Although advanced medical diagnostic methods already have been using noninvasive, portable, and wearable diagnostic electronics, these devices have insufficient adhesion to accurately respond to internal body injuries. Therefore, we propose a high-adhesive hydrogel-based strain sensor made from gelatin, cellulose nanofiber (CNF), and cross-linked poly(acrylic acid) grafted with N-hydrosuccinimide ester. The adhesive strain sensor, with excellent conformability and stretchability, firmly adheres to the skin, making it suitable for accurately evaluating the severity of anterior talofibular ligament sprain. Its strong adhesive (up to 192 kPa) can adapt to the surface characterization of ankles. The high-adhesive hydrogel-based strain sensor has a high tensile strength (680%) and achieves a high gauge factor (GF) of 8.29. Simultaneously, it also presents a 40 μm ultralow detection limit. Additionally, after a deep learning model was integrated to improve sensing accuracy, the system achieved a diagnostic accuracy of 95%, significantly surpassing the magnetic resonance imaging (MRI) gold standard of 81.1%.

PMID:40042081 | DOI:10.1021/acssensors.4c03472

Eur J Nucl Med Mol Imaging. 2025 Mar 5. doi: 10.1007/s00259-025-07146-w. Online ahead of print.

NO ABSTRACT

PMID:40042637 | DOI:10.1007/s00259-025-07146-w

Cardiovasc Res. 2025 Mar 5:cvaf037. doi: 10.1093/cvr/cvaf037. Online ahead of print.

ABSTRACT

BACKGROUND: Alternative splicing of Titin (TTN) I-band exons produce protein isoforms with variable size and elasticity, but the mechanisms whereby TTN splice factors regulate exon usage and thereby determining cardiomyocyte passive stiffness and diastolic function, is not well understood. Non-coding RNA transcripts from the antisense strand of protein-coding genes have been shown to regulate alternative splicing of the sense gene. The TTN gene locus harbours >80 natural antisense transcripts (NATs) with unknown function in the human heart. The aim of this study was to determine if TTN antisense transcripts play a role in alternative splicing of TTN.

METHODS AND RESULTS: RNA-sequencing and RNA in situ hybridization (ISH) of cardiac tissue from heart failure patients (HF), unused donor hearts and human iPS-derived cardiomyocytes (iPS-CMs) were used to determine the expression and localization of TTN NATs. Live cell imaging was used to analyze the effect of NATs on sarcomere properties. RNA ISH, immunofluorescence was performed in iPS-CMs to study the interaction between NATs, TTN mRNA and splice factor protein RBM20.We found that TTN-AS1-276 was the predominant TTN NAT in the human heart and that it was upregulated in HF. Knock down of TTN-AS1-276 in human iPS-CMs resulted in decreased interaction between the splicing factor RBM20 and TTN pre-mRNA, decreased TTN I-band exon skipping, and markedly lower expression of the less compliant TTN isoform N2B. The effect on TTN exon usage was independent of sense-antisense exon overlap and polymerase II elongation rate. Furthermore, knockdown resulted in longer sarcomeres with preserved alignment, improved fractional shortening and relaxation times.

CONCLUSIONS: We demonstrate a role for TTN-AS1-276 in facilitating alternative splicing of TTN and regulating sarcomere properties. This transcript could constitute a target for improving cardiac passive stiffness and diastolic function in conditions such as heart failure with preserved ejection fraction.

PMID:40042822 | DOI:10.1093/cvr/cvaf037

Neurogenetics. 2025 Mar 5;26(1):34. doi: 10.1007/s10048-025-00816-9.

ABSTRACT

Schizophrenia (SCZ) is a chronic and severe mental disorder with a complex molecular aetiology. Emerging evidence indicates a potential association between the gut microbiome and the development of SCZ. Considering the under-representation of African populations in SCZ research, this study aimed to explore the association between the gut microbiome and SCZ within a South African cohort. Gut microbial DNA was obtained from 89 participants (n = 41 SCZ cases; n = 48 controls) and underwent 16S rRNA (V4) sequencing. Data preparation and taxa classification were performed with the DADA2 pipeline in R studio followed by diversity analysis using QIIME2. Analysis of Compositions of Microbiomes with Bias Correction (ANCOM-BC) was utilised to identify differentially abundant taxa. No statistically significant differences were observed between SCZ patients and controls in terms of alpha-diversity (Shannon q = 0.09; Simpson q = 0.174) or beta-diversity (p = 0.547). Five taxa, namely Prevotella (p = 0.037), Faecalibacterium (p = 0.032), Phascolarctobacterium (p = 0.002), Dialister (p = 0.043), and SMB53 (p = 0.012), were differentially abundant in cases compared to controls, but this observation did not survive correction for multiple testing. This exploratory study suggests a potential association between the relative abundance of Prevotella, Faecalibacterium, Phascolarctobacterium, Dialister, and SMB53 with SCZ case-control status. Given the lack of significance after correcting for multiple testing, these results should be interpreted with caution. Mechanistic studies in larger samples are warranted to confirm these findings and better understand the association between the gut microbiome and SCZ.

PMID:40042645 | DOI:10.1007/s10048-025-00816-9

Elife. 2025 Mar 5;13:RP102986. doi: 10.7554/eLife.102986.

ABSTRACT

Outcomes can vary even when choices are repeated. Such ambiguity necessitates adjusting how much to learn from each outcome by tracking its variability. The medial prefrontal cortex (mPFC) has been reported to signal the expected outcome and its discrepancy from the actual outcome (prediction error), two variables essential for controlling the learning rate. However, the source of signals that shape these coding properties remains unknown. Here, we investigated the contribution of cholinergic projections from the basal forebrain because they carry precisely timed signals about outcomes. One-photon calcium imaging revealed that as mice learned different probabilities of threat occurrence on two paths, some mPFC cells responded to threats on one of the paths, while other cells gained responses to threat omission. These threat- and omission-evoked responses were scaled to the unexpectedness of outcomes, some exhibiting a reversal in response direction when encountering surprising threats as opposed to surprising omissions. This selectivity for signed prediction errors was enhanced by optogenetic stimulation of local cholinergic terminals during threats. The enhanced threat-evoked cholinergic signals also made mice erroneously abandon the correct choice after a single threat that violated expectations, thereby decoupling their path choice from the history of threat occurrence on each path. Thus, acetylcholine modulates the encoding of surprising outcomes in the mPFC to control how much they dictate future decisions.

PMID:40042523 | DOI:10.7554/eLife.102986

Elife. 2025 Mar 5;13:RP100949. doi: 10.7554/eLife.100949.

ABSTRACT

Root causal gene expression levels - or root causal genes for short - correspond to the initial changes to gene expression that generate patient symptoms as a downstream effect. Identifying root causal genes is critical towards developing treatments that modify disease near its onset, but no existing algorithms attempt to identify root causal genes from data. RNA-sequencing (RNA-seq) data introduces challenges such as measurement error, high dimensionality and non-linearity that compromise accurate estimation of root causal effects even with state-of-the-art approaches. We therefore instead leverage Perturb-seq, or high-throughput perturbations with single-cell RNA-seq readout, to learn the causal order between the genes. We then transfer the causal order to bulk RNA-seq and identify root causal genes specific to a given patient for the first time using a novel statistic. Experiments demonstrate large improvements in performance. Applications to macular degeneration and multiple sclerosis also reveal root causal genes that lie on known pathogenic pathways, delineate patient subgroups and implicate a newly defined omnigenic root causal model.

PMID:40042510 | DOI:10.7554/eLife.100949

Alzheimers Dement. 2025 Mar;21(3):e14493. doi: 10.1002/alz.14493.

ABSTRACT

INTRODUCTION: Late-life cognitive impairment and depression frequently co-occur and share many symptoms. However, the specific neural and clinical factors contributing to both their common and distinct profiles in older adults remain unclear.

METHODS: We investigated resting-state correlates of cognitive and depressive symptoms in older adults (n = 248 and n = 95) using clinical, blood, and neuroimaging data. We computed a connectivity matrix across default mode, executive control, and salience networks. Cross-validated elastic net regression identified features reflecting cognitive function and depressive symptoms. These features were validated on a held-out dataset.

RESULTS: We discovered that white matter hyperintensities and nine overlapping nodes spanning all three networks are associated with both cognitive function and depressive symptoms, including left amygdala, left hippocampus, and bilateral ventral tegmental area.

DISCUSSION: Our findings reveal intertwined neural nodes influencing cognitive impairment and depressive symptoms in late life, offering insights into shared characteristics and potential therapeutic targets.

HIGHLIGHTS: Resting-state neuroimaging markers are associated with symptoms of cognitive decline and late-life depression. Symptom-associated connectivity alterations were present across three major brain networks of interest, including the salience, default mode, and executive control networks. Some regions of interest are associated with both cognitive function and depressive symptoms, including the left amygdala, left hippocampus, and bilateral ventral tegmental area.

PMID:40042417 | DOI:10.1002/alz.14493

Cardiovasc Res. 2025 Mar 5:cvaf016. doi: 10.1093/cvr/cvaf016. Online ahead of print.

ABSTRACT

AIMS: Patients with chronic kidney disease (CKD) show a high risk of cardiovascular diseases, predominantly caused by accelerated vascular calcification. Vascular calcification is a highly regulated process with no current treatment. The vasoconstriction-inhibiting factor (VIF) peptide was recently discovered with vasoregulatory properties, but no information regarding calcification has been described.

METHODS AND RESULTS: In the present work, the inhibitory calcification effect of the VIF peptide was analysed in vitro in vascular smooth muscle cells (VSMCs), ex vivo in rat aortic rings, as well as in vivo in rats treated with vitamin D and nicotine (VDN). The VIF peptide inhibits vascular calcification by acting as a calcimimetic for the calcium-sensing receptor, increasing carboxylated matrix Gla protein production and blocking the activation of calcification pathways. The VIF peptide decreased calcium influx, the production of reactive oxygen species, and the activation of multiple kinases in VSMCs. Furthermore, calcium deposition in the aortas of patients with CKD negatively correlates with the VIF peptide concentration. Moreover, we show the cleavage of the VIF peptide from chromogranin-A by 'proprotein convertase subtilisin/kexin type 2' and 'carboxypeptidase E' enzymes. In addition, 'cathepsin K' degrades the VIF peptide. The active site of the native 35 amino acid-sequence long VIF peptide was identified with seven amino acids, constituting a promising drug candidate with promise for clinical translation.

CONCLUSION: The elucidation of the underlying mechanism by which the VIF peptide inhibits vascular calcification, as well as the active sequence and the cleavage and degradation enzymes, forms the basis for developing preventive and therapeutic measures to counteract vascular calcification.

PMID:40042167 | DOI:10.1093/cvr/cvaf016

Allergy. 2025 Mar 5. doi: 10.1111/all.16521. Online ahead of print.

NO ABSTRACT

PMID:40042067 | DOI:10.1111/all.16521

Toxicol Res (Camb). 2025 Feb 27;14(1):tfaf025. doi: 10.1093/toxres/tfaf025. eCollection 2025 Feb.

ABSTRACT

Melasma is a chronic condition that leads to the buildup of melanin pigment in the epidermis and dermis due to active melanocytes. Even though it is considered a non-life-threatening condition, pigment disorders have a negative impact on quality of life. Since melasma treatment is not sufficient and complicated, new treatment options are sought. Research on metformin and ascorbic acid suggested that they might be used against melasma in the scope of "drug repositioning."The MNT-1 human melanoma cell line was used to assess the effects of metformin, ascorbic acid, and metformin+ascorbic acid combination on cytotoxicity and oxidative stress. Melanin, cAMP, L-3,4-dihydroxyphenylalanine (L-DOPA) and tyrosinase levels were determined by commercial ELISA kits and tyrosinase gene expression was analyzed with RT-qPCR. Cytopathological evaluations were performed by phase contrast microscopy. Tyrosinase expression was determined by immunofluorescence (IF) staining of MNT-1 cells. The online service TargetNet was used for biological target screening. The parameters were not significantly altered by ascorbic acid applied at non-cytotoxic concentrations. On the contrary, metformin dramatically raised tyrosinase and intracellular ROS levels. Moreover, intracellular ROS levels and tyrosinase levels were found to be considerably elevated with the combined treatment. Also, potential metformin and ascorbic acid interactions were determined. According to the results, it can be said that these parameters were not significantly altered by ascorbic acid. On the contrary, metformin dramatically raised tyrosinase and intracellular oxidative stress levels. Moreover, intracellular oxidative stress and tyrosinase levels were elevated with the combined treatment. In conclusion, individual treatments of ascorbic acid or metformin may only provide a limited effect when treating melasma and extensive in vitro and in vivo research are required.

PMID:40040652 | PMC:PMC11878769 | DOI:10.1093/toxres/tfaf025

Annu Int Conf IEEE Eng Med Biol Soc. 2024 Jul;2024:1-7. doi: 10.1109/EMBC53108.2024.10782657.

ABSTRACT

Drug-target interaction (DTI) prediction speeds up drug repurposing, accelerates drug screening, and reduces drug design timeframe. Previous DTI prediction frameworks lack consideration for the multimodal nature of DTI, advanced feature representation techniques, and generalizability on unseen drugs and proteins. Therefore, we propose a novel framework that combines a multimodal graph neural network with direct, molecular-level structural learning via model ensembling. We use a multimodal biomedical that contains drugs, proteins, diseases, and pathways, all of which have meaningful feature embeddings generated via language models or knowledge graphs. We also employ a structural learning module that exploits molecular-level information and runs independently from the graph. Lastly, the graph and structural modules are combined, forming the optimal prediction. Our proposed framework outperformed multiple benchmark DTI frameworks on real-world datasets. After testing on an independent dataset, we conclude our framework is generalizable to unseen drugs and proteins. Our model can be easily extended to other biomedical link prediction problems, such as drug-drug interaction.

PMID:40040060 | DOI:10.1109/EMBC53108.2024.10782657

Mol Pain. 2025 Mar 4:17448069251327805. doi: 10.1177/17448069251327805. Online ahead of print.

ABSTRACT

μ-opioid receptor (MOP) plays a critical role in mediating opioid analgesic effects. Genetic variations, particularly those in the MOP gene (Oprm1), significantly influence individual variations in opioid efficacy and side effects across species, highlighting the need for pharmacogenomic research in human and veterinary contexts. This study aimed to identify single-nucleotide variations (SNVs) within Oprm1 in 100 cats of various breeds. Oprm1 spans over 170 kb and consists of five exons that combine to yield three splice variants in the cat Ensembl database. Among these variants, Oprm1-202 is an ortholog of the MOR-1 transcript, which is the most abundant in humans and mice. Oprm1-202 shares 92% and 87% coding sequences (CDS) and 96% and 94% amino acid sequence identity with human and mouse MOR-1, respectively. Phylogenetic trees were constructed from the CDS and amino acid sequences of nine species, including humans, cats, and mice. Both the CDS and amino acid sequences of MOP in cats showed phylogenetic development closer to that of primates than of rodents. Four SNVs were identified in the CDS of Oprm1. One SNV was located in exon 1 and the other three in exon 2 of Oprm1, all of which were synonymous substitutions. Although synonymous mutations generally have a limited functional impact, they may influence splicing and receptor expression. Further research is required to assess the effects of these SNVs on opioid efficacy, receptor expression, and analgesic responses across breeds, considering the potential breed-specific genetic factors in cat species.

PMID:40040278 | DOI:10.1177/17448069251327805

Afr J Thorac Crit Care Med. 2024 Dec 11;30(4):e1899. doi: 10.7196/AJTCCM.2024.v30i4.1899. eCollection 2024.

ABSTRACT

BACKGROUND: Bronchiectasis, a chronic suppurative lung condition, is a largely neglected disease, especially in low- to middle-income countries (LMICs), from which there is a paucity of data. Post-infectious causes are more common in LMICs, while in high-income countries, inborn errors of immunity (IEIs), recurrent aspiration, primary ciliary dyskinesia (PCD) and cystic fibrosis are more common. Children living with HIV (CLWH), especially those who are untreated, are at increased risk of bronchiectasis. Data on risk factors, diagnosis and follow-up of children with bronchiectasis are required to inform clinical practice and policy.

OBJECTIVES: To describe the demographics, medical history, aetiology, clinical characteristics and results of special investigations in children with bronchiectasis.

METHODS: We undertook a retrospective descriptive study of children aged <16 years with chest computed tomography (CT) scan-confirmed bronchiectasis in Johannesburg, South Africa, over a 10-year period. Demographics, medical history, aetiology, clinical characteristics and results of special investigations were described and compared according to HIV status.

RESULTS: A total of 91 participants (51% male, 98% black African) with a median (interquartile range) age of 7 (3 - 12) years were included in the study. Compared with HIV-uninfected children, CLWH were older at presentation (median 10 (6 - 13) years v. 4 (3 - 9) years; p<0.01), and more likely to be stunted (p<.01), to have clubbing (p<0.01) and hepatosplenomegaly (p=0.03), and to have multilobar involvement on the chest CT scan (p<0.01). All children had a cause identified, and the majority (86%) of these were presumed to be post-infectious, based on a previous history of a severe lower respiratory tract infection. This group included all 38 CLWH. Only a small proportion of the participants had IEIs, secondary immune deficiencies or PCD.

CONCLUSION: A post-infectious cause for bronchiectasis was the most common aetiology described in children from an LMIC in Africa, especially CLWH. With improved access to diagnostic techniques, the aetiology of bronchiectasis in LMICs is likely to change.

STUDY SYNOPSIS: What the study adds. In this retrospective descriptive study of children aged <16 years with chest computed tomography scan-confirmed bronchiectasis in Johannesburg, South Africa (SA), over a 10-year period, we report that a post-infectious cause for bronchiectasis was the most commonly described, and that HIV was an important contributor. A large proportion of children with bronchiectasis in low- and middle-income countries such as SA do not benefit from an extensive work-up for the non-infectious causes of bronchiectasis.Implications of the findings. With improved access to diagnostic techniques, including improvements in early diagnosis and access to treatment for children living with HIV, the aetiology of bronchiectasis is likely to change in the coming years.

PMID:40041419 | PMC:PMC11874181 | DOI:10.7196/AJTCCM.2024.v30i4.1899