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Abstract Nontuberculous mycobacteria (NTM) infection diagnosis remains a challenge due to its overlapping clinical symptoms with tuberculosis (TB), leading to inappropriate treatment. Herein, we employed noninvasive metabolic phenotyping coupled with comprehensive statistical modeling to discover potential biomarkers for the differential diagnosis of NTM infection versus TB. Urine samples from 19 NTM and 35 TB patients were collected, and untargeted metabolomics was performed using rapid liquid chromatography-mass spectrometry. The urine metabolome was analyzed using a combination of univariate and multivariate statistical approaches, incorporating machine learning. Univariate analysis revealed significant alterations in amino acids, especially tryptophan metabolism, in NTM infection compared to TB. Specifically, NTM infection was associated with upregulated levels of methionine but downregulated levels of glutarate, valine, 3-hydroxyanthranilate, and tryptophan. Five machine learning models were used to classify NTM and TB. Notably, the random forest model demonstrated excellent performance [area under the receiver operating characteristic (ROC) curve greater than 0.8] in distinguishing NTM from TB. Six potential biomarkers for NTM infection diagnosis, including methionine, valine, glutarate, 3-hydroxyanthranilate, corticosterone, and indole-3-carboxyaldehyde, were revealed from univariate ROC analysis and machine learning models. Altogether, our study suggested new noninvasive biomarkers and laid a foundation for applying machine learning to NTM differential diagnosis.

Abstract In this work, we present the results of the ortho-positronium (o-Ps) annihilation lifetimes and nitrogen adsorption measurements for different porous materials and an approach for describing the annihilation of o-Ps in a pore, which results in a surface-volume formula (SVF) for calculating the pore-related o-Ps lifetime. This proposed formula gives the relationship between the o-Ps annihilation rate and the effective pore radius, bulk composition, and pore structure, including pore geometry and topology. The pore-related o-Ps lifetimes of different materials calculated by the SVF are consistent with experimental results for both micro- and mesopores (and macropores) with different geometries and topologies. The SVF is convenient for calculations of pore dimensions for many cases of metal organic frameworks and zeolites. This approach enables us to fully explain the temperature dependence of the o-Ps annihilation lifetime over a wide temperature range, 20–700 K.

Abstract O6-Methylguanine-DNA-methyltransferase (MGMT) promoter methylation was shown in many studies to be an important predictive biomarker for temozolomide (TMZ) resistance and poor progression-free survival in glioblastoma multiforme (GBM) patients. However, identifying the MGMT methylation status using molecular techniques remains challenging due to technical limitations, such as the inability to obtain tumor specimens, high prices for detection, and the high complexity of intralesional heterogeneity. To overcome these difficulties, we aimed to test the feasibility of using a novel radiomics-based machine learning (ML) model to preoperatively and noninvasively predict the MGMT methylation status. In this study, radiomics features extracted from multimodal images of GBM patients with annotated MGMT methylation status were downloaded from The Cancer Imaging Archive (TCIA) public database for retrospective analysis. The radiomics features extracted from multimodal images from magnetic resonance imaging (MRI) had undergone a two-stage feature selection method, including an eXtreme Gradient Boosting (XGBoost) feature selection model followed by a genetic algorithm (GA)-based wrapper model for extracting the most meaningful radiomics features for predictive purposes. The cross-validation results suggested that the GA-based wrapper model achieved the high performance with a sensitivity of 0.894, specificity of 0.966, and accuracy of 0.925 for predicting the MGMT methylation status in GBM. Application of the extracted GBM radiomics features on a low-grade glioma (LGG) dataset also achieved a sensitivity 0.780, specificity 0.620, and accuracy 0.750, indicating the potential of the selected radiomics features to be applied more widely on both low- and high-grade gliomas. The performance indicated that our model may potentially confer significant improvements in prognosis and treatment responses in GBM patients.

The development of accurate predictions for a new drug's absorption, distribution, metabolism, and excretion profiles in the early stages of drug development is crucial due to high candidate failure rates. The absence of comprehensive, standardised, and updated pharmacokinetic (PK) repositories limits pre-clinical predictions and often requires searching through the scientific literature for PK parameter estimates from similar compounds. While text mining offers promising advancements in automatic PK parameter extraction, accurate Named Entity Recognition (NER) of PK terms remains a bottleneck due to limited resources. This work addresses this gap by introducing novel corpora and language models specifically designed for effective NER of PK parameters. Leveraging active learning approaches, we developed an annotated corpus containing over 4000 entity mentions found across the PK literature on PubMed. To identify the most effective model for PK NER, we fine-tuned and evaluated different NER architectures on our corpus. Fine-tuning BioBERT exhibited the best results, achieving a strict F 1 score of 90.37% in recognising PK parameter mentions, significantly outperforming heuristic approaches and models trained on existing corpora. To accelerate the development of end-to-end PK information extraction pipelines and improve pre-clinical PK predictions, the PK NER models and the labelled corpus were released open source at https://github.com/PKPDAI/PKNER ., (© 2024. The Author(s).)

Optimization algorithms (OAs) are a vital tool to deal with complex problems, and the improvement of OA is inseparable from practical strategies and mechanisms. Among the OAs, Bee Algorithm (BA) is an intelligent algorithm with a simple mechanism and easy implementation, in which effectiveness has been proven when handling optimization problems. Nevertheless, BA still has some fundamental drawbacks, which can hinder its effectiveness and accuracy. Therefore, this paper proposes a novel approach to tackle the shortcomings of BA by combining it with Genetic Algorithm (GA). The main intention is to combine the strengths of both optimization techniques, which are the exploitative search ability of BA and the robustness with the crossover and mutation capacity of GA. An investigation of a real-life suspension footbridge is considered to validate the effectiveness of the proposed method. A baseline Finite Element model of the bridge is constructed based on vibration measurement data and model updating, which is used to generate different hypothetical damage scenarios. The proposed HBGA is tested against BA, GA, and PSO to showcase its effectiveness in detecting damage for each scenario. The results show that the proposed algorithm is effective in dealing with the damage assessment problems of SHM., (© 2022. The Author(s).)

Regardless of the overwhelming use of next-generation sequencing technologies, microarray-based genotyping combined with the imputation of untyped variants remains a cost-effective means to interrogate genetic variations across the human genome. This technology is widely used in genome-wide association studies (GWAS) at bio-bank scales, and more recently, in polygenic score (PGS) analysis to predict and stratify disease risk. Over the last decade, human genotyping arrays have undergone a tremendous growth in both number and content making a comprehensive evaluation of their performances became more important. Here, we performed a comprehensive performance assessment for 23 available human genotyping arrays in 6 ancestry groups using diverse public and in-house datasets. The analyses focus on performance estimation of derived imputation (in terms of accuracy and coverage) and PGS (in terms of concordance to PGS estimated from whole-genome sequencing data) in three different traits and diseases. We found that the arrays with a higher number of SNPs are not necessarily the ones with higher imputation performance, but the arrays that are well-optimized for the targeted population could provide very good imputation performance. In addition, PGS estimated by imputed SNP array data is highly correlated to PGS estimated by whole-genome sequencing data in most cases. When optimal arrays are used, the correlations of PGS between two types of data are higher than 0.97, but interestingly, arrays with high density can result in lower PGS performance. Our results suggest the importance of properly selecting a suitable genotyping array for PGS applications. Finally, we developed a web tool that provides interactive analyses of tag SNP contents and imputation performance based on population and genomic regions of interest. This study would act as a practical guide for researchers to design their genotyping arrays-based studies. The tool is available at: https://genome.vinbigdata.org/tools/saa/ ., (© 2022. The Author(s).)

Chronic kidney disease (CKD) is a persistent impairment of kidney function. Genome-wide association studies (GWAS) have revealed multiple genetic loci associated with CKD susceptibility but the complete genetic basis is not yet clear. Since CKD shares risk factors with cardiovascular diseases and diabetes, there may be pleiotropic loci at play but may go undetected when using single phenotype GWAS. Here, we used multi-phenotype GWAS in the Norfolk Island isolate (n = 380) to identify new loci associated with CKD. We performed a principal components analysis on different combinations of 29 quantitative traits to extract principal components (PCs) representative of multiple correlated phenotypes. GWAS of a PC derived from glomerular filtration rate, serum creatinine, and serum urea identified a suggestive peak (p min  = 1.67 × 10 -7 ) that mapped to KCNIP4. Inclusion of other secondary CKD measurements with these three kidney function traits identified the KCNIP4 locus with GWAS significance (p min  = 1.59 × 10 -9 ). Finally, we identified a group of two SNPs with increased minor allele frequencies as potential functional variants. With the use of genetic isolate and the PCA-based multi-phenotype GWAS approach, we have revealed a potential pleotropic effect locus for CKD. Further studies are required to assess functional relevance of this locus., (© 2021. The Author(s).)

Micro-CT scan images enhanced by iodine staining provide high-resolution visualisation of soft tissues in laboratory mice. We have compared Micro-CT scan-derived left ventricular (LV) mass with dissection and weighing. Ex-vivo micro-CT scan images of the mouse hearts were obtained following staining by iodine. The LV was segmented and its volume was assessed using a semi-automated method by Drishti software. The left ventricle was then dissected in the laboratory and its actual weight was measured and compared against the estimated results. LV mass was calculated multiplying its estimated volume and myocardial specific gravity. Thirty-five iodine-stained post-natal mouse hearts were studied. Mice were of either sex and 68 to 352 days old (median age 202 days with interquartile range 103 to 245 days) at the time of sacrifice. Samples were from 20 genetically diverse strains. Median mouse body weight was 29 g with interquartile range 24 to 34 g. Left Ventricular weights ranged from 40.0 to 116.7 mg. The segmented LV mass estimated from micro-CT scan and directly measured dissected LV mass were strongly correlated (R 2  = 0. 97). Segmented LV mass derived from Micro-CT images was very similar to the physically dissected LV mass (mean difference = 0.09 mg; 95% confidence interval - 3.29 mg to 3.1 mg). Micro-CT scanning provides a non-destructive, efficient and accurate visualisation tool for anatomical analysis of animal heart models of human cardiovascular conditions. Iodine-stained soft tissue imaging empowers researchers to perform qualitative and quantitative assessment of the cardiac structures with preservation of the samples for future histological analysis.

Retinal arterioles, venules and capillaries are differentially affected in diabetes, and studying vascular alterations may provide information on pathogenesis of diabetic retinopathy (DR). We conducted a cross-sectional study on 49 diabetic patients, who underwent fundus photography and optical coherence tomographic angiography (OCT-A). Fundus photographs were analysed using semi-automated software for arteriolar and venular parameters, including central retinal arteriolar equivalent (CRAE), central retinal venular equivalent (CRVE) and fractal dimension (FD). Capillary parameters were measured using OCT-A, including capillary density index (CDI) and capillary FD of superficial (SVP) and deep (DVP) vascular plexuses. Severe DR was defined as severe non-proliferative DR and proliferative DR. We found that eyes with severe DR had narrower CRAE and sparser SVP CDI than eyes without. In logistic regression analysis, capillary parameters were more associated with severe DR than arteriolar or venular parameters. However, combining arteriolar, venular and capillary parameters provided the strongest association with severe DR. In linear regression analysis, eyes with poorer visual acuity had lower CRAE and FD of arterioles, venules, and DVP capillaries. We concluded that the retinal microvasculature is globally affected in severe DR, reflecting widespread microvascular impairment in perfusion. Arteriolar, venular and capillary parameters provide complementary information in assessment of DR.

We investigated the effect of various dietary polyunsaturated fatty acid (PUFA) sources on the fatty acid profiles of muscle, liver, heart and kidney of Australian prime lambs. Seventy-two White Suffolk x Corriedale first-cross lambs weaned at 6 months of age were randomly allocated to the following six treatments: (1) Control: Lucerne hay only; wheat-based pellets infused with 50 ml/kg dry matter (DM) of oil from (2) rice bran (RBO); (3) canola (CO); (4) rumen-protected (RPO), (5) flaxseed (FSO) and (6) safflower (SO) sources in a completely randomized experimental design. Lambs in CO, FSO, SO and RPO treatments achieved contents of eicosapentaenoic acid (EPA, 22:5n-3) plus docosahexaenoic acid (DHA, 22:6n-3) in the longissimus dorsi muscle ranging from 31.1 to 57.1 mg/135 g, over and above the 30 mg per standard serve (135 g) threshold for "source" claim under the Australian guidelines. There was no difference in n-3 LC-PUFA contents in longissimus dorsi muscle of lambs fed dietary oils of plant origin. The highest 18:3n-3 (ALA) contents achieved with FSO diet in the muscle, liver and heart were 45.6, 128.1 and 51.3 mg/100 g, respectively. Liver and kidney contained high contents of n-3 LC-PUFA (ranging from 306.7 to 598.2 mg/100 g and 134.0 to 300.4 mg/100 g, respectively), with all values readily exceeding the 'good source' status (60 mg per serve under Australian guidelines). The liver and kidney of PUFA fed lambs can be labelled as 'good source' of n-3 LC-PUFA based on EPA and DHA contents stipulated by the Food Standards of Australia and New Zealand guidelines. Therefore, if lamb consumers consider eating the liver and kidney as their dietary protein sources, they can adequately obtain the associated health benefits of n-3 LC-PUFA.

We previously identified peptides that are actively transported across the intact tympanic membrane (TM) of rats with infected middle ears. To assess the possibility that this transport would also occur across the human TM, we first developed and validated an assay to evaluate transport in vitro using fragments of the TM. Using this assay, we demonstrated the ability of phage bearing a TM-transiting peptide to cross freshly dissected TM fragments from infected rats or from uninfected rats, guinea pigs and rabbits. We then evaluated transport across fragments of the human TM that were discarded during otologic surgery. Human trans-TM transport was similar to that seen in the animal species. Finally, we found that free peptide, unconnected to phage, was transported across the TM at a rate comparable to that seen for peptide-bearing phage. These studies provide evidence supporting the concept of peptide-mediated drug delivery across the intact TM and into the middle ears of patients.