Miracle-dz/UniFAR-FTUs huggingface dataset:
Baicalin Inhibits Biofilm Formation and the Quorum-Sensing System by Regulating the MsrA Drug Efflux Pump in Staphylococcus saprophyticus

Staphylococcus saprophyticus (S. saprophyticus) is one of the main pathogens that cause serious infection due to its acquisition of antibiotic resistance. The efflux pump decreases antibiotic abundance, and biofilm compromises the penetration of antibiotics. It has been reported that baicalin is a potential agent to inhibit efflux pumps, biofilm formation, and quorum-sensing systems. The purpose of this study was to investigate whether baicalin can inhibit S. saprophyticus biofilm formation and the quorum-sensing system by inhibiting the MsrA efflux pump. First, the mechanism of baicalin inhibiting efflux was investigated by the ethidium bromide (EtBr) efflux assay, measurement of ATP content, and pyruvate kinase (PK) activities. These results revealed that baicalin significantly reduced the efflux of EtBr, the ATP content, and the activity of PK. Moreover, its role in biofilm formation and the agr system was studied by crystal violet staining, confocal laser scanning microscopy, scanning electron microscopy, and real-time polymerase chain reaction. These results showed that baicalin decreased biofilm formation, inhibited bacterial aggregation, and downregulated mRNA transcription levels of the quorum-sensing system regulators agrA, agrC, RNAIII, and sarA. Correlation analysis indicated that there was a strong positive correlation between the efflux pump and biofilm formation and the agr system. We demonstrate for the first time that baicalin inhibits biofilm formation and the agr quorum-sensing system by inhibiting the efflux pump in S. saprophyticus. Therefore, baicalin is a potential therapeutic agent for S. saprophyticus biofilm-associated infections.
The Role of Radical Prostatectomy and Lymph Node Dissection in Clinically Node Positive Patients

Patients diagnosed with clinically node-positive prostate cancer represent a population that has historically been thought to harbor systemic disease. Increasing evidence supports the role of local therapies in advanced disease, but few studies have focused on this particular population. In this review we discuss the limited role for conventional cross sectional imaging for accurate nodal staging and how molecular imaging, although early results are promising, is still far from widespread clinical utilization. To date, evidence regarding the role of radical prostatectomy and pelvic lymph node dissection in clinically node-positive disease comes from retrospective studies; overall surgery appears to be a reasonable option in selected patients, with improved oncological outcomes that could be attributed to both to its potential curative role in disease localized to the pelvis and to the improved staging to help guide subsequent multimodal treatment. The role of surgery in clinically node-positive disease needs higher-level evidence but meanwhile, radical prostatectomy with extended pelvic lymph-node dissection can be offered as a part of a multimodality approach with the patient.
Radiomics in paediatric neuro-oncology : MRI textural features as diagnostic and prognostic biomarkers

Motivation: Brain and central nervous system tumours form the second most common group of cancers in children in the UK, accounting for 27% of all childhood cancers. Despite current advances in magnetic resonance imaging (MRI), non-invasive characterisation of paediatric brain tumours remains challenging. Radiomics, the high-throughput extraction and analysis of quantitative image features (e.g. texture), offers potential solutions for tumour characterisation and decision support. Aim and Methods: In search for diagnostic and prognostic oncological markers, the aim of this thesis was to study the application of MRI texture analysis (TA) for the characterisation of paediatric brain tumours. To this end, single and multi-centre experiments were carried out, within a supervised classification framework, on clinical MR imaging datasets of common brain tumour types. Results: TA of conventional MRI was successfully used for diagnostic classification of common paediatric brain tumours. A key contribution of this thesis was to provide evidence that diagnostic classification could be optimised by extending the analysis to include three-dimensional features obtained from multiple MR imaging slices. In addition to this, TA was shown to have a good cross-centre transferability, which is essential for long-term clinical adoption of the technique. Finally, fifteen textural features extracted from T2-weighted MRI were identified to be of significant prognostic value for paediatric medulloblastoma. Conclusion: It was shown that MRI TA provides valuable quantifiable information that can supplement qualitative assessments conducted by radiologists, for the characterisation of paediatric brain tumours. TA can potentially have a large clinical impact, since MR imaging is routinely used in the brain cancer clinical work-flow worldwide, providing an opportunity to improve personalised healthcare and decision-support at low cost.
The Role of Heterotrophic Bacteria and Archaea in the Transformation of Lignin in the Open Ocean

Abstract The pelagic ocean receives terrigenous inputs of a range of organic compounds; however, the role that this terrigenous material plays in the ocean carbon cycle and biological pump is not entirely understood, and questions remain as to how oceanic cycles of terrigenous and autochthonous carbon interact. A significant portion of organic carbon that cannot be utilized by marine microbes in the epipelagic ocean escapes microbial remineralization to be sequestered in the deep ocean as refractory dissolved organic matter. Lignin, a ‘model’ terrigenous compound, is thought to be refractory in the open ocean unless chemically altered. However, in this study, incubation experiments performed using lignin-amended oligotrophic seawater from the Sargasso Sea exhibited bacteria and archaea growth that doubled compared to unamended control treatments. The increase in bacteria and archaea cell abundance in lignin-amended treatments coincided with a 21-25% decrease in absorbance (250 – 400 nm) of chromophoric dissolved organic matter (CDOM), suggesting that certain microbes may be capable of altering fractions of this ostensibly recalcitrant organic matter. Furthermore, the microbial response to the lignin-amended treatments appears to be taxon-specific. Two phyla of Archaea, Euryarchaeota and Thaumarchaeota, exhibited an increase in abundance of 7 fold and 28 fold (from 2.42 x 106 cells L-1 to 1.72 x 107 cells L-1, and from 1.60 x 106 cells L-1 to 4.54 x 107 cells L-1, respectively), over four days of incubation in lignin-amended treatments. Additionally, an increase of 11 fold and 13 fold, (from 2.93 x 106 cells L-1 to 3.30 x 107 cells L-1, and from 3.26 x 106 cells L-1 to 4.28 x 107 cells L-1, respectively) was observed in the abundance of these phyla in treatments containing lignin with added nitrogen and phosphorus, thus raising questions regarding primary and / or secondary responses to lignin degradation. Our findings indicate that marine bacteria and archaea play a role in the transformation of the optical properties of lignin in the open ocean and that they may serve as a potential sink for a portion of the lignin macromolecule.
Amide Proton Transfer Weighted Imaging Shows Differences in Multiple Sclerosis Lesions and White Matter Hyperintensities of Presumed Vascular Origin

Objectives: To assess the ability of 3D amide proton transfer weighted (APTw) imaging based on magnetization transfer analysis to discriminate between multiple sclerosis lesions (MSL) and white matter hyperintensities of presumed vascular origin (WMH) and to compare APTw signal intensity of healthy white matter (healthy WM) with APTw signal intensity of MSL and WHM. Materials and Methods: A total of 27 patients (16 female, 11 males, mean age 39.6 years) with multiple sclerosis, 35 patients (17 females, 18 males, mean age 66.6 years) with small vessel disease (SVD) and 20 healthy young volunteers (9 females, 11 males, mean age 29 years) were included in the MSL, the WMH, and the healthy WM group. MSL and WMH were segmented on fluid attenuated inversion recovery (FLAIR) images underlaid onto APTw images. Histogram parameters (mean, median, 10th, 25th, 75th, 90th percentile) were calculated. Mean APTw signal intensity values in healthy WM were defined by “Region of interest” (ROI) measurements. Wilcoxon rank sum tests and receiver operating characteristics (ROC) curve analyses of clustered data were applied. Results: All histogram parameters except the 75 and 90th percentile were significantly different between MSL and WMH (p = 0.018–p = 0.034). MSL presented with higher median values in all parameters. The histogram parameters offered only low diagnostic performance in discriminating between MSL and WMH. The 10th percentile yielded the highest diagnostic performance with an AUC of 0.6245 (95% CI: [0.532, 0.717]). Mean APTw signal intensity values of MSL were significantly higher than mean values of healthy WM (p = 0.005). The mean values of WMH did not differ significantly from the values of healthy WM (p = 0.345). Conclusions: We found significant differences in APTw signal intensity, based on straightforward magnetization transfer analysis, between MSL and WMH and between MSL and healthy WM. Low AUC values from ROC analyses, however, suggest that it may be challenging to determine type of lesion with APTw imaging. More advanced analysis of the APT CEST signal may be helpful for further differentiation of MSL and WMH.
Micro-Ultrasound Imaging for Accuracy of Diagnosis in Clinically Significant Prostate Cancer: A Meta-Analysis

Background: Prostate cancer is a frequently diagnosed malignant solid tumor in men. The accuracy of diagnosis is becoming increasingly important. This meta-analysis evaluated the accuracy of micro-ultrasound in the diagnosis of clinically significant prostate cancer. Methods: We searched PubMed, Embase, Web of Science, and Cochrane Library databases to recruit studies in English. The quality assessment of diagnostic accuracy studies-2 protocol was used to evaluate the literature quality. Publication bias was analyzed using Deeks' funnel plot asymmetry test. We calculated the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and 95% confidence interval (95% CI) for studies of micro-ultrasound imaging for prostate cancer. The results were assessed by the summary receiver-operating characteristic curve (SROC). Ultimately, a univariable meta-regression and subgroup analysis, Fagan plot, and a likelihood matrix were conducted. Results: A total of seven studies containing 769 patients were included in this meta-analysis. Micro-ultrasound had a pooled sensitivity, specificity, DOR, and an area under the SROC of 0.91, 0.49, 10, and 0.82, respectively. Based on these findings, micro-ultrasound has superior ability to diagnose clinically significant prostate cancer. Conclusion: Micro-ultrasound is a more convenient and cost-effective method in real-time imaging during the biopsy procedure in detecting clinically significant prostate cancer. Although micro-ultrasound has shown promising results, more clinical data and comprehensive analysis are still needed.
Identifying SNAREs by Incorporating Deep Learning Architecture and Amino Acid Embedding Representation

SNAREs (soluble N-ethylmaleimide-sensitive factor activating protein receptors) are a group of proteins that are crucial for membrane fusion and exocytosis of neurotransmitters from the cell. They play an important role in a broad range of cell processes, including cell growth, cytokinesis, and synaptic transmission, to promote cell membrane integration in eukaryotes. Many studies determined that SNARE proteins have been associated with a lot of human diseases, especially in cancer. Therefore, identifying their functions is a challenging problem for scientists to better understand the cancer disease as well as design the drug targets for treatment. We described each protein sequence based on the amino acid embeddings using fastText, which is a natural language processing model performing well in its field. Because each protein sequence is similar to a sentence with different words, applying language model into protein sequence is challenging and promising. After generating, the amino acid embedding features were fed into a deep learning algorithm for prediction. Our model which combines fastText model and deep convolutional neural networks could identify SNARE proteins with an independent test accuracy of 92.8%, sensitivity of 88.5%, specificity of 97%, and Matthews correlation coefficient (MCC) of 0.86. Our performance results were superior to the state-of-the-art predictor (SNARE-CNN). We suggest this study as a reliable method for biologists for SNARE identification and it serves a basis for applying fastText word embedding model into bioinformatics, especially in protein sequencing prediction.
Salivary Biomarkers for Oral Squamous Cell Carcinoma Diagnosis and Follow-Up: Current Status and Perspectives

Oral cancer is the sixth most common cancer type in the world, and 90% of it is represented by oral squamous cell carcinoma (OSCC). Despite progress in preventive and therapeutic strategies, delay in OSCC diagnosis remains one of the major causes of high morbidity and mortality; indeed the majority of OSCC has been lately identified in the advanced clinical stage (i.e., III or IV). Moreover, after primary treatment, recurrences and/or metastases are found in more than half of the patients (80% of cases within the first 2 years) and the 5-year survival rate is still lower than 50%, resulting in a serious issue for public health. Currently, histological investigation represents the “gold standard” of OSCC diagnosis; however, recent studies have evaluated the potential use of non-invasive methods, such as “liquid biopsy,” for the detection of diagnostic and prognostic biomarkers in body fluids of oral cancer patients. Saliva is a biofluid containing factors such as cytokines, DNA and RNA molecules, circulating and tissue-derived cells, and extracellular vesicles (EVs) that may be used as biomarkers; their analysis may give us useful information to do early diagnosis of OSCC and improve the prognosis. Therefore, the aim of this review is reporting the most recent data on saliva biomarker detection in saliva liquid biopsy from oral cancer patients, with particular attention to circulating tumor DNA (ctDNA), EVs, and microRNAs (miRNAs). Our results highlight that saliva liquid biopsy has several promising clinical uses in OSCC management; it is painless, accessible, and low cost and represents a very helpful source of diagnostic and prognostic biomarker detection. Even if standardized protocols for isolation, characterization, and evaluation are needed, recent data suggest that saliva may be successfully included in future clinical diagnostic processes, with a considerable impact on early treatment strategies and a favorable outcome.
Children With Metabolically Healthy Obesity: A Review

Children with “metabolically healthy obesity” (MHO) are a distinct subgroup of youth with obesity, who are less prone to the clustering of cardiometabolic risk factors. Although this phenotype, frequently defined by the absence of metabolic syndrome components or insulin resistance, was first described during the early 1980s, a consensus-based definition of pediatric MHO was introduced only recently, in 2018. The purpose of this review was to concisely summarize current knowledge regarding the MHO phenomenon in youth. The prevalence of MHO in children varies from 3 to 87%, depending on the definition used and the parameters evaluated, as well as the ethnicity and the pubertal status of the sample. The most consistent predictors of MHO in youth include younger age, lower body mass index, lower waist circumference, and lower body fat measurements. Various hypotheses have been proposed to elucidate the underlying factors maintaining the favorable MHO phenotype. While preserved insulin sensitivity and lack of inflammation were previously considered to be the main etiological factors, the most recent findings have implicated adipokine levels, the number of inflammatory immune cells in the adipose tissue, and the reduction of visceral adiposity due to adipose tissue expandability. Physical activity and genetic factors also contribute to the MHO phenotype. Obesity constitutes a continuum-increased risk for cardiometabolic complications, which is less evident in children with MHO. However, some findings have highlighted the emergence of hepatic steatosis, increased carotid intima-media thickness and inflammatory biomarkers in the MHO group compared to peers without obesity. Screening should be directed at those more likely to develop clustering of cardiometabolic risk factors. Lifestyle modifications should include behavioral changes focusing on sleep duration, screen time, diet, physical activity, and tobacco smoke exposure. Weight loss has also been associated with the improvement of insulin sensitivity and inflammation. Further investigative efforts are needed in order to elucidate the mechanisms which protect against the clustering of cardiometabolic risk factors in pediatric obesity, to provide more efficient, targeted treatment approaches for children with obesity, and to identify the protective factors preserving the MHO profile, avoiding the crossover of MHO to the phenotype with metabolically unhealthy obesity.
The Initial Oral Microbiota of Neonates Among Subjects With Gestational Diabetes Mellitus

Objective: The objective was to investigate the potential effect of gestational diabetes mellitus on the initial neonatal oral microbiome community structure. Methods: Oral samples were collected from 20 full-term, vaginally delivered newborns with sterile swabs. Nine of them had mothers diagnosed with gestational diabetes mellitus (GDM group), while 11 had non-diabetic mothers (NDM group). The oral microbiota was analyzed using multi-barcode 16S rRNA sequencing on Illumina MiSeq system. Results: The results showed that the birth weight, gestational age and gestational weight gain were significantly higher in NDM group. There was a significant correlation between gestational age and birth weight. Neonatal oral microbiome was composed of five dominant phyla from Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria, and Tenericutes. Compared to NDM group, a higher alpha diversity and reduction of phylum Firmicutes were observed in GDM group. Genus Lactobacillus dominated in NDM group, while Alistipes, Streptococcus, and Faecalibacterium were overabundant in GDM group. Additionally, carbohydrate metabolism increased in NDM group, whereas amino acid metabolism, vitamin metabolism and lipopolysaccharide biosynthesis were more abundant in GDM group. Conclusions: This study showed a distinct oral microbiota profile in neonates born to mothers with GDM, which indicated that maternal diabetes status played an important role in neonatal initial oral microbiota.
A Spike Train Distance Robust to Firing Rate Changes Based on the Earth Mover’s Distance

Neural spike train analysis methods are mainly used for understanding the temporal aspects of neural information processing. One approach is to measure the dissimilarity between the spike trains of a pair of neurons, often referred to as the spike train distance. The spike train distance has been often used to classify neuronal units with similar temporal patterns. Several methods to compute spike train distance have been developed so far. Intuitively, a desirable distance should be the shortest length between two objects. The Earth Mover’s Distance (EMD) can compute spike train distance by measuring the shortest length between two spike trains via shifting a fraction of spikes from one spike train to another. The EMD could accurately measure spike timing differences, temporal similarity, and spikes time synchrony. It is also robust to firing rate changes. Victor and Purpura (1996) distance measures the minimum cost between two spike trains. Although it also measures the shortest path between spike trains, its output can vary with the time-scale parameter. In contrast, the EMD measures distance in a unique way by calculating the genuine shortest length between spike trains. The EMD also outperforms other existing spike train distance methods in measuring various aspects of the temporal characteristics of spike trains and in robustness to firing rate changes. The EMD can effectively measure the shortest length between spike trains without being considerably affected by the overall firing rate difference between them. Hence, it is suitable for pure temporal coding exclusively, which is a predominant premise underlying the present study.
New Dihydroisocoumarin Root Growth Inhibitors From the Sponge-Derived Fungus Aspergillus sp. NBUF87

Six new dihydroisocoumarins, aspergimarins A−F (1−6), were discovered together with five known analogs (7−11) from a monoculture of the sponge-derived fungus Aspergillus sp. NBUF87. The structures of these compounds were elucidated through comprehensive spectroscopic methods, and absolute configurations were assigned after X-ray crystallography, use of the modified Mosher’s method, and comparison of electronic circular dichroism (ECD) data with literature values for previously reported analogs. Compounds 1−11 were evaluated in a variety of bioassays, and at 100 μM, both 1 and 5 showed significant inhibitory effects on the lateral root growth of Arabidopsis thaliana Columbia-0 (Col-0). Moreover, at 100 μM, 5 also possessed notable inhibition against the primary root growth of Col-0. Meanwhile, 1−11 were all found to be inactive in vitro against acetylcholinesterase (AChE) (IC50 > 100 μM), four different types of human-derived cancer cell lines (IC50 > 50 μM), as well as methicillin-resistant Staphylococcus aureus and Escherichia coli (MIC > 50 μg/mL), and Plasmodium falciparum W2 (EC50 > 100 μg/mL), in phenotypic tests.