Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of Kelch domain-containing protein 7B in breast tumours and breast cancer cell lines

Adenocarcinomas exhibit great heterogeneity, with many genetic and epigenetic alterations. The Kelch domain-containing protein 7B (KLHDC7B) has recently been identified as epigenetically modified and upregulated in breast cancer. The potential reversibility of epigenetic states offers exciting possibilities for novel cancer diagnostics and drugs. However, to properly evaluate specific inhibitors, the role of KLHDC7B in the development and progression of breast cancer should be established. With that objective in mind, the present study investigated a series of human breast tumours and correlated their clinicopathology, according to the Elston-Ellis modification of the Scarff-Bloom-Richardson (SBR) grading system, with KLHDC7B mRNA expression, analysed using quantitative PCR (qPCR). The results revealed that KLHDC7B was significantly upregulated in grade 3 tumours, and that KLHDC7B expression varied according to the tumour grade and the individual, being downregulated in well-differentiated and moderately-differentiated tumours (grade 1–2) and upregulated in poorly-differentiated tumours (grade 3). Immunohistochemical staining revealed that ductal tumours and tumours with a higher percentage of Ki67 positive cells showed the highest levels of KLHDC7B. Receptor expression, HER, p53 status, presence of metastasis, and vascular invasion showed no association with KLHDC7B expression. Previous studies have proposed KLHDC7B as an epigenetic marker of breast cancer. We propose that KLHDC7B should be used as a marker for poorly-differentiated tumours only; use of KLHDC7B without considering tumour grade could lead to an inaccurate diagnosis. Finally, we suggest the appropriate breast cancer cell lines to use to determine the functions of KLHDC7B. KLHDC7B expression was tested in the non-tumour cell line MCF-10A and in the breast cancer cell lines MCF-7, MDA-MB-231 and MDA-MB-468, using qPCR and western blotting. The results revealed that all tested cancer cell lines overexpressed KLHDC7B mRNA, but MDA-MB-468 exhibited a much lower level of protein expression relative to mRNA. Although the breast cancer cell lines used may be appropriate for studying KLHDC7B epigenetic status, MDA-MB-468 should be excluded from functional experiments.
Identification of iron and zinc responsive genes in pearl millet using genome-wide RNA-sequencing approach

Pearl millet (Pennisetum glaucum L.), an important source of iron (Fe) and zinc (Zn) for millions of families in dryland tropics, helps in eradicating micronutrient malnutrition. The crop is rich in Fe and Zn, therefore, identification of the key genes operating the mineral pathways is an important step to accelerate the development of biofortified cultivars. In a first-of-its-kind experiment, leaf and root samples of a pearl millet inbred ICMB 1505 were exposed to combinations of Fe and Zn stress conditions using the hydroponics method, and a whole-genome transcriptome assay was carried out to characterize the differentially expressed genes (DEGs) and pathways. A total of 37,093 DEGs under different combinations of stress conditions were identified, of which, 7,023 and 9,996 DEGs were reported in the leaf and root stress treatments, respectively. Among the 10,194 unique DEGs, 8,605 were annotated to cellular, biological, and molecular functions and 458 DEGs were assigned to 39 pathways. The results revealed the expression of major genes related to the mugineic acid pathway, phytohormones, chlorophyll biosynthesis, photosynthesis, and carbohydrate metabolism during Fe and Zn stress. The cross-talks between the Fe and Zn provided information on their dual and opposite regulation of key uptake and transporter genes under Fe and Zn deficiency. SNP haplotypes in rice, maize, sorghum, and foxtail millet as well as in Arabidopsis using pearl millet Fe and Zn responsive genes could be used for designing the markers in staple crops. Our results will assist in developing Fe and Zn-efficient pearl millet varieties in biofortification breeding programs and precision delivery mechanisms to ameliorate malnutrition in South Asia and Sub-Saharan Africa.
Visualisation of cerebral arteries by means of cycled super-selective arterial spin labeling angiography

Poster: "ECR 2016 / C-2064 / Visualisation of cerebral arteries by means of cycled super-selective arterial spin labeling angiography" by: "T. Lindner1, O. Jansen1, M. Helle2; 1Kiel/DE, 2Hamburg/DE"
Multi-modal feature selection with anchor graph for Alzheimer's disease

In Alzheimer's disease, the researchers found that if the patients were treated at the early stage of the disease, it could effectively delay the development of the disease. At present, multi-modal feature selection is widely used in the early diagnosis of Alzheimer's disease. However, existing multi-modal feature selection algorithms focus on learning the internal information of multiple modalities. They ignore the relationship between modalities, the importance of each modality and the local structure in the multi-modal data. In this paper, we propose a multi-modal feature selection algorithm with anchor graph for Alzheimer's disease. Specifically, we first use the least square loss and l2,1−norm to obtain the weight of the feature under each modality. Then we embed a modal weight factor into the objective function to obtain the importance of each modality. Finally, we use anchor graph to quickly learn the local structure information in multi-modal data. In addition, we also verify the validity of the proposed algorithm on the published ADNI dataset.
A case study and parametric analysis of predicting hurricane-induced building damage using data-driven machine learning approach

As coastal populations increase every year, greater numbers of people and buildings to support them are left vulnerable to severe hazards associated with hurricanes, which have shown signs of increasing strength and frequency related to climate change. Community-level decision making is essential to adequately prepare populations for the risks associated with imminent hurricanes and to adapt buildings to be more resilient. This creates a need for state-of-the-art methods such as data-driven machine learning to predict the damage that buildings will experience during hurricanes and support decisions for community stakeholders. Previous research has attempted to proactively forecast hurricane damage using numerical frameworks for individual building archetypes or by incorporating a narrow spectrum of input features. The focus of this study is a novel machine learning framework trained on building, hazard, and geospatial data to hindcast damage from Hurricanes Harvey, Irma, Michael, and Laura, with the objective of forecasting expected damage from future hurricanes. Performance of different algorithms were investigated including k-nearest neighbors, decision tree, random forest, and gradient boosting trees algorithms. In predicting qualitative damage states, random forest outperforms other algorithms with 76% accuracy in the hindcast. Parametric studies identify which features contribute the most to accurate predictions and demonstrate that prediction accuracy increases linearly for this case study with additional reconnaissance data to train the model. Finally, a comparison is drawn between this model and the ability of Federal Emergency Management Agency’s Hazus Multi-Hazard Hurricane Model to estimate building-specific damage on the same hindcast set of buildings.
We can’t afford the candy! The influence of parenting by lying about money on mobile phone addiction and the roles of anxiety and socioeconomic status among Chinese adolescents

Background Extant research has indicated that parenting practice, such as harsh parenting, rejection, and neglect increases the risk of mobile phone addiction. However, no research to date has examined the association between parenting by lying about money and adolescent mobile phone addiction. Objective The current study used a survey to test whether parenting by lying about money may be associated with adolescent mobile phone addiction. The mediation of anxiety and moderation of socioeconomic status were also examined. Materials and methods We recruited 971 adolescents from five secondary schools in a city in central China. Of the participants, 448 (46.14%) were boys and 523 (53.86%) were girls (Mage = 13.63, SDage = 1.01). Results The results of mediation analysis indicated that parenting by lying about money positively predicted mobile phone addiction (B = 0.144, p < 0.01); parenting by lying about money positively predicted anxiety (B = 0.126, p < 0.01) and mobile phone addiction (B = 0.107, p < 0.01). Anxiety positively predicted mobile phone addiction (B = 0.293, p < 0.01). Moreover, the bias-corrected bootstrapping mediation test indicated that the process by which parenting by lying about money predicted mobile phone addiction through anxiety was significant (indirect effect = 0.037, SE = 0.011, 95% CI = [0.017, 0.059]). Conclusion The current study suggests that parenting by lying about money may lead to mobile phone addiction through the mediation of anxiety. However, the effect was stronger for adolescents with higher level of socioeconomic status than their counterparts.
Effect of water intake on postexercise cardiovascular recovery

Physical exercise elicits an increase in heart rate (HR), blood pressure (BP) and, consequently, in the rate-pressure product (RPP). Recovery of HR immediately after exercise indicates cardiovascular health. Blood pressure also decreases after exercise, occasionally reaching values lower than pre-exercise levels (postexercise hypotension). Studies have shown a positive effect of water intake on HR recovery after exercise. However, little is known about the effect of water intake on postexercise BP and RPP responses. The objective of this study was to evaluate the effects of water intake on postexercise cardiac work assessed by HR, BP and RPP. Fourteen healthy volunteers (22 ± 1.4 years) participated in the study. The experimental session consisted of HR, systolic (SBP) and diastolic BP (DBP) recording at rest, followed by submaximal exercise on a cycle ergometer. Next, the subjects consumed water and the cardiovascular variables were recorded during recovery. In addition, a control session without postexercise water intake was performed. The RPP was calculated from the product of HR and SBP. Water intake prevented a postexercise hypotensive effect on DBP, but accelerated postexercise HR and RPP reduction during recovery when compared to the control session. It was concluded that water intake is an effective strategy to reduce postexercise cardiac work.
Isoimperatorin enhances 3T3-L1 preadipocyte differentiation by regulating PPARγ and C/EBPα through the Akt signaling pathway

Lipodystrophic patients have an adipose tissue triglyceride storage defect that causes ectopic lipid accumulation, leading to severe insulin resistance. The present study investigated the potential role of isoimperatorin on 3T3-L1 adipocyte differentiation. mRNA and protein levels of differentiation- and lipid accumulation-associated genes, as well as the adipogenesis-related signaling pathway were analyzed in control and isoimperatorin-treated differentiated 3T3-L1 adipocytes using reverse transcription-quantitative PCR and western blot analysis. Results determined that isoimperatorin promoted 3T3-L1 fibroblast adipogenesis in a dose-dependent manner compared with standard differentiation inducers. Isoimperatorin significantly increased mRNA and protein expression of the crucial adipogenic transcription factors peroxisome proliferator activated receptor-γ (PPARγ) and CCAAT enhancer binding protein-α (C/EBPα). mRNA expression of the downstream adipogenesis-related genes sterol regulatory element-binding transcription factor 1c, adipocyte protein 2, fatty acid synthase, adiponectin and diacylglycerol O-acyltransferase 2 were also significantly increased following isoimperatorin treatment. The underlying mechanism likely involved activation of the Akt signaling pathway. Taken together, the present findings indicated that isoimperatorin may alter PPARγ and C/EBPα expression via the Akt signaling pathway, resulting in promotion of adipogenesis. The results highlighted the potential use of isoimperatorin as a therapeutic agent for preventing diabetes.
Transfer learning in hand movement intention detection based on surface electromyography signals

Over the past several years, electromyography (EMG) signals have been used as a natural interface to interact with computers and machines. Recently, deep learning algorithms such as Convolutional Neural Networks (CNNs) have gained interest for decoding the hand movement intention from EMG signals. However, deep networks require a large dataset to train appropriately. Creating such a database for a single subject could be very time-consuming. In this study, we addressed this issue from two perspectives: (i) we proposed a subject-transfer framework to use the knowledge learned from other subjects to compensate for a target subject’s limited data; (ii) we proposed a task-transfer framework in which the knowledge learned from a set of basic hand movements is used to classify more complex movements, which include a combination of mentioned basic movements. We introduced two CNN-based architectures for hand movement intention detection and a subject-transfer learning approach. Classifiers are tested on the Nearlab dataset, a sEMG hand/wrist movement dataset including 8 movements and 11 subjects, along with their combination, and on open-source hand sEMG dataset “NinaPro DataBase 2 (DB2). ” For the Nearlab database, the subject-transfer learning approach improved the average classification accuracy of the proposed deep classifier from 92.60 to 93.30% when classifier was utilizing 10 other subjects’ data via our proposed framework. For Ninapro DB2 exercise B (17 hand movement classes), this improvement was from 81.43 to 82.87%. Moreover, three stages of analysis in task-transfer approach proved that it is possible to classify combination hand movements using the knowledge learned from a set of basic hand movements with zero, few samples and few seconds of data from the target movement classes. First stage takes advantage of shared muscle synergies to classify combined movements, while second and third stages take advantage of novel algorithms using few-shot learning and fine-tuning to use samples from target domain to further train the classifier trained on the source database. The use of information learned from basic hand movements improved classification accuracy of combined hand movements by 10%.
Spinal Cord Stimulation for Freezing of Gait: From Bench to Bedside

Spinal cord stimulation (SCS) has been used for the treatment of chronic pain for nearly five decades. With a high degree of efficacy and a low incidence of adverse events, it is now considered to be a suitable therapeutic alternative in most guidelines. Experimental studies suggest that SCS may also be used as a therapy for motor and gait dysfunction in parkinsonian states. The most common and disabling gait dysfunction in patients with Parkinson's disease (PD) is freezing of gait (FoG). We review the evolution of SCS for gait disorders from bench to bedside and discuss potential mechanisms of action, neural substrates, and clinical outcomes.
Mycobacterium tuberculosis Rv0790c inhibits the cellular autophagy at its early stage and facilitates mycobacterial survival

Rv0790c is predicted to be a conserved hypothetical protein encoded by Mycobacterium tuberculosis (Mtb). However, its function in Mtb infection remains largely unknown. In this study, we found that Rv0790c promoted bacillary survival of M. smegmatis (Ms), both in vitro and in vivo. The bacillary burden of Ms exogenously expressing Rv0790c increased, whereas in Rv0790c-knockouts the bacillary burden decreased in infected macrophages. Multiple cellular processes were analyzed to explore the underlying mechanisms. We found that neither inflammatory regulation nor apoptotic induction were responsible for the promotion of bacillary survival mediated by Rv0790c. Interestingly, we found that Rv0790c facilitates mycobacterial survival through cellular autophagy at its early stage. Immunoprecipitation assay of autophagy initiation-related proteins indicated that Rv0790c interacted with mTOR and enhanced its activity, as evidenced by the increased phosphorylation level of mTOR downstream substrates, ULK-1, at Ser757 and P70S6K, at Thr389. Our study uncovers a novel autophagy suppressor encoded by mycobacterial Rv0790c, which inhibits the early stage of cellular autophagy induction upon Mtb infection and takes an important role in maintaining intracellular mycobacterial survival. It may aid in understanding the mechanism of Mtb evasion of host cellular degradation, as well as hold the potential to develop new targets for the prevention and treatment of tuberculosis.
The large numbers of minicolumns in the primary visual cortex of humans, chimpanzees and gorillas are related to high visual acuity

Minicolumns are thought to be a fundamental neural unit in the neocortex and their replication may have formed the basis of the rapid cortical expansion that occurred during primate evolution. We sought evidence of minicolumns in the primary visual cortex (V-1) of three great apes, three rodents and representatives from three other mammalian orders: Eulipotyphla (European hedgehog), Artiodactyla (domestic pig) and Carnivora (ferret). Minicolumns, identified by the presence of a long bundle of radial, myelinated fibers stretching from layer III to the white matter of silver-stained sections, were found in the human, chimpanzee, gorilla and guinea pig V-1. Shorter bundles confined to one or two layers were found in the other species but represent modules rather than minicolumns. The inter-bundle distance, and hence density of minicolumns, varied systematically both within a local area that might represent a hypercolumn but also across the whole visual field. The distance between all bundles had a similar range for human, chimpanzee, gorilla, ferret and guinea pig: most bundles were 20–45 μm apart. By contrast, the space between bundles was greater for the hedgehog and pig (20–140 μm). The mean density of minicolumns was greater in tangential sections of the gorilla and chimpanzee (1,243–1,287 bundles/mm2) than in human (314–422 bundles/mm2) or guinea pig (643 bundles/mm2). The minicolumnar bundles did not form a hexagonal lattice but were arranged in thin curving and branched bands separated by thicker bands of neuropil/somata. Estimates of the total number of modules/minicolumns within V-1 were strongly correlated with visual acuity.
Examining The Association Between Self-Reported Postpartum Depression and Breastfeeding Habits of Women In Georgia

Postpartum depression affects approximately 13% of women and negatively impacts their partners and children. This interpretive phenomenological study explored the lived experience of postpartum depression. Rich descriptions of four women’s experiences were collected through conversational interviews, a focus group and fabric art. Three themes were identified: cast adrift, torn asunder and safely home. The findings suggested that women experience isolation, loss of identity and loss of sanity. Positive aspects of PPD were also revealed. Implications for nursing practice suggest increased targeted supportive programs for women shown to be at risk for PPD and increased support for all women and their families during the transition to parenthood. Recommendations for future nursing research include attention to fathers’ postpartum experiences and the need for longitudinal studies of women’s PPD experiences. Finally, nurse researchers are encouraged to use artwork as a source of rich data. Lived Experience of Postpartum Depression iv
Understanding AF Mechanisms Through Computational Modelling and Simulations

AF is a progressive disease of the atria, involving complex mechanisms related to its initiation, maintenance and progression. Computational modelling provides a framework for integration of experimental and clinical findings, and has emerged as an essential part of mechanistic research in AF. The authors summarise recent advancements in development of multi-scale AF models and focus on the mechanistic links between alternations in atrial structure and electrophysiology with AF. Key AF mechanisms that have been explored using atrial modelling are pulmonary vein ectopy; atrial fibrosis and fibrosis distribution; atrial wall thickness heterogeneity; atrial adipose tissue infiltration; development of repolarisation alternans; cardiac ion channel mutations; and atrial stretch with mechano-electrical feedback. They review modelling approaches that capture variability at the cohort level and provide cohort-specific mechanistic insights. The authors conclude with a summary of future perspectives, as envisioned for the contributions of atrial modelling in the mechanistic understanding of AF.
The relevance between the immune response-related gene module and clinical traits in head and neck squamous cell carcinoma

Purpose Head and neck squamous cell carcinoma (HNSCC) is the sixth most prevalent cancer in the world, accounting for more than 90% of head and neck malignant tumors. However, its molecular mechanism is largely unknown. To help elucidate the potential mechanism of HNSCC tumorigenesis, we investigated the gene interaction patterns associated with tumorigenesis. Methods Weighted gene co-expression network analysis (WGCNA) can help us to predict the intrinsic relationship or correlation between gene expression. Additionally, we further explored the combination of clinical information and module construction. Results Sixteen modules were constructed, among which the key module most closely associated with clinical information was identified. By analyzing the genes in this module, we found that the latter may be related to the immune response, inflammatory response and formation of the tumor microenvironment. Sixteen hub genes were identified—ARHGAP9, SASH3, CORO1A, ITGAL, PPP1R16B, TBC1D10C, IL10RA, ITK, AKNA, PRKCB, TRAF3IP3, GIMAP4, CCR7, P2RY8, GIMAP7, and SP140. We further validated these genes at the transcriptional and translation levels. Conclusion The innovative use of a weighted network to analyze HNSCC samples provides new insights into the molecular mechanism and prognosis of HNSCC. Additionally, the hub genes we identified can be used as biomarkers and therapeutic targets of HNSCC, laying the foundation for the accurate diagnosis and treatment of HNSCC in clinical and research in the future.