Miracle-dz/UniFAR-FTUs huggingface dataset:
Human organotypic brain slice culture: a novel framework for environmental research in neuro-oncology

Therapeutically resected, adult brain segments were maintained and characterized for an extended period to study glioblastoma progression and treatment in its almost natural environment. When it comes to the human brain, models that closely mimic in vivo conditions are lacking. Living neuronal tissue is the closest representation of the in vivo human brain outside of a living person. Here, we present a method that can be used to maintain therapeutically resected healthy neuronal tissue for prolonged periods without any discernible changes in tissue vitality, evidenced by immunohistochemistry, genetic expression, and electrophysiology. This method was then used to assess glioblastoma (GBM) progression in its natural environment by microinjection of patient-derived tumor cells into cultured sections. The result closely resembles the pattern of de novo tumor growth and invasion, drug therapy response, and cytokine environment. Reactive transformation of astrocytes, as an example of the cellular nonmalignant tumor environment, can be accurately simulated with transcriptional differences similar to those of astrocytes isolated from acute GBM specimens. In a nutshell, we present a simple method to study GBM in its physiological environment, from which valuable insights can be gained. This technique can lead to further advancements in neuroscience, neuro-oncology, and pharmacotherapy.
Improving Recommender Systems with Rich Side Information

Recommender systems have become extremely popular in recent years since they can provide personalized information to user from a large amount of data, which is typically noisy and hard to exploit. Traditional approaches mainly leverage the user-item rating matrix for recommendation. Beyond the rating matrix, however, there exists rich side information in recommender systems, which is a good source to improve the performance of rating prediction. In this thesis, we studied three types of side information (i.e., content, temporal, spatial), pointed out some open issues that are unsolved by the existing models and proposed our solutions in these areas. We incorporate side information with some domain knowledge to improve the recommender systems. In recommendation with content information, we proposed a feature centric model to analyze the feature-level preferences instead of the item-level preferences, thus, make prediction according to feature-level preferences. We further proposed a recommendation by blending content and attributes in heterogeneous networks. In recommendation with temporal information, we proposed temporal matrix factorization to model the user’s interest shift over time; such changes are essential for developing accurate recommender systems. In recommendation with spatial information, we proposed a cross-region collaborative filtering method to deal with the POI (Point of Interest) recommendation when the user travels to a new place; in this model, the long-term and short-term preferences are considered respectively. All these models are evaluated in real life data sets with the state-of-the-art methods.
Effect of Sulforaphane and 5-Aza-2’-Deoxycytidine on Melanoma Cell Growth

Background: UV exposure-induced oxidative stress is implicated as a driving mechanism for melanoma. Increased oxidative stress results in DNA damage and epigenetic dysregulation. Accordingly, we explored whether a low dose of the antioxidant sulforaphane (SFN) in combination with the epigenetic drug 5-aza-2’-deoxycytidine (DAC) could slow melanoma cell growth. SFN is a natural bioactivated product of the cruciferous family, while DAC is a DNA methyltransferase inhibitor. Methods: Melanoma cell growth characteristics, gene transcription profiles, and histone epigenetic modifications were measured after single and combination treatments with SFN and DAC. Results: We detected melanoma cell growth inhibition and specific changes in gene expression profiles upon combinational treatments with SFN and DAC, while no significant alterations in histone epigenetic modifications were observed. Dysregulated gene transcription of a key immunoregulator cytokine—C-C motif ligand 5 (CCL-5)—was validated. Conclusions: These results indicate a potential combinatorial effect of a dietary antioxidant and an FDA-approved epigenetic drug in controlling melanoma cell growth.
Implementation of Bagged SVM Ensemble Model for Classification of Epileptic States using EEG.

BACKGROUND AND OBJECTIVE To decipher EEG (Electroencephalography) intending to locate inter-ictal and ictal discharges for supporting the diagnoses of epilepsy and locating the seizure focus is a critical task. The aim of this work is to find how the ensemble model distinguishes between two different set of problem which are group 1: inter-ictal and ictal, group 2: controlled and inter-ictal using approximate entropy as a parameter. METHOD The work is divided to conquer two problem groups the first being classifying inter ictal and ictal for which case 1(C-E), case 2(D-E) are considered which is Group 1. The other group (Group 2) is classifying between inter-ictal and controlled for which case 3 (A-C), case 4(B-C), case 5 (A-D) and case 6(B-D) are considered. To divide the EEG into sub-bands DWT (Discrete Wavelet Transform) is used and approximate Entropy is extracted out of all the five sub-bands of EEG for each case. Bagged SVM is used to classify between different groups considered. RESULTS Highest accuracy for Group 1 using Bagged SVM Ensemble model for case 1 is 96.83% with testing data; which is similar to 97% achieved by using training data. For case 2 (D-E) 93.92% with training and 84.83% with testing data has been obtained. For Group 2 there is a large disparity between SVM and Bagged Ensemble model where with the latter 76%,81.66%,72.835% and 71.16% for case 3 , case 4 , case 5 and case 6 has been obtained. While for training data set 92.87%, 91.74 %, 92% and 92.64% are attained respectively. The results obtained by SVM for Group 2 were at huge difference from the highest accuracy achieved by bagged SVM for both training and the testing data. CONCLUSION Bagged Ensemble model has outperformed SVM model for every case with huge difference with both training as well as testing dataset for Group 2 and marginally better for Group 1.
Quality Improvement of Few-Layers Defective Graphene from Biomass and Application for H2 Generation

Pyrolysis of filmogenic natural polymers gives rise to the formation of films of few-layers defective, undoped, and doped graphenes with low electrical conductivity (3000 to 5000 Ω/sq). For the sake of valorization of biomass wastes, it would be of interest to decrease the density of structural defects in order to increase the conductivity of the resulting few-layers graphene samples. In the present study, analytical and spectroscopic evidence is provided showing that by performing the pyrolysis at the optimal temperature (1100 °C), under a low percentage of H2, a significant decrease in the density of defects related to the presence of residual oxygen can be achieved. This improvement in the quality of the resulting few-layers defective graphene is reflected in a decrease by a factor of about 3 or 5 for alginic acid and chitosan, respectively, of the electrical resistance. Under optimal conditions, few-layers defective graphene films with a resistance of 1000 Ω /sq were achieved. The electrode made of high-quality graphene prepared at 1100 °C under Ar/H2 achieved a H2 production of 3.62 µmol with a positive applied bias of 1.1 V under LED illumination for 16 h.
FCMPASS Software Aids Extracellular Vesicle Light Scatter Standardization

The study of extracellular vesicles (EVs) is a rapidly growing field due to their great potential in many areas of clinical medicine including diagnostics, prognostics, theranostics, and therapeutics. Flow cytometry is currently one of the most popular methods of analyzing EVs due to it being a high‐throughput, multiparametric technique, that is readily available in the majority of research labs. Despite its wide use, few commercial flow cytometers are designed specifically for the detection of EVs. Many flow cytometers used for EV analysis are working at their detection limits and are unable to detect the majority of EVs. Currently, very little standardization exists for EV flow cytometry, which is an issue because flow cytometers vary considerably in the way they collect scattered or fluorescent light from particles being interrogated. This makes published research hard to interpret, compare, and in some cases, impossible to reproduce. Here we demonstrate a method of flow cytometer light scatter standardization, utilizing flow cytometer postacquisition analysis software (FCMPASS). FCMPASS is built upon Mie theory and enables the approximation of flow cytometer geometric parameters either by analyzing beads of known diameter and refractive index or by inputting the collection angle if known. The software is then able to create a scatter‐diameter curve and scatter‐refractive index curve that enables researchers to convert scattering data and instrument sensitivity into standardized units. Furthermore, with the correct controls, light scatter data can be converted to diameter distributions or refractive index distributions. FCMPASS therefore offers a freely available and ergonomic method of standardizing and further extending EV characterization using flow cytometry.
Detection of mutational patterns in cell‐free DNA of colorectal cancer by custom amplicon sequencing

Monitoring the mutational patterns of solid tumors during cancer therapy is a major challenge in oncology. Analysis of mutations in cell‐free (cf) DNA offers a noninvasive approach to detect mutations that may be prognostic for disease survival or predictive for primary or secondary drug resistance. A main challenge for the application of cfDNA as a diagnostic tool is the diverse mutational landscape of cancer. Here, we developed a flexible end‐to‐end experimental and bioinformatic workflow to analyze mutations in cfDNA using custom amplicon sequencing. Our approach relies on open‐software tools to select primers suitable for multiplex PCR using minimal cfDNA as input. In addition, we developed a robust linear model to identify specific genetic alterations from sequencing data of cfDNA. We used our workflow to design a custom amplicon panel suitable for detection of hotspot mutations relevant for colorectal cancer and analyzed mutations in serial cfDNA samples from a pilot cohort of 34 patients with advanced colorectal cancer. Using our method, we could detect recurrent and patient‐specific mutational patterns in the majority of patients. Furthermore, we show that dynamic changes of mutant allele frequencies in cfDNA correlate well with disease progression. Finally, we demonstrate that sequencing of cfDNA can reveal mechanisms of resistance to anti‐Epidermal Growth Factor Receptor(EGFR) antibody treatment. Thus, our approach offers a simple and highly customizable method to explore genetic alterations in cfDNA.
miRNA Predictors of Pancreatic Cancer Chemotherapeutic Response: A Systematic Review and Meta-Analysis

Background: pancreatic cancer (PC) has increasing incidence and mortality in developing countries, and drug resistance is a significant hindrance to the efficacy of successful treatment. The objective of this systematic review and meta-analysis was to evaluate the association between miRNAs and response to chemotherapy in pancreatic cancer patients. Methods: the systematic review and meta-analysis was based on articles collected from a thorough search of PubMed and Science Direct databases for publications spanning from January 2008 to December 2018. The articles were screened via a set of inclusion and exclusion criteria based on the preferred reporting items for systematic review and meta-analysis (PRISMA) guidelines. Data was extracted, collated and tabulated in MS Excel for further synthesis. Hazard ratio (HR) was selected as the effect size metric to be pooled across studies for the meta-analysis, with the random effects model being applied. Subgroup analysis was also conducted, and the presence of publication bias in the selected studies was assessed. Publication bias of the included studies was quantified. Findings: of the 169 articles screened, 43 studies were included in our systematic review and 13 articles were included in the meta-analysis. Gemcitabine was observed to be the principal drug used in a majority of the studies. A total of 48 miRNAs have been studied, and 18 were observed to have possible contributions to chemoresistance, while 15 were observed to have possible contributions to chemosensitivity. 41 drug-related genetic pathways have been identified, through which the highlighted miRNA may be affecting chemosensitivity/resistance. The pooled HR value for overall survival was 1.603; (95% Confidence Interval (CI) 1.2–2.143; p-value: 0.01), with the subgroup analysis for miR-21 showing HR for resistance of 2.061; 95% CI 1.195–3.556; p-value: 0.09. Interpretation: our results highlight multiple miRNAs that have possible associations with modulation of chemotherapy response in pancreatic cancer patients. Further studies are needed to discover the molecular mechanisms underlying these associations before they can be suggested for use as biomarkers of response to chemotherapeutic interventions in pancreatic cancer.
An Injectable and Tumor-Specific Responsive Hydrogel with Tissue-Adhesive and Nanomedicine-Releasing Abilities for Precise Locoregional Chemotherapy

Locoregional chemotherapy, especially using implantable hydrogel depots to sustainably deliver chemotherapeutics at tumor site, has shown great potential for improving antitumor efficacy and reducing systemic toxicity. However, the hydrogel applications are limited by some intrinsic constraints, especially the contradiction between increasing drug penetration and accumulation in tumor and decreasing random drug diffusion into surrounding normal tissues. Herein, we report a unique "Jekyll and Hyde" nanoparticle-hydrogel (NP-gel) hybrid platform, which can keep dormant in adjacent normal tissues but be activated by mildly acidic and hyaluronidase-rich microenvironment in malignant tumor tissues to unidirectionally release tumor-targeting and penetrative doxorubicin (DOX)-loaded NPs. Apart from tumor-specific recognition, penetration, internalization and release, NP-gel features: shear-thinning behavior for injection, tissue-adhesiveness for continuous on-site activation, and full biodegradability for safe use. Precise delivery was clearly demonstrated in both tumor-grafted and tumor-resected mice. A single peritumoral injection of DOX-loaded NP-gel exhibited a significantly higher drug accumulation in tumor for 3 weeks than in nontarget organs and thus long-term tumor remission. More importantly, significant inhibition in tumor recurrence without detectable toxicity to healthy organs was demonstrated when applied after tumor resection. The designed system displayed long-acting and precise anticancer efficacy, paving the way toward effective tumor locoregional treatment. STATEMENT OF SIGNIFICANCE: Injectable hydrogels, allowing sustained drug delivery directly at tumor site, has shown great potential for locoregional chemotherapy. However, how to achieve tumor-specific drug accumulation but meanwhile impede the random drug diffusion into surrounding normal tissues remains an insurmountable challenge, especially considering high drug concentration gradient, higher interstitial fluid pressure and denser extracellular matrix in tumor than adjacent normal tissue. Herein, a 'Jekyll and Hyde' nanoparticle-hydrogel hybrid formulation was designed to keep dormant in adjacent normal tissues but be activated by mildly acidic and hyaluronidase-rich microenvironment in malignant tumor tissues to unidirectionally release tumor-targeting and penetrative DOX-loaded nanoparticles, leading to a significant tumor inhibition and antirecurrence efficiency without detectable toxicity to healthy organs, thus presenting great potential for precise locoregional chemotherapy.
Endophytic Beauveria bassiana in Foliar-Treated Citrus limon Plants Acting as a Growth Suppressor to Three Successive Generations of Diaphorina citri Kuwayama (Hemiptera: Liviidae)

Entomopathogenic fungi are commonly applied as inundative sprays to protect plants against insect pests. Their artificial establishment as fungal endophytes to provide other benefits to the host plants aside mere protection against the primary pests has also been widely demonstrated. In the present study, two fungal strains of Beauveria bassiana and one strain of Isaria fumosorosea were assessed in a pathogenicity test against adults of Asian citrus psyllid (Diaphorina citri) and found to induce 50% reduction in the survival rate of D. citri adults within 5 days of exposure. The ability of the three fungal strains to endophytically colonize Citrus limon, the impact on plant growth and the effects of systemic colonization on 3 successive generations of D. citri feeding on colonized plants was evaluated. Citrus seedlings at 4 months post-planting were inoculated with each of the fungal strains via foliar spraying. Both strains of B. bassiana successfully colonized the seedlings. One of the B. bassiana strains (BB Fafu-13) was sustained up to 12 weeks in the colonized seedlings, whereas the other B. bassiana strain (BB Fafu-16) was only recovered up to 8 weeks post-inoculation. Isaria fumosorosea (IF Fafu-1) failed to colonize the plant. Both strains of B. bassiana induced significant improvement in plant height and flush production in endophytically colonized seedlings. In addition, endophytic B. bassiana caused 10–15% D. citri adult mortality within 7 days of exposure. Female D. citri feeding on B. bassiana challenged plants laid fewer eggs as compared to those feeding on endophyte-free seedlings, while reduction in adult emergence was recorded on B. bassiana treated plants. With this study, we present the first evidence of B. bassiana artificial establishment as fungal endophyte in citrus plants and its negative effects on D. citri.
A Predictive Approach for Fraud Detection Using Hidden Markov Model

Today world online banking service is the most popular and provides a fast and easy way to make transactions. As increasing online transaction, the number of fraud transaction is also increased by various thefts. In this paper, we design a model with sequence of operations in online transaction by using hidden markov model (HMM) and decides whether the user act as a normal user or fraud user. The HMM is initially trained with customer’s last few transactions. In the trained system, the new transaction is evaluated with transition and observation probability. Depends upon the observation probability, system finds the acceptance probability and decides the transaction will be declined or not. Normally existing fraud detection system for online banking will detect the fraudulent transaction after completion of the transaction. It is additional burden to find fraudulent after transactions. This causes the economic loss and makes the bank name as unsecured. Our model predicts the fraudulent during the transaction time and prevents the money transfer. The main objective is to ensure that the genuine transactions should not be rejected. Index Terms Online banking –clustering-Hidden Markov Model-Fraud detection
Comparison of the therapeutic effects of adipose-derived and bone marrow mesenchymal stem cells on erectile dysfunction in diabetic rats

The aim of the present study was to compare the effects of adipose-derived mesenchymal stem cell (ADSC) and bone marrow mesenchymal stem cell (BMSC) transplantation into the corpora cavernosa of diabetic rats with erectile function. ADSCs and BMSCs were isolated and identified by flow cytometry. Rats with streptozocin-induced diabetes were screened using apomorphine to obtain a rat model of diabetic erectile dysfunction, followed by transplantation of ADSCs and BMSCs into the corpora cavernosa. Two weeks later, the rats were again injected with apomorphine, the intracavernous pressure (ICP) and mean arterial pressure (MAP) of the penile tissue were measured, and the corpus cavernosum tissues were harvested. Angiogenic endothelial nitric oxide synthase (eNOS) expression was detected by western blotting and immunofluorescence analysis. The blood vessels in the corpus cavernosum were observed following hematoxylin and eosin (H&E) staining, and the expression of collagen was detected by Sirius Red staining. The cellular ultrastructure was examined by transmission electron microscopy. Intracavernous injection of ADSCs significantly increased ICP and ICP/MAP. Western blotting and immunofluorescence results revealed that ADSC treatment improved the expression of eNOS in the penile tissue of diabetic rats. The H&E staining results demonstrated that ADSC treatment promoted revascularization of the corpus cavernosum, and the results of Sirius Red staining revealed that ADSC treatment reduced penile collagen in diabetic rats. Transmission electron microscopy examination revealed that the ultrastructure of the tissues in the ADSC-treated group was more complete compared with that in the untreated diabetic model group. In conclusion, ADSCs were found to be more effective compared with BMSCs in treating diabetes-related erectile dysfunction.
Chronic Central Pain Among Community-Dwelling Survivors of Moderate-to-Severe Traumatic Brain Injury: A Quantitative Sensory Testing Study

Background: Central pain associated with changes in sensory thresholds is one of the most enduring consequences of major trauma. Yet it remains sparsely studied among community-dwelling survivors of moderate-to-severe traumatic brain injury (TBI). Purpose: To describe and compare thermal and mechanical sensory thresholds in home-based patients with and without central pain after moderate-to-severe TBI with a cohort of healthy controls. Design: Cross-sectional. Method: Thresholds for cold/heat detection, thermal pain, touch, and distorted sensation were gathered using quantitative sensory testing (QST). QST was performed on the painful and contralateral pain-free body regions in TBI participants with pain (TBI-P) and on both forearms in TBI participants without pain (TBI-NP) and healthy controls (HC). Central pain was characterized using the Brief Pain Inventory–Short Form. Results: We tested 16 TBI-P patients, 17 TBI-NP patients, and 16 HC. Mean time since injury for TBI patients was 24 ± 15 months. TBI-P and TBI-NP patients showed significant loss in innocuous mechanical sensitivity compared to HC (F = 18.929; Bonferroni-adjusted p ≤ .001). Right–left differences in cold pain sensations were significantly larger in TBI-P than in TBI-NP and HC participants (F = 14.352; Bonferroni-adjusted p ≤ .001). Elevated heat sensitivity thresholds were also observed in TBI-P participants but remained within normal range. Conclusion: Damage to cutaneous mechanoreceptors is a necessary, but not sufficient, condition for the development of chronic central pain following TBI. Damage or incomplete recovery of cutaneous thermoreceptors may be a contributing factor to chronic pain after TBI.