Miracle-dz/UniFAR-FTUs huggingface dataset:
Nano-Delivery of a Novel Inhibitor of Polynucleotide Kinase/Phosphatase (PNKP) for Targeted Sensitization of Colorectal Cancer to Radiation-Induced DNA Damage

Inhibition of the DNA repair enzyme polynucleotide kinase/phosphatase (PNKP) increases the sensitivity of cancer cells to DNA damage by ionizing radiation (IR). We have developed a novel inhibitor of PNKP, i.e., A83B4C63, as a potential radio-sensitizer for the treatment of solid tumors. Systemic delivery of A83B4C63, however, may sensitize both cancer and normal cells to DNA damaging therapeutics. Preferential delivery of A83B4C63 to solid tumors by nanoparticles (NP) was proposed to reduce potential side effects of this PNKP inhibitor to normal tissue, particularly when combined with DNA damaging therapies. Here, we investigated the radio-sensitizing activity of A83B4C63 encapsulated in NPs (NP/A83) based on methoxy poly(ethylene oxide)-b-poly(α-benzyl carboxylate-ε-caprolactone) (mPEO-b-PBCL) or solubilized with the aid of Cremophor EL: Ethanol (CE/A83) in human HCT116 colorectal cancer (CRC) models. Levels of γ-H2AX were measured and the biodistribution of CE/A83 and NP/A83 administered intravenously was determined in subcutaneous HCT116 CRC xenografts. The radio-sensitization effect of A83B4C63 was measured following fractionated tumor irradiation using an image-guided Small Animal Radiation Research Platform (SARRP), with 24 h pre-administration of CE/A83 and NP/A83 to Luc+/HCT116 bearing mice. Therapeutic effects were analyzed by monitoring tumor growth and functional imaging using Positron Emission Tomography (PET) and [18F]-fluoro-3’-deoxy-3’-L:-fluorothymidine ([18F]FLT) as a radiotracer for cell proliferation. The results showed an increased persistence of DNA damage in cells treated with a combination of CE/A83 or NP/A83 and IR compared to those only exposed to IR. Significantly higher tumor growth delay in mice treated with a combination of IR and NP/A83 than those treated with IR plus CE/A83 was observed. [18F]FLT PET displayed significant functional changes for tumor proliferation for the drug-loaded NP. This observation was attributed to the higher A83B4C63 levels in the tumors for NP/A83-treated mice compared to those treated with CE/A83. Overall, the results demonstrated a potential for A83B4C63-loaded NP as a novel radio-sensitizer for the treatment of CRC.
Glycoprotein Targeted CAR-NK Cells for the Treatment of SARS-CoV-2 Infection

H84T-Banana Lectin (BanLec) CAR-NK cells bind high mannose glycosites that decorate the SARS-CoV-2 envelope, thereby decreasing cellular infection in a model of SARS-CoV-2. H84T-BanLec CAR-NK cells are innate effector cells, activated by virus. This novel cellular agent is a promising therapeutic, capable of clearing circulating SARS-CoV-2 virus and infected cells. Banana Lectin (BanLec) binds high mannose glycans on viral envelopes, exerting an anti-viral effect. A point mutation (H84T) divorces BanLec mitogenicity from antiviral activity. SARS-CoV-2 contains high mannose glycosites in proximity to the receptor binding domain of the envelope Spike (S) protein. We designed a chimeric antigen receptor (CAR) that incorporates H84T-BanLec as the extracellular moiety. Our H84T-BanLec CAR was devised to specifically direct NK cell binding of SARS-CoV-2 envelope glycosites to promote viral clearance. The H84T-BanLec CAR was stably expressed at high density on primary human NK cells during two weeks of ex vivo expansion. H84T-BanLec CAR-NK cells reduced S-protein pseudotyped lentiviral infection of 293T cells expressing ACE2, the receptor for SARS-CoV-2. NK cells were activated to secrete inflammatory cytokines when in culture with virally infected cells. H84T-BanLec CAR-NK cells are a promising cell therapy for further testing against wild-type SARS-CoV-2 virus in models of SARS-CoV-2 infection. They may represent a viable off-the-shelf immunotherapy for patients suffering from COVID-19.
Permutation-Matrix Approach to Optimal Assignment Design

The paper presents a new iterative approach to solving Linear Assignment problems (LAP) and finding a perfect matching in a weighted bipartite graph iteratively. For that, a new permutation-matrix model of optimal linear assignment is proposed, which allows recursively finding solutions on a set of augmenting paths built based on the current matching. The results can be combined with other methods for solving a LAP such as the Hungarian Algorithm and minimal cost method in order to find an optimum faster
Locked Nucleic Acid Hydrolysis Probes for the Specific Identification of Probiotic Strains Bifidobacterium animalis subsp. lactis DSM 15954 and Bi-07™

Probiotic health benefits are now well-recognized to be strain specific. Probiotic strain characterization and identification is thus important in clinical research and in the probiotic industry. This is becoming especially important with reports of probiotic products failing to meet the declared strain content, potentially compromising their efficacy. Availability of reliable identification methods is essential for strain authentication during discovery, evaluation and commercialization of a probiotic strain. This study aims to develop identification methods for strains Bifidobacterium animalis subsp. lactis DSM 15954 and Bi-07 (Bi-07™) based on real-time PCR, targeting single nucleotide polymorphisms (SNPs). The SNPs were targeted by PCR assays with locked nucleic acid (LNA) probes, which is a novel application in probiotic identification. The assays were then validated following the guidelines for validating qualitative real-time PCR assays. Each assay was evaluated for specificity against 22 non-target strains including closely related Bifidobacterium animalis subsp. lactis strains and were found to achieve 100% true positive and 0% false positive rates. To determine reaction sensitivity and efficiency, three standard curves were established for each strain. Reaction efficiency values were 86, 91, and 90% (R square values > 0.99), and 87, 84, and 86% (R square values > 0.98) for B. animalis subsp. lactis DSM 15954 and Bi-07 assays, respectively. The limit of detection (LOD) was 5.0 picograms and 0.5 picograms of DNA for DSM 15954 and Bi-07 assays, respectively. Each assay was evaluated for accuracy using five samples tested at three different DNA concentrations and both assays proved to be highly repeatable and reproducible. Standard deviation of Cq values between two replicates was always below 1.38 and below 1.68 for DSM 15954 and Bi-07 assays, respectively. The assays proved to be applicable to mono-strain and multi-strain samples as well as for samples in various matrices of foods or dietary supplement ingredients. Overall, the methods demonstrated high specificity, sensitivity, efficiency and precision and broad applicability to sample, matrix and machine types. These methods facilitate strain level identification of the highly monophyletic strains B. animalis subsp. lactis DSM 15954 and Bi-07 to ensure probiotic efficacy and provide a strategy to identify other closely related probiotics organisms.
Control of Thruster-Assisted, Bipedal Legged Locomotion of the Harpy Robot

Fast constraint satisfaction, frontal dynamics stabilization, and avoiding fallovers in dynamic, bipedal walkers can be pretty challenging. The challenges include underactuation, vulnerability to external perturbations, and high computational complexity that arise when accounting for the system full-dynamics and environmental interactions. In this work, we study the potential roles of thrusters in addressing some of these locomotion challenges in bipedal robotics. We will introduce a thruster-assisted bipedal robot called Harpy. We will capitalize on Harpy’s unique design to propose an optimization-free approach to satisfy gait feasibility conditions. In this thruster-assisted legged locomotion, the reference trajectories can be manipulated to fulfill constraints brought on by ground contact and those prescribed for states and inputs. Unintended changes to the trajectories, especially those optimized to produce periodic orbits, can adversely affect gait stability and hybrid invariance. We will show our approach can still guarantee stability and hybrid invariance of the gaits by employing the thrusters in Harpy. We will also show that the thrusters can be leveraged to robustify the gaits by dodging fallovers or jumping over large obstacles.
Microfluidic Platforms for High-Throughput Pancreatic Ductal Adenocarcinoma Organoid Culture and Drug Screening

Pancreatic Ductal Adenocarcinoma (PDAC), the most common pancreatic cancer type, is believed to become the second leading cause of cancer-related deaths by 2030 with mortality rates of up to 93%. It is often detected at a late stage due to lacking symptoms, and therefore surgical removal of the tumor is the only treatment option for patients. Only 20% of the tumors are resectable, mainly due to early metastasis. Therefore, for 80% of cases chemotherapeutic treatment is the leading therapy for patients. PDAC is characterized by high-density stroma which induces hypoxic conditions and high interstitial pressure. These factors impact carcinogenesis and progression of PDAC and support the formation of an immunosuppressive microenvironment that renders this tumor type refractory to immunotherapies. Most in vitro PDAC models have limited translational relevance, as these fail to recapitulate relevant aspects of PDAC complexity. Altogether, there is an urgent need for novel and innovative PDAC modeling platforms. Here, we discuss the relevance of microfluidic and organoid technologies as platforms for modeling bio- and physicochemical features of PDAC and as translational models that enable high-throughput phenotypic drug screenings, while also allowing for the development of novel personalized models used to identify treatment responsive patient subsets.
sUAS and Machine Learning Integration in Waterfowl Population Surveys

The rapid technological development of small Unmanned Aircraft Systems (sUAS) has led to an increase in capabilities of aerial image collection and analysis for monitoring a variety of wildlife species including waterfowl. Biologists mainly rely on conducting ocular surveys from fixed-wing aircraft or helicopters to estimate waterfowl abundance. sUAS provide an alternative that is safer, less expensive, and more flexible. Researchers have attempted to estimate waterfowl abundance from aerial imagery, but this method has proven to be too time consuming. Machine learning provides the opportunity to more efficiently estimate waterfowl abundance from aerial imagery. In this paper, we present a new integrated system of sUAS and machine learning for waterfowl population surveys. This system provides a user-friendly process for sUAS survey design, deployment, and data post-processing using deep learning methods to automatically detect and count waterfowl. To develop this system, we conducted many sUAS flights to capture a diversity of imagery and assembled six datasets of imagery taken from both fix-winged aircraft and sUAS flights. We used these datasets to develop and evaluate state-of-the-art deep learning models for waterfowl detection. Our system of using a combination of sUAS and machine learning has proved to be an efficient and accurate approach for collecting, analyzing, and estimating waterfowl abundance.
Factors Influencing the Creativity of Chinese Upper-Secondary-School Students Participating in Programming Education

Purpose: This study explored whether instructional characteristics, learner characteristics, family socioeconomic status, and gender influence creativity in the context of programming education in China. Methods: A total of 851 upper-secondary-school students in Beijing, China, were surveyed using the Creativity Scale, Programming Learning Scale, Programming Teaching Scale and Family Socioeconomic Status Questionnaire. SPSS (version 22) was used for correlation analysis, t-test and regression analysis. Results: (1) Teachers’ programming teaching method and management; students’ programming learning approach, attitude, and engagement; gender; and family economic capital were all significantly associated with creativity. (2) There were significant differences between males and females in terms of creativity, programming learning approach and programming learning attitude. (3) Learner attitudes, engagement, and approach, and their family economic capital, were strong predictors of creativity, with the strongest influence of learners’ attitudes to programming learning and weaker influence of family economic capital. Conclusion: The main factors that influence creativity in the context of programming education are programming teaching method, programming teaching management, programming learning approach, programming learning attitude, programming learning engagement and family economic capital. Among these, learner factors (attitude, engagement, and approach) and family economic capital are the key factors influencing creativity. These findings provide a basis for improving the creativity of Chinese programming learners and inspire teachers to consider learner factors and gender differences as they design and manage their instruction. Furthermore, the influence of family economic capital on the creativity of learners cannot be ignored.
Involvement of Small Colony Variant-Related Heme Biosynthesis Genes in Staphylococcus aureus Persister Formation in vitro

Background: Persisters are important reasons for persistent infections, and they can lead to antibiotic treatment failure in patients and consequently chronic infection. Staphylococcus aureus small colony variants (SCVs) have been shown to be related to persistent infection. Mutations in the genes of the heme biosynthesis pathway lead to the formation of SCVs. However, the relationship between heme production genes and persister has not been tested. Methods:HemA and hemB were knocked out by allelic replacement from S. aureus strain USA500 separately, and then, the heme deficiency was complemented by overexpression of related genes and the addition of hemin. The stress-related persister assay was conducted. RNA-sequencing was performed to find genes and pathways involved in heme-related persister formation, and relative genes and operons were further knocked out and overexpressed to confirm their role in each process. Results: We found that heme biosynthesis deficiency can lead to decreased persister. After complementing the corresponding genes or hemin, the persister levels could be restored. RNA-seq on knockout strains showed that various metabolic pathways were influenced, such as energy metabolism, amino acid metabolism, carbohydrate metabolism, and membrane transport. Overexpression of epiF and operon asp23 could restore USA500∆hemA persister formation under acid stress. Knocking out operon arc in USA500∆hemA could further reduce USA500∆hemA persister formation under acid and oxidative stress. Conclusion: Heme synthesis has a role in S. aureus persister formation.
Effect of Cyclic Heat Stress on Feeding-Related Hypothalamic Neuropeptides of Three Broiler Populations and Their Ancestor Jungle Fowl

Heat stress (HS) has been increasingly jeopardizing the sustainability of the poultry production. Moreover, modern high-performing chickens are far less able to withstand HS than their predecessors due to higher growth rate and metabolic rates. Performance losses caused by HS are mainly ascribed to decreases in feed consumption. Since feed intake is tightly controlled by the hypothalamic centers of hunger and satiety, we sought to determine the effect of chronic cyclic HS on the expression of feeding-related hypothalamic neuropeptides (FRHN) in unselected chickens (i.e., the ancestor junglefowl—JF) and three broiler lines from diverse stages of genetic selection (i.e., the slow growing ACRB, the moderate growing 95RN, and the fast growing MRB). From 29 to 56 days, birds (n = 150 birds for each population) were subjected to either thermoneutral (TN, 25°C) or cyclic heat stress (HS, 36°C, 0900–1,800 h) conditions. Molecular data were analyzed by two-way ANOVA with interaction between the main factors, namely environmental temperature and line. The expression of major FHRN, like neuropeptide Y, agouti-related peptide, proopiomelanocortin, and cocaine and amphetamine regulated transcript remained unchanged. However, melanocortin receptor 1 exhibited a line-dependent decreasing trend from JF to MRB under both TN and HS (p = 0.09), adiponectin expression showed a distinct trend toward significance with 95RB exhibiting the highest mRNA level irrespective of the environmental temperature (p = 0.08), and JF had a greater mRNA abundance of visfatin than ACRB under TN (p < 0.05). The hypothalamic integration of circadian information, acclimation to long-lasting HS exposure, stable hypothalamic pathways unaffected by evolution and genetic selection, focus on mRNA abundances, and use of the entire hypothalamus masking gene expression in specific hypothalamic nuclei are all possible explanations for the lack of variations observed in this study. In conclusion, this is the first assessment of the impacts of heat stress on feeding-related hypothalamic neuropeptides of chicken, with a valuable and informative comparison between the ancestor junglefowl and three differently performing broiler lines.
The Chest Radiographic Thoracic Area Can Serve as a Prediction Marker for Morbidity and Mortality in Infants With Congenital Diaphragmatic Hernia

Objective: Valid postnatal prediction parameters for neonates with congenital diaphragmatic hernia (CDH) are lacking, but recently, the chest radiographic thoracic area (CRTA) was proposed to predict survival with high sensitivity. Here, we evaluated whether the CRTA correlated with morbidity and mortality in neonates with CDH and was able to predict these with higher sensitivity and specificity than prenatal observed-to-expected (O/E) lung-to-head ratio (LHR). Methods: In this retrospective cohort study, all neonates with CDH admitted to our institution between 2013 and 2019 were included. The CRTA was measured using the software Horos (V. 3.3.5) and compared with O/E LHR diagnosed by fetal ultrasonography in relation to outcome parameters including survival, extracorporeal membrane oxygenation (ECMO) support, and chronic lung disease (CLD). Results: In this study 255 neonates were included with a survival to discharge of 84%, ECMO support in 46%, and 56% developing a CLD. Multiple regression analysis demonstrated that the CRTA correlates significantly with survival (p = 0.001), ECMO support (p < 0.0001), and development of CLD (p = 0.0193). The CRTA displayed a higher prognostic validity for survival [area under the curve (AUC) = 0.822], ECMO support (AUC = 0.802), and developing a CLD (AUC = 0.855) compared with the O/E LHR. Conclusions: Our data suggest that the postnatal CRTA might be a better prognostic parameter for morbidity and mortality than the prenatal O/E LHR.
A Historical Perspective on Surgical Manipulation of the Membranous Labyrinth for Treatment of Meniere's Disease

Meniere's disease is an inner ear disorder without a known cause. Endolymphatic hydrops is a swelling of the endolymph spaces that has been observed consistently on post-mortem histology in patients with a history of Meniere's disease but can occur in asymptomatic individuals and in association with other diseases. Since its discovery, Meniere's disease has been a disorder managed primarily by otolaryngologists. Surgical treatments, therefore, have accompanied attempts at medical management. Inspired by patients' sensations of ear fullness and later by the histologic findings of hydrops, surgeons began manipulating the membranous labyrinth to relieve episodes of vertigo while attempting to preserve hearing. This review highlights this history of manipulation of the membranous labyrinth. These procedures indicate a rich history of innovation that parallels developments in otologic surgery. The studies involving patients are uniformly retrospective, with some procedures performed first in animal models of endolymphatic hydrops. Many approaches were endorsed by eminent otologic surgeons. Surgeries on the endolymphatic sac are performed by some surgeons today; however, procedures on the membranous labyrinth resulted in similar symptomatic relief through a minimally invasive technique, in many cases performed using only local anesthetic. Episodic vertigo in patients with Meniere's disease is a distressing symptom, yet spontaneous remissions are common. The reports of procedures on the membranous labyrinth reviewed here consistently indicated fewer vertigo episodes. Variable degrees of hearing loss were common following these procedures, and many were abandoned. Additional innovative surgeries are inevitable, but we must understand better the relationships among endolymphatic hydrops, Meniere's disease pathophysiology, and patient symptoms.
Predicting the Next Location for Trajectories From Stolen Vehicles

In this article, we consider the External Sensor Trajectory Prediction problem for stolen vehicle trajectories. This analysis brings new challenges to the problem, as crime patterns are dynamic and drivers of stolen vehicles tend to move away from the sensors, which increases data dispersion. We analyze the effectiveness of different machine learning models and propose semantic enrichment with criminal data and points of interest to solve our problem. We also investigate the best attributes to improve EST prediction models, and how different spatial level representations can leverage prediction accuracy.
The Application of Artificial Intelligence and Machine Learning in Pituitary Adenomas

Pituitary adenomas (PAs) are a group of tumors with complex and heterogeneous clinical manifestations. Early accurate diagnosis, individualized management, and precise prediction of the treatment response and prognosis of patients with PA are urgently needed. Artificial intelligence (AI) and machine learning (ML) have garnered increasing attention to quantitatively analyze complex medical data to improve individualized care for patients with PAs. Therefore, we critically examined the current use of AI and ML in the management of patients with PAs, and we propose improvements for future uses of AI and ML in patients with PAs. AI and ML can automatically extract many quantitative features based on massive medical data; moreover, related diagnosis and prediction models can be developed through quantitative analysis. Previous studies have suggested that AI and ML have wide applications in early accurate diagnosis; individualized treatment; predicting the response to treatments, including surgery, medications, and radiotherapy; and predicting the outcomes of patients with PAs. In addition, facial imaging-based AI and ML, pathological picture-based AI and ML, and surgical microscopic video-based AI and ML have also been reported to be useful in assisting the management of patients with PAs. In conclusion, the current use of AI and ML models has the potential to assist doctors and patients in making crucial surgical decisions by providing an accurate diagnosis, response to treatment, and prognosis of PAs. These AI and ML models can improve the quality and safety of medical services for patients with PAs and reduce the complication rates of neurosurgery. Further work is needed to obtain more reliable algorithms with high accuracy, sensitivity, and specificity for the management of PA patients.