Miracle-dz/UniFAR-FTUs huggingface dataset:
Refinement of Spatial Receptive Fields in the Developing Mouse Lateral Geniculate Nucleus Is Coordinated with Excitatory and Inhibitory Remodeling

Receptive field properties of individual visual neurons are dictated by the precise patterns of synaptic connections they receive, including the arrangement of inputs in visual space and features such as polarity (On vs Off). The inputs from the retina to the lateral geniculate nucleus (LGN) in the mouse undergo significant refinement during development. However, it is unknown how this refinement corresponds to the establishment of functional visual response properties. Here we conducted in vivo and in vitro recordings in the mouse LGN, beginning just after natural eye opening, to determine how receptive fields develop as excitatory and feedforward inhibitory retinal afferents refine. Experiments used both male and female subjects. For in vivo assessment of receptive fields, we performed multisite extracellular recordings in awake mice. Spatial receptive fields at eye-opening were >2 times larger than in adulthood, and decreased in size over the subsequent week. This topographic refinement was accompanied by other spatial changes, such as a decrease in spot size preference and an increase in surround suppression. Notably, the degree of specificity in terms of On/Off and sustained/transient responses appeared to be established already at eye opening and did not change. We performed in vitro recordings of the synaptic responses evoked by optic tract stimulation across the same time period. These recordings revealed a pairing of decreased excitatory and increased feedforward inhibitory convergence, providing a potential mechanism to explain the spatial receptive field refinement. SIGNIFICANCE STATEMENT The development of precise patterns of retinogeniculate connectivity has been a powerful model system for understanding the mechanisms underlying the activity-dependent refinement of sensory systems. Here we link the maturation of spatial receptive field properties in the lateral geniculate nucleus (LGN) to the remodeling of retinal and inhibitory feedforward convergence onto LGN neurons. These findings should thus provide a starting point for testing the cell type-specific plasticity mechanisms that lead to refinement of different excitatory and inhibitory inputs, and for determining the effect of these mechanisms on the establishment of mature receptive fields in the LGN.
Total knee arthroplasty: improving outcomes with a multidisciplinary approach

Total knee arthroplasty (TKA) is the most commonly performed inpatient surgical procedure within the USA and is estimated to reach 3.48 million procedures annually by 2030. As value-based care initiatives continue to focus on hospital readmission rates and patient satisfaction, it has become essential for health care providers to develop and implement a multidisciplinary approach to enhance TKA outcomes while minimizing unnecessary expenditures. Through this necessity, clinical care pathways have been developed to standardize, organize, and improve the quality and efficiency of patient care while simultaneously encouraging the collaboration among various medical care providers. Here, we review several systems based programs and specialty care practices that can be adopted into the standard orthopedic practice.
Interleukin-22 Immunotherapy during Severe Influenza Enhances Lung Tissue Integrity and Reduces Secondary Bacterial Systemic Invasion

ABSTRACT Severe bacterial (pneumococcal) infections are commonly associated with influenza and are significant contributors to the excess morbidity and mortality of influenza. Disruption of lung tissue integrity during influenza participates in bacterial pulmonary colonization and dissemination out of the lungs. Interleukin-22 (IL-22) has gained considerable interest in anti-inflammatory and anti-infection immunotherapy over the last decade. In the current study, we investigated the effect of exogenous IL-22 delivery on the outcome of pneumococcal superinfection postinfluenza. Our data show that exogenous treatment of influenza virus-infected mice with recombinant IL-22 reduces bacterial dissemination out of the lungs but is without effect on pulmonary bacterial burden. Reduced systemic bacterial dissemination was linked to reinforced pulmonary barrier functions, as revealed by total protein measurement in the bronchoalveolar fluids, intratracheal fluorescein isothiocyanate-dextran tracking, and histological approaches. We describe an IL-22-specific gene signature in the lung tissue of influenza A virus (IAV)-infected (and naive) mice that might explain the observed effects. Indeed, exogenous IL-22 modulates the gene expression profile in a way that suggests reinforcement of tissue integrity. Our results open the way to alternative approaches for limiting postinfluenza bacterial superinfection, particularly, systemic bacterial invasion.
Collision Avoidance/Mitigation System: Motion Planning of Autonomous Vehicle via Predictive Occupancy Map

Despite development efforts toward autonomous vehicle technologies, the number of collisions and driver interventions of autonomous vehicles tested in California seems to be reaching a plateau. One of the main reasons for this is the lack of defensive driving functionality; i.e. emergency collision avoidance when other human drivers make mistakes. In this paper, a collision avoidance/mitigation system (CAMS) is proposed to rapidly evaluate risks associated with all surrounding vehicles and to maneuver the vehicle into a safer region when faced with critically dangerous situations. First, a risk assessment module, namely, predictive occupancy map (POM), is proposed to compute potential risks associated with surrounding vehicles based on relative position, velocity, and acceleration. Then, the safest trajectory with the lowest risk level is selected among the 12 local trajectories through the POM. To ensure stable and successful collision avoidance of the ego-vehicle, the lateral and longitudinal acceleration profiles are planned while considering the vehicle stability limit. The performance of the proposed algorithm is validated based on side and rear-end collision scenarios, which are difficult to predict and to monitor. The simulation results show that the proposed CAMS via POM detect a collision risk 1.4 s before the crash, and avoids the collision successfully.
Graphene: recent advances in engineering, medical and biological sciences, and future prospective

Graphene, a two dimensional carbon allotrope, has been appeared as an interesting material of the 21st century, and received world-wide attention due to its extraordinary thermal, optical, and mechanical properties. Graphene and its derivatives are being studied in different field of science from medicine and pharmaceutics to engineering and industries. Graphene materials have mainly been explored in electronics, clean energy devices, biosensors and environmental remediation also in biomedicine field, their antimicrobial activity and their capacity as drug delivery or gene delivery platforms and tissue engineering scaffold have been reported. This article provides an overview of graphene and its recent advances in different fields including biomedicine and industries.
A theoretical interpretation of variance-based convergence criteria in perturbation-based theories

As huge differences exist between the computational costs of low level MM and high level QM Hamiltonians, the errors in indirect QM/MM simulation are mostly introduced in QM/MM end-state corrections. QM/MM end-state corrections can be obtained from integration of the partial derivatives of alchemical Hamiltonians or from perturbation-based estimators including free energy perturbation (FEP) and acceptance ratio methods. When using FEP or exponential averaging (EXP), researchers tend to only simulate MM end states and calculate single point energy to get the free energy estimates. In this case the sample size hysteresis arises and the convergence is determined by bias elimination rather than variance minimization. Various criteria are proposed to evaluate this convergence issue. Under the approximation of Gaussian distributed energy difference Ulf (JCTC. 2017, 13 (11), 5745-5752. ) presented practical considerations into the convergence issue and concluded that the variance of distribution is the best convergence criterion and other convergence criteria are variance-dependent. However, this question is only partially answered. In this paper we present theoretical interpretations to dig the underlying statistical nature behind the problem. Still, the variance of the distribution is the central quantity for all convergence criteria in Gaussian approximated Exponential averaging (GEXP). Further, we prove that these estimators are nonlinearly dependent on the variance of the free energy estimate. As these estimators are often orders of magnitude overestimated, the variance of the FEP estimate is orders of magnitude underestimated. Hence, computing this statistical uncertainty is meaningless in practice. The effective sample size is also proven to be a function of the overlap scalar. We hope this literature can help readers to get a deeper understanding of perturbation-based theories.
Synchronization Algorithms for FBMC Systems

Filter bank multicarrier (FBMC) systems, such as FMT and OFDM/OQAM systems, can provide reduced sensitivity to narrowband interference, high flexibility to allocate group of subchannels to different users and a high spectral containment. On the other hand, as all the multicarrier modulation schemes, one of their major drawbacks is their sensitivity to CFO and symbol timing errors. In this thesis the problem of CFO and symbol timing synchronization is examined and new data-aided and blind estimation techniques are proposed. Specifically, it is presented a new joint symbol timing and CFO synchronization algorithm based on the LS approach. Moreover, the joint ML phase offset, CFO and symbol timing estimator for a multiple access OFDM/OQAM system is considered. It is also proposed a closed-form CFO estimator based on the best linear unbiased estimation principle for FMT systems. Blind CFO estimators based on the ML principle for low SNR are also considered and, moreover, a closed-form CFO synchronization algorithm based on the LS method is derived. Finally, it is also proposed, under the assumption of low SNR, the joint ML symbol timing and phase offset estimator.
Using rotational thromboelastometry clot firmness at 5 minutes (ROTEM® EXTEM A5) to predict massive transfusion and in‐hospital mortality in trauma: a retrospective analysis of 1146 patients

Viscoelastic assays such as TEG® and ROTEM® are increasingly used to guide transfusion of blood products. The EXTEM assay maximum clot firmness (MCF) is a ROTEM measure available after 25–29 min used to guide early decisions. EXTEM A10, the clot firmness at 10 min, is an accepted early surrogate, but investigators differ on whether A5, the clot firmness at 5 min, is acceptable. We re‐examined this in a retrospective observational analysis of 1146 trauma patients in one centre who had ROTEM data recorded. A5 and A10 both correlated well with maximum clot firmness, with Pearson coefficients of r = 0.92 and r = 0.96, respectively. The correlations of A5, A10 and maximum clot firmness with requirement for massive transfusion were all similarly high, with c‐stats of 0.87, 0.89 and 0.90, respectively. The correlations with mortality were also similar but weaker, with c‐stats of 0.67, 0.69 and 0.69, respectively. Using a previously validated cut‐off of A5 < 35 mm to predict massive transfusion gave a sensitivity of 95%, specificity 83%, positive predictive value 9.3% and negative predictive value 100%. Using a value of A5 < 29 mm, for a pragmatic positive predictive value of 20%, gave a sensitivity of 67%, specificity 95% and negative predictive value 99%. Whether aiming for a high sensitivity or a strong predictive value, A5 was non‐inferior to A10 and actually missed fewer cases needing massive transfusion. A5 has similar utility to both A10 and maximum clot firmness as an early measure of clot firmness, and a low A5 value is strongly predictive of the need for massive transfusion.
Chemical modelling of glycolaldehyde and ethylene glycol in star-forming regions

Glycolaldehyde (HOCH$_2$CHO) and ethylene glycol ((CH$_2$OH)$_2$) are two complex organic molecules detected in the hot cores and hot corinos of several star-forming regions. The ethylene glycol/glycolaldehyde abundance ratio seems to show an increase with the source luminosity. In the literature, several surface-chemistry formation mechanisms have been proposed for these two species. With the UCLCHEM chemical code, we explored the different scenarios and compared the predictions for a range of sources of different luminosities with the observations. None of the scenarios reproduce perfectly the trend. A better agreement is, however, found for a formation through recombination of two HCO radicals followed by successive hydrogenations. The reaction between HCO and CH$_2$OH could also contribute to the formation of glycolaldehyde in addition to the hydrogenation pathway. The predictions are improved when a trend of decreasing H$_2$ density within the core region with T $\geq$ 100 K as a function of luminosity, is included in the model. Destruction reactions of complex organic molecules in the gas phase would also need to be investigated, since they can affect the abundance ratios once the species have desorbed in the warm inner regions of the star-forming regions.
The Educational Affordances of Mobile Instant Messaging (MIM): Results of Whatsapp® Used in Higher Education

The popularity of Mobile Instant Messaging MIM has prompted educators to integrate it in teaching and learning in higher education. WhatsApp® is a multi-platform instant messaging application widely used worldwide, however, there is still little applied research on its use as a platform for educational activities in management higher education. In this article, the authors present a quantitative and qualitative assessment of a concrete experience of WhatsApp® use that involved 140 undergraduate management students. Data were collected through questionnaires answered by the participants after the end of the experience of use, and also via content analysis of their conversations inside their WhatsApp® groups. The results indicate five main educational affordances of MIM that can be considered in management education: interactivity, knowledge sharing, sense of presence, collaboration and ubiquity. The article also explores the limitations of this tool and provides suggestions of good practices of MIM use for teaching and learning.
Accurate prediction of human mirna targets via graph modeling and machine learning approaches

miRNAs are small endogenous non-coding RNA molecules that have a critical function in suppressing genes and they also correlate with many diseases and cancers. Due to the importance of their effects in several cell activities, discovering their mechanisms is an important task. Because the functionality of miRNAs tightly connected to the way they recognize their targets miRNA target prediction has received a lot of attentions in research. Despite that, most of current methods suffer from high false positive rates and they are not able to provide much insight to the actual process of miRNA targeting. In this dissertation, we present two novel approaches aimed at addressing existing issues in miRNA target prediction; one approach to improve false positive rate and the other to substantiate multiple hypotheses pertaining to biological mechanism of miRNA targeting and to provide insight into the actual mechanism. To address the first issue, we present Correlation Graph model that captures nucleotide correlations between miRNA sequence and the target. This model makes it possible to characterize nucleotide correlations other than Watson-Crick base pairings between two parts of the duplex. We designed an SVM based algorithm and tested our model on human data and it achieved a sensitivity of 86% with a false positive rate below 13% which is a significant performance improvement in comparison to the state-of-the-art methods miRanda and RNAhybrid. The second part of this dissertation addresses the issue of understanding the mechanism of miRNA targeting. It contains a multi-hypothesis learner algorithm that utilizes features collected from literature pertaining to the mechanisms of targeting. These features enable the algorithm to partition data in a way very relevant to the biological features. The algorithm uses these partitions to learn multiple hypotheses. Our evaluations on human and mouse datasets show our method has comparable performance to that of high performance classifiers such as RandomForest. Moreover, feature selection on the resulting partitions confirms that the partitioning mechanism is compatible with biological mechanisms. These partitions could be used for further in vivo experiments to verify the currently proposed targeting approaches and to discover the new mechanisms. Index words: miRNA target prediction, miRNA, Machine Learning, Graph Modeling, Feature selection, Re-sampling Accurate Prediction of Human miRNA targets via Graph Modeling and Machine Learning Approaches
Parotid gland radiation dose‐xerostomia relationships based on actual delivered dose for nasopharyngeal carcinoma

Abstract Xerostomia induced by radiotherapy is a common toxicity for head and neck carcinoma patients. In this study, the deformable image registration of planning computed tomography (CT) and weekly cone‐beam CT (CBCT) was used to override the Hounsfield unit value of CBCT, and the modified CBCT was introduced to estimate the radiation dose delivered during the course of treatment. Herein, the beams from each patient's treatment plan were applied to the modified CBCT to construct the weekly delivered dose. Then, weekly doses were summed together to obtain the accumulated dose. A total of 42 parotid glands (PGs) of 21 nasopharyngeal carcinoma patients were analyzed. Doses delivered to the parotid glands significantly increased compared with the planning doses. V20, V30, V40, Dmean, and D50 increased by 11.3%, 28.6%, 44.4%, 9.5%, and 8.4% respectively. Of the 21 patients included in the study, eight developed xerostomia and the remaining 13 did not. Both planning and delivered PG Dmean for all patients exceeded tolerance (26 Gy). Among the 21 patients, the planning dose and delivered dose of Dmean were 30.6 Gy and 33.6 Gy, respectively, for patients with xerostomia, and 26.3 Gy and 28.0 Gy, respectively, for patients without xerostomia. The D50 of the planning and delivered dose for patients was below tolerance (30 Gy). The results demonstrated that the p‐value of V20, V30, D50, and Dmean difference of the delivery dose between patients with xerostomia and patients without xerostomia was less than 0.05. However, for the planning dose, the significant dosimetric difference between the two groups only existed in D50 and Dmean. Xerostomia is closely related to V20, V30, D50, and Dmean.
Natural Honey and Cardiovascular Risk Factors; Effects on Blood Glucose, Cholesterol, Triacylglycerole, CRP, and Body Weight Compared with Sucrose

It has been found that honey ameliorates cardiovascular risk factors in healthy individuals and in patients with elevated risk factors. The present study investigated the effect of natural honey on total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triacylglycerole, C-reactive protein (CRP), fasting blood glucose (FBG), and body weight in overweight individuals. There were 55 patients, overweight or obese, who were randomly recruited into the study and assigned into two groups: control group (17 subjects) and experimental group (38 subjects). Patients in the control group received 70 g of sucrose daily for a maximum of 30 days and patients in the experimental group received 70 g of natural honey for the same period. In the control and experimental groups, body weight, body mass index, body fat weight, total cholesterol, LDL-C, HDL-C, triacylglycerole, FBG, and CRP were measured before treatment and at day 31 after the commencement of treatment. Results showed that honey caused a mild reduction in body weight (1.3%) and body fat (1.1%). Honey reduced total cholesterol (3%), LDL-C (5.8), triacylglycerole (11%), FBG (4.2%), and CRP (3.2%), and increased HDL-C (3.3%) in subjects with normal values, while in patients with elevated variables, honey caused reduction in total cholesterol by 3.3%, LDL-C by 4.3%, triacylglycerole by 19%, and CRP by 3.3% (p < 0.05). It is our conclusion that consumption of natural honey reduces cardiovascular risk factors, particularly in subjects with elevated risk factors, and it does not increase body weight in overweight or obese subjects.
Effects of Site and Cultivar on Consumer Acceptance of Pomegranate.

Pomegranate (Punica granatum L.) is an important fruit in many cultures. The fruit and juice have risen in popularity as it was discovered that pomegranate has relatively high antioxidant activity compared to most other fruits. In this study, six cultivars were utilized to determine consumer acceptance compared to the industry standard, 'Wonderful,' which comprises 90% to 95% of commercial production in the United States. Fruit were sourced from 2 cultivar field trials, one in inland Riverside, California, and one in coastal Ventura County, California. Cultivars selected for the study included 'Eversweet,' 'Green Globe,' 'Haku Botan,' 'Loffani,' 'Phoenicia,' 'Wonderful,' and 'cv. 857,' an heirloom cultivar from Ventura County, CA, U.S.A. Pomegranate arils were subject to sensory evaluation by 87 untrained consumer panelists in late 2016. Panelists were given pomegranate arils and asked to score the samples using a 9-point Hedonic scale for the following fruit quality traits: aril color, sweetness, tartness, seed hardness, bitterness, and overall desirability. There were significant differences among cultivars for all traits assessed by the sensory panelists. There were differences in acceptance among consumers for 'Wonderful' depending on if it was grown on the coast versus inland, and consumers preferred inland- versus coastal-grown 'Wonderful. ' 'Wonderful' pomegranate was associated with cultivars that consumers scored low on desirability for bitterness. Cultivars that scored well in overall desirability compared with 'Wonderful' were 'cv. 857,' 'Eversweet,' 'Green Globe,' and 'Phoenicia. ' PRACTICAL APPLICATION Consumer sensory panels are important to determine scientifically which cultivars are desired by the public. These panels allowed for the determination of which pomegranate cultivars are liked or disliked by consumers and why. If the pomegranate growers know the most desirable cultivars for consumers, they are more likely to adopt and plant them, thus potentially increasing the diversity in the marketplace, as has been with apples, peaches, plums, pears, mangoes, strawberries, raspberries, blueberries, and citrus.