Miracle-dz/UniFAR-FTUs huggingface dataset:
Immune Infiltration and N(6)-Methyladenosine ncRNA Isoform Detection in Acute Lung Injury

Acute lung injury (ALI) is a severe form of sepsis that is associated with a high rate of morbidity and death in critically ill individuals. The emergence of ALI is the result of several factors at work. Case mortality rates might range from 40% to 70%. Researchers have discovered that epigenetic alterations are important in the pathophysiology of ALI and that using epigenetic inhibitors may help reduce symptoms. In embryonic development, circadian rhythm, the cell cycle, and cancer, methylation of m6A seems to be relevant all along the way. According to recent research, posttranscriptional methylation is a key player in the development of alveolar lymphoma. In this study, we clustered ALI based on m6A-related factors, analyzed different classes of immune cell enrichment and inflammatory cytokine expression, screened clustered differential genes for ALI to construct coexpression networks, screened key ALI genes potentially regulated by m6A modifications, and then typed the disease based on key genes to compare the consistency of different clustering results. Our findings have revealed a hitherto undiscovered prognostic sign and a therapeutic target for ALI therapy in m6A and immune invading cells, respectively.
Case Report: Training Monitoring and Performance Development of a Triathlete With Spinal Cord Injury and Chronic Myeloid Leukemia During a Paralympic Cycle

Introduction Paratriathlon allows competition for athletes with various physical impairments. The wheelchair category stands out from other paratriathlon categories, since competing in swimming, handcycling, and wheelchair racing entails substantial demands on the upper extremity. Therefore, knowledge about exercise testing and training is needed to improve performance and avoid overuse injuries. We described the training monitoring and performance development throughout a Paralympic cycle of an elite triathlete with spinal cord injury (SCI) and a recent diagnosis of chronic myeloid leukemia (CML). Case Presentation/Methods A 30-year-old wheelchair athlete with 10-years experience in wheelchair basketball contacted us for guidance regarding testing and training in paratriathlon. Laboratory and field tests were modified from protocols used for testing non-disabled athletes to examine their physical abilities. In handcycling, incremental tests were used to monitor performance development by means of lactate threshold (POBLA) and define heart rate-based training zones. All-out sprint tests were applied to calculate maximal lactate accumulation rate (V˙Lamax) as a measure of glycolytic capabilities in all disciplines. From 2017 to 2020, training was monitored to quantify training load (TL) and training intensity distribution (TID). Results From 2016 to 2019, the athlete was ranked within the top ten at the European and World Championships. From 2017 to 2019, annual TL increased from 414 to 604 h and demonstrated a shift in TID from 77-17-6% to 88-8-4%. In this period, POBLA increased from 101 to 158 W and V˙Lamax decreased from 0.56 to 0.36 mmol·l−1·s−1. TL was highest during training camps. In 2020, after he received his CML diagnosis, TL, TID, and POBLA were 317 h, 94-5-1%, and 108 W, respectively. Discussion TL and TID demonstrated similar values when compared with previous studies in para-swimming and long-distance paratriathlon, respectively. In contrast, relative TL during training camps exceeded those described in the literature and was accompanied by physical stress. Increased volumes at low intensity are assumed to increase POBLA and decrease V˙Lamax over time. CML treatment and side effects drastically decreased TL, intensity, and performance, which ultimately hindered a qualification for Tokyo 2020/21. In conclusion, there is a need for careful training prescription and monitoring in wheelchair triathletes to improve performance and avoid non-functional overreaching.
Economic Analysis of the Link between Advances in Biopharmaceutical Manufacturing and Healthcare Delivery Costs

Concerns about increasing expenditures on new biologic medicines has speared interests in finding solutions to contain healthcare delivery costs whilst, at least, maintaining population health indicators at the same levels. Often overlooked are investments in pharmaceutical manufacturing research, which perhaps is because manufacturing costs are thought to only make a small fraction of drug prices, and hence any impact on healthcare delivery costs is small enough to be ignored. This thesis provides evidence, to the contrary, that the impact on healthcare delivery costs cannot be trivialized. Starting with a systematic review of literature, this thesis finds that there are inconsistencies in what items are included or excluded from estimates of drug administration costs. On the back of this finding, this thesis evaluated drug administration costs for a sample of biologic drugs to identify manufacturing choices that explain most the observed variation in administration costs. It presents an algorithm pharmaceutical manufacturers could use to predict the expected administration-cost savings from reformulating biologic drug candidates still in development and/or existing medicines already on the market. This thesis goes further to argue that a primary focus on the monetary costs of drug administration ignores intangible benefits from satisfying end-user preferences for different modes of drug administration. The monetary value of these intangible benefits could be in the same order of magnitude as savings on the direct monetary costs of drug administration. In addition, this thesis shows that using cost-reducing process innovations in drug manufacturing, as opposed to cost-increasing ones, is associated with a higher number of products available for clinical use and lower prices over time; whilst the likelihood that a drug product is no longer available is seemingly unrelated to the process innovation deployed in manufacturing. The evidence put together indicate significant societal benefits from developing and implementing innovations in pharmaceutical manufacturing.
Resilience and Regulation of Emotions in Adolescents: Serial Mediation Analysis through Self-Esteem and the Perceived Social Support

The aim of this study was to test a model that takes into account self-esteem and perceived social support as potential mediators of the relationship between resilience and emotional regulation. The study involved 251 adolescents aged between 14 and 19 years (M = 16.85). The study procedure consisted of completing paper-and-pencil questionnaires to measure resilience, self-esteem, and answer questions about perceived social support and emotional regulation. Bootstrap sampling analysis showed statistically significant serial mediation (B = 0.030; p < 0.001). As a result of the analysis, a positive direct relationship between resilience and emotional regulation was observed (B = 0.061; p < 0.001). Our results suggest that self-esteem and perception of social support may mediate the relationship between resilience and emotional regulation. The findings have an applicable value. They can be used to develop preventive and educational programs, as well as therapeutic interventions. The obtained results show that interventions aimed at resilience can improve self-assessment and perceived social support and thus favor the high level of emotional regulation skills in the adolescent group.
Building diverse climate coalitions: The pitfalls and promise of equity- and identity-based messaging.

In response to the largest climate demonstrations in history and growing recognition of the disproportionate impacts of climate change on disadvantaged communities, environmental organizations are increasingly looking to diversify their memberships and enhance public outreach. In this review, we consider unique challenges inherent in building racially, ethnically, and socioeconomically diverse climate coalitions and highlight three often implicit assumptions that may undermine the effectiveness of equity-and identity-based climate communications and public outreach efforts: (a) that pro-diversity messaging is viewed as inclusive by both racial and ethnic majority and minority groups; (b) that making specific identity groups salient will engage targeted individuals; and (c) that enhancing the salience of climate-related inequities bolsters public support for efforts to reduce those inequities. Drawing from psychological research and theory as well as real-world examples, we discuss problems with each of these assumptions, highlight current knowledge gaps, and offer practical recommendations for more effectively tailoring communications to broaden public engagement across differences.
Older Adults’ Physical Activity and Social Participation During COVID-19

ABSTRACT COVID-19 disrupted older adults’ physical and social participation. We examined changes in social participation and physical activity during COVID-19 and perceptions of precautionary measures and online or outdoor classes in 155 older adults (M age = 70.50 ± 4.62 years). Patrons at Calgary recreation centers ≥ 65 years recruited via e-mail were surveyed between August-September 2020. Social participation (p <0.01) and resistance (p <0.01) and flexibility (p =0.03) physical activity declined. Mild physical activity increased (p =0.03). 33.57% attended online classes. Most precautionary measures were endorsed. Understanding behavior and receptivity to precautions helps providers adapt to COVID-19.
A retrospective assessment of the dental malpractice cases filed in Riyadh from 2009-2015

Introduction: Malpractice is one of the most significant hazards to patient safety in healthcare and is considered the second factor associated with the overall quality of the healthcare system. Aims and Objectives: This study aimed to assess the prevalence of malpractice in dentistry and its possible causes in Riyadh, Saudi Arabia during 2009-2015. Methodology: A cross-sectional retrospective analysis of the dental complaints filed by the patients in the general directorate of forensic medicine centers in Riyadh was reviewed, and the data was collected. Descriptive statistics of frequency distribution and percentages were calculated using the collected data. The Chi-square test for categorical variables was performed with a significance level set at P < 0.05. Results: The Riyadh region reported 168 (14.5%) dental malpractice cases during 2009- 2015. The highest number of malpractice cases was reported in 2010 (18.45%), and the least number of cases was reported in 2011 (10.1%). Prosthodontic specialty had the highest number of lawsuits (32.4%), followed by orthodontics (20.2%) and endodontics (15.8%). The Chi-square test showed no association between the different specialties and types of malpractice (P = 0.881) and between compensation and the type of malpractice (P = 0.832). Among the 114 cases, financial compensation was the most common retribution. Conclusion: Dental malpractice prevalence was high in the private sector, followed by the government and military sectors, with the highest number of cases registered against the prosthodontic specialty. Dental malpractice is a serious concern that can be prevented by fair and honest policies and thorough patient education.
Machine Learning–Based Overall Survival Prediction of Elderly Patients With Multiple Myeloma From Multicentre Real-Life Data

Objective To use machine learning methods to explore overall survival (OS)-related prognostic factors in elderly multiple myeloma (MM) patients. Methods Data were cleaned and imputed using simple imputation methods. Two data resampling methods were implemented to facilitate model building and cross validation. Four algorithms including the cox proportional hazards model (CPH); DeepSurv; DeepHit; and the random survival forest (RSF) were applied to incorporate 30 parameters, such as baseline data, genetic abnormalities and treatment options, to construct a prognostic model for OS prediction in 338 elderly MM patients (>65 years old) from four hospitals in Beijing. The C-index and the integrated Brier score (IBwere used to evaluate model performances. Results The 30 variables incorporated in the models comprised MM baseline data, induction treatment data and maintenance therapy data. The variable importance test showed that the OS predictions were largely affected by the maintenance schema variable. Visualizing the survival curves by maintenance schema, we realized that the immunomodulator group had the best survival rate. C-indexes of 0.769, 0.780, 0.785, 0.798 and IBS score of 0.142, 0.112, 0.108, 0.099 were obtained from the CPH model, DeepSurv, DeepHit, and the RSF model respectively. The RSF model yield best scores from the fivefold cross-validation, and the results showed that different data resampling methods did affect our model results. Conclusion We established an OS model for elderly MM patients without genomic data based on 30 characteristics and treatment data by machine learning.
Optimisation of alginate-pectin bead formulation using central composite design guided electrospray technique

Alginate-pectin beads act as a carrier in improving the oral bioavailability of bioactive compounds. Electrospray technique facilitates the production of uniform size and shape of alginate-pectin beads. Interaction between key electrospray process parameters affects the size and shape of the beads. A proper model should be employed to establish these correlating interactions. In the present work, the electrospray technique was guided with a central composite design (CCD) and response surface methodology (RSM). One quadratic and one linear model were obtained for size and sphericity coefficient, respectively. The CCD-RSM empirical model derived from the present work is essential to determine the significant factors and their levels in producing beads with consistent size and sphericity coefficient. The results indicated that the applied voltage had the most significant influence on size, while the alginate-pectin concentration was the most prominent factor in producing spherical beads. Spherical beads with a minimum size of 2.97 mm were obtained at an alginate-pectin concentration of 3.5%, a flow rate of 10.0 mL/h, an applied voltage of 2.4 kV, and a distance between the nozzle and the gelation bath of 16.0 cm.
Bioactive compounds, volatile, and texture profile of muffins after partial substitution of butter and milk

The aim of the present work was to determine the optimal level for partial substitution of butter and milk with pistachio paste and rose water. The quantity of pistachio paste added to the muffins was 6, 9, and 12%, while the quantity of rose water was 5% for all the samples, except for control sample. A significant increase in protein (6.52 - 8.01%), total phenols (13.19 - 18.54 mg GAE/100 g), and antioxidant capacity (10.83 - 16.69% RSA) was observed, as well as a decrease in fat (13.06 - 11.98%). The concentrations of individual sugars namely sucrose, glucose, and fructose were not significantly influenced by the added pistachio paste. The volatile compounds which were predominant in the analysed samples were benzaldehyde, D-limonene, 1,3-dioxolane, 4-methyl-2-phenyl-, β-myrcene, α-pinene, β-linalool, phenylethyl alcohol, and β-citronellol. Regarding the textural profile, the muffin samples added with pistachio paste and rose water were not significantly influenced (p > 0.05).
Evaluation of Antioxidant and Cytotoxic Activity of Hydro-Ethanolic Extracts Obtained from Steiractinia aspera Cuatrec

In this work, the antioxidant activity of the hydro-ethanolic extracts of the leaves, flowers, and aerial parts of Steiractinia aspera Cuatrec, both fresh and post-distillation, was evaluated by ABTS+·, FRAP, H2O2 and DPPH assays. The cytotoxic activity was evaluated in MCF-7, MCF-10A and HT-29 cell lines. The hydro-ethanolic extracts were obtained by matrix solid-phase dispersion (MSPD) and ultrasound-assisted solvent extraction (SE). The fresh-leaf MSPD extract had the highest antioxidant activity, and the post-distillation leaf ultrasound-assisted SE extract had the highest cytotoxicity in the MCF-7 breast cancer cell line, although not selective, which was evaluated by sulforhodamine B assay. On the other hand, ROS was evaluated by flow cytometry which showed that post-distillation leaf extract is pro-oxidant. Chlorogenic acid, kaempferol-3-glucoside and quercetin were found in the fresh leaves’ extracts, according to HPLC-DAD. PLC-DAD permitted the isolation of p-coumaric acid, E-3-(4-(((E)-3-(3,4-dihydroxyphenyl) acryloyl) oxy)-3-hydroxyphenyl) acrylic acid and a diglucosylated derivative of ursolic acid, which were analyzed by 1H and 13C NMR. Our results suggest that the fresh leaf extract of Steiractinia aspera Cuatrec has potential use for antioxidant applications.
Entanglements in urban governance in new African cities: Appolonia City in the Greater Accra Region, Ghana

ABSTRACT Large scale urban development projects, marketed as “new cities,” are emerging across the African continent. However, there is a limited empirical insight into how their partnerships, involving foreign investors and the local African landowners, are brokered, and the extent to which local communities are engaged in such projects. Using the Appolonia City project in Ghana and drawing analytical insights from the DEDA urban governance framework, this paper scrutinizes the partnership between Rendeavour, the foreign investor, and the Appolonia community, the owners of the land used for the project, to interrogate the extent to which the community has been involved, and the benefits that have accrued. We find that the traditional rulers saw the project as an opportunity to secure community lands against ongoing unauthorized encroachments, and to assist the local economy. We argue that the 99-year lease granted to Rendeavour in return for a 10% equity stake does not reflect a partnership where concessions and benefits are equally distributed. The paper concludes by reflecting on the implications of the unequal partnership arrangements and the ensuing entangled urban governance process that set in motion project outcomes that do not necessarily reflect the needs of urban citizens.
Board 14: Work in Progress: #FunTimesWithTheTA - A Series of Fun Supplementary Lessons for Introductory Level Biomedical Instrumentation Students (Part II)

Orlando is a PhD student in Biomedical Engineering at Purdue University. Orlando graduated from Vanderbilt University in 2014 with a Bachelor of Engineering in Biomedical Engineering. His academic interests involve developing wearable sensors for mobile health platforms and developing engaging engineering design activities for undergraduate students. He has several years of experience with analog circuit design and embedded systems. His previous work includes developing an impedance analyzer for a microfluidic blood-brain barrier model. On the education side, he has developed a number of lab activities for first year and junior level Biomedical Engineering students. Aside from his academic pursuits, he is an avid electronics hobbyist and tinkerer. He spends most of his free time developing open source hardware for students, educators, and makers alike.
Predicting the Spread of SARS-CoV-2 in Italian Regions: The Calabria Case Study, February 2020–March 2022

Despite the stunning speed with which highly effective and safe vaccines have been developed, the emergence of new variants of SARS-CoV-2 causes high rates of (re)infection, a major impact on health care services, and a slowdown to the socio-economic system. For COVID-19, accurate and timely forecasts are therefore essential to provide the opportunity to rapidly identify risk areas affected by the pandemic, reallocate the use of health resources, design countermeasures, and increase public awareness. This paper presents the design and implementation of an approach based on autoregressive models to reliably forecast the spread of COVID-19 in Italian regions. Starting from the database of the Italian Civil Protection Department (DPC), the experimental evaluation was performed on real-world data collected from February 2020 to March 2022, focusing on Calabria, a region of Southern Italy. This evaluation shows that the proposed approach achieves a good predictive power for out-of-sample predictions within one week (R-squared > 0.9 at 1 day, R-squared > 0.7 at 7 days), although it decreases with increasing forecasted days (R-squared > 0.5 at 14 days).
Landform classification based on landform geospatial structure – a case study on Loess Plateau of China

ABSTRACT Landform classification, which is a key topic of geography, is of great significance to a wide range of fields including human construction, geological structure research, environmental governance, etc. Previous studies of landform classification generally paid attention to the topographic or texture information, whilst the watershed spatial structure has not been used. This study developed a new landform classification method based on watershed geospatial structure. Via abstracting the landform into the internal and marginal structure, we adopted the gully weighted complex network (GWCN) and watershed boundary profile (WBP) to simulate the watershed geospatial structure. Introducing various indices to quantitatively depict the watershed geospatial structure, we conducted the landform classification on the Northern Shaanxi of Loess Plateau with a watershed-based strategy and established the classification map. The classified landform distribution has significant spatial aggregation and clear regional boundaries. Classification accuracy reached 89% and the kappa coefficient reached 0.87%. Besides, the proposed method has a positive response to some similar and complex landforms. In general, the present study first utilized the watershed geospatial structure to conduct landform classification and is an efficient landform classification method with well accuracy and universality, offering additional insights for landform classification and mapping.