Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation of multiple sclerosis-related pathways through the integration of genomic and proteomic data

Multiple sclerosis (MS) has a complex pathophysiology, variable clinical presentation, and unpredictable prognosis; understanding the underlying mechanisms requires combinatorial approaches that warrant the integration of diverse molecular omics data. Here, we combined genomic and proteomic data of the same individuals among a Turkish MS patient group to search for biologically important networks. We previously identified differentially-expressed proteins by cerebrospinal fluid proteome analysis of 179 MS patients and 42 non-MS controls. Among this study group, 11 unrelated MS patients and 60 independent, healthy controls were subjected to whole-genome SNP genotyping, and genome-wide associations were assessed. Pathway enrichment analyses of MS-associated SNPs and differentially-expressed proteins were conducted using the functional enrichment tool, PANOGA. Nine shared pathways were detected between the genomic and proteomic datasets after merging and clustering the enriched pathways. Complement and coagulation cascade was the most significantly associated pathway (hsa04610, P = 6.96 × 10−30). Other pathways involved in neurological or immunological mechanisms included adherens junctions (hsa04520, P = 6.64 × 10−25), pathogenic Escherichia coli infection (hsa05130, P = 9.03 × 10−14), prion diseases (hsa05020, P = 5.13 × 10−13). We conclude that integrating multiple datasets of the same patients helps reducing false negative and positive results of genome-wide SNP associations and highlights the most prominent cellular players among the complex pathophysiological mechanisms.
Stable C and N isotope analysis elucidated the importance of zooplankton in a tropical seagrass bed of Santiago Island, Northwestern Philippines

ABSTRACT The role of zooplankton in a tropical seagrass ecosystem was investigated in milkfish farms pollution-impacted and -unimpacted seagrass beds in Santiago Island coral reefs, Northwestern Philippines. The aim was to compare between the two sites: (1) abiotic factors and zooplankton community parameters, and (2) the trophic structure using C and N stable isotopes. Low water (98–119 mV) and sediment (–121 to −138 mV) Oxidation Reduction Potential values indicated a reducing environment in the impacted site. Zooplankton in the impacted site showed the typical community response to eutrophication (low diversity, but high total abundance due to the dominance of the cyclopoid copepod Oithona oculata), generally few elevated δ15N values, but a significant shift towards depleted 13C due to the organic enrichment of fish-farm feeds. Apart from suggesting a highly complex food web with POM and zooplankton as main food sources in the unimpacted site, the Bayesian mixing model simulation generated reduced complexity in feeding interactions between basal sources, zooplankton, and fish including adults of a key fish species, Siganus fuscescens, in the impacted sites. In this study, C and N stable isotope analysis has clarified the importance of zooplankton as fish prey in a seagrass bed food web.
Effects of various factors on biomass, bioethanol, and biohydrogen production in green alga Chlamydomonas reinhardtii

Extensive usage of nonrenewable fossil fuels has urged the community to look into alternate renewable energy such as biofuels. The production of biofuels, including bioethanol, biohydrogen, biodiesel, etc., from crop plants again leads to food insecurity. Hence, the usage of algae, particularly green algae, is the best alternatives to generate biofuels. In the present study, the effects of various factors involved in algal growth in turn bioethanol and biohydrogen production levels were established by choosing green alga Chlamydomonas reinhardtii. Specifically, we crosschecked the effect of heavy metal Cobalt (Co), sodium bicarbonate, and Tris-acetate-phosphate (TAP) medium without Tris base on growth and biofuel production from C. reinhardtii under in vitro conditions. In the current work, 0.2 mg/l Co in TAP medium enhanced the growth and biomass in C. reinhardtii cultures. Furthermore, ethanol production levels were improved in feedstocks grown in TAP medium with 2.0 mg/l sodium bicarbonate. In another experiment, hydrogen production was high in full TAP medium with Tris (trisaminomethane) base when compared to TAP without Tris base. In conclusion, this work may be useful to improve the biomass and biofuel production in green algae.
Twenty-four-hour cloud cover calculation using a ground-based imager with machine learning

Abstract. In this study, image data features and machine learning methods were used to calculate 24 h continuous cloud cover from image data obtained by a camera-based imager on the ground. The image data features were the time (Julian day and hour), solar zenith angle, and statistical characteristics of the red–blue ratio, blue–red difference, and luminance. These features were determined from the red, green, and blue brightness of images subjected to a pre-processing process involving masking removal and distortion correction. The collected image data were divided into training, validation, and test sets and were used to optimize and evaluate the accuracy of each machine learning method. The cloud cover calculated by each machine learning method was verified with human-eye observation data from a manned observatory. Supervised machine learning models suitable for nowcasting, namely, support vector regression, random forest, gradient boosting machine, k-nearest neighbor, artificial neural network, and multiple linear regression methods, were employed and their results were compared. The best learning results were obtained by the support vector regression model, which had an accuracy, recall, and precision of 0.94, 0.70, and 0.76, respectively. Further, bias, root mean square error, and correlation coefficient values of 0.04 tenths, 1.45 tenths, and 0.93, respectively, were obtained for the cloud cover calculated using the test set. When the difference between the calculated and observed cloud cover was allowed to range between 0, 1, and 2 tenths, high agreements of approximately 42 %, 79 %, and 91 %, respectively, were obtained. The proposed system involving a ground-based imager and machine learning methods is expected to be suitable for application as an automated system to replace human-eye observations.
Simultaneous quantification of the major flavonoids from wild spinach by UHPLC-HRMS and their neuroprotective effects in a model of H2O2-induced oxidative stress on SH-SY5Y cells

A modified UHPLC-HRMS method for simultaneous quantification of eight flavonoids from the aerial parts of the wild spinach (Chenopodium bonus-henricus L.) was re-validated for specificity, the limit of detection and quantitation limit, linearity, accuracy, and precision. The glycosides of spinacetin (Chbhnf-04, Chbhnf-06, and Chbhnf-08) and patuletin (Chbhnf-01) were the predominant compounds. The total amount of assayed flavonoids from the aerial parts of a title plant was estimated to be 1.82% and 1.4% in two different populations from Vitosha Mountain (Bulgaria). The neuroprotective properties of compounds Chbhnf-02, Chbhnf-04, Chbhnf-06, Chbhnf-07, Chbhnf-08 were further assessed using a model of H2O2-induced oxidative stress on human neuroblastoma SH-SY5Y cells. All tested flavonoids demonstrated statistically significant neuroprotective activity close to that of silibinin. Patuletin (Chbhnf-07) and spinacetin (Chbhnf-08) triglycosides showed the most protective effects at the lowest concentration of 50 µM.
Prevalence of shigellosis and associated risk factors among undergraduate students of a private university in Ogun State, Nigeria

This cross-sectional, institutional-based study aimed to determine the prevalence of shigellosis and associated risk factors among Babcock University students in Ogun State, Nigeria. One hundred and twenty (120) undergraduate students, 80 females and 40 males, were asked to provide stool specimen in a sterile leak-proof single-use universal bottle with a screw-capped lid. Standard microbiological techniques were used to analyse the stool samples. A questionnaire was designed to collect demographic and clinical information from participants. The data obtained were statistically analysed using the SPSS Statistics software (version 18.0). The study showed that there was no occurrence of shigellosis among the study participants (0%), but other enteric pathogens infection were present in all participants (100%). The three most common mono-infections found among the study participants included Staphylococcus aureus (40%), followed by Escherichia coli (16.7%), and Salmonella typhi and Bacillus spp. (3.3%, each). While the most common prevalence of dual-infections included Staphylococcus aureus and Escherichia coli (33.3%), followed by Staphylococcus aureus and Salmonella typhi (3.3%). The proportion of participants who were asymptomatic (66.7%) was significantly higher than the symptomatic ones (33.3%). Identified risk factors of non-Shigella enteric infection included consumption of beef, vegetables, fruits, poultry/poultry products, as well as street foods, poor hand hygiene before eating, anal cleaning, and poor hand hygiene after toileting. Although shigellosis did not exist among undergraduate students of Babcock University, this study highlighted the existence of other enteric infections among the study participants. Therefore, the necessary preventive measures should be ensured and sustained.
Current Status and Future Outlook on Occupational Health and Safety Research in Sudan: A Concise Review

The concept of occupational health and safety (OHS) describes the strategies, guidelines, and actions typically adopted and implemented to prevent, minimize or manage the risks associated with the health and safety of people and property. Over the years, the rapid growth, development and operation of various industries in developing countries have resulted in numerous accidents, injuries and illnesses. Given the short- and long-term effects of such issues, it is imperative to identify, examine and highlight the potential areas where workplace-related incidences could occur in the industry. Therefore, this paper presents an overview of the current status and future outlook on occupational health and safety (OHS) research in Sudan. The review of the literature indicates that although OHS research is still in its infancy in Sudan, various researchers have examined the nature, sources, and impacts of accidents, injuries, and illnesses that severely comprise workers’ health and safety. Furthermore, workers in Sudan are routinely exposed to toxic chemicals, medical wastes, noxious gases, noise pollution and other workplace-related risks that severely affect human health, safety and the environment. However, many employers, workers and government agencies have ample knowledge of OHS and its importance in the workplace. The studies also highlighted the crucial role played by OHS not only on health and safety but also the overall organisational performance and operational management in workplaces. Therefore, the design, development, and integration of OHS programmes into the workplace could greatly minimize and eliminate work-related accidents, illness, injuries or death.
The Relationship between Intellectual Property Risk and Stability of Asymmetric Research and Development Alliance

Small- and medium-sized enterprises (SMEs) establish asymmetric research and development (R&D) alliance with core enterprises to improve innovation efficiency. Unfortunately, the gap in the status and bargaining power between enterprises in such partnerships makes the intellectual property risk situation complicated. While gaining support and assistance from core enterprises, SMEs face the risk of exposing their core knowledge and key resources, which seriously affects the stability of R&D alliance and the sustainability of cooperative innovation. How to protect the intellectual property rights of SMEs in the asymmetric R&D alliance and improve the alliance’s stability is an urgent problem to be solved. Based on the theory of resource dependence and transaction cost, this study uses 260 high-tech companies participating in the asymmetric R&D alliance as a sample to conduct empirical research from the perspective of SMEs in a weak position. The purpose of this study is to sort out the types of intellectual property risks in the alliance and clarify the relationship between them and the stability of asymmetric R&D alliance. Furthermore, this study examines the moderating effects of contract governance mechanisms and relational contracts to explore effective governance mechanisms at the alliance level. Empirical results show that the intellectual property investment risk and the intellectual property loss risk have a significant negative impact on the stability of asymmetric R&D alliance. The contract governance mechanism negatively moderates the impact of intellectual property investment risk on the stability of the asymmetric R&D alliance. The relationship governance mechanism negatively moderates the impact of intellectual property loss risk on the stability of the asymmetric R&D alliance. The contract and relationship governance mechanism jointly negatively moderate the impact of intellectual property investment risk and loss risk on the stability of the asymmetric R&D alliance.
DDDT_A_323715 3765..3772

1Department of Anesthesiology, Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China; 2Department of Anesthesiology, Haining Maternal and Child Health Hospital, Jiaxing, People’s Republic of China Purpose: Treatment of spinal anesthesia-induced hypotension in patients with severe preeclampsia assumes special concern as hypotension may further reduce placental perfusion. Phenylephrine is still the first-line vasopressor for treating spinal anesthesia-induced hypotension. However, the optimal dose of phenylephrine used as intravenous (IV) boluses in patients with severe preeclampsia has not been clearly determined. We aim to calculate the 90% effective dose (ED90) of phenylephrine as IV boluses for treating spinal anesthesiainduced hypotension in patients with severe preeclampsia undergoing cesarean delivery. Patients and Methods: Forty patients with severe preeclampsia were enrolled in this prospective sequential allocation dose-finding trial. Using the biased coin up-and-down (BCUD) method, all patients in our study received an IV bolus phenylephrine of either 40, 50, 60, 70, or 80 μg when the mean arterial pressure (MAP) decreased to less than 80% of the baseline level and the ED90 was determined. The primary outcome was the success of the assigned phenylephrine bolus to maintain the MAP at or above 80% of baseline value between the induction of spinal anesthesia and delivery of the fetus. Secondary outcomes included hypertension, nausea, vomiting, bradycardia, upper sensory level of anesthesia, umbilical blood gases, and Apgar score. Estimating of the ED90 with 95% confidence interval (CI) was achieved by isotonic regression method. Results: The ED90 of phenylephrine was estimated as 62.00 μg (95% CI=50.00–67.40 μg) using the isotonic regression method. No patients enrolled in our study experienced bradycardia and those patients who developed hypertension were all observed at the dose level 70 μg. Conclusion: For clinical practice, we recommend that phenylephrine 60 μg may be both effective and safe for treatment of spinal anesthesia-induced hypotension in severe preeclampsia during cesarean delivery.
Theoretical and Practical Issues of Research on the Consumption Needs for Safe Foods in Vietnam Using the Willingness to Pay Model

Research on consumer needs for safe foods under the willingness to pay (WTP) approach based on consumer behavior has been performed widely and has contributed greatly to the development of safe foods, assisted enterprises’ decision-making processes in improving agricultural and food products, and provided orientation to policymakers in improving public health as well as in fostering sustainable economic growth. Some of the methods used for measuring WTP for safe foods, such as contingent value (CV), choice experiment (CE), and auction experiment (AE), have made significant contributions to the evaluation of consumers’ WTP for food safety. Moreover, the application of these models has helped to estimate the effects of many factors such as demography, consumer habits, continuation of food safety, individual characteristics, promotion, and product attributes, etc., on the WTP for food safety. The trend of safe food consumption in Vietnam has distinct characteristics, some of which come from national cultural identities; therefore, Vietnamese researchers may approach the empirical studies on this issue all over the world in order to find proper methods for studying consumer needs for safe foods in Vietnam.
Depression and Anxiety as Important Aggravating Factors of Pain in Morton’s Neuroma: A Case Report

This report represents a case of Morton’s neuroma with episodic severe pain in the forefoot. Initially, the patient was prescribed naproxen 500mgtwiceperday,anti-inﬂammatorytopicalcream,andmassage. Ina follow up visit, the patient was still experiencing frequent episodic sharp pain. In a detailed patient interview, it was revealed that she has depres-sionandanxietyandsuﬀersfromsocialisolation,whichco-occurredwith episodes of severe pain. Therefore, she was referred to a psychologist and a community support group and started practicing body relaxation techniques such as guided imagery and breathing exercises. The new treatment strategy had a major impact on improving her symptoms. This report aims to illustrate that depression and anxiety can be one of the main aggravating factors in conditions that cause episodic pain, as in this case of Morton’s neuroma. Removing psychosocial contributors of pain has the potential to decrease the need for more invasive interventions.
Performance and competitiveness of red vs. green phenotypes of a cyanobacterium grown under artificial lake browning

Increasing inputs of dissolved organic matter (DOM) to northern lakes is resulting in ‘lake browning. ’ Lake browning profoundly affects phytoplankton community composition by modifying two important environmental drivers—light and nutrients. The impact of increased DOM on native isolates of red and green-pigmented cyanobacteria identified as Pseudanabaena, which emerged from a Dolichospermum bloom (Dickson Lake, Algonquin Provincial Park, Ontario, Canada) in 2015, were examined under controlled laboratory conditions. The genomes were sequenced to identify phylogenetic relatedness and physiological similarities, and the physical and chemical effects of increased DOM on cellular performance and competitiveness were assessed. Our study findings were that the isolated red and green phenotypes are two distinct species belonging to the genus Pseudanabaena; that both isolates remained physiologically unaffected when grown independently under defined DOM regimes; and that neither red nor green phenotype achieved a competitive advantage when grown together under defined DOM regimes. While photosynthetic pigment diversity among phytoplankton offers niche-differentiation opportunities, the results of this study illustrate the coexistence of two distinct photosynthetic pigment phenotypes under increasing DOM conditions.
Convolutional Neural Networks in Medical Image Understanding

In the era of social media images/pictures play a vital role. Facebook, whatsapp, instagram everywhere we see a lot of pictures nowadays. Along with social media, the pictures play a very important role in medical science. Medical Image can help in diagnosis, clinical treatment and teaching tasks. Traditional classification of images has reached an end because of its time taking nature and efforts made to extract, select and classify . This problem is solved with the help of CNN(Convolutional neural network). In medical science we have treatment for body anomalies that were not there before . Using the deep learning models of CNN we can detect the disease like Cancer ,Lung Infection and treat it. This article aims to provide a comprehensive survey of applications of CNNs in medical image understanding.
Urban Fine Management of Multisource Spatial Data Fusion Based on Smart City Construction

With the increase of the types of urban management objects, the intelligent management of the whole city has become a matter of concern in various countries, and it is also one of the indispensable links in urban development. In the construction of cities all over the world, the intelligent and scientific management system has been used innovatively. We provide excellent facilities for transportation development, information exchange, and resource progress. The research on urban fine management based on multisource spatial data fusion is proposed. Aiming at the traffic problems in urban fine management, this paper proposes a deep network architecture based on multisource data fusion. Multisource spatial data fusion technology is used to analyze urban traffic data. Deep network architecture is used to improve the precision management status of a smart city and the accuracy of traffic condition prediction. Then, the convolution neural network technology is explored in the data fusion technology strategy. The research results show that the framework has the ability to deal with heterogeneous data and urban big data and can effectively improve the traffic management state in the construction of a smart city and effectively solve the complexity of urban fine management and processing efficiency in the construction of a smart city.
FLOW PATTERNS IN THE MAGNETIC NANOFLUID CORE OF A MINIATURE PLANAR SPIRAL TRANSFORMER

This paper analyses mathematical models and numerical simulation results for a notional miniature, planar, spiral transformer (MPST) fabricated in MEMS technology, for galvanic separation, proposed to equip an electric harvesting device (EHD). Two types of core – ferrite and (partially) magnetic nanofluid – are considered. We found that magnetization body forces occur in the super-paramagnetic nanofluid core and they result in complex, steady state flows consisting of fully 3D recirculation cells.
Self-Evaluation of Jurnal Informatika Sunan Kalijaga (JISKa): Perspectives of Reviewers and Authors

The success of JISKa is inseparable from the role of reviewers and authors. Unfortunately, JISKa had never been assessed or evaluated by reviewers and authors despite the fact that assessment from the reviewers and authors would be valuable feedback for JISKa’s self-evaluation. Therefore, survey-based research has recently been conducted to assess JISKa’s performance using the User Acceptance Test of OJS version 2.4. 8.0. This study used a survey method to obtain an assessment and evaluation from reviewers and authors related to JISKa.The respondents in this study consist of 68 authors and 26 reviewers. The result of this study stated that 91.2% of the authors and 84.6% of reviewers are satisfied with JISKa. A percentage number of 100% of writers and reviewers wants JISKa to raise its level of Sinta accreditation. This accreditation is awarded in 2018 and will end in 2023. JISKa is now on Sinta 4.The JISKa website appearance looks good and easy to use. The dashboard on the JISKa page is user-friendly for the author. However, the current version of JISKa OJS 2.4. 8.0 needs to be upgraded to OJS version 3. There are some points for the future consideration of JISKa: JISKa needs to promote itself more, upgrade the OJS version, and provide the reviewers with certificates of appreciation for future consideration.