Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanistic insights of magnolol antimicrobial activity against Mycoplasma using untargeted metabolomic analyses

The unreasonable use of antibiotics is one of the important causes of antimicrobial resistance (AMR) that poses a huge public health threat. Magnolol is a traditional Chinese medicine exhibiting antibacterial-, antifungal-, anti-inflammatory-, and antioxidant activities. However, it is unclear whether magnolol has an inhibitory effect on mycoplasma. This study found that magnolol showed excellent inhibitory activity against various mycoplasmas. Magnolol showed dose-dependent inhibition of Mycoplasma synoviae growth and biofilm formation in vitro. Magnolol caused severely sunken and wrinkled M. synoviae cell membranes at the minimum inhibitory concentration, and an enlarged cell diameter. The chicken embryo infection model showed that magnolol significantly reduced M. synoviae pathogenicity in vivo. Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that the citrate cycle, glycolysis/gluconeogenesis, and pyruvate metabolism were significantly disturbed at the minimum inhibitory concentration of magnolol. Interestingly, 41% of differential metabolites were in the categories of lipids and lipid-like molecules. Protegenin A was up-regulated 58752-fold after magnolol treatment. It belongs to fatty acyls, and destroys cell membrane integrity and cell activity. Ghosphatidylethanolamine, phosphatidylglycerol, phosphatidic acid, and phosphatidylserine related to membrane maintenance and stress response were widely down-regulated. Collectively, our results illustrate the feasibility of magnolol as a phytochemical compound to treat mycoplasma infection.
Plant functional trait shifts explain concurrent changes in the structure and function of grassland soil microbial communities

Land‐use intensification drives changes in microbial communities and the soil functions they regulate, but the mechanisms underlying these changes are poorly understood as land use can affect soil communities both directly (e.g. via changes in soil fertility) and indirectly (e.g. via changes in plant inputs). The speed of microbial responses is also poorly understood. For instance, whether it is long‐term legacies or short‐term changes in land‐use intensity that drive changes in microbial communities. To address these topics, we measured multiple microbial functions, bacterial and fungal biomass and abiotic soil properties at two time intervals 3 years apart. This was performed in 150 grassland sites differing greatly in management intensity across three German regions. Observed changes in microbial soil properties were related to both long‐term means and short‐term changes in: abiotic soil properties, land‐use intensity, community abundance‐weighted means of plant functional traits and plant biomass properties in regression and structural equation models. Plant traits, particularly leaf phosphorus, and soil pH were the best predictors of change in soil microbial function, as well as fungal and bacterial biomass, while land‐use intensity showed weaker effects. Indirect legacy effects, in which microbial change was explained by the effects of long‐term land‐use intensity on plant traits, were important, thus indicating a time lag between plant community and microbial change. Whenever the effects of short‐term changes in land‐use intensity were present, they acted directly on soil microorganisms. Synthesis. The results provide new evidence that soil communities and their functioning respond to short‐term changes in land‐use intensity, but that both rapid and longer time‐scale responses to changes in plant functional traits are at least of equal importance. This suggests that management which shapes plant communities may be an effective means of managing soil communities and the functions and services they provide.
Significance of total and specific IgE in asthma of Iraqi adult patients

A case-control retrospective study was conducted during January – June 2019 on 104 patients with asthma (50 females and 54 males) and 111 non-asthmatic healthy subjects matched patients for gender (54 females and 57 males) to assess role of total and specific IgE serum levels in patho-physiology of disease using ELISA and multiplex immunoblot kits. The mean age ± standard deviation of asthma patients was 37.9 ± 12.1 years, while it was lower among control (35.9 ± 10.5 years), but the difference was not significant. Males and females were similarly distributed among asthma cases (48.1 and 51.9%, respectively) and control (48.6 and 51.4%, respectively). Most of asthma cases were observed to have mild disease (49%), followed by moderate and severe asthma (93.4 and 11.5%, respectively). It was also observed that 51.9% of patients had a family history of asthma. With respect to allergen type, 21.2% of asthma cases were seropositive for mixed types of allergens. Median level of total IgE was significantly (p < 0.001(elevated in sera of asthma cases (204.1 ng/ml) compared to control subjects (163.3 ng/ml). The level positively paralleled the severity of disease. The highest level was observed in severe cases (244.9ng/ml, while the lowest level was recorded in mild cases (189.7 ng/ml). The level of specific IgE showed some variations among asthma cases distributed according to the type of allergen, the highest median was recorded in seronegative cases (215.2 ng/ml), while a lowest level was observed in cases seropositive for animal dander (189.3 ng/ml). Logistic regression analysis revealed that total asthma patients, as well as male and female cases were at an increased risk to develop asthma episodes due to elevated serum level of IgE.ROC analysis demonstrated that elevated serum level of IgE occupied a significant (p = 0.001) area under curve (AUC), which was 0.828. In conclusion, the present study confirms the significant role of total and specific IgE in patho-physiology of bronchial asthma and its correlation with disease severity and allergen type in adults
Moving cancer care closer to home: a single-centre experience of home chemotherapy administration for patients with myelodysplastic syndrome

Myelodysplastic syndrome (MDS) is a disease of elderly with a median age of 70.1 Azacitidine is approved for high-risk MDS, chronic myelomonocytic leukaemia (CMML) and acute myeloid leukaemia (AML) with less than 30% blasts.2 Treatment with azacitidine has shown reduced transfusion requirement, improved leukaemia-free and overall survival.2 3 However, many elderly patients may find it difficult to attend day case 7 days a month until progression and further additional attendances for blood tests, clinics and transfusions. We recognised that the requirement for patients to make multiple hospital visits for chemotherapy treatment was having an increasingly negative impact on their quality of life and that of their relatives/carers. This also resulted in patients declining accessible treatment for their disease. Community chemotherapy service was set up with a view to improve the outcome and quality of care by taking treatment closer to home. National Health Service white paper in 2010 focused on extending choice for patients and moving cancer services away from major cancer centres when feasible. Key driver for community chemotherapy is improved patient choice and experience.4 5 In this article, we explain our community chemotherapy initiative project and our experiences so far. ### Aim The initial aim of the service was to reduce the number of visits required by patients to hospital, giving greater choice in the delivery of their treatment and therefore reducing the impact of their disease on their daily lives. The service was also aimed to increase efficiency in the delivery of chemotherapy by the Trust. These continued to be the overarching aims of the service to ultimately improve the experience of our patients and efficiency of the service. ### Project details All suitable patients who are under the care of a Heart of England Foundation Trust (HEFT) haematology consultants receiving treatment with subcutaneous chemotherapy within the Birmingham …
Drought Forecasting: Application of Ensemble and Advanced Machine Learning Approaches

Depending on the severity and spatial-temporal variability, droughts can have a wide range of impacts such as crop failure, water shortages, and food insecurity. Accurate and timely forecasting is necessary to mitigate the hazards of extreme weather events, such as droughts, brought on by climate change. A district like Chitradurga in India, which typically receives around 450–600 mm of annual rainfall, will require advanced drought mitigation strategies and plans before the onset of the drought. This research focuses on 1-step lead time forecasting of meteorological drought episodes making use of the 6-month Standardised Precipitation Index (SPI-6) as indicator. The fine resolution rainfall data (0.25 $^{\circ }\,\,\times0.25^{\circ }$ ) obtained from the Indian Meteorological Department was used to derive the 6-month SPI data of 23 grid stations. The 1-step lead time SPI-6 time series was forecast considering the antecedent SPI-6 time series data as model input. The Mutual Information was used to determine the most relevant input features for drought forecasting. The standard Artificial Neural Network, an advanced machine learning framework - Multivariate Adaptive Regression Splines, and the ensemble learning-based CatBoost Regression and Gradient Tree Boosting paradigms were employed to forecast drought episodes. Error and efficiency metrics were employed for performance evaluation of the simulated models. The multivariate adaptive regression splines and gradient tree boosting forecasts had slightly higher accuracy and lower error rates than the artificial neural network model, which suggests that they may be more reliable for drought forecasting. The root mean square error and normalized Nash-Sutcliffe efficiency ranges of the multivariate adaptive regression splines model (during test phase) were 0.37–0.54 and 0.78–0.87, respectively. The thematic maps that were created using spatial interpolation of model forecasts from all the stations also confirmed that the district as a whole experienced drought in April 2019.
Investigation and Comparison of Iteration Curves of Optimization Algorithms

The iteration history curve of optimization algorithms is a saturation- type development curve or sigmoid shape curve. After an overview of several different sigmoid curves, the iteration history curve of the RVA (Random Virus Algorithm) is analysed in order to find its best settings for a given optimization problem. The analysis of the characteristics and numerical parameters of the iteration history curve provides the possibility to discover the speed and efficiency of the algorithm without the necessity to wait throughout the whole running until its final result, which can speed up numerical experiments during the search for the solution to the optimization problem and while ‘fine tuning’ the algorithm to the given task. Since sigmoid-type curves can be found in many different fields of life (the history of the sport world records, comparison of the achievements of several groups), the results of this analysis can be used in several different domains of life, when the ranking, comparison, evaluation or qualification of several individuals or groups is important.
The effects of dexamethasone and erythropoietin on mice sciatic nerve crush injury: histopathologic and functional outcomes

Peripheral neuropathies are one of the major causes of motor and sensory disability. The multitude of nerve injuries and associated comorbidities provides a strong impetus to find a drug that potentiate or accelerate axonal regeneration. Systemic drug delivery has been a promising strategy in this regard. This study aimed to evaluate dexamethasone and erythropoietin effects on sciatic nerve regeneration. Twenty-three mice were randomly assigned to sham, control, dexamethasone, erythropoietin, and dexamethasone + erythropoietin groups. The left sciatic nerve was crushed using mosquito hemostatic forceps. Medications were administered once daily for 28 days. The sham group received neither crush injury nor medication. Histopathologic and walking track analyses were performed. Medical therapy influence on functional recovery was observed in as soon as 14 days. Although functional recovery was superior in the dexamethasone + erythropoietin group, a complete return to near-normal function was seen after 28 days in all of the groups. Dexamethasone yielded superior SFI values compared to the erythropoietin on day 14, although this was not statistically significant (p = 0.534). Histopathologically, recovery of average axonal number up to 75% normal nerve and significant decline of axonal swelling was observed in the erythropoietin and dexamethasone + erythropoietin groups, which were statistically significant compared to the dexamethasone group (p = 0.008). Marked immunoreactivity to Glial fibrillary acidic protein (GFAP) was present in the dexamethasone group. Furthermore, immunoreactivity to S-100 protein was observed in regenerated nerves in all groups. Present data provide insights into the neurotrophic effects of dexamethasone and erythropoietin on sciatic crush; however, further investigation is required to justify the clinical application of these agents.
Hey, You! The Importance of Pragmatics in Localizations of Mass Effect in French and Spanish

The localization of video game dialog for diverse audiences is challenging because of differences in linguistic features between languages and pragmatic norms between cultures. For example, localizers must decide how to translate the English second-person singular pronoun “you” into languages that have a pragmatic distinction between formal and informal pronouns (e.g., “vous” and “tu” in French). These distinctions are used in social interaction to signal politeness, respect, and social distance, which are important elements that shape player experience in role-playing games. We analyze the dialog from French and Spanish localizations of Mass Effect and show they have strikingly different strategies for translating pronouns. French mostly uses formal pronouns while Spanish mostly uses informal pronouns. We explain how these differences affect player experience and argue that effective localization requires a clear strategy for dealing with pragmatics. We conclude by making practical suggestions for how game creators can better support localization.
Green sukuk in Saudi Arabia: Challenges and potentials of sustainability in the light of Saudi Vision 2030

This research aimed to provide insights into the green sukuk in Saudi Arabia regarding its challenges and potential of sustainability in the light of Saudi Vision 2030 for financing green projects. Moreover, it examines the current framework adopted by the Saudi Electricity Company (SEC) for facilitating transition to a low–carbon economy and circular economy, empowering communities, and enabling responsible business practices. Due to the nature of the topic, the research followed the descriptive research design. The results indicated that the issuance of green sukuk faces some challenges including lack of a clear definition, lack of awareness of its benefits, absence of a standard for measuring it, lack of institutional capacity, and the long time required to structure and legalize it. Consequently, a clear definition and measurement standard should be presented. Furthermore, the results of this research have implications for researchers, governments, policymakers, industries, businesses, investors and regulators regarding the development and raising of green sukuk.
Twenty years of emotional-behavioral problems of community adolescents living in Italy measured through the Achenbach system of empirically based assessment (ASEBA): a systematic review and meta-analysis

Background This is a systematic review and meta-analysis of emotional and behavioral problems among Italian community adolescents in the last 20 years, as assessed through the ASEBA questionnaires CBCL 6–18, YSR 11–18 and TRF 6–18. Research questions address: (1) pooled means of problems’ scores in questionnaires scales; (2–3) variations in scores according to sociodemographic and time-related factors, and studies’ quality; (4) trends in research with ASEBA instruments along with other outcomes, e.g., psychopathological symptoms. Methods A systematic literature review of Scopus, EBSCO, PubMed, Web of Science, and ProQuest databases using the PRISMA 2020 guidelines was conducted on November, 2021, and of grey literature on December, 2021. The quality of studies was assessed through the Newcastle-Ottawa Scale. Results Forty-four studies were eligible for the systematic review, of which 34 were included for meta-analysis. Results showed that: (1) emotional-behavioral problems were higher when assessed by the CBCL and lower when assessed by the YSR compared to normative data; (2) there were no gender and age differences, except for higher scores of Anxious/Depression symptoms, in girls. (3) internalizing and attention problems increased over the last two decades. (4) major trends of Italian research investigate adolescents’ emotional behavioral problems concerning attachment, comorbid symptoms, especially internet addictions, and eating disorders. Discussion Despite some limitations (e.g., low-medium quality of most studies, no data on the TRF, under-representation of some geographical areas, some search-related choices), these data provides Italian practitioners and international researchers of some parameter to evaluate Italian adolescents emotional-behavioral problems. Registered on PROSPERO N. CRD42022299999.
Understanding the influence of “hot” models in climate impact studies: a hydrological perspective

Abstract. Efficient adaptation strategies to climate change require the estimation of future impacts and the uncertainty surrounding this estimation. Over- or underestimating future uncertainty may lead to maladaptation. Hydrological impact studies typically use a top-down approach in which multiple climate models are used to assess the uncertainty related to the climate model structure and climate sensitivity. Despite ongoing debate, impact modelers have typically embraced the concept of “model democracy”, in which each climate model is considered equally fit. The newer Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations, with several models showing a climate sensitivity larger than that of Phase 5 (CMIP5) and larger than the likely range based on past climate information and understanding of planetary physics, have reignited the model democracy debate. Some have suggested that “hot” models be removed from impact studies to avoid skewing impact results toward unlikely futures. Indeed, the inclusion of these models in impact studies carries a significant risk of overestimating the impact of climate change. This large-sample study looks at the impact of removing hot models on the projections of future streamflow over 3107 North American catchments. More precisely, the variability in future projections of mean, high, and low flows is evaluated using an ensemble of 19 CMIP6 general circulation models (GCMs), 5 of which are deemed hot based on their global equilibrium climate sensitivity (ECS). The results show that the reduced ensemble of 14 climate models provides streamflow projections with reduced future variability for Canada, Alaska, the Southeast US, and along the Pacific coast. Elsewhere, the reduced ensemble has either no impact or results in increased variability in future streamflow, indicating that global outlier climate models do not necessarily provide regional outlier projections of future impacts. These results emphasize the delicate nature of climate model selection, especially based on global fitness metrics that may not be appropriate for local and regional assessments.
The Manufacturing Conditions for the Direct and Reproducible Formation of Electrospun PCL/Gelatine 3D Structures for Tissue Regeneration

Electrospinning is a versatile technique for fabricating nanofibrous scaffolds for tissue engineering applications. However, the direct formation of 3D sponges through electrospinning has previously not been reproducible. We used a Taguchi experimental design approach to optimise the electrospinning parameters for forming PCL and PCL/gelatine 3D sponges. The following parameters were investigated to improve sponge formation: solution concentration, humidity, and solution conductivity. Pure PCL sponges were achievable. However, a much fluffier sponge formed by increasing the solution conductivity with gelatine. The optimal conditions for sponge formation 24 w/v% 80:20 PCL:gelatine on aluminium foil at ≥70% humidity, 15 cm, 22 kV and 1500 µL/h. The resulting sponge had a highly porous structure with a fibre diameter of ~1 µm. They also supported significantly higher cell viability than 2D electrospun mats, dropcast films of the same material and even the TCP positive control. Our study demonstrates that the direct formation of PCL/gelatine 3D sponges through electrospinning is feasible and promising for tissue engineering applications. The sponges have a highly porous structure and support cell viability, which are essential properties for tissue engineering scaffolds. Further studies are needed to optimise the manufacturing process and evaluate the sponges’ long-term performance in vivo.
3D RECONSTRUCTION FROM MULTI-VIEW GOOGLE EARTH SATELLITE STEREO IMAGES BY GENERATING VIRTUAL RPC BASED ON 3D HOMOGRAPHY-BASED GEOREFERENCING

Abstract. In this paper, we propose a method for performing 3D reconstruction by generating virtual RPC parameters from multi-view satellite stereo images provided by Google Earth (GE) software. In the multi-view stereo (MVS) image in a general case, after the pose and parameters of the camera are estimated, a dense 3D surface can be reconstructed. However, in the case of satellite images, it is not easy to obtain the original images with pose parameters of an area of interest. In the case of GE software, which can obtain images across the globe, the images provided are georeferenced and modified to fit the ground control point (GCP), so there is no camera model to explain the projection relationship. Therefore, the purpose of the proposed method is to perform 3D reconstruction by generating virtual camera parameters in modified satellite images obtained from GE software. In the proposed method, satellite images obtained from GE are estimated to be pinhole images using structure from motion (SfM) for initial reconstruction. After initial reconstruction, the 3D model is transformed from a distorted hexahedral space formed along a pixel ray to a UTM coordinate system metric space through a 3D homography-based georeferencing. A virtual rational polynomial camera (RPC) parameter is calculated through the satellite images and the 3D interspace correspondence point of UTM coordinates. The result is generated by virtual RPC and the MVS method using the RPC model. The reconstructed DSM using virtual RPC is improved over the initial reconstruction of the proposed process, and error measurement in the area with GT obtained significant results with an average of 1.366m on an MAE method.