Miracle-dz/UniFAR-FTUs huggingface dataset:
miRNA and mRNA Expression Profiles Associated with Lymph Node Metastasis and Prognosis in Penile Carcinoma

Penile cancer (PeC) is a rare disease, and no prognostic biomarkers have been adopted in clinical practice yet. The objective of the present study was to identify differentially expressed miRNAs (DEmiRs) and genes (DEGs) as potential biomarkers for lymph node metastasis and other prognostic factors in PeC. Tumor samples were prospectively obtained from 24 patients with squamous cell carcinoma of the penis. miRNA microarray analysis was performed comparing tumors from patients with inguinal lymph node metastatic and localized disease, and the results were validated by qRT-PCR. Eighty-three gene expression levels were also compared between groups through qRT-PCR. Moreover, DEmiRs and DEGs expression levels were correlated with clinicopathological variables, cancer-specific (CSS), and overall survival (OS). TAC software, TM4 MeV 4.9 software, SPSS v.25. 0, and R software v.4. 0.2 were used for statistical analyses. We identified 21 DEmiRs in microarray analysis, and seven were selected for validation. miR-744-5p and miR-421 were overexpressed in tissue samples of metastatic patients, and high expression of miR-421 was also associated with lower OS. We found seven DEGs (CCND1, EGFR, ENTPD5, HOXA10, IGF1R, MYC, and SNAI2) related to metastatic disease. A significant association was found between increased MMP1 expression and tumor size, grade, pathological T stage, and perineural invasion. Other genes were also associated with clinicopathological variables, CSS and OS. Finally, we found changes in mRNA–miRNA regulation that contribute to understanding the mechanisms involved in tumor progression. Therefore, we identified miRNA and mRNA expression profiles as potential biomarkers associated with lymph node metastasis and prognosis in PeC, in addition to disruption in mRNA–miRNA regulation during disease progression.
Use and Perceptions of Electronic Cigarettes among Young Chinese Generation: Expanding the Theory of Planned Behaviour

The Theory of Planned Behaviour (TPB) is recognized as powerful predictive model to explain consumer purchase behaviour. However, there have been relatively few studies that determine the role of TPB’s constructs in e-cigarettes decision-making process. Moreover, the TPB ignores the impulsive motivation (i.e., hedonism) and unconscious motivation (i.e., habit) and perceived knowledge in the literature. This study adopted a quantitative method based on a survey with 293 young respondents using e-cigarettes. The proposed hypotheses were empirically tested with SPPS and AMOS. This study revealed that perceived knowledge positively influenced attitude, subjective norm (SN), and perceived behavioural control (PBC) respectively. The results showed a positive relationship between attitude, SN, PBC and intention, and intention positively influenced actual e-cigarettes use behaviour. The results also demonstrated how consumers’ hedonic motivation and habit influence intention. Lastly, the theoretical and practical implications and limitations were discussed.
A képlékenység termodinamikája

Ebben az irasban a keplekeny es a reologiai, (hibas szohasznalattal viszkoelasztoplasztikus) anyagmodellek kapcsolatat targyaljuk a nemegyensulyi termodinamika alapjan. Annak erdekeben, hogy mondanivalonk konnyebben erthető es attekinthetőbb legyen roviden osszefoglaljuk a legfontosabb fogalmakat a klasszikus rugalmassagtanbol, illetve a klasszikus es a hagyomanyos termodinamikai hatterű keplekenysegtanbol. A termodinamikai keplekenyseget teljesen a nemegyensulyi termodinamika fogalomrendszeren belul targyaljuk, elterően a szokott, a mechanikaban kialakult fogalmakra alapozott targyalastol. A nemegyensulyi termodinamika a keplekeny alakvaltozasokkal jaro folyamatok időbeli lefolyasanak leirasat teszi lehetőve. A keplekeny es a rugalmas deformacio időbeli valtozasa kuszasi es feszultsegrelaxacios jelensegekkel egyutt leirhato. Homogen testek peldajan—kozonseges diferencialegyenletek megoldasaval—mutatjuk meg a disszipativ hatasok numerikus regularizalo hatasat.
Differentiating Cannabis Products: Drugs, Food, and Supplements

“Hemp” refers to non-intoxicating, low delta-9 tetrahydrocannabinol (Δ9-THC) cultivars of Cannabis sativa L. “Marijuana” refers to cultivars with high levels of Δ9-THC, the primary psychoactive cannabinoid found in the plant and a federally controlled substance used for both recreational and therapeutic purposes. Although marijuana and hemp belong to the same genus and species, they differ in terms of chemical and genetic composition, production practices, product uses, and regulatory status. Hemp seed and hemp seed oil have been shown to have valuable nutritional capacity. Cannabidiol (CBD), a non-intoxicating phytocannabinoid with a wide therapeutic index and acceptable side effect profile, has demonstrated high medicinal potential in some conditions. Several countries and states have facilitated the use of THC-dominant medical cannabis for certain conditions, while other countries continue to ban all forms of cannabis regardless of cannabinoid profile or low psychoactive potential. Today, differentiating between hemp and marijuana in the laboratory is no longer a difficult process. Certain thin layer chromatography (TLC) methods can rapidly screen for cannabinoids, and several gas and liquid chromatography techniques have been developed for precise quantification of phytocannabinoids in plant extracts and biological samples. Geographic regulations and testing guidelines for cannabis continue to evolve. As they are improved and clarified, we can better employ the appropriate applications of this uniquely versatile plant from an informed scientific perspective.
The Critical Need for a Meaning-Centered Team-Level Intervention to Address Healthcare Provider Distress Now

COVID-19 has unveiled and amplified the burnout, grief, and other forms of distress among healthcare providers (HCPs) that long preceded the pandemic. The suffering of the healthcare workforce cannot be simply and sufficiently addressed with a single psychotherapeutic intervention. Nevertheless, the National Academies of Sciences, Engineering, and Medicine Studies recommended prioritizing interventions that generate an increased sense of meaning in life and in work to reduce burnout and cultivate clinician wellbeing. Despite their guidance, there is a dearth of interventions for HCPs specifically targeting meaning and purpose as an avenue to reduce HCP distress. In a time when such an intervention has never been more essential, Meaning-Centered Pyschotherapy (MCP), a brief, evidence-based intervention designed for patients with advanced cancer may be key. This piece describes the principles underlying MCP and how it might be adapted and applied to ameliorate burnout among HCPs while providing a rationale to support future empirical studies in this area. Importantly, the systemic factors that contribute to the emotional and mental health burdens of HCPs are discussed, emphasizing the need for systems-level changes that are needed to leverage the potential outcomes of MCP for HCPs.
DEEP2: Deep Learning Powered De-scattering with Excitation Patterning

Limited throughput is a key challenge in in-vivo deep-tissue imaging using nonlinear optical microscopy. Point scanning multiphoton microscopy, the current gold standard, is slow especially compared to the wide-field imaging modalities used for optically cleared or thin specimens. We recently introduced 'De-scattering with Excitation Patterning or DEEP', as a widefield alternative to point-scanning geometries. Using patterned multiphoton excitation, DEEP encodes spatial information inside tissue before scattering. However, to de-scatter at typical depths, hundreds of such patterned excitations are needed. In this work, we present DEEP$^2$, a deep learning based model, that can de-scatter images from just tens of patterned excitations instead of hundreds. Consequently, we improve DEEP's throughput by almost an order of magnitude. We demonstrate our method in multiple numerical and physical experiments including in-vivo cortical vasculature imaging up to four scattering lengths deep, in alive mice.
The continuing decline of science and mathematics enrolments in Australian high schools

Is there a crisis in Australian science and mathematics education? Declining enrolments in upper secondary Science and Mathematics courses have gained much attention from the media, politicians and high-profile scientists over the last few years, yet there is no consensus amongst stakeholders about either the nature or the magnitude of the changes. We have collected raw enrolment data from the education departments of each of the Australian states and territories from 1992 to 2012 and analysed the trends for Biology, Chemistry, Physics, two composite subject groups (Earth Sciences and Multidisciplinary Sciences), as well as entry, intermediate and advanced Mathematics. The results of these analyses are discussed in terms of participation rates, raw enrolments and gender balance. We have found that the total number of students in Year 12 increased by around 16% from 1992 to 2012 while the participation rates for most Science and Mathematics subjects, as a proportion of the total Year 12 cohort, fell (Biology (-10%), Chemistry (-5%), Physics (-7%), Multidisciplinary Science (-5%), intermediate Mathematics (-11%), advanced Mathematics (-7%) in the same period. There were increased participation rates in Earth Sciences (+0.3%) and entry Mathematics (+11%). In each case the greatest rates of change occurred prior to 2001 and have been slower and steadier since. We propose that the broadening of curriculum offerings, further driven by students' self-perception of ability and perceptions of subject difficulty and usefulness, are the most likely cause of the changes in participation. While these continuing declines may not amount to a crisis, there is undoubtedly serious cause for concern.
Using Artificial Intelligence to Enhance Ongoing Psychological Interventions for Emotional Problems in Real- or Close to Real-Time: A Systematic Review

Emotional disorders are the most common mental disorders globally. Psychological treatments have been found to be useful for a significant number of cases, but up to 40% of patients do not respond to psychotherapy as expected. Artificial intelligence (AI) methods might enhance psychotherapy by providing therapists and patients with real- or close to real-time recommendations according to the patient’s response to treatment. The goal of this investigation is to systematically review the evidence on the use of AI-based methods to enhance outcomes in psychological interventions in real-time or close to real-time. The search included studies indexed in the electronic databases Scopus, Pubmed, Web of Science, and Cochrane Library. The terms used for the electronic search included variations of the words “psychotherapy”, “artificial intelligence”, and “emotional disorders”. From the 85 full texts assessed, only 10 studies met our eligibility criteria. In these, the most frequently used AI technique was conversational AI agents, which are chatbots based on software that can be accessed online with a computer or a smartphone. Overall, the reviewed investigations indicated significant positive consequences of using AI to enhance psychotherapy and reduce clinical symptomatology. Additionally, most studies reported high satisfaction, engagement, and retention rates when implementing AI to enhance psychotherapy in real- or close to real-time. Despite the potential of AI to make interventions more flexible and tailored to patients’ needs, more methodologically robust studies are needed.
Role of Brassinosteroids in plants responses to salinity stress: A review

Brassinosteroid emerges as an essential phytohormone that helps the plant to maintain plant growth and development. It also helps the plants grow well under adverse conditions along with normal conditions. In this review article, we have discussed the functional role of brassinosteroid (BRS) in plants under salinity stress conditions. Salinity stress is one of the most devastating abiotic stresses which adversely affect plant growth by disturbing their metabolic pathway. This article also comprises the occurrence, structure and signalling pathway of the brassinosteroid. Application of brassinosteroid improves the plant status under salinity by enhancing the antioxidant enzyme activity in plants. Moreover, we also reported the different growth parameters enhanced by brassinosteroid application in plants under salinity. BRSs also maintain plant growth through the regulation of expression of various genes whose products are involved in various biochemical and physiological processes. This review is based on the various aspects in much detail which are required to understand the proper mechanism of BRS, such as i) the role of BRS signaling pathways in providing tolerance to the plants, ii) changes due to the presence or absence of BRS in plants under stress conditions, iii) BRSs application on the regulation of different genes and transcriptional factor, iv) regulation in ion homeostasis, v) reduction of oxidative stress via different mechanisms under salinity stress. However, a lot of knowledge is required to understand the role of BRS in alleviating salinity stress and needs future research work on BRS with its different derivatives in the alleviation of salt stress.
Highly Aligned Ni-Decorated GO–CNT Nanostructures in Epoxy with Enhanced Thermal and Electrical Properties

In this study, graphene oxide–carbon nanotubes nanostructures decorated with nickel nanoparticles (NiGNT) were prepared through the molecular-level-mixing method, followed by a reduction process, and then applied as reinforcements to enhance the epoxy resin matrix. The ferromagnetism of the Ni nanoparticles allowed NiGNT nanostructures to be vertically aligned within the composite with the assistance of a magnetic field. Due to the alignment distribution of the NiGNT, the composites demonstrated enhanced anisotropic thermal and electrical conduction performances, compared with pure epoxy and randomly distributed composites. The aligned distribution of NiGNT–epoxy composites displayed 2.7 times higher thermal conductivity and around 104 times better electrical conduction performance, compared with pure epoxy. The thermal expansion of NiGNT–epoxy composite was also restricted in the aligned direction of NiGNT nanostructures. Thus, NiGNT–epoxy composites show great potential as future aerospace, aviation, and automobile materials.
The Androgen Receptor and Its Crosstalk With the Src Kinase During Castrate-Resistant Prostate Cancer Progression

While the androgen receptor (AR) signalling is the mainstay therapeutic target for metastatic prostate cancers, these tumours will inevitably develop therapy resistance to AR pathway inhibitors suggesting that prostate tumour cells possess the capability to develop mechanisms to bypass their dependency on androgens and/or AR to survive and progress. In many studies, protein kinases such as Src are reported to promote prostate tumour progression. Specifically, the pro-oncogene tyrosine Src kinase regulates prostate cancer cell proliferation, adhesion, invasion, and metastasis. Not only can Src be activated under androgen depletion, low androgen, and supraphysiological androgen conditions, but also through crosstalk with other oncogenic pathways. Reciprocal activations between Src and AR proteins had also been reported. These findings rationalize Src inhibitors to be used to treat castrate-resistant prostate tumours. Although several Src inhibitors had advanced to clinical trials, the failure to observe patient benefits from these studies suggests that further evaluation of the roles of Src in prostate tumours is required. Here, we summarize the interplay between Src and AR signalling during castrate-resistant prostate cancer progression to provide insights on possible approaches to treat prostate cancer patients.
Meteorological Influence of Mineral Dust Distribution Over South-Western Africa Deserts Using Reanalysis and Satellite Data

This study investigated the meteorological influence of mineral dust in the south-western African region using satellite and reanalysis datasets by studying 1) the seasonal transport and distribution of mineral dust in the region; 2) the relationship between precipitation, wind and desert dust, and 3) the long-term trends of dust column density, precipitation rate and surface wind speed. The results show that the Namib desert is the main source of dust in the region, with the density and distribution varying by seasons. The study found that the greatest dust distribution occurs in the June-July-August (JJA) season, attributed to the southwesterly winds which transport the dust into the interior of the region. Moreover, small dust aerosols less that 20 µm are observed at highest altitudes between 7 and 10.28 km. Favourable meteorological such as strong and fast winds and low precipitation, and low vegetation played a vital role in the production and distribution of dust aerosols. Over a long time (i.e., from 1990 to 2020), dust column density trend increased, while precipitation and surface wind speed trends decreased. This study provides significant basis for assessing and monitoring of the desertification processes and their effect on regional climate variability and change in Southwest Africa, where data is ground-based data is scarce and related efforts are rare.
Cover Crop Effects on Near-Surface Soil Aggregate Stability in the Southern Mississippi Valley Loess (MLRA 134)

The use of cover crops (CC) during the agricultural fallow period has been shown to help alleviate soil compaction and provide stabilizing effects against soil erosion. These benefits are particularly important as many of the silty, loess-derived soils of the major land resource area (MLRA) 134, the Southern Mississippi Valley Loess, have large erosion potentials. This study evaluated the effects of CC and no-cover crop (NCC) treatments on a selection of silt-loam soils in MLRA 134. Treatments were implemented during Fall 2018 and Fall 2019 and consisted of a range of CC species. Soil samples from the top 10 cm were collected to evaluate a suite of soil properties. Soil texture, pH, soil organic matter, and Mehlich-3 extractable Mg, Na, and Ca were unaffected (P > 0.05) by CC treatment. Total water-stable aggregate concentration was unaffected (P > 0.05) by CC treatment and soil depth (i.e., 0 - 5 and 5 - 10 cm). Soil bulk density was greater (P < 0.05) under NCC (1.27 g·cm −3 ) than under CC treatment (1.24 g·cm −3 ). Water-stable aggregate concentration was unaffected (P > 0.05) by CC treatment and soil depth, but was 21.5 times greater (P < 0.05) in the 0 - 0.25-mm (1.14 g·g −1 ) than in the > 4-mm (0.05 g·g −1 ) size class. Study results indicate that, even among sites with large variability, CC can have consistent, short-term, positive effects on soil properties, but a long-term commitment to continuous, annual cover crops is necessary for the full realization of potential benefits.
Path Counting for Grid-Based Navigation

Counting the number of shortest paths on a grid is a simple procedure with close ties to Pascal’s triangle. We show how path counting can be used to select relatively direct grid paths for AI-related applications involving navigation through spatial environments. Typical implementations of Dijkstra’s algorithm and A* prioritize grid moves in an arbitrary manner, producing paths which stray conspicuously far from line-of-sight trajectories. We find that by counting the number of paths which traverse each vertex, then selecting the vertices with the highest counts, one obtains a path that is reasonably direct in practice and can be improved by refining the grid resolution. Central Dijkstra and Central A* are introduced as the basic methods for computing these central grid paths. Theoretical analysis reveals that the proposed grid-based navigation approach is related to an existing grid-based visibility approach, and establishes that central grid paths converge on clear sightlines as the grid spacing approaches zero. A more general property, that central paths converge on direct paths, is formulated as a conjecture.
Estimation of mechanical power and energy cost in elite wheelchair racing by analytical procedures and numerical simulations

Abstract The aim was to compare the mechanical power and energy cost of an elite wheelchair sprinter in the key-moments of the stroke cycle. The wheelchair-athlete system was 3D scanned and then computational fluid dynamics was used to estimate the drag force. Mechanical power and energy cost were derived from a set of formulae. The effective area in the catch, release and recovery phases were 0.41 m2, 0.33 m2 and 0.24 m2, respectively. Drag increased with speed and varied across the key-moments. The catch required the highest total power (range: 62.76–423.46 W), followed-up by the release (61.50–407.85 W) and the recovery (60.09–363.89 W).
The effect of low dose teophillyne on the improvement of copd assessment test score, interleukin-8 level and sputum neutrophil count in patients with stable COPD

Background: Harmful particles from cigarette smoke induces an inflammatory immune response in the lungs, followed by the release of proinflammatory cytokines such as TNF-α and IL-8 and damages histone deacetylase 2 (HDAC2) in the cell core leading to glucocorticoid resistance in COPD. Low dose Theophylline of below 10mg/L has an anti-inflammatory effect by activating HDAC. This study aimed to analyze the effect of low dose theophylline on the clinical improvement of stable COPD patients assessed by the COPD Assessment Test (CAT) score, IL-8 level, and sputum neutrophil count.Methods: We conducted a quasi-experimental clinical study using a pre-post test in stable COPD patients visiting the Pulmonary Outpatient Clinic of DR. Moewardi hospital Surakarta, between July and September 2016. The samples were taken using a consecutive sampling technique, assigned into two groups, treatment, receiving standard therapy plus 70 mg low dose theophylline per 8 hours, and control receiving standard therapy only. CAT score, IL-8 level, and sputum neutrophil count were measured at baseline and four weeks after treatment.Results: The treatment group's CAT score decreased by 3.67±3.58 pg/ml and increased by 2.40±3.38 pg/ml in the control group (p=0.003). IL-8 level decreased by 4.31±13.06 pg/ml in the treatment group and increased by 0.88±13.89 pg/ml in the control group (p=0.116). The sputum neutrophil count decreased in both treatment and control groups by 4.00 ±40.33 pg/ml and 2. 87±39. 91 pg/ml (p=0.939). Conclusion: Statistically low dose theophylline significantly lowers the CAT score of stable COPD patients. It also decreases IL-8 level and sputum neutrophil count, although it is not significant.