Miracle-dz/UniFAR-FTUs huggingface dataset:
Electrical properties and Mott parameters of polycrystalline diamond films synthesized by HF CVD method from hydrogen/methanol gas mixture

Abstract The influence of diamond crystallinity and preferred orientation on electronic conductivity of synthetic diamond films grown by hot filament chemical vapor deposition (HFCVD) was investigated. The CVD diamond films of different morphologies and crystallite sizes varying from 36 nm to 67 nm, measured in h2 2 0i direction were considered. The charge transport mechanism in the diamond samples was studied using temperature dependent DC conductivity measurements. The obtained results showed that in the temperature range of 90 K to 300 K charge transport is realized via Variable Range Hopping (VRH, m = 1/4) mechanism. Using VRH model, the Mott parameters were evaluated i.e. density of states at Fermi level N(EF) (0.22 × 1015 eV-1·cm-3 to 1.7 × 1015 eV-1·cm-3), hopping energy W (43.5 meV to 142.3 meV) and average hopping distance R (1.49 × 10-5cm to 2.56 × 10-5cm). It was shown that above mentioned parameters strongly depend on diamond film preferential orientation.
Individual-level specialisation and interspecific resource partitioning in bees revealed by pollen DNA metabarcoding

It is increasingly recognised that intraspecific variation in traits, such as morphology, behaviour, or diet is both ubiquitous and ecologically important. While many species of predators and herbivores are known to display high levels of between-individual diet variation, there is a lack of studies on pollinators. It is important to fill in this gap because individual-level specialisation of flower-visiting insects is expected to affect their efficiency as pollinators with consequences for plant reproduction. Accordingly, the aim of our study was to quantify the level of individual-level specialisation and foraging preferences, as well as interspecific resource partitioning, across different temporal scales in three co-occurring species of bees of the genus Ceratina (Hymenoptera: Apidae: Xylocopinae), C. chalybea, C. nigrolabiata, and C. cucurbitina. We conducted a field experiment where we provided artificial nesting opportunities for the bees and combined a short-term mark-recapture study with the dissection of the bees’ nests to obtain repeated samples from individual foraging females and complete pollen provisions from their nests. Hence, we could study variation of the composition of pollen collected by the bees at different temporal scales. We used DNA metabarcoding based on the ITS2 locus to identify the composition of the pollen samples. We found that the composition of pollen carried on the bodies of female bees and stored in the brood provisions in their nests significantly differed among the three co-occurring species. At the intraspecific level, individual females consistently differed in their level of specialisation and in the composition of pollen carried on their bodies and stored in their nests. Our study thus provides evidence of consistent individual-level specialisation in pollinators across multiple temporal scales. We also demonstrate that higher generalisation at the species level stemmed from larger among-individual variation in diets as observed in other types of consumers, such as predators. Our study thus reveals how specialisation and foraging preferences of bees change from the scale of individual foraging bouts to complete pollen provisions accumulated in their nests over their lifetime. Such multi-scale view of foraging behaviour is necessary to improve our understanding of the functioning of plant-flower visitor communities.
Alternative oxidase1a and 1d limit proline-dependent oxidative stress and aid salinity recovery in Arabidopsis

A link between Pro catabolism and mitochondrial reactive oxygen species production has been established across eukaryotes and in plants increases in leaf respiration rates have been reported following Pro exposure. Here we investigated how alternative oxidases (AOXs) of the mitochondrial electron transport chain accommodate the large, atypical flux resulting from Pro catabolism and limit oxidative stress during Pro breakdown in mature Arabidopsis leaves. Following Pro treatment, AOX1a and AOX1d accumulate at transcript and protein levels, with AOX1d approaching the level of the typically dominant AOX1a isoform. We therefore sought to determine the function of both AOX isoforms under Pro respiring conditions. Oxygen consumption rate measurements in aox1a and aox1d leaves suggested these AOXs can functionally compensate for each other to establish enhanced AOX catalytic capacity in response to Pro. Generation of aox1a.aox1d lines showed complete loss of AOX proteins and activity upon Pro treatment, yet full respiratory induction in response to Pro remained possible via the cytochrome pathway. However, aox1a.aox1d leaves suffered increased levels of oxidative stress and damage during Pro metabolism compared to WT or the single mutants. During recovery from salt stress, when high rates of Pro catabolism occur naturally, photosynthetic rates in aox1a.aox1d recovered slower than WT or the single aox lines, showing that both AOX1a and AOX1d are beneficial for cellular metabolism during Pro drawdown following osmotic stress. This work provides physiological evidence of a beneficial role for AOX1a but also the less studied AOX1d isoform in allowing safe catabolism of alternative respiratory substrates like Pro. One sentence summary The alternative oxidase of plant mitochondria contributes to Pro catabolism by preventing oxidative stress in the electron transport chain and this aids recovery of leaf metabolic rates following salinity stress.
Mixed Effects Machine Learning Models for Colon Cancer Metastasis Prediction using Spatially Localized Immuno-Oncology Markers

Spatially resolved characterization of the transcriptome and proteome promises to provide further clarity on cancer pathogenesis and etiology, which may inform future clinical practice through classifier development for clinical outcomes. However, batch effects may potentially obscure the ability of machine learning methods to derive complex associations within spatial omics data. Profiling thirty-five stage three colon cancer patients using the GeoMX Digital Spatial Profiler, we found that mixed-effects machine learning (MEML) methods† may provide utility for overcoming significant batch effects to communicate key and complex disease associations from spatial information. These results point to further exploration and application of MEML methods within the spatial omics algorithm development life cycle for clinical deployment.
Evolutionary conservation of maternal RNA localization in fishes and amphibians revealed by TOMO-Seq

Asymmetrical localization of biomolecules inside the egg, results in uneven cell division and establishment of many biological processes, cell types and the body plan. However, our knowledge about evolutionary conservation of localized mRNAs is still limited to a few candidates. Our goal was to compare localization profiles along the animal-vegetal axis of mature eggs from four models, Xenopus laevis, Danio rerio, Ambystoma mexicanum and Acipenser ruthenus using the spatial expression method called TOMO-Seq. We revealed that RNAs of many known important genes such as germ layer determinants, germ plasm factors and members of key signalling pathways, are localized in completely different profiles among the models. There was also a poor correlation between vegetally localized genes but a relatively good correlation between animally localized genes. These findings indicate that the regulation of embryonic development within the animal kingdom is highly diverse and cannot be deduced based on a single model.
Deep Transfer Learning of Drug Responses by Integrating Bulk and Single-cell RNA-seq data

Massively bulk RNA sequencing databases incorporating drug screening have opened up an avenue to inform the optimal clinical application of cancer drugs. Meanwhile, the growing single-cell RNA sequencing (scRNA-seq) data contributes to improving therapeutic effectiveness by studying the heterogeneity of drug responses for cancer cell subpopulations. There is a clear significance in developing computational biology approaches to predict and interpret cancer drug response in single cell data from clinical samples. Here, we introduce scDEAL, a deep transfer learning framework for cancer drug response prediction at single-cell level by integrating large-scale bulk cell line data. The true innovation of scDEAL is to translate cancer cell line drug responses into predicting clinical drug responses via learning relations of gene expressions and drug responses at bulk-level and transfer to predict drug responses in scRNA-seq. Another innovation is the integrated gradient feature interpretation to infer a comprehensive set of signature genes to reveal potential drug resistance mechanisms. We benchmarked scDEAL on six scRNA-seq datasets and indicate its model interpretability through these case studies. We believe that this work may help study cell reprogramming, drug selection, and repurposing for improving therapeutic efficacy.
Small molecule photocatalysis enables drug target identification via energy transfer

The identification of cellular targets that can be exploited for therapeutic benefit, broadly known as target ID, remains a fundamental goal in drug discovery. In recent years, the application of new chemical and biological technologies that accelerate target ID has become commonplace within drug discovery programs, as a complete understanding of how molecules react in a cellular environment can lead to increased binding selectivity, improved safety profiles, and clinical efficacy. Established approaches using photoaffinity labelling (PAL) are often costly and time-consuming due to poor signal-to-noise coupled with extensive probe optimization. Such challenges are exacerbated when dealing with low abundance membrane proteins or multiple protein target engagement, typically rendering target ID unfeasible. Herein, we describe a general platform for photocatalytic small molecule target ID, which hinges upon the generation of high-energy carbene intermediates via visible light-mediated Dexter energy transfer. By decoupling the reactive warhead from the drug, catalytic signal amplification results in multiple labelling events per drug, leading to unprecedented levels of target enrichment. Through the development of cell permeable photo-catalyst conjugates, this method has enabled the quantitative target and off target identification of several drugs including (+)-JQ1, paclitaxel, and dasatinib. Moreover, this methodology has led to the target ID of two GPCRs – ADORA2A and GPR40 – a class of drug target seldom successfully uncovered in small molecule PAL campaigns.
The Ethiopian developmental state and struggles over the reproduction of young migrant women’s labor at the Hawassa Industrial Park

ABSTRACT Tens of thousands of young Ethiopian women have migrated from small towns and rural areas to work in the Hawassa Industrial Park (HIP), where working conditions and wages are far below their expectations. Low wages and a high cost of living mean that workers face severe challenges in meeting their basic needs for food and shelter that are necessary for reproducing their own labor. Attention to struggles over the reproduction of migrant women’s labor at the HIP generates insights into the practices of the Ethiopian developmental state. The developmental state actively makes and reproduces cheap labor to attract international capital and support economic growth. The state protects international textile manufacturers from the burden of reproducing the labor that manufacturers rely on for profits. The case of the HIP is a necessary complement to recent scholarship on urban Africa that has focused overwhelmingly on the informal economy. The precarious nature of factory work leads some young women to search out stability with small scale, often informal, entrepreneurial work, a process that disrupts conventional narratives of economic development. The complex relationship between wage labor and self-employment suggests possibilities for pro-poor policies that go beyond reproducing labor for international manufacturers.
Drugs of Abuse Differentially Alter the Neuronal Excitability of Prefrontal Layer V Pyramidal Cell Subtypes

The medial prefrontal cortex (mPFC) plays an important role in regulating executive functions including reward seeking, task flexibility, and compulsivity. Studies in humans have demonstrated that drugs of abuse, including heroin, cocaine, methamphetamine, and alcohol, alter prefrontal function resulting in the consequential loss of inhibitory control and increased compulsive behaviors, including drug seeking. Within the mPFC, layer V pyramidal cells, which are delineated into two major subtypes (type I and type II, which project to subcortical or commissurally to other cortical regions, respectively), serve as the major output cells which integrate information from other cortical and subcortical regions and mediate executive control. Preclinical studies examining changes in cellular physiology in the mPFC in response to drugs of abuse, especially in regard to layer V pyramidal subtypes, are relatively sparse. In the present study, we aimed to explore how heroin, cocaine, methamphetamine, ethanol, and 3,4-methylenedioxypyrovalerone (MDPV) alter the baseline cellular physiology and excitability properties of layer V pyramidal cell subtypes. Specifically, animals were exposed to experimenter delivered [intraperitoneal (i.p.)] heroin, cocaine, the cocaine-like synthetic cathinone MDPV, methamphetamine, ethanol, or saline as a control once daily for five consecutive days. On the fifth day, whole-cell physiology recordings were conducted from type I and type II layer V pyramidal cells in the mPFC. Changes in cellular excitability, including rheobase (i.e., the amount of injected current required to elicit action potentials), changes in input/output curves, as well as spiking characteristics induced by each substance, were assessed. We found that heroin, cocaine, methamphetamine, and MDPV decreased the excitability of type II cells, whereas ethanol increased the excitability of type I pyramidal cells. Together, these results suggest that heroin, cocaine, MDPV, and methamphetamine reduce mPFC commissural output by reducing type II excitability, while ethanol increases the excitability of type I cells targeting subcortical structures. Thus, separate classes of abused drugs differentially affect layer V pyramidal subtypes in the mPFC, which may ultimately give rise to compulsivity and inappropriate synaptic plasticity underlying substance use disorders.
Depression, Anxiety, and Suicidal Ideation in Chinese University Students During the COVID-19 Pandemic

Coronavirus disease-2019 (COVID-19) pandemic has seriously threatened the global public health security and caused a series of mental health problem. Current research focuses mainly on mental health status and related factors in the COVID-19 pandemic among Chinese university students. Data from 11133 participants was obtained through an online survey. The Patient Health Question-9 (PHQ-9) was used to assess depressive symptoms, the Social Support Rate Scale (SSRS) was used to assess social support. We also used 7-item Generalized Anxiety Disorder Scale (GAD-7) to assess anxiety symptoms. Totally, 37.0% of the subjects were experiencing depressive symptoms, 24.9% anxiety symptoms, 20.9% comorbid depressive and anxiety symptoms, and 7.3% suicidal ideation. Multivariable logistic regression analysis revealed an increased presence of mental health problems in female students, graduate students, and those with personal COVID-19 exposure. Awareness of COVID-19, living with family were protective factors that reduced anxiety and depression symptoms. In addition, male, personal COVID-19 exposure, depressive and anxiety symptoms were risk factors for suicidal ideation. Social support, COVID-19 preventive and control measures, prediction of COVID-19 trends, living with family and graduate students are protective factors for reducing suicidal ideation.
Elucidation of Novel Molecular Targets for Therapeutic Strategies in Urothelial Carcinoma: A Literature Review

Urothelial carcinoma therapy is a rapidly evolving and expanding field. Traditional cytotoxic chemotherapy regimens have not produced optimal long-term outcomes, and many urothelial cancer patients have comorbidities that disqualify them as chemotherapy candidates. In recent years, a plethora of novel therapeutic agents that target diverse molecular pathways has emerged as alternative treatment modalities for not only metastatic urothelial carcinoma, but also for muscle-invasive bladder cancer and non-muscle invasive bladder cancer in adjuvant and definitive settings. This review paper aims to discuss the various categories of therapeutic agents for these different types of urothelial cancer, discussing immunotherapy, antibody-drug conjugates, kinase inhibitors, CAR-T cell therapy, peptide vaccination, and other drugs targeting pathways such as angiogenesis, DNA synthesis, mTOR/PI3K/AKT, and EGFR/HER-2.
Discovery of Quality Markers of Nucleobases, Nucleosides, Nucleotides and Amino Acids for Chrysanthemi Flos From Different Geographical Origins Using UPLC–MS/MS Combined With Multivariate Statistical Analysis

Nucleobases, nucleosides, nucleotides and amino acids, as crucial nutrient compositions, play essential roles in determining the flavor, function and quality of Chrysanthemi Flos. The quality of Chrysanthemi Flos from different geographical origins is uneven, but there have been no reports about the screening of their quality markers based on nutritional ingredients. Here, we developed a comprehensive strategy integrating ultra performance liquid chromatography coupled with triple-quadrupole linear ion-trap tandem mass spectrometry (UPLC–MS/MS) and multivariate statistical analysis to explore quality markers of Chrysanthemi Flos from different geographical origins and conduct quality evaluation and discrimination of them. Firstly, a fast, sensitive, and reliable UPLC–MS/MS method was established for simultaneous quantification 28 nucleobases, nucleosides, nucleotides and amino acids of Chrysanthemi Flos from nine different regions in China. The results demonstrated that Chrysanthemi Flos from nine different cultivation regions were rich in the above 28 nutritional contents and their contents were obvious different; however, correlation analysis showed that altitude was not the main factor for these differences, which required further investigation. Subsequently, eight crucial quality markers for nine different geographical origins of Chrysanthemi Flos, namely, 2′-deoxyadenosine, guanosine, adenosine 3′,5′-cyclic phosphate (cAMP), guanosine 3′,5′-cyclic monophosphate (cGMP), arginine, proline, glutamate and tryptophan, were screened for the first time using partial least squares discriminant analysis (PLS-DA) and the plot of variable importance for projection (VIP). Moreover, a hierarchical clustering analysis heat map was employed to intuitively clarify the distribution of eight quality markers in the nine different regions of Chrysanthemi Flos. Finally, based on the contents of selected eight quality markers, support vector machines (SVM) model was established to predict the geographical origins of Chrysanthemi Flos, which yielded excellent prediction performance with an average prediction accuracy of 100%. Taken together, the proposed strategy was suitable to discover the quality markers of Chrysanthemi Flos and could be used to discriminate its geographical origin.
The Ageing Brain: Investigating the Role of Age in Changes to the Human Cerebral Microvasculature With an in silico Model

Ageing causes extensive structural changes to the human cerebral microvasculature, which have a significant effect on capillary bed perfusion and oxygen transport. Current models of brain capillary networks in the literature focus on healthy adult brains and do not capture the effects of ageing, which is critical when studying neurodegenerative diseases. This study builds upon a statistically accurate model of the human cerebral microvasculature based on ex-vivo morphological data. This model is adapted for “healthy” ageing using in-vivo measurements from mice at three distinct age groups—young, middle-aged, and old. From this new model, blood and molecular exchange parameters are calculated such as permeability and surface-area-to-volume ratio, and compared across the three age groups. The ability to alter the model vessel-by-vessel is used to create a continuous gradient of ageing. It was found that surface-area-to-volume ratio reduced in old age by 6% and permeability by 24% from middle-age to old age, and variability within the networks also increased with age. The ageing gradient indicated a threshold in the ageing process around 75 years old, after which small changes have an amplified effect on blood flow properties. This gradient enables comparison of studies measuring cerebral properties at discrete points in time. The response of middle aged and old aged capillary beds to micro-emboli showed a lower robustness of the old age capillary bed to vessel occlusion. As the brain ages, there is thus increased vulnerability of the microvasculature—with a “tipping point” beyond which further remodeling of the microvasculature has exaggerated effects on the brain. When developing in-silico models of the brain, age is a very important consideration to accurately assess risk factors for cognitive decline and isolate early biomarkers of microvascular health.
A Brief Research Report on the Perception and Satisfaction of Italian University Students With Disabilities and Specific Learning Disabilities at the Emergency Remote Teaching During the COVID-19 Lockdown

Introduction: The COVID-19 pandemic has inevitably transformed face-to-face teaching to remote teaching (e-learning or blended) which has had psychological and social impacts on the mental health of university students. Object: In this study, we surveyed university students with disabilities and specific learning disabilities (SLDs) on their perceptions of and satisfaction with emergency remote teaching (ERT) during the lockdown phase (March–April 2020) and following restrictions due to the COVID-19 pandemic. We compared the responses of students with disabilities and SLDs with those of normotypical students. Methodology: A questionnaire was completed remotely: five items on the ERT were designed as ad hoc questions and five items were taken from the Short Form 12 Health Survey (SF-12) to evaluate physical and mental self-perceived health. There was a total of 163 students surveyed, 67 students with disabilities and/or SLDs and 96 normotypical students. Results and Conclusion: Students with disabilities and SLDs were more satisfied with remote teaching than the normotypical students. In fact, only 22% of the students with disabilities or SLDs indicated that they were dissatisfied with the teaching method used due to difficulties encountered, including those related to a weak technological infrastructure. We found that among all the students, important social and emotional aspects emerged as a consequence of the absence of interactions and relationships with both faculty and peer groups.