Miracle-dz/UniFAR-FTUs huggingface dataset:
MLN2238 exerts its anti-tumor effects via regulating ROS/JNK/mitochondrial signaling pathways in intrahepatic cholangiocarcinoma

Background: Intrahepatic Cholangiocarcinoma (iCCA) is a highly malignant tumor with limited treatment options that contributes largely to cancer-related deaths worldwide. Compared with traditional transcriptomic analysis, single-cell RNA sequencing (scRNA-seq) is emerging as a more advanced and popular tool for the in-depth exploration of cellular diversity and molecular complexity. As a next-generation proteasome inhibitor, MLN2238 presents better pharmacodynamics, pharmacokinetics, and therapeutic responses in various cancers. However, its effects and mechanisms of action in iCCA remain unknown. Methods: iCCA tumor heterogeneity was determined based on 4,239 qualified scRNA-seq data from 10 iCCA samples. The potential biological roles of proteasome-related genes in iCCA were investigated using a pseudo-trajectory reconstruction. The effect of MLN2238 on iCCA cell proliferation was estimated using the CCK-8, EdU, and clone formation assays. Flow cytometry was used to examine the effect of added MLN2238 on cell cycle and apoptosis levels. Autophagic flux was detected using AdPlus-mCherry-GFP-LC3B cells. ROS levels and mitochondrial membrane potential were determined using DCFH-DA probing and JC-1 staining. JNK activation and mitochondrial apoptosis were observed using western blotting and immunofluorescence microscopy, respectively. Finally, we used a tumor-bearing mouse model to validate its efficacy in vivo for iCCA treatment. Results: Proteasome-related genes were dysregulated in iCCA progression and expressed at higher levels in tumor tissues. MLN2238 suppressed cell proliferation, blocked the cell cycle in the G2/M phase, promoted apoptosis, and induced cytoprotective autophagy in iCCA cells. Furthermore, MLN2238 increased ROS levels and activated the JNK signaling pathway. Inhibition of ROS and JNK activation by NAC and SP600125 significantly reversed MLN2238-induced apoptosis. MLN2238 also suppressed the growth of iCCA tumors in vivo. Conclusion: Proteasome-related genes play pivotal roles in iCCA development. MLN2238, as a proteasome inhibitor, induces apoptosis in iCCA cells through ROS/JNK/mitochondrial signaling pathways, and hence, making MLN2238 a potential therapeutic choice for iCCA.
Sex-specific transcriptional rewiring in the brain of Alzheimer’s disease patients

Sex-specific differences may contribute to Alzheimer’s disease (AD) development. AD is more prevalent in women worldwide, and female sex has been suggested as a disease risk factor. Nevertheless, the molecular mechanisms underlying sex-biased differences in AD remain poorly characterized. To this end, we analyzed the transcriptional changes in the entorhinal cortex of symptomatic and asymptomatic AD patients stratified by sex. Co-expression network analysis implemented by SWItchMiner software identified sex-specific signatures of switch genes responsible for drastic transcriptional changes in the brain of AD and asymptomatic AD individuals. Pathway analysis of the switch genes revealed that morphine addiction, retrograde endocannabinoid signaling, and autophagy are associated with both females with AD (F-AD) and males with (M-AD). In contrast, nicotine addiction, cell adhesion molecules, oxytocin signaling, adipocytokine signaling, prolactin signaling, and alcoholism are uniquely associated with M-AD. Similarly, some of the unique pathways associated with F-AD switch genes are viral myocarditis, Hippo signaling pathway, endometrial cancer, insulin signaling, and PI3K-AKT signaling. Together these results reveal that there are many sex-specific pathways that may lead to AD. Approximately 20–30% of the elderly have an accumulation of amyloid beta in the brain, but show no cognitive deficit. Asymptomatic females (F-asymAD) and males (M-asymAD) both shared dysregulation of endocytosis. In contrast, pathways uniquely associated with F-asymAD switch genes are insulin secretion, progesterone-mediated oocyte maturation, axon guidance, renal cell carcinoma, and ErbB signaling pathway. Similarly, pathways uniquely associated with M-asymAD switch genes are fluid shear stress and atherosclerosis, FcγR mediated phagocytosis, and proteoglycans in cancer. These results reveal for the first time unique pathways associated with either disease progression or cognitive resilience in asymptomatic individuals. Additionally, we identified numerous sex-specific transcription factors and potential neurotoxic chemicals that may be involved in the pathogenesis of AD. Together these results reveal likely molecular drivers of sex differences in the brain of AD patients. Future molecular studies dissecting the functional role of these switch genes in driving sex differences in AD are warranted.
Weighted gene co-expression network analysis reveals key module and hub genes associated with the anthocyanin biosynthesis in maize pericarp

Anthocyanins are the visual pigments that present most of the colors in plants. Its biosynthesis requires the coordinated expression of structural genes and regulatory genes. Pericarps are the rich sources of anthocyanins in maize seeds. In the experiment, the transcriptomes of transparent and anthocyanins-enriched pericarps at 15, 20, and 25 DAP were obtained. The results output 110.007 million raw reads and 51407 genes’ expression matrix. Using data filtration in R language, 2057 genes were eventually identified for weighted gene co-expression network analysis. The results showed that 2057 genes were classified into ten modules. The cyan module containing 183 genes was confirmed to be the key module with the highest correlation value of 0.98 to the anthocyanins trait. Among 183 genes, seven structural genes were mapped the flavonoid biosynthesis pathway, and a transcription factor Lc gene was annotated as an anthocyanin regulatory gene. Cluster heatmap and gene network analysis further demonstrated that Naringenin, 2-oxoglutarate 3-dioxygenase (Zm00001d001960), Dihydroflavonol 4-reductase (Zm00001d044122), Leucoanthocyanidin dioxygenase (Zm00001d014914), anthocyanin regulatory Lc gene (Zm00001d026147), and Chalcone synthase C2 (Zm00001d052673) participated in the anthocyanins biosynthesis. And the transcription factor anthocyanin regulatory Lc gene Zm00001d026147 may act on the genes Chalcone synthase C2 (Zm00001d052673) and Dihydroflavonol 4-reductase (Zm00001d044122). The yeast one-hybrid assays confirmed that the Lc protein could combine with the promoter region of C2 and directly regulate the anthocyanin biosynthesis in the pericarp. These results may provide a new sight to uncover the module and hub genes related to anthocyanins biosynthesis in plants.
Collective intelligence in teams: Contextualizing collective intelligent behavior over time

Collective intelligence (CI) in organizational teams has been predominantly understood and explained in terms of the quality of the outcomes that the team produces. This manuscript aims to extend the understanding of CI in teams, by disentangling the core of actual collective intelligent team behavior that unfolds over time during a collaboration period. We posit that outcomes do support the presence of CI, but that collective intelligence itself resides in the interaction processes within the team. Teams behave collectively intelligent when the collective behaviors during the collaboration period are in line with the requirements of the (cognitive) tasks the team is assigned to and the (changing) environment. This perspective results in a challenging, but promising research agenda armed with new research questions that call for unraveling longitudinal fine-grained interactional processes over time. We conclude with exploring methodological considerations that assist researchers to align concept and methodology. In sum, this manuscript proposes a more direct, thorough, and nuanced understanding of collective intelligence in teams, by disentangling micro-level team behaviors over the course of a collaboration period. With this in mind, the field of CI will get a more fine-grained understanding of what really happens at what point in time: when teams behave more or less intelligently. Additionally, when we understand collectively intelligent processes in teams, we can organize targeted interventions to improve or maintain collective intelligence in teams.
Doctors' adherence to guidelines recommendations and glycaemic control in diabetic patients in Quetta, Pakistan: Findings from an observational study

Background Poor control of diabetes mellitus (DM) is partly attributed to doctors' poor adherence to guidelines. Objective To evaluate doctors' adherence to pharmacotherapeutic recommendations of DM management guidelines and factors associated with guidelines adherence and glycaemic control. Methods This prospective observational study included 30 doctors who were treating DM patients in their private clinics in Quetta, Pakistan. On visit 1, a total of 600 prescriptions written by 30 enrolled doctors (20 patients per doctor) were noted along with patients' sociodemographic and clinical characteristics. American Diabetes Association guidelines was used as a reference. The prescriptions noted were judged for guidelines compliance. Of 600 enrolled patients, 450 patients (15 patients per doctor) were followed for one more visit and included in final analysis. Glycated hemoglobin (HbA1c) level noted one visit 2 was related with the respective prescription on visit 1. Data were analyzed by SPSS (version 23). A p-value <0.05 was considered statistically significant. Results Patients received a median of two antidiabetic drugs (range: 1–5). A total of 73.1% patients were on polytherapy. Metformin was the most frequently prescribed (88.4%) antidiabetic followed by gliptins (46.2%). A total of 41.6% prescriptions were judged guidelines compliant. In multivariate binary logistic regressions (MVBLR) analysis, chronic kidney disease (CKD) (OR = 0.422) and polytherapy (OR = 0.367) had statistically significant negative associations (p-value <0.05) with guidelines' compliant prescriptions. The group of doctors comprised of specialists and consultants wrote significantly (p-value = 0.004) high number of guidelines adherent prescriptions (mean rank = 20.25) than the group comprised of medical officers (mean rank = 11.34). On visit 2, only 39.5% patients were on goal glycemic levels. In MVBLR analysis, suffering from dyslipidemia (OR = 0.134) and CKD (OR = 0.111), receiving sulfonylurea (OR = 0.156) and guidelines' compliant prescription (OR = 4.195) were significantly (p-value <0 .05) associated with glycemic control. Conclusion Although guidelines compliant prescriptions produced better glycemic control, but doctors' adherence to guidelines and glycemic control were poor. Polytherapy and CKD emerged as risk factors for guidelines divergent prescriptions. Dyslipidemia, CKD and reception of sulfonylureas had negative association with glycemic control.
Size-dependent hygroscopicity of levoglucosan and D-glucose aerosol nanoparticles

Abstract. The interaction between water vapor and aerosol nanoparticles is important in atmospheric processes. Hygroscopicity of sub-10 nm organic nanoparticles and their concentration-dependent thermodynamic properties (e.g., water activity) in the highly supersaturated concentration range are, however, scarcely available. Here we investigate the size dependence of hygroscopicity of organics (i.e., levoglucosan, D-glucose) in dry particle diameter down to 6 nm using a nano-hygroscopicity tandem differential mobility analyzer (nano-HTDMA). Our results show that there is only weak size-dependent hygroscopic growth of both levoglucosan and D-glucose nanoparticles with diameters down to 20 nm. In the diameter range smaller than 20 nm (down to 6 nm), we observed strong size-dependent hygroscopic growth for D-glucose nanoparticles. The hygroscopic growth factors cannot be determined for levoglucosan below 20 nm due to its evaporation. In addition, we compare hygroscopicity measurements for levoglucosan and D-glucose nanoparticles with E-AIM (standard UNIFAC – functional group activity coefficients), the ideal solution theory, and differential Köhler analysis (DKA) predictions. The ideal solution theory describes the measured hygroscopic growth factors of levoglucosan with diameters down to 20 nm and D-glucose nanoparticles with diameters larger than 60 nm, while E-AIM (standard UNIFAC) can successfully predict the growth factors of D-glucose nanoparticles with diameters from 100 down to 6 nm at RH above 88 %–40 % (e.g., at RH above 88 % for 100 nm D-glucose, at RH above 40 % for 6 nm D-glucose). The use of the DKA method leads to good agreement with measured hygroscopic growth factors of D-glucose aerosol nanoparticles with diameters from 100 down to 6 nm. Predicted water activity for these aqueous organic solutions (i.e., levoglucosan, D-glucose) from different parameterization methods agrees well with observations in the low solute concentration range (< 20 mol kg−1) and starts to deviate from observations in the high solute concentration (> 20 mol kg−1).
Decoherence induced by interacting quantum spin baths

We study decoherence induced on a two-level system coupled to a one-dimensional quantum spin chain. We consider the cases where the dynamics of the chain is determined by the Ising, XY, or Heisenberg exchange Hamiltonian. This model of quantum baths can be of fundamental importance for the understanding of decoherence in open quantum systems, since it can be experimentally engineered by using atoms in optical lattices. As an example, here we show how to implement a pure dephasing model for a qubit system coupled to an interacting spin bath. We provide results that go beyond the case of a central spin coupled uniformly to all the spins of the bath, in particular showing what happens when the bath enters different phases, or becomes critical; we also study the dependence of the coherence loss on the number of bath spins to which the system is coupled and we describe a coupling-independent regime in which decoherence exhibits universal features, irrespective of the system-environment coupling strength. Finally, we establish a relation between decoherence and entanglement inside the bath. For the Ising and the XY models we are able to give an exact expression for the decay of coherences, while for the Heisenberg bathmore » we resort to the numerical time-dependent density matrix renormalization group. « less
U n c o rr e c t ed A u t ho r P r oo f Extremely Early-Onset Frontotemporal Dementia: A Case Report and Literature Review

11 Background: In most cases, the onset of frontotemporal dementia (FTD) occurs between the ages of 45 and 65 years. However, some patients experience an extremely early disease onset. 12 13 Objective: To investigate the clinical, genetic, and pathological features of extremely early-onset FTD. 14 Methods: We conducted a comprehensive clinical, genetic, and neuropathological analysis of a 25-year-old patient experiencing the onset of behavioral variant frontotemporal dementia (bvFTD). In addition, we conducted a literature review and summarized the clinical, genetic, and pathological features of patients with FTD with onset age ≤ 25 years. 17 Results: The patient was diagnosed with bvFTD; however, there was no family history of FTD, no positive genetic test results and no deposition of TDP43, tau, ubiquitin, and synuclein in the brain. Literature screening identiﬁed 18 patients with onset age ≤ 25 years with FTD. The youngest patient was 14-years-of-age. Most patients (8/14) had a positive family history. The most common clinical phenotype was the behavioral variant (12/14). Genetic results were reported for 11 patients; the most common pathogenic gene was MAPT (10/12), with four cases of G389R, two cases of P301S, one case of G335S, one case of G335A, one case of G335V, and one case of L315R. Pathological results were reported for 13 patients; the most common pathological subtype was tau (8/13). 18 19 20 21 22 23 24 Conclusion: FTD can start at an extremely early age. The most common phenotype of extremely early onset FTD was the behavioral variant, the most common pathogenic gene was MAPT, and the most common neuropathological type was tau.
High sulphur dioxide deposition velocities measured with the flux/gradient technique in a boreal forest in the Alberta oil sands region

The emission of SO 2 from the Athabasca oil sands region (AOSR) has been shown to impact the surrounding forest area and human exposure. Recent studies using aircraft-based measurements have demonstrated that deposition of SO 2 to the forest is at a rate many times higher than model estimates. Here we use the flux/gradient method to estimate SO 2 deposition rates at two tower sites in the boreal forest downwind of AOSR SO 2 emissions. We use both continuous and passive sampler measurements and compare both techniques. The measurements predict SO 2 deposition velocities ranging 15 from 2.1–5.9 cm s -1 . There are uncertainties associated with the passive sampler flux/gradient analysis, primarily due to an assumed Schmidt number, a required assumption of independent variables, and potential wind effects. We estimate the total uncertainty as ±2 cm s -1 . Accounting for these uncertainties, the measurements are near (or slightly higher than) the previous aircraft-based measurements (1.2–3.2 cm s -1 ) and significantly higher than model estimates for the same measurement periods (0.1–0.6 cm s -1 ), suggesting that SO 2 has a much shorter lifetime in the atmosphere than is currently predicted by 20 models. in a boreal forest to determine dry SO 2 deposition velocities downwind of oil 50 sands production facilities. Measurements were made with both long-term (2-3 week exposure period) passive samplers and continuous in-situ gas analyzers at two tower locations in the same forest. Continuous SO 2 measurements demonstrated that the site was subjected to relatively strong, intermittent plumes of SO 2 , which we assumed were not re-emitted from the forest (hence eliminating uncertainty due to bi-directional fluxes). Here we determine average values of turbulent diffusion coefficients ( 𝐾𝐾 ) based on momentum flux and stability measurements, and we assess the uncertainties due to the long-term 55 averaging of these variables using continuous SO 2 gradient measurements. Following this approach, we determine a range of SO 2 dry deposition velocities.
An Improved Classifier Chain Ensemble for Multi-DimensionalClassification with Conditional Dependence

An Improved Classifier Chain Ensemble for Multi-Dimensional Classification with Conditional Dependence Joseph Ethan Heydorn Department of Computer Science, BYU Master of Science We focus on multi-dimensional classification (MDC) problems with conditional dependence, which we call multiple output dependence (MOD) problems. MDC is the task of predicting a vector of categorical outputs for each input. Conditional dependence in MDC means that the choice for one output value affects the choice for others, so it is not desirable to predict outputs independently. We show that conditional dependence in MDC implies that a single input can map to multiple correct output vectors. This means it is desirable to find multiple correct output vectors per input. Current solutions for MOD problems are not sufficient because they predict only one of the correct output vectors per input, ignoring all others. We modify four existing MDC solutions, including chain classifiers, to predict multiple output vectors. We further create a novel ensemble technique named weighted output vector ensemble (wove) which combines these multiple predictions from multiple chain classifiers in a way that preserves the integrity of output vectors and thus preserves conditional dependence among outputs. We verify the effectiveness of wove by comparing it against 7 other solutions on a variety of data sets and find that it shows significant gains over existing methods.
Instant and delayed effects of March biomass burning aerosols over the Indochina Peninsula

Abstract. By analyzing observations and simulations from the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), we investigated instant and delayed responses of large-scale atmospheric circulations and precipitation to biomass burning (BB) aerosols over the Indochina Peninsula (ICP) in the peak emission of March. The results show that the BB aerosols inhibit precipitation over the ICP in March and promote precipitation from early April to mid April. Specifically, the March BB aerosols over the ICP can induce mid- to lower-tropospheric heating and planetary boundary layer cooling to enhance local atmospheric stability; meanwhile, the perturbation heating can trigger an anomalous low in the lower troposphere to moisten the mid troposphere. However, the convection suppression due to the stabilized atmosphere dominates over the favorable water-vapor condition induced by large-scale circulation responses, leading to overall reduced precipitation over the ICP in March. For the delayed effect, the anomalous low can provide more water vapor as the monsoon advances in early April, although it becomes much weaker without BB aerosols' strong heating. On the other hand, the convective instability above 850 hPa is enhanced by more water vapor, resulting in enhanced precipitation over the ICP, northern South China Sea, and southern China. Thereafter, the condensational latent heating gradually takes over from the BB aerosol radiative heating, acting as the main driver for maintaining the anomalous circulation and thus the delayed effect in mid April.
Statically Fused Unbiased Converted Measurements Kalman Filter

—Active radar and sonar systems often report Doppler measurements in addition to the position measurements such as range and bearing. The tracker can perform better by making full use of the Doppler measurements. However, due to the high nonlinearity of the Doppler measurements with respect to the target state in the Cartesian coordinate systems, those measurements are not always fully exploited. This paper mainly focuses on dealing with the Doppler measurements as well as the position measurements in Polar coordinates. The Statically Fused Converted Position and Doppler Measurements Kalman Filter (SF-CMKF) with additive debiased measurement conversion has been presented. However, the exact compensation for the bias of the measurement conversion are multiplicative and depend on the statistics of the cosine of the angle measurement errors. As a result, the consistency and performance of the SF-CMKF may be suboptimal in the large angle error situations. In this paper, the multiplicative unbiased position and Doppler measurement conversion for two-dimensional (Polar-to-Cartesian) tracking are derived, and the SF-CMKF is improved by using those conversion. Monte Carlo simulations are presented to demonstrate the statistic consistency of the multiplicative unbiased conversion and the superior performance of the modiﬁed SF-CMKF (SF-UCMKF).