Miracle-dz/UniFAR-FTUs huggingface dataset:
Evidence for Multiple Subpopulations of Herpesvirus-Latently Infected Cells

Latency is the defining characteristic of the Herpesviridae and central to the tumorigenesis phenotype of Kaposi’s sarcoma-associated herpesvirus (KSHV). KSHV-driven primary effusion lymphomas (PEL) rapidly develop resistance to therapy, suggesting tumor instability and plasticity. ABSTRACT Kaposi’s sarcoma-associated herpesvirus (KSHV)-associated primary effusion lymphomas (PEL) are traditionally viewed as homogenous regarding viral transcription and lineage of origin, but so far this contention has not been explored at the single-cell level. Single-cell RNA sequencing of latently infected PEL supports the existence of multiple subpopulations even within a single cell line. At most 1% of the cells showed evidence of near-complete lytic transcription. The majority of cells only expressed the canonical viral latent transcripts: those originating from the latency locus, the viral interferon regulatory factor locus, and the viral lncRNA nut-1/Pan/T1.1; however, a significant fraction of cells showed various degrees of more permissive transcription, and some showed no evidence of KSHV transcripts whatsoever. Levels of viral interleukin-6 (IL-6)/K2 mRNA emerged as the most distinguishing feature to subset KSHV-infected PEL. One newly uncovered phenotype is the existence of BCBL-1 cells that readily adhered to fibronectin and that displayed mesenchymal lineage-like characteristics. IMPORTANCE Latency is the defining characteristic of the Herpesviridae and central to the tumorigenesis phenotype of Kaposi’s sarcoma-associated herpesvirus (KSHV). KSHV-driven primary effusion lymphomas (PEL) rapidly develop resistance to therapy, suggesting tumor instability and plasticity. At any given time, a fraction of PEL cells spontaneously reactivate KSHV, suggesting transcriptional heterogeneity even within a clonal cell line under optimal growth conditions. This study employed single-cell mRNA sequencing to explore the within-population variability of KSHV transcription and how it relates to host cell transcription. Individual clonal PEL cells exhibited differing patterns of viral transcription. Most cells showed the canonical pattern of KSHV latency (LANA, vCyc, vFLIP, Kaposin, and vIRFs), but a significant fraction evidenced extended viral gene transcription, including of the viral IL-6 homolog, open reading frame K2. This study suggests new targets of intervention for PEL. It establishes a conceptual framework to design KSHV cure studies analogous to those for HIV.
Effect of dexamethasone as an analgesic adjuvant to multimodal pain treatment after total knee arthroplasty: randomised clinical trial

Abstract Objective To investigate the effects of one and two doses of intravenous dexamethasone in patients after total knee arthroplasty. Design Randomised, blinded, placebo controlled trial with follow-up at 90 days. Setting Five Danish hospitals, September 2018 to March 2020. Participants 485 adult participants undergoing total knee arthroplasty. Intervention A computer generated randomised sequence stratified for site was used to allocate participants to one of three groups: DX1 (dexamethasone (24 mg)+placebo); DX2 (dexamethasone (24 mg)+dexamethasone (24 mg)); or placebo (placebo+placebo). The intervention was given preoperatively and after 24 hours. Participants, investigators, and outcome assessors were blinded. All participants received paracetamol, ibuprofen, and local infiltration analgesia. Main outcome measures The primary outcome was total intravenous morphine consumption 0 to 48 hours postoperatively. Multiplicity adjusted threshold for statistical significance was P<0.017 and minimal important difference was 10 mg morphine. Secondary outcomes included postoperative pain. Results 485 participants were randomised: 161 to DX1, 162 to DX2, and 162 to placebo. Data from 472 participants (97.3%) were included in the primary outcome analysis. The median (interquartile range) morphine consumptions at 0-48 hours were: DX1 37.9 mg (20.7 to 56.7); DX2 35.0 mg (20.6 to 52.0); and placebo 43.0 mg (28.7 to 64.0). Hodges-Lehmann median differences between groups were: −2.7 mg (98.3% confidence interval −9.3 to 3.7), P=0.30 between DX1 and DX2; 7.8 mg (0.7 to 14.7), P=0.008 between DX1 and placebo; and 10.7 mg (4.0 to 17.3), P<0.001 between DX2 and placebo. Postoperative pain was reduced at 24 hours with one dose, and at 48 hours with two doses, of dexamethasone. Conclusion Two doses of dexamethasone reduced morphine consumption during 48 hours after total knee arthroplasty and reduced postoperative pain. Trial registration Clinicaltrials.gov NCT03506789.
Numerical Study on Compound-Slope Seawalls with Different Types of Protective Facings

ABSTRACT Zeng, C. -S. ; Zhan, J.-M. , and Hu, W. -Q. , 2022. Numerical study on compound-slope seawalls with different types of protective facings. Journal of Coastal Research, 38(1), 182–195. Coconut Creek (Florida), ISSN 0749-0208. The compound seawall is an important infrastructure to protect the coast effectively against tide and wave impacts. In this paper, a hybrid realizable k – ∊/laminar model and a volume of fluid interface capture method were used to study compound-slope seawalls with different types of protective facings. An analytical method was used to separate the incident wave and the reflected wave, and the numerical results for a compound-slope seawall with a hollow-block protective facing structure were verified by experimental results. The monitored wave surface, incident wave, and reflected wave data in the numerical simulation were compared with the experimental results, and the results show that the numerical model can simulate the interaction process of waves and compound-slope seawalls well. Furthermore, a series of numerical simulation studies on compound-slope seawalls under different protective facing structures with different wave heights, wave periods, water depths, and structure slopes was conducted. The results show that the hollow-block protective facings have a significant weakening effect on the reflected wave height, wave run-up, and wave force when the wave is moderate, which is important for the safety of seawall and onshore building structures.
Improving Genetic Status Despite Fragmentation and Small Effective Population Size in Hill's Thistle (Cirsium hillii)

Abstract. Small, fragmented populations are at greater risk of extirpation due to reduced genetic diversity from inbreeding and genetic drift. These processes ultimately decrease individual fitness and reduce the ability of a population to adapt. Hill's thistle (Cirsium hillii) is classified as a threatened species throughout much of its range, primarily due to the destruction and fragmentation of its habitat. This study addresses the impact of population size and isolation on the genetic diversity of Hill's thistle. We used microsatellite markers to genotype plants collected from the Lower Peninsula of Michigan in 2001, and from the Lower Peninsula and Drummond Island in 2012, in order to assess genetic differentiation across time and space, as well as to investigate rates of inbreeding in isolated and nonisolated populations. Genetic differentiation between the sample sites in the mainland population of Hill's thistle increased significantly between 2001 and 2012, indicative of increased fragmentation and isolation of the sample sites. However, the 2012 population exhibited lower inbreeding and no difference in heterozygosity or allelic diversity compared to 2001, suggesting the population is stable, or growing, in spite of isolation. Conversely, the population on Drummond Island displayed higher levels of inbreeding and lower number of effective alleles and heterozygosity compared to the mainland, typical of a small, isolated population. Our results indicate that the mainland population of Hill's thistle is persisting but should continue to be monitored demographically due to ongoing habitat loss.
Summer Populations of Northern Long-eared Bat in an Eastern Kentucky Forest Following Arrival of White-nose Syndrome

Abstract. Myotis bats have experienced significant population losses due to white-nose syndrome (WNS) throughout large portions of their distributions in eastern North America. As closed-space foragers, these species comprise an important feeding guild within eastern forests. An understanding of where summer populations remain and how their ecology has changed following impact from WNS is needed to assess fully the recovery potential of Myotis bats. We used acoustic sampling, capture surveys, radiotelemetry and roost surveys from 2015 to 2018 to evaluate the status of northern long-eared bat (Myotis septentrionalis) in an eastern Kentucky forest following region-wide impacts from WNS to this species. Acoustic activity of Myotis remained unchanged over the 4 y of sampling, with activity of these bats greatest in mid- to late July. Northern long-eared bats represented 97% of the Myotis captured, indicating activity levels likely reflected patterns for this species. We located 18 roost trees of northern long-eared bats in five tree species, including both live and dead trees. All roost trees were on upper slopes within 100 m of ridge top roads. Maximum exit counts, 24 and 21, at two roosts occurred in late May and early June, suggesting these dates represented the summer maternity period of northern long-eared bats in this forest. Our results demonstrated that post-WNS populations of northern long-eared bats on Robinson Forest formed small colonies, day-roosted in trees near roads on forested ridge tops, were reproductively active, and maintained steady levels of activity across the 4 y of sampling. These data suggest that local populations of northern long-eared bats are surviving WNS and continue to persist during summer months in forests of the Appalachian Mountain region. We hypothesize presence of ridge top roads, often associated with forest logging operations, may be important habitat elements for increasing availability of preferred roosting habitat for summer populations of northern long-eared bats in actively managed forests.
Structural Breaks and Explosive Behavior in the Long-Run: The Case of Australian Real House Prices, 1870–2020

Abstract In this article, we use tests of explosive behavior in real house prices with annual data for the case of Australia for the period 1870–2020. The main contribution of this paper is the use of very long time series. It is important to use longer span data because it offers more powerful econometric results. To detect episodes of potential explosive behavior in house prices over this long period, we use the recursive unit root tests for explosiveness proposed by Phillips et al. (2011), (2015a,b). According to the results, there is a clear speculative bubble behavior in real house prices between 1997 and 2020, speculative process that has not yet been adjusted.
The crystal structure of 4-phenyl-4-[2-(pyridine-4-carbonyl)hydrazinylidene]butanoic acid, C16H15N3O3

Abstract C16H15N3O3, monoclinic, P21/c (no. 14), a = 9.4957(3) Å, b = 18.2275(5) Å, c = 9.0896(3) Å, β = 114.372(1)°, V = 1433.05(15) Å3, Z = 4, R gt (F) = 0.0380, wR ref (F 2) = 0.1011, T = 173 K.
An orbit determination method of spacecraft based on distribution regression

Abstract A new method of orbit determination (OD) is proposed: distribution regression. The paper focuses on the process of using sparse observation data to determine the orbit of the spacecraft without any prior information. The standard regression process is to learn a map from real numbers to real numbers, but the approach put forward in this paper is to map from probability distributions to real-valued responses. According to the new algorithm, the number of orbital elements can be predicted by embedding the probability distribution into the reproducing kernel Hilbert space. While making full use of the edge of big data, it also avoids the problem that the algorithm cannot converge due to improper initial values in precise OD. The simulation experiment proves the effectiveness, robustness, and rapidity of the algorithm in the presence of noise in the measurement data.
When will I get out of the Hospital? Modeling Length of Stay using Comorbidity Networks

ABSTRACT A reliable and accurate estimate of the expected hospital length of stay (LOS) of a patient is important to patients, medical providers, and insurance companies. Predicting hospital Length of Stay (LOS) is a complex and ill-structured problem, driven by many factors such as a patient’s individual characteristics, treatment plans, and disease-interactions. In this paper, we develop a novel model to predict the expected LOS at the time of admission by combining network science and deep learning. We propose a two-dimensional construct of latent comorbidities comprising historical and probable comorbidities that a patient does not currently manifest but could likely develop during the course of hospital stay. The probable comorbidities are derived from a network comprising relationships among diseases observed in 3.2 million patient records in hundreds of US hospitals. We employ this construct of latent comorbidities in deep learning models to predict patients’ LOS using almost 10 million other patient visits belonging to various disease categories. Implementing these models and analyses required a high-performance computing (Big Data) facility. The average mean absolute percent error of our models across all categories of diseases was 29.8%, which is the best in the current state-of-the-art. Our primary contribution is in developing a generalizable method to create a predictor construct for recognizing underlying relationships through network analyses, which can then be used in a deep learning model to predict an exogenous dependent variable.
A study on the carbonation of binary and ternary blended cement mortar and concrete

ABSTRACT Carbonation of concrete has always been a durability concern leading to the corrosion of steel in reinforced concrete. The present paper deals with carbonation resistance of cement mortar and concrete when supplementary cementitious materials like fly ash and blast furnace slag partially replaces cement. The work had been carried out in two phases, first being the measure of carbonation depth and compressive strength of the samples with water binder ratios of 0.35, 0.5 and 0.65 to train the artificial neural network. Based on the results from carbonation depth, the consistency of Fick’s law of diffusion that governs the carbon dioxide (CO2) ingress into concrete has been ascertained with the help of linear-programming problem. In the second phase of the study, cement mortar samples of water binder ratios 0.4, 0.5 and 0.6 had been tested to verify the reliability of phenolphthalein indicator in identifying the depth of carbonation with the help of microscopic analysis such as Thermo gravimetric analysis (TGA). The same specimens have been used to identify the phases of crystalline materials of post-carbonation samples using X-Ray diffraction (XRD). An attempt has been made to quantify the carbonated products of calcium hydroxides and C-S-H.
Microenvironment-associated gene HSD11B1 may serve as a prognostic biomarker in clear cell renal cell carcinoma: a study based on TCGA, RT‑qPCR, Western blotting, and immunohistochemistry

ABSTRACT Clear cell renal cell carcinoma (ccRCC) is one of the most common malignant tumors worldwide. The clinical treatment of ccRCC is strongly associated with the tumor microenvironment (TME). Identifying potential markers of ccRCC is important to improve prognosis. Therefore, in the present study, the levels of immune/stromal components and the proportion of tumor-infiltrating immune cells (TIICs) were determined in 611 ccRCC samples using the ESTIMATE and CIBERSORT analytical tools. Subsequently, hydroxysteroid 11-beta dehydrogenase-1 (HSD11B1) was identified by univariate Cox regression analysis, protein-protein interaction (PPI) networks and clinical survival analysis to be associated with ccRCC prognosis. At the same time, the abundance of HSD11B1 increased significantly in ccRCC was verified by western blotting, RT‑qPCR and immunostaining analysis. Furthermore, Gene Set Enrichment Analysis (GSEA) and TME suggested that HSD11B1 was involved in TME immune-related status. Taken together, the results of the present study demonstrated that HSD11B1 is a potential prognostic biomarker associated with immune cell infiltration in ccRCC.
Prognostic value of programmed death ligand 1 (PD-L1) in glioblastoma: a systematic review, meta-analysis and validation based on dataset

ABSTRACT Excellent prognostic value of programmed death ligand 1 (PD-L1) is observed in patients with other cancers; however, the prognostic value of PD-L1 in glioblastoma (GBM) remains unclear. Therefore, this meta-analysis evaluated the prognostic value of PD-L1 in GBM. We performed a systematic search in databases to screen eligible articles. The hazard ratio (HR) and 95% confidence interval (95% CI) were extracted from included articles. This meta-analysis included 15 studies, and the forest plot indicated that increased PD-L1 expression was associated with poorer overall survival (OS) of GBM (HR, 1.16; 95% CI, 1.05–1.27; P = 0.002). Furthermore, stratified analysis confirmed that PD-L1 expression was associated with unfavorable OS at the protein level (HR, 1.30; 95% CI, 1.13–1.48; P< 0.001) and messenger ribonucleic acid (mRNA) level (HR, 1.05; 95% CI, 1.00–1.09; P= 0.041). The analysis of a dataset verified the prognostic value of PD-L1 and revealed an association between PD-L1 mRNA expression and the status of isocitrate dehydrogenase (IDH). In conclusion, increased PD-L1 expression predicts unfavorable OS in GBM and may be a promising prognostic biomarker of GBM.
Scaling Membership of Byzantine Consensus

Scaling Byzantine Fault Tolerant (BFT) systems in terms of membership is important for secure applications with large participation such as blockchains. While traditional protocols have low latency, they cannot handle many processors. Conversely, blockchains often have hundreds to thousands of processors to increase robustness, but they typically have high latency or energy costs. We describe various sources of unscalability in BFT consensus protocols. To improve performance, many BFT protocols optimize the “normal case,” where there are no failures. This can be done in a modular fashion by wrapping existing BFT protocols with a building block that we call alliance. In normal case executions, alliance can scalably determine if the initial conditions of a BFT consensus protocol predetermine the outcome, obviating running the consensus protocol. We give examples of existing protocols that solve alliance. We show that a solution based on hypercubes and MACs has desirable scalability and performance in normal case executions, with only a modest overhead otherwise. We provide important optimizations. Finally, we evaluate our solution using the ns3 simulator and show that it scales up to thousands of processors and compare with prior work in various network topologies.
Unsicherheiten bei der Quantifizierung von Hochwasser‐Schadenspotenzialen

Die Ermittlung von Hochwasser‐Schadenspotenzialen bei Nutzen‐Kosten‐Analysen erfolgt in den einzelnen Bundesländern meist mit herkömmlichen nutzungsorientierten Schadensmodellen. Dabei geben Schadensfunktionen einen Erwartungswert (Mittelwert) für den zu erwartenden Schaden in Abhängigkeit von der Nutzung und den hochwasserspezifischen Einwirkungsparametern an. Die große Streubreite der real auftretenden Schäden wird dabei vernachlässigt.
Integrated Analysis of miRNAs Associated With Sugarcane Responses to Low-Potassium Stress

Sugarcane is among the most important global crops and a key bioenergy source. Sugarcane production is restricted by limited levels of available soil potassium (K+). The ability of plants to respond to stressors can be regulated by a range of microRNAs (miRNAs). However, there have been few studies regarding the roles of miRNAs in the regulation of sugarcane responses to K+-deficiency. To understand how these non-coding RNAs may influence sugarcane responses to low-K+ stress, we conducted expression profiling of miRNAs in sugarcane roots under low-K+ conditions via high-throughput sequencing. This approach led to the identification of 324 and 42 known and novel miRNAs, respectively, of which 36 were found to be differentially expressed miRNAs (DEMs) under low-K+ conditions. These results also suggested that miR156-x/z and miR171-x are involved in these responses as potential regulators of lateral root formation and the ethylene signaling pathway, respectively. A total of 705 putative targets of these DEMs were further identified through bioinformatics predictions and degradome analyses, and GO and KEGG enrichment analyses revealed these target mRNAs to be enriched for catalytic activity, binding functions, metabolic processes, plant hormone signal transduction, and mitogen-activated protein kinase (MAPK) signaling. In summary, these data provide an overview of the roles of miRNAs in the regulation of sugarcane response to low-K+ conditions.
The Relationship Between Resilience and Posttraumatic Growth Among the Primary Caregivers of Children With Developmental Disabilities: The Mediating Role of Positive Coping Style and Self-Efficacy

This study was conducted to investigate the relationship between posttraumatic growth (PTG), resilience, positive coping style, and self-efficacy among the primary caregivers of children with developmental disorders in Chongqing, China. A total of 198 primary caregivers (parents and grandparents) aged from 22 to 66 years old (M = 35.55, SD = 9.16), including 155 females (78.3%) and 43 males (21.7%), were enrolled. The Posttraumatic Growth Inventory, Connor-Davidson Resilience Scale-10, Simplified Coping Style Questionnaire, and General Self-Efficacy Scale were used for data collection. The results found that PTG could be positively predicted by resilience. Positive coping style and self-efficacy mediated the relationship between resilience and PTG. The different levels of PTG were determined by the resident location, monthly income and education of the primary caregivers. The results suggest that it is critical to improve the mental health of the primary caregivers (parents and grandparents) of children with developmental disabilities. Our results also provide a scientific basis for future research.
Druggable Lipid Binding Sites in Pentameric Ligand-Gated Ion Channels and Transient Receptor Potential Channels

Lipids modulate the function of many ion channels, possibly through direct lipid-protein interactions. The recent outpouring of ion channel structures by cryo-EM has revealed many lipid binding sites. Whether these sites mediate lipid modulation of ion channel function is not firmly established in most cases. However, it is intriguing that many of these lipid binding sites are also known sites for other allosteric modulators or drugs, supporting the notion that lipids act as endogenous allosteric modulators through these sites. Here, we review such lipid-drug binding sites, focusing on pentameric ligand-gated ion channels and transient receptor potential channels. Notable examples include sites for phospholipids and sterols that are shared by anesthetics and vanilloids. We discuss some implications of lipid binding at these sites including the possibility that lipids can alter drug potency or that understanding protein-lipid interactions can guide drug design. Structures are only the first step toward understanding the mechanism of lipid modulation at these sites. Looking forward, we identify knowledge gaps in the field and approaches to address them. These include defining the effects of lipids on channel function in reconstituted systems using asymmetric membranes and measuring lipid binding affinities at specific sites using native mass spectrometry, fluorescence binding assays, and computational approaches.