Miracle-dz/UniFAR-FTUs huggingface dataset:
Loss of presenilin-1 in smooth muscle cells ameliorates elastin aortopathy

Smooth muscle cell (SMC) accumulation is central to the pathogenesis of elastin-defective arterial diseases, such as atherosclerosis, pulmonary hypertension and supravalvular aortic stenosis (SVAS). We previously demonstrated that elastin insufficiency activates the Notch pathway in aortic SMCs, resulting in hypermuscularization. Activation of Notch is catalyzed by the enzyme gamma-secretase, but the role of specific catalytic subunits PSEN-1 or PSEN-2 in elastin aortopathy is not defined. This study utilizes genetic approaches to query the role of PSEN-1/2 in the pathogenesis of elastin mutant mice, which model human SVAS. Although endothelial cell-specific Psen1 deletion does not improve elastin aortopathy, deletion of either Psen1 in SMCs or Psen2 globally attenuates Notch downstream gene expression and SMC proliferation, mitigating aortic disease. With SMC-specific Psen1 deletion in elastin nulls, these rescue effects are more robust and in fact, survival is increased. On the background of Psen1 deletion in SMCs, global Psen2 deletion yields additional benefits in regard to elastin aortopathy. Finally, SMC deletion of Psen1 also attenuates hypermuscularization in newborns heterozygous for the elastin null gene, which genetically mimics SVAS. Taken together, these findings put forth SMC PSEN-1 as a potential therapeutic target in elastin aortopathy.
Marigold: Efficient k-means Clustering in High Dimensions

How can we efficiently and scalably cluster high-dimensional data? The k -means algorithm clusters data by iteratively reducing intra-cluster Euclidean distances until convergence. While it finds applications from recommendation engines to image segmentation, its application to high-dimensional data is hindered by the need to repeatedly compute Euclidean distances among points and centroids. In this paper, we propose Marigold ( k -means for high-dimensional data), a scalable algorithm for k -means clustering in high dimensions. Marigold prunes distance calculations by means of (i) a tight distance-bounding scheme; (ii) a stepwise calculation over a multiresolution transform; and (iii) exploiting the triangle inequality. To our knowledge, such an arsenal of pruning techniques has not been hitherto applied to k -means. Our work is motivated by time-critical Angle-Resolved Photoemission Spectroscopy (ARPES) experiments, where it is vital to detect clusters among high-dimensional spectra in real time. In a thorough experimental study with real-world data sets we demonstrate that Marigold efficiently clusters high-dimensional data, achieving approximately one order of magnitude improvement over prior art.
An Optimization Method for CS Projection Matrix Based on Quasi-Newton Method

In compressed sensing( CS for short) theory,the projection matrix optimization is a kind of approach of improving performance by increasing the amount of information of observational data.This paper presents a CS projection matrix optimization algorithm based on quasi-New ton method.The algorithm is divided into tw o steps.First,use threshold function to restrain the non-diagonal elements in order to make the M utual Coherence betw een the projection matrix and sparse dictionary approximate Welch bound.Second,use Rank tw o to check and get Hessian matrix inverse to amend the direction of the gradient search.Tw o steps are alternately performed until the projection matrix w hich meets the requirement of the optimal solution is w orked out.This algorithm alw ays maintains descent and has a super-linear convergence rate,w hich requires less computation.Experimental results show that w hen signal sparse degree or observation data is identical,this proposed algorithm outperforms other algorithms.
Dotori: A Key-Value SSD Based KV Store

Key-value SSDs (KVSSDs) represent a major shift in the storage stack design, with numerous potential benefits. Despite this, their lack of native features critical to operation in real world scenarios hinders their adoption, and these benefits go unrealized. Moreover, simply adapting existing key-value stores to run on KVSSDs proves underwhelming, as KVSSDs operate at lower raw device performance when compared to modern block SSDs. This paper introduces Dotori. Dotori is a KVSSD based key-value store that provides much needed functionality in a KVSSD through an upper layer in the host, and takes advantage of the unique KVSSD interface to enable further gains in functionality and performance. At the core of Dotori is a novel B+tree design that is only practical when the underlying storage device is a KVSSD. We test Dotori with an enterprise grade KVSSD against state-of-the-art block SSD based key-value stores through a range of micro-benchmarks and real world workloads. Despite low KVSSD raw device performance, Dotori achieves superior performance to these block-device based key-value stores while also showing significant gains in other important metrics.
A Design Space Exploration and Evaluation for Main-Memory Hash Joins in Storage Class Memory

In this paper, we seek to perform a rigorous experimental study of main-memory hash joins in storage class memory (SCM). In particular, we perform a design space exploration in real SCM for two state-of-the-art join algorithms: partitioned hash join (PHJ) and non-partitioned hash join (NPHJ), and identify the most crucial factors to implement an SCM-friendly join. Moreover, we present a rigorous evaluation with a broad spectrum of workloads for both joins and provide an in-depth analysis for choosing the most suitable algorithm in real SCM environment. With the most extensive experimental analysis up-to-date, we maintain that although there is no one universal winner in all scenarios, PHJ is generally superior to NPHJ in real SCM.
Lagrangian Dynamic Formulation of a Four-Bar Mechanism with Minimal Coordinates

This article describes the detailed steps in formulating the dynamic equation of a four-bar mechanism in the minimal coordinate form using Lagrangian formulation. It is well-known that a four-bar mechanism possesses one degree-of-freedom (d.o.f.), and, hence, ideally a single dynamic equation is su‐cient to completely describe the dynamics of the closed system. However, using only single coordinate to parameterize the entire system when constructing the dynamic equation tends to be a very tedious process, hence extra number of generalized coordinates are often introduced in order to simplify the modeling process. In this article, we show the systematic process of using the extra number of generalized coordinates to parameterize the conflguration of the closed system, and reducing the required coordinates to only one when formulating the dynamic equations in this case.
Wormhole for electron waves in graphene

The theory of transformation optics for light has fascinated the scientific community for almost one decade due to its revolutionary and groundbreaking implications. Because the propagation of electrons in condensed-matter systems is also described by a wave equation, one may also envision the extension of this idea to matter waves. Here, we suggest that graphene can be used as a platform to demonstrate a ``tunnel'' or ``wormhole'' for electrons. Based on an effective medium approach, we theoretically demonstrate that two properly designed graphene-based nanomaterials can effectively ``annihilate'' one another from an electronic point of view, and provide for the delocalization of the wave-function stationary states, similar to a wormhole.
When Database Meets New Storage Devices: Understanding and Exposing Performance Mismatches via Configurations

NVMe SSD hugely boosts the I/O speed, with up to GB/s throughput and microsecond-level latency. Unfortunately, DBMS users can often find their high-performanced storage devices tend to deliver less-than-expected or even worse performance when compared to their traditional peers. While many works focus on proposing new DBMS designs to fully exploit NVMe SSDs, few systematically study the symptoms, root causes and possible detection methods of such performance mismatches on existing databases. In this paper, we start with an empirical study where we systematically expose and analyze the performance mismatches on six popular databases via controlled configuration tuning. From the study, we find that all six databases can suffer from performance mismatches. Moreover, we conclude that the root causes can be categorized as databases' unawareness of new storage devices characteristics in I/O size, I/O parallelism and I/O sequentiality. We report 17 mismatches to developers and 15 are confirmed. Additionally, we realize testing all configuration knobs yields low efficiency. Therefore, we propose a fast performance mismatch detection framework and evaluation shows that our framework brings two orders of magnitude speedup than baseline without sacrificing effectiveness.
Relationship Between Alcohol Consumption and Risky Sexual Behaviors Among Adolescents and Young Adults: A Meta-Analysis

Objectives: Adolescents exposed to alcohol have increased risky sexual behaviors (RSBs); however, the association between alcohol consumption and RSBs has to be systematically and quantitatively reviewed. We conducted a meta-analysis of the literature to systematically and quantitatively review the association between alcohol consumption and RSBs in adolescents and young adults. Methods: We searched for qualified articles published from 2000 to 2020 and calculated pooled odds ratios (ORs) using the random-effect model. We also conducted meta-regression and sensitivity analyses to identify potential heterogeneity moderators. Results: The meta-analysis of 50 studies involving 465,595 adolescents and young adults indicated that alcohol consumption was significantly associated with early sexual initiation (OR = 1.958, 95% confidence interval (CI) = 1.635–2.346), inconsistent condom use (OR = 1.228, 95% CI = 1.114–1.354), and having multiple sexual partners (OR = 1.722, 95% CI = 1.525–1.945). Conclusion: Alcohol consumption is strongly associated with RSBs, including early sexual initiation, inconsistent condom use, and multiple sexual partners among adolescents and young adults. To prevent the adverse consequences of alcohol consumption, drinking prevention programs should be initiated at an early age and supported by homes, schools, and communities.
Gendered ethnic choice effects at the transition to upper secondary education in Switzerland

Positive ethnic choice effects, namely a higher likelihood of attending more demanding educational tracks among students of immigrant origin compared to their native peers, are observed in many countries. Immigrant optimism, and thus the striving for upward social mobility, is seen as a key mechanism for explaining ethnic choice effects. However, research on this topic often ignores gendered educational pathways and trajectories. Based on data from German-speaking Switzerland on two school-leaver cohorts, our interest is on whether ethnic choice effects are observable for both female and male students whose parents were born in the Balkans, Turkey or Portugal. In addition, we examine the extent to which aspirations contribute to explaining ethnic choice effects for both genders. To disentangle the direct effect of a migration background and the mediating effect of aspirations on educational attainment at upper secondary level, we apply the reformulated KHB method in our analyzes. Overall, our findings indicate that migrant women have made up ground on their native peers between the two school-leaving cohorts, contributing to the widening of the gender gap within the migrant group of interest. Of particular importance, however, is our finding that ethnic choice effects are observed only for men, while we do not observe any evidence of ethnic choice effects in the sample of women. Consistent with previous findings, our results show that aspirations mediate part of the ethnic choice effect. Our findings support the consideration that the room for ethnic choice effects is related to the proportion of young men and women striving for academic education, with gender differences in this regard being particularly pronounced in education systems with a high degree of vocational specificity.
GAP-43 closely interacts with BDNF in hippocampal neurons and is associated with Alzheimer's disease progression

Introduction Growth-associated protein 43 (GAP-43) is known as a neuronal plasticity protein because it is widely expressed at high levels in neuronal growth cones during axonal regeneration. GAP-43 expressed in mature adult neurons is functionally important for the neuronal communication of synapses in learning and memory. Brain-derived neurotrophic factor (BDNF) is closely related to neurodegeneration and synaptic plasticity during the aging process. However, the molecular mechanisms regulating neurodegeneration and synaptic plasticity underlying the pathogenesis and progression of Alzheimer's disease (AD) still remain incompletely understood. Methods Remarkably, the expressions of GAP-43 and BDNF perfectly match in various neurons in the Human Brain Atlas database. Moreover, GAP-43 and BDNF are highly expressed in a healthy adults' hippocampus brain region and are inversely correlated with the amyloid beta (Aβ), which is the pathological peptide of amyloid plaques found in the brains of patients with AD. Results These data led us to investigate the impact of the direct molecular interaction between GAP-43 and BDNF in hippocampal neuron fate. In this study, we show that GAP-43 and BDNF are inversely associated with pathological molecules for AD (Tau and Aβ). In addition, we define the three-dimensional protein structure for GAP-43 and BDNF, including the predictive direct binding sites via analysis using ClusPro 2.0, and demonstrate that the deprivation of GAP-43 and BDNF triggers hippocampal neuronal death and memory dysfunction, employing the GAP-43 or BDNF knock-down cellular models and 5XFAD mice. Conclusion These results show that GAP-43 and BDNF are direct binding partners in hippocampal neurons and that their molecular signaling might be potential therapeutic targets for AD.
Development and validation of a prognostic nomogram for rectal cancer patients who underwent surgical resection

Objective: The purpose of this study was to develop and validate a nomogram model for the prediction of survival outcome in rectal cancer patients who underwent surgical resection. Methods: A total of 9,919 consecutive patients were retrospectively identified using the Surveillance, Epidemiology, and End Results (SEER) database. Significant prognostic factors were determined by the univariate and multivariate Cox analysis. The nomogram model for the prediction of cancer-specific survival (CSS) in rectal cancer patients were developed based on these prognostic variables, and its predictive power was assessed by the concordance index (C-index). Calibration curves were plotted to evaluate the associations between predicted probabilities and actual observations. The internal and external cohort were used to further validate the predictive performance of the prognostic nomogram. Results: All patients from the SEER database were randomly split into a training cohort (n = 6,944) and an internal validation cohort (n = 2,975). The baseline characteristics of two cohorts was comparable. Independent prognostic factors were identified as age, pT stage, lymph node metastasis, serum CEA level, tumor size, differentiation type, perineural invasion, circumferential resection margin involvement and inadequate lymph node yield. In the training cohort, the C-index of the nomogram was 0.719 (95% CI: 0.696–0.742), which was significantly higher than that of the TNM staging system (C-index: 0.606, 95% CI: 0.583–0.629). The nomogram had a C-index of 0.726 (95% CI: 0.691–0.761) for the internal validation cohort, indicating a good predictive power. In addition, an independent cohort composed of 202 rectal cancer patients from our institution were enrolled as the external validation. Compared with the TNM staging system (C-index: 0.573, 95% CI: 0.492–0.654), the prognostic nomogram still showed a better predictive performance, with the C-index of 0.704 (95% CI: 0.626–0.782). Calibration plots showed a good consistency between predicted probability and the actual observation in the training and two validation cohorts. Conclusion: The nomogram showed an excellent predictive ability for survival outcome of rectal cancer patients, and it might provide an accurate prognostic stratification and help clinicians determine individualized treatment strategies.
The KDM5B and KDM1A lysine demethylases cooperate in regulating androgen receptor expression and signalling in prostate cancer

Histone H3 lysine 4 (H3K4) methylation is key epigenetic mark associated with active transcription and is a substrate for the KDM1A/LSD1 and KDM5B/JARID1B lysine demethylases. Increased expression of KDM1A and KDM5B is implicated in many cancer types, including prostate cancer (PCa). Both KDM1A and KDM5B interact with AR and promote androgen regulated gene expression. For this reason, there is great interested in the development of new therapies targeting KDM1A and KDM5B, particularly in the context of castrate resistant PCa (CRPC), where conventional androgen deprivation therapies and androgen receptor signalling inhibitors are no longer effective. As there is no curative therapy for CRPC, new approaches are urgently required to suppress androgen signalling that prevent, delay or reverse progression to the castrate resistant state. While the contribution of KDM1A to PCa is well established, the exact contribution of KDM5B to PCa is less well understood. However, there is evidence that KDM5B is implicated in numerous pro-oncogenic mechanisms in many different types of cancer, including the hypoxic response, immune evasion and PI3/AKT signalling. Here we elucidate the individual and cooperative functions of KDM1A and KDM5B in PCa. We show that KDM5B mRNA and protein expression is elevated in localised and advanced PCa. We show that the KDM5 inhibitor, CPI-455, impairs androgen regulated transcription and alternative splicing. Consistent with the established role of KDM1A and KDM5B as AR coregulators, we found that individual pharmacologic inhibition of KDM1A and KDM5 by namoline and CPI-455 respectively, impairs androgen regulated transcription. Notably, combined inhibition of KDM1A and KDM5 downregulates AR expression in CRPC cells. Furthermore, combined KDM1A and KDM5 inhibition impairs PCa cell proliferation and invasion more than individual inhibition of KDM1A and KDM5B. Collectively our study has identified individual and cooperative mechanisms involving KDM1A and KDM5 in androgen signalling in PCa. Our findings support the further development of KDM1A and KDM5B inhibitors to treat advanced PCa. Further work is now required to confirm the therapeutic feasibility of combined inhibition of KDM1A and KDM5B as a novel therapeutic strategy for targeting AR positive CRPC.
Population analysis and the effects of Gaussian basis set quality and quantum mechanical approach: main group through heavy element species

Atomic charge and its distribution across molecules provide important insight into chemical behavior. Though there are many studies on various routes for the determination of atomic charge, there are few studies that examine the broader impact of basis set and quantum method used over many types of population analysis methods across the periodic table. Largely, such a study of population analysis has focused on main-group species. In this work, atomic charges were calculated using several population analysis methods including orbital-based methods (Mulliken, Löwdin, and Natural Population Analysis), volume-based methods (Atoms-in-Molecules (AIM) and Hirshfeld), and potential derived charges (CHELP, CHELPG, and Merz-Kollman). The impact of basis set and quantum mechanical method choices upon population analysis has been considered. The basis sets utilized include Pople (6-21G**, 6-31G**, 6-311G**) and Dunning (cc-pVnZ, aug-cc-pVnZ; n = D, T, Q, 5) basis sets for main group molecules. For the transition metal and heavy element species examined, relativistic forms of the correlation consistent basis sets were used. This is the first time the cc-pVnZ-DK3 and cc-pwCVnZ-DK3 basis sets have been examined with respect to their behavior across all levels of basis sets for atomic charges for an actinide. The quantum methods chosen include two density functional (PBE0 and B3LYP), Hartree-Fock, and second-order Møller-Plesset perturbation theory (MP2) approaches.
Add-on effect of the Guizhi Fuling formula for management of reduced fertility potential in women with polycystic ovary syndrome: A systematic review and meta-analysis of randomized controlled trials

Background Guizhi Fuling (GZFL) pill, a traditional Chinese herbal formula including Semen Persicae, Ramulus Cinnamomi, Poria, Radix Paeoniae Alba, and Cortex Moutan, has been widely applied in the management of gynecological diseases. Objective To evaluate the add-on effect of the GZFL formula for treating reduced fertility potential in women with polycystic ovary syndrome (PCOS) by conducting a systematic review and meta-analysis. Methods Two reviewers independently searched the PubMed, Embase, Cochrane Library, Wanfang, SinoMed, and CKNI databases until 09/11/2022. Eligible studies were randomized controlled trials (RCTs) of the GZFL formula plus Western medicine versus the Western medicine for treating PCOS. The primary endpoint was the ovulation, pregnancy, and miscarriage rate. The secondary endpoints included the serum follicle-stimulating hormone (FSH), total testosterone, luteinizing hormone (LH), estradiol, and homeostasis model assessment insulin resistance (HOMA-IR). Results There were 16 RCTs with 1,385 patients identified. The GZFL formula plus Western medicine significantly improved the ovulation rate (risk ratios [RR] 1.24; 95% confidence intervals [CI] 1.15–1.34) and pregnancy rate (RR 1.53; 95% CI 1.38 to 1.69) than the Western medicine alone. Adjuvant treatment with the GZFL formula also significantly decreased the serum FSH (mean difference [MD] -0.48 U/l; 95% CI -0.80 to -0.15), total testosterone (standard mean difference [SMD] -1.07; 95% CI -1.71 to -0.44), LH level (MD -2.19 U/l; 95% CI -3.04 to -1.34), and HOMA-IR (MD -0.47; 95% CI -0.60 to -0.34). However, there was no significant difference in the miscarriage rate (RR 0.89; 95% CI 0.36–2.20) and serum estradiol level (SMD 0.34; 95% CI -0.25 to 0.94) between two groups. Conclusions The GZFL formula as adjuvant therapy can improve the ovulation and pregnancy rates in women with PCOS. Its beneficial effects may correlate with reducing FSH, total testosterone, and LH and ameliorating insulin resistance. However, more well-designed RCTs with larger samples and multicenter trials are required to confirm the current findings due to uncertainty of the evidence. Systematic review registration PROSPERO identifier, CRD42022354530.