Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of KRAS Mutation Subtypes in Non–small Cell Lung Cancer

KRAS is the most commonly mutated oncogene in NSCLC and development of direct KRAS inhibitors has renewed interest in this molecular variant. Different KRAS mutations may represent a unique biologic context with different prognostic and therapeutic impact. We sought to characterize genomic landscapes of advanced, KRAS-mutated non–small cell lung cancer (NSCLC) in a large national cohort to help guide future therapeutic development. Molecular profiles of 17,095 NSCLC specimens were obtained using DNA next-generation sequencing of 592 genes (Caris Life Sciences) and classified on the basis of presence and subtype of KRAS mutations. Co-occurring genomic alterations, tumor mutational burden (TMB), and PD-L1 expression [22C3, tumor proportion score (TPS) score] were analyzed by KRAS mutation type. Across the cohort, 4,706 (27.5%) samples harbored a KRAS mutation. The most common subtype was G12C (40%), followed by G12V (19%) and G12D (15%). The prevalence of KRAS mutations was 37.2% among adenocarcinomas and 4.4% in squamous cell carcinomas. Rates of high TMB (≥10 mutations/Mb) and PD-L1 expression varied across KRAS mutation subtypes. KRAS G12C was the most likely to be PD-L1 positive (65.5% TPS ≥ 1%) and PD-L1 high (41.3% TPS ≥ 50%). STK11 was mutated in 8.6% of KRAS wild-type NSCLC but more frequent in KRAS-mutant NSCLC, with the highest rate in G13 (36.2%). TP53 mutations were more frequent in KRAS wild-type NSCLC (73.6%). KRAS mutation subtypes have different co-occurring mutations and a distinct genomic landscape. The clinical relevance of these differences in the context of specific therapeutic interventions warrants investigation.
Targeting Tumor–Stromal IL6/STAT3 Signaling through IL1 Receptor Inhibition in Pancreatic Cancer

A hallmark of pancreatic ductal adenocarcinoma (PDAC) is the presence of a dense, desmoplastic stroma and the consequent altered interactions between cancer cells and their surrounding tumor microenvironment (TME) that promote disease progression, metastasis, and chemoresistance. We have previously shown that IL6 secreted from pancreatic stellate cells (PSC) stimulates the activation of STAT3 signaling in tumor cells, an established mechanism of therapeutic resistance in PDAC. We have now identified the tumor cell–derived cytokine IL1α as an upstream mediator of IL6 release from PSCs that is involved in STAT3 activation within the TME. Herein, we show that IL1α is overexpressed in both murine and human PDAC tumors and engages with its cognate receptor IL1R1, which is strongly expressed on stromal cells. Further, we show that IL1R1 inhibition using anakinra (recombinant IL1 receptor antagonist) significantly reduces stromal-derived IL6, thereby suppressing IL6-dependent STAT3 activation in human PDAC cell lines. Anakinra treatment results in significant reduction in IL6 and activated STAT3 levels in pancreatic tumors from Ptf1aCre/+;LSL-KrasG12D/+; Tgfbr2flox/flox (PKT) mice. Additionally, the combination of anakinra with cytotoxic chemotherapy significantly extends overall survival compared with vehicle treatment or anakinra monotherapy in this aggressive genetic mouse model of PDAC. These data highlight the importance of IL1 in mediating tumor–stromal IL6/STAT3 cross-talk in the TME and provide a preclinical rationale for targeting IL1 signaling as a therapeutic strategy in PDAC.
Elevated Neutrophil-to-Lymphocyte Ratio in Perioperative Periods is Suggestive of Poor Prognosis in Patients with Colorectal Cancer

Background Recent data suggest that alterations in the neutrophil-to-lymphocyte ratio (NLR) in the perioperative periods can serve as prognostic factors. However, research on the clinical impact has been limited and even discordant in patients with colorectal cancer (CRC). Patients and Methods The optimal cut-off value of preoperative NLR (NLR-pre), postoperative NLR (NLR-post), and its change (NLR-delta) were determined to maximize differences in overall survival (OS) between groups. Patients were categorized into four groups (NLR-trend) as follows: G1, low NLR-pre and NLR-post; G2, low NLR-pre and high NLR-post; G3, high NLR-pre and low NLR-post; and G4, high NLR-pre and NLR-post. Discriminatory performance was compared using integrated AUC (iAUC) between all indicators. Results A total of 576 patients diagnosed with stage I–IV CRC were included. The cut-off points were determined as 2.33 for NLR-pre, 2.06 for NLR-post, and −1.08 for NLR-delta. Subgroup dichotomization using NLR-pre, NLR-post, NLR-delta and NLR-trend were all identified as significant prognostic factors by univariate analysis. However, NLR-trend was only remained as an independent prognostic factor in the multivariate analysis. The iAUC of the NLR-trend was superior to that of NLR-pre (bootstrap iAUC mean difference=0.036; 95% CI 0.013–0.073), NLR-post (bootstrap iAUC mean difference=0.045; 95% CI 0.019–0.081) and NLR-delta (bootstrap iAUC mean difference=0.061; 95% CI 0.025–0.104). Conclusion Risk stratification and combining of preoperative and postoperative NLR (NLR-trend) can improve prognostic discrimination compared with single measurements or simple changes in NLR in patients with CRC.
AnnaBellaDB: a key value store for stateless network functions

The cloud-native paradigm has become a widely applied approach to ensure elasticity and reliability of applications running in the cloud. One recurrent motif is the stateless design of applications, which aims to decouple the life-cycle of application states from the life-cycle of individual application instances. Application data is written to and read from cloud databases, deployed close to the application code to ensure low latency bounds on state access. When applying a stateless design, the performance of the cloud service is often limited by the cloud database. In order not to become a bottleneck, database instances are distributed on multiple hosts, and strive to ensure data locality for all application instances. However, the shared nature of certain states, and the inevitable dynamics of the application workload necessarily lead to inter-host data access within the data center or even across data centers and edge servers, if the service is geographically distributed. To minimize the service performance loss due to the stateless design of applications, we propose a latency and access pattern aware state storage design and adapt it to Anna, a key-value store from academia to showcase a proof-of-concept that is ideal to store network function states. To foster further research in this area, we make our solution open-source.
Higher Trimethylamine-N-Oxide Plasma Levels with Increasing Age Are Mediated by Diet and Trimethylamine-Forming Bacteria

Many cohort studies have investigated the link between diet and plasma TMAO levels, reporting incongruent results, while gut microbiota were only recently included into analyses. In these studies, taxonomic data were recorded that are not a good proxy for TMA formation, as specific members of various taxa exhibit genes catalyzing this reaction, demanding function-based technologies for accurate quantification of TMA-synthesizing bacteria. ABSTRACT The gut microbiota-dependent metabolite trimethylamine-N-oxide (TMAO) is linked to an increased risk for cardiovascular diseases. Trimethylamine (TMA), which is subsequently oxidized to TMAO in the liver, is formed by intestinal bacteria via distinct biochemical routes from dietary precursors that are enriched in animal product-based foods. To get a full picture of the entire process of the diet > gut microbiota > TMAO axis, we quantified potential TMA-forming gut bacteria and plasma metabolites using gene-targeted assays and targeted metabolomics on a subsample (n = 425) of a German population-based cohort study. We specifically compared persons reporting daily meat intake with those that rarely or never consume meat. While meat intake did not predict TMAO plasma levels in our study, two major bacterial TMA-forming pathways were linked to the metabolite’s concentration. Furthermore, advancing age was strongly associated with TMAO. Construction of a structural equation model allowed us to disentangle the different routes that promote higher TMAO levels with increasing age, demonstrating, for the first time, a functional role of gut microbiota in the process, where specific food items augmented abundances of TMA-forming bacteria that were associated with higher TMAO plasma concentrations. Analyses stratified by age showed an association between carotid intima-media thickness and TMAO only in individuals >65 of age, indicating that this group is particularly affected by the metabolite. IMPORTANCE Many cohort studies have investigated the link between diet and plasma TMAO levels, reporting incongruent results, while gut microbiota were only recently included into analyses. In these studies, taxonomic data were recorded that are not a good proxy for TMA formation, as specific members of various taxa exhibit genes catalyzing this reaction, demanding function-based technologies for accurate quantification of TMA-synthesizing bacteria. Using this approach, we demonstrated that abundances of the main components leading to TMAO formation, i.e., TMA precursors and TMA-forming bacteria, are uncoupled and not governed by the same (dietary) factors. Results emphasize that all levels leading to TMA(O) formation should be considered for accurate risk assessment, rejecting the simple view that diets rich in TMA precursors directly lead to increased plasma levels of this hazardous compound. The results can assist in developing strategies to reduce TMAO levels, specifically in the elderly, who are prone to TMAO-associated diseases.
Preparation method of vinorelbine

The invention belongs to the field of pharmaceutical synthesis, and provides a novel method used for synthesizing vinorelbine tartrate. According to the novel method, catharanthine tartrate and vindoline are taken as initial raw materials, vinorelbine crude products are obtained via a two-step one-pot procedure reaction instead of an original four-step reaction, synthesis steps are simplified, and yield is increased. The vinorelbine crude products are subjected to normal phase silica gel column purification and reverse phase silica gel column purification, so that purity of obtained vinorelbine purified products is increased substantially; and at the same time, increasing of vinorelbine purity possesses significant influences on salifying effects of vinorelbine with tartaric acid, so that after recrystallization, purity of the obtained vinorelbine tartrate is higher than 99.5%, and accords with requirements of United States Pharmacopeia; competitive advantage is more excellent; all of the operation processes are normal operation processes; and it is more beneficial for industrialized production.
Proteomic Profiling of Extracellular Vesicles Separated from Plasma of Former National Football League Players at Risk for Chronic Traumatic Encephalopathy

Chronic Traumatic Encephalopathy (CTE) is a tauopathy that affects individuals with a history of exposure to repetitive head impacts, including National Football League (NFL) players. Extracellular vesicles (EVs) are known to carry tau in Alzheimer’s disease and other tauopathies. We examined protein profiles of EVs separated from the plasma of former NFL players at risk for CTE. EVs were separated from the plasma from former NFL players and age-matched controls using size-exclusion chromatography. Label-free quantitative proteomic analysis identified 675 proteins in plasma EVs, and 17 proteins were significantly differentially expressed between former NFL players and controls. Total tau (t-tau) and tau phosphorylated at threonie181 (p-tau181) in plasma-derived EVs were measured by ultrasensitive immunoassay. Level of t-tau and p-tau181 in EVs were significantly different, and the area under the receiver operating characteristic curve (AUC) of t-tau and p-tau181 showed 0.736 and 0.715, respectively. Machine learning analysis indicated that a combination of collagen type VI alpha 3 and 1 chain (COL6A3 and COL6A1) and reelin (RELN) can distinguish former NFL players from controls with 85% accuracy (AUC = 0.85). Based on the plasma EV proteomics, these data provide protein profiling of plasma EVs for CTE, and indicate combination of COL6A3, RELN and COL6A1 in plasma EVs may serve as the potential diagnostic biomarkers for CTE.
Thailand’s Private Vocational College Administrator’s Competencies in the 21st Century

This article is intended to present an analysis of Thailand’s Private Vocational College Administrator’s Competencies in the 21st Century that affecting to the effectiveness of educational administration in Private Vocational College in Thailand. The analysis found that the competencies of Thailand’s Private Vocational College Administrator’s Competencies in the 21st Century consisted of 6 factors: Results-Based Management (RBM); Teamwork; Transformational leadership; Synthetic analytical thinking; Personnel potential development and Moral and ethical aspects.
The inhibitory role of synthesized Nickel oxide nanoparticles against Hep-G2, MCF-7, and HT-29 cell lines: the inhibitory role of NiO NPs against Hep-G2, MCF-7, and HT-29 cell lines

ABSTRACT Nickel oxide nanoparticles (NiO NPs) were synthesized via the facile sol–gel method. The synthesized NiO NPs were characterized using X-ray diffraction (XRD), Field-Emission Scanning Electron Microscopy (FESEM), Transmission Electron Microscopy (TEM), Raman and Fourier Transform Infrared (FT-IR) techniques. The effect of particle size was analyzed on structural alterations, electrochemical behaviors, and cytotoxic effect of synthesized NiO NPs. According to TEM results, the particle sizes of synthesized NiO NPs were 8.2, 15.4, and 21.7 nm at 300, 400, and 500 °C, respectively. Electrochemical behaviors of synthesized NiO NPs were assessed through the cyclic voltammetry (CV) technique. The results showed that the magnitude of the current density was decreased in treated samples exposed to higher temperature values. The cytotoxic activity of synthesized nanoparticles was investigated against human liver cancer cell (Hep-G2), breast cancer cell (MCF-7), and colon cancer cell (HT-29) lines using the MTT assay. The results demonstrated that synthesized NiO NPs had higher cytotoxicity at 300 °C than at 400 and 500 °C, because of their small particle size. Thus, synthesized NiO NPs exhibit acceptable cytotoxic effects against Hep-G2, MCF-7, and HT-29 cancer cell lines so that they could be a good choice for cancer treatment. GRAPHICAL ABSTRACT
A City-Wide Crowdsourcing Delivery System with Reinforcement Learning

The revolution of online shopping in recent years demands corresponding evolution in delivery services in urban areas. To cater to this trend, delivery by the crowd has become an alternative to the traditional delivery services thanks to the advances in ubiquitous computing. Notably, some studies use public transportation for crowdsourcing delivery, given its low-cost delivery network with millions of passengers as potential couriers. However, multiple practical impact factors are not considered in existing public-transport-based crowdsourcing delivery studies due to a lack of data and limited ubiquitous computing infrastructures in the past. In this work, we design a crowdsourcing delivery system based on public transport, considering the practical factors of time constraints, multi-hop delivery, and profits. To incorporate the impact factors, we build a reinforcement learning model to learn the optimal order dispatching strategies from massive passenger data and package data. The order dispatching problem is formulated as a sequential decision making problem for the packages routing, i.e., select the next station for the package. A delivery time estimation module is designed to accelerate the training process and provide statistical delivery time guarantee. Three months of real-world public transportation data and one month of package delivery data from an on-demand delivery platform in Shenzhen are used in the evaluation. Compared with existing crowdsourcing delivery algorithms and widely used baselines, we achieve a 40% increase in profit rates and a 29% increase in delivery rates. Comparison with other reinforcement learning algorithms shows that we can improve the profit rate and the delivery rate by 9% and 8% by using time estimation in action filtering. We share the data used in the project to the community for other researchers to validate our results and conduct further research.1 [1].
A sociocultural norm perspective on Big Five prediction.

The Big Five predict numerous preferences, decisions, and behaviors-but why? To help answer this key question, the present research develops the sociocultural norm perspective (SNP) on Big Five prediction-a critical revision and extension of the sociocultural motives perspective. The SNP states: Agreeableness, Extraversion, and Conscientiousness predict outcomes positively if those outcomes are socioculturally normative. Openness, by contrast, predicts outcomes negatively if they are socioculturally normative. Moreover, the SNP specifies unique mechanisms that underlie those predictions. Two mechanisms are social (social trust for Agreeableness, social attention for Extraversion) and two are cognitive (rational thought for Conscientiousness, independent thought for Openness). The present research develops the SNP by means of three large-scale experiments (Ntotal = 7,404), which used a new, tailor-made experimental paradigm-the minimal norm paradigm. Overall, the SNP provides norm-based, culture-focused, and mechanism-attentive explanations for why the Big Five predict their outcomes. The SNP also has broader relevance: It helps explain why Big Five effects vary across cultures and, thus, dispels the view that such variation threatens the validity of the Big Five. It suggests that the psychology of norms would benefit from attention to the Big Five. Finally, it helps bridge personality, social, and cross-cultural psychology by integrating their key concepts-the Big Five, conformity, and sociocultural norms. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Alternative Approaches to Ensuring Adequate Nurse Staffing

Supplemental Digital Content is available in the text. Objective: The objective of this study was to addresses the basic question of whether alternative legislative approaches are effective in encouraging hospitals to increase nurse staffing. Methods: Using 16 years of nationally representative hospital-level data from the American Hospital Association (AHA) annual survey, we employed a difference-in-difference design to compare changes in productive hours per patient day for registered nurses (RNs), licensed practical/vocational nurses (LPNs), and nursing assistive personnel (NAP) in the state that mandated staffing ratios, states that legislated staffing committees, and states that legislated public reporting, to changes in states that did not implement any nurse staffing legislation before and after the legislation was implemented. We constructed multivariate linear regression models to assess the effects with hospital and year fixed effects, controlling for hospital-level characteristics and state-level factors. Results: Compared with states with no legislation, the state that legislated minimum staffing ratios had an 0.996 (P<0.01) increase in RN hours per patient day and 0.224 (P<0.01) increase in NAP hours after the legislation was implemented, but no statistically significant changes in RN or NAP hours were found in states that legislated a staffing committee or public reporting. The staffing committee approach had a negative effect on LPN hours (difference-in-difference=−0.076, P<0.01), while the public reporting approach had a positive effect on LPN hours (difference-in-difference=0.115, P<0.01). There was no statistically significant effect of staffing mandate on LPN hours. Conclusions: When we included California in the comparison, our model suggests that neither the staffing committee nor the public reporting approach alone are effective in increasing hospital RN staffing, although the public reporting approach appeared to have a positive effect on LPN staffing. When we excluded California form the model, public reporting also had a positive effect on RN staffing. Future research should examine patient outcomes associated with these policies, as well as potential cost savings for hospitals from reduced nurse turnover rates.
Clinical and genetic spectra of autosomal dominant tubulointerstitial kidney disease

Abstract Autosomal dominant tubulointerstitial kidney disease (ADTKD) is a clinical entity defined by interstitial fibrosis with tubular damage, bland urinalysis and progressive kidney disease. Mutations in UMOD and MUC1 are the most common causes of ADTKD but other rarer (REN, SEC61A1), atypical (DNAJB11) or heterogeneous (HNF1B) subtypes have been described. Raised awareness, as well as the implementation of next-generation sequencing approaches, have led to a sharp increase in reported cases. ADTKD is now believed to be one of the most common monogenic forms of kidney disease and overall it probably accounts for ∼5% of all monogenic causes of chronic kidney disease. Through international efforts and systematic analyses of patient cohorts, critical insights into clinical and genetic spectra of ADTKD, genotype–phenotype correlations as well as innovative diagnostic approaches have been amassed during recent years. In addition, intense research efforts are addressed towards deciphering and rescuing the cellular pathways activated in ADTKD. A better understanding of these diseases and of possible commonalities with more common causes of kidney disease may be relevant to understand and target mechanisms leading to fibrotic kidney disease in general. Here we highlight recent advances in our understanding of the different subtypes of ADTKD with an emphasis on the molecular underpinnings and its clinical presentations.
Prevalence and associations of COVID-19 testing in an online sample of transgender and non-binary individuals

Background Testing for COVID-19 and linkage to services is fundamental to successful containment and control of transmission. Yet, knowledge on COVID-19 testing among transgender and non-binary communities remains limited. Methods Between October 2020 and November 2020, we examined the prevalence and associations of COVID-19 testing in an online sample of transgender and non-binary people (n=536). Multivariable hierarchical logistic regression analyses examined associations between COVID-19 testing and participants’ sociodemographic, mental health, substance use, gender affirmation, economic changes and healthcare experiences. Results Prevalence of COVID-19 testing in this sample was 35.5% (n=190/536). In the final model, transgender and non-binary participants from upper socioeconomic income background and Europe, who reported having active alcohol use disorder, limited access to gender-affirming surgery, had more than 20% reduction in income, and experienced mistreatment in a health facility due to gender identity had significantly increased odds of COVID-19 testing (all p<0.05); those who reported recent tobacco use had significantly lower odds of COVID-19 testing (p=0.007). Conclusions These findings highlight structural disparities in COVID-19 testing and reinforce the importance of increasing testing strategies for transgender and non-binary populations.