Multiple Types Research Articles

Organizing logic multiplicity in hybrid organizations: The role of organizational culture

AbstractHybrid organizations must deal with institutional complexity and find ways to manage conflicting demands in their organizational environment to engage in their required, day‐to‐day activities. The objective of this qualitative research is to elaborate on the mechanisms that hybrid organizations use to mitigate the destabilizing effects of such institutional logic multiplicity in their value creation processes. By combining value configuration analyses and the hybrid organizing concept as a theoretical background, the authors conduct a case study with 14 nonprofit microfinance organizations (MFOs) that illustrates the importance of an integrative organizational culture as a core foundation that can align and integrate social and economic demands. Successful nonprofit MFOs align competing institutional logics in a hierarchy of goals, explicitly defining their means and objectives. Independent of the type of logic multiplicity they face, they use the hierarchy to define their organizational identity and transfer it to a corresponding organizational culture that can balance diverse institutional demands. From a theoretical perspective, this study advances institutional logic approaches; it also identifies effective mechanisms hybrid organizations can use to cope with logic multiplicity by applying a value configuration perspective.

SaLTy: a novel Staphylococcus aureus Lineage Typer.

Staphylococcus aureus asymptomatically colonises 30 % of humans but can also cause a range of diseases, which can be fatal. In 2017 S. aureus was associated with 20 000 deaths in the USA alone. Dividing S. aureus isolates into smaller sub-groups can reveal the emergence of distinct sub-populations with varying potential to cause infections. Despite multiple molecular typing methods categorising such sub-groups, they do not take full advantage of S. aureus genome sequences when describing the fundamental population structure of the species. In this study, we developed Staphylococcus aureus Lineage Typing (SaLTy), which rapidly divides the species into 61 phylogenetically congruent lineages. Alleles of three core genes were identified that uniquely define the 61 lineages and were used for SaLTy typing. SaLTy was validated on 5000 genomes and 99.12 % (4956/5000) of isolates were assigned the correct lineage. We compared SaLTy lineages to previously calculated clonal complexes (CCs) from BIGSdb (n=21 173). SALTy improves on CCs by grouping isolates congruently with phylogenetic structure. SaLTy lineages were further used to describe the carriage of Staphylococcal chromosomal cassette containing mecA (SCCmec) which is carried by methicillin-resistant S. aureus (MRSA). Most lineages had isolates lacking SCCmec and the four largest lineages varied in SCCmec over time. Classifying isolates into SaLTy lineages, which were further SCCmec typed, allowed SaLTy to describe high-level MRSA epidemiology. We provide SaLTy as a simple typing method that defines phylogenetic lineages (https://github.com/LanLab/SaLTy). SaLTy is highly accurate and can quickly analyse large amounts of S. aureus genome data. SaLTy will aid the characterisation of S. aureus populations and ongoing surveillance of sub-groups that threaten human health.

Crash modification factors for high friction surface treatment on horizontal curves of two-lane highways: A combined propensity scores matching and empirical Bayes before-after approach

Horizontal curves are locations that, as a result of the changing alignment, may be a contributing factor in roadway departure crashes. One low-cost countermeasure to mitigate crashes at these locations is the installation of the high friction surface treatment (HFST), which increases roadway friction and is intended to help keep drivers on the roadway when traversing a horizontal curve. This treatment has been implemented at numerous curves in Pennsylvania, but the overall safety effectiveness is not known. The purpose of this study is to estimate a suite of Crash Modification Factors (CMFs) for HFST applied to curve sections of undivided two-lane roadways. A novel combination of the empirical Bayes observational before-after study design and propensity score matching was used to estimate CMFs for multiple crash types, crash severities, and roadway settings (urban and rural). Propensity score matching was implemented to identify the most appropriate reference group to use within the empirical Bayes methodology. The results indicate that the installation of HFST is associated with a statistically significant decrease in all crash types and severities considered.

The Impact of Adversarial Attacks on Federated Learning: A Survey.

Federated learning (FL) has emerged as a powerful machine learning technique that enables the development of models from decentralized data sources. However, the decentralized nature of FL makes it vulnerable to adversarial attacks. In this survey, we provide a comprehensive overview of the impact of malicious attacks on FL by covering various aspects such as attack budget, visibility, and generalizability, among others. Previous surveys have primarily focused on the multiple types of attacks and defenses but failed to consider the impact of these attacks in terms of their budget, visibility, and generalizability. This survey aims to fill this gap by providing a comprehensive understanding of the attacks' effect by identifying FL attacks with low budgets, low visibility, and high impact. Additionally, we address the recent advancements in the field of adversarial defenses in FL and highlight the challenges in securing FL. The contribution of this survey is threefold: first, it provides a comprehensive and up-to-date overview of the current state of FL attacks and defenses. Second, it highlights the critical importance of considering the impact, budget, and visibility of FL attacks. Finally, we provide ten case studies and potential future directions towards improving the security and privacy of FL systems.

Molecular epidemiology and molecular typing methods of Acinetobacter baumannii: An updated review.

The aim of this study was to go through the molecular methods used for typing of carbapenem-resistant Acientobacter baumannii (CRAB) isolates for investigating the molecular epidemiology all over the world. Multiple typing techniques are required to understand the source and nature of outbreaks caused by Acientobacter baumannii (A. baumannii) and acquired resistance to antimicrobials. Nowadays, there is gradual shift from traditional typing methods to modern molecular methods to study molecular epidemiology and infection control. Molecular typing of A. baumannii strains has been revolutionized significantly in the last 2 decades. A few sequencing-based techniques have been proven as a breakthrough and opened new prospects, which have not been achieved by the traditional methods. In this review, discussed different pre-existing and recently used typing methods to explore the molecular epidemiology of A. baumannii pertaining in context with human infections.

Critical points with prescribed energy for a class of functionals depending on a parameter: existence, multiplicity and bifurcation results

We look for critical points with prescribed energy for the family of even functionals Φμ=I1−μI2 , where I1,I2 are C 1 functionals on a Banach space X, and μ∈R . For a given c∈R and several classes of Φμ , we prove the existence of infinitely many couples (μn,c,un,c) such that Φμn,c′(±un,c)=0andΦμn,c(±un,c)=c∀n∈N. More generally, we analyse the structure of the solution set of the problem Φμ′(u)=0,Φμ(u)=c with respect to µ and c. In particular, we show that the maps c↦μn,c are continuous, which gives rise to a family of energy curves for this problem. The analysis of these curves provide us with several bifurcation and multiplicity type results, which are then applied to some elliptic problems. Our approach is based on the nonlinear generalized Rayleigh quotient method developed in Il’yasov (2017 Topol. Methods Nonlinear Anal. 49 683–714).

Advances in Genetic Reprogramming: Prospects from Developmental Biology to Regenerative Medicine.

The foundations of cell reprogramming were laid by Yamanaka and co-workers, who showed that somatic cells can be reprogrammed into pluripotent cells (induced pluripotency). Since this discovery, the field of regenerative medicine has seen advancements. For example, because they can differentiate into multiple cell types, pluripotent stem cells are considered vital components in regenerative medicine aimed at the functional restoration of damaged tissue. Despite years of research, both replacement and restoration of failed organs/tissues have remained elusive scientific feats. However, with the inception of cell engineering and nuclear reprogramming, useful solutions have been identified to counter the need for compatible and sustainable organs. By combining the science underlying genetic engineering and nuclear reprogramming with regenerative medicine, scientists have engineered cells to make gene and stem cell therapies applicable and effective. These approaches have enabled the targeting of various pathways to reprogramme cells, i.e., make them behave in beneficial ways in a patient-specific manner. Technological advancements have clearly supported the concept and realization of regenerative medicine. Genetic engineering is used for tissue engineering and nuclear reprogramming and has led to advances in regenerative medicine. Targeted therapies and replacement of traumatized, damaged, or aged organs can be realized through genetic engineering. Furthermore, the success of these therapies has been validated through thousands of clinical trials. Scientists are currently evaluating induced tissue-specific stem cells (iTSCs), which may lead to tumour-free applications of pluripotency induction. In this review, we present state-of-the-art genetic engineering that has been used in regenerative medicine. We also focus on ways that genetic engineering and nuclear reprogramming have transformed regenerative medicine and have become unique therapeutic niches.

Unified Fuzzy Control of High-Order Nonlinear Systems With Multitype State Constraints.

This article presents a unified adaptive fuzzy control approach for high-order nonlinear systems (HONSs) with multitype state constraints. Existing methods always require the upper and lower constraint boundaries are strictly positive and negative functions (or constants), respectively, which is often inconsistent with the actual constraints. In this article, "multitype state constraint" means that the upper and lower constraint boundaries include multiple types, such as both being strictly positive (or negative), sometime be positive or negative, and so on (cases ①-⑥). By designing a unified mapping function (UMF), the multitype state constraints are processed under removal the feasibility conditions (FCs). Furthermore, a technical design makes the proposed method also applicable to unconstrained HONSs without changing the control structure. By means of a fuzzy-logic system (FLS) and fixed-time stability theory (FTST), the proposed algorithm can ensure that the tracking error converges to a zero-centered neighborhood within a fixed time, and the singularity which often appears in the existing fixed-time control (FTC) methods of HONSs is effectively avoided. Simulation results demonstrate the scheme developed.

Enhanced Insurance Risk Assessment using Discrete Four-Variate Sarmanov Distributions and Generalized Linear Models

This research paper investigated multivariate risk assessment in insurance, focusing on four risks of a singular person and their interdependence. This research examined various risk indicators in non-life insurance which was under-writing for organizations with clients that purchase several non-life insurance policies. The risk indicators are probabilities of frequency claims and correlations of two risk lines. The closed forms of probability mass functions evaluated the probabilities of frequency claims. Three generalized linear models of four-variate Sarmanov distributions were proposed for marginals, incorporating various characteristics of policyholders using explanatory variables. All three models were discrete models that were a combination of Poisson and Gamma distributions. Some properties of four-variate Sarmanov distributions were explicitly shown in closed forms. The dataset spanned a decade and included the exposure of each individual to risk over an extended period. The correlations between the two risk types were evaluated in several statistical ways. The parameters of the three Sarmanov model distributions were estimated using the maximum likelihood method, while the results of the three models were compared with a simpler four-variate negative binomial generalized linear model. The research findings showed that Model 3 was the most accurate of all three models since the AIC and BIC were the lowest. In terms of the correlation, it was found that the risk of claiming auto insurances was related to claiming home insurances. Model 1 could be used for the risk assessment of an insurance company that had customers who held multiple types of insurances in order to predict the risks that may occur in the future. When the insurance company can forecast the risks that may occur in the future, the company will be able to calculate appropriate insurance premiums.

The Next Era of Assessment: Can Ensuring High-Quality, Equitable Patient Care Be the Defining Characteristic?

Previous eras of assessment in medical education have been defined by how assessment is done, from knowledge exams popularized in the 1960s to the emergence of work-based assessment in the 1990s to current efforts to integrate multiple types and sources of performance data through programmatic assessment. Each of these eras was a response to why assessment was performed (e.g., assessing medical knowledge with exams; assessing communication, professionalism, and systems competencies with work-based assessment). Despite the evolution of assessment eras, current evidence highlights the graduation of trainees with foundational gaps in the ability to provide high-quality care to patients presenting with common problems, and training program leaders report they graduate trainees they would not trust to care for themselves or their loved ones. In this article, the authors argue that the next era of assessment should be defined by why assessment is done: to ensure high-quality, equitable care. Assessment should place focus on demanding graduates possess the knowledge, skills, attitudes, and adaptive expertise to meet the needs of all patients and ensuring that graduates are able to do this in an equitable fashion. The authors explore 2 patient-focused assessment approaches that could help realize the promise of this envisioned era: entrustable professional activities (EPAs) and resident sensitive quality measures (RSQMs)/TRainee Attributable and Automatable Care Evaluations in Real-time (TRACERs). These examples illustrate how the envisioned next era of assessment can leverage existing and new data to provide precision education assessment that focuses on providing formative and summative feedback to trainees in a manner that seeks to ensure their learning outcomes prepare them to ensure high-quality, equitable patient outcomes.

Genetic diversity of endosymbiotic bacteria Wolbachia infecting two mosquito species of the genus Eretmapodites occurring in sympatry in the Comoros archipelago.

The influence of Wolbachia on mosquito reproduction and vector competence has led to renewed interest in studying the genetic diversity of these bacteria and the phenotypes they induced in mosquito vectors. In this study, we focused on two species of Eretmapodites, namely Eretmapodites quinquevittatus and Eretmapodites subsimplicipes, from three islands in the Comoros archipelago (in the Southwestern Indian Ocean). Using the COI gene, we examined the mitochondrial genetic diversity of 879 Eretmapodites individuals from 54 sites. Additionally, we investigated the presence and genetic diversity of Wolbachia using the wsp marker and the diversity of five housekeeping genes commonly used for genotyping through Multiple Locus Sequence Typing (MLST). Overall, Er. quinquevittatus was the most abundant species in the three surveyed islands and both mosquito species occurred in sympatry in most of the investigated sites. We detected a higher mitochondrial genetic diversity in Er. quinquevittatus with 35 reported haplotypes (N = 615 specimens, Hd = 0.481 and π = 0.002) while 13 haplotypes were found in Er. subsimplicipes (N = 205 specimens, Hd = 0.338 and π = 0.001), this difference is likely due to the bias in sampling size between the two species. We report for the first time the presence of Wolbachia in these two Eretmapodites species. The prevalence of Wolbachia infection varied significantly between species, with a low prevalence recorded in Er. quinquevittatus (0.8%, N = 5/627) while infection was close to fixation in Er. subsimplicipes (87.7%, N = 221/252). Both male and female individuals of the two mosquito species appeared to be infected. The analysis of MLST genes revealed the presence of two Wolbachia strains corresponding to two new strain types (STs) within the supergroups A and B, which have been named wEretA and wEretB. These strains were found as mono-infections and are closely related, phylogenetically, to Wolbachia strains previously reported in Drosophila species. Finally, we demonstrate that maternal transmission of Wolbachia is imperfect in Er. subsimplicipes, which could explain the presence of a minority of uninfected individuals in the field.

Developing Dynamic Structure-Based Pharmacophore and ML-Trained QSAR Models for the Discovery of Novel Resistance-Free RET Tyrosine Kinase Inhibitors.

Activation of RET tyrosine kinase plays a critical role in the pathogenesis of various cancers, including non-small cell lung cancer, papillary thyroid cancers, multiple endocrine neoplasia type 2A and 2B (MEN2A, MEN2B), and familial medullary thyroid cancer. Gene fusions and point mutations in the RET proto-oncogene result in constitutive activation of RET signaling pathways. Consequently, developing effective inhibitors to target RET is of utmost importance. Small molecules have shown promise as inhibitors by binding to the kinase domain of RET and blocking its enzymatic activity. However, the emergence of resistance due to single amino acid changes poses a significant challenge. In this study, a structure-based dynamic pharmacophore-driven approach using E-pharmacophore modeling from molecular dynamics trajectories is proposed to select low energy favorable hypotheses, and ML-trained QSAR models to predict pIC50 values of compounds. For this aim, extensive small molecule libraries were screened using developed ligand-based models and potent compounds which are capable of inhibiting RET activation were proposed.

Abstract 2083: Discovery of ETX-19477, a novel and selective PARG inhibitor with high potency against tumors with underlying replication stress

Abstract DNA damage response (DDR) is an important cellular process that is regulated by poly ADP ribosylation (PARylation). PARP1 binds to DNA break sites and then catalyzes PARylation, which leads to recruitment of repair factors and initiation of base-excision and single-strand break (SSB) repair. Removal of PAR chains is performed by PARG and is also critical for successful completion of DNA repair. Suppression of PAR chain hydrolysis via PARG depletion or inhibition leads to defective single-strand break repair, reduced kinetics of repair, and hypersensitivity to certain DNA damaging agents. Cancer cells demonstrate high levels of replication stress, characterized as the slowing or stalling of replication forks during DNA replication. Replication stress generates DNA SSBs and exposes unligated Okazaki fragments which activate PARP1. PARP1 catalyzed PARylation slows replication fork progression as a protective mechanism, initiates damage repair, and promotes fork reversal. PAR chain removal, via PARG activity, enables completion of damage repair, replication fork restart, and recovery from replication stress. Under conditions of replication stress, PARP inhibition can result in unrestrained fork progression and the occurrence of DNA double strand breaks from fork runoff. In contrast, PARG inhibition causes prolonged slowing or stalling of replication fork progression, which can lead to replication catastrophe and cancer cell death. Because of these opposing roles, PARG inhibitors show distinct pharmacology as compared to PARP inhibitors in certain cancer cells including cancer cells that are BRCA wild type, homologous recombination proficient, and PARP inhibitor insensitive or resistant. ETX-19477 is a novel inhibitor of PARG that demonstrates low nM, on-target activity in cells as measured by the accumulation of PAR chains. ETX-19477 induces death and/or inhibits the proliferation of multiple cancer cell types including ER+HER2- breast, serous and mucinous ovarian, lung, and gastric cancers and induces pan-nuclear γH2AX expression, a hallmark of replication catastrophe. Preclinical studies demonstrate that ETX-19477 is orally bioavailable with favorable pharmacokinetics. Oral treatment of mice with ETX-19477 is well tolerated and shows robust dose-dependent in vivo anti-tumor activity in breast and ovarian cell-line derived and patient-derived xenograft models. Efficacy is observed with either once or twice daily dosing and with a discontinuous dosing regimen. In mouse xenograft models, induction of γH2AX expression in tumor tissue correlates with tumor growth inhibition. Preclinical data show ETX-19477 demonstrates potent and specific anti-proliferative effects by exposing underlying existing replication stress vulnerabilities in cancer cells across multiple tumor types. ETX-19477 will be advanced into clinical trials in 2024. Citation Format: John P. Holleran, Tamara S. Rodems, Shweta Sharma, Angelina M. Santini, Cindy Wuerz, Juping Liu, Lu Tian, Joseph Dosch, Joy Nader, Richard Rivera, Shyama Herath, Joseph Marakovits, Christopher McBride, Ryan Stansfield, Amy Salyards, James M. Veal, Jeffrey A. Stafford, Gretchen Bain. Discovery of ETX-19477, a novel and selective PARG inhibitor with high potency against tumors with underlying replication stress [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2083.

Abstract 2961: Investigating the role of aging and treatment-induced senescence in the metastatic liver cancer tumor microenvironment

Abstract Liver senescence, marked by the progressive decline in hepatic cell function and regenerative capacity, plays a vital role in the context of aging, chronic liver diseases, and cancer progression, particularly when influenced by anti-cancer therapies. This study is designed to extensively characterize liver senescence under two specific conditions: replicative aging and therapy-induced changes. We examined liver samples from 20 individuals, covering a wide age range (young, <40 years; old, >60 years), and 16 cases of colorectal cancer (CRC) liver metastasis (ages 37-66). Our integrative approach melds single-nucleus RNA-sequencing (snRNA-seq) and ATAC-sequencing (snATAC-seq) to investigate the transcriptomic and epigenetic landscapes across a spectrum of liver cell types, including hepatocytes, cholangiocytes, stellate cells, liver sinusoidal endothelial cells, and diverse immune cells. Key findings include an upregulation of senescence markers such as CDKN1A, CDKN2A, and HMGB1, particularly in specific hepatocytes from older individuals and various cell types in the CRC liver metastasis group. Furthermore, we noted a distinctive senescence-associated secretory phenotype (SASP) across multiple immune cell types in our treated CRC liver metastasis group and upregulation of treatment-induced senescence gene signatures, such as SenCan. Moreover, hepatic stellate cells from older subjects exhibited augmented senescence-related gene signatures (SenSig) and transcription factors (SenMayo), with myofibroblast-like and FAP+ stellate cells showing a marked senescence phenotype, evidenced by elevated SASP molecule expression (CCL2, SERPINE1, GLB1, IGFBP7, IGFBP3).Incorporating advanced high-resolution imaging techniques, our study delves into the detailed morphological characteristics and spatial distribution of senescence markers within the liver in the setting of replicative aging and treatment-induced senescence. This study sheds light on the heterogeneity and intricacies of senescence-associated gene expression within liver cell populations. By combining comprehensive multiomic data with advanced high-resolution spatial profiling, we aim to decipher unique senescence phenotypes in the context of both replicative and treatment-induced senescence. Our work highlights the significance of cellular senescence in liver pathologies and cancer progression, suggesting new directions for therapeutic interventions that target these complex dynamics. Citation Format: Kelsey Gallant, Alla Karpova, Xiang Li, Michael Iglesia, Andrew Houston, Daniel Rapp, Chien-Wei Peng, Clara Liu, John Herdon, Feng Chen, Ryan Fields, Li Ding. Investigating the role of aging and treatment-induced senescence in the metastatic liver cancer tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2961.

Abstract 2513: MAGE-A3, MAGE-A4, and PD-L1 protein show co-expression in colon, lung and bladder cancer

Abstract PD-L1 programmed death ligand 1/CD274 has been shown to be an excellent immune therapy target for many tumors. Currently, studies have shown PD-L1in combination with other immune therapy targets can improve patient outcomes generating the need for new targets. One candidate is the cancer testis antigen Melanoma Antigen Gene Family (MAGE-A) because these genes have limited expression in normal tissues and high expression in cancer. Clinical trials have already begun targeting MAGE-A3 and MAGE-A4 proteins in multiple tumor types. Protein assessment of individual MAGE-A family members has been challenging due to sequence homology as high as ninety-five percent between members. Previously, with the use of CytoSections two highly specific antibodies for immunohistochemistry to MAGE-A3 (clone OTI1H1) and MAGE-A4 (clone OTI2C1) were found. In this study, the MAGE-A3 and MAGE-A4 antibodies were screened with PD-L1 on colon, lung, and bladder cancers. Results show detection of both MAGE-A3 and MAGE-A4 in 25% of colon; 30% of lung; and 20% of bladder cancers. More than 70% of the lung and bladder cancers were positive for MAGE-A4 but only six of twenty-four colon cancers were positive for MAGE-A4. The results show 60 percent of the positive for MAGEA3 or MAGEA4 in colon, lung, and bladder cancers were also positive for PD-L1. This study suggests that MAGE-A3 and MAGE-A4 have tumor specific expression patterns and a potential to be a co-immunotherapy target with PD-L1. Citation Format: Rachel Gonzalez, YiChen Guo, Jina Yom, Bailey Gilmore, Eden Zewdu, Xi-Andy Han, Dehe Kong, Tianli Qu, Qi Ren, Xiaomin Hu, Ranran Zhang, Zhaohui Wu, Alex Strom, Xuan Liu, Wei Fu. MAGE-A3, MAGE-A4, and PD-L1 protein show co-expression in colon, lung and bladder cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2513.

ON MULTIPLICATIVE (s,P)-CONVEXITY AND RELATED FRACTIONAL INEQUALITIES WITHIN MULTIPLICATIVE CALCULUS

In this paper, we propose a fresh conception about convexity, known as the multiplicative [Formula: see text]-convexity. Along with this direction, we research the properties of such type of convexity. In the framework of multiplicative fractional Riemann–Liouville integrals and under the [Formula: see text]differentiable [Formula: see text]-convexity, we investigate the multiplicative fractional inequalities, including the Hermite–Hadamard- and Newton-type inequalities. To further verify the validity of our primary outcomes, we give a few numerical examples. As applications, we proffer a number of inequalities of multiplicative type in special means as well.

Activating mutations in JAK2 and CALR differentially affect intracellular calcium flux in store operated calcium entry

BackgroundCalcium (Ca2+) signaling regulates various vital cellular functions, including integrin activation and cell migration. Store-operated calcium entry (SOCE) via calcium release-activated calcium (CRAC) channels represents a major pathway for Ca2+ influx from the extracellular space in multiple cell types. The impact of JAK2-V617F and CALR mutations which are disease initiating in myeloproliferative neoplasms (MPN) on SOCE, calcium flux from the endoplasmic reticulum (ER) to the cytosol, and related key signaling pathways in the presence or absence of erythropoietin (EPO) or thrombopoietin (TPO) is poorly understood. Thus, this study aimed to elucidate the effects of these mutations on the aforementioned calcium dynamics, in cellular models of MPN.MethodsIntracellular Ca2+ levels were measured over a time frame of 0–1080 s in Fura-2 AM labeled myeloid progenitor 32D cells expressing various mutations (JAK2-WT/EpoR, JAK2-V617F/EpoR; CALR-WT/MPL, CALR-ins5/MPL, and del52/MPL). Basal Ca2+ concentrations were assessed from 0–108 s. Subsequently, cells were stimulated with EPO/TPO in Ca2+-free Ringer solution, measuring Ca2+ levels from 109–594 s (store depletion). Then, 2 mM of Ca2+ buffer resembling physiological concentrations was added to induce SOCE, and Ca2+ levels were measured from 595–1080 s. Fura-2 AM emission ratios (F340/380) were used to quantify the integrated Ca2+ signal. Statistical significance was assessed by unpaired Student's t-test or Mann–Whitney-U-test, one-way or two-way ANOVA followed by Tukey's multiple comparison test.ResultsFollowing EPO stimulation, the area under the curve (AUC) representing SOCE significantly increased in 32D-JAK2-V617F cells compared to JAK2-WT cells. In TPO-stimulated CALR cells, we observed elevated Ca2+ levels during store depletion and SOCE in CALR-WT cells compared to CALR-ins5 and del52 cells. Notably, upon stimulation, key components of the Ca2+ signaling pathways, including PLCγ-1 and IP3R, were differentially affected in these cell lines. Hyper-activated PLCγ-1 and IP3R were observed in JAK2-V617F but not in CALR mutated cells. Inhibition of calcium regulatory mechanisms suppressed cellular growth and induced apoptosis in JAK2-V617F cells.ConclusionsThis report highlights the impact of JAK2 and CALR mutations on Ca2+ flux (store depletion and SOCE) in response to stimulation with EPO and TPO. The study shows that the JAK2-V617F mutation strongly alters the regulatory mechanism of EpoR/JAK2-dependent intracellular calcium balance, affecting baseline calcium levels, EPO-induced calcium entry, and PLCγ-1 signaling pathways. Our results reveal an important role of calcium flux in the homeostasis of JAK2-V617F positive cells.

Venture Capital and Dividend Policy

In this paper, we empirically examine the impact of venture capital investment on the dividend policy of the invested companies using a sample of list companies from China’s ChiNext market during the period 2014 to 2019. Our empirical results show that different types of VC investments have different impacts on the dividend policies of the invested companies. To be specific, we found independent venture capital companies (IVCs) promote the company’s dividend payment and increase the level of dividend payments while corporate venture capital (CVC) inhibits the company’s dividend payment. The joint participation of multiple types of venture capital investment (syndication) also increases the company’s dividend distribution. Our main contributions are two-fold. First, we provide a comprehensive analysis in the field of VC and dividend policy; second, we differentiate VC from the perspective of investment objectives and examine its different impacts on the dividend policies of the invested companies.

Circulating tumor DNA (ctDNA) as a biomarker for lung cancer: Early detection, monitoring and therapy prediction.

Circulating tumor DNA (ctDNA), i.e., DNA shed from tumor cells into the bloodstream, is emerging as one of the most useful plasma biomarkers in patients with multiple types of cancer, including patients with non-small cell lung cancer (NSCLC). Indeed, NSCLC was the first malignancy in which measurement of ctDNA was approved for clinical use, i.e., mutational testing of EGFR for predicting response to EGFR tyrosine kinase inhibitors in patients with advanced disease. Although historically the gold standard method for EGFR mutational analysis required tumor tissue, the use of ctDNA is more convenient and safer for patients, results in a faster turn-around-time for return of results, provides a more complete representation of genetic alteration in heterogeneous tumors and is less costly to perform. Emerging uses of ctDNA in patients with lung or suspected lung cancer include screening for early disease, surveillance following initial treatment and monitoring response to therapy in metastatic disease. For evaluating therapy response, ctDNA appears to be especially useful in patients receiving targeted therapies against driver oncogenes or immunotherapy. Further work should not only validate these emerging findings but also aim to optimize and standardize ctDNA assays.

Explainable machine learning for predicting stomatal conductance across multiple plant functional types

Stomatal conductance (gs) is a key leaf-level function controlling water, carbon, and energy exchange between vegetation and the surrounding environment. Conventionally, semi-empirical models have been used to model gs, but these models require re-parameterization as ecosystems undergo phenological changes over the growing season. In contrast, machine learning (ML) models offer a potential path to overcome this problem but are less interpretable than process-based models. This study explores ML as an approach to develop flexible and robust models of gs for a range of plant functional types (PFTs), including C3 crops, C3 grasses, shrubs, and tree species across different continents. An explainable machine-learning approach (eXML) was used here to provide novel interpretations and insights into the ML model formulations and relative predictor importance. We contrast the performance of three ML architectures: extreme gradient boosting, random forests, and neural networks. Models were developed and examined using many combinations of environmental and physiological predictors. The results demonstrated that ML models significantly outperform conventional semi-empirical models in predicting gs responses to the environment, while not requiring re-parameterization as is required in the semi-empirical paradigm. Particular focus is placed on models formulated around predictor sets that are: (a) relevant to gs estimation in modern terrestrial biophysical simulation models, and (b) composed of variables describing environmental and physiological drivers that can be remotely sensed non-invasively. “Generalized” models developed using data from all four PFTs demonstrated strong predictive performance using only three predictor variables, capturing 63–80 % of the variability in stomatal conductance across all ML architectures. Four predictor variables resulted in models capturing 79–83 % of gs variability, and models developed using all five predictor variables examined here were able to capture as much as 87 % of gs variability across all PFTs. Uncertainty in gs predictions was quantified using quantile regression. Shapley additive explanations was applied to unravel instance-based positive and negative contributions of environmental and physiological predictors to gs modeling, while illustrating that the models are consistent with the underlying ecophysiology. This work demonstrates the power of ML to introduce a new paradigm in the simulation of highly dynamic ecophysiological processes critical to environmental prediction.