Miracle-dz/UniFAR-FTUs huggingface dataset:
Functional observability and target state estimation in large-scale networks

Significance Observing the states of a network is fundamental to our ability to explore and control the dynamics of complex natural, social, and technological systems. The problem of determining whether the system is observable has been addressed by network control researchers over the past decade. Progress on the further problem of actually designing and implementing efficient algorithms to infer the states from limited measurements has been hampered by the high dimensionality of large-scale networks. Noting that often only a small number of state variables in a network are essential for control, intervention, and monitoring purposes, this work develops a graph-based theory and highly scalable methods that achieve accurate estimation of target variables of network systems with minimal sensing and computational resources. The quantitative understanding and precise control of complex dynamical systems can only be achieved by observing their internal states via measurement and/or estimation. In large-scale dynamical networks, it is often difficult or physically impossible to have enough sensor nodes to make the system fully observable. Even if the system is in principle observable, high dimensionality poses fundamental limits on the computational tractability and performance of a full-state observer. To overcome the curse of dimensionality, we instead require the system to be functionally observable, meaning that a targeted subset of state variables can be reconstructed from the available measurements. Here, we develop a graph-based theory of functional observability, which leads to highly scalable algorithms to 1) determine the minimal set of required sensors and 2) design the corresponding state observer of minimum order. Compared with the full-state observer, the proposed functional observer achieves the same estimation quality with substantially less sensing and fewer computational resources, making it suitable for large-scale networks. We apply the proposed methods to the detection of cyberattacks in power grids from limited phase measurement data and the inference of the prevalence rate of infection during an epidemic under limited testing conditions. The applications demonstrate that the functional observer can significantly scale up our ability to explore otherwise inaccessible dynamical processes on complex networks.
The interplay of GTP-binding protein AGB1 with ER stress sensors IRE1a and IRE1b modulates Arabidopsis unfolded protein response and bacterial immunity

ABSTRACT In eukaryotic cells, the accumulation of unfolded or misfolded proteins in the endoplasmic reticulum (ER) results in ER stress that induces a cascade of reactions called the unfolded protein response (UPR). In Arabidopsis, the most conserved UPR sensor, Inositol-requiring enzyme 1 (IRE1), responds to both abiotic- and biotic-induced ER stress. Guanine nucleotide-binding proteins (G proteins) constitute another universal and conserved family of signal transducers that have been extensively investigated due to their ubiquitous presence and diverse nature of action. Arabidopsis GTP-binding protein β1 (AGB1) is the only G-protein β-subunit encoded by the Arabidopsis genome that is involved in numerous signaling pathways. Mounting evidence suggests the existence of a crosstalk between IRE1 and G protein signaling during ER stress. AGB1 has previously been shown to control a distinct UPR pathway independently of IRE1 when treated with an ER stress inducer tunicamycin. Our results obtained with combinatorial knockout mutants support the hypothesis that both IRE1 and AGB1 synergistically contribute to ER stress responses chemically induced by dithiothreitol (DTT) as well as to the immune responses against a phytopathogenic bacterium Pseudomonas syringae pv. tomato strain DC3000. Our study highlights the crosstalk between the plant UPR transducers under abiotic and biotic stress.
Roles of Receptor Phosphorylation and Rab Proteins in G Protein-Coupled Receptor Function and Trafficking

The G protein-coupled receptors form the most abundant family of membrane proteins and are crucial physiologic players in the homeostatic equilibrium, which we define as health. They also participate in the pathogenesis of many diseases and are frequent targets of therapeutic intervention. Considering their importance, it is not surprising that different mechanisms regulate their function, including desensitization, resensitization, internalization, recycling to the plasma membrane, and degradation. These processes are modulated in a highly coordinated and specific way by protein kinases and phosphatases, ubiquitin ligases, protein adaptors, interaction with multifunctional complexes, molecular motors, phospholipid metabolism, and membrane distribution. This review describes significant advances in the study of the regulation of these receptors by phosphorylation and endosomal traffic (where signaling can take place); we revisited the bar code hypothesis and include two additional observations: 1) that different phosphorylation patterns seem to be associated with internalization and endosome sorting for recycling or degradation, and 2) that, surprisingly, phosphorylation of some G protein-coupled receptors appears to be required for proper receptor insertion into the plasma membrane. SIGNIFICANCE STATEMENT G protein-coupled receptor phosphorylation is an early event in desensitization/signaling switching, endosomal traffic, and internalization. These events seem crucial for receptor responsiveness, cellular localization, and fate (recycling/degradation) with important pharmacological/therapeutic implications. Phosphorylation sites vary depending on the cells in which they are expressed and on the stimulus that leads to such covalent modification. Surprisingly, evidence suggests that phosphorylation also seems to be required for proper insertion into the plasma membrane for some receptors.
The improvement of biocompatibility by incorporating porphyrins into carbon dots with photodynamic effects and pH sensitivities

Photodynamic therapy (PDT) is a promising new treatment for cancer; however, the hydrophobic interactions and poor solubility in water of photosensitizers limit the use in clinic. Nanoparticles especially carbon dots have attracted the attention of the world’s scientists because of their unique properties such as good solubility and biocompatibility. In this paper, we integrated carbon dots with different porphyrins to improve the properties of porphyrins and evaluated their efficacy as PDT drugs. The spectroscopic characteristics of porphyrins nano-conjugates were studied. Singlet oxygen generation rate and the light- and dark-induced toxicity of the conjugates were studied. Our results showed that the covalent interaction between CDs and porphyrins has improved the biocompatibility. The synthesized conjugates also inherit the pH sensitivity of the carbon dots, while the conjugation also decreases the hemolysis ratio making them a promising candidate for PDT. The incorporation of carbon dots into porphyrins improved their biocompatibility by reducing toxicity.
Defining the interactome of the human mitochondrial ribosome identifies SMIM4 and TMEM223 as respiratory chain assembly factors

Human mitochondria express a genome that encodes thirteen core subunits of the oxidative phosphorylation system (OXPHOS). These proteins insert into the inner membrane co-translationally. Therefore, mitochondrial ribosomes engage with the OXA1L-insertase and membrane-associated proteins, which support membrane insertion of translation products and early assembly steps into OXPHOS complexes. To identify ribosome-associated biogenesis factors for the OXPHOS system, we purified ribosomes and associated proteins from mitochondria. We identified TMEM223 as a ribosome-associated protein involved in complex IV biogenesis. TMEM223 stimulates the translation of COX1 mRNA and is a constituent of early COX1 assembly intermediates. Moreover, we show that SMIM4 together with C12ORF73 interacts with newly synthesized cytochrome b to support initial steps of complex III biogenesis in complex with UQCC1 and UQCC2. Our analyses define the interactome of the human mitochondrial ribosome and reveal novel assembly factors for complex III and IV biogenesis that link early assembly stages to the translation machinery.
The passive recipient: Neural correlates of negative self‐view in depression

Previous studies have argued that people tend to isolate themselves from negative information. This tendency is modulated by the individual's role in social interaction, that is, as an initiative actor (e.g., “I hit Tom”) or a passive recipient (e.g., “Paul hits me”). Depressed patients tend to focus on negative aspects of themselves and cope with situations passively. It is still an open question how the actor/recipient role affects the behavioral and neural responses to self in depression.
Computer-Generated R.E.N.A.L. Nephrometry Scores Yield Comparable Predictive Results to Those of Human-Expert Scores in Predicting Oncologic and Perioperative Outcomes

Purpose: We sought to automate R.E. N.A. L. (for radius, exophytic/endophytic, nearness of tumor to collecting system, anterior/posterior, location relative to polar line) nephrometry scoring of preoperative computerized tomography scans and create an artificial intelligence-generated score (AI-score). Subsequently, we aimed to evaluate its ability to predict meaningful oncologic and perioperative outcomes as compared to expert human-generated nephrometry scores (H-scores). Materials and Methods: A total of 300 patients with preoperative computerized tomography were identified from a cohort of 544 consecutive patients undergoing surgical extirpation for suspected renal cancer at a single institution. A deep neural network approach was used to automatically segment kidneys and tumors, and geometric algorithms were developed to estimate components of R.E. N.A. L. nephrometry score. Tumors were independently scored by medical personnel blinded to AI-scores. AI- and H-score agreement was assessed using Lin’s concordance correlation and their predictive abilities for both oncologic and perioperative outcomes were assessed using areas under the curve. Results: Median age was 60 years (IQE 51–68), and 40% were female. Median tumor size was 4.2 cm and 91.3% had malignant tumors, including 27%, 37% and 24% with high stage, grade and necrosis, respectively. There was significant agreement between H-scores and AI-scores (Lin’s ⍴=0.59). Both AI- and H-scores similarly predicted meaningful oncologic outcomes (p <0.001) including presence of malignancy, necrosis, and high-grade and -stage disease (p <0.003). They also predicted surgical approach (p <0.004) and specific perioperative outcomes (p <0.05). Conclusions: Fully automated AI-generated R.E. N.A. L. scores are comparable to human-generated R.E. N.A. L. scores and predict a wide variety of meaningful patient-centered outcomes. This unambiguous artificial intelligence-based scoring is intended to facilitate wider adoption of the R.E. N.A. L. score.
Agency and Identity in the Collective Self

Contemporary research on human sociality is heavily influenced by the social identity approach, positioning social categorization as the primary mechanism governing social life. Building on the distinction between agency and identity in the individual self (“I” vs. “Me”), we emphasize the analogous importance of distinguishing collective agency from collective identity (“We” vs. “Us”). While collective identity is anchored in the unique characteristics of group members, collective agency involves the adoption of a shared subjectivity that is directed toward some object of our attention, desire, emotion, belief, or action. These distinct components of the collective self are differentiated in terms of their mental representations, neurocognitive underpinnings, conditions of emergence, mechanisms of social convergence, and functional consequences. Overall, we show that collective agency provides a useful complement to the social categorization approach, with unique implications for multiple domains of human social life, including collective action, responsibility, dignity, violence, dominance, ritual, and morality.
LipidOne: user-friendly lipidomic data analysis tool for a deeper interpretation in a systems biology scenario

SUMMARY LC/MS-based analysis techniques combined with specialised lipid tool allow for the qualitative and quantitative determination of thousands of lipid molecules. Some recent bioinformatics tools have been developed to study changes in the lipid profile in case-control experiments and correlate these changes to different enzyme activity or gene expression. However, the existing tools have the limitation to treat only the assembled lipid molecules. In reality, each individual molecule can be considered as an assembly of smaller parts, often called building blocks. These are the result of a myriad of biochemical synthesis and transformation processes that, from a systems biology perspective, should not be ignored. Here, we present LipidOne, a new lipidomic tool which highlights all qualitative and quantitative changes in lipid building blocks both among all detected lipid classes and among experimental groups. Thanks to LipidOne, even differences in lipid building blocks can now be linked to the activity of specific classes of enzymes, transcripts and genes. AVAILABILITY AND IMPLEMENTATION LipidOne software is freely available at www.dcbb. unipg.it/LipidOne and https://github.com/matteogiulietti/LipidOne. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
A Novel Programmable Current Reference with FGMOSFETs

of variation in supply voltage and temperature. The proposed circuit has an output current varying from 473.09 nA to 15.71 A. The circuit performs well over a temperature range of 0 C to 100 C and supply voltage range of 0.5 V to 2.5 V. The circuit has a very low temperature dependency of 1.9 nA/ C and supply voltage dependency of 10.28 nA/V respectively. This circuit avoids the need for re-design and re-fabrication for dierent values of output current. —Floating gate MOSFET(FGMOSFET), bias voltage, subtraction technique, temperature dependency, supply voltage dependency
Association of β-Amyloid and Basal Forebrain With Cortical Thickness and Cognition in Alzheimer and Lewy Body Disease Spectra

Objective Cholinergic degeneration and β-amyloid contribute to brain atrophy and cognitive dysfunction in Alzheimer disease (AD) and Lewy body disease (LBD), but their relationship has not been comparatively evaluated. Methods In this cross-sectional study, we recruited 28 normal controls (NC), 55 patients with AD mild cognitive impairment (MCI), 34 patients with AD dementia, 28 patients with LBD MCI, and 51 patients with LBD dementia. Participants underwent cognitive evaluation, brain MRI to measure the basal forebrain (BF) volume and global cortical thickness (CTh), and 18F-florbetaben (FBB) PET to measure the standardized uptake value ratio (SUVR). Using general linear models and path analyses, we evaluated the association of FBB-SUVR and BF volume with CTh or cognitive dysfunction in the AD spectrum (AD and NC) and LBD spectrum (LBD and NC), respectively. Covariates included age, sex, education, deep and periventricular white matter hyperintensities, intracranial volume, hypertension, diabetes, and hyperlipidemia. Results BF volume mediated the association between FBB-SUVR and CTh in both the AD and LBD spectra, while FBB-SUVR was associated with CTh independently of BF volume only in the LBD spectrum. Significant correlation between voxel-wise FBB-SUVR and CTh was observed only in the LBD group. FBB-SUVR was independently associated with widespread cognitive dysfunction in both the AD and LBD spectra, especially in the memory domain (standardized beta [B] for AD spectrum = −0.60, B for LBD spectrum = −0.33). In the AD spectrum, BF volume was associated with memory dysfunction (B = 0.18), and CTh was associated with language (B = 0.21) and executive (B = 0.23) dysfunction. In the LBD spectrum, however, BF volume and CTh were independently associated with widespread cognitive dysfunction. Conclusions There is a common β-amyloid–related degenerative mechanism with or without the mediation of BF in the AD and LBD spectra, while the association of BF atrophy with cognitive dysfunction is more profound and there is localized β-amyloid–cortical atrophy interaction in the LBD spectrum.
Systems biology of angiogenesis signaling: Computational models and omics

Abstract Angiogenesis is a highly regulated multiscale process that involves a plethora of cells, their cellular signal transduction, activation, proliferation, differentiation, as well as their intercellular communication. The coordinated execution and integration of such complex signaling programs is critical for physiological angiogenesis to take place in normal growth, development, exercise, and wound healing, while its dysregulation is critically linked to many major human diseases such as cancer, cardiovascular diseases, and ocular disorders; it is also crucial in regenerative medicine. Although huge efforts have been devoted to drug development for these diseases by investigation of angiogenesis‐targeted therapies, only a few therapeutics and targets have proved effective in humans due to the innate multiscale complexity and nonlinearity in the process of angiogenic signaling. As a promising approach that can help better address this challenge, systems biology modeling allows the integration of knowledge across studies and scales and provides a powerful means to mechanistically elucidate and connect the individual molecular and cellular signaling components that function in concert to regulate angiogenesis. In this review, we summarize and discuss how systems biology modeling studies, at the pathway‐, cell‐, tissue‐, and whole body‐levels, have advanced our understanding of signaling in angiogenesis and thereby delivered new translational insights for human diseases. This article is categorized under: Cardiovascular Diseases > Computational Models Cancer > Computational Models
Solar activity analysis using publicly available SDO-AIA data

Data from the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO) are used to analyze solar activity over a two year period. Image processing techniques are used to derive time series of characteristics of the distribution of intensities of solar images taken at 211 angstrom. Days with exceptionally high activity levels are identied in the time series. A comparison between the obtained series and the ocially published sunspot numbers shows a high correlation. This analysis is a case study demonstrating possibilities for amateur astronomers and astrostatisticians. The AIA/SDO data server is just one of many astronomical data sources publicly available. This oers new opportunities to the non-professional community to access data collected by high-end, professional instruments. This working paper should inspire fellow hobbyists to experiment with such data, and to develop code to explore, visualize and analyze the data. The domain of astrostatistics, which has been rediscovered by the professional community in recent years, is easily accessible to hobby scientists.
A MODEL FOR LOYALTY IN THE CONTEXT OF CUSTOMER RELATIONSHIP MARKETING

This paper focuses on the effect communication on the sales performance within CRM. The paper uses the hotel business as an example to evaluate if communication within Customer Relationship Management creates loyalty measured by the re-purchase behavior of existing hotel guests. The re-purchase behavior is regarded in the paper as the final outcome of loyalty. In addition the research evaluates the qualitative distinctions between the most common message transmitters in direct marketing, namely e-mail and post mail. Over the last years an increasing number of companies have replaced the costly media channel post mail with the cheaper channel e-mail. This was done without a fundamental knowledge of the effect of switching marketing channels on the sales performance. Different variables are responsible for customer loyalty. The author uses the European Customer Satisfaction Index model (ECSI) to create a new model which describes loyalty from a Customer Relationship Management standpoint. For the quantitative research the marketing actions and bookings of four hotels in Germany were reviewed over a time period of 4.5 years. Due to relatively low marketing budgets hotels rely on direct marketing, therefore the results should also be applicable as a bench mark for other SME’s. The results show a direct correlation between communication and the sales performance. Also a clear qualitative distinction between e-mail and post mail as a message transmitter within CRM could be identified. The outcome should stimulate manager to a re-evaluate their existing communication strategy and should be used as a basis for further research.
“Dying with a Smile, Just Knowing that Somebody’s Listened to Me”: End-Of-Life Care and Medical Assistance in Dying in Canadian Prisons

Medical assistance in dying (MAiD) has been legal in Canada since 2016 and some incarcerated patients who are at the end of their lives are eligible for the procedure. Interviews with nine incarcerated men at a federal penitentiary in Canada provide insight into some of the ways that people who are navigating aging and end-of-life in prison think about MAiD. Interview themes are organized around: experience with death and dying; possibilities and barriers related to applications for release from prison at end-of-life; experiences of peer-caregiving in a prison palliative care program; support for MAiD and the expansion of eligibility criteria; what a good death looks like. Themes are contextualized alongside federal guidelines related to end-of-life care (EOLC) and MAiD for prisoners, highlighting that sound policy requires both generalizable principles and attention to nuance. MAiD rests on patient voluntariness, and thus autonomy over EOLC decisions is paramount for prisoners.
miR-647 inhibits hepatocellular carcinoma cell progression by targeting protein tyrosine phosphatase receptor type F

ABSTRACT Hepatocellular carcinoma (HCC) is a kind of malignant tumor derived from hepatocytes and hepatobiliary cells, and its occurrence is prevalent worldwide. Although medical technology is developing rapidly, the therapeutic efficacy of HCC is still poor. Emerging evidence manifests that microRNAs (miRNAs) play a crucial role in various cancers and have been regarded as cancer suppressor gene. However, the regulatory mechanisms mediated by miR-647 involved in HCC remain unclear. Hence, to clarify the regulatory mechanisms mediated by miR-647 in HCC, we studied the independent effects of miR-647 and explored protein tyrosine phosphatase receptor type F (PTPRF) in the constructed HCC cell line (HCV-huh7.5). Thereafter, we used dual-luciferase gene reporting and Western blot to investigate the relationship between PTPRF and miR-647. Furthermore, we studied the mechanism of miR-647 on PTPRF in HCV-huh7.5. We found that miR-647 could not only promote the proliferation and invasion of HCV-huh7.5 cells but also facilitate cell migration, while PTPRF has the opposite effect. Besides, the results of cell function experiment implied that the overexpression of miR-647 or inhibition of PTPFRF remarkably influenced the Erk signaling pathway, which could regulate cell proliferation, migration, and invasion. In addition, the dual luciferase reporting identified PTPRF as a direct target of miR-647. We further demonstrated that miR-647 inhibitor or PTPRF knockdown administration boosted HCV-huh7.5 cell proliferation, migration, and invasion by targeting PTPRF. These findings provided clues for the mechanism of miR-647 in promoting the biology of HCV-huh7.5 cells by inhibiting the expression level of PTPRF.