Miracle-dz/UniFAR-FTUs huggingface dataset:
Anti-Proliferation Effect of Theasaponin E1 on the ALDH-Positive Ovarian Cancer Stem-Like Cells

Ovarian cancer has the highest mortality rate of all gynecological malignancies and the five-year death rate of patients has remained high in the past five decades. Recently, with the rise of cancer stem cells (CSCs) theory, an increasing amount of research has suggested that CSCs give rise to tumor recurrence and metastasis. Theasaponin E1 (TSE1), which was isolated from green tea (Camellia sinensis) seeds, has been proposed to be an effective compound for tumor treatment. However, studies on whether TSE1 takes effect through CSCs have rarely been reported. In this paper, ALDH-positive (ALDH+) ovarian cancer stem-like cells from two platinum-resistant ovarian cancer cell lines A2780/CP70 and OVCAR-3 were used to study the anti-proliferation effect of TSE1 on CSCs. The ALDH+ cells showed significantly stronger sphere forming vitality and stronger cell migration capability. In addition, the stemness marker proteins CD44, Oct-4, Nanog, as well as Bcl-2 and MMP-9 expression levels of ALDH+ cells were upregulated compared with the original tumor cells, indicating that they have certain stem cell characteristics. At the same time, the results showed that TSE1 could inhibit cell proliferation and suspension sphere formation in ALDH+ cells. Our data suggests that TSE1 as a natural compound has the potential to reduce human ovarian cancer mortality. However, more research is still needed to find out the molecular mechanism of TSE1-mediated inhibition of ALDH+ cells and possible drug applications on the disease.
Gated Path Planning Networks

Value Iteration Networks (VINs) are effective differentiable path planning modules that can be used by agents to perform navigation while still maintaining end-to-end differentiability of the entire architecture. Despite their effectiveness, they suffer from several disadvantages including training instability, random seed sensitivity, and other optimization problems. In this work, we reframe VINs as recurrent-convolutional networks which demonstrates that VINs couple recurrent convolutions with an unconventional max-pooling activation. From this perspective, we argue that standard gated recurrent update equations could potentially alleviate the optimization issues plaguing VIN. The resulting architecture, which we call the Gated Path Planning Network, is shown to empirically outperform VIN on a variety of metrics such as learning speed, hyperparameter sensitivity, iteration count, and even generalization. Furthermore, we show that this performance gap is consistent across different maze transition types, maze sizes and even show success on a challenging 3D environment, where the planner is only provided with first-person RGB images.
Cold atmospheric plasma treatment inhibits growth in colorectal cancer cells

Abstract Plasma oncology is a relatively new field of research. Recent developments have indicated that cold atmospheric plasma (CAP) technology is an interesting new therapeutic approach to cancer treatment. In this study, p53 wildtype (LoVo) and human p53 mutated (HT29 and SW480) colorectal cancer cells were treated with the miniFlatPlaSter – a device particularly developed for the treatment of tumor cells – that uses the Surface Micro Discharge (SMD) technology for plasma production in air. The present study analyzed the effects of plasma on colorectal cancer cells in vitro and on normal colon tissue ex vivo. Plasma treatment had strong effects on colon cancer cells, such as inhibition of cell proliferation, induction of cell death and modulation of p21 expression. In contrast, CAP treatment of murine colon tissue ex vivo for up to 2 min did not show any toxic effect on normal colon cells compared to H2O2 positive control. In summary, these results suggest that the miniFlatPlaSter plasma device is able to kill colorectal cancer cells independent of their p53 mutation status. Thus, this device presents a promising new approach in colon cancer therapy.
Optimizing likelihood models for particle trajectory segmentation in multi-state systems

Particle tracking offers significant insight into the molecular mechanics that govern the behavior of living cells. The analysis of molecular trajectories that transition between different motive states, such as diffusive, driven and tethered modes, is of considerable importance, with even single trajectories containing significant amounts of information about a molecule’s environment and its interactions with cellular structures. Hidden Markov models (HMM) have been widely adopted to perform the segmentation of such complex tracks. In this paper, we show that extensive analysis of hidden Markov model outputs using data derived from multi-state Brownian dynamics simulations can be used both for the optimization of likelihood models describing the states of the system and for characterization of the technique’s failure mechanisms. The major drivers of HMM failure were found to be likelihood overlap, which was visualized using the Bhattacharyya coefficient, and state mixing caused by state transitions that occur between time points in a particle’s trajectory both of which are intrinsically associated with the multi-state nature of the data. This approach provides critical information for the visualization of HMM failure and successful design of particle tracking experiments where trajectories contain multiple mobile states.
NeuroImage: Clinical Test-retest variability of resting-state networks in healthy aging and prodromal Alzheimer's disease

In recent years, changes in resting-state networks (RSN), identi ﬁ ed by functional magnetic resonance imaging (fMRI), have gained increasing attention as potential biomarkers and trackers of neurological disorders such as Alzheimer's disease (AD). Intersession reliability of RSN is fundamental to this approach. In this study, we investigated the test-retest reliability of three memory related RSN (i.e., the default mode, salience, and executive control network) in 15 young, 15 healthy seniors (HS), and 15 subjects a ﬀ ected by mild cognitive impairment (MCI) with positive biomarkers suggestive of incipient AD (6 females each). FMRI was conducted on three separate occasions. Independent Component Analysis decomposed the resting-state data into RSNs. Comparisons of variation in functional connectivity between groups were made applying di ﬀ erent thresholds in an explorative approach. Intersession test-retest reliability was evaluated by intraclass correlation coe ﬃ cient (ICC) comparisons. To assess the e ﬀ ect of gray matter volume loss, motion, cerebrospinal ﬂ uid based biomarkers and the time gap between sessions on intersession variation, the former four were correlated se- parately with the latter. Data showed that i) young subjects ICCs (relative to HS/MCI-subjects) had higher intersession reliability, ii) stringent statistical thresholds need to be applied to prevent false-positives, iii) both HS and MCI-subjects (re-lative to young) showed signi ﬁ cantly more clusters of intersession variation in all three RSN, iv) while inter- session variation was highly correlated with head motion, it was also correlated with biomarkers (especially phospho-tau), the time gap between sessions and local GMV. Results indicate that time gaps between sessions should be kept constant and that head motion must be taken into account when using RSN to assess aging and neurodegeneration. In patients with prodromal AD, re-test reliability may be increased by accouting for overall disease burden by including biomarkers of neuronal injury (especially phospho-tau) in statistical analyses. Local atrophy however, does not seem to play a major role in regards to reliability, but should be used as covariate depending on the research question.
Exploring the Interconnectedness of Cryptocurrencies using Correlation Networks

Correlation networks were used to detect characteristics which, although fixed over time, have an important influence on the evolution of prices over time. Potentially important features were identified using the websites and whitepapers of cryptocurrencies with the largest userbases. These were assessed using two datasets to enhance robustness: one with fourteen cryptocurrencies beginning from 9 November 2017, and a subset with nine cryptocurrencies starting 9 September 2016, both ending 6 March 2018. Separately analysing the subset of cryptocurrencies raised the number of data points from 115 to 537, and improved robustness to changes in relationships over time. Excluding USD Tether, the results showed a positive association between different cryptocurrencies that was statistically significant. Robust, strong positive associations were observed for six cryptocurrencies where one was a fork of the other; Bitcoin / Bitcoin Cash was an exception. There was evidence for the existence of a group of cryptocurrencies particularly associated with Cardano, and a separate group correlated with Ethereum. The data was not consistent with a token's functionality or creation mechanism being the dominant determinants of the evolution of prices over time but did suggest that factors other than speculation contributed to the price.
Systematically Ensuring the Confidence of Real-Time Home Automation IoT Systems

Recent advances and industry standards in Internet of Things (IoT) have accelerated the real-world adoption of connected devices. To manage this hybrid system of digital real-time devices and analog environments, the industry has pushed several popular home automation IoT (HA-IoT) frameworks, such as If-This-Then-That (IFTTT), Apple HomeKit, and Google Brillo. Typically, users author device interactions by specifying the triggering sensor event and the triggered device command. In this seemingly simple software system, two dominant factors govern the system confidence properties with respect to the physical world. First, IoT users are largely nonexperts who lack the comprehensive consideration regarding potential impact and joint effect with existing rules. Second, while the increasing complexity of IoT devices enables fine-grained control (e.g., heater temperature) of continuous real-time environments, even two simply connected devices can have a huge state space to explore. In fact, bugs that wrongfully control devices and home appliances can have ramifications on system correctness and even user physical safety. It is crucial to help users to make sure the system they created meets their expectation. In this article we introduce how techniques from hybrid automata can be practically applied to assist nonexpert IoT users in the confidence checking of such hybrid HA-IoT systems. We propose an automated framework for end-to-end programming assistance. We build and check the Linear Hybrid Automata (LHA) model of the system automatically. We also present a quantifier elimination-based method to analyze the counterexample found and synthesize fix suggestions. We implemented a platform, MenShen, based on this framework and proposed techniques. We conducted sets of real HA-IoT case studies with up to 46 devices and 65 rules. Empirical results show that MenShen can find violations and generate rule fix suggestions in only 10 seconds.
Distal Vessel Occlusions: When to Consider Endovascular Thrombectomy.

See related article, p 1662 In recent years, endovascular thrombectomy (EVT) has revolutionized care for stroke patients with occlusions of the internal carotid or M1 segment middle cerebral artery.1 In the patient population with distal occlusions, for example, M2 segment, we face increasing heterogeneity with regards to clinical presentation (nondisabling versus disabling symptoms, high versus low eloquence), anatomic variability (number, location, and diameter of different M2 segments) and to our perception of imaging (relative amount of ischemic changes in the segment artery’s territory). Yet, there is growing evidence on safety and efficacy of EVT over standard care practice for M2 segment occlusions.2–4 Distally located clots have not been a primary focus of EVT trials thus far. In this issue, Grossberg et al5 report their experience on EVT for distal vessel occlusions beyond the M2 segment and in any anterior or posterior cerebral artery segment. The most frequent occlusions that were treated were in the M3 segment. From a strict procedural point of view, this report demonstrates the technical feasibility of reopening distal vessel occlusions in 83%. The chosen treatments were stent-retriever technology in 38% of cases, intraarterial thrombolysis in 37% of cases, and aspiration in 31% of cases. Notably, the reperfusion rates were highest when stent-retrievers could be deployed (92%). The report by Grossberg et al5 provides us with insight on …
The CYP71AZ P450 Subfamily: A Driving Factor for the Diversification of Coumarin Biosynthesis in Apiaceous Plants

The production of coumarins and furanocoumarins (FCs) in higher plants is widely considered a model illustration of the adaptation of plants to their environment. In this report, we show that the multiplication of cytochrome P450 variants within the CYP71AZ subfamily has contributed to the diversification of these molecules. Multiple copies of genes encoding this enzyme family are found in Apiaceae, and their phylogenetic analysis suggests that they have different functions within these plants. CYP71AZ1 from Ammi majus and CYP71AZ3, 4, and 6 from Pastinaca sativa were functionally characterized. While CYP71AZ3 merely hydroxylated esculetin, the other enzymes accepted both simple coumarins and FCs. Superimposing in silico models of these enzymes led to the identification of different conformations of three regions in the enzyme active site. These sequences were subsequently utilized to mutate CYP71AZ4 to resemble CYP71AZ3. The swapping of these regions lead to significantly modified substrate specificity. Simultaneous mutations of all three regions shifted the specificity of CYP71AZ4 to that of CYP71AZ3, exclusively accepting esculetin. This approach may explain the evolution of this cytochrome P450 family regarding the appearance of FCs in parsnip and possibly in the Apiaceae.
Optimal Infinite Horizon Decentralized Networked Controllers With Unreliable Communication

We consider a decentralized networked control system (DNCS) consisting of a remote controller and a collection of linear plants, each associated with a local controller. Each local controller directly observes the state of its colocated plant and can inform the remote controller of the plant's state through an unreliable uplink channel. The downlink channels from the remote controller to local controllers were assumed to be perfect. The objective of the local controllers and the remote controller is to cooperatively minimize the infinite horizon time average of expected quadratic cost. The finite horizon version of this problem was solved in our prior work (“Optimal local and remote controllers with unreliable uplink channels,” IEEE, May 2019). The optimal strategies in the finite horizon case were shown to be characterized by coupled Riccati recursions. In this article, we show that if the link failure probabilities are below certain critical thresholds, then the coupled Riccati recursions of the finite horizon solution reach a steady state and the corresponding decentralized strategies are optimal. Above these thresholds, we show that no strategy can achieve finite cost. We exploit a connection between our DNCS Riccati recursions and the coupled Riccati recursions of an auxiliary Markov jump linear system to obtain our results. Our main result in Theorem 1 explicitly identifies the critical thresholds for the link failure probabilities and the optimal decentralized control strategies when all link failure probabilities are below their thresholds.
Breaking down Leukemia Walls: Heteronemin, a Sesterterpene Derivative, Induces Apoptosis in Leukemia Molt4 Cells through Oxidative Stress, Mitochondrial Dysfunction and Induction of Talin Expression

Heteronemin, the most abundant secondary metabolite in the sponge Hippospongia sp. , exhibited potent cytotoxic activity against several cancer cell lines. It increased the percentage of apoptotic cells and reactive oxygen species (ROS) in Molt4 cells. The use of ROS scavenger, N-acetyl cysteine (NAC), suppressed both the production of ROS from mitochondria and cell apoptosis that were induced by heteronemin treatment. Heteronemin upregulated talin and phosphorylated talin expression in Molt4 cells but it only upregulated the expression of phosphorylated talin in HEK293 cells. However, pretreatment with NAC reversed these effects. Talin siRNA reversed the activation of pro-apoptotic cleaved caspases 3 and 9. On the other hand, the downstream proteins including FAK and NF-κB (p65) were not affected. In addition, we confirmed that heteronemin directly modulated phosphorylated talin expression through ROS generation resulting in cell apoptosis, but it did not affect talin/FAK complex. Furthermore, heteronemin interfered with actin microfilament and caused morphology changes. Taken together, these findings suggest that the cytotoxic effect of heteronemin is associated with oxidative stress and induction of phosphorylated talin expression. Our results suggest that heteronemin represents an interesting candidate which can be further developed as a drug lead against leukemia.
Self-Attentive Neural Collaborative Filtering

This paper has been withdrawn as we discovered a bug in our tensorflow implementation that involved accidental mixing of vectors across batches. This lead to different inference results given different batch sizes which is completely strange. The performance scores still remain the same but we concluded that it was not the self-attention that contributed to the performance. We are withdrawing the paper because this renders the main claim of the paper false. Thanks to Guan Xinyu from NUS for discovering this issue in our previously open source code.
Atrophy , hypometabolism and clinical trajectories in amyloid negative probable AD patients

About 15% of patients clinically diagnosed with Alzheimer’s disease do not show high tracer retention on amyloid PET. The present study investigates the clinical and demographic features, patterns of brain atrophy and hypometabolism and longitudinal clinical trajectories of these patients, with a particular emphasis on the AD-mimic typical amnestic subgroup. 38 amyloid PET-negative patients carrying a pre-PET diagnosis of AD (Aβneg-AD) from 4 centers (Amsterdam, Melbourne, San Francisco and Caen) were included in this study (11/27 females/males; mean age=67±9). Detailed clinical histories, including the clinical diagnoses before and after the PET scan and at follow-up (>2 years), were collected. Patients were classified according to their pre-PET clinical phenotype as amnestic (memory predominant), non-amnestic (predominant language, visuospatial or frontal symptoms), or non-specific (diffuse cognitive deficits). Demographic, clinical, neuropsychological, MRI and FDG-PET data obtained at the time of the amyloid-PET scan were compared between Aβneg-AD subgroups, 27 Aβ-positive AD cases with a typical amnestic clinical presentation (Aβpos-AD; 14/13 females/males; mean age=71±10) and 29 Aβ-negative cognitively healthy controls (Aβneg-HC; 15/14 females/males; mean age=69±12) matched for age, gender and education. There were 19 amnestic, 13 non-amnestic, and 7 non-specific Aβneg cases. Aβneg-AD subgroups did not differ in age, gender, education or APOE4 proportion. After the PET scan, clinicians altered the diagnosis in 68% of Aβneg-AD cases including 44% of amnestic versus 94% of non-amnestic and non-specific cases. Amnestic Aβneg-AD were most often reclassified as frontotemporal dementia, non-amnestic as frontotemporal dementia or corticobasal degeneration, and non-specific as dementia with Lewy bodies. The longer-term clinical followup was consistent with the post-PET diagnosis in most cases (89%), including in amnestic Aβneg-AD whose post-PET diagnosis remained AD. While the non-amnestic and non-specific Aβneg-AD usually showed patterns of atrophy and hypometabolism suggestive of another degenerative disorder, the amnestic Aβneg-AD had subtle atrophy and hypometabolism, restricted to the retrosplenium – posterior cingulate – posterior hippocampus junction. AβnegAD patients have heterogeneous clinical presentations and likely represent a mixed population of initially misdiagnosed, mostly neurodegenerative, conditions. The clinical, cognitive, MRI and FDG profiles aided to find an alternative post-PET diagnosis in most non-amnestic cases. In the largest and most intriguing subgroup of amnestic Aβneg-AD however, the patients mimic typical AD in their clinical presentation and follow-up, so that an alternative diagnosis was not made in more than half of the cases – highlighting the need for a clinical framework and terminology to define these patients, who may have underlying limbic-predominant, non-Aβdriven pathologies.
Cytomegalovirus infection in a patient with systemic lupus erythematosus and acute myocardial infarction – cause or causal relationship?

ABSTRACT The possible role of infectious and inflammatory states in the pathogenesis of atherosclerotic disease has been a matter of debate in the literature. There are case reports of active cytomegalovirus (CMV) infection unmasking underlying dormant systemic lupus erythematosus (SLE). CMV infection has also been postulated to be associated with atherosclerosis development in the coronaries. We present a unique case where a patient with newly diagnosed SLE and acute myocardial infarction was found to have high anti-CMV titers suggesting concomitant active CMV infection. A literature review has postulated strong affiliation of CMV infection with the development of coronary artery disease, an avenue which has yet to be explored further by ongoing research.
A Retrospective Review of the Clinical Characteristics and Blood Glucose Data from Cellnovo System Users using Data Collected from the Cellnovo Online Platform

Abstract Technological advances have led to innovative insulin delivery systems for patients with type 1 diabetes mellitus. In particular, the combination of miniature engineering and software algorithms contained in continuous subcutaneous insulin infusion (CSII) system pumps provide the user and the healthcare practitioner with an opportunity to review and adjust blood glucose (BG) levels according to system feedback, and to modify or programme their regimen according to their needs. While CSII pumps record a number of data parameters such as BG level, carbohydrate intake, activity and insulin delivered, these data are generally ‘locked in’ and can only be accessed by uploading to a cloud-based system, thus information is not contemporaneous. The Cellnovo Diabetes Management System (Cellnovo, Bridgend, UK) allows data to be transmitted securely and wirelessly in real time to a secure server, which is then retrieved by an online platform, the Cellnovo Online platform, enabling continuous access by the user and by clinicians. In this article, the authors describe a retrospective review of the patient data automatically uploaded to the Cellnovo Online platform. Baseline clinical and demographic characteristics collected at the start of pump therapy are shown for all patients, and BG data from a sub-cohort of patients who have been using the system for at least 6 months and who take and record an average of three BG level tests per day are presented to demonstrate glycaemic data over time.