Miracle-dz/UniFAR-FTUs huggingface dataset:
Primary Disruption of the Memory-Related Subsystems of the Default Mode Network in Alzheimer’s Disease: Resting-State Functional Connectivity MRI Study

Background: Recent studies have indicated that the default mode network (DMN) comprises at least three subsystems: The medial temporal lobe (MTL) and dorsal medial prefrontal cortex (DMPFC) subsystems and a core comprising the anterior MPFC (aMPFC) and posterior cingulate cortex (PCC). Additionally, the disruption of the DMN is related to Alzheimer’s disease (AD). However, little is known regarding the changes in these subsystems in AD, a progressive disease characterized by memory impairment. Here, we performed a resting-state functional connectivity (FC) analysis to test our hypothesis that the memory-related MTL subsystem was predominantly disrupted in AD. Method: To reveal specific subsystem changes, we calculated the strength and number of FCS in the DMN intra- and inter-subsystems across individuals and compared the FC of the two groups. To further examine which pairs of brain regional functional connections contributed to the subsystem alterations, correlation coefficients between any two brain regions in the DMN were compared across groups. Additionally, to identify which regions made the strongest contributions to the subsystem changes, we calculated the regional FC strength (FCS), which was compared across groups. Results: For the intra-subsystem, decreased FC number and strength occurred in the MTL subsystem of AD patients but not in the DMPFC subsystem or core. For the inter-subsystems, the AD group showed decreased FCS and number between the MTL subsystem and PCC and a decreased number between the PCC and DMPFC subsystem. Decreased inter-regional FCS were found within the MTL subsystem in AD patients relative to controls: The posterior inferior parietal lobule (pIPL) showed decreased FC with the hippocampal formation (HF), parahippocampal cortex (PHC) and ventral MPFC (vMPFC). Decreased inter-regional FCS of the inter-subsystems were also found in AD patients: The HF and/or PHC showed decreased FC with dMPFC and TPJ, located in the DMPFC subsystem, and with PCC. AD patients also showed decreased FC between the PCC and TLC of the dMPFC subsystem. Furthermore, the HF and PHC in the MTL subsystem showed decreased regional FCS. Conclusion: Decreased intrinsic FC was mainly associated with the MTL subsystem of the AD group, suggesting that the MTL subsystem is predominantly disrupted.
Global Non-convex Optimization with Discretized Diffusions

An Euler discretization of the Langevin diffusion is known to converge to the global minimizers of certain convex and non-convex optimization problems. We show that this property holds for any suitably smooth diffusion and that different diffusions are suitable for optimizing different classes of convex and non-convex functions. This allows us to design diffusions suitable for globally optimizing convex and non-convex functions not covered by the existing Langevin theory. Our non-asymptotic analysis delivers computable optimization and integration error bounds based on easily accessed properties of the objective and chosen diffusion. Central to our approach are new explicit Stein factor bounds on the solutions of Poisson equations. We complement these results with improved optimization guarantees for targets other than the standard Gibbs measure.
Towards Providing Explanations for AI Planner Decisions

In order to engender trust in AI, humans must understand what an AI system is trying to achieve, and why. To overcome this problem, the underlying AI process must produce justifications and explanations that are both transparent and comprehensible to the user. AI Planning is well placed to be able to address this challenge. In this paper we present a methodology to provide initial explanations for the decisions made by the planner. Explanations are created by allowing the user to suggest alternative actions in plans and then compare the resulting plans with the one found by the planner. The methodology is implemented in the new XAI-Plan framework.
Biogas Biocatalysis: Methanotrophic Bacterial Cultivation, Metabolite Profiling, and Bioconversion to Lactic Acid

Anaerobic digestion (AD) of waste substrates, and renewable biomass and crop residues offers a means to generate energy-rich biogas. However, at present, AD-derived biogas is primarily flared or used for combined heat and power (CHP), in part due to inefficient gas-to-liquid conversion technologies. Methanotrophic bacteria are capable of utilizing methane as a sole carbon and energy source, offering promising potential for biological gas-to-liquid conversion of AD-derived biogas. Here, we report cultivation of three phylogenetically diverse methanotrophic bacteria on biogas streams derived from AD of a series of energy crop residues. Strains maintained comparable central metabolic activity and displayed minimal growth inhibition when cultivated under batch configuration on AD biogas streams relative to pure methane, although metabolite analysis suggested biogas streams increase cellular oxidative stress. In contrast to batch cultivation, growth arrest was observed under continuous cultivation configuration, concurrent with increased biosynthesis and excretion of lactate. We examined the potential for enhanced lactate production via the employ of a pyruvate dehydrogenase mutant strain, ultimately achieving 0.027 g lactate/g DCW/h, the highest reported lactate specific productivity from biogas to date.
Polysomnographic Sleep Disturbances Due to High-Dose Zolpidem Use: A Case Report.

ABSTRACT Zolpidem is widely prescribed for the treatment of insomnia and is used to both induce and maintain sleep. Previously, zolpidem was thought to have low abuse potential; however, several reports have documented dose escalation and abuse in the past two decades. Here, we report the case of a patient with high-dose zolpidem dependence who underwent polysomnography (PSG) and the Multiple Sleep Latency Test (MSLT). The patient, a 29-year-old man, was administered zolpidem at doses of 300 to 1,200 mg/day, but he abused zolpidem to feel energetic. Consequently, he had a car accident while on a high dose, which the PSG revealed caused activation instead of sedation. The MSLT showed excessive daytime sleepiness despite a lack of subjective sleepiness under this condition. Our findings suggest that disrupted sleep and daytime sleepiness caused by supratherapeutic zolpidem doses could place individuals at high risk for accidents, including those who are unaware of sleepiness.
Enhanced Knock Code Authentication with High Security and Improved Convenience

Since smartphone contains various personal data, security is one of the important aspects in smartphone technologies. Up to now, various authentication techniques have been proposed to protect smartphones. The pattern lock on the Android system is one of the most widely used authentication methods for low-cost devices but it is known to be vulnerable to smudge attack or shoulder surfing attack. LG’s smartphone uses its own technique, which is called “Knock Code. ” The knock code completes the authentication by touching the user defined area in turn on the screen. In this paper, we propose the new, enhanced version of knock code by adding the sliding operation and by using flexible area recognition. We conducted security analysis, which shows that under the same password size, the search space is overwhelmingly larger than the original algorithm. Also, by using the sliding operation, the proposed scheme shows resilience against smudge attacks. We implemented the prototype of our scheme. Experimental results show that compared with the original Knock Code and Android pattern lock, our scheme is more convenient while providing better security.
Modeling Multimodal Dynamic Spatiotemporal Graphs

Spatiotemporal graphs (STGs) are a powerful tool for modeling multi-agent interaction scenarios, used commonly in human trajectory prediction and proactive planning and decision making for safe human-robot interaction. However, many current STG-backed methods rely on a static graph assumption, i.e. that the underlying graphical structure maintains the same nodes and edges throughout the scenario. This assumption is frequently broken in real-world applications, especially in highly-dynamic problems such as human trajectory prediction in crowds. To remove the reliance on this assumption, we present a methodology for modeling and predicting agent behavior in both highly dynamic and multimodal scenarios (i.e. where the scene's graphical structure is time-varying and there are many possible highly-distinct futures for each agent). Our approach to model dynamic STGs augments prior multimodal, multi-agent modeling methods with a gating function on edge models that smoothly adds and removes edge influence from a node. We demonstrate the performance of our approach on the ETH multi-human trajectory dataset and on NBA basketball player trajectories. Both are highly-dynamic, multimodal, and multi-agent interaction scenarios which serve as proxies for many robotic applications.
Distributed State Estimation Over Time-Varying Graphs: Exploiting the Age-of-Information

We study the problem of designing a distributed observer for an LTI system over a time-varying communication graph. The limited existing work on this topic imposes various restrictions either on the observation model or on the sequence of communication graphs. In contrast, we propose a single-time-scale distributed observer that works under mild assumptions. Specifically, our communication model only requires strong-connectivity to be preserved over nonoverlapping, contiguous intervals that are even allowed to grow unbounded over time. We show that under suitable conditions that bound the growth of such intervals, joint observability is sufficient to track the state of any discrete-time LTI system exponentially fast, at any desired rate. We also develop a variant of our algorithm that is provably robust to worst-case adversarial attacks, provided the sequence of graphs is sufficiently connected over time. The key to our approach is the notion of a “freshness-index” that keeps track of the age-of-information being diffused across the network. Such indices enable nodes to reject stale estimates of the state, and, in turn, contribute to stability of the error dynamics.
The Controversial Role of TGF-β in Neovascular Age-Related Macular Degeneration Pathogenesis

The multifunctional transforming growth factors-beta (TGF-βs) have been extensively studied regarding their role in the pathogenesis of neovascular age-related macular degeneration (nAMD), a major cause of severe visual loss in the elderly in developed countries. Despite this, their effect remains somewhat controversial. Indeed, both pro- and antiangiogenic activities have been suggested for TGF-β signaling in the development and progression of nAMD, and opposite therapies have been proposed targeting the inhibition or activation of the TGF-β pathway. The present article summarizes the current literature linking TGF-β and nAMD, and reviews experimental data supporting both pro- and antiangiogenic hypotheses, taking into account the limitations of the experimental approaches.
Circulating Levels of Osteopontin Predict Patients’ Outcome after Resection of Colorectal Liver Metastases

For colorectal liver metastases (CRLM), surgical resection is the only potentially curative therapy, but even successfully resected patients often face disease recurrence, leading to 5-year survival rate below 50%. Despite available preoperative stratification strategies, it is not fully elucidated which patients actually benefit from CRLM resection. Here we evaluated osteopontin, a secreted glyco-phosphoprotein, as a biomarker in the context of CRLM resection. Tissue levels of osteopontin were analysed in CRLM using reverse transcription polymerase chain reaction (RT-PCR) and immunohistochemistry. Pre- and postoperative osteopontin serum concentrations were analysed by enzyme-linked immunosorbent assay (ELISA) in 125 patients undergoing resection of CRLM as well as 65 healthy controls. Correlating with an upregulation of osteopontin tissue expression in CRLM, osteopontin serum levels were significantly elevated in patients with CRLM compared to healthy controls. Importantly, high pre- and post-operative osteopontin serum levels were associated with a poor prognosis after tumour resection. Patients with initial osteopontin serum levels above our ideal cut-off value of 264.4 ng/mL showed a significantly impaired median overall survival of 304 days compared to 1394 days for patients with low osteopontin levels. Together, our data suggest a role of osteopontin as a prognostic biomarker in patients with resectable CRLM that might help to identify patients who particularly benefit from liver resection.
Dynamic characteristics of the mitochondrial genome in SCNT pigs

Abstract Most animals generated by somatic cell nuclear transfer (SCNT) are heteroplasmic; inheriting mitochondrial genetics from both donor cells and recipient oocytes. However, the mitochondrial genome and functional mitochondrial gene expression in SCNT animals are rarely studied. Here, we report the production of SCNT pigs to study introduction, segregation, persistence and heritability of mitochondrial DNA transfer during the SCNT process. Porcine embryonic fibroblast cells from male and female Xiang pigs were transferred into enucleated oocytes from Yorkshire or Landrace pigs. Ear biopsies and blood samples from SCNT-derived pigs were analyzed to characterize the mitochondrial genome haplotypes and the degree of mtDNA heteroplasmy. Presence of nuclear donor mtDNA was less than 5% or undetectable in ear biopsies and blood samples in the majority of SCNT-derived pigs. Yet, nuclear donor mtDNA abundance in 14 tissues in F0 boars was as high as 95%. Additionally, mtDNA haplotypes influenced mitochondrial respiration capacity in F0 fibroblast cells. Our results indicate that the haplotypes of recipient oocyte mtDNA can influence mitochondrial function. This leads us to hypothesize that subtle developmental influences from SCNT-derived heteroplasmy can be targeted when using donor and recipient mitochondrial populations from breeds of swine with limited evolutionary divergence.
Mass spectrometric discrimination of phospholipid patterns in cisplatin-resistant and -sensitive cancer cells.

RATIONALE Development of therapy-resistant cancer is a major problem in clinical oncology, and there is an urgent need for novel markers identifying development of the resistant phenotype. Lipidomics represents a promising approach to discriminate lipid profiles of malignant phenotype cells. Alterations in phospholipid distribution or chemical composition have been reported in various pathologies including cancer. Here we were curious whether quantitative differences in phospholipid composition between cisplatin-resistant and -sensitive model cancer cell lines could be revealed by mass spectrometric means. METHODS The phospholipid contents of cell membranes of the cancer cell lines CCRF-CEM and A2780, both responsive and resistant to cisplatin, were analyzed by solid-phase extraction (SPE) and electrospray ionization mass spectrometry (ESI-MS and tandem mass spectrometry (MS/MS)). Extracts were obtained by disruption of cells with a dounce tissue grinder set followed by centrifugation. To minimize the enzymatic activity, phospholipids were extracted from cell extracts by SPE immediately after the cell lysis and analyzed by MS. Both supernatant and pellet fractions of cell extracts were analyzed. RESULTS A phospholipid profile specific for cell lines and their phenotypes was revealed. We have documented by quantitative analysis that phosphocholines PC P-34:0, PC 34:1, PC 20:2_16:0, LPC 18:1 and LPC 16:0 PLs were present in the 200-400 μM concentration range in CCRF-CEM cisplatin-responsive cells, but absent in their cisplatin-resistant cells. Similarly, PC 34:1, LPC 18:1 and LPC 16:0 were increased in cisplatin-responsive A2780 cells, and PC 20:2_16:0 was downregulated in cisplatin-resistant A2780 cells. CONCLUSIONS In this work we showed that the ESI-MS analysis of the lipid content of the therapy-resistant and -sensitive cells can clearly distinguish the phenotypic pattern and determine the potential tumor response to cytotoxic therapy. Lipid entities revealed by mass spectrometry and associated with development of therapy resistance can thus support molecular diagnosis and provide a potential complementary cancer biomarker.
Ecological fallacy as a novel risk factor for poor translation in neuroscience research: A systematic review and simulation study

Translational neuroscience is largely concerned with establishing causal links between biological processes and functional outcomes. Exciting new methods have emerged and top‐tier biomedical journals are placing increasingly high demand for experiments that link outcomes. One pitfall to making these connections is the “ecological fallacy”—establishing a relationship between outcomes based on aggregate (averaged) results (a distinct issue from correlation vs causation).
Patterns of Neuropsychological Dysfunction and Cortical Volume Changes in Logopenic Aphasia.

BACKGROUND Neuropsychological assessment can add essential information to the characterization of individuals presenting with the logopenic variant of primary progressive aphasia (lvPPA). OBJECTIVE This study examined the neuropsychological characteristics of lvPPA patients. We also examined differences in regional and whole brain atrophy based on neuropsychological profiles. METHODS We conducted a hierarchical cluster analysis on memory, executive functioning, and visuospatial neuropsychological test data for 56 individuals with lvPPA. We then compared resultant clusters to left middle temporal, inferior parietal, and superior parietal regions-of-interest using multivariate analysis of covariance. We also performed voxel-level analyses. RESULTS We identified three clusters characterized as lvPPA with no neurocognitive impairment (n = 5), lvPPA with mild neurocognitive deficits (n = 23), and lvPPA with marked cognitive deficits (n = 28). WAB-AQ was associated with left middle temporal volume. Superior parietal volumes were smaller for the lvPPA group with marked cognitive symptoms compared to the less severe groups. Voxel-level analyses showed greater atrophy in temporal, parietal, lateral occipital, and frontal regions, left worse than right. Age, disease duration, gender, WAB-AQ, and PiB-PET did not account for differences between groups. CONCLUSIONS LvPPA patients without cognitive deficits in other domains were relatively uncommon while 50% of our sample exhibited pronounced neurocognitive deficits outside the language domain. Pronounced cognitive deficits in lvPPA are associated with widespread atrophy, left worse than right. Our study underscores the importance of examining neuropsychological function in addition to language in patients with lvPPA.
Cross-Sectoral Information Transfer in the Chinese Stock Market around Its Crash in 2015

This paper applies effective transfer entropy to research the information transfer in the Chinese stock market around its crash in 2015. According to the market states, the entire period is divided into four sub-phases: the tranquil, bull, crash, and post-crash periods. Kernel density estimation is used to calculate the effective transfer entropy. Then, the information transfer network is constructed. Nodes’ centralities and the directed maximum spanning trees of the networks are analyzed. The results show that, in the tranquil period, the information transfer is weak in the market. In the bull period, the strength and scope of the information transfer increases. The utility sector outputs a great deal of information and is the hub node for the information flow. In the crash period, the information transfer grows further. The market efficiency in this period is worse than that in the other three sub-periods. The information technology sector is the biggest information source, while the consumer staples sector receives the most information. The interactions of the sectors become more direct. In the post-crash period, information transfer declines but is still stronger than the tranquil time. The financial sector receives the largest amount of information and is the pivot node.
A cost model for a graph-based intermediate-representation in a dynamic compiler

Compilers provide many architecture-agnostic, high-level optimizations trading off peak performance for code size. High-level optimizations typically cannot precisely reason about their impact, as they are applied before the final shape of the generated machine code can be determined. However, they still need a way to estimate their transformation’s impact on the performance of a compilation unit. Therefore, compilers typically resort to modelling these estimations as trade-off functions that heuristically guide optimization decisions. Compilers such as Graal implement many such handcrafted heuristic trade-off functions, which are tuned for one particular high-level optimization. Heuristic trade-off functions base their reasoning on limited knowledge of the compilation unit, often causing transformations that heavily increase code size or even decrease performance. To address this problem, we propose a cost model for Graal’s high-level intermediate representation that models relative operation latencies and operation sizes in order to be used in trade-off functions of compiler optimizations. We implemented the cost model in Graal and used it in two code-duplication-based optimizations. This allowed us to perform a more fine-grained code size trade-off in existing compiler optimizations, reducing the code size increase of our optimizations by up to 50% compared to not using the proposed cost model in these optimizations, without sacrificing performance. Our evaluation demonstrates that the cost model allows optimizations to perform fine-grained code size and performance trade-offs outperforming hard-coded heuristics.
A Stepwise NaHSO3 Addition Mode Greatly Improves H2 Photoproduction in Chlamydomonas reinhardtii

NaHSO3 addition greatly increases the yield of H2 photoproduction in a unicellular green alga Chlamydomonas reinhardtii through removing O2 and activating hydrogenase but significantly impairs the activity of PSII, an electron source for H2 photoproduction. Here, a stepwise addition mode of total 13 mM NaHSO3, an optimal concentration for H2 photoproduction of C. reinhardtii identified in a previous one step addition method, significantly improved H2 photoproduction. Such improvement was believed to be the result of increased residual PSII activity in an anaerobic background, but was at least independent of two alternative electron sinks for H2 photoproduction, cyclic electron transport around PSI and CO2 assimilation. Based on the above results, we propose that increased residual PSII activity in an anaerobic environment is an efficient strategy to enhance H2 photoproduction in C. reinhardtii, and the stepwise NaHSO3 addition mode is a case study in the strategy.