Miracle-dz/UniFAR-FTUs huggingface dataset:
Sensor Placement and Leakage Isolation with Differential Evolution

Leakages in water distribution systems (WDS) can cause significant economic losses. Therefore finding leaks in water pipes is nowadays a crucial task for water utilities. In this paper, the effects of leakages on the hydraulics of WDS, particularly with regard to flow and pressure, are investigated. From the discrepancy of the unperturbed and the perturbed WDS due to the occurrence of leakage a methodology is developed, which enables an efficient sensor placement of flow meters and pressure sensors. This is achieved by a Fault Sensitivity Matrix (FSM). A special Genetic Algorithm (GA) called Differential Evolution (DE), which saves significantly on computation time in large WDS, is used to find the optimal position of a minimum number of sensors. DE is chosen because of its good rate of convergence.Once an optimal sensor placement is obtained, DE is also used for leakage location. The methodology was tested in two different WDS. The first WDS is the model network Poulakis (2003) used. The second is a partial network in the city of Linz, where the task is to find an ideal sensor placement to guarantee efficient leakage isolation. In this paper we show that DE performs excellent on both tasks, the sensor placement and the leakage isolation, for the two investigated systems. Additionally the implementation of demand and measurement uncertainties is outlined.
Engineering Macrophage Exosome Disguised Biodegradable Nanoplatform for Enhanced Sonodynamic Therapy of Glioblastoma

Sonodynamic therapy (SDT) exhibits high tissue penetration and negligible radiation damage to normal tissues, and thus emerges as a promising cancer therapeutic modality for glioblastoma (GBM). However, the blood−brain barrier (BBB) and hypoxic microenvironment greatly limit the SDT efficiency. In this work, a biodegradable nanoplatform (termed as CSI) is fabricated by encapsulating catalase (CAT) into silica nanoparticles (CAT@SiO2) for tumor hypoxia relief, and then loaded with the sonosensitizer indocyanine green (ICG). Inspired by the ability of macrophages to cross the BBB, CSI is further coated with AS1411 aptamer‐modified macrophage exosomes to form CSI@Ex‐A, which possesses efficient BBB penetration and good cancer‐cell‐targeting capability. After tumor cell endocytosis, highly expressed glutathione (GSH) triggeres biodegradation of the nanoplatform and the released CAT catalyzes hydrogen peroxide (H2O2) to produce O2 to relieve tumor hypoxia. The GSH depletion and O2 self‐supplying effectively enhances the SDT efficiency both in vitro and in vivo. In addition, the resulting CSI@Ex‐A exhibits good biocompatibility and long circulation time. These findings demonstrate that CSI@Ex‐A may serve as a competent nanoplatform for GBM therapy, with potential for clinical translation.
A randomized controlled trial of supervised remotely-delivered attention bias modification for posttraumatic stress disorder

Abstract Background Many individuals with posttraumatic stress disorder (PTSD) have limited access to first-line treatments, warranting the development of remotely-delivered treatments. Attention bias modification (ABM), targeting perturbed threat-related attentional patterns, shows promise when delivered in-person. However, previous studies found ABM to be ineffective when delivered remotely. Randomized clinical trials usually applied two variations of ABM: ABM away from threat or attention control training (ACT) balancing attention between threat-related and neutral stimuli. We tested remotely-delivered ACT/ABM with tighter supervision and video-based interactions that resemble in-clinic protocols. We expected to replicate the results of in-clinic trials, in which ACT outperformed ABM for PTSD. Methods In this double-blinded, parallel-group randomized controlled trial, 60 patients diagnosed with PTSD were randomized (ABM n = 30; ACT n = 30). Patients performed eight bi-weekly remotely-delivered supervised ABM/ACT sessions. Symptoms were assessed pre- and post-treatment with Clinician-Administered PTSD Scale 5 (CAPS-5) severity score and PTSD diagnosis as the primary outcomes. Current depressive episode, current anxiety-related comorbidity, and time elapsed since the trauma were examined as potential moderators of treatment outcome. Results Significant decrease in CAPS-5 severity scores and PTSD diagnosis was observed following both ACT and ABM with no between-group difference. Patients without depression or whose trauma occurred more recently had greater symptom reduction in the ACT than the ABM group. Conclusions Contrary to our expectation, symptoms decreased similarly following ACT and ABM. Moderator analyses suggest advantage for ACT in non-depressed patients and patients whose trauma occurred more recently. Further refinements in remotely-delivered ABM/ACT may be needed.
Protein-lipid interaction at low pH induces oligomerization of the MakA cytotoxin from Vibrio cholerae

The α-pore-forming toxins (α-PFTs) from pathogenic bacteria damage host cell membranes by pore formation. We demonstrate a remarkable, hitherto unknown mechanism by an α-PFT protein from Vibrio cholerae. As part of the MakA/B/E tripartite toxin, MakA is involved in membrane pore formation similar to other α-PFTs. In contrast, MakA in isolation induces tube-like structures in acidic endosomal compartments of epithelial cells in vitro. The present study unravels the dynamics of tubular growth, which occurs in a pH-, lipid-, and concentration-dependent manner. Within acidified organelle lumens or when incubated with cells in acidic media, MakA forms oligomers and remodels membranes into high-curvature tubes leading to loss of membrane integrity. A 3.7 Å cryo-electron microscopy structure of MakA filaments reveals a unique protein-lipid superstructure. MakA forms a pinecone-like spiral with a central cavity and a thin annular lipid bilayer embedded between the MakA transmembrane helices in its active α-PFT conformation. Our study provides insights into a novel tubulation mechanism of an α-PFT protein and a new mode of action by a secreted bacterial toxin.
Vibrio cholerae was found in cultured bullfrog

Abstract Bullfrog is one of the most important economic aquatic animals in China that is widely cultured in southern China and is a key breed recommended as an industry of poverty alleviation in China. During recent years, a fatal bacterial disease has often been found in cultured bullfrogs. The clinical manifestations of the diseased bullfrogs were severe intestinal inflammation and an anal prolapse. A bacterial pathogen was isolated from the diseased bullfrog intestines. The bacterium was identified as Vibrio cholerae using morphological, biochemical and 16S rRNA phylogenetic analysis. In this study, V. cholerae was isolated and identified in diseased bullfrogs for the first time, providing a basis for the diagnosis and control of the disease. Therefore, attention should be paid to the modes of transmission of V. cholerae from bullfrog and formulate reasonable safety measures.
ADAM8 signaling drives neutrophil migration and ARDS severity

Acute respiratory distress syndrome (ARDS) results in catastrophic lung failure and has an urgent, unmet need for improved early recognition and therapeutic development. Neutrophil influx is a hallmark of ARDS and is associated with the release of tissue-destructive immune effectors, such as matrix metalloproteinases (MMPs) and membrane-anchored metalloproteinase disintegrins (ADAMs). Here, we observed using intravital microscopy that Adam8–/– mice had impaired neutrophil transmigration. In mouse pneumonia models, both genetic deletion and pharmacologic inhibition of ADAM8 attenuated neutrophil infiltration and lung injury while improving bacterial containment. Unexpectedly, the alterations of neutrophil function were not attributable to impaired proteolysis but resulted from reduced intracellular interactions of ADAM8 with the actin-based motor molecule Myosin1f that suppressed neutrophil motility. In 2 ARDS cohorts, we analyzed lung fluid proteolytic signatures and identified that ADAM8 activity was positively correlated with disease severity. We propose that in acute inflammatory lung diseases such as pneumonia and ARDS, ADAM8 inhibition might allow fine-tuning of neutrophil responses for therapeutic gain.
An Efficient

—The optimization methods for solving the normalized cut model usually involve three steps, i.e., problem relaxation, problem solving and post-processing. However, these methods are problematic in both performance since they do not directly solve the original problem, and efﬁciency since they usually depend on the time-consuming eigendecomposition and k -means (or spectral rotation) for post-processing. In this paper, we propose a fast optimization method to speedup the classical normalized cut clustering process, in which an auxiliary variable is introduced and alternatively updated along with the cluster indicator matrix. The new method is faster than the conventional three-step optimization methods since it solves the normalized cut problem in one step. Theoretical analysis reveals that the new method is able to monotonically decrease the normalized cut objective function and converge in ﬁnite iterations. Moreover, we have proposed efﬁcient methods for adjust two regularization parameters. Extensive experimental results show the superior performance of the new method. Moreover, it is faster than the existing methods for solving the normalized cut.
Infrared spectrometric biomarkers for ulcerative colitis screening using human serum samples

This study uses infrared spectrometry coupled with data analysis techniques to understand colitis‐induced alterations in the molecular components of serum samples. Using samples from 18 ulcerative colitis patients and 28 healthy volunteers, we assessed features such as absorbance values at wavenumbers of 1033 and 1076 cm−1, and the ratios at 1121 versus 1020 cm−1 and 1629 versus 1737 cm−1. Through the deconvolution of the amide I band, protein secondary structure analysis was performed. Colitis‐induced alterations are reflected as fluctuations in the vibrational modes, and are used to identify associated spectral signatures. The results of the study show statistically significant differences in five identifying spectral signatures. Among them, the sensitivity and specificity of the spectral signature, I1121/I1020, were 100% and 86%, respectively. These findings resemble our earlier proof‐of‐concept investigations in mouse models and provide preliminary evidence that this could be a reliable diagnostic test for human patients.
Biased and inflexible interpretations of ambiguous social situations: Associations with eating disorder symptoms and socioemotional functioning.

BACKGROUND Research indicates that difficulties across multiple socioemotional functioning domains (e.g., social emotion expression/regulation, response to social elicitors of emotion) and negatively biased interpretations of ambiguous social situations may affect eating disorder symptoms. The impact of inflexible interpretations of social situations on eating disorder symptoms is less clear. The present study therefore examined relations between inflexible and biased social interpretations, socioemotional functioning, and eating disorder symptoms. METHOD A total of 310 participants from the general population, recruited from an online crowdsourcing platform, completed measures of socioemotional functioning (e.g., rejection sensitivity, negative social exchange), eating disorder symptoms, and positive and negative interpretation bias and inflexibility on a single measurement occasion. RESULTS Socioemotional functioning impairments (Pillai's trace = 0.11, p < .001), but not negative (β = .07, p = .162) or positive (β = -.01, p = .804) interpretation bias or inflexible interpretations (β = .04, p = .446), were associated with eating disorder symptoms in multiple regression models. In network analyses controlling statistically for multiple markers of socioemotional functioning, eating disorder symptoms were directly associated with negative (but not positive) interpretation bias. Inflexible interpretations were indirectly linked to symptoms via co-dampening of positive emotions. Exploratory causal discovery analyses suggested that several socioemotional functioning variables (social anxiety, depression, negative social exchange) may cause eating disorder symptoms. CONCLUSIONS Consistent with cognitive-interpersonal models of disordered eating, our results suggest that less accurate (biased, inflexible) interpretations of social information contribute to patterns of cognition (anxious anticipation of rejection) and emotion regulation (down-regulation of positive social emotion) thought to encourage disordered eating. PUBLIC SIGNIFICANCE This study suggests that less accurate interpretations of ambiguous social information encourage anxious anticipation of rejection and downregulation of positive social emotions, both of which are thought to promote eating disorder symptoms. Knowledge provided by this study about the likely relations between interpretive processes, social/emotional functioning, and eating disorder symptoms may help inform treatments for eating disorders, particularly those that attempt to modify patterns of interpretation.
Physician Satisfaction With Telehealth: A Systematic Review and Agenda for Future Research

Background and Objectives: The use of telehealth has risen dramatically due to the Covid-19 pandemic and is expected to be a regular part of patient care moving forward. We know little currently about how satisfied physicians are with this type of patient care. The present systematic review examines physician satisfaction with telehealth, as physician acceptance remains vital to telehealth gaining wider and more permanent adoption. Methods: A PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses)–guided systematic review of empirical articles published between 2010 and 2020 that contain a finding examining physician satisfaction with using telehealth, using 4 article databases (PubMed, Web of Science, COCHRANE, and CINAHL), to identify relevant studies. A standardized data abstraction Excel sheet was used to extract relevant information from each of the included studies. Relevant study findings related to physician satisfaction with telehealth were reviewed for each of the 37 studies by the coauthors. Results: A total of 37 published studies were included in the review. Thirty-three of the 37 (89%) studies reviewed were classified as having findings showing moderate to high levels of physician satisfaction with telehealth. Just under 60% of the studies focused on physician satisfaction with providing telemedicine to patients (21/37). Twelve other studies focused on physician satisfaction with teleconsultations with other providers. Four studies examined physician satisfaction with both. The type of patient telemedicine or provider teleconsultation performed varied greatly across the 37 studies, with several different diagnoses or care situations included. Research designs used in the studies were less robust, with all studies using primary data for assessing physician satisfaction but only one study providing any type of multivariate analysis of physician satisfaction with telehealth. Conclusion: The results of this review support the observation that physicians across different specialties, geographic locations, practice locations, and care situations appear satisfied with engaging in telehealth for both patient care and consultations with other physicians. The research on telehealth should be enhanced, given how ubiquitous telehealth has become due to the Covid-19 pandemic. This enhancement should include larger physician sample sizes in studies of telehealth satisfaction; more research focused on telehealth in the primary care setting; and the types of virtual modalities that have become more commonplace for physicians to use due to the Covid-19 pandemic.
Analysis of the influence of glutathione S-transferase (GSTM1 and GSTT1) genes on the risk of essential hypertension

Abstract Background Essential hypertension (EH) results from a complex interaction between environmental factors and an individual’s genetic background. Aim To assess the relationship between polymorphisms in GSTM1 and GSTT1 and the risk of EH. Subjects and methods A multiplex-PCR was used to identify the genotypic profiles of GSTM1 and GSTT1 in 160 patients and 210 controls. Results The frequency of GSTM1-null genotype was higher in patients younger than 61 years when compared to those over 61 years. Interestingly, GSTT1-null was significantly associated with the risk of EH (OR 4; 95% CI 2.6–6.3; p < 0.0001). While GSTM1-null showed no trend (OR 0.7; 95% CI 0.5–1.1, p = 0.12). Individuals carrying the combined GSTT1-null/GSTM1-null were 2.4 times more at risk for hypertension compared to those harbouring the combined GSTT1-present/GSTM1-present genotype (OR 2.4; 95% CI 1.3–4.4; p = 0.005). Additionally, the presence of the combined GSTT1-null/GSTM1-present was associated with an increased risk of EH compared to GSTT1-present/GSTM1-present carriers (OR 6.75; 95% CI 3.4–13.2; p < 0.0001). Conclusion This study showed that the GSTT1-null alone or in interaction with GSTM1-present or GSTM1-null was associated with a higher risk of hypertension. Moreover, the GSTM1-null seems to be associated with the age of onset of hypertension.
DeepUCT: Complex cascaded deep learning network for improved ultrasound tomography

Ultrasound computed tomography is an inexpensive and radiation-free medical imaging technique used to quantify the tissue acoustic properties for advanced clinical diagnosis. Image reconstruction in ultrasound tomography is often modeled as an optimization scheme solved by iterative methods like full-waveform inversion. These iterative methods are computationally expensive, while the optimization problem is ill-posed and nonlinear. To address this problem, we propose to use deep learning to overcome the computational burden and ill-posedness, and achieve near real-time image reconstruction in ultrasound tomography. We aim to directly learn the mapping from the recorded time-series sensor data to a spatial image of acoustical properties. To accomplish this, we develop a deep learning model using two cascaded convolutional neural networks with an encoder–decoder architecture. We achieve a good representation by first extracting the intermediate mapping-knowledge and later utilizing this knowledge to reconstruct the image. This approach is evaluated on synthetic phantoms where simulated ultrasound data are acquired from a ring of transducers surrounding the region of interest. The measurement data is acquired by forward modeling the wave equation using the k-wave toolbox. Our simulation results demonstrate that our proposed deep-learning method is robust to noise and significantly outperforms the state-of-the-art traditional iterative method both quantitatively and qualitatively. Furthermore, our model takes substantially less computational time than the conventional full-wave inversion method.
High-resolution structure-function mapping of intact hearts reveals altered sympathetic control of infarct border zones

Remodeling of injured sympathetic nerves on the heart after myocardial infarction (MI) contributes to adverse outcomes such as sudden arrhythmic death, yet the underlying structural mechanisms are poorly understood. We sought to examine microstructural changes on the heart after MI and to directly link these changes with electrical dysfunction. We developed a high-resolution pipeline for anatomically precise alignment of electrical maps with structural myofiber and nerve-fiber maps created by customized computer vision algorithms. Using this integrative approach in a mouse model, we identified distinct structure-function correlates to objectively delineate the infarct border zone, a known source of arrhythmias after MI. During tyramine-induced sympathetic nerve activation, we demonstrated regional patterns of altered electrical conduction aligned directly with altered neuroeffector junction distribution, pointing to potential neural substrates for cardiac arrhythmia. This study establishes a synergistic framework for examining structure-function relationships after MI with microscopic precision that has potential to advance understanding of arrhythmogenic mechanisms.
Quantifying the risks versus benefits of the Pfizer COVID-19 vaccine in Australia: a Bayesian network analysis

The Pfizer COVID-19 vaccine is associated with increased myocarditis incidence. Constantly evolving evidence regarding incidence and case fatality of COVID-19 and myocarditis related to infection or vaccination, creates challenge for risk-benefit analysis of vaccination programs. Challenges are complicated further by emerging evidence of waning vaccine effectiveness, and variable effectiveness against variants. Here, we build on previous work on the COVID-19 Risk Calculator (CoRiCal) by integrating Australian and international data to inform a Bayesian network that calculates probabilities of outcomes for the Delta variant under different scenarios of Pfizer COVID-19 vaccine coverage, age groups ([≥]12 years), sex, community transmission intensity and vaccine effectiveness. The model estimates that in a population where 5% were unvaccinated, 5% had one dose, 60% had two doses and 30% had three doses, the probabilities of developing and dying from COVID-19-related myocarditis were 239-5847 and 1430-384,684 times higher (depending on age and sex), respectively, than developing vaccine-associated myocarditis. For one million people with this vaccine coverage, where transmission intensity was equivalent to 10% chance of infection over two months, 68,813 symptomatic COVID-19 cases and 981 deaths would be prevented, with 42 and 16 expected cases of vaccine-associated myocarditis in males and females, respectively. The model may be updated to include emerging best evidence, data pertinent to different countries or vaccines, and other outcomes such as long COVID.