Miracle-dz/UniFAR-FTUs huggingface dataset:
Case Report: Treatment of Delusions of Theft Based on the Assessment of Photos of Patients' Homes

Background The occurrence of behavioral and psychological symptoms of dementia is affected by individualized context. However, details regarding delusion of theft have been poorly documented. This report describes a useful assessment to understand the environmental context of delusion through two cases of Alzheimer's disease (AD). Familial interview was conducted to assess the phenomenological features. Photos of patients' homes were used to increase the assessment accuracy and check the individualized environmental contexts; this is known as Photo Assessment of Living Environment (PA-LE). Case Description Case 1 was of an 88-year-old woman whose Mini-Mental State Examination (MMSE) score was 23/30. She believed that one neighbor stole her wallet and stored it on a shelf in the living room. She sometimes placed it in other places, such as under the bed as safekeeping. The delusion often occurred when getting ready to go shopping. PA-LE confirmed that the room and shelf were not cluttered, although the incorrect storage place seemed to be hard-to-find. Case 2 was of a 78-year-old woman. The MMSE score was 20/30. She believed that some neighbors stole her garden items. The delusion was limited to her garden, yet the items were varied. Auditory hallucinations exacerbated her belief that the neighbors intruded the garden. PA-LE confirmed that the garden was cluttered with several duplicated items. Moreover, the patient inaccurately remembered the condition of the garden. Non-pharmacological approaches were tailored to the patients' environmental and psychological states, referring to the interview and PA-LE. This included environmental adjustment or increasing self-esteem. Antipsychotics were also prescribed. Environmental and psychological triggers of delusion were improved by the interventions, and the patients had uneventful courses without active delusions. Conclusion Evaluating patients' homes using photos could detect the environmental context of delusion of theft among patients with AD and assist in the management.
Case Report: Clinical and Hematological Characteristics of εγδβ Thalassemia in an Italian Patient

Introduction εγδβ thalassemia is a rare form of β-thalassemia mostly described in children originating from Northern Europe. Only anecdotic cases from the Mediterranean area are reported. The diagnosis is challenging, considering the rarity of the disease and its heterogeneous clinical presentation. Most patients have neonatal microcytic anemia, sometimes requiring in utero and/or neonatal transfusions, and typically improving with age. Case Description We report on an Italian newborn presenting with severe neonatal anemia that required red blood cell transfusion. After the first months of life, hemoglobin levels improved with residual very low mean corpuscular volume. β and α thalassemia, IRIDA syndrome, and sideroblastic anemia were excluded. Finally, a diagnosis of εγδβ thalassemia was made after microarray analysis of single nucleotide polymorphisms revealed a 26 kb single copy loss of chromosome 11p15.4, including the HBD, HBBP1, HBG1, and HBB genes. Conclusions Despite its rarity, the diagnosis of εγδβ thalassemia should be considered in newborns with severe neonatal anemia requiring in utero and/or neonatal transfusions, but also in older infants with microcytic anemia, after excluding more prevalent red blood cell disorders.
MD2 Is a Potential Biomarker Associated with Immune Cell Infiltration in Gliomas

Background Glioma is the most common primary malignant tumor in the central nervous system. Myeloid differentiation protein 2 (MD2) acts as a coreceptor of toll-like receptor 4 (TLR4) to mediate innate immune response. However, the actual roles of MD2 in the regulation of progression and immune cell infiltration in gliomas remain largely unclear. This study aims to explore whether MD2 could be an independent prognostic factor through the mediation of immune cell infiltration in gliomas. Methods The mRNA expression and DNA methylation differential analyses of MD2 were performed using CGGA, TCGA and Rembrandt databases and survival analyses were performed using Kaplan-Meier plotter. Univariate and multivariate Cox regression was applied to analyze the prognostic value of MD2 and nomograms were constructed to evaluate the clinical value of MD2. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were utilized to analyze MD2-related signal pathways. Furthermore, correlations between MD2 and immune cell infiltration were calculated by TIMER and CIBERSOPT. The correlation between MD2 expression and the infiltrations of macrophages and neutrophils was experimentally verified by the knockdown of MD2 expression using small interfering RNA (siRNA) in glioma cells. Results We found that MD2 was overexpressed and associated with a poor prognosis in gliomas. Meanwhile, higher expression of MD2 could be a result of lower DNA methylation of MD2 gene in gliomas. In addition, univariate and multivariate Cox regression analysis indicated that MD2 could be an independent prognostic factor for gliomas. Further functional enrichment analysis revealed that the functions of MD2 were closely related to immune responses. Moreover, the expression level of MD2 was strongly correlated with the infiltration and polarization of pro-tumor phenotype of tumor-associated macrophages and tumor-associated neutrophils in gliomas. Conclusions These findings have provided strong evidence that MD2 could be served as a valuable immune-related biomarker to diagnose and predict the progression of gliomas.
Multilocus Sequence Typing and Antifungal Susceptibility of Vaginal and Non-vaginal Candida glabrata Isolates From China

Candida glabrata is a common cause of Candida infections. In our present study, we investigated the antifungal susceptibility and molecular epidemiology of vaginal and non-vaginal C. glabrata isolates. Seventy-six vaginal C. glabrata strains isolated from patients with vulvovaginal candidiasis and 57 non-vaginal C. glabrata isolates were collected at two hospitals in Shanghai, China. Antifungal susceptibility was examined using a broth microdilution method. Multilocus sequence typing was used for genotyping. Overall, 28 (21.1%), 28 (21.1%), and 29 (21.8%) C. glabrata isolates were resistant to fluconazole, itraconazole, and voriconazole, respectively. Briefly, 18 (23.7%), 18 (23.7%), and 19 (25%) vaginal strains were resistant to fluconazole, itraconazole, and voriconazole. While the resistance to these antifungals were all 17.5% (10/57) in non-vaginal strains. All isolates retained susceptibility to amphotericin B, and only four non-vaginal isolates were caspofungin resistant. Genotyping identified 17 ST patterns. In non-vaginal samples, the same genotypes appear as in the vaginal samples, except for one genotype (ST-182), while in the vaginal samples more genotypes appear (ST8, ST19, ST45, ST55, ST66, ST80, ST138, and ST17). The most common genotype was ST7 (81 strains), followed by ST10 (14 strains) and ST15 (11 strains). The majority of resistant phenotype strains (25/30, 83.3%) correlated to the predominant genotype (ST7), and the rest belonged to ST3 (2/30, 6.7%), ST10 (1/30, 3.3%), ST19 (1/30, 3.3%), and ST45 (1/30, 3.3%). Our survey revealed cross-resistance in vaginal and non-vaginal C. glabrata isolates. Moreover, there is no genotype associated with the resistance phenotype.
Event Detection and Identification in Distribution Networks Based on Invertible Neural Networks and Pseudo Labels

Anomalous event detection and identification are important to support situational awareness and security analysis in power grids. Particularly, the distribution network is with complicated topology, variable load behaviors, and integration of nonlinear distributed generators (DGs), which is difficult to implement complete modeling mathematically. With the deployment of advanced measurement devices such as μPMUs in distribution networks, massive data containing rich system status information becomes available. In this paper, a framework for event detection, localization, and classification is studied to extract event features from measurements in distribution networks. Specifically, a method based on an invertible neural network (INN) is employed to model the complex distributions of normal-state measurements offline in a flexible way. It then establishes explicit likelihoods as the indicator to enable real-time event detection. Furthermore, a Jacobian-based method is utilized for spatial localization. Finally, as the events in practical power grids are mostly recorded unlabeled, the pseudo label (PL) based approach, superior in the separating ability for events under a low labeling rate, and is used to implement event classification. Several typical types of events simulated in the IEEE 34-bus system and real-world cases in a low-voltage system verify the effectiveness and superiorities of the framework.
A Data-Driven Customer-Search Modeling With the Consideration of Traffic Environment

In order to explore the determinants of vacant taxi drivers' customer-search behavior, this paper intends to calibrate a time-dependent Multinomial Logit (MNL) model by mining over 1.6 billion GPS records from about 8,400 taxis in Shanghai, China. First, based on the ordering points to identify the clustering structure (OPTICS) algorithm, the downtown area of Shanghai city is divided into 47 hotspots to identify the hot areas of customer delivery and searching. Then, by investigating a typical search delivery process of a vacant taxi, five candidate factors that may affect the customer-search behavior are summarized and defined. Using the maximum likelihood method, the significant factors are finally found. The results reveal that the relative passenger demand, the regional likelihood of pick-ups as well as the expected rate of return are the most significant factors influencing customer-search behavior. Although the impact of traffic situation (i.e., the en-route delay and traffic condition of the target hotspot) is not particularly significant, service providers and policymakers should still take full advantage of it to schedule taxi service and mitigate the traffic congestion caused by the circulation of vacant taxis. Besides, this paper also shows that the customer-search behavior of a vacant taxi driver varies with the time of day. Findings in this paper are expected to provide comprehensive insights about factors that should be considered in the future operation pattern of a taxi service system where human driver taxis and self-driving taxis are mixed.
Modulation of ERCC1-XPF Heterodimerization Inhibition via Structural Modification of Small Molecule Inhibitor Side-Chains

Inhibition of DNA repair enzymes is an attractive target for increasing the efficacy of DNA damaging chemotherapies. The ERCC1-XPF heterodimer is a key endonuclease in numerous single and double strand break repair processes, and inhibition of the heterodimerization has previously been shown to sensitize cancer cells to DNA damage. In this work, the previously reported ERCC1-XPF inhibitor 4 was used as the starting point for an in silico study of further modifications of the piperazine side-chain. A selection of the best scoring hits from the in silico screen were synthesized using a late stage functionalization strategy which should allow for further iterations of this class of inhibitors to be readily synthesized. Of the synthesized compounds, compound 6 performed the best in the in vitro fluorescence based endonuclease assay. The success of compound 6 in inhibiting ERCC1-XPF endonuclease activity in vitro translated well to cell-based assays investigating the inhibition of nucleotide excision repair and disruption of heterodimerization. Subsequently compound 6 was shown to sensitize HCT-116 cancer cells to treatment with UVC, cyclophosphamide, and ionizing radiation. This work serves as an important step towards the synergistic use of DNA repair inhibitors with chemotherapeutic drugs.
Does Environmental Information Disclosure Improve the Health Level of Middle-Aged and Old Residents? Evidence From China

Objective The purpose of this study is to empirically examine the impact of environmental information disclosure on the health of middle-aged and old residents and investigate whether such disclosure can improve the health of middle-aged and old residents. Methods This study matches the data of the Pollution Information Transparency Index (PITI) and China Health and Retirement Longitudinal Study in 2018 and uses the ordered logistic regression model to assess the impact of environmental information disclosure on the health of middle-aged and old residents. Furthermore, stepwise regression, ordinary least square, and ordered probit regression models are used for robustness tests. The IV-Ordered probit regression model solves the endogenous problem. Results Environmental information disclosure has a significant positive correlation with the health level of middle-aged and old residents. After the robustness test and endogenous problem handling, this conclusion still holds. Estimation results show that when PITI increases by 1 unit, the probability of improving the self-reported health level and actual health level of middle-aged and old residents increases by 1 and 0.87%, respectively. The impact of environmental information disclosure on the health of middle-aged and old residents also has significant regional heterogeneity. Specifically, the impact is mainly reflected in the central region of China. Conclusion Environmental information disclosure can improve the health of middle-aged and old residents. To improve the health of middle-aged and old residents, it is necessary to implement and enhance the environmental information disclosure system continuously. The anti-driving effect of environmental information disclosure on the treatment of environmental pollution must be intensified further, particularly focusing on the central region of China, where is more polluted and more concentrated than other regions.
A Comparative Study on the Use of Raw and Filtered Images for Multi-class Image Classification

Manufacturing processes have since then developed to accommodate the ever-growing consumer demand for a wide range of products. Being so, for businesses to adapt, they must engage in the manufacturing and selling of various types of products. Often times in the factory, one would oversee the overall manufacturing processes of several products. This has been proven to be workable, yet, at times, inefficient. Multi-class image classification may serve to be the answer for increasing efficiency in monitoring the overall manufacturing process. To demonstrate the technology and apply it in an electronic device manufacturing setting, the researchers created their own dataset that consists of 4 different classes (with each class having 1000 images -- 1000 for training, 518 for validation, and 5 for testing). Following the Convolutional Neural Network (CNN) model, the researchers made use of the Python programming language to execute the multi-class image classification program. It was investigated if there would be any difference in the model and output accuracy if the images that would be fed to the program will undergo no filtering and gaussian filtering. Training and testing were performed for a total of 5 times for each set, and training loss, training accuracy, validation loss, validation accuracy, and actual accuracy were recorded. The mean values of the aforementioned show that Gaussian filtered images yielded much more favorable results as actual accuracy was at 95% -- which is 5% higher than the actual accuracy for the set of raw images.
The Multifaceted Neurotoxicity of Astrocytes in Ageing and Age-Related Neurodegenerative Diseases: A Translational Perspective

In a healthy physiological context, astrocytes are multitasking cells contributing to central nervous system (CNS) homeostasis, defense, and immunity. In cell culture or rodent models of age-related neurodegenerative diseases (NDDs), such as Alzheimer’s disease (AD) and Parkinson’s disease (PD), numerous studies have shown that astrocytes can adopt neurotoxic phenotypes that could enhance disease progression. Chronic inflammatory responses, oxidative stress, unbalanced phagocytosis, or alteration of their core physiological roles are the main manifestations of their detrimental states. However, if astrocytes are directly involved in brain deterioration by exerting neurotoxic functions in patients with NDDs is still controversial. The large spectrum of NDDs, with often overlapping pathologies, and the technical challenges associated with the study of human brain samples complexify the analysis of astrocyte involvement in specific neurodegenerative cascades. With this review, we aim to provide a translational overview about the multi-facets of astrocyte neurotoxicity ranging from in vitro findings over mouse and human cell-based studies to rodent NDDs research and finally evidence from patient-related research. We also discuss the role of ageing in astrocytes encompassing changes in physiology and response to pathologic stimuli and how this may prime detrimental responses in NDDs. To conclude, we discuss how potentially therapeutic strategies could be adopted to alleviate or reverse astrocytic toxicity and their potential to impact neurodegeneration and dementia progression in patients.
Magnetic Nanoparticle-Mediated Orientation of Collagen Hydrogels for Engineering of Tendon-Mimetic Constructs

Despite the high incidence of tendon injuries worldwide, an optimal treatment strategy has yet to be defined. A key challenge for tendon repair is the alignment of the repaired matrix into orientations which provide maximal mechanical strength. Using oriented implants for tissue growth combined with either exogenous or endogenous stem cells may provide a solution. Previous research has shown how oriented fiber-like structures within 3D scaffolds can provide a framework for organized extracellular matrix deposition. In this article, we present our data on the remote magnetic alignment of collagen hydrogels which facilitates long-term collagen orientation. Magnetic nanoparticles (MNPs) at varying concentrations can be contained within collagen hydrogels. Our data show how, in response to the magnetic field lines, MNPs align and form string-like structures orientating at 90 degrees from the applied magnetic field from our device. This can be visualized by light and fluorescence microscopy, and it persists for 21 days post-application of the magnetic field. Confocal microscopy demonstrates the anisotropic macroscale structure of MNP-laden collagen gels subjected to a magnetic field, compared to gels without MNP dosing. Matrix fibrillation was compared between non- and biofunctionalized MNP hydrogels, and different gels dosed with varying MNP concentrations. Human adipose stem cells (hASCs) seeded within the magnetically aligned gels were observed to align in parallel to MNP and collagen orientation 7 days post-application of the magnetic field. hASCs seeded in isotropic gels were randomly organized. Tenocyte-likeness of the cells 7 days post-seeding in collagen I scaffolds was confirmed by the positive expression of tenomodulin and scleraxis proteins. To summarize, we have developed a convenient, non-invasive protocol to control the collagen I hydrogel architecture. Through the presence or absence of MNP dosing and a magnetic field, collagen can be remotely aligned or randomly organized, respectively, in situ. Tendon-like cells were observed to organize in parallel to unidirectionally aligned collagen fibers and polydirectionally in non-aligned collagen constructs. In this way, we were able to engineer the constructs emulating a physiologically and pathologically relevant tendon niche. This can be considered as an innovative approach particularly useful in tissue engineering or organ-on-a-chip applications for remotely controlling collagen matrix organization to recapitulate the native tendon.
Anaplastic Lymphoma Kinase Tyrosine Kinase Inhibitor-Associated Cardiotoxicity: A Recent Five-Year Pharmacovigilance Study

Background: Clinical trials frequently reported anaplastic lymphoma kinase tyrosine kinase inhibitors (ALK-TKIs) associated with cardiac adverse drug events (AEs) but minimal postmarketing data. We aimed to research real-world cardiac disorders associated with ALK-TKIs based on the Food and Drug Administration Adverse Event Reporting System (FAERS). Methods: Extract reports from the FAERS from the first quarter of 2016 to the second quarter of 2021 were obtained. Data mining of cardiac disorders associated with ALK-TKIs was carried out using disproportionality analysis to determine the clinical characteristics of AEs. Results: In total, 605 cases were screened out. These events were found to be more prevalent in patients ≥45 years (50.74%) and women (50.74%). The onset time of cardiac disorders was variable and concentrated within 2 months, with a median time of 33 days. The outcomes tended to be poor, with 20.93% fatality proportion. Cardiac arrhythmia was a common adverse event of ALK-TKIs, especially bradycardia. Crizotinib and lorlatinib showed positive signals in cardiac disorders, especially in heart failure, and brigatinib presented no signals. The study also found that myocarditis caused by ceritinib and cardiomyopathy caused by lorlatinib may be potential new adverse drug reactions. Conclusion: ALK-TKIs were reported more frequently in cardiotoxicity than other drugs and could often manifest earlier. We also found potential new AE signals in specific drugs and need more clinical studies to confirm. Our study helps fill the safety information of ALK-TKIs in the heart and provides directions for further research.
An in vitro Assessment of the Haemodynamic Features Occurring Within the True and False Lumens Separated by a Dissection Flap for a Patient-Specific Type B Aortic Dissection

One of the highest mortality rates of cardiovascular diseases is aortic dissections with challenging treatment options. Currently, less study has been conducted in developing in vitro patient-specific Type B aortic dissection models, which mimic physiological flow conditions along the true and false lumens separated by a dissection flap with multiple entry and exit tears. A patient-specific Stanford Type B aortic dissection scan was replicated by an in-house manufactured automatic injection moulding system and a novel modelling technique for creating the ascending aorta, aortic arch, and descending aorta incorporating arterial branching, the true/false lumens, and dissection flap with entry and exit intimal tears. The physiological flowrates and pressure values were monitored, which identified jet stream fluid flows entering and exiting the dissection tears. Pressure in the aorta’s true lumen region was controlled at 125/85 mmHg for systolic and diastolic values. Pressure values were obtained in eight sections along the false lumen using a pressure transducer. The true lumen systolic pressure varied from 122 to 128 mmHg along the length. Flow patterns were monitored by ultrasound along 12 sections. Detailed images obtained from the ultrasound transducer probe showed varied flow patterns with one or multiple jet steam vortices along the aorta model. The dissection flap movement was assessed at four sections of the patient-specific aorta model. The displacement values of the flap varied from 0.5 to 3 mm along the model. This model provides a unique insight into aortic dissection flow patterns and pressure distributions. This dissection phantom model can be used to assess various treatment options based on the surgical, endovascular, or hybrid techniques.