Miracle-dz/UniFAR-FTUs huggingface dataset:
Fundamental Moist Modes of the Equatorial Troposphere

Abstract Raymond's diabatic parameterizations are combined with a three-dimensional channel model on an equatorial beta plane. The equatorially symmetric moist modes of this model for an atmosphere initially at rest are “nonlinear WISHE” (wind-induced surface heat exchange) modes. These modes are driven by the enhanced sea–air fluxes of entropy produced by self-generated westerly winds. Two varieties of these modes are found, those which move to the east at 8 m s−1 and those which move to the west at 4 m s−1. In both modes heavy rain occurs in air that has been moistened by convection of low precipitation efficiency. This preconditioning introduces a phase shift of several days between strong surface entropy fluxes into an air column and the heaviest rainfall. This phase shift may be responsible for the relatively low modal propagation speeds compared to those seen in other models. The modes identified in simulations with uniform sea surface temperature play a fundamental role in a simulation with a warm-.
An efficient and robust maneuvering mode to calibrate low cost magnetometer for improved heading estimation for pedestrian navigation

Abstract Personal navigation systems intend to provide the navigation information in any environment, indoors and outdoors, and at any time. In outdoor environments, the positioning solution is typically provided by using Global Positioning System (GPS). However, GPS is inaccurate or unavailable in most of indoor environments and therefore other externally-referenced sensing techniques are required. Inertial sensing techniques are used for pedestrian navigation in association with dead reckoning approach. Magnetometers can be used to derive the user’s heading by sensing the Earth’s magnetic field. In this paper, an efficient and robust maneuvering mode to calibrate low cost magnetometer is recommended for pedestrian navigation applications. Additionally, other maneuvering modes and errors associated with each mode to achieve best estimation for the calibration parameters in the 3D Space are also provided. Also, the effect of using different maneuvering modes (DMM) on the heading estimation for the pedestrian navigation is studied. The results show that the coordinated mode is suitable to perform the calibration process as the unit is rotated in a way to cover the whole 3D space.
The role of noncoding RNAs in pancreatic birth defects

Congenital defects in the pancreas can cause severe health issues such as pancreatic cancer and diabetes which require lifelong treatment. Regenerating healthy pancreatic cells to replace malfunctioning cells has been considered a promising cure for pancreatic diseases including birth defects. However, such therapies are currently unavailable in the clinic. The developmental gene regulatory network underlying pancreatic development must be reactivated for in vivo regeneration and recapitulated in vitro for cell replacement therapy. Thus, understanding the mechanisms driving pancreatic development will pave the way for regenerative therapies. Pancreatic progenitor cells are the precursors of all pancreatic cells which use epigenetic changes to control gene expression during differentiation to generate all of the distinct pancreatic cell types. Epigenetic changes involving DNA methylation and histone modifications can be controlled by noncoding RNAs (ncRNAs). Indeed, increasing evidence suggests that ncRNAs are indispensable for proper organogenesis. Here, we summarize recent insight into the role of ncRNAs in the epigenetic regulation of pancreatic development. We further discuss how disruptions in ncRNA biogenesis and expression lead to developmental defects and diseases. This review summarizes in vivo data from animal models and in vitro studies using stem cell differentiation as a model for pancreatic development.
Optoelectronic investigation of nanodiamond interactions with human blood

We present optoelectronic investigation of in vitro interactions of whole human blood with different nanodiamond biomarkers. Plasmo-chemical modifications of detonation nanodiamond particles gives the possibility for controlling their surface for biological applications. Optical investigations reveal the biological activity of nanodiamonds in blood dependent on its surface termination. We compare different types of nanodiamonds: commercial non-modified detonation nanodiamonds, and nanodiamonds modified by MW PACVD method with H2-termination, and chemically modified nanodiamond with O2-termination. The absorption spectra, and optical microscope investigations were conducted. The results indicate haemocompatibility of non-modified detonation nanodiamond as well as modified nanodiamonds, which enables their application for drug delivery, as well as sensing applications.
Sex determination using the clavicle by deep learning in a Thai population

Determining sex is a critical process in estimating biological profiles from skeletal remains. The clavicle is interesting in studying sex determination because it is durable to the environment, slow to decay, challenging to destroy, making the clavicle useful in autopsies and identification which can then lead to verification. The goal of this study was to use deep learning in determining sex from clavicles within the Thai population and obtain the accuracies for the validation set using a convolutional neural network (GoogLeNet). A total of 200 pairs of clavicles were obtained from 200 Thai persons (100 males and 100 females) as part of a training group. For the deep learning approach, the clavicle was photographed, and each clavicle image was submitted to the training model for sex determination. Training groups of 200 samples were made. Images of the same size were input into the training model. The percentage of the validation set accuracy was calculated from the MATLAB program. GoogLeNet was the best training model and get the result of validation set accuracy. The results of this study found accuracies for a validation set with the highest overall right lateral view of the clavicle with an accuracy of 95%. Accuracy from the validation set of each view of the clavicle can demonstrate the forensic value of sex determination. A deep learning approach with clavicles can determine the sex and is simple to utilize for forensic anthropology professionals.
The rs2275913 polymorphism of the interleukin-17A gene is associated with the risk of ovarian endometriosis

Abstract The aim of this study was to explore the relationship between two genetic variants (rs2275913 and rs3748067) of interleukin-17A (IL-17A) and the risk of ovarian endometriosis in northern Chinese women. This study was performed in 316 patients with ovarian endometriosis and 328 female control subjects. The genotypes of the two polymorphisms were determined by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. The mRNA expression of IL-17A was detected by quantitative real-time PCR (qRT-PCR). There was a significant difference in the genotype distributions of the rs2275913 polymorphism between the patients and control subjects (p = .006). Compared with the GG genotype of rs2275913, the AA genotype was correlated with a higher susceptibility to the development of ovarian endometriosis (OR = 2.28, 95% confidence interval (CI) = 1.37–3.80). Furthermore, the levels of IL-17A mRNA were higher in the ectopic endometrium from ovarian endometriosis patients carrying the rs2275913 AA genotype than in those carrying the rs2275913 GG genotype (p = .007). This study suggested that the rs2275913 polymorphism at the promoter region of IL-17A may be a functional genetic variant, and the rs2275913 AA genotype is associated with a higher risk of developing ovarian endometriosis in northern Chinese women. IMPACT STATEMENT What is already known on this subject? Interleukin-17A (IL-17A) is a crucial proinflammatory and angiogenic cytokine that has been shown to participate in the pathogenesis of chronic inflammatory and autoimmune diseases. Genetic variants in IL-17A may alter the expression of the IL-17A, and are associated with the susceptibility to a wide range of human diseases. What do the results of this study add? This study suggested that the rs2275913 polymorphism at the promoter region of IL-17A may be a functional genetic variant that affects the expression of IL-17A mRNA in ectopic endometrial tissues. The AA genotype of rs2275913 was associated with a higher risk of developing ovarian endometriosis in northern Chinese women. What are the implications of these findings for clinical practice and/or further research? IL-17A may be a potential biomarker for early diagnosis and gene-targeted therapy of ovarian endometriosis.
Chemogenomic Profiling of a Plasmodium falciparum Transposon Mutant Library Reveals Shared Effects of Dihydroartemisinin and Bortezomib on Lipid Metabolism and Exported Proteins

Malaria control is seriously threatened by the emergence and spread of Plasmodium falciparum resistance to the leading antimalarial, artemisinin. The potent killing activity of artemisinin results from oxidative damage unleashed by free heme activation released by hemoglobin digestion. ABSTRACT The antimalarial activity of the frontline drug artemisinin involves generation of reactive oxygen species (ROS) leading to oxidative damage of parasite proteins. To achieve homeostasis and maintain protein quality control in the overwhelmed parasite, the ubiquitin-proteasome system kicks in. Even though molecular markers for artemisinin resistance like pfkelch13 have been identified, the intricate network of mechanisms driving resistance remains to be elucidated. Here, we report a forward genetic screening strategy that enables a broader identification of genetic factors responsible for altering sensitivity to dihydroartemisinin (DHA) and a proteasome inhibitor, bortezomib (BTZ). Using a library of isogenic piggyBac mutants in P. falciparum, we defined phenotype-genotype associations influencing drug responses and highlighted shared mechanisms between the two processes, which mainly included proteasome-mediated degradation and the lipid metabolism genes. Additional transcriptomic analysis of a DHA/BTZ-sensitive piggyBac mutant showed it is possible to find differences between the two response mechanisms on the specific components for regulation of the exportome. Our results provide further insight into the molecular mechanisms of antimalarial drug resistance. IMPORTANCE Malaria control is seriously threatened by the emergence and spread of Plasmodium falciparum resistance to the leading antimalarial, artemisinin. The potent killing activity of artemisinin results from oxidative damage unleashed by free heme activation released by hemoglobin digestion. Although the ubiquitin-proteasome system is considered critical for parasite survival of this toxicity, the diverse genetic changes linked to artemisinin resistance are complex and, so far, have not included the ubiquitin-proteasome system. In this study, we use a systematic forward genetic approach by screening a library of P. falciparum random piggyBac mutants to decipher the genetic factors driving malaria parasite responses to the oxidative stress caused by antimalarial drugs. This study compares phenotype-genotype associations influencing dihydroartemisinin responses with the proteasome inhibitor bortezomib to delineate the role of ubiquitin-proteasome system. Our study highlights shared and unique pathways from the complex array of molecular processes critical for P. falciparum survival resulting from the oxidative damage of artemisinin.
Evaluation of an Electronic Care and Rehabilitation Planning Tool With Stroke Survivors With Aphasia: Usability Study

Background Patients with chronic illnesses with physical and cognitive disabilities, particularly stroke survivors with aphasia, are often not involved in design and evaluation processes. As a consequence, existing eHealth services often do not meet the needs of this group of patients, which has resulted in a digital divide. Objective The aim of this study was to examine the effectiveness and user satisfaction of an electronic care and rehabilitation planning tool from the perspective of stroke survivors with aphasia. This would help us gain knowledge on how such a tool would need to be adapted for these patients for further development. Methods Usability tests were conducted with 9 postdischarge stroke survivors with aphasia. Effectiveness was measured using task-based tests, and user satisfaction was studied through qualitative interviews at the end of each test. All tests were audio recorded, and each test lasted approximately 1 hour. The data were analyzed using qualitative content analysis. As the tool can be used by stroke survivors either independently or with some support from their next of kin or care professionals, the research group decided to divide the participants into 2 groups. Group 1 did not receive any support during the tests, and group 2 received some minor support from the moderator. Results The results showed that the care and rehabilitation planning tool was not effective for stroke survivors with aphasia, as many participants in group 1 did not accomplish the tasks successfully. Despite several usability problems and challenges in using the tool because of patients’ disabilities, the participants were positive toward using the tool and found it useful for their care and rehabilitation journey. Conclusions There is a need to involve patients with chronic illnesses more in the design and evaluation processes of health information systems and eHealth services. eHealth services and health information systems designed for this group of patients should be more adaptable and flexible to provide them with appropriate functionalities and features, meet their needs, and be useful and easy to use. In addition, the design and evaluation processes should be adapted, considering the challenges of this patient group.
Ventral striatum dopamine release encodes unique properties of visual stimuli in mice

The mesolimbic dopamine system is an evolutionarily conserved set of brain circuits that play a role in attention, appetitive behavior, and reward processing. In this circuitry, ascending dopaminergic projections from the ventral midbrain innervate targets throughout the limbic forebrain, such as the ventral striatum/nucleus accumbens (NAc). Dopaminergic signaling in the NAc has been widely studied for its role in behavioral reinforcement, reward prediction error encoding, and motivational salience. Less well characterized is the role of dopaminergic neurotransmission in the response to surprising or alerting sensory events. To address this, we used the genetically encoded dopamine sensor dLight1 and fiber photometry to explore the ability of striatal dopamine release to encode the properties of salient sensory stimuli in mice, such as threatening looming discs. Here, we report that lateral NAc (LNAc) dopamine release encodes the rate and magnitude of environmental luminance changes rather than the visual stimulus threat level. This encoding is highly sensitive, as LNAc dopamine could be evoked by light intensities that were imperceptible to human experimenters. We also found that light-evoked dopamine responses are wavelength-dependent at low irradiances, independent of the circadian cycle, robust to previous exposure history, and involve multiple phototransduction pathways. Thus, we have further elaborated the mesolimbic dopamine system’s ability to encode visual information in mice, which is likely relevant to a wide body of scientists employing light sources or optical methods in behavioral research involving rodents.
Deep Learning Segmentation of the Right Ventricle in Cardiac MRI: The M&Ms Challenge

In recent years, several deep learning models have been proposed to accurately quantify and diagnose cardiac pathologies. These automated tools heavily rely on the accurate segmentation of cardiac structures in MRI images. However, segmentation of the right ventricle is challenging due to its highly complex shape and ill-defined borders. Hence, there is a need for new methods to handle such structure's geometrical and textural complexities, notably in the presence of pathologies such as Dilated Right Ventricle, Tricuspid Regurgitation, Arrhythmogenesis, Tetralogy of Fallot, and Inter-atrial Communication. The last MICCAI challenge on right ventricle segmentation was held in 2012 and included only 48 cases from a single clinical center. As part of the 12th Workshop on Statistical Atlases and Computational Models of the Heart (STACOM 2021), the M&Ms-2 challenge was organized to promote the interest of the research community around right ventricle segmentation in multi-disease, multi-view, and multi-center cardiac MRI. Three hundred sixty CMR cases, including short-axis and long-axis 4-chamber views, were collected from three Spanish hospitals using nine different scanners from three different vendors, and included a diverse set of right and left ventricle pathologies. The solutions provided by the participants show that nnU-Net achieved the best results overall. However, multi-view approaches were able to capture additional information, highlighting the need to integrate multiple cardiac diseases, views, scanners, and acquisition protocols to produce reliable automatic cardiac segmentation algorithms.
Current and emerging approaches to noncompetitive AR inhibition

The androgen receptor (AR) has been shown to be a key determinant in the pathogenesis of castration‐resistant prostate cancer (CRPC). The current standard of care therapies targets the ligand‐binding domain of the receptor and can afford improvements to life expectancy often only in the order of months before resistance occurs. Emerging preclinical and clinical compounds that inhibit receptor activity via differentiated mechanisms of action which are orthogonal to current antiandrogens show promise for overcoming treatment resistance. In this review, we present an authoritative summary of molecules that noncompetitively target the AR. Emerging small molecule strategies for targeting alternative domains of the AR represent a promising area of research that shows significant potential for future therapies. The overall quality of lead candidates in the area of noncompetitive AR inhibition is discussed, and it identifies the key chemotypes and associated properties which are likely to be, or are currently, positioned to be first in human applications.
Single-round Self-supervised Distributed Learning using Vision Transformer

Despite the recent success of deep learning in the field of medicine, the issue of data scarcity is exacerbated by concerns about privacy and data ownership. Distributed learning approaches, including federated learning, have been investigated to address these issues. However, they are hindered by the need for cumbersome communication overheads and weaknesses in privacy protection. To tackle these challenges, we propose a self-supervised masked sampling distillation method for the vision transformer. This method can be implemented without continuous communication and can enhance privacy by utilizing a vision transformer-specific encryption technique. We conducted extensive experiments on two different tasks, which demonstrated the effectiveness of our method. We achieved superior performance compared to the existing distributed learning strategy as well as the fine-tuning only baseline. Furthermore, since the self-supervised model created using our proposed method can achieve a general semantic understanding of the image, we demonstrate its potential as a task-agnostic self-supervised foundation model for various downstream tasks, thereby expanding its applicability in the medical domain.
Candida albicans Promotes Oral Cancer via IL-17A/IL-17RA-Macrophage Axis

The relationship between fungi and cancer is gradually receiving attention. Among them, some clinical evidence has shown that Candida may be a contributor to gastrointestinal cancers, especially oral cancer. ABSTRACT The association between Candida albicans (C. albicans) and oral cancer (OC) has been noticed for a long time, but the mechanisms for C. albicans promoting OC are rarely explored. In this study, we determined that C. albicans infection promoted OC incidence in a 4-nitroquinoline 1-oxide (4NQO)-induced mouse tongue carcinogenesis model as well as promoted OC progression in a tongue tumor-bearing mouse model (C3H/HeN-SCC VII). We then demonstrated that tumor-associated macrophage (TAMs) infiltration was elevated during C. albicans infection. Meanwhile, the attracted TAMs polarized into M2-like macrophages with high expression of programmed death ligand 1 (PD-L1) and galectin-9 (GAL-9). Further analysis suggested that the interleukin (IL)-17A/IL-17RA pathway activated in OC cells was a contributor to the excessive TAMs infiltration in C. albicans-infected mice. Thus, we constructed IL-17A neutralization and macrophage depletion experiments in C3H/HeN-SCC VII mice to explore the role of IL-17A/IL-17RA and TAMs in OC development caused by C. albicans infection. The results showed that both IL-17A neutralization and macrophage depletion tended to reduce the TAMs number and tumor size in mice with C. albicans infection. Collectively, our finding revealed that C. albicans promoted OC development via the IL-17A/IL-17RA-macrophage axis, opening perspectives for revealing C. albicans-tumor immune microenvironment links. IMPORTANCE The relationship between fungi and cancer is gradually receiving attention. Among them, some clinical evidence has shown that Candida may be a contributor to gastrointestinal cancers, especially oral cancer. However, the underlying mechanisms for Candida promoting oral cancer need to be explored. For this reason, this study demonstrated the role of C. albicans in oral cancer development. Moreover, this study revealed the underlying mechanisms for C. albicans promoting oral cancer from the perspective of the tumor immune microenvironment.
Persistent homology‐based functional connectivity and its association with cognitive ability: Life‐span study

Brain‐segregation attributes in resting‐state functional networks have been widely investigated to understand cognition and cognitive aging using various approaches [e.g., average connectivity within/between networks and brain system segregation (BSS)]. While these approaches have assumed that resting‐state functional networks operate in a modular structure, a complementary perspective assumes that a core‐periphery or rich club structure accounts for brain functions where the hubs are tightly interconnected to each other to allow for integrated processing. In this article, we apply a novel method, persistent homology (PH), to develop an alternative to standard functional connectivity by quantifying the pattern of information during the integrated processing. We also investigate whether PH‐based functional connectivity explains cognitive performance and compare the amount of variability in explaining cognitive performance for three sets of independent variables: (1) PH‐based functional connectivity, (2) graph theory‐based measures, and (3) BSS. Resting‐state functional connectivity data were extracted from 279 healthy participants, and cognitive ability scores were generated in four domains (fluid reasoning, episodic memory, vocabulary, and processing speed). The results first highlight the pattern of brain‐information flow over whole brain regions (i.e., integrated processing) accounts for more variance of cognitive abilities than other methods. The results also show that fluid reasoning and vocabulary performance significantly decrease as the strength of the additional information flow on functional connectivity with the shortest path increases. While PH has been applied to functional connectivity analysis in recent studies, our results demonstrate potential utility of PH‐based functional connectivity in understanding cognitive function.