Stress Granules in Cancer.

The capacity of cells to organize complex biochemical reactions in intracellular space is a fundamental organizational principle of life. Key to this organization is the compartmentalization of the cytoplasm into distinct organelles, which is frequently achieved through intracellular membranes. Recent evidence, however, has added a new layer of flexibility to cellular compartmentalization. As such, in response to specific stimuli, liquid-liquid phase separations can lead to the rapid rearrangements of the cytoplasm to form membraneless organelles. Stress granules (SGs) are one such type of organelle that form specifically when cells are faced with stress stimuli, to aid cells in coping with stress. Inherently, altered SG formation has been linked to the pathogenesis of diseases associated with stress and inflammatory conditions, including cancer. Exciting discoveries have indicated an intimate link between SGs and tumorigenesis. Several pro-tumorigenic signaling molecules including the RAS oncogene, mTOR, and histone deacetylase 6 (HDAC6) have been shown to upregulate SG formation. Based on these studies, SGs have emerged as structures that can integrate oncogenic signaling and tumor-associated stress stimuli to enhance cancer cell fitness. In addition, growing evidence over the past decade suggests that SGs function not only to regulate the switch between survival and cell death, but also contribute to cancer cell proliferation, invasion, metastasis, and drug resistance. Although much remains to be learned about the role of SGs in tumorigenesis, these studies highlight SGs as a key regulatory hub in cancer and a promising therapeutic target.

Mature microRNA-binding protein QKI promotes microRNA-mediated gene silencing.

Although Argonaute (AGO) proteins have been the focus of microRNA (miRNA) studies, we observed AGO-free mature miRNAs directly interacting with RNA-binding proteins, implying the sophisticated nature of fine-tuning gene regulation by miRNAs. To investigate microRNA-binding proteins (miRBPs) globally, we analyzed PAR-CLIP data sets to identify RBP quaking (QKI) as a novel miRBP for let-7b. Potential existence of AGO-free miRNAs were further verified by measuring miRNA levels in genetically engineered AGO-depleted human and mouse cells. We have shown that QKI regulates miRNA-mediated gene silencing at multiple steps, and collectively serves as an auxiliary factor empowering AGO2/let-7b-mediated gene silencing. Depletion of QKI decreases interaction of AGO2 with let-7b and target mRNA, consequently controlling target mRNA decay. This finding indicates that QKI is a complementary factor in miRNA-mediated mRNA decay. QKI, however, also suppresses the dissociation of let-7b from AGO2, and slows the assembly of AGO2/miRNA/target mRNA complexes at the single-molecule level. We also revealed that QKI overexpression suppresses cMYC expression at post-transcriptional level, and decreases proliferation and migration of HeLa cells, demonstrating that QKI is a tumour suppressor gene by in part augmenting let-7b activity. Our data show that QKI is a new type of RBP implicated in the versatile regulation of miRNA-mediated gene silencing.

Real-time chlorophyll-a forecasting using machine learning framework with dimension reduction and hyperspectral data.

Since water is an essential resource in various fields, it requires constant monitoring. Chlorophyll-a concentration is a crucial indicator of water quality and can be used to monitor water quality. In this study, we developed methods to forecast chlorophyll-a concentrations in real-time using hyperspectral data on IoT platform and various machine learning algorithms. Compared to regular cameras that record information only in the three broad color bands of red, green, and blue, the hyperspectral images of drinking water sources record the data in dozens or even hundreds of distinct small wavelength bands, providing each pixel in an image with a full spectrum. Different machine learning algorithms have been developed using hyperspectral data and field observations of water quality and weather conditions. Previous studies have predicted chlorophyll concentrations using either partial least squares (PLS), which is a dimensionality reduction method, or machine learning. In contrast, our study employed the PLS technique as a preprocessing step to diminish the dimensionality of the hyperspectral data, followed by the application of the machine learning techniques with optimized hyperparameters to improve the precision of the predictions, thereby introducing a real-time mechanism for chlorophyll-a prediction. Consequently, a machine learning algorithm with R2 values of 0.9 or above and sufficiently small RMSE was developed for real-time chlorophyll-a forecasting. Real-time chlorophyll-a forecasting using LightGBM has the best performance, with a mean R2 of 0.963 and a mean RMSE of 2.679. This paper is expected to have applications in algal bloom early detection on monitoring systems.

Insights into the Role of microRNAs as Clinical Tools for Diagnosis, Prognosis, and as Therapeutic Targets in Alzheimer's Disease.

Neurodegenerative diseases (NDDs) are a diverse group of neurological disorders characterized by alterations in the structure and function of the central nervous system. Alzheimer's disease (AD), characterized by impaired memory and cognitive abilities, is the most prevalent type of senile dementia. Loss of synapses, intracellular aggregation of hyperphosphorylated tau protein, and extracellular amyloid-ß peptide (Aß) plaques are the hallmarks of AD. MicroRNAs (miRNAs/miRs) are single-stranded ribonucleic acid (RNA) molecules that bind to the 3' and 5' untranslated regions of target genes to cause post-transcriptional gene silencing. The brain expresses over 70% of all experimentally detected miRNAs, and these miRNAs are crucial for synaptic function and particular signals during memory formation. Increasing evidence suggests that miRNAs play a role in AD pathogenesis and we provide an overview of the role of miRNAs in synapse formation, Aß synthesis, tau protein accumulation, and brain-derived neurotrophic factor-associated AD pathogenesis. We further summarize and discuss the role of miRNAs as potential therapeutic targets and biomarkers for AD detection and differentiation between early- and late-stage AD, based on recent research. In conclusion, altered expression of miRNAs in the brain and peripheral circulation demonstrates their potential as biomarkers and therapeutic targets in AD.

Advancements in the Application of Nanomedicine in Alzheimer's Disease: A Therapeutic Perspective.

Alzheimer's disease (AD) is a progressive neurodegenerative disease that affects most people worldwide. AD is a complex central nervous system disorder. Several drugs have been designed to cure AD, but with low success rates. Because the blood-brain and blood-cerebrospinal fluid barriers are two barriers that protect the central nervous system, their presence has severely restricted the efficacy of many treatments that have been studied for AD diagnosis and/or therapy. The use of nanoparticles for the diagnosis and treatment of AD is the focus of an established and rapidly developing field of nanomedicine. Recent developments in nanomedicine have made it possible to effectively transport drugs to the brain. However, numerous obstacles remain to the successful use of nanomedicines in clinical settings for AD treatment. Furthermore, given the rapid advancement in nanomedicine therapeutics, better outcomes for patients with AD can be anticipated. This article provides an overview of recent developments in nanomedicine using different types of nanoparticles for the management and treatment of AD.

Mercaptoamine-assisted Post-encapsulation of Metal Nanoparticles within Preformed Zeolites and their Analogues for Hydroisomerization and Methane Decomposition.

We report a general synthetic strategy for post-encapsulation of metal nanoparticles within preformed zeolites using post-synthetic modification. Both anionic and cationic precursors to metal nanoparticle are supported on 8- and 10-membered ring zeolites and analogues during wet impregnation using 2-aminoethanethiol (AET) as a bi-grafting agent. Thiol groups are coordinated to metal centers, whereas amine moieties are dynamically attached to micropore walls via acid-base interactions. The dynamic acid-base interactions cause the even distribution of the metal-AET complex throughout the zeolite matrix. These processes encapsulate Au, Rh, and Ni precursors within the CHA, *MRE, MFI zeolite, and SAPO-34 zeolite analogues, for which small channel apertures preclude the post-synthesis impregnation of metal precursors. Sequential activation forms small and uniform nanoparticles (1-2.5 nm in diameter), as confirmed through electron microscopy and X-ray absorption spectroscopy. Containment within the small micropores protected the nanoparticles against harsh thermal sintering conditions and prevented the fouling of the metal surface by coke, thus resulting in a high catalytic performance in n-dodecane hydroisomerization and methane decomposition. The remarkable specificity of the thiol to metal precursors and the dynamic acid-base interaction make these protocols extendable to various metal-zeolite systems, suitable for shape-selective catalysts in challenging chemical environments.

TrkB deubiquitylation by USP8 regulates receptor levels and BDNF-dependent neuronal differentiation.

Ubiquitylation of receptor tyrosine kinases (RTKs) regulates both the levels and functions of these receptors. The neurotrophin receptor TrkB (also known as NTRK2), a RTK, is ubiquitylated upon activation by brain-derived neurotrophic factor (BDNF) binding. Although TrkB ubiquitylation has been demonstrated, there is a lack of knowledge regarding the precise repertoire of proteins that regulates TrkB ubiquitylation. Here, we provide mechanistic evidence indicating that ubiquitin carboxyl-terminal hydrolase 8 (USP8) modulates BDNF- and TrkB-dependent neuronal differentiation. USP8 binds to the C-terminus of TrkB using its microtubule-interacting domain (MIT). Immunopurified USP8 deubiquitylates TrkB in vitro, whereas knockdown of USP8 results in enhanced ubiquitylation of TrkB upon BDNF treatment in neurons. As a consequence of USP8 depletion, TrkB levels and its activation are reduced. Moreover, USP8 protein regulates the differentiation and correct BDNF-dependent dendritic formation of hippocampal neurons in vitro and in vivo We conclude that USP8 positively regulates the levels and activation of TrkB, modulating BDNF-dependent neuronal differentiation.This article has an associated First Person interview with the first author of the paper.

Assessment of the feasibility of developing a clinical pathway using a clinical order log.

A clinical pathway (CP) is a tool for effectively managing a care process. There are several research efforts on developing clinical pathways (CPs) in the process mining domain. However, the nature of the data affects data analysis results, and patient clinical variability makes it challenging to develop CPs. Thus, it is crucial to determine candidate care processes that can be standardized as CPs before applying process mining techniques. This paper proposed a method for assessing CP feasibility regarding clinical complexity using clinical order logs from electronic health records. The proposed method consists of data preparation, activity & trace homogeneity evaluations, and process inspection using process mining. Each step consists of metrics to measure the homogeneity of processes and a visualization method to demonstrate the diversity of processes based on the log. The case study was conducted with five surgical groups of patients from a tertiary hospital in South Korea to validate the proposed method. The five groups of patients were successfully assessed. In addition, the visualization methods helped clinical experts grasp the diversity of care processes.

Process mining for healthcare: Characteristics and challenges.

Process mining techniques can be used to analyse business processes using the data logged during their execution. These techniques are leveraged in a wide range of domains, including healthcare, where it focuses mainly on the analysis of diagnostic, treatment, and organisational processes. Despite the huge amount of data generated in hospitals by staff and machinery involved in healthcare processes, there is no evidence of a systematic uptake of process mining beyond targeted case studies in a research context. When developing and using process mining in healthcare, distinguishing characteristics of healthcare processes such as their variability and patient-centred focus require targeted attention. Against this background, the Process-Oriented Data Science in Healthcare Alliance has been established to propagate the research and application of techniques targeting the data-driven improvement of healthcare processes. This paper, an initiative of the alliance, presents the distinguishing characteristics of the healthcare domain that need to be considered to successfully use process mining, as well as open challenges that need to be addressed by the community in the future.

TA-Unet: Integrating Triplet Attention Module for Drivable Road Region Segmentation.

Road segmentation has been one of the leading research areas in the realm of autonomous driving cars due to the possible benefits autonomous vehicles can offer. Significant reduction of crashes, greater independence for the people with disabilities, and reduced traffic congestion on the roads are some of the vivid examples of them. Considering the importance of self-driving cars, it is vital to develop models that can accurately segment drivable regions of roads. The recent advances in the area of deep learning have presented effective methods and techniques to tackle road segmentation tasks effectively. However, the results of most of them are not satisfactory for implementing them into practice. To tackle this issue, in this paper, we propose a novel model, dubbed as TA-Unet, that is able to produce quality drivable road region segmentation maps. The proposed model incorporates a triplet attention module into the encoding stage of the U-Net network to compute attention weights through the triplet branch structure. Additionally, to overcome the class-imbalance problem, we experiment on different loss functions, and confirm that using a mixed loss function leads to a boost in performance. To validate the performance and efficiency of the proposed method, we adopt the publicly available UAS dataset, and compare its results to the framework of the dataset and also to four state-of-the-art segmentation models. Extensive experiments demonstrate that the proposed TA-Unet outperforms baseline methods both in terms of pixel accuracy and mIoU, with 98.74% and 97.41%, respectively. Finally, the proposed method yields clearer segmentation maps on different sample sets compared to other baseline methods.

Seaweeds in the Oncology Arena: Anti-Cancer Potential of Fucoidan as a Drug-A Review.

Marine natural products are a discerning arena to search for the future generation of medications to treat a spectrum of ailments. Meanwhile, cancer is becoming more ubiquitous over the world, and the likelihood of dying from it is rising. Surgery, radiation, and chemotherapy are the mainstays of cancer treatment worldwide, but their extensive side effects limit their curative effect. The quest for low-toxicity marine drugs to prevent and treat cancer is one of the current research priorities of researchers. Fucoidan, an algal sulfated polysaccharide, is a potent therapeutic lead candidate against cancer, signifying that far more research is needed. Fucoidan is a versatile, nontoxic marine-origin heteropolysaccharide that has received much attention due to its beneficial biological properties and safety. Fucoidan has been demonstrated to exhibit a variety of conventional bioactivities, such as antiviral, antioxidant, and immune-modulatory characteristics, and anticancer activity against a wide range of malignancies has also recently been discovered. Fucoidan inhibits tumorigenesis by prompting cell cycle arrest and apoptosis, blocking metastasis and angiogenesis, and modulating physiological signaling molecules. This review compiles the molecular and cellular aspects, immunomodulatory and anticancer actions of fucoidan as a natural marine anticancer agent. Specific fucoidan and membranaceous polysaccharides from Ecklonia cava, Laminaria japonica, Fucus vesiculosus, Astragalus, Ascophyllum nodosum, Codium fragile serving as potential anticancer marine drugs are discussed in this review.

Prognostic implication of elevated cardiac troponin I in patients visiting emergency department without diagnosis of coronary artery disease.

OBJECTIVES: Elevated cardiac troponin is not uncommon in patients visiting emergency department (ED) even without coronary artery disease, but its prognostic implication is not well understood in such patients. METHODS: In this retrospective single-center registry, we investigated clinical outcome of patients visiting ED without documented coronary artery disease. Patients were categorized according to the maximal value of Siemens ADVIA Centaur TnI-Ultra assay (TnI) within 24 h after visit. Primary endpoint was 180-day all-cause death that included cardiac and non-cardiac death. RESULTS: A total of 35,205 patients with median age 61 years and male gender 54.7% were included. Below the lowest level of detection (LOD) (≤0.006 ng/mL), between LOD and assay-specific <99th percentile (0.007-0.039 ng/mL), below median of ≥99th percentile (0.040-0.149 ng/mL), and above median of ≥99th percentile (≥0.150 ng/mL) TnI were found in 18,502 (52.6%), 11,338 (32.2%), 3,029 (8.6%), and 2,336 (6.6%) patients. In the 180-day follow-up period, 4,341 (12.3%) all-cause death including 694 (2.0%) cardiovascular death and 3,647 (10.4%) non-cardiovascular death developed. The risks of all-cause, cardiovascular, and non-cardiovascular death increased across higher TnI strata (hazard ratio [HR]=1.3 to 2.4; 2.0 to 9.3; 1.3 to 1.7; p<0.001, all). Analyses of multivariate models showed consistent results. CONCLUSIONS: In patients visiting ED, elevated TnI was associated with higher risk of 180-day cardiovascular and non-cardiovascular death. Patients with elevated TnI may need additional evaluation or careful follow-up even without primary diagnosis of coronary artery disease.

Binary Superlattice Design by Controlling DNA-Mediated Interactions.

Most binary superlattices created using DNA functionalization rely on particle size differences to achieve compositional order and structural diversity. Here we study two-dimensional (2D) assembly of DNA-functionalized micron-sized particles (DFPs), and employ a strategy that leverages the tunable disparity in interparticle interactions, and thus enthalpic driving forces, to open new avenues for design of binary superlattices that do not rely on the ability to tune particle size (i.e., entropic driving forces). Our strategy employs tailored blends of complementary strands of ssDNA to control interparticle interactions between micron-sized silica particles in a binary mixture to create compositionally diverse 2D lattices. We show that the particle arrangement can be further controlled by changing the stoichiometry of the binary mixture in certain cases. With this approach, we demonstrate the ability to program the particle assembly into square, pentagonal, and hexagonal lattices. In addition, different particle types can be compositionally ordered in square checkerboard and hexagonal-alternating string, honeycomb, and Kagome arrangements.

Assembly of three-dimensional binary superlattices from multi-flavored particles.

Binary superlattices constructed from nano- or micron-sized colloidal particles have a wide variety of applications, including the design of advanced materials. Self-assembly of such crystals from their constituent colloids can be achieved in practice by, among other means, the functionalization of colloid surfaces with single-stranded DNA sequences. However, when driven by DNA, this assembly is traditionally premised on the pairwise interaction between a single DNA sequence and its complement, and often relies on particle size asymmetry to entropically control the crystalline arrangement of its constituents. The recently proposed "multi-flavoring" motif for DNA functionalization, wherein multiple distinct strands of DNA are grafted in different ratios to different colloids, can be used to experimentally realize a binary mixture in which all pairwise interactions are independently controllable. In this work, we use various computational methods, including molecular dynamics and Wang-Landau Monte Carlo simulations, to study a multi-flavored binary system of micron-sized DNA-functionalized particles modeled implicitly by Fermi-Jagla pairwise interactions. We show how self-assembly of such systems can be controlled in a purely enthalpic manner, and by tuning only the interactions between like particles, demonstrate assembly into various morphologies. Although polymorphism is present over a wide range of pairwise interaction strengths, we show that careful selection of interactions can lead to the generation of pure compositionally ordered crystals. Additionally, we show how the crystal composition changes with the like-pair interaction strengths, and how the solution stoichiometry affects the assembled structures.

Differential effects of BDNF and neurotrophin 4 (NT4) on endocytic sorting of TrkB receptors.

Neurotrophins are a family of growth factors playing key roles in the survival, development, and function of neurons. The neurotrophins brain-derived neurotrophic factor (BDNF) and NT4 both bind to and activate TrkB receptors, however, they mediate distinct neuronal functions. The molecular mechanism of how TrkB activation by BDNF and NT4 leads to diverse outcomes is unknown. Here, we report that BDNF and NT4 lead to differential endocytic sorting of TrkB receptors resulting in diverse biological functions in cultured cortical neurons. Fluorescent microscopy and surface biotinylation experiments showed that both neurotrophins stimulate internalization of TrkB with similar kinetics. Exposure to BDNF for 2-3 h reduced the surface pool of TrkB receptors to half, whereas a longer treatment (4-5 h) with NT4 was necessary to achieve a similar level of down-regulation. Although BDNF and NT4 induced TrkB phosphorylation with similar intensities, BDNF induced more rapid ubiquitination and degradation of TrkB than NT4. Interestingly, TrkB receptor ubiquitination by these ligands have substantially different pH sensitivities, resulting in varying degrees of receptor ubiquitination at lower pH levels. Consequently, NT4 was capable of maintaining longer sustained downstream signaling activation that correlated with reduced TrkB ubiquitination at endosomal pH. Thus, by leading to altered endocytic trafficking itineraries for TrkB receptors, BDNF and NT4 elicit differential TrkB signaling in terms of duration, intensity, and specificity, which may contribute to their functional differences in vivo. The neurotrophins, brain-derived neurotrophic factor (BDNF) and neurotrophin-4 (NT4), both bind to and activate TrkB receptors, however, they mediate distinct neuronal functions. Here, we propose that BDNF and NT4 lead to differential endocytic sorting of TrkB receptors resulting in diverse biological functions. BDNF induces more rapid ubiquitination and degradation of TrkB than NT4. Consequently, NT4 is capable of maintaining more sustained signaling downstream of TrkB receptors.

Effect of Nonionic Surfactant on Association/Dissociation Transition of DNA-Functionalized Colloids.

We report the effect of nonionic surfactants (Pluronics F127 and F88) on the melting transition of micron-sized colloids confined in two dimensions, mediated by complementary single-stranded DNA as a function of the surfactant concentration. Micron-sized silica particles were functionalized with single-stranded DNA using cyanuric chloride chemistry. The existence of covalently linked DNA on particles was confirmed by fluorescence spectroscopy. The nonionic surfactant not only plays a significant role in stabilization of particles, with minimization of nonspecific binding, but also impacts the melting temperature, which increases as a function of the nonionic surfactant concentration. These results suggest that the melting transition for DNA-mediated assembly is sensitive to commonly used additives in laboratory buffers, and that these common solution components may be exploited as a facile and independent handle for tuning the melting temperature and, thus, the assembly and possibly crystallization within these systems.

Anxiety-associated alternative polyadenylation of the serotonin transporter mRNA confers translational regulation by hnRNPK.

The serotonin transporter (SERT) is a major regulator of serotonergic neurotransmission and anxiety-related behaviors. SERT is expressed in two alternative polyadenylation forms that differ by an evolutionarily conserved element in the 3' untranslated region of its mRNA. Expression of SERT mRNA containing the distal polyadenylation element is associated with decreased anxiety-related behaviors in mice and humans, suggesting that this element has behaviorally relevant modulatory effects on SERT expression. We have identified heterogeneous nuclear ribonucleoprotein K (hnRNPK), a protein known to integrate multiple signal transduction pathways with gene expression, as a SERT distal polyadenylation element binding protein. This interaction is functionally meaningful because genetic manipulation of hnRNPK alters expression of the SERT protein. Furthermore, the trophic factor S100ß induces Src-family kinase-mediated tyrosine phosphorylation of hnRNPK and increased SERT expression. These results identify a previously unknown mechanism of regulated SERT expression and provide a putative mechanism by which the SERT distal polyadenylation element modulates anxiety-related behaviors.

Insight into the Association between Slitrk Protein and Neurodevelopmental and Neuropsychiatric Conditions.

Slitrk proteins belong the leucine-rich repeat transmembrane family and share structural similarities with the Slits and tropomyosin receptor kinase families, which regulate the development of the nervous system. Slitrks are highly expressed in the developing nervous system of vertebrates, modulating neurite outgrowth and enhancing synaptogenesis; however, the expression and function of Slitrk protein members differ. Slitrk protein variations have been associated with various sensory and neuropsychiatric conditions, including myopia, deafness, obsessive-compulsive disorder, autism spectrum disorders, schizophrenia, attention-deficit/hyperactivity disorder, glioma, and Tourette syndrome; however, the underlying mechanism remains unclear. Therefore, the Slitrk family members' protein expression, roles in the signaling cascade, functions, and gene mutations need to be comprehensively studied to develop therapeutics against neurodegenerative diseases. This study presents complete and pertinent information demonstrating the relationship between Slitrk family proteins and neuropsychiatric illnesses. This review briefly discusses neurodevelopmental disorders, the leucine-rich repeat family, the Slitrk family, and the association of Slitrk with the neuropathology of representative disorders.

An updated review on animal models to study attention-deficit hyperactivity disorder.

Attention-deficit hyperactivity disorder (ADHD) is a neuropsychiatric disorder affecting both children and adolescents. Individuals with ADHD experience heterogeneous problems, such as difficulty in attention, behavioral hyperactivity, and impulsivity. Recent studies have shown that complex genetic factors play a role in attention-deficit hyperactivity disorders. Animal models with clear hereditary traits are crucial for studying the molecular, biological, and brain circuit mechanisms underlying ADHD. Owing to their well-managed genetic origins and the relative simplicity with which the function of neuronal circuits is clearly established, models of mice can help learn the mechanisms involved in ADHD. Therefore, in this review, we highlighting the important genetic animal models that can be used to study ADHD.

Signal alignment for cross-datasets in P300 brain-computer interfaces.

Objective.Transfer learning has become an important issue in the brain-computer interface (BCI) field, and studies on subject-to-subject transfer within the same dataset have been performed. However, few studies have been performed on dataset-to-dataset transfer, including paradigm-to-paradigm transfer. In this study, we propose a signal alignment (SA) for P300 event-related potential (ERP) signals that is intuitive, simple, computationally less expensive, and can be used for cross-dataset transfer learning.Approach.We proposed a linear SA that uses the P300's latency, amplitude scale, and reverse factor to transform signals. For evaluation, four datasets were introduced (two from conventional P300 Speller BCIs, one from a P300 Speller with face stimuli, and the last from a standard auditory oddball paradigm).Results.Although the standard approach without SA had an average precision (AP) score of 25.5%, the approach demonstrated a 35.8% AP score, and we observed that the number of subjects showing improvement was 36.0% on average. Particularly, we confirmed that the Speller dataset with face stimuli was more comparable with other datasets.Significance.We proposed a simple and intuitive way to align ERP signals that uses the characteristics of ERP signals. The results demonstrated the feasibility of cross-dataset transfer learning even between datasets with different paradigms.