Novel insights into the roles of migrasome in cancer.

Cell migration, a hallmark of cancer malignancy, plays a critical role in cancers. Improperly initiated or misdirected cell migration can lead to invasive metastatic cancer. Migrasomes are newly discovered vesicular cellular organelles produced by migrating cells and depending on cell migration. Four marker proteins [NDST1 (bifunctionalheparan sulfate N-deacetylase/N-sulfotransferase 1), EOGT (Epidermal growth factor domains pecific O-linked N-acetylglucosaminetransferase), CPQ (carboxypeptidase Q), and PIGK (phosphatidylinositol glycan anchor biosynthesis, class K)] of migrasomes were successfully identified. There are three marker proteins (NDST1, PIGK, and EOGT) of migrasome expressed in cancer. In this review, we will discuss the process of migrasome discovery, the formation of migrasome, the possible functions of migrasome, and the differences between migrasomes and exosomes, especially, the biological functions of migrasome marker proteins in cancer, and discuss some possible roles of migrasomes in cancer. We speculate that migrasomes and migracytosis can play key roles in regulating the development of cancer.

Porous Organic Framework Materials (MOF, COF, and HOF) as the Multifunctional Separator for Rechargeable Lithium Metal Batteries.

The separator is an important component in batteries, with the primary function of separating the positive and negative electrodes and allowing the free passage of ions. Porous organic framework materials have a stable connection structure, large specific surface area, and ordered pores, which are natural places to store electrolytes. And these materials with specific functions can be designed according to the needs of researchers. The performance of porous organic framework-based separators used in rechargeable lithium metal batteries is much better than that of polyethylene/propylene separators. In this paper, the three most classic organic framework materials (MOF, COF, and HOF) are analyzed and summarized. The applications of MOF, COF, and HOF separators in lithium-sulfur batteries, lithium metal anode, and solid electrolytes are reviewed. Meanwhile, the research progress of these three materials in different fields is discussed based on time. Finally, in the conclusion, the problems encountered by MOF, COF, and HOF in different fields as well as their future research priorities are presented. This review will provide theoretical guidance for the design of porous framework materials with specific functions and further stimulate researchers to conduct research on porous framework materials.

Regional perspectives on patient safety policies and initiatives: a focus group study with patient safety leaders in the Middle East and Asian regions.

Preventing and reducing risks and harm to patients is of critical importance as unsafe care is a leading cause of death and disability globally. However, the lack of consolidated information on patient safety policies and initiatives at regional levels represents an evidence gap with implications for policy and planning. The aim of the study was to answer the question of what patient safety policies and initiatives are currently in place in the Middle East and Asian regions and what were the main strengths, weaknesses, opportunities and threats in developing these. A qualitative approach using online focus groups was adopted. Participants attended focus groups beginning in August 2022. A topic guide was developed using a strengths, weaknesses, opportunities and threats framework analysis approach. The Consolidated Criteria for Reporting Qualitative Research checklist was used to ensure the recommended standards of qualitative data reporting were met. 21 participants from 11 countries participated in the study. Current patient safety policies identified were categorised across 5 thematic areas and initiatives were categorised across a further 10 thematic areas. Strengths of patient safety initiatives included enabling healthcare worker training, leadership commitment in hospitals, and stakeholder engagement and collaboration. Weaknesses included a disconnect between health delivery and education, implementation gaps, low clinical awareness and buy-in at the facility level, and lack of leadership engagement. Just culture, safety by design and education were considered opportunities, alongside data collection and reporting for research and shared learning. Future threats were low leadership commitment, changing leadership, poor integration across the system, a public-private quality gap and political instability in some contexts. Undertaking further research regionally will enable shared learning and the development of best practice examples. Future research should explore the development of policies and initiatives for patient safety at the provider, local and national levels that can inform action across the system.

An ensemble machine learning model generates a focused screening library for the identification of CDK8 inhibitors.

The identification of an effective inhibitor is an important starting step in drug development. Unfortunately, many issues such as the characterization of protein binding sites, the screening library, materials for assays, etc., make drug screening a difficult proposition. As the size of screening libraries increases, more resources will be inefficiently consumed. Thus, new strategies are needed to preprocess and focus a screening library towards a targeted protein. Herein, we report an ensemble machine learning (ML) model to generate a CDK8-focused screening library. The ensemble model consists of six different algorithms optimized for CDK8 inhibitor classification. The models were trained using a CDK8-specific fragment library along with molecules containing CDK8 activity. The optimized ensemble model processed a commercial library containing 1.6 million molecules. This resulted in a CDK8-focused screening library containing 1,672 molecules, a reduction of more than 99.90%. The CDK8-focused library was then subjected to molecular docking, and 25 candidate compounds were selected. Enzymatic assays confirmed six CDK8 inhibitors, with one compound producing an IC50 value of ≤100 nM. Analysis of the ensemble ML model reveals the role of the CDK8 fragment library during training. Structural analysis of molecules reveals the hit compounds to be structurally novel CDK8 inhibitors. Together, the results highlight a pipeline for curating a focused library for a specific protein target, such as CDK8.

Superior cerebellar peduncle deep brain stimulation for cerebral palsy.

OBJECTIVE: Patients with coexisting spastic cerebral palsy (CP) and dystonia have limited treatment options. In this study, the authors aimed to evaluate the efficacy of deep brain stimulation (DBS) targeting the superior cerebellar peduncles (SCPs) in adults with CP. METHODS: Five patients with CP and medically refractory dystonia and spasticity underwent SCP DBS. Assessments included the Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS), modified Ashworth scale (mAS), and tests of cognition, mental status, and quality of life preoperatively and at 3, 6, and 12 months postoperatively (in both DBS ON and OFF states, double blinded). Active contacts and fiber bundles were examined. RESULTS: Four patients completed follow-up. The BFMDRS motor score decreased from 74 to 52 at 12 months postoperatively (30%, p = 0.008). The mean mAS score indicated significant spasticity reduction (from 2.9 ± 0.9 to 1.9 ± 0.6 after 12 months, p = 0.0454). Quality of life improved (p < 0.01), while cognition remained unaffected. Active contacts were found within the dentato-rubro-thalamic tract, with variable efficiency in decussating and nondecussating portions. CONCLUSIONS: In this pilot trial, SCP DBS showed promise as a well-tolerated treatment for CP, improving dystonic symptoms, spasticity, quality of life, and functional capacities. However, caution is needed when interpreting the results given the small sample size and heterogeneous motor outcomes.

Adaptation and validation of the Claremont Purpose Scale to measure Chinese adolescents' purpose in life.

Despite purpose measures being developed for adolescents, quantitative research investigating purposes prior to late adolescence and in non-Western societies remains nascent. This study evaluated the psychometric soundness of the Claremont Purpose Scale among Chinese adolescents. An initial prestudy (n = 34) was conducted to ensure linguistic equivalence. Subsequently, Study 1 (n = 1691) assessed the scale's reliability and factor structure, also investigating its functional equivalence across gender, adolescence stages, and language versions at the item level. Study 2 (n = 7842) investigated the scale's construct, convergent, predictive, and incremental validity, as well as tested for the scale's measurement invariance across different groups at the scale level. The results support the scale's use as a tool for researchers and practitioners to understand and cultivate purpose in adolescents.

Layer-Specific Knowledge Distillation for Class Incremental Semantic Segmentation.

Recently, class incremental semantic segmentation (CISS) towards the practical open-world setting has attracted increasing research interest, which is mainly challenged by the well-known issue of catastrophic forgetting. Particularly, knowledge distillation (KD) techniques have been widely studied to alleviate catastrophic forgetting. Despite the promising performance, existing KD-based methods generally use the same distillation schemes for different intermediate layers to transfer old knowledge, while employing manually tuned and fixed trade-off weights to control the effect of KD. These KD-based methods take no consideration of feature characteristics from different intermediate layers, limiting the effectiveness of KD for CISS. In this paper, we propose a layer-specific knowledge distillation (LSKD) method to assign appropriate knowledge schemes and weights for various intermediate layers by considering feature characteristics, aiming to further explore the potential of KD in improving the performance of CISS. Specifically, we present a mask-guided distillation (MD) to alleviate the background shift on semantic features, which performs distillation by masking the features affected by the background. Furthermore, a mask-guided context distillation (MCD) is presented to explore global context information lying in high-level semantic features. Based on them, our LSKD assigns different distillation schemes according to feature characteristics. To adjust the effect of layer-specific distillation adaptively, LSKD introduces a regularized gradient equilibrium method to learn dynamic trade-off weights. Additionally, our LSKD makes an attempt to simultaneously learn distillation schemes and trade-off weights of different layers by developing a bi-level optimization method. Extensive experiments on widely used Pascal VOC 12 and ADE20K show our LSKD clearly outperforms its counterparts while achieving state-of-the-art results.

Difference in muscle metabolism caused by metabolism disorder of rainbow trout liver exposed to ammonia stress.

Ammonia pollution is an important environmental stress factors in water eutrophication. The intrinsic effects of ammonia stress on liver toxicity and muscle quality of rainbow trout were still unclear. In this study, we focused on investigating difference in muscle metabolism caused by metabolism disorder of rainbow trout liver at exposure times of 0, 3, 6, 9 h at 30 mg/L concentrations. Liver transcriptomic analysis revealed that short-term (3 h) ammonia stress inhibited carbohydrate metabolism and glycerophospholipid production but long-term (9 h) ammonia stress inhibited the biosynthesis and degradation of fatty acids, activated pyrimidine metabolism and mismatch repair, lead to DNA strand breakage and cell death, and ultimately caused liver damage. Metabolomic analysis of muscle revealed that ammonia stress promoted the reaction of glutamic acid and ammonia to synthesize glutamine to alleviate ammonia toxicity, and long-term (9 h) ammonia stress inhibited urea cycle, hindering the alleviation of ammonia toxicity. Moreover, it accelerated the consumption of flavor amino acids such as arginine and aspartic acid, and increased the accumulation of bitter substances (xanthine) and odorous substances (histamine). These findings provide valuable insights into the potential risks and hazards of ammonia in eutrophic water bodies subject to rainbow trout.

Nontargeted metabolomics and enzyme inhibitory and antioxidant activities for chemical and biological characterization of jujube (Ziziphus jujuba) extracts.

The chemical and biologically active characterization of jujube samples (fruits, cores, and leaves) were carried out by the integrated nontargeted metabolomics and bioassay. Firstly, collision cross-section values of active compounds in jujubes were determined by ultrahigh-performance liquid chromatography coupled with ion mobility quadrupole time-of-flight mass spectrometry. Then, a multidimensional statistical analysis that contained principal component analysis, partial least squares-discriminant analysis and hierarchical clustering analysis was employed to effectively cluster different tissues and types of jujubes, making identification more scientific. Furthermore, angiotensin-converting enzyme (ACE) and 2, 2-diphenyl-1-picrylhydrazyl (DPPH) were used to evaluate the quality of jujubes from a double activity dimension. The analytical results obtained by using ACE and DPPH to evaluate the quality of jujube were different from multivariate statistics, providing a reference for the application of jujube. Therefore, integrating chemical and biological perspectives to evaluate the quality of jujube provided a more comprehensive evaluation and effective reference for clinical needs.

Optimizing Deep Brain Stimulation in Essential Tremor: A Randomized Controlled Trial for Target Consideration.

BACKGROUND AND OBJECTIVES: The thalamic ventral intermediate nucleus (VIM) is a well-established target for deep brain stimulation (DBS) in the treatment of essential tremor (ET). Increasing data indicate that the posterior subthalamic area (PSA) may be superior, but high-level evidence is limited. We aimed at further comparing the intraindividual efficacy and side effect profile of PSA vs VIM DBS in ET. METHODS: In this randomized, double-blind, crossover trial, 4-contact DBS leads were bilaterally implanted with single-trajectory covering the VIM and PSA. Patients were randomized postsurgery to 2 groups, receiving VIM stimulation (4-7 months) and then PSA stimulation (8-11 months) or vice versa. The primary end point was the difference in improvement from baseline to the end of the VIM vs PSA DBS period in the total score of the Fahn-Tolosa-Marin Tremor Rating Scale (FTM-TRS). RESULTS: Ten patients with medically refractory ET were enrolled, and 9 completed the study. The difference between reduction of FTM-TRS total score in the PSA vs VIM DBS period was -7.4 (95% CI: -28.5 to 13.7, P = .328). Clinical benefit was achieved at significantly lower stimulation intensity under PSA DBS. Furthermore, PSA DBS provided greater improvement in head tremor subscore of FTM-TRS (PSA vs VIM: -2.2, P = .020) and disease-specific quality of life (PSA vs VIM: -13.8, P = .046) and induced fewer speech (Dysphonia Severity Index score: P = .043; diadochokinetic rate: P = .007; VDI score: P = .005) and gait disturbances compared with VIM DBS. Seven patients remained with PSA DBS after the crossover phase. CONCLUSION: Our study confirms that PSA-DBS is comparable with VIM-DBS in suppressing tremors, superior in improving disease-specific quality of life, and possibly more effective in reducing head tremor.

Identification of selective dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) inhibitors and their effects on tau and microtubule.

The overexpression of dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A), commonly observed in neurodegenerative diseases like Alzheimer's disease (AD) and Down syndrome (DS), can induce the formation of neurofibrillary tangles (NFTs) and amyloid plaques. Hence, designing a selective DYRK1A inhibitor would result in a promising small molecule for treating neurodegenerative diseases. Developing selective inhibitors for DYRK1A has been a difficult challenge due to the highly preserved ATP-binding site of protein kinases. In this study, we employed a structure-based virtual screening (SBVS) campaign targeting DYRK1A from a database containing 1.6 million compounds. Enzymatic assays were utilized to verify inhibitory properties, confirming that Y020-3945 and Y020-3957 showed inhibitory activity towards DYRK1A. In particular, the compounds exhibited high selectivity for DYRK1A over a panel of 120 kinases, reduced the phosphorylation of tau, and reversed the tubulin polymerization for microtubule stability. Additionally, treatment with the compounds significantly reduced the secretion of inflammatory cytokines IL-6 and TNF-α activated by DYRK1A-assisted NFTs and Aß oligomers. These identified inhibitors possess promising therapeutic potential for conditions associated with DYRK1A in neurodegenerative diseases. The results showed that Y020-3945 and Y020-3957 demonstrated structural novelty compared to known DYRK1A inhibitors, making them a valuable addition to developing potential treatments for neurodegenerative diseases.

Embedded bioprinted multicellular spheroids modeling pancreatic cancer bioarchitecture towards advanced drug therapy.

The desmoplastic bioarchitecture and microenvironment caused by fibroblasts have been confirmed to be closely related to the drug response behavior of pancreatic ductal adenocarcinoma (PDAC). Despite the extensive progress in developing PDAC models as in vitro drug screening platforms, developing efficient and controllable approaches for the construction of physiologically relevant models remains challenging. In the current study, multicellular spheroid models that emulate pancreatic cancer bioarchitecture and the desmoplastic microenvironment are bioengineered. An extrusion-based embedded dot bioprinting strategy was established to fabricate PDAC spheroids in a one-step process. Cell-laden hydrogel beads were directly deposited into a methacrylated gelatin (GelMA) suspension bath to generate spherical multicellular aggregates (SMAs), which further progressed into dense spheroids through in situ self assembly. By modulating the printing parameters, SMAs, even from multiple cell components, could be manipulated with tunable size and flexible location, achieving tunable spheroid patterns within the hydrogel bath with reproducible morphological features. To demonstrate the feasibility of this printing strategy, we fabricated desmoplastic PDAC spheroids by printing SMAs consisting of tumor cells and fibroblasts within the GelMA matrix bath. The produced hybrid spheroids were further exposed to different concentrations of the drug gemcitabine to verify their potential for use in cell therapy. Beyond providing a robust and facile bioprinting system that enables desmoplastic PDAC bioarchitecture bioengineering, this work introduces an approach for the scalable, flexible and rapid fabrication of cell spheroids or multi-cell-type spheroid patterns as platforms for advanced drug therapy or disease mechanism exploration.

The Impact of miR-122 on Cancer.

MiRNAs are confirmed to be a kind of short and eminently conserved noncoding RNAs, which regulate gene expression at the post-transcriptional level via binding to the 3'- untranslated region (3'-UTR) of targeting multiple target messenger RNAs. Recently, growing evidence stresses the point that they play a crucial role in a variety of pathological processes, including human cancers. Dysregulated miRNAs act as oncogenes or tumor suppressor genes in many cancer types. Among them, we noticed that miR-122 has been widely reported to significantly influence carcinogenicity in a variety of tumors by regulating target genes and signaling pathways. Here, we focused on the expression of miR-122 in regulatory mechanisms and tumor biological processes. We also discussed the effects of miR-122 dysregulation in various types of human malignancies and the potential to develop new molecular miR-122-targeted therapies. The present review suggests that miR-122 may be a potentially useful cancer diagnosis and treatment biomarker. More clinical diagnoses need to be further launched in the future. A promising direction to improve the outcomes for cancer patients will likely combine miR-122 with other traditional tumor biomarkers.

Perspective from single-cell sequencing: Is inflammation in acute ischemic stroke beneficial or detrimental?

BACKGROUND: Acute ischemic stroke (AIS) is a common cerebrovascular event associated with high incidence, disability, and poor prognosis. Studies have shown that various cell types, including microglia, astrocytes, oligodendrocytes, neurons, and neutrophils, play complex roles in the early stages of AIS and significantly affect its prognosis. Thus, a comprehensive understanding of the mechanisms of action of these cells will be beneficial for improving stroke prognosis. With the rapid development of single-cell sequencing technology, researchers have explored the pathophysiological mechanisms underlying AIS at the single-cell level. METHOD: We systematically summarize the latest research on single-cell sequencing in AIS. RESULT: In this review, we summarize the phenotypes and functions of microglia, astrocytes, oligodendrocytes, neurons, neutrophils, monocytes, and lymphocytes, as well as their respective subtypes, at different time points following AIS. In particular, we focused on the crosstalk between microglia and astrocytes, oligodendrocytes, and neurons. Our findings reveal diverse and sometimes opposing roles within the same cell type, with the possibility of interconversion between different subclusters. CONCLUSION: This review offers a pioneering exploration of the functions of various glial cells and cell subclusters after AIS, shedding light on their regulatory mechanisms that facilitate the transformation of detrimental cell subclusters towards those that are beneficial for improving the prognosis of AIS. This approach has the potential to advance the discovery of new specific targets and the development of drugs, thus representing a significant breakthrough in addressing the challenges in AIS treatment.

Synthesis and evaluation of potent (iso)ellipticine-based inhibitors of MYLK4 accessed via expeditious synthesis from isoquinolin-5-ol.

The K2S2O8-mediated generation of p-iminoquinone contributed to the regioselective substitution of isoquinolin-5,8-dione. This hydroxyl group-guided substitution was also applied to selected heterocycles and addressed the regioselectivity issue of quinones. This study has provided an expeditious pathway from isoquinolin-5-ol (5) to ellipticine (1) and isoellipticine (2), which benefits the comprehensive comparison of their activity. Compounds 1 and 2 displayed marked MYLK4 inhibitory activity with IC50 values of 7.1 and 6.1 nM, respectively. In the cellular activity of AML cells (MV-4-11 and MOLM-13), compound 1 showed better AML activity than compound 2.

Application of intraarterial superselective indocyanine green angiography in bypass surgery for adult moyamoya disease.

Background: Extracranial-intracranial (EC-IC) bypass surgery is the main treatment approach to moyamoya disease, and an accurate assessment of the patency of anastomosis is critical for successful surgery. So far, the most common way to do this is the intraoperative intravenous indocyanine green (ICG) video-angiography. Intra-arterial ICG-VA has been applied to treat peripheral cerebral aneurysms, spinal arteriovenous fistulas, and dural arteriovenous fistulas, but few reports have concerned the use of arterial injection of ICG to evaluate anastomotic patency. This research aims to explore the feasibility and effects of catheter-guided superficial temporal artery injection of ICG in the evaluation of anastomotic patency after bypass surgery. Methods: In this study, 20 patients with moyamoya disease or syndrome who underwent bypass surgery were divided into two groups, one who received intravenous ICG angiography and the other who received intra-arterial ICG angiography, to compare the two injection methods for vascular anastomosis patency. We conducted conventional intraoperative digital subtraction angiography (DSA) in a hybrid operating room during extracranial-intracranial (EC-IC) bypass surgery, including the additional step of injecting ICG into the main trunk of the superficial temporal artery (STA) through a catheter. Results: Intra-arterial injection of indocyanine green video-angiography (ICG-VA) indicated good patency of the vascular anastomosis when compared with conventional digital subtraction angiography (DSA) and intravenous ICG-VA, confirming the feasibility of using the arterial injection of ICG for assessing anastomotic patency. And intra-arterial ICG-VA results in faster visualization than intravenous ICG-VA (p < 0.05). Besides, ICG-VA through arterial injection provided valuable information on the vascular blood flow direction after the bypass surgery, and allowed for visual inspection of the range of cortical brain supply from the superficial temporal artery and venous return from the cortex. Moreover, arterial injection of ICG offered a rapid dye washout effect, reducing the repeat imaging time. Conclusion: This study indicates that intra-arterial ICG-VA has good effects in observing the direction of blood flow in blood vessels and the range of cortical brain supply from the STA, which reflects blood flow near the anastomosis and provides additional information that may allow the postoperative prediction of cerebral hyperperfusion syndrome. However, the procedure of intra-arterial ICG-VA is relatively complicated compared to intravenous ICG-VA.

Intestinal epithelial dopamine receptor signaling drives sex-specific disease exacerbation in a mouse model of multiple sclerosis.

Although the gut microbiota can influence central nervous system (CNS) autoimmune diseases, the contribution of the intestinal epithelium to CNS autoimmunity is less clear. Here, we showed that intestinal epithelial dopamine D2 receptors (IEC DRD2) promoted sex-specific disease progression in an animal model of multiple sclerosis. Female mice lacking Drd2 selectively in intestinal epithelial cells showed a blunted inflammatory response in the CNS and reduced disease progression. In contrast, overexpression or activation of IEC DRD2 by phenylethylamine administration exacerbated disease severity. This was accompanied by altered lysozyme expression and gut microbiota composition, including reduced abundance of Lactobacillus species. Furthermore, treatment with N2-acetyl-L-lysine, a metabolite derived from Lactobacillus, suppressed microglial activation and neurodegeneration. Taken together, our study indicates that IEC DRD2 hyperactivity impacts gut microbial abundances and increases susceptibility to CNS autoimmune diseases in a female-biased manner, opening up future avenues for sex-specific interventions of CNS autoimmune diseases.

A self-training algorithm based on the two-stage data editing method with mass-based dissimilarity.

A self-training algorithm is a classical semi-supervised learning algorithm that uses a small number of labeled samples and a large number of unlabeled samples to train a classifier. However, the existing self-training algorithms consider only the geometric distance between data while ignoring the data distribution when calculating the similarity between samples. In addition, misclassified samples can severely affect the performance of a self-training algorithm. To address the above two problems, this paper proposes a self-training algorithm based on data editing with mass-based dissimilarity (STDEMB). First, the mass matrix with the mass-based dissimilarity is obtained, and then the mass-based local density of each sample is determined based on its k nearest neighbors. Inspired by density peak clustering (DPC), this study designs a prototype tree based on the prototype concept. In addition, an efficient two-stage data editing algorithm is developed to edit misclassified samples and efficiently select high-confidence samples during the self-training process. The proposed STDEMB algorithm is verified by experiments using accuracy and F-score as evaluation metrics. The experimental results on 18 benchmark datasets demonstrate the effectiveness of the proposed STDEMB algorithm.