Functional Analysis Research Articles

Characterised intron retention profiles in muscle tissue of idiopathic inflammatory myopathy subtypes

ObjectivesIdiopathic inflammatory myopathies (IIMs) are a group of heterogeneous autoimmune diseases. Intron retention (IR) serves as an important post-transcriptional and translational regulatory mechanism. This study aims to identify changes in...

Sustained ecological impacts of invasive crayfish following claw injury

ABSTRACT Human activities have significantly accelerated the translocation of species outside their native range with severe consequences for global biodiversity. Freshwater crayfish are a particularly successful group of invasive species, as exemplified by the increasingly widespread marbled crayfish Procambarus virginalis Lyko, 2017. A significant portion of crayfish populations has regenerating or missing claws. At the same time, claws play important roles in crayfish feeding and intraspecific interactions, altering their ability to invade new areas and impact native communities. Here, using functional response analyses, we combined laboratory experiments and modeling to investigate whether the number of claws on marbled crayfish modulates its ecological impact (focusing on predation rate) as well as its intraspecific interactions via population dynamic modeling. We found that the number of claws did not affect the marbled crayfish’s functional response type (hyperbolic type II), attack rates, or handling times when preying on chironomid larvae. Rates of partial prey consumption were overall low (<2%), and claw number had a significant effect on the partial consumption rate of prey, which tended to increase with the number of claws and prey density. The presence of multiple intraspecific predators influenced marbled crayfish non-trophic behavior, with antagonistic effects prevalent between crayfish pairs regardless of claw status. Moreover, the impact of multiple predators was prey density-dependent, with the highest levels of antagonism shown at the lowest prey density across crayfish groups. Our findings indicate that the ecological influence of invasive crayfish remains unchanged by the number of claws, highlighting the escalating, context-independent threat these species pose to freshwater ecosystems.

Research of active compounds from Allii Macrostemonis Bulbus and potential targets against Non-Hodgkin's Lymphoma based on Network pharmacology.

Non-Hodgkin's Lymphoma (NHL) is a series of lymphoid malignancies in some aggressive subtypes with unsatisfactory treatment effects. Allii Macrostemonis Bulbus (Xie Bai) is a traditional Chinese medicine with anti-cancer activities, which may potentially suppress aggressive NHL. This study tries to discover active components and targets of Xie Bai in treating NHL by network pharmacology-based approaches. Compounds and related targets of Xie Bai were collected from the Traditional Chinese Medicine Database and Analysis Platform. Target genes associated with NHL were searched by GeneCards and DisGeNET, then the overlapped targets were further analyzed by STRING tool, GO, and KEGG pathway enrichment analysis. Molecular docking was employed to verify the interaction between compounds and targets. 11 bioactive compounds were successfully identified, with 30 targets that were screened out for the treatment of NHL. Functional enrichment analysis suggested that Xie Bai exerted its potential effects against NHL via pathways in cancer, such as PI3K/ AKT, p53, and MAPK signaling pathways. Molecular docking results showed that 3 active compounds (quercetin, beta-sitosterol, and naringenin) had good affinity with selected 6 targets（TP53, AKT1, CASP3, CCND1, HPK1, and NLRP3). Identifying six potential genes could accurately be docked with Xie Bai and had close interactions with NHL, which may provide insight into further research and new treatment strategy.

Topology optimization of anisotropic structure for arbitrary objective functionals with exact free boundary representation

A new approach to performing sensitivity analysis of arbitrary objective functionals for anisotropic elasticity is proposed in this work. Three different objective functionals have been considered, and good agreement is achieved between derived topological derivatives and numerical ones. Following the verification of topological derivatives, structural topology optimizations for selected anisotropic problems are conducted. To efficiently achieve the exact free boundary representation, our Finite Element Method (FEM)-based optimization comprises two loops. In the initial loop, a fixed and coarse mesh is employed to solve the anisotropic problem and update the level-set function. Once this loop concludes, the second loop reconstructs the material domain, ensuring an exact boundary representation. The convergence of the second loop is facilitated by (1) utilizing topological derivatives instead of explicit derivatives of ϕ (similar to density derivatives) and (2) imposing the exact volume constraint on the Reaction-Diffusion Equation (RDE)-based level-set method. Moreover, we introduce a scheme to prevent structural breakdown, allowing for the standalone implementation of Loop 2 always with exact free boundary representation. The previously proposed algorithm for the exact volume constraint has been generalized to accommodate inequalities, resulting in an acceleration of the equivalent optimization process.

Identification of key genes and signalling pathways in clear cell renal cell carcinoma: An integrated bioinformatics approach.

Clear cell Renal Cell Carcinoma (ccRCC) is one of the most prevalent types of kidney cancer. Unravelling the genes responsible for driving cellular changes and the transformation of cells in ccRCC pathogenesis is a complex process. In this study, twelve microarray ccRCC datasets were chosen from the gene expression omnibus (GEO) database and subjected to integrated analysis. Through GEO2R analysis, 179 common differentially expressed genes (DEGs) were identified among the datasets. The common DEGs were subjected to functional enrichment analysis using ToppFun followed by construction of protein-protein interaction network (PPIN) using Cytoscape. Clusters within the DEGs PPIN were identified using the Molecular Complex Detection (MCODE) Cytoscape plugin. To identify the hub genes, the centrality parameters degree, betweenness, and closeness scores were calculated for each DEGs in the PPIN. Additionally, Gene Expression Profiling Interactive Analysis (GEPIA) was utilized to validate the relative expression levels of hub genes in the normal and ccRCC tissues. The common DEGs were highly enriched in Hypoxia-inducible factor (HIF) signalling and metabolic reprogramming pathways. VEGFA, CAV1, LOX, CCND1, PLG, EGF, SLC2A1, and ENO2 were identified as hub genes. Among 8 hub genes, only the expression levels of VEGFA, LOX, CCND1, and EGF showed a unique expression pattern exclusively in ccRCC on compared to other type of cancers.

Gene Co-Expression Analysis of Multiple Brain Tissues Reveals Correlation of FAM222A Expression with Multiple Alzheimer's Disease-Related Genes.

Alzheimer's disease (AD) is the most common form of dementia in the elderly marked by central nervous system (CNS) neuronal loss and amyloid plaques. FAM222A, encoding an amyloid plaque core protein, is an AD brain atrophy susceptibility gene that mediates amyloid-β aggregation. However, the expression interplay between FAM222A and other AD-related pathway genes is unclear. Our goal was to study FAM222A's whole-genome co-expression profile in multiple tissues and investigate its interplay with other AD-related genes. We analyzed gene expression correlations in Genotype-Tissue Expression (GTEx) tissues to identify FAM222A co-expressed genes and performed functional enrichment analysis on identified genes in CNS system. Genome-wide gene expression profiling identified 673 genes significantly correlated with FAM222A (p < 2.5×10-6) in 48 human tissues, including 298 from 13 CNS tissues. Functional enrichment analysis revealed that FAM222A co-expressed CNS genes were enriched in multiple AD-related pathways. Gene co-expression network analysis for identified genes in each brain region predicted other disease associated genes with similar biological function. Furthermore, co-expression of 25 out of 31 AD-related pathways genes with FAM222A was replicated in brain samples from 107 aged subjects from the Aging, Dementia and TBI Study. This gene co-expression study identified multiple AD-related genes that are associated with FAM222A, indicating that FAM222A and AD-associated genes can be active simultaneously in similar biological processes, providing evidence that supports the association of FAM222A with AD.

Huangqin-Huanglian Decoction Protects Liver against Non-alcoholic Fatty Liver Disease in High Fat-diet Mice.

Traditional Chinese medicine (TCM) has the advantage of low toxicity of natural ingredients, multiple targets and effects, and low medication costs. It has unique advantages for metabolic and chronic diseases. Huangqin-Huanglian decoction (HQHLD) is composed of Scutellariae Radix, Coptidis Rhizoma, Rehmanniae Radix, and Gentianae Radix Et Rhozima; it has great potential for the treatment of NAFLD with the modern pharmacological research and TCM theory, but there is still a relative lack of research on the potential targets and pharmacological effects of HQHLD. In this work, we have used network pharmacology to predict the targets and signaling pathways of HQHLD, and validated NAFLD-related targets using the HFD model in order to explore more therapeutic drugs and methods for NAFLD. We collected the HQHLD ingredients and NAFLD targets through TCMSP, ETCM, DisGeNET, HGMD, MalaCards, OMIM, and TTD, built ingredients-target networks by Cytoscape, and screened key ingredients in HQHLD. DAVID and Metascape databases were used for GO functional enrichment analysis and KEGG pathway enrichment analysis, respectively. Molecular docking of the key ingredients and key targets was performed by AutoDock. We verified the effect of HQHLD on high-fat diet (HFD) mice by measuring the weight, liver weight index, and the level of TG, TC, LDL-C, and HDLC. HE staining and oil-red staining were performed to detect the damage and fat accumulation in the liver. The changes in INSR, PPAR-α, PPAR-γ, TNF-α, and caspase3 were experimented with WB. With the network pharmacology analysis, we found quercetin, baicalein, sitosterol, wogonin, oroxylin-A, glycyrrhizin, hydroberberine, berberine, sesamin, and carotene to be the main ingredients in HQHLD. According to KEGG pathway analysis, INSR, AKT, JNK1, PPAR-α, PPAR-γ, and the other 16 targets are the main targets of HQHLD in the treatment of NAFLD. We took HFD mice as the in vivo model of NAFLD. Our results showed that HQHLD could reduce liver weight, and TG and LDL-C levels, and increase HDL-C level in serum. By HE and oil red staining, we found that HQHLD could protect the morphology of hepatocytes and reduce fat in the liver. We also found HQHLD to protect the liver by increasing the expression of INSR and PPAR-α, and reducing the expression of PPAR-γ, TNF-α, and caspase3 in the liver. In conclusion, our study has firstly studied the main ingredients and key targets of HQHDL in treating NAFLD by network pharmacology analysis, and preliminarily confirmed that HQHLD could alleviate NAFLD in a multi-target way by lowering fatty acids, and decreasing insulin resistance, inflammation, and apoptosis in the liver.

Network Pharmacological Analysis and Experimental Validation of the Effects of Silybin on Proliferation, Migration, and Immunotherapy of Papillary Thyroid Cancer.

The study aimed to use network pharmacology research and in vitro experiments to investigate the material basis and molecular mechanisms of silybin in the treatment of papillary thyroid carcinoma. Papillary thyroid cancer (PTC) has a decent prognosis; however, recurrence and metastasis are the leading causes of death in patients with PTC. A key research focus in thyroid cancer treatment is the inhibition of PTC proliferation, invasion, and migration. Silybin, the major active element in the traditional Chinese herb silymarin, has been used to treat a range of diseases, including cancer, but no study has been undertaken to determine whether it can help prevent PTC. In this study, we attempted to determine through network pharmacology and in vitro experiments if silybin inhibits the development of papillary thyroid cancer by inhibiting cell cycle and invasive migration. To predict the probable targets and underlying mechanisms of silybin against PTC, a network pharmacology research was performed. In vitro experiments were conducted to further evaluate silybin's anti-cancer properties and priority targets against PTC. The datasets revealed a total of 489 silybin targets acting on PTC, and functional enrichment analysis suggested that the target genes were enriched in functions and pathways related to PTC development, invasion, migration, and immunotherapy. By constructing these target PPI networks, the seven hub genes, fibronectin 1 (FN1), tissue inhibitor of metalloproteinases 1 (TIMP1), N-cadherin (CDH2), collagen type III alpha 1 chain (COL3A1), cyclin D1 (CCND1), AP-1 transcription factor subunit (JUN), and hepatocyte growth factor receptor (MET) were found. These hub genes were determined to be highly linked to a worse clinicopathological form, a higher risk of metastatic recurrence, and a worse prognosis of PTC. The common immunological checkpoint gene expression levels were positively correlated with the expression levels of the hub genes. Silybin decreased the proliferative and metastatic capacity of PTC cells, according to in vitro investigations. When PTC was treated with silybin, the FN1/AKT signaling pathway was blocked, CCND1 expression was reduced, and CDH2, Vimentin, Snail, Slug and PD-L1 expressions were dramatically reduced, while E-cadherin expression was significantly elevated. These findings provide preliminary evidence that silybin inhibits PTC cell proliferation, metastasis, and invasion by altering the FN1/AKT signaling pathway and inhibiting the EMT process. Silybin can reverse immunosuppression in papillary thyroid cancer by affecting immunological checkpoint gene expression levels. These studies provide a theoretical and experimental scientific basis for the potential anticancer effects of silybin on PTC.

IL1R2 is a Novel Prognostic Biomarker for Lung Adenocarcinoma.

The aim of this study is to figure out the role of IL1R2 in LUAD (lung adenocarcinoma). IL1R2, a special member of IL-1 receptor family, binds to IL-1 and plays an important role in inhibiting IL-1 pathway, which seems to be involved in tumorigenesis. Emerging studies demonstrated higher IL1R2 expression levels in several malignancies. In the present study, we assessed the expression of IL1R2 in LUAD tissues with immunohistochemistry and explored various databases to determine whether it could be a potential prognostic biomarker and therapeutic target. The expression level of IL1R2 in lung adenocarcinoma was analyzed by Immunohistochemistry and UALCAN database. The correlation between IL1R2 expression and the patient prognosis was identified by Kaplan-Meier plotter. The correlation of IL1R2 expression with immune infiltrates was clarified by TIMER database. The protein-protein interaction network and gene functional enrichment analysis were constructed and performed by STRING and Metascape database. Immunohistochemistry showed that the expression of IL1R2 was higher in tumor tissues of LUAD patients and that patients with lower IL1R2 level have a better prognosis than their counterparts. We validated our findings in several online databases and found that IL1R2 gene was also positively correlated with B cells and neutrophils and biomarkers of CD8+T cells and exhausted T cells. PPI network and gene enrichment analyses showed that expression of IL1R2 was also associated with complex functionspecific networks involving IL-1 signal, NF-KappaB transcription factors. According to these findings, we demonstrated that IL1R2 was involved in the progression and prognosis of LUAD and the underlying mechanism needs further investigation.

Exploring the Impact of DotStore: A Case Study on E-Commerce Innovation

Abstract: This research paper investigates the transformative role of DotStore, an emerging e-commerce platform, in revolutionizing online retail. DotStore's innovative features, user-centric design, and customizable solutions have disrupted traditional e-commerce paradigms, offering businesses unprecedented opportunities for growth and success. Through an indepth analysis of DotStore's functionalities, case studies, and market trends, this paper elucidates the platform's impact on the digital marketplace, shedding light on its implications for future e-commerce development.

A Study of ZSM-5 Molecular Sieve Shaping for an Innovative Cyclohexene Hydration Process

The development of the zeolite molecular sieves (ZSM-5) molding technique is essential for the cyclohexene hydration reaction distillation process in both industrial and research settings. The reactive distillation process can solve many of the drawbacks associated with the existing technique of manufacturing cyclohexanol via cyclohexene hydration, such as high catalyst digestibility, low conversion rate, and operational challenges. This study developed a series of molded ZSM-5 catalysts with various binder types and contents were constructed. The suggested pseudo-boehmite and hydroxypropyl methylcellulose were chosen as binders for extrusion molding of ZSM-5. The effects of binders on the strength reliability were investigated by strength tests and statistical analysis of the Weibull function. The effects of binders on the physical structure, acidity, and catalytic performance of ZSM-5 were investigated by X-ray diffraction, scanning electron microscopy, physical adsorption of N2, and desorption of NH3. The findings demonstrate that the addition of binder has no effect on ZSM-5's crystal structure. The experiment's results showed that the molded catalyst could be used for the hydration process with over 95% selectivity and a yield of 10.45% cyclohexanol. Copyright © 2024 by Authors, Published by BCREC Publishing Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).

A cross-cultural study of differential item functioning analysis of beliefs about Language Learning Inventory (BALLI)

This research examines students' beliefs about language learning by evaluating the measurement equivalence of the beliefs about Language Learning Inventory (BALLI). The graded response model (GRM) was used to examine differential item functioning (DIF) in the BALLI across four different countries, namely: Iran, Malaysia, Indonesia, and Bangladesh. The sample was drawn from 1613, including 500 males and 1113 females who completed the online version of the BALLI, comprising five subscales of beliefs about foreign language aptitude, the difficulty of language learning, the nature of language learning, learning and communication strategies, and motivations and expectations. Most BALLI items showed non-uniform DIF. This finding implies that students in different countries had different perceptions of the BALLI items. Therefore, researchers should be very cautious about using the BALLI in different countries. This cross-cultural comparison may generate new insights into revising the BALLI items or developing another scale to compare students' beliefs about language learning in different countries.

English medium instruction learners’ self-efficacy, engagement, and satisfaction; developing a measurement instrument

ABSTRACT This paper describes the development of a survey instrument to measure learners’ self-efficacy, engagement, and satisfaction within the context of English Medium Instruction (EMI) classes, with reference to both language issues and the discipline being taught. The paper presents details of analysis of the instrument using the Rasch model. The survey was administered to 287 tertiary students enrolled in EMI classes in Japan. Results of a Rasch Principal Components Analysis of Residuals showed the three intended constructs to be largely unidimensional. Item-level analysis, as well as reliability and separation measures and an investigation of Wright maps, provided further evidence that the items are working adequately to measure each of the three constructs and to allow differentiation between levels of each construct among the respondents. In addition, the effectiveness of the 6-point Likert scale used was confirmed with an analysis of category structure functioning. Finally, a correlation analysis with a subset (n = 97) of the participants for which English proficiency test scores were available was conducted. Results showed a small, statistically significant and positive relationship between reading proficiency and each of the three constructs.

An In-Silico Approach to Identify Therapeutic Target and Markers Associated with Diabetic Nephropathy.

Renal disease in T2DM could arise independent of hyperglycemia, aka non diabetic kidney disease. Their prevalence ranges from 33%to72.5% among T2DM patients. Specific molecular signatures that distinguish Diabetic Nephropathy from NDKD (FSGS) in T2DM might provide new targets for CKD management. Five original GEO microarray DN and FSGS datasets were evaluated (GSE111154, GSE96804, GSE125779, GSE129973 and GSE121233). Each of the three groups (DN, FSGS, and Controls) had equal renal transcriptome data (n=32) included in the analysis to eliminate bias. The DEGs were identified using TAC4.0. Pathway analysis was performed on the discovered genes that aligned to official gene symbols using Reactome, followed by functional gene enrichment analysis using Funrich,Enrichr. STRING and Network analyst investigated PPI, followed by Webgestalt's pathway enrichment. Finally, using the Targetscan7.0 and DIANA tools, filtered differential microRNAs downregulated in DN were evaluated for target identification. Between the three groups, DN, FSGS, and Control, a total of 194 DEGs. with foldchange >2&<-2 and P-value0.01 were found in the renal transcriptome. In comparison to control, 45 genes were elevated particularly in DN, whereas 43 were upregulated specifically in FSGS. DN datasets were compared to FSGS in a separate analysis. FABP4, EBF1, ADIRF, and ART4 were shown to be among the substantially up-regulated genes unique to DN in both analyses. The transcriptional regulation of white adipocytes was discovered by a pathway analysis. The molecular markers revealed might be employed as specific targets in the aetiology of DN, as well as in T2DM patients' therapeutic care.

Predictive and Prognostic Biomarkers in Patients With Mycosis Fungoides and Sézary Syndrome (BIO-MUSE): Protocol for a Translational Study.

Cutaneous T-cell lymphoma (CTCL) is a rare group of lymphomas that primarily affects the skin. Mycosis fungoides (MF) is the most common form of CTCL and Sézary syndrome (SS) is more infrequent. Early stages (IA-IIA) have a favorable prognosis, while advanced stages (IIB-IVB) have a worse prognosis. Around 25% of patients with early stages of the disease will progress to advanced stages. Malignant skin-infiltrating T-cells in CTCL are accompanied by infiltrates of nonmalignant T-cells and other immune cells that produce cytokines that modulate the inflammation. Skin infection, often with Staphylococcus aureus, is frequent in advanced stages and can lead to sepsis and death. S. aureus has also been reported to contribute to the progression of the disease. Previous reports indicate a shift from Th1 to Th2 cytokine production and dysfunction of the skin barrier in CTCL. Treatment response is highly variable and often unpredictable, and there is a need for new predictive and prognostic biomarkers. This prospective translational study aims to identify prognostic biomarkers in the blood and skin of patients with MF and SS. The Predictive and Prognostic Biomarkers in Patients With MF and SS (BIO-MUSE) study aims to recruit 120 adult patients with MF or SS and a control group of 20 healthy volunteers. The treatments will be given according to clinical routine. The sampling of each patient will be performed every 3 months for 3 years. The blood samples will be analyzed for lactate dehydrogenase, immunoglobulin E, interleukins, thymus and activation-regulated chemokine, and lymphocyte subpopulations. The lymphoma microenvironment will be investigated through digital spatial profiling and single-cell RNA sequencing. Microbiological sampling and analysis of skin barrier function will be performed. The life quality parameters will be evaluated. The results will be evaluated by the stage of the disease. Patient inclusion started in 2021 and is still ongoing in 2023, with 18 patients and 20 healthy controls enrolled. The publication of selected translational findings before the publication of the main results of the trial is accepted. This study aims to investigate blood and skin with a focus on immune cells and the microbiological environment to identify potential new prognostic biomarkers in MF and SS. ClinicalTrials.gov NCT04904146; https://www.clinicaltrials.gov/study/NCT04904146. DERR1-10.2196/55723.

Complete sequence of carbapenem-resistant Ralstonia mannitolilytica clinical isolate co-producing novel class D β-lactamase OXA-1176 and OXA-1177 in Japan.

In 2020, the Ralstonia mannitolilytica strain JARB-RN-0044 was isolated from a midstream urine sample of an elderly hospitalized patient in Japan and was highly resistant to carbapenem (i.e., imipenem, meropenem, and doripenem). Whole-genome sequencing revealed that the complete genome consists of two replicons, a 3.5-Mb chromosome and a 1.5-Mb large non-chromosomal replicon which has not been reported in R. mannitolilytica, and referred to as the "megaplasmid" in this study based on Cluster of Orthologous Group of proteins functional analysis. The strain JARB-RN-0044 harbored two novel OXA-60 and OXA-22 family class D β-lactamase genes blaOXA-1176 and blaOXA-1177 on the megaplasmid. Cloning experiments indicated that Escherichia coli recombinant clone expressing blaOXA-1176 gene showed increased minimum inhibitory concentrations (MICs) of imipenem, meropenem, and doripenem, indicating that blaOXA-1176 gene encodes carbapenemase. In contrast, E. coli recombinant clone expressing blaOXA-1177 gene showed increased MICs of piperacillin and cefazolin, but not of carbapenem. Interestingly, the 44.6 kb putative prophage region containing genes encoding phage integrase, terminase, head and tail protein was identified in the downstream region of blaOXA-1176 gene, and comparative analysis with some previously reported R. mannitolilytica isolates revealed that the prophage region was unique to strain JARB-RN-0044. The existence of a highly carbapenem-resistant R. mannitolilytica isolate may raise human health concerns in Japan, where the population is rapidly aging.IMPORTANCERalstonia mannitolilytica is an aerobic non-fermenting Gram-negative rod commonly found in aquatic environments and soil. The bacteria can occasionally cause severe hospital-acquired bloodstream infections in immunocompromised patients and it has been recently recognized as an emerging opportunistic human pathogen. Furthermore, some R. mannitolilytica isolates are resistant to various antimicrobial agents, including β-lactams and aminoglycosides, making antimicrobial therapy challenging and clinically problematic. However, clinical awareness of this pathogen is limited. To our knowledge, in Japan, there has been only one report of a carbapenem-resistant R. mannitolilytica clinical isolate from urine by Suzuki et al. in 2015. In this study, whole-genome sequencing analysis revealed the presence and genetic context of novel blaOXA-1176 and blaOXA-1177 genes on the 1.5 Mb megaplasmid from highly carbapenem-resistant R. mannitolilytica isolate and characterized the overall distribution of functional genes in the chromosome and megaplasmid. Our findings highlight the importance of further attention to R. mannitolilytica isolate in clinical settings.

Terpenoids and Triterpenoid Saponins: Future Treatment for Depression

Background: Depression is a crippling mental disorder with high prevalence around the world. The available clinical antidepressants have been effective to a certain degree, and different side effects have limited their application. This leads to the necessity of finding new treatments. Herbal plants are a substantial source of new drug leads. Terpenoid compounds are secondary metabolites representing an enormous category of structures found commonly in plants either as aglycones or attached to sugar moieties. These phytochemicals have been extensively studied for their various biological effects, and several have been investigated for potential therapeutic effects in the treatment of depression. Aim: This review aims to highlight the current knowledge on some terpenoids and triterpenoid saponins as potential antidepressant agents and their mechanisms of action, which may provide a better understanding of the potential antidepressant-like effects of these compounds and lead to the development of auspicious molecules with high efficiency and low side effects for depressive disorders treatment. Methods: A total of 16 plants containing antidepressant agents are reviewed in this article. 9 terpenoids and 23 triterpenoid saponins compounds have been reported to becommonly found in plant extracts, indicating potential use for depression. To enhance the datum of this review, the mechanism of action for the candidate compounds has been predicted via functional enrichment analysis. Results: The behavioural and neurochemical effects, as well as the possible mechanisms of action, have been evaluated in rodents by different predictive models of depression, mainly the acute stress models of the forced swimming test (FST) and tail suspension test (TST). The involved mechanisms include enhancing monoamine neurotransmitters, ameliorating brain-derived neurotrophic factor (BDNF), and normalizing the hypothalamus-pituitary-adrenal (HPA) axis. Preclinical studies support the potential antidepressant activities of some terpenoid compounds. Furthermore, the functional enrichment analysis has confirmed the previous pre-clinical findings and predicted further mechanisms of action, including cellular calcium ion homeostasis, cellular response to dopamine, endocrine resistance, and regulating GABAergic, serotonergic, glutamatergic, and dopaminergic synapse, bedsides neurotransmitter reuptake. Conclusion: Terpenoids and triterpenoid saponins provide a large number of natural compounds. This review sheds light on terpenoids and triterpenoid saponins compounds with antidepressantlike activity and their potential mechanisms of action. However, more evaluations are required to confirm that these compounds are promising for discovering antidepressant drugs.

Activities of daily living with grasp types and force measurements during object manipulation

Background: Limited scientific evidence guides hand rehabilitation towards improved hand function, and safe early return to work. Grasp types, the subunits of object manipulation and the forces which may improve functional outcomes, have been identified as missing links that may inform rehabilitation after second to fifth metacarpal fractures, through progression of basic and instrumental activities of daily living (ADL). The aim of the study was to collect ADL forces through grasp types to inform hand rehabilitation for second to fifth metacarpal fractures. Methods: This cross-sectional, quantitative study included 32 conveniently sampled healthy adults aged 20 and 59 years. Thirty-one (31) ADLs, both basic and instrumental, each associated with a predominant grasp type, were tested. The participants donned two testing gloves, with force sensing resistors (FSRs) glued to the fingertips, the ADLs were performed, and forces measured. The researcher imported the force data into an Excel spreadsheet for both descriptive and inferential analyses with STATA. Results: Fourteen males and 18 females, with a mean age of 37 years, participated. Statistically significant differences between genders were found for seven grasp types. Three thumb-adducted power palm grasps, three thumb-abduction precision pad grasps, and one thumb-abduction power palm grasp constituted the testing. Light and heavy ADLs and their associated grasp types were identified. Conclusion: To ensure optimal hand function, early safe return to ADLs should be the goal of second to fifth metacarpal fracture rehabilitation and may be achieved by incorporating active grasp types as exercises with graded resisted grasp types and ADLs. Implications for practice • Occupational therapists can incorporate grasp types in their observation during assessments of individuals who sustained second to fifth metacarpal fractures to determine the subcomponents of functional deficits. • Hand rehabilitation may be augmented by incorporating grasp types in isolation during unresisted active joint range of motion. • Occupational therapists, guided by the analysis of hand functioning, can incorporate ADLs with the predominant grasp types which may improve hand function. • Grasp force data may guide safe and early return to function.

Exploring the ferroptosis-related gene lipocalin 2 as a potential biomarker for sepsis-induced acute respiratory distress syndrome based on machine learning

BackgroundSepsis is a major cause of mortality in patients, and ARDS is one of the most common outcomes. The pathophysiology of acute respiratory distress syndrome (ARDS) caused by sepsis is significantly impacted by genes related to ferroptosis. MethodsIn this study, Weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) networks, functional enrichment analysis, and machine learning were employed to identify characterized genes and to construct receiver operating characteristic (ROC) curves. Additionally, DNA methylation levels were quantified and single-cell analysis was conducted. To validate the alterations in the expression of Lipocalin-2 (LCN2) and ferroptosis-related proteins in the in vitro model, Western blotting was carried out, and the changes in intracellular ROS and Fe2+ levels were detected. ResultsA combination of eight machine learning algorithms, including RFE, LASSO, RandomForest, SVM-RFE, GBDT, Bagging, XGBoost, and Boruta, were used with a machine learning model to highlight the significance of LCN2 as a key gene in sepsis-induced ARDS. Analysis of immune cell infiltration showed a positive correlation between neutrophils and LCN2. In a cell model induced by LPS, it was found that Fer-1, a ferroptosis inhibitor, was able to reverse the expression of LCN2. Knocking down LCN2 in BEAS-2B cells reversed the LPS-induced lipid peroxidation, Fe2+ levels, ACSL4, and GPX4 levels, indicating that LCN2, a FRG, plays a crucial role in mediating ferroptosis. ConclusionUpon establishing an FRG model for individuals with sepsis-induced ARDS, we determined that LCN2 could be a dependable marker for predicting survival in these patients. This finding provides a basis for more accurate ARDS diagnosis and the exploration of innovative treatment options.

Relationship between the Uncertainty of Empirical Orthogonal Function (EOF) Modes and Sampling Sizes in Climate Models

Abstract This study investigates the relationship between the uncertainty of empirical orthogonal function (EOF) modes and sampling size in climate models, using simulated results of preindustrial control (piControl) experiments in phase 6 of the Coupled Model Intercomparison Project (CMIP6), and taking the North Atlantic Oscillation (NAO) and El Niño–Southern Oscillation (ENSO) as examples. The results indicate that this relationship can be quantified by a concise fitting function [i.e., y = a/(x − b)]. Here, y is the 5%–95% confidence interval of congruence coefficient, x is the sampling size, and a and b are two parameters depending on models or observations. As compared with b, which modulates the sampling size in the fitting function, the parameter a scales the sampling size and thus plays a much more important role. Further analysis indicates that the parameter a, or the uncertainty of EOF1 mode, decreases dramatically with the increase of the difference between variance fractions of EOF1 and EOF2 modes, approximately in the form of a power function. The minimum sampling size to ensure a reliable EOF mode can also be estimated by the fitting function and shows a great diversity among models both for the NAO and ENSO. The diversity suggests the importance of estimating the minimum sampling size before model evaluations on climate variability modes and projections on the future change in modes, particularly when the EOF2 mode explains the variance close to EOF1 mode. Significance Statement Empirical orthogonal function (EOF) analysis, principal component analysis, or eigenvector analysis has been widely used in various research fields. However, it remains as an open question as to how large the sampling size is required to be to obtain reliable modes through the EOF method. In this study, we investigate the relationship between the uncertainty of EOF results and sampling size in current climate models, using adequately long simulated data, and we find that this relationship can be depicted by the fitting function y = a/(x − b). Here, y represents the uncertainty, x is the sampling size, and a and b are parameters. The parameter a is closely related to the difference between variance fractions of first and second EOF modes and plays a more important role in the fitting function. The minimum sampling sizes that are required to obtain reliable EOF modes can also be estimated by the fitting function and vary greatly from model to model. The results provide a basis for judging the reliability of EOF modes, particularly when the first and second EOF modes explain similar variance fractions.