Biclustering analysis on tree-shaped time-series single cell gene expression data of Caenorhabditis elegans.

BACKGROUND: In recent years, gene clustering analysis has become a widely used tool for studying gene functions, efficiently categorizing genes with similar expression patterns to aid in identifying gene functions. Caenorhabditis elegans is commonly used in embryonic research due to its consistent cell lineage from fertilized egg to adulthood. Biologists use 4D confocal imaging to observe gene expression dynamics at the single-cell level. However, on one hand, the observed tree-shaped time-series datasets have characteristics such as non-pairwise data points between different individuals. On the other hand, the influence of cell type heterogeneity should also be considered during clustering, aiming to obtain more biologically significant clustering results. RESULTS: A biclustering model is proposed for tree-shaped single-cell gene expression data of Caenorhabditis elegans. Detailedly, a tree-shaped piecewise polynomial function is first employed to fit non-pairwise gene expression time series data. Then, four factors are considered in the objective function, including Pearson correlation coefficients capturing gene correlations, p-values from the Kolmogorov-Smirnov test measuring the similarity between cells, as well as gene expression size and bicluster overlapping size. After that, Genetic Algorithm is utilized to optimize the function. CONCLUSION: The results on the small-scale dataset analysis validate the feasibility and effectiveness of our model and are superior to existing classical biclustering models. Besides, gene enrichment analysis is employed to assess the results on the complete real dataset analysis, confirming that the discovered biclustering results hold significant biological relevance.

Multichannel Nanogenerator-Driven Collaborative Metabolic Fingerprint Diagnostic Strategy for Early Screening and Risk Evaluation of Nonalcoholic Fatty Liver Disease.

Nonalcoholic fatty liver disease (NAFLD), along with its progressive forms nonalcoholic steatohepatitis (NASH) and NASH fibrosis, has emerged as a global health crisis. However, the absence of robust screening and risk evaluation tools contributes to the underdiagnosis of NAFLD. Herein, we reported a multichannel nanogenerator-assisted laser desorption/ionization mass spectrometry (LDI-MS) platform for early screening and risk evaluation of NAFLD. Specifically, titanium oxide nanosheets (TiNS) and covalent-organic framework nanosheets (COFNS) were employed as nanogenerators with excellent optical properties and exhibited efficient desorption/ionization during the LDI-MS process. Only ∼0.025 µL of serum without pretreatments and separation, serum metabolic fingerprints (SMFs) can be extracted within seconds. Notably, integrated SMFs from TiNS and COFNS significantly improved diagnostic performance and achieved the area under the curve (AUC) values of 1.000 with 100% sensitivity and 100% specificity for the validation sets of global diagnosis, early diagnosis, high-risk NASH, and NASH fibrosis evaluation. Additionally, four biomarker panels were identified, and their diagnostic AUC values were more than 0.944. Ultimately, key metabolic pathways indicating the change from simple NAFLD to high-risk NASH and NASH fibrosis were uncovered. This work provided a noninvasive and high-throughput screening and risk evaluation strategy for NAFLD healthcare management, thus contributing to the precise treatment of the NALFD.

Clinical and Economic Insights into Parkinson's Disease Hospitalization: A Comprehensive Study of 19719 Inpatient Cases in Hubei Province, China.

OBJECTIVE: Parkinson's Disease (PD) is a profoundly incapacitating neurodegenerative disorder, which presents a substantial challenge to the economic sustainability of the global healthcare system. The present study seeks to clarify the factors that contribute to the costs associated with PD hospitalization and analyze the economic burden it imposes. METHODS: We examined data of 19,719 patients with a primary diagnosis of PD who were admitted to hospitals in Hubei Province, China, during the study period. Healthcare data were obtained from the database of electronic medical records. The study presents a comprehensive analysis of the demographic characteristics and investigates the factors that affect their healthcare expenditure. RESULTS: The cohort consisted of 10,442 (53.0%) males and 9,277 (47.0%) females. The age group of 66-70 years experienced the highest incidence of hospitalization among PD patients, with a mortality rate of 0.76‰. The average length of stay for patients was 9.9 ± 8.6 days and the average cost per patient was $1759.9 ± 4787.7. Surgical interventions were conducted on a mere 2.0% of the total inpatient population. The primary cost component for these interventions was material expenses, accounting for 70.1% of the total. Non-surgical patients primarily incurred expenses related to diagnosis and medication. Notably, surgical patients faced a substantial out-of-pocket rate, reaching up to 90.6%. Surgery was identified as the most influential factor that negatively affected both length of stay and hospitalization costs. Inpatients exhibited significant associations with prolonged length of stay and increased medical expenditure as age increased. Male patients had significantly longer hospital stays and higher medical costs than did females. Additionally, patient's occupation and type of medical insurance exerted significant effects on both length of stay and medical expense. CONCLUSION: Age significantly affects PD hospitalization costs. Given the prevailing demographic shift towards an aging population, the government's medical insurance burden related to PD will continue to escalate. Meanwhile, high treatment expenses and out-of-pocket rates impose substantial financial burdens on patients, limiting surgical intervention access to a small fraction of patients. Addressing these issues is of utmost importance in order to ensure comprehensive disease management for the majority of individuals affected by PD.

Advancing stroke therapy: innovative approaches with stem cell-derived extracellular vesicles.

Stroke is a leading cause of mortality and long-term disability globally, with acute ischemic stroke (AIS) being the most common subtype. Despite significant advances in reperfusion therapies, their limited time window and associated risks underscore the necessity for novel treatment strategies. Stem cell-derived extracellular vesicles (EVs) have emerged as a promising therapeutic approach due to their ability to modulate the post-stroke microenvironment and facilitate neuroprotection and neurorestoration. This review synthesizes current research on the therapeutic potential of stem cell-derived EVs in AIS, focusing on their origin, biogenesis, mechanisms of action, and strategies for enhancing their targeting capacity and therapeutic efficacy. Additionally, we explore innovative combination therapies and discuss both the challenges and prospects of EV-based treatments. Our findings reveal that stem cell-derived EVs exhibit diverse therapeutic effects in AIS, such as promoting neuronal survival, diminishing neuroinflammation, protecting the blood-brain barrier, and enhancing angiogenesis and neurogenesis. Various strategies, including targeting modifications and cargo modifications, have been developed to improve the efficacy of EVs. Combining EVs with other treatments, such as reperfusion therapy, stem cell transplantation, nanomedicine, and gut microbiome modulation, holds great promise for improving stroke outcomes. However, challenges such as the heterogeneity of EVs and the need for standardized protocols for EV production and quality control remain to be addressed. Stem cell-derived EVs represent a novel therapeutic avenue for AIS, offering the potential to address the limitations of current treatments. Further research is needed to optimize EV-based therapies and translate their benefits to clinical practice, with an emphasis on ensuring safety, overcoming regulatory hurdles, and enhancing the specificity and efficacy of EV delivery to target tissues.

Prediction of mass spectrometry ionization efficiency based on COSMO-RS and machine learning algorithms.

Non-targeted analysis of high-resolution mass spectrometry (MS) can identify thousands of compounds, which also gives a huge challenge to their quantification. The aim of this study is to investigate the impact of mass spectrometry ionization efficiency on various compounds in food at different solvent ratios and to develop a predictive model for mass spectrometry ionization efficiency to enable non-targeted quantitative prediction of unknown compounds. This study covered 70 compounds in 14 different mobile phase ratio environments in positive ion mode to analyze the rules of the matrix effect. With the organic phase ratio from low to high, most compounds changed by 1.0 log units in log IE. The addition of formic acid enhanced the signal but also promoted the matrix effect, which often occurred in compounds with strong ionization capacity. It was speculated that the matrix effect was mainly in the form of competitive charge and charged droplet' gasification sites during MS detection. Subsequently, we present a log IE prediction method built using the COSMO-RS software and the artificial neural network (ANN) algorithm to address this difficulty and overcome the shortcomings of previous models, which always ignore the matrix effect. This model was developed following the principles of QSAR modeling recommended by the Organization for Economic Cooperation and Development (OECD). Furthermore, we validated this approach by predicting the log IE of 70 compounds, including those not involved in the log IE model development. The results presented demonstrate that the method we put forward has an excellent prediction accuracy for log IE (R2pred = 0.880), which means that it has the potential to predict the log IE of new compounds without authentic standards.

DFT investigation of the DDQ-catalytic mechanism for constructing C-O bonds.

In this study, we investigated the photo-catalytic mechanisms for the construction of C-O bonds from arenes (benzene, 2',6'-dimethyl-[1,1'-biphenyl]-2-carboxylic acid, or 2,4-dichloro-1-fluorobenzene), catalyzed by 2,3-dichloro-5,6-dicyano-p-benzoquinone (DDQ). All the structures for the Gibbs free surfaces were calculated at the M06-2X-D3/ma-def2-SVP level in the SMD solvent model. Also, TDDFT calculations of DDQ were performed at the PBE1PBE-D3/ma-def2-SVP level in the SMD solvent model. The computational results indicated that DDQ, serving as a photo-catalyst, would be excited under visible light of 450 nm, aligning well with experimental observations as reflected in the UV-vis spectrum. Gibbs free energy surface analyses of the three reactions suggested that the path involving 3DDQ* activating the reactant (-COOH, H2O, or CH3OH) is favorable. Additionally, the role of O2 was investigated, revealing that it could facilitate the recycling of DDQ by lowering the energy barrier for the conversion of the DDQH˙ radical (not DDQH2) into DDQ. The use of ρhole and ρele can reveal the photo-catalytic reaction and charge transfer processes, while localized orbital locator isosurfaces and electron spin density isosurface graphs were employed to analyze structures and elucidate the single electron distribution. These computational results offer valuable insights into the studied interactions and related processes, shedding light on the mechanisms governing C-O bond formation from arenes catalyzed by DDQ.

Alkali metal hydroxide-catalyzed mechanisms of Csp-H silylation of alkynes: a DFT investigation.

Mechanisms for the Csp-H silylation between prop-2-yn-1-ylcyclohexane and triethylsilane, catalyzed by MOH/MH (M = Na or K), were investigated at the M06-L-D3/ma-def2-TZVP level. The SMD model was applied to simulate the solvent effect of 1,2-dimethoxyethane (DME). Computational results suggested that the Csp-H activation of prop-2-yn-1-ylcyclohexane could be achieved by MOH to generate R-CC-M compounds, which continued to react with triethylsilane to yield the final product: (3-cyclohexylprop-1-yn-1-yl) triethylsilane. Moreover, analysis of the Gibbs free energy surface of the three reactions suggested that a path with the participation of LiOH had the highest energy barrier, which was consistent with experimental results showing that only a small amount of product had been formed. The obtained KH could interact readily with the H2O molecule with a much lower energy barrier (0.6 kcal mol-1) than that using the path with prop-2-yn-1-ylcyclohexane. Furthermore, compared to MOH, MH could catalyze the reaction with lower energy barriers, and the reactions became exothermic, thereby benefiting the reaction. Finally, the mechanism for obtaining the byproduct (prop-1-yn-1-ylcyclohexane) was posited: it had a higher energy barrier than the path to yield the main product. Frontier orbital, noncovalent interactions (NCI), Fukui function and dual descriptor analyses could be used to analyze the structure and reveal the reaction substances.

Highly precise thickness measurement of multilayer films based on the cross-correlation algorithm using a widely tunable MG-Y laser.

Inspired by the demodulation algorithm of Fabry-Perot composite sensors in the field of fiber-optic sensing, this paper proposes a method based on a widely tunable modulated grating Y-branch (MG-Y) laser combined with the cross-correlation algorithm to achieve a highly precise measurement of the optical thickness of each layer of a multilayer optical sample. A sample consisting of a double glass stack was selected, and the interference spectrum of the stacked sample was acquired using a widely tunable MG-Y laser. A fast Fourier transform (FFT) algorithm combined with a finite impulse response (FIR) bandpass filter was utilized to separate the different frequency components of the multilayer optical sample. The normalized spectra of each layer were reconstructed using the Hilbert transform. Subsequently, a cross-correlation algorithm was employed to process the normalized spectrum and determine the optical thickness of each layer with high precision. The samples were measured at predetermined locations, with 150 consecutive measurements performed to assess the repetition of the thickness. The standard deviation of these measurements was found to be lower than 1.5 nm. The results show that the cross-correlation algorithm is advantageous in the optical thickness measurement of multilayer films.

Comparison of Locking Plate Alone and Locking Plate Combined with 3D Printed Polymethylmethacrylate Augmentation in Treating Proximal Humerus Fractures in the Elderly.

BACKGROUND: Locking plates are widely used in open reduction internal fixation (ORIF) for proximal humeral fracture (PHF). However, the optimal surgical treatment of unstable, displaced PHF in elderly patients remains controversial. This study aimed to compare the radiological and clinical outcomes of surgical treatment of PHF in the elderly with locking plate (LP) alone and locking plate combined with 3D printed polymethylmethacrylate (PMMA) prosthesis augmentation (LP-PA). METHODS: From May 2015 to April 2021, a total of 97 patients aged ≥ 60 years with acute unstable PHF who underwent osteosynthesis with either LP (46 patients) or LP-PA (51 patients) were retrospectively analyzed. For the LP-PA group, a customized proximal humeral prosthesis made of PMMA cement was intra-operatively fabricated by a three-dimensional (3D) printed prototype mold for the humeral medial support. Radiological outcomes were analyzed by measuring the value of neck-shaft angle (NSA) and humeral head height (HHH). The clinical outcomes were evaluated using Constant-Murley Score (CMS), Disabilities of the Arm Shoulder and Hand (DASH) score, American Shoulder and Elbow Surgeons (ASES) score, and the shoulder range of motion (ROM). Pain was measured using a visual analogue scale (VAS). RESULTS: At the one-year follow-up, all fractures healed radiologically and clinically. The mean changes of NSA and HHH over the follow-up period were markedly smaller in the LP-PA group (3.8 ± 0.9° and 1.7 ± 0.3 mm) than those in the LP group (9.7 ± 2.1° and 3.2 ± 0.6 mm, both P < 0.0001). The LP-PA group also presented lower DASH score (17.1 ± 3.6), higher ASES score (89.5 ± 11.2) and better ROM in forward elevation (142 ± 26°) and external rotation (59 ± 11°) compared to the LP group (28.9 ± 4.8 for DASH score, P < 0.0001; 82.3 ± 9.0 for ASES score, P < 0.001; 129 ± 21° for forward elevation, P = 0.008; and 52 ± 9° for external rotation, P = 0.001). There was no significant difference in overall complication rate between the two groups, although the complication rate of screw perforation was higher in the LP-PA group (P = 0.172). CONCLUSIONS: For PHF in elderly patients, the combination of LP fixation and PMMA prosthesis augmentation effectively improved humeral head support and reduction maintenance, providing satisfactory outcomes both radiologically and clinically. This technique also reduced the incidence of screw perforation associated with plate fixation alone, making it a reasonable option to ensure satisfactory clinical outcomes.

Microfluidized hemp protein isolate: an effective stabilizer for high-internal-phase emulsions with improved oxidative stability.

BACKGROUND: Hemp protein isolates (HPIs), which provide a well-balanced profile of essential amino acids comparable to other high-quality proteins, have recently garnered significant attention. However, the underutilized functional attributes of HPIs have constrained their potential commercial applications within the food and agriculture field. This study advocates the utilization of dynamic-high-pressure-microfluidization (DHPM) for the production of stable high-internal-phase emulsions (HIPEs), offering an efficient approach to fully exploit the potential of HPI resources. RESULTS: The findings underscore the effectiveness of DHPM in producing HPI as a stabilizing agent for HIPEs with augmented antioxidant activity. Microfluidized HPI exhibited consistent adsorption and anchoring at the oil-water interface, resulting in the formation of a dense and compact layer. Concurrently, the compression of droplets within HIPEs gave rise to a polyhedral framework, conferring viscoelastic properties and a quasi-solid behavior to the emulsion. Remarkably, HIPEs stabilized by microfluidized HPI demonstrated superior oxidative and storage stability, attributable to the establishment of an antioxidative barrier by microfluidized HPI particles. CONCLUSION: This study presents an appealing approach for transforming liquid oils into solid-like fats using HPI particles, all without the need for surfactants. HIPEs stabilized by microfluidized HPI particles hold promise as emerging food ingredients for the development of emulsion-based formulations with enhanced oxidative stability, thereby finding application in the food and agricultural industries. © 2023 Society of Chemical Industry.

Opening and Constructing Stable Lithium-ion Channels within Polymer Electrolytes.

Lithium-ion batteries play an integral role in various aspects of daily life, yet there is a pressing need to enhance their safety and cycling stability. In this study, we have successfully developed a highly secure and flexible solid-state polymer electrolyte (SPE) through the in situ polymerization of allyl acetoacetate (AAA) monomers. This SPE constructed an efficient Li+ transport channel inside and effectively improved the solid-solid interface contact of solid-state batteries to reduce interfacial impedance. Furthermore, it exhibited excellent thermal stability, an ionic conductivity of 3.82×10-4 S cm-1 at room temperature (RT), and a Li+ transport number (tLi+) of 0.66. The numerous oxygen vacancies on layered inorganic SiO2 created an excellent environment for TFSI- immobilization. Free Li+ migrated rapidly at the C=O equivalence site with the poly(allyl acetoacetate) (PAAA) matrix. Consequently, when cycled at 0.5C and RT, it displayed an initial discharge specific capacity of 140.6 mAh g-1 with a discharge specific capacity retention rate of 70 % even after 500 cycles. Similarly, when cycled at a higher rate of 5C, it demonstrated an initial discharge specific capacity of 132.3 mAh g-1 while maintaining excellent cycling stability.

A chromosome-level genome assembly of Hong Kong catfish (Clarias fuscus) uncovers a sex-determining region.

BACKGROUND: Hong Kong catfish (Clarias fuscus) is an ecologically and economically important species that is widely distributed in freshwater regions of southern China. Hong Kong catfish has significant sexual growth dimorphism. The genome assembly of the Hong Kong catfish would facilitate study of the sex determination and evolution mechanism of the species. RESULTS: The first high-quality chromosome-level genome of the Hong Kong catfish was constructed. The total genome was 933.4 Mb, with 416 contigs and a contig N50 length of 8.52 Mb. Using high-throughput chromosome conformation capture (Hi-C) data, the genome assembly was divided into 28 chromosomes with a scaffold N50 length of 36.68 Mb. A total of 23,345 protein-coding genes were predicted in the genome, and 94.28% of the genes were functionally annotated in public databases. Phylogenetic analysis indicated that C. fuscus and Clarias magur diverged approximately 63.7 million years ago. The comparative genome results showed that a total of 60 unique, 353 expanded and 851 contracted gene families were identified in Hong Kong catfish. A sex-linked quantitative trait locus identified in a previous study was located in a sex-determining region of 30.26 Mb (0.02 to 30.28 Mb) on chromosome 13 (Chr13), the predicted Y chromosome. This QTL region contained 785 genes, of which 18 were identified as sex-related genes. CONCLUSIONS: This study is the first to report the chromosome-level genome assembly of Hong Kong catfish. The study provides an excellent genetic resource that will facilitate future studies of sex determination mechanisms and evolution in fish.

In Situ Construction Channels of Lithium-Ion Fast Transport and Uniform Deposition to Ensure Safe High-Performance Solid Batteries.

Solid-state lithium-ion batteries (SLIBs) are the promising development direction for future power sources because of their high energy density and reliable safety. To optimize the ionic conductivity at room temperature (RT) and charge/discharge performance to obtain reusable polymer electrolytes (PEs), polyvinylidene fluoride (PVDF), and poly(vinylidene fluoride-hexafluoro propylene) (P(VDF-HFP)) copolymer combined with polymerized methyl methacrylate (MMA) monomers are used as substrates to prepare PE (LiTFSI/OMMT/PVDF/P(VDF-HFP)/PMMA [LOPPM]). LOPPM has interconnected lithium-ion 3D network channels. The organic-modified montmorillonite (OMMT) is rich in the Lewis acid centers, which promoted lithium salt dissociation. LOPPM PE possessed high ionic conductivity of 1.1 × 10-3 S cm-1 and a lithium-ion transference number of 0.54. The capacity retention of the battery remained 100% after 100 cycles at RT and 0.5 C. The initial capacity of one with the second-recycled LOPPM PE is 123.9 mAh g-1 . This work offered a feasible pathway for developing high-performance and reusable LIBs.

Charge Transfer Modulation in Vanadium-Doped WS2 /Bi2 O2 Se Heterostructures.

The field of photovoltaics is revolutionized in recent years by the development of two-dimensional (2D) type-II heterostructures. These heterostructures are made up of two different materials with different electronic properties, which allows for the capture of a broader spectrum of solar energy than traditional photovoltaic devices. In this study, the potential of vanadium (V)-doped WS2 is investigated, hereafter labeled V-WS2 , in combination with air-stable Bi2 O2 Se for use in high-performance photovoltaic devices. Various techniques are used to confirm the charge transfer of these heterostructures, including photoluminescence (PL) and Raman spectroscopy, along with Kelvin probe force microscopy (KPFM). The results show that the PL is quenched by 40%, 95%, and 97% for WS2 /Bi2 O2 Se, 0.4 at.% V-WS2 /Bi2 O2 Se, and 2 at.% V-WS2 /Bi2 O2 Se, respectively, indicating a superior charge transfer in V-WS2 /Bi2 O2 Se compared to pristine WS2 /Bi2 O2 Se. The exciton binding energies for WS2 /Bi2 O2 Se, 0.4 at.% V-WS2 /Bi2 O2 Se and 2 at.% V-WS2 /Bi2 O2 Se heterostructures are estimated to be ≈130, 100, and 80 meV, respectively, which is much lower than that for monolayer WS2 . These findings confirm that by incorporating V-doped WS2 , charge transfer in WS2 /Bi2 O2 Se heterostructures can be tuned, providing a novel light-harvesting technique for the development of the next generation of photovoltaic devices based on V-doped transition metal dichalcogenides (TMDCs)/Bi2 O2 Se.

Beneficial Effects of Angiotensin II Receptor Blockers on Mortality in Patients with COVID-19: A Retrospective Study from 2019 to 2020 in China.

BACKGROUND: The COVID-19 pandemic has become a serious global public health problem. Although the use of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor type 1 blockers (ARBs) has been recommended in patients with COVID-19 and cardiovascular diseases (CVDs), according to the results of some small-sample retrospective analyses, there remains a lack of sufficient evidence to validate their efficacy. This multicenter retrospective study investigated whether ACEI/ARB administration was beneficial in patients with COVID-19 and CVDs. METHODS: A total of 11,231 patients with confirmed COVID-19 and CVDs, from 138 hospitals in Hubei Province, were included in this multicenter retrospective study. We compared the clinical characteristics and outcomes between the ARB and non-ARB groups and analyzed the risk factors for in-hospital death using univariate and multivariate Cox regression analyses and Kaplan-Meier curves. RESULTS: In the multivariate Cox regression model, after adjusting for age, gender, comorbidities, and in-hospital medications, ARB use was associated with lower all-cause mortality (adjusted HR, 0.53; 95% CI, 0.38-0.73; P < 0.001). After propensity score-matched analysis, the adjusted HR for the use of ARB associated with all-cause mortality was 0.62 (95% CI, 0.40-0.88; P = 0.02). Further subgroup analyses found that the adjusted HRs for the use of ARB associated with all-cause mortality were 0.52 (95% CI, 0.30-0.89; P = 0.016), 0.37 (95% CI, 0.21-0.64; P < 0.001), 0.42 (95% CI, 0.28-0.64; P < 0.001), and 0.55 (95% CI, 0.37-0.84; P = 0.005) in patients with heart failure, diabetes, and hypercholesterolemia, and severe COVID-19, respectively. CONCLUSIONS: ARB administration was significantly associated with a lower risk of all-cause mortality in patients with COVID-19 and CVDs. TRIAL REGISTRATION: ClinicalTrials.gov NCT05615792. https://www. CLINICALTRIALS: gov/ct2/show/NCT05615792.

Liver X receptor agonists exert antitumor effects against hepatocellular carcinoma via inducing REPS2 expression.

Recent studies show that liver X receptor (LXR) agonists exert significant antitumor effects in a variety of tumor cell lines including hepatocellular carcinoma (HCC). But the molecular mechanisms underlying LXR antitumor activity are not fully understood. In this study we investigated the effect of LXR agonist T0901317 (T317) on HCC development and its relationship with RalA binding protein 1 (RALBP1)-associated EPS domain containing 2 (REPS2)/epidermal growth factor receptor (EGFR) signaling axis. We showed that T317 (0.1-0.5 µM) dose-dependently increased REPS2 expression in normal hepatocytes (BNLCL.2 and LO2) and HCC cells (HepG2 and Huh-7). Using promoter activity assay and chromatin immunoprecipitation (CHIP) assay we demonstrated that T317 enhanced REPS2 expression at the transcriptional level via promoting the binding of LXR protein to the LXR-response element (LXRE) in the REPS2 promoter region. We showed that the inhibitory effect of T317 on the proliferation and migration of HCC cells was closely related to REPS2. Moreover, we revealed that T317 (400 nM) increased expression of REPS2 in HepG2 cells, thus inhibiting epidermal growth factor (EGF)-mediated endocytosis of EGFR as well as the downstream activation of AKT/NF-κB, p38MAPK, and ERK1/2 signaling pathways. Clinical data analysis revealed that REPS2 expression levels were inversely correlated with the development of HCC and reduced REPS2 expression associated with poor prognosis, suggesting that REPS2 might be involved in the development of HCC. In conclusion, this study provides new insights into the potential mechanisms of LXR agonist-inhibited HCC.

Integrated Network Analysis to Determine CNN1, MYL9, TAGLN, and SORBS1 as Potential Key Genes Associated with Prostate Cancer.

BACKGROUND: Prostate cancer (PCa) is challenging to treat. It is necessary to screen for related biological markers to accurately predict the prognosis and recurrence of prostate cancer. METHODS: Three data sets, GSE28204, GSE30521, and GSE69223, from the Gene Expression Omnibus (GEO) database were integrated into this study. After the identification of differentially expressed genes (DEGs) between PCa and normal prostate tissues, network analyses including protein-protein interaction (PPI) network, and weighted gene co-expression network analysis (WGCNA) were used to select hub genes. Gene Ontology (GO) term analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to annotate the functions of DEGs and hub modules of the networks. Survival analysis was performed to validate the correlation between the key genes and PCa relapse. RESULTS: In total, 867 DEGs were identified, including 201 upregulated and 666 downregulated genes. Three hub modules of the PPI network and one hub module of the weighted gene co-expression network were determined. Moreover, four key genes (CNN1, MYL9, TAGLN, and SORBS1) were significantly associated with PCa relapse (p < 0.05). CONCLUSIONS: CNN1, MYL9, TAGLN, and SORBS1 may be potential biomarkers for PCa development.

Accumulation of squalene in filamentous fungi Trichoderma virens PS1-7 in the presence of butenafine hydrochloride, squalene epoxidase inhibitor: biosynthesis of 13C-enriched squalene.

Squalene is a triterpenoid compound and widely used in various industries such as medicine and cosmetics due to its strong antioxidant and anticancer properties. The purpose of this study is to increase the accumulation of squalene in filamentous fungi using exogeneous butenafine hydrochloride, which is an inhibitor for squalene epoxidase. The detailed settings achieved that the filamentous fungi, Trichoderma virens PS1-7, produced squalene up to 429.93 ± 51.60 mg/L after culturing for 7 days in the medium consisting of potato infusion with glucose at pH 4.0, in the presence of 200 µm butenafine. On the other hand, no squalene accumulation was observed without butenafine. This result indicated that squalene was biosynthesized in the filamentous fungi PS1-7, which can be used as a novel source of squalene. In addition, we successfully obtained highly 13C-enriched squalene by using [U-13C6]-glucose as a carbon source replacing normal glucose.

A novel score to estimate thrombus burden and predict intracranial hypertension in cerebral venous sinus thrombosis.

BACKGROUND: Current methods to evaluate the severity of cerebral venous sinus thrombosis (CVST) lack patient-specific indexes. Herein, a novel scoring method was investigated to estimate the thrombus burden and the intracranial pressure (ICP) of CVST. METHODS: In this retrospective study from January 2019 through December 2021, we consecutively enrolled patients with a first-time confirmed diagnosis of CVST by contrast-enhanced magnetic resonance venography (CE-MRV) or computed tomography venography (CTV). In these patients, a comprehensive CVST-Score was established using magnetic resonance black-blood thrombus imaging (MRBTI) to estimate the thrombus burden semi-quantitatively. The relationship between CVST-Score and ICP was explored to assess the potential of using the CVST-score to evaluate ICP noninvasively and dynamically. RESULTS: A total of 87 patients were included in the final analysis. The CVST-Scores in different ICP subgroups were as follows: 4.29±2.87 in ICP<250mmH2O subgroup, 11.36±3.86 in ICP =250-330mmH2O subgroup and 14.99±3.15 in ICP>330mmH2O subgroup, respectively (p<0.001). For patients with ICP ≤330mmH2O, the CVST-Score was linearly and positively correlated with ICP (R2=0.53). The receiver operating characteristic (ROC) curves showed the optimal CVST-Score cut-off values to predict ICP ≥250mmH2O and >330mmH2O were 7.15 and 11.62, respectively (P<0.001). Multivariate analysis indicated CVST-Score as an independent predictor of ICP ≥250mmH2O (odds ratio, 2.15; 95% confidence interval, 1.49-3.10; p<0.001). CONCLUSIONS: A simple and noninvasive CVST-Score can rapidly estimate the thrombus burden and predict the severity of intracranial hypertension in patients with CVST. The CVST-Score can aid in evaluating therapeutic responses and avoiding unnecessary invasive procedures at long-term follow-up.

Identification of a glioma functional network from gene fitness data using machine learning.

Glioblastoma multiforme (GBM) is an aggressive form of brain tumours that remains incurable despite recent advances in clinical treatments. Previous studies have focused on sub-categorizing patient samples based on clustering various transcriptomic data. While functional genomics data are rapidly accumulating, there exist opportunities to leverage these data to decipher glioma-associated biomarkers. We sought to implement a systematic approach to integrating data from high throughput CRISPR-Cas9 screening studies with machine learning algorithms to infer a glioma functional network. We demonstrated the network significantly enriched various biological pathways and may play roles in glioma tumorigenesis. From densely connected glioma functional modules, we further predicted 12 potential Wnt/ß-catenin signalling pathway targeted genes, including AARSD1, HOXB5, ITGA6, LRRC71, MED19, MED24, METTL11B, SMARCB1, SMARCE1, TAF6L, TENT5A and ZNF281. Cox regression modelling with these targets was significantly associated with glioma overall survival prognosis. Additionally, TRIB2 was identified as a glioma neoplastic cell marker in single-cell RNA-seq of GBM samples. This work establishes novel strategies for constructing functional networks to identify glioma biomarkers for the development of diagnosis and treatment in clinical practice.