Synthesis and characterization of Craig-type antiaromatic species with [4n + 2] π electrons.

Antiaromaticity is extended from aromaticity as a complement to describe the unsaturated cyclic molecules with antiaromatic destabilization. To prepare antiaromatic species is a particularly challenging goal in synthetic chemistry because of the thermodynamic instability of such molecules. Among that, both Hückel and Möbius antiaromatic species have been reported, whereas the Craig one has not been realized to date. Here, we report the first example of planar Craig antiaromatic species. Eight Craig antiaromatic compounds were synthesized by deprotonation-induced reduction process and were fully characterized as follows. Single-crystal X-ray crystallography showed that these complexes have planar structures composed of fused five-membered rings with clearly alternating carbon-carbon bond lengths. In addition, proton NMR (1H NMR) spectroscopy in these structures showed distinctive upfield shifts of the proton peaks to the range of antiaromatic peripheral hydrogens. Experimental spectroscopy observations, along with density-functional theory (DFT) calculations, provided evidence for the Craig antiaromaticity of these complexes. Further study experimentally and theoretically revealed that the strong exothermicity of the acid-base neutralization process was the driving force for this challenging transformation forming Craig antiaromatic species. Our findings complete a full cycle of aromatic chemistry, opening an avenue for the development of new class of antiaromatic systems.

scAnno: a deconvolution strategy-based automatic cell type annotation tool for single-cell RNA-sequencing data sets.

Undoubtedly, single-cell RNA sequencing (scRNA-seq) has changed the research landscape by providing insights into heterogeneous, complex and rare cell populations. Given that more such data sets will become available in the near future, their accurate assessment with compatible and robust models for cell type annotation is a prerequisite. Considering this, herein, we developed scAnno (scRNA-seq data annotation), an automated annotation tool for scRNA-seq data sets primarily based on the single-cell cluster levels, using a joint deconvolution strategy and logistic regression. We explicitly constructed a reference profile for human (30 cell types and 50 human tissues) and a reference profile for mouse (26 cell types and 50 mouse tissues) to support this novel methodology (scAnno). scAnno offers a possibility to obtain genes with high expression and specificity in a given cell type as cell type-specific genes (marker genes) by combining co-expression genes with seed genes as a core. Of importance, scAnno can accurately identify cell type-specific genes based on cell type reference expression profiles without any prior information. Particularly, in the peripheral blood mononuclear cell data set, the marker genes identified by scAnno showed cell type-specific expression, and the majority of marker genes matched exactly with those included in the CellMarker database. Besides validating the flexibility and interpretability of scAnno in identifying marker genes, we also proved its superiority in cell type annotation over other cell type annotation tools (SingleR, scPred, CHETAH and scmap-cluster) through internal validation of data sets (average annotation accuracy: 99.05%) and cross-platform data sets (average annotation accuracy: 95.56%). Taken together, we established the first novel methodology that utilizes a deconvolution strategy for automated cell typing and is capable of being a significant application in broader scRNA-seq analysis. scAnno is available at https://github.com/liuhong-jia/scAnno.

The NF-κB/Relish Activates miR-308 to Negatively Regulate Imd Pathway Immune Signaling in Drosophila.

The strength and duration of the NF-κB signaling response must be tightly modulated to avoid an inadequate or excessive immune response. Relish, a core NF-κB transcription factor of the Drosophila Imd pathway, can control the expression of antimicrobial peptides, including Dpt and AttA, to defend against Gram-negative bacterial infections, but whether Relish may regulate miRNA expression to participate in the immune response remains unclear. In this study, taking advantage of Drosophila S2 cells and different overexpression/knockout/knockdown flies, we first found that Relish could directly activate the expression of miR-308 to negatively regulate the immune response and promote the survival of Drosophila during Enterobacter cloacae infection. Second, our results demonstrated that Relish-mediated expression of miR-308 could suppress target gene Tab2 to attenuate the Drosophila Imd pathway signal during the middle and late stages of the immune response. Third, we detected the dynamic expression patterns of Dpt, AttA, Relish, miR-308, and Tab2 in wild-type flies after E. coli infection, which further revealed that the feedback regulatory loop of Relish-miR-308-Tab2 plays a crucial role in the immune response and homeostasis maintenance of the Drosophila Imd pathway. Overall, our present study not only illustrates an important mechanism by which this Relish-miR-308-Tab2 regulatory axis can negatively control the Drosophila immune response and participate in homeostasis maintenance but also provides new insights into the dynamic regulation of the NF-κB/miRNA expression network of animal innate immunity.

pH-Responsive Amphiphilic Triblock Fluoropolymers as Assemble Oxygen Nanoshuttles for Enhancing PDT against Hypoxic Tumor.

Photodynamic therapy (PDT) is a cancer treatment strategy that utilizes photosensitizers to convert oxygen within tumors into reactive singlet oxygen (1O2) to lyse tumor cells. Nevertheless, pre-existing tumor hypoxia and oxygen consumption during PDT can lead to an insufficient oxygen supply, potentially reducing the photodynamic efficacy. In response to this issue, we have devised a pH-responsive amphiphilic triblock fluorinated polymer (PDP) using copper-mediated RDRP. This polymer, composed of poly(ethylene glycol) methyl ether acrylate, 2-(diethylamino)ethyl methacrylate, and (perfluorooctyl)ethyl acrylate, self-assembles in an aqueous environment. Oxygen, chlorine e6 (Ce6), and doxorubicin (DOX) can be codelivered efficiently by PDP. The incorporation of perfluorocarbon into the formulation enhances the oxygen-carrying capacity of PDP, consequently extending the lifetime of 1O2. This increased lifetime, in turn, amplifies the PDT effect and escalates the cellular cytotoxicity. Compared with PDT alone, PDP@Ce6-DOX-O2 NPs demonstrated significant inhibition of tumor growth. This study proposes a novel strategy for enhancing the efficacy of PDT.

Prognostic Utility of Left Atrial Strain From MRI Feature Tracking in Ischemic and Nonischemic Dilated Cardiomyopathy: A Multicenter Study.

BACKGROUND. MRI-based prognostic evaluation in patients with dilated cardiomyopathy (DCM) has historically used markers of late gadolinium enhancement (LGE) and feature tracking (FT)-derived left ventricular global longitudinal strain (LVGLS). Early data indicate that FT-derived left atrial strain (LAS) parameters, including reservoir, conduit, and booster, may also have prognostic roles in such patients. OBJECTIVE. The purpose of our study was to evaluate the prognostic utility of LAS parameters, derived from MRI FT, in patients with ischemic or nonischemic DCM, including in comparison with the traditional parameters of LGE and LVGLS. METHODS. This retrospective study included 811 patients with ischemic or nonischemic DCM (median age, 60 years; 640 men, 171 women) who underwent cardiac MRI at any of five centers. FT-derived LAS parameters and LVGLS were measured using two- and four-chamber cine images. LGE percentage was quantified. Patients were assessed for a composite outcome of all-cause mortality or heart failure hospitalization. Multivariable Cox regression analyses including demographic characteristics, cardiovascular risk factors, medications used, and a wide range of cardiac MRI parameters were performed. Kaplan-Meier analyses with log-rank tests were also performed. RESULTS. A total of 419 patients experienced the composite outcome. Patients who did, versus those who did not, experience the composite outcome had larger LVGLS (-6.7% vs -8.3%, respectively; p < .001) as well as a smaller LAS reservoir (13.3% vs 19.3%, p < .001), LAS conduit (4.7% vs 8.0%, p < .001), and LAS booster (8.1% vs 10.3%, p < .001) but no significant difference in LGE (10.1% vs 11.3%, p = .51). In multivariable Cox regression analyses, significant independent predictors of the composite outcome included LAS reservoir (HR = 0.96, p < .001) and LAS conduit (HR = 0.91, p < .001). LAS booster and LGE were not significant independent predictors in the models. LVGLS was a significant independent predictor only in a model that initially included LAS booster but not the other LAS parameters. In Kaplan-Meier analysis, all three LAS parameters were significantly associated with the composite outcome (p < .001). CONCLUSION. In this multicenter study, LAS reservoir and LAS conduit were significant independent prognostic markers in patients with ischemic or nonischemic DCM, showing greater prognostic utility than the currently applied markers of LVGLS and LGE. CLINICAL IMPACT. FT-derived LAS analysis provides incremental prognostic information in patients with DCM.

Differential expression of FSTL1 and its correlation with the pathological process of periodontitis.

AIMS: This study aimed to elucidate the alterations in Follistatin-like protein 1 (FSTL1) and its association with the pathological process of periodontitis. METHODS: This study included 48 patients with periodontitis and 42 healthy controls. The expression level of FSTL1 in the gingiva was determined by RT-qPCR, validated using the dataset GSE16134, and subsequently examined by western blotting. Bioinformatics analysis revealed a single-cell distribution of FSTL1, characteristic of angiogenesis and immune cell infiltration. The expression and distribution of FSTL1, vascular endothelial marker protein CD31 and myeloperoxidase (MPO), the indicator of neutrophil activity, were determined by immunohistochemistry (IHC). A series of correlation analyses was performed to determine the associations between FSTL1 and clinical parameters, including probing depth (PD) and clinical attachment loss (CAL), and their potential role in angiogenesis (CD31) and neutrophil infiltration (MPO). RESULTS: FSTL1 was significantly upregulated in the gingiva of patients with periodontitis compared to their healthy counterparts. In addition, FSTL1 was positively correlated with the clinical parameters PD (r = .5971, p = .0005) and CAL (r = .6078, p = .0004). Bioinformatic analysis and IHC indicated that high FSTL1 expression was significantly correlated with angiogenesis and neutrophil infiltration in periodontitis. Moreover, receiver operating characteristic (ROC) analysis demonstrated that FSTL1 could serve as an independent indicator for evaluating the severity of periodontitis (area under the curve [AUC] = 0.9011, p < .0001). CONCLUSION: This study demonstrated FSTL1 upregulation in periodontitis and its potential contribution to the disease via angiogenesis and neutrophil infiltration.

Intracranial stimulation and EEG feature analysis reveal affective salience network specialization.

Emotion is represented in limbic and prefrontal brain areas, herein termed the affective salience network (ASN). Within the ASN, there are substantial unknowns about how valence and emotional intensity are processed-specifically, which nodes are associated with affective bias (a phenomenon in which participants interpret emotions in a manner consistent with their own mood). A recently developed feature detection approach ('specparam') was used to select dominant spectral features from human intracranial electrophysiological data, revealing affective specialization within specific nodes of the ASN. Spectral analysis of dominant features at the channel level suggests that dorsal anterior cingulate (dACC), anterior insula and ventral-medial prefrontal cortex (vmPFC) are sensitive to valence and intensity, while the amygdala is primarily sensitive to intensity. Akaike information criterion model comparisons corroborated the spectral analysis findings, suggesting all four nodes are more sensitive to intensity compared to valence. The data also revealed that activity in dACC and vmPFC were predictive of the extent of affective bias in the ratings of facial expressions-a proxy measure of instantaneous mood. To examine causality of the dACC in affective experience, 130 Hz continuous stimulation was applied to dACC while patients viewed and rated emotional faces. Faces were rated significantly happier during stimulation, even after accounting for differences in baseline ratings. Together the data suggest a causal role for dACC during the processing of external affective stimuli.

Insight into the role of mitochondrion-related gene anchor signature in mitochondrial dysfunction of neutrophilic asthma.

OBJECTIVE: At present, targeting molecular-pharmacological therapy is still difficult in neutrophilic asthma. The investigation aims to identify and validate mitochondrion-related gene signatures for diagnosis and specific targeting therapeutics in neutrophilic asthma. METHODS: Bronchial biopsy samples of neutrophilic asthma and healthy people were identified from the GSE143303 dataset and then matched with human mitochondrial gene data to obtain mitochondria-related differential genes (MitoDEGs). Signature mitochondria-related diagnostic markers were jointly screened by support vector machine (SVM) analysis, least absolute shrinkage, and selection operator (LASSO) regression. The expression of marker MitoDEGs was evaluated by validation datasets GSE147878 and GSE43696. The diagnostic value was evaluated by receiver operating characteristic (ROC) curve analysis. Meanwhile, the infiltrating immune cells were analyzed by the CIBERSORT. Finally, oxidative stress level and mitochondrial functional morphology for asthmatic mice and BEAS-2B cells were evaluated. The expression of signature MitoDEGs was verified by qPCR. RESULTS: 67 MitoDEGs were identified. Five signature MitoDEGs (SOD2, MTHFD2, PPTC7, NME6, and SLC25A18) were further screened out. The area under the curve (AUC) of signature MitoDEGs presented a good diagnostic performance (more than 0.9). There were significant differences in the expression of signature MitoDEGs between neutrophilic asthma and non-neutrophilic asthma. In addition, the basic features of mitochondrial dysfunction were demonstrated by in vitro and in vivo experiments. The expression of signature MitoDEGs in the neutrophilic asthma mice presented a significant difference from the control group. CONCLUSIONS: These MitoDEGs signatures in neutrophilic asthma may hold potential as anchor diagnostic and therapeutic targets in neutrophilic asthma.

Assumption-free analysis for amplification-based quantitative nucleic acid detection.

The accurate detection and quantification of biological species that are rarely present but potentially devastating is of paramount importance for the life sciences, biosecurity, food safety, and environmental monitoring. Consequently, there has been significant interest in the sensitive and accurate detection of nucleic acids, leveraging both chemical and biological methods. Among these, quantitative polymerase chain reaction (qPCR) is regarded as the gold standard due to its sensitivity and precision in identifying specific nucleic acid targets. Despite the widespread adoption of qPCR for nucleic acid detection, the analysis of qPCR data typically depends on the use of calibrated standard curves and a threshold method to interpret signal measurements. In this study, we use a stochastic simulation to show the limitations of the threshold method due to its assumptions on amplification kinetics. We propose a new approach for the absolute quantification of nucleic acids that overcomes these limitations by reconstructing the efficiency profile across amplification cycles and using cumulative amplification folds to build a standard curve, thus avoiding the constant efficiency assumption. Our method, validated through experiments with nucleic acid amplification in the presence of potent inhibitors, demonstrates improved accuracy in quantifying nucleic acids, avoiding the systematic errors of the threshold method. This innovation enhances the reliability of nucleic acid quantification, especially where traditional methods struggle with kinetic variability.

Development and validation of a deep learning model for predicting postoperative survival of patients with gastric cancer.

BACKGROUND: Deep learning (DL), a specialized form of machine learning (ML), is valuable for forecasting survival in various diseases. Its clinical applicability in real-world patients with gastric cancer (GC) has yet to be extensively validated. METHODS: A combined cohort of 11,414 GC patients from the Surveillance, Epidemiology and End Results (SEER) database and 2,846 patients from a Chinese dataset were utilized. The internal validation of different algorithms, including DL model, traditional ML models, and American Joint Committee on Cancer (AJCC) stage model, was conducted by training and testing sets on the SEER database, followed by external validation on the Chinese dataset. The performance of the algorithms was assessed using the area under the receiver operating characteristic curve, decision curve, and calibration curve. RESULTS: DL model demonstrated superior performance in terms of the area under the curve (AUC) at 1, 3, and, 5 years post-surgery across both datasets, surpassing other ML models and AJCC stage model, with AUCs of 0.77, 0.80, and 0.82 in the SEER dataset and 0.77, 0.76, and 0.75 in the Chinese dataset, respectively. Furthermore, decision curve analysis revealed that the DL model yielded greater net gains at 3 years than other ML models and AJCC stage model, and calibration plots at 3 years indicated a favorable level of consistency between the ML and actual observations during external validation. CONCLUSIONS: DL-based model was established to accurately predict the survival rate of postoperative patients with GC.

Exploring Ribosomal Genes as Potential Biomarkers of the Immune Microenvironment in Respiratory Syncytial Virus Infection.

Respiratory syncytial virus (RSV) is the most common pathogen causing acute lower respiratory tract infection in infants and children. Due to limited knowledge of the pathological and molecular mechanisms of immunodeficiency underlying RSV disease, there is currently a lack of an approved and effective RSV vaccine to combat RSV infections. This study aimed to identify genes associated with immune dysfunction using bioinformatics methods to gain insights into the role of dysregulated immune genes in RSV disease progression, and to predict potential therapeutic drugs by targeting dysregulated immune-related genes. 423 immune-related differential genes (DEIRGs) were filtered from the blood samples of 87 healthy individuals and 170 RSV patients. According to CIBERSORT analysis, the blood of RSV patients showed increased infiltration of various immune cells. Subsequently, ten immune-related hub genes were screened via Protein-Protein Interaction Networks. Six signature immune-related genes (RPS2, RPS5, RPS13, RPS14, RPS18, and RPS4X) as candidate characteristic genes for the diagnostic model were identified by Lasso regression. The AUC value of the ROC curve of the six signature genes was 0.884. This result, intriguingly, suggested that all six immune-related genes with a good internal validation effect were ribosome family genes. Finally, through molecular docking analyses targeting these differential immune genes, ADO and fluperlapine were found to have high stable binding to major proteins of important immune-related genes in nine drug-protein interactions. Overall, the present study screened immune-related genes that are dysregulated in the development of RSV disease to investigate the pathogenesis of RSV infection from the standpoint of immune disorders. Unexpectedly, bioinformatics analysis revealed that ribosome family genes may be involved in the immune dysregulation of RSV disease, and these genes as targets formed the basis for potential drug modification candidates in RSV disease.

Inorganic salt starvation improves the polysaccharide production and CO2 fixation by Porphyridium purpureum.

The microalgae industry shows a promising future in the production of high-value products such as pigments, phycoerythrin, polyunsaturated fatty acids, and polysaccharides. It was found that polysaccharides have high biomedical value (such as antiviral, antibacterial, antitumor, antioxidative) and industrial application prospects (such as antioxidants). This study aimed to improve the polysaccharides accumulation of Porphyridium purpureum CoE1, which was effectuated by inorganic salt starvation strategy whilst supplying rich carbon dioxide. At a culturing temperature of 25 °C, the highest polysaccharide content (2.89 g/L) was achieved in 50% artificial seawater on the 12th day. This accounted for approximately 37.29% of the dry biomass, signifying a 25.3% increase in polysaccharide production compared to the culture in 100% artificial seawater. Subsequently, separation, purification and characterization of polysaccharides produced were conducted. Furthermore, the assessment of CO2 fixation capacity during the cultivation of P. purpureum CoE1 was conducted in a 10 L photobioreactor. This indicated that the strain exhibited an excellent CO2 fixation capacity of 1.66 g CO2/g biomass/d. This study proposed an efficient and feasible approach that not only increasing the yield of polysaccharides by P. purpureum CoE1, but also fixing CO2 with a high rate, which showed great potential in the microalgae industry and Bio-Energy with Carbon Capture and Storage.

Role of αENaC in root resorption of adjacent teeth due to entirely impacted mandibular third molars.

BACKGROUND: Entirely impacted mandibular third molar (EIM3M) concerns the pathological external root resorption (ERR) of the adjacent mandibular second molar (M2M) and formation of granulation tissue between two molars. The study aimed to clarify the effect of αENaC, a mechano-sensitive molecule, to explore the mechanical mechanism in this scenario. METHODS: The force EIM3M exerted on M2M was proved by finite element analysis. αENaC expressions were tested by real-time polymerase chain reaction (PCR), immunoblotting and immunofluorescence. Inflammatory and epithelial-mesenchymal transition (EMT)-related molecules expressions were also detected by real-time PCR. The correlation was analyzed by Spearman's correlation analysis, and receiver-operator characteristic (ROC) curve was further exhibited. RESULTS: The force was concentrated in the ERR area. αENaC was upregulated, positively correlated with ERR degree and localized to the fibroblasts in ERR granulation tissues. Moreover, αENaC was respectively and positively associated with elevated TNF-α and N-cadherin in ERR granulation tissues. More importantly, ROC analysis verified αENaC as a novel indication of the incidence of this disease. CONCLUSIONS: Our finding revealed the force from EIM3M causing ERR of M2M, and elucidated the expression and localization of αENaC and its positive correlation with inflammation, EMT and disease severity, suggesting a novel indication in this disease.

Expression patterns of mechanosensitive ion channel PIEZOs in irreversible pulpitis.

BACKGROUND: Mechanosensitive ion channel PIEZOs have been widely reported to involve inflammation and pain. This study aimed to clarify expression patterns of PIEZOs and their potential relations to irreversible pulpitis. MATERIALS AND METHODS: Normal pulp tissues (n = 29) from patients with impacted third molars and inflamed pulp tissues (n = 23) from patients with irreversible pulpitis were collected. Pain levels were assessed using a numerical rating scale. PIEZO expressions were measured using real-time PCR and then confirmed using GEO datasets GSE77459, immunoblot, and immunohistochemistry staining. Correlations of PIEZO mRNA expression with inflammatory markers, pain markers, or clinical pain levels were evaluated using Spearman's correlation analysis. Univariate analysis was conducted to analyze PIEZO expressions based on pain description and clinical examinations of cold test, percussion, palpation, and bite test. RESULTS: Compared with normal pulp tissues, mRNA expression levels of PIEZO1 were significantly increased in inflamed pulp tissues, while PIEZO2 was significantly decreased, which was further confirmed in GSE77459 and on a protein and histological level. The positive correlation of the mRNA expression levels between PIEZO1 and inflammatory markers, as well as between PIEZO2 and pain markers, was verified. PIEZO2 expression was also positively correlated with pain levels. Besides, irreversible pulpitis patients who reported continuous pain and who detected a positive response to cold stimulus exhibited a higher expression level of PIEZO2 in the inflamed pulp tissues. By contrast, patients reporting pain duration of more than one week showed a higher expression level of PIEZO1. CONCLUSIONS: This study demonstrated the upregulation of PIEZO1 and the downregulation of PIEZO2 in irreversible pulpitis and revealed the potential relation of PIEZO1 and PIEZO2 to inflammation and pain. These findings suggested that PIEZOs might play critical roles in the progression of irreversible pulpitis and paved the way for further investigations aimed at novel therapies of irreversible pulpitis by targeting PIEZOs.

Radical Fluorosulfonamidation: A Facile Access to Sulfamoyl Fluorides.

Recently, the introduction of fluorosulfonyl (-SO2F) groups have attracted considerable research interests, as this moiety could often afford enhanced activities and new functions in the context of chemical biology and drug discovery. Herein, we report the design and synthesis of 1-fluorosulfamoyl-pyridinium (FSAP) salts, which could serve as an effective photoredox-active precursor to fluorosulfamoyl radicals and enable the direct radical C-H fluorosulfonamidation of a variety of (hetero)arenes. This method features mild conditions, visible light, broad substrate scope, good group tolerance, etc., and a metal-free protocol is also viable by using organic photocatalysts. Further, FSAP can also be applied to the radical functionalization of alkenes via 1,2-difunctionalization, radical distal migration, tandem radical-polar crossover reactions, etc. In addition, a formal C-H methylamination of (hetero)arenes by combining this radical C-H fluorosulfonamidation with subsequent hydrolysis as well as product derivatization are also demonstrated.

On triangle inequalities of correlation-based distances for gene expression profiles.

BACKGROUND: Distance functions are fundamental for evaluating the differences between gene expression profiles. Such a function would output a low value if the profiles are strongly correlated-either negatively or positively-and vice versa. One popular distance function is the absolute correlation distance, [Formula: see text], where [Formula: see text] is similarity measure, such as Pearson or Spearman correlation. However, the absolute correlation distance fails to fulfill the triangle inequality, which would have guaranteed better performance at vector quantization, allowed fast data localization, as well as accelerated data clustering. RESULTS: In this work, we propose [Formula: see text] as an alternative. We prove that [Formula: see text] satisfies the triangle inequality when [Formula: see text] represents Pearson correlation, Spearman correlation, or Cosine similarity. We show [Formula: see text] to be better than [Formula: see text], another variant of [Formula: see text] that satisfies the triangle inequality, both analytically as well as experimentally. We empirically compared [Formula: see text] with [Formula: see text] in gene clustering and sample clustering experiment by real-world biological data. The two distances performed similarly in both gene clustering and sample clustering in hierarchical clustering and PAM (partitioning around medoids) clustering. However, [Formula: see text] demonstrated more robust clustering. According to the bootstrap experiment, [Formula: see text] generated more robust sample pair partition more frequently (P-value [Formula: see text]). The statistics on the time a class "dissolved" also support the advantage of [Formula: see text] in robustness. CONCLUSION: [Formula: see text], as a variant of absolute correlation distance, satisfies the triangle inequality and is capable for more robust clustering.

Identification of Myocardial Scarring Using Contrast-Free Cardiac MRI in Patients With Autoimmune Rheumatic Diseases.

BACKGROUND: Late gadolinium enhancement (LGE) cardiac MRI is the method of choice in revealing the presence of myocardial scarring, but its availability remains limited in clinical practice. PURPOSE: To assess myocardial scarring in patients with autoimmune rheumatic diseases (ARDs) using contrast-free cardiac MRI with a radiomics model. STUDY TYPE: Retrospective. POPULATION: One hundred ninety-two patients (mean age, 41 years ± 15, 62 men) with or without ARDs, grouped into a training set of 153 patients and a testing set of 39 patients. FIELD STRENGTH/SEQUENCE: 3.0 T/ cine imaging with a balanced steady-state free precession sequence, T1 mapping with a modified Look-Locker inversion recovery sequence, and LGE imaging with a phase-sensitive inversion recovery gradient echo sequence. ASSESSMENT: LGE assessment was the reference standard for identifying myocardial scarring. Based on motion features extracted from cine images and tissue characterization features extracted from native T1 maps, a fully automated radiomics model with T1, cine MRI, or combined inputs was developed. STATISTICAL TESTS: Logistic regression model was used to detect myocardial scarring using contrast-free cardiac MRI parameters. Receiver operating characteristic curves were analyzed to assess the accuracy, sensitivity, and specificity in detecting myocardial scarring. Sensitivities of the models were further assessed in patients with various myocardial scarring proportions. Z-statistic and dice coefficient were assessed to compare the performance. P-values <0.05 were considered significant. RESULTS: The multivariable regression model exhibited an accuracy of 85.3%, a sensitivity of 93.5%, and a specificity of 50.0%. The radiomics model with T1 and cine MRI input exhibited an accuracy of 75.7%, a sensitivity of 60.9%, and a specificity of 85.5%. Moreover, the radiomics model showed a sensitivity of 90.9% among patients with >25% myocardial scarring. DATA CONCLUSIONS: The proposed radiomics model allowed for the identification of myocardial scarring similar to LGE, but on contrast-free cardiac MRI in patients with ARDs. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

Combination of microbial and chemical synthesis for the sustainable production of ß-elemene, a promising plant-extracted anticancer compound.

Beta-elemene, a class of sesquiterpene derived from the Chinese medicinal herb Curcuma wenyujin, is widely used in clinical medicine due to its broad-spectrum antitumor activity. However, the unsustainable plant extraction prompted the search for environmentally friendly strategies for ß-elemene production. In this study, we designed a Yarrowia lipolytica cell factory that can continuously produce germacrene A, which is further converted into ß-elemene with 100% yield through a Cope rearrangement reaction by shifting the temperature to 250°C. First, the productivity of four plant-derived germacrene A synthases was evaluated. After that, the metabolic flux of the precursor to germacrene A was maximized by optimizing the endogenous mevalonate pathway, inhibiting the competing squalene pathway, and expressing germacrene A synthase gene in multiple copies. Finally, the most promising strain achieved the highest ß-elemene titer reported to date with 5.08 g/L. This sustainable and green method has the potential for industrial ß-elemene production.

A robust soft sensor based on artificial neural network for monitoring microbial lipid fermentation processes using Yarrowia lipolytica.

Microbial oils produced by Yarrowia lipolytica offer an environmentally friendly and sustainable alternative to petroleum as well as traditional lipids from animals and plants. The accurate measurement of fermentation parameters, including the substrate concentration, dry cell weight, and lipid accumulation, is the foundation of process control, which is indispensable for industrial lipid production. However, it remains a great challenge to measure the complex parameters online during the lipid fermentation process, which is nonlinear, multivariate, and characterized by strong coupling. As a type of AI technology, the artificial neural network model is a powerful tool for handling extremely complex problems, and it can be employed to develop a soft sensor to monitor the microbial lipid fermentation process of Y. lipolytica. In this study, we first analyzed and emphasized the volume of sodium hydroxide and dissolved oxygen concentration as central parameters of the fermentation process. Then, a soft sensor based on a four-input artificial neural network model was developed, in which the input variables were fermentation time, dissolved oxygen concentration, initial glucose concentration, and additional volume of sodium hydroxide. This provides the possibility of online monitoring of dry cell weight, glucose concentration, and lipid production with high accuracy, which can be extended to similar fermentation processes characterized by the addition of bases or acids, as well as changes of the dissolved oxygen concentration.

Actigraphic correlates of neuropsychiatric symptoms in adults with focal epilepsy.

OBJECTIVES: Disability in patients with epilepsy (PWEs) is multifactorial: beyond seizure frequency/severity, PWEs are prone to a range of neuropsychiatric, cognitive, and somatic comorbidities that significantly affect quality of life. Here, we explored how variations in seizure severity and the burden of self-reported somatic/neuropsychiatric symptoms correlate with disruptions to 24 h activity patterns (rest-activity rhythms [RARs]), determined through wrist accelerometry/actigraphy. METHODS: Multiday wrist-actigraphy recordings were obtained from 59 adult patients with focal epilepsy (44% male, ages 18-72), who contemporaneously responded to validated psychometric instruments to measure anxiety, depression, sleepiness, and somatic symptoms. We conducted a similar in silico psychometric-actigraphic correlation in a publicly available data set of 1747 Hispanic subjects (35% male, ages 18-65) from the Study of Latinos (SOL) Sueño Ancillary Study. RARs were analyzed via a sigmoidally-transformed cosine model (quantifying amplitude, steepness, acrophase, and robustness) and nonparametric measures to estimate RAR stability, fragmentation, and sleep. RESULTS: Compared with matched SOL subjects, RARs from PWE subjects featured a significantly lower amplitude, a wider rest phase, and significantly more total daily sleep. Within PWEs, similar RAR distortions were associated with seizure intractability and/or anticonvulsant polytherapy, whereas high anxiety, depression, and somatic symptom scores were associated with lower RAR robustness and acrophase delay. We applied the SOL data set to train logistic regression models to dichotomously classify subjective anxiety, depression, and sleepiness symptoms using demographic and RAR parameters. When tested on PWEs, these models predicted prevalent anxiety and depression symptom burden (accuracy ~70%) but failed to predict subjective sleepiness. SIGNIFICANCE: Together these results demonstrate that RAR features may encode prevalent depression and anxiety symptoms in patients with focal epilepsy, potentially offering wearable-derived endpoints to adjunct clinical care and drug/device trials. With larger PWE-specific actigraphic-psychometric data sets, we may identify RAR signatures that may more precisely correlate with varying seizure frequency, the burden of anticonvulsant therapy, and prevalent mood/anxiety symptoms.