Engineering IscB to develop highly efficient miniature editing tools in mammalian cells and embryos.

The IscB proteins, as the ancestors of Cas9 endonuclease, hold great promise due to their small size and potential for diverse genome editing. However, their activity in mammalian cells is unsatisfactory. By introducing three residual substitutions in IscB, we observed an average 7.5-fold increase in activity. Through fusing a sequence-non-specific DNA-binding protein domain, the eIscB-D variant achieved higher editing efficiency, with a maximum of 91.3%. Moreover, engineered ωRNA was generated with a 20% reduction in length and slightly increased efficiency. The engineered eIscB-D/eωRNA system showed an average 20.2-fold increase in activity compared with the original IscB. Furthermore, we successfully adapted eIscB-D for highly efficient cytosine and adenine base editing. Notably, eIscB-D is highly active in mouse cell lines and embryos, enabling the efficient generation of disease models through mRNA/ωRNA injection. Our study suggests that these miniature genome-editing tools have great potential for diverse applications.

Distinct virtual histology of grey matter atrophy in four neuroinflammatory diseases.

Grey matter (GM) atrophies are observed in multiple sclerosis, neuromyelitis optica spectrum disorders [NMOSD; both anti-aquaporin-4 antibody-positive (AQP4+) and -negative (AQP4-) subtypes] and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). Revealing the pathogenesis of brain atrophy in these disorders would help their differential diagnosis and guide therapeutic strategies. To determine the neurobiological underpinnings of GM atrophies in multiple sclerosis, AQP4+ NMOSD, AQP4- NMOSD and MOGAD, we conducted a virtual histology analysis that links T1-weighted image derived GM atrophy and gene expression using a multicentre cohort of 324 patients with multiple sclerosis, 197 patients with AQP4+ NMOSD, 75 patients with AQP4- NMOSD, 47 patients with MOGAD and 2169 healthy control subjects. First, interregional GM atrophy profiles across the cortical and subcortical regions were determined using Cohen's d between patients with multiple sclerosis, AQP4+ NMOSD, AQP4- NMOSD or MOGAD and healthy controls. The GM atrophy profiles were then spatially correlated with the gene expression levels extracted from the Allen Human Brain Atlas, respectively. Finally, we explored the virtual histology of clinical-feature relevant GM atrophy using a subgroup analysis that stratified by physical disability, disease duration, number of relapses, lesion burden and cognitive function. Multiple sclerosis showed a severe widespread GM atrophy pattern, mainly involving subcortical nuclei and brainstem. AQP4+ NMOSD showed an obvious widespread pattern of GM atrophy, predominately located in occipital cortex as well as cerebellum. AQP4- NMOSD showed a mild widespread GM atrophy pattern, mainly located in frontal and parietal cortices. MOGAD showed GM atrophy mainly involving the frontal and temporal cortices. High expression of genes specific to microglia, astrocytes, oligodendrocytes and endothelial cells in multiple sclerosis, S1 pyramidal cells in AQP4+ NMOSD, as well as S1 and CA1 pyramidal cells in MOGAD, had spatial correlations with GM atrophy profile, while no atrophy profile-related gene expression was found in AQP4- NMOSD. Virtual histology of clinical feature-relevant GM atrophy pointed mainly to the shared neuronal and endothelial cells, among the four neuroinflammatory diseases. The unique underlying virtual histology patterns were microglia, astrocytes and oligodendrocytes for multiple sclerosis; astrocytes for AQP4+ NMOSD; and oligodendrocytes for MOGAD. Neuronal and endothelial cells were shared potential targets across these neuroinflammatory diseases. These findings may help the differential diagnoses of these diseases and promote the use of optimal therapeutic strategies.

The role of the sensory input intervention in recovery of the motor function in hypoxic ischemic encephalopathy rat model.

Motor disturbances predominantly characterize hypoxic-ischemic encephalopathy (HIE). Among its intervention methods, environmental enrichment (EE) is strictly considered a form of sensory intervention. However, limited research uses EE as a single sensory input intervention to validate outcomes postintervention. A Sprague-Dawley rat model subjected to left common carotid artery ligation and exposure to oxygen-hypoxic conditions is used in this study. EE was achieved by enhancing the recreational and stress-relief items within the cage, increasing the duration of sunlight, colorful items exposure, and introducing background music. JZL184 (JZL) was administered as neuroprotective drugs. EE was performed 21 days postoperatively and the rats were randomly assigned to the standard environment and EE groups, the two groups were redivided into control, JZL, and vehicle injection subgroups. The Western blotting and behavior test indicated that EE and JZL injections were efficacious in promoting cognitive function in rats following HIE. In addition, the motor function performance in the EE-alone intervention group and the JZL-alone group after HIE was significantly improved compared with the control group. The combined EE and JZL intervention group exhibited even more pronounced improvements in these performances. EE may enhance motor function through sensory input different from the direct neuroprotective effect of pharmacological treatment.NEW & NOTEWORTHY Rarely does literature assess motor function, even though it is common after hypoxia ischemic encephalopathy (HIE). Previously used environmental enrichment (EE) components have not been solely used as sensory inputs. Physical factors were minimized in our study to observe the effects of purely sensory inputs.

U-fiber diffusion kurtosis and susceptibility characteristics in relapsing-remitting multiple sclerosis may be related to cognitive deficits and neurodegeneration.

OBJECTIVES: To evaluate the diffusion kurtosis and susceptibility change in the U-fiber region of patients with relapsing-remitting multiple sclerosis (pwRRMS) and their correlations with cognitive status and degeneration. MATERIALS AND METHODS: Mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), kurtosis fractional anisotropy (KFA), and the mean relative quantitative susceptibility mapping (mrQSM) values in the U-fiber region were compared between 49 pwRRMS and 48 healthy controls (HCs). The U-fiber were divided into upper and deeper groups based on the location. The whole brain volume, gray and white matter volume, and cortical thickness were obtained. The correlations between the mrQSM values, DKI-derived metrics in the U-fiber region and clinical scale scores, brain morphologic parameters were further investigated. RESULTS: The decreased MK, AK, RK, KFA, and increased mrQSM values in U-fiber lesions (p < 0.001, FDR corrected), decreased RK, KFA, and increased mrQSM values in U-fiber non-lesions (p = 0.034, p < 0.001, p < 0.001, FDR corrected) were found in pwRRMS. There were differences in DKI-derived metrics and susceptibility values between the upper U-fiber region and the deeper one for U-fiber non-lesion areas of pwRRMS and HCs (p < 0.05), but not for U-fiber lesions in DKI-derived metrics. The DKI-derived metrics and susceptibility values were widely related with cognitive tests and brain atrophy. CONCLUSION: RRMS patients show abnormal diffusion kurtosis and susceptibility characteristics in the U-fiber region, and these underlying tissue abnormalities are correlated with cognitive deficits and degeneration. CLINICAL RELEVANCE STATEMENT: The macroscopic and microscopic tissue damages of U-fiber help to identify cognitive impairment and brain atrophy in multiple sclerosis and provide underlying pathophysiological mechanism. KEY POINTS: • Diffusion kurtosis and susceptibility changes are present in the U-fiber region of multiple sclerosis. • There are gradients in diffusion kurtosis and susceptibility characteristics in the U-fiber region. • Tissue damages in the U-fiber region are correlated with cognitive impairment and brain atrophy.

Comparison of diffusion tensor imaging (DTI) tissue characterization parameters in white matter tracts of patients with multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD).

OBJECTIVE: To investigate the microstructural properties of T2 lesion and normal-appearing white matter (NAWM) in 20 white matter tracts between multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) and correlations between the tissue damage and clinical variables. METHODS: The white matter (WM) compartment of the brain was segmented for 56 healthy controls (HC), 48 patients with MS, and 38 patients with NMOSD, and for the patients further subdivided into T2 lesion and NAWM. Subsequently, the diffusion tensor imaging (DTI) tissue characterization parameters of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were compared for 20 principal white matter tracts. The correlation between tissue damage and clinical variables was also investigated. RESULTS: The higher T2 lesion volumes of 14 fibers were shown in MS compared to NMOSD. MS showed more microstructure damage in 13 fibers of T2 lesion, but similar microstructure in seven fibers compared to NMOSD. MS and NMOSD had microstructure damage of NAWM in 20 fibers compared to WM in HC, with more damage in 20 fibers in MS compared to NMOSD. MS patients showed higher correlation between the microstructure of T2 lesion areas and NAWM. The T2 lesion microstructure damage was correlated with duration and impaired cognition in MS. CONCLUSIONS: Patients with MS and NMOSD show different patterns of microstructural damage in T2 lesion and NAWM areas. The prolonged disease course of MS may aggravate the microstructural damage, and the degree of microstructural damage is further related to cognitive impairment. CLINICAL RELEVANCE STATEMENT: Microstructure differences between T2 lesion areas and normal-appearing white matter help distinguish multiple sclerosis and neuromyelitis optica spectrum disorder. In multiple sclerosis, lesions rather than normal-appearing white matter should be a concern, because the degree of lesion severity correlated both with normal-appearing white matter damage and cognitive impairment. KEY POINTS: • Multiple sclerosis and neuromyelitis optica spectrum disorder have different damage patterns in T2 lesion and normal-appearing white matter areas. • The microstructure damage of normal-appearing white matter is correlated with the microstructure of T2 lesion in multiple sclerosis and neuromyelitis optica spectrum disorder. • The microstructure damage of T2 lesion in multiple sclerosis is correlated with duration and cognitive impairment.

A novel MRI-based deep learning networks combined with attention mechanism for predicting CDKN2A/B homozygous deletion status in IDH-mutant astrocytoma.

OBJECTIVES: To develop a high-accuracy MRI-based deep learning method for predicting cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) homozygous deletion status in isocitrate dehydrogenase (IDH)-mutant astrocytoma. METHODS: Multiparametric brain MRI data and corresponding genomic information of 234 subjects (111 positives for CDKN2A/B homozygous deletion and 123 negatives for CDKN2A/B homozygous deletion) were obtained from The Cancer Imaging Archive (TCIA) and The Cancer Genome Atlas (TCGA) respectively. Two independent multi-sequence networks (ResFN-Net and FN-Net) are built on the basis of ResNet and ConvNeXt network combined with attention mechanism to classify CDKN2A/B homozygous deletion status using MR images including contrast-enhanced T1-weighted imaging (CE-T1WI) and T2-weighted imaging (T2WI). The performance of the network is summarized by three-way cross-validation; ROC analysis is also performed. RESULTS: The average cross-validation accuracy (ACC) of ResFN-Net is 0.813. The average cross-validation area under curve (AUC) of ResFN-Net is 0.8804. The average cross-validation ACC and AUC of FN-Net is 0.9236 and 0.9704, respectively. Comparing all sequence combinations of the two networks (ResFN-Net and FN-Net), the sequence combination of CE-T1WI and T2WI performed the best, and the ACC and AUC were 0.8244, 0.8975 and 0.8971, 0.9574, respectively. CONCLUSIONS: The FN-Net deep learning networks based on ConvNeXt network achieved promising performance for predicting CDKN2A/B homozygous deletion status of IDH-mutant astrocytoma. CLINICAL RELEVANCE STATEMENT: A novel deep learning network (FN-Net) based on preoperative MRI was developed to predict the CDKN2A/B homozygous deletion status. This network has the potential to be a practical tool for the noninvasive characterization of CDKN2A/B in glioma to support personalized classification and treatment planning. KEY POINTS: • CDKN2A/B homozygous deletion status is an important marker for glioma grading and prognosis. • An MRI-based deep learning approach was developed to predict CDKN2A/B homozygous deletion status. • The predictive performance based on ConvNeXt network was better than that of ResNet network.

Spatial structural abnormality maps associated with cognitive and physical performance in relapsing-remitting multiple sclerosis.

OBJECTIVES: We aimed to characterize the brain abnormalities that are associated with the cognitive and physical performance of patients with relapsing-remitting multiple sclerosis (RRMS) using a deep learning algorithm. MATERIALS AND METHODS: Three-dimensional (3D) nnU-Net was employed to calculate a novel spatial abnormality map by T1-weighted images and 281 RRMS patients (Dataset-1, male/female = 101/180, median age [range] = 35.0 [17.0, 65.0] years) were categorized into subtypes. Comparison of clinical and MRI features between RRMS subtypes was conducted by Kruskal-Wallis test. Kaplan-Meier analysis was conducted to investigate disability progression in RRMS subtypes. Additional validation using two other RRMS datasets (Dataset-2, n = 33 and Dataset-3, n = 56) was conducted. RESULTS: Five RRMS subtypes were identified: (1) a Frontal-I subtype showing preserved cognitive performance and mild physical disability, and low risk of disability worsening; (2) a Frontal-II subtype showing low cognitive scores and severe physical disability with significant brain volume loss, and a high propensity for disability worsening; (3) a temporal-cerebellar subtype demonstrating lowest cognitive scores and severest physical disability among all subtypes but remaining relatively stable during follow-up; (4) an occipital subtype demonstrating similar clinical and imaging characteristics as the Frontal-II subtype, except a large number of relapses at baseline and preserved cognitive performance; and (5) a subcortical subtype showing preserved cognitive performance and low physical disability but a similar prognosis as the occipital and Frontal-II subtypes. Additional validation confirmed the above findings. CONCLUSION: Spatial abnormality maps can explain heterogeneity in cognitive and physical performance in RRMS and may contribute to stratified management. KEY POINTS: Question Can a deep learning algorithm characterize the brain abnormalities associated with the cognitive and physical performance of patients with RRMS? Findings Five RRMS subtypes were identified by the algorithm that demonstrated variable cognitive and physical performance. Clinical relevance The spatial abnormality maps derived RRMS subtypes had distinct cognitive and physical performances, which have a potential for individually tailored management.

Quantitative Fluorescent Lateral Flow Strip Sensor for Myocardial Infarction Using Purity-Color Upconversion Nanoparticles.

Acute myocardial infarction is a serious cardiovascular disease and poses significant risks to human health. Its early diagnosis and real-time detection are of great importance. Herein, we design a low-cost device that has a high sensitivity of cTnT and cTnI detection. Dual-color upconversion nanoparticles (UCNPs) are prepared as probes, which not only have high-purity red upconversion luminescence (UCL) under 980 or 808 nm excitation but also achieve good temperature sensing. Temperature-dependent multicolor emission excitation is obtained, and the color turns from white to orange and red with increasing temperature. In particular, the maximum SR and SA values based on nonthermally coupled levels are 4.76% K-1 and 8.6% K-1, which are higher than those based on thermally coupled levels. With the UCNPs-based lateral flow strip (LFS), the specific detection of cTnI and cTnT antigens in samples is achieved with a detection limit of 0.001 ng/mL, which is 1 order of magnitude lower than that of their clinical cutoff. The UCNPs-LFS device has a low-cost laser diode and a simplified laser and permits a mobile-phone camera to collect the results, which has an important influence on the field of biomarker sensing.

Increased cortical lesion load contributed to pathological changes beyond focal lesion in cortical gray matter of multiple sclerosis: a diffusion kurtosis imaging analysis.

Biomarkers specific to cortical gray matter (cGM) pathological changes of multiple sclerosis (MS) are desperately needed to better understand the disease progression. The cGM damage occurs in cortical lesion (CL) and normal-appearing cGM (NAcGM) areas. While the association between CL load and cGM damage has been reported, little is known about how different CL types, i.e. intracortical lesion (ICL) and leukocortical lesion (LCL) would be associated with cGM damage. In our study, relapsing-remitting MS patients and healthy controls were divided into 4 groups according to CL load level. NAcGM diffusion kurtosis imaging (DKI)/diffusion tensor imaging (DTI) values and cGM volume (cGMV) were used to characterize the pathological changes in cGM. Univariate general linear model was used for group comparisons and stepwise regression analysis was used to assess the effects of ICL volume and LCL volume on NAcGM damage. We found peak values in DKI/DTI values, cGMV and neuropsychological scores in high CL load group. Kurtosis fractional anisotropy (KFA) was the most sensitive in characterizing NAcGM damage, and LCL volume related more to NAcGM damage. Our findings suggested KFA could become a surrogate biomarker to cGM damage, and LCL might be the main factor in whole brain NAcGM damage.

Enhancing precision medicine: a nomogram for predicting platinum resistance in epithelial ovarian cancer.

BACKGROUND: This study aimed to develop a novel nomogram that can accurately estimate platinum resistance to enhance precision medicine in epithelial ovarian cancer(EOC). METHODS: EOC patients who received primary therapy at the General Hospital of Ningxia Medical University between January 31, 2019, and June 30, 2021 were included. The LASSO analysis was utilized to screen the variables which contained clinical features and platinum-resistance gene immunohistochemistry scores. A nomogram was created after the logistic regression analysis to develop the prediction model. The consistency index (C-index), calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were used to assess the nomogram's performance. RESULTS: The logistic regression analysis created a prediction model based on 11 factors filtered down by LASSO regression. As predictors, the immunohistochemical scores of CXLC1, CXCL2, IL6, ABCC1, LRP, BCL2, vascular tumor thrombus, ascites cancer cells, maximum tumor diameter, neoadjuvant chemotherapy, and HE4 were employed. The C-index of the nomogram was found to be 0.975. The nomogram's specificity is 95.35% and its sensitivity, with a cut-off value of 165.6, is 92.59%, as seen by the ROC curve. After the nomogram was externally validated in the test cohort, the coincidence rate was determined to be 84%, and the ROC curve indicated that the nomogram's AUC was 0.949. CONCLUSION: A nomogram containing clinical characteristics and platinum gene IHC scores was developed and validated to predict the risk of EOC platinum resistance.

One novel transfer learning-based CLIP model combined with self-attention mechanism for differentiating the tumor-stroma ratio in pancreatic ductal adenocarcinoma.

PURPOSE: To develop a contrastive language-image pretraining (CLIP) model based on transfer learning and combined with self-attention mechanism to predict the tumor-stroma ratio (TSR) in pancreatic ductal adenocarcinoma on preoperative enhanced CT images, in order to understand the biological characteristics of tumors for risk stratification and guiding feature fusion during artificial intelligence-based model representation. MATERIAL AND METHODS: This retrospective study collected a total of 207 PDAC patients from three hospitals. TSR assessments were performed on surgical specimens by pathologists and divided into high TSR and low TSR groups. This study developed one novel CLIP-adapter model that integrates the CLIP paradigm with a self-attention mechanism for better utilizing features from multi-phase imaging, thereby enhancing the accuracy and reliability of tumor-stroma ratio predictions. Additionally, clinical variables, traditional radiomics model and deep learning models (ResNet50, ResNet101, ViT_Base_32, ViT_Base_16) were constructed for comparison. RESULTS: The models showed significant efficacy in predicting TSR in PDAC. The performance of the CLIP-adapter model based on multi-phase feature fusion was superior to that based on any single phase (arterial or venous phase). The CLIP-adapter model outperformed traditional radiomics models and deep learning models, with CLIP-adapter_ViT_Base_32 performing the best, achieving the highest AUC (0.978) and accuracy (0.921) in the test set. Kaplan-Meier survival analysis showed longer overall survival in patients with low TSR compared to those with high TSR. CONCLUSION: The CLIP-adapter model designed in this study provides a safe and accurate method for predicting the TSR in PDAC. The feature fusion module based on multi-modal (image and text) and multi-phase (arterial and venous phase) significantly improves model performance.

A Comparative Study on Effects of Three Butyric Acid-Producing Additives on the Growth Performance, Non-specific Immunity, and Intestinal Microbiota of the Sea Cucumber Apostichopus japonicus.

The providers of butyric acid, Clostridium butyricum (CB), sodium butyrate (SB), and tributyrin (TB), have been extensively studied as aquafeed additives in recent years. However, no comparative study has been reported on the probiotic effects of CB, SB, and TB as feed additives on sea cucumber (Apostichopus japonicus). A 63-day feeding trial was performed to assess the effects of dietary live cells of C. butyricum (CB group, the basal diet supplemented with 1% CB), sodium butyrate (SB group, the basal diet supplemented with 1% SB), and tributyrin (TB group, the basal diet supplemented with 1% TB) on the growth, non-specific immunity, and intestinal microbiota of A. japonicus with a basal diet group as the control. Results indicated that all three additives considerably increased A. japonicus growth, with dietary CB having the optimal growth-promoting effect. Of the seven non-specific enzyme parameters measured in coelomocytes of A. japonicus (i.e., the activities of phagocytosis, respiratory burst, superoxide dismutase, alkaline phosphatase, acid phosphatase, catalase, and lysozyme), dietary CB, SB, and TB considerably increased the activities of six, five, and six of them, respectively. The immune genes (Aj-p105, Aj-p50, Aj-rel, and Aj-lys) expression in the mid-intestine tissues of A. japonicus was significantly increased by all three additives. The CB group had the highest expression of all four genes. Additionally, the relative expression of Aj-p105, Aj-p50, and Aj-lys genes was significantly up-regulated in the three additive groups after stimulation with inactivated Vibrio splendidus. Dietary CB enhanced the intestinal microbial diversity and richness in A. japonicus while dietary TB decreased them. Meanwhile, dietary CB, SB, and TB significantly enhanced the abundance of Firmicutes, unclassified_f_Rhodobacteraceae, and Proteobacteria, respectively, while dietary CB and SB reduced the abundance of Vibrio. Dietary CB and SB improved the stability of microbial ecosystem in the intestine of A. japonicus. In contrast, dietary TB appeared to have a negative effect on the stability of intestinal microbial ecosystem. All three additives improved the intestinal microbial functions associated with energy production and immunity regulation pathways, which may contribute directly to growth promotion and non-specific immunity enhancement in A. japonicus. Collectively, in terms of enhancing growth and non-specific immunity, as well as improving intestinal microbiota, dietary live cells of C. butyricum exhibited the most effective effects in A. japonicus.

The clinical and imaging data fusion model for single-period cerebral CTA collateral circulation assessment.

BACKGROUND: The Chinese population ranks among the highest globally in terms of stroke prevalence. In the clinical diagnostic process, radiologists utilize computed tomography angiography (CTA) images for diagnosis, enabling a precise assessment of collateral circulation in the brains of stroke patients. Recent studies frequently combine imaging and machine learning methods to develop computer-aided diagnostic algorithms. However, in studies concerning collateral circulation assessment, the extracted imaging features are primarily composed of manually designed statistical features, which exhibit significant limitations in their representational capacity. Accurately assessing collateral circulation using image features in brain CTA images still presents challenges. METHODS: To tackle this issue, considering the scarcity of publicly accessible medical datasets, we combined clinical data with imaging data to establish a dataset named RadiomicsClinicCTA. Moreover, we devised two collateral circulation assessment models to exploit the synergistic potential of patients' clinical information and imaging data for a more accurate assessment of collateral circulation: data-level fusion and feature-level fusion. To remove redundant features from the dataset, we employed Levene's test and T-test methods for feature pre-screening. Subsequently, we performed feature dimensionality reduction using the LASSO and random forest algorithms and trained classification models with various machine learning algorithms on the data-level fusion dataset after feature engineering. RESULTS: Experimental results on the RadiomicsClinicCTA dataset demonstrate that the optimized data-level fusion model achieves an accuracy and AUC value exceeding 86%. Subsequently, we trained and assessed the performance of the feature-level fusion classification model. The results indicate the feature-level fusion classification model outperforms the optimized data-level fusion model. Comparative experiments show that the fused dataset better differentiates between good and bad side branch features relative to the pure radiomics dataset. CONCLUSIONS: Our study underscores the efficacy of integrating clinical and imaging data through fusion models, significantly enhancing the accuracy of collateral circulation assessment in stroke patients.

The role of Connexin26 regulated by MiR-2114-3p in the pathogenesis of ovarian cancer.

OBJECTIVES: The purpose of our research was to determine the expression of Cx26 and miR-2114-3p, and their effects on proliferation, migration, and invasion in ovarian cancer and their mechanisms. MATERIALS AND METHODS: Transcriptome sequencing was performed and differentially expressed Cx26 was screened. The mRNA and protein levels of Cx26 in EOC and normal ovarian tissues were verified. The relationship between Cx26 levels and prognostics was analyzed. Cx26 Lentiviral vectors were constructed to detect its effect on ovarian cancer. WB verified that PI3K/AKT pathway was the possible signal pathway regulated by Cx26. The interaction between miR-2114-3p and Cx26 was detected by double luciferase reporter assay and qrt-PCR. CCK8, clone formation, transwell, and flow cytometry assays were conducted in cells transfected miR-2114-3p plasmids. The vivo experiment investigated the effects of Cx26 on subcutaneous tumor growth, PI3K expression, proliferation proteins Ki67 and PCNA. RESULTS: Cx26 was up-regulated in EOC tissue and cell lines, and was associated with poor prognosis of ovarian cancer, while miR-2114-3p was down-regulated in EOC cell lines. Cx26 was a direct target of miR-2114-3p. Cx26 overexpression and miR-2114-3p inhibition promoted the growth, motility, invasiveness, and S phase arrest of EOC cells. Additionally, Cx26 could activated PI3K pathway whatever in vivo and in vitro. CONCLUSIONS: Dysregulation of Cx26 is critical in EOC patients. Manipulation of this mechanism may influence the survival of EOC patients. MiR-2114-3p regulates the tumor-promoting activity of Cx26 in EOC. By inhibiting the PI3K pathway or knocking down Cx26 effectively inhibits tumor growth in EOC cells and Nude mouse model.

Cerebellar connectome alterations and associated genetic signatures in multiple sclerosis and neuromyelitis optica spectrum disorder.

BACKGROUND: The cerebellum plays key roles in the pathology of multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD), but the way in which these conditions affect how the cerebellum communicates with the rest of the brain (its connectome) and associated genetic correlates remains largely unknown. METHODS: Combining multimodal MRI data from 208 MS patients, 200 NMOSD patients and 228 healthy controls and brain-wide transcriptional data, this study characterized convergent and divergent alterations in within-cerebellar and cerebello-cerebral morphological and functional connectivity in MS and NMOSD, and further explored the association between the connectivity alterations and gene expression profiles. RESULTS: Despite numerous common alterations in the two conditions, diagnosis-specific increases in cerebellar morphological connectivity were found in MS within the cerebellar secondary motor module, and in NMOSD between cerebellar primary motor module and cerebral motor- and sensory-related areas. Both diseases also exhibited decreased functional connectivity between cerebellar motor modules and cerebral association cortices with MS-specific decreases within cerebellar secondary motor module and NMOSD-specific decreases between cerebellar motor modules and cerebral limbic and default-mode regions. Transcriptional data explained > 37.5% variance of the cerebellar functional alterations in MS with the most correlated genes enriched in signaling and ion transport-related processes and preferentially located in excitatory and inhibitory neurons. For NMOSD, similar results were found but with the most correlated genes also preferentially located in astrocytes and microglia. Finally, we showed that cerebellar connectivity can help distinguish the three groups from each other with morphological connectivity as predominant features for differentiating the patients from controls while functional connectivity for discriminating the two diseases. CONCLUSIONS: We demonstrate convergent and divergent cerebellar connectome alterations and associated transcriptomic signatures between MS and NMOSD, providing insight into shared and unique neurobiological mechanisms underlying these two diseases.

Obesity induces male mice infertility via oxidative stress, apoptosis, and glycolysis.

In brief: The current declining trend in male fertility parallels the increasing prevalence of obesity worldwide. This paper revealed that the poor in vitro fertilization rates and decreased sperm motility in obese mice due to excessive oxidative stress enhanced apoptosis and impaired glucose metabolism in the testes. Abstract: Obesity is an urgent public health problem in recent decades, linked to reduced reproductive potential, and negatively affects the success of assisted reproduction technology. The aim of this study is to investigate the mechanisms underlying impaired male fertility caused by obesity. Male C57BL/6 mice fed a high-fat diet for 20 weeks served as mouse models with moderate (20% < body fat rate (BFR) < 30%) and severe obesity (BFR > 30%). Our results showed poor in vitro fertilization rates and decreased sperm motility in obese mice. Abnormal testicular structures were identified in male mice with moderate and severe obesity. The expression level of malondialdehyde increased with obesity severity. This finding indicates that oxidative stress plays a role in male infertility caused by obesity, which was further confirmed by the decreased expression of nuclear factor erythroid 2-related factor 2, superoxide dismutase, and glutathione peroxidases. Our study also found that the expression of cleaved caspase-3 and B-cell lymphoma-2 showed an obesity severity-dependent manner indicating that apoptosis is highly correlated with male infertility caused by obesity. Moreover, the expression of glycolysis-related proteins, including glucose transporter 8, lactate dehydrogenase A, monocarboxylate transporter 2 (MCT2), and MCT4, decreased significantly in the testes of obese male mice, suggesting energy supply for spermatogenesis is impaired by obesity. Taken together, our findings provide evidence that obesity impairs male fertility through oxidative stress, apoptosis, and blockage of energy supply in the testes and suggest that male obesity influences fertility through complex and multiple mechanisms.

Brain age gap in neuromyelitis optica spectrum disorders and multiple sclerosis.

OBJECTIVE: To evaluate the clinical significance of deep learning-derived brain age prediction in neuromyelitis optica spectrum disorder (NMOSD) relative to relapsing-remitting multiple sclerosis (RRMS). METHODS: This cohort study used data retrospectively collected from 6 tertiary neurological centres in China between 2009 and 2018. In total, 199 patients with NMOSD and 200 patients with RRMS were studied alongside 269 healthy controls. Clinical follow-up was available in 85 patients with NMOSD and 124 patients with RRMS (mean duration NMOSD=5.8±1.9 (1.9-9.9) years, RRMS=5.2±1.7 (1.5-9.2) years). Deep learning was used to learn 'brain age' from MRI scans in the healthy controls and estimate the brain age gap (BAG) in patients. RESULTS: A significantly higher BAG was found in the NMOSD (5.4±8.2 years) and RRMS (13.0±14.7 years) groups compared with healthy controls. A higher baseline disability score and advanced brain volume loss were associated with increased BAG in both patient groups. A longer disease duration was associated with increased BAG in RRMS. BAG significantly predicted Expanded Disability Status Scale worsening in patients with NMOSD and RRMS. CONCLUSIONS: There is a clear BAG in NMOSD, although smaller than in RRMS. The BAG is a clinically relevant MRI marker in NMOSD and RRMS.

Effectiveness and comparative effectiveness of evidence-based psychotherapies for posttraumatic stress disorder in clinical practice.

BACKGROUND: While evidence-based psychotherapy (EBP) for posttraumatic stress disorder (PTSD) is a first-line treatment, its real-world effectiveness is unknown. We compared cognitive processing therapy (CPT) and prolonged exposure (PE) each to an individual psychotherapy comparator group, and CPT to PE in a large national healthcare system. METHODS: We utilized effectiveness and comparative effectiveness emulated trials using retrospective cohort data from electronic medical records. Participants were veterans with PTSD initiating mental healthcare (N = 265 566). The primary outcome was PTSD symptoms measured by the PTSD Checklist (PCL) at baseline and 24-week follow-up. Emulated trials were comprised of 'person-trials,' representing 112 discrete 24-week periods of care (10/07-6/17) for each patient. Treatment group comparisons were made with generalized linear models, utilizing propensity score matching and inverse probability weights to account for confounding, selection, and non-adherence bias. RESULTS: There were 636 CPT person-trials matched to 636 non-EBP person-trials. Completing ⩾8 CPT sessions was associated with a 6.4-point greater improvement on the PCL (95% CI 3.1-10.0). There were 272 PE person-trials matched to 272 non-EBP person-trials. Completing ⩾8 PE sessions was associated with a 9.7-point greater improvement on the PCL (95% CI 5.4-13.8). There were 232 PE person-trials matched to 232 CPT person-trials. Those completing ⩾8 PE sessions had slightly greater, but not statistically significant, improvement on the PCL (8.3-points; 95% CI 5.9-10.6) than those completing ⩾8 CPT sessions (7.0-points; 95% CI 5.5-8.5). CONCLUSIONS: PTSD symptom improvement was similar and modest for both EBPs. Although EBPs are helpful, research to further improve PTSD care is critical.

Update to the Newly Developed Expression for the Stability Ratio of Colloidal Dispersions.

The colloidal stability, one of the basic and important properties of a colloidal dispersion, is commonly evaluated in terms of the stability ratio. In this study, a recently developed expression for the stability ratio is updated, by reformulating the fraction of successful collisions leading to secondary minimum coagulation. The updated formula reinterprets the statistical meaning of the fraction of successful collisions leading to primary or secondary minimum coagulation, ensuring that the total fraction of successful collisions is always less than or equals to 1. It was shown to be superior to the available expressions in accounting for the contribution of the primary and secondary minimum coagulations on the stability ratio. It can well interpret the stability of colloidal dispersions of spherical particles; moreover, it is of great potential to be applied to colloidal dispersions of plate-like particles. In addition, this formula is found to be consistent with the concept of the critical coagulation concentration and well interpret the effects of particle size, counterion valence, surface potential, and Hamaker constant on the colloidal stability.

LINC02870 facilitates SNAIL translation to promote hepatocellular carcinoma progression.

Exploring the roles of long noncoding RNAs (lncRNAs) in tumorigenesis and metastasis could contribute to the recognition of novel diagnostic and therapeutic targets. LINC02870 is a novel lncRNA, whose role in tumors has not been reported. Herein, we focused on the function and mechanism of LINC02870 in human hepatocellular carcinoma (HCC). We first carried out a pan-cancer study of LINC02870 expression and its relationship to prognosis, and LINC02870 was determined to be a possible oncogene in HCC. Upregulated expressions of LINC02870 were also found in our HCC samples compared to the para-tumor samples. Moreover, overexpression of LINC02870 promoted the growth, migration, and invasion of HCC cells. Subsequently, binding proteins of LINC02870 were identified by a number of in silico analyses, including correlation analysis, signaling network analysis, and survival analysis. Intriguingly, the most promising binding protein of LINC02870 was predicted and confirmed to be eukaryotic translation initiation factor 4 gamma 1 (EIF4G1), an important component of the eukaryotic translation initiation factor 4F complex that initiates cap-dependent translation. Further investigation showed that LINC02870 increased the translation of SNAIL to induce malignant phenotypes in HCC cells. Additionally, HCC patients with higher expression levels of LINC02870 and EIF4G1 had shorter survival times than those with lower expression levels. Thus, our findings suggested that LINC02870 induced SNAIL translation and correlated with poor prognosis and tumor progression in HCC.