Electron, hole, and energy transfer dynamics in non-fullerene small-molecule acceptors.

When photoexcited, an organic photovoltaic (OPV) donor/acceptor (D/A) blend is expected to undergo charge separation (CS) through three channels: electron transfer, hole transfer, and energy transfer-induced electron/hole transfer. However, previous spectroscopic studies on various blends based on non-fullerene acceptors (NFAs) have not been able to directly characterize the dynamics of these processes, due to spectral overlap of the involved intermediate species. Herein, we study the excited-state dynamics of D/A blends composed of PBDB-T (D) and a L-series NFA (L4 or L5) and show that the species responsible for these processes in the PBDB-T/L4 blend can be spectroscopically identified, allowing us to disentangle their dynamics. Moreover, we confirm the occurrence of photoinduced CS in neat L4 and L5 films, providing direct evidence that CS can occur under nearly zero driving force in OPV systems. Further density functional theory calculations suggest that specific molecular packing patterns may play an important role in facilitating CS.

Excellent Barocaloric Effect by Modulating Geometrical Frustrations in Mn3Pt.

Barocaloric materials hold great promise for next-generation solid-state cooling devices because of their green and efficient cooling performance. The insights into low-pressure-driven barocaloric materials are expected to pave the way for the widespread application of barocaloric refrigeration technology. Here, we reveal the low-pressure-driven large barocaloric effect (BCE) modulated by geometrical frustrations in Mn3Pt. The highest sensitivity to pressure of Mn3Pt in metal BCE materials results in an excellent temperature-change strength of 9.77 K 100-1 MPa-1. Neutron powder diffraction and first-principles calculations point out the dual effect of geometrical frustration on modulating the unusual BCE, which not only induces giant volume expansion by inspiring strong spin fluctuation and magnetic moment but also enhances the sensitivity of magnetic phase transition. The model of the dual effect of geometrical frustration in magnets with geometrical frustration is established, which will promote the research progress of barocaloric refrigeration devices.

The exciton dynamics and charge transfer in polymers with the effects of chlorine substituents.

Donor-acceptor (D-A) type conjugated polymers, particularly those with electron-withdrawing halogen substituents, have demonstrated high efficiency as donor materials in solar energy conversion. In our previous work, we have successfully synthesized three low-cost D-A type conjugated polymers (designated as PJ-1, PJ-2, and PJ-3) through a gradual chlorination process, of which, devices based on PJ-1 exhibited exceptional power conversion efficiency (15.01%) and figure-of-merit values (45.48). In this study, we further investigated the excited-state dynamics of the three donor polymers by transient absorption spectroscopy to explore the dynamic reasons behind the high power conversion efficiency of PJ-1. Our findings revealed that PJ-1 exhibited pronounced aggregation, which facilitated intermolecular interactions, thereby enhancing charge transport capability and suppressing trap-assisted recombination. Furthermore, the PJ-1-based heterojunction presented efficient exciton dissociation and enhanced hole transfer efficiency. These results underscore the potential of chlorine substitution in improving exciton dissociation and charge transfer via regulating aggregation behavior and energy level, offering a straightforward and effective approach to engineer high-performance conjugated polymer donor materials for photovoltaic applications.

Insulin-like growth factor-2 mRNA-binding protein 2 facilitates post-ischemic angiogenesis by increasing the stability of fibroblast growth factor 2 mRNA and its protein expression.

Background: Post-ischemic angiogenesis is crucial for reestablishing blood flow in conditions such as peripheral artery disease (PAD). The role of insulin-like growth factor-2 mRNA-binding protein 2 (IGF2BP2) in post-transcriptional RNA metabolism and its involvement in post-ischemic angiogenesis remains unclear. Methods: Using a human GEO database and a hind-limb ischemia (HLI) mouse model, the predominant isoform IGF2BP2 in ischemic gastrocnemius tissue was identified. Adeno-associated virus with the Tie1 promoter induced IGF2BP2 overexpression in the HLI model, evaluating the expression of vascular structural proteins (CD31 and α-SMA) and blood flow recovery after HLI. In vitro experiments with human umbilical vein endothelial cells (HUVECs) demonstrated that lentivirus-mediated IGF2BP2 overexpression upregulates cell proliferation, migration, and tube formation. GeneCards, RNAct databases, and subsequent reverse transcription quantitative polymerase chain reaction (RT-qPCR) predicted IGF2BP2 interactions with fibroblast growth factor 2 (FGF2) mRNA, and actinomycin D treatment, binding site predictions and CLIP-seq data further confirmed this interaction. Furthermore, western blotting, enzyme-linked immunosorbent assay, and RNA immunoprecipitation followed by RT-qPCR were performed to validate IGF2BP2's interaction with FGF2 mRNA and to assess its role in stabilizing FGF2 mRNA, as well as its impact on FGF2 protein expression. Results: HLI reduced IGF2BP2 expression in the gastrocnemius tissue, which gradually increased during blood flow recovery. IGF2BP2 overexpression in HLI mice accelerated blood flow recovery and increased capillary and small artery densities. The overexpression of IGF2BP2 in HUVECs stimulated proliferation, migration, and tube formation by interacting with FGF2 mRNA to increase its stability. This interaction resulted in increased levels of FGF2 protein and secretion, ultimately promoting angiogenesis. Conclusions: IGF2BP2 contributes to blood flow restoration post-ischemia in vivo and promotes angiogenesis in HUVECs by enhancing FGF2 mRNA stability and FGF2 protein expression and secretion. These findings underscore IGF2BP2's therapeutic potential in ischemic conditions, such as PAD.

Blood-brain barrier breakdown in dementia with Lewy bodies.

BACKGROUND: Blood-brain barrier (BBB) dysfunction has been viewed as a potential underlying mechanism of neurodegenerative disorders, possibly involved in the pathogenesis and progression of Alzheimer's disease (AD). However, a relation between BBB dysfunction and dementia with Lewy bodies (DLB) has yet to be systematically investigated. Given the overlapping clinical features and neuropathology of AD and DLB, we sought to evaluate BBB permeability in the context of DLB and determine its association with plasma amyloid-ß (Aß) using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). METHODS: For this prospective study, we examined healthy controls (n = 24, HC group) and patients diagnosed with AD (n = 29) or DLB (n = 20) between December 2020 and April 2022. Based on DCE-MRI studies, mean rates of contrast agent transfer from intra- to extravascular spaces (Ktrans) were calculated within regions of interest. Spearman's correlation and multivariate linear regression were applied to analyze associations between Ktrans and specific clinical characteristics. RESULTS: In members of the DLB (vs HC) group, Ktrans values of cerebral cortex (p = 0.024), parietal lobe (p = 0.007), and occipital lobe (p = 0.014) were significantly higher; and Ktrans values of cerebral cortex (p = 0.041) and occipital lobe (p = 0.018) in the DLB group were significantly increased, relative to those of the AD group. All participants also showed increased Ktrans values of parietal ( ß  = 0.391; p = 0.001) and occipital ( ß  = 0.357; p = 0.002) lobes that were significantly associated with higher scores of the Clinical Dementia Rating, once adjusted for age and sex. Similarly, increased Ktrans values of cerebral cortex ( ß  = 0.285; p = 0.015), frontal lobe ( ß  = 0.237; p = 0.043), and parietal lobe ( ß = 0.265; p = 0.024) were significantly linked to higher plasma Aß1-42/Aß1-40 ratios, after above adjustments. CONCLUSION: BBB leakage is a common feature of DLB and possibly is even more severe than in the setting of AD for certain regions of the brain. BBB leakage appears to correlate with plasma Aß1-42/Aß1-40 ratio and dementia severity.

A novel method to reconstruct the complex facial nerve defect after extended parotidectomy with masseteric nerve and descending hypoglossal nerve.

This study aims to present a novel technique for reconstructing complex facial nerve defects using the masseteric nerve and descending hypoglossal nerve. Here, we report a case involving a patient with locally advanced parotid malignancy who underwent extended parotidectomy with resection of the invaded facial nerve. Following tumor resection, the proximal end of the facial nerve was inaccessible, leading to the formation of multiple distal branch defects. Subsequently, we performed reconstruction of the complex facial nerve defect using the masseteric nerve for the zygomatic and upper buccal branches and the descending hypoglossal nerve for the lower buccal and submandibular branches. There were no significant operative or post-operative complications observed. Upon 18 months of follow-up, the facial function of the patient had been restored to House-Brackmann-III grade. In conclusion, this dual nerve transposition approach proves to be an effective method for reconstructing complex facial nerve defects subsequent to extended parotidectomy.

Functional reconstruction of tissue defects after total parotidectomy using a modified submandibular gland flap.

OBJECTIVE: Reconstruction of soft tissue defects after total parotidectomy requires a feasible and effective pedicled flap with sufficient volume. In this study, we introduce a modified submandibular gland flap (SMGF) for functional reconstruction of soft tissue defects resulting from total parotidectomy. MATERIALS AND METHODS: This study included 12 patients diagnosed with parotid gland carcinoma undergoing total parotidectomy and ipsilateral selective neck dissection. The modified SMGF was harvested and transferred to the parotid bed. This procedure was coupled with anastomosis between the parotid gland duct and Wharton's duct. The feasibility of the surgery, postoperative complications, facial profile restoration, and salivary secretion were assessed. RESULTS: All SMGFs pedicled only over the proximal facial artery survived without major complications. Facial profiles were well-restored, and salivary secretion was partially reserved. During the postoperative follow-up, no tumor recurrence was observed in any of the cases, and the volume of the SMGFs did not show obvious atrophy. CONCLUSIONS: The modified SMGF is a viable solution for volume restoration and functional reconstruction after total parotidectomy. CLINICAL RELEVANCE: This modified technique is simple and feasible for the functional reconstruction of soft tissue defects after total parotidectomy compared to other flaps and is worthy of clinical promotion.

A platelet-related signature for predicting the prognosis and immunotherapy benefit in bladder cancer based on machine learning combinations.

Background: Bladder cancer carries a large societal burden, with over 570,000 newly diagnosed cases and 210,000 deaths globally each year. Platelets play vital functions in tumor progression and therapy benefits. We aimed to construct a platelet-related signature (PRS) for the clinical outcome of bladder cancer cases. Methods: Ten machine learning techniques were used in the integrative operations to build PRS using the datasets from The Cancer Genome Atlas (TCGA), gene series expression (GSE)13507, GSE31684, GSE32894 and GSE48276. A number of immunotherapy datasets and prediction scores, including GSE91061, GSE78220, and IMvigor210, were utilized to assess how well the PRS predicted the benefit of immunotherapy. Vitro experiment was performed to verify the role of α1C-tubulin (TUBA1C) in bladder cancer. Results: Enet (alpha =0.4) algorithm-based PRS had the highest average C-index of 0.73 and it was suggested as the optimal PRS. PRS acted as an independent risk factor for bladder cancer and patients with high PRS score portended a worse overall survival rate, with the area under the curve of 1-, 3- and 5-year operating characteristic curve being 0.754, 0.779 and 0.806 in TCGA dataset. A higher level of immune-activated cells, cytolytic function and T cell co-stimulation was found in the low PRS score group. Low PRS score demonstrated a higher tumor mutation burden score and programmed cell death protein 1 & cytotoxic T-lymphocyte associated protein 4 immunophenoscore, lower tumor immune dysfunction and exclusion score, intratumor heterogeneity score and immune escape score in bladder cancer, suggesting the PRS as an indicator for predicting immunotherapy benefits. Vitro experiment showed that TUBA1C was upregulated in bladder cancer and knockdown of TUBA1C obviously suppressed tumor cell proliferation. Conclusions: The present study developed an ideal PRS for bladder cancer, which may be used as a predictor of prognosis, a risk classification system, and a therapy guide.

Machine learning-based analysis of Ebola virus' impact on gene expression in nonhuman primates.

Introduction: This study introduces the Supervised Magnitude-Altitude Scoring (SMAS) methodology, a novel machine learning-based approach for analyzing gene expression data from non-human primates (NHPs) infected with Ebola virus (EBOV). By focusing on host-pathogen interactions, this research aims to enhance the understanding and identification of critical biomarkers for Ebola infection. Methods: We utilized a comprehensive dataset of NanoString gene expression profiles from Ebola-infected NHPs. The SMAS system combines gene selection based on both statistical significance and expression changes. Employing linear classifiers such as logistic regression, the method facilitates precise differentiation between RT-qPCR positive and negative NHP samples. Results: The application of SMAS led to the identification of IFI6 and IFI27 as key biomarkers, which demonstrated perfect predictive performance with 100% accuracy and optimal Area Under the Curve (AUC) metrics in classifying various stages of Ebola infection. Additionally, genes including MX1, OAS1, and ISG15 were significantly upregulated, underscoring their vital roles in the immune response to EBOV. Discussion: Gene Ontology (GO) analysis further elucidated the involvement of these genes in critical biological processes and immune response pathways, reinforcing their significance in Ebola pathogenesis. Our findings highlight the efficacy of the SMAS methodology in revealing complex genetic interactions and response mechanisms, which are essential for advancing the development of diagnostic tools and therapeutic strategies. Conclusion: This study provides valuable insights into EBOV pathogenesis, demonstrating the potential of SMAS to enhance the precision of diagnostics and interventions for Ebola and other viral infections.

Constructing Multiscale Fibrous Morphology to Achieve 20% Efficiency Organic Solar Cells by Mixing High and Low Molecular Weight D18.

This study underscores the significance of precisely manipulating the morphology of the active layer in organic solar cells (OSCs). By blending polymer donors of D18 with varying molecular weights, a multiscale interpenetrating fiber network structure within the active layer is successfully created. The introduction of 10% low molecular weight D18 (LW-D18) into high molecular weight D18 (HW-D18) produces MIX-D18, which exhibits an extended exciton diffusion distance and orderly molecular stacking. Devices utilizing MIX-D18 demonstrate superior electron and hole transport, improves exciton dissociation, enhances charge collection efficiency, and reduces trap-assisted recombination compared to the other two materials. Through the use of the nonfullerene acceptor L8-BO, a remarkable power conversion efficiency (PCE) of 20.0% is achieved. This methodology, which integrates the favorable attributes of high and low molecular weight polymers, opens a new avenue for enhancing the performance of OSCs.

CTsynther: Contrastive Transformer model for end-to-end retrosynthesis prediction.

Retrosynthesis prediction is a fundamental problem in organic chemistry and drug synthesis. We proposed an end-to-end deep learning model called CTsynther (Contrastive Transformer for single-step retrosynthesis prediction model) that could provide single-step retrosynthesis prediction without external reaction templates or specialized knowledge. The model introduced the concept of contrastive learning in Transformer architecture and employed a contrastive learning language representation model at the SMILES sentence level to enhance model inference by learning similarities and differences between various samples. Mixed global and local attention mechanisms allow the model to capture features and dependencies between different atoms to improve generalization. We further investigated the embedding representations of SMILES learned automatically from the model. Visualization results show that the model could effectively acquire information about identical molecules and improve prediction performance. Experiments showed that the accuracy of retrosynthesis reached 53.5% and 64.4% for with and without reaction types, respectively. The validity of the predicted reactants is improved, showing competitiveness compared with semi-template methods.

RG108 attenuates acute kidney injury by inhibiting P38 MAPK/FOS and JNK/JUN pathways.

Acute kidney injury (AKI) is an important clinical syndrome characterised by a sudden decline in renal function, often accompanied by renal inflammation and tubular epithelial cell damage. It has been reported that inhibiting DNA methylation significantly suppress the progression of AKI. In the current study, we investigate the effect of the DNA methyltransferase (DNMT) inhibitor RG108 in cisplatin- and hypoxia-reoxygenation-induced AKI. The expression of kidney injury molecules and inflammatory factors was examined by immunofluorescence, Western blotting and Real-time PCR. The results demonstrated that RG108 treatment significantly reduced kidney inflammation and injury. Furthermore, RNA-seq analysis was performed to reveal the regulatory mechanism of RG108 in AKI. The expression of the FOS and JUN genes, which are downstream of the MAPK pathway, were significant increased in AKI. Meanwhile, the expression of FOS and JUN were both inhibited by RG108, which is similar to what we found treatment with a specific JNK inhibitor and a specific p38 MAPK inhibitor, and thus attenuated renal inflammation and injury. In conclusion, we suggest that RG108 inhibits P38 MAPK/FOS and JNK/JUN pathways and attenuates renal injury and inflammatory responses. In these results, RG108 may become a novel MAPK pathway inhibitor and a clinical candidate for the treatment of AKI.

Reinforcement learning-driven exploration of peptide space: accelerating generation of drug-like peptides.

Using amino acid residues in peptide generation has solved several key problems, including precise control of amino acid sequence order, customized peptides for property modification, and large-scale peptide synthesis. Proteins contain unknown amino acid residues. Extracting them for the synthesis of drug-like peptides can create novel structures with unique properties, driving drug development. Computer-aided design of novel peptide drug molecules can solve the high-cost and low-efficiency problems in the traditional drug discovery process. Previous studies faced limitations in enhancing the bioactivity and drug-likeness of polypeptide drugs due to less emphasis on the connection relationships in amino acid structures. Thus, we proposed a reinforcement learning-driven generation model based on graph attention mechanisms for peptide generation. By harnessing the advantages of graph attention mechanisms, this model effectively captured the connectivity structures between amino acid residues in peptides. Simultaneously, leveraging reinforcement learning's strength in guiding optimal sequence searches provided a novel approach to peptide design and optimization. This model introduces an actor-critic framework with real-time feedback loops to achieve dynamic balance between attributes, which can customize the generation of multiple peptides for specific targets and enhance the affinity between peptides and targets. Experimental results demonstrate that the generated drug-like peptides meet specified absorption, distribution, metabolism, excretion, and toxicity properties and bioactivity with a success rate of over 90$\%$, thereby significantly accelerating the process of drug-like peptide generation.

Altered Resting-State Electroencephalogram Microstate Characteristics in Stroke Patients.

BACKGROUND: Stroke remains a leading cause of disability globally and movement impairment is the most common complication in stroke patients. Resting-state electroencephalography (EEG) microstate analysis is a non-invasive approach of whole-brain imaging based on the spatiotemporal pattern of the entire cerebral cortex. The present study aims to investigate microstate alterations in stroke patients. METHODS: Resting-state EEG data collected from 24 stroke patients and 19 healthy controls matched by age and gender were subjected to microstate analysis. For four classic microstates labeled as class A, B, C and D, their temporal characteristics (duration, occurrence and coverage) and transition probabilities (TP) were extracted and compared between the two groups. Furthermore, we explored their correlations with clinical outcomes including the Fugl-Meyer assessment (FMA) and the action research arm test (ARAT) scores in stroke patients. Finally, we analyzed the relationship between the temporal characteristics and spectral power in frequency bands. False discovery rate (FDR) method was applied for correction of multiple comparisons. RESULTS: Microstate analysis revealed that the stroke group had lower occurrence of microstate A which was regarded as the sensorimotor network (SMN) compared with the control group (p = 0.003, adjusted p = 0.036, t = -2.959). The TP from microstate A to microstate D had a significant positive correlation with the Fugl-Meyer assessment of lower extremity (FMA-LE) scores (p = 0.049, r = 0.406), but this finding did not survive FDR adjustment (adjusted p = 0.432). Additionally, the occurrence and the coverage of microstate B were negatively correlated with the power of delta band in the stroke group, which did not pass adjustment (p = 0.033, adjusted p = 0.790, r = -0.436; p = 0.026, adjusted p = 0.790, r = -0.454, respectively). CONCLUSIONS: Our results confirm the abnormal temporal dynamics of brain activity in stroke patients. The study provides further electrophysiological evidence for understanding the mechanism of brain motor functional reorganization after stroke.

Study on the Adsorption Law of n-Pentane in Silica Slit Nanopores.

As the main components of shale, inorganic minerals are important carriers for oil and gas adsorption, whose pore structures and surface properties have significant effects on the fluid adsorption capacity. In this study, slit nanopores (SNPs) were constructed by silica. To investigate the microscopic adsorption law of n-pentane in silica, the grand canonical Monte Carlo (GCMC) method was used to simulate the adsorption behaviors of n-pentane in silica nanoparticles. The effects of different surface wettability, pore size, temperature, and pressure values on the adsorption behavior of pentane were discussed, revealing the micro adsorption mechanism of pentane in silica with different pore sizes and wettability and evaluating the degree of oil and gas utilization. The research results indicate that the adsorption capacity of pentane is greatly affected by the temperature under low-pressure conditions. With the increase of the pore size, the adsorption capacity of pentane increases linearly, and the number of adsorbed pentane molecules gradually decreases. The availability of oil and gas increases, and the oil and gas are more easily extracted. As the surface hydrophobicity of minerals increases, the van der Waals force between minerals and pentane also increases, leading to an increase in the number of adsorbed states of pentane. The stronger the hydrophilicity of the wall, the fewer the pentane molecules adsorbed on the surface, which would improve the efficiency of oil and gas extraction. This study provides potential for the development of novel surfactants based on adsorption selectivity.

Cadmium exposure induces skeletal muscle insulin resistance through the reactive oxygen species-mediated PINK1/Parkin pathway.

Epidemiological studies have suggested a positive association between environmental cadmium (Cd) exposure and type 2 diabetes mellitus (T2DM). Skeletal muscle insulin resistance (IR) plays a critical role in the pathogenesis of T2DM. This study aimed to investigate the effects of chronic low-level Cd exposure on skeletal muscle IR and its potential mechanism. Rats were exposed to drinking water containing 2 or 10 mg/L Cd for 24 weeks. Differentiated L6 myotubes were treated with Cd for 72 h. Immunofluorescence, flow cytometry assay, RNA-sequencing, and Seahorse analysis were conducted to determine the effects of Cd and its underlying mechanism on relevant parameters, including insulin sensitivity, glucose uptake, oxidative stress, mitophagy, and mitochondrial function in skeletal muscle and L6 myotubes. N-acetyl-cysteine (NAC), a scavenger of reactive oxygen species (ROS), and mitophagy inhibitor Cyclosporin A (CsA) were used to confirm the role of oxidative stress in mitophagy and mitochondrial dysfunction caused by Cd. We found that rats exposed to 10 mg/L Cd exhibited hyperglycemia and skeletal muscle IR. Cd markedly increased IRS-1 phosphorylation at Ser612, while decreased levels of phosphorylated PI3K, Akt, AS160, inhibited GLUT4 translocation and glucose uptake. Mechanistically, Cd increased the intracellular ROS, hydrogen peroxide, and malondialdehyde levels and decreased antioxidase activity in L6 myotubes. Furthermore, Cd upregulated the mRNA and protein levels of LC3II/I, PINK1, and Parkin. In addition, Cd induced the formation of mitophagosomes, reduced the mitochondrial membrane potential, decreased the adenosine triphosphate content, and impaired the mitochondrial respiratory capacity. Strikingly, NAC ameliorated oxidative stress, excessive mitophagy, and the associated reduction in myotube insulin sensitivity, while inhibition of mitophagy by CsA alleviated skeletal muscle IR. In conclusion, this study reveals a previously unrecognized mechanism that chronic low-level Cd exposure may induce mitophagy by activating the PINK1/Parkin signal pathway by increasing ROS, thus causing skeletal muscle IR and elevated blood glucose.

Spock2 Functions as a Key Time-Series Gene of Endothelial Cells in Sepsis-Induced Cardiomyopathy.

ABSTRACT: The study aimed to investigate the pathogenesis of sepsis-induced cardiomyopathy, a leading cause of mortality in septic patients. Transcriptome data from cecal ligation and puncture-induced septic mice were analyzed at different time points (24, 48, and 72 hours) using GSE171546 data. Through weighted gene co-expression network analysis, time series, and differential expression analyses, key time-series differentially expressed genes were identified. In addition, single-cell sequencing data (GSE207363) were used for both differential and pseudotime analyses to pinpoint differentially expressed genes specific to endothelial cells. The study highlighted Spock2, S100a9, S100a8, and Xdh as differential genes specific to endothelial cells in a time-dependent manner. Immunofluorescence validation confirmed the increased expression of SPOCK2 in the endothelial cells of cecal ligation and puncture-induced septic mice. Furthermore, in vitrostudies showed that deletion of Spock2 significantly increased LPS-induced apoptosis and necrosis in human umbilical vein endothelial cells. In conclusion, SPOCK2 expression was increased in septic cardiac endothelial cells and LPS-induced human umbilical vein endothelial cells and may play a protective role.

Altered Brain Functional and Effective Connectivity Induced by Electroacupuncture in Rats Following Anterior Cruciate Ligament Transection.

Background: The chronic pain arising from knee osteoarthritis (KOA) is a prevalent clinical manifestation. As a traditional Chinese approach, electroacupuncture (EA) has a positive influence in relieving chronic pain from KOA. The study aims to explore functional connectivity (FC) and effective connectivity (EC) alterations induced by EA in anterior cruciate ligament transection (ACLT) rat model of KOA using resting-state functional magnetic resonance imaging (fMRI). Methods: After the establishment of ACLT, rats were randomly divided into the EA group and the sham-EA group. The EA group received EA intervention while the sham-EA group received sham-intervention for 3 weeks. Mechanical pain threshold (MPT) assessment was performed before and after intervention, and fMRI was conducted after intervention. Results: EA intervention effectively relieved pain in post-ACLT rats. Results of rest-state functional connectivity (rs-FC) analysis revealed that compared with the sham-EA group, the EA group had higher FC between the right raphe and the left auditory cortex, the left caudate_ putamen and the left internal capsule (IC), as well as the right zona incerta (ZI) and the left piriform cortex, but lower FC between the right raphe and the left hippocampus ventral, as well as the right septum and the left septum. Furthermore, Granger causality analysis (GCA) found the altered EC between the right septum and the left septum, as well as the left IC and the right septum. Conclusion: The results confirmed the effect of EA on analgesia in post- ACLT rats. The alterations of FC and EC, mainly involving basal ganglia and limbic system neural connections, might be one of the neural mechanisms underlying the effect of EA, providing novel information about connectomics plasticity of EA following ACLT.

Machine learning developed an intratumor heterogeneity signature for predicting clinical outcome and immunotherapy benefit in bladder cancer.

Background: Bladder cancer is a common malignancy with high invasion and poor clinical outcome. Intratumor heterogeneity (ITH) is linked to cancer progression and metastasis and high ITH can accelerate tumor evolution. Our objective is to develop an ITH-related signature (IRS) for predicting clinical outcome and immunotherapy benefit in bladder cancer. Methods: Integrative procedure containing ten machine learning methods was applied to develop an IRS with The Cancer Genome Atlas (TCGA), gene series expression (GSE)13507, GSE31684, GSE32984 and GSE48276 datasets. To evaluate the performance of IRS in predicting the immunotherapy benefit, we also used several predicting scores and three immunotherapy datasets, including GSE91061, GSE78220 and IMvigor210. Results: The predicting model constructed with Enet (alpha =0.2) algorithm had a highest average C-index of 0.69, which was suggested as the optimal IRS. As an independent risk factor for bladder cancer, IRS had a powerful performance in predicting the overall survival (OS) rate of patients, with an area under curve of 1-, 3- and 5-year receiver operating characteristic (ROC) curve being 0.744, 0.791 and 0.816 in TCGA dataset. Bladder cancer patients with low IRS score presented with a higher level of immune-activated cells, cytolytic function and T cell co-stimulation. We also found a lower tumor immune dysfunction and exclusion (TIDE) score, lower immune escape score, higher programmed cell death protein 1 (PD-1) & cytotoxic T-lymphocyte associated protein 4 immunophenoscore, higher tumor mutation burden (TMB) score, higher response rate and better prognosis in bladder cancer with low IRS score. Bladder cancer cases with high IRS score had a higher half maximal inhibitory concentration value of common chemotherapy and targeted therapy regimens. Conclusions: The current study developed an optimal IRS for bladder cancer patients, which acted as an indicator for predicting prognosis, stratifying risk and guiding treatment for bladder cancer patients. Further analysis should be focused on the exploration the differentially expressed genes (DEGs) and related underlying mechanism mediating the development of bladder cancer in different IRS score group.