MARK2 variants cause autism spectrum disorder via the downregulation of WNT/ß-catenin signaling pathway.

Microtubule affinity-regulating kinase 2 (MARK2) contributes to establishing neuronal polarity and developing dendritic spines. Although large-scale sequencing studies have associated MARK2 variants with autism spectrum disorder (ASD), the clinical features and variant spectrum in affected individuals with MARK2 variants, early developmental phenotypes in mutant human neurons, and the pathogenic mechanism underlying effects on neuronal development have remained unclear. Here, we report 31 individuals with MARK2 variants and presenting with ASD, other neurodevelopmental disorders, and distinctive facial features. Loss-of-function (LoF) variants predominate (81%) in affected individuals, while computational analysis and in vitro expression assay of missense variants supported the effect of MARK2 loss. Using proband-derived and CRISPR-engineered isogenic induced pluripotent stem cells (iPSCs), we show that MARK2 loss leads to early neuronal developmental and functional deficits, including anomalous polarity and dis-organization in neural rosettes, as well as imbalanced proliferation and differentiation in neural progenitor cells (NPCs). Mark2+/- mice showed abnormal cortical formation and partition and ASD-like behavior. Through the use of RNA sequencing (RNA-seq) and lithium treatment, we link MARK2 loss to downregulation of the WNT/ß-catenin signaling pathway and identify lithium as a potential drug for treating MARK2-associated ASD.

Mechanical response analysis of primary support for shallow buried loess tunnel under surface surcharge.

At present, the research on the influence of surrounding soil deformation induced by tunnel construction under the action of surcharge is generally based on the situation after the tunnel has been built, and less consideration is given to the existence of surface surcharge near the planned route of the tunnel when the tunnel is not built. Therefore, based on the Luochuan tunnel under construction, this study monitors the deformation of shallowly buried loess tunnels under different surcharge conditions and analyzes the influence of varying surcharge conditions on the deformation and stress of the tunnel through numerical simulation to determine the effective range of surface surcharge. The results show that the influence of surcharge load on tunnel stability is the most significant when located at the tunnel axis, and the influence degree increases with the increase of load. The adverse effects of surcharge load mainly occur in the range of 2 times the tunnel diameter. Once the range is exceeded, the internal force of the tunnel support structure is not sensitive to the surcharge load. In engineering, the surface surcharge can be controlled within the safety displacement limit by referring to the displacement calculation results.

Phenotypic and genotypic characteristics of children with PCDH19 clustering epilepsy in China.

PURPOSE: PCDH19 gene variants, termed PCDH19 clustering epilepsy, represent a distinct etiology of epilepsy. This study aimed to elucidate the clinical manifestations and explore the genotypes and phenotypes of children affected by PCDH19 clustering epilepsy. METHODS: This retrospective study included medical history, magnetic resonance imaging, video-electroencephalography, and genetic analysis of patients diagnosed with PCDH19 Clustering Epilepsy at the Neurology Department of Beijing Children's Hospital from 2015 to 2023. Chi-square tests and logistic regression analyses were conducted to study the factors associated with developmental delay in patients. RESULTS: The age at seizure onset ranged from 5 to 61 months among all 30 patients (median 14 months; IQR 9.25-22.5 months). Among the 30 patients, 29 were female and 1 was male. Clusters of seizures and fever-triggered seizures were observed, with the most prevalent seizure types being focal to bilateral tonic-clonic seizures (FBTCS). Seizures were successfully controlled in 15 patients. Unfortunately, one patient experienced a sudden unexpected death in epilepsy (SUDEP). Additionally, 14 patients had hereditary mutations, 14 had de novo mutations, 1 had both hereditary and de novo mutations, and 1 male patient had a mosaic component mutation of 0.64 due to a somatic mutation. Developmental delays were identified in 17 patients (56.7 %), and 6 patients (20 %) were diagnosed with autism spectrum disorder (ASD). Among the 17 patients, 9 experienced developmental delays before the onset of epilepsy, while 8 were initially normal but later developed developmental delays during disease progression. Statistical analysis revealed that the presence of drug-resistant epilepsy was an independent risk factor for the occurrence of developmental delays (P = 0.020, OR = 9.758, 95 % CI (1.440-66.111)). CONCLUSION: In this study, 13 new potential rare pathogenic variations in PCDH19 clustering epilepsy were identified. The clinical features observed in patients are consistent with known phenotypic features, and we found that patients with drug-resistant epilepsy are more likely to have developmental delays. The severity of the phenotype in patients with PCDH19 variants ranged from drug-responsive seizures to refractory epilepsy.

BertTCR: a Bert-based deep learning framework for predicting cancer-related immune status based on T cell receptor repertoire.

The T cell receptor (TCR) repertoire is pivotal to the human immune system, and understanding its nuances can significantly enhance our ability to forecast cancer-related immune responses. However, existing methods often overlook the intra- and inter-sequence interactions of T cell receptors (TCRs), limiting the development of sequence-based cancer-related immune status predictions. To address this challenge, we propose BertTCR, an innovative deep learning framework designed to predict cancer-related immune status using TCRs. BertTCR combines a pre-trained protein large language model with deep learning architectures, enabling it to extract deeper contextual information from TCRs. Compared to three state-of-the-art sequence-based methods, BertTCR improves the AUC on an external validation set for thyroid cancer detection by 21 percentage points. Additionally, this model was trained on over 2000 publicly available TCR libraries covering 17 types of cancer and healthy samples, and it has been validated on multiple public external datasets for its ability to distinguish cancer patients from healthy individuals. Furthermore, BertTCR can accurately classify various cancer types and healthy individuals. Overall, BertTCR is the advancing method for cancer-related immune status forecasting based on TCRs, offering promising potential for a wide range of immune status prediction tasks.

Genotype and Phenotype Characteristics of 58 Cases of Mitochondrial Epilepsy with Nuclear DNA Mutations in Children.

OBJECTIVE: Identify the genotype and clinical characteristics of mitochondrial epilepsy caused by nDNA mutations in Chinese children and explore the treatment and prognosis of the condition. STUDY DESIGN: This is a retrospective cohort study conducted at a single center, including patients diagnosed with an established nDNA mutation-associated primary mitochondrial disease between October 2012 and March 2023 who also met the practical clinical definition of epilepsy published by the ILAE in 2014. RESULTS: Of the 58 patients identified, 74.1% had an onset before the age of 1 year and 63.8% had seizures as their initial symptom. Developmental and epileptic encephalopathy (DEE) (31%) are the most common phenotypes. The most frequently observed MRI abnormalities include abnormal signal asymmetry in the bilateral basal ganglia and/or brainstem (34.7%), as well as brain atrophy, myelin sheath dysplasia, and corpus callosum dysplasia (32.7%). Of the 40 patients followed, seizure treatment was effective in 18 of the cases, while it was ineffective in 22. The mitochondrial DNA depletion syndrome (MDS) was found to be more difficult to control seizures than other phenotypes (P < 0.05). Additionally, the MDS was associated with a significantly higher mortality rate compared to alternative phenotypes (P < 0.05). CONCLUSIONS: The onset of mitochondrial epilepsy due to nDNA mutations is early and seizures are the most common initial symptom. DEE is the most common phenotype. Characteristic MRI abnormalities in the brain may be helpful in the diagnosis of primary mitochondrial disease. People with MDS typically face challenges in seizure control and have a poor prognosis.

Metabolites isolated from Penicillium HDS-Z-1E, an endophytic fungal strain isolated from Taxus cuspidata and their activation effect of catalase.

Objective: To study the compounds isolated from Penicillium HDS-Z-1E, an endophytic fungal strain isolated from Taxus cuspidata and their activation effect of catalase (CAT). Methods: The chemical constituents were isolated from Penicillium HDS-Z-1E, by using silica gel, Sephadex LH-20 and HPLC. The structural elucidations of five metabolites were elucidated on the basis of spectroscopic including 1H-NMR, 13C-NMR, HMBC and HSQC. Their activation sites of catalase have been investigated by molecular docking. Results: Five metabolites, compounds (1-5) were isolated from Penicillium HDS-Z-1E and identified as 4-hydroxy-4-methyltetrahydro-2H-pyran-2-one (1), 4-hydroxymethyl-5, 6-dihydro-pyran-2-one (2), 5, 6-dihydro-2-oxo-2H-pyran-4-carboxylic (3), N-acetyl-hydrazinobenzoic acid (4), and methyl 2-(2, 5-dihydroxyphenyl) acetate (5). Conclusion: Compound 3 is a new compound. Compounds 3 and 4 may have potential activators of catalase, providing a theoretical basis for the development of CAT activators.

PrCRS: a prediction model of severe CRS in CAR-T therapy based on transfer learning.

BACKGROUND: CAR-T cell therapy represents a novel approach for the treatment of hematologic malignancies and solid tumors. However, its implementation is accompanied by the emergence of potentially life-threatening adverse events known as cytokine release syndrome (CRS). Given the escalating number of patients undergoing CAR-T therapy, there is an urgent need to develop predictive models for severe CRS occurrence to prevent it in advance. Currently, all existing models are based on decision trees whose accuracy is far from meeting our expectations, and there is a lack of deep learning models to predict the occurrence of severe CRS more accurately. RESULTS: We propose PrCRS, a deep learning prediction model based on U-net and Transformer. Given the limited data available for CAR-T patients, we employ transfer learning using data from COVID-19 patients. The comprehensive evaluation demonstrates the superiority of the PrCRS model over other state-of-the-art methods for predicting CRS occurrence. We propose six models to forecast the probability of severe CRS for patients with one, two, and three days in advance. Additionally, we present a strategy to convert the model's output into actual probabilities of severe CRS and provide corresponding predictions. CONCLUSIONS: Based on our findings, PrCRS effectively predicts both the likelihood and timing of severe CRS in patients, thereby facilitating expedited and precise patient assessment, thus making a significant contribution to medical research. There is little research on applying deep learning algorithms to predict CRS, and our study fills this gap. This makes our research more novel and significant. Our code is publicly available at https://github.com/wzy38828201/PrCRS . The website of our prediction platform is: http://prediction.unicar-therapy.com/index-en.html .

A New Quinazolinone Alkaloid along with Known Compounds with Seed-Germination-Promoting Activity from Rhodiola tibetica Endophytic Fungus Penicillium sp. HJT-A-6.

A new quinazolinone alkaloid named peniquinazolinone A (1), as well as eleven known compounds, 2-(2-hydroxy-3-phenylpropionamido)-N-methylbenzamide (2), viridicatin (3), viridicatol (4), (±)-cyclopeptin (5a/5b), dehydrocyclopeptin (6), cyclopenin (7), cyclopenol (8), methyl-indole-3-carboxylate (9), 2,5-dihydroxyphenyl acetate (10), methyl m-hydroxyphenylacetate (11), and conidiogenone B (12), were isolated from the endophytic Penicillium sp. HJT-A-6. The chemical structures of all the compounds were elucidated by comprehensive spectroscopic analysis, including 1D and 2D NMR and HRESIMS. The absolute configuration at C-13 of peniquinazolinone A (1) was established by applying the modified Mosher's method. Compounds 2, 3, and 7 exhibited an optimal promoting effect on the seed germination of Rhodiola tibetica at a concentration of 0.01 mg/mL, while the optimal concentration for compounds 4 and 9 to promote Rhodiola tibetica seed germination was 0.001 mg/mL. Compound 12 showed optimal seed-germination-promoting activity at a concentration of 0.1 mg/mL. Compared with the positive drug 6-benzyladenine (6-BA), compounds 2, 3, 4, 7, 9, and 12 could extend the seed germination period of Rhodiola tibetica up to the 11th day.

Meta-DHGNN: method for CRS-related cytokines analysis in CAR-T therapy based on meta-learning directed heterogeneous graph neural network.

Chimeric antigen receptor T-cell (CAR-T) immunotherapy, a novel approach for treating blood cancer, is associated with the production of cytokine release syndrome (CRS), which poses significant safety concerns for patients. Currently, there is limited knowledge regarding CRS-related cytokines and the intricate relationship between cytokines and cells. Therefore, it is imperative to explore a reliable and efficient computational method to identify cytokines associated with CRS. In this study, we propose Meta-DHGNN, a directed and heterogeneous graph neural network analysis method based on meta-learning. The proposed method integrates both directed and heterogeneous algorithms, while the meta-learning module effectively addresses the issue of limited data availability. This approach enables comprehensive analysis of the cytokine network and accurate prediction of CRS-related cytokines. Firstly, to tackle the challenge posed by small datasets, a pre-training phase is conducted using the meta-learning module. Consequently, the directed algorithm constructs an adjacency matrix that accurately captures potential relationships in a more realistic manner. Ultimately, the heterogeneous algorithm employs meta-photographs and multi-head attention mechanisms to enhance the realism and accuracy of predicting cytokine information associated with positive labels. Our experimental verification on the dataset demonstrates that Meta-DHGNN achieves favorable outcomes. Furthermore, based on the predicted results, we have explored the multifaceted formation mechanism of CRS in CAR-T therapy from various perspectives and identified several cytokines, such as IFNG (IFN-γ), IFNA1, IFNB1, IFNA13, IFNA2, IFNAR1, IFNAR2, IFNGR1 and IFNGR2 that have been relatively overlooked in previous studies but potentially play pivotal roles. The significance of Meta-DHGNN lies in its ability to analyze directed and heterogeneous networks in biology effectively while also facilitating CRS risk prediction in CAR-T therapy.

BERT-siRNA: siRNA target prediction based on BERT pre-trained interpretable model.

Silencing mRNA through siRNA is vital for RNA interference (RNAi), necessitating accurate computational methods for siRNA selection. Current approaches, relying on machine learning, often face challenges with large data requirements and intricate data preprocessing, leading to reduced accuracy. To address this challenge, we propose a BERT model-based siRNA target gene knockdown efficiency prediction method called BERT-siRNA, which consists of a pre-trained DNA-BERT module and Multilayer Perceptron module. It applies the concept of transfer learning to avoid the limitation of a small sample size and the need for extensive preprocessing processes. By fine-tuning on various siRNA datasets after pretraining on extensive genomic data using DNA-BERT to enhance predictive capabilities. Our model clearly outperforms all existing siRNA prediction models through testing on the independent public siRNA dataset. Furthermore, the model's consistent predictions of high-efficiency siRNA knockdown for SARS-CoV-2, as well as its alignment with experimental results for PDCD1, CD38, and IL6, demonstrate the reliability and stability of the model. In addition, the attention scores for all 19-nt positions in the dataset indicate that the model's attention is predominantly focused on the 5' end of the siRNA. The step-by-step visualization of the hidden layer's classification progressively clarified and explained the effective feature extraction of the MLP layer. The explainability of model by analysis the attention scores and hidden layers is also our main purpose in this work, making it more explainable and reliable for biological researchers.

Clinical analysis of PAFAH1B1 gene variants in pediatric patients with epilepsy.

PURPOSE: PAFAH1B1, also known as LIS1, is associated with type I lissencephaly in humans, which is a severe developmental brain disorder believed to result from abnormal neuronal migration. Our objective was to characterize the genotypes and phenotypes of PAFAH1B1-related epilepsy. METHODS: We conducted a comprehensive analysis of the medical histories, magnetic resonance imaging findings, and video-electroencephalogram recordings of 11 patients with PAFAH1B1 variants at the Neurology Department of Beijing Children's Hospital from June 2017 to November 2022. RESULTS: The age of onset of epilepsy ranged from 2 months to 4 years, with a median onset age of 5 months. Among these 11 patients (comprising 6 boys and 5 girls), all were diagnosed with lissencephaly type 1. Predominantly, generalized tonic-clonic and spasm seizures characterized PAFAH1B1-related epilepsy. Additionally, 10 out of the 11 patients exhibited severe developmental disorders. All patients exhibited de novo variants, with three individuals displaying 17p13.3 deletions linked to haploinsufficiency of PAFAH1B1. Four variants were previously unreported. Notably, three patients with 17p13.3 deletions displayed developmental delay and drug resistant epilepsy, whereas the single patient with mild developmental delay, Intelligence Quotient (IQ) 57 and well-controlled seizures had a splicing-site variant. CONCLUSION: The severity of the phenotype in patients with PAFAH1B1 variants ranged from drug-responsive seizures to severe epileptic encephalopathy. These observations underscore the clinical heterogeneity of PAFAH1B1-related disorders, with most patients exhibiting developmental disorders. Moreover, the severity of epilepsy appears to be linked to genetic variations.

Corrigendum: Prediction of severe CRS and determination of biomarkers in B cell-acute lymphoblastic leukemia treated with CAR-T cells.

[This corrects the article DOI: 10.3389/fimmu.2023.1273507.].

UGT1A polymorphism rs4148324 associated with topiramate plasma concentration to dose ratio in children with epilepsy.

PURPOSE: The objective of this study is to evaluate the association between genetic polymorphisms and the concentration to dose ratio of topiramate in children with epilepsy. METHODS: A cohort of 163 pediatric patients with epilepsy receiving topiramate therapy were enrolled. The ultra-performance liquid chromatography-tandem mass spectrometry method was employed to measure the trough plasma concentration of topiramate at steady-state. These concentrations were normalized by dividing them by the ratio of total daily dose to body weight, yielding the concentration to dose ratio (CDR) of topiramate. MassArray system identified 30 single nucleotide polymorphisms associated with the pharmacokinetics and pharmacodynamics of topiramate. The CDR values were logarithmic transformed (lnCDR) for normal distribution. The association between the identified genetic polymorphisms and lnCDR was assessed using the PLINK software, employing linear regression analysis with adjustments by epilepsy types, estimated glomerular filtration rate, alanine aminotransferase, valproic acid, phenobarbital, and oxcarbazepine. RESULTS: Variant rs4148324 (UGT1A1/3/4/5/6/7/8/9/10, BETA = 0.182, P = 0.010) was significantly associated with lnCDR of topiramate. Patients carrying the G allele exhibited higher normalized topiramate plasma concentrations. No other significant associations were found. CONCLUSIONS: In pediatric patients receiving topiramate therapy, rs4148324 was associated with normalized topiramate plasma concentration. Further studies are warranted to validate and confirm the findings.

A score-based method of immune status evaluation for healthy individuals with complete blood cell counts.

BACKGROUND: With the COVID-19 outbreak, an increasing number of individuals are concerned about their health, particularly their immune status. However, as of now, there is no available algorithm that effectively assesses the immune status of normal, healthy individuals. In response to this, a new score-based method is proposed that utilizes complete blood cell counts (CBC) to provide early warning of disease risks, such as COVID-19. METHODS: First, data on immune-related CBC measurements from 16,715 healthy individuals were collected. Then, a three-platform model was developed to normalize the data, and a Gaussian mixture model was optimized with expectation maximization (EM-GMM) to cluster the immune status of healthy individuals. Based on the results, Random Forest (RF), Light Gradient Boosting Machine (LightGBM) and Extreme Gradient Boosting (XGBoost) were used to determine the correlation of each CBC index with the immune status. Consequently, a weighted sum model was constructed to calculate a continuous immunity score, enabling the evaluation of immune status. RESULTS: The results demonstrated a significant negative correlation between the immunity score and the age of healthy individuals, thereby validating the effectiveness of the proposed method. In addition, a nonlinear polynomial regression model was developed to depict this trend. By comparing an individual's immune status with the reference value corresponding to their age, their immune status can be evaluated. CONCLUSION: In summary, this study has established a novel model for evaluating the immune status of healthy individuals, providing a good approach for early detection of abnormal immune status in healthy individuals. It is helpful in early warning of the risk of infectious diseases and of significant importance.

Prediction of severe CRS and determination of biomarkers in B cell-acute lymphoblastic leukemia treated with CAR-T cells.

Introduction: CAR-T cell therapy is a novel approach in the treatment of hematological tumors. However, it is associated with life-threatening side effects, such as the severe cytokine release syndrome (sCRS). Therefore, predicting the occurrence and development of sCRS is of great significance for clinical CAR-T therapy. The study of existing clinical data by artificial intelligence may bring useful information. Methods: By analyzing the heat map of clinical factors and comparing them between severe and non-severe CRS, we can identify significant differences among these factors and understand their interrelationships. Ultimately, a decision tree approach was employed to predict the timing of severe CRS in both children and adults, considering variables such as the same day, the day before, and initial values. Results: We measured cytokines and clinical biomarkers in 202 patients who received CAR-T therapy. Peak levels of 25 clinical factors, including IFN-γ, IL6, IL10, ferritin, and D-dimer, were highly associated with severe CRS after CAR T cell infusion. Using the decision tree model, we were able to accurately predict which patients would develop severe CRS consisting of three clinical factors, classified as same-day, day-ahead, and initial value prediction. Changes in serum biomarkers, including C-reactive protein and ferritin, were associated with CRS, but did not alone predict the development of severe CRS. Conclusion: Our research will provide significant information for the timely prevention and treatment of sCRS, during CAR-T immunotherapy for tumors, which is essential to reduce the mortality rate of patients.

[Heat-sensitive moxibustion for migraine without aura: a randomized controlled trial].

OBJECTIVE: To compare the clinical effect between heat-sensitive moxibustion and mild moxibustion for migraine without aura. METHODS: A total of 54 patients with migraine without aura were randomized into an observation group (27 cases, 2 cases dropped off) and a control group (27 cases, 2 cases dropped off). The basic western medication treatment was adopted in the two groups. In the control group, mild moxibustion was applied at Shuaigu (GB 8), Fengchi (GB 20) and Yanglingquan (GB 34) on the affected side. In the observation group, the frequent acupoint areas of the affected side i.e. Shuaigu (GB 8), Fengchi (GB 20), Taiyang (EX-HN 5), Taichong (LR 3), Yanglingquan (GB 34) were determined, 3 acupoints with strong heat-sensitive sensation were selected each time and mild moxibustion was adopted. The treatment was given once a day, 5 times of treatment was as one course and 2 courses were required in the two groups. Before and after treatment, the scores of migraine symptom, visual analogue scale (VAS), migraine specific quality of life questionnaire (MSQ) were observed, and the clinical efficacy was evaluated after treatment in the two groups. RESULTS: After treatment, the scores of migraine symptom and VAS were decreased compared with those before treatment (P<0.01), while the MSQ scores were increased compared with those before treatment (P<0.01) in the two groups. After treatment, the scores of migraine symptom and VAS in the observation group were lower than those in the control group (P<0.05), while the MSQ score in the observation group was higher than that in the control group (P<0.01). The total effective rate was 92.0% (23/25) in the observation group, which was superior to 72.0% (18/25) in the control group (P<0.05). CONCLUSION: Both heat-sensitive moxibustion and mild moxibustion can effectively alleviate the clinical symptoms, improve the headache degree and life quality in patients with migraine without aura, the clinical efficacy of heat-sensitive moxibustion is superior to that of mild moxibustion.

Population pharmacokinetics of topiramate in Chinese children with epilepsy.

OBJECTIVE: Topiramate, a broad-spectrum antiepileptic drug, exhibits substantial inter-individual variability in both its pharmacokinetics and therapeutic response. The aim of this study was to investigate the influence of patient characteristics and genetic variants on topiramate clearance using population pharmacokinetic (PPK) models in a cohort of Chinese pediatric patients with epilepsy. METHOD: The PPK model was constructed using a nonlinear mixed-effects modeling approach, utilizing a dataset comprising 236 plasma concentrations of topiramate obtained from 181 pediatric patients with epilepsy. A one-compartment model combined with a proportional residual model was employed to characterize the pharmacokinetics of topiramate. Covariate analysis was performed using forward addition and backward elimination to assess the influence of covariates on the model parameters. The model was thoroughly evaluated through goodness-of-fit analysis, bootstrap, visual predictive checks, and normalized prediction distribution errors. Monte Carlo simulations were utilized to devise topiramate dosing strategies. RESULT: In the final PPK models of topiramate, body weight, co-administration with oxcarbazepine, and a combined genotype of GKIR1-UGT (GRIK1 rs2832407, UGT2B7 rs7439366, and UGT1A1 rs4148324) were identified as significant covariates affecting the clearance (CL). The clearance was estimated using the formulas CL (L/h) = 0.44 × (BW/11.7)0.82 × eOXC for the model without genetic variants and CL (L/h) = 0.49 × (BW/11.7)0.81 × eOXC × eGRIK1-UGT for the model incorporating genetic variants. The volume of distribution (Vd) was estimated using the formulas Vd (L) = 6.6 × (BW/11.7). The precision of all estimated parameters was acceptable. Furthermore, the model demonstrated good predictability, exhibiting stability and effectiveness in describing the pharmacokinetics of topiramate. CONCLUSION: The clearance of topiramate in pediatric patients with epilepsy may be subject to the influence of factors such as body weight, co-administration with oxcarbazepine, and genetic polymorphism. In this study, PPK models were developed to better understand and account for these factors, thereby improving the precision and individualization of topiramate therapy in children with epilepsy.

RAP80 phase separation at DNA double-strand break promotes BRCA1 recruitment.

RAP80 has been characterized as a component of the BRCA1-A complex and is responsible for the recruitment of BRCA1 to DNA double-strand breaks (DSBs). However, we and others found that the recruitment of RAP80 and BRCA1 were not absolutely temporally synchronized, indicating that other mechanisms, apart from physical interaction, might be implicated. Recently, liquid-liquid phase separation (LLPS) has been characterized as a novel mechanism for the organization of key signaling molecules to drive their particular cellular functions. Here, we characterized that RAP80 LLPS at DSB was required for RAP80-mediated BRCA1 recruitment. Both cellular and in vitro experiments showed that RAP80 phase separated at DSB, which was ascribed to a highly disordered region (IDR) at its N-terminal. Meanwhile, the Lys63-linked poly-ubiquitin chains that quickly formed after DSBs occur, strongly enhanced RAP80 phase separation and were responsible for the induction of RAP80 condensation at the DSB site. Most importantly, abolishing the condensation of RAP80 significantly suppressed the formation of BRCA1 foci, encovering a pivotal role of RAP80 condensates in BRCA1 recruitment and radiosensitivity. Together, our study disclosed a new mechanism underlying RAP80-mediated BRCA1 recruitment, which provided new insight into the role of phase separation in DSB repair.

[Effect of acupuncture on swallowing function for patients of Parkinson's disease with dysphagia].

OBJECTIVE: To observe the effects of acupuncture on swallowing function and quality of life for patients with dysphagia in Parkinson's disease (PD). METHODS: A total of 60 patients of PD with dysphagia were randomly divided into an observation group (30 cases, 2 cases dropped off) and a control group (30 cases, 3 cases dropped off). The control group was given conventional medication therapy and rehabilitation training. On the basis of the treatment as the control group, the observation group was given acupuncture at Fengfu (GV 16), Baihui (GV 20), Shenting (GV 24), Yintang (GV 24+), Yansanzhen and bilateral Fengchi (GB 20), 30 min each time, once a day, 6 times a week for 4 weeks. Before and after treatment, the Kubota water swallowing test, standardized swallowing assessment (SSA) and swallowing quality of life (SWAL-QOL) were used to evaluate the swallowing function and quality of life of the two groups. RESULTS: After treatment, the Kubota water swallowing test grade, SSA scores in the two groups were decreased compared with those before treatment (P<0.05, P<0.001)，the SWAL-QOL scores were increased compared with those before treatment (P<0.001); in the observation group，the Kubota water swallowing test grade and SSA score were lower than those in the control group (P<0.05)，the SWAL-QOL score was higher than that in the control group (P<0.001). CONCLUSION: On the basis of conventional medication therapy and rehabilitation training，acupuncture could improve the swallowing function and quality of life for patients of PD with dysphagia.