Cognitive function in Parkinson's disease: associations with perivascular space in basal ganglia.

BACKGROUND: Cognitive impairment is one of the most common symptoms of Parkinson's disease (PD), and may be detectable through changes in neural features visualized by magnetic resonance imaging (MRI). Mild cognitive impairment is a transitional state between normal aging and dementia, and early recognition of Parkinson's disease with mild cognitive impairment (PD-MCI) can help improve the quality of life and treatment for patients. This study investigated the association of enlarged perivascular space (EPVS) and white matter hyperintensity (WMH) with PD-MCI. AIMS: This study aimed to evaluate whether EPVS and WMH can be used as potential MRI markers for PD-MCI. METHODS: This retrospective study involved 200 patients with PD who underwent cranial MRI in our hospital from April 2021 to April 2022. Patients were divided into those with no cognitive impairment (PD-NCI) or mild cognitive impairment. Uni- and multivariate logistic regression analyzed associations of EPVS, WMH, and clinicodemographic characteristics with cognitive decline. RESULTS: Univariate regression identified severe EPVS in basal ganglia, severe WMH, older age, late-onset, male sex, low educational level, longer duration of disease, low triglycerides, low uric acid, and low scores on the Mini-mental State Exam as risk factors for PD-MCI. After adjusting for clinicodemographic risk factors in multivariate regression, low education level and EPVS in basal ganglia remained risk factors for cognitive impairment. CONCLUSIONS: Severe EPVS in basal ganglia and poor education, but not WMH, are independent risk factors of PD-MCI. Our findings suggest that non-invasive detection of EPVS in basal ganglia by MRI may be a valuable early indicator of cognitive decline in PD patients.

As a novel prognostic model for breast cancer, the identification and validation of telomere-related long noncoding RNA signatures.

BACKGROUND: Telomeres are a critical component of chromosome integrity and are essential to the development of cancer and cellular senescence. The regulation of breast cancer by telomere-associated lncRNAs is not fully known, though. The goals of this study were to describe predictive telomere-related LncRNAs (TRL) in breast cancer and look into any possible biological roles for these RNAs. METHODS: We obtained RNA-seq data, pertinent clinical data, and a list of telomere-associated genes from the cancer genome atlas and telomere gene database, respectively. We subjected differentially expressed TRLs to co-expression analysis and univariate Cox analysis to identify a prognostic TRL. Using LASSO regression analysis, we built a prognostic model with 14 TRLs. The accuracy of the model's prognostic predictions was evaluated through the utilization of Kaplan-Meier (K-M) analysis as well as receiver operating characteristic (ROC) curve analysis. Additionally, immunological infiltration and immune drug prediction were done using this model. Patients with breast cancer were divided into two subgroups using cluster analysis, with the latter analyzed further for variations in response to immunotherapy, immune infiltration, and overall survival, and finally, the expression of 14-LncRNAs was validated by RT-PCR. RESULTS: We developed a risk model for the 14-TRL, and we used ROC curves to demonstrate how accurate the model is. The model may be a standalone prognostic predictor for patients with breast cancer, according to COX regression analysis. The immune infiltration and immunotherapy results indicated that the high-risk group had a low level of PD-1 sensitivity and a high number of macrophages infiltrating. In addition, we've discovered a number of small-molecule medicines with considerable for use in treating high-risk groups. The cluster 2 subtype showed the highest immune infiltration, the highest immune checkpoint expression, and the worst prognosis among the two subtypes defined by cluster analysis, which requires more attention and treatment. CONCLUSION: As a possible biomarker, the proposed 14-TRL signature could be utilized to evaluate clinical outcomes and treatment efficacy in breast cancer patients.

Robust Attitude Estimation for Low-Dynamic Vehicles Based on MEMS-IMU and External Acceleration Compensation.

Attitude determination based on a micro-electro-mechanical system inertial measurement unit (MEMS-IMU) has attracted extensive attention. The non-gravitational components of the MEMS-IMU have a significant effect on the accuracy of attitude estimation. To improve the attitude estimation of low-dynamic vehicles under uneven soil conditions or vibrations, a robust Kalman filter (RKF) was developed and tested in this paper, where the noise covariance was adaptively changed to compensate for the external acceleration of the vehicle. The state model for MEMS-IMU attitude estimation was initially constructed using a simplified direction cosine matrix. Subsequently, the variance of unmodeled external acceleration was estimated online based on filtering innovations of different window lengths, where the acceleration disturbance was addressed by tradeoffs in time-delay and prescribed computation cost. The effectiveness of the RKF was validated through experiments using a three-axis turntable, an automatic vehicle, and a tractor tillage test. The turntable experiment demonstrated that the angle result of the RKF was 0.051° in terms of root mean square error (RMSE), showing improvements of 65.5% and 29.2% over a conventional KF and MTi-300, respectively. The dynamic attitude estimation of the automatic vehicle showed that the RKF achieves smoother pitch angles than the KF when the vehicle passes over speed bumps at different speeds; the RMSE of pitch was reduced from 0.875° to 0.460° and presented a similar attitude trend to the MTi-300. The tractor tillage test indicated that the RMSE of plough pitch was improved from 0.493° with the KF to 0.259° with the RKF, an enhancement of approximately 47.5%, illustrating the superiority of the RKF in suppressing the external acceleration disturbances of IMU-based attitude estimation.

Development and validation of a nomogram for freezing of gait in patients with Parkinson's Disease.

OBJECTIVES: Freezing of gait (FOG) is a common and complex disabling episodic gait disturbance in patients with Parkinson's disease (PD). Currently, the treatment of FOG remains a challenge for clinicians. The aim of our study was to develop a nomogram for FOG risk based on data collected from Chinese patients with PD. MATERIALS & METHODS: A total of 379 PD patients (197 with FOG) from Kunming Medical University were recruited as a training cohort. Additionally, 339 PD patients (166 with FOG) were recruited from West China Hospital of Sichuan University, to serve as the validation cohort. The least absolute shrinkage and selection operator regression model was used to select clinical and demographic characteristics as well as blood markers, which were incorporated into a predictive model using multivariate logistic regression to predict the risk of developing FOG. The model was validated using the validation dataset, and model performance was evaluated using the C-index, calibration plot, and decision curve analyses. RESULTS: The final predictive model included the REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ) score, Parkinson's Disease Questionnaire (PDQ39), H-Y stage, and visuospatial function. The model showed good calibration and good discrimination, with a C-index value of 0.772 against the training cohort and 0.766 against the validation cohort. Decision curve analysis demonstrated the clinical utility of the nomogram. CONCLUSION: A nomogram incorporating RBDSQ, PDQ39, H-Y stage, and visuospatial function may reliably predict the risk of FOG in PD patients.

Plasma neurofilament light chain levels are associated with depressive and anxiety symptoms in Parkinson's disease.

The present study aimed to explore the association of plasma neurofilament light chain (NfL) levels with depression and anxiety in Parkinson's disease (PD). This prospective study enrolled 116 patients with PD and 38 healthy controls, and found plasma NfL levels were higher in patients with depression or anxiety than in those without these symptoms. Binary logistic regression identified NfL concentration as an independent predictor of depression and anxiety in PD. In conclusion, elevated plasma NfL may be associated with severity of depression and anxiety in PD patients and may serve as a diagnostic biomarker of PD with moderate to severe depression or anxiety.

REM sleep behavioral disorder may be an independent risk factor for orthostatic hypotension in Parkinson's disease.

PURPOSE: The purpose of this study was to evaluate the association between clinically possible rapid eye movement (REM) sleep behavioral disorder (pRBD) and orthostatic hypotension (OH) in PD patients, as well as to explore the mechanisms underlying the association. METHODS: PD patients (n = 116) were assigned to a group with OH (PD-OH) or without OH (PD-NOH). General demographic and clinical data were collected. A series of scales were used to assess the clinical symptoms in the two groups. RESULTS: A total of 27 patients (23.3%) had OH. The PD-OH group showed significantly higher H-Y staging score and significantly higher frequencies of pRBD, anxiety, depression, and cognitive impairment than the PD-NOH group. Binary logistic regression analysis identified the following factors as independently associated with PD-OH: H-Y staging [odds ratio (OR) 2.565, 95% confidence interval (CI) 1.160-5.673; P = 0.020], RBD (OR 7.680, 95% CI 1.944-30.346; P = 0.004), UPDRS II (OR 1.021, 95% CI 0.980-1.063; P = 0.020), depression (OR 7.601, 95% CI 1.492-38.718; P = 0.015), and cognitive impairment (OR 0.824, 95% CI 0.696-0.976; P = 0.025). CONCLUSIONS: Our results suggest that pRBD is an independent risk factor for OH in patients with PD. We speculate that there may be a close relationship between RBD and OH, which requires attention. Early diagnosis of RBD may help predict the appearance of OH in PD patients.

Suicide and suicide attempts after subthalamic nucleus stimulation in Parkinson's disease: a systematic review and meta-analysis.

BACKGROUND: Deep-brain stimulation is a well-established, effective treatment for patients with advanced Parkinson's disease. Recent studies examining rates of suicide attempts and suicides after deep-brain stimulation in the bilateral subthalamic nucleus have reported varying results. Using this systematic review and meta-analysis, we aim to obtain a comprehensive understanding of suicidality in Parkinson's patients after subthalamic nucleus deep brain stimulation. METHODS: We systematically examined Medline, PubMed, Web of Science, and Embase databases to identify studies published before November 2019 that measured rates of suicidality in Parkinson's patients who underwent subthalamic nucleus stimulation. A meta-analysis of the data from the included studies was conducted using Stata 12.0. RESULTS: A total of 18 studies met the eligibility criteria of this study. We found that the pooled rate of suicidal ideation was 4% (95% CI 0.00-7.2%, range 2-17%). The pooled rate of suicide attempts was 1% (95% CI 1.0-2.0%), while the pooled rate of suicide was 1% (95% CI 0.0-1.0%). CONCLUSIONS: Our findings indicate a relatively high rate of suicidality among Parkinson's patients after subthalamic nucleus deep-brain stimulation. It is important for clinicians to carefully monitor psychiatric disorders, especially suicidal ideation and suicide attempts, in Parkinson's patients before and after subthalamic nucleus deep-brain stimulation.

UNC13A variant rs12608932 is associated with increased risk of amyotrophic lateral sclerosis and reduced patient survival: a meta-analysis.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease associated with both genetic and environmental risk factors. Previous studies trying to find an association between ALS and unc-13 homolog A (UNC13A) gene variants have shown inconsistent results. This study aimed to conduct a meta-analysis of the association between the C allele of rs12608932, a single-nucleotide polymorphism located in an intron of UNC13A, and risk of ALS and patient survival. METHODS: PubMed, Web of Science, Embase, Chinese National Knowledge Infrastructure, Wanfang, and SinoMed databases were systematically searched for genome-wide association studies or case-control studies published up to January 2019 on the association between this variant in UNC13A and risk and/or prognosis of ALS. Data from eligible studies were extracted and analyzed. RESULTS: The pooled data (28,072 patients with sporadic ALS and 56,545 controls) showed that rs12608932(C) was associated with an increased risk of ALS (OR = 1.13, 95%CI 1.07-1.20). Subgroup analysis revealed that rs12608932(C) increased the risk of sporadic ALS in non-Asian individuals, including those from the USA and Europe (OR 1.17, 95%CI 1.10-1.25, P < 0.000), but not in Japanese or Chinese subjects (OR 1.01, 95%CI 0.92-1.10, P = 0.85). The available data demonstrated that the CC genotype decreased the survival time of patients with ALS (OR 1.33, 95%CI 1.19-1.49, P < 0.001). CONCLUSION: The present meta-analysis suggests that rs12608932(C) is associated with increased ALS susceptibility, especially in Caucasian and European subjects, and that the CC genotype of rs12608932 is associated with reduced ALS patient survival.

A Coarse-Alignment Method Based on the Optimal-REQUEST Algorithm.

In this paper, we proposed a coarse-alignment method for strapdown inertial navigation systems based on attitude determination. The observation vectors, which can be obtained by inertial sensors, usually contain various types of noise, which affects the convergence rate and the accuracy of the coarse alignment. Given this drawback, we studied an attitude-determination method named optimal-REQUEST, which is an optimal method for attitude determination that is based on observation vectors. Compared to the traditional attitude-determination method, the filtering gain of the proposed method is tuned autonomously; thus, the convergence rate of the attitude determination is faster than in the traditional method. Within the proposed method, we developed an iterative method for determining the attitude quaternion. We carried out simulation and turntable tests, which we used to validate the proposed method's performance. The experiment's results showed that the convergence rate of the proposed optimal-REQUEST algorithm is faster and that the coarse alignment's stability is higher. In summary, the proposed method has a high applicability to practical systems.

A Novel Hybrid of a Fading Filter and an Extreme Learning Machine for GPS/INS during GPS Outages.

In this paper, a novel algorithm based on the combination of a fading filter (FF) and an extreme learning machine (ELM) is presented for Global Positioning System/Inertial Navigation System (GPS/INS) integrated navigation systems. In order to increase the filtering accuracy of the model, a variable fading factor fading filter based on the fading factor is proposed. It adjusts the fading factor by the ratio of the estimated covariance before and after the moment which proves to have excellent performance in our experiment. An extreme learning machine based on a Fourier orthogonal basis function is introduced that considers the deterioration of the accuracy of the navigation system during GPS outages and has a higher positioning accuracy and faster learning speed than the typical neural network learning algorithm. In the end, a simulation and real road test are performed to verify the effectiveness of this algorithm. The results show that the accuracy of the fading filter based on a variable fading factor is clearly improved, and the proposed improved ELM algorithm can provide position corrections during GPS outages more effectively than the other algorithms (ELM and the traditional radial basis function neural network).

Coarse Alignment Technology on Moving base for SINS Based on the Improved Quaternion Filter Algorithm.

Initial alignment of the strapdown inertial navigation system (SINS) is intended to determine the initial attitude matrix in a short time with certain accuracy. The alignment accuracy of the quaternion filter algorithm is remarkable, but the convergence rate is slow. To solve this problem, this paper proposes an improved quaternion filter algorithm for faster initial alignment based on the error model of the quaternion filter algorithm. The improved quaternion filter algorithm constructs the K matrix based on the principle of optimal quaternion algorithm, and rebuilds the measurement model by containing acceleration and velocity errors to make the convergence rate faster. A doppler velocity log (DVL) provides the reference velocity for the improved quaternion filter alignment algorithm. In order to demonstrate the performance of the improved quaternion filter algorithm in the field, a turntable experiment and a vehicle test are carried out. The results of the experiments show that the convergence rate of the proposed improved quaternion filter is faster than that of the tradition quaternion filter algorithm. In addition, the improved quaternion filter algorithm also demonstrates advantages in terms of correctness, effectiveness, and practicability.

C-C Motif Chemokine Ligand 5 (CCL5) as a Predictive Marker for Non-sentinel Lymph Node Presence in Initial-Stage Breast Cancer with 1-2 Affected Sentinel Lymph Nodes.

The objective of our study was to use quantum dots for the purpose of seeing and detecting C-C motif chemokine ligand 5 (CCL5) inside the tissue of sentinel lymph nodes (SLN) and primary tumors. This endeavor aimed to enhance the accuracy of predicting the condition of non-sentinel lymph nodes and provide valuable insights for making informed treatment choices. We analyzed breast cancer patients who underwent sentinel lymph node biopsy followed by axillary lymph node removal due to one or two positive sentinel lymph nodes at the Second People's Hospital of Wuhu, China, between August 2018 and July 2022. Quantum dot technology was employed to visualize and determine CCL5 in the tissue samples from 84 patients. Out of a group diagnosed with breast cancer, 208 underwent sentinel lymph node biopsy. From this pool, 84 tested positive and subsequently underwent axillary lymph node removal. The presence of distinct orange-red fluorescence, linked to quantum dots, was evident in the cellular components of both primary tumors and positive sentinel lymph node tissues. We found a significant relationship between higher levels of SLNCCL5 and advanced tumor growth (P < 0.05). To understand the predictive value of SLN CCL5 related to non-sentinel lymph node status, we utilized the receiver operating characteristic (ROC) method. The area under the curve (AUC) calculated was 0.745 with a cutoff point of 23.285. Multivariate logistic regression was used to understand the effect of tumor dimensions and SLNCCL5 levels on non-sentinel lymph node status in specific patients. Both the size of the tumor and SLNCCL5 levels were found to have a significant impact (P < 0.05). Data suggested that the presence of positive SLNCCL5 might serve as an assessment parameter for anticipating the condition of non-SLN in cases of breast cancer involving T1 or T2 tumors with one or two positive sentinel lymph nodes.

Meta-analysis of the association of prosaposin polymorphisms rs4747203 and rs885828 with risk of Parkinson's disease.

BACKGROUND: Previous research has established a connection between polymorphisms rs4747203 and rs885828 in the prosaposin (PSAP) gene and an increased risk of Parkinson's disease (PD). However, other studies have found no significant difference in risk compared to the general population. METHODS: To evaluate the current evidence linking rs4747203 and rs885828 to PD risk, we conducted a comprehensive search of PubMed, the Web of Science, Embase, and the Cochrane Library for relevant studies up until May 2023. In addition, we analyzed data from the publicly available "PD Variant Browser". We performed a meta-analysis using Stata 17.0 to synthesize the findings from the selected studies. RESULTS: Our meta-analysis, which included data from six published studies and the public database, revealed no significant association between PD risk and either rs4747203 [OR (95% CI) = 0.99 (0.93-1.05), I2 = 90.3%, P = 0.635] or rs885828 [OR (95% CI) = 1.01 (0.95-1.07), I2 = 90.7%, P = 0.773]. These results remained consistent when examining subgroups of individuals within or outside of Asia. CONCLUSION: The available evidence does not support an association between the genotype at rs4747203 or rs885828 and the risk of PD.

Differences in gray matter atrophy and functional connectivity between motor subtypes of Parkinson's disease.

Parkinson's disease (PD) patients with postural gait abnormalities exhibit poorer motor function scores, more severe non-motor symptoms, faster cognitive function deterioration, and a less favorable response to drugs and surgery compared to PD patients with tremor. This discrepancy is believed to be associated with more pronounced gray matter atrophy and abnormal functional connectivity. To investigate the distinctive pathological mechanisms between PD subtypes, we examined gray matter volume (GMV) and functional connectivity in patients with Parkinson's disease presenting with postural instability/gait difficulty (PD-PIGD), patients with tremor-dominant Parkinson's disease (PD-TD), and healthy controls. Voxel-based morphometry (VBM) of T1-weighted images was conducted to compare GMV among 64 PD-PIGD patients, 44 PD-TD patients, and 32 controls. Subsequently, functional connectivity within regions showing reduced GMV was compared across the groups. We analyzed whether differences among the groups were associated with clinical characteristics and neuroimaging biomarkers using partial correlation and binary logistic regression. Our comparison between PD-PIGD and PD-TD patients revealed a link between PD-PIGD and more extensive frontotemporal atrophy, potentially indicating increased basal ganglia activity accompanied by decreased cerebellum activity. Furthermore, in addition to the smaller GMV in the left middle temporal gyrus, the increased functional connectivity between this brain region and the right caudate was also the independent risk factor for PD-PIGD. In addition, we compared brain network connectivity between the PIGD and TD subtypes, using an independent component analysis (ICA). We found that Compared to PD-TD, PD-PIGD patients showed an enhanced sensorimotor network (SMN) around the left supplementary motor area. These findings suggest that severe gray matter atrophy and abnormal functional connectivity and brain networks may serve as pathophysiological mechanisms distinguishing PD-PIGD patients from other subtypes.

MRI brain structural and functional networks changes in Parkinson disease with REM sleep behavior disorders.

Background: Rapid eye movement sleep behavior disorder (RBD) is common in individuals with Parkinson's disease (PD). In spite of that, the precise mechanism underlying the pathophysiology of RBD among PD remains unclear. Objective: The aim of the present study was to analyze gray matter volumes (GMVs) as well as the changes of functional connectivity (FC) among PD patients with RBD (PD-RBD) by employing a combination of voxel-based morphometry (VBM) and FC methods. Methods: A total of 65 PD patients and 21 healthy control (HC) subjects were included in this study. VBM analyses were performed on all subjects. Subsequently, regions with significant different GMVs between PD patients with and without RBD (PD-nRBD) were selected for further analysis of FC. Correlations between altered GMVs and FC values with RBD scores were also investigated. Additionally, receiver operating characteristic (ROC) curves were employed for the evaluation of the predictive value of GMVs and FC in identifying RBD in PD. Results: PD-RBD patients exhibited lower GMVs in the left middle temporal gyrus (MTG) and bilateral cuneus. Furthermore, we observed higher FC between the left MTG and the right postcentral gyrus (PoCG), as well as lower FC between the bilateral cuneus (CUN) and the right middle frontal gyrus (MFG) among PD-RBD patients in contrast with PD-nRBD patients. Moreover, the GMVs of MTG (extending to the right PoCG) was positively correlated with RBD severity [as measured by REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ) score]. Conversely, the FC value between the bilateral CUN and the right MTG in PD-RBD patients was negatively correlated with RBDSQ score. Conclusion: This study revealed the presence replace with GMV and FC changes among PD-RBD patients, which were closely linked to the severity of RBD symptoms. Furthermore, the combination of basic clinical characteristics, GMVs and FC values effectively predicted RBD for individuals with PD.

Low serum uric acid levels may be a potential biomarker of poor sleep quality in patients with Parkinson's disease.

BACKGROUND: Sleep disorders are common non-motor symptoms in patients with Parkinson's disease (PD). However, the pathogenesis of sleep disorders in PD patients remains unclear. Previous studies have implicated oxidative stress in sleep disorders associated with PD. Considering uric acid (UA) acts as a natural antioxidant, in this study, we aimed to assess the use of serum UA as a potential biomarker of sleep disorder in PD patients. METHODS: This study recruited 149 PD patients and 84 Age- and sex-matched individuals. According to the Pittsburgh Sleep Quality Index (PSQI) score, PD patients were divided into three groups, good (≤5), intermediate (6-10), and poor (>10). Multivariate logistic regression and receiver operating characteristic (ROC) curve analyses were also performed to identify clinical features and serum UA levels that help establish an accurate diagnostic model for poor sleep quality in PD patients. RESULTS: PD patients who experienced poor sleep quality had lower serum UA levels. PSQI scores have significant negative relationships with serum UA levels and significant positive relationships with Hamilton Depression Scale (HAMD) scores in PD. Poor sleep quality was independently associated with serum UA levels and HAMD scores. A serum UA level of 328.7 µmol/L and HAMD scores of 19.5 could distinguish PD patients with poor or intermediate sleep to a certain extent, sensitivity of 79.4% and specificity of 76.6%. CONCLUSIONS: Low serum UA levels may correlate with the severity of sleep disorder in PD patients and may serve as a biomarker for poor sleep quality in PD.

Peritumoral lymphangiogenesis induced by vascular endothelial growth factor C and D promotes lymph node metastasis in breast cancer patients.

BACKGROUND: Mounting clinical and experimental data suggest that the migration of tumor cells into lymph nodes is greatly facilitated by lymphangiogenesis. Vascular endothelial growth factor (VEGF)-C and D have been identified as lymphangiogenic growth factors and play an important role in tumor lymphangiogenesis. The purpose of this study was to investigate the location of lymphangiogenesis driven by tumor-derived VEGF-C/D in breast cancer, and to determine the role of intratumoral and peritumoral lymphatic vessel density (LVD) in lymphangiogenesis in breast cancer. METHODS: The expression levels of VEGF-C/D were determined by immunohistochemistry, and intratumoral LVD and peritumoral LVD were assessed using immunohistochemistry and the D2-40 antibody in 73 patients with primary breast cancer. The associations of intratumoral LVD and peritumoral LVD with VEGF-C/D expression, clinicopathological features and prognosis were assessed. RESULTS: VEGF-C and D expression were significantly higher in breast cancer than benign disease (P < 0.01). VEGF-C (P < 0.001) and VEGF-D (P = 0.005) expression were significantly associated with peritumoral LVD, but not intratumoral LVD. Intratumoral LVD was associated with tumor size (P = 0.01). Peritumoral LVD was significantly associated with lymph node metastasis (LNM; P = 0.005), lymphatic vessel invasion (LVI; P = 0.017) and late tumor,node, metastasis (TNM) stage (P = 0.011). Moreover, peritumoral LVD was an independent risk factor for axillary lymph node metastasis, overall survival and disease-free survival in multivariate analysis. CONCLUSIONS: This study suggests that tumor-derived VEGF-C/D induce peritumoral lymphangiogenesis, which may be one mechanism that leads to lymphatic invasion and metastatic spread. Peritumoral LVD has potential as an independent prognostic factor in breast cancer patients.

CCL5 secreted by luminal B breast cancer cells induces polarization of M2 macrophages through activation of MEK/STAT3 signaling pathway via CCR5.

In humans, breast cancer affects a large number of females and causes a high rate of mortality worldwide. Chemokine (C-C motif) ligand 5 (CCL5) is one of the cytokines that is highly correlated to the invasive and metastatic stages of breast cancer. Our previous study has suggested the prognostic value of CCL5 expression in luminal B (HER2 - ) breast cancer. In this study, CCL5 expression was upregulated or knockdown in a luminal B breast cancer cell line, ZR7530. Further, we elucidated the effects of CCL5 on the differentiation of THP-1 monocytes into M2 macrophages. Overexpression of CCL5 affected THP-1-M2 differentiation and phosphorylation of MEK1/2, ERK1/2, and STAT2 in the cocultivated cell lines. We report that the knockdown of CCR5, a receptor of CCL5 in THP-1, inhibited the effect of ZR7530 in promoting THP-1-M2 differentiation. Furthermore, our data revealed that the inhibition of MEK1/2 and STAT3 in THP-1 cells produced equivalent results similar to those of CCL5 knockdown. In summary, we revealed the role of CCL5 in the polarization of M2 macrophages. Furthermore, we studied its interaction with CCR5 and MEK/STAT3 signaling members. These targets could be used as key regulatory members in human breast cancer therapy.

Construction and analysis of a competing endogenous RNA network associated with circRNAs dysregulated in medial temporal lobe epilepsy.

The aetiology and pathogenesis of medial temporal lobe epilepsy (MTLE) remain unclear, and effective treatments are lacking. The involvement of a dysregulated competing endogenous RNA (ceRNA) network in MTLE is only partially understood. The purpose of this study was to investigate MTLE regulatory networks composed of messenger RNAs (mRNAs), circular RNAs (circRNAs), long non-coding RNAs (lncRNAs), and microRNAs (miRNAs) through a ceRNA network map. RNA sequencing (RNA-seq) and small RNA-seq were used to detect mRNAs, circRNAs, miRNAs, and lncRNAs differentially expressed between post-operation hippocampal tissues of MTLE patients (n = 3) and paracancer tissues (n = 3). We performed bioinformatics analysis to identify differentially expressed RNAs and construct the corresponding ceRNA network. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of differentially expressed RNAs were conducted to explore the biological processes and pathways involved in MTLE. We identified 352 differentially expressed mRNAs, 179 circRNAs, and 42 miRNAs in MTLE. A ceRNA network composed of mRNAs, circRNAs, and miRNAs was constructed. GO and KEGG analysis of the network suggested a key role of synapses and mTOR, cAMP, ErbB, FoxO, and HIF-1 signalling pathways in MTLE. We identify a new circRNA-miRNA-mRNA ceRNA network in MTLE. These results can help clarify the aetiology of MTLE and identify targeted molecular therapies.

Downregulation of CHCHD2 may Contribute to Parkinson's Disease by Reducing Expression of NFE2L2 and RQCD1.

BACKGROUND: Parkinson's disease (PD) is associated with coiled-coil-helix-coiled-coilhelix domain containing 2 (CHCHD2) downregulation, which has been linked to reduced cyclocytase activity and increased levels of oxygen free radicals, leading to mitochondrial fragmentation and apoptosis. Little is known about how CHCHD2 normally functions in the cell and, therefore, how its downregulation may contribute to PD. OBJECTIVE: This study aimed to identify such target genes using chromatin immunoprecipitation sequencing from SH-SY5Y human neuroblastoma cells treated with neurotoxin 1-methyl-4- phenylpyridinium (MPP+) as a PD model. METHODS: In this study, we established a MPP+ -related SH-SY5Y cell model and evaluated the effects of CHCHD2 overexpression on cell proliferation and apoptosis. At the same time, we used high-throughput chromatin immunoprecipitation sequencing to identify its downstream target gene in SH-SY5Y cells. In addition, we verified the possible downstream target genes and discussed their mechanisms. RESULTS: The expression level of α-synuclein increased in SH-SY5Y cells treated with MPP+, while the protein expression level of CHCHD2 decreased significantly, especially after 24 h of treatment. Chip-IP results showed that CHCHD2 might regulate potential target genes such as HDX, ACP1, RAVER2, C1orf229, RN7SL130, GNPTG, erythroid 2 Like 2 (NFE2L2), required for cell differentiation 1 homologue (RQCD1), solute carrier family 5 member 7 (SLA5A7), and NAcetyltransferase 8 Like (NAT8L). NFE2L2 and RQCD1 were validated as targets using PCR and western blotting of immunoprecipitates, and these two genes together with SLA5A7 and NAT8L were upregulated in SH-SY5Y cells overexpressing CHCHD2. Downregulation of CHCHD2 may contribute to PD by leading to inadequate expression of NFE2L2 and RQCD1 as well as, potentially, SLA5A7 and NAT8L. CONCLUSION: Our results suggest that CHCHD2 plays a protective role by maintaining mitochondrial homeostasis and promoting proliferation in neurons. In this study, the changes of CHCHD2 and downstream target genes such as NFE2L2/RQCD1 may have potential application prospects in the future. These findings provide leads to explore PD pathogenesis and potential treatments.