Nephrotic syndrome associated with solid malignancies: a systematic review.

BACKGROUND: Nephrotic syndrome (NS) can occur as a paraneoplastic disorder in association with various types of carcinoma. However, paraneoplastic nephrotic syndrome (PNS) is often misdiagnosed as idiopathic nephrotic syndrome or as an adverse effect of oncology treatment, leading to delayed diagnosis and suboptimal treatment. The characteristics of NS associated with solid malignancies are not yet elucidated. We systematically summarized the clinical data for 128 cases of NS combined with solid malignancies with the aim of informing the clinical management of PNS. METHODS: We searched the PubMed database for articles published from the date of inception through to October 2023 using the following keywords: "cancer" or "malignant neoplasms" or "neoplasia" or "tumors" and "nephrotic syndrome", "nephrotic" or "syndrome, nephrotic". All data were extracted from case reports and case series, and the extraction included a method for identifying individual-level patient data. RESULTS: A literature search yielded 105 cases of PNS and 23 of NS induced by cancer therapy. The median age at diagnosis was 60 years, with a male to female ratio of 1.8:1. In patients with PNS, manifestations of NS occurred before, concomitantly with, or after diagnosis of the tumor (in 36%, 30%, and 34% of cases, respectively). Membranous nephropathy (49%) was the most prevalent renal pathology and found particularly in patients with lung, colorectal, or breast carcinoma. Regardless of whether treatment was for cancer alone or in combination with NS, the likelihood of remission was high. CONCLUSION: The pathological type of NS may be associated with specific malignancies in patients with PNS. Prompt identification of PNS coupled with suitable therapeutic intervention has a significant impact on the outcome for patients.

Entanglement Structure and Information Protection in Noisy Hybrid Quantum Circuits.

In the context of measurement-induced entanglement phase transitions, the influence of quantum noises, which are inherent in real physical systems, is of great importance and experimental relevance. In this Letter, we present a comprehensive theoretical analysis of the effects of both temporally uncorrelated and correlated quantum noises on entanglement generation and information protection. This investigation reveals that entanglement within the system follows q^{-1/3} scaling for both types of quantum noises, where q represents the noise probability. The scaling arises from the Kardar-Parisi-Zhang fluctuation with effective length scale L_{eff}∼q^{-1}. More importantly, the information protection timescales of the steady states are explored and shown to follow q^{-1/2} and q^{-2/3} scaling for temporally uncorrelated and correlated noises, respectively. The former scaling can be interpreted as a Hayden-Preskill protocol, while the latter is a direct consequence of Kardar-Parisi-Zhang fluctuations. We conduct extensive numerical simulations using stabilizer formalism to support the theoretical understanding. This Letter not only contributes to a deeper understanding of the interplay between quantum noises and measurement-induced phase transition but also provides a new perspective to understand the effects of Markovian and non-Markovian noises on quantum computation.

Metabolic syndrome and risk of subclinical hypothyroidism: a systematic review and meta-analysis.

Background: Subclinical hypothyroidism (SCH) is a common endocrine subclinical disorder, the main adverse consequences of which are the development of clinical hypothyroidism and the promotion of ischemic heart disease. Metabolic syndrome (MetS) is a collection of metabolic problems. The goal of this meta-analysis was to evaluate the relationship between MetS and SCH. Methods: Suitable publications were identified using PubMed, Embase, and the Cochrane Library. The meta-analysis included only studies in English that reported odds ratio (OR) data for MetS and SCH. Two researchers combined data using a random-effects model. OR and 95% confidence intervals (CIs) were used to present the results. Results: MetS was associated with an elevated risk of developing SCH (OR 2.56, 95% CI 1.44-4.55). However, the individual components of MetS were not associated with the risk of SCH. Subgroup analysis revealed that different definitions of MetS had varying effects on SCH. Sensitivity analysis confirmed that our results were robust. Conclusions: This meta-analysis indicates that patients with MetS have an increased risk of SCH, while there is no significant association between the five individual components of MetS and the risk of SCH. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023454415.

Oxygen Vacancy-Driven Heterointerface Breaks the Linear-Scaling Relationship of Intermediates toward Electrocatalytic CO2 Reduction.

Smart metal-metal oxide heterointerface construction holds promising potentials to endow an efficient electron redistribution for electrochemical CO2 reduction reaction (CO2RR). However, inhibited by the intrinsic linear-scaling relationship, the binding energies of competitive intermediates will simultaneously change due to the shifts of electronic energy level, making it difficult to exclusively tailor the binding energies to target intermediates and the final CO2RR performance. Nonetheless, creating specific adsorption sites selective for target intermediates probably breaks the linear-scaling relationship. To verify it, Ag nanoclusters were anchored onto oxygen vacancy-rich CeO2 nanorods (Ag/OV-CeO2) for CO2RR, and it was found that the oxygen vacancy-driven heterointerface could effectively promote CO2RR to CO across the entire potential window, where a maximum CO Faraday efficiency (FE) of 96.3% at -0.9 V and an impressively high CO FE of over 62.3% were achieved at a low overpotential of 390 mV within a flow cell. The experimental and computational results collectively suggested that the oxygen vacancy-driven heterointerfacial charge spillover conferred an optimal electronic structure of Ag and introduced additional adsorption sites exclusively recognizable for *COOH, which, beyond the linear-scaling relationship, enhanced the binding energy to *COOH without hindering *CO desorption, thus resulting in the efficient CO2RR to CO.

Versatile Framework for Drug-Target Interaction Prediction by Considering Domain-Specific Features.

Predicting drug-target interactions (DTIs) is one of the crucial tasks in drug discovery, but traditional wet-lab experiments are costly and time-consuming. Recently, deep learning has emerged as a promising tool for accelerating DTI prediction due to its powerful performance. However, the models trained on limited known DTI data struggle to generalize effectively to novel drug-target pairs. In this work, we propose a strategy to train an ensemble of models by capturing both domain-generic and domain-specific features (E-DIS) to learn diverse domain features and adapt them to out-of-distribution data. Multiple experts were trained on different domains to capture and align domain-specific information from various distributions without accessing any data from unseen domains. E-DIS provides a comprehensive representation of proteins and ligands by capturing diverse features. Experimental results on four benchmark data sets in both in-domain and cross-domain settings demonstrated that E-DIS significantly improved model performance and domain generalization compared to existing methods. Our approach presents a significant advancement in DTI prediction by combining domain-generic and domain-specific features, enhancing the generalization ability of the DTI prediction model.

E3 Ubiquitin Ligase RNF13 Suppresses TLR Lysosomal Degradation by Promoting LAMP-1 Proteasomal Degradation.

As a highly organized system, endo-lysosomes play a crucial role in maintaining immune homeostasis. However, the mechanisms involved in regulating endo-lysosome progression and subsequent inflammatory responses are not fully understood. By screening 103 E3 ubiquitin ligases in regulating endo-lysosomal acidification, it is discovered that lysosomal RNF13 inhibits lysosome maturation and promotes inflammatory responses mediated by endosomal Toll-like receptors (TLRs) in macrophages. Mechanistically, RNF13 mediates K48-linked polyubiquitination of LAMP-1 at residue K128 for proteasomal degradation. Upon TLRs activation, LAMP-1 promotes lysosomes maturation, which accelerates lysosomal degradation of TLRs and reduces TLR signaling in macrophages. Furthermore, peripheral blood mononuclear cells (PBMCs) from patients with rheumatoid arthritis (RA) show increased RNF13 levels and decreased LAMP-1 expression. Accordingly, the immunosuppressive agent hydroxychloroquine (HCQ) can increase the polyubiquitination of RNF13. Taken together, the study establishes a linkage between proteasomal and lysosomal degradation mechanisms for the induction of appropriate innate immune response, and offers a promising approach for the treatment of inflammatory diseases by targeting intracellular TLRs.

Polyploid giant cancer cells induced by Docetaxel exhibit a senescence phenotype with the expression of stem cell markers in ovarian cancer cells.

Docetaxel (Doc) plays a crucial role in clinical antineoplastic practice. However, it is continuously documented that tumors frequently develop chemoresistance and relapse, which may be related to polyploid giant cancer cells (PGCCs). The aim of this study was investigate the formation mechanism and biological behavior of PGCCs induced by Doc. Ovarian cancer cells were treated with Doc, and then the effect of Doc on cellular viability was evaluated by MTT assay and microscopic imaging analysis. The biological properties of PGCCs were further evaluated by Hoechst 33342 staining, cell cycle and DNA content assay, DNA damage response (DDR) signaling detection, ß-galactosidase staining, mitochondrial membrane potential detection, and reverse transcription-quantitative polymerase chain reaction. The results indicated that Doc reduced cellular viability; however, many cells were still alive, and were giant and polyploid. Doc increased the proportion of cells stayed in the G2/M phase and reduced the number of cells. In addition, the expression of γ-H2A.X was constantly increased after Doc treatment. PGCCs showed senescence-associated ß-galactosidase activity and an increase in the monomeric form of JC-1. The mRNA level of octamer-binding transcription factor 4 (OCT4) and krüppel-like factor 4 (KLF4) was significantly increased in PGCCs. Taken together, our results suggest that Doc induces G2/M cell cycle arrest, inhibits the proliferation and activates persistent DDR signaling to promote the formation of PGCCs. Importantly, PGCCs exhibit a senescence phenotype and express stem cell markers.

Inhibition of the p62-Nrf2-GPX4 Pathway Confers Sensitivity to Butachlor-Induced Splenic Macrophage Ferroptosis.

Butachlor is widely used in agriculture around the world and therefore poses environmental and public health hazards due to persistent and poor biodegradability. Ferroptosis is a type of iron-mediated cell death controlled by glutathione (GSH) and GPX4 inhibition. P62 is an essential autophagy adaptor that regulates Keap1 to activate nuclear factor erythroid 2-related factor 2 (Nrf2), which effectively suppresses lipid peroxidation, thereby relieving ferroptosis. Here, we found that butachlor caused changes in splenic macrophage structure, especially impaired mitochondrial morphology with disordered structure, which is suggestive of the occurrence of ferroptosis. This was further confirmed by the detection of iron metabolism, the GSH system, and lipid peroxidation. Mechanistically, butachlor suppressed the protein level of p62 and promoted Keap1-mediated degradation of Nrf2, which results in decreased GPX4 expression and accelerated splenic macrophage ferroptosis. These findings suggest that targeting the p62-Nrf2-GPX4 signaling axis may be a promising strategy for treating inflammatory diseases.

Optimization and validation of a virus-like particle pseudotyped virus neutralization assay for SARS-CoV-2.

Spike-protein-based pseudotyped viruses were used to evaluate vaccines during the COVID-19 pandemic. However, they cannot be used to evaluate the envelope (E), membrane (M), and nucleocapsid (N) proteins. The first generation of virus-like particle (VLP) pseudotyped viruses contains these four structural proteins, but their titers for wild-type severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are relatively low, even lower for the omicron variant, rendering them unsuitable for neutralizing antibody detection. By optimizing the spike glycoprotein signal peptide, substituting the complexed M and E proteins with SARS-COV-1, optimizing the N protein with specific mutations (P199L, S202R, and R203M), and truncating the packaging signal, PS9, we increased the titer of the wild-type VLP pseudotyped virus over 100-fold, and successfully packaged the omicron VLP pseudotyped virus. The SARS-CoV-2 VLP pseudotyped viruses maintained stable titers, even through 10 freeze-thaw cycles. The key neutralization assay parameters were optimized, including cell type, cell number, and viral inoculum. The assay demonstrated minimal variation in both intra- and interassay results, at 11.5% and 11.1%, respectively. The correlation between the VLP pseudotyped virus and the authentic virus was strong (r = 0.9). Suitable for high-throughput detection of various mutant strains in clinical serum. In summary, we have developed a reliable neutralization assay for SARS-CoV-2 based on VLP pseudotyped virus.

Inhomogeneous Strain Behaviors of the High Strength Pipeline Girth Weld under Longitudinal Loading.

Unforeseen failures in girth welds present a significant challenge for the pipeline industry. This study utilizes 3D Digital Image Correlation (DIC) assisted cross-weld tensile testing to analyze the strain response of high-strength thick-walled pipelines, providing essential insights into the strain migration and fracture mechanisms specific to girth welds. The results reveal that the welding process significantly affects the mechanical distribution within the girth weld. The tested Shielded Metal Arc Welded (SMAW-ed) pipe exhibited undermatched girth welds due to high heat input, while Gas Metal Arc Welding (GMAW) introduced a narrower weld and Heat-Affected Zone (HAZ) with higher hardness than the base metal, indicative of overmatched girth welds. Strain migration, resulting from a combination of metallurgical heterogeneous materials and geometrical reinforcement strengthening, progressed from the softer HAZ to the base metal in the SMAW-ed sample with reinforcement, ultimately leading to fracture in the base metal. In contrast, the GMAW-ed sample shows no strain migration. Reinforcement significantly improves the tensile strength of girth welds and effectively prevents failure in the weld region. Sufficient reinforcement is crucial for minimizing the risk of failure in critical areas such as the weld metal and HAZ, particularly in SMAW-ed pipes.

Inverse optical scatterometry using sketch-guided deep learning.

Optical scatterometry, also referred to as optical critical dimension (OCD) metrology, is a widely used technique for characterizing nanostructures in semiconductor industry. As a model-based optical metrology, the measurement in optical scatterometry is not straightforward but involves solving a complicated inverse problem. So far, the methods for solving the inverse scattering problem, whether traditional or deep-learning-based, necessitate a predefined geometric model, but they are also constrained by this model with poor applicability. Here, we demonstrate a sketch-guided neural network (SGNN) for nanostructure reconstruction in optical scatterometry. By learning from training data based on the designed generic profile model, the neural network acquires not only scattering knowledge but also sketching techniques, that allows it to draw the profiles corresponding to the input optical signature, regardless of whether the sample structure is the same as the generic profile model or not. The accuracy and strong generalizability of proposed approach is validated by using a series of one-dimensional gratings. Experiments have also demonstrated that it is comparable to nonlinear regression methods and outperforms traditional deep learning methods. To our best knowledge, this is the first time that the concept of sketching has been introduced into deep learning for solving the inverse scattering problem. We believe that our method will provide a novel solution for semiconductor metrology, enabling fast and accurate reconstruction of nanostructures.

A Dual-Polarization Programmable Metasurface for Green and Secure Wireless Communication.

Dual-polarization programmable metasurfaces can flexibly manipulate electromagnetic (EM) waves while providing approximately twice the information capacity. Therefore, they hold significant applications in next-generation communication systems. However, there are three challenges associated with the existing dual-polarization programmable metasurfaces. This article aims to propose a novel design to address them. First, the design overcomes the challenge of element- and polarization-independent controls, enabling more powerful manipulations of EM waves. Second, by using more energy-efficient tunable components and reducing their number, the design can be nearly passive (maximum power consumption of 27.7 mW), leading to a significant decrease in the cost and power consumption of the system (at least two orders of magnitude lower than the power consumption of conventional programmable metasurfaces). Third, the design can operate in a broad bandwidth, which is attractive for practical engineering applications. Both the element and array of the metasurface are meticulously designed, and their performance has been carefully studied. The experiments demonstrate that 2D wide-angle beam scanning can be realized. Moreover, secure communication based on directional information modulation can be implemented by exploiting the metasurface and an efficient discrete optimization algorithm, showing its programmable, multiplexing, broadband, green, and secure features.

AQP1 Deficiency Drives Phthalate-Induced Epithelial Barrier Disruption through Intestinal Inflammation.

Di-2-ethylhexyl phthalate (DEHP) is frequently used as a plasticizer to enhance the plasticity and durability of agricultural products, which pose adverse effects to human health and the environment. Aquaporin 1 (AQP1) is a main water transport channel protein and is involved in the maintenance of intestinal integrity. However, the impact of DEHP exposure on gut health and its potential mechanisms remain elusive. Here, we determined that DEHP exposure induced a compromised duodenum structure, which was concomitant with mitochondrial structural injury of epithelial cells. Importantly, DEHP exposure caused duodenum inflammatory epithelial cell damage and strong inflammatory response accompanied by activating the TLR4/MyD88/NF-κB signaling pathway. Mechanistically, DEHP exposure directly inhibits the expression of AQP1 and thus leads to an inflammatory response, ultimately disrupting duodenum integrity and barrier function. Collectively, our findings uncover the role of AQP1 in phthalate-induced intestinal disorders, and AQP1 could be a promising therapeutic approach for treating patients with intestinal disorders or inflammatory diseases.

Surface and underwater acoustic target recognition using only two hydrophones based on machine learning.

Surface and underwater (S/U) acoustic targets recognition is an important application of passive sonar. It is difficult to distinguish them due to the mixture of underwater target radiation noise and marine environmental noise. In previous studies, although using a single hydrophone was able to identify S/U acoustic targets, there were still a few hydrophones that had poor accuracy. In this paper, S/U acoustic targets recognition using two hydrophones based on Gradient Boosting Decision Tree is proposed, and it is first found out as high as 100% accuracy could be achieved with the implementation of SACLANT 1993 data. The real experimental data are always rare and insufficient. The big training dataset is generated using environmental information by acoustic model named KRAKEN. Simulation and experimental data used in the model are heterogeneous, and the differences between these two kinds of data are assimilated by using vertical linear array feature extraction method. The model realizes the recognition of S/U acoustic targets based on channel information besides source spectrum information. By using the combination of two hydrophones, the surface and underwater targets recognition accuracy reached 1 and 0.9384, while they are only 0.4715 and 0.5620 using a single hydrophone, respectively.

Clinical predictive value of the CRP-albumin-lymphocyte index for prognosis of critically ill patients with sepsis in intensive care unit: a retrospective single-center observational study.

Background: Sepsis is a complex syndrome characterized by physiological, pathological, and biochemical abnormalities caused by infection. Its development is influenced by factors such as inflammation, nutrition, and immune status. Therefore, we combined C-reactive protein (CRP), albumin, and lymphocyte, which could reflect above status, to be the CRP-albumin-lymphocyte (CALLY) index, and investigated its association with clinical prognosis of critically ill patients with sepsis. Methods: This retrospective observational study enrolled critically ill patients with sepsis who had an initial CRP, albumin, and lymphocyte data on the first day of ICU admission. All data were obtained from the Affiliated Hospital of Jiangsu University. The patients were divided into quartiles (Q1-Q4) based on their CALLY index. The outcomes included 30-/60-day mortality and acute kidney injury (AKI) occurrence. The association between the CALLY index and these clinical outcomes in critically ill patients with sepsis was evaluated using Cox proportional hazards and logistic regression analysis. Results: A total of 1,123 patients (63.0% male) were included in the study. The 30-day and 60-day mortality rates were found to be 28.1 and 33.4%, respectively, while the incidence of AKI was 45.6%. Kaplan-Meier analysis revealed a significant association between higher CALLY index and lower risk of 30-day and 60-day mortality (log-rank p < 0.001). Multivariate Cox proportional hazards analysis indicated that the CALLY index was independently associated with 30-day mortality [HR (95%CI): 0.965 (0.935-0.997); p = 0.030] and 60-day mortality [HR (95%CI): 0.969 (0.941-0.997); p = 0.032]. Additionally, the multivariate logistic regression model showed that the CALLY index served as an independent risk predictor for AKI occurrence [OR (95%CI): 0.982 (0.962-0.998); p = 0.033]. Conclusion: The findings of this study indicated a significant association between the CALLY index and both 30-day and 60-day mortality, as well as the occurrence of AKI, in critically ill patients with sepsis. These findings suggested that the CALLY index may be a valuable tool in identifying sepsis patients who were at high risk for unfavorable outcomes.

Text information security protection method based on computer-generated holograms.

Currently, computer-generated holograms (CGHs) based on ray tracing technology are generated faster and faster, and the reconstructed scenes are getting bigger and bigger and contain more and more information. Based on this situation, there are also more applications of using CGHs to hide information, but there is a lack of research on the ability to hide information. To address this issue, this paper proposes a point-sampling CGH method based on ray tracing. Our method utilizes ray tracing techniques to rapidly sample text information at different depths in the scene and hides the depth-encoded text information in the carrier image using discrete cosine transform. The reconstructed image after embedding shows good results, with a peak signal-to-noise ratio (PSNR) of 29.56 dB between the hidden images before and after embedding. The PSNR value between the embedded carrier image and the original carrier image is 51.66 dB, making it difficult for the human eye to distinguish, thereby effectively protecting the generated CGH. We also analyzed the maximum information density and observed that computational holograms obtain the maximum information density at 200×200 resolution.

Exploring the causal association between serum metabolites and erectile dysfunction: a bidirectional Mendelian randomisation study.

Erectile dysfunction is a common sexual disorder in men. Some studies have found a strong association between some serum metabolites and erectile dysfunction. To investigate this association further, we used bidirectional Mendelian randomisation to investigate causality and possible biological mechanisms.Firstly, this study screened the statistics of genome-wide association studies of serum metabolites and erectile dysfunction to obtain instrumental variables. Inverse variance weighting was used as the primary method for causal effect analysis of instrumental variables in forward or reverse Mendelian randomisation, and the results obtained by MR-Egger regression and the weighted median method were used as references. Subsequently, the metabolites causally associated with erectile dysfunction were subjected to replication analyses and meta-analyses, and the results of the meta-analyses were analysed by pathway analyses to find influential pathways. In this process, Mendelian randomisation results need to be assessed for stability and reliability using sensitivity analysis.It was found that a total of six serum metabolites were causally associated with erectile dysfunction in a forward Mendelian randomisation study. 1,3,7-trimethyluraten (0.85 (0.73-0.99), P = 0.0368), ergothioneine (0.65 (0.45-0.94), P = 0.0226) and gamma-glutamylglutamate (0.63 (0.46-0.88), P = 0.0059) were protective against the development of erectile dysfunction, whereas 2-hydroxyhippurate (1.10 (1.02-1.19), P = 0.0152), N2,N2-dimethylguanosine (1.57 (1.02-2.40), P = 0.0395) and octanoylcarnitine (1.38 (1.06-1.82), P = 0.0183) were able to induce the development of erectile dysfunction. In addition, metabolic pathway analysis showed that 1,3,7-trimethylurate was able to influence the development of erectile dysfunction via the caffeine metabolism pathway (P = 0.0454). On the other hand, reverse Mendelian randomisation analysis showed that erectile dysfunction reduced serum homocitrulline levels (0.99 (0.97-1.00), P = 0.0360). Sensitivity analyses, including heterogeneity tests and pleiotropy tests, confirmed the reliability of the results.In conclusion, this study demonstrated a bidirectional causal relationship between serum metabolites and erectile dysfunction using bidirectional Mendelian randomisation analysis and replication meta-analysis. On this basis, this study provides a new direction of thinking and strong evidence for the therapeutic application and adjunctive diagnosis of serum metabolites in erectile dysfunction, and provides a certain reference value for subsequent related studies.

A Study on the effects of repetitive transcranial magnetic stimulation on EEG microstate in patients with Parkinson's disease.

Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive neuromodulation technology that can modulate cerebral cortical excitability. Electroencephalography (EEG) microstate analysis is an important tool for studying dynamic changes in brain functional activity. This study explores the pathophysiological changes in Parkinson's disease (PD) patients by analyzing the EEG microstate of PD patients, and analyzes the impact of rTMS on the clinical symptoms of PD patients. In a trial, 25 patients with PD and 18 healthy subjects of the same age were included. The clinical scale (the third part of Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (UPDRS-III) and Montreal Cognitive Assessment (MoCA)) scores of each patient were evaluated and the microstate characteristic parameters of all subjects were calculated. 10 Hz rTMS was used to stimulate the bilateral primary motor cortex (M1) of PD patients. After two weeks of treatment (10 times), the clinical scale score of each patient was re-evaluated and the microstate characteristic parameters were calculated. At the baseline, the occurrence, duration and coverage of microstate C in PD patients were significantly higher than those in healthy controls (P < 0.05),and were significantly negatively correlated with the MoCA score (P < 0.05). The duration and coverage of microstate D in PD patients were significantly lower than those in healthy controls (P < 0.05), and were significantly negatively correlated with UPDRS-III score (P < 0.05). After rTMS treatment in the PD group, the scale score of UPDRS-III was significantly reduced (P < 0.05) and the scale score of MoCA was significantly increased. Moreover, the occurrence and coverage of microstate B were significantly increased (p < 0.05). The occurrence, duration and coverage of microstate C were significantly reduced (P < 0.05). The occurrence, duration and coverage of microstate D were significantly increased (P < 0.05). This study shows that abnormal brain functional activity of PD patients can change microstate characteristic parameters, and these changes are significantly related to the decline of motor and cognitive functions. Furthermore, rTMS can improve the motor and cognitive functions and adjust the microstate characteristic parameters of PD patients. EEG microstate analysis can reflect the therapeutic effect of rTMS on PD patients.