Protein from tiger nut meal extracted by deep eutectic solvent and alkali-soluble acid precipitation: A comparative study on structure, function, and nutrition.

Protein from tiger nut meal (TNP) performance high nutritional value. This study optimized the extraction parameters for TNP (DES-TNP) using deep eutectic solvent, with HBD: HBA = 5:1, Liquid: Solid = 11:1, and the moisture content was 15 %. A comprehensive comparison was conducted with the protein extracted using alkali-soluble acid precipitation (ASAE-TNP). DES-TNP demonstrated significantly higher purity (76.21 ± 2.59 %) than ASAE-TNP (67.48 ± 1.11 %). Density functional theory confirmed the successful synthesis of DES and its strong interaction with TNP. Moreover, DES-TNP and ASAE-TNP were different in structure (microscopic, secondary, and tertiary) and molecular weight distribution. The discrepancy contributed to the different functional properties, DES-TNP exhibiting better solubility, emulsification and foaming properties at pH13 compared to ASAE-TNP. For nutritional properties, DES-TNP and ASAE-TNP exhibited similar amino acid composition and digestibility, but the total amino acid content of DES-TNP was higher. This study presented a novel method for the extraction and comprehensive utilization of TNP.

Misdiagnosis Diagnosis of Pneumocystis Pneumonia as Chemical Pneumonitis.

Background: Auxiliaries, a mixed chemicals, for printing and dyeing characterized by their diverse range and complex chemical compositions are commonly utilized in the textile industry. These chemicals can lead to environmental contamination and pose health risks to humans. Case Description: A 29-year-old man who worked in a printing and dyeing factory in Suzhou, China, reported having tightness in his chest and coughing. Despite seeking medical treatment at several hospitals, the initial diagnosis remained elusive. High-resolution chest CT scans showed multifocal lesions in both lungs. The patient had no significant medical history, and the respiratory symptoms only surfaced after exposure to dyeing auxiliaries. Physicians initially suspected chemical pneumonitis due to occupational exposure. However, a subsequent evaluation at a hospital specializing in occupational diseases led to a diagnosis of AIDS and pneumocystis pneumonia. Conclusion: This case underscores the importance of comprehensive clinical diagnosis to avoid biases and reduce the incidence of misdiagnosis.

Improving Broiler Health through Cecal Microbiota Transplantation: A Comprehensive Study on Growth, Immunity, and Microbial Diversity.

Cecal microbiota has emerged as a prominent intervention target for improving the production and welfare of poultry. This is essential for the overall health and performance of broiler chickens. The current study focused on investigating the effect of cecal microbiota transplantation (CMT) from healthy donor chickens on the growth performance, immunity, and microbial composition of newly hatched chicks and evaluated the effect of sample storage on the microbial diversity of the cecal samples. A healthy "Wannan Yellow Chicken line" was selected as the donor, and 180 1-day-old chicks from the same line were used as recipients for a 60-day feed trial. The chicks were randomly allocated to three groups (60 birds per group) with three replicates in each group. The three treatment groups were CMT-0 (control, normal saline solution), CMT-I (1:12 cecal content, normal saline supplemented with 10% glycerol), and CMT-II (1:6 cecal content, normal saline supplemented with 10% glycerol). The results of weight gain and absolute organ weight showed significant improvements in the CMT-II group compared with the CMT-0 group. Serum IgG level was significantly improved (p < 0.05) in CMT-I compared with that in the CMT-0. However, IL-6 levels increased in CMT-I and then significantly decreased in CMT-II. The cecal microbial diversity of CMT treatment was compared between two groups, fresh samples (FS) and stored samples at -80°C (SS). The results showed that beneficial taxa, such as Firmicutes and Verrucomicrobiota, were substantially more abundant in both CMT-I and CMT-II than in CMT-0 in both FS and SS. Microbial function analysis at levels 1, 2, and 3 showed improved metabolism, genetic information processing, cellular processes, environmental information processing, and organismal systems in CMT-I and CMT-II for both FS and SS groups. However, the SS group showed decreased microbial diversity and function. To conclude, cecal microbiota transplantation is a promising strategy for enhancing the productivity and health of broiler chickens.

Regeneration of sedimentary manganese in coastal sediments deciphered by 224Ra/228Th disequilibria.

Manganese (Mn) is a vital micronutrient and participates in multiple biochemical reactions and enzyme catalytic activities. Its cycling is tightly connected with iron (Fe) and nitrogen (N). Although coastal sediments are recognized as an important source of dissolved Mn to marine waters, this contribution remains inadequately quantified. In the summer of 2019 and 2020, we investigated benthic fluxes of dissolved Mn, Fe and ammonia (NH4+) in the Changjiang Estuary and East China Sea shelf using the 224Ra/228Th disequilibrium approach. Our results showed that the availability of reactive Mn oxides (MnD) played a crucial role in sedimentary Mn regeneration, as revealed by the positive correlation (r = 0.75, P < 0.05) between Mn fluxes and MnD contents. In addition, the positive correlation (r = 0.80, P < 0.01) between the decomposition rates of sedimentary organic matter (NH4+ flux) and Mn fluxes suggested that the reduction of MnD was mainly driven by the organic carbon oxidation. Furthermore, NH4+ and Mn fluxes exhibited an exponential increase against the product of dissolved oxygen concentration (DO) and the amplification factor of sediment surface area (ξ). In this context, ξ represents the rate of bottom water DO pumped into the sediment via physical reworking and bio-irrigation. In contrast to the most efficient Fe released from sediment overlain by hypoxic waters (DO <62.5 µM), the maximum Mn flux (63.5 ± 9.4 mmol m-2 d-1) was observed at sediment with oxygenated bottom waters (DO = 158 µM). This implies that the regeneration of Mn was associated with a more permissive redox state compared to that of Fe. We further demonstrated that Mn flux was 1-2 orders of magnitude higher than those estimated through traditional methods. Therefore, coastal sediments may contribute more Mn to ocean waters than previously thought. The precise estimation of Mn release from coastal sediments holds critical significance for research on the global Mn budget.

EMG-based Multi-User Hand Gesture Classification via Unsupervised Transfer Learning Using Unknown Calibration Gestures.

The poor generalization performance and heavy training burden of the gesture classification model contribute as two main barriers that hinder the commercialization of sEMG-based human-machine interaction (HMI) systems. To overcome these challenges, eight unsupervised transfer learning (TL) algorithms developed on the basis of convolutional neural networks (CNNs) were explored and compared on a dataset consisting of 10 gestures from 35 subjects. The highest classification accuracy obtained by CORrelation Alignment (CORAL) reaches more than 90%, which is 10% higher than the methods without using TL. In addition, the proposed model outperforms 4 common traditional classifiers (KNN, LDA, SVM, and Random Forest) using the minimal calibration data (two repeated trials for each gesture). The results also demonstrate the model has a great transfer robustness/flexibility for cross-gesture and cross-day scenarios, with an accuracy of 87.94% achieved using calibration gestures that are different with model training, and an accuracy of 84.26% achieved using calibration data collected on a different day, respectively. As the outcomes confirm, the proposed CNN TL method provides a practical solution for freeing new users from the complicated acquisition paradigm in the calibration process before using sEMG-based HMI systems.

MEMS Fingertip Strain Plethysmography for Cuffless Estimation of Blood Pressure.

OBJECTIVE: To develop a cuffless method for estimating blood pressure (BP) from fingertip strain plethysmography (SPG) recordings. METHODS: A custom-built micro-electromechanical systems (MEMS) strain sensor is employed to record heartbeat-induced vibrations at the fingertip. An XGboost regressor is then trained to relate SPG recordings to beat-to-beat systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP) values. For this purpose, each SPG segment in this setup is represented by a feature vector consisting of cardiac time interval, amplitude features, statistical properties, and demographic information of the subjects. In addition, a novel concept, coined geometric features, are introduced and incorporated into the feature space to further encode the dynamics in SPG recordings. The performance of the regressor is assessed on 32 healthy subjects through 5-fold cross-validation (5-CV) and leave-subject-out cross validation (LSOCV). RESULTS: Mean absolute errors (MAEs) of 3.88 mmHg and 5.45 mmHg were achieved for DBP and SBP estimations, respectively, in the 5-CV setting. LSOCV yielded MAEs of 8.16 mmHg for DBP and 16.81 mmHg for SBP. Through feature importance analysis, 3 geometric and 26 integral-related features introduced in this work were identified as primary contributors to BP estimation. The method exhibited robustness against variations in blood pressure level (normal to critical) and body mass index (underweight to obese), with MAE ranges of [1.28, 4.28] mmHg and [2.64, 7.52] mmHg, respectively. CONCLUSION: The findings suggest high potential for SPG-based BP estimation at the fingertip. SIGNIFICANCE: This study presents a fundamental step towards the augmentation of optical sensors that are susceptible to dark skin tones.

Sex-Specific and State-Dependent Neuromodulation Regulates Male and Female Locomotion and Sexual Behaviors.

Males and females display dimorphic behaviors that often involve sex-specific locomotor patterns. How the sexually dimorphic locomotion is mediated is poorly understood. In this study, we identify a neuropeptide that oppositely regulates locomotion for efficient sexual behaviors in Drosophila males and females. We find that males are less active than females if isolated. However, when sexually aroused through activating homologous but sexually dimorphic pC1 neurons, males exhibit higher activity levels than females. We discover diuretic hormone 44 (DH44) that functions in pC1 neurons in a sex-specific way to inhibit male locomotion and promote female locomotion. Surprisingly, DH44 exerts opposite effects in sexually aroused flies to promote male locomotion and suppress female locomotion, which is crucial for successful male courtship and female receptivity. These findings demonstrate sexually dimorphic and state-dependent control of locomotor activity by pC1 neuronal activity and DH44 modulation.

Preferential remineralization of phosphorus from organic matter in river-dominated coastal sediments.

In coastal sediments characterized by substantial terrestrial input, the Redfield ratio may not be adequate to determine whether phosphorus (P) is preferentially remineralized relative to carbon (C). Employing a two end-member δ13C mixing model, we observed a gradual decrease in the fraction of terrestrial organic matter as the distance from the river mouth increased. Consequently, the C/P ratio of sedimentary organic matter before early diagenetic alteration (Cu/Pu) decreased from 213 ± 26 to 126 ± 4. In contrast, the C/P ratio of sedimentary organic matter after early diagenetic alteration (Corg/Porg) increased from 208 ± 32 to 265 ± 23. The deviation of Corg/Porg ratios from Cu/Pu ratios suggests that P was preferentially remineralized from organic matter relative to C. Moreover, the degree of preferential remineralization (DPR) of P, represented by (Corg/Porg)/(Cu/Pu), increased with the distance from the river mouth, suggesting a connection to cross-shelf transport. Besides preferential P remineralization, the control mechanisms for P regeneration from sediments strongly depend on the dissolved oxygen (DO) levels of bottom water. Under oxygenated bottom water (DO >120 µM), the precipitation of Fe oxides reduced benthic DIP flux, resulting in a C/P ratio in flux well above the Cu/Pu ratio (1813 ± 725 vs. 213 ± 26). Conversely, when bottom water DO was low (DO<100 µM), the dissolution of Fe oxides and preferential P remineralization increased DIP fluxes, but the precipitation of authigenic apatite suppressed DIP fluxes, leading to C/P ratios in flux approximating Cu/Pu ratios (129 ± 35 vs. 158 ± 10 and 200 ± 82 vs. 141 ± 7). In a moderate redox state (100 < DO <120 µM), preferential P remineralization and the dissolution of Fe oxides increased DIP fluxes, resulting in C/P ratios in flux below Cu/Pu ratios (29 ± 8 vs. 131 ± 5 and 15 ± 6 vs. 126 ± 4).

A Robust and Real-Time Framework of Cross-Subject Myoelectric Control Model Calibration via Multi-Source Domain Adaptation.

Surface electromyogram (sEMG) has been widely used in hand gesture recognition. However, most previous studies focused on user-personalized models, which require a great amount of data from each new target user to learn the user-specific EMG patterns. In this work, we present a novel real-time gesture recognition framework based on multi-source domain adaptation, which learns extra knowledge from the data of other users, thereby reducing the data collection burdens on the target user. Additionally, compared with conventional domain adaptation methods which treat data from all users in the source domain as a whole, the proposed multi-source method treat data from different users as multiple separate source domains. Therefore, more detailed statistical information on the data distribution from each user can be learned effectively. High-density sEMG (256 channels) from 20 subjects was used to validate the proposed method. Importantly, we evaluated our method with a simulated real-time processing pipeline on continuous sEMG data stream, rather than well-segmented data. The false alarm rate during rest periods in an EMG data stream, which is typically neglected by previous studies performing offline analyses, was also considered. Our results showed that, with only 1 s sEMG data per gesture from the new user, the 10-gesture classification accuracy reached 87.66 % but the false alarm rate was reduced to 1.95 %. Our method can reduce the frustratingly heavy data collection burdens on each new user.

Molecular dynamics investigation on the interfacial thermal resistance between annealed pyrolytic graphite and copper.

Modern highly integrated microelectronic products often face the challenge of internal heat dissipation, leading to a significant decrease in their operational efficiency. Annealed Pyrolytic Graphite (APG), due to its superior thermal conductivity, has garnered attention from researchers. The interface thermal resistance between APG and supporting materials like copper significantly affects heat transfer during APG's operation. Existing studies rarely delve into the influence of factors such as the shape of APG material interfaces on thermal resistance from a microscopic perspective. In this paper, utilizing transient thermo-reflectance method and non-equilibrium molecular dynamics simulations, the interface thermal resistance of the APG-Cu structure was investigated under different conditions. The impact of parameters such as copper thickness, interface micro-surface morphology, and APG thickness on the calculated interface thermal resistance was examined. Simulation results revealed that copper thickness had a minor effect on the interface thermal resistance. This is because the phonon participation ratio remains unaffected by changes in the thickness of the copper layer. The interfacial thermal resistance beneath microscopically cylindrical copper surfaces was considerably lower than that of rectangular copper surfaces. This is because beneath the cylindrical surface, the enlarged interface contact area facilitates enhanced thermal transport between the interfaces. The computed results of the radial distribution function in the paper also indirectly validate this viewpoint. The magnitude of interfacial thermal resistance for different APG layers was influenced by the coupling effect of intermolecular forces and the layered stacking structure of APG. The interfacial thermal resistance under the condition of three layers of APG reaches its minimum value, which is 2.2 × 10-9 (K m2 W-1). Furthermore, from the phonon perspective, it is found that the interfacial thermal resistance with different numbers of APG layers is closely related to the localization or delocalization state of phonons. As the number of APG layers increased, the interface thermal resistance showed a trend of initial decrease followed by an increase, this is because the average phonon participation ratio increases and then decreases with the number of APG layers. The average phonon participation ratio reaches its maximum value of 0.45778 under the condition of three layers of APG.

Integrative omics analysis elucidates the genetic basis underlying seed weight and oil content in soybean.

Synergistic optimization of key agronomic traits by traditional breeding has dramatically enhanced crop productivity in the past decades. However, the genetic basis underlying coordinated regulation of yield- and quality-related traits remains poorly understood. Here, we dissected the genetic architectures of seed weight and oil content by combining genome-wide association studies (GWAS) and transcriptome-wide association studies (TWAS) using 421 soybean (Glycine max) accessions. We identified 26 and 33 genetic loci significantly associated with seed weight and oil content by GWAS, respectively, and detected 5,276 expression quantitative trait loci (eQTLs) regulating expression of 3,347 genes based on population transcriptomes. Interestingly, a gene module (IC79), regulated by two eQTL hotspots, exhibited significant correlation with both seed weigh and oil content. Twenty-two candidate causal genes for seed traits were further prioritized by TWAS, including Regulator of Weight and Oil of Seed 1 (GmRWOS1), which encodes a sodium pump protein. GmRWOS1 was verified to pleiotropically regulate seed weight and oil content by gene knockout and overexpression. Notably, allelic variations of GmRWOS1 were strongly selected during domestication of soybean. This study uncovers the genetic basis and network underlying regulation of seed weight and oil content in soybean and provides a valuable resource for improving soybean yield and quality by molecular breeding.

A neural pathway for social modulation of spontaneous locomotor activity (SoMo-SLA) in Drosophila.

Social enrichment or social isolation affects a range of innate behaviors, such as sex, aggression, and sleep, but whether there is a shared mechanism is not clear. Here, we report a neural mechanism underlying social modulation of spontaneous locomotor activity (SoMo-SLA), an internal-driven behavior indicative of internal states. We find that social enrichment specifically reduces spontaneous locomotor activity in male flies. We identify neuropeptides Diuretic hormone 44 (DH44) and Tachykinin (TK) to be up- and down-regulated by social enrichment and necessary for SoMo-SLA. We further demonstrate a sexually dimorphic neural circuit, in which the male-specific P1 neurons encoding internal states form positive feedback with interneurons coexpressing doublesex (dsx) and Tk to promote locomotion, while P1 neurons also form negative feedback with interneurons coexpressing dsx and DH44 to inhibit locomotion. These two opposing neuromodulatory recurrent circuits represent a potentially common mechanism that underlies the social regulation of multiple innate behaviors.

sEMG-Based Inter-Session Hand Gesture Recognition via Domain Adaptation with Locality Preserving and Maximum Margin.

Surface electromyography (sEMG)-based gesture recognition can achieve high intra-session performance. However, the inter-session performance of gesture recognition decreases sharply due to the shift in data distribution. Therefore, developing a robust model to minimize the data distribution difference is crucial to improving the user experience. In this work, based on the inter-session gesture recognition task, we propose a novel algorithm called locality preserving and maximum margin criterion (LPMM). The LPMM algorithm integrates three main modules, including domain alignment, pseudo-label selection, and iteration result selection. Domain alignment is designed to preserve the neighborhood structure of the feature and minimize the overlap of different classes. The pseudo-label selection and iteration result selection can avoid the decrease in accuracy caused by mislabeled samples. The proposed algorithm was evaluated on two of the most widely used EMG databases. It achieves a mean accuracy of 98.46% and 71.64%, respectively, which is superior to state-of-the-art domain adaptation methods.

The potential mechanism of Guizhi Fuling Wan effect in the treatment of cervical squamous cell carcinoma: A bioinformatics analysis investigation.

As a global malignancy with high mortality rate, targeted drug development for Uterine Cervical Neoplasms is an important direction. The traditional formula Guizhi Fuling Wan (GFW) is widely used in gynecological diseases. However, its potential mechanism of action remains to be discovered. We retrieved GFW and cervical squamous cell carcinoma (CSCC) targets from public databases. The protein-protein interaction network was obtained by string computational analysis and imported Cytoscape_v3.9.0 to obtain the core network and the top 10 Hub genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used for enrichment analysis of the core network, and then molecular docking to verify whether the selected signaling pathway binds well to the core node. Finally, clinical prognostic analysis and expression differences of Hub genes were validated using the Cancer Genome Atlas database and R language. Our search yielded 152 common targets for GFW and CSCC. The interleukin-17 signaling pathway, tumor necrosis factor signaling pathway, and Toll-like signaling pathway were then selected for further molecular docking from the hub genes enrichment analysis results, which showed good binding. Among the Hub genes, JUN, VEGFA, IL1B, and EGF had a poor prognosis for CSCC. In conclusion, this study illustrates that GFW can have adjuvant therapeutic effects on CSCC through multiple targets and multiple pathways, providing a basis for further research.

One-shot random forest model calibration for hand gesture decoding.

Objective.Most existing machine learning models for myoelectric control require a large amount of data to learn user-specific characteristics of the electromyographic (EMG) signals, which is burdensome. Our objective is to develop an approach to enable the calibration of a pre-trained model with minimal data from a new myoelectric user.Approach.We trained a random forest (RF) model with EMG data from 20 people collected during the performance of multiple hand grips. To adapt the decision rules for a new user, first, the branches of the pre-trained decision trees were pruned using the validation data from the new user. Then new decision trees trained merely with data from the new user were appended to the pruned pre-trained model.Results.Real-time myoelectric experiments with 18 participants over two days demonstrated the improved accuracy of the proposed approach when compared to benchmark user-specific RF and the linear discriminant analysis models. Furthermore, the RF model that was calibrated on day one for a new participant yielded significantly higher accuracy on day two, when compared to the benchmark approaches, which reflects the robustness of the proposed approach.Significance.The proposed model calibration procedure is completely source-free, that is, once the base model is pre-trained, no access to the source data from the original 20 people is required. Our work promotes the use of efficient, explainable, and simple models for myoelectric control.

The emergence of machine learning force fields in drug design.

In the field of molecular simulation for drug design, traditional molecular mechanic force fields and quantum chemical theories have been instrumental but limited in terms of scalability and computational efficiency. To overcome these limitations, machine learning force fields (MLFFs) have emerged as a powerful tool capable of balancing accuracy with efficiency. MLFFs rely on the relationship between molecular structures and potential energy, bypassing the need for a preconceived notion of interaction representations. Their accuracy depends on the machine learning models used, and the quality and volume of training data sets. With recent advances in equivariant neural networks and high-quality datasets, MLFFs have significantly improved their performance. This review explores MLFFs, emphasizing their potential in drug design. It elucidates MLFF principles, provides development and validation guidelines, and highlights successful MLFF implementations. It also addresses potential challenges in developing and applying MLFFs. The review concludes by illuminating the path ahead for MLFFs, outlining the challenges to be overcome and the opportunities to be harnessed. This inspires researchers to embrace MLFFs in their investigations as a new tool to perform molecular simulations in drug design.

A regional genomic surveillance program is implemented to monitor the occurrence and emergence of SARS-CoV-2 variants in Yubei District, China.

BACKGROUND: In December 2022, Chongqing experienced a significant surge in coronavirus disease 2019 (COVID-19) epidemic after adjusting control measures in China. Given the widespread immunization of the population with the BA.5 variant, it is crucial to actively monitor severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant evolution in Chongqing's Yubei district. METHODS: In this retrospective study based on whole genome sequencing, we collected oropharyngeal and nasal swab of native COVID-19 cases from Yubei district between January to May 2023, along with imported cases from January 2022 to January 2023. Through second-generation sequencing, we generated a total of 578 genomes. RESULTS: Phylogenetic analyses revealed these genomes belong to 47 SARS-CoV-2 Pango lineages. BA.5.2.48 was dominant from January to April 2023, rapidly replaced by XBB* variants from April to May 2023. Bayesian Skyline Plot reconstructions indicated a higher evolutionary rate (6.973 × 10-4 subs/site/year) for the XBB.1.5* lineage compared to others. The mean time to the most recent common ancestor (tMRCA) of BA.5.2.48* closely matched BA.2.75* (May 27, 2022). Using multinomial logistic regression, we estimated growth advantages, with XBB.1.9.1 showing the highest growth advantage (1.2, 95% HPI:1.1-1.2), followed by lineage FR.1 (1.1, 95% HPI:1.1-1.2). CONCLUSIONS: Our monitoring reveals the rapid replacement of the previously prevalent BA.5.2.48 variant by XBB and its sub-variants, underscoring the ineffectiveness of herd immunity and breakthrough BA.5 infections against XBB variants. Given the ongoing evolutionary pressure, sustaining a SARS-CoV-2 genomic surveillance program is imperative.

DNA methylation remodeled amino acids biosynthesis regulates flower senescence in carnation (Dianthus caryophyllus).

Dynamic DNA methylation regulatory networks are involved in many biological processes. However, how DNA methylation patterns change during flower senescence and their relevance with gene expression and related molecular mechanism remain largely unknown. Here, we used whole genome bisulfite sequencing to reveal a significant increase of DNA methylation in the promoter region of genes during natural and ethylene-induced flower senescence in carnation (Dianthus caryophyllus L.), which was correlated with decreased expression of DNA demethylase gene DcROS1. Silencing of DcROS1 accelerated while overexpression of DcROS1 delayed carnation flower senescence. Moreover, among the hypermethylated differentially expressed genes during flower senescence, we identified two amino acid biosynthesis genes, DcCARA and DcDHAD, with increased DNA methylation and reduced expression in DcROS1 silenced petals, and decreased DNA methylation and increased expression in DcROS1 overexpression petals, accompanied by decreased or increased amino acids content. Silencing of DcCARA and DcDHAD accelerates carnation flower senescence. We further showed that adding corresponding amino acids could largely rescue the senescence phenotype of DcROS1, DcCARA and DcDHAD silenced plants. Our study not only demonstrates an essential role of DcROS1-mediated remodeling of DNA methylation in flower senescence but also unravels a novel epigenetic regulatory mechanism underlying DNA methylation and amino acid biosynthesis during flower senescence.

Systemic lupus erythematosus with chronic persistent intracranial hypertension: A case report.

OBJECTIVE: The aim is to investigate the clinical characteristics of systemic lupus erythematosus with intracranial hypertension. METHODS: The clinical characteristics of one case of systemic lupus erythematosus with chronic persistent intracranial hypertension were analyzed, and related literature was reviewed by searching Medline and Wanfang databases. RESULTS: Intracranial hypertension in SLE patients may occur at the onset or during the course of the disease. Our patient was diagnosed with IH 3 years after the onset of SLE. Headache and papilledema were the most common symptoms of intracranial hypertension, followed by nausea or vomiting, vision changes, and cerebral palsy. Our patient had a headache and cranial hypertension that lasted for years, but no papilledema was found. Corticosteroid is currently the mainstay of the treatment of IIH in patients with SLE, and immunosuppressive agents, acetazolamide, intravenous mannitol and furosemide are also used. However, our patient did not respond to these treatments and presents the characteristics of chronic persistent intracranial hypertension. CONCLUSION: Systemic lupus erythematosus with intracranial hypertension is a rare manifestation of SLE, which is not completely parallel to SLE activity. Headache and papilledema were the most common presenting symptoms. Different from previous reported cases, our patient had poor response to treatments, showing chronic and persistent characteristics.