Emotion recognition of EEG signals based on contrastive learning graph convolutional model.

Objective.Electroencephalogram (EEG) signals offer invaluable insights into the complexities of emotion generation within the brain. Yet, the variability in EEG signals across individuals presents a formidable obstacle for empirical implementations. Our research addresses these challenges innovatively, focusing on the commonalities within distinct subjects' EEG data.Approach.We introduce a novel approach named Contrastive Learning Graph Convolutional Network (CLGCN). This method captures the distinctive features and crucial channel nodes related to individuals' emotional states. Specifically, CLGCN merges the dual benefits of CL's synchronous multisubject data learning and the GCN's proficiency in deciphering brain connectivity matrices. Understanding multifaceted brain functions and their information interchange processes is realized as CLGCN generates a standardized brain network learning matrix during a dataset's learning process.Main results.Our model underwent rigorous testing on the Database for Emotion Analysis using Physiological Signals (DEAP) and SEED datasets. In the five-fold cross-validation used for dependent subject experimental setting, it achieved an accuracy of 97.13% on the DEAP dataset and surpassed 99% on the SEED and SEED_IV datasets. In the incremental learning experiments with the SEED dataset, merely 5% of the data was sufficient to fine-tune the model, resulting in an accuracy of 92.8% for the new subject. These findings validate the model's efficacy.Significance.This work combines CL with GCN, improving the accuracy of decoding emotional states from EEG signals and offering valuable insights into uncovering the underlying mechanisms of emotional processes in the brain.

The Effect of the Morphology of the Femur and Acetabulum in Dysplastic Hips on the Selection of Arthroplasty Femoral Implants: A Computer Tomography-Based Study.

OBJECTIVES: Due to the technical challenges associated with femoral reconstruction in total hip arthroplasty for patients with developmental dysplasia of the hip (DDH), the exact indications for using femoral modular stems, despite their satisfactory clinical outcomes, remain poorly investigated. This study sought to assess the morphology of the femur and acetabulum, and to investigate the discriminative ability of femoral anteversion (FA), acetabular anteversion (AA), and combined anteversion (CA) on the selection of femoral modular stem in dysplastic hips. METHODS: Retrospective data were collected from multiple centers on a total of 230 cases who underwent THA due to DDH from January 1, 2020, to March 1, 2023. There were 46 males and 184 females, with an average age of 51.57 ± 14.87. Patients were stratified according to Crowe and Eftekhar classifications. FA, AA, and CA were measured using computed tomography (CT). The distribution of these indices in different grades of dysplastic hips was compared, and the correlation between these indices and the selection of femoral modular stem was analyzed. Receiver operating characteristic (ROC) and likelihood statistics were performed to investigate the discriminating and predictive value of each index in selecting modular stem. RESULTS: Two hundred and thirty hips were included in the study. FA increased as the subluxation percentage increased: type I, 21.5°; type II, 28.6°; type III, 34.9°; and type IV, 39.7°. AA was smaller in type I (16.9°) and higher in types II, III, and IV (18.9-22.6°). The area under the curve for the modular stem was 0.87 for FA, 0.86 for CA, and 0.65 for AA. The optimal cutoff values were FA > 32.6°, CA > 50.7°, and AA > 23.3°. CONCLUSION: Excessive AA and femoral anteversion FA were observed in Crowe types II, III, and IV cases. FA and CA demonstrated strong discriminative ability and predictive value in the selection of a modular stem. The best cutoff values were ≥32.6° for FA and ≥50.7° for CA in discriminating the use of modular stem. Surgeons may contemplate the use of a modular stem when the preoperative evaluation approaches the cutoff value.

Defective autophagy of pericytes enhances radiation-induced senescence promoting radiation brain injury.

BACKGROUND: Radiation-induced brain injury (RBI) represents a major challenge for cancer patients undergoing cranial radiotherapy. However, the molecular mechanisms and therapeutic strategies of RBI remain inconclusive. With the continuous exploration of the mechanisms of RBI, an increasing number of studies have implicated cerebrovascular dysfunction as a key factor in RBI-related cognitive impairment. As pericytes are a component of the neurovascular unit, there is still a lack of understanding in current research about the specific role and function of pericytes in RBI. METHODS: We constructed a mouse model of RBI-associated cognitive dysfunction in vivo and an in vitro radiation-induced pericyte model to explore the effects of senescent pericytes on the blood-brain barrier and normal CNS cells, even glioma cells. To further clarify the effects of pericyte autophagy on senescence, molecular mechanisms were explored at the animal and cellular levels. Finally, we validated the clearance of pericyte senescence by using senolytic drug and all-trans retinoic acid to investigate the role of radiation-induced pericyte senescence. RESULTS: Our findings indicated that radiation-induced pericyte senescence plays a key role in blood-brain barrier dysfunction, leading to RBI and subsequent cognitive decline. Strikingly, pericyte senescence also contributes to the growth and invasion of glioma cells. We further demonstrate that defective autophagy in pericytes is a vital regulatory mechanism for pericyte senescence. Moreover, autophagy activated by rapamycin can reverse pericyte senescence. Notably, the elimination of senescent cells by senolytic drugs significantly mitigated radiation-induced cognitive dysfunction. DISSCUSSION: Our results demonstrated that pericyte senescence may be a promising therapeutic target for RBI and glioma progression.

Development and clinical validation of a deep learning-based knee CT image segmentation method for robotic-assisted total knee arthroplasty.

BACKGROUND: This study aimed to develop a novel deep convolutional neural network called Dual-path Double Attention Transformer (DDA-Transformer) designed to achieve precise and fast knee joint CT image segmentation and to validate it in robotic-assisted total knee arthroplasty (TKA). METHODS: The femoral, tibial, patellar, and fibular segmentation performance and speed were evaluated and the accuracy of component sizing, bone resection and alignment of the robotic-assisted TKA system constructed using this deep learning network was clinically validated. RESULTS: Overall, DDA-Transformer outperformed six other networks in terms of the Dice coefficient, intersection over union, average surface distance, and Hausdorff distance. DDA-Transformer exhibited significantly faster segmentation speeds than nnUnet, TransUnet and 3D-Unet (p < 0.01). Furthermore, the robotic-assisted TKA system outperforms the manual group in surgical accuracy. CONCLUSIONS: DDA-Transformer exhibited significantly improved accuracy and robustness in knee joint segmentation, and this convenient and stable knee joint CT image segmentation network significantly improved the accuracy of the TKA procedure.

Artificial intelligence automatic measurement technology of lumbosacral radiographic parameters.

Background: Currently, manual measurement of lumbosacral radiological parameters is time-consuming and laborious, and inevitably produces considerable variability. This study aimed to develop and evaluate a deep learning-based model for automatically measuring lumbosacral radiographic parameters on lateral lumbar radiographs. Methods: We retrospectively collected 1,240 lateral lumbar radiographs to train the model. The included images were randomly divided into training, validation, and test sets in a ratio of approximately 8:1:1 for model training, fine-tuning, and performance evaluation, respectively. The parameters measured in this study were lumbar lordosis (LL), sacral horizontal angle (SHA), intervertebral space angle (ISA) at L4-L5 and L5-S1 segments, and the percentage of lumbar spondylolisthesis (PLS) at L4-L5 and L5-S1 segments. The model identified key points using image segmentation results and calculated measurements. The average results of key points annotated by the three spine surgeons were used as the reference standard. The model's performance was evaluated using the percentage of correct key points (PCK), intra-class correlation coefficient (ICC), Pearson correlation coefficient (r), mean absolute error (MAE), root mean square error (RMSE), and box plots. Results: The model's mean differences from the reference standard for LL, SHA, ISA (L4-L5), ISA (L5-S1), PLS (L4-L5), and PLS (L5-S1) were 1.69°, 1.36°, 1.55°, 1.90°, 1.60%, and 2.43%, respectively. When compared with the reference standard, the measurements of the model had better correlation and consistency (LL, SHA, and ISA: ICC = 0.91-0.97, r = 0.91-0.96, MAE = 1.89-2.47, RMSE = 2.32-3.12; PLS: ICC = 0.90-0.92, r = 0.90-0.91, MAE = 1.95-2.93, RMSE = 2.52-3.70), and the differences between them were not statistically significant (p > 0.05). Conclusion: The model developed in this study could correctly identify key vertebral points on lateral lumbar radiographs and automatically calculate lumbosacral radiographic parameters. The measurement results of the model had good consistency and reliability compared to manual measurements. With additional training and optimization, this technology holds promise for future measurements in clinical practice and analysis of large datasets.

Effects of sodium intake, age, gender, blood sampling time on distribution of plasma aldosterone, renin activity, deoxycorticosterone, cortisol, cortisone, and 24 h urinary aldosterone levels in normotensive individuals based on LC-MS/MS.

PURPOSE: This study aims to analyze the distribution of plasma aldosterone, renin activity, deoxycorticosterone (DOC), cortisol, cortisone, and 24 h urinary aldosterone (24 h-uAld) levels based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) method. MATERIALS AND METHODS: Plasma and 24 h urine were collected from 129 healthy volunteers in Northeast China. The effect of sodium intake, age, gender, blood sampling time on plasma aldosterone concentration (PAC), plasma renin activity (PRA), PAC to PRA ratio (ARR), DOC, cortisol, cortisone, cortisol to cortisone ratio, and 24 h-uAld were investigated by nonparametric test, multiple linear regression and Harris-Boyd's standard deviate test. RESULTS: There was no significant difference observed in 24 h-uAld, PAC (AM), PRA(AM), ARR (AM), DOC (AM), cortisol (AM), cortisone (AM), and cortisol to cortisone (AM) between high and low sodium intake group. Significant differences were observed between morning and afternoon sampling groups in terms of PAC, ARR, DOC, cortisol, and cortisone. Reference intervals (RIs) of 24 h-uAld, PAC (AM) were recommended to be partitioned by gender. RI of PRA was recommended age stratification. CONCLUSION: We recommend that the same reference interval could be used regardless of sodium intake. Gender is the main influence factor for 24 h-uAld, PAC, and ARR. Age is key influence factor for PRA.

Study on the Application Effect of Three-dimensional Reconstruction Technology in Locating Small Pulmonary Nodules During VATS Surgery.

Objective: To compare the positioning effect of three-dimensional reconstruction technology and Hook-wire puncture operation on small pulmonary nodules during video-assisted thoracoscopic surgery (VATS), and evaluate its effectiveness, efficiency, and safety. Methods: The subjects of this study were 50 patients with small pulmonary nodules admitted to the Department of Cardiothoracic Surgery of Heilongjiang Provincial Hospital from January 2020 to December 2022, and all underwent thoracoscopic surgical resection. All study subjects met the inclusion criteria, grouping according to the intraoperative positioning method, the control group (n = 25) used Hook-wire puncture positioning, and the observation group (n = 25) used three-dimensional reconstruction technology. The positioning effect, pain level, and postoperative complications were compared between the two groups. Results: The incidence rate of complications after puncture was 16.00% in the control group and 4.00% in the observation group, the complication rate in the observation group was significantly lower; the positioning success rate of the observation group was 96.00%, which was higher than that of the control group (92.00%). The operation time (32.25±6.08) min was lower than (38.50±7.12) min in the control group. The two groups had no statistical significance in the wedge resection success rate, VAS score, and complication rate (P > .05). Conclusion: Three-dimensional reconstruction technology mainly makes preliminary judgments on the location, shape, size, and relationship between nodules and surrounding tissues based on preoperative CT scan images. It can select suitable scanning locations, map puncture paths, and anchor them in and around small lung nodules. The operation is simple, and the positioning success rate is high. The existence of three-dimensional reconstruction technology to position the guide wire can quickly shorten the time to detect lesions, shorten the time of VATS, reduce the occurrence of pulmonary infection in patients, and improve the prognosis.

Analysis of the Efficacy of Psychological Intervention in 85 patients with New Coronavirus Pneumonia.

Objective: To investigate the effectiveness of strengthen psychological intervention in 85 clients who had pneumonia caused by a novel coronavirus. Methods: As the study's subjects, 162 new coronavirus pneumonia clients admitted to our hospital between January 2020 and September 2020 had their clinical records retrospectively examined. According to different nursing methods, 162 patients with new coronavirus pneumonia were separated into a control team (n=77) and an experimental team (n=85). The test group received the intense psychological intervention, whereas the controlling team only received standard nursing care. The two groups' treatment compliance and nursing satisfaction were observed, the self-rating symptom scale (SCL-90) scores and coping style (MCMQ) grades of the two teams prior to and after the interference was contrasted, and the nursing quality of the two teams was contrasted. Results: In terms of compliance, the overall treatment compliance rate of patients in the experimental group increased significantly. In terms of the psychological state of the experimental group, significant improvements were observed in all psychological dimensions of the patients in the experimental group, including a reduction in negative emotions and an increase in nursing satisfaction. In terms of self-coping, patients in the experimental group showed significant improvement in various dimensions. And the quality of nursing care in the experimental group has been significantly improved. Conclusion: This study highlights the importance of intensive psychological intervention in the overall care of COVID-19 patients and its role in improving patient treatment compliance, negative emotions, self-coping styles and patient health.

Evaluating the accuracy of a new robotically assisted system in cadaveric total knee arthroplasty procedures.

BACKGROUND: Robot-assisted total knee arthroplasty (TKA) has been shown to facilitate high-precision bone resection, which is an important goal in TKA. The aim of this cadaveric study was to analyze the accuracy of the target angle and bone resection thickness of a recently introduced robotic TKA system. METHODS: This study used 4 frozen cadaveric specimens (8 knees), 2 different implant designs, navigation, and a robotic system. The 4 surgeons who participated in this study were trained and familiar with the basic principles and operating procedures of this system. The angle of the bone cuts performed using the robotic system was compared with the target angles from the intraoperative plan. For each bone cut, the resection thickness was recorded and compared with the planned resection thickness. RESULTS: The mean angular difference for all specimens was less than 1°, and the standard deviation was less than 2°. The mean difference between the planned and measured angles was close to 0 and not significantly different from 0 except for the difference in the frontal tibial component angle, which was 0.88°. The mean difference in the hip-knee-ankle axis angle was - 0.21°± 1.06°. The mean bone resection difference for all specimens was less than 1 mm, and the standard deviation was less than 0.5 mm. CONCLUSIONS: The results of the cadaveric experimental study showed that the new TKA system can realize highly accurate bone cuts and achieve planned angles and resection thicknesses. Despite the limitations of small sample sizes and large differences between cadaveric and clinical patients, the accuracy of cadaveric experiments provides strong support for subsequent clinical trials.

Perilipin1 inhibits Nosema bombycis proliferation by promoting Domeless- and Hop-mediated JAK-STAT pathway activation in Bombyx mori.

Lipid droplets (LDs) are dynamic organelles that participate in the regulation of lipid metabolism and cellular homeostasis inside of cells. LD-associated proteins, also known as perilipins (PLINs), are a family of proteins found on the surface of LDs that regulate lipid metabolism, immunity, and other functions. In silkworms, pébrine disease caused by infection by the microsporidian Nosema bombycis (Nb) is a severe threat to the sericultural industry. Although we found that Nb relies on lipids from silkworms to facilitate its proliferation, the relationship between PLINs and Nb proliferation remains unknown. Here, we found Nb infection caused the accumulation of LDs in the fat bodies of silkworm larvae. The characterized perilipin1 gene (plin1) promotes the accumulation of intracellular LDs and is involved in Nb proliferation. plin1 is similar to perilipin1 in humans and is conserved in all insects. The expression of plin1 was mostly enriched in the fat body rather than in other tissues. Knockdown of plin1 enhanced Nb proliferation, whereas overexpression of plin1 inhibited its proliferation. Furthermore, we confirmed that plin1 increased the expression of the Domeless and Hop in the JAK-STAT immune pathway and inhibited Nb proliferation. Taken together, our current findings demonstrate that plin1 inhibits Nb proliferation by promoting the JAK-STAT pathway through increased expression of Domeless and Hop. This study provides new insights into the complicated connections among microsporidia pathogens, LD surface proteins, and insect immunity.IMPORTANCELipid droplets (LDs) are lipid storage sites in cells and are present in almost all animals. Many studies have found that LDs may play a role in host resistance to pathogens and are closely related to innate immunity. The present study found that a surface protein of insect lipid droplets could not only regulate the morphological changes of lipid droplets but also inhibit the proliferation of a microsporidian pathogen Nosema bombycis (Nb) by activating the JAK-STAT signaling pathway. This is the first discovery of the relationship between microsporidian pathogen and insect lipid surface protein perilipin and insect immunity.

In Silico Design and Synthesis of Antifungal Peptides Guided by Quantitative Antifungal Activity.

Antifungal peptides (AFPs) are emerging as promising candidates for advanced antifungal therapies because of their broad-spectrum efficacy and reduced resistance development. In silico design of AFPs, however, remains challenging, due to the lack of an efficient and well-validated quantitative assessment of antifungal activity. This study introduced an AFP design approach that leverages an innovative quantitative metric, named the antifungal index (AFI), through a three-step process, i.e., segmentation, single-point mutation, and global multipoint optimization. An exhaustive search of 100 putative AFP sequences indicated that random modifications without guidance only have a 5.97-20.24% chance of enhancing antifungal activity. Analysis of the search results revealed that (1) N-terminus truncation is more effective in enhancing antifungal activity than the modifications at the C-terminus or both ends, (2) introducing the amino acids within the 10-60% sequence region that enhance aromaticity and hydrophobicity are more effective in increasing antifungal efficacy, and (3) incorporating alanine, cysteine, and phenylalanine during multiple point mutations has a synergistic effect on enhancing antifungal activity. Subsequently, 28 designed peptides were synthesized and tested against four typical fungal strains. The success rate for developing promising AFPs, with a minimal inhibitory concentration of ≤5.00 µM, was an impressive 82.14%. The predictive and design tool is accessible at https://antifungipept.chemoinfolab.com.

A fully automatic MRI-guided decision support system for lumbar disc herniation using machine learning.

Background: Normalized decision support system for lumbar disc herniation (LDH) will improve reproducibility compared with subjective clinical diagnosis and treatment. Magnetic resonance imaging (MRI) plays an essential role in the evaluation of LDH. This study aimed to develop an MRI-based decision support system for LDH, which evaluates lumbar discs in a reproducible, consistent, and reliable manner. Methods: The research team proposed a system based on machine learning that was trained and tested by a large, manually labeled data set comprising 217 patients' MRI scans (3255 lumbar discs). The system analyzes the radiological features of identified discs to diagnose herniation and classifies discs by Pfirrmann grade and MSU classification. Based on the assessment, the system provides clinical advice. Results: Eventually, the accuracy of the diagnosis process reached 95.83%. An 83.5% agreement was observed between the system's prediction and the ground-truth in the Pfirrmann grade. In the case of MSU classification, 95.0% precision was achieved. With the assistance of this system, the accuracy, interpretation efficiency and interrater agreement among surgeons were improved substantially. Conclusion: This system showed considerable accuracy and efficiency, and therefore could serve as an objective reference for the diagnosis and treatment procedure in clinical practice.

Two-Stage Deep Learning Model for Diagnosis of Lumbar Spondylolisthesis Based on Lateral X-Ray Images.

BACKGROUND: Diagnosing early lumbar spondylolisthesis is challenging for many doctors because of the lack of obvious symptoms. Using deep learning (DL) models to improve the accuracy of X-ray diagnoses can effectively reduce missed and misdiagnoses in clinical practice. This study aimed to use a two-stage deep learning model, the Res-SE-Net model with the YOLOv8 algorithm, to facilitate efficient and reliable diagnosis of early lumbar spondylolisthesis based on lateral X-ray image identification. METHODS: A total of 2424 lumbar lateral radiographs of patients treated in the Beijing Tongren Hospital between January 2021 and September 2023 were obtained. The data were labeled and mutually identified by 3 orthopedic surgeons after reshuffling in a random order and divided into a training set, validation set, and test set in a ratio of 7:2:1. We trained 2 models for automatic detection of spondylolisthesis. YOLOv8 model was used to detect the position of lumbar spondylolisthesis, and the Res-SE-Net classification method was designed to classify the clipped area and determine whether it was lumbar spondylolisthesis. The model performance was evaluated using a test set and an external dataset from Beijing Haidian Hospital. Finally, we compared model validation results with professional clinicians' evaluation. RESULTS: The model achieved promising results, with a high diagnostic accuracy of 92.3%, precision of 93.5%, and recall of 93.1% for spondylolisthesis detection on the test set, the area under the curve (AUC) value was 0.934. CONCLUSIONS: Our two-stage deep learning model provides doctors with a reference basis for the better diagnosis and treatment of early lumbar spondylolisthesis.

Halogen doped graphene quantum dots modulate TDP-43 phase separation and aggregation in the nucleus.

TDP-43 is implicated in the dynamic formation of nuclear bodies and stress granules through phase separation. In diseased states, it can further condense into pathological aggregates in the nucleus and cytoplasm, contributing to the onset of amyotrophic lateral sclerosis. In this study, we evaluate the effect of graphene quantum dots (GQDs) with different functional groups on TDP-43's phase separation and aggregation in various cellular locations. We find that halogen atom-doped GQDs (GQDs-Cl, Cl-GQDs-OH) penetrate the nuclear envelope, inhibiting the assembly of TDP-43 nuclear bodies and stress granules under oxidative stress or hyperosmotic environments, and reduce amyloid aggregates and disease-associated phosphorylation of TDP-43. Mechanistic analysis reveals GQDs-Cl and Cl-GQDs-OH modulate TDP-43 phase separation through hydrophobic and electrostatic interactions. Our findings highlight the potential of GQDs-Cl and Cl-GQDs-OH in modulating nuclear protein condensation and pathological aggregation, offering direction for the innovative design of GQDs to modulate protein phase separation and aggregation.

Is AI 3D-printed PSI an accurate option for patients with developmental dysplasia of the hip undergoing THA?

BACKGROUND: In traditional surgical procedures, significant discrepancies are often observed between the pre-planned templated implant sizes and the actual sizes used, particularly in patients with congenital hip dysplasia. These discrepancies arise not only in preoperative planning but also in the precision of implant placement, especially concerning the acetabular component. Our study aims to enhance the accuracy of implant placement during Total Hip Arthroplasty (THA) by integrating AI-enhanced preoperative planning with Patient-Specific Instrumentation (PSI). We also seek to assess the accuracy and clinical outcomes of the AI-PSI (AIPSI) group in comparison to a manual control group. METHODS: This study included 60 patients diagnosed with congenital hip dysplasia, randomly assigned to either the AIPSI or manual group, with 30 patients in each. No significant demographic differences between were noted the two groups. A direct anterior surgical approach was employed. Postoperative assessments included X-rays and CT scans to measure parameters such as the acetabular cup anteversion angle, acetabular cup inclination angle, femoral stem anteversion angle, femoral offset, and leg length discrepancy. Functional scores were recorded at 3 days, 1 week, 4 weeks, and 12 weeks post-surgery. Data analysis was conducted using SPSS version 22.0, with the significance level was set at α = 0.05. RESULTS AND CONCLUSION: The AIPSI group demonstrated greater prosthesis placement accuracy. With the aid of PSI, AI-planned THA surgery provides surgeons with enhanced precision in prosthesis positioning. This approach potentially offers greater insights and guidelines for managing more complex anatomical variations or cases.

Comparative analysis of the intestinal flora of BmNPV-resistant and BmNPV-sensitive silkworm varieties.

Bombyx mori nucleopolyhedrovirus (BmNPV) is a very common and infectious virus that affects silkworms and hinders silk production. To investigate the intestinal flora of BmNPV-resistant and BmNPV-sensitive silkworm varieties, 16 S rDNA high-throughput sequencing was performed. The results of the cluster analysis showed that the intestinal flora of the resistant silkworm variety was more abundant than that of the sensitive silkworm variety. This was found even when infection with BmNPV caused a sharp decline in the number of intestinal floral species in both resistant and sensitive silkworm varieties. The abundances of the intestinal flora, including Aureimonas, Ileibacterium, Peptostreptococcus, Pseudomonas, Enterococcus, and Halomonas, in the resistant variety were considerably greater after infection with BmNPV than those in the sensitive variety. After infection with BmNPV, four kinds of important intestinal bacteria, namely, f_Saccharimonadaceae, Peptostreptococcus, Aureirmonas, and f_Rhizobiaceae, were found in the resistant silkworm variety. In the sensitive silkworm variety, only Faecalibaculum was an important intestinal bacterium. The differential or important bacteria mentioned above might be involved in immunoreaction or antiviral activities, especially in the intestines of BmNPV-resistant silkworms. By conducting a functional enrichment analysis, we found that BmNPV infection did not change the abundance of important functional components of the intestinal flora in resistant or sensitive silkworm varieties. However, some functional factors, such as the biosynthesis, transport, and catabolism of secondary metabolites (e.g., terpenoids and polyketides) and lipid transport and metabolism, were more important in the resistant silkworm variety than in the sensitive variety; thus, these factors may increase the resistance of the host to BmNPV. To summarize, we found significant differences in the composition, abundance, and function of the intestinal flora between resistant and sensitive silkworm varieties, especially after infection with BmNPV, which might be closely related to the resistance of resistant silkworm varieties to BmNPV.

The Function of Different Subunits of the Molecular Chaperone CCT in the Microsporidium Nosema bombycis: NbCCTζ Interacts with NbCCTα.

Chaperonin containing tailless complex polypeptide 1 (CCT) is a molecular chaperone protein that consists of eight completely different subunits and assists in the folding of newly synthesized peptides. The zeta subunit of CCT is a regulatory factor for the folding and assembly of cytoskeletal proteins as individuals or complexes. In this study, the zeta subunit of Nosema bombycis (NbCCTζ) is identified for the first time. The complete ORF of the NbCCTζ gene is 1533 bp in length and encodes a 510 amino acid polypeptide. IFA results indicate that NbCCTζ is colocalized with actin and ß-tubulin in the cytoplasm during the proliferative phase and that NbCCTζ is completely colocalized with NbCCTα in the cytoplasm of N. bombycis throughout the entire life cycle. Furthermore, the yeast two-hybrid assay revealed that the NbCCTζ interacts with NbCCTα. The transcriptional level of NbCCTζ is significantly downregulated by knocking down the NbCCTα gene, while the transcriptional level of NbCCTα is downregulated after knocking down the NbCCTζ gene. These results suggest that NbCCTζ may play a vital role in the proliferation of N. bombycis by coordinating with NbCCTα.

Agrobacterium rhizogenes-mediated marker-free transformation and gene editing system revealed that AeCBL3 mediates the formation of calcium oxalate crystal in kiwifruit.

The transformation and gene editing of the woody species kiwifruit are difficult and time-consuming. The fast and marker-free genetic modification system for kiwifruit has not been developed yet. Here, we establish a rapid and efficient marker-free transformation and gene editing system mediated by Agrobacterium rhizogenes for kiwifruit. Moreover, a removing-root-tip method was developed to significantly increase the regeneration efficiency of transgenic hairy roots. Through A. rhizogenes-mediated CRISPR/Cas9 gene editing, the editing efficiencies of CEN4 and AeCBL3 achieved 55 and 50%, respectively. And several homozygous knockout lines for both genes were obtained. Our method has been successfully applied in the transformation of two different species of kiwifruit (Actinidia chinensis 'Hongyang' and A.eriantha 'White'). Next, we used the method to study the formation of calcium oxalate (CaOx) crystals in kiwifruit. To date, little is known about how CaOx crystal is formed in plants. Our results indicated that AeCBL3 overexpression enhanced CaOx crystal formation, but its knockout via CRISPR/Cas9 significantly impaired crystal formation in kiwifruit. Together, we developed a fast maker-free transformation and highly efficient CRISPR-Cas9 gene editing system for kiwifruit. Moreover, our work revealed a novel gene mediating CaOx crystal formation and provided a clue to elaborate the underlying mechanisms.

Cuprotosis clusters predict prognosis and immunotherapy response in low-grade glioma.

Cuprotosis, an emerging mode of cell death, has recently caught the attention of researchers worldwide. However, its impact on low-grade glioma (LGG) patients has not been fully explored. To gain a deeper insight into the relationship between cuprotosis and LGG patients' prognosis, we conducted this study in which LGG patients were divided into two clusters based on the expression of 18 cuprotosis-related genes. We found that LGG patients in cluster A had better prognosis than those in cluster B. The two clusters also differed in terms of immune cell infiltration and biological functions. Moreover, we identified differentially expressed genes (DEGs) between the two clusters and developed a cuprotosis-related prognostic signature through the least absolute shrinkage and selection operator (LASSO) analysis in the TCGA training cohort. This signature divided LGG patients into high- and low-risk groups, with the high-risk group having significantly shorter overall survival (OS) time than the low-risk group. Its predictive reliability for prognosis in LGG patients was confirmed by the TCGA internal validation cohort, CGGA325 cohort and CGGA693 cohort. Additionally, a nomogram was used to predict the 1-, 3-, and 5-year OS rates of each patient. The analysis of immune checkpoints and tumor mutation burden (TMB) has revealed that individuals belonging to high-risk groups have a greater chance of benefiting from immunotherapy. Functional experiments confirmed that interfering with the signature gene TNFRSF11B inhibited LGG cell proliferation and migration. Overall, this study shed light on the importance of cuprotosis in LGG patient prognosis. The cuprotosis-related prognostic signature is a reliable predictor for patient outcomes and immunotherapeutic response and can help to develop new therapies for LGG.

Clinical application of artificial intelligence-assisted three-dimensional planning in direct anterior approach hip arthroplasty.

PURPOSE: The objective of this study was to investigate the efficacy of an artificial intelligence-assisted 3D planning system (AIHIP) in total hip arthroplasty by direct anterior approach and assess the reliability of the AIHIP preoperative program in terms of both interobserver and intraobserver agreement. METHODS: A retrospective analysis was conducted on patients who underwent unilateral primary THA via direct anterior approach from June 2019 to March 2022. Participants were randomly assigned to receive either the AIHIP system (n = 220) or the 2D template (control group) (n = 220) for preoperative planning. The primary outcome aimed to evaluate the correspondence between the prosthesis selected intro-operation and the one planned preoperatively, as well as to calculate the intraclass correlation coefficient (ICC). Secondary outcomes included operation time, intraoperative blood loss, fluoroscopy times, Harris hip score (HHS), lower limb length difference (LLD), femoral offset (FO), and bilateral femoral offset difference. RESULTS: No significant differences were observed in gender, age, body mass index (BMI), aetiology, and American Society of Anesthesiologists (ASA) score between the two groups. Both planning methods exhibited good intraobserver agreement for component planning (ICC: 0.941-0.976). Interobserver agreement for component planning was comparable between the two methods (ICC: 0.882-0.929). In the AIHIP group, the accuracy of acetabular cup and femoral stem prosthetics planning significantly improved, with accuracies within the size range of ± 0 and ± 1 being 76.8% and 90.5% and 79.5% and 95.5%, respectively. All differences between two groups were statistically significant (p < 0.05). Patients receiving AIHIP preoperative planning experienced shorter operation times, reduced intraoperative blood loss, fewer fluoroscopy times, and lower leg length discrepancy (LLD) (p < 0.05). Moreover, they demonstrated a higher Harris hip score (HHS) at three days post-surgery (p < 0.05). However, no significant differences were found in femoral offset (FO), difference of bilateral femoral offsets, and HHS at 1 month after the operation. CONCLUSION: Utilizing AIHIP for preoperative planning of direct anterior approach THA can significantly enhance the accuracy of prosthetic sizing with good reliability, decrease operation time, reduce intraoperative blood loss, and more effectively restore the length of both lower limbs. This approach has greater clinical application value.