Results: Twenty-seven patients achieved a clinical response; symptoms of depression and suicidal ideation were significantly improved after treatment with ECT, which was reflected in a significant decrease in the scores of HAMD and BSSI (p < 0.001). The efficacy was predicted by ALFF, fALFF, ReHo, and whole-brain-based functional connectivity. We found that models built on a subset of features of ALFF in the left insula, fALFF in the left superior parietal gyrus, right superior parietal gyrus, and right angular, and functional connectivity between the left superior frontal gyrus, dorsolateral–right paracentral lobule, right middle frontal gyrus, orbital part–left cuneus, right olfactory cortex–left hippocampus, left insula–left thalamus, and left anterior cingulate gyrus–right hippocampus to have the best predictive performance (AUC > 0.8). Conclusions: The local brain function in the insula, superior parietal gyrus, and angular gyrus as well as characteristic changes in the functional connectivity of cortical–limbic circuits may serve as potential markers for efficacy judgment of ECT and help to provide optimized individual treatment strategies for adolescents with depression and suicidal ideation in the early stages of treatment.Objects: The efficacy of electroconvulsive therapy (ECT) in the treatment of adolescents with treatment-refractory depression is still unsatisfactory, and the individual differences are large. It is not clear which factors are related to the treatment effect. Resting-state fMRI may be a good tool to predict the clinical efficacy of this treatment, and it is helpful to identify the most suitable population for this treatment. Methods: Forty treatment-refractory depression adolescents were treated by ECT and evaluated using HAMD and BSSI scores before and after treatment, and were then divided into a treatment response group and a non-treatment group according to the reduction rate of the HAMD scale. We extracted the ALFF, fALFF, ReHo, and functional connectivity of patients as predicted features after a two-sample  Electroconvulsive therapy (ECT) is considered to be one of the best methods for MDD for all ages ,2, especThe efficacy of ECT has been found to correlate with an increased fractional amplitude of low-frequency fluctuation (fALFF) in regions such as the prefrontal cortex, insula, and hippocampus, as well as increased GMV in regions such as the anterior cingulate gyrus, insula, thalamus, caudate nucleus, and hippocampus . These sWith the development of artificial intelligence (AI), machine learning techniques have also started to be frequently used in the diagnosis and risk prediction of depression. Cui et al.  developeThe aim of the study is to investigate the pattern differences at baseline in adolescents with treatment-refractory depression with different responses to ECT. Predictive models for the responding and non-responding groups were constructed using analyses based on ALFF, fALFF, ReHo, and FC. We used a logistic regression model (LRM) as well as SVM for prediction, and brain imaging at baseline of adolescents showing a response to ECT may help to expand our understanding of brain function predictors of the response to ECT.≥ 17; (2) with a diagnosis of treatment refractory depression and no history of ECT treatment; and (3) patients with severe suicidal ideation  in the past week. Participants were excluded if they: (1) had a neurological or serious physical condition, any history of alcohol or drug abuse, any other somatic diseases, or morphological anomalies of the brain; (2) had any surgically placed electronic or metal materials that might interfere with fMRI assessment; or (3) had head motion exceeding 2.5 mm in translation or 2.5° in rotation. The clinical scale was assessed using HAMD and BSSI, response rate = (pre-treatment HAMD − post-treatment HAMD)/pre-treatment HAMD; if the response rate was ≥50%, they were considered to be responders, whilst if the response rate was <50%, they were considered to be non-responders. The study protocol was approved by the Human Research and Ethics Committee of the First Affiliated Hospital of Chongqing Medical University (no. 2017-157). Written informed consent was obtained from all adolescents and their parents. We registered the study in the Chinese Clinical Trial Registry, the ID is ChiCTR2200064527.Forty adolescents with treatment-refractory depression between 12 and 17 years of age were enrolled. The diagnosis was confirmed by two psychiatrists using the Mini International Neuropsychiatric Interview for Children and Adolescents (MINI-KID). The inclusion criteria were as follows: (1) the Hamilton Depression Rating Scale (HAMD 17) Modified bitemporal ECT was delivered by Thymatron DGx  at the First Affiliated Hospital of Chongqing Medical University. The first three sessions of ECT took place on continuous days; the remaining were performed every 2 days, with a break on weekends; after eight sessions, the ECT was completed. The first energy for ECT was 5% for all patients. The stimulation energy was adjusted based on the seizure time. The energy was increased by 5% in the subsequent treatment if the seizure time was <25 s. Anesthesia was induced with succinylcholine (0.5–1 mg/kg) and propofol (1.5–2 mg/kg).2; matrix = 64 × 64; flip angle = 90°; slice number = 33; slice thickness/gap = 4.0/0 mm; scanner time = 8 min; and 240 volumes. Three-dimensional T1-weighted MR images were used for rs-fMRI co-registration .MR images were obtained using a 3T GE Signa HDxt scanner  with an eight-channel head coil. Participants were instructed to relax with their eyes closed, stay awake, and avoid thinking as much as possible. None of the patients reported falling asleep during the scan. Foam pads and earplugs were used to fix their heads to minimize head motion and reduce machine noise, respectively. The echo-planar imaging pulse sequence parameters were as follows: repetition time (TR) = 2000 ms; echo time (TE) = 40 ms; field of view (FOV) = 240 × 240 mmThe data were preprocessed using DPARSF software. The specific preprocessing process is as follows. (1) Data format conversion: convert DICOM format to NIFTI format. (2) Remove first time point: remove the initial 10 time points. (3) Slice timing: correct each layer of scanned data to one time point. (4) Realignment: covariate processing of white matter signals, cerebrospinal fluid signals, and head movement parameters  using the Fristion-24 model. (5) Spatial normalization: because of the differences in subject head size, we need to perform spatial normalization, as follows. DARTEL alignment is used to align the brain fMRI images to the standard brain template, the standardized images need to be resampled, and the spatial resolution of the resampled functional images is 3 mm × 3 mm × 3 mm. (6) Spatial smoothing: the purpose is to reduce the impact of spatial noise on the data and reduce the differences in brain structure between subjects. (7) Detrending: during data acquisition, the noise of the machine will gradually increase, and this process may make our data change accordingly, so we need to complete the detrending to remove this effect. (8) Low-pass filter (0.01–0.10 Hz): the purpose of this is to reduce the impact of physiological noise such as the subject’s breathing and heartbeat on the acquired data. The next step is to calculate the whole-brain ALFF, fALFF, and ReHo for all patients; feature extraction based on the AAL template extracts the average ALFF, fALFF, and ReHo for the 90 brain regions of the patient group and FC for each brain region based on the whole brain as features.t-test was performed for each feature, and features with p < 0.05 were screened; (2) the optimal subset of features was selected using LASSO. In this method, the parameter λ controls the balance between data fit and sparsity, which is a parameter determined by using 10-fold cross-validation. Based on the selected features, LRM and SVM are constructed. SVM are a class of generalized linear classifiers that perform the binary classification of data in a supervised learning manner, where the decision boundary is a hyperplane of maximum margins for the learned samples, which can be reduced to a problem of solving convex quadratic programming. For the model built from the training set, the performance of the model is evaluated using a test set. The evaluation metrics include the accuracy (ACC), sensitivity (SEN), specificity (SPEC), positive prediction rate (PPV), negative prediction rate (NPV), area under the ROC curve (AUC), and discriminant performance . The following R packages  were used for pattern classification analysis: .Based on the dataset of 40 patients, 75% of the data was randomly selected as the training set, and the remaining 25% was used as the validation set. Based on the training set, feature selection was performed as follows: (1) a two-sample A total of 40 adolescents with treatment-refractory depression enrolled in the study completed ECT. Of these, 27 (67.5%) patients achieved a clinical response (HAMD rate ≥ 50%). The other 13 (22.5%) did not achieve a clinical response (HAMD reduction rate < 50%), and there were no significant differences in age, gender, education, disease duration, HAMD, or BSSI scores between the two groups at baseline. After ECT, both groups showed a reduction in depressive and suicidal ideation scores .The performance of the LRM and SVM built based on the optimal subset of features selected for the training set in the validation set is shown in The predictive performance of the brain function of nine brain regions for efficacy was further evaluated based on the full data, which showed that the AUC of the patient group at baseline was 0.829 for ALFF of the INS.L, 0.835 for fALFF of the SPG.L, 0.781 for fALFF of the SPG.R, 0.721 for fALFF of the ANG.R, 0.687 for FC of SFGdor.L–PCL.R, 0.909 for FC of ORBmid.R–CUN.L, 0.829 for FC of OLF.R–HIP.L, 0.798 for FC of INS.L–THA.L, and 0.852 for FC of ACG.L–HIP.R; the ROC curves are shown in This study investigated the possible predictive ability of brain functional imaging to predict whether adolescents with treatment-refractory depression respond to ECT. Our results showed that the accuracy of LRM is 81.8% and accuracy of SVM is 81.8%. We found that the ALFF of INS.L, the fALFF of SPG.L, SPG.R, ANG.R, and the FC of SFGdor.L–PCL.R, ORBmid.R–CUN.L, OLF.R–HIP.L, INS.L–THA.L, and ACG.L–HIP.R may predict the response to ECT in adolescents with depression. The present results suggest that local brain function and FC may serve as potential predictors of response to ECT in depressed adolescent patients.Both the dorsolateral superior frontal gyrus and the orbitofrontal middle gyrus are important regions of the prefrontal cortex, and the dorsolateral prefrontal cortex is thought to have a relatively important role in working memory and emotion regulation ,11, whilThe relationship between the prefrontal cortex and depression has also been explored in more studies in rs-fMRI-based studies, such as Zhang et al. , who fouWe found that an abnormal FC in subcortical areas may predict the response to ECT in adolescents with treatment-refractory depression, such as INS and ACG, and also found that both the local brain function and FC in INS.L were predictive of the response to ECT. INS is an important component of the limbic system, which is thought to represent cognitive, emotional, and visual capacities. Studies have also demonstrated that there is a reduction in the FC of INS with other brain regions in depressive patients, such as the anterior cingulate cortex, which can indicate the severity of depressive symptoms . BouckaeThe parietal cortex, which plays a crucial role in the process of focusing attention, mainly includes the postcentral gyrus, superior parietal gyrus, and inferior parietal gyrus. The parietal lobe of the brain is composed primarily of the sensory and cortical components that monitor the response of various body parts to external stimuli. In addition, the parietal lobe is also involved in working memory and attentional capacity . In our Methodologically, this study used both LRM and SVM, which were applied to demonstrate the validity of the results. Validation algorithms were used to verify the reproducibility and reliability. Machine learning studies will have an impact on precision medicine. The development of radiomics has created an ideal environment for the application of brain imaging in psychiatry, where psychiatric disorders do not yet appear as “lesions” in conventional brain imaging, but where markers and features predictive of mental disorders can still be obtained. We gathered functional brain activity features from functional brain imaging, and stepwise analysis can facilitate our findings to change clinical practice, which can contribute to the dissemination of potential markers.There are still some limitations; first, we used medications in our study, so we could not exclude the impact of medications. Second, the prediction of this study mainly includes the brain function feature, such as ALFF, fALFF and functional connectivity. This result may not be reliable enough in other samples, so more indicators can be included in future research, such as biochemistry, gene, EEG, cognition and others, which may enhance the predictive effect of treatment response to depression. Third, because our sample size is small and has not been validated in an independent sample, our results should be treated with caution that may not apply to other independent samples. Due to the small amount of data, this study only preliminarily proves the prediction performance of functional characteristics. The sample should be further increased, especially by incorporating a multi-center sample, to establish a more reliable and better performance model. Finally, we did not observe the long-term effects of ECT for adolescents, so further research is needed.In summary, altered brain function in adolescents with treatment-refractory depression may be an important cause of symptom onset, which also suggests that brain function may play a predictive role for the effect of ECT in depressive adolescents. This study explores the predictive power of local brain function and functional connectivity on the efficacy of ECT in adolescent with treatment-refractory depression, and the results show high accuracy. It also evokes that brain regions such as the superior frontal gyrus, superior parietal gyrus, cingulate cortex, hippocampus, thalamus, and insula have the potential to predict the response to ECT.


Objective: Explore a new deep learning (DL) object detection algorithm for clinical auxiliary diagnosis of lumbar spondylolisthesis and compare it with doctors’ evaluation to verify the effectiveness and feasibility of the DL algorithm in the diagnosis of lumbar spondylolisthesis.Methods: Lumbar lateral radiographs of 1,596 patients with lumbar spondylolisthesis from three medical institutions were collected, and senior orthopedic surgeons and radiologists jointly diagnosed and marked them to establish a database. These radiographs were randomly divided into a training set , a validation set (n = 240), and a test set (n = 239) in a ratio of 0.7 : 0.15: 0.15. We trained two DL models for automatic detection of spondylolisthesis and evaluated their diagnostic performance by PR curves, areas under the curve, precision, recall, F1-score. Then we chose the model with better performance and compared its results with professionals’ evaluation.Results: A total of 1,780 annotations were marked for training , validation (263), and test (275). The Faster Region-based Convolutional Neural Network (R-CNN) showed better precision (0.935), recall (0.935), and F1-score (0.935) in the detection of spondylolisthesis, which outperformed the doctor group with precision (0.927), recall (0.892), f1-score (0.910). In addition, with the assistance of the DL model, the precision of the doctor group increased by 4.8%, the recall by 8.2%, the F1-score by 6.4%, and the average diagnosis time per plain X-ray was shortened by 7.139 s.Conclusion: The DL detection algorithm is an effective method for clinical diagnosis of lumbar spondylolisthesis. It can be used as an assistant expert to improve the accuracy of lumbar spondylolisthesis diagnosis and reduce the clinical workloads. Spondylolisthesis implies forward translation of the superior vertebra relative to the adjacent inferior vertebra on the sagittal plane . The etiAccording to relevant guidelines, the lumbar lateral radiograph in a standing position is the most appropriate non-invasive examination method for detecting spondylolisthesis . Some reAmong various forms of artificial intelligence (AI), machine learning is the most widely applied . As an eIn the study, we proposed a DL algorithm to diagnose spondylolisthesis using only lumbar lateral radiographs. 1) To train the best model using the multi-center dataset and ensure stable detection performance; 2) To compare diagnostic performance between the detection model and clinical doctors; 3) To compare the clinician’s diagnostic performance with and without the assistance of the DL model. It was expected that our DL model could act as an assistant to help doctors reduce medical errors during diseases detection and treatment.This is a retrospective study involving multiple institutions. The study was approved by the Institutional Ethics Committee, and the requirement for informed consent was waived due to the retrospective nature of the study and negligible risks involved. Patients whose conditions fit for the study were selected from the databases of the Union Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology, Daye People’s Hospital, and Nanzhang County People’s Hospital.In this retrospective study, the inclusion criteria were as follows: 1) patients aged 18 years or older; 2) patients diagnosed with lumbar spondylolisthesis; 3) including complete lateral imaging of the lumbar spine. The criteria for exclusion included: 1) patients with a history of spinal fracture, deformity, tumor, osteomyelitis, or internal fixation; 2) poor X-ray imaging; 3) foreign objects obstructing affect image reading. Multiple spondylolisthesis observed from plain radiographs was not an exclusion criterion. Finally, a total of 1,596 radiographs from patients with spondylolisthesis diagnosed between December 2017 to December 2022 were selected for this study. The detailed selection process is shown in The lateral X-ray images were analyzed and graded by a chief orthopedic physician with more than 15 years of experience in spine specialties and a chief physician of imaging department with more than 15 years of professional experience in imaging. In cases of disagreement, a chief orthopedic expert with 20 years of clinical experience reviewed the patient’s clinical information and additional imaging examination, and arrived at a conclusion after discussions with those two physicians.The classification of lumbar spondylolisthesis is divided into 4 grades according to the Meyerding classification method . The anthttps://github.com/wkentaro/labelme).All the acquired X-ray images of the lumbar spine were stored in high-quality JPEG format. And the region of interest (RoI) of each image was manually annotated by experienced orthopedic surgeons and radiologists based on the previous image diagnosis results. The RoIs of the posterior vertebral body were manually labeled using the Labelme software package  taken from December 2017 to December 2022 for training, validation and testing . These rData was processed to ensure the detection accuracy of the target. The imported images were resized with the shorter edge’s dimensions fixed and pixels to 800, and the longer side was resized proportionally. At the same time, there is a 50% probability for each image to be flipped horizontally, increasing the richness of the image. In addition, through image normalization, the value of features (or images) were adjusted to a similar range, which speeds up network convergence. Specifically, image normalization is the process of transforming a raw image to a unique standardized form through a series of transformations in order to eliminate the influence of other transformation functions on the image. In this study, we used common normalization parameters: mean =  and std = . These parameters can make different images comparable and improve model training effectiveness.Two DL detection models, Faster R-CNN  and Retihttp://www.ubuntu.com) with an NVIDIA V100 GPU (CUDA 10.2 and cuDNN 7.6.5) (http://developer.nvidia.com), 32 GB VRAM.We ran the DL framework-pytorch on the Ubuntu 16.04 operation system , we obtained the performance difference of two models in classification. These indicators were presented in detail in the Furthermore, to validate the performance of the DL models in images without spondylolisthesis, lateral lumbar radiographs of 239 subjects  without spondylolisthesis were added as a control group, and the number of false positives (FPs) in the control group was calculated.To compare the difference in diagnosing spondylolisthesis by DL algorithms and doctors, we set up a group of six doctors, and compared their results with those of the DL model. The six doctors in this group are all orthopedic surgeons with more than 5 years of orthopedic experience and passed the intermediate certificate examination (none of the six doctors were involved in diagnosis or labeling). We recorded the precision, sensitivity, F1-score, and the diagnosis time of the doctor group. Four weeks later, the diagnostic test of the doctor group assisted by AI was carried out, in which the images were shuffled.Since each lateral lumbar radiograph may have multiple locations of lumbar spondylolisthesis while generally more parts are normal, receiver operating characteristic (ROC) curves and specificities are not applicable here. To study the impact of resolution on detection of lumbar spondylolisthesis, we used images with different resolutions for detection and plotted corresponding fROC curves.t-test was used to compare diagnostic performances of Faster R-CNN and RetinaNet. The Mann-Whitney was used to compare diagnostic performances of doctors with or without AI assistance. The Student’s t-test was used to compare diagnostic performances of Faster R-CNN and doctors without AI assistance. The bootstrapping were performed using packages “boot” of R 4.1.2 . Other statistical analyses were performed using SAS Statistics software . All statistical tests were two-sided, and p < 0.05 was considered statistically significant.Continuous variables were presented as median [interquartile range (IQR)]. Categorical variables were expressed by counts and percentages. For the comparison of baseline characteristics among different data sets, the ANOVA test was used for continuous variables and χ2 test was used for categorical variables. Precision, recall, F1-score, TP, FN, and FP were selected as diagnostic performances, and the corresponding 95% confidence intervals were estimated using bootstrapping with 1,000 bootstraps. The paired-samples p > 0.05)  .The PR curves output by the two trained DL models are shown in The original image was imported into the AI model and the model automatically executed the entire procedure and produced results with position markers and spondylolisthesis probability of spondylolisthesis . The timThe six points without AI assistance in the doctor group were all near the bottom of the fROC curve, and the six points with higher values represented diagnosis after AI assistance . The docp = 0.004), the average sensitivity of diagnosis increased by 8.2% from 0.892 to 0.974 (p = 0.004), and the average F1 score increased by 6.4% from 0.910 to 0.974. Without AI assistance and with AI assistance, the average diagnosis time of the doctor group was 25.452 s and 18.355 s, respectively (p = 0.004), and the average diagnosis time of each plain X-ray film was shortened by 7.139 s with AI assistance.As shown in The results showed that when the resolution was reduced to 512 pixels, the detection performance decreased slightly, while a significant decrease in detection performance occurred when the resolution was reduced to 256 pixels .In our study, we proposed a DL-based identification and diagnosis method for lumbar spondylolisthesis. The trained DL model, in the independent testing set, the precision of DL model for lumbar spondylolisthesis diagnosis was 0.935, recall was 0.935, and F1-score was 0.935. Compared with evaluation of attending physicians in orthopedics, the performance of the DL model was significantly higher. With the assistance of AI, the diagnostic performance of the doctor group has been significantly improved.Lumbar spondylolisthesis is one of the most common spinal disorders, with studies showing that approximately 4%–6% of the population suffer from spondylolisthesis and lumbar spondylolisthesis . AlthougMRI/CT/X-rays can be used to detect spondylolisthesis, but according to the latest guidelines, lateral lumbar radiographs are the most appropriate non-invasive examination for spondylolisthesis, especially in the absence of reliable evidence. MRI is mostly used to evaluate the neurological status of spondylolisthesis patients with spinal stenosis, and CT mostly for patients with contraindications for MRI examination.Early studies on AI diagnosis of spondylolisthesis primarily concentrated on CT/MRI images, which also produced positive outcomes. This study focused on the detection of spondylolisthesis in lumbar spine radiographs. We first proposed to detect spondylolisthesis by identifying the structure between the posterior borders of adjacent vertebral bodies, so as to achieve high-precision detection of spondylolisthesis on lateral lumbar radiographs. In this study, we developed and investigated two different types of algorithms for spondylolisthesis detection, where Faster R-CNN showed better performance than RetinaNet in spondylolisthesis detection. Faster R-CNN is a two-stage algorithm with real-time performance and higher detection accuracy, while RetinaNet is a state-of-the-art one-stage algorithm that focuses on detection speed . Consideetc. Single-stage detection algorithms do not include the stage of candidate region proposal generation, and directly give class probabilities and spatial coordinates of objects. You only look once (YOLO) and RetinaNet are typical single-stage algorithms.Currently, mainstream target detection algorithms based on DL are mainly divided into two-stage and single-stage. The first stage of the two-stage algorithm works to identify candidate regions in the target image, and the subsequent stage to classify the candidate regions. Typical two-stage algorithms include Region-based Convolutional Neural Network (R-CNN), Fast R-CNN and Faster R-CNN, Analysis of the diagnostic results of the physician group showed that they frequently missed multiple or minor spondylolisthesis. However, Faster R-CNN extracts feature maps for each input image through region proposal networks and sliding window M × N feature maps, which leads to the algorithm being able to accurately detect spondylolisthesis . And theFor the detection of images with different resolutions, when the resolution is reduced to 512, the detection effect slightly decreases, and when further reduced to 256, the detection effect significantly decreases. This may be in lateral lumbar spine images, the structure between vertebrae is a small target relative to the entire image. If the image resolution is lowered, information may be lost, making it difficult to fully reflect vertebral features and leading to a decrease in detection performance.In detection, missed diagnosis is inevitable. When analyzing the images of missed diagnosis, we found that severe lumbar spondylolisthesis, especially those with the grade greater than 4, are prone to be missed. This may be because most patients only have mild to moderate lumbar spondylolisthesis, and the number of patients with severe lumbar spondylolisthesis is relatively small. During the training process, algorithms may not be able to fully learn about particularly severe lumbar spondylolisthesis. However, in actual clinical work, this type of severe lumbar spondylolisthesis is rarely missed because its degree of slippage is severe and obvious on plain films. This suggests that we need to collect more data to improve algorithm performance.This study still has some limitations. First, the DL algorithm is designed to detect lumbar spondylolisthesis, but since it would be affected by the shape of the vertebral body, especially the shape of the posterior edge of the vertebral body, cases with a medical history of fractures, tumors, osteomyelitis, and internal fixation operations are excluded. Therefore, users should consider this major limitation. Second, this model can only identify whether there is spondylolisthesis on the lateral lumbar spine radiograph, but the type of spondylolisthesis  still needs to be comprehensively analyzed by the doctor based on the patient’s medical history and other image details and data. Third, the basic diagnostic data was mainly analyzed and assessed by an orthopedist and a radiologist who specialized in the spine. The limited number of specialists involved may compromise the reliability of the DL models’ performance. If more experienced doctors participate in diagnosis and labeling, human bias can be effectively reduced, thereby improving research validity. Finally, although we have used data from three hospitals and the amount of data is large enough, and the training effect is good, it is still not enough for a mature and excellent algorithm. Therefore, in the future, we will collect more data from hospitals and establish larger multi-center databases and external validation sets to further improve algorithm performance.Although these factors indicate that there is room for further investigation, we believe that the rigor and standards we demonstrated for the research ensured its value and the overall results deserve full consideration. If the performance of the algorithms we proposed can be validated by others, this fast and accurate model has great potential to assist doctors in emergency rooms, and outpatient and inpatient clinics. Besides, in areas with limited resources and a shortage of medical professionals, this model could provide spondylolisthesis prediagnosis from readily available X-ray images.We developed a DL model to diagnose and locate lumbar intervertebral position of spondylolisthesis. Compared with the orthopedic surgeons, the DL model showed significant advantages in the diagnostic accuracy and speed of lumbar spondylolisthesis. The results proved that our approach is feasible and demonstrated the excellent performance of the DL model in the diagnosis of lumbar spondylolisthesis. This technology is expected to become a second expert, assisting clinicians to improve the accuracy of lumbar spondylolisthesis diagnosis and properly reduce the frontline doctors’ workloads.


Previous observational studies have reported that thyroid dysfunction is associated with hallux valgus (HV). However, the causal effect of thyroid dysfunction on hallux valgus is still unknown. To assess whether there is a causal relationship between thyroid dysfunction and hallux valgus, we performed a two-sample Mendelian randomization (MR) study.Q test, MR-presso, MR-Egger regression, and the leave-one-out test were used as sensitivity analysis, and the MR-pleiotropy test was performed to examine pleiotropy.The data of the two-sample Mendelian randomization study were obtained from public databases. In this study, hypothyroidism, hyperthyroidism, free thyroxine (FT4), and thyrotropin (TSH) were chosen as exposures. The single nucleotide polymorphisms (SNP) of hypothyroidism and hyperthyroidism were from the genome-wide association studies (GWAS) of the IEU database, including 337,159 subjects. Data for FT4 and TSH  were extracted from the ThyroidOmics Consortium. HV was used as the outcome. The SNPs associated with HV were selected from a GWAS of 202,617 individuals in the fignngen database. The inverse variance weighted (IVW) method was used as the primary analysis. Four complementary methods were applied, including MR-presso, MR-Egger, and weighted median. In addition, Cochran’s p = 0.028). There were no significant causal effects of hyperthyroidism, FT4, and TSH on HV (p > 0.05). Sensitivity analyses showed that the results were robust and reliable, and no horizontal pleiotropy was detected.According to the results of IVW, we found that there was a causal relationship between hypothyroidism and HV, and hypothyroidism increased the incidence of HV (OR = 2.838 (95% CI: 1.116–7.213); Our findings provided genetic support that hypothyroidism might increase the risk of HV. It will predict the occurrence of HV in patients with hypothyroidism and provide suggestions for early prevention and intervention. Hallux valgus (HV) is one of the most common forefoot deformities , which iPrevious large-scale observational studies have found a significant correlation between hypothyroidism and HV , but no Based on previous studies, we hypothesize that there may be a causal relationship between thyroid dysfunction and the risk of HV, and in this study, two-sample Mendelian randomization (MR) analysis was used to verify this. MR is an epidemiological statistical method that uses genetic variation as an instrumental variable (IV) to infer causal relationships between exposures and outcomes . BecauseWe aimed to investigate the causal relationship between thyroid dysfunction and the risk of HV. Because all of the data in this study were obtained from public databases, no consent was required from the participants. We reported our study according to the STROBE-MR statement . The keyhttps://gwas.mrcieu.ac.uk/), including 337,159 subjects and 10,894,596 SNPs. The study included 16,376 hypothyroidism samples and 320,783 control samples. There were also 2,547 hyperthyroidism cases and 334,612 ncases. The GWAS data of FT4 and TSH are all from The ThyroidOmics Consortium database , containing 72,167 samples , hyperthyroidism (decreased TSH), FT4, and TSH were chosen as exposures. The single nucleotide polymorphisms (SNP) of hypothyroidism and hyperthyroidism were from the genome-wide association studies (GWAS) of the IEU database ( samples Table 1.https://www.finngen.fi/en), which included 20,2617 samples  and 16,383,115 SNPs. All participants were of European ancestry.HV was selected as the outcome, and its GWAS data were obtained from the FinnGen database . To remove the linkage disequilibrium between each SNP, we set the distance to 10,000 KB and the LD r2 to< 0.001 (http://www.phenoscanner.medschl.cam.ac.uk/) to search for phenotypes that may be affected by each SNP and remove the SNPs related to HV-associated phenotypes  based on three assumptions Figure 1o< 0.001 . To remoenotypes . SNPs foenotypes . Finally removed  .p< 0.05 representing statistical significance.We used inverse variance weighting (IVW) as the primary method to evaluate the causal relationship between thyroid dysfunction and the risk of HV . IVW assQ was used as a heterogeneity test; p< 0.05 represents the existence of heterogeneity  ; = 0.028) Figure 3p = 0.131) and FT4 (p = 0.132) were used as exposure. However, when hypothyroidism (p = 0.001) and TSH (p = 0.0004) were considered exposures, we discovered heterogeneity. The sources of these heterogeneities may be due to differences in the source of SNP data, experimental conditions, detection methods, and included populations. When heterogeneity was present, the random-effects model in IVW was chosen  express TRalpha-1 mRNA at regions of bone remodeling . A part Other studies have found that the synovium of patients with rheumatoid arthritis (RA) and osteoarthritis (OA) contains a network of thyroid hormones. Thyroid hormones are strongly biodegraded in the synovium, and synoviocytes play an important role in the activation and degradation of thyroid hormones . HV is fMost of the previous knowledge about the etiology of HV is that abnormalities in anatomy or biomechanics lead to the occurrence of the disease . No studThere are some advantages to our study. First of all, compared with observational studies, we use MR studies for causal inference and select genetic variation as IV, which can avoid the interference of other confounding factors and reverse causality. Second, all samples were drawn from European populations, and our results are less susceptible to differences in demographics. Most importantly, we demonstrate for the first time a causal relationship between hypothyroidism and HV, which may provide new strategies for the treatment of HV.There are also some deficiencies in this study. First, thyroid hormones include multiple subtypes, such as T3 and T4, but due to research limitations, we cannot obtain the SNP data of the remaining subtypes. We were not able to explore other thyroid hormone subtypes as exposures for causal effects on HV. Second, FT4 and TSH are often used as indicators for the diagnosis of hypothyroidism, but they have not shown a causal relationship with hallux valgus. This may be caused by a relatively insufficient sample size of FT4 and TSH. Third, the participants we included were all from European populations, so it is not clear whether our findings are applicable to other populations. In addition, some of the methods we used in this study did not produce the same results as IVW, but all of the SNPs included in our study met the assumption of effective IV, and the MR-presso results were consistent with IVW, so our results are still reliable.We used the two-sample MR to study the causal relationship between thyroid function and HV and proved that there is a positive causal relationship between hypothyroidism and HV. Hypothyroidism could increase the risk of HV. It will predict the occurrence of HV in patients with hypothyroidism and provide suggestions for early prevention and intervention. However, the results of this study need to be further confirmed by basic experiments.The original contributions presented in the study are included in the article/Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.BX: research design and paper writing. ZB, XC, and DN: collection and organization of data. CZ, XS, and ZG: analysis and visualization of results. JW and WS: research quality assessment. All authors contributed to the article and approved the submitted version.


Childhood cancer is becoming an emerging healthcare issue in mainland China. Extensive evidence in the literature has demonstrated that cancer and its treatment experience can cause psychological distress that can lead to developmental problems in children with cancer. This study aims to screen for early warning of psychological crisis in children aged 8–18 years with cancer, establish a model of early warning intervention for children with cancer, and explore its application effects.We recruited 345 children with cancer and aged 8–18 years as the study participants, of whom 173 children were selected as historical controls during the period between December 2019 and March 2020 and 172 children were selected as the intervention group during the period between July 2020 and October 2020. The routine nursing model was adopted for the control group, and the early warning and intervention model was applied for the intervention group. The early warning and intervention model consisted of four stages: (1) establishing a management team to assess the risk of psychological crisis, (2) developing a three-level early warning response mechanism, (3) developing specific response plans, and (4) creating an evaluation summary and optimization mode. The DASS-21 was used to evaluate the psychological status of children with cancer before and 3 months after the intervention.t = 12.144, P < 0.05), anxiety symptoms , and stress symptoms  in the intervention group. The incidence rates of depression, anxiety, and stress were significantly lower in the intervention group  than in the control group  .The average age of the control group was 11.43 ± 2.39 years, with 58.96% boys and 61.27% diagnosed with leukemia. The average age of the intervention group was 11.62 ± 2.31 years, with 58.72% boys and 61.63% diagnosed with leukemia. There was a significant reduction in depressive symptoms (4.91 ± 3.98, Our study suggests that the early detection and timely management of psychological symptoms through a nursing intervention model can effectively reduce depressive, anxiety, and stress symptoms in Chinese children with cancer. Future work should include conducting qualitative interviews to understand the psychological experiences of children with cancer throughout their entire life cycle. Cancer is a major disease that seriously threatens the physical and mental health of adolescents. Its incidence and survival rates are increasing year by year . In 2017Adolescence is an important period for physical growth and mental development. When adolescents are diagnosed with serious conditions during this critical period, they may be more sensitive to physiological and emotional changes than adults, making them a high-risk group for psychological and mental health crises. Some studies have shown that the diagnosis and treatment of cancer make adolescents bear more psychological pressure than what is required, which leads to different psychological reactions during different stages of cancer –10. ExceHowever, research has shown that children with cancer show both negative and positive psychological responses in their fight against cancer. According to the relevant literature, children possess a definite cultural knowledge base after the age of 8 years to have an initial understanding of society and their personal thoughts . As theiThe psychological problems of children with cancer and the relevant intervention strategies to be adopted have attracted the attention of researchers. Many research groups have evaluated different types of psychological interventions for adolescents with cancer. A study of psychological crisis intervention models in foreign countries has been recorded as early as 1964 when American psychologist Gerald Caplan first proposed the theory of psychological crisis. He divided the formation and evolution process of psychological crisis into four stages. Later researchers proposed the development of ecological models, situational ecological models, psychological first aid, and seven-stage psychological crisis intervention models. Chinese researchers proposed a real-time reservation model, an online-to-offline model, and a cognitive regulatory model. These models were mainly applied to healthy children and therefore lacked research on early identification, warning, and intervention of psychological problems in adolescents with cancer. Therefore, this study will construct an early warning and intervention model for psychological crisis in children with cancer and explore its application effect.Adolescents with cancer were recruited from the Children's Hospital of Chongqing Medical University. The inclusion criteria were as follows: (1) children aged 8–18 years (this age group has self-reporting capabilities); (2) children diagnosed with cancer by the standard guidelines for the diagnosis and treatment of childhood malignancies ; and (3)α = 0.05 and β = 0.1. According to the bilateral test table, Z0.05 = 1.96 and Z0.1 = 1.282; after literature review , and the scale has good reliability and validity. Based on the total score, there were five levels: (1) normal, depression (≤9), anxiety (≤7), and stress (≤14); (2) mildly abnormal, depression (10–13), anxiety (8–9), and stress (15–18); (3) moderately abnormal, depression (14–20), anxiety (10–14), and stress (19–25); (4) severe abnormal, depression (21–27), anxiety (15–19), and stress (26–33); and (5) extremely severe abnormal, depression (≥28), anxiety (≥20), and stress (≥34).The Depression Anxiety Stress Scale (DASS-21) is a self-assessment scale and was translated into Chinese by Xu et al. ; it contPatients in the control group received routine nursing care. Nurses received patients warmly when they were admitted, introduced them to the environment of the hospital, implemented the doctor's advice, communicated with them before the operation, listened to them, and took care of them.The intervention group was based on routine nursing care and also implemented the early warning and intervention model of psychological crisis . The early model includes four steps.Two doctors formulated treatment plans and discussed patients' conditions with their family members. Of four nurses, one was responsible for coordination and quality control, and the others were responsible for implementing nursing interventions. Two psychological counselors developed the intervention plans, trained in psychological knowledge, and provided one-on-one counseling if necessary. One community worker mobilized the support resources of the community or school, and another organized volunteer activities. In addition, the team should receive training in terms of the characteristics of children's psychological and behavioral development and crisis intervention, skills of psychological counseling and program implementation, clinical application of cognitive behavioral therapy, training of comfortable nursing ability of pediatric nurse, and procedures and considerations of the intervention.According to the scoring standard of the Depression Anxiety Stress Scale (DASS-21), the early warning of a psychological crisis in adolescents with cancer was divided into three levels .Establish archives (the first week): general information, family education, medical insurance, and psychological status.Physiological support (every week): doctors, nurses, and patients formulated plans and promoted orderly activities, providing patients with timely care, reducing physical injury in operation and side effects of drugs, and helping patients establish a regular and healthy lifestyle, for example, providing children with healthy food and ensuring that they get enough sleep.Psychological support (every week): providing cognitive therapy through semistructured interviews, understanding patients' adverse cognition, and correcting through semantic analysis, imitation, or decentralization.Behavioral therapy (every week): analyzing the frequency and severity of adverse behaviors of patients, and correcting through systematic desensitization, imitation learning, self-management, role-playing, and self-confidence training.(1)Evaluation and summary: after 3 months of early warning intervention, we assessed the current psychological status of the children with cancer by the DASS-21.Social support (every week): holding a series of lectures on “caring for children with cancer”; holding theme activities on a weekly basis, such as music activities, painting activities, sharing stories, film appreciation, and knowledge contests; and establishing a network group, for example, online communication, release of disease-related knowledge, psychological counseling, and regular children education. For example, Xiao Ming (assumed name) told us that he would eventually die from cancer. Then, we corrected his misconception, gave him confidence in overcoming the disease, and asked the recovered children to share their stories.P value in pairwise comparison. t-test, paired t-test, and analysis of variance method were used for quantitative data conforming to normal distribution. All tests were two-sided, and statistical significance was defined as P < 0.05.SPSS Statistics 22.0 was used for statistical analysis. The measurement data are described as the mean [±standard deviation (SD)]. The count data are described as the frequency and percentage (%). The chi-square test was applied to compare the qualitative data. The Bonferroni method was used to correct the There were no significant differences in the baseline characteristics of the intervention and control groups. The study participants were young in age (55.07% were 8–12 years old) and comprised a higher percentage of males (58.84%), mainly lived in cities (66.96%), mostly taken care of by their parents (90%), and mostly diagnosed with leukemia (61.63%) and had medical insurance (74.2%). The caregiver's cultural level was relatively low (72.46% received secondary school education) .P < 0.05)  were lower than those in the control group , and the difference between the two groups was statistically significant ( < 0.05) . In addi < 0.05) .P < 0.05).As shown in Children aged 8–18 years with cancer have obvious psychological problems. In this study, it was found that the detection rates of depression, anxiety, and stress in the intervention group before the intervention were 57.56%, 69.77%, and 41.28%, respectively, which were higher than those of middle school students  . Our preThe research results showed that the score and the detection rate of depression, anxiety, and stress in the intervention group were all markedly lower than those in the control group after the intervention. This means the early model effectively improves the psychological state of children with cancer. Furthermore, in the intervention group, the scores for depression, anxiety, and stress were greatly different from those after the intervention. In contrast, the scores for depression and stress in the control group were not observably different from those after the intervention; only the difference in the score of anxiety was statistically significant. All these indicated that traditional nursing intervention could appropriately alleviate the anxiety of children with cancer, but had no obvious effect on depression and stress. The early model could provide timely preventive interventions by comprehensively assessing the psychological and social conditions of children, thereby effectively improving their psychological problems, consistent with reports by researchers such as Chen Jin –25. ReseThis study constructed an early warning and intervention model for psychological crisis in children with cancer. First, qualification setting and responsibility clarifying and a multidisciplinary team including doctors, nurses, psychological counselors, community workers, and volunteers were established. Teamwork can effectively improve the members' ability to solve problems. Second, we developed the response of early warning and included the appropriate psychological scale to scientifically formulate grading standards. We arranged the response personnel, formulated intervention programs, and implemented preventive intervention rigorously and in a systematic way. Preventive intervention was carried out to correct patients’ unreasonable beliefs or cognition; to help them establish peer, social, and information support system; and to prevent the occurrence of psychological crisis. In addition, the specific implementation details of the program were formulated. The intervention program was set up after considering the physical, psychological, social, and spiritual aspects and combined with various interventions. Online and offline interventions were carried out simultaneously, which compensated for the deficiencies of routine psychological intervention. After the intervention, evaluation, feedback analysis, and file improvement were conducted. On this account, personalized and precise warning interventions could be achieved, effectively preventing and reducing the occurrence of psychological crisis in children with cancer.Children with cancer have obvious mental health problems. The early warning and intervention model of psychological crisis contained three aspects, which were regular assessment of psychological crisis, screening for psychological crisis, and intervention of psychological crisis, which was conducive to early detection and intervention of psychological problems in children with cancer, thereby preventing the occurrence or reducing the severity of the psychological problems.Clinicians and nurses should pay more attention to early diagnosis and intervention of children with cancer to improve the disease outcome. Future work should include conducting qualitative interviews to understand the psychological experiences of children with cancer throughout their entire life cycle.This study did not classify the patients' disease diagnosis. It is necessary to collect information on the diagnosis of children with cancer to research whether there are differences in different cancer types. In addition, this is a historical controlled trial and not a randomized clinical trial, and therefore, the presence of some confounding variables cannot be ruled out.


Urachal tumors are exceedingly rare, and adenocarcinoma is the most common malignant urachal neoplasm. Here, an especially rare patient of primary urachal leiomyosarcoma from our hospital was reported, and only five patients have been reported thus far since 1981.A 24-year-old man was admitted due to urinary tract symptoms. Both urogenital ultrasonography and contrast-enhanced computed tomography showed a mass at the dome of the urinary bladder. Laparoscopic surgical resection was performed, and histopathologic examination of the mass confirmed the diagnosis of urachal leiomyosarcoma. No recurrence was noted after one and a half years.Because the leiomyosarcoma located in the extraperitoneal space of Retzius and may manifest with nonspecific abdominal or urinary symptoms, early and definitive preoperative diagnosis is challenging. Partial cystectomy with complete excision of the urachus is recommended. Because only a few patients have been recorded, clinical outcomes and recurrence risks are difficult to assess. The urachus is a ductal remnant that arises embryologically, originating from the involution of the allantois and cloaca and extending between the bladder dome and the umbilicus . The tubA 24-year-old man manifested the symptoms of dysuria, urinary frequency, and urgency for more than a week. Urogenital ultrasonography (US) revealed a hypoechoic mass at the dome of the bladder. The patient was treated with anti-inflammatory therapy and discharged from the local hospital after improvement. Thereafter, the patient sought consultation at our hospital for further evaluation. Contrast-enhanced abdominal computed tomography (CT) showed a heterogeneous 2.7 cm × 2.1 cm × 2.1 cm mass at the dome of the bladder Figure 1The urachus is a 3.0 - 10.0 cm tubular structure extending from the allantois to the early fetal bladder. During embryonic development, the upper part of the allantois will be reduced gradually. After birth, it is replaced by fibromuscular tissue, also known as the median umbilical ligament. In patient of partial obliteration of the urachus, various diseases including fistula, diverticulum, or tumor may occur. The tumor primarily occurs in males and is usually localized in the bladder dome or anterior wall. Urachal adenocarcinoma is the most common pathological type (up to 80%), with an occasional occurrence of squamous cell carcinoma , 11. ProLeiomyosarcoma is a malignant neoplasm characterized by smooth muscle differentiation. The World Health Organization (WHO) proposed a histological classification of leiomyosarcoma which is divided into myxoid and epithelioid leiomyosarcoma . LeiomyoUS is the preferred method in the detection of urachal leiomyosarcoma. US can show the urachal tract between the bladder dome and the umbilicus allowing localization of the tumor. The CT appearance of a leiomyosarcoma is not specific; necrotic or cystic change is usually observed and reveals no enhancement; therefore, it shows an uneven and avid enhancement on contrast-enhanced CT. On MRI, the urachal leiomyosarcoma is reported to be isointense on T1-weighted imaging (T1WI) and heterogeneously hyperintense on T2-weighted imaging (T2WI). A high signal intensity on T2WI is associated with fluid, necrosis, or mucin. The contrast-enhanced MRI findings are similar to that of the contrast-enhanced CT.18F-fluorodeoxyglucose (FDG) PET/CT may be helpful for diagnosing primary and recurrent urachal adenocarcinoma . In identifying the primary focus, FDG PET/CT does not seem to yield additional information compared with CT or MR. However, it may detect metastatic lesions not seen on other imaging modalities, causing changes in tumor stage and patient management  for urachal cancer, but none of them have been fully validated. The Sheldon staging system is complex and has eight categories, while the Mayo system is simpler and more proportional for patient distribution. Based on the Mayo system, urachal cancer is classified into four stages: Stage I, tumor confined to urachus and/or bladder; Stage II, tumor extending beyond the muscular layer of urachus and/or bladder; Stage III, tumor infiltrating the regional lymph node; and Stage IV, tumor infiltrating non-regional lymph nodes or distant sites . TherefoCompared with other modalities for staging of urachal cancer, MRI has more advantages in soft tissue resolution and multi-plane imaging capabilities. For primary UrC, MRI can provide the tumors’ location, size, morphology, extent of peritoneal tissue, and/or local structures beyond bladder invasion. For recurrent UrC, it can accurately evaluate recurrence and metastatic patterns. Studies have shown Mayo stage at MRI is highly consistent with pathology .18F-FDG uptake due to hypocellularity of tumors which may limit the sensitivity of 18F-FDG PET/CT . For chemotherapy, we suggest that it should not be recommended on a routine basis, as types of treatment used are heterogeneous and the benefits are unclear. Postoperative chemotherapy may be considered due to positive margins, lymph node or peritoneal involvement, or unresected umbilicus and a high likelihood of relapse . FinallyAs a result of the lack of data on urachal leiomyosarcomas, follow-up scheme of this entity is not clear in the literature . For theLeiomyosarcoma is a type of soft-tissue sarcoma usually occurring in the soft tissues of the extremities and trunk. It is aggressive and spreads hematogenously which are characteristics of a malignant neoplasm. Primary leiomyosarcoma of the urachus is extremely rare, and it tends to be easily misdiagnosed. Understanding the embryological basis of these urachal disorders and their imaging features coupled with histopathological, examination is crucial for the correct diagnosis and management.Our patient reported the following about his disease: “Throughout my clinical care, I have been concerned that my disease would come back. I now have an abdominal ultrasonography every three months to keep track of my disease. Fortunately, I am now in good health. Thanks are given to the doctors and nurses who have taken care of me and helped me.”The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.The studies involving human participants were reviewed and approved by Institutional Ethics Committee of the Suining Central Hospital. The patients/participants provided their written informed consent to participate in this study.JY, QD, and GY participated in the study design and writing of the manuscript. JY, QD, GY, CT, HL, and YL participated in clinical data collection and analysis, and carried out the interpretation of the CT images. LY performed the pathological and immunohistochemical examinations. GY, MM, AB, RL, GT and BF all revised the paper critically for intellectual content. All authors contributed to the article and approved the submitted version.


Drug therapy is the most commonly used treatment for primary trigeminal neuralgia (PTN), in which carbamazepine is the first-line drug. Recently, the anti-epileptic drug gabapentin has also been widely used in patients with PTN, but whether it can be used as a substitute for carbamazepine still needs to be verified. Our study aimed to assess the safety and efficacy of gabapentin vs. carbamazepine as a treatment for PTN.We searched seven electronic databases for studies published as of 31 July 2022. All randomized controlled trials (RCTs) of gabapentin vs. carbamazepine on patients with PTN that met the inclusion criteria were included. Meta-analysis was conducted using Revman 5.4 and Stata 14.0, in which forest plots, funnel plots, and sensitivity analysis were performed. Mean difference (MD) and odds ratio (OR) with 95% confidence intervals (CIs) were used for the measurement indicators of continuous and categorical variables, respectively.P < 0.001), reduced the adverse event rate , and improved the visual analog scale (VAS) score . Although the funnel plot showed evidence of publication bias, the sensitivity analysis revealed the stability of the results.A total of 18 RCTs with 1,604 patients were eventually identified. The meta-analysis showed that compared with the carbamazepine group, the gabapentin group significantly improved the effective rate (OR = 2.02, 95% CI 1.56 to 2.62, The current evidence showed that gabapentin may be superior to carbamazepine in relation to efficacy and safety in patients with PTN. It is crucial that more RCTs are conducted to confirm the conclusion in the future. Trigeminal neuralgia (TN) is a common peripheral neuropathy in neurology. The characteristic symptoms of TN include unilateral, paroxysmal, provocable, and without sensory loss of facial pain . It can There are more women with PTN, and it is more common after the age of 40. It can be described by patients as electrocautery, tearing, acupuncture, or knife cutting. At the onset, patients often show a painful expression, and it is necessary to rub the face tightly with a towel to relieve the pain. The onset of the disease is acute, and it stops suddenly after 1–2 min and relapses after a period of time. The interval between relapses shortens as the disease aggravates . At presAt present, drugs can be used for nerve block, and then, neurotomy, microvascular decompression, or radiofrequency thermocoagulation can be used for treatment, but available treatments are still far from the ideal effect and pain tend to recur –12. CarbGabapentin has been used in clinics for more than 10 years as a new type of anti-epileptic drug. Its good curative effect for neuropathic pain has been reported in many literature studies , 15. PTNSeven electronic databases  were comprehensively searched from inception to 15 August 2022 for all studies involving gabapentin vs. carbamazepine for the treatment of PTN. The combination of “gabapentin”, “carbamazepine”, and “primary trigeminal neuralgia” used the Boolean operator “AND” to carry out the specific search. Language restrictions and publication status were not considered in our literature search. A hand search of the reference lists of the original articles and previous reviews was also conducted to screen other potentially eligible studies.The inclusion criteria were as follows: (P) patients with primary trigeminal neuralgia (PTN); (I) intervention: the test group received oral gabapentin treatment; (C) comparison: the control group received oral carbamazepine treatment; (O) main outcome indicators: the effective rate, the adverse event rate, and the visual analog scale (VAS) score; and (S) study design: randomized controlled trials (RCTs). The major exclusion criteria were as follows: (1) patients with secondary trigeminal neuralgia (STN) or other diseases; (2) non-randomized controlled studies; (3) treatment with other interventions; and (4) the relevant data not reported.XZ and SG independently reviewed RCTs included in the final analysis and extracted relevant data directly from the articles. The following information was extracted from each included study: author's name, year of publication, treatment of test and control group, sample size, patients' characteristics, study's years of onset, and the results of main outcome indicators .The VAS score was used to assess the pain degree of patients, with a total score of 10 points. In order to categorize the patients, the VAS score was divided into three categories: mild or no pain (0–2), moderate pain (3–6), and severe pain (7–10). Compared with before treatment, the VAS score decreased by >50% after treatment indicated effective treatment; otherwise, it was considered ineffective.Quality assessment of RCTs was performed using the Cochrane bias risk assessment tool (The Cochrane Collaboration) by the following items: random sequence generation, allocation concealment, blinding (performance bias and detection bias), incomplete outcome data (attrition bias), selective reporting (reporting bias), and other bias.2 statistic the Cochrane Q-test. Statistical heterogeneity will determine the choice of model (fixed or random effect). An assessment of possible publication bias was carried out using funnel plots and Egger's test. If I2 is >50% or the p-value of publication bias is < 0.05, the potential source of heterogeneity or publication bias would be tested by sensitivity analysis, which was evaluated by removing study after study from the pooled results using the leave-one-out method.All statistical analyses were performed by using Review Manager, version 5.4, software (The Nordic Cochrane Centre) and Stata 14.0 . Specifically, data for effect sizes of continuous outcomes were calculated as mean difference (MD) with a 95% confidence interval (CI), and odds ratio (OR) was used for categorical outcomes. Heterogeneity between studies was assessed using the IA total of 549 potentially relevant articles were identified by the searches. After the removal of duplicates, 463 articles were identified. After going through the titles and abstracts, another 336 articles were excluded. Full-text articles from the remaining 127 studies were assessed for eligibility, and 109 studies were further excluded because they did not meet the inclusion criteria. Eventually, 18 RCTs were deemed eligible and were included in the final meta-analysis –33. FiguThe detailed characteristics of these 18 eligible studies are summarized in The included RCTs were assessed for bias using the Cochrane Risk of Bias Assessment tool . Among t2 = 13%, P = 0.29), so a fixed-effects model was selected for analysis, which revealed that the gabapentin group showed a high effective rate compared with the carbamazepine group after treatment  (All the included studies measured the effective rate after treatment. The included studies showed no notable heterogeneity (I0.00001) .2 = 97%, P < 0.00001), so the random effects model was selected for further analysis, and it showed that the gabapentin group had a lower VAS score than the carbamazepine group   .2 = 0%, P = 0.99). A significant decrease in adverse event rate was observed in the gabapentin group when compared with the carbamazepine group   .p-values of Egger's test for the effective rate and the adverse event rate were <0.05 , and significant heterogeneity existed in the included literature for VAS score, we conducted a sensitivity analysis on the meta-analysis results of the three variables -cyclohexaneacetic acid, and its molecular structure is related to the neurotransmitter γ-aminobutyric acid. It has been widely used for TN in recent years, but its analgesic mechanism has not been fully elucidated. Its molecular structure is similar to that of γ-aminobutyric acid, and it is a voltage-gated calcium channel c281 subunit blocker , 41. At Studies have found that inflammatory factors are closely related to the occurrence and progression of TN. Due to changes in nerve demyelination, intraneural mast cells, macrophages, and vascular endothelial cells are damaged and inflammatory responses are induced . Tumor nThis study had the following limitations: (1) The allocation sequence concealment and risk of blinding bias in most studies were unclear, and there may be limitations; (2) although all included studies had the same purpose, each included study differed in terms of patient disease severity and drug dosage. There were different degrees of differences in terms of time and intervention time, and these differences may lead to heterogeneity of outcomes. (3) The currently included studies were all published in Chinese, which may affect the extrapolation of the results of this study. Therefore, the final conclusion is still needed to be further verified by more large-sample, multi-center high-quality RCTs.Existing evidence shows that gabapentin is effective in the treatment of PTN, and it is even better than carbamazepine in terms of therapeutic effect and safety. Gabapentin may be a better choice in cases where first-line drugs such as carbamazepine are ineffective in controlling pain or have severe side effects. In addition, the findings of this review are limited by the quality and limitation of the included studies, and more high-quality studies subdivided research should be further carried out.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.SG designed the study. XZ performed a database search, data extraction, and quality evaluation. SG and XZ performed the statistical analysis, verified the data, and drafted the manuscript. All authors contributed to the article and approved the submitted version.


Sexual health is an important component of general health.To evaluate sexual function and sexual quality of life (SQOL) in women during the COVID-19 pandemic.This descriptive, cross-sectional study was conducted in Turkey. Data were collected via a Visual Analog Scale (VAS), Female Sexual Function Index (FSFI), and Sexual Quality of Life-Female (SQOL-F) questionnaire.The mean FSFI score was 26.91±5.62, and 39.1% of the women had an FSFI score of 26.55 or lower. The mean SQOL-F score was 79.08±20.90. FSFI score was significantly associated with employment status (β=-0.661), partner education (β=1.698), sexual compatibility between partners (β=0.518), sexual satisfaction (β=0.230), fatigue level (β= -0.120), and frequency of sexual intercourse (β=0.160). In addition, SQOL-F score was significantly associated with sexual desire (β=2.625), satisfaction (β=1.338), pain or discomfort (β=1.274), age (β= -0.356), sexual compatibility between partners (β=1.984), and fatigue level (β=-0.981) (p<0.05).Less than half of the women participating in this study had sexual dysfunction, and overall SQOL was moderate to high. These results were associated with some descriptive characteristics of the women and were similar to those reported in pre-pandemic studies conducted in Turkey. Over the course of history, humanity has faced numerous epidemics and mass deaths. Since the first reported case of novel coronavirus disease 2019 (COVID-19), millions of people worldwide have diedSexual health is an important component of general health, and mass disasters affect reproductive health, especially in women(1) How is women's SF during the COVID-19 pandemic?(2) What factors are associated with women's SF during the COVID-19 pandemic?(3) How is women's SQOL during the COVID-19 pandemic?(4) What factors are associated with women's SQOL during the COVID-19 pandemic?After obtaining ethical approval, a descriptive/relational cross-sectional study was carried out between April 10, 2021 and May 10, 2021. The sample size for the study was calculated based on the expected prevalence in the population. A recent meta-analysis conducted in Turkey was used as a reference for statistical power analysisThis study was conducted online during partial closures imposed because of the COVID-19 pandemic. For this reason, data were collected using an online questionnaire hosted on Google Forms. A link to the questionnaire was sent to the participants' personal social media accounts , WhatsApp, and e-mail addresses. After obtaining permission from the group administrators of social media, WhatsApp, and similar groups with large membership, we informed the members about the study and invited them to participate in the online survey. Questionnaires created on the Google Forms platform can be configured tallow each participant to complete the survey only once and require all questions to be answered. These settings were used to prevent multiple form submissions from the same participant and potential data loss due incomplete submissions. The data collection tools used in the questionnaire included a sociodemographic information form, the Visual Analog Scale (VAS), Female Sexual Function Index (FSFI), and Sexual Quality of Life-Female (SQOL-F) questionnaire.We developed this form in light of the literature to determine the women's sociodemographic characteristics and various factors believed to potentially affect SF and SQOLThe VAS is a unidimensional scale developed for pain assessment and is also used to determine individuals’ thoughts and feelings about various situationsThe FSFI was developed by Rosen et al. in 2000 to evaluate women's sexual function over the last 4 weeks. The scale is a 19-item multidimensional scale consisting of 6 subscales: desire, arousal, lubrication, orgasm, satisfaction, and pain. Items 3-14 and 15-19 are rated on a 6-point (0-5) Likert-type scale and the other items on a 5-point (1-5) Likert-type scale. Raw scores on this scale range from 4 to 95, and final scores after multiplying by the coefficients range from 2 to 36. The effect coefficients used to calculate the total scale score were determined to be 0.6 for sexual desire, 0.3 for sexual arousal and lubrication, and 0.4 for orgasm, satisfaction, and painThe SQOL-F was developed by Symonds et al. in 2005 to evaluate SQOL in womenStudy data were analysed using SPSS for Windows version 25.0 . Frequency, median, minimum, maximum, mean, and standard deviation were used as descriptive statistics in the data analysis. The Kolmogorov-Smirnov test was used to determine whether the data were normally distributed. Parametric tests were used to analyse scale and subscale scores showing normal distribution. Quantitative variables were analysed using independent samples t test, Mann-Whitney U test, one-way analysis of variance (ANOVA), Kruskal-Walli's analysis, and Bonferroni test for multiple comparisons. Chi-square analysis was performed in independent samples to assess the relationship of qualitative data. Relationships between variables were analysed using correlation analysis. Multiple linear regression analyses were performed to determine the effect of independent variables on the dependent variable. Factors affecting FSFI scores were identified using logistic regression analysis. The logistic regression model was created using factors reported to be associated with SD in the literature and the variables that showed significant differences related to FSFI score in the statistical comparisons made in this study. Although independent-samples t test analysis showed FSFI scores were associated with number of pregnancies, births, and children, only the pregnancy variable was included in the model due to the high correlation between these three variables. Continuous variables in the model were analysed without grouping. The statistical results were analysed within a 95% confidence interval and an alpha value below 0.05 was considered significant.Before starting the study, ethical approval was obtained from the Eastern Mediterranean University Ethics Committee  and a research permit was obtained from the Ministry of Health. Participants were asked to submit their consent via an online consent form prepared in accordance with the Declaration of Helsinki.The women who participated in the study had a mean FSFI total score of 26.91±5.62 . In addition, 39.1% (n=252) of the women had an FSFI score of 26.55 or lower, indicating sexual dysfunction. The mean SQOL-F score was 79.08±20.90 .In this study, comparison of the general characteristics of participants with and without SD according to their FSFI score revealed no statistically significant differences in income level, history of birth, or history of COVID-19. However, there were significant differences between the subgroups in terms of employment status, education level, and partner education level. Moreover, statistical comparisons showed that women with SD were older and had older partners, had more pregnancies, births, and children, had reported lower VAS sexual compatibility and sexual satisfaction scores, higher VAS fatigue level, and lower monthly frequency of sexual intercourse p<0.05; .The results of the logistic regression analysis to identify factors associated with women's SD are shown in The results of our multiple regression analysis to identify factors associated with women's SQOL are shown in Correlation analysis revealed significant positive correlations between SQOL-F and FSFI total and sexual desire, arousal, lubrication, orgasm, satisfaction subscale scores. Similarly, there were statistically significant positive correlations between SQOL-F and average monthly frequency of sexual intercourse and VAS levels of sexual compatibility and sexual satisfaction. In contrast, significant negative correlations were detected between SQOL-F and pain or discomfort subscale scores, age, partner age, marriage duration, numbers of pregnancies, births, and children, and VAS fatigue level .Sexuality, considered a necessity for continuation of the species on one hand and a basic human need on the other, is an extremely complex and delicate phenomenon that encompasses physical, mental, learning, and social dimensionsStudies conducted in different countries of the world have demonstrated a decrease in FSFI scores and an increase in the prevalence of female SD compared to the pre-pandemic periodThe discrepancy between our findings and those reported in other countries may be due to differences in the impact of COVID-19 among countries and to cultural differences. However, we attribute the difference between our results and those reported in other studies conducted in Turkey to the larger sample included in our study. In response to the first research question, less than half of the women participating in the study had SD, and we concluded that SF was not affected by the pandemic.As female sexuality is not studied as often as male sexuality, both the etiology and pathophysiology of female SD have not been determined in detail, and thus neither have methods for its treatmentIt is known that working status and fatigue level are associated and that fatigue affects sexuality. Pre-pandemic studies showed that women with symptoms of fatigue had SD and that increased fatigue adversely affected the sexual cycleStudies on the effect of education on SF both before and during the COVID-19 pandemic have yielded contradictory results. Schiva et al. (2020) reported that FSFI scores during the pandemic were lower in women with a high education levelWith age, sexual function in women may be affected by hormonal changes, the onset of chronic diseases, and social and psychological factorsCompatibility between partners is another important element related to SF. Sexual compatibility was reported to be strongly associated with sexual satisfactionVarying results have been reported concerning the relationship between obstetric history and SF during the COVID-19 pandemic. Two studies suggested that number of children was not associated with SFThe pandemic has caused changes in all parts of life, including sexual behaviors and habitsA quality sex life is described not only in terms of not having diseases and disabilities affecting reproductive and sexual functions, but also in terms of not having feelings that suppress sexuality, such as fear, shame, and guilt; being able to control one's sexual behavior; and deriving satisfaction. In short, SQOL refers to the state of being satisfied with one's sex lifeSexual quality of life is a subjective experience that may be affected by the COVID-19 pandemic. However, studies have yielded differing results on this subject. While some studies on the subject showed that women's SQOL decreased during the COVID-19 pandemicIn two studies evaluating SQOL in healthy women in Turkey before the pandemic, the mean SQOL-F scores were 81.09±22.04, and 71.54±20.46 In this study we also investigated factors associated with women's SQOL and the results obtained in this section answer our fourth research question. Schiavi et al. (2020) stated that SD was associated with level of sexual satisfaction and quality of lifeThe results of the study suggest that the effect of age on SQOL varies. A strong positive relationship was found between partner age and SQOL in one study conducted during the pandemicThere are studies demonstrating a relationship between the frequency of sexual intercourse and SQOL. In a study conducted before the pandemic, people who had sexual intercourse 3 to 4 times a month had high SQOLMutual pleasure and compatibility are important components of sexual satisfaction and develop not from the absence of sexual dysfunction, but as a result of positive sexual experiences In all cultures, there are customs related to relationships between men and women, including formal marriage. However, marital relationships often differ among societies because they are guided by culturally determined norms. Factors such as family structure, age, education level, economic status, and having children can affect satisfaction, compatibility, and sex life Adequate sleep and rest are also essential for staying healthy and recovering from illness. Quality sleep and rest support SQOL, and a healthy sex life also contributes to quality sleep and restThe main limitation of this study is that the study sample consisted predominantly of working and educated women. Although we invited women from all walks of life to participate in the online survey, we suspect that conservative and low education women may have been hesitant to answer the questionnaire because it included questions about their sexual life. Secondly, when the questionnaires were examined, we noted that those with unrealistic responses  were submitted by participants who reported a low education level and were not working, and these questionnaires were excluded from the study. We attributed this to mistakes made by low-educated women during data entry because they were not accustomed to using online survey forms. For these two reasons, the study sample consisted mainly of working and educated women, which limits the generalizability of our findings.Less than half of the women participating in this study had sexual dysfunction, and overall sexual quality of life was moderate to high. These results are similar to those of pre-pandemic studies conducted in Turkey. Therefore, we conclude that the SF and SQOL of the participants were not affected by the pandemic. In addition, we identified several factors associated with the participants' SF and SQOL. Factors related to female SD in this study were not working, older self and partner age, higher number of pregnancies, births, and children, greater fatigue, and lower female and partner education level, frequency of sexual intercourse, sexual compatibility, and satisfaction. Among these factors, not working and high fatigue level were negatively associated with SF, whereas high sexual intercourse frequency, partner education level, sexual compatibility, and satisfaction were positively associated with SF.Factors found to vary significantly with SQOL included sexual desire, arousal, lubrication, orgasm, satisfaction, pain or discomfort, frequency of sexual intercourse, level of compatibility between partners and sexual satisfaction, level of fatigue, age of the women and her partner, marriage duration, and number of pregnancies, births, and children. Of these factors, high levels of sexual desire, satisfaction, and compatibility between partners were positively associated with SQOL, while older age, sexual pain or discomfort, and high fatigue level were negatively associated with SQOL.This large study offers insight about SF and SQOL in healthy women during the COVID-19 pandemic. In addition, the results are important in revealing that modifiable factors such as fatigue, frequency of sexual intercourse, compatibility between partners, and sexual satisfaction are correlates of SF and SQOL. These findings should be supported and causal relationships investigated with prospective randomized controlled trials.


Halophytes play a crucial role in the ecological restoration of saline and alkaline land and hold promising benefits to food security in China. Although a variety of aspects of halophytes have been extensively addressed, there is still a lack of overall understanding of the leaf nitrogen (N) and phosphorus (P) stoichiometric characteristics, especially at a national scale. We compiled a national dataset of 311 observations from 113 sampling sites across China to explore the changing trends and influencing factors on leaf N and P concentrations, and N:P ratio of halophytes. The results showed that leaf N concentration decreased significantly with increasing latitude (LAT), which was mainly driven by the mean annual temperature (MAT) and mean annual precipitation (MAP). The leaf P concentration increased remarkably with increasing longitude (LON), which was induced by the variation in soil total P (TP) content. The leaf N:P ratio increased as LAT increased and LON decreased, which was potentially regulated by the MAT, MAP, and soil TP content. The scaling exponents of the N-P relationship differed significantly among halophyte types and were 0.40, 0.87, and 1.39 for euhalophyte, pseudohalophyte, and recretohalophyte, respectively. The leaf N concentration exhibited significant differences among ecosystem types and halophyte types, whereas the leaf P concentration and N:P ratio remained relatively stable. In summary, the leaf N concentration and N-P scaling exponent might be the classification criteria for halophyte types from the perspective of plant nutrient resource allocation. Moreover, this study characterized the spatial distribution and allocation strategy of leaf N and P stoichiometry in halophytes by data integration analysis, providing the basic information for nutrient management in the processes of the future domestication and introduction of halophytes. CurrentPhragmites australis, Kalidium foliatum, and Suaeda plants. In addition, based on their adaptation mechanisms to the high-salt environment, the halophytes could also be divided into euhalophytes, pseudohalophytes, and recretohalophytes physiologically  is an elementary approach in which basic principles are used to explore the coupling of global N, and P cycles via their biotic interactions and their responses to climate change . The ideChina is a geographically diverse country, with many types of climate zones and various types of plant flora, making it an ideal place to explore the influence of environmental conditions on plant nutrient cycling and balance . In receIn the present study, we collected data on leaf N and P stoichiometry, along with geographical, climatic, and soil nutrient information from published literature. Our main aims were to: 1) characterize the geographical patterns of leaf N and P stoichiometry; 2) identify the variation in leaf N and P stoichiometry among different ecosystems and plant types; 3) test whether the allometric scaling relationship exist among different halophyte types. Overall, our study was expected to enhance the understanding of the ecological adaptions of the halophytes and provide some basic information for the rational utilization of halophyte resources in the future.22.1The data were collected from the Web of Science and China National Knowledge Infrastructure (CNKI) database by using the keyword combinations, i.e.,  AND (plant OR leaf) AND (carbon OR nutrient OR nitrogen OR phosphorus OR stoichiometry). Data were collected from published studies mainly focused on the leaf N and P concentrations of halophytes, along with the geographical, climatic, and soil nutrient information associated with the leaf samples obtained from 2010 to 2021, mainly according to the saline soil characteristics of the halophyte distribution area in China. Moreover, authoritative texts of plant taxonomy were used to make sure the division accuracy of halophyte types for the included plant species .http://www.worldclim.org/; The database consisted of 311 observations from 113 sampling sites across China Figure 1The functional groups were also recorded, including the ecosystem type , life form , phylogenetic development (dicotyledon and monocotyledon), halophyte type  and photosynthetic pathway (C3 and C4 herbs). Leaf samples, used for determining the leaf N and P concentrations, were collected during the growing season (mainly from July to October). The leaf N:P ratios were expressed on a mass basis.Previously, 2.2The arithmetic means of each species were calculated within each site. The frequency distribution of the leaf N and P concentrations, and N:P ratios were slightly skewed; therefore, we calculated the arithmetic means . Standar33.1The mean leaf N concentration of halophytes across China was 22.47 mg/g =9.43 mg/g), falling between those of the desert and grassland ecosystems across northern China, and those of wetland ecosystems across eastern coastal China and global coastal regions  rather than qualitatively.It was observed that the leaf N:P of halophytes was 13.79, slightly lower than the N-limitation threshold value, which suggested that the plant growth of halophytes was likely not limited by soil nutrient deficiencies. The leaf N concentration and N-P scaling exponent exhibited differences among halophyte types, which would be a guideline for the taxonomic classification of this special plant group. Overall, our work would help draw attention to the spatial and temporal distribution patterns and allocation strategies of nutrients in halophytes at the national scale, as well as the other special plant resources, and further providing beneficial scientific support for the nutrient management in the saline-alkali grain cultivation.However, there are several limitations in this study as well. In details, it is well known that halophytes have developed specialized molecular mechanisms and cellular structures to tolerate high salt stress, and these adaptations might induce the changes in plant nutrient allocation strategies. In this study, we just observed that leaf N concentration increased with soil pH, which was in line with previous studies . We also5As a special germplasm resource with an extremely important strategic significance, halophytes should be fully characterized from different perspectives. Here, we explored the spatial distribution patterns and allocation strategies in the leaf N and P stoichiometry of halophytes at the national scale using the data integration analysis. The leaf N and P stoichiometry of halophytes exhibited clear biogeographical patterns, and mainly driven by temperature and soil P content. The leaf N concentration and N-P scaling exponent could serve as a reference for the type division of halophytes. In summary, our results have provided new insights into the plant ecological adaptation especially with special habitats and the basic information on the nutrient management for the halophytes cultivation.The original contributions presented in the study are included in the article/RT: Methodology, Conceptualization, Data curation, Software, Writing – original draft. CM: Data curation, Writing – review & editing. CL: Data curation, Writing – review & editing. WY: Data curation, Software, Writing – original draft. NZ: Data curation, Software, Writing – original draft. GW: Methodology, Writing – review & editing. TW: Methodology, Writing – review & editing, Project administration, Resources, Supervision.