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IntroductionGonadotropin-releasing hormone (GnRH) is widely used in the timed artificial insemination protocol for sheep. However, there remains a debate regarding its impact on pregnancy rates during artificial insemination. This study aims to evaluate the effect of GnRH on the pregnancy rates in Huyang ewes, analyze the pre-implantation metabolite changes caused by GnRH using metabolomics, and elucidate the mechanism effect on pregnancy rates.MethodsAll ewes were administered a vaginal progesterone sponge containing 45 mg of flurogestone acetate for 12 days and received 330 units of equine chorionic gonadotropin (eCG) intramuscularly after sponge removal. The experimental group (n = 69) received an intramuscular treatment of 17 μg GnRH agonist triptorelin 48 h after sponge removal on Day 0, while the control group (n = 41) received 1 mL of sterile saline solution. All ewes underwent a single vaginal insemination 58 h after the withdrawal of the progesterone sponge. The difference in pregnancy rates between the two groups was calculated. Metabolomic analysis was performed on plasma samples collected on Day 7 after the treatment of GnRH agonist.ResultsGonadotropin-releasing hormone (GnRH) treatment significantly reduced the pregnancy rate in the experimental group compared with the control group (72.2 vs. 82.9%, p

BackgroundGonadotrophin-releasing hormone (GnRH) administration significantly decreases the pregnancy rate of recipient ewes after embryo transfer, possibly because GnRH affects endometrial epithelial cell function. Therefore, this study investigated the effect of GnRH on endometrial epithelial cells.MethodsTranscriptome sequencing was used to determine the regulatory effect of GnRH on the ewe endometrium, and the S100A4 gene, which showed altered transcription, was screened as a candidate regulator of this effect. Endometrial epithelial cells were further isolated, the S100A4 protein was immunoprecipitated, and host proteins that interacted with S100A4 were identified by mass spectrometry. We further verified the effects of S100A4 and GNAI2 on the proliferation of endometrial epithelial cells via overexpression/knockdown experiments and subsequent CCK-8 and EdU assays. The effect of S100A4 deletion in endometrial cells on reproduction was verified in mice with S100A4 knockout.ResultsOur results showed that S100A4 gene transcription in endometrial cells was significantly inhibited after GnRH administration. GNAI2 was identified as a downstream interacting protein of S100A4, and S100A4 was confirmed to activate the MAPK signaling pathway to promote cell proliferation by targeting GNAI2.ConclusionGnRH can suppress the expression of S100A4 in the endometrium, consequently inhibiting the proliferation of endometrial cells through the S100A4/GNAI2/MAPK signaling pathway. These findings suggest a potential explanation for the limited efficacy of GnRH in promoting embryo implantation.

IntroductionSuperovulation is a critical step in assisted reproductive technology, but the use of human chorionic gonadotropin (hCG) as a trigger for superovulation can result in ovarian hyperstimulation. Thus, the use of Gonadotropin-releasing hormone agonist (GnRHa) trigger has been increasingly adopted, although it has been associated with a higher rate of pregnancy failure compared to natural cycles. This study aimed to investigate the effect of GnRHa trigger on embryo implantation in a mouse model.MethodsMice in the superovulation (PG) group were administered 7.5 IU of PMSG, followed by the injection of 3.5 μg of GnRHa (Leuprorelin) 48 h later, while mice in the control group (CTR) mated naturally. We compared the number of oocytes, blastocysts, and corpus luteum between the two groups and the implantation sites after the transfer of natural blastocysts. Ovaries, uterus, and serum 2 and 4 days after mating were collected for qRT-PCR, transcriptome sequencing, and hormone assays.ResultsThe PG group had more oocytes, blastocysts, and corpus luteum after superovulation than the CTR group. However, the mRNA expression of leukemia inhibitory factor (Lif) and the number of implantation sites were reduced in the PG group. The ELISA assay revealed that superovulation increased ovarian estrogen secretion. The transcriptome analysis showed that superphysiological estrogen led to a response of the uterus to a high estrogen signal, resulting in abnormal endometrium and extracellular matrix remodeling and up-regulation of ion transport and inflammation-related genes.ConclusionOur findings suggest that a combination of PMSG and GnRHa trigger impaired embryo implantation in mice, as the excessive uterine response to superphysiological estrogen levels can lead to the change of gene expression related to endometrial remodeling, abnormal expression of uterine ion transport genes and excessive immune-related genes.

Acquired cystic disease-associated renal cell carcinoma (ACD-RCC) is an extremely rare kidney tumor seen mainly in patients with end-stage renal disease. Currently, there are few reports on this type of tumor. We describe the case of a 58-year-old man who had been receiving peritoneal dialysis for more than nine years due to chronic renal insufficiency and uremia. One year after undergoing left renal clear cell renal cell carcinoma resection, a space-occupying lesion was found in the right kidney for which he underwent right nephrectomy. The histopathology of this tumor showed solid or tubular cell arrangements, with some areas of cyst formation. Vacuoles of varying sizes were present in the cytoplasm, and varying amounts of calcium oxalate crystals were found in the tumor cells or interstitium. The pathological diagnosis was ACD-RCC. Next-generation sequencing detected mutations in the PTCH1, MTOR, FAT1, SOS1, RECQL4, and CDC73 genes in the right renal tumor. This is a rare case of a patient with ACD-RCC in the right kidney and clear cell renal cell carcinoma in the left kidney. The findings suggest that mutations in PTCH1 associated with ACD-RCC may have acted as oncogenic drivers for the development of ACKD-RCC, together with providing insight into mechanisms underlying ACD-RCC development, as well as diagnostic and treatment options.

Stroke has become a major disease that seriously threatens human health due to its high incidence and disability rates. Most patients undergo upper limb motor dysfunction after stroke, which significantly impairs the ability of stroke survivors in their activities of daily living (ADL). Robots provide an optional solution for stroke rehabilitation by attending therapy in the hospital and the community, however, the rehabilitation robot still has difficulty in providing needed assistance interactively like human clinicians in conventional therapy. For safe and rehabilitation training, a human-robot interaction space reshaping method was proposed based on the recovery states of patients. According to different recovery states, we designed seven experimental protocols suitable for distinguishing rehabilitation training sessions. To achieve assist-as-needed (AAN) control, a PSO-SVM classification model and an LSTM-KF regression model were introduced to recognize the motor ability of patients with electromyography (EMG) and kinematic data, and a region controller for interaction space shaping was studied. Ten groups of offline and online experiments and corresponding data processing were conducted, and the machine learning and AAN control results were presented, which ensured the effective and the safe upper limb rehabilitation training. To discuss the human-robot interaction in different training stages and sessions, we defined a quantified assistance level index that characterizes the rehabilitation needs by considering the engagement of the patients and had the potential to apply in clinical upper limb rehabilitation training.

BackgroundThe aging of the world population poses a major health challenge, and brain–computer interface (BCI) technology has the potential to provide assistance and rehabilitation for the elderly.ObjectivesThis study aimed to investigate the electroencephalogram (EEG) characteristics during motor imagery by comparing young and elderly, and study Convolutional Neural Networks (CNNs) classification for the elderly population in terms of fatigue analysis in both frontal and parietal regions.MethodsA total of 20 healthy individuals participated in the study, including 10 young and 10 older adults. All participants completed the left- and right-hand motor imagery experiment. The energy changes in the motor imagery process were analyzed using time–frequency graphs and quantified event-related desynchronization (ERD) values. The fatigue level of the motor imagery was assessed by two indicators: (θ + α)/β and θ/β, and fatigue-sensitive channels were distinguished from the parietal region of the brain. Then, rhythm entropy was introduced to analyze the complexity of the cognitive activity. The phase-lock values related to the parietal and frontal lobes were calculated, and their temporal synchronization was discussed. Finally, the motor imagery EEG data was classified by CNNs, and the accuracy was discussed based on the analysis results.ResultFor the young and elderly, ERD was observed in C3 and C4 channels, and their fatigue-sensitive channels in the parietal region were slightly different. During the experiment, the rhythm entropy of the frontal lobe showed a decreasing trend with time for most of the young subjects, while there was an increasing trend for most of the older ones. Using the CNN classification method, the elderly achieved around 70% of the average classification accuracy, which is almost the same for the young adults.ConclusionCompared with the young adults, the elderly are less affected by the level of cognitive fatigue during motor imagery, but the classification accuracy of motor imagery data in the elderly may be slightly lower than that in young persons. At the same time, the deep learning method also provides a potentially feasible option for the application of motor-imagery BCI (MI-BCI) in the elderly by considering the ERD and fatigue phenomenon together.

Bacteremia caused by Herbaspirillum huttiense (H. huttiense) is relatively rare in positive blood cultures. H. huttiense is an opportunistic bacterium in patients with cancer and cirrhosis and has also been described in immunocompromised hosts. In this study, H. huttiense was isolated from a patient with repeated chest tightness and chest pain. Smears were prepared, stained, and examined by microscopy. Single colonies were analyzed by Gram staining, matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS), 16S rRNA sequencing and Next-Generation Sequencing (NGS). Antibiotic sensitivity was assessed by agar dilution. Almost all publications on H. huttiense infections in the PubMed/ScienceDirect/EBSCO databases were reviewed and summarized. Blood sample culturing yielded white, gelatinous, and slightly raised colonies without hemolytic rings. The bacilli were found to be Gram-negative, and MS results showed 99.2% homology with H. huttiense. This was confirmed by 16S rRNA gene sequencing, phylogenetic tree analysis and NGS all of which were homologous with H. huttiense in GenBank. Antibiotic susceptibility tests were performed to determine the minimum inhibitory concentrations (MICs) of imipenem, meropenem, piperacillin-tazobactam, and levofloxacin. A comprehensive literature review revealed that H. huttiense was an emergent pathogen. After medical treatment, the patient’s body temperature returned to normal. This is the first report of bacteremia caused by H. huttiense in China. The findings could improve the awareness and attention of the rare pathogenic microorganisms in China.

Nitrogen (N) deposition rates are increasing in the temperate steppe due to human activities. Understanding the plastic responses of plant dominant species to increased N deposition through the lens of multiple traits is crucial for species selection in the process of vegetation restoration. Here, we measured leaf morphological, physiological, and anatomical traits of two dominant species (Stipa glareosa and Peganum harmala) after 3-year N addition (0, 1, 3, and 6 g N m−2 year−1, designated N0, N1, N3, and N6, respectively) in desert steppe of Inner Mongolia. We separately calculated the phenotypic plasticity index (PI) of each trait under different N treatments and the mean phenotypic plasticity index (MPI) of per species. The results showed that N addition increased the leaf N content (LNC) in both species. N6 increased the contents of soluble protein and proline, and decreased the superoxide dismutase (SOD) and the peroxidase (POD) activities of S. glareosa, while increased POD and catalase (CAT) activities of P. harmala. N6 increased the palisade tissue thickness (PT), leaf thickness (LT), and palisade-spongy tissue ratio (PT/ST) and decreased the spongy tissue–leaf thickness ratio (ST/LT) of S. glareosa. Furthermore, we found higher physiological plasticity but lower morphological and anatomical plasticity in both species, with greater anatomical plasticity and MPI in S. glareosa than P. harmala. Overall, multi-traits comparison reveals that two dominant desert-steppe species differ in their plastic responses to N addition. The higher plasticity of S. glareosa provides some insight into why S. glareosa has a broad distribution in a desert steppe.

BackgroundSubacute thyroiditis (SAT) is a self-limited inflammatory thyroid disease with recurring episodes. However, the results regarding the recurrence rate and risk factors for SAT are inconsistent. This meta-analysis aimed to summarize the evidence of the recurrence rate and the risk factors for SAT.MethodsThe present study involved the performance of a systematic literature search of all English studies published in PubMed, Embase, Web of Science, and The Cochrane Library from inception to August 20, 2021. Cohort studies that reported the SAT recurrence rate and risk factors for recurrence were included. Two independent investigators extracted relevant information. Fixed- and random-effects models were used to pool effect sizes based on study heterogeneity.ResultsEighteen cohort studies were identified. The pooled findings showed that the recurrence rate was 12.0% (95% CI: 8.2%, 17.1%). The risk of recurrence in the glucocorticoids group was higher than that in the NSAIDs group (RR = 1.84, 95% CI: 1.04, 3.24). However, there was no significant difference in age or sex between the recurrence group and the non-recurrence group. Findings from one or two cohort studies also indicated that the copresence of HLA-B*18:01 and -B*35, the number of days required to taper prednisolone (PSL) to 5 mg/day, the duration of disease before treatment less than 30 days, the sialic acid level, or the TSH level at the termination of treatment and further extension of the hypoechoic area and increase in thyroid volume were related to the recurrence of SAT.ConclusionRecurrence was common in SAT patients. The present study indicated that glucocorticoid treatment was associated with a higher recurrence rate of SAT than NSAIDs treatment. The clinical implications of this association should be interpreted with caution, and further clinical trials on the long-term effects of different treatment strategies are needed.

The salt layer is critical for the structural deformation in the salt-bearing fold-and-thrust system, which not only acts as the efficient décollement layer but also flows to form salt tectonics. Kuqa Depression has a well-preserved thin-skinned fold-and-thrust system with the salt layer as the décollement. To investigate the effects of salt thickness on the structural deformation in the Kuqa Depression, three discrete element models with different salt thicknesses were constructed. The experiment without salt was controlled by several basal décollement dominant faults, forming several imbricate sheets. The experiments with salt developed the decoupled deformation with the salt layer as the upper décollement (subsalt, intrasalt, and suprasalt), significantly similar to the Kuqa Depression along the northern margin of Tarim Basin. Basal décollement dominant imbricated thrusts formed at the subsalt units, while the monoclinal structure formed at the suprasalt units. The decoupled deformation was also observed in the tectonic deformation graphics, distortional strain fields, and max shear stress fields. However, the salt layer was thickened in the thick salt model, and the salt thickness of the thin salt model varied slightly because the thin salt weakened the flowability of the salt. The lower max shear stress zone was easily formed in the distribution region of salt under the action of compression stress, which is conducive to the flow convergence of salt and the crumpled deformation of interlayer in salt. The results are well consistent with the natural characteristics of structural deformation in the Kuqa Depression. Our modeling result concerns the structural characteristics and evolution of salt-related structures and the effects of salt thickness on the structural deformation in the compressional stress field, which might be helpful for the investigations of salt-related structures in other salt-bearing fold-and-thrust belts.

Hypoxia and inflammation often coincide in pathogenic conditions such as acute respiratory distress syndrome (ARDS) and chronic lung diseases, which are significant contributors to morbidity and mortality for the general population. For example, the recent global outbreak of Coronavirus disease 2019 (COVID-19) has placed viral infection-induced ARDS under the spotlight. Moreover, chronic lung disease ranks the third leading cause of death in the United States. Hypoxia signaling plays a diverse role in both acute and chronic lung inflammation, which could partially be explained by the divergent function of downstream target pathways such as adenosine signaling. Particularly, hypoxia signaling activates adenosine signaling to inhibit the inflammatory response in ARDS, while in chronic lung diseases, it promotes inflammation and tissue injury. In this review, we discuss the role of adenosine at the interphase of hypoxia and inflammation in ARDS and chronic lung diseases, as well as the current strategy for therapeutic targeting of the adenosine signaling pathway.

Purine nucleotides and nucleosides are at the center of biologic reactions. In particular, adenosine triphosphate (ATP) is the fundamental energy currency of cellular activity and adenosine has been demonstrated to play essential roles in human physiology and pathophysiology. In this review, we examine the role of purinergic signaling in acute and chronic pulmonary inflammation, with emphasis on ATP and adenosine. ATP is released into extracellular space in response to cellular injury and necrosis. It is then metabolized to adenosine monophosphate (AMP) via ectonucleoside triphosphate diphosphohydrolase-1 (CD39) and further hydrolyzed to adenosine via ecto-5′-nucleotidase (CD73). Adenosine signals via one of four adenosine receptors to exert pro- or anti-inflammatory effects. Adenosine signaling is terminated by intracellular transport by concentrative or equilibrative nucleoside transporters (CNTs and ENTs), deamination to inosine by adenosine deaminase (ADA), or phosphorylation back into AMP via adenosine kinase (AK). Pulmonary inflammatory and hypoxic conditions lead to increased extracellular ATP, adenosine diphosphate (ADP) and adenosine levels, which translates to increased adenosine signaling. Adenosine signaling is central to the pulmonary injury response, leading to various effects on inflammation, repair and remodeling processes that are either tissue-protective or tissue destructive. In the acute setting, particularly through activation of adenosine 2A and 2B receptors, adenosine signaling serves an anti-inflammatory, tissue-protective role. However, excessive adenosine signaling in the chronic setting promotes pro-inflammatory, tissue destructive effects in chronic pulmonary inflammation.

Background: Gonadotrophin-releasing hormone (GnRH) administration significantly decreases the pregnancy rate of recipient ewes after embryo transfer, possibly because GnRH affects endometrial epithelial cell function. Therefore, this study investigated the effect of GnRH on endometrial epithelial cells. Methods: Transcriptome sequencing was used to determine the regulatory effect of GnRH on the ewe endometrium, and the S100A4 gene, which showed altered transcription, was screened as a candidate regulator of this effect. Endometrial epithelial cells were further isolated, the S100A4 protein was immunoprecipitated, and host proteins that interacted with S100A4 were identified by mass spectrometry. We further verified the effects of S100A4 and GNAI2 on the proliferation of endometrial epithelial cells via overexpression/ knockdown experiments and subsequent CCK-8 and EdU assays. The effect of S100A4 deletion in endometrial cells on reproduction was verified in mice with S100A4 knockout. Results: Our results showed that S100A4 gene transcription in endometrial cells was significantly inhibited after GnRH administration. GNAI2 was identified as a downstream interacting protein of S100A4, and S100A4 was confirmed to activate the MAPK signaling pathway to promote cell proliferation by targeting GNAI2. Conclusion: GnRH can suppress the expression of S100A4 in the endometrium, consequently inhibiting the proliferation of endometrial cells through the S100A4/GNAI2/MAPK signaling pathway. These findings suggest a potential explanation for the limited efficacy of GnRH in promoting embryo implantation. [ABSTRACT FROM AUTHOR]

ObjectiveCerebral white matter hyperintensity can lead to cerebral small vessel disease, MRI images in the brain are used to assess the degree of pathological changes in white matter regions. In this paper, we propose a framework for automatic 3D segmentation of brain white matter hyperintensity based on MRI images to address the problems of low accuracy and segmentation inhomogeneity in 3D segmentation. We explored correlation analyses of cognitive assessment parameters and multiple comparison analyses to investigate differences in brain white matter hyperintensity volume among three cognitive states, Dementia, MCI and NCI. The study explored the correlation between cognitive assessment coefficients and brain white matter hyperintensity volume.MethodsThis paper proposes an automatic 3D segmentation framework for white matter hyperintensity using a deep multi-mapping encoder-decoder structure. The method introduces a 3D residual mapping structure for the encoder and decoder. Multi-layer Cross-connected Residual Mapping Module (MCRCM) is proposed in the encoding stage to enhance the expressiveness of model and perception of detailed features. Spatial Attention Weighted Enhanced Supervision Module (SAWESM) is proposed in the decoding stage to adjust the supervision strategy through a spatial attention weighting mechanism. This helps guide the decoder to perform feature reconstruction and detail recovery more effectively.ResultExperimental data was obtained from a privately owned independent brain white matter dataset. The results of the automatic 3D segmentation framework showed a higher segmentation accuracy compared to nnunet and nnunet-resnet, with a p-value of

ObjectiveToday, cerebrovascular disease has become an important health hazard. Therefore, it is necessary to perform a more accurate and less time-consuming registration of preoperative three-dimensional (3D) images and intraoperative two-dimensional (2D) projection images which is very important for conducting cerebrovascular disease interventions. The 2D–3D registration method proposed in this study is designed to solve the problems of long registration time and large registration errors in 3D computed tomography angiography (CTA) images and 2D digital subtraction angiography (DSA) images.MethodsTo make a more comprehensive and active diagnosis, treatment and surgery plan for patients with cerebrovascular diseases, we propose a weighted similarity measure function, the normalized mutual information-gradient difference (NMG), which can evaluate the 2D–3D registration results. Then, using a multi-resolution fusion optimization strategy, the multi-resolution fused regular step gradient descent optimization (MR-RSGD) method is presented to attain the optimal value of the registration results in the process of the optimization algorithm.ResultIn this study, we adopt two datasets of the brain vessels to validate and obtain similarity metric values which are 0.0037 and 0.0003, respectively. Using the registration method proposed in this study, the time taken for the experiment was calculated to be 56.55s and 50.8070s, respectively, for the two sets of data. The results show that the registration methods proposed in this study are both better than the Normalized Mutual (NM) and Normalized Mutual Information (NMI).ConclusionThe experimental results in this study show that in the 2D–3D registration process, to evaluate the registration results more accurately, we can use the similarity metric function containing the image gray information and spatial information. To improve the efficiency of the registration process, we can choose the algorithm with gradient optimization strategy. Our method has great potential to be applied in practical interventional treatment for intuitive 3D navigation.

BackgroundDiabetes is one of the most common metabolic diseases and continues to be a leading cause of death worldwide. The NLRP3 inflammasome has been shown to exert detrimental effects on diabetic models. However, evidence linking NLRP3 inflammasome and pre-diabetes has been scarcely explored. Herein, we aimed to determine whether the NLRP3 inflammasome correlates with insulin resistance and liver pathology in a cohort of pre-diabetic subjects.Methods50 pre-diabetic subjects were randomly assigned to a Pre-diabetes Control (DC, n=25) and a Pre-diabetes exercise (DEx, n=25) group. 25 Normal subjects (NC) were selected as controls. The DEx group performed a 6-month combined Yijingjing and resistance training intervention, while DC and NC group remained daily routines. Clinical metabolic parameters were determined with an automatic biochemistry analyzer; inflammatory cytokines were quantified by the ELISA assay; the protein expressions of NLRP3 inflammasome components in PBMCs were evaluated by Western Blot.ResultsThe insulin resistance, liver injury and NLRP3 inflammasome activity were higher in pre-diabetic individuals than in normal control group. However, 6-month exercise intervention counteracted this trend, significantly improved insulin sensitivity, reduced liver injury and inhibited the overactivation of NLRP3 inflammasome in pre-diabetic subjects. Moreover, positive correlations between insulin resistance, liver pathology and NLRP3 inflammasome were also found.ConclusionsOur study suggests that exercise training is an effective strategy to alleviate insulin resistance and liver injury in elderly pre-diabetic subjects which is probably associated with the inhibition of NLRP3 inflammasome activity.

ObjectiveLife form and body composition may affect the health of college students. This study will explore the relationship between the demographic variables of female college students and their body composition and health promoting lifestyle, so as to provide useful reference for the future design and planning of college students' physical and mental health courses and improving their physical activity level.MethodsUsing the method of questionnaire and bioelectrical resistance measurement, a questionnaire on healthy lifestyle of college students was constructed on the basis of consulting a large number of relevant research literature. Relevant survey samples were obtained through random sampling, and their body composition was measured; use SPSS21.0 statistical analysis software to conduct statistical analysis on relevant indicators.Results and conclusions(1) at present, female college students generally lack leisure activities and sleep, the proportion of regular fitness habits is low, and the number of snacks and average daily online time are generally too high; The overweight rate and body fat rate of female college students are generally too high, while the standard rate of muscle weight is generally too low. (2) Female college students' health promoting lifestyle has the highest score of self-realization, followed by interpersonal support and the worst behavior of sports participation; The older the college students, the worse their sports participation and overall health promotion behavior; The better the Conscious health status, the better the self-realization, exercise participation and nutritional behavior; The more exercise time per day, the higher their participation in sports and the stronger their health responsibility; The more time spent on the Internet every day, the worse the health responsibility and sports participation. (3) The more time female college students spend on the Internet every day, the higher the probability of overweight. Those with regular exercise habits have a lower proportion of overweight and high body fat rate, while the better their sleep and night snack behavior, the lower their body fat rate. The older college students are, the larger their visceral fat area is, the better their exercise habits and sleep behavior are, the smaller their visceral fat area is, and the lower their visceral fat level is.

IntroductionThis study investigated the effect of Yijinjing combined with elastic band exercise on muscle mass and muscle function in patients with prediabetes.MethodsThis study was a randomized controlled trial designed in parallel (Chinese Clinical Trial Registry: ChiCTR2000039049). Participants with prediabetes (n = 47) were randomly divided into control (n = 21, 63.5 ± 4.7 years,16 females) and exercise (n = 26, 62.0 ± 5.0 years, 20 females) groups. The former maintained their original lifestyle, and the latter received Yijinjing combined with elastic band exercise five times a week for 6 months. All the outcome measures were assessed immediately at baseline, after 3- and 6-month intervention.ResultsAfter 6-month of the exercise, the body weight, body mass index, leg fat mass, gynoid fat mass, and total body fat mass in exercise group were significantly decreased compared with those at baseline (p < 0.05). Compared with those at baseline, total lean mass decreased at 3 and 6 months in both groups. The total muscle mass loss in the exercise group was always less than that in control group at all time periods, but the difference was not statistically significant. Handgrip strength, gait speed, reaction time, leg power, eye-closed and single-legged standing, and sit-and-reach were significantly improved for the exercise group at 3 and 6 months (p < 0.05). Gait speed and reaction time between both groups at 3 and 6 months were significant different (p < 0.05), and leg power at 6 months (p < 0.05). Compared with baseline, the reaction time of control group at six months was significantly improved (p < 0.05), and no other significant changes were observed. Compared with those at baseline, fasting plasma glucose, 2-h post-meal plasma glucose, fasting insulin, total cholesterol, and insulin resistance index in exercise group gradually decreased, and growth hormone was gradually increased with significance at 6 months (p < 0.05). 25-hydroxyvitamin D gradually and significantly increased in both groups at 3 and 6 months (p < 0.05). But two groups’ testosterone levels weren’t significant change.ConclusionYijinjing combined with elastic band exercise can substantially reduce the body weight and body fat content of middle-aged and elderly patients with Prediabetes, improve muscle function and growth hormone secretion, and delay muscle mass reduction and diabetes development.Clinical trial registration[http://www.chictr.org.cn/showproj.aspx?proj=62753], identifier [ChiCTR2000039049].

BackgroundPain is a common complication after stroke with a high incidence and mortality rate. Many studies in the field of pain after stroke have been published in various journals. However, bibliometric analysis in the domain of pain after stroke is still lacking. This study aimed to deliver a visual analysis to analyze the global trends in research on the comorbidity of pain after stroke in the last 12 years.MethodsThe publications from the Web of Science (WoS) in the last 12 years (from 2010 to 2021) were collected and retrieved. CiteSpace software was used to analyze the relationship of publication year with countries, institutions, journals, authors, references, and keywords.ResultsA total of 322 publications were included in the analysis. A continuous but unstable growth in the number of articles published on pain after stroke was observed over the last 12 years. The Peoples' R China (65), Chang Gung University (10), and Topic in Stroke Rehabilitation (16) were the country, institution, and journal with the highest number of publications, respectively. Analysis of keywords showed that shoulder pain after stroke and central post-stroke pain were the research development trends and focus in this research field.ConclusionThis study provides a visual analysis method for the trend and frontiers of pain research after stroke. In the future, large sample, randomized controlled trials are needed to identify the potential treatments and pathophysiology for pain after stroke.

It is a challenge to automatically and accurately segment the liver and tumors in computed tomography (CT) images, as the problem of over-segmentation or under-segmentation often appears when the Hounsfield unit (Hu) of liver and tumors is close to the Hu of other tissues or background. In this paper, we propose the spatial channel-wise convolution, a convolutional operation along the direction of the channel of feature maps, to extract mapping relationship of spatial information between pixels, which facilitates learning the mapping relationship between pixels in the feature maps and distinguishing the tumors from the liver tissue. In addition, we put forward an iterative extending learning strategy, which optimizes the mapping relationship of spatial information between pixels at different scales and enables spatial channel-wise convolution to map the spatial information between pixels in high-level feature maps. Finally, we propose an end-to-end convolutional neural network called Channel-UNet, which takes UNet as the main structure of the network and adds spatial channel-wise convolution in each up-sampling and down-sampling module. The network can converge the optimized mapping relationship of spatial information between pixels extracted by spatial channel-wise convolution and information extracted by feature maps and realizes multi-scale information fusion. The proposed ChannelUNet is validated by the segmentation task on the 3Dircadb dataset. The Dice values of liver and tumors segmentation were 0.984 and 0.940, which is slightly superior to current best performance. Besides, compared with the current best method, the number of parameters of our method reduces by 25.7%, and the training time of our method reduces by 33.3%. The experimental results demonstrate the efficiency and high accuracy of Channel-UNet in liver and tumors segmentation in CT images.