Multidrug-resistant (MDR) bacterial infections have emerged as a serious challenge of global public health crisis. The overuse and misuse of conventional antibiotics have dramatically accelerated the emergence, evolution and worldwide spread of drug-resistant bacterial strains, necessitating urgent exploration of novel antibacterial strategies. Bacteriophages serve as natural bacterial predators offering distinct advantages including high host specificity, autonomous self-replication capabilities and cost-effective large-scale production. However, wild-type phages present significant clinical limitations due to their narrow host ranges, susceptibility to rapid immune clearance and poor penetration of bacterial biofilms, which severely restrict their therapeutic applications. The convergence of synthetic biology, nanotechnology and advanced gene editing technologies has accelerated the development of engineered bacteriophage platforms, providing programmable, scalable and clinically translatable pathways to overcome these inherent biological constraints. Here, we systematically delineate four fundamental strategies for engineered bacteriophage development. Chemical modification utilizes reactive functional groups such as amino, carboxyl and thiol moieties on capsid proteins through esterification, amidation or click chemistry reactions to achieve precise drug conjugation and surface functionalization. In vivo editing encompasses ultraviolet or chemical mutagenesis for random mutation induction, homologous recombination for targeted genetic alterations, recombineering methodologies including electroporation-mediated bacteriophage recombination engineering, and CRISPR-Cas systems for precise genome editing to enable exact genetic reconstruction and host range reprogramming. In vitro synthesis leverages genome engineering platforms where intact phage genomes are transferred into yeast or host bacteria to facilitate highly efficient homologous recombination, enabling large DNA fragment assembly and cross-gene host range expansion without bacterial toxicity constraints. Directed evolution combines artificial selection through mutation library screening with rational design approaches involving chimeric receptor binding protein construction or site-specific mutagenesis, effectively balancing the discovery of unknown adaptive pathways with targeted host specificity modification. Moreover, we comprehensively discuss therapeutic applications across diverse clinical scenarios. Engineered bacteriophage effectively disrupt bacterial biofilms through sophisticated functionalized delivery platforms including nanozyme-conjugated phages, phage-liposome nanoconjugates and bio-responsive hydrogels, demonstrating significantly enhanced bactericidal efficiency compared to unmodified free phages. These bioengineered vectors attenuate bacterial virulence and resensitize pathogens to antibiotics by delivering CRISPR-Cas systems or base editors to disrupt critical virulence factors such as pili, capsule synthesis machineries and quorum sensing systems, or by inactivating antibiotic resistance determinants including beta-lactamase genes. As an intelligent nanomedicine delivery platform, engineered bacteriophage enable precise pathogen elimination an through photocatalytic reactive oxygen species generation, immunomodulatory interventions, or controlled release of antibacterial drugs. Furthermore, oral administration of engineered bacteriophage facilitates microbiota modulation, which selectively eliminate intestinal pathogens while preserve beneficial commensal microbiota, thereby restoring microbial community balance and preventing complications associated with dysbiosis. Finally, we critically analyze persistent challenges including host strain matching complexity, evolution of bacterial resistance mechanisms, pharmacokinetic optimization requirements, optimal administration route selection, large-scale production quality control standards and clinical dosing determination protocols. Through multidisciplinary integration of synthetic biology, infectious disease medicine and immunology, future translational medicine studies of bacteriophage should establish comprehensive technical platforms encompassing rapid phage screening, intelligent rational design, rigorous in vivo evaluation and standardized clinical validation processes, ultimately advancing engineered bacteriophage from laboratory innovations to clinically approved therapeutics for effectively combating MDR bacterial infections.

Electroencephalography (EEG) is a non-invasive neurophysiological monitoring technique. It records the electrical activity of the cerebral cortex using electrodes placed on the scalp surface. Owing to its high safety, portability, and millisecond-level temporal resolution, EEG has been widely utilized in a variety of fields, including clinical diagnosis, brain-computer interfaces (BCIs), and cognitive neuroscience research. However, due to its microvolt-level amplitude, EEG is highly susceptible to various artifacts, including electrooculographic (EOG), electrocardiographic (ECG), electromyographic (EMG), and power line interference (PLI). These artifacts can obscure genuine neural activity and introduce spurious electrophysiological features. Consequently, they may compromise EEG signal quality, thereby reducing the reliability of downstream analyses. To address this issue, numerous EEG artifact removal methods have been developed, including both traditional denoising techniques and deep learning-based approaches. Traditional EEG denoising methods have long served as the primary solutions for artifact removal. Representative approaches include filtering, regression, and blind source separation. Although these methods have demonstrated effectiveness in specific scenarios, they suffer from several inherent limitations. Filtering assumes that artifacts and EEG signals can be separated in the frequency domain, but many artifacts, such as EOG and EMG, overlap with EEG spectra, which may lead to the loss of valuable neural information. Regression methods require high-quality artifact references to estimate and subtract contaminations, limiting their effectiveness in reference-free scenarios. Blind source separation can remove artifacts without external references, but it typically requires the number of EEG channels to exceed the number of sources, restricting its application in single- or low-channel EEG recordings. Deep learning-based EEG denoising methods address these limitations effectively. First, they learn the nonlinear mapping between contaminated and clean EEG directly from data in an end-to-end manner. This approach does not rely on assumptions about spectral separability, thereby preserving neural activity more completely. Second, the reference information is incorporated during the training phase, allowing the trained model to perform artifact removal independently without external references. Third, deep learning models can be flexibly designed to accommodate various recording setups, achieving robust denoising for both high-density and single-channel EEG. Collectively, these advantages enable deep learning-based methods to overcome the main challenges of traditional approaches, providing more accurate and reliable EEG signal recovery. The superior denoising performance of deep learning-based EEG denoising methods has attracted increasing attention in EEG artifact removal research. As a result, many deep learning-based denoising methods have been developed and successfully applied in neural engineering areas. However, a systematic review of the techniques and applications in this field is still lacking. To address this gap, this paper reviews recent advances in deep learning-based EEG denoising from four perspectives: technical principle, benchmark dataset, denoising model, and evaluation method. Representative applications in neural signal analysis and BCI decoding are also summarized. Furthermore, the advantage, existing challenge, and future research direction of deep learning-based EEG denoising are discussed. This review aims to provide valuable theoretical insights and technical guidance for researchers. It is also expected to promote further advances and broader applications of deep learning-based EEG denoising techniques.

Consciousness, which underpins human perception, cognition, and behavioural responses, has long been a major focus of neuroscience and medicine. Alterations in consciousness occur not only during reversible processes such as sleep and anaesthesia, but also in pathological conditions, including disorders of consciousness (DOC) and brain injury. With recent advances in the synchronized acquisition and analysis of multimodal physiological signals, such as electroencephalography (EEG) and electrocardiography (ECG), the dynamic interactions between the heart and brain have become increasingly apparent. A growing body of evidence indicates that heart-brain interactions are closely associated with the maintenance and transition of consciousness states, offering a novel perspective for elucidating their underlying mechanisms and supporting relevant clinical assessments. Current approaches to heart-brain interaction analysis for consciousness-state assessment can be broadly grouped into three categories: ECG-based methods, EEG-based methods, and heart-brain coupling analysis. These approaches characterize heart-brain interactions during changes in consciousness from the complementary perspectives of autonomic regulation, cortical interoceptive processing, and cross-system information transfer, respectively. Nevertheless, this field remains at an early stage. Most studies have focused on a single experimental context or a fixed analytical method, with insufficient systematic consideration of the applicability and limitations of different approaches. Moreover, the mechanisms underlying the emergence and alteration of consciousness remain incompletely understood. Accordingly, this review examines heart-brain interaction methods employed in recent consciousness-state assessment studies in accordance with progressively deeper analytical perspectives, and systematically evaluates the advantages and limitations of these methods across distinct consciousness-related conditions. Heart rate variability (HRV) is one of the classical ECG-based indices used to investigate heart-brain interactions. It refers to fluctuations in consecutive interbeat intervals over a specified time period and is regarded as a physiological measure of autonomic nervous system regulation that may indirectly reflect the strength of heart-brain interactions. Depending on the analytical dimension, HRV analysis is commonly divided into time-domain, frequency-domain, and complexity-index analyses. These approaches characterize autonomic activity in terms of temporal fluctuations, the distribution of frequency components, and nonlinear dynamical properties, respectively. Although extensive research supports their physiological interpretation, they cannot characterize directional interactions from the heart to the brain. Among EEG-based methods for heart-brain interaction analysis, EEG activity directly related to cardiac fluctuations has received particular attention. One of the most widely used measures is the heartbeat-evoked potential (HEP). HEP-based approaches are considered to directly reflect the capacity of the cerebral cortex to process cardiac afferent signals and may be especially advantageous for characterizing rapidly changing consciousness levels, such as those observed during sleep. However, they do not comprehensively capture dynamic bidirectional information exchange between the brain and heart and are susceptible to cardiac artefacts, respiration, and variation in preprocessing procedures. Heart-brain coupling analysis quantifies functional associations between ECG and EEG through cross-system interaction measures, thereby assessing dynamic interactions between the heart and brain. It emphasizes information transfer, feedback regulation, and cross-timescale coordination between the two systems, offering a more comprehensive perspective for investigating changes in consciousness during sleep, anaesthesia, and DOC. However, the neurophysiological mechanisms and physiological interpretation of individual computational indices have not yet been fully established, and the robustness of their results and their potential for clinical generalization require further validation. Finally, this review summarizes the commonalities and differences among the three classes of methods across research domains involving different consciousness states. It further argues that heart-brain interaction research requires deeper investigation at both the mechanistic level of consciousness and the level of clinical application. Current challenges and key issues are identified, and future directions and feasible pathways for heart-brain interaction research are discussed, with the aim of providing new perspectives for researchers in related fields.

With Glycyrrhizae Radix et Rhizoma-Gypsum Fibrosum drug pair as the research object, supramolecular chemistry of traditional Chinese medicine(TCM) was used to study differences between the compatibility of herbal medicine Glycyrrhizae Radix et Rhizoma with mineral medicine Gypsum Fibrosum and its main component CaSO_4·2H_2O, so as to preliminarily discuss the scientific connotation of compatibility of Gypsum Fibrosum in clinical application. A Malvern particle sizer, a scanning electron microscope(SEM), and a conductivity meter were used to observe and determine the physical properties such as microscopic morphology, particle size, and conductivity of Gypsum Fibrosum, CaSO_4·2H_2O, and water decoctions of them with Glycyrrhizae Radix et Rhizoma. An inductively coupled plasma optical emission spectrometer(ICP-OES) was employed to detect the inorganic metal elements in Glycyrrhizae Radix et Rhizoma-Gypsum Fibrosum and Glycyrrhizae Radix et Rhizoma-CaSO_4·2H_2O. Isothermal titration calorimetry(ITC) was conducted to quantify the interactions of Gypsum Fibrosum and CaSO_4·2H_2O with Glycyrrhizae Radix et Rhizoma. A Fourier transform infrared spectrometer(FTIR) was used to analyze the characteristic absorption peak change of Glycyrrhizae Radix et Rhizoma-Gypsum Fibrosum and Glycyrrhizae Radix et Rhizoma-CaSO_4·2H_2O. X-ray diffraction(XRD) was performed to determine the crystal structure and phase composition of Glycyrrhizae Radix et Rhizoma-Gypsum Fibrosum and Glycyrrhizae Radix et Rhizoma-CaSO_4·2H_2O. Further, glycyrrhizic acid(GA) was substituted for Glycyrrhizae Radix et Rhizoma to co-decoct with Gypsum Fibrosum, CaSO_4·2H_2O, and freeze-dried powder of their respective water decoctions. The results of XRD were used for verification analysis. The results showed that although CaSO_4·2H_2O is the main component of Gypsum Fibrosum, there were significant differences between their decoctions and between the decoctions of them with Glycyrrhizae Radix et Rhizoma. Specifically,(1) Both CaSO_4·2H_2O and Gypsum Fibrosum were amorphous fibrous. However, the particle size and conductivity were significantly different between the decoctions of CaSO_4·2H_2O and Gypsum Fibrosum alone.(2) Under SEM, Glycyrrhizae Radix et Rhizoma-CaSO_4·2H_2O was a hybrid system with various morphologies, while Glycyrrhizae Radix et Rhizoma-Gypsum Fibrosum presented uniform nanoparticles.(3) The particle sizes and conductivities of Glycyrrhizae Radix et Rhizoma-CaSO_4·2H_2O and Glycyrrhizae Radix et Rhizoma-Gypsum Fibrosum were significantly different and did not follow the same tendency as those of the decoctions of CaSO_4·2H_2O and Gypsum Fibrosum alone.(4) Compared with Glycyrrhizae Radix et Rhizoma-CaSO_4·2H_2O, Glycyrrhizae Radix et Rhizoma-Gypsum Fibrosum had stronger molecular binding ability and functional group structure change.(5) The crystal form was largely different between the freeze-dried powder of CaSO_4·2H_2O decoction and Gypsum Fibrosum decoction, and their crystal forms were also significantly different from those of the freeze-dried powder of Glycyrrhizae Radix et Rhizoma-CaSO_4·2H_2O and Glycyrrhizae Radix et Rhizoma-Gypsum Fibrosum decoctions. The reason for the series of differences is that Gypsum Fibrosum is richer in trace elements than CaSO_4·2H_2O. The XRD results of GA-Gypsum Fibrosum and GA-CaSO_4·2H_2O decoctions further prove the importance of trace elements in Gypsum Fibrosum for supramolecule formation. This research preliminarily reveals the influence of compatibility of Gypsum Fibrosum or CaSO_4·2H_2O on decoction phase state, material form, and crystal form, providing a basis for the rational clinical application of Gypsum Fibrosum.
Drugs, Chinese Herbal/chemistry* ; Calcium Sulfate/chemistry* ; Glycyrrhiza/chemistry* ; Crystallization ; Particle Size ; Medicine, Chinese Traditional ; Rhizome/chemistry*

The 2024 National Education Work Conference pointed out that at the current juncture of the critical period for achieving the goals and tasks of the 14th Five-Year Plan,the implementation of the Education Powerhouse Construction Plan Outline should be taken as the main line of work,and building first-class disciplines is an crucial task for a higher education powerhouse.In 2022,forensic medicine was officially listed as a first-level discipline under the medical category,presenting an un-precedented historical opportunity for the development of forensic medicine.The forensic medicine dis-cipline of Southern Medical University comprehensively improves the quality of talent cultivation and facilitates the construction of first-class disciplines as its main direction.It aims to initiate and imple-ment a high-level faculty team building plan featuring"combining recruitment and cultivation,inter-disciplinary integration";make vigorous efforts to establish a first-level doctoral program,refine advan-tageous second-level disciplines and research directions;and establish an innovative research platform from a high starting point with deep integration.The discipline adheres to moral cultivation and the Five Domains of Education simultaneous development,to build a high-quality talent joint training model.Guided by the construction of the national legal system and industry needs,the discipline will enhance social service capabilities.The forensic medicine construction in our university will continue to contribute to the rule of law in China and educational power.

Objective To analyze the characteristics and risk factors associated with postoperative deep vein thrombosis(DVT)of the lower extremities in patients undergoing surgery for lumbar degenerative diseases.Methods A retrospective analysis was conducted on clinical data from 298 patients who were hospitalized for lumbar degenerative diseases and underwent lumbar spine surgery treatment in the First Affiliated Hospital of Nanchang University from October 1,2022 to April 15,2023.Patients were divided into DVT group(n=71)and non-DVT group(n=227)according to whether DVT of the lower limbs occurred within 1 week postoperatively.The incidence and distribution characteristics of postoperative DVT were analyzed.Univariate and binary logistic regression analyses were performed to identify risk factors for DVT,and receiver operating characteristic(ROC)curves were used to determine cut-off values for relevant risk factors.Results A total of 298 patients were included,among whom 159 were males(53.4%)and 139 were females(46.6%),with an average age of(64.5±9.8)years.DVT occurred in 71 patients,and the incidence of lower extremity DVT was 23.8%.In the DVT group,there were 49 cases(69.0%)of intermuscular vein thrombosis,and 22 cases of other types of thrombosis(7 cases of peroneal vein thrombosis,4 cases of posterior tibial vein thrombosis,3 cases of common femoral vein thrombosis,1 case of anterior tibial vein thrombosis,and 7 cases of multiple thrombosis);58 cases(81.7%)had DVT in one lower extremity,and 13 cases(18.3%)had DVT in both lower extremities.Univariate analysis results showed that age,body mass index(BMI),length of hospital stay,history of hypertension,operative time,and intraoperative blood loss were associated with the occurrence of lower extremity DVT after surgery for lumbar degenerative diseases(P<0.05).Binary logistic regression analysis results indicated that older age(OR=1.079,P<0.01),higher BMI(OR=1.130,P=0.01),history of hypertension(OR=2.992,P<0.01),and larger intraoperative blood loss(OR=1.002,P=0.03)were independent risk factors for the occurrence of lower extremity DVT.ROC curve analysis demonstrated that patients with age>58.5 years,BMI>24.01 kg/m2,history of hypertension,and intraoperative blood loss>550 ml had a significantly increased risk of postoperative lower limb DVT.Conclusions The incidence of lower extremity DVT after surgery for lumbar degenerative disease is high,and intermuscular venous thrombosis is more common.Older age,higher BMI,history of hypertension,and larger intraoperative blood loss are independent risk factors for the occurrence of lower extremity DVT after surgery.

Objective:To investigate the risk factors and their predictive efficacy for early postoperative complications in elderly patients with hip fracture.Methods:A retrospective cohort study was conducted on the clinical data of 203 elderly patients with hip fracture admitted to the 908th Hospital of the Joint Logistics Support Force of the PLA and the First Affiliated Hospital of Nanchang University from January 2022 to December 2023, including 54 males and 149 females, aged 65-100 years [(80.5±7.7)years]. There were 96 patients with femoral neck fracture and 107 patients with intertrochanteric fracture. According to the AO/OTA classification, the fracture was classified as type 31A in 107 patients and type 31B in 96. Among them, 81 patients were treated with proximal femoral nail antirotation (PFNA), 65 with semi-hip arthroplasty, 52 with total hip arthroplasty (THA), and 5 with closed reduction and cannulated nail internal fixation. The patients were divided into complication group ( n=65) and non-complication group ( n=138) according to whether complications (mainly including delirium, lung infection, stress ulcer, and deep vein thrombosis of the lower limbs) occurred within 15 days after surgery. The gender, age, age stage, educational level, cause of injury, associated underlying diseases before surgery, AO/OTA classification, American Society of Anesthesiologists (ASA) classification, 5-factor modified frailty index (mFI-5) score, prognostic nutritional index (PNI), anesthesia method, operation method, operation time, intraoperative blood loss, length of hospital stay, etc., were recorded in the two groups. Univariate analysis and multivariate binary logistic regression analysis were used to evaluate the correlation between the above indexes and the occurrence of early postoperative complications in elderly patients with hip fracture and to determine their independent risk factors. The receiver operating characteristic (ROC) curve was plotted and the area under the curve (AUC) was calculated to evaluate the predictive efficacy of each risk factor for the occurrence of early postoperative complications in elderly patients with hip fracture. Results:Univariate analysis showed a certain correlation between age, age stage, associated underlying diseases before surgery, AO/OTA classification, ASA classification, mFI-5 score, PNI, operation method, and length of hospital stay and the occurrence of early postoperative complications in elderly patients with hip fracture ( P<0.05), while gender, educational level, cause of injury, anesthesia method, operation time, and intraoperative blood loss were not correlated with the occurrence of early postoperative complications in elderly patients with hip fracture ( P>0.05). The results of multivariate binary logistic regression analysis showed that the associated underlying diseases before surgery ( OR=5.46, 95% CI 1.33, 22.39, P<0.05), mFI-5 score ( OR=15.90, 95% CI 5.36, 47.15, P<0.01), and PNI ( OR=0.70, 95% CI 0.60, 0.81, P<0.01) were significantly correlated with the occurrence of early postoperative complications in elderly patients with hip fracture. The results of ROC curve analysis showed that mFI-5 score (AUC=0.85, 95% CI 0.80, 0.91) and PNI (AUC=0.87, 95% CI 0.82, 0.93) had moderate predictive efficacy, while the early warning efficacy of associated underlying diseases was low (AUC=0.54, 95% CI 0.45, 0.62). The combination of the above risk factors was more effective in predicting early postoperative complications in elderly patients with hip fracture (AUC=0.95, 95% CI 0.92, 0.98). Conclusions:The mFI-5 score, PNI, and associated underlying diseases before surgery are independent risk factors for early postoperative complications in elderly patients with hip fracture. The mFI-5 score and PNI have a higher predictive efficacy than associated diseases before surgery on the occurrence of early postoperative complications in elderly patients with hip fracture, while the combination of the above risk factors provides a significantly better predictive performance.

This study compared the differences in intestinal absorption characteristics of eleven active components in Rubus multibracteatus(RM) extract(protocatechuic acid, tiliroside, scutellarin, luteoloside, astragalin, epicatechin, catechin, xanthotoxin, p-coumaric acid, caffeic acid, and apigenin-7-O-glucuronide) between normal rats and inflammatory pain model rats using the in-vitro everted intestinal sac model. The RM extract was administered at absorption concentrations of 25.0, 50.0, and 100.0 mg·mL~(-1). The contents of the eleven components in intestinal absorption solution samples were quantified by ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS), and their cumulative absorption(Q) and absorption rate constant(K_a) were calculated to evaluate the absorption characteristics of these components in normal rats and inflammatory pain model rats. The results show that except for catechin, epicatechin, and caffeic acid, the cumulative absorption-time curves of the other eight components(protocatechuic acid, tiliroside, scutellarin, luteoloside, astragalin, xanthotoxin, p-coumaric acid, and apigenin-7-O-glucuronide) exhibit an upward trend without saturation, with correlation coefficients(R~2) all > 0.9, indicating linear absorption. However, the overall absorption of all components is not dose-dependent with increasing concentration, suggesting that their absorption mechanisms are not solely passive diffusion. In both normal and model rats, the jejunum shows the highest absorption for all components except xanthotoxin. The overall absorption of seven components(excluding protocatechuic acid, caffeic acid, apigenin-7-O-glucuronide, and luteoloside) in normal rats is better than that in model rats across all intestinal segments. These findings indicate that the pathological state of inflammatory pain alters the intestinal absorption of RM extract, and its mechanism needs further investigation.
Animals ; Rats ; Intestinal Absorption/drug effects* ; Male ; Rats, Sprague-Dawley ; Drugs, Chinese Herbal/metabolism* ; Disease Models, Animal ; Pain/metabolism* ; Intestines/drug effects* ; Intestinal Mucosa/metabolism*

ObjectiveTo observe the clinical efficacy and safety of Mailuoning compound solution in the treatment of hip joint pain via nerve blocks around the hip joint. MethodsFrom March 2015 to March 2019，a total of 136 patients with hip joint pain who met the inclusion criteria were admitted and divided into an observation group and a control group according to the random number table method. Among them，six cases fell off due to failure to complete five treatments，and finally， 130 patients entered clinical observation，with 65 cases in each group. The observation group used Mailuoning compound solution for nerve blocks around the hip joint（including obturator nerve，femoral nerve branch，superior gluteal nerve， and hip fascia）. The control used Mailuoning compound solution for a simple obturator nerve block. The differences in the visual analogue scale （VAS） and Harris score of hip joint of the two groups before and after treatment were observed. Any adverse drug reactions and adverse events during the treatment of the patients were recorded. ResultsThe VAS score of the two groups was significantly decreased after treatment （P<0.01）. The observation group had a more significant decrease compared to the control group（P<0.01）. The total Harris score of hip joint， pain degree，function score， and motion of joint of the two groups were significantly improved after treatment （P<0.01）. Compared with the control group，the improvement in the total Harris score of hip joint， pain degree，and function score was more significant in the observation group （P<0.01）. The clinical efficacy based on the Harris score of hip joint of the two groups was compared. The excellent and good rate of the observation group was 84.62% （55/65）， which was significantly better than that of the control group ［56.92% （37/65）］ （χ²=12.05，P<0.01）. The follow-up results showed that the patients who achieved excellent and good results had stable curative effects and low recurrence rates，and there was no significant difference in recurrence rate between the two groups. Case analysis showed that after treatment of femoral head necrosis，the saccular transparent shadow of the femoral head was significantly reduced，and the number of bone trabeculae increased. The low-density shadow decreased as can be seen on hip X-rays. In patients with hip osteoporosis after treatment，the number of bone trabeculae increased， and the low density shadow reduced. ConclusionThe use of Mailuoning compound solution for nerve blocks around the hip joint gives full play to the synergistic effect of Mailuoning compound solution and nerve block. It can effectively relieve hip joint pain，promote the recovery of hip joint function，reduce the disability rate，and improve the quality of life of patients. Early intervention is an important link in the treatment of hip joint pain diseases，which can effectively control the development of the patient's disease. Mailuoning compound solution is a new idea and method to treat hip joint pain through neuroregulation，which is easy to operate，with high safety and good therapeutic effect. In future studies，a larger sample size is needed，and more in-depth research should be conducted on the imaging changes and mechanisms of action for various hip joint pain diseases.

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*