With the widespread use of antibiotics, drug-resistant bacterial infections have become a significant threat to human health. Finding new antibacterial strategies that can effectively control drug-resistant bacterial infections has become an urgent task. Unlike small molecule drugs that target bacterial proteins, antisense oligonucleotide (ASO) can target genes related to bacterial resistance, pathogenesis, growth, reproduction and biofilm formation. By regulating the expression of these genes, ASO can inhibit or kill bacteria, providing a novel approach for the development of antibacterial drugs. To overcome the challenge of delivering antisense oligonucleotide into bacterial cells, various drug delivery systems have been applied in this field, including cell-penetrating peptides, lipid nanoparticles and inorganic nanoparticles, which have injected new momentum into the development of antisense oligonucleotide in the antibacterial realm. This review summarizes the current development of small nucleic acid drugs, the antibacterial mechanisms, targets, sequences and delivery vectors of antisense oligonucleotide, providing a reference for the research and development of antisense oligonucleotide in the treatment of bacterial infections.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.

OBJECTIVE: To illustrate the role of dehydrocorydaline (DHC) in chronic constriction injury (CCI)-induced neuropathic pain and the underlying mechanism. METHODS: C57BL/6J mice were randomly divided into 3 groups by using a random number table, including sham group (sham operation), CCI group [intrathecal injection of 10% dimethyl sulfoxide (DMSO)], and CCI+DHC group (intrathecal injection of DHC), 8 mice in each group. A CCI mouse model was conducted to induce neuropathic pain through ligating the right common sciatic nerve. On day 14 after CCI modeling or sham operation, mice were intrathecal injected with 5 µL of 10% DMSO or 10 mg/kg DHC (5 µL) into the 5th to 6th lumbar intervertebral space (L5-L6). Pregnant ICR mice were sacrificed for isolating primary spinal neurons on day 14 of embryo development for in vitro experiment. Pain behaviors were evaluated by measuring the paw withdrawal mechanical threshold (PWMT) of mice. Immunofluorescence was used to observe the activation of astrocytes and microglia in mouse spinal cord. Protein expressions of inducible nitric oxide synthase (iNOS), tumor necrosis factor alpha (TNF-α), interleukin 6 (IL-6), phosphorylation of N-methyl-D-aspartate receptor subunit 2B (p-NR2B), and NR2B in the spinal cord or primary spinal neurons were detected by Western blot. RESULTS: In CCI-induced neuropathic pain model, mice presented significantly decreased PWMT, activation of glial cells, overexpressions of iNOS, TNF-α, IL-6, and higher p-NR2B/NR2B ratio in the spinal cord (P<0.05 or P<0.01), which were all reversed by a single intrathecal injection of DHC (P<0.05 or P<0.01). The p-NR2B/NR2B ratio in primary spinal neurons were also inhibited after DHC treatment (P<0.05). CONCLUSION An intrathecal injection of DHC relieved CCI-induced neuropathic pain in mice by inhibiting the neuroinflammation and neuron hyperactivity.
Animals ; Neuralgia/etiology* ; Mice, Inbred C57BL ; Analgesics/pharmacology* ; Neuroinflammatory Diseases/pathology* ; Constriction ; Male ; Receptors, N-Methyl-D-Aspartate/metabolism* ; Nitric Oxide Synthase Type II/metabolism* ; Mice, Inbred ICR ; Microglia/pathology* ; Spinal Cord/drug effects* ; Female ; Mice ; Tumor Necrosis Factor-alpha/metabolism* ; Disease Models, Animal ; Constriction, Pathologic/complications* ; Interleukin-6/metabolism* ; Astrocytes/metabolism* ; Chronic Disease ; Neurons/metabolism*

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

BACKGROUND: There is a gap in understanding the effects of different acupoints and treatment methods (acupuncture and moxibustion) on microcirculatory changes in the lumbar region. OBJECTIVE: This study aimed to assess the thermal effects of acupuncture at Weizhong (BL40), with acupuncture at Chize (LU5) and moxibustion at both acupoints as control interventions. DESIGN, SETTING, PARTICIPANTS AND INTERVENTIONS: In this randomized controlled trial, 140 healthy participants were equally divided into four groups: acupuncture at BL40 (Acu-BL40), acupuncture at LU5 (Acu-LU5), moxibustion at BL40 (Mox-BL40) and moxibustion at LU5 (Mox-LU5). Participants underwent a 30-minute session of their assigned treatment. Infrared thermal imaging was used to collect temperature data on the areas of interest for analysis. MAIN OUTCOME MEASURES: The primary measure was the change in average temperature of the observed area after the intervention. The secondary measures included periodic temperature changes every 5 min and the temperature changes of the Governor Vessel and Bladder Meridian in the observed area after the intervention. RESULTS: Significant interactions were observed between treatments and acupoints affecting temperature (P < 0.001). The Acu-BL40 group showed a notably higher increase in mean temperature after 30 min compared to the Acu-LU5 and Mox-BL40 groups, with increases of 0.29 (95% confidence interval [CI] = 0.17 to 0.41) and 0.24 (95% CI = 0.08 to 0.41) °C, respectively. CONCLUSION: Acupuncture at BL40 acupoint can significantly increase the mean temperature in the observed area, highlighting the specific thermal effect of acupuncture compared to moxibustion in the lumbar area. This suggests a potential therapeutic benefit of acupuncture at BL40 for managing lumbar conditions. TRIAL REGISTRATION ClinicalTrials.gov (NCT05665426). Please cite this article as: Zheng SY, Wang XY, Lin LN, Liu S, Huang XX, Liu YY, Yu XS, Pan W, Fang JQ, Liang Y. Lumbar temperature change after acupuncture or moxibustion at Weizhong (BL40) or Chize (LU5) in healthy adults: A randomized controlled trial. J Integr Med. 2025; 23(2): 145-151.
Adult ; Female ; Humans ; Male ; Young Adult ; Acupuncture Points ; Acupuncture Therapy ; Body Temperature ; Healthy Volunteers ; Lumbosacral Region/physiology* ; Moxibustion ; Adolescent

Objective:To investigate the incidence of postoperative complications in Chinese patients with gastric or colorectal cancer, and to evaluate the risk factors for postoperative complications.Methods:This was a national, multicenter, prospective, registry-based, cohort study of data obtained from the database of the Prevalence of Abdominal Complications After Gastro- enterological Surgery (PACAGE) study sponsored by the China Gastrointestinal Cancer Surgical Union. The PACAGE database prospectively collected general demographic characteristics, protocols for perioperative treatment, and variables associated with postoperative complications in patients treated for gastric or colorectal cancer in 20 medical centers from December 2018 to December 2020. The patients were grouped according to the presence or absence of postoperative complications. Postoperative complications were categorized and graded in accordance with the expert consensus on postoperative complications in gastrointestinal oncology surgery and Clavien-Dindo grading criteria. The incidence of postoperative complications of different grades are presented as bar charts. Independent risk factors for occurrence of postoperative complications were identified by multifactorial unconditional logistic regression.Results:The study cohort comprised 3926 patients with gastric or colorectal cancer, 657 (16.7%) of whom had a total of 876 postoperative complications. Serious complications (Grade III and above) occurred in 4.0% of patients (156/3926). The rate of Grade V complications was 0.2% (7/3926). The cohort included 2271 patients with gastric cancer with a postoperative complication rate of 18.1% (412/2271) and serious complication rate of 4.7% (106/2271); and 1655 with colorectal cancer, with a postoperative complication rate of 14.8% (245/1655) and serious complication rate of 3.0% (50/1655). The incidences of anastomotic leakage in patients with gastric and colorectal cancer were 3.3% (74/2271) and 3.4% (56/1655), respectively. Abdominal infection was the most frequently occurring complication, accounting for 28.7% (164/572) and 39.5% (120/304) of postoperative complications in patients with gastric and colorectal cancer, respectively. The most frequently occurring grade of postoperative complication was Grade II, accounting for 65.4% (374/572) and 56.6% (172/304) of complications in patients with gastric and colorectal cancers, respectively. Multifactorial analysis identified (1) the following independent risk factors for postoperative complications in patients in the gastric cancer group: preoperative comorbidities (OR=2.54, 95%CI: 1.51-4.28, P<0.001), neoadjuvant therapy (OR=1.42, 95%CI:1.06-1.89, P=0.020), high American Society of Anesthesiologists (ASA) scores (ASA score 2 points:OR=1.60, 95% CI: 1.23-2.07, P<0.001, ASA score ≥3 points:OR=0.43, 95% CI: 0.25-0.73, P=0.002), operative time >180 minutes (OR=1.81, 95% CI: 1.42-2.31, P<0.001), intraoperative bleeding >50 mL (OR=1.29,95%CI: 1.01-1.63, P=0.038), and distal gastrectomy compared with total gastrectomy (OR=0.65,95%CI: 0.51-0.83, P<0.001); and (2) the following independent risk factors for postoperative complications in patients in the colorectal cancer group: female (OR=0.60, 95%CI: 0.44-0.80, P<0.001), preoperative comorbidities (OR=2.73, 95%CI: 1.25-5.99, P=0.030), neoadjuvant therapy (OR=1.83, 95%CI:1.23-2.72, P=0.008), laparoscopic surgery (OR=0.47, 95%CI: 0.30-0.72, P=0.022), and abdominoperineal resection compared with low anterior resection (OR=2.74, 95%CI: 1.71-4.41, P<0.001). Conclusion:Postoperative complications associated with various types of infection were the most frequent complications in patients with gastric or colorectal cancer. Although the risk factors for postoperative complications differed between patients with gastric cancer and those with colorectal cancer, the presence of preoperative comorbidities, administration of neoadjuvant therapy, and extent of surgical resection, were the commonest factors associated with postoperative complications in patients of both categories.

Objective:To examine the impact of varied surgical treatment strategies on the prognosis of patients with initial resectable gastric cancer liver metastases (IR-GCLM).Methods:This is a retrospective cohort study. Employing a retrospective cohort design, the study selected clinicopathological data from the national multi-center retrospective cohort study database, focusing on 282 patients with IR-GCLM who underwent surgical intervention between January 2010 and December 2019. There were 231 males and 51 males, aging ( M(IQR)) 61 (14) years (range: 27 to 80 years). These patients were stratified into radical and palliative treatment groups based on treatment decisions. Survival curves were generated using the Kaplan-Meier method and distinctions in survival rates were assessed using the Log-rank test. The Cox risk regression model evaluated HR for various factors, controlling for confounders through multivariate analysis to comprehensively evaluate the influence of surgery on the prognosis of IR-GCLM patients. A restricted cubic spline Cox proportional hazard model assessed and delineated intricate associations between measured variables and prognosis. At the same time, the X-tile served as an auxiliary tool to identify critical thresholds in the survival analysis for IR-GCLM patients. Subgroup analysis was then conducted to identify potential beneficiary populations in different surgical treatments. Results:(1) The radical group comprised 118 patients, all undergoing R0 resection or local physical therapy of primary and metastatic lesions. The palliative group comprised 164 patients, with 52 cases undergoing palliative resections for gastric primary tumors and liver metastases, 56 cases undergoing radical resections for gastric primary tumors only, 45 cases undergoing palliative resections for gastric primary tumors, and 11 cases receiving palliative treatments for liver metastases. A statistically significant distinction was observed between the groups regarding the site and the number of liver metastases (both P<0.05). (2) The median overall survival (OS) of the 282 patients was 22.7 months (95% CI: 17.8 to 27.6 months), with 1-year and 3-year OS rates were 65.4% and 35.6%, respectively. The 1-year OS rates for patients in the radical surgical group and palliative surgical group were 68.3% and 63.1%, while the corresponding 3-year OS rates were 42.2% and 29.9%, respectively. A comparison of OS between the two groups showed no statistically significant difference ( P=0.254). Further analysis indicated that patients undergoing palliative gastric cancer resection alone had a significantly worse prognosis compared to other surgical options ( HR=1.98, 95% CI: 1.21 to 3.24, P=0.006). (3) The size of the primary gastric tumor significantly influenced the patients′ prognosis ( HR=2.01, 95% CI: 1.45 to 2.79, P<0.01), with HR showing a progressively increasing trend as tumor size increased. (4) Subgroup analysis indicates that radical treatment may be more effective compared to palliative treatment in the following specific cases: well/moderately differentiated tumors ( HR=2.84, 95% CI 1.49 to 5.41, P=0.001), and patients with liver metastases located in the left lobe of the liver ( HR=2.06, 95% CI 1.19 to 3.57, P=0.010). Conclusions:In patients with IR-GCLM, radical surgery did not produce a significant improvement in the overall prognosis compared to palliative surgery. However, within specific patient subgroups (well/moderately differentiated tumors, and patients with liver metastases located in the left lobe of the liver), radical treatment can significantly improve prognosis compared to palliative approaches.

Objective To explore the treatment for endometriosis(EMs)by Professor SITU Yi,a Guangdong famous traditional Chinese medicine physician,thus to provide reference for the diagnosis and treatment of EMs in traditional Chinese medicine based on personalized knowledge graph analysis and data mining technology.Methods Based on the literature research achievements of diagnosis and treatment of EMs,the ontology knowledge tree of famous physician's principles,methods,prescriptions and medicines was established by user-computer integration method.The medical records of EMs patients treated by Professor SITU Yi in the outpatient department of Guangdong Provincial Hospital of Chinese Medicine from 2013 to 2019 were collected.After standardization of the data of medical records,the knowledge set was defined,the knowledge map of TCM diagnosis and treatment of EMs was constructed,and the symptom characteristics and medication rules for EMs were analyzed.Results The core symptoms of EMs patients were dysmenorrhea,chronic pelvic pain and infertility,with the predominated syndrome of blood stasis.The pathogenesis of EMs patients was mainly due to qi stagnation,kidney deficiency,and qi deficiency.Frequent itemset analysis yielded the core drug groups of"Corydalis Rhizoma,Cyperi Rhizoma,Paeoniae Radix Alba""Lycii Fructus,Taxilli Herba,Poria,Dioscoreae Rhizoma"and"Aurantii Fructus,Leonuri Herba".The EMs word cloud map constructed on the basis of knowledge element clustering and neural network algorithm showed that the drug combinations of"Salviae Miltiorrhizae Radix et Rhizoma,Paeoniae Radix Rubra""Corydalis Rhizoma,Curcumae Radix""Cinnamomi Ramulus,Moutan Cortex,Paeoniae Radix Rubra,Poria""Salviae Miltiorrhizae Radix et Rhizoma,Paeoniae Radix Rubra,Sparganii Rhizoma,Curcumae Rhizoma""Chuanxiong Rhizoma,Corydalis Rhizoma"and"Taxilli Herba,Cuscutae Semen"were commonly used for the treatment of EMs by Professor SITU Yi.The results of hierarchical clustering analysis and association network construction for Chinese medicinals,symptoms and syndromes showed that there were complex inner link among the syndromes,symptoms and medication.Conclusion For the treatment of EMs,Professor SITU Yi usually adopt the methods of activating blood to remove stasis and tonifying kidney,and also performs the periodic therapy and simultaneous application of purging and nourishing therapeutics.Knowledge graph analysis and data mining based on semantic web are helpful to unveil the tacit knowledge of clinical diagnosis and treatment experience of Professor SITU Yi,which can provide reference for the differentiation and treatment of EMs with Chinese medicine.

The experience of professor YANG Wen-Hui in treating lumbago disease with YANG's Baliao-acupoints moxibustion is introduced in this paper.YANG Wen-Hui believes that the basic pathogenesis of lumbago disease is'cold causes lower back pain',and based on the philosophical idea of'harmony in Shushu(the ways to cultivate health)',he proposes'YANG's Baliao-acupoints moxibustion'for the treatment of lumbago disease.According to the patient's condition,professor YANG used the acupoints of Shangliao(BL31),Ciliao(BL32),Zhongliao(BL33),and selected the moxa cone like jujube core,soybean or wheat grain,and applied moxibustion with the technique of'San Yang Kai Tai'or'Ruo feng Chui Yun',the number of moxibustion is proportional to the age of the patient.YANG's Baliao-acupoints moxibustion in treating lumbago disease exerts highly and remarkable clinical efficacy,and it was widely acclaimed by the patients.