ObjectiveTo explore the therapeutic effect of Xuebijing injection （XBJ） on severe acute pancreatitis induced acute lung injury （SAP-ALI） by regulating formyl peptide receptors （FPRs）/nucleotide-binding oligomerization domain-like receptor 3 （NLRP3） inflammatory pathway. MethodsSixty rats were randomly divided into a sham group， a SAP-ALI model group， low-， medium-， and high-dose XBJ groups （4， 8， and 12 mL·kg^-1）， and a positive drug （BOC2， 0.2 mg·kg^-1） group. For the sham group， the pancreas of rats was only gently flipped after laparotomy， and then the abdomen was closed， while for the remaining five groups， SAP-ALI rat models were established by retrograde injection of 5% sodium taurocholate （Na-Tc） via the biliopancreatic duct. XBJ and BOC2 were administered via intraperitoneal injection once daily for 3 d prior to modeling and 0.5 h after modeling. Blood was collected from the abdominal aorta 6 h after the completion of modeling， and the expression of interleukin （IL）-1β， IL-6， and tumor necrosis factor-α （TNF-α） in plasma was measured by enzyme-linked immunosorbent assay （ELISA）. The amount of ascites was measured， and the dry-wet weight ratios of pancreatic and lung tissue were determined. Pancreatic and lung tissue was taken for hematoxylin-eosin （HE） staining to observe pathological changes and then scored. The protein expression levels of FPR1， FPR2， and NLRP3 in lung tissue were detected by the immunohistochemical method. Western blot was used to detect the expression of FPR1， FPR2， and NLRP3 in lung tissue. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of FPR1， FPR2， and NLRP3 in lung tissue. ResultsCompared with the sham group， the SAP-ALI model group showed significantly decreased dry-wet weight ratio of lung tissue （P<0.01）， serious pathological changes of lung tissue， a significantly increased pathological score （P<0.01）， and significantly increased protein and mRNA expression levels of FPR1， FPR2， and NLRP3 in lung tissue （P<0.01）. After BOC2 intervention， the above detection indicators were significantly reversed （P<0.01）. After treatment with XBJ， the groups of different XBJ doses achieved results consistent with BOC2 intervention. ConclusionXBJ can effectively improve the inflammatory response of the lungs in SAP-ALI rats and reduce damage. The mechanism may be related to inhibiting the expression of FPRs and NLRP3 in lung tissue， which thereby reduces IL-1β and simultaneously antagonize the release of inflammatory factors IL-6 and TNF-α.

ObjectiveTo study the pharmacological substances and mechanisms through which sesquiterpene ZH-13 from Aquilariae Lignum Resinatum improves neuroinflammation. MethodsBV-2 microglial cells were stimulated with lipopolysaccharide （LPS） to induce neuroinflammation. The cells were divided into the normal group， the model group， and the ZH-13 low- and high-dose treatment groups （10， 20 μmol·L^-1）. The model group was treated with 1 μmol·L^-1 LPS. Cell viability was assessed using the cell proliferation and activity assay （CCK-8 kit）. Nitric oxide （NO） release in the cell supernatant was measured using a nitric oxide kit （Griess method）. The mRNA expression levels of interleukin-1β （IL-1β）， tumor necrosis factor-α （TNF-α）， inducible nitric oxide synthase （iNOS）， and interleukin-6 （IL-6） were detected by real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）. The phosphorylation of mitogen-activated protein kinase （MAPK） pathway proteins was assessed by Western blot. ResultsCompared with the model group， ZH-13 dose-dependently reduced NO release from BV-2 cells under LPS stimulation （P<0.05， P<0.01）. In the 20 μmol·L^-1 ZH-13 treatment group， the mRNA expression levels of IL-1β， TNF-α， iNOS， and IL-6 were significantly reduced compared to the model group （P<0.05， P<0.01）. In both the low- and high-dose ZH-13 groups， the expression of the inflammatory factor TNF-α and the phosphorylation of c-Jun N-terminal kinase （JNK） in the upstream MAPK pathway were significantly reduced （P<0.05）. After stimulation with the JNK agonist anisomycin （Ani）， both low- and high-dose ZH-13 treatment groups showed reduced phosphorylation of JNK proteins compared to the Ani-treated group （P<0.01）. ConclusionThe sesquiterpene compound ZH-13 from Aquilariae Lignum Resinatum significantly ameliorates LPS-induced neuroinflammatory responses in BV-2 cells by inhibiting excessive JNK phosphorylation and reducing TNF-α expression. These findings elucidate the pharmacological substances and mechanisms underlying the sedative and calming effects of Aquilariae Lignum Resinatum.

AIM: To explore the diagnostic value of 18 MHz color Doppler ultrasonography for epiretinal membrane.METHODS: A total of 44 cases(80 eyes)of patients with proposed diagnosis of cataract and vitreous opacity by fundus examination in our hospital between January 2020 and January 2022 were collected, and the affected eyes were examined by optical coherence tomography(OCT)and 18 MHz color Doppler ultrasonography, and the differences in the diagnostic sensitivity, specificity, and accuracy were compared between 18 MHz color Doppler ultrasonography and OCT for the diagnosis of epiretinal membrane.RESULTS: In the 80 eyes detected by 18 MHz color Doppler ultrasonography, 62 had epiretinal membrane and 18 had non epiretinal membrane. Totally 54 eyes were confirmed to have epiretinal membrane by OCT, 13 eyes were not diagnosed with epiretinal membrane, 5 eyes were missed diagnosis, and 8 eyes were misdiagnosed. The diagnostic consistency between 18 MHz color Doppler ultrasonography and OCT was high(Kappa=0.892, P<0.05); the 18 MHz color Doppler ultrasonography detection sensitivity of epiretinal membrane was 92%, specificity was 62%, missed diagnosis rate was 8%, misdiagnosis rate was 38%, and accuracy was 84%; compared with OCT detection, 18 MHz color Doppler ultrasonography detected a lower specificity, correct rate, positive prediction accuracy, negative prediction accuracy, and higher misdiagnosis rate(all P<0.05), and the difference in diagnostic sensitivity compared with leakage rate was not statistically significant(all P>0.05).CONCLUSION: 18 MHz color Doppler ultrasonography has some value in identifying epiretinal membrane lesions and is consistent with OCT testing.

Houpo Qiwutang originated from the Synopsis of the Golden Chamber， and it consists of seven medicines： Magnoliae Officinalis Cortex， Rhei Radix et Rhizoma， Aurantii Fructus Immaturus， Cinnamomi Ramulus， Zingiberis Rhizoma Recens， Glycyrrhizae Radix et Rhizoma， and Jujubae Fructus. It is a basic formula for the treatment of abdominal fullness. Through the bibliometric method， the historical history， drug base， preparation and dosage， decoction method， and ancient and modern applications of Houpu Qiwu Tang were analyzed by means of textual research. The research finds that Houpu Qiwu Tang has been passed down through the generations in an orderly manner with fewer changes. The drug base of this formula is basically clear， and the base of Magnoliae Officinalis Cortex， Rhei Radix et Rhizoma， Cinnamomi Ramulus， Zingiberis Rhizoma Recens， and Jujubae Fructus is consistent with the 2020 edition of Chinese Pharmacopoeia. The mainstream base of Aurantii Fructus Immaturus is the dried young fruit of Citrus aurantium of Rutaceae family， and the historical mainstream base of Glycyrrhizae Radix et Rhizoma is the dried root of Glycyrrhiza uralensis of Leguminosae family. The modern dosage of this formula is 110.40 g of Magnoliae Officinalis Cortex， 41.40 g of Rhei Radix et Rhizoma， 69 g of Aurantii Fructus Immaturus， 27.60 g of Cinnamomi Ramulus， 69 g of Zingiberis Rhizoma Recens， 41.40 g of Glycyrrhizae Radix et Rhizoma， and 30 g of Jujubae Fructus. In addition， the decoction method is to add 2 000 mL of water with the above seven flavors of the medicine， boil it to 800 mL， and then take 160 mL in a warm state each time. The amount of the medicine taken for each time is 22.08 g of Magnoliae Officinalis Cortex， 8.28 g of Rhei Radix et Rhizoma， 13.80 g of Aurantii Fructus Immaturus， 5.52 g of Cinnamomi Ramulus， 13.80 g of Zingiberis Rhizoma Recens， 8.28 g of Glycyrrhizae Radix et Rhizoma， and 6 g of Jujubae Fructus. The modern application of this formula involves the digestive system， respiratory system， and urinary system. It is more advantageous in digestive system diseases such as early postoperative inflammatory bowel obstruction， functional dyspepsia， gastric pain， functional abdominal distension， and gastric reflux esophagitis. By comprehensively examining the key information of Houpu Qiwu Tang， this paper aims to provide literature support for the development and clinical application of this formula.

As biological sample biobanks progressively demonstrate their significant value in the field of biomedical research， they also pose challenges to existing social norms and ethical rules， making the normative issue of informed consent of participants highly concerned. The current research has insufficient exploration of informed consent in the collection， preservation， utilization， and other links of the sample. In response to the complexity and diversity of each link， it is advocated to refine informed consent strategies to ensure comprehensive protection of participants’ rights and interests. Given the continuity and dynamism of informed consent， it is recommended to establish a flexible review mechanism to address changes in research content， increased risks， and changes in participant capabilities， ensuring the ethical legitimacy of the research and the autonomy in making decisions of participants. Meanwhile， it is emphasized to fully confirm informed consent before sample entry into the bank， adopt suitable consent forms for outbound utilization and waste disposal， and pay special attention to ethical and legal issues related to human genetic resources.

Objective: To explore the causal association between dietary components (carbohydrate, fat, protein, and sugar) and 119 genera of known gut microbiota using Mendelian randomization (MR) methods. Methods: Genome-wide association study (GWAS) data for dietary components were collected from the DietGen, while GWAS data for gut microbiota were collected from the MiBioGen. Single nucleotide polymorphism (SNP) loci associated with the four dietary components were used as instrumental variables, and 119 known gut microbiota genera were used as the outcomes. MR analysis was performed using inverse variance weighted (IVW) method. Heterogeneity was evaluated using Cochran's Q test, horizontal pleiotropy and exclude outliers were tested using MR-Egger regression and MR-PRESSO test. Common genetic pleiotropic genes between dietary components and gut microbiota were identified by MAGMA and PLACO analyses. Results: The MR analysis revealed causal associations between carbohydrates and 4 gut microbiota genera, fats and 14 genera, proteins and 14 genera, and sugars and 11 genera (all P<0.05). The MR-Egger regression analysis showed no horizontal pleiotropy among the selected SNPs, and the MR-PRESSO test did not identify any outliers (all P>0.05). The MAGMA and PLACO analyses revealed that 74.42% (32/43) of the causal associations had pleiotropic genes, with 1 to 10 pleiotropic genes identified. Multiple causal association groups shared the same pleiotropic genes. Conclusion There are potential genetic and causal associations between dietary components and gut microbiota.

The innate immune system can be boosted in response to subsequent triggers by pre-exposure to microbes or microbial products, known as “trained immunity”. Compared to classical immune memory, innate trained immunity has several different features. Firstly, the molecules involved in trained immunity differ from those involved in classical immune memory. Innate trained immunity mainly involves innate immune cells (e.g., myeloid immune cells, natural killer cells, innate lymphoid cells) and their effector molecules (e.g., pattern recognition receptor (PRR), various cytokines), as well as some kinds of non-immune cells (e.g., microglial cells). Secondly, the increased responsiveness to secondary stimuli during innate trained immunity is not specific to a particular pathogen, but influences epigenetic reprogramming in the cell through signaling pathways, leading to the sustained changes in genes transcriptional process, which ultimately affects cellular physiology without permanent genetic changes (e.g., mutations or recombination). Finally, innate trained immunity relies on an altered functional state of innate immune cells that could persist for weeks to months after initial stimulus removal. An appropriate inducer could induce trained immunity in innate lymphocytes, such as exogenous stimulants (including vaccines) and endogenous stimulants, which was firstly discovered in bone marrow derived immune cells. However, mature bone marrow derived immune cells are short-lived cells, that may not be able to transmit memory phenotypes to their offspring and provide long-term protection. Therefore, trained immunity is more likely to be relied on long-lived cells, such as epithelial stem cells, mesenchymal stromal cells and non-immune cells such as fibroblasts. Epigenetic reprogramming is one of the key molecular mechanisms that induces trained immunity, including DNA modifications, non-coding RNAs, histone modifications and chromatin remodeling. In addition to epigenetic reprogramming, different cellular metabolic pathways are involved in the regulation of innate trained immunity, including aerobic glycolysis, glutamine catabolism, cholesterol metabolism and fatty acid synthesis, through a series of intracellular cascade responses triggered by the recognition of PRR specific ligands. In the view of evolutionary, trained immunity is beneficial in enhancing protection against secondary infections with an induction in the evolutionary protective process against infections. Therefore, innate trained immunity plays an important role in therapy against diseases such as tumors and infections, which has signature therapeutic effects in these diseases. In organ transplantation, trained immunity has been associated with acute rejection, which prolongs the survival of allografts. However, trained immunity is not always protective but pathological in some cases, and dysregulated trained immunity contributes to the development of inflammatory and autoimmune diseases. Trained immunity provides a novel form of immune memory, but when inappropriately activated, may lead to an attack on tissues, causing autoinflammation. In autoimmune diseases such as rheumatoid arthritis and atherosclerosis, trained immunity may lead to enhance inflammation and tissue lesion in diseased regions. In Alzheimer’s disease and Parkinson’s disease, trained immunity may lead to over-activation of microglial cells, triggering neuroinflammation even nerve injury. This paper summarizes the basis and mechanisms of innate trained immunity, including the different cell types involved, the impacts on diseases and the effects as a therapeutic strategy to provide novel ideas for different diseases.

Obstructive sleep apnea (OSA) is an increasingly widespread sleep-breathing disordered disease, and is an independent risk factor for many high-risk chronic diseases such as hypertension, coronary heart disease, stroke, arrhythmias and diabetes, which is potentially fatal. The key to the prevention and treatment of OSA is early diagnosis and treatment, so the assessment and diagnostic technologies of OSA have become a research hotspot. This paper reviews the research progresses of severity assessment parameters and diagnostic technologies of OSA, and discusses their future development trends. In terms of severity assessment parameters of OSA, apnea hypopnea index (AHI), as the gold standard, together with the percentage of duration of apnea hypopnea (AH%), lowest oxygen saturation (LSpO₂), heart rate variability (HRV), oxygen desaturation index (ODI) and the emerging biomarkers, constitute a multi-dimensional evaluation system. Specifically, the AHI, which measures the frequency of sleep respiratory events per hour, does not fully reflect the patients’ overall sleep quality or the extent of their daytime functional impairments. To address this limitation, the AH%, which measures the proportion of the entire sleep cycle affected by apneas and hypopneas, deepens our understanding of the impact on sleep quality. The LSpO₂ plays a critical role in highlighting the potential severe hypoxic episodes during sleep, while the HRV offers a different perspective by analyzing the fluctuations in heart rate thereby revealing the activity of the autonomic nervous system. The ODI provides a direct and objective measure of patients’ nocturnal oxygenation stability by calculating the number of desaturation events per hour, and the biomarkers offers novel insights into the diagnosis and management of OSA, and fosters the development of more precise and tailored OSA therapeutic strategies. In terms of diagnostic techniques of OSA, the standardized questionnaire and Epworth sleepiness scale (ESS) is a simple and effective method for preliminary screening of OSA, and the polysomnography (PSG) which is based on recording multiple physiological signals stands for gold standard, but it has limitations of complex operations, high costs and inconvenience. As a convenient alternative, the home sleep apnea testing (HSAT) allows patients to monitor their sleep with simplified equipment in the comfort of their own homes, and the cardiopulmonary coupling (CPC) offers a minimal version that simply analyzes the electrocardiogram (ECG) signals. As an emerging diagnostic technology of OSA, machine learning (ML) and artificial intelligence (AI) adeptly pinpoint respiratory incidents and expose delicate physiological changes, thus casting new light on the diagnostic approach to OSA. In addition, imaging examination utilizes detailed visual representations of the airway’s structure and assists in recognizing structural abnormalities that may result in obstructed airways, while sound monitoring technology records and analyzes snoring and breathing sounds to detect the condition subtly, and thus further expands our medical diagnostic toolkit. As for the future development directions, it can be predicted that interdisciplinary integrated researches, the construction of personalized diagnosis and treatment models, and the popularization of high-tech in clinical applications will become the development trends in the field of OSA evaluation and diagnosis.

ObjectiveAutism spectrum disorder (ASD) is a neurodevelopmental condition characterized by difficulties with communication and social interaction, restricted and repetitive behaviors. Previous studies have indicated that individuals with ASD exhibit early and lifelong attention deficits, which are closely related to the core symptoms of ASD. Basic visual attention processes may provide a critical foundation for their social communication and interaction abilities. Therefore, this study explores the behavior of children with ASD in capturing attention to changes in topological properties. MethodsOur study recruited twenty-seven ASD children diagnosed by professional clinicians according to DSM-5 and twenty-eight typically developing (TD) age-matched controls. In an attention capture task, we recorded the saccadic behaviors of children with ASD and TD in response to topological change (TC) and non-topological change (nTC) stimuli. Saccadic reaction time (SRT), visual search time (VS), and first fixation dwell time (FFDT) were used as indicators of attentional bias. Pearson correlation tests between the clinical assessment scales and attentional bias were conducted. ResultsThis study found that TD children had significantly faster SRT (P<0.05) and VS (P<0.05) for the TC stimuli compared to the nTC stimuli, while the children with ASD did not exhibit significant differences in either measure (P>0.05). Additionally, ASD children demonstrated significantly less attention towards the TC targets (measured by FFDT), in comparison to TD children (P<0.05). Furthermore, ASD children exhibited a significant negative linear correlation between their attentional bias (measured by VS) and their scores on the compulsive subscale (P<0.05). ConclusionThe results suggest that children with ASD have difficulty shifting their attention to objects with topological changes during change detection. This atypical attention may affect the child’s cognitive and behavioral development, thereby impacting their social communication and interaction. In sum, our findings indicate that difficulties in attentional capture by TC may be a key feature of ASD.

Objective By combining biological detection and imaging evaluation, a clinical prediction model is constructed based on a large cohort to improve the accuracy of distinguishing between benign and malignant pulmonary nodules. Methods A retrospective analysis was conducted on the clinical data of the 32 627 patients with pulmonary nodules who underwent chest CT and testing for 7 types of lung cancer-related serum autoantibodies (7-AABs) at our hospital from January 2020 to April 2024. The univariate and multivariate logistic regression models were performed to screen independent risk factors for benign and malignant pulmonary nodules, based on which a nomogram model was established. The performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results A total of 1 017 patients with pulmonary nodules were included in the study. The training set consisted of 712 patients, including 291 males and 421 females, with a mean age of (58±12) years. The validation set included 305 patients, comprising 129 males and 176 females, with a mean age of (58±13) years. Univariate ROC curve analysis indicated that the combination of CT and 7-AABs testing achieved the highest area under the curve (AUC) value (0.794), surpassing the diagnostic efficacy of CT alone (AUC=0.667) or 7-AABs alone (AUC=0.514). Multivariate logistic regression analysis showed that radiological nodule diameter, nodule nature, and CT combined with 7-AABs detection were independent predictors, which were used to construct a nomogram prediction model. The AUC values for this model were 0.826 and 0.862 in the training and validation sets, respectively, demonstrating excellent performance in DCA. Conclusion The combination of 7-AABs with CT significantly enhances the accuracy of distinguishing between benign and malignant pulmonary nodules. The developed predictive model provides strong support for clinical decision-making and contributes to achieving precise diagnosis and treatment of pulmonary nodules.