Chronic pain is a complex condition shaped by long-standing alterations in both physiological and psychological processes. Rather than representing a simple continuation of acute nociceptive signaling, chronic pain is increasingly understood as the outcome of progressive dysregulation within distributed neural systems that govern sensation, affect, motivation, and cognitive control. Neuroimaging and electrophysiological studies indicate that this state is accompanied by extensive plastic changes in deep brain structures and large-scale networks. Beyond well-described central sensitization processes, chronic pain is characterized by disrupted oscillatory rhythms and altered connectivity within large-scale brain networks, including thalamo-cortical circuits and prefrontal-limbic-reward networks. These findings support a conceptual shift from viewing chronic pain as a focal, lesion-driven phenomenon toward recognizing it as a disorder of distributed network pathology. Pharmacological treatments remain central to clinical practice, yet their long-term efficacy is often limited and frequently accompanied by substantial side effects. The ongoing concerns about opioid-related risks and the inadequate therapeutic response in a subset of patients highlight the need for safe, non-pharmacological approaches that can address not only pain but also comorbid disturbances in mood, sleep, and social functioning. Neuromodulation provides a promising path toward mechanism-based and non-pharmacological management of chronic pain by employing physical or chemical stimulation to alter the excitability and synchrony of specific neural populations within central, peripheral, and autonomic systems. While invasive deep brain stimulation demonstrates that targeting deep brain structures can be effective, its clinical application is restricted by surgical risks and cost, highlighting the importance of non-invasive techniques capable of reaching deep targets. Current non-invasive approaches, such as transcranial electric stimulation, are constrained by limited penetration depth and insufficient spatial precision. These limitations hinder reliable engagement of deep regions implicated in pain, including the thalamus and nucleus accumbens, and tend to produce broad, non-specific modulation of cross-network oscillatory activity. Temporal interference (TI) stimulation has emerged as a means of overcoming these obstacles. By delivering interacting high-frequency currents that generate a low-frequency envelope within the head, TI enables focal stimulation of deep targets while minimizing superficial current delivery. Recent multiscale modeling and animal studies indicate that TI exploits the nonlinear rectification properties of neuronal membranes in response to high-frequency carriers, as well as their phase-locked responses to low-frequency envelopes, to generate “peak-focused” electric fields in deep regions under relatively low superficial current loads. Moreover, TI appears to exhibit potential advantages in terms of cell-type selectivity and rhythm-specific engagement, including differential responses across neuronal subtypes and distinct coupling to θ-, β-, and γ-band oscillations. These features suggest a promising avenue for correcting abnormal rhythms and network dynamics that contribute to chronic pain. This review summarizes current knowledge of the neural mechanisms underlying chronic pain and recent advances in TI research. It examines functional disturbances across key pain-related regions and networks, outlines the principles and technical characteristics of TI, and discusses potential deep-brain targets and stimulation strategies relevant to chronic pain. Evidence to date indicates that TI, with its non-invasiveness, tolerability, and capacity for precise deep brain modulation, holds great promise for the management of treatment-resistant chronic pain and may evolve into a new generation of precise and efficient non-pharmacological analgesic strategies.

Chronic pain is a complex condition shaped by long-standing alterations in both physiological and psychological processes. Rather than representing a simple continuation of acute nociceptive signaling, chronic pain is increasingly understood as the outcome of progressive dysregulation within distributed neural systems that govern sensation, affect, motivation, and cognitive control. Neuroimaging and electrophysiological studies indicate that this state is accompanied by extensive plastic changes in deep brain structures and large-scale networks. Beyond well-described central sensitization processes, chronic pain is characterized by disrupted oscillatory rhythms and altered connectivity within large-scale brain networks, including thalamo-cortical circuits and prefrontal-limbic-reward networks. These findings support a conceptual shift from viewing chronic pain as a focal, lesion-driven phenomenon toward recognizing it as a disorder of distributed network pathology. Pharmacological treatments remain central to clinical practice, yet their long-term efficacy is often limited and frequently accompanied by substantial side effects. The ongoing concerns about opioid-related risks and the inadequate therapeutic response in a subset of patients highlight the need for safe, non-pharmacological approaches that can address not only pain but also comorbid disturbances in mood, sleep, and social functioning. Neuromodulation provides a promising path toward mechanism-based and non-pharmacological management of chronic pain by employing physical or chemical stimulation to alter the excitability and synchrony of specific neural populations within central, peripheral, and autonomic systems. While invasive deep brain stimulation demonstrates that targeting deep brain structures can be effective, its clinical application is restricted by surgical risks and cost, highlighting the importance of non-invasive techniques capable of reaching deep targets. Current non-invasive approaches, such as transcranial electric stimulation, are constrained by limited penetration depth and insufficient spatial precision. These limitations hinder reliable engagement of deep regions implicated in pain, including the thalamus and nucleus accumbens, and tend to produce broad, non-specific modulation of cross-network oscillatory activity. Temporal interference (TI) stimulation has emerged as a means of overcoming these obstacles. By delivering interacting high-frequency currents that generate a low-frequency envelope within the head, TI enables focal stimulation of deep targets while minimizing superficial current delivery. Recent multiscale modeling and animal studies indicate that TI exploits the nonlinear rectification properties of neuronal membranes in response to high-frequency carriers, as well as their phase-locked responses to low-frequency envelopes, to generate “peak-focused” electric fields in deep regions under relatively low superficial current loads. Moreover, TI appears to exhibit potential advantages in terms of cell-type selectivity and rhythm-specific engagement, including differential responses across neuronal subtypes and distinct coupling to θ-, β-, and γ-band oscillations. These features suggest a promising avenue for correcting abnormal rhythms and network dynamics that contribute to chronic pain. This review summarizes current knowledge of the neural mechanisms underlying chronic pain and recent advances in TI research. It examines functional disturbances across key pain-related regions and networks, outlines the principles and technical characteristics of TI, and discusses potential deep-brain targets and stimulation strategies relevant to chronic pain. Evidence to date indicates that TI, with its non-invasiveness, tolerability, and capacity for precise deep brain modulation, holds great promise for the management of treatment-resistant chronic pain and may evolve into a new generation of precise and efficient non-pharmacological analgesic strategies.

ObjectiveThe widespread adoption of portable fundus cameras for primary care and community screening is hindered by limitations in current autofocus(AF) technologies. Image-based methods relying on sharpness evaluation require iterative searches, resulting in slow convergence, while projection-based techniques are susceptible to optical artifacts and calibration errors. To address these challenges, this study introduces a novel AF system based on direct wavefront sensing, designed to deliver simultaneous high speed, high precision, and operational robustness within the compact form factor essential for portable ophthalmic devices. MethodsOur approach fundamentally reimagines the AF process by directly measuring the ocular wavefront aberration. We developed a custom portable fundus camera integrating a miniaturized Shack-Hartmann wavefront sensor (SHWS) into the optical path. An 850 nm laser diode projects a point source onto the retina via oblique illumination to minimize corneal reflections. Light scattered from this spot carries the eye’s refractive error through the imaging optics and is directed to the SHWS, positioned at a plane optically conjugate to the primary color CMOS imaging sensor. A microlens array within the SHWS samples the incident wavefront, generating a pattern of focal spots on a CCD. Real-time centroid analysis of these spots provides a map of local wavefront slopes. These measurements are processed through a singular value decomposition (SVD) algorithm to fit a Zernike polynomial basis set, enabling real-time reconstruction of the wavefront phase. The defocus component (S) is extracted from the second-order Zernike coefficients, providing a direct, quantitative measure of the refractive error in diopters. This value serves as a precise error signal in a closed-loop control system, which commands a voice-coil actuated focusing lens to its null position in a single, deterministic step, eliminating the need for iterative search algorithms. ResultsComprehensive evaluation demonstrated the system’s high performance. Testing on a calibrated model eye (OEMI-7) established a highly linear relationship between the computed defocus S and the focusing lens position across a ±20 Diopter (D) compensation range, achievable within a 5 mm mechanical travel. The system achieved a focusing precision of 0.08 D, corresponding to an 18-fold improvement over a conventional projection spot-size method tested under identical conditions. The total focus acquisition time, encompassing wavefront measurement, computation, and lens actuation, averaged under 0.5 s. Clinical validation with 25 human volunteers (50 eyes, refractive range -15 D to +10 D) confirmed practical efficacy. The wavefront-sensing AF succeeded in 92% of attempts with a mean time of 0.5 s, substantially outperforming a projection-based benchmark which achieved only a 32% success rate with an average time of 4.25 s. The system provided instantaneous directional guidance and maintained stability during minor ocular movements. Objective assessment of image quality, via amplitude contrast of retinal vasculature, showed consistent and significant enhancement following AF correction across the entire tested diopter range. ConclusionThis work successfully implements and validates a direct wavefront-sensing autofocus paradigm for portable fundus cameras. By directly quantifying and compensating for the optical defocus aberration, this method bypasses the fundamental limitations of image-processing and projection-based techniques, enabling rapid, precise, and deterministic diopter compensation. The developed system delivers an exceptional combination of a wide operational range (±20 D), high accuracy (0.08 D), fast convergence (0.5 s), and a compact physical footprint. This technology provides a practical and high-performance focusing solution capable of enhancing the reliability, throughput, and diagnostic utility of portable retinal imaging in large-scale screening applications. Future efforts will be directed towards system cost optimization and performance adaptation for diverse ocular conditions.

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 explore a new model of intelligent medication education for pharmaceutical outpatient clinics by constructing dynamic HTML web pages through the DeepSeek-V3-0324 large-scale model. METHODS Clinical pharmacists integrated key clinical information such as patients’ basic information， medication history and medication precautions in real time， and generated a standardized medication education list through the DeepSeek-V3-0324 large-scale model and manual review. RESULTS The DeepSeek-V3-0324 large-scale model was applied in the pharmaceutical outpatient clinics to generate a personalized medication education list， which could effectively solve the disunity of pharmacy guidance caused by the lack of standardization of medication education and the difference of individualized experience of pharmacists in the traditional pharmaceutical outpatient clinics in the face of complex cases， and medication errors caused by forgetting or misremembering information among certain special patient populations after receiving medication education. CONCLUSIONS The transformation and application of artificial intelligence technology in pharmaceutical outpatient clinics is an innovation of pharmaceutical outpatient service means， which can provide patients with immediate and personalized medication education and improve the quality of pharmaceutical care. However， it is also necessary to face the lag of database update and the lack of risk management， as well as the lack of diversification of medication education lists.

Sleep deprivation (SD) has emerged as a significant modifiable risk factor for Alzheimer’s disease (AD), with mounting evidence demonstrating its multifaceted role in accelerating AD pathogenesis through diverse molecular, cellular, and systemic mechanisms. SD is refined within the broader spectrum of sleep-wake and circadian disruption, emphasizing that both acute total sleep loss and chronic sleep restriction destabilize the homeostatic and circadian processes governing glymphatic clearance of neurotoxic proteins. During normal sleep, concentrations of interstitial Aβ and tau fall as cerebrospinal fluid oscillations flush extracellular waste; SD abolishes this rhythm, causing overnight rises in soluble Aβ and tau species in rodent hippocampus and human CSF. Orexinergic neurons sustain arousal, and become hyperactive under SD, further delaying sleep onset and amplifying Aβ production. At the molecular level, SD disrupts Aβ homeostasis through multiple converging pathways, including enhanced production via beta-site APP cleaving enzyme 1 (BACE1) upregulation, coupled with impaired clearance mechanisms involving the glymphatic system dysfunction and reduced Aβ-degrading enzymes (neprilysin and insulin-degrading enzyme). Cellular and histological analyses revealed that these proteinopathies are significantly exacerbated by SD-induced neuroinflammatory cascades characterized by microglial overactivation, astrocyte reactivity, and sustained elevation of pro-inflammatory cytokines (IL-1β, TNF-α, IL-6) through NF‑κB signaling and NLRP3 inflammasome activation, creating a self-perpetuating cycle of neurotoxicity. The synaptic and neuronal consequences of chronic SD are particularly profound and potentially irreversible, featuring reduced expression of critical synaptic markers (PSD95, synaptophysin), impaired long-term potentiation (LTP), dendritic spine loss, and diminished neurotrophic support, especially brain-derived neurotrophic factor (BDNF) depletion, which collectively contribute to progressive cognitive decline and memory deficits. Mechanistic investigations identify three core pathways through which SD exerts its neurodegenerative effects: circadian rhythm disruption via BMAL1 suppression, orexin system hyperactivity leading to sustained wakefulness and metabolic stress, and oxidative stress accumulation through mitochondrial dysfunction and reactive oxygen species overproduction. The review critically evaluates promising therapeutic interventions including pharmacological approaches (melatonin, dual orexin receptor antagonists), metabolic strategies (ketogenic diets, and Mediterranean diets rich in omega-3 fatty acids), lifestyle modifications (targeted exercise regimens, cognitive behavioral therapy for insomnia), and emerging technologies (non-invasive photobiomodulation, transcranial magnetic stimulation). Current research limitations include insufficient understanding of dose-response relationships between SD duration/intensity and AD pathology progression, lack of long-term longitudinal clinical data in genetically vulnerable populations (particularly APOE ε4 carriers and those with familial AD mutations), the absence of standardized SD protocols across experimental models that accurately mimic human chronic sleep restriction patterns, and limited investigation of sex differences in SD-induced AD risk. The accumulated evidence underscores the importance of addressing sleep disturbances as part of multimodal AD prevention strategies and highlights the urgent need for clinical trials evaluating sleep-focused interventions in at-risk populations. The review proposes future directions focused on translating mechanistic insights into precision medicine approaches, emphasizing the need for biomarkers to identify SD-vulnerable individuals, chronotherapeutic strategies aligned with circadian biology, and multi-omics integration across sleep, proteostasis and immune profiles may delineate precision-medicine strategies for at-risk populations. By systematically examining these critical connections, this analysis positions sleep quality optimization as a viable strategy for AD prevention and early intervention while providing a comprehensive roadmap for future mechanistic and interventional research in this rapidly evolving field.

A scoping review was performed to systematically search and summarize the clinical research in the treatment of dysmenorrhea with oral Chinese patent medicines. The oral Chinese patent medicines for treating dysmenorrhea in three major drug lists, guidelines, and textbooks were screened, and the relevant clinical trials were retrieved from eight Chinese and English databases. The key information of the included trials was extracted and visually analyzed. A total of 50 Chinese patent medicines were included, among which oral Chinese patent medicines for the dysmenorrhea patients with the syndrome of Qi stagnation and blood stasis accounted for the highest proportion, and the average daily cost varied greatly among Chinese patent medicines. A total of 150 articles were included, involving 22 Chinese patent medicines, among which Guizhi Fuling Capsules/Pills, Sanjie Zhentong Capsules, and Dan'e Fukang Soft Extract were the most frequently studied. These articles mainly reported randomized controlled trial(RCT), which mainly focused on the comparison of the intervention effect between Chinese patent medicines combined with western medicine and western medicine alone, and the sample size was generally 51-100 cases. The high-frequency outcome indicators belonged to nine domains such as effective rate, adverse reactions, and laboratory examinations. This study showed that oral Chinese patent medicines had advantages in the treatment of dysmenorrhea, and the annual number of related clinical trials showed an overall growing trend. However, there were still problems such as insufficient safety information and vague description of traditional Chinese medicine(TCM) syndromes types in the instructions of Chinese patent medicines. The available clinical research had shortcomings such as uneven distribution of Chinese patent medicines, limited research scale, poor methodological rigor, and insufficient standardization of outcome indicators. In the future, it is necessary to deepen the development of high-quality clinical research and improve the contents of the instructions to ensure the effectiveness and safety of the clinical application of oral Chinese patent medicines in the treatment of dysmenorrhea.
Dysmenorrhea/drug therapy* ; Humans ; Drugs, Chinese Herbal/administration & dosage* ; Female ; Administration, Oral ; Nonprescription Drugs/administration & dosage*

Yinyang Gongji Pills have the effects of strengthening the body resistance to eliminate pathogenic factors, removing stasis, and reducing swelling, which is a commonly used traditional Chinese medicine(TCM) formula for treating intestinal accumulation. A real-world, registered, and single-arm clinical trial was conducted to observe the clinical efficacy and safety of Yinyang Gongji Pills combined with capecitabine in the treatment of advanced colorectal cancer and analyze the clinical characteristics of the patients. A total of 60 patients with advanced colorectal cancer who refused or could not tolerate standard treatment of western medicine were included in the study. They were treated with Yinyang Gongji Pills combined with capecitabine until disease progression or intolerable adverse events occurred. The main observation indicators were progression-free survival(PFS) and safety. The treatment effects of the patients under different baseline characteristics were analyzed. The clinical trial has found that the median PFS of all enrolled patients was 7.3 months, with 30.1% of patients having a PFS exceeding 12.0 months. Layered analysis showed that the median PFS of patients with the onset site being the colon and rectum were respectively 8.4 and 4.7 months. The median PFS of patients with high, medium, and low tumor burden were respectively 7.0, 4.7, and 10.8 months. The median PFS of patients with wild-type and mutant-type RAS/BRAF were respectively 7.9 and 6.9 months. The median PFS of patients with KPS scores ≥80 and ≤70 were respectively 7.9 and 6.5 months. The median PFS of patients treated with Yinyang Gongji Pills for ≥6, 3-6, and ≤3 months were respectively 8.0, 5.2, and 4.2 months. The median PFS of patients with spleen, kidney, liver, and lung syndrome differentiation in TCM were respectively 8.3, 6.7, 7.3, and 5.6 months. The median PFS of patients with TCM pathological factors including phlegm, dampness, and blood stasis were respectively 7.0, 7.3, and 6.5 months. Common adverse reactions include anemia, decreased white blood cells, decreased appetite, fatigue, and hand foot syndrome, with incidence rates being respectively 44.2%, 34.6%, 42.3%, 32.7%, and 17.3%. The results showed that the combination of Yinyang Gongji Pills and capecitabine demonstrated potential clinical efficacy and good safety in this study. The patients have clinical characteristics such as low tumor burden, onset site at the colon, KPS scores ≥ 80, long duration of oral TCM, and TCM syndrome differentiation including spleen or liver.
Humans ; Capecitabine/adverse effects* ; Colorectal Neoplasms/mortality* ; Drugs, Chinese Herbal/adverse effects* ; Male ; Middle Aged ; Female ; Aged ; Adult ; Treatment Outcome

This study aims to investigate the mechanism of Mahuang Lianqiao Chixiaodou Decoction(MHLQ) and its main active components in treating immunoglobin A nephropathy(IgAN). The rat model of IgAN was established by a combination of measures including gavage of bovine serum albumin, subcutaneous injection of carbon tetrachloride, and tail vein injection of lipopolysaccharide. The modeled rats were randomized into model, low-, medium-, and high-dose(1.773, 3.545, and 7.090 g·kg~(-1), respectively) MHLQ, phillyrin(PHI, 0.020 g·kg~(-1)), pseudoephedrine(PSE, 0.020 g·kg~(-1)), and losartan potassium(LP, 9.003 mg·kg~(-1)) groups, and Wistar rats were used as the control. Rats were administrated with corresponding drugs by gavage, and those in the control and model groups received an equal volume of normal saline. All the groups were treated for 4 consecutive weeks. Urine, serum, liver, and kidney samples were collected from rats in each group at the end of drug administration. The 24 h urine protein and renal function were examined, and staining was performed to observe the pathological changes in the renal tissue. The immunofluorescence assay was employed to detect the expression of IgA and complement C3/C3b/C3c in the renal tissue. Electron microscopy was employed to observe the ultrastructure of the renal tissue. Enzyme-linked immunosorbent assay was performed to determine the expression of complement C3 and sublytic C5b-9 in the serum and renal tissue. Western blot was performed to determine the expression levels of hepatic and renal complement C3/C3b/C3c, C5/C5a, C5b-9, and complement factor B(CFB). Immunohistochemistry(IHC) was employed to measure the expression of complement C3 in the renal tissue. The results showed that compared with the control group, the model group had elevated levels of blood urea nitrogen and serum creatinine, proliferation of glomerular mesangial cells and extracellular matrix, and glomerular deposition of IgA immune complexes or electron-dense material. In addition, the model group showcased increased serum C3 levels and up-regulated expression of CFB, C3/C3b/C3c, C5/C5a, and C5b-9 in the renal tissue and C3/C3b/C3c and C5b-9 in the hepatic tissue. After treatment with MHLQ and its active components, all of the above indexes were reversed. In conclusion, MHLQ and its active components can improve the renal function and reduce the deposition of immune complexes and pathological damage in the renal tissue of the rat model of IgAN by inhibiting the alternative pathway complement activation.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Glomerulonephritis, IGA/genetics* ; Rats ; Male ; Disease Models, Animal ; Rats, Wistar ; Complement Activation/drug effects* ; Kidney/immunology* ; Humans

This study aims to explore the mechanism of lung and gut protection by Tanreqing Capsules on the mice infected with influenza virus based on "the lung-gut axis". A total of 110 C57BL/6J mice were randomized into control group, model group, oseltamivir group, and low-and high-dose Tanreqing Capsules groups. Ten mice in each group underwent body weight protection experiments, and the remaining 12 mice underwent experiments for mechanism exploration. Mice were infected with influenza virus A/Puerto Rico/08/1934(PR8) via nasal inhalation for the modeling. The lung tissue was collected on day 3 after gavage, and the lung tissue, colon tissue, and feces were collected on day 7 after gavage for subsequent testing. The results showed that Tanreqing Capsules alleviated the body weight reduction and increased the survival rate caused by PR8 infection. Compared with model group, Tanreqing Capsules can alleviate the lung injury by reducing the lung index, alleviating inflammation and edema in the lung tissue, down-regulating viral gene expression at the late stage of infection, reducing the percentage of neutrophils, and increasing the percentage of T cells. Tanreqing Capsules relieved the gut injury by restoring the colon length, increasing intestinal lumen mucin secretion, alleviating intestinal inflammation, and reducing goblet cell destruction. The gut microbiota analysis showed that Tanreqing Capsules increased species diversity compared with model group. At the phylum level, Tanreqing Capsules significantly increased the abundance of Firmicutes and Actinobacteria, while reducing the abundance of Bacteroidota and Proteobacteria to maintain gut microbiota balance. At the genus level, Tanreqing Capsules significantly increased the abundance of unclassified＿f＿Lachnospiraceae while reducing the abundance of Bacteroides, Eubacterium, and Phocaeicola to maintain gut microbiota balance. In conclusion, Tanreqing Capsules can alleviate mouse lung and gut injury caused by influenza virus infection and restore the balance of gut microbiota. Treating influenza from the lung and gut can provide new ideas for clinical practice.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Lung/metabolism* ; Mice, Inbred C57BL ; Capsules ; Orthomyxoviridae Infections/virology* ; Gastrointestinal Microbiome/drug effects* ; Male ; Humans ; Female ; Influenza A virus/physiology* ; Influenza, Human/virology*