Irritable bowel syndrome with diarrhea （IBS-D）， as a prototypical disorder involving the microbiota-gut-brain axis， remains poorly understood in terms of its pathogenesis， posing ongoing challenges for clinical diagnosis. Omics technologies， leveraging their high-throughput detection and systematic analysis advantages， has emerged as a critical tool for deciphering the complex mechanisms underlying traditional Chinese medicine （TCM） treatment of IBS-D. This systematic review summarizes the research progress of transcriptomics， proteomics， metabolomics， microbiomics， and multi-omics integration techniques in TCM interventions for IBS-D. In single-omics studies， transcriptomics using techniques like RNA-seq， reveals the regulatory mechanisms of TCM on IBS-related signaling pathways. Proteomics， leveraging quantitative technologies such as 2D-difference gel electrophoresis and tandem mass tag， identifies differentially expressed proteins and elucidates the action targets of TCM in treating IBS-D. Metabolomics， employing methods like UPLC-Q-TOF-MS and LC-MS/MS， discovers metabolic pathways regulated by TCM to improve metabolic disturbances in IBS-D. Microbiomics， based on 16S rRNA sequencing， confirms that TCM can reshape the gut microbiota structure and restore the intestinal microecological balance， thereby improving IBS-D. Multi-omics integration further overcomes the limitations of single-omics approaches by synthesizing information from transcriptomics， proteomics， metabolomics， and microbiomics， enabling a more comprehensive and systematic elucidation of the complex mechanisms underlying TCM treatment for IBS-D. In the future， research related to IBS-D should be advanced from three aspects： stratified clinical research based on TCM syndrome types， multi-omics integration verification mechanisms， and emerging omics to explore new mechanisms， providing more innovative ideas for the precise diagnosis and treatment of this disease.

Hepatitis B virus （HBV） exclusively infects liver parenchymal cells and forms covalently closed circular DNA （cccDNA） within their nuclei. HBV cccDNA serves as the essential template for viral gene transcription， the sole source of progeny virus production， and the key driver of viral antigen expression， and it is the molecular basis for the persistence of HBV infection. Therefore， elimination and/or functional silencing of cccDNA is the key to eradicate chronic HBV infection. This article discusses the critical scientific issues that need to be solved during elimination of the harm of HBV infection from the perspectives of the synthesis， transcription， and clearance of cccDNA， as well as the impact of nonparenchymal cells on cccDNA， in order to provide a reference for eradicating HBV infection in the future.

ObjectiveThis paper aims to investigate the effect and mechanism of Runmu Xiaoyao powder on mice with dry eye and the syndrome of liver depression-heat syndrome based on the toll-like receptor 4 （TLR4）/myeloid differentiation primary response protein 88 （MyD88）/nuclear factor-κB （NF-κB） signaling pathway. MethodsSixty-six C57BL/6J female mice were randomly divided into a normal group， a model group， a sodium hyaluronate group， and high-， medium-， and low-dose Runmu Xiaoyao powder groups， with 11 mice per group. Except for those in the normal group， mice in the other groups were subjected to mouse models with dry eye and liver depression-heat syndrome by instilling a benzalkonium chloride solution and applying chronic pain stimulation in a dry environment. After modeling， mice in the high-， medium-， and low-dose Runmu Xiaoyao powder groups were administered intragastrically with 29.7， 14.85， 7.43 g·kg^-1， respectively， twice a day for 14 consecutive days. The mice in the sodium hyaluronate group received 5 μL of sodium hyaluronate eye drops in each eye twice daily. The mice in the normal and model groups were administered intragastrically with an equal volume of deionized water. Measurements were taken of tear secretion in mice， irritability scores， corneal fluorescein staining， and histopathological changes in the cornea， lacrimal glands， meibomian glands， and liver tissue. Enzyme-linked immunosorbent assay （ELISA） was used to detect the levels of interleukin-1β （IL-1β） and tumour necrosis factor-α （TNF-α） in serum. Immunohistochemistry （IHC） was used to detect the protein expression of IL-1β and TNF-α in corneal and lacrimal gland tissues. Real-time quantitative polymerase chain reaction（Real-time PCR） and Western blot were employed to detect the mRNA and protein expressions of TLR4， MyD88， and NF-κB p65 in corneal， lacrimal gland， and meibomian gland tissues. ResultsCompared with those in the normal group， mice in the model group exhibited significantly reduced tear secretion， significantly higher irritability scores， and more pronounced corneal fluorescence staining， with marked pathological damage observed in the cornea， lacrimal glands， meibomian glands， and liver tissue. IL-1β and TNF-α levels in serum were significantly elevated. The protein expressions of IL-1β and TNF-α in corneal and lacrimal gland tissues， as well as the mRNA and protein expressions of TLR4， MyD88， and NF-κB p65 in corneal， lacrimal gland， and meibomian gland tissues， were all significantly increased （P<0.01）. Compared with the model group， the sodium hyaluronate group and Runmu Xiaoyao powder groups with different doses exhibited increased tear secretion to varying degrees， alleviated corneal fluorescence staining and histopathological damage， reduced IL-1β and TNF-α levels in serum， and downregulated protein expressions of IL-1β and TNF-α in corneal and lacrimal gland tissues， as well as the mRNA and protein expressions of TLR4， MyD88， and NF-κB p65 in corneal， lacrimal gland， and meibomian gland tissues. The high-dose Runmu Xiaoyao powder group demonstrated a more pronounced effect， with multiple indicators showing superior results compared to those in the sodium hyaluronate group （P<0.05， P<0.01）. ConclusionRunmu Xiaoyao powder down-regulates the TLR4/MyD88/NF-κB signaling pathway activity in the cornea， lacrimal glands， and meibomian glands of model mice with dry eye and liver depression-heat syndrome， thereby suppressing inflammatory responses and mitigating ocular surface tissue damage. The therapeutic effect is dose-dependent， and the high-dose group exerts the most prominent effect.

Hemoglobin (Hb) concentration is a key clinical biomarker for diagnosing and managing anemia, ischemic stroke, perioperative blood loss, and chronic diseases such as renal failure. Traditional venous blood sampling remains the gold standard due to its high accuracy, but its invasive nature limits frequent testing, real time monitoring, and large scale screening. This has driven growing interest in non-invasive Hb detection technologies over the past decade. Among these, optical methods are the most promising because of their safety, potential for continuous monitoring, and compatibility with portable or wearable devices. This paper systematically reviews major advances in optical non invasive Hb detection from the last ten years. We focus on near-infrared spectroscopy branches—photoplethysmography (PPG) and dynamic spectrum (DS)—and also cover color analysis/RGB imaging, Raman spectroscopy, and photoacoustic spectroscopy. For each technology, we explain its detection principles, analyze advantages and limitations, and summarize optimization strategies reported in recent literature. PPG, based on pulsatile blood volume changes, underpins many commercial continuous monitors. However, its accuracy is constrained by motion artifacts, individual physiological variations (e.g., skin tone, tissue thickness), and low AC signal to noise ratio. In contrast, DS—an advanced derivative of PPG—uses a differential principle to extract absorbance changes between systolic and diastolic peaks. This theoretically eliminates interference from static tissues (skin, bone, venous blood) and common mode noise (e.g., ambient light), positioning DS as a more robust framework for high precision Hb quantification. Beyond spectral methods, color analysis/RGB imaging offers a hardware minimalist approach. By analyzing images of vascular rich, thin tissues (e.g., conjunctiva, nail beds, palms), it enables Hb estimation using smartphone cameras. Recent advances have shifted from manual RGB feature extraction to deep learning models and spectral super resolution that reconstruct hyperspectral data from RGB inputs, significantly improving screening accuracy. Our academic perspective emphasizes critical and integrative analysis. We highlight persistent challenges that hinder clinical translation: profound individual biological variability (skin optics, microvascular architecture), sensitivity to measurement conditions (pressure, ambient light), and a lack of standardized validation protocols and multi center trials. A central thesis is that no single optical method is universally superior; each involves trade offs between accuracy, complexity, cost, and practicality. Looking forward, we posit that the next performance leap will come from multimodal information fusion—combining PPG, electrocardiogram (ECG), bioimpedance, or different optical modalities to compensate for individual differences and environmental noise. AI and deep learning are essential not only for image analysis but also for automated, end to end feature extraction from complex waveforms like PPG sequences. Advancing hardware (tunable lasers, quantum dot LEDs, novel sensor designs) is crucial to improve signal fidelity and portability. Finally, we advocate for clinical scenario specific optimization and rigorous standardized evaluation frameworks to gain regulatory approval (e.g., FDA, NMPA) and achieve widespread clinical acceptance. In conclusion, this review synthesizes a decade of progress. Optical non-invasive Hb detection has evolved from proof of concept studies to emerging products and validated screening tools, but the journey toward reliable, clinic ready quantitative devices continues. The convergence of smarter algorithms, fused sensing modalities, and focused clinical validation offers the most promising path to transform this potential into routine medical practice, ultimately enabling personalized, continuous, and accessible hematological management.

Acute kidney injury (AKI) is a prevalent and life-threatening clinical syndrome characterised by a rapid decline in renal function and diverse pathological etiologies. The condition has been demonstrated to be associated with elevated mortality rates and an increased risk of progression to chronic kidney disease. At present, clinicians depend heavily on conventional functional markers, such as serum creatinine and urine output, for the diagnosis and staging of the disease. It is evident that these conventional indicators characteristically manifest a considerable temporal delay and only undergo modification subsequent to considerable tissue damage. This severely restricts the timeframe for early detection and timely therapeutic intervention. Furthermore, standard markers fail to provide specific biological information regarding the underlying cellular injury mechanisms. The utilisation of advanced probe technologies in molecular imaging offers a robust alternative to overcome these inherent diagnostic limitations.This comprehensive review systematically evaluates recent progress in the design and application of two primary categories of molecular imaging tools for acute kidney disease, specifically reactive probes and enzyme-activated probes. Reactive probes are engineered to specifically interact with redox-active chemical species, including hydrogen peroxide, peroxynitrite, hypochlorous acid, and sulfur dioxide. Because oxidative stress constitutes a primary early event in acute renal tubular damage, these probes enable researchers and clinicians to visualize early cellular injury and radical accumulation well before global renal functional decline becomes evident. We discuss the application of these reactive probes across multiple imaging modalities including fluorescence imaging, magnetic resonance imaging (MRI), positron emission tomography (PET), and photoacoustic techniques. Photoacoustic imaging combines high spatial resolution with deep tissue penetration and has successfully demonstrated the ability to provide diagnostic alerts up to 12 h before any detectable rise in serum creatinine levels. Additionally, specific reactive probes have shown promising translational potential when tested by high-throughput screening in clinical human urine samples. Enzyme-activated probes target the specific catalytic activity of disease-relevant enzymes. These include well-documented renal tubular structural biomarkers such as NAG, GGT, and ALP, along with apoptosis-related caspases and specific nitroreductases. By responding only to enzymatic cleavage, these tools provide highly specific and pathology-directed imaging readouts. Recent structural design strategies in this field have advanced significantly beyond single-enzyme detection. Researchers are now focusing on sophisticated dual-target recognition to minimize background noise, multimodal integration to cross-validate imaging signals, and theranostic applications where probes simultaneously deliver diagnostic feedback and therapeutic agents to injured tissues. Nanotechnology serves as a fundamental enabler for realizing these advanced probe functions. By precisely optimizing nanoparticle parameters such as hydrodynamic size, surface charge, and targeting ligands, researchers can achieve amplified signal output, highly precise kidney delivery, and protection against premature degradation in the systemic circulation. For example, modifying surface charges can significantly enhance the active uptake of nanoprobes by damaged renal tubular epithelial cells.While preclinical probe development has progressed rapidly, moving these technologies into routine clinical practice remains a major challenge. We analyze the translational feasibility and current obstacles from biological, technological, and regulatory perspectives. Although biological targets such as KIM-1, FAP, and ALP have been validated in extensive patient cohorts, practical barriers severely limit their immediate clinical application. These obstacles involve complex changes in in vivo pharmacokinetics. During an acute injury episode, the extreme drop in the glomerular filtration rate alters probe clearance and can cause unwanted systemic accumulation or confusing background imaging signals. Other major hurdles include a lack of comprehensive long-term toxicity data and the absence of standardized manufacturing protocols to ensure batch-to-batch consistency. Future successful translation will require rigorous multi-center clinical studies to confirm the true diagnostic value of these probes over traditional markers. Researchers must also establish strict standardization of imaging procedures and comprehensive safety evaluations. Ultimately, this review provides a thorough reference framework for designing clinically translatable molecular probes and building a precision diagnostic imaging system for acute kidney injury.

Objective To investigate the expression of six-transmembrane epithelial antigen of prostate 4 (STEAP4) in prostate cancer (PCa), explore its correlation with the infiltration of regulatory T cells (Tregs) and CD8+T cells within the tumor-infiltrating T lymphocyte population, and to predict the potential role of STEAP4 in promoting PCa progression. Methods The clinicopathological data and tumor tissue specimens were collected from 90 PCa patients undergoing radical prostatectomy at our hospital during Jan.2018 and Dec.2024.The protein expressions of STEAP4, forkhead box transcription factor P3 (FoxP3), and CD8+T cells in tumor tissues were detected with immunohistochemistry.The correlation between STEAP4 expression and the infiltration of Tregs (FoxP3 T cells), CD8+T cells and clinicopathological characteristics was analyzed.The relationship between STEAP4 expression and prognosis was evaluated with Kaplan-Meier survival curves. Results STEAP4 expression was significantly higher in PCa tissues than in adjacent benign tissues (P＜0.001).STEAP4 expression was significantly associated with serum total prostate-specific antigen (tPSA) level, seminal vesicle invasion, extraprostatic extension, International Society of Urological Pathology (ISUP) grading, and pathological T stage (all P＜0.05).The mean infiltration density of Tregs (FoxP3 T cells) in PCa tissues was significantly higher than that in adjacent benign tissues[ (11.09±5.05) cells/HPF vs. (3.92±1.59) cells/HPF, P＜0.001], while the mean infiltration density of CD8+T cells was significantly lower[ (6.07±2.90) cells/HPF vs. (27.23±6.75) cells/HPF, P＜0.001].In PCa tissues, STEAP4 expression showed a significant positive correlation with Treg (FoxP3 T cells) infiltration density (r_s=0.472, P＜0.001) and a significant negative correlation with CD8+T-cell infiltration density (r_s=-0.495, P＜0.001).Kaplan-Meier survival curves indicated that high STEAP4 expression group and low STEAP4 expression group in PCa patients was not correlated with overall survival (OS) or recurrence-free survival (P=0.562, 0.346). Conclusion STEAP4 is highly expressed in PCa tissues, and its expression is closely associated with tumor-infiltrating lymphocytes, particularly Tregs and CD8+T cells, suggesting that STEAP4 may cooperate with Tregs and CD8+T cells to regulate the tumor microenvironment, thereby promoting PCa progression.

Metabolic dysfunction-associated fatty liver disease （MAFLD） is a chronic liver disease closely related to metabolic dysfunction. Its global prevalence is increasing year by year and shows a trend toward younger onset. It is closely associated with cardiovascular and cerebrovascular diseases， chronic kidney disease， and extrahepatic malignant tumors， and has become a major public health problem affecting the health of the Chinese population. At present， the treatment of MAFLD mainly focuses on lifestyle intervention. When metabolic cardiovascular risk factors and liver injury are present， pharmacological intervention is required. However， there is still no specific drug therapy for MAFLD. In recent years， many studies have found that the pathogenesis of MAFLD involves interactions among multiple factors， including insulin resistance， oxidative stress， endoplasmic reticulum stress， programmed cell death， immune dysregulation， inflammasomes， gut microbiota imbalance， and bile acid metabolism. Traditional Chinese medicine （TCM） has advantages in integrated regulation with multiple components and multiple targets， and shows significant efficacy in the treatment of MAFLD. Active components of Chinese medicinal herbs and Chinese medicine compound formulas exert definite therapeutic effects by regulating multiple signaling pathways to improve lipid metabolism disorders， inhibit inflammatory responses， and regulate the gut microbiota， thereby effectively improving clinical symptoms and delaying the occurrence and development of MAFLD. Therefore， strengthening research on the mechanisms of action of TCM in MAFLD is of crucial importance and significance for its treatment. This article summarizes the mechanisms by which Chinese medicine monomers and compound formulas intervene in MAFLD through the regulation of related signaling pathways， based on the retrieval and analysis of relevant literature from multiple databases， with the aim of providing theoretical support and a reference basis for the clinical application of TCM in the treatment of MAFLD.

Objective​ To analyze the current status of nuclear radiation health emergency response capacity in areas of the nuclear power plants in Guangdong Province, and to formulate a construction plan for municipal-level nuclear radiation health emergency response teams. Methods Provincial-, municipal-, and county-level administrative regions in the nuclear power plant host areas of Guangdong Province were selected as the study subjects. A series of questionnaires designed by the National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, were used to assess the capacity of nuclear radiation health emergency response. Based on the findings, a construction plan for municipal-level nuclear radiation health emergency response teams was formulated. Results A total of 13 administrative regions which host nuclear power plants were involved, including one provincial-level, six municipal-level, and six county-level regions. The availability rates of 31 capacity indicators of nuclear radiation health emergency response among 13 administrative regions ranged from 15% to 100%, with an average of 51%. Provincial-level capacity of nuclear radiation health emergency response was relatively well established, county-level radiation monitoring and protection capacity was nearly absent, municipal-level regions possessed basic capacity, but with obvious regional disparities and a general lack of specialized facilities and materials required for the treatment of nuclear radiation injuries, making them the key level for improvement in nuclear radiation health emergency response. The Construction Plan for Municipal-Level Nuclear Radiation Health Emergency Response Teams specifies that the total number of team members should be no fewer than 30 to ensure rapid response and immediate arrival at the scene. The List of Key Professional Equipment proposes the prioritized allocation of five categories of equipment: personal basic equipment, contamination detection and classification equipment, decontamination equipment, medical treatment equipment, and command and logistical support equipment. Conclusion Nuclear radiation health emergency response capacity in Guangdong Province requires further improvement, particularly in standardized development of municipal-level nuclear radiation health emergency response teams. The Construction Plan for Municipal-Level Nuclear Radiation Health Emergency Response Teams defines capacity requirements and provides a list of essential equipment, offering a practical reference for other regions.

Stroke is the main cause of death and disability among adults in China and is characterized by high incidence， disability， mortality， and recurrence rates. The combination of traditional Chinese and Western medicine has great potential in treating stroke and its sequelae. The classic traditional Chinese medicine prescription Da Chengqitang （DCQT） has a long history and proven efficacy in treating stroke. Clinically， DCQT is often used to treat stroke and its sequelae. However， the number and quality of clinical trials of DCQT in treating stroke need to be improved. Because of the insufficient basic research， the active ingredients and multi-target mechanism of action of DCQT remain unclear. Our research group has previously confirmed that DCQT can effectively reverse neurological damage， reduce iron deposition， and downregulate the levels of pro-inflammatory cytokines in the rat model of hemorrhagic stroke. The treatment mechanism is related to the nuclear factor erythroid 2-related factor 2 （Nrf2）-mediated signaling pathway and p38 mitogen-activated protein kinase （MAPK） signaling-mediated microglia activation. To clarify the pharmacodynamic basis and anti-stroke mechanism of DCQT， this article reviews the research progress in the treatment of stroke with DCQT in terms of clinical trials， pharmacodynamic material basis， safety evaluation， and mechanisms of absorbed components. This article summarizes 45 major phytochemical components of DCQT， 11 of which are currently confirmed absorbed components. Among them， emodin， rhein， chrysophanol， aloe-emodin， synephrine， hesperidin， naringin， magnolol， and honokiol can be used as quality markers （Q-markers） of DCQT. The mechanism of DCQT in treating stroke is complex， involving regulation of inflammatory responses， neuronal damage， oxidative stress， blood-brain barrier， brain-derived neurotrophic factor， and anti-platelet aggregation. This article helps to deeply understand the pharmacodynamic basis and mechanism of DCQT in treating stroke and provides a theoretical basis for the clinical application of DCQT in treating stroke and the development of stroke drugs.

Disorders of consciousness (DOC) are pathological conditions characterized by severely suppressed brain function and the persistent interruption or loss of consciousness. Accurate diagnosis and evaluation of DOC are prerequisites for precise treatment. Traditional assessment methods are primarily based on behavioral scales, which are inherently subjective and rely on observable behaviors. Moreover, traditional methods have a high misdiagnosis rate, particularly in distinguishing minimally conscious state (MCS) from vegetative state/unresponsive wakefulness syndrome (VS/UWS). This diagnostic uncertainty has driven the exploration of objective, reliable, and efficient assessment tools. Among these tools, electroencephalography (EEG) has garnered significant attention for its non-invasive nature, portability, and ability to capture real-time neurodynamics. This paper systematically reviews the application of EEG biomarkers in DOC assessment. These biomarkers are categorized into 3 main types: resting-state EEG features, task-related EEG features, and features derived from transcranial magnetic stimulation-EEG (TMS-EEG). Resting-state EEG biomarkers include features based on spectrum, microstates, nonlinear dynamics, and brain network metrics. These biomarkers provide baseline representations of brain activity in DOC patients. Studies have shown their ability to distinguish different levels of consciousness and predict clinical outcomes. However, because they are not task-specific, they are challenging to directly associate with specific brain functions or cognitive processes. Strengthening the correlation between resting-state EEG features and consciousness-related networks could offer more direct evidence for the pathophysiological mechanisms of DOC. Task-related EEG features include event-related potentials, event-related spectral modulations, and phase-related features. These features reveal the brain’s responses to external stimuli and provide dynamic information about residual cognitive functions, reflecting neurophysiological changes associated with specific cognitive, sensory, or behavioral tasks. Although these biomarkers demonstrate substantial value, their effectiveness rely on patient cooperation and task design. Developing experimental paradigms that are more effective at eliciting specific EEG features or creating composite paradigms capable of simultaneously inducing multiple features may more effectively capture the brain activity characteristics of DOC patients, thereby supporting clinical applications. TMS-EEG is a technique for probing the neurodynamics within thalamocortical networks without involving sensory, motor, or cognitive functions. Parameters such as the perturbational complexity index (PCI) have been proposed as reliable indicators of consciousness, providing objective quantification of cortical dynamics. However, despite its high sensitivity and objectivity compared to traditional EEG methods, TMS-EEG is constrained by physiological artifacts, operational complexity, and variability in stimulation parameters and targets across individuals. Future research should aim to standardize experimental protocols, optimize stimulation parameters, and develop automated analysis techniques to improve the feasibility of TMS-EEG in clinical applications. Our analysis suggests that no single EEG biomarker currently achieves an ideal balance between accuracy, robustness, and generalizability. Progress is constrained by inconsistencies in analysis methods, parameter settings, and experimental conditions. Additionally, the heterogeneity of DOC etiologies and dynamic changes in brain function add to the complexity of assessment. Future research should focus on the standardization of EEG biomarker research, integrating features from resting-state, task-related, and TMS-EEG paradigms to construct multimodal diagnostic models that enhance evaluation efficiency and accuracy. Multimodal data integration (e.g., combining EEG with functional near-infrared spectroscopy) and advancements in source localization algorithms can further improve the spatial precision of biomarkers. Leveraging machine learning and artificial intelligence technologies to develop intelligent diagnostic tools will accelerate the clinical adoption of EEG biomarkers in DOC diagnosis and prognosis, allowing for more precise evaluations of consciousness states and personalized treatment strategies.