ObjectiveThis study aims to systematically analyze the blood-absorbed components and metabolic profiles of Xiebaisan（XBS） in normal and chronic bronchitis （CB） mice using ultra performance liquid chromatography-quadrupole-electrostatic field orbitrap high resolution mass spectrometry（UPLC-Q-Exactive Orbitrap MS）， while comparing differences between the two states. MethodsThirty female BABL/c mice were randomly divided into the normal group， the normal drug administration group， the CB group， the CB drug administration group and the dexamethasone group， with 6 mice in each group. The CB mouse model was established by inducing with ovalbumin （OVA）. The mice in the normal drug administration group and the CB drug administration group started to be gavaged with XBS（13.2 g·kg^-1） from the 21^st day， and the dexamethasone group mice were simultaneously gavaged with dexamethasone （0.5 mg·kg^-1） until the end of the 35^th day of the experiment. Subsequently， serum samples were collected and evaluated for their efficacy， based on the pharmacological evaluation indicators， to determine the efficacy of XBS in treating CB. Then the UPLC-Q-Exactive Orbitrap MS was employed to identify and analyze the chemical constituents， blood-absorbed components， and metabolites of XBS. Chemometric analysis was conducted to reveal metabolic profile differences under "dual states". Concurrently， Real-time PCR technology was utilized to detect the expression levels of key liver metabolic enzymes CYP2E1， CYP3A1， UGT1A1， and UGT1A6. ResultsA total of 28 prototype components and 158 metabolites （including 48 phase Ⅰ metabolites and 110 phase Ⅱ metabolites） of XBS were unambiguously identified in the serum of normal mice. Additionally， a comprehensive characterization was performed on a total of 32 prototype components and 178 metabolites （including 50 phase Ⅰ metabolites and 128 phase Ⅱ metabolites） of XBS in the serum of CB mice. Among them， 27 prototype components were detected in both states， including 12 flavonoids， 2 alkaloids， 3 triterpenes， 4 organic acids， 3 amides， 1 stilbene and 2 other compounds. The chemometrics analysis revealed no significant difference in the prototype components and metabolites of XBS between normal and CB mice； however， there was a significant increase in the in-vivo exposure of XBS in CB mice. Compared to normal mice， the levels of phase Ⅰ metabolites such as oxidation， reduction and methylation of blood components of XBS as well as phase Ⅱ metabolites of glucuronidation showed significant changes in CB mice. Real-time PCR further confirmed that these alterations were attributed to the upregulation of CYP2E1 （P<0.05）， CYP3A1 （P>0.05）， UGT1A1 （P<0.01） and UGT1A6 （P<0.01） enzymes expression in the liver of CB mice. ConclusionThis study elucidated the disparities in the levels of the blood-absorbed components and metabolic profiles of XBS in normal and CB mice， especially in oxidation， reduction， methylation in phase Ⅰ metabolism and glucoaldehyde acidification in phase Ⅱ metabolism. And there are related to the differences in the expression levels of phase Ⅰ and phase Ⅱ metabolic enzymes CYP2E1， CYP3A1， UGT1A1 and UGT1A6 in the liver.

Objective To investigate the impact of two different algorithms, AAA and AXB, on the dose distribution of postoperative radiotherapy for left-sided breast cancer after breast-conserving surgery. Methods A total of 96 target volumes from patients who underwent breast-conserving surgery for left-sided breast cancer were selected for dose verification using a two-dimensional matrix system. The planned dose distributions were simulated using both AAA and AXB algorithms. Dosimetric differences in organs at risk and the target volumes were then compared to identify the algorithm that could reduce the radiation dose to organs at risk without compromising the dose distribution to the target volume. Dose verification was performed on the plans generated by both algorithms, and the pass rates of plans for each target volume using both algorithms were compared to provide a quantitative basis for the precise selection of subsequent radiotherapy plans. Results Both AAA and AXB plans met the radiotherapy requirements. The AXB algorithm demonstrated significant advantages in the D₉₈, D₂, homogeneity index, and conformity index for the planning target volume, as well as in the V₅ and V₂₀ for the left lung. The AXB algorithm showed advantages in the V₃₀ for the heart and the maximum and mean doses for the skin. With the 2 mm/2% criterion in dose verification, the gamma pass rate was higher for the AXB algorithm. Conclusion Through a comparative analysis of the two algorithms, this study revealed that the AXB algorithm offers certain advantages in the dose distribution of radiotherapy after breast-conserving surgery for left-sided breast cancer. These findings provide an important reference for the rational selection of algorithms in clinical practice and are expected to improve radiotherapy efficacy and patient prognosis.

To thoroughly implement the strategic deployment outlined in the Opinions of the Central Committee of the Communist Party of China and the State Council on Promoting the Inheritance and Innovative Development of Traditional Chinese Medicine regarding research on dominant diseases of traditional Chinese medicine and to uphold the development philosophy of equal emphasis on traditional Chinese medicine and western medicine，the China Association of Chinese Medicine has fully played a leading academic role by systematically organizing and conducting a series of academic youth salons on clinical dominant diseases of traditional Chinese medicine. On September 13，2024，the 36^th Youth Salon on Clinical Dominant Diseases was successfully held in Nanjing，focusing on the advantages of traditional Chinese medicine and the integrative traditional Chinese medicine and western medicine in the diagnosis and treatment of erectile dysfunction （ED）. The conference brought together leading experts from traditional Chinese medicine，western medicine，and interdisciplinary fields，facilitating in-depth multidisciplinary discussions that led to key consensus on optimizing traditional Chinese medicine treatment protocols for ED，researching and developing new drugs of traditional Chinese medicine，and advancing interdisciplinary development in traditional Chinese medicine. This salon systematically sorted out the clinical strengths and distinctive features of traditional Chinese medicine in the diagnosis and treatment of ED. Based on current research foundations and clinical needs，it identified key directions for future scientific layout and scientific research tackling： （1） Standardization of syndrome differentiation system of traditional Chinese medicine for ED. （2） Optimization and standardization of intervention methods of integrated traditional Chinese medicine and western medicine. （3） High-quality clinical research guided by evidence-based medicine. （4） In-depth analysis of the pharmacological mechanisms of traditional Chinese medicine in the treatment of ED. （5） Clinical translation and application promotion of new drugs of traditional Chinese medicine. （6） Interdisciplinary integration and innovation in traditional Chinese medicine. For each research direction，key focus areas，expected objectives，and clinical value were further refined，along with the establishment of a scientifically sound priority funding level evaluation system. Therefore，building on the series of salons on the ED-focused dominant diseases of traditional Chinese medicine，this paper provides standardized guidance for clinical practice of traditional Chinese medicine in ED management，effectively contributing to the high-quality development of traditional Chinese medicine. It serves as a valuable reference for national scientific and technological strategic layout， research and development decision-making in new drugs of traditional Chinese medicine，research topic planning，and clinical guideline formulation.

Arsenic trioxide (ATO) serves as a component of traditional Chinese medicine and a modern anticancer agent, demonstrating remarkable efficacy in the long-term treatment of acute promyelocytic leukemia. With increasing research into its application in solid tumors, ATO's diverse mechanisms of action and potential clinical value have attracted widespread attention. ATO can inhibit tumor cell proliferation by inducing various forms of cell death, such as apoptosis, autophagy, pyroptosis, necroptosis, and ferroptosis, as well as by regulating cell differentiation. Moreover, its modulatory effects on the tumor immune microenvironment provide a new aspectto its antitumor activity. Nevertheless, the clinical application of ATO in solid tumors faces challenges such as low bioavailability, inadequate targeting, and adverse effects. The development of nanocarriers and targeted delivery systems has emerged asa key strategy for enhancing the therapeutic efficacy of ATO. This review systematically summarizes the multiple mechanisms of action of ATO in solid tumors and recent advances in nanodelivery technologies, explores the potential of ATO-based combination therapies, and discusses future directions, aiming to provide a theoretical foundation and practical guidance for the clinical application of ATO in solid tumors.

The application of immunosuppressants has significantly reduced the incidence rate of rejection reaction after liver transplantation， but the clinical efficacy of immunosuppressants is greatly affected by individual differences between patients. This article systematically reviews the recent research advances in the interaction between immunosuppressants and gut microbiota， with a focus on the regulatory role and mechanism of intestinal microflora communities on the efficacy of immunosuppressants. Studies have shown that intestinal microbiome is one of the key factors influencing the efficacy of immunosuppressive therapy after liver transplantation. This review aims to provide a theoretical basis for in-depth research in this field and provide new insights for developing individualized immunosuppressive treatment regimens based on the regulation of intestinal microflora.

With the rapid advancement of synthetic biology, CRISPR-Cas systems have emerged as a powerful tool for gene editing, demonstrating significant potential in various fields, including medicine, agriculture, and industrial biotechnology. This review comprehensively summarizes the significant progress in applying artificial intelligence (AI) technologies to the design, mining, and modification of CRISPR-Cas systems. AI technologies, especially machine learning, have revolutionized sgRNA design by analyzing high-throughput sequencing data, thereby improving the editing efficiency and predicting off-target effects with high accuracy. Furthermore, this paper explores the role of AI in sgRNA design and evaluation, highlighting its contributions to the annotation and mining of CRISPR arrays and Cas proteins, as well as its potential for modifying key proteins involved in gene editing. These advancements have not only improved the efficiency and precision of gene editing but also expanded the horizons of genome engineering, paving the way for intelligent and precise genome editing.
CRISPR-Cas Systems/genetics* ; Artificial Intelligence ; Gene Editing/methods* ; RNA, Guide, CRISPR-Cas Systems/genetics* ; Machine Learning ; Humans ; Genetic Engineering/methods* ; Synthetic Biology

Growth factors (GFs) are a class of peptides that facilitate cell growth by binding to specific receptors on the cell membrane. With unique properties, GFs are widely applied in the repair of injured tissue. To address the limitations associated with natural peptide-based GFs and recombinant GFs, researchers have developed diverse GF mimetics. This article offers a comprehensive review on common types of GFs and their applications in tissue repair and summarizes the features of GF mimetics currently under development. The aim is to provide valuable references for promoting the application of GFs in regenerative medicine.
Intercellular Signaling Peptides and Proteins/therapeutic use* ; Humans ; Tissue Engineering/methods* ; Regenerative Medicine/methods* ; Animals ; Wound Healing/drug effects* ; Biomimetic Materials

Childhood primary renal tubular diseases are chronic kidney diseases characterized by impaired renal tubular reabsorption. Primary renal tubular disease has diverse clinical manifestations and lacks of specificity. Laboratory tests are limited，making it prone to missed diagnosis and misdiagnosis. Based on the current knowledge of renal tubular diseases，authors propose early warning signals of renal tubular diseases such as family history of primary tubular diseases，unexplained polyhydramnios during pregnancy，polydipsia，polyuria，delayed growth and development or rickets，decreased muscle strength and tone，unexplained electrolyte disturbance，hyperuricemia，acid-base disturbance，positive urine sugar test，renal tubular proteinuria，urinary imaging examination suggesting kidney stones，calcium deposition，renal cysts and early onset of eye，ear，joint and neuron injury.Meanwhile，some universal management strategies for primary renal tubular disease are proposed，emphasizing the importance of multidisciplinary collaboration，genetic testing and individualized intervention to improve the long-term prognosis of childhood primary renal tubular diseases.

With the widespread application of information technology in the field of Traditional Chinese Medicine(TCM),the data in the TCM domain is becoming increasingly rich.The emergence of data-driven research in TCM has utilized knowledge graphs for the management,analysis,and presentation of TCM data,becoming a crucial method for the inheritance and innovation of Traditional Chinese Medicine.Therefore,reasoning based on TCM knowledge graphs has become a hot topic in contemporary TCM research.In order to better utilize knowledge graph reasoning technology to promote innovation and development in TCM,this article,after providing an overview of TCM knowledge graph reasoning,focuses on the development of knowledge graph reasoning in TCM and its applications from three perspectives:logic rule-based,distributed representation,and neural network-based methods.Finally,the article summarizes the advantages and disadvantages of knowledge reasoning methods and provides prospects for research and applications in TCM knowledge graph reasoning,including studies on interpretability,temporal knowledge graphs,and the fusion of multimodal information.

Objective:To analyze the gene mutation spectrum of children with T-acute lymphoblastic leukemia (T-ALL) using next generation sequencing technology and to evaluate the value of gene mutations in prognosis stratification.Methods:A case series analysis was made.The clinical data of newly diagnosed pediatric T-ALL patients in the First Affiliated Hospital of Zhengzhou University from January 1, 2019 to February 29, 2024 were analyzed retrospectively.T-ALL gene mutations were analyzed.The relationships of gene mutations with clinical features and induction of responses to therapy were studied.The effects of gene mutations on overall survival (OS) and event-free survival (EFS) were examined by the Kaplan-Meier method and COX regression model.Results:A total of 80 newly diagnosed pediatric T-ALL patients were enrolled in the study, with a male-to-female ratio of 3.4∶1.0 and a median age of 8 (range, 2-17) years.A total of 57 mutations were detected in 74 patients, 46.2% (37/74) of whom showed 3 or more gene mutations.The coexistence of mutated genes was obvious. PTEN mutations were more prevalent in male patients ( P=0.018).Initial leukocyte counts were higher in patients with PTEN mutations ( P=0.038) and lower in patients with JAK3 mutations ( P=0.002).Patients with NOTCH1 mutations had a higher positive rate of fusion genes ( P=0.043).Patients with PTEN mutations had a higher rate of minimal residual disease(MRD) remission after 15/19 d of treatment with induction therapy, respectively ( P=0.013).The rate of MRD remission after 33/46 d of treatment with induction therapy was higher in patients with the FBXW7 mutation ( P=0.004) and lower in patients with JAK3 mutations ( P=0.003).Multifactorial COX regression analysis showed that IL7R mutation and three or more gene mutations were independent risk factors for OS and EFS in T-ALL patients(OS: HR=3.252, 7.357, 95% CI: 1.020-10.372, 1.646-32.882; EFS: HR=3.372, 3.009, 95% CI: 1.234-9.214, 1.174-7.708; all P<0.05). Conclusions:Gene mutations are prevalent in T-ALL children and correlate with clinical manifestations and prognosis.The coexistence of mutated genes is obvious.Pediatric T-ALL patients with IL7R mutations and three or more gene mutations have a poorer prognosis.