Colorectal cancer (CRC), a prevalent and deadly digestive malignancy, primarily causes death through recurrence and metastasis. Current treatments include surgery, radiotherapy, chemotherapy, and immunotherapy, but they have significant side effects and high recurrence rates. Research shows traditional Chinese medicine (TCM) can alleviate symptoms, reduce adverse reactions, enhance quality of life, prevent recurrence and metastasis post-surgery, and improve survival rates. This review explores TCM's theoretical framework, advantages in CRC management, and potential in modulating intestinal flora for CRC prevention and treatment.

Root rot represents a significant disease affecting the cultivation of Platycodon grandiflorum. The screening of biocontrol strains with antagonistic properties against this disease can provide valuable microbial resources for the environmentally friendly prevention and control of Platycodon grandiflorum diseases. In this investigation, high-throughput bacterial isolation techniques were utilized to isolate and purify endophytic bacteria from the roots of Platycodon grandiflorum. An antagonistic bacterial strain R34B7, was identified through the plate confrontation culture method, exhibiting a notable inhibitory rate of 52.18% against the pathogen causing root rot. Morphological characteristics, physiological and biochemical properties, and molecular identification results collectively confirmed that the antagonistic endophytic bacterium R34B7 belonged to the species Serratia plymuthica. The control efficacy of strain R34B7 against Platycodon grandiflorum root rot was assessed using tissue-cultured seedlings of Platycodon grandiflorum, revealing a disease control efficacy of 44.44%. Furthermore, the fermented supernatant of strain R34B7 demonstrated considerable inhibitory effects on both the mycelial growth and spore germination of the pathogen. By examining the extracellular hydrolytic enzymes and growth-promoting factors of strain R34B7, it was discovered that this strain possesses the abilities to produce protease, chitinase, fix nitrogen, solubilize phosphorus, synthesize siderophores, and produce indole-3-acetic acid, indicating its potential for growth promotion. The antagonistic bacterium R34B7 identified in this study exhibits promising biocontrol activity against root rot and holds considerable potential for further development and utilization.

To prepare a progesterone pressure-sensitive gel patch combined with a microneedle to enhance drug release, HPLC was used to determine the preparation's progesterone content. One-way and orthogonal experiments were used to optimize the patch's prescription. Adhesion, sensory evaluation, cumulative release, and cumulative penetration were used as evaluation indices. Three microneedles with varying needle heights were made using 3D printing, and the cumulative penetration of the patch and microneedles was calculated and compared with the patch alone. The orthogonal experiments showed that the optimal prescription for the patches was Duro-Tak 87-2677 pressure-sensitive adhesive (87.5%), tributyl citrate (2%), isopropyl myristate (5%), dibutylated hydroxytoluene (0.5%), and drug (5%). The patches were prepared according to the optimized prescription, resulting in good patch formability and adhesion. In the transdermal penetration test, the cumulative penetration of the patch was 52.35 ± 7.88 μg·cm^-2 at 24 h, and the cumulative penetration of the patch in combination with 500, 750, and 1 000 μm microneedles was 226.01 ± 7.46, 278.78 ± 6.59, 422.95 ± 16.81 μg·cm^-2, respectively. The experiment was approved by the Experimental Animal Ethics Committee of Xinjiang Medical University (IACUC-20220725-8). The optimal patch prescription was screened through one-way and orthogonal experiments, and the transdermal penetration effect of patch and microneedle combination preparation was better than that of single use, which can effectively increase the in vitro transdermal penetration of the drug, and the above study provides a theoretical basis for the application of transdermal patches of progesterone.

Five compounds were isolated and purified from the water extract of Elaeagnus oxycarpa Schlechtend leaf by multi-dimensional reversed-phase preparative liquid chromatographic system based on the separation and enrichment model. Their structures were identified by spectral analysis such as NMR, MS, UV, IR and by comparison with literature information as 2, 4(1H, 3H)-pyrimidinedione (1), elaeagnussugarester B (2), elaeagnussugarester A (3), elaeagnussugarester C (4), gallic acid (5). Compounds 2-4 are new compounds, compound 1 was isolated from Elaeagnus oxycarpa Schlechtend for the first time. The antioxidant and anti-tyrosinase activities of these compounds were evaluated by using the 2, 2-diphenyl-1-picrylhydrazyl (DPPH) free radical method, the 2, 2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) free radical method, the potassium ferricyanide reduction method and the colorimetric method with L-tyrosine as substrate. The results showed that compounds 2-5 have good antioxidant activities and inhibitory effect on tyrosinase. Compound 4 exhibited the most strong antioxidant activities, with IC₅₀ = 3.59 ± 0.06 μmol·L^-1 for DPPH free radical scavenging ability, IC₅₀ = 10.04 ± 0.20 μmol·L^-1 for ABTS free radical scavenging ability, and total reduction capacity of compound 4 was better than vitamin C respectively. Compound 3 possessed better inhibitory effect on tyrosinase with IC₅₀ = 0.25 ± 0.06 mmol·L^-1.

Direct compression is an ideal method for tablet preparation, but it requires the powder's high functional properties. The functional properties of the powder during compression directly affect the quality of the tablet. 15 parameters such as Py, FES-8KN, FES-12KN, FES-16KN, CR-8KN, CR-12KN, and CR-16KN were used as the characteristic variables in this paper. Unsupervised learning methods like principal component analysis, cluster analysis, and factor analysis were applied to analyze and classify the compression behavior data of 36 traditional Chinese medicine powders. The results showed that both different dimensionality reduction classification methods could effectively differentiate the compression behavior characteristics of 36 traditional Chinese medicine compound powders. The hierarchical cluster analysis results showed a better agreement with the actual compression phenomena of the powders, where group 1 was high elasticity and low compressibility, group 2 was easily compressed and hard to break, group 3 was excellent compressibility and compactibility. This study is expected to provide references and ideas for predicting the behavior of traditional Chinese medicine powders and the screening of tablet formulations.

New drugs approved by authorities are classified into two categories: new molecular entities (NME) and fixed dose combination (FDC) formulations, both of which are documented by scientific experiments and clinical trials. Complex diseases frequently possess multifactorial causes, and drugs that only focus on a single target may not achieve satisfactory results; moreover, it is difficult to achieve full optimization of the pharmacodynamics, pharmacokinetics, safety, and patient compliance for a drug. Therefore, combinatorial remedies with two (or more) drugs at a fixed dose may provide patients with better treatment options. Based upon understanding the various molecular regulation of pathological processes and principles of drug action, clinicians and pharmacologists are able to design new FDC to achieve optimum efficiency in clinical practice. In this sense the significance of FDC is no less than NME, because it is closer to clinical practice and directly meets the needs of patients. This article briefly analyzes the development of FDC from the microscopic characteristics of pathology and the molecular mechanism of drug action with influential examples.

Antibody drug conjugates (ADC) have emerged as a cutting-edge technology in anti-tumor treatment, making significant strides in recent years. ADC couple a highly active small molecule toxin payload to highly specific antibodies through a linker, enabling precise targeting of tumor cells while reducing systemic toxicity, thereby expanding the therapeutic window. However, due to the complexity of ADC molecule design, its efficacy and safety are influenced by various factors. Model-informed drug development (MIDD) is a powerful tool that utilizes various mathematical models for modeling and simulation to conduct quantitative analysis, guiding drug development and decision-making. By integrating multi-faceted data and information using mathematical models, it is possible to gain insights into the complex mechanisms, pharmacokinetics, and pharmacodynamics of ADC, providing unique perspectives for optimizing ADC development processes and clinical translation decisions. This review will introduce the basic concepts of MIDD and ADC and discuss application cases of MIDD in different stages of ADC development, aiming to provide beneficial references for the advancement of ADC.

Inflammatory diseases (IDs) are a general term of diseases characterized by chronic inflammation as the primary pathogenetic mechanism, which seriously affect the quality of patient′s life and cause significant social and medical burden. Current drugs for IDs include nonsteroidal anti-inflammatory drugs, corticosteroids, immunomodulators, biologics, and antioxidants, but these drugs may cause gastrointestinal side effects, induce or worsen infections, and cause non-response or intolerance. Given the outstanding performance of metal polyphenol network (MPN) in the fields of drug delivery, biomedical imaging, and catalytic therapy, its application in the diagnosis and treatment of IDs has attracted much attention and significant progress has been made. In this paper, we first provide an overview of the types of IDs and their generating mechanisms, then sort out and summarize the different forms of MPN in recent years, and finally discuss in detail the characteristics of MPN and their latest research progress in the diagnosis and treatment of IDs. This research may provide useful references for scientific research and clinical practice in the related fields.

As the biggest tissue of human body, skin is the first barrier of resisting external aggression. Collagen is one of important parts of the skin, which could not only affect the aesthetics of skin, but also influence the health and normal function of skin. It is the great significance to find ways that could inhibit the loss of collagen. The mechanisms of the collagen degradation in skin are complex and multifaceted. Natural bioactive products have unique advantages in treating the loss of collagen, which have multi-targets and mechanisms. In this review, the mechanisms of skin collagen degradation are discussed, and the research progress of natural bioactive products in resisting skin aging through promoting collagen synthesis are reviewed, in order to provide references for futural research.

The general models for intermediates quality analysis in the production process of Yaobitong capsule were established by near infrared spectroscopy (NIRS) combined with chemometrics, realizing the rapid determination of notoginsenoside R1, ginsenoside Rg1, ginsenoside Re, ginsenoside Rb1, ginsenoside Rd and moisture. The spray-dried fine powder and total mixed granule were selected as research objects. The contents of five saponins were determined by high performance liquid chromatography and the moisture content was determined by drying method. The measured contents were used as reference values. Meanwhile, NIR spectra were collected. After removing abnormal samples by Monte Carlo cross validation (MCCV), Monte Carlo uninformative variables elimination (MC-UVE) and competitive adaptive reweighted sampling (CARS) were used to select feature variables respectively. Based on the feature variables, quantitative models were established by partial least squares regression (PLSR), extreme learning machine (ELM) and ant lion optimization least squares support vector machine (ALO-LSSVM). The results showed that CARS-ALO-LSSVM model had the optimum effect. The correlation coefficients of the six index components were greater than 0.93, and the relative standard errors were controlled within 6%. ALO-LSSVM was more suitable for a large number of samples with rich information, and the prediction effect and stability of the model were significantly improved. The general models with good predicting effect can be used for the rapid quality determination of Yaobitong capsule intermediates.