With the widespread use of antibiotics, drug-resistant bacterial infections have become a significant threat to human health. Finding new antibacterial strategies that can effectively control drug-resistant bacterial infections has become an urgent task. Unlike small molecule drugs that target bacterial proteins, antisense oligonucleotide (ASO) can target genes related to bacterial resistance, pathogenesis, growth, reproduction and biofilm formation. By regulating the expression of these genes, ASO can inhibit or kill bacteria, providing a novel approach for the development of antibacterial drugs. To overcome the challenge of delivering antisense oligonucleotide into bacterial cells, various drug delivery systems have been applied in this field, including cell-penetrating peptides, lipid nanoparticles and inorganic nanoparticles, which have injected new momentum into the development of antisense oligonucleotide in the antibacterial realm. This review summarizes the current development of small nucleic acid drugs, the antibacterial mechanisms, targets, sequences and delivery vectors of antisense oligonucleotide, providing a reference for the research and development of antisense oligonucleotide in the treatment of bacterial infections.

ObjectiveNeuroinflammation plays a crucial role in both the onset and progression of ischemic stroke, exerting a significant impact on the recovery of the central nervous system. Excessive neuroinflammation can lead to secondary neuronal damage, further exacerbating brain injury and impairing functional recovery. As a result, effectively modulating and reducing neuroinflammation in the brain has become a key therapeutic strategy for improving outcomes in ischemic stroke patients. Among various approaches, targeting immune regulation to control inflammation has gained increasing attention. This study aims to investigate the role of in vitro induced regulatory T cells (Treg cells) in suppressing neuroinflammation after ischemic stroke, as well as their potential therapeutic effects. By exploring the mechanisms through which Tregs exert their immunomodulatory functions, this research is expected to provide new insights into stroke treatment strategies. MethodsNaive CD4⁺ T cells were isolated from mouse spleens using a negative selection method to ensure high purity, and then they were induced in vitro to differentiate into Treg cells by adding specific cytokines. The anti-inflammatory effects and therapeutic potential of Treg cells transplantation in a mouse model of ischemic stroke was evaluated. In the middle cerebral artery occlusion (MCAO) model, after Treg cells transplantation, their ability to successfully migrate to the infarcted brain region and their impact on neuroinflammation levels were examined. To further investigate the role of Treg cells in stroke recovery, the changes in cytokine expression and their effects on immune cell interactions was analyzed. Additionally, infarct size and behavioral scores were measured to assess the neuroprotective effects of Treg cells. By integrating multiple indicators, the comprehensive evaluation of potential benefits of Treg cells in the treatment of ischemic stroke was performed. ResultsTreg cells significantly regulated the expression levels of both pro-inflammatory and anti-inflammatory cytokines in vitro and in vivo, effectively balancing the immune response and suppressing excessive inflammation. Additionally, Treg cells inhibited the activation and activity of inflammatory cells, thereby reducing neuroinflammation. In the MCAO mouse model, Treg cells were observed to accumulate in the infarcted brain region, where they significantly reduced the infarct size, demonstrating their neuroprotective effects. Furthermore, Treg cell therapy notably improved behavioral scores, suggesting its role in promoting functional recovery, and increased the survival rate of ischemic stroke mice, highlighting its potential as a promising therapeutic strategy for stroke treatment. ConclusionIn vitro induced Treg cells can effectively suppress neuroinflammation caused by ischemic stroke, demonstrating promising clinical application potential. By regulating the balance between pro-inflammatory and anti-inflammatory cytokines, Treg cells can inhibit immune responses in the nervous system, thereby reducing neuronal damage. Additionally, they can modulate the immune microenvironment, suppress the activation of inflammatory cells, and promote tissue repair. The therapeutic effects of Treg cells also include enhancing post-stroke recovery, improving behavioral outcomes, and increasing the survival rate of ischemic stroke mice. With their ability to suppress neuroinflammation, Treg cell therapy provides a novel and effective strategy for the treatment of ischemic stroke, offering broad application prospects in clinical immunotherapy and regenerative medicine.

Forsythia suspensa is a traditional Chinese medicine and a commonly used landscaping plant. Its dried fruit is used in medicine for its functions of clearing heat, removing toxins, reducing swelling, dissipating masses, and dispersing wind and heat. It possesses extremely high medicinal and economic value. However, the genetic differentiation and diversity of its wild populations remain unclear. In this study, chloroplast genome sequences were obtained from 15 wild individuals of F. suspensa using high-throughput sequencing technology. The sequence characteristics and intraspecific variations were analyzed. The results were as follows:(1) The full length of the F. suspensa chloroplast genome ranged from 156 184 to 156 479 bp, comprising a large single-copy region, a small single-copy region, and two inverted repeat regions. The chloroplast genome encoded a total of 132 genes, including 87 protein-coding genes, 37 tRNA genes, and 8 rRNA genes.(2) A total of 166-174 SSR loci, 792 SNV loci, and 63 InDel loci were identified in the F. suspensa chloroplast genome, indicating considerable genetic variation among individuals.(3) Population structure analysis revealed that F. suspensa could be divided into five or six groups. Both the population structure analysis and phylogenetic reconstruction results indicated significant genetic variation within the wild populations of F. suspensa, with no obvious correlation between intraspecific genetic differentiation and geographical distribution. This study provides new insights into the genetic diversity and differentiation within F. suspensa species and offers additional references for the conservation of species diversity and the utilization of germplasm resources in wild F. suspensa.
Genome, Chloroplast ; Forsythia/classification* ; Phylogeny ; Genetic Variation ; Chloroplasts/genetics* ; Microsatellite Repeats

Traditional Chinese medicine(TCM) decoction pieces are a core carrier for the inheritance and innovation of TCM, and their quality and safety are critical to public health and the sustainable development of the industry. Conventional quality control models, while having established a well-developed system through long-term practice, still face challenges such as relatively long inspection cycles, insufficient objectivity in characterizing complex traits, and urgent needs for improving the efficiency of integrating multidimensional quality information when confronted with the dual demands of large-scale production and precision quality control. With the rapid development of artificial intelligence, machine learning can deeply analyze multidimensional data of the morphology, spectroscopy, and chemical fingerprints of decoction pieces by constructing high-dimensional feature space analysis models, significantly improving the standardization level and decision-making efficiency of quality evaluation. This article reviews the research progress in the application of machine learning in the processing, production, and rapid quality evaluation of TCM decoction pieces. It further analyzes current challenges in technological implementation and proposes potential solutions, offering theoretical and technical references to advance the digital and intelligent transformation of the industry.
Machine Learning ; Drugs, Chinese Herbal/standards* ; Quality Control ; Medicine, Chinese Traditional/standards* ; Humans

OBJECTIVE: To precise classify sacral meningeal cysts, effective guide minimally invasive neurosurgery and postoperative personalized rehabilitation by multiple dimensions radiographic reconstruction MRI. METHODS: From March to December 2021, based on the original 3D-fast imaging employing steadystate acquisition (FIESTA) scanning sequence, 92 patients with sacral meningeal cysts were pre-operatively evaluated by multiple dimensional reconstruction MRI. The shape of nerve root and the leakage of cyst were reconstructed according to the direction of nerve root or leakage track showed on original MRI scans. Sacral canal cysts were accurately classified as including nerve root and without nerve root, so as to accurately design the incision of skin and formulate corresponding open range of the posterior wall of the sacral canal. Under the microscope intraoperation, the shape of the nerve roots inside cysts or leakage track of the cysts without nerve roots were verified and explored. After the reinforcement and shaping operation, several reexaminations of multiple dimensional reconstruction MRI were performed to understand the deformation of the nerve root and hydrops in the operation cavity, so as to formulate a persona-lized rehabilitation plan for the patients. RESULTS: Among the 92 patients with sacral mengingeal cyst, 58 (63.0%) cysts with nerve root cyst, 29 (31.5%) cysts without nerve root cyst, and 5 (5.4%) cysts with mixed sacral canal cyst. In 58 patients with nerve root cysts, the accuracy of preoperative clinical classification on MRI image reached 96.6% (56/58) through confirmation by operating microscope. Only 2 cases of large single cyst with nerve root on the head of cyst were mistaken for without nerve root type. In 29 patients with sacral cyst without nerve root, the accuracy of preoperative image reached 100% through confirmation by operating microscope. The accuracy of judging the internal nerve root and leakage of 12 cases with recurrent sacral cyst was also 100%. Two cases of delayed postoperative hydrops were found one month after operation. After rehabilitation treatment by moxibustion and bathing, the hydrops disappeared 4-6 months after operation. CONCLUSION Multiple dimensional reconstruction MRI can precisely make clinical classification of sacral meningeal cysts before operation, guide minimally invasive neurosurgery effectively, and improve the rehabilitation effect.
Humans ; Magnetic Resonance Imaging/methods* ; Male ; Female ; Sacrum/surgery* ; Adult ; Middle Aged ; Imaging, Three-Dimensional/methods* ; Cysts/rehabilitation* ; Aged ; Adolescent ; Young Adult ; Spinal Nerve Roots/diagnostic imaging* ; Minimally Invasive Surgical Procedures ; Neurosurgical Procedures/methods*

OBJECTIVE: To identify the key features of facial and tongue images associated with anemia in female populations, establish anemia risk-screening models, and evaluate their performance. METHODS: A total of 533 female participants (anemic and healthy) were recruited from Shuguang Hospital. Facial and tongue images were collected using the TFDA-1 tongue and face diagnosis instrument. Color and texture features from various parts of facial and tongue images were extracted using Face Diagnosis Analysis System (FDAS) and Tongue Diagnosis Analysis System version 2.0 (TDAS v2.0). Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection. Ten machine learning models and one deep learning model (ResNet50V2 + Conv1D) were developed and evaluated. RESULTS: Anemic women showed lower a-values, higher L- and b-values across all age groups. Texture features analysis showed that women aged 30-39 with anemia had higher angular second moment (ASM)and lower entropy (ENT) values in facial images, while those aged 40-49 had lower contrast (CON), ENT, and MEAN values in tongue images but higher ASM. Anemic women exhibited age-related trends similar to healthy women, with decreasing L-values and increasing a-, b-, and ASM-values. LASSO identified 19 key features from 62. Among classifiers, the Artificial Neural Network (ANN) model achieved the best performance [area under the curve (AUC): 0.849, accuracy: 0.781]. The ResNet50V2 model achieved comparable results [AUC: 0.846, accuracy: 0.818]. CONCLUSION Differences in facial and tongue images suggest that color and texture features can serve as potential TCM phenotype and auxiliary diagnostic indicators for female anemia.
Humans ; Female ; Tongue/diagnostic imaging* ; Adult ; Anemia/diagnosis* ; Middle Aged ; Face/diagnostic imaging* ; Young Adult ; Machine Learning

Haloacetic acids(HAAs),as a class of disinfection byproducts in drinking water,pose potential threats to human health,so the rapid,accurate and simultaneous detection of HAAs is of great significance for ensuring drinking water safety.Aiming at the challenges in HAAs detection and risk analysis,a novel method for synchronous rapid detection of seven kinds of HAAs in drinking water based on in situ derivatization technology and headspace gas chromatography was developed in this study.Through single-factor optimization experiments,the optimal reaction parameters for in situ derivatization were determined,including the type and dosage of salting-out agent,the acidity of reaction system,the amount of phase transfer catalyst,the dosage of derivatization agent,and the extraction solvent volume.Methodologic validation showed that the seven kinds of HAAs exhibited excellent linear relationships within their respective detection concentration ranges(R2>0.998).The method detection limits(MDLs)ranged from 0.04 to 0.33 μg/L,and the limits of quantification(LOQs)were between 0.14 and 1.34 μg/L.For real water samples,the average spiked recoveries of the seven HAAs ranged from 90.9%to 107.7%,with relative standard deviation(RSDs)between 1.55%and 6.49%,and the HAAs contents in all tested samples were below the limits specified in the Standards for Drinking Water Quality(GB 5749-2022)of China.This method was featured with simple operation,fast analysis speed,high sensitivity,and good accuracy,providing an efficient and reliable technical support for routine monitoring of HAAs contaminants in drinking water and showing promising application value for widespread promotion.

Objective:The components of Rubus parvifolius L. were analyzed based on UPLC-MS/MS technology and combined with network pharmacology analysis to explore the mechanism of action of Rubi Parvifolii Radix in treating inflammation, cough, fever, influenza and sore throat. Method:The chemical constituents of Rubi Parvifolii Radix were identified according to the information of mass spectrometry. The network pharmacology was used to analyze the corresponding targets and related pathways of its chemical components, and the "component-target-pathway" interaction diagram was drawn. PyMOL 2.5.7 software wasused to perform molecular docking between active components and key targets.Results:Twenty chemical components were identified by UPLC-MS/MS, and 15 components were screened out by network pharmacology, which can be used as quality markers of Rubi Parvifolii Radix, namely Azelaic acid, Procyanidol B3, Caprolactam, Bis (2-ethylhexyl) adipate, Cryptochlorogenic acid, 3-O-Feruloylquinic, Ellagic acid, Aurantiamide acetate, 2 α,3 β,19 α,23-Tetrahydroxyurs-12-en-28-oic acid, L-Epicatechin, (E)-3-Indoleacrylic acid, Euscaphic acid, Suberic acid, Diisononyl phthalate and Prodelphinidin T4. Molecular docking showed that 5 compounds compared with the reference substance could bind to the target proteins of disease well. Conclusions:The 15 active ingredients in Rubi Parvifolii Radix, including Caprolactam and (E)-3-Indoleacrylic acid, may play a therapeutic role in treating colds, high fever, sore throat, and inflammation by acting on targets such as AKT1 and TNF. This provides a certain reference for the clinical application of Rubi Parvifolii Radix.

Objective:To analyze the extraction, chemical composition, antioxidant, and anti-inflammatory activity of the TCM formula essential oil for the treatment of upper respiratory tract infections (URTI); To provide a scientific basis for its further development.Methods:The formula essential oil was extracted using the steam distillation method and analyzed for chemical composition by gas chromatography-mass spectrometry (GC-MS). The DPPH, ABTS scavenging ability, and hydroxyl radical scavenging ability of volatile oils were measured. The effect of the essential oil on the viability of RAW264.7 cells was assessed using the CCK-8 assay. ELISA and Western blot methods were used to determine the effects of volatile oil on LPS induced inflammatory cytokines IL-6 and TNF-α.Results:The average extraction rate of the formula essential oil was 1.12%, with a density of 0.973 2 g/ml. Twelve main chemical components were identified, with 1,8-cineole (42.9%) and patchoulol (19.9%) being the predominant constituents. The essential oil exhibited DPPH and ABTS radical scavenging capacities of 52% and 59%, respectively, and a hydroxyl radical scavenging capacity exceeding 70%. Essential oil could reduce the levels of IL-6 and TNF-α ( P<0.05). Conclusion:TCM formula essential oil for the treatment of URTI contains multiple bioactive components and demonstrates significant antioxidant and anti-inflammatory effects.