Cancer remains a leading cause of global mortality, necessitating the development of advanced therapeutic strategies with enhanced efficacy and reduced systemic toxicity. Among promising bioactive agents, lactoferrin (LF)—a multifunctional iron-binding glycoprotein abundantly found in mammalian milk and exocrine secretions—has garnered significant interest for its potent and multifaceted anti-cancer properties. This review provides a comprehensive analysis of the current understanding of LF’s role in oncology, encompassing its structural biology, diverse mechanisms of action, and groundbreaking advancements in its application through nano-engineering. LF exerts anti-tumor effects through multiple pathways, including extracellular action, intracellular action, and immune regulation. It demonstrates a remarkable affinity for cancer cell membranes, binding to overexpressed anionic components such as glycosaminoglycans and sialic acids, as well as to specific receptors including the low-density lipoprotein receptor-related protein-1 (LRP-1). This selective binding facilitates targeted uptake. Upon internalization, LF orchestrates a direct assault by inducing cell-cycle arrest in phases such as G0/G1 or S phase through the modulation of key regulators including cyclins, CDKs, and p53. Furthermore, it promotes programmed cell death via apoptotic pathways, involving caspase activation and downregulation of anti-apoptotic proteins such as survivin. A more recently elucidated mechanism is the induction of ferroptosis, an iron-dependent form of cell death characterized by overwhelming lipid peroxidation. Beyond direct cytotoxicity, LF acts as a potent immunomodulator. It enhances natural killer (NK) cell activity, modulates T-lymphocyte populations, and crucially reprograms tumor-associated macrophages (TAMs) from a pro-tumor M2 state to an anti-tumor M1 state, thereby reversing the immunosuppressive tumor microenvironment (TME). The translation of LF’s potential has been significantly accelerated by nanotechnology. The inherent biocompatibility and natural tumor-targeting capabilities of LF make it an ideal platform for sophisticated drug-delivery systems. This review details various fabrication strategies for LF-based nanoparticles (NPs), including self-assembly, sol-in-oil emulsion, and electrostatic nanocomplexes, among others. Research demonstrates that nano-formulations not only protect LF from degradation but also enhance its bioactivity and anti-cancer potency. More importantly, LF NPs serve as versatile carriers for a wide array of therapeutic agents, including conventional chemotherapeutics, natural compounds, and imaging agents. These engineered systems enable synergistic therapy and facilitate site-specific delivery. Notably, the ability of LF to bind to receptors on the blood-brain barrier (BBB) has been leveraged to develop nano-systems for glioblastoma treatment. Other innovative designs utilize LF to modulate the TME—for instance, by alleviating tumor hypoxia to sensitize cells to radiotherapy and chemotherapy. Despite compelling pre-clinical evidence, the clinical translation of LF and its nano-formulations remains nascent. While early-phase trials have established a favorable safety profile for recombinant human LF, larger Phase III studies have yielded mixed results, underscoring the complexity of its action in humans. Key challenges include enhancing drug targeting, optimizing loading efficiency, ensuring batch-to-batch reproducibility, and achieving deep tumor penetration. Future research must focus on the rational design of next-generation LF-NPs. This entails developing standardized manufacturing protocols, engineering “smart” stimuli-responsive systems for targeted drug release in the TME, and constructing multi-targeting platforms. A concerted interdisciplinary effort is paramount to bridge the gap between bench and bedside. In conclusion, LF, particularly in its nano-engineered forms, represents a highly promising and versatile agent in the oncological arsenal, holding immense potential for precise and effective cancer therapy.

Cancer remains a leading cause of global mortality, necessitating the development of advanced therapeutic strategies with enhanced efficacy and reduced systemic toxicity. Among promising bioactive agents, lactoferrin (LF)—a multifunctional iron-binding glycoprotein abundantly found in mammalian milk and exocrine secretions—has garnered significant interest for its potent and multifaceted anti-cancer properties. This review provides a comprehensive analysis of the current understanding of LF’s role in oncology, encompassing its structural biology, diverse mechanisms of action, and groundbreaking advancements in its application through nano-engineering. LF exerts anti-tumor effects through multiple pathways, including extracellular action, intracellular action, and immune regulation. It demonstrates a remarkable affinity for cancer cell membranes, binding to overexpressed anionic components such as glycosaminoglycans and sialic acids, as well as to specific receptors including the low-density lipoprotein receptor-related protein-1 (LRP-1). This selective binding facilitates targeted uptake. Upon internalization, LF orchestrates a direct assault by inducing cell-cycle arrest in phases such as G0/G1 or S phase through the modulation of key regulators including cyclins, CDKs, and p53. Furthermore, it promotes programmed cell death via apoptotic pathways, involving caspase activation and downregulation of anti-apoptotic proteins such as survivin. A more recently elucidated mechanism is the induction of ferroptosis, an iron-dependent form of cell death characterized by overwhelming lipid peroxidation. Beyond direct cytotoxicity, LF acts as a potent immunomodulator. It enhances natural killer (NK) cell activity, modulates T-lymphocyte populations, and crucially reprograms tumor-associated macrophages (TAMs) from a pro-tumor M2 state to an anti-tumor M1 state, thereby reversing the immunosuppressive tumor microenvironment (TME). The translation of LF’s potential has been significantly accelerated by nanotechnology. The inherent biocompatibility and natural tumor-targeting capabilities of LF make it an ideal platform for sophisticated drug-delivery systems. This review details various fabrication strategies for LF-based nanoparticles (NPs), including self-assembly, sol-in-oil emulsion, and electrostatic nanocomplexes, among others. Research demonstrates that nano-formulations not only protect LF from degradation but also enhance its bioactivity and anti-cancer potency. More importantly, LF NPs serve as versatile carriers for a wide array of therapeutic agents, including conventional chemotherapeutics, natural compounds, and imaging agents. These engineered systems enable synergistic therapy and facilitate site-specific delivery. Notably, the ability of LF to bind to receptors on the blood-brain barrier (BBB) has been leveraged to develop nano-systems for glioblastoma treatment. Other innovative designs utilize LF to modulate the TME—for instance, by alleviating tumor hypoxia to sensitize cells to radiotherapy and chemotherapy. Despite compelling pre-clinical evidence, the clinical translation of LF and its nano-formulations remains nascent. While early-phase trials have established a favorable safety profile for recombinant human LF, larger Phase III studies have yielded mixed results, underscoring the complexity of its action in humans. Key challenges include enhancing drug targeting, optimizing loading efficiency, ensuring batch-to-batch reproducibility, and achieving deep tumor penetration. Future research must focus on the rational design of next-generation LF-NPs. This entails developing standardized manufacturing protocols, engineering “smart” stimuli-responsive systems for targeted drug release in the TME, and constructing multi-targeting platforms. A concerted interdisciplinary effort is paramount to bridge the gap between bench and bedside. In conclusion, LF, particularly in its nano-engineered forms, represents a highly promising and versatile agent in the oncological arsenal, holding immense potential for precise and effective cancer therapy.

The Type III Secretion System (T3SS) serves as a pivotal virulence apparatus for numerous Gram-negative bacterial pathogens, enabling them to infect both animal and plant hosts. Functioning as a molecular syringe, the T3SS directly translocates bacterial effector proteins from the bacterial cytoplasm into the interior of eukaryotic host cells. These effectors are central weapons that precisely manipulate a wide spectrum of host cellular physiological processes, ranging from cytoskeletal dynamics to immune signaling, to establish a favorable niche for bacterial survival and proliferation. Among the diverse arsenal of T3SS effectors, the YopJ family constitutes a critical group of virulence factors. Members of this family are characterized by a conserved catalytic triad structure—a hallmark of the CE clan of cysteine proteases that has been evolutionarily repurposed to confer acetyltransferase activity. A defining and intriguing feature of these enzymes is their stringent dependence on a host-derived eukaryotic cofactor, inositol hexakisphosphate (IP₆), for allosteric activation. This requirement acts as a sophisticated molecular safeguard, ensuring enzymatic activity only within the appropriate host environment, thereby preventing detrimental effects on the bacterium itself. While seminal studies on individual members such as Yersinia’s YopJ and Salmonella’s AvrA have provided deep mechanistic insights, a systematic and integrative understanding of the structure-function relationships across the entire family remains fragmented. Key questions persist regarding how a conserved catalytic core has diverged to recognize distinct host substrates in different kingdoms of life. To address this gap, this article provides a systematic review of the YopJ family, focusing on three interconnected aspects: their structural features, their catalytic mechanism, and their divergent immunosuppressive strategies in animal versus plant hosts. By conducting a comparative analysis of the sequences and resolved three-dimensional structures of three representative members (e.g., HopZ1a, PopP2, AvrA), we elucidate regions of significant variation embedded within the conserved core catalytic architecture. These variable regions, often involving surface loops and substrate-binding interfaces, are crucial determinants of target specificity and functional specialization. The functional divergence of this effector family is most apparent when comparing their modes of action in different hosts. In animal hosts, YopJ-family effectors primarily sabotage innate immune signaling pathways. They achieve this by acetylating key serine and threonine residues within the activation loops of critical kinases in the MAPK and NF‑κB pathways. This post-translational modification blocks the phosphorylation and subsequent activation of these kinases, leading to potent suppression of inflammatory cytokine production. Conversely, in plant hosts, the strategy broadens to dismantle the two-tiered plant immune system. YopJ homologs target a more diverse set of substrates, including immune-associated receptor-like cytoplasmic kinases (RLCKs), microtubule networks via tubulin acetylation (which disrupts cellular trafficking and signaling), and transcription factors central to defense gene regulation. This multi-target approach effectively suppresses both Pattern-Triggered Immunity (PTI) and Effector-Triggered Immunity (ETI). In conclusion, this synthesis aims to deepen the mechanistic understanding of YopJ family-mediated pathogenesis by integrating structural biology with cellular function across host kingdoms. Elucidating the precise molecular basis for substrate selection—how conserved platforms achieve target diversity—is a major frontier. Furthermore, this knowledge provides a vital theoretical foundation for developing novel anti-virulence strategies. Targeting the conserved IP₆-binding pocket or the catalytic acetyltransferase activity itself represents a promising avenue for designing broad-spectrum inhibitors that could disarm this critical family of bacterial effectors, potentially offering new therapeutic approaches against a range of pathogenic bacteria.

Renal fibrosis is the common pathological endpoint of many forms of chronic kidney disease (CKD), yet the mechanisms determining effective repair versus persistent fibrotic remodeling remain incompletely understood. Peritubular capillaries (PTCs) are not merely passive targets of fibrotic injury, but form a dynamic vascular microenvironment linking regional perfusion, oxygen delivery, tubular metabolism, endothelial barrier integrity, pericyte support, immune-cell trafficking, and extracellular matrix (ECM) remodeling. We propose that PTC abnormalities should not be interpreted simply as reduced capillary density, but as a multidimensional disturbance of microvascular structure and function. Structural vascular preservation does not necessarily indicate effective microcirculation: anatomically detectable capillaries may still exhibit impaired perfusion, barrier dysfunction, abnormal endothelial-pericyte interactions, disturbed oxygen metabolism, or reduced network connectivity. Conversely, increased angiogenesis does not necessarily signify successful vascular repair if vessels remain immature, poorly perfused, or inadequately integrated into the existing network. To organize these abnormalities, we conceptualize PTC remodeling into four predominant but nonexclusive states: endothelial barrier disruption with inflammatory adhesion; endothelial-pericyte uncoupling with no-reflow; dysregulated angiogenesis with network simplification; and capillary rarefaction with fibrotic matrix locking. These states are not sequential stages of CKD. They may coexist within the same kidney, overlap within the same anatomical region, and vary with disease etiology, injury phase, vascular compartment, and treatment exposure. We further propose six dimensions for evaluating PTC status—structural presence, functional perfusion, barrier integrity, pericyte coupling, oxygen metabolism, and network connectivity—so that vascular quantity, function, and reparative capacity are assessed separately rather than inferred from a single endothelial marker or capillary-density measurement. Mechanistically, these states converge on a bidirectional microvascular-fibrotic feedback loop. Barrier disruption facilitates leukocyte recruitment and alters vascular paracrine signaling. Endothelial-pericyte uncoupling compromises capillary stability, whereas abnormal pericyte contraction may increase local vascular resistance and contribute to no-reflow before overt capillary loss. Dysregulated angiogenesis may generate vessels that fail to mature or connect to an effective perfusion network. Progressive capillary rarefaction compromises oxygen delivery, while sustained tubular transport demand and mitochondrial dysfunction may aggravate regional oxygen supply-demand mismatch. Injured tubules, immune cells, endothelial cells, pericytes, and fibroblasts communicate through soluble mediators, extracellular vesicles, direct cell contact, and cell-matrix signaling. Importantly, fibrosis is not merely a downstream consequence of microvascular injury. Altered ECM may increase diffusion distance, modify mechanotransduction, impair endothelial survival and migration, and restrict capillary reopening and regeneration. We use the term matrix locking to describe this sustained constraint on vascular repair, while emphasizing that current evidence does not establish irreversible disease in humans. This framework also has therapeutic implications. PTC-directed treatment should not be reduced to increasing vessel number or uniformly promoting angiogenesis. Instead, intervention should be matched to the dominant and potentially reversible abnormality: preserving endothelial barrier function; restoring endothelial-pericyte stability and reducing pathological microvascular resistance; normalizing angiogenesis so that vascular growth is accompanied by maturation, barrier competence, network integration, and effective perfusion; and, in advanced rarefaction, relieving matrix-related constraints while supporting vascular regeneration. The context- and time-dependent effects of signaling through VEGF, Tie2, PDGF-B/PDGFRβ, eNOS/NO, and related pathways indicate that the same molecular signal may exert different effects depending on disease context and timing. Therapeutic efficacy should therefore be evaluated by restoration of effective microcirculation and tissue function rather than by isolated molecular changes or capillary counts alone. Despite increasing mechanistic evidence, the translational basis for this framework remains limited. Most causal and interventional data derive from animal or cell models, whereas human evidence is largely limited to pathological observations, patient-sample associations, and prognostic studies. Currently available circulating and urinary candidate biomarkers generally lack sufficient specificity for PTC injury or state assignment, and no standardized quantitative thresholds have been externally validated. The four-state model should therefore be regarded as a hypothesis-generating analytical framework rather than a clinicopathological classification system. Future studies should integrate spatially resolved tissue phenotyping, blood and urine biomarkers, and dynamic microcirculatory assessment in longitudinal cohorts. They should test reproducibility, assess prognostic value beyond conventional pathology, estimated glomerular filtration rate, and proteinuria, and determine whether changes in PTC status precede or mediate therapeutic benefit. Linking reproducible microvascular phenotypes to defined mechanisms, treatment response, and long-term renal outcomes will be essential to determine whether state-directed assessment and restoration of the PTC microenvironment can ultimately inform patient stratification and therapeutic decision-making.

Objective: To analyze the spatial-temporal clustering characteristics of pulmonary tuberculosis (PTB) in Zhangjiajie City, Hunan Province from 2016 to 2024, so as to provide a basis for formulating regional PTB prevention and control strategies. Methods: Data of reported PTB cases in Zhangjiajie City from 2016 to 2024 were collected from the Tuberculosis Surveillance System of China Disease Prevention and Control Information System, and the reported incidence of PTB was analyzed. Joinpoint regression model was used to analyze the trend in reported incidence of PTB from 2016 to 2024. With township (subdistrict) as the basic spatial unit, global and local spatial autocorrelation and hotspot analysis were used to analyze the spatial distribution characteristics of PTB, and spatial-temporal scan analysis was used to identify spatial-temporal clustering characteristics. Results: A total of 14 176 PTB cases were reported in Zhangjiajie City from 2016 to 2024, with an average annual reported incidence of 104.42/105, showing an overall downward trend (AAPC=-5.005%, P<0.05). Global spatial autocorrelation analysis showed that except for 2021-2022, the reported incidence of PTB showed positive spatial correlation in other years, with Moran's I values ranging from 0.134 to 0.306 (all P<0.05). Local spatial autocorrelation analysis and hotspot analysis showed that high-high clusters and hotspot areas from 2016 to 2024 were concentrated in Badagongshan Town, Longtanping Town, Chenjiahe Town, Shanghexi Township, and Liaojiacun Township of Sangzhi County, and Yinjiaxi Township and Luoshui Township of Yongding District. Spatial-temporal scan analysis showed that Class Ⅰ cluster was located in the northwest, centered on Badagongshan Town, covering 13 townships in Sangzhi County, with clustering period spanning from 2017 to 2020. The Class Ⅱ cluster was located in the southwest, centered on Maoyanhe Town, covering 7 townships in Yongding District, with clustering period spanning from 2020 to 2023. Conclusions The reported incidence of PTB in Zhangjiajie City from 2016 to 2024 showed an overall downward trend. The spatial-temporal clusters shifted from the northwest of Sangzhi County to the southwest of Yongding District.

This study aims to investigate the effects and mechanisms of the effective-compounds of Jinshui Huanxian formula (ECC-JHF) in improving pulmonary fibrosis. Animal experiments were approved by the Ethics Committee of the Animal Experiment Center of Henan University of Chinese Medicine (approval number: IACUC-202306012). The mouse model of pulmonary fibrosis was induced using bleomycin (BLM). Hematoxylin-eosin (H&E) staining was used to detect the histopathological changes of lung tissues. Masson staining was used to assess the degree of fibrosis in lung tissues. Immunofluorescence (IF) and real-time quantitative PCR (qPCR) were performed to measure the expression of collagen type I (COL I), α-smooth muscle actin (α-SMA), fibronectin (FN), interleukin (IL)-1β, IL-6, and tumor necrosis factor α (TNF-α) in lung tissues. Flow cytometry (FCM) was employed to detect the proportion of M1 and M2 macrophages in the bronchoalveolar lavage fluid (BALF) of mice. IF and qPCR were also used to detect the expression of lipase family member N (LIPN) in lung tissues. Free fatty acid assay kit was used to detect the level of free fatty acids in lung tissue. Bone marrow-derived macrophages (BMDMs) were treated with interleukin-4 (IL-4) to induce M2 polarization. FCM was used to measure the proportion of CD206⁺ M2 macrophages. IF was utilized to detect LIPN expression and lipid droplet decomposition. The results showed that in BLM-induced pulmonary fibrosis mice, ECC-JHF significantly attenuated BLM-induced alveolar inflammation and collagen deposition, inhibited fibroblast activation in lung tissues, and decreased the proportion of M2 macrophages in BALF. It also significantly suppressed LIPN expression and free fatty acid level in lung tissues. In the IL-4 induced BMDMs M2 polarization model, ECC-JHF significantly inhibited the proportion of CD206⁺ M2 macrophages, down-regulated the expression of LIPN, and blocked lipid droplet catabolism. These results suggest that ECC-JHF may alleviate bleomycin-induced pulmonary fibrosis by inhibiting lipid droplet decomposition and M2 macrophage polarization.

The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

ObjectiveTo investigate the influence of histone deacetylase 3 (HDAC3) on the occurrence, development of psoriasis-like inflammation in mice, and the relative immune mechanisms. MethodsHealthy C57BL/6 mice aged 6-8 weeks were selected and randomly divided into 3 groups: control group (Control), psoriasis model group (IMQ), and HDAC3 inhibitor RGFP966-treated psoriasis model group (IMQ+RGFP966). One day prior to the experiment, the back hair of the mice was shaved. After a one-day stabilization period, the mice in Control group was treated with an equal amount of vaseline, while the mice in IMQ group was treated with imiquimod (62.5 mg/d) applied topically on the back to establish a psoriasis-like inflammation model. The mice in IMQ+RGFP966 group received intervention with a high dose of the HDAC3-selective inhibitor RGFP966 (30 mg/kg) based on the psoriasis-like model. All groups were treated continuously for 5 d, during which psoriasis-like inflammation symptoms (scaling, erythema, skin thickness), body weight, and mental status were observed and recorded, with photographs taken for documentation. After euthanasia, hematoxylin-eosin (HE) staining was used to assess the effect of RGFP966 on the skin tissue structure of the mice, and skin thickness was measured. The mRNA and protein expression levels of HDAC3 in skin tissues were detected using reverse transcription real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot (WB), respectively. Flow cytometry was employed to analyze neutrophils in peripheral blood and lymph nodes, CD4⁺ T lymphocytes, CD8⁺ T lymphocytes in peripheral blood, and IL-17A secretion by peripheral blood CD4⁺ T lymphocytes. Additionally, spleen CD4⁺ T lymphocyte expression of HDAC3, CCR6, CCR8, and IL-17A secretion levels were analyzed. Immunohistochemistry was used to detect the localization and expression levels of HDAC3, IL-17A, and IL-10 in skin tissues. ResultsCompared with the Control group, the IMQ group exhibited significant psoriasis-like inflammation, characterized by erythema, scaling, and skin wrinkling. Compared with the IMQ group, RGFP966 exacerbated psoriasis-like inflammatory symptoms, leading to increased hyperkeratosis. The psoriasis area and severity index (PASI) skin symptom scores were higher in the IMQ group than those in the Control group, and the scores were further elevated in the IMQ+RGFP966 group compared to the IMQ group. Skin thickness measurements showed a trend of IMQ+RGFP966>IMQ>Control. The numbers of neutrophils in the blood and lymph nodes increased sequentially in the Control, IMQ, and IMQ+RGFP966 groups, with a similar trend observed for CD4⁺ and CD8⁺ T lymphocytes in the blood. In skin tissues, compared with the Control group, the mRNA and protein levels of HDAC3 decreased in the IMQ group, but RGFP966 did not further reduce these expressions. HDAC3 was primarily located in the nucleus. Compared with the Control group, the nuclear HDAC3 content decreased in the skin tissues of the IMQ group, and RGFP966 further reduced nuclear HDAC3. Compared with the Control and IMQ groups, RGFP966 treatment decreased HDAC3 expression in splenic CD4⁺ and CD8⁺ T cells. RGFP966 treatment increased the expression of CCR6 and CCR8 in splenic CD4⁺ T cells and enhanced IL-17A secretion by peripheral blood and splenic CD4⁺ T lymphocytes. Additionally, compared with the IMQ group, RGFP966 reduced IL-10 protein levels and upregulated IL-17A expression in skin tissues. ConclusionRGFP966 exacerbates psoriatic-like inflammatory responses by inhibiting HDAC3, increasing the secretion of the cytokine IL-17A, and upregulating the expression of chemokines CCR8 and CCR6.

In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Machine Learning ; Algorithms ; Humans ; Quality Control

To clarify the occurrence and distribution of broad bean wilt virus 2(BBWV2) on Rehmannia glutinosa, this study collected 87 R. glutinosa samples with typical symptoms of viral disease such as chlorosis and crumple from Wenxian county and Wuzhi county in Jiaozuo city, Henan province and Qiaocheng district in Bozhou city, Anhui province. The BBWV2 CP target band was amplified from 37 R. glutinosa samples by RT-PCR technology. The total detection rate reached 42.5%, among which 43.0% was detected in samples from Henan province. The detection rate in samples from Anhui province was 37.5%. 37 BBWV2 CP sequences were obtained by cloning and sequencing of BBWV2 positive samples(data has been submitted to GenBank, accession numbers: PP407959-PP407995), and the sequence analysis of these CP sequences with 91 other BBWV2 isolates in GenBank showed a high genetic diversity with a consistency rate of 70.8%-100%. Meanwhile, phylogenetic analysis showed that BBWV2 could be divided into three groups according to CP sequences, among which the BBWV2 in R. glutinosa isolates obtained in this study were all located in group 3. This study identified the differences in the occurrence, distribution, and genetic diversity of BBWV2 in R. glutinosa from Henan province and Anhui province and provided a theoretical basis for the prevention and control of BBWV2.
Rehmannia/virology* ; Phylogeny ; Plant Diseases/virology* ; China ; Molecular Sequence Data ; Fabavirus/classification*