Pulmonary fibrosis（PF） is a progressive and life-threatening disease with limited therapeutic options， highlighting the urgent need for innovative drug discovery strategies. To address this challenge， the authors propose the formula-originated rational intelligent screening&translation（FIRST）， a systematic framework for developing anti-fibrotic monomers derived from classical traditional Chinese medicine（TCM）. The strategy integrates three key dimensions， including tissue-oriented intelligent screening of active compounds， structural optimization based on drug-target spatial interactions and plant biosynthetic pathways， and cross-scale validation of drug. We further highlight its applications in discovering tissue-oriented novel drugs from clinically validated TCM， the development and mechanistic elucidation of anti-fibrotic therapeutics， as well as the clinical translation and secondary development of candidate drugs. This strategy paves the way for first-in-class， formula-derived monomeric drugs with defined structures， clarified mechanisms， and proven safety， offering a transformative avenue to meet the urgent therapeutic needs of PF and setting a new paradigm for TCM-based drug innovation.

Pulmonary fibrosis（PF） is a progressive and life-threatening disease with limited therapeutic options， highlighting the urgent need for innovative drug discovery strategies. To address this challenge， the authors propose the formula-originated rational intelligent screening&translation（FIRST）， a systematic framework for developing anti-fibrotic monomers derived from classical traditional Chinese medicine（TCM）. The strategy integrates three key dimensions， including tissue-oriented intelligent screening of active compounds， structural optimization based on drug-target spatial interactions and plant biosynthetic pathways， and cross-scale validation of drug. We further highlight its applications in discovering tissue-oriented novel drugs from clinically validated TCM， the development and mechanistic elucidation of anti-fibrotic therapeutics， as well as the clinical translation and secondary development of candidate drugs. This strategy paves the way for first-in-class， formula-derived monomeric drugs with defined structures， clarified mechanisms， and proven safety， offering a transformative avenue to meet the urgent therapeutic needs of PF and setting a new paradigm for TCM-based drug innovation.

ObjectiveTo establish the multi-technique characteristic profiles of Alumen by X-ray diffraction（XRD）， Fourier-transform infrared spectroscopy（FTIR） and thermogravimetric-differential thermal analysis（TG-DTA）， and to explore the spectral characteristics for rapid identification of Alumen and its potential adulterant， Ammonium alum. MethodsA total of 27 batches of Alumen samples from 8 production regions were collected for preliminary identification based on visual characteristics. The PDF standard cards of XRD were used to differentiate Alumen from A. alum， and the XRD characteristic profiles of Alumen were established， and then the common peaks were screened. Based on hierarchical clustering analysis（HCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， the characteristic information that could be used for identification of Alumen was selected with variable importance in the projection（VIP） value>1. FTIR characteristic profiles of Alumen were established， and key wavenumbers for identification were screened by HCA and OPLS-DA with VIP value>1. Meanwhile， the thermogravimetric differences between Alumen and A. alum were analyzed by TG-DTA， and the thermogravimetric traits that could be used for identification were screened. ResultsAlumen and A. alum could not be effectively distinguished by traits alone. However， by comparing the PDF standard cards of XRD， 15 batches of Alumen and 12 batches of A. alum could be distinguished. In the XRD profiles， 10 characteristic peaks were confirmed， corresponding to diffraction angles of 14.560°， 24.316°， 12.620°， 32.122°， 17.898°， 34.642°， 27.496°， 46.048°， 40.697° and 21.973°. In the FTIR profiles， 4 wavenumber ranges（399.193-403.050， 1 186.010-1 471.420， 1 801.190-2 620.790， 3 612.020-3 997.710 cm^-1） and 12 characteristic wavenumbers（1 428.994， 1 430.922， 1 432.851， 1 434.779， 1 436.708， 1 438.636， 1 440.565， 1 442.493， 1 444.422， 1 446.350， 1 448.279， 1 450.207 cm^-1） were identified. In the TG-DTA profiles， there were characteristic decomposition peaks of ammonium ion and mass reduction features near 555.34 ℃ for A. alum. These characteristics could serve as important criteria for distinguishing the authenticity of Alumen. ConclusionXRD， FTIR and TG-DTA can be used to rapidly detect Alumen and A. alum， and combined with the discriminant features selected through chemometrics， the rapid and accurate identification of Alumen and A. alum can be achieved. The research findings provide new approaches for the rapid identification of Alumen.

ObjectiveTo establish the multi-technique characteristic profiles of Alumen by X-ray diffraction（XRD）， Fourier-transform infrared spectroscopy（FTIR） and thermogravimetric-differential thermal analysis（TG-DTA）， and to explore the spectral characteristics for rapid identification of Alumen and its potential adulterant， Ammonium alum. MethodsA total of 27 batches of Alumen samples from 8 production regions were collected for preliminary identification based on visual characteristics. The PDF standard cards of XRD were used to differentiate Alumen from A. alum， and the XRD characteristic profiles of Alumen were established， and then the common peaks were screened. Based on hierarchical clustering analysis（HCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， the characteristic information that could be used for identification of Alumen was selected with variable importance in the projection（VIP） value>1. FTIR characteristic profiles of Alumen were established， and key wavenumbers for identification were screened by HCA and OPLS-DA with VIP value>1. Meanwhile， the thermogravimetric differences between Alumen and A. alum were analyzed by TG-DTA， and the thermogravimetric traits that could be used for identification were screened. ResultsAlumen and A. alum could not be effectively distinguished by traits alone. However， by comparing the PDF standard cards of XRD， 15 batches of Alumen and 12 batches of A. alum could be distinguished. In the XRD profiles， 10 characteristic peaks were confirmed， corresponding to diffraction angles of 14.560°， 24.316°， 12.620°， 32.122°， 17.898°， 34.642°， 27.496°， 46.048°， 40.697° and 21.973°. In the FTIR profiles， 4 wavenumber ranges（399.193-403.050， 1 186.010-1 471.420， 1 801.190-2 620.790， 3 612.020-3 997.710 cm^-1） and 12 characteristic wavenumbers（1 428.994， 1 430.922， 1 432.851， 1 434.779， 1 436.708， 1 438.636， 1 440.565， 1 442.493， 1 444.422， 1 446.350， 1 448.279， 1 450.207 cm^-1） were identified. In the TG-DTA profiles， there were characteristic decomposition peaks of ammonium ion and mass reduction features near 555.34 ℃ for A. alum. These characteristics could serve as important criteria for distinguishing the authenticity of Alumen. ConclusionXRD， FTIR and TG-DTA can be used to rapidly detect Alumen and A. alum， and combined with the discriminant features selected through chemometrics， the rapid and accurate identification of Alumen and A. alum can be achieved. The research findings provide new approaches for the rapid identification of Alumen.

Traditional Chinese Medicine (TCM), as a treasure of the Chinese nation, plays a significant role in maintaining public health. In 2019, the Central Committee of the Communist Party of China and the State Council proposed for the first time the establishment of a TCM registration and evaluation evidence system that integrates TCM theory, "personal experience" and clinical trials (referred to as the "Three-in-One" System) to promote the inheritance and innovation of TCM. Subsequently, the National Medical Products Administration issued several guiding principles to advance the improvement and implementation of this system. Owing to the complexity of its implementation, there are still differing understandings within the TCM industry regarding the positioning of the "Three-in-One" Registration and Evaluation Evidence System, as well as the connotation and value orientation of the "personal experience." To address this, Academician WANG Qi, President of the TCM Association, China International Exchange and Promotion Association for Medical and Healthcare and TCM master, led a group of academicians, TCM masters, TCM pharmacology experts and clinical TCM experts to convene a "Seminar on Promoting the Implementation of the ′Three-in-One′ Registration and Evaluation Evidence System for Chinese Medicinals." Through extensive discussions, an expert consensus was formed, clarifying the different roles of the TCM theory, "personal experience" and clinical trials within the system. It was further emphasized that the "personal experience" is the core of this system, and its data should be derived from clinical practice scenarios. In the future, the improvement of this system will require collaborative efforts across multiple fields to promote the high-quality development of the Chinese medicinal industry.

OBJECTIVE: To observe the clinical efficacy of acupuncture combined with thunder-fire moxibustion in treating low back pain with cold-damp. METHODS: Seventy-two patients of low back pain with cold-damp were randomly divided into an observation group (36 cases, 1 case was eliminated) and a control group (36 cases, 1 case dropped out). The control group received acupuncture at Jizhong (GV6), Yaoyangguan (GV3), ashi points, bilateral Shenshu (BL23), Dachangshu (BL25), and Weizhong (BL40) for 30 min daily. The observation group was treated with thunder-fire moxibustion in addition to the same acupuncture regimen as the control group, once daily. Both groups were treated for 6 consecutive days followed by one rest day, for a total duration of 4 weeks. The visual analog scale (VAS) score, Oswestry disability index (ODI) score, Japanese Orthopedic Association (JOA) score, present pain intensity (PPI) score, and serum levels of β-endorphin (β-EP), 5-hydroxytryp tamin (5-HT), and substance P (SP) were compared before and after treatment, and the clinical efficacy was also compared between the two groups. RESULTS: Compared before treatment, the VAS scores, ODI scores, PPI scores, and serum levels of 5-HT and SP were decreased (P<0.01), while JOA scores and serum levels of β-EP were increased (P<0.01) in both groups after treatment. The observation group showed lower VAS, ODI, and PPI scores and serum levels of 5-HT and SP than those in the control group (P<0.05), as well as higher JOA score and serum level of β-EP (P<0.05). The total effective rate in the observation group was 94.3% (33/35), higher than 82.9% (29/35) in the control group (P<0.05). CONCLUSION Acupuncture combined with thunder-fire moxibustion could effectively alleviate pain and improve lumbar function in patients of low back pain with cold-damp, possibly by regulating β-EP, 5-HT, and SP levels.
Humans ; Moxibustion ; Low Back Pain/blood* ; Male ; Female ; Adult ; Middle Aged ; Acupuncture Therapy ; Acupuncture Points ; Treatment Outcome ; Combined Modality Therapy ; beta-Endorphin/blood* ; Young Adult ; Aged

The glucagon receptor (GCGR) is a critical target for the treatment of metabolic disorders such as Type 2 Diabetes Mellitus (T2DM) and obesity. Activation of GCGR enhances systemic insulin sensitivity through paracrine stimulation of insulin secretion, presenting a promising avenue for treatment. However, the discovery of effective GCGR agonists remains a challenging and resource-intensive process, often requiring time-consuming wet-lab experiments to synthesize and screen potential compounds. Recent advances in artificial intelligence technologies have demonstrated great potential in accelerating drug discovery by streamlining screening and efficiently predicting bioactivity. In the present work, we propose DeepGCGR, a two-layer deep learning model that leverages graph convolutional networks (GCN) integrated with a multiple attention mechanism to expedite the identification of GCGR agonists. In the first layer, the model predicts the bioactivity of various compounds against GCGR, efficiently filtering large chemical libraries to identify promising candidates. In the second layer, DeepGCGR classifies high bioactive compounds based on their functional effects on GCGR signaling, identifying those with potential agonistic or antagonistic effects. Moreover, DeepGCGR was specifically applied to identify novel GCGR-regulating compounds for the treatment of T2DM from natural products derived from traditional Chinese medicine (TCM). The proposed method will not only offer an effective strategy for discovering GCGR-targeting compounds with functional activation properties but also provide new insights into the development of T2DM therapeutics.
Deep Learning ; Drug Discovery/methods* ; Humans ; Diabetes Mellitus, Type 2/metabolism* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/pharmacology*

Glioblastoma (GBM) is a highly aggressive primary brain tumor characterized by poor prognosis. Conventional chemo-radiotherapy demonstrates limited therapeutic efficacy and is often accompanied by significant side effects, largely due to factors such as drug resistance, radiation resistance, the presence of the blood-brain barrier (BBB), and the activation of DNA damage repair mechanisms. There is a pressing need to enhance treatment efficacy, with BRD4 identified as a promising target for increasing GBM sensitivity to therapy. Lacking small molecule inhibitors, BRD4 can be degraded using PROteolysis Targeting Chimera (PROTAC), thereby inhibiting DNA damage repair. To deliver PROTAC, SIAIS171142 (SIS) effectively, we designed a responsive nanocapsule, MPL_(SS)P@SIS, featuring GBM-targeting and GSH-responsive drug release. Modified with 1-methyl-l-tryptophan (MLT), nanocapsules facilitate targeted delivery of SIS, downregulating BRD4 and sensitizing GBM cells to radiotherapy and chemotherapy. After intravenous administration, MPL_(SS)P@SIS selectively accumulates in tumor tissue, enhancing the effects of radiotherapy and temozolomide (TMZ) by increasing DNA damage and oxidative stress. GSH activates the nanocapsules, triggering BRD4 degradation and hindering DNA repair. In mouse models, the nanosensitizer, combined with TMZ and X-ray irradiation, efficiently inhibited the growth of GBM. These findings demonstrate a novel PROTAC-based sensitization strategy targeting BRD4, offering a promising approach for effective GBM therapy.

OBJECTIVE: Rhei Radix et Rhizoma has five types of products, namely, raw rhubarb (RR), wine rhubarb (WR), vinegar rhubarb (VR), cooked rhubarb (CR), and rhubarb charcoal (RC). However, Rhei Radix et Rhizoma is easily contaminated with fungi and mycotoxins if not harvested or processed properly. Here, we intend to analyze how microbiome assemblies and co-occurrence patterns are influenced by sampling locations and processing methods. METHODS: High-throughput sequencing and internal transcribed spacer 2 (ITS2) were carried out to study the diversities (α- and β-diversity), composition (dominant taxa and potential biomarkers), and network complexitity of surface fungi on RR, WR, VR, CR, and RC collected from Gansu and Sichuan provinces, China. RESULTS: The phyla Ascomycota and Basidiomycota; the genera Kazachstania, Malassezia, and Asterotremella; and the species Kazachstania exigua, Asterotremella pseudolonga, and Malassezia restricta were the dominant fungi and exhibited differences in the two provinces and the five processed products. The α-diversity and network complexity were strongly dependent on processing methods. Chao 1, the Shannon index, and network complexity and connectivity were highest in the CR group. The α-diversity and network complexity were influenced by sampling locations. Chao 1 and network complexity and connectivity were highest in the Gansu Province. CONCLUSION The assembly and network of the surface microbiome on Rhei Radix et Rhizoma were shaped by processing methods and sampling locations. This paper offers a comprehensive understanding of microorganisms, which can provide early warning for potential mycotoxins and ensure the safety of drugs and consumers.