Objective: To improve the efficiency and standardization of preoperative anemia diagnosis and treatment by establishing a systematic intelligent management platform for preoperative anemia. Methods: A multidisciplinary collaborative model was adopted to develop a preoperative anemia management system that integrates intelligent early warning, standardized treatment pathways, and quality control. The system utilizes natural language processing technology to automatically capture laboratory data and establish evidence-based medical decision support functions. A pre-post study design was employed to compare changes in preoperative anemia screening rates, preoperative anemia intervention rates, reasonable use of iron supplements, and perioperative red blood cell transfusion rates before and after system implementation. Results: After system implementation, the standardization of anemia diagnosis and treatment significantly improved: 1) Screening effectiveness: The anemia screening rate increased to 50.00% (an increase of 27.24%); 2) Intervention effectiveness: The anemia treatment rate rose to 56.30% (an increase of 14.02%); 3) Treatment standardization: The reasonable use rate of iron supplements increased to 55.33% (an increase of 21.02%); the red blood cell transfusion rate decreased to 18.29% (a decrease of 4.07%), and the amount of red blood cell transfusions was reduced by 291 units. Conclusion: This system achieves full-process management of preoperative anemia through information technology, significantly enhancing the standardization of diagnosis and treatment as well as intervention effectiveness, providing an effective solution for perioperative anemia management.

By systematically combing ancient and modern literature， this paper examined Tribuli Fructus and Astragali Complanati Semen（ACS） used in the famous classical formulas from the aspects of name， origin， production area， harvesting and processing， clinical efficacy， so as to provide a basis for the development of famous classical formulas containing such medicinal materials. The results showed that the names of Tribuli Fructus in the past dynasties were mostly derived from its morphology， and there were nicknames such as Baijili， Cijili and Dujili. The name of ACS in the past dynasties were mostly originated from its production areas， and there were nicknames such as Baijili， Shayuan Jili and Tongjili. Because both of them had the name of Baijili， confusion began to appear in the Song dynasty. In ancient and modern times， the main origin of Tribuli Fructus were Tribulus terrestris， and ancient literature recorded the genuine producing areas of Tribuli Fructus was Dali in Shaanxi and Tianshui in Gansu， but today it is mainly cultivated in Anhui and Shandong. The fruit is the medicinal part， harvested in autumn throughout history. There is no description of the quality of Tribuli Fructus in ancient times， and the plump， firm texture， grayish-white color is the best in modern times. Traditional processing methods for Tribuli Fructus included stir-frying and wine processing， while modern commonly used is purified， fried and salt-processed. The ancient records of Tribuli Fructus were spicy， bitter， and warm in nature， with modern research adding that it is slightly toxic. The main effects of ancient and modern times include treating wind disorders， improving vision， promoting muscle growth， and treating vitiligo. The mainstream base of ACS used throughout history is Astragalus complanatus. Ancient texts indicated ACS primarily originated from Shaanxi province. Today， the finest varieties come from Tongguan and Dali in Shaanxi. The medicinal part is the seed， traditionally harvested in autumn. Modern harvesting occurs in late autumn or early winter， followed by sun-drying. Ancient texts valued seeds with a fragrant aroma as superior， while modern standards prioritize plump， uniform and free of impurities. Traditional processing methods for ACS included frying until blackened and wine-frying， while modern practice commonly employs purification methods. In terms of medicinal properties， the ancient and modern records are sweet and warm in nature. Due to originally classified under Tribuli Fructus， its effects were thus regarded as equivalent to those of Tribuli Fructus， serving as the medicine for treating wind disorders， additional functions included tonifying the kidneys and treating vitiligo. The present record of its efficacy is to tonify the kidney and promote Yang， solidify sperm and reduce urine， nourish the liver and brighten the eye， etc. Based on the textual research results， it is suggested that when developing the famous classical formulas of Tribuli Fructus medicinal materials， we should pay attention to the specific reference object of Baijili， T. terrestris and A. complanatus should be identified and selected， and the processing method should be in accordance with the requirements of the formulas.

Natural product-based drug combinations (NPDCs) present distinctive advantages in treating complex diseases. While high-throughput screening (HTS) and conventional computational methods have partially accelerated synergistic drug combination discovery, their applications remain constrained by experimental data fragmentation, high costs, and extensive combinatorial space. Recent developments in artificial intelligence (AI), encompassing traditional machine learning and deep learning algorithms, have been extensively applied in NPDC identification. Through the integration of multi-source heterogeneous data and autonomous feature extraction, prediction accuracy has markedly improved, offering a robust technical approach for novel NPDC discovery. This review comprehensively examines recent advances in AI-driven NPDC prediction, presents relevant data resources and algorithmic frameworks, and evaluates current limitations and future prospects. AI methodologies are anticipated to substantially expedite NPDC discovery and inform experimental validation.
Artificial Intelligence ; Biological Products/chemistry* ; Humans ; Drug Combinations ; Drug Discovery/methods* ; Machine Learning ; Algorithms

Peri-implant keratinized mucosa (PIKM) augmentation refers to surgical procedures aimed at increasing the width of PIKM. Consensus reports emphasize the necessity of maintaining a minimum width of PIKM to ensure long-term peri-implant health. Currently, several surgical techniques have been validated for their effectiveness in increasing PIKM. However, the selection and application of PIKM augmentation methods may present challenges for dental practitioners due to heterogeneity in surgical techniques, variations in clinical scenarios, and anatomical differences. Therefore, clear guidelines and considerations for PIKM augmentation are needed. This expert consensus focuses on the commonly employed surgical techniques for PIKM augmentation and the factors influencing their selection at second-stage surgery. It aims to establish a standardized framework for assessing, planning, and executing PIKM augmentation procedures, with the goal of offering evidence-based guidance to enhance the predictability and success of PIKM augmentation.
Humans ; Consensus ; Dental Implants ; Mouth Mucosa/surgery* ; Keratins

Advancements in artificial intelligence (AI) and emerging technologies are rapidly expanding the exploration of chemical space, facilitating innovative drug discovery. However, the transformation of novel compounds into safe and effective drugs remains a lengthy, high-risk, and costly process. Comprehensive early-stage evaluation is essential for reducing costs and improving the success rate of drug development. Despite this need, no comprehensive tool currently supports systematic evaluation and efficient screening. Here, we present druglikeFilter, a deep learning-based framework designed to assess drug-likeness across four critical dimensions: 1) physicochemical rule evaluated by systematic determination, 2) toxicity alert investigated from multiple perspectives, 3) binding affinity measured by dual-path analysis, and 4) compound synthesizability assessed by retro-route prediction. By enabling automated, multidimensional filtering of compound libraries, druglikeFilter not only streamlines the drug development process but also plays a crucial role in advancing research efforts towards viable drug candidates, which can be freely accessed at https://idrblab.org/drugfilter/.

Increasing evidence showed that histone deacetylase 6 (HDAC6) dysfunction is directly associated with the onset and progression of various diseases, especially cancers, making the development of HDAC6-targeted anti-tumor agents a research hotspot. In this study, artificial intelligence (AI) technology and molecular simulation strategies were fully integrated to construct an efficient and precise drug screening pipeline, which combined Voting strategy based on compound-protein interaction (CPI) prediction models, cascade molecular docking, and molecular dynamic (MD) simulations. The biological potential of the screened compounds was further evaluated through enzymatic and cellular activity assays. Among the identified compounds, Cmpd.18 exhibited more potent HDAC6 enzyme inhibitory activity (IC₅₀ = 5.41 nM) than that of tubastatin A (TubA) (IC₅₀ = 15.11 nM), along with a favorable subtype selectivity profile (selectivity index ≈ 117.23 for HDAC1), which was further verified by the Western blot analysis. Additionally, Cmpd.18 induced G2/M phase arrest and promoted apoptosis in HCT-116 cells, exerting desirable antiproliferative activity (IC₅₀ = 2.59 μM). Furthermore, based on long-term MD simulation trajectory, the key residues facilitating Cmpd.18's binding were identified by decomposition free energy analysis, thereby elucidating its binding mechanism. Moreover, the representative conformation analysis also indicated that Cmpd.18 could stably bind to the active pocket in an effective conformation, thus demonstrating the potential for in-depth research of the 2-(2-phenoxyethyl)pyridazin-3(2H)-one scaffold.

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

Objective To observe the effects of Postmenstrual Proliferative Prescription(mainly composed of Codonopsis Radix,Atractylodis Macrocephalae Rhizoma,Poria,Rehmanniae Radix Praeparata,Paeoniae Radix Alba,Angelicae Sinensis Radix,Chuanxiong Rhizoma,Cervi Cornu Degelatinatum,Corni Fructus,Cuscutae Semen,and Eucommiae Cortex)through replenishing qi and blood on the ovulation rate and pregnancy rate in patients with ovulatory dysfunction infertility caused by polycystic ovarian syndrome(PCOS)during ovulation-induction treatment,and to explore the therapeutic effects and possible therapeutic mechanism.Methods Sixty patients with ovulatory dysfunction infertility due to PCOS were randomly divided into a treatment group and a control group,with 30 patients in each group.The control group was given Clomifene Citrate Capsules to promote ovulation,and the treatment group was given Postmenstrual Proliferative Prescription on the basis of the ovulation-induction program of the control group starting from the fifth day of menstruation or progesterone withdrawal bleeding.The two groups were treated for one menstrual cycle as a course of treatment.The changes in the serum sex hormones of estradiol(E2),follicle-stimulating hormone(FSH),luteinizing hormone(LH),and progesterone(P)on the 2nd to 5th day of menstruation,as well as the changes in serum growth differentiation factor 9(GDF9)and bone morphogenetic protein 15(BMP15)levels on the 2nd to 5th day of menstruation and on the day of human chorionic gonadotropin(HCG)injection were observed in the two groups.Moreover,the ovulation rate,pregnancy rate and clinical efficacy of the patients in the two groups were analyzed.Results(1)No statistically significant differences in serum levels of sex hormones E2,FSH,LH and P on the 2nd to 5th day of menstruation were shown between the two groups of patients(P＞0.05).(2)On the 2nd to 5th day of menstruation and on the day of HCG injection,there were no significant differences in the serum GDF9 and BMP15 levels between the two groups(P＞0.05).(3)The ovulation rate and pregnancy rate in the treatment group were 93.33%(28/30)and 26.67%(8/30)respectively,which were significantly higher than 70.00%(21/30)and 13.33%(4/30)in the control group.And the differences tested by chi-square test were statistically significant between the two groups(P＜0.05).(4)The total effective rate of the treatment group was 93.33%(28/30),and that of the control group was 70.00%(21/30).The intergroup comparison(tested by rank sum test)showed that the therapeutic efficacy of the treatment group was significantly superior to that of the control group,and the difference was statistically significant(P＜0.05).Conclusion Postmenstrual Proliferative Prescription through replenishing qi and blood can improve the ovulation rate and pregnancy rate during ovulation-induction treatment in the patients with ovulatory dysfunction infertility due to PCOS.It is indicated that Postmenstrual Proliferative Prescription can enhance the quality of the oocytes and the potential of embryo implantation during the ovulation-induction treatment.

Objective To explore the dynamic changes and mechanisms of neurological and cognitive functions in mice with traumatic brain injury (TBI). Methods Totally 60 12⁃month⁃old Balb/ c mice were divided into control group (10 in group) and TBI group (50 in group). TBT model mice were divided into 5 subgroups according to the time of model construction, including model 1 day, model 1 day, model 3 day, model 7 day, model 14 days and model 28 days group with 10 in each group. At the 29th day of the experiment, neurological scores and step down tests were carried out. After the test, the mice were sacrificed for brains which were detected by immunohistochemistry staining, inflammatory cytokine tests and Western blotting. Results Compared with the control group, the neurological scores of mice in TBI group increased, and then decreased after the 7th day when the scores reached the peak. However, the latency of step down errors was lower than control group, and the number of step down errors was higher than control group which had no changes. Compared with the control group, the expression of lonized calcium⁃binding adapter molecule 1(IBA1), chemokine C⁃X3⁃C⁃motif ligand1 (CX3CL1), C⁃X3⁃C chemokine receptor 1(CX3CR1), NOD⁃like receptor thermal protein domain associated protein 3 (NLRP3), and phosphorylation nuclear factor(p⁃NF)⁃κB in TBI group increased and reached to the peak at the 7th day, and then started to decrease. At the same time, the levels of inflammatory cytokines interleukin⁃6(IL⁃6) and tumor necrosis factor⁃α(TNF⁃α) first increased to the peak, and then began to decrease. However, compared with the control group, the expression of amyloid β(Aβ) protein and p⁃Tau protein in the model group continued to increase at all time. Conclusion The TBI model caused continuous activation of microglia along with inflammatory response, which first increased and then decreased, resultsing in neurological scores changes. In addition, the inflammatory response may act as a promoter of Aβ protein deposition and Tau protein phosphorylation, leading to cognitive impairment in mice.

Objective By analyzing the means of donor maintenance from the perspective of intensive care medicine,the difference of clinical indicators before and after donor treatment is obtained,summarizing the treatment experience and effect of clinical maintenance of donor donors,and providing more clinical evidence for the maintenance and treatment of organ donation donors.Methods A retrospective analysis was performed on 76 organ donors collected from the Department of Intensive Care Medicine,Army Medical Center,Chinese People's Liberation Army from January 2014 to December 2021,collected donor maintenance treatment,including mechanical ventilation,continuous renal replacement therapy(CRRT)treatment,enteral nutrition and parenteral nutrition,enteral and parenteral nutrition,plasma exchange,at the same time,the paired t test was used to compare the organ function before and after treatment.Results The lung,liver and kidney of 76 donors were evaluated before and after treatment to determine the number of eligible donors.The difference between the number of eligible donors of kidney and liver before and after treatment was statistically significant(P<0.05).There was no significant difference in lung evaluation(P>0.05).Conclusion Timely and effective organ support therapy for organ transplantation donors is beneficial to the recovery of organ function and improve the utilization rate of organ.