The chronicity of infectious diseases is an important field in the collaborative research of traditional Chinese and Western medicine. The warm disease theory of pathogen invading nutrient and blood aspects in traditional Chinese medicine （TCM） takes the struggle between healthy Qi and pathogenic Qi and cementation of Yin as the core pathogenesis， providing a unique theoretical framework for explaining the common pathology of infectious chronic diseases. This theory originated from Yin-Yang interaction in the Internal Classic and was enriched with WU Youke's theory of intruding pathogen interacting and lingering in blood vessels and YE Tianshi's theory of long-term illness entering collaterals. Combining the theory with modern medical knowledge， our team has condensed the dynamic pathogenesis model of deficiency （nutrient and blood aspects） and excess （pathogen） interacting in the blood collaterals of Yin aspect， the core feature of which is the four-dimensional interactions of cause （pathogen characteristics）， location （three Yin locations of diseases）， nature （deficiency and excess）， and potential （transmission trend）. The common pathology of infectious chronic diseases is reflected in interactions. That is， the interactions between nutrient and blood deficiency （immune exhaustion and metabolic disorder） and pathogen excess （pathogen persistence and fibrous hyperplasia） in the liver collaterals （Jueyin）， kidney collaterals （Shaoyin）， lung collaterals （Taiyin） and other blood collaterals of Yin aspect form the pathological damage characterized by immune inflammatory response-continuous tissue damage with excessive repair. Taking the inheritance and innovative development of classics as the main line， this paper systematically discusses the scientific connotation of the theory of pathogen invading nutrient and blood aspects and the paths of inheritance and innovation and clarifies the original significance of this theory in the chronic development of infectious diseases. Furthermore， taking clinical diseases as an example， this paper reflects the guiding value of this classical theory in the modern diagnosis and treatment of infectious diseases with integrated traditional Chinese and Western medicine and the application potential of this theory in solving complex medical problems through the construction of the innovative paradigm of precise diagnosis and treatment with integrated traditional Chinese and Western medicine.

ObjectiveBased on the regulation of macrophage M2 polarization， this study aims to explore the molecular mechanism and action targets of the Qijia Rougan prescription and its key effector ingredients in anti-fibrosis， thereby providing a basis and reference for the development of new drugs for hepatic fibrosis. MethodsA rat model of hepatic fibrosis was established by subcutaneous injection of 40%CCl₄， followed by oral administration of Qijia Rougan granules. The volume of collagen fibers was detected using Masson staining， the fibrosis markers Collagen Ⅰ and α-SMA were detected using immunohistochemistry， the proportion of M2 macrophages was detected by flow cytometry. The expression levels of M2 macrophage phenotype markers CD163 and CD206 were detected using immunofluorescence double staining. Western blot was used to detect the levels of the transforming growth factor-β （TGF-β）， platelet derived growth factor subunit B （PDGFB）， interleukin-10 （IL-10）， phosphorylated Janus kinase 1 （p-JAK1）， and phosphorylated signal transducer and activator of transcription 6 （p-STAT6）. Real-time fluorescent quantitative PCR was used to detect the relative expression levels of JAK1， STAT6， Arginase 1（Arg1）， and Fizz1. Based on the theory of serum pharmacology， liquid chromatography-mass spectrometry and WENN analysis were used to obtain the active ingredients of Qijia Rougan prescription. Molecular docking and molecular dynamics simulation were performed to analyze the effector ingredients and their targets. The identified effector ingredients were interfered with IL-4-induced M2 polarization of RAW264.7 macrophage in vitro to validate the targets. ResultsQijia Rougan prescription significantly reduced the content of fibrosis markers α-SMA and Collagen Ⅰ， as well as collagen fiber content （P<0.05）. It decreased the proportion of M2 macrophages and the levels of related cytokines IL-10， TGF-β and PDGFB， and up-regulated the levels of p-JAK1 and p-STAT6 （P<0.05）. A total of 1 214 compounds were identified from Qijia Rougan prescription， medicated serum and blank serum， and 29 ingredients were finalized by Venn analysis， including 15 blood-entry prototypes and 14 drug metabolites. Molecular docking showed that enoxolone and berberine bound more strongly to JAK1， with binding free energies of -9.6 kcal·mol^-1（1 cal≈4.184 J） and -9.1 kcal·mol^-1， respectively. Molecular dynamics simulations showed that JAK1-enoxolone and JAK1-berberine exhibited stable simulation trajectories within 100 ns， with essentially identical conformations and high protein overlap before and after simulation. Their binding free energies were -25.18 5.0.81 kcal·mol^-1 and -27.39 7.0.85 kcal·mol^-1， respectively. The number of hydrogen bonds formed between JAK1 and enoxolone ranges from 0 to 5， and most of the time can be maintained at 2-3. In vitro intervention with enoxolone or berberine significantly reduced p-JAK1 and p-STAT6 levels （P<0.05）. ConclusionQijia Rougan prescription inhibits M2 macrophage polarization in hepatic fibrosis. Enoxolone and berberine are the key effector ingredients of Qijia Rougan prescription to inhibit macrophage M2 polarization through targeting JAK1 and modulating the JAK1/STAT6 signaling pathway， thereby ameliorating hepatic fibrosis. This study provides a basis for prescription optimization， clinical application and new drug development， as well as a reference for monolithic anti-hepatic fibrosis research.

Background: The hypotension prediction index (HPI) is an algorithm designed to predict hypotension. Some studies have reported that HPI-guided hemodynamic management strategies decrease intraoperative hypotension and complications; however, the effect of HPI on reducing perioperative complications is controversial. This meta-analysis aimed to assess the efficacy of the HPI in reducing major complications and intraoperative hypotension. Methods: We conducted this meta-analysis according to the PRISMA statement and Cochrane Handbook guidelines. A comprehensive literature review was conducted to identify studies focusing on the efficacy of HPI-guided management in reducing intraoperative hypotension and postoperative complications. The PubMed, Embase, Scopus, and Web of Science databases were searched, and the resulting data were combined to calculate the pooled mean differences or risk ratios (RRs) with 95% CIs of both randomized controlled trials (RCTs) and retrospective studies, as appropriate. Heterogeneity and potential publication bias were also assessed. Results: Nineteen articles (12 RCTs and 7 retrospective studies) with 2570 recruited patients were included in this meta-analysis. The critical evaluation of the study quality revealed a low risk of bias in the included RCTs. Among the non-randomized trials, one was rated 7, two were rated 8, and the remaining four were rated 9 on the Newcastle-Ottawa Scale, indicating high quality and a low risk of bias. HPI-guided management significantly reduced intraoperative hypotension and associated major complications (RR = 0.79, 95% CI [0.69–0.90], I2 = 0, P < 0.001). Blood loss and length of hospital stay were comparable between the groups. Conclusions HPI-guided management significantly reduced intraoperative hypotension and major complications.

Objective To explore the application value of computed tomography (CT) three-dimensional reconstruction in total knee arthroplasty (TKA). Methods A total of 102 patients who underwent TKA in our hospital between April 2022 and April 2025 were enrolled and divided using a random number table into a traditional group (51 cases, routine preoperative evaluation) and a study group (51 cases, CT three-dimensional reconstruction-assisted surgery). The therapeutic efficacy at 3 months postoperatively and perioperative indicators were compared between the two groups. The hip-knee-ankle (HKA) angle was measured preoperatively and at 3 months postoperatively. The Hospital for Special Surgery (HSS) knee score and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score were recorded preoperatively and at 3 and 6 months postoperatively. Complications were documented. Results The excellent/good rate in the study group (92.16%) was higher than that in the traditional group (74.51%) (P<0.05). The operation time, intraoperative blood loss, postoperative drainage volume, and hospital stay in the study group were (69.52 ± 7.11) min, (102.69 ± 8.54) mL, (167.33 ± 12.35) mL, and (10.93 ± 2.37) days, respectively, which were shorter than those in the traditional group [(78.45 ± 5.98) min, (108.36 ± 10.02) mL, (175.96 ± 14.93) mL, and (12.04 ± 1.95) days] (P<0.05). At 3 months postoperatively, the HKA angle was 178.02° ± 1.05° in the study group and 177.45° ± 1.34° in the traditional group, both were significantly improved compared with those before operation, with the study group showing better improvement (P<0.05). The HSS knee and WOMAC scores in both groups at 3 and 6 months postoperatively were improved compared with preoperative scores (P<0.05). At 3 and 6 months postoperatively, the study group showed higher HSS knee score and lower WOMAC score than the traditional group (P<0.05). The incidence of complications in the study group (3.92%) was lower than that in the traditional group (17.65%) (P<0.05). Conclusion TKA guided by CT three-dimensional reconstruction improved the excellent/good rate, optimized HKA angle and knee function, shortened operation time and hospital stay, reduced intraoperative blood loss and postoperative drainage volume, and decreased the incidence of complications.

Objective To explore the application value of computed tomography (CT) three-dimensional reconstruction in total knee arthroplasty (TKA). Methods A total of 102 patients who underwent TKA in our hospital between April 2022 and April 2025 were enrolled and divided using a random number table into a traditional group (51 cases, routine preoperative evaluation) and a study group (51 cases, CT three-dimensional reconstruction-assisted surgery). The therapeutic efficacy at 3 months postoperatively and perioperative indicators were compared between the two groups. The hip-knee-ankle (HKA) angle was measured preoperatively and at 3 months postoperatively. The Hospital for Special Surgery (HSS) knee score and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score were recorded preoperatively and at 3 and 6 months postoperatively. Complications were documented. Results The excellent/good rate in the study group (92.16%) was higher than that in the traditional group (74.51%) (P<0.05). The operation time, intraoperative blood loss, postoperative drainage volume, and hospital stay in the study group were (69.52 ± 7.11) min, (102.69 ± 8.54) mL, (167.33 ± 12.35) mL, and (10.93 ± 2.37) days, respectively, which were shorter than those in the traditional group [(78.45 ± 5.98) min, (108.36 ± 10.02) mL, (175.96 ± 14.93) mL, and (12.04 ± 1.95) days] (P<0.05). At 3 months postoperatively, the HKA angle was 178.02° ± 1.05° in the study group and 177.45° ± 1.34° in the traditional group, both were significantly improved compared with those before operation, with the study group showing better improvement (P<0.05). The HSS knee and WOMAC scores in both groups at 3 and 6 months postoperatively were improved compared with preoperative scores (P<0.05). At 3 and 6 months postoperatively, the study group showed higher HSS knee score and lower WOMAC score than the traditional group (P<0.05). The incidence of complications in the study group (3.92%) was lower than that in the traditional group (17.65%) (P<0.05). Conclusion TKA guided by CT three-dimensional reconstruction improved the excellent/good rate, optimized HKA angle and knee function, shortened operation time and hospital stay, reduced intraoperative blood loss and postoperative drainage volume, and decreased the incidence of complications.

Objective To explore the application value of computed tomography (CT) three-dimensional reconstruction in total knee arthroplasty (TKA). Methods A total of 102 patients who underwent TKA in our hospital between April 2022 and April 2025 were enrolled and divided using a random number table into a traditional group (51 cases, routine preoperative evaluation) and a study group (51 cases, CT three-dimensional reconstruction-assisted surgery). The therapeutic efficacy at 3 months postoperatively and perioperative indicators were compared between the two groups. The hip-knee-ankle (HKA) angle was measured preoperatively and at 3 months postoperatively. The Hospital for Special Surgery (HSS) knee score and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score were recorded preoperatively and at 3 and 6 months postoperatively. Complications were documented. Results The excellent/good rate in the study group (92.16%) was higher than that in the traditional group (74.51%) (P<0.05). The operation time, intraoperative blood loss, postoperative drainage volume, and hospital stay in the study group were (69.52 ± 7.11) min, (102.69 ± 8.54) mL, (167.33 ± 12.35) mL, and (10.93 ± 2.37) days, respectively, which were shorter than those in the traditional group [(78.45 ± 5.98) min, (108.36 ± 10.02) mL, (175.96 ± 14.93) mL, and (12.04 ± 1.95) days] (P<0.05). At 3 months postoperatively, the HKA angle was 178.02° ± 1.05° in the study group and 177.45° ± 1.34° in the traditional group, both were significantly improved compared with those before operation, with the study group showing better improvement (P<0.05). The HSS knee and WOMAC scores in both groups at 3 and 6 months postoperatively were improved compared with preoperative scores (P<0.05). At 3 and 6 months postoperatively, the study group showed higher HSS knee score and lower WOMAC score than the traditional group (P<0.05). The incidence of complications in the study group (3.92%) was lower than that in the traditional group (17.65%) (P<0.05). Conclusion TKA guided by CT three-dimensional reconstruction improved the excellent/good rate, optimized HKA angle and knee function, shortened operation time and hospital stay, reduced intraoperative blood loss and postoperative drainage volume, and decreased the incidence of complications.

ObjectiveTo address the key challenges in breast electrical impedance tomography (EIT) reconstruction including the severe ill‑posedness of the inverse problem, limited measurement information from the electrodes, low contrast of small lesions, as well as the common drawbacks of traditional reconstruction methods such as boundary blurring, low spatial resolution, and weak small-target detection capability, and to overcome the limitations of existing deep learning approaches namely low training efficiency, insufficient physical consistency, and substantial information loss during the low‑to‑high dimensional mapping process, this study proposes a multi‑scale attention and dynamic sparse mask fusion network (MADS‑Net). The proposed method aims to enhance high‑resolution reconstruction accuracy, small-lesion detectability, noise robustness, and computational efficiency in breast‑screening-oriented EIT, thereby providing a feasible solution for the application of EIT in breast functional imaging. MethodsThe proposed network adopts a strategy of “locate first, reconstruct later”. It realizes adaptive allocation of computational resources through a dynamic mask module, alleviates information loss in the low-to-high dimensional mapping process via a multi-scale attention mechanism, and embeds physical constraints to improve the physical rationality of reconstruction results. The performance of the proposed method was validated through systematic numerical simulations, agar phantom experiments, and porcine tissue experiments. Comparisons were made with mainstream methods including the Gauss-Newton algorithm, convolutional neural networks, U-Net, and Deep D-Bar. The image correlation coefficient (ICC), root mean square error (RMSE), and peak signal-to-noise ratio (PSNR) were adopted as quantitative evaluation metrics. Furthermore, lesion‑level evaluation metrics were introduced to assess the capability of different methods in reconstructing abnormal target boundaries and small‑sized target regions. ResultsExperimental results demonstrate that MADS-Net outperforms all comparison methods across all test scenarios. In numerical simulations, it achieves higher accuracy in target morphology and spatial location recovery as well as better background suppression. In agar phantom experiments, its detection and imaging reliability for small targets is significantly superior to the comparison methods. In porcine tissue experiments, the model maintains good generalization performance and can adapt to complex biological tissue imaging scenarios. Quantitative results show that MADS-Net achieves an average ICC of 0.917 6±0.048 8, an RMSE as low as0.060 6±0.031 6, and a PSNR of (23.893 9±2.685 3) dB. It successfully detects tiny targets as small as 5 mm within a 100 mm diameter sensing field, reduces the total training duration by 23.5% compared with the baseline method, and maintains stable reconstruction performance even under strong noise interference. ConclusionThe results demonstrate that MADS-Net achieves favorable EIT reconstruction performance in numerical simulations, agar phantom experiments, and porcine tissue experiments, even under common practical imaging challenges including low signal-to-noise ratio and blurred tissue boundaries. This study provides a methodological reference for further research on EIT in breast-screening-related scenarios and other medical functional imaging tasks, and also offers a low-cost, radiation-free alternative for breast lesion screening that aligns with the clinical demand for non-invasive diagnostic tools. It should be noted that real clinical breast data have not yet been used for validation in this study, and the clinical applicability of the proposed method requires further investigation. Future work will prioritize collecting multi-center real clinical breast datasets, and further optimize the model’s generalization ability to adapt to individual differences in breast tissue composition to promote its clinical application.

The sensitive scalp is a complex syndrome characterised by abnormal nerve sensations, such as stinging, itching, burning, and tightness, and diminished tolerance to physical or chemical stimuli that would not typically cause such unpleasant responses, with its pathology involving physical barrier destruction at the stratum corneum level, neural hyperreactivity and sensory nerve sensitization, and local immunological dysregulation and chronic low‑grade inflammation. The homeostasis of the scalp microenvironment plays a crucial regulatory role in maintaining the hair follicle growth cycle, yet this “soil” factor has long been underappreciated in hair loss research, which has traditionally centered on intrinsic follicular defects, such as genetic predisposition or androgen-driven mechanisms. In this review, we summarized the potential mechanisms underlying the imbalance in the “barrier-neural-immune” network in sensitive scalps. Sensitive scalp is further manifested as impaired skin barrier, including increased transepidermal water loss and abnormal lipid secretion. These alterations are accompanied by increased surface pH, excessive secretion of sebum rich in free fatty acids, reduced microbial diversity, and dysbiosis characterized by a reduction in Cutibacterium and an increase in Staphylococcus colonization. Mechanistically, we also analyzed how neurogenic inflammation, mediated by substances such as substance P (SP) and calcitonin gene-related peptide (CGRP), along with persistent low-grade inflammation, disrupts the microenvironment of the hair follicle stem cell niche through mechanisms involving mechanosensitive ion channels (e.g., Piezo1), oxidative stress, and cytokine cascades. When the barrier is compromised, the weakened stratum corneum may facilitate the penetration of external stimuli, sensitizing cutaneous nerve endings. Those hyperresponsive nerves then fire off neuropeptides like substance P and CGRP. These peptides activate mast cells and other immune cells via the MrgprB2 receptor, prompting degranulation and a wave of pro-inflammatory mediators that kick off neurogenic inflammation. At the same time, oxidative stress and inflammatory cytokines drive a persistent low-grade inflammation that directly damages the hair follicle stem cell niche. Physical compression from shrinking hair shafts activates Piezo1 channels, setting off calcium influx and Caspase‑3‑dependent apoptotic signaling. We primarily considered the interactions between inflammatory signaling and the sensitization of the androgen receptor (AR) pathway, as well as the inhibition of the Wnt/β‑catenin pathway, which may subsequently contribute to hair follicle miniaturization and disruption of the growth cycle. The inflammatory microenvironment appears to boost AR expression in dermal papilla cells, making them more sensitive to dihydrotestosterone (DHT). This heightened sensitivity may promote the expression of transforming growth factor-β1 (TGF-β1), TGF-β2, and Dickkopf-1 (DKK1), which suppress the Wnt/β‑catenin pathway—essential for follicle growth and regeneration—potentially accelerating follicular miniaturization and stalling the growth cycle. Coupled with direct inflammatory apoptosis, oxidative stress, and circadian disruption, these routes may collectively speed up hair follicle stem cell depletion and diffuse hair thinning. These findings point to the need for more mechanistic and translational research to test the proposed pathways and explore therapies that target the microenvironment in sensitive scalp-related hair loss. Ultimately, we hope to provide theoretical support for the intervention of hair loss by restoring the steady state of the scalp microenvironment and combining with new precision delivery technologies such as microneedles.

Objective By combining biological detection and imaging evaluation, a clinical prediction model is constructed based on a large cohort to improve the accuracy of distinguishing between benign and malignant pulmonary nodules. Methods A retrospective analysis was conducted on the clinical data of the 32 627 patients with pulmonary nodules who underwent chest CT and testing for 7 types of lung cancer-related serum autoantibodies (7-AABs) at our hospital from January 2020 to April 2024. The univariate and multivariate logistic regression models were performed to screen independent risk factors for benign and malignant pulmonary nodules, based on which a nomogram model was established. The performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results A total of 1 017 patients with pulmonary nodules were included in the study. The training set consisted of 712 patients, including 291 males and 421 females, with a mean age of (58±12) years. The validation set included 305 patients, comprising 129 males and 176 females, with a mean age of (58±13) years. Univariate ROC curve analysis indicated that the combination of CT and 7-AABs testing achieved the highest area under the curve (AUC) value (0.794), surpassing the diagnostic efficacy of CT alone (AUC=0.667) or 7-AABs alone (AUC=0.514). Multivariate logistic regression analysis showed that radiological nodule diameter, nodule nature, and CT combined with 7-AABs detection were independent predictors, which were used to construct a nomogram prediction model. The AUC values for this model were 0.826 and 0.862 in the training and validation sets, respectively, demonstrating excellent performance in DCA. Conclusion The combination of 7-AABs with CT significantly enhances the accuracy of distinguishing between benign and malignant pulmonary nodules. The developed predictive model provides strong support for clinical decision-making and contributes to achieving precise diagnosis and treatment of pulmonary nodules.

AIM To establish a UPLC-MS/MS method for the simultaneous content determination of liquiritin,liquiritin apioside,verbascoside,narirutin,isoacteoside,apigetrin,hesperidin,isoliquiritin,ononin,liquiritigenin,glycyrrhizic acid,isoliquiritigenin,honokiol,obovatol,pogostone and magnolol in Jiawei Huoxiang Zhengqi Soft Capsules.METHODS The analysis was performed on a 40 ℃ thermostatic ZORBAX Eclipse Plus C18 column(2.1 mm×100 mm,1.8 μm),with the mobile phase comprising of 0.1％formic acid-acetonitrile flowing at 0.4 mL/min in a gradient elution manner,and electron spray ionization source was adopted in positive and negative ion scanning with multiple reaction monitoring mode.RESULTS Sixteen constituents showed good linear relationships within their own ranges(r＞0.990 0),whose average recoveries were 83.74％-105.12％with the RSDs of 1.10％-4.8％.CONCLUSION This accurate,sensitive,stable and reproducible method can provide a reference for the overall quality control of Jiawei Huoxiang Zhengqi Soft Capsules.