Chronic obstructive pulmonary disease （COPD）， as one of the three major causes of death， is a complex systemic disease with high prevalence， high mortality， high disability， frequent acute exacerbations， and a variety of pulmonary complications. The pathogenesis is complex. Western medicine has no effective specificity scheme for a complete cure. However， multiple-component and multiple-target characteristics of traditional Chinese medicine （TCM） demonstrate significant advantages in COPD treatment through multi-link， multi-pathway， and multi-mechanism intervention. Therefore， exploring the essence of COPD pathogenesis and discovering effective TCM treatment drugs through the application of TCM principles and prescriptions is a key focus of modern research. Animal models are of paramount importance in medical research. It is the first consideration to select appropriate animals， adopt reasonable modeling methods to replicate stable animal models that closely resemble the clinical manifestations and pathophysiological characteristics of COPD， and use appropriate evaluation methods to determine the success of COPD animal models in experimental research. The core of experimental research lies in observing the intervention effect of TCM on COPD animal models， exploring the specific pathways and regulatory mechanisms of TCM on COPD disease， and finding TCM monomers， single herbs， and TCM formulas with definite curative effects. At present， animal model research on COPD mainly involves model establishment， model evaluation， efficacy observation， mechanism exploration， and other aspects. In recent years， there has been no systematic organization， update， and reflection on the relevant research on TCM intervention in COPD animal models. This study reviewed the selection of animals for the COPD model， methods for establishing COPD animal models， model evaluation methods， and the intervention effects of TCM on COPD animal models. It aims to grasp the current research status and identify existing problems for further improvement， in order to provide evidence and support for scientific research and clinical treatment of COPD.

Chronic obstructive pulmonary disease （COPD）， as one of the three major causes of death， is a complex systemic disease with high prevalence， high mortality， high disability， frequent acute exacerbations， and a variety of pulmonary complications. The pathogenesis is complex. Western medicine has no effective specificity scheme for a complete cure. However， multiple-component and multiple-target characteristics of traditional Chinese medicine （TCM） demonstrate significant advantages in COPD treatment through multi-link， multi-pathway， and multi-mechanism intervention. Therefore， exploring the essence of COPD pathogenesis and discovering effective TCM treatment drugs through the application of TCM principles and prescriptions is a key focus of modern research. Animal models are of paramount importance in medical research. It is the first consideration to select appropriate animals， adopt reasonable modeling methods to replicate stable animal models that closely resemble the clinical manifestations and pathophysiological characteristics of COPD， and use appropriate evaluation methods to determine the success of COPD animal models in experimental research. The core of experimental research lies in observing the intervention effect of TCM on COPD animal models， exploring the specific pathways and regulatory mechanisms of TCM on COPD disease， and finding TCM monomers， single herbs， and TCM formulas with definite curative effects. At present， animal model research on COPD mainly involves model establishment， model evaluation， efficacy observation， mechanism exploration， and other aspects. In recent years， there has been no systematic organization， update， and reflection on the relevant research on TCM intervention in COPD animal models. This study reviewed the selection of animals for the COPD model， methods for establishing COPD animal models， model evaluation methods， and the intervention effects of TCM on COPD animal models. It aims to grasp the current research status and identify existing problems for further improvement， in order to provide evidence and support for scientific research and clinical treatment of COPD.

Objective To explore a method for rapid and differential diagnosis of rejection after kidney transplantation through urine hyperspectral imaging technology. Methods Hyperspectral data information from urine samples of 118 recipients after kidney transplantation was collected, and a deep learning model was constructed to diagnose and classify the types of rejection. Results A deep learning diagnostic model based on the 34-layer residual network (ResNet-34) was constructed, and 118 patients were included and divided into the training set and the test set. Based on the pathological results of the transplanted kidney puncture, the urine samples of the patients were classified into five groups: the non-rejection group, the T-cell-mediated rejection group, the antibody-mediated rejection group, the mixed rejection group and the nephropathy recurrence group. The results showed that the diagnostic sensitivities of the model for the above five groups were 0.960, 0.980, 0.930, 0.940 and 0.943 respectively, and the diagnostic specificities were 0.983, 0.993, 0.997, 0.989 and 0.989 respectively. The overall diagnostic accuracy rate reached 95.7%. Conclusions The study provides a non-invasive, rapid and accurate auxiliary diagnostic method for the differential diagnosis of rejection after kidney transplantation.

ObjectiveTo explore the potential mechanism of Changji'an Formula （肠激安方） on intestinal permeability for rats with diarrhea-predominant irritable bowel syndrome （IBS-D） of liver depression and spleen deficiency syndrome by the microRNA-29b-3p （miR-29b-3p）/tumor necrosis factor receptor-associated factor 3 （TRAF3）/nuclear factor-κB （NF-κB）/myosin light chain kinase （MLCK） axis. MethodsTwenty-four 1-day-old male Sprague-Dawley （SD） suckling rats were selected， and the IBS-D rat model of liver depression and spleen deficiency syndrome was established via a three-factor method，i.e. maternal separation plus acetic acid stimulation and restraint stress， for 6 consecutive weeks. After successful modeling， the rats were randomly divided into a model group， pinaverium bromide group， low-dose and high-dose Changji'an Formula groups， with 6 rats in each group. Another 6 age-matched non-modeled SD rats were included as the control group. The low-dose and high-dose Changji'an Formula groups were given intragastric administration of Changji'an Formula solution at doses of 16.74 g/（kg·d） and 33.48 g/（kg·d）， respectively； the pinaverium bromide group received intragastric administration of pinaverium bromide tablets at 0.018 g/（kg·d）； and the control group was given distilled water at 10 ml/（kg·d） via intragastric gavage. The intervention was conducted once daily for 14 consecutive days. After the gavage treatment， the fecal water content of rats in each group was measured. Enzyme-linked immunosorbent assay （ELISA） was used to detect the serum levels of intestinal permeability indicators， including D-lactic acid （D-LA）， diamine oxidase （DAO）， and lipopolysaccharide （LPS）. Quantitative real-time polymerase chain reaction （qRT-PCR） was conducted to determine the mRNA expression levels of miR-29b-3p， TRAF3， tumor necrosis factor-α （TNF-α）， p65， p50， and MLCK in colonic tissues. Western Blot analysis was employed to detect the protein expression levels of TRAF3， TNF-α， p65， phosphorylated p65 （p-p65）， MLCK， myosin light chain （MLC）， phosphorylated MLC （p-MLC）， and tight junction proteins including junctional adhesion molecule-A （JAM-A）， Occludin， and Claudin-1 in colonic tissues. ResultsCompared with the control group， the model group exhibited significantly increased fecal water content and serum levels of D-LA， DAO， and LPS， along with decreased protein expression levels of JAM-A， Occludin， and Claudin-1 in colonic tissues （P＜0.05 or P＜0.01）. Additionally， in the model group， the mRNA expression levels of miR-29b-3p， TNF-α， p65， p50， and MLCK in colonic tissues were up-regulated， while the mRNA and protein expression levels of TRAF3 were down-regulated； the protein levels of TNF-α and MLCK， as well as the ratios of p-p65/p65 and p-MLC/MLC， significantly elevated （P＜0.01）. Compared with the model group， all treatment groups showed reduced fecal water content and serum levels of D-LA， DAO， and LPS， along with down-regulated mRNA expression levels of miR-29b-3p， TNF-α， p65， p50， and MLCK， and up-regulated TRAF3 mRNA expression in colonic tissues. Moreover， the pinaverium bromide group and high-dose Changji'an Formula group presented increased protein levels of Occludin， Claudin-1， and TRAF3， as well as decreased protein levels of TNF-α and MLCK， and reduced ratios of p-p65/p65 and p-MLC/MLC in colonic tissues （P＜0.05 or P＜0.01）. Compared with the low-dose Changji'an Formula group， the high-dose group had lower fecal water content and serum levels of DAO and LPS （P＜0.01）. In comparison with the pinaverium bromide group， the high-dose Changji'an Formula group showed a significant decrease in serum DAO level （P＜0.01）. ConclusionsChangji'an Formula can reduce intestinal permeability and restore intestinal barrier function in IBS-D rats of liver depression and spleen deficiency syndrome by regulating the miR-29b-3p/TRAF3/NF-κB/MLCK axis.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that severely affects the health of the elderly, marked by its incurability, high prevalence, and extended latency period. The current approach to AD prevention and treatment emphasizes early detection and intervention, particularly during the pre-AD stage of mild cognitive impairment (MCI), which provides an optimal “window of opportunity” for intervention. Clinical detection methods for MCI, such as cerebrospinal fluid monitoring, genetic testing, and imaging diagnostics, are invasive and costly, limiting their broad clinical application. Speech, as a vital cognitive output, offers a new perspective and tool for computer-assisted analysis and screening of cognitive decline. This is because elderly individuals with cognitive decline exhibit distinct characteristics in semantic and audio information, such as reduced lexical richness, decreased speech coherence and conciseness, and declines in speech rate, voice rhythm, and hesitation rates. The objective presence of these semantic and audio characteristics lays the groundwork for computer-based screening of cognitive decline. Speech information is primarily sourced from databases or collected through tasks involving spontaneous speech, semantic fluency, and reading, followed by analysis using computer models. Spontaneous language tasks include dialogues/interviews, event descriptions, narrative recall, and picture descriptions. Semantic fluency tasks assess controlled retrieval of vocabulary items, requiring participants to extract information at the word level during lexical search. Reading tasks involve participants reading a passage aloud. Summarizing past research, the speech characteristics of the elderly can be divided into two major categories: semantic information and audio information. Semantic information focuses on the meaning of speech across different tasks, highlighting differences in vocabulary and text content in cognitive impairment. Overall, discourse pragmatic disorders in AD can be studied along three dimensions: cohesion, coherence, and conciseness. Cohesion mainly examines the use of vocabulary by participants, with a reduction in the use of nouns, pronouns, verbs, and adjectives in AD patients. Coherence assesses the ability of participants to maintain topics, with a decrease in the number of subordinate clauses in AD patients. Conciseness evaluates the information density of participants, with AD patients producing shorter texts with less information compared to normal elderly individuals. Audio information focuses on acoustic features that are difficult for the human ear to detect. There is a significant degradation in temporal parameters in the later stages of cognitive impairment; AD patients require more time to read the same paragraph, have longer vocalization times, and produce more pauses or silent parts in their spontaneous speech signals compared to normal individuals. Researchers have extracted audio and speech features, developing independent systems for each set of features, achieving an accuracy rate of 82% for both, which increases to 86% when both types of features are combined, demonstrating the advantage of integrating audio and speech information. Currently, deep learning and machine learning are the main methods used for information analysis. The overall diagnostic accuracy rate for AD exceeds 80%, and the diagnostic accuracy rate for MCI also exceeds 80%, indicating significant potential. Deep learning techniques require substantial data support, necessitating future expansion of database scale and continuous algorithm upgrades to transition from laboratory research to practical product implementation.

Objective: To investigate the effect of integrin α5 on the expression of NOD-like receptor thermal protein domain associated protein 3 (NLRP3) in periodontal ligament fibroblasts (PDLFs) within an inflammatory microenvironment. Methods: This study was approved by the Ethics Committee of Laboratory animals. After rat PDLFs were treated with LPS (0.5, 5, and 50 µg/mL) for 24 h, the primary medium was discarded and replaced with serum-free culture medium. After 24 h, the supernatant was collected and mixed with DMEM medium containing 10% exosome-free serum at a volume ratio of 1:1 to obtain conditioned medium (CM). The groups were labeled as the 0.5-CM, 5-CM, and 50-CM groups. In addition, PDLFs cultured in DMEM medium containing 10% exosome-free serum were considered the 0-CM group. PDLFs were cultured with the above CM. In the inhibitor group, PDLFs were cultured in 0-CM containing different concentrations of integrin α5 inhibitor ATN-161 (0, 0.025, 0.25, 2.5, 25, and 250 μg/mL). The effect of CM and integrin α5 inhibitor ATN-161 on cell viability was assessed using the CCK-8 assay. According to the CCK-8 results, in further inhibitor intervention experiments, PDLFs were cultured in 0-CM, 5-CM (without/with 25 μg/mL ATN-161), and 0-CM containing 25 μg/mL ATN-161, which were labeled as the 0-CM, 5-CM, ATN-161+5-CM, and ATN-161 groups, respectively. The expression changes of integrin α5 and NLRP3 were detected using Western blot and qRT-PCR techniques. For in vivo experiments, 24 rats were randomly divided into four groups (n=6). The control group contained healthy rats that received no treatment. The rats in the other three groups were injected with 40 µL of 0-CM containing 25 μg/mL ATN-161 or 5-CM (without or with 25 μg/mL ATN-161) on the palatal side of the left maxillary first molar every three days; these groups were classified as the ATN-161, 5-CM, and ATN-161+5-CM groups, respectively. On the 30th day, the left maxillary tissue of rats was used for Micro-CT, HE staining, and immunohistochemical detection. Results : The CCK-8 assay showed that CM, 25 μg/mL ATN-161, and ATN-161 concentrations below 25 μg/mL had no significant effect on cell viability at 12 h and 24 h (P > 0.05). 50-CM and 25 μg/mL ATN-161 significantly inhibited cell viability at 48 h (P < 0.05). For in vitro experiments, compared to the 0-CM group, both the protein and mRNA levels of integrin α5 and NLRP3 were significantly increased in rat PDLFs in the 5-CM group (P < 0.05). Intervention with 25 μg/mL ATN-161 significantly attenuated the enhancement of 5-CM on the expression of integrin α5 and NLRP3 (P < 0.05). For in vivo experiments, compared to the control group, alveolar bone resorption and periodontal inflammatory cell infiltration were significantly increased in the 5-CM and ATN-161+5-CM groups, and the expression of integrin α5 and NLRP3 was significantly increased (P < 0.01). However, compared to the 5-CM group, the ATN-161+5-CM group had less alveolar bone resorption and fewer periodontal inflammatory cells. Further, the expression of integrin α5 and NLRP3 was significantly reduced (P < 0.01). Conclusion In vitro and in vivo experiments showed that integrin α5 mediated NLRP3 expression in PDLFs under an inflammatory microenvironment. ATN-161 inhibited the expression of integrin α5, thus significantly downregulating the expression of NLRP3, which plays a role in inhibiting inflammation.

BACKGROUND:Recent research indicates that disc degeneration is closely related to abnormal stress load,and mechanotransduction proteins play a key role in it. OBJECTIVE:To investigate the role and mechanism of mechanotransduction proteins in the mechanotransduction process induced by abnormal mechanical stimulation in disc degeneration,and to summarize the current treatment strategies targeting mechanotransduction to delay intervertebral disc degeneration. METHODS:Using"intervertebral disc,nucleus pulposus,annulus fibrosus,cartilaginous endplate,cell,mechanics,signal transduction,protein,biomechanics"as Chinese search terms,and"intervertebral disc,nucleus pulposus,annulus fibrosus,cartilaginous endplate,cell,mechanical stimulation,signal transduction,protein,biomechanics"as English search terms,relevant literature in the PubMed and CNKI databases was searched.A total of 88 articles were ultimately included for review. RESULTS AND CONCLUSION:Disc cells can sense external mechanical stimulation through various mechanotransduction proteins and convert it into biological responses within the cells.These transduction proteins mainly include collagen proteins in the extracellular matrix,cell membrane surface receptors(such as integrins and ion channels),and cytoskeleton structural proteins.Their regulation of mechanotransduction processes primarily involves the activation of multiple pathways,such as the PI3K/AKT signaling pathway,nuclear factor-kB signaling pathway,and Ca2+/Calpain2/Caspase3 pathway.Mechanotransduction proteins play a key role in the mechanotransduction of disc cells.Abnormal expression of these proteins or resulting changes in the extracellular matrix environment can disrupt the mechanical balance of disc cells,leading to disc degeneration.In-depth study of the expression and regulatory mechanisms of mechanotransduction proteins in disc cells,and identification of key pathological links and therapeutic targets,is of significant importance for developing treatment strategies for disc degeneration.Current strategies to delay intervertebral disc degeneration by targeting mechanotransduction mainly include regulation of transduction proteins and improvement of the extracellular matrix.However,research in this area is still in its early stages.As research continues,new breakthroughs are expected in the regulation of disc degeneration by mechanotransduction proteins.

Objective: This study aims to investigate the anatomical relationship among the nerve roots, intervertebral space, pedicles, and intradural rootlets of the cervical spine for improving operative outcomes and exploring neuroventral decompression approach in posterior endoscopic cervical discectomy (PECD). Methods: Cervical computed tomography myelography imaging data from January 2021 to May 2023 were collected, and the RadiAnt DICOM Viewer Software was employed to conduct multiplane reconstruction. The following parameters were recorded: width of nerve root (WN), nerve root-superior pedicle distance (NSPD), nerve root-inferior pedicle distance (NIPD), and the relationship between the intervertebral space and the nerve root (shoulder, anterior, and axillary). Additionally, the descending angles between the spinal cord and the ventral (VRA) and dorsal (DRA) rootlets were measured. Results: The WN showed a gradual increase from C4 to C7, with measurements notably larger in men compared to women. The NSPD decreased gradually from the C2–3 to the C5–6 levels. However, the NIPD showed an opposite level-related change, notably larger than the NSPD at the C4–5, C5–6, and C7–T1 levels. Furthermore, significant differences in NIPD were observed between different age groups and genders. The incidence of the anterior type exhibited a gradual decrease from the C2–3 to the C5–6 levels. Conversely, the axillary type exhibited an opposite level-related change. Additionally, the VRA and DRA decreased as the level descended, with measurements significantly larger in females. Conclusion A prediction of the positional relationship between the intervertebral space and the nerve root is essential for the direct neuroventral decompression in PECD to avoid damaging the neural structures. The axillary route of the nerve root offers a safer and more effective pathway for performing direct neuroventral decompression compared to the shoulder approach.