Objective: To map the research hotspots, developmental trends, and existing challenges in the integration of artificial intelligence (AI) with multi-omics in traditional Chinese medicine (TCM) through comprehensive bibliometric analysis. Methods: China National Knowledge Infrastructure (CNKI), Wanfang Data, China Science and Technology Journal Database (VIP), Chaoxing Journal Database, PubMed, and Web of Science were searched to collect literature on the theme of AI in TCM multi-omics research from the inception of each database to December 31, 2024. Eligible records were required to simultaneously address AI, TCM, and multi-omics. Quantitative and visual analyses of publication growth, core authorship networks, institutional collaboration patterns, and keyword co-occurrence were performed using Microsoft Excel 2021, NoteExpress v4.0.0, and Cite Space 6.3.R1. AI application modes in TCM multi-omics research were also categorized and summarized. Results: A total of 1 106 articles were enrolled (932 Chinese and 174 English). Publication output has increased continuously since 2010 and accelerated after 2016. Region-specific collaboration clusters were identified, dominated by Beijing University of Chinese Medicine, China Academy of Chinese Medical Sciences, Shanghai University of Traditional Chinese Medicine, and Nanjing University of Chinese Medicine. Keyword co-occurrence analysis revealed that current AI applications predominantly centered on metabolomics and algorithms such as cluster analysis and data mining. Research foci mainly ranked as follows: single herbs, herbal formulae, and disease-syndrome differentiation. Conclusion Machine learning methods are the predominant integrative modality of AI in the realm of TCM multi-omics research at present, utilized for processing omics data and uncovering latent patterns therein. The domain of TCM, in addition to investigating omics information procured through high-throughput technologies, also integrates data on traditional Chinese medicinal substances and clinical phenotypes, progressing towards joint analysis of multi-omics, high-dimensionality of data, and multi-modality of information. Deep learning approaches represent an emerging trend in the field.

Abstract In Unani medicine, Bawl (urine) is recognized as a key diagnostic tool, with humoural imbalances assessed via parameters like color, consistency, sediment, clarity, froth, odor, and volume. This conceptual review explores how these classical diagnostic indicators may be contextualized alongside modern urinalysis markers (e.g., bilirubin, protein, ketones, and sedimentation) and examined through emerging artificial intelligence (AI) frameworks. Potential applications include ResNet-18 for color classification, You Only Look Once version 8 (YOLOv8) for sediment detection, long short-term memory (LSTM) for viscosity estimation, and EfficientDet for froth analysis, with standardized urine images/videos forming the basis of future datasets. Additionally, a comparative ontology is proposed to align Unani perspectives with diagnostic approaches in traditional Chinese medicine, encouraging cross-system integration. By synthesizing classical epistemology with computational intelligence, this review highlights pathways for developing AI-based decision support systems to promote personalized, accessible, and telemedicine-enabled healthcare.

Objective: To review and synthesize preclinical and clinical evidence regarding traditional Chinese medicine (TCM) formulations and bioactive herbal compounds in lupus nephritis (LN), and to identify direction and research priorities for integrating TCM with professional care. Methods: A narrative literature review was conducted by searching Scopus, PubMed, Web of Science, and Google Scholar for articles published between January 1, 2011 and March 31, 2024. Search terms combined controlled vocabulary [e.g., medical subject headings (MeSH)] and free-text words including lupus nephritis, traditional Chinese medicine, Chinese herbal medicine, formulation, and names of specific herbs [Leigongteng (Tripterygii Wilfordii Radix et Rhizoma), Baishao (Paeoniae Radix Alba), and Yinghao (Artemisiae Annuae Herba)]. Both randomized controlled trials and observational studies were included, along with mechanistic preclinical studies and pharmacologic investigations. Inclusion criteria were studies that reported renal outcomes (proteinuria and estimated glomerular filtration rate), immune-modulatory mechanisms, or safety and herb-drug interaction data. Studies without primary data, case reports, or those lacking relevance to LN were excluded. References of key articles were manually screened to identify additional eligible studies. Results: TCM formulas [e.g., Liuwei Dihuang Pills (六味地黄丸), Zhibai Dihuang Pills (知柏地黄丸), and Huanglian Jiedu Decoction (黄连解毒汤)] and herbal medicines [e.g., extracts from Leigongteng (Tripterygii Wilfordii Radix et Rhizoma), Baishao (Paeoniae Radix Alba), and Yinghao (Artemisiae Annuae Herba)] were commonly used in the above studies. TCM formulations and their constituent compounds showed multi-modal mechanisms relevant to LN pathogenesis, encompassing immunomodulation (reduction of autoreactive B/T cell activity, regulatory T cell enhancement), inhibition of pro-inflammatory signaling pathways nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), mitogen-activated protein kinase (MAPK), nucleotide-binding oligomerization domain (NOD), leucine-rich repeat (LRR) and pyrin domain-containing protein 3 (NLRP3 inflammasome), anti-fibrotic and antioxidant effects, and direct renal-protective properties. In many studies, these indicators can reduce proteinuria and improve renal function. Clinical data, while promising, are heterogeneous in design, sample size, endpoints, and TCM formulation standardization. Safety concerns (notably with Tripterygium preparations) and potential herb-drug interactions with immunosuppressants remained important considerations. Conclusion TCM offers biologically plausible and multi-targeted adjuvant strategies for LN that may enhance therapeutic efficacy and reduce toxicity when combined with modern therapies. To translate these promises into clinical practice, future work should prioritize the standardization of TCM preparations, randomized controlled trials with clinically meaningful renal endpoints, elucidation of molecular mechanisms, and systematic evaluation of pharmacokinetic and safety interactions. Such integrative research will be essential to define the TCM’s role in evidence-based, patient-centered LN management.

Objective: To evaluate the effectiveness and safety of the tonifying spleen and reinforcing Qi (TSRQ) therapy combined with thyroid hormone replacement therapy (THRT) for treating Hashimoto’s hypothyroidism. Methods: From database foundation to January 14, 2025, PubMed, Web of Science, Cochrane, Embase, China National Knowledge Infrastructure (CNKI), Wanfang Data, China Science and Technology Journal Database (VIP), and China Biomedical Literature Database (CBM) were searched for relevant information. Randomized clinical trials (RCTs) evaluating the efficacy and safety of TSRQ therapy combined with THRT for Hashimoto’s hypothyroidism were eligible for inclusion. Following quality assessment, data were analyzed using Stata 15.1 to conduct a meta-analysis and systematic review. Subgroup analysis was used to identify the sources of heterogeneity. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) system was adopted to evaluate the certainty of the evidence. Results: This study included 30 RCTs, comprising 2 687 patients with Hashimoto’s hypothyroidism. Overall methodological quality was acceptable, with no studies exhibiting a high risk of bias. Meta-analysis demonstrated that TSRQ therapy combined with THRT significantly enhanced serum free triiodothyronine (fT3) levels [standardized mean difference (SMD) = 0.76, 95% confidence interval (CI): 0.57 to 0.94, P < 0.001] and free thyroxine (fT4) levels (SMD = 0.86, 95% CI: 0.61 to 1.11, P < 0.001), while reducing thyroid-stimulating hormone (TSH) levels (SMD = – 0.99, 95% CI: – 1.20 to – 0.78, P < 0.001) compared with THRT alone. Furthermore, the combination therapy significantly decreased anti-thyroid peroxidase antibody (TPOAb) levels (SMD = – 1.46, 95% CI: – 1.79 to – 1.13, P < 0.001) and anti-thyroglobulin antibody (TgAb) levels (SMD = – 1.46, 95% CI: – 1.80 to – 1.11, P < 0.001). TSRQ therapy did not adversely impact the safety profile of THRT. However, while some sources of heterogeneity have been identified (e.g., specific detection methodologies, I² = 0.0%, P = 0.938), there remains a portion of unexplained heterogeneity (e.g., publication year, I² = 93.4%, P < 0.001), which has undermined confidence in these pooled estimates. The evidence ratings for fT3, fT4, and TSH were limited, and those for TPOAb and TgAb were even more limited. Conclusion TSRQ therapy combined with THRT may strengthen thyroid function and modulate immune dysregulation in patients with Hashimoto’s hypothyroidism without increasing adverse event incidence.

Objective: To explore the feasibility of constructing a lung cancer early-warning risk model based on facial image features, providing novel insights into the early screening of lung cancer. Methods: This study included patients with pulmonary nodules diagnosed at the Physical Examination Center of Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from November 1, 2019 to December 31, 2024, as well as patients with lung cancer diagnosed in the Oncology Departments of Yueyang Hospital of Integrated Traditional Chinese and Western Medicine and Longhua Hospital during the same period. The facial image information of patients with pulmonary nodules and lung cancer was collected using the TFDA-1 tongue and facial diagnosis instrument, and the facial diagnosis features were extracted from it by deep learning technology. Statistical analysis was conducted on the objective facial diagnosis characteristics of the two groups of participants to explore the differences in their facial image characteristics, and the least absolute shrinkage and selection operator (LASSO) regression was used to screen the characteristic variables. Based on the screened feature variables, four machine learning methods: random forest, logistic regression, support vector machine (SVM), and gradient boosting decision tree (GBDT) were used to establish lung cancer classification models independently. Meanwhile, the model performance was evaluated by indicators such as sensitivity, specificity, F1 score, precision, accuracy, the area under the receiver operating characteristic (ROC) curve (AUC), and the area under the precision-recall curve (AP). Results: A total of 1 275 patients with pulmonary nodules and 1 623 patients with lung cancer were included in this study. After propensity score matching (PSM) to adjust for gender and age, 535 patients were finally included in the pulmonary nodule group and the lung cancer group, respectively. There were significant differences in multiple color space metrics (such as R, G, B, V, L, a, b, Cr, H, Y, and Cb) and texture metrics [such as gray-levcl co-occurrence matrix (GLCM)-contrast (CON) and GLCM-inverse different moment (IDM)] between the two groups of individuals with pulmonary nodules and lung cancer (P < 0.05). To construct a classification model, LASSO regression was used to select 63 key features from the initial 136 facial features. Based on this feature set, the SVM model demonstrated the best performance after 10-fold stratified cross-validation. The model achieved an average AUC of 0.8729 and average accuracy of 0.799 0 on the internal test set. Further validation on an independent test set confirmed the model’s robust performance (AUC = 0.823 3, accuracy = 0.729 0), indicating its good generalization ability. Feature importance analysis demonstrated that color space indicators and the whole/lip Cr components (including color-B-0, wholecolor-Cr, and lipcolor-Cr) were the core factors in the model’s classification decisions, while texture indicators [GLCM-angular second moment (ASM)_2, GLCM-IDM_1, GLCM-CON_1, GLCM-entropy (ENT)_2] played an important auxiliary role. Conclusion The facial image features of patients with lung cancer and pulmonary nodules show significant differences in color and texture characteristics in multiple areas. The various models constructed based on facial image features all demonstrate good performance, indicating that facial image features can serve as potential biomarkers for lung cancer risk prediction, providing a non-invasive and feasible new approach for early lung cancer screening.

Objective: To investigate the therapeutic efficacy and potential mechanisms of fecal microbiota transplantation (FMT) in patients with type 2 diabetes mellitus (T2DM), and to preliminarily identify the traditional Chinese medicine (TCM) syndrome element characteristics of FMT in the treatment of T2DM. Methods: Between March 25, 2023 and September 30, 2024, T2DM patients who met the inclusion and exclusion criteria were enrolled at the Department of Rheumatology and Endocrinology of the Second Affiliated Hospital of Fujian University of Traditional Chinese Medicine. Participants received oral microbiota capsules as an adjunct to metformin therapy. Information obtained by four diagnostic methods of TCM, along with clinical and laboratory parameters, was collected before and after the intervention. Metagenomic sequencing was employed to analyze the gut microbiota, and Spearman correlation analysis was used to explore the relationship between laboratory indicators and differential bacterial genera. According to the post-treatment reduction in glycosylated hemoglobin (HbA1c), patients were categorized into a response (R) group and a non-response (NR) group. Treatment outcomes, safety indicators, gut microbiota changes, and TCM syndrome element features were compared between the two groups. Results: A total of 53 T2DM patients were included in the final analysis, and 30 patients were assigned to R group and 23 to NR group. After treatment, the R group exhibited significant reductions in HbA1c, fasting plasma glucose (FPG), and 2-hour postprandial glucose (2hPG) (P < 0.05 or P < 0.01). The NR group also showed significant decreases in HbA1c and FPG levels P < 0.01 or P < 0.05. Compared with the NR group, after treatment, FPG level in the R group demonstrated significant reductions (P < 0.01). As compared with before treatment, pancreatic islet function demonstrated enhancement in the R group, a significant increase in the 2-hour pastprandial C-peptide (2hC-P) levels in R group (P < 0.05), whereas no marked change was observed in the NR group. Regarding body composition indicators, the R group showed significantly lower waist-hip ratio (WHR), visceral fat (VF), and subcutaneous fat (SF) levels compared with the NR group (P < 0.01). After treatment, the NR group exhibited a significant elevation in aspartate aminotransferase (AST) levels (P < 0.05). Other safety-related indicators fluctuated within normal reference ranges, and no other adverse events, such as diarrhea, fever, or nausea, were reported. Metagenomic sequencing showed that FMT improved the diversity and richness of the gut microbiota, remodeling its overall structure. At the phylum level, the abundance of p_Firmicutes decreased significantly (P < 0.01), while the abundances of p_Bacteroidota and p_Proteobacteria increased significantly (P < 0.01). At the family level, among the 125 identified taxa, the abundances of f_Bacteroidaceae, f_Lactobacillaceae, and f_Sutterellaceae were significantly elevated, whereas six families, including f_Lachnospiraceae, f_Ruminococcaceae, and f_Coriobacteriaceae, were significantly decreased (all P < 0.05). Among the 367 taxa at the genus level, the top 10 differential genera showed significantly increased abundances of g_Bacteroides and g_Sutterella, and significantly decreased abundances in eight genera, including g_Faecalibacterium, g_Ruminococcus, g_Blautia, and g_Collinsella (all P < 0.05). Correlation analysis suggested that the phylum p_Bacillota was positively correlated with improvements in T2DM laboratory parameters, g_norank_f_Prevotellaceae was significantly positively correlated with fasting C-peptide (FC-P) and 2hC-P (P < 0.05). HbA1c demonstrated a significantly positive correlation with g_Blautia and g_Gemmiger (P < 0.05) and a significantly negative correlation with g_Bacteroides and g_Collinsella (P > 0.05). Analysis of syndrome element characteristics revealed that the R group was primarily characterized by pathological patterns of dampness, phlegm, and Yang deficiency. Before treatment, statistically significant reductions in syndrome element scores were observed for dampness, Yang deficiency, spleen, phlegm, Qi deficiency, Qi stagnation, and Yin deficiency (P < 0.01), as well as for heat and liver (P < 0.05). The NR group was mainly featured with Qi deficiency and Yin deficiency. Statistically significant changes in their syndrome element scores after treatment were noted for Qi deficiency (P < 0.01), and for spleen, Qi stagnation, liver, and blood deficiency (P < 0.05). In this group, the score changes for Yang deficiency, Yin deficiency, heat, and dampness were not statistically significant (P > 0.05). Conclusion The principles of syndrome element differentiation can be effectively applied to predict treatment efficacy and facilitate patient selection for FMT in the treatment of T2DM. Patients with T2DM presented with specific TCM syndrome element characteristics, notably dampness, phlegm, and Yang deficiency, represent a highly responsive population to FMT therapy.

Objective: To investigate the effects of Zuogui Jiangtang Yishen Formula (左归降糖益肾方, ZGJTYSF) in regulating the nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3)/caspase-1/gasdermin D (GSDMD) signaling axis on pyroptosis in rats with diabetic kidney disease (DKD). Methods: Fifty male specific pathogen-free (SPF) grade Goto-Kakizaki (GK) rats (12 weeks old) were fed a high-fat diet for one month to establish an early DKD model. Model establishment was confirmed when fasting blood glucose (FBG) ≥ 11.1 mmol/L and urinary albumin-to-creatinine ratio (uACR) ≥ 30 mg/g. The successfully modeled early DKD rats were randomly divided by random number table into five groups (n = 10 per group): model group; dapagliflozin group (1.0 mg/kg, by gavage, served as positive control); and low-, medium-, and high-dose of ZGJTYSF groups (4.9, 9.9, and 19.9 g/kg, respectively, by gavage). Age-matched male SPF Wistar rats (n = 10) served as control group. Rats in control and model groups were gavaged with equivalent volumes of distilled water. Treatment lasted 12 weeks. Changes in uACR, FBG, and renal function were observed in all groups. Hematoxylin-eosin (HE), periodic acid-Schiff (PAS), and Masson staining were used to observe renal histopathological changes. Immunohistochemistry was performed to detect the localization and expression of caspase-1, GSDMD, and NLRP3 in rat renal tissues. Terminal deoxynucleotidyl transferase deoxyuridine triphosphate (dUTP) nick end labeling (TUNEL) was utilized to detect pyroptosis in renal tissues. Quantitative real-time polymerase chain reaction (qPCR) and Western blot were applied to detect mRNA and protein expression levels of NLRP3, caspase-1, GSDMD, interleukin (IL)-1β, and IL-18. Results: Compared with model group, all doses of ZGJTYSF showed reductions in FBG, with medium- and high-dose of ZGJTYSF groups demonstrating significant decreases at week 8 and 12 (P < 0.05). For uACR, all doses of ZGJTYSF groups exhibited a decreasing trend, with high-dose of ZGJTYSF group being significantly lower than low- and medium-dose of ZGJTYSF groups at week 12 (P < 0.05) and showing no significant difference from dapagliflozin group (P > 0.05). No significant differences in renal function parameters (serum creatinine, blood urea nitrogen, and uric acid) were observed among groups (P > 0.05). Histopathological examination revealed milder glomerular and tubular lesions in both ZGJTYSF groups and dapagliflozin group, with renal pathological changes in high-dose of ZGJTYSF group resembling those in dapagliflozin group. Immunohistochemistry demonstrated significantly reduced expression of caspase-1, GSDMD, and NLRP3 in renal tissues of dapagliflozin group and high-dose of ZGJTYSF group compared with model group (P < 0.05 or P < 0.01), while the differences in low- and medium-dose of ZGJTYSF groups were not statistically significant (P > 0.05). TUNEL assay showed significantly fewer TUNEL-positive cells in renal tissues of dapagliflozin and high-dose of ZGJTYSF groups (P < 0.01), indicating a marked reduction in pyroptotic cells. Molecular analysis revealed that compared with model group, both dapagliflozin and high-dose of ZGJTYSF groups showed significantly downregulated mRNA and protein expression levels of NLRP3, caspase-1, GSDMD, IL-1β, and IL-18 in renal tissues (P < 0.01), while low- and medium-dose of ZGJTYSF groups showed downward trends without statistical significance (P > 0.05). Conclusion ZGJTYSF may inhibit renal pyroptosis by regulating the NLRP3/caspase-1/GSDMD signaling axis, thereby preventing and treating early renal injury in DKD and delaying the onset and progression of DKD.

Objective: To observe the effects of moxibustion at Huantiao (GB30) acupoint on nerve repair, regeneration, and function in rats with sciatic nerve injury (SNI), and explore the possible mechanism of SNI improvement via moxibustion. Methods: A total of 70 specific pathogen-free (SPF) grade male Sprague-Dawley (SD) rats were randomly assigned to control group (n = 10) and model group (n = 60). Following replication of SNI to model group rats, 60 SNI model rats were randomly allocated to SNI groups of 1 d, 3 d, and 7 d and moxibustion groups of 1 d, 3 d, and 7 d with 10 rats in each group. Moxibustion groups were given moxibustion at the Huantiao (GB30) acupoint on the affected side with a 5 cm distance from the skin under isoflurane respiratory anesthesia and treated once a day for 20 min for 1 d, 3 d, and 7 d, respectively. Control and SNI groups were anesthetized with isoflurane daily for 20 min. Open field tests and thermal pain threshold tests were conducted, and the general condition of rats was observed in each group pre-modeling and on treatment day 1, 3, and 7. At the end of the treatment, immunofluorescence was used to detect the axonal growth rate, axonal growth density, and Schwann cells (SCs) proliferation in the middle 1-mm cross-section of the crush injury segment in rats. The gastrocnemius muscles on both sides of the rats were taken and weighed to calculate the wet weight ratio of the gastrocnemius muscles on both sides to observe the muscle atrophy of the rats, and hematoxylin-eosin (HE) staining was used to observe the pathomorphological changes of the gastrocnemius muscles on the affected side. Quantitative real-time polymerase chain reaction (qPCR) was used to detect the expression levels of nerve growth factor (NGF), interferon (IFN), macrophage migration inhibitory factor (MIF), interleukin (IL)-4, and transforming growth factor (TGF)-β in the sciatic nerve tissue of the rats. Results: After modeling, rats in both moxibustion and SNI groups showed typical signs of pain behaviors (bending and curling of the hind soles of the affected side, licking claws, and lameness) and decreased activity compared with control group. The main benefits of moxibustion were evident from day 3: compared with SNI group, rats in moxibustion group had marked relief of pain behavior, increased activity levels and movement, and a lower response to thermal pain. At the same time, moxibustion significantly promoted the repair of SNI, as evidenced by the significantly better axonal growth rate, growth density, and SCs proliferation density in the crush injury segment compared with SNI group (P < 0.01). Moxibustion also regulated the local microenvironment of the injury, up-regulated the pro-nerve repair factors NGF, IL-4, and TGF-β (P < 0.05), and down-regulated the pro-inflammatory factors IFN-γ (P < 0.01) and MIF (P < 0.05). By day 7, the histomorphology of the gastrocnemius muscle in moxibustion group was improved, as indicated by enlarged muscle fibers, elevated regular myocyte morphology and wet weight ratio of the affected and unaffected sides (P < 0.05), as well as a sustained high expression levels of NGF, IL-4, and TGF-β (P < 0.05, P < 0.05, and P < 0.01, respectively), and a maintenance of low level of IFN-γ (P < 0.01). Concurrently, the MIF level was not significantly different from SNI group (P > 0.05). Conclusion Moxibustion at the Huantiao (GB30) acupoint effectively improves motor function and promotes recovery of sensory function and nerve regeneration in SNI rats, which may be related to the regulation of local inflammatory response, the promotion of nerve growth factor expression, the improvement of regenerative microenvironment, and the acceleration of SCs proliferation and axonal growth rate in damaged nerves.

Objective: To perform an in silico bioinformatics analysis to identify differentially expressed microRNAs (miRNAs) implicated in rheumatoid arthritis (RA) pathogenesis and evaluate their potential as biomarkers for assessing therapeutic efficacy and monitoring acupuncture treatment. Methods: miRNA microarray data (CEL and TXT formats) were acquired from human and murine RA models, with the latter undergoing acupuncture treatment. Data were normalized using the robust multi-array average (RMA) method and analyzed for differential expression. Differential expression analysis identified miRNAs through a comparative analysis of RA human tissues, acupuncture-treated murine RA models, and a bibliographic search for miRNAs implicated in RA pathogenesis and acupuncture treatment. Bioinformatics analysis was performed to identify potential target genes for each miRNA and signaling pathways via search tools for the Retrieval of Interacting Genes/Proteins (STRING) and ShinyGO. Gene-drug interaction analysis was performed through Drug-Gene Interaction Database (DGIdb) screening. Interaction networks were constructed with the Cytoscape v3.10.3 software. Results: The hsa-miR-125a-5p and hsa-miR-125b-5p were identified as potential biomarkers associated with RA pathogenesis, presenting 468 and 455 target genes, respectively. These genes were enriched in 20 signaling pathways, including Janus kinasa-signal transducer and activator of transcription (JAK-STAT), mitogen-activated protein kinase (MAPK), phosphoinositide 3-kinase-protein kinase B (PI3K-Akt), and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling pathway, which have been associated with RA pathogenesis and progression. Drug-gene interaction networks revealed that 22 genes were significantly associated with 58 RA treatment drugs, among which 13 genes interacted with members of the hsa-miR-125 family. Conclusion The hsa-miR-125a-5p and hsa-miR-125b-5p demonstrate critical regulatory role in RA pathogenesis by modulating signaling pathways, including JAK-STAT, MAPK, PI3K-Akt, and NF-κB. Our findings show that the hsa-miR-125a-5p and hsa-miR-125b-5p exhibit differential expression patterns in response to pharmacological intervention in various diseases, including RA management. This suggests their potential roles as biomarkers for monitoring acupuncture treatment. Although existing evidence indicates that acupuncture can modify miRNA expression profiles, rigorous validation through biological models remains essential to confirm these results.