Background: Emerging evidence suggests that gut microbiota plays a predominant role in Crohn’s disease (CD). However, the microbiome alterations in the early stage of CD patients still remain unclear. The present study aimed to identify dysbacteriosis in patients with early CD and explore specific gut bacteria related to the progression of CD. Methods: This study was nested within a longitudinal prospective Chinese CD cohort, and it included 18 early CD patients, 22 advanced CD patients and 30 healthy controls. The microbiota communities were investigated using high-throughput Illumina HiSeq sequencing targeting the V3–V4 region of 16S ribosomal DNA (rDNA) gene. The relationship between the gut microbiota and clinical characteristics of CD was analyzed. Results: Differential microbiota compositions were observed in CD samples (including early and advanced CD samples) and healthy controls samples. Notably, Lachnospiracea_incertae_sedis and Parabacteroides were enriched in the early CD patients, Escherichia/Shigella, Enterococcus and Proteus were enriched in the advanced CD patients, and Roseburia, Gemmiger, Coprococcus, Ruminococcus 2, Butyricicoccus, Dorea, Fusicatenibacter, Anaerostipes, Clostridium IV were enriched in the healthy controls [LDA score (log10) > 2]. Furthermore, Kruskal–Wallis Rank sum test results showed that Blautia, Clostridium IV, Coprococcus, Dorea, Fusicatenibacter continued to significantly decrease in early and advanced CD patients, and Escherichia/Shigella and Proteus continued to significantly increase compared with healthy controls (P < 0.05). The PICRUSt analysis identified 16 remarkably different metabolic pathways [LDA score (log10) > 2]. Some genera were significantly correlated with various clinical parameters, such as fecal calprotectin, erythrocyte sedimentation rate, C-reactive protein, gland reduce, goblet cells decreased, clinical symptoms (P < 0.05). Conclusions: Dysbacteriosis occurs in the early stage of CD and is associated with the progression of CD. This data provides a foundation that furthers the understanding of the role of gut microbiota in CD’s pathogenesis.

This study investigated the longitudinal effects of acute (7-day) and prolonged (3-month) high-altitude exposure on gut microbiota in healthy adult males, addressing the limited data available in human populations. A cohort of 406 healthy adult males was followed, and fecal samples were collected at three time points: baseline at 800 m (406 samples), 7 days after ascending to 4,500 m (406 samples), and 2 weeks post-return to 800 m following 3 months at high altitude (186 samples). High-throughput 16S ribosomal DNA sequencing was employed to analyze microbiota composition and diversity. Results revealed significant changes in alpha- and beta-diversity, with acute high-altitude exposure inducing more pronounced effects compared to prolonged exposure. Specifically, acute exposure increased opportunistic pathogens ( Ruminococcus and Oscillibacter ) but decreased beneficial short-chain fatty acid producers ( Faecalibacterium and Bifidobacterium ). Notably, these changes in microbiota persisted even after returning to low altitude, indicating long-term remodeling. Functional analyses revealed substantial changes in metabolic pathways, suggesting microbiota-driven adaptations to energy utilization under high-altitude hypoxic conditions. In summary, acute high-altitude exposure caused dramatic changes in gut microbiota, while prolonged exposure led to structural and functional reshaping. These findings enhance our understanding of how high-altitude environments reshape gut microbiota. IMPORTANCE: This study is the first to investigate the impact of high-altitude exposure on gut microbiota adaptation in a large-scale longitudinal cohort. It seeks to enhance understanding of how high-altitude environments reshape gut microbiota. Acute exposure to high altitude significantly affected both α-diversity and β-diversity of gut microbiota, with acute exposure causing more pronounced changes than prolonged adaptation, indicating temporary disruptions in microbial communities. Notable shifts in microbial abundance were observed, including increased levels of genera linked to hypoxic stress (e.g., Gemmiger , Ruminococcus , and Parabacteroides ) and decreased levels of beneficial bacteria (e.g., Faecalibacterium , Roseburia , and Bifidobacterium ), suggesting possible adverse health effects. Functional analysis indicated changes in metabolism-related pathways post-exposure, supporting the idea that high-altitude adaptations involve metabolic adjustments for energy management. These findings enhance understanding of high-altitude physiology, illustrating the role of gut microbiota in hypoxic health.

Despite universal endoscopic screening, early detection of gastric cancer is challenging, led researchers to seek for a novel approach in detecting. Raman spectroscopy measurements as a fingerprint of biochemical structure, enable accurate prediction of gastric lesions non-destructively. This study aimed to evaluate the diagnostic power of Raman spectroscopy in early gastric cancer (EGC), and reveal dynamic biomolecular changes in vitro from normal to EGC. To clarify the biochemical alterations in Correa's cascade, Raman spectra of human normal gastric mucosa, intestinal metaplasia, dysplasia, and adenocarcinoma were compared at tissue and cellular levels based on a self-developed data processing program. For effectively identify EGC, Raman spectroscopy was used combined with multiple machine learning methods, including partial least-squares discriminant analysis (PLS-DA), support vector machine (SVM), and convolutional neural network (CNN) with leave-one-out (LOO) cross validation. A total of 450 Raman spectra were investigated in this study. The upregulation of ν_sym(O-P-O) backbone (p < 0.001) was identified as a favorable factor for the diagnosis of EGC, the area under the ROC curve (AUC) was up to 0.918. In addition, higher levels of lactic acid (p < 0.001), lipids (p < 0.001), phenylalanine (p = 0.002), and carotenoids (p < 0.001) were detected in EGC. Multivariate machine learning methods for diagnosis of EGC based on Raman spectroscopy, the sensitivity, specificity, accuracy, and AUC were 91.0%, 100%, 94.8%, and 95.8% for SVM, and 84.8%, 92.0%, 88.8%, and 95.5% for CNN, respectively. Raman spectroscopy can be used as a powerful tool for detecting EGC while elucidating biomolecular dynamics in tumorigenesis. (Chictr.org.cn, ChiCTR2200060720.).

Background: Colorectal cancer (CRC), a commonly diagnosed cancer often develops slowly from benign polyps called adenoma to carcinoma. Altered gut microbiota is implicated in colorectal carcinogenesis. It is warranted to find non-invasive progressive microbiota biomarkers that can reflect the dynamic changes of the disease. This study aimed to identify and evaluate potential progressive fecal microbiota gene markers for diagnosing advanced adenoma (AA) and CRC. Results: Metagenome-wide association was performed on fecal samples from different cohorts of 871 subjects (247 CRC, 234 AA, and 390 controls). We characterized the gut microbiome, identified microbiota markers, and further constructed a colorectal neoplasms classifier in 99 CRC, 94 AA, and 62 controls, and validated the results in 185 CRC, 140 AA, and 291 controls from 3 independent cohorts. 21 species and 277 gene markers were identified whose abundance was significantly increased or decreased from normal to AA and CRC. The progressive gene markers were distributed in metabolic pathways including amino acid and sulfur metabolism. A diagnosis model consisting of four effect indexes was constructed based on the markers, the sensitivities of the Adenoma Effect Index 1 for AA, Adenoma Effect Index 2 for high-grade dysplasia (HGD) adenoma were 71.3% and 76.5%, the specificities were 90.5% and 90.3%, respectively. CRC Effect Index 1 for all stages of CRC and CRC Effect Index 2 for stage III–IV CRC to predict CRC yielded an area under the curve (AUC) of 0.839 (95% CI 0.804–0.873) and 0.857 (95% CI 0.793–0.921), respectively. Combining with fecal immunochemical test (FIT) significantly improved the sensitivity of CRC Effect Index 1 and CRC Effect Index 2 to 96.7% and 100%. Conclusions: This study reports the successful diagnosis model establishment and cross-region validation for colorectal advanced adenoma and carcinoma based on the progressive gut microbiota gene markers. The results suggested that the novel diagnosis model can significantly improve the diagnostic performance for advanced adenoma.

Few studies have provided data on the metabolomics characteristics of metabolic diseases such as hyperuricemia and hyperbilirubinemia in the Tibetan plateau. In the current study, we sought to investigate the serum metabolomics characteristics of hyperbilirubinemia and hyperuricemia in the Tibetan plateau, with the aim to provide a basis for further research on their pathogenesis, prevention, and treatment. The study participants were born in low-altitude areas below 1000 m and had no prior experience living in a high-altitude area before entering Golmud, Tibet (average elevation: 3000 m) and Yushu, Qinghai (average elevation: 4200 m). Thirty-four participants with hyperbilirubinemia (18 in Golmud and 16 in Yushu), 24 participants with hyperuricemia, and 22 healthy controls were enrolled. The serum samples of subjects were separated and then sent to a local tertiary hospital for biochemical examination. Serum widely targeted technology, based on the ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) platform, was used to detect serum metabolites and differential metabolites. Compared to the healthy controls, hyperbilirubinemia patients from Golmud showed 19 differential metabolites, hyperbilirubinemia patients from Yushu showed 12 differential metabolites, and hyperuricemia patients from Yushu showed 23 differential metabolites. Compared to the hyperbilirubinemia patients from Golmud that is at a low altitude, the Yushu groups had 33 different metabolites. Differential metabolites are primarily classified into amino acids and their derivatives, nucleotides and their derivatives, organic acids and their derivatives, and lipids/fatty acids. These are related to metabolic pathways such as caffeine metabolism, arachidonic acid metabolism, and tyrosine metabolism. Hyperbilirubinemia and hyperuricemia in the Tibetan plateau have unique serum metabolomics characteristics. Glycine derivatives and arachidonic acid and its derivatives were associated with plateau hyperbilirubinemia, and vanillic acid and pentadecafluorooctanoic acid were associated with plateau hyperuricemia.