Supplementary Materials.zip

Supplementary materials<br

Table_1_Fecal Microbiota Transplantation Modulates the Gut Flora Favoring Patients With Functional Constipation.XLSX

Intestinal dysmotility is common in many diseases and is correlated with gut microbiota dysbiosis and systemic inflammation. Functional constipation (FC) is the most typical manifestation of intestinal hypomotility and reduces patients’ quality of life. Some studies have reported that fecal micriobiota transplantation (FMT) may be an effective and safe therapy for FC as it corrects intestinal dysbiosis. This study was conducted to evaluate how FMT remodels the gut microbiome and to determine a possible correlation between certain microbes and clinical symptoms in constipated individuals. Data were retrospectively collected on 18 patients who underwent FMT between January 1, 2019 and June 30, 2020. The fecal bacterial genome was detected by sequencing the V3–V4 hypervariable regions of the 16S rDNA gene. Fecal short chain fatty acids (SCFAs) were detected by gas chromatography-mass spectrometry, and serum inflammatory factor concentrations were detected via enzyme-linked immunosorbent assay. Comparing the changes in fecal microbiome compositions before and after FMT revealed a significant augmentation in the alpha diversity and increased abundances of some flora such as Clostridiales, Fusicatenibacter, and Paraprevotella. This was consistent with the patients experiencing relief from their clinical symptoms. Abundances of other flora, including Lachnoanaerobaculum, were decreased, which might correlate with the severity of patients’ constipation. Although no differences were found in SCFA production, the butyric acid concentration was correlated with both bacterial alterations and clinical symptoms. Serum IL-8 levels were significantly lower after FMT than at baseline, but IL-4, IL-6, IL-10, and IL-12p70 levels were not noticeably changed. This study showed how FMT regulates the intestinal microenvironment and affects systemic inflammation in constipated patients, providing direction for further research on the mechanisms of FMT. It also revealed potential microbial targets for precise intervention, which may bring new breakthroughs in treating constipation.</p

Additional file 2 of Perturbed gut microbiome and fecal and serum metabolomes are associated with chronic kidney disease severity

Additional file 2: Additional Fig. 1. Correlation analysis between CKD severity-related microbiotas and clinical parameters. (A) Spearman correlation analysis showed significant relationships between eGFR and CKD severity-related microbial family, comprising Enterobacteriaceae, Lactobacillaceae and Veillonellaceae (P<0.05). (B) Heatmaps representation of spearman correlation between continuous clinical parameters and the CKD severity-related species (*P<0.05, **P<0.01, ***P<0.001). (C) Multivariate analysis by using canonical correspondence analysis (CCA) showed that there were insufficient influences of hypertension (HBP), type 2 diabetes (D2M), hemoglobin (HB) and serum albumin (Alb) on CKD severity-related microbial species

Galbraith plot [<b>12</b>] analysis of the amount of heterogeneity from all the included studies (AA vs. GG).

<p>The y-axis shows the ratio of the log OR to its standard error (SE), and the x-axis shows the reciprocal of the SE. Each study is represented by the name of the first author. A regression line runs centrally through the name. At a 2 standard deviation distance parallel to the regression line, the 2 lines create an interval. Studies lacking in heterogeneity would lie within the 95% confidence interval (positioned 2 units above and below the central regression line).</p

The L’Abbé plot [<b>14</b>] for the assessment of CRC risk in each group (G/A+A/A vs. G/G).

<p>Each circle represents individual trial sizes, and the circles are proportional to the study weights (participant number). The diagonal dotted line indicates that the CRC risk was equal in the two arms within the trials. The solid regression line represented a summary OR of 1.127 (G/A+A/A vs. G/G), which was estimated from the pooled results of all 22 studies.</p

Image_2_Treatment Response, Survival Benefit and Safety Profile of PD-1 Inhibitor Plus Apatinib Versus Apatinib Monotherapy in Advanced Colorectal Cancer Patients.tif

PurposeProgrammed cell death protein 1 (PD-1) inhibitor plus apatinib is reported to be a promising strategy for advanced cancers. Moreover, a PD-1 inhibitor or apatinib exerts a certain efficacy in advanced colorectal cancer (CRC), whereas their synergistic effect is unclear. This study aimed to evaluate the treatment efficacy and safety of a PD-1 inhibitor plus apatinib in advanced CRC patients.MethodsIn total, 45 advanced CRC patients who received a PD-1 inhibitor plus apatinib (PD-1 inhibitor plus apatinib group, N=20) or apatinib monotherapy (apatinib group, N=25) as third-line therapies were enrolled in the current study.ResultsThe objective response rate (20.0% vs. 8.0%) (P=0.383) and disease control rate (70.0% vs. 52.0%) (P=0.221) were numerically increased in the PD-1 inhibitor plus apatinib group, respectively, compared with the apatinib group, but no statistical significance was observed. The median progression-free survival (PFS) was 7.5 versus 4.8 months; the 1-year PFS rate was 32.5% versus 9.9%; the median overall survival (OS) was 12.3 versus 8.7 months; and the 1-year OS rate was 50.7% versus 27.0% in the PD-1 inhibitor plus apatinib group versus the apatinib group, respectively. PFS (P=0.038) and OS (P=0.048) were prolonged in the PD-1 inhibitor plus apatinib group compared with the apatinib group. PD-1 inhibitor plus apatinib (versus apatinib) was independently associated with longer PFS (P=0.012) and OS (P=0.009). The majority of the adverse events were of grade 1-2, wherein the incidence was similar between groups, except for the fact that the incidence of capillary proliferation was elevated in the PD-1 inhibitor plus apatinib group compared with the apatinib group (25.5% versus 0.0%) (P=0.013).ConclusionPD-1 inhibitor plus apatinib presents a potential improvement in efficacy and survival benefit compared with apatinib monotherapy, with tolerable safety in advanced CRC patients.</p

Additional file 3 of Perturbed gut microbiome and fecal and serum metabolomes are associated with chronic kidney disease severity

Additional file 3: Additional Fig. 2. Association of clinical phenotypes and CKD severity-related metabolites. Heatmaps representation of spearman correlation between clinical parameters and the CKD severity-related metabolites of arginine and proline metabolism, arachidonic acid metabolism, ubiquinone and other terpenoid-quinone biosynthesis and glutathione metabolism in (A) fecal and (B) blood samples (*P<0.05, **P<0.01, ***P<0.001)

Image_1_Treatment Response, Survival Benefit and Safety Profile of PD-1 Inhibitor Plus Apatinib Versus Apatinib Monotherapy in Advanced Colorectal Cancer Patients.tif

PurposeProgrammed cell death protein 1 (PD-1) inhibitor plus apatinib is reported to be a promising strategy for advanced cancers. Moreover, a PD-1 inhibitor or apatinib exerts a certain efficacy in advanced colorectal cancer (CRC), whereas their synergistic effect is unclear. This study aimed to evaluate the treatment efficacy and safety of a PD-1 inhibitor plus apatinib in advanced CRC patients.MethodsIn total, 45 advanced CRC patients who received a PD-1 inhibitor plus apatinib (PD-1 inhibitor plus apatinib group, N=20) or apatinib monotherapy (apatinib group, N=25) as third-line therapies were enrolled in the current study.ResultsThe objective response rate (20.0% vs. 8.0%) (P=0.383) and disease control rate (70.0% vs. 52.0%) (P=0.221) were numerically increased in the PD-1 inhibitor plus apatinib group, respectively, compared with the apatinib group, but no statistical significance was observed. The median progression-free survival (PFS) was 7.5 versus 4.8 months; the 1-year PFS rate was 32.5% versus 9.9%; the median overall survival (OS) was 12.3 versus 8.7 months; and the 1-year OS rate was 50.7% versus 27.0% in the PD-1 inhibitor plus apatinib group versus the apatinib group, respectively. PFS (P=0.038) and OS (P=0.048) were prolonged in the PD-1 inhibitor plus apatinib group compared with the apatinib group. PD-1 inhibitor plus apatinib (versus apatinib) was independently associated with longer PFS (P=0.012) and OS (P=0.009). The majority of the adverse events were of grade 1-2, wherein the incidence was similar between groups, except for the fact that the incidence of capillary proliferation was elevated in the PD-1 inhibitor plus apatinib group compared with the apatinib group (25.5% versus 0.0%) (P=0.013).ConclusionPD-1 inhibitor plus apatinib presents a potential improvement in efficacy and survival benefit compared with apatinib monotherapy, with tolerable safety in advanced CRC patients.</p

Characteristics of the studies included in the meta-analysis.

<p>HWE: Hardy–Weinberg equilibrium; US: United States; UK: United Kingdom; HNPCC: hereditary nonpolyposis colorectal cancer; sCRC: sporadic colorectal cancer; sCC: sporadic colonic cancer; FB: family-based study; PB: population-based study; HB: hospital-based study; PCR: polymerase chain reaction; SSCP: single-stranded conformation polymorphism; RFLP: restriction fragment length polymorphism; HPLC: high-performance liquid chromatography.</p

Additional file 1 of Perturbed gut microbiome and fecal and serum metabolomes are associated with chronic kidney disease severity

Additional file 1: Additional Tables 1–10. Additional tables are separated in sheets in a single excel file. The first line in each sheet contains the title of each additional table. Supplementary Table 1. Post-hoc multiple analysis for study population characteristics. Supplementary Table 2. Comparisons of micaobial alpha diversity, beta diversity and taxa in each of the CKD groups with controls. Supplementary Table 3. Spearman correlation analysis between clinical data and CKD severity-specific species. Supplementary Table 4. Significant KO genes of those four metabolism pathways between each of the CKD groups and healthy controls. Supplementary Table 5. All differential fecal metabolites among each of the CKD groups and controls (VIP>1, FDR1, FDR<0.05). Supplementary Table 7. Comparison of fecal metabolites related to Arginine and proline metabolism, Arachidonic acid metabolism, Ubiquinone and other terpenoid-quinone biosynthesis and Glutathione metabolism between each of the CKD groups and healthy control group.Statistical analysis was performed by Wilcoxon rank-sum test. Benjamini-Hochberg procedure was employed for the multiple test adjustments. Supplementary Table 8. Comparison of serum metabolites related to Arginine and proline metabolism, Arachidonic acid metabolism, Ubiquinone and other terpenoid-quinone biosynthesis and Glutathione metabolism between each of the CKD groups and healthy control group.Statistical analysis was performed by Wilcoxon rank-sum test. Benjamini-Hochberg procedure was employed for the multiple test adjustments. Supplementary Table 9. Spearman correlation analysis between clinical data and CKD severity-specific metabolites. Supplementary Table10. Performance of random-forest models discriminating CKD patients at different groups from controls based on 100-fold Cross-Validation