Data_Sheet_2_Comprehensive assessment of invalid and indeterminate results in Truenat MTB-RIF testing across sites under the national TB elimination program of India.docx

IntroductionTruenat MTB-RIF assay (Truenat), a nucleic acid amplification test (NAAT), is a real-time polymerase chain reaction (RT-PCR) chip-based assay that can detect Mycobacterium tuberculosis (Mtb) and rifampicin (RIF) drug resistance using portable, battery-operated devices. The National TB Elimination Program (NTEP) in India introduced this novel tool at the district and subdistrict level in 2020. This study aimed to assess the level and causes of inconclusive results (invalid results, errors, and indeterminate results) in MTB and RIF testing at NTEP sites and the root causes of these in the programmatic setting.MethodsTruenat testing data from 1,690 functional Truenat sites under the NTEP from April to June 2021 were analyzed to assess the rates of errors, invalid MTB results, and indeterminate RIF results. Following this analysis, 12 Truenat sites were selected based on site performance in Truenat testing, diversity of climatic conditions, and geographical terrain. These sites were visited to assess the root causes of their high and low rates of inconclusive results using a structured checklist.ResultsA total of 327,649 Truenat tests performed for MTB and RIF testing were analyzed. The rate of invalid MTB results was 5.2% [95% confidence interval (CI): 5.11–5.26; n = 16,998] and the rate of errors was 2.5% (95% CI: 2.46–2.57; n = 8,240) in Truenat MTB chip testing. For Mtb-positive samples tested using the Truenat RIF chip for detection of RIF resistance (n = 40,926), the rate of indeterminate results was 15.3% (95% CI: 14.97–15.67; n = 6,267) and the rate of errors was 1.6% (95% CI: 1.53–1.78; n = 675). There was a 40.1% retesting gap for Mtb testing and a 78.2% gap for inconclusive RR results. Among the inconclusive results retested, 27.9% (95% CI: 27.23–28.66; n = 4,222) were Mtb-positive, and 9.2% (95% CI: 7.84–10.76; n = 139) were detected as RR.ConclusionThe main causes affecting Truenat testing performance include suboptimal adherence to standard operating procedures (SOPs), inadequate training, improper storage of testing kits, inadequate sputum quality, lack of quality control, and delays in the rectification of machine issues. Root cause analysis identified that strengthening of training, external quality control, and supervision could improve the rate of inconclusive results. Ensuring hands-on training of technicians for Truenat testing and retesting of samples with inconclusive results are major recommendations while planning for Truenat scale-up. The recommendations from the study were consolidated into technical guidance documents and videos and disseminated to laboratory staff working at the tiered network of TB laboratories under the NTEP in order to improve Truenat MTB-RIF testing performance.</p

Additional file 6 of Single-cell analysis of menstrual endometrial tissues defines phenotypes associated with endometriosis

Additional file 6. References for genes described in Fig. 6

Additional file 3 of Single-cell analysis of menstrual endometrial tissues defines phenotypes associated with endometriosis

Additional file 3. Cell cluster composition of ME is similar when ME is analyzed after enrichment for endometrial tissues and digested or analyzed as digested whole ME. Comparison of UMAP plots is shown for ME samples prepared by tissue enrichment of menstrual effluent (“ME-Tissue”; 6 diagnosed subjects and 5 controls) or when tissue digestion is applied to unfractionated ME (“whole ME”, 5 diagnosed subjects, and 4 controls). The various cell types are generally well represented between the two approaches to ME preparation. Of note there is an increased yield of epithelial cells in ME samples enriched for tissue. The positive gene markers used to generate the cell clusters shown are included in Additional file 2

Data_Sheet_1_Comprehensive assessment of invalid and indeterminate results in Truenat MTB-RIF testing across sites under the national TB elimination program of India.docx

IntroductionTruenat MTB-RIF assay (Truenat), a nucleic acid amplification test (NAAT), is a real-time polymerase chain reaction (RT-PCR) chip-based assay that can detect Mycobacterium tuberculosis (Mtb) and rifampicin (RIF) drug resistance using portable, battery-operated devices. The National TB Elimination Program (NTEP) in India introduced this novel tool at the district and subdistrict level in 2020. This study aimed to assess the level and causes of inconclusive results (invalid results, errors, and indeterminate results) in MTB and RIF testing at NTEP sites and the root causes of these in the programmatic setting.MethodsTruenat testing data from 1,690 functional Truenat sites under the NTEP from April to June 2021 were analyzed to assess the rates of errors, invalid MTB results, and indeterminate RIF results. Following this analysis, 12 Truenat sites were selected based on site performance in Truenat testing, diversity of climatic conditions, and geographical terrain. These sites were visited to assess the root causes of their high and low rates of inconclusive results using a structured checklist.ResultsA total of 327,649 Truenat tests performed for MTB and RIF testing were analyzed. The rate of invalid MTB results was 5.2% [95% confidence interval (CI): 5.11–5.26; n = 16,998] and the rate of errors was 2.5% (95% CI: 2.46–2.57; n = 8,240) in Truenat MTB chip testing. For Mtb-positive samples tested using the Truenat RIF chip for detection of RIF resistance (n = 40,926), the rate of indeterminate results was 15.3% (95% CI: 14.97–15.67; n = 6,267) and the rate of errors was 1.6% (95% CI: 1.53–1.78; n = 675). There was a 40.1% retesting gap for Mtb testing and a 78.2% gap for inconclusive RR results. Among the inconclusive results retested, 27.9% (95% CI: 27.23–28.66; n = 4,222) were Mtb-positive, and 9.2% (95% CI: 7.84–10.76; n = 139) were detected as RR.ConclusionThe main causes affecting Truenat testing performance include suboptimal adherence to standard operating procedures (SOPs), inadequate training, improper storage of testing kits, inadequate sputum quality, lack of quality control, and delays in the rectification of machine issues. Root cause analysis identified that strengthening of training, external quality control, and supervision could improve the rate of inconclusive results. Ensuring hands-on training of technicians for Truenat testing and retesting of samples with inconclusive results are major recommendations while planning for Truenat scale-up. The recommendations from the study were consolidated into technical guidance documents and videos and disseminated to laboratory staff working at the tiered network of TB laboratories under the NTEP in order to improve Truenat MTB-RIF testing performance.</p

Additional file 12 of Single-cell analysis of menstrual endometrial tissues defines phenotypes associated with endometriosis

Additional file 12. Stromal cells exhibit distinguishing gene markers differentially regulated in ME from endometriosis cases (n=11) and controls (n=9). Violin plots of the top 10 genes that distinguish endometriosis cases and controls within the total stromal cell population in ME. The data suggest that IL11 and other transcripts may be useful in distinguishing stromal cells isolated from ME obtained from endometriosis case vs control subjects

Additional file 9 of Single-cell analysis of menstrual endometrial tissues defines phenotypes associated with endometriosis

Additional file 9. The UMAP plot derived from a reanalysis of endometriosis cases (n=10) and controls (n=9) after removal of one subject on hormones. For this reanalysis, a total of 1112 singlet cells were eliminated from the ME-tissue run from one affected subject on hormones. Only the singlets were analyzed for this revised figure which shows only subtle changes in the details of the UMAP shown in Fig. 3 of the main text

Additional file 4 of Single-cell analysis of menstrual endometrial tissues defines phenotypes associated with endometriosis

Additional file 4. Cell clusters of ME samples distinguish endometriosis cases and symptomatic cases vs. controls. The combined UMAP plot shown in Fig. 1 is split into controls (n = 9), cases (n = 11), and subjects with suggestive symptoms of endometriosis but without laparoscopic tissue diagnosis – the “symptomatic” group (n = 13). Comparisons of uterine NK (uNK) cell and B cell frequencies in the symptomatic group show a trend that is similar to cases vs. controls. The positive gene markers used to generate the cell clusters shown are included in Additional file 2

Additional file 8 of Single-cell analysis of menstrual endometrial tissues defines phenotypes associated with endometriosis

Additional file 8. uNK subclusters reveal a proliferating uNK subcluster enriched in control ME. We have examined subclusters of uterine NK (uNK) cells in our dataset and identified a subcluster whose gene expression patterns reflect cell proliferation, with substantial enrichment of MKI67 and TOP2A. This subset is over 98% matched to a proliferative uNK cell subcluster defined in the decidua of first trimester pregnancy [26]. This subset corresponds to our subset uNK2 that is enriched in controls (Fig. 3)

Additional file 11 of Single-cell analysis of menstrual endometrial tissues defines phenotypes associated with endometriosis

Additional file 11. A reanalysis of stromal cells from endometriosis cases (n=10) and controls (N=9) after removal of one subject on hormones. Not surprisingly, this revised figure shows alterations in the spatial distribution of the UMAP compared to Figure 5 in the main text, but no significant differences in the cell subset distribution comparing cases and controls

Additional file 5 of Single-cell analysis of menstrual endometrial tissues defines phenotypes associated with endometriosis

Additional file 5. Top 10 genes in groups 2 and 4 stromal cell subclusters from Figs. 5 and 6