Catalytic Asymmetric 1,3-Dipolar [3 + 6] Cycloaddition of Azomethine Ylides with 2‑Acyl Cycloheptatrienes: Efficient Construction of Bridged Heterocycles Bearing Piperidine Moiety

Conjugated cyclic trienes without nonbenzenoid aromatic characteristic were successfully employed as fine-tunable dipolarophiles in the Cu­(I)-catalyzed asymmetric azomethine ylide-involved 1,3-dipolar [3 + 6] cycloaddition for the first time, affording a variety of bridged heterocycles bearing piperidine moiety in good yield with exclusive regioselectivity and excellent stereoselectivity. 2-Acyl group is the key factor that determines the annulation preferentially through [3 + 6]-pathway, while 2-ester group modulates the annulation through [3 + 2]-pathway

Association between <i>MTHFD1</i> G1958A Polymorphism and Neural Tube Defects Susceptibility: A Meta-Analysis

<div><p>Objectives</p><p>The methylenetetrahydrofolate dehydrogenase (<i>MTHFD1</i>) gene, as one of the key genes involved in the folate pathway, has been reported to play a critical role in the pathogenesis of neural tube defects (NTDs). However, the results of published studies are contradictory and inconclusive. Thus, this meta-analysis aimed to evaluate the effect of the common polymorphism in the <i>MTHFD1</i> gene, the G1958A (R653Q, dbSNP ID: rs2236225) variant, on the risk of NTDs in all eligible studies.</p><p>Methods</p><p>Relevant literature published before January 3, 2014 was retrieved from the MEDLINE, EMBASE, Cochrane Library, and CBM databases. Pooled crude odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) were calculated to evaluate the association between the <i>MTHFD1</i> G1958A polymorphism and NTDs risk.</p><p>Results</p><p>We performed a meta-analysis of nine studies with a total of 4,302 NTDs patients and 4,238 healthy controls. Our results demonstrated a significant correlation between the <i>MTHFD1</i> G1958A polymorphism and NTDs in an overall meta-analysis. For family-based studies, the study subjects were classified as NTD cases, mothers with NTDs offspring, and fathers with NTDs offspring. We found no association between any of the fathers’ genotypes and NTDs, whereas there was a clear excess of the 1958A allele in the mothers of children with NTDs compared with controls individuals.</p><p>Conclusions</p><p>In summary, our meta-analysis strongly suggests that the <i>MTHFD1</i> G1958A polymorphism might be associated with maternal risk for NTDs in Caucasian populations. However, the evidence of this association should be interpreted with caution due to the selective nature of publication of genetic association studies.</p></div

Forest plots of ORs for the association between the <i>MTHFD1</i> G1958A polymorphism and susceptibility to NTDs in family-based studies for each subgroup under (A: A allele vs. G allele; B: AA vs. AG+GG; C: AA vs. GG; D: AA vs. AG).

<p>Forest plots of ORs for the association between the <i>MTHFD1</i> G1958A polymorphism and susceptibility to NTDs in family-based studies for each subgroup under (A: A allele vs. G allele; B: AA vs. AG+GG; C: AA vs. GG; D: AA vs. AG).</p

Main characteristics of the studies included in the meta-analysis.

<p>PCR-RFLP, Polymerase chain reaction-restriction fragment length polymorphism; PCR-SSCP, PCR-single strand conformation polymorphism; NOS, Newcastle-Ottawa scale.</p

Forest plots of ORs for the association between the <i>MTHFD1</i> G1958A polymorphism and susceptibility to NTDs (A: A allele vs. G allele; B: AA vs. AG+GG; C: AA vs. GG; D: AA vs. AG).

<p>Forest plots of ORs for the association between the <i>MTHFD1</i> G1958A polymorphism and susceptibility to NTDs (A: A allele vs. G allele; B: AA vs. AG+GG; C: AA vs. GG; D: AA vs. AG).</p

Summary ors of the association between <i>MTHFD1</i> G1958A polymorphism and risk for NTDs.

<p>OR, odd ratio; CI; confidence interval.</p

Table1_Diagnostic performance of GcfDNA in kidney allograft rejection: a meta-analysis.DOCX

In this comprehensive meta-analysis, our objective was to evaluate the diagnostic utility of graft-derived cell-free DNA (GcfDNA) in kidney allograft rejection and explore associated factors. We conducted a thorough search of PubMed, Embase, and the Cochrane Library databases, spanning from their inception to September 2022. Statistical analysis was executed utilizing Stata 15, Meta-DiSc 1.4, and Review Manager 5.4 software. The combined pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the summary receiver operating characteristics (SROC) curve from the synthesis of findings across ten studies were as follows: 0.75 (0.67–0.81), 0.78 (0.72–0.83), 3.36 (2.89–4.35), 0.32 (0.24–0.44), 8.77 (4.34–17.74), and 0.83 (0.80–0.86), respectively. Among the ten studies primarily focused on GcfDNA’s diagnostic potential for antibody-mediated rejection (ABMR), the optimal cut-off threshold demonstrated substantial diagnostic efficacy, with pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, DOR, and area under the summary receiver operating characteristics curve values of 0.83 (0.74–0.89), 0.75 (0.70–0.80), 3.37 (2.64–4.30), 0.23 (0.15–0.36), 14.65 (7.94–27.03), and 0.85 (0.82–0.88), respectively. These results underscore the high diagnostic accuracy of GcfDNA in detecting rejection. Furthermore, the optimal cut-off threshold proves effective in diagnosing ABMR, while a 1% threshold remains a robust diagnostic criterion for rejection. Notably, for ABMR diagnosis, droplet digital PCR digital droplet polymerase chain reaction emerges as a superior method in terms of accuracy when compared to other techniques. Nonetheless, further research is warranted to substantiate these findings.</p

Flow diagram of studies with specific reasons for inclusion/exclusion in the present meta-analysis.

<p>Flow diagram of studies with specific reasons for inclusion/exclusion in the present meta-analysis.</p

Table2_Diagnostic performance of GcfDNA in kidney allograft rejection: a meta-analysis.DOCX

In this comprehensive meta-analysis, our objective was to evaluate the diagnostic utility of graft-derived cell-free DNA (GcfDNA) in kidney allograft rejection and explore associated factors. We conducted a thorough search of PubMed, Embase, and the Cochrane Library databases, spanning from their inception to September 2022. Statistical analysis was executed utilizing Stata 15, Meta-DiSc 1.4, and Review Manager 5.4 software. The combined pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the summary receiver operating characteristics (SROC) curve from the synthesis of findings across ten studies were as follows: 0.75 (0.67–0.81), 0.78 (0.72–0.83), 3.36 (2.89–4.35), 0.32 (0.24–0.44), 8.77 (4.34–17.74), and 0.83 (0.80–0.86), respectively. Among the ten studies primarily focused on GcfDNA’s diagnostic potential for antibody-mediated rejection (ABMR), the optimal cut-off threshold demonstrated substantial diagnostic efficacy, with pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, DOR, and area under the summary receiver operating characteristics curve values of 0.83 (0.74–0.89), 0.75 (0.70–0.80), 3.37 (2.64–4.30), 0.23 (0.15–0.36), 14.65 (7.94–27.03), and 0.85 (0.82–0.88), respectively. These results underscore the high diagnostic accuracy of GcfDNA in detecting rejection. Furthermore, the optimal cut-off threshold proves effective in diagnosing ABMR, while a 1% threshold remains a robust diagnostic criterion for rejection. Notably, for ABMR diagnosis, droplet digital PCR digital droplet polymerase chain reaction emerges as a superior method in terms of accuracy when compared to other techniques. Nonetheless, further research is warranted to substantiate these findings.</p

DataSheet2_Diagnostic performance of GcfDNA in kidney allograft rejection: a meta-analysis.DOCX

In this comprehensive meta-analysis, our objective was to evaluate the diagnostic utility of graft-derived cell-free DNA (GcfDNA) in kidney allograft rejection and explore associated factors. We conducted a thorough search of PubMed, Embase, and the Cochrane Library databases, spanning from their inception to September 2022. Statistical analysis was executed utilizing Stata 15, Meta-DiSc 1.4, and Review Manager 5.4 software. The combined pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the summary receiver operating characteristics (SROC) curve from the synthesis of findings across ten studies were as follows: 0.75 (0.67–0.81), 0.78 (0.72–0.83), 3.36 (2.89–4.35), 0.32 (0.24–0.44), 8.77 (4.34–17.74), and 0.83 (0.80–0.86), respectively. Among the ten studies primarily focused on GcfDNA’s diagnostic potential for antibody-mediated rejection (ABMR), the optimal cut-off threshold demonstrated substantial diagnostic efficacy, with pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, DOR, and area under the summary receiver operating characteristics curve values of 0.83 (0.74–0.89), 0.75 (0.70–0.80), 3.37 (2.64–4.30), 0.23 (0.15–0.36), 14.65 (7.94–27.03), and 0.85 (0.82–0.88), respectively. These results underscore the high diagnostic accuracy of GcfDNA in detecting rejection. Furthermore, the optimal cut-off threshold proves effective in diagnosing ABMR, while a 1% threshold remains a robust diagnostic criterion for rejection. Notably, for ABMR diagnosis, droplet digital PCR digital droplet polymerase chain reaction emerges as a superior method in terms of accuracy when compared to other techniques. Nonetheless, further research is warranted to substantiate these findings.</p