Effect of luteinizing hormone on follicle stimulating hormone-activated paracrine signalling in rat ovary

‘Pure' follicle stimulating hormone (FSH) and luteinizing hormone (LH) are expected shortly to become available for pharmaceutical use in the clinical setting. To test the contribution of LH to optimal ovarian responsiveness to FSH, 21-day-old hypophysectomized, immature, female rats received four s.c. injections of recombinant human LH (rhLH; total dose 1-10 IU) and/or rhFSH (total dose 30-72 IU) given at 12-hourly intervals. At 48 h after the first injection, ovaries were removed, weighed and used to isolate granulosa and thecal/interstitial cells for assessment of basal and gonadotrophin-responsive steroidogenesis in vitro, or homogenized to extract total RNA for Northern analysis of 17-hydroxylase/C17-20-lyase (cytochrome P-450c17α) mRNA. Serum oestradiol and uterine weight were measured as indices of ovarian oestrogen production; and-rostenedione was measured to reflect ovarian androgen production. Consistent with the two-cell, two-gonadotrophin model of oestrogen synthesis, increased ovarian oestrogen secretion only occurred if both rhFSH and rhLH were given simultaneously. Treatment with rhFSH alone stimulated ovarian weight gain and granulosa cell aromatase activity without oestrogen secretion, whereas rhLH alone stimulated thecal androgen synthesis and androgen secretion. When the total rhLH dose was fixed at 1 IU, giving rise to an unmeasurably low serum concentration of rhLH, additional treatment with rhFSH (30-72 IU) dose-dependently stimulated serum androgen concentrations as well as oestrogen concentrations. The ∼2.0 kb-sized P-450c17α mRNA transcript was undetectable in the ovaries of untreated control animals but was abundant in the ovaries of positive controls treated with 15 IU of pregnant mare serum gonadotrophin. Treatment with 1 IU of rhLH alone barely induced a P-450c17α mRNA signal and treatment with 30 IU of rhFSH alone was completely ineffective. However, combined treatment with 1 IU of rhLH and 30 IU of rhFSH markedly enhanced the P-450c17α mRNA signal to a level approaching the positive-control. Since P-450c17α mRNA is expressed exclusively in thecal cells, which do not possess FSH receptors, we conclude that (i) rhFSH upregulates thecal P-450c17α mRNA and hence follicular androgen synthesis via granulosa-on-theca paracrine signalling, and (ii) tonic stimulation by rhLH is required to facilitate thecal responsiveness to this rhFSH-activated paracrine signal(s

Urology never events in the UK: a retrospective 10-year review

Objectives: The aim was to assess the prevalence of never events (NEs) specific to urology in the United Kingdom and identify commonly occurring themes. Methods: Data from the National Health Service (NHS) NEs website were obtained and all NEs from 2012 to 2022 were reviewed. Urology-specific NEs were identified and further analysed in their respective categories. Data regarding the total number of surgical procedures performed in the NHS specific to each specialty were obtained via the NHS Hospital Episode Statistics website. Results: There were 3972 NEs recorded over the 10-year period with 95 (2.4%) of these as a result of urology surgery. The most common surgical intervention associated with a urological NE was ureteric stenting, which comprised 45/95 (47.4%) of all analysed NEs. These consisted of wrong site ureteric stent insertion (n = 29), wrong site ureteric stent removal (n = 9), wrong stent type (n = 5) and retained guidewires (n = 2). There were 7.14 million urology surgeries performed in the 10-year period, and prevalence was 0.0013%. Conclusion: NEs are fully preventable serious incidents in the NHS. This is the first study to investigate the prevalence of NEs in urology in the United Kingdom. This study demonstrates that in the last 10 years the prevalence of urology NEs is low at 0.0013%, with ureteric stent procedures accounting for more than half of the NEs. Urologists should be mindful of the potential for wrong site surgery in urologic stenting procedures

Randomized trial comparing luteinizing hormone supplementation timing strategies in older women undergoing ovarian stimulation

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Rare variants in the sodium-dependent phosphate transporter gene SLC34A3 explain missing heritability of urinary stone disease

Urinary stone disease (USD) is a major health burden affecting over 10% of the United Kingdom population. While stone disease is associated with lifestyle, genetic factors also strongly contribute. Common genetic variants at multiple loci from genome-wide association studies account for 5% of the estimated 45% heritability of the disorder. Here, we investigated the extent to which rare genetic variation contributes to the unexplained heritability of USD. Among participants of the United Kingdom 100,000-genome project, 374 unrelated individuals were identified and assigned diagnostic codes indicative of USD. Whole genome gene-based rare variant testing and polygenic risk scoring against a control population of 24,930 ancestry-matched controls was performed. We observed (and replicated in an independent dataset) exome-wide significant enrichment of monoallelic rare, predicted damaging variants in the SLC34A3 gene for a sodium-dependent phosphate transporter that were present in 5% cases compared with 1.6% of controls. This gene was previously associated with autosomal recessive disease. The effect on USD risk of having a qualifying SLC34A3 variant was greater than that of a standard deviation increase in polygenic risk derived from GWAS. Addition of the rare qualifying variants in SLC34A3 to a linear model including polygenic score increased the liability-adjusted heritability from 5.1% to 14.2% in the discovery cohort. We conclude that rare variants in SLC34A3 represent an important genetic risk factor for USD, with effect size intermediate between the fully penetrant rare variants linked with Mendelian disorders and common variants associated with USD. Thus, our findings explain some of the heritability unexplained by prior common variant genome-wide association studies

DNA insertions distinguish the duplicated renin genes of DBA/2 and M. hortulanus mice

In a survey of inbred and wild mouse DNAs for genetic variation at the duplicate renin loci, Ren-1 and Ren-2 , a variant Not I hybridization pattern was observed in the wild mouse M. hortulanus . To determine the basis for this variation, the structure of the M. hortulanus renin loci has been examined in detail and compared to that of the inbred strain DBA/2. Overall, the gross features of structure in this chromosomal region are conserved in both Mus species. In particular, the sequence at the recombination site between the linked Ren-1 and Ren-2 loci was found to be identical in both DBA/2 and M. hortulanus , indicating that the renin gene duplication occurred prior to the divergence of ancestors of these mice. Renin flanking sequences in M. hortulanus , however, were found to lack four DNA insertions totaling approximately 10.5 kb which reside near the DBA/2 loci. The postduplication evolution of the mouse renin genes in thus characterized by a number of insertion and/or deletion events within nearby flanking sequences. Analysis of renin expression showed little or no difference between these mice in steady state renin RNA levels in most tissues examined, suggesting that these insertions do not influence expression at those sites. A notable exception is the adrenal gland, in which DBA/2 and M. hortulanus mice exhibit different patterns of developmentally regulated renin expression.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46988/1/335_2004_Article_BF00570438.pd

Use of Temporally Validated Machine Learning Models To Predict Outcomes of Percutaneous Nephrolithotomy Using Data from the British Association of Urological Surgeons Percutaneous Nephrolithotomy Audit

\ua9 2024 European Association of Urology. Background and objective: Machine learning (ML) is a subset of artificial intelligence that uses data to build algorithms to predict specific outcomes. Few ML studies have examined percutaneous nephrolithotomy (PCNL) outcomes. Our objective was to build, streamline, temporally validate, and use ML models for prediction of PCNL outcomes (intensive care admission, postoperative infection, transfusion, adjuvant treatment, postoperative complications, visceral injury, and stone-free status at follow-up) using a comprehensive national database (British Association of Urological Surgeons PCNL). Methods: This was an ML study using data from a prospective national database. Extreme gradient boosting (XGB), deep neural network (DNN), and logistic regression (LR) models were built for each outcome of interest using complete cases only, imputed, and oversampled and imputed/oversampled data sets. All validation was performed with complete cases only. Temporal validation was performed with 2019 data only. A second round used a composite of the most important 11 variables in each model to build the final model for inclusion in the shiny application. We report statistics for prognostic accuracy. Key findings and limitations: The database contains 12 810 patients. The final variables included were age, Charlson comorbidity index, preoperative haemoglobin, Guy\u27s stone score, stone location, size of outer sheath, preoperative midstream urine result, primary puncture site, preoperative dimercapto-succinic acid scan, stone size, and image guidance (https://endourology.shinyapps.io/PCNL_Demographics/). The areas under the receiver operating characteristic curve was >0.6 in all cases. Conclusions and clinical implications: This is the largest ML study on PCNL outcomes to date. The models are temporally valid and therefore can be implemented in clinical practice for patient-specific risk profiling. Further work will be conducted to externally validate the models. Patient summary: We applied artificial intelligence to data for patients who underwent a keyhole surgery to remove kidney stones and developed a model to predict outcomes for this procedure. Doctors could use this tool to advise patients about their risk of complications and the outcomes they can expect after this surgery

Use of temporally validated machine learning models to predict outcomes of percutaneous nephrolithotomy using data from the British Association of Urological Surgeons percutaneous nephrolithotomy audit

Background and objective: Machine learning (ML) is a subset of artificial intelligence that uses data to build algorithms to predict specific outcomes. Few ML studies have examined percutaneous nephrolithotomy (PCNL) outcomes. Our objective was to build, streamline, temporally validate, and use ML models for prediction of PCNL outcomes (intensive care admission, postoperative infection, transfusion, adjuvant treatment, postoperative complications, visceral injury, and stone-free status at follow-up) using a comprehensive national database (British Association of Urological Surgeons PCNL). Methods: This was an ML study using data from a prospective national database. Extreme gradient boosting (XGB), deep neural network (DNN), and logistic regression (LR) models were built for each outcome of interest using complete cases only, imputed, and oversampled and imputed/oversampled data sets. All validation was performed with complete cases only. Temporal validation was performed with 2019 data only. A second round used a composite of the most important 11 variables in each model to build the final model for inclusion in the shiny application. We report statistics for prognostic accuracy. Key findings and limitations: The database contains 12 810 patients. The final variables included were age, Charlson comorbidity index, preoperative haemoglobin, Guy’s stone score, stone location, size of outer sheath, preoperative midstream urine result, primary puncture site, preoperative dimercapto-succinic acid scan, stone size, and image guidance (https://endourology.shinyapps.io/PCNL_Demographics/). The areas under the receiver operating characteristic curve was >0.6 in all cases. Conclusions and clinical implications: This is the largest ML study on PCNL outcomes to date. The models are temporally valid and therefore can be implemented in clinical practice for patient-specific risk profiling. Further work will be conducted to externally validate the models. Patient summary: We applied artificial intelligence to data for patients who underwent a keyhole surgery to remove kidney stones and developed a model to predict outcomes for this procedure. Doctors could use this tool to advise patients about their risk of complications and the outcomes they can expect after this surgery

Bariatric surgery emphasizes biological sex differences in rodent hepatic lipid handling

Abstract Background Eighty percent of patients who receive bariatric surgery are women, yet the majority of preclinical studies are in male rodents. Because sex differences drive hepatic gene expression and overall lipid metabolism, we sought to determine whether sex differences were also apparent in these endpoints in response to bariatric surgery. Methods Two cohorts of age-matched virgin male and female Long-Evans rats were placed on a high fat diet for 3 weeks and then received either Sham or vertical sleeve gastrectomy (VSG), a surgery which resects 80% of the stomach with no intestinal rearrangement. Results Each sex exhibited significantly decreased body weight due to a reduction in fat mass relative to Sham controls (p < 0.05). Microarray and follow-up qPCR on liver revealed striking sex differences in gene expression after VSG that reflected a down-regulation of hepatic lipid metabolism and an up-regulation of hepatic inflammatory pathways in females vs. males after VSG. While the males had a significant reduction in hepatic lipids after VSG, there was no reduction in females. Ad lib-fed and fasting circulating triglycerides, and postprandial chylomicron production were significantly lower in VSG relative to Sham animals of both sexes (p < 0.01). However, hepatic VLDL production, highest in sham-operated females, was significantly reduced by VSG in females but not males. Conclusions Taken together, although both males and females lose weight and improve plasma lipids, there are large-scale sex differences in hepatic gene expression and consequently hepatic lipid metabolism after VSG.http://deepblue.lib.umich.edu/bitstream/2027.42/135948/1/13293_2017_Article_126.pd