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Modular reconfiguration of flexible production systems using machine learning and performance estimates
YesThis paper presents an agent-based framework for reconfiguring modular assembly
systems using machine learning and system performance estimates based on previous
reconfigurations. During a reconfiguration, system integrators and engineers make changes to
the machine to meet new production requirements by increasing capacity or manufacturing
new product variants. The framework provides a method for automatically evaluating these
changes in terms of impact on the performance of the production system, and building a
knowledge base. Such knowledge is used to support future reconfigurations by recommending
changes that are likely to improve the performance based on previous reconfigurations. The
agent architecture of the framework has two levels, one for individual assembly stations and
one for the entire production line. Knowledge bases of changes are built and utilised at both
levels using machine learning and performance estimates. A prototype implementation of the
proposed framework has been evaluated on an assembly production system in an industrial
scenario. Preliminary results show that framework helps to reduce the time and resources
required to complete a system reconfiguration and reach the desired production objectives.This work was supported by the SURE Research Projects Fund of the University of Bradford and the European Commission [grant agreement n. 314762]
HNF1B mutations are associated with a Gitelman-like tubulopathy that develops during childhood
Mutations in the transcription factor hepatocyte nuclear factor 1B (HNF1B) are the most common inherited cause of renal malformations, yet also associated with renal tubular dysfunction, most prominently magnesium wasting with hypomagnesemia. The presence of hypomagnesemia has been proposed to help select appropriate patients for genetic testing. Yet, in a large cohort, hypomagnesemia was discriminatory only in adult, but not in pediatric patients. We therefore investigated whether hypomagnesemia and other biochemical changes develop with age.This article is freely available via Open Access. Click on the Additional Link to access full-text
HNF1B Mutations Are Associated With a Gitelman-like Tubulopathy That Develops During Childhood
Background: Mutations in the transcription factor hepatocyte nuclear factor 1B (HNF1B) are the most
common inherited cause of renal malformations, yet also associated with renal tubular dysfunction, most
prominently magnesium wasting with hypomagnesemia. The presence of hypomagnesemia has been
proposed to help select appropriate patients for genetic testing. Yet, in a large cohort, hypomagnesemia
was discriminatory only in adult, but not in pediatric patients. We therefore investigated whether hypomagnesemia and other biochemical changes develop with age.
Methods: We performed a retrospective analysis of clinical, biochemical, and genetic results of pediatric
patients with renal malformations tested for HNF1B mutations, separated into 4 age groups. Values were
excluded if concurrent estimated glomerular filtration rate (eGFR) was <30 ml/min per 1.73 m2
, or after
transplantation.
Results: A total of 199 patients underwent HNF1B genetic testing and mutations were identified in 52
(mutþ). The eGFRs were comparable between mutþ and mut in any age group. Although median
plasma magnesium concentrations differed significantly between mutþ and mut patients in all age
groups, overt hypomagnesemia was not present until the second half of childhood in the mutþ group.
There was also a significant difference in median potassium concentrations in late childhood with lower
values in the mutþ cohort.
Conclusions: The abnormal tubular electrolyte handling associated with HNF1B mutations develops with
age and is not restricted to magnesium, but consistent with a more generalized dysfunction of the distal
convoluted tubule, reminiscent of Gitelman syndrome. The absence of these abnormalities in early
childhood should not preclude HNF1B mutations from diagnostic considerations
Uncovering Genomic Causes of Co-Morbidity in Epilepsy: Gene-Driven Phenotypic Characterization of Rare Microdeletions
Childhood cognitive ability accounts for associations between cognitive ability and brain cortical thickness in old age
Associations between brain cortical tissue volume and cognitive function in old age are frequently interpreted as suggesting that preservation of cortical tissue is the foundation of successful cognitive aging. However, this association could also, in part, reflect a lifelong association between cognitive ability and cortical tissue. We analyzed data on 588 subjects from the Lothian Birth Cohort 1936 who had intelligence quotient (IQ) scores from the same cognitive test available at both 11 and 70 years of age as well as high-resolution brain magnetic resonance imaging data obtained at approximately 73 years of age. Cortical thickness was estimated at 81 924 sampling points across the cortex for each subject using an automated pipeline. Multiple regression was used to assess associations between cortical thickness and the IQ measures at 11 and 70 years. Childhood IQ accounted for more than two-third of the association between IQ at 70 years and cortical thickness measured at age 73 years. This warns against ascribing a causal interpretation to the association between cognitive ability and cortical tissue in old age based on assumptions about, and exclusive reference to, the aging process and any associated disease. Without early-life measures of cognitive ability, it would have been tempting to conclude that preservation of cortical thickness in old age is a foundation for successful cognitive aging when, instead, it is a lifelong association. This being said, results should not be construed as meaning that all studies on aging require direct measures of childhood IQ, but as suggesting that proxy measures of prior cognitive function can be useful to take into consideration
Renal malformations associated with mutations of developmental genes: messages from the clinic
Renal tract malformations (RTMs) account for about 40% of children with end-stage renal failure. RTMs can be caused by mutations of genes normally active in the developing kidney and lower renal tract. Moreover, some RTMs occur in the context of multi-organ malformation syndromes. For these reasons, and because genetic testing is becoming more widely available, pediatric nephrologists should work closely with clinical geneticists to make genetic diagnoses in children with RTMs, followed by appropriate family counseling. Here we highlight families with renal cysts and diabetes, renal coloboma and Fraser syndromes, and a child with microdeletion of chromosome 19q who had a rare combination of malformations. Such diagnoses provide families with often long-sought answers to the question “why was our child born with kidney disease”. Precise genetic diagnoses will also help to define cohorts of children with RTMs for long-term clinical outcome studies
Uncovering genomic causes of co-morbidity in epilepsy: Gene-driven phenotypic characterization of rare microdeletions
Background
Patients with epilepsy often suffer from other important conditions. The existence of such co-morbidities is frequently not recognized and their relationship with epilepsy usually remains unexplained.
Methodology/Principal Findings
We describe three patients with common, sporadic, non-syndromic epilepsies in whom large genomic microdeletions were found during a study of genetic susceptibility to epilepsy. We performed detailed gene-driven clinical investigations in each patient. Disruption of the function of genes in the deleted regions can explain co-morbidities in these patients.
Conclusions/Significance
Co-morbidities in patients with epilepsy can be part of a genomic abnormality even in the absence of (known) congenital malformations or intellectual disabilities. Gene-driven phenotype examination can also reveal clinically significant unsuspected condition
Effects of rare kidney diseases on kidney failure: a longitudinal analysis of the UK National Registry of Rare Kidney Diseases (RaDaR) cohort
\ua9 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licenseBackground: Individuals with rare kidney diseases account for 5–10% of people with chronic kidney disease, but constitute more than 25% of patients receiving kidney replacement therapy. The National Registry of Rare Kidney Diseases (RaDaR) gathers longitudinal data from patients with these conditions, which we used to study disease progression and outcomes of death and kidney failure. Methods: People aged 0–96 years living with 28 types of rare kidney diseases were recruited from 108 UK renal care facilities. The primary outcomes were cumulative incidence of mortality and kidney failure in individuals with rare kidney diseases, which were calculated and compared with that of unselected patients with chronic kidney disease. Cumulative incidence and Kaplan–Meier survival estimates were calculated for the following outcomes: median age at kidney failure; median age at death; time from start of dialysis to death; and time from diagnosis to estimated glomerular filtration rate (eGFR) thresholds, allowing calculation of time from last eGFR of 75 mL/min per 1\ub773 m2 or more to first eGFR of less than 30 mL/min per 1\ub773 m2 (the therapeutic trial window). Findings: Between Jan 18, 2010, and July 25, 2022, 27 285 participants were recruited to RaDaR. Median follow-up time from diagnosis was 9\ub76 years (IQR 5\ub79–16\ub77). RaDaR participants had significantly higher 5-year cumulative incidence of kidney failure than 2\ub781 million UK patients with all-cause chronic kidney disease (28% vs 1%; p<0\ub70001), but better survival rates (standardised mortality ratio 0\ub742 [95% CI 0\ub732–0\ub752]; p<0\ub70001). Median age at kidney failure, median age at death, time from start of dialysis to death, time from diagnosis to eGFR thresholds, and therapeutic trial window all varied substantially between rare diseases. Interpretation: Patients with rare kidney diseases differ from the general population of individuals with chronic kidney disease: they have higher 5-year rates of kidney failure but higher survival than other patients with chronic kidney disease stages 3–5, and so are over-represented in the cohort of patients requiring kidney replacement therapy. Addressing unmet therapeutic need for patients with rare kidney diseases could have a large beneficial effect on long-term kidney replacement therapy demand. Funding: RaDaR is funded by the Medical Research Council, Kidney Research UK, Kidney Care UK, and the Polycystic Kidney Disease Charity
Effects of rare kidney diseases on kidney failure: a longitudinal analysis of the UK National Registry of Rare Kidney Diseases (RaDaR) cohort
Background
Individuals with rare kidney diseases account for 5–10% of people with chronic kidney disease, but constitute more than 25% of patients receiving kidney replacement therapy. The National Registry of Rare Kidney Diseases (RaDaR) gathers longitudinal data from patients with these conditions, which we used to study disease progression and outcomes of death and kidney failure.
Methods
People aged 0–96 years living with 28 types of rare kidney diseases were recruited from 108 UK renal care facilities. The primary outcomes were cumulative incidence of mortality and kidney failure in individuals with rare kidney diseases, which were calculated and compared with that of unselected patients with chronic kidney disease. Cumulative incidence and Kaplan–Meier survival estimates were calculated for the following outcomes: median age at kidney failure; median age at death; time from start of dialysis to death; and time from diagnosis to estimated glomerular filtration rate (eGFR) thresholds, allowing calculation of time from last eGFR of 75 mL/min per 1·73 m2 or more to first eGFR of less than 30 mL/min per 1·73 m2 (the therapeutic trial window).
Findings
Between Jan 18, 2010, and July 25, 2022, 27 285 participants were recruited to RaDaR. Median follow-up time from diagnosis was 9·6 years (IQR 5·9–16·7). RaDaR participants had significantly higher 5-year cumulative incidence of kidney failure than 2·81 million UK patients with all-cause chronic kidney disease (28% vs 1%; p<0·0001), but better survival rates (standardised mortality ratio 0·42 [95% CI 0·32–0·52]; p<0·0001). Median age at kidney failure, median age at death, time from start of dialysis to death, time from diagnosis to eGFR thresholds, and therapeutic trial window all varied substantially between rare diseases.
Interpretation
Patients with rare kidney diseases differ from the general population of individuals with chronic kidney disease: they have higher 5-year rates of kidney failure but higher survival than other patients with chronic kidney disease stages 3–5, and so are over-represented in the cohort of patients requiring kidney replacement therapy. Addressing unmet therapeutic need for patients with rare kidney diseases could have a large beneficial effect on long-term kidney replacement therapy demand.
Funding
RaDaR is funded by the Medical Research Council, Kidney Research UK, Kidney Care UK, and the Polycystic Kidney Disease Charity
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