Genetic programming assisted stochastic optimization strategies for optimization of glucose to gluconic acid fermentation

This article presents two hybrid strategies for the modeling and optimization of the glucose to gluconic acid batch bioprocess. In the hybrid approaches, first a novel artificial intelligence formalism, namely, genetic programming (GP), is used to develop a process model solely from the historic process input-output data. In the next step, the input space of the GP-based model, representing process operating conditions, is optimized using two stochastic optimization (SO) formalisms, viz., genetic algorithms (GAs) and simultaneous perturbation stochastic approximation (SPSA). These SO formalisms possess certain unique advantages over the commonly used gradient-based optimization techniques. The principal advantage of the GP-GA and GP-SPSA hybrid techniques is that process modeling and optimization can be performed exclusively from the process input-output data without invoking the detailed knowledge of the process phenomenology. The GP-GA and GP-SPSA techniques have been employed for modeling and optimization of the glucose to gluconic acid bioprocess, and the optimized process operating conditions obtained thereby have been compared with those obtained using two other hybrid modeling-optimization paradigms integrating artificial neural networks (ANNs) and GA/SPSA formalisms. Finally, the overall optimized operating conditions given by the GP-GA method, when verified experimentally resulted in a significant improvement in the gluconic acid yield. The hybrid strategies presented here are generic in nature and can be employed for modeling and optimization of a wide variety of batch and continuous bioprocesses

Development and Standardisation of a Method for Inflicting Frostbite Injury in Rats and Formulation of Essential Oil in Treatment of Frostbite

Frostbite is a cold induced injury which occurs due to exposure of a particular site of body to sub-zero temperature. One of the primary reasons for lack of proper studies about the underlying mechanism of frostbite injury is due to non-availability of any reliable animal model and method for inflicting frostbite. In our current research, a device was designed and standardised to inflict frostbite wound in wistar rat. A formulation comprising different combination of essential oils was also developed and its activity was assessed and found effective in the treatment of frostbite wound

Assessment of the incorporation of CNV surveillance into gene panel next-generation sequencing testing for inherited retinal diseases.

BACKGROUND: Diagnostic use of gene panel next-generation sequencing (NGS) techniques is commonplace for individuals with inherited retinal dystrophies (IRDs), a highly genetically heterogeneous group of disorders. However, these techniques have often failed to capture the complete spectrum of genomic variation causing IRD, including CNVs. This study assessed the applicability of introducing CNV surveillance into first-tier diagnostic gene panel NGS services for IRD. METHODS: Three read-depth algorithms were applied to gene panel NGS data sets for 550 referred individuals, and informatics strategies used for quality assurance and CNV filtering. CNV events were confirmed and reported to referring clinicians through an accredited diagnostic laboratory. RESULTS: We confirmed the presence of 33 deletions and 11 duplications, determining these findings to contribute to the confirmed or provisional molecular diagnosis of IRD for 25 individuals. We show that at least 7% of individuals referred for diagnostic testing for IRD have a CNV within genes relevant to their clinical diagnosis, and determined a positive predictive value of 79% for the employed CNV filtering techniques. CONCLUSION: Incorporation of CNV analysis increases diagnostic yield of gene panel NGS diagnostic tests for IRD, increases clarity in diagnostic reporting and expands the spectrum of known disease-causing mutations

Clustered Coding Variants in the Glutamate Receptor Complexes of Individuals with Schizophrenia and Bipolar Disorder

Current models of schizophrenia and bipolar disorder implicate multiple genes, however their biological relationships remain elusive. To test the genetic role of glutamate receptors and their interacting scaffold proteins, the exons of ten glutamatergic ‘hub’ genes in 1304 individuals were re-sequenced in case and control samples. No significant difference in the overall number of non-synonymous single nucleotide polymorphisms (nsSNPs) was observed between cases and controls. However, cluster analysis of nsSNPs identified two exons encoding the cysteine-rich domain and first transmembrane helix of GRM1 as a risk locus with five mutations highly enriched within these domains. A new splice variant lacking the transmembrane GPCR domain of GRM1 was discovered in the human brain and the GRM1 mutation cluster could perturb the regulation of this variant. The predicted effect on individuals harbouring multiple mutations distributed in their ten hub genes was also examined. Diseased individuals possessed an increased load of deleteriousness from multiple concurrent rare and common coding variants. Together, these data suggest a disease model in which the interplay of compound genetic coding variants, distributed among glutamate receptors and their interacting proteins, contribute to the pathogenesis of schizophrenia and bipolar disorders

The diagnostic utility of clinical exome sequencing in 60 patients with hearing loss disorders: A single‐institution experience

From Wiley via Jisc Publications RouterHistory: received 2020-12-21, rev-recd 2021-04-08, accepted 2021-05-08, pub-electronic 2021-07-05Article version: VoRPublication status: PublishedFunder: Mexico’s National Council of Science and Technology; Grant(s): (CONACyT)‐392996Funder: Peter Mount award (Manchester University NHS Foundation Trust); Grant(s): G70658Funder: Data Driven Award (Manchester University NHS Foundation Trust); Grant(s): NH_SY_020419Funder: Manchester NIHR BRC; Grant(s): BRC‐1215‐20007Funder: Wellcome Trust; Grant(s): 200990/Z/16/