Are computational applications the “crystal ball” in the IVF laboratory? The evolution from mathematics to artificial intelligence

Mathematics rules the world of science. Innovative technologies based on mathematics have paved the way for implementation of novel strategies in assisted reproduction. Ascertaining efficient embryo selection in order to secure optimal pregnancy rates remains the focus of the in vitro fertilization scientific community and the strongest driver behind innovative approaches. This scoping review aims to describe and analyze complex models based on mathematics for embryo selection, devices, and software most widely employed in the IVF laboratory and algorithms in the service of the cutting-edge technology of artificial intelligence. Despite their promising nature, the practicing embryologist is the one ultimately responsible for the success of the IVF laboratory and thus the one to approve embracing pioneering technologies in routine practice. Applied mathematics and computational biology have already provided significant insight into the selection of the most competent preimplantation embryo. This review describes the leap of evolution from basic mathematics to bioinformatics and investigates the possibility that computational applications may be the means to foretell a promising future for the IVF clinical practice.     

Gluten neuropathy: electrophysiological progression and HLA associations

Journal of Neurology - Gluten neuropathy (GN) is the term used to describe peripheral neuropathy that occurs in patients with gluten sensitivity (GS) or coeliac disease (CD) in the absence of other...     

Disruption of neonatal Purkinje cell function underlies injury-related learning deficits

It is hypothesized that perinatal cerebellar injury leads to long-term functional deficits due to circuit dysmaturation. Using a novel integration of GCaMP6f fiber photometry with automated measurement of cerebellar behavior using the ErasmusLadder, we causally link cerebellar injury to altered Purkinje cell responses during maladaptive behavior. Chemogenetic inhibition of neonatal Purkinje cells is sufficient to phenocopy the effects of perinatal cerebellar injury. Our results uncover a direct link between perinatal cerebellar injury and activity-dependent maturation of cerebellar cortex.

Perinatal complications of preterm or term neonates often result in adaptive behavioral deficits. While injury to the developing cerebellum has been correlated to long-term behavioral abnormalities, especially in locomotor function, the specific neural circuits and physiological mechanisms that are disrupted are unknown. Recent work characterized the spatial and temporal components of interlimb coordination in cerebellum-dependent locomotor learning (1). However, the sparsity of techniques available to directly measure neuronal activity during adaptive cerebellar behavior hampers efforts to identify the functional and mechanistic basis of behavioral pathology.We designed a unique method to measure Purkinje cell (PC) activity during an adaptive cerebellum-dependent locomotor learning task. We utilized the ErasmusLadder––an automated behavioral system that can accurately quantify cerebellum-dependent locomotor learning and adaptive behavior. The ErasmusLadder enables the use of an associative conditioned-learning paradigm that is temporally tuned to define cerebellum-specific aspects of motor learning over multiple trials (2, 3). By directly integrating fiber photometry of the genetically encoded Ca²⁺ indicator—GCaMP6f—with the ErasmusLadder, we successfully and simultaneously recorded population responses of PCs in mice in real time during unrestrained behavior on the ErasmusLadder. We used our method to integrate PC activity measurement with adaptive behavioral quantification to identify a mechanistic basis for locomotor learning dysfunction in a clinically relevant mouse model of neonatal brain injury (4).