Recurrent Implantation Failure-update overview on etiology,diagnosis, treatment and future directions

Recurrent implantation failure (RIF) refers to cases in which women have had three failed in vitro fertilization (IVF) attempts with good quality embryos. The definition should also take advanced maternal age and embryo stage into consideration. The failure of embryo implantation can be a consequence of uterine, male, or embryo factors, or the specific type of IVF protocol. These cases should be investigated to determine the most likely etiologies of the condition, as this is a complex problem with several variables. There are multiple risk factors for recurrent implantation failure including advanced maternal age, smoking status of both parents, elevated body mass index, and stress levels. Immunological factors such as cytokine levels and presence of specific autoantibodies should be examined, as well as any infectious organisms in the uterus leading to chronic endometritis. Uterine pathologies such as polyps and myomas as well as congenital anatomical anomalies should be ruled out. Sperm analysis, pre-implantation genetic screening and endometrial receptivity should be considered and evaluated, and IVF protocols should be tailored to specific patients or patient populations. Treatment approaches should be directed toward individual patient cases. In addition, we suggest considering a new initial step in approach to patients with RIF, individualized planned activities to activate the brain's reward system in attempt to improve immunological balance in the body.     

Characterization of aphid resistance loci in black raspberry (<Emphasis Type="Italic">Rubus occidentalis</Emphasis> L.)

Viruses vectored by the aphid Amphorophora agathonica cause decline in black raspberry plant health resulting in a shortened life and poor fruit quality of the infected plantings. New aphid resistant cultivars could increase the longevity of plantings providing growers and processors with consistent fruit production. Recent exploration of the native range of black raspberry identified three sources of aphid resistance: Ag₄ from Ontario (ON), Canada, Ag₅ from Maine (ME), and a third source from Michigan (MI) with no formal designation. The objectives of this study were to assess segregation of these three sources of aphid resistance in populations with single and combined sources and develop markers that can identify each source of resistance. A genetic linkage map constructed for ORUS 4305 placed the ON aphid resistance locus on Rubus linkage group (RLG) 6. Segregation ratios in populations with single and combined sources, and linkage mapping in two populations (ORUS 4304 and ORUS 4812) segregating for the Ag₅ and MI sources, respectively, indicated that these three sources of resistance are each conferred by single dominant genes/alleles that are linked on RLG6. Confirmation of marker association in 16 validation populations identified four markers that could be used to predict resistance; however, none could distinguish between the ON and MI sources. These four markers may be useful for screening populations to enrich the field-planted progeny for aphid resistance. Fine mapping of the resistance loci is needed to develop functional markers at each of the resistance loci to enable pyramiding and durable aphid resistance.     

Are all data types and connectivity models created equal? Validating common connectivity approaches with dispersal data

Aim

There is enormous interest in applying connectivity modelling to resistance surfaces for identifying corridors for conservation action. However, the multiple analytical approaches used to estimate resistance surfaces and predict connectivity across resistance surfaces have not been rigorously compared, and it is unclear what methods provide the best inferences about population connectivity. Using a large empirical data set on puma (Puma concolor), we are the first to compare several of the most common approaches for estimating resistance and modelling connectivity and validate them with dispersal data.

Location

Southern California, USA.

Methods

We estimate resistance using presence‐only data, GPS telemetry data from puma home ranges and genetic data using a variety of analytical methods. We model connectivity with cost distance and circuit theory algorithms. We then measure the ability of each data type and connectivity algorithm to capture GPS telemetry points of dispersing pumas.

Results

We found that resource selection functions based on GPS telemetry points and paths outperformed species distribution models when applied using cost distance connectivity algorithms. Point and path selection functions were not statistically different in their performance, but point selection functions were more sensitive to the transformation used to convert relative probability of use to resistance. Point and path selection functions and landscape genetics outperformed other methods when applied with cost distance; no methods outperformed one another with circuit theory.

Main conclusions

We conclude that path or point selection functions, or landscape genetic models, should be used to estimate landscape resistance for wildlife. In cases where resource limitations prohibit the collection of GPS collar or genetic data, our results suggest that species distribution models, while weaker, may still be sufficient for resistance estimation. We recommend the use of cost distance‐based approaches, such as least‐cost corridors and resistant kernels, for estimating connectivity and identifying functional corridors for terrestrial wildlife.

     

Exploring how patients understand and assess their diabetes control

Background

Poor understanding of diabetes management targets is associated with worse disease outcomes. Patients may use different information than providers to assess their diabetes control. In this study, we identify the information patients use to gauge their current level of diabetes control and explore patient-perceived barriers to understanding the hemoglobin A1c value (HbA1c).

Methods

Adults who self-reported a diagnosis of diabetes were recruited from outpatient, academically-affiliated, Internal Medicine clinics. Semi-structured interviews were conducted with participants and collected data were analyzed using thematic analysis.

Results

The mean age of the 25 participants was 56.8 years. HbA1c was one of several types of information participants used to assess diabetes control. Other information included perceived self-efficacy and adherence to self-care, the type and amount of medications taken, the presence or absence of symptoms attributed to diabetes, and feedback from self-monitoring of blood glucose. Most participants reported familiarity with the HbA1c (22 of 25), though understanding of the value’s meaning varied significantly. Inadequate diabetes education and challenges with patient-provider communication were cited as common barriers to understanding the HbA1c.

Conclusions

In addition to the HbA1c, several categories of information influenced participants’ assessments of their diabetes control. Increased provider awareness of the factors that influence patients’ perceptions of diabetes control can inform effective, patient-centered approaches for communicating vital diabetes-related information, facilitating behavior change towards improved patient outcomes.

     

Hypothalamic Sirt1 protects terminal Schwann cells and neuromuscular junctions from age‐related morphological changes

Neuromuscular decline occurs with aging. The neuromuscular junction (NMJ), the interface between motor nerve and muscle, also undergoes age‐related changes. Aging effects on the NMJ components—motor nerve terminal, acetylcholine receptors (AChRs), and nonmyelinating terminal Schwann cells (tSCs)—have not been comprehensively evaluated. Sirtuins delay mammalian aging and increase longevity. Increased hypothalamic Sirt1 expression results in more youthful physiology, but the relationship between NMJ morphology and hypothalamic Sirt1 was previously unknown. In wild‐type mice, all NMJ components showed age‐associated morphological changes with ~80% of NMJs displaying abnormalities by 17 months of age. Aged mice with brain‐specific Sirt1 overexpression (BRASTO) had more youthful NMJ morphologic features compared to controls with increased tSC numbers, increased NMJ innervation, and increased numbers of normal AChRs. Sympathetic NMJ innervation was increased in BRASTO mice. In contrast, hypothalamic‐specific Sirt1 knockdown led to tSC abnormalities, decreased tSC numbers, and more denervated endplates compared to controls. Our data suggest that hypothalamic Sirt1 functions to protect NMJs in skeletal muscle from age‐related changes via sympathetic innervation.     

17β-Estradiol Directly Lowers Mitochondrial Membrane Microviscosity and Improves Bioenergetic Function in Skeletal Muscle

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A pseudo-receiver domain in Atg32 is required for mitophagy

Mitochondria are targeted for degradation by mitophagy, a selective form of autophagy. In Saccharomyces cerevisiae, mitophagy is dependent on the autophagy receptor, Atg32, an outer mitochondrial membrane protein. Once activated, Atg32 recruits the autophagy machinery to mitochondria, facilitating mitochondrial capture in phagophores, the precursors to autophagosomes. However, the mechanism of Atg32 activation remains poorly understood. To investigate this crucial step in mitophagy regulation, we examined the structure of Atg32. We have identified a structured domain in Atg32 that is essential for the initiation of mitophagy, as it is required for the proteolysis of the C-terminal domain of Atg32 and the subsequent recruitment of Atg11. The solution structure of this domain was determined by NMR spectroscopy, revealing that Atg32 contains a previously undescribed pseudo-receiver (PsR) domain. Our data suggests that the PsR domain of Atg32 regulates Atg32 activation and the initiation of mitophagy.

Abbreviations:AIM: Atg8-interacting motif; GFP: green fluorescent protein; LIR: LC3-interacting region; NMR: nuclear magnetic resonance; NOESY: nuclear Overhauser effect spectroscopy; PDB: protein data bank; PsR: pseudo-receiver; RMSD: root-mean-square deviation     

Integration of Visual Information in Auditory Cortex Promotes Auditory Scene Analysis through Multisensory Binding

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A new target for Alzheimer’s disease: A small molecule SERCA activator is neuroprotective in vitro and improves memory and cognition in APP/PS1 mice

Amongst the cellular cacophony of altered signals in Alzheimer’s disease (AD), disrupted Ca²⁺ homeostasis and consequential endoplasmic reticulum (ER) stress signals have been recognized as key determinants of neuron fate. This altered Ca²⁺ state is accompanied by a failing sarco/endoplasmic reticulum Ca²⁺-ATPase (SERCA) pump, which has been recognized as a causal feature of the underlying disease state. Repair of the Ca²⁺ dyshomeostasis represents a putative drug target via alleviation of ER stress and rescue of injured neurons, effectively modifying the AD state. Herein, we report a small molecule SERCA activator that rescues brain cells and raises ER Ca²⁺ in vitro, and shows efficacy in the APP/PS1 double transgenic mouse model of Alzheimer’s disease. These results support SERCA activation as a therapeutic target for AD.     

Small molecule SUMOylation activators are novel neuroprotective agents

Neuronal loss characterizes many of the most intractable nervous system diseases that deprive our ageing population of their quality of life. Neuroprotective pharmacological modalities are urgently needed to address this burgeoning population. Small ubiquitin-like modifier (SUMO) conjugation has been established as an endogenous neuroprotective response, and we have discovered several classes of small molecules that enhance SUMO conjugation. Herein we describe the hit to lead campaign that enabled the discovery of 3 diverse classes of drug-like SUMOylation activators. Optimized compounds were ultimately validated in cell-based models of neuronal loss and provide a foundation for establishing systemically active SUMO activators to treat degenerative diseases such as Parkinson’s disease, Alzheimer’s disease, and stroke.