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Infertility affects ∼12 % of couples, with environmental chemical exposure as a potential contributor. Of the chemicals that are actively manufactured, very few are assessed for reproductive health effects. Rodents are commonly used to evaluate reproductive effects, which is both costly and time consuming. Thus, there is a pressing need for rapid methods to test a broader range of chemicals. Here, we developed a strategy to evaluate large numbers of chemicals for reproductive toxicity via a yeast, S. cerevisiae high-throughput assay to assess gametogenesis as a potential new approach method (NAM). By simultaneously assessing chemicals for growth effects, we can distinguish if a chemical affects gametogenesis only, proliferative growth only or both. We identified a well-known mammalian reproductive toxicant, bisphenol A (BPA) and ranked 19 BPA analogs for reproductive harm. By testing mixtures of BPA and its analogs, we found that BPE and 17 ß-estradiol each together with BPA showed synergistic effects that worsened reproductive outcome. We examined an additional 179 environmental chemicals including phthalates, pesticides, quaternary ammonium compounds and per- and polyfluoroalkyl substances and found 57 with reproductive effects. Many of the chemicals were found to be strong reproductive toxicants that have yet to be tested in mammals. Chemicals having affect before meiosis I division vs. meiosis II division were identified for 16 gametogenesis-specific chemicals. Finally, we demonstrate that in general yeast reproductive toxicity correlates well with published reproductive toxicity in mammals illustrating the promise of this NAM to quickly assess chemicals to prioritize the evaluation for human reproductive harm.

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While high-throughput (HTP) assays have been proposed as platforms to rapidly assess reproductive toxicity, there is currently a lack of established assays that specifically address germline development/function and fertility. We assessed the applicability domains of yeast (S. cerevisiae) and nematode (C. elegans) HTP assays in toxicity screening of 124 environmental chemicals, determining their agreement in identifying toxicants and their concordance with reproductive toxicity in vivo. We integrated data generated in the two models and compared results using a streamlined, semi-automated benchmark dose (BMD) modeling approach. We then extracted and modeled relevant mammalian in vivo data available for the matching chemicals included in the Toxicological Reference Database (ToxRefDB). We ranked potencies of common compounds using the BMD and evaluated correlation between the datasets using Pearson and Spearman correlation coefficients. We found moderate to good correlation across the three data sets, with r = 0.48 (95% CI: 0.28-1.00, p<0.001) and rs = 0.40 (p=0.002) for the parametric and rank order correlations between the HTP BMDs; r = 0.95 (95% CI: 0.76-1.00, p=0.0005) and rs = 0.89 (p=0.006) between the yeast assay and ToxRefDB BMDs; and r = 0.81 (95% CI: 0.28-1.00, p=0.014) and rs = 0.75 (p=0.033) between the worm assay and ToxRefDB BMDs. Our findings underscore the potential of these HTP assays to identify environmental chemicals that exhibit reproductive toxicity. Integrating these HTP datasets into mammalian in vivo prediction models using machine learning methods could further enhance the predictive value of these assays in future rapid screening efforts.

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Reproduction is a functional outcome that relies on complex cellular, tissue, and organ interactions that span the developmental period to adulthood. Thus, the assessment of its disruption by environmental chemicals would benefit significantly from scalable and innovative approaches to testing using functionally comparable reproductive models such as the nematode C. elegans. We adapted a previously described low-throughput in vivo chromosome segregation assay using C. elegans predictive of reproductive toxicity and leveraged available public data sources (ToxCast, ICE) to screen and characterize 133 physiologically-relevant chemicals in a high-throughput manner. The screening outcome was further validated in a second, independent in vivo assay assessing embryonic viability. In total, 13 chemicals were classified as reproductive toxicants with the two most active chemicals belonging to the large family of Quaternary Ammonium Compounds (QACs) commonly used as disinfectants but with limited available reproductive toxicity data. We compared the results from the C. elegans assay with ToxCast in vitro data compiled from 700+ cell response assays and 300+ signaling pathways-based assays. We did not observe a difference in the bioactivity or in the average potency (AC50) between the top and bottom chemicals. However, the intended target categories were significantly different between the classified chemicals with, in particular, an over-representation of steroid hormone targets for the high Z-score chemicals. Taken together, these results point to the value of in vivo models that scale to high-throughput level for reproductive toxicity assessment and to the need to prioritize the assessment of QACs impacts on reproduction.

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In many organisms, most notably Drosophila, homologous chromosomes associate in somatic cells, a phenomenon known as somatic pairing, which takes place without double strand breaks or strand invasion, thus requiring some other mechanism for homologs to recognize each other. Several studies have suggested a "specific button" model, in which a series of distinct regions in the genome, known as buttons, can associate with each other, mediated by different proteins that bind to these different regions. Here, we use computational modeling to evaluate an alternative "button barcode" model, in which there is only one type of recognition site or adhesion button, present in many copies in the genome, each of which can associate with any of the others with equal affinity. In this model, buttons are nonuniformly distributed, such that alignment of a chromosome with its correct homolog, compared with a nonhomolog, is energetically favored; since to achieve nonhomologous alignment, chromosomes would be required to mechanically deform in order to bring their buttons into mutual register. By simulating randomly generated nonuniform button distributions, many highly effective button barcodes can be easily found, some of which achieve virtually perfect pairing fidelity. This model is consistent with existing literature on the effect of translocations of different sizes on homolog pairing. We conclude that a button barcode model can attain highly specific homolog recognition, comparable to that seen in actual cells undergoing somatic homolog pairing, without the need for specific interactions. This model may have implications for how meiotic pairing is achieved.

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Reproduction is a functional outcome that relies on complex cellular, tissue, and organ interactions that span the developmental period to adulthood. Thus, the assessment of its disruption by environmental chemicals is remarkably painstaking in conventional toxicological animal models and does not scale up to the number of chemicals present in our environment and requiring testing. We adapted a previously described low-throughput in vivo chromosome segregation assay using C. elegans predictive of reproductive toxicity and leveraged available public data sources (ToxCast, ICE) to screen and characterize 133 physiologically-relevant chemicals in a high-throughput manner. The screening outcome was further validated in a second, independent in vivo assay assessing embryonic viability. In total, 13 chemicals were classified as reproductive toxicants with the two most active chemicals belonging to the large family of Quaternary Ammonium Compounds (QACs) commonly used as disinfectants but with limited available reproductive toxicity data. We compared the results from the C. elegans assay with ToxCast in vitro data compiled from 700+ cell response assays and 300+ signaling pathways-based assays. We did not observe a difference in the bioactivity or in average potency (AC50) between the top and bottom chemicals. However, the intended target categories were significantly different between the classified chemicals with, in particular, an over-representation of steroid hormone targets for the high Z-score chemicals. Taken together, these results point to the value of in vivo models that scale to high-throughput level for reproductive toxicity assessment and to the need to prioritize the assessment of QACs impacts on reproduction.

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Measurements of Drosophila fecundity are used in a wide variety of studies, such as investigations of stem cell biology, nutrition, behavior, and toxicology. In addition, because fecundity assays are performed on live flies, they are suitable for longitudinal studies such as investigations of aging or prolonged chemical exposure. However, standard Drosophila fecundity assays have been difficult to perform in a high-throughput manner because experimental factors such as the physiological state of the flies and environmental cues must be carefully controlled to achieve consistent results. In addition, exposing flies to a large number of different experimental conditions (such as chemical additives in the diet) and manually counting the number of eggs laid to determine the impact on fecundity is time-consuming. We have overcome these challenges by combining a new multiwell fly culture strategy with a novel 3D-printed fly transfer device to rapidly and accurately transfer flies from one plate to another; the RoboCam, a low-cost, custom built robotic camera to capture images of the wells automatically; and an image segmentation pipeline to automatically identify and quantify eggs. We show that this method is compatible with robust and consistent egg laying throughout the assay period; and demonstrate that the automated pipeline for quantifying fecundity is very accurate (r2 = 0.98 for the correlation between the automated egg counts and the ground truth) In addition, we show that this method can be used to efficiently detect the effects on fecundity induced by dietary exposure to chemicals. Taken together, this strategy substantially increases the efficiency and reproducibility of high throughput egg laying assays that require exposing flies to multiple different media conditions.

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Outcomes of tracheostomized patients with COVID-19 are seldomly investigated with conflicting evidence from the existing literature. OBJECTIVES: To create a study evaluating the impact of COVID-19 on tracheostomized patients by comparing clinical outcomes and weaning parameters in COVID-19 positive and negative cohorts. DESIGN SETTING AND PARTICIPANTS: A retrospective observational cohort study of 604 tracheostomized patients hospitalized in 16 ICUs in New York City between March 9, 2020, and September 8, 2021. MAIN OUTCOMES AND MEASURES: Patients were stratified into two cohorts: 398 COVID-19 negative (COVID-ve) and 206 COVID-19 positive (COVID+ve) patients. Clinical characteristics, outcomes, and weaning parameters (first pressure support [PS], tracheostomy collar [TC], speech valve placement, and decannulation) were analyzed. RESULTS: COVID+ve had fewer comorbidities including coronary artery disease, congestive heart failure, malignancy, chronic kidney disease, liver disease, and HIV (p < 0.05). Higher Fio2 (53% vs 44%), positive end-expiratory pressure (PEEP) (7.15 vs 5.69), Pco2 (45.8 vs 38.2), and lower pH (7.41 vs 7.43) were observed at the time of tracheostomy in COVID+ve (p < 0.005). There was no statistical difference in post-tracheostomy complication rates. Longer time from intubation to tracheostomy (15.90 vs 13.60 d; p = 0.002), tracheostomy to first PS (2.87 vs 1.80 d; p = 0.005), and TC placement (11.07 vs 4.46 d; p < 0.001) were seen in COVID+ve. However, similar time to speech valve placement, decannulation, and significantly lower 1-year mortality (23.3% vs 36.7%; p = 0.001) with higher number of discharges to long-term acute care hospital (LTACH) (23.8% vs 13.6%; p = 0.015) were seen in COVID+ve. CONCLUSIONS AND RELEVANCE: Patients with COVID-19 required higher Fio2 and PEEP ventilatory support at the time of tracheostomy, with no observed change in complication rates. Despite longer initial weaning period with PS or TC, similar time to speech valve placement or decannulation with significantly lower mortality and higher LTACH discharges suggest favorable outcome in COVID-19 positive patients. Higher ventilatory support requirements and prolonged weaning should not be a deterrent to pursuing a tracheostomy.

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In many organisms, most notably Drosophila, homologous chromosomes in somatic cells associate with each other, a phenomenon known as somatic homolog pairing. Unlike in meiosis, where homology is read out at the level of DNA sequence complementarity, somatic homolog pairing takes place without double strand breaks or strand invasion, thus requiring some other mechanism for homologs to recognize each other. Several studies have suggested a "specific button" model, in which a series of distinct regions in the genome, known as buttons, can associate with each other, presumably mediated by different proteins that bind to these different regions. Here we consider an alternative model, which we term the "button barcode" model, in which there is only one type of recognition site or adhesion button, present in many copies in the genome, each of which can associate with any of the others with equal affinity. An important component of this model is that the buttons are non-uniformly distributed, such that alignment of a chromosome with its correct homolog, compared with a non-homolog, is energetically favored; since to achieve nonhomologous alignment, chromosomes would be required to mechanically deform in order to bring their buttons into mutual register. We investigated several types of barcodes and examined their effect on pairing fidelity. We found that high fidelity homolog recognition can be achieved by arranging chromosome pairing buttons according to an actual industrial barcode used for warehouse sorting. By simulating randomly generated non-uniform button distributions, many highly effective button barcodes can be easily found, some of which achieve virtually perfect pairing fidelity. This model is consistent with existing literature on the effect of translocations of different sizes on homolog pairing. We conclude that a button barcode model can attain highly specific homolog recognition, comparable to that seen in actual cells undergoing somatic homolog pairing, without the need for specific interactions. This model may have implications for how meiotic pairing is achieved.

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The synaptonemal complex (SC) is a dynamic structure formed between chromosomes during meiosis which stabilizes and supports many essential meiotic processes such as pairing and recombination. In budding yeast, Zip1 is a functionally conserved element of the SC that is important for synapsis. Here, we directly measure the kinetics of Zip1-GFP assembly and disassembly in live cells of the yeast S. cerevisiae. The imaging of SC assembly in yeast is challenging due to the large number of chromosomes packed into a small nucleus. We employ a zip3Δ mutant in which only a few chromosomes undergo synapsis at any given time, initiating from a single site on each chromosome, thus allowing the assembly and disassembly kinetics of single SCs to be accurately monitored in living cells. SC assembly occurs with both monophasic and biphasic kinetics, in contrast to the strictly monophasic assembly seen in C. elegans. In wild-type cells, once maximal synapsis is achieved, programmed final disassembly rapidly follows, as Zip1 protein is actively degraded. In zip3Δ, this period is extended and final disassembly is prolonged. Besides final disassembly, we found novel disassembly events involving mostly short SCs that disappeared in advance of programmed final disassembly, which we termed "abortive disassembly." Abortive disassembly is distinct from final disassembly in that it occurs when Zip1 protein levels are still high, and exhibits a much slower rate of disassembly, suggesting a different mechanism for removal in the two types of disassembly. We speculate that abortive disassembly events represent defective or stalled SCs, possibly representing SC formation between non-homologs, that is then targeted for dissolution. These results reveal novel aspects of SC assembly and disassembly, potentially providing evidence of additional regulatory pathways controlling not just the assembly, but also the disassembly, of this complex cellular structure.

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OBJECTIVES: The COVID-19 pandemic in the USA has been accompanied by high rates of mortality and an unprecedented need for palliative care delivery. Little is known about the use of palliative care services in intensive care unit (ICU) settings during the COVID-19 pandemic. METHODS: This is a retrospective cohort study of critically ill COVID-19 patients requiring ICU admission, between 7 March and 14 April 2020 to two academic teaching hospitals in New York City. Palliative care consultation included a one-time telemedicine consultation or continued telemedicine consultation and follow-up with multidisciplinary team involvement. Patient information was collected from the electronic health record and analyses were conducted with Stata V.15.1 (StataCorp) statistical software. RESULTS: A total of 151 critically ill patients with COVID-19 pneumonia requiring ICU admission were identified, of whom 59 (39.07%) received an inpatient palliative care consultation. More than half of patients died (n=85/151, 56.29%), with 57.65% (n=49/85) of these patients receiving palliative care services during their hospitalisation. Patients who received palliative care consultation were more likely to be older, sicker and receive mechanical ventilation than their counterparts. Patients who died and did not receive palliative care were younger and required non-invasive ventilation support. CONCLUSION: There is a lack of utilisation of palliative care in COVID-19 patients admitted to the ICU. Further research into predictors of poor outcomes in critically ill COVID-19 patients may help identify patients that would benefit from early palliative care involvement going forward.

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BACKGROUND: Little is known about how to best communicate with older adults about dietary behaviors and related factors in complex chronic disease care. Photo-based communication could promote efficient information exchange and activate patients to effectively communicate their lived experiences. We conducted a pilot study to assess the feasibility and acceptability of a photo-based patient-clinician communication intervention to promote dietary discussions in geriatric primary care. METHODS: Older adult patients with 2+ concurrent chronic conditions received in-person training on photo-taking with a smartphone before taking photos in response to the prompt, "What aspects of your everyday life affect what you eat and how much you have to eat?" Patients then shared photos and their narratives with their primary care clinician during a clinic visit. Patients and clinicians completed separate audio-recorded post-visit interviews to assess perspectives on the intervention. Interview transcripts were analyzed using a thematic analysis approach. RESULTS: Fourteen patient-clinician dyads completed the study. All except one patient-clinician dyad (93%) completed the intervention as trained. 93% of patients and 86% of clinicians reported that they would "definitely" or "probably" be willing to engage in a future visit with photo-sharing. Patients and clinicians shared similar perspectives on how sharing of photos during the visit enhanced communication and information exchange about dietary practices and other health-related factors, influenced clinical recommendations made during the visits, and strengthened the patient-clinician relationship. CONCLUSION: Incorporation of a photo-based patient-clinician communication intervention to promote discussions regarding diet and other health-related factors could be a patient-centered strategy to help deliver comprehensive geriatric primary care.

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BACKGROUND: Despite their large numbers and widespread use, very little is known about the extent to which per- and polyfluoroalkyl substances (PFAS) can cross the placenta and expose the developing fetus. OBJECTIVE: The aim of our study is to develop a computational approach that can be used to evaluate the of extend to which small molecules, and in particular PFAS, can cross to cross the placenta and partition to cord blood. METHODS: We collected experimental values of the concentration ratio between cord and maternal blood (RCM) for 260 chemical compounds and calculated their physicochemical descriptors using the cheminformatics package Mordred. We used the compiled database to, train and test an artificial neural network (ANN). And then applied the best performing model to predict RCM for a large dataset of PFAS chemicals (n = 7982). We, finally, examined the calculated physicochemical descriptors of the chemicals to identify which properties correlated significantly with RCM. RESULTS: We determined that 7855 compounds were within the applicability domain and 127 compounds are outside the applicability domain of our model. Our predictions of RCM for PFAS suggested that 3623 compounds had a log RCM > 0 indicating preferable partitioning to cord blood. Some examples of these compounds were bisphenol AF, 2,2-bis(4-aminophenyl)hexafluoropropane, and nonafluoro-tert-butyl 3-methylbutyrate. SIGNIFICANCE: These observations have important public health implications as many PFAS have been shown to interfere with fetal development. In addition, as these compounds are highly persistent and many of them can readily cross the placenta, they are expected to remain in the population for a long time as they are being passed from parent to offspring. IMPACT: Understanding the behavior of chemicals in the human body during pregnancy is critical in preventing harmful exposures during critical periods of development. Many chemicals can cross the placenta and expose the fetus, however, the mechanism by which this transport occurs is not well understood. In our study, we developed a machine learning model that describes the transplacental transfer of chemicals as a function of their physicochemical properties. The model was then used to make predictions for a set of 7982 per- and polyfluorinated alkyl substances that are listed on EPA's CompTox Chemicals Dashboard. The model can be applied to make predictions for other chemical categories of interest, such as plasticizers and pesticides. Accurate predictions of RCM can help scientists and regulators to prioritize chemicals that have the potential to cause harm by exposing the fetus.

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During meiosis, homologous chromosomes become associated side by side in a process known as homologous chromosome pairing. Pairing requires long range chromosome motion through a nucleus that is full of other chromosomes. It remains unclear how the cell manages to align each pair of chromosomes quickly while mitigating and resolving interlocks. Here, we use a coarse-grained molecular dynamics model to investigate how specific features of meiosis, including motor-driven telomere motion, nuclear envelope interactions, and increased nuclear size, affect the rate of pairing and the mitigation/resolution of interlocks. By creating in silico versions of three yeast strains and comparing the results of our model to experimental data, we find that a more distributed placement of pairing sites along the chromosome is necessary to replicate experimental findings. Active motion of the telomeric ends speeds up pairing only if binding sites are spread along the chromosome length. Adding a meiotic bouquet significantly speeds up pairing but does not significantly change the number of interlocks. An increase in nuclear size slows down pairing while greatly reducing the number of interlocks. Interestingly, active forces increase the number of interlocks, which raises the question: How do these interlocks resolve? Our model gives us detailed movies of interlock resolution events which we then analyze to build a step-by-step recipe for interlock resolution. In our model, interlocks must first translocate to the ends, where they are held in a quasi-stable state by a large number of paired sites on one side. To completely resolve an interlock, the telomeres of the involved chromosomes must come in close proximity so that the cooperativity of pairing coupled with random motion causes the telomeres to unwind. Together our results indicate that computational modeling of homolog pairing provides insight into the specific cell biological changes that occur during meiosis.

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A large subset of meiotic recombination intermediates form within the physical context of synaptonemal complex (SC), but the functional relationship between SC structure and homologous recombination remains obscure. Our prior analysis of strains deficient for SC central element proteins demonstrated that tripartite SC is dispensable for interhomolog recombination in Saccharomyces cerevisiae. Here, we report that while dispensable for recombination per se, SC proteins promote efficient mismatch repair at interhomolog recombination sites. Failure to repair mismatches within heteroduplex-containing meiotic recombination intermediates leads to genotypically sectored colonies (postmeiotic segregation events). We discovered increased postmeiotic segregation at THR1 in cells lacking Ecm11 or Gmc2, or in the SC-deficient but recombination-proficient zip1[Δ21-163] mutant. High-throughput sequencing of octad meiotic products furthermore revealed a genome-wide increase in recombination events with unrepaired mismatches in ecm11 mutants relative to wildtype. Meiotic cells missing Ecm11 display longer gene conversion tracts, but tract length alone does not account for the higher frequency of unrepaired mismatches. Interestingly, the per-nucleotide mismatch frequency is elevated in ecm11 when analyzing all gene conversion tracts, but is similar between wildtype and ecm11 if considering only those events with unrepaired mismatches. Thus, in both wildtype and ecm11 strains a subset of recombination events is susceptible to a similar degree of inefficient mismatch repair, but in ecm11 mutants a larger fraction of events fall into this inefficient repair category. Finally, we observe elevated postmeiotic segregation at THR1 in mutants with a dual deficiency in MutSγ crossover recombination and SC assembly, but not in the mlh3 mutant, which lacks MutSγ crossovers but has abundant SC. We propose that SC structure promotes efficient mismatch repair of joint molecule recombination intermediates, and that absence of SC is the molecular basis for elevated postmeiotic segregation in both MutSγ crossover-proficient (ecm11, gmc2) and MutSγ crossover-deficient (msh4, zip3) strains.

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BACKGROUND AND OBJECTIVES: Even before the COVID-19 pandemic, older adults with cognitive impairment living alone (an estimated 4.3 million individuals in the United States) were at high risk for negative health outcomes. There is an urgent need to learn how this population is managing during the pandemic. RESEARCH DESIGN AND METHODS: This is a qualitative study of 24 adults aged 55 and older living alone with cognitive impairment from diverse racial/ethnic backgrounds. Participants' lived experiences during the pandemic were elicited via 59 ethnographic interviews conducted over the phone either in English, Spanish, or Cantonese. Using a qualitative content analysis approach, interview transcripts were analyzed to identify codes and themes. RESULTS: Qualitative analysis of transcripts revealed 5 themes: (a) fear generated by the pandemic, (b) distress stemming from feeling extremely isolated, (c) belief in misinformation, (d) strategies for coping during the pandemic, and (e) the importance of access to essential services. DISCUSSION AND IMPLICATIONS: This pandemic put a spotlight on the precarity and unmet needs of older adults living alone with cognitive impairment. Findings underscore the need to expand access to home care aides and mental health services for this population.

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Here, we describe three endosymbiotic bacterial strains isolated from the gills of the shipworm, Bankia setacea (Teredinidae: Bivalvia). These strains, designated as Bs08T, Bs12T and Bsc2T, are Gram-stain-negative, microaerobic, gammaproteobacteria that grow on cellulose and a variety of substrates derived from lignocellulose. Phenotypic characterization, phylogeny based on 16S rRNA gene and whole genome sequence data, amino acid identity and percentage of conserved proteins analyses, show that these strains are novel and may be assigned to the genus Teredinibacter. The three strains may be differentiated and distinguished from other previously described Teredinibacter species based on a combination of four characteristics: colony colour (Bs12T, purple; others beige to brown), marine salt requirement (Bs12T, Bsc2T and Teredinibacter turnerae strains), the capacity for nitrogen fixation (Bs08T and T. turnerae strains) and the ability to respire nitrate (Bs08T). Based on these findings, we propose the names Teredinibacter haidensis sp. nov. (type strain Bs08T=ATCC TSD-121T=KCTC 62964T), Teredinibacter purpureus sp. nov. (type strain Bs12T=ATCC TSD-122T=KCTC 62965T) and Teredinibacter franksiae sp. nov. (type strain Bsc2T=ATCC TSD-123T=KCTC 62966T).

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OBJECTIVES: To examine audio-recorded primary care interactions with patient-initiated photo sharing around food and diet choices. METHODS: Data were 13 audio recordings of primary care visits with English-, Chinese-, or Spanish-speaking patients 60+ with two or more chronic conditions. Patients and clinicians completed pre-intervention surveys and some training on photo-taking / photo-sharing discussion. Data were analyzed using discourse analysis. RESULTS: Photo-based communication interactions lasted 3:34-28:37 min and averaged one-third of the visit. Clinicians and patients both initiated the photo-based talk and transition to other topics occurred smoothly. In eight of 13 interactions, the photo-based communication task was raised, but conversation did not occur at that moment. When discussed, the photos raised opportunities to talk about patient's decision-making which led to dietary suggestions including clinical nutrition suggestions and referrals to other specialty clinics. CONCLUSION: Photo-based communication in primary care can be used to promote patient activation and facilitate collaborative decision making that accounts for the patients' lived experiences and lifeworld. PRACTICE IMPLICATIONS: By setting the agenda early, clinicians or patients can designate the photo-sharing as a relevant part of the visit. Photos may be most relevant as part of the problem presentation, diagnosis, or treatment recommendation sections of the visit.

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Data are conflicting regarding the impact of tobacco smoking in people with pneumonia due to SARS-CoV-2 infection (COVID-19). We performed a retrospective multicentre cohort study of 9991 consecutive patients hospitalized in a major New York academic center between March 7th and June 5th, 2020 with laboratory-confirmed COVID-19. The clinical outcomes assessed included risk of hospitalization, in-hospital mortality, risk of intensive care unit (ICU) admission, and need for mechanical ventilation among smokers (current and former). Multivariable logistic regression and propensity score models were built to adjust for potential confounders. Among 9991 consecutive patients diagnosed with COVID-19, 2212 (22.1%) patients were self-reported smokers (406 current and 1806 former). Current smoking was not associated with an increased risk of hospitalization (propensity score [PS]-adjusted OR 0.91; p = .46), in-hospital mortality (PS-OR 0.77; p = .12), ICU admission (PS-OR 1.18; p = .37), or intubation (PS-OR 1.04; p = .85). Similarly, former smoking was not associated with an increased risk of hospitalization (PS-OR 0.88; p = .11), in-hospital mortality (PS-OR 1.03; p = .78), ICU admission (PS-OR 1.03; p = .95), or intubation (PS-OR 0.93; p = .57). Furthermore, smoking (current or former) was not associated with an increased risk of hospitalization (PS-OR 0.85; p = .05), in-hospital mortality (PS-OR 0.94; p = .49), ICU admission (PS-OR 0.86; p = .17), or intubation (PS-OR 0.79; p = .06). Smoking is a well-known risk factor associated with greater susceptibility and subsequent increased severity of respiratory infections. In the current COVID-19 pandemic, smokers may have increased risk and severe pneumonia. In the current COVID-19 pandemic, smokers are believed to have an increased risk of mortality as well as severe pneumonia. However, in our analysis of real-world clinical data, smoking was not associated with increased in-patient mortality in COVID-19 pneumonia, in accordance with prior reports.

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Programmed cellular responses to cycling ovarian-derived steroid hormones are central to normal endometrial function. Abnormalities therein, as in the estrogen-dependent, progesterone-"resistant" disorder, endometriosis, predispose to infertility and poor pregnancy outcomes. The endometrial stromal fibroblast (eSF) is a master regulator of pregnancy success. However, the complex hormone-epigenome-transcriptome interplay in eSF by each individual steroid hormone, estradiol (E2) and/or progesterone (P4), under physiologic and pathophysiologic conditions, is poorly understood and was investigated herein. Genome-wide analysis in normal, early and late stage eutopic eSF revealed: i) In contrast to P4, E2 extensively affected the eSF DNA methylome and transcriptome. Importantly, E2 resulted in a more open versus closed chromatin, confirmed by histone modification analysis. Combined E2 with P4 affected a totally different landscape than E2 or P4 alone. ii) P4 responses were aberrant in early and late stage endometriosis, and mapping differentially methylated CpG sites with progesterone receptor targets from the literature revealed different but not decreased P4-targets, leading to question the P4-"resistant" phenotype in endometriosis. Interestingly, an aberrant E2-response was noted in eSF from endometriosis women; iii) Steroid hormones affected specific genomic contexts and locations, significantly enriching enhancers and intergenic regions and minimally involving proximal promoters and CpG islands, regardless of hormone type and eSF disease state. iv) In eSF from women with endometriosis, aberrant hormone-induced methylation signatures were mainly due to existing DNA methylation marks prior to hormone treatments and involved known endometriosis genes and pathways. v) Distinct DNA methylation and transcriptomic signatures revealed early and late stage endometriosis comprise unique disease subtypes. Taken together, the data herein, for the first time, provide significant insight into the hormone-epigenome-transcriptome interplay of each steroid hormone in normal eSF, and aberrant E2 response, distinct disease subtypes, and pre-existing epigenetic aberrancies in the setting of endometriosis, provide mechanistic insights into how endometriosis affects endometrial function/dysfunction.

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