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The recent COVID-19 pandemic led to uncertainty and severe health and economic concerns. Previous studies indicated that owning a companion animal, such as a dog or a cat, has benefits for good mental health. Interactions with animals may help with depression and anxiety, particularly under stress-prone conditions. Human–animal interactions may even improve peer-to-peer social relationships, as well as enhance feelings of respect, trust, and empathy between people. Interestingly, it has also been shown that stress and poor well-being of dog owners negatively affect the well-being of their companion animals. However, a dramatic increase in dog abandonment could potentially occur due to COVID-19 related health, economic and social stresses, as well as due to the inconclusive reports of companion animals being potential COVID-19 carriers. Such a scenario may lead to high costs and considerable public health risks. Accordingly, we hypothesized that the COVID-19 pandemic, and the related social isolation, might lead to dramatic changes in human–dog bidirectional relationships. Using unique prospective and retrospective datasets, our objectives were to investigate how people perceived and acted during the COVID-19 pandemic social isolation, in regards to dog adoption and abandonment; and to examine the bidirectional relationship between the well-being of dog owners and that of their dogs. Overall, according to our analysis, as the social isolation became more stringent during the pandemic, the interest in dog adoption and the adoption rate increased significantly, while abandonment did not change. Moreover, there was a clear association between an individual’s impaired quality of life and their perceptions of a parallel deterioration in the quality of life of their dogs and reports of new behavioral problems. As humans and dogs are both social animals, these findings suggest potential benefits of the human–dog relationships during the COVID-19 pandemic, in accordance with the One Welfare approach that implies that there is a bidirectional connection between the welfare and health of humans and non-human animals. As our climate continues to change, more disasters including pandemics will likely occur, highlighting the importance of research into crisis-driven changes in human–animal relationships.

The Red List of Threatened Species, published by the International Union for Conservation of Nature (IUCN), is a crucial tool for conservation decision-making. However, despite substantial effort, numerous species remain unassessed or have insufficient data available to be assigned a Red List extinction risk category. Moreover, the Red Listing process is subject to various sources of uncertainty and bias. The development of robust automated assessment methods could serve as an efficient and highly useful tool to accelerate the assessment process and offer provisional assessments. Here, we aimed to (1) present a machine learning–based automated extinction risk assessment method that can be used on less known species; (2) offer provisional assessments for all reptiles—the only major tetrapod group without a comprehensive Red List assessment; and ( 3) evaluate potential effects of human decision biases on the outcome of assessments. We use the method presented here to assess 4,369 reptile species that are currently unassessed or classified as Data Deficient by the IUCN. The models used in our predictions were 90% accurate in classifying species as threatened/nonthreatened, and 84% accurate in predicting specific extinction risk categories. Unassessed and Data Deficient reptiles were considerably more likely to be threatened than assessed species, adding to mounting evidence that these species warrant more conservation attention. The overall proportion of threatened species greatly increased when we included our provisional assessments. Assessor identities strongly affected prediction outcomes, suggesting that assessor effects need to be carefully considered in extinction risk assessments. Regions and taxa we identified as likely to be more threatened should be given increased attention in new assessments and conservation planning. Lastly, the method we present here can be easily implemented to help bridge the assessment gap for other less known taxa.

The rapid pace of current global warming lead to the advancement of spring migration in the majority of long-distance migratory bird species. While data on arrival timing to breeding grounds in Europe is plentiful, information from the African departure sites are scarce. Here we analysed changes in arrival timing at a stopover site in Israel and any links to Enhanced Vegetation Index (EVI) on the species-specific African non-breeding range in three migratory passerines between 2000–2017. Differences in wing length between early and late arriving individuals were also examined as a proxy for migration distance. We found that male redstart, but not females, advanced arrival to stopover site, but interestingly, not as a response to EVI phenology. Blackcap and barred warbler did not shift arrival timing significantly, although the arrival of blackcap was dependent on EVI. Barred warbler from the early arrival phase had longer wings, suggesting different populations. Our study further supports the existence species-specific migration decisions and inter-sexual differences, which may be triggered by both exogenous (local vegetation condition) and endogenous cues. Given rapid rate of changes in environmental conditions at higher latitudes, some migrants may experience difficulty in the race to match global changes to ensure their survival.

Post-partum metritis is among the most prevalent disease in dairy cows affecting animal welfare and inflicting considerable economic loses. While post-partum contamination of the uterus is rife in dairy cows, only a fraction of these animals will develop metritis. Our main objective was to compare the bacterial communities and the inflammatory response in the endometrium of healthy and metritic dairy cows. Holstein–Friesian cows ( n  = 35) were sampled immediately following clinical classification as healthy ( n  = 21), suffering from metritis ( n  = 13) or septic metritis ( n  = 1), based on veterinary examination at 5–10 days post-partum. Polymorphonuclear cells (PMN) percentage in endometrial cytology was significantly higher in cows with metritis. Full-thickness uterine biopsy analysis revealed that the luminal epithelium in inter-caruncle areas was preserved in healthy cows, but in metritis it was compromised, with marked PMN infiltration particularly in the apical endometrium. Gram staining revealed that bacterial load and spatial distribution was associated with disease severity. 16S-rDNA bacterial community analysis revealed unique endometrial bacterial community composition in metritic cows, as compared to more diverse communities among healthy cows. The most abundant phyla in healthy cows were Proteobacteria (31.8 ± 9.3%), Firmicutes (27.9 ± 8.4%) and Bacteroidetes (19.7 ± 7.2%), while Bacteroidetes (60.3 ± 10.3%), Fusobacteria (13.4 ± 5.9%) and Firmicutes (10.5 ± 3.3%) were most abundant in the endometrial mucosa of metritic cows. Relative abundance of Bacteroidetes (19.7 ± 7.2% vs. 60.3 ± 10.3%), Fusobacteria (7.5 ± 5.2% vs. 13.4 ± 5.9%) and Proteobacteria (31.8 ± 9.3% vs. 7.3 ± 5.6%) phyla differed significantly between healthy and metritic cows. In summary, endometrial PMN abundance, spatial distribution and bacterial communities differed between healthy and metritic dairy cows at early post-partum.

Mammalian models, and mouse studies in particular, play a central role in our understanding of placental development. Magnetic resonance imaging (MRI) could be a valuable tool to further these studies, providing both structural and functional information. As fluid dynamics throughout the placenta are driven by a variety of flow and diffusion processes, diffusion-weighted MRI could enhance our understanding of the exchange properties of maternal and fetal blood pools—and thereby of placental function. These studies, however, have so far been hindered by the small sizes, the unavoidable motions, and the challenging air/water/fat heterogeneities, associated with mouse placental environments. The present study demonstrates that emerging methods based on the spatiotemporal encoding (SPEN) of the MRI information can robustly overcome these obstacles. Using SPEN MRI in combination with albumin-based contrast agents, we analyzed the diffusion behavior of developing placentas in a cohort of mice. These studies successfully discriminated the maternal from the fetal blood flows; the two orders of magnitude differences measured in these fluids’ apparent diffusion coefficients suggest a nearly free diffusion behavior for the former and a strong flow-based component for the latter. An intermediate behavior was observed by these methods for a third compartment that, based on maternal albumin endocytosis, was associated with trophoblastic cells in the interphase labyrinth. Structural features associated with these dynamic measurements were consistent with independent intravital and ex vivo fluorescence microscopy studies and are discussed within the context of the anatomy of developing mouse placentas.

Background Discovery that the transcriptional output of the human genome is far more complex than predicted by the current set of protein-coding annotations and that most RNAs produced do not appear to encode proteins has transformed our understanding of genome complexity and suggests new paradigms of genome regulation. However, the fraction of all cellular RNA whose function we do not understand and the fraction of the genome that is utilized to produce that RNA remain controversial. This is not simply a bookkeeping issue because the degree to which this un-annotated transcription is present has important implications with respect to its biologic function and to the general architecture of genome regulation. For example, efforts to elucidate how non-coding RNAs (ncRNAs) regulate genome function will be compromised if that class of RNAs is dismissed as simply 'transcriptional noise'. Results We show that the relative mass of RNA whose function and/or structure we do not understand (the so called 'dark matter' RNAs), as a proportion of all non-ribosomal, non-mitochondrial human RNA (mt-RNA), can be greater than that of protein-encoding transcripts. This observation is obscured in studies that focus only on polyA-selected RNA, a method that enriches for protein coding RNAs and at the same time discards the vast majority of RNA prior to analysis. We further show the presence of a large number of very long, abundantly-transcribed regions (100's of kb) in intergenic space and further show that expression of these regions is associated with neoplastic transformation. These overlap some regions found previously in normal human embryonic tissues and raises an interesting hypothesis as to the function of these ncRNAs in both early development and neoplastic transformation. Conclusions We conclude that 'dark matter' RNA can constitute the majority of non-ribosomal, non-mitochondrial-RNA and a significant fraction arises from numerous very long, intergenic transcribed regions that could be involved in neoplastic transformation.

Lipson et al . profile the yeast transcriptome using single-molecule sequencing. This approach avoids the inherent biases of the digestion, ligation and amplification steps in alternative methods based on microarrays or other sequencing technologies. We present single-molecule sequencing digital gene expression (smsDGE), a high-throughput, amplification-free method for accurate quantification of the full range of cellular polyadenylated RNA transcripts using a Helicos Genetic Analysis system. smsDGE involves a reverse-transcription and polyA-tailing sample preparation procedure followed by sequencing that generates a single read per transcript. We applied smsDGE to the transcriptome of Saccharomyces cerevisiae strain DBY746, using 6 of the available 50 channels in a single sequencing run, yielding on average 12 million aligned reads per channel. Using spiked-in RNA, accurate quantitative measurements were obtained over four orders of magnitude. High correlation was demonstrated across independent flow-cell channels, instrument runs and sample preparations. Transcript counting in smsDGE is highly efficient due to the representation of each transcript molecule by a single read. This efficiency, coupled with the high throughput enabled by the single-molecule sequencing platform, provides an alternative method for expression profiling.

RNA Seq provides unparalleled levels of information about the transcriptome including precise expression levels over a wide dynamic range. It is essential to understand how technical variation impacts the quality and interpretability of results, how potential errors could be introduced by the protocol, how the source of RNA affects transcript detection, and how all of these variations can impact the conclusions drawn. Multiple human RNA samples were used to assess RNA fragmentation, RNA fractionation, cDNA synthesis, and single versus multiple tag counting. Though protocols employing polyA RNA selection generate the highest number of non-ribosomal reads and the most precise measurements for coding transcripts, such protocols were found to detect only a fraction of the non-ribosomal RNA in human cells. PolyA RNA excludes thousands of annotated and even more unannotated transcripts, resulting in an incomplete view of the transcriptome. Ribosomal-depleted RNA provides a more cost-effective method for generating complete transcriptome coverage. Expression measurements using single tag counting provided advantages for assessing gene expression and for detecting short RNAs relative to multi-read protocols. Detection of short RNAs was also hampered by RNA fragmentation. Thus, this work will help researchers choose from among a range of options when analyzing gene expression, each with its own advantages and disadvantages.

Free‐roaming cats (FRCs) form nondomiciliary population groups that might lead to adverse environmental effects, as well as to welfare impairment of the cats themselves. Though criticized by ecologists, for the last two decades, the trap–neuter–return (TNR) programs were often employed aiming to manage these populations. At present, no accepted and accessible monitoring scheme exists to determine the effectiveness of those programs. In the current study, we present the reliability and validity of an applicable monitoring scheme, as an adjunct tool for a TNR program of FRC in an urban environment. The monitoring scheme is based on cat observation counts along randomly chosen transects. Fifty‐four transects were repeatedly walked for three years, between 2012‐2014, in 27 neighborhoods within an urban area of 19.3 Km2. Cat numbers counted in the 2014 observations were significantly higher than cat numbers found in the 2012 observations (prevalence ratio = 1.258, CI95%= 1.198–1.322, p < 0.001). The method revealed high reliability when different observers and different transects in the same neighborhood were compared (R2 = 0.548 and R2 = 0.391, respectively, for measuring cat counts per km, p < 0.001; and R2 = 0.5 and R2 = 0.74, respectively, for measuring neutering percentage, p < 0.001). This scheme was constructively validated by measurements of municipal data on the number of neutered cats and demonstrated high correlation (R2 = 0.59, p < 0.001). Conducting cat observations using friendly calling and feeding resulted in an increased number of FRC observed per km walk (by 79% and 22%–30%, respectively). However, these manipulations did not alter the recorded percentage of neutered cats. The proposed scheme provides spatio‐temporal data that can contribute to the management programs of such cat metapopulations in an urban environment. The presentation of the reliability and validity of an applicable monitoring scheme of free‐roaming cats in an urban environment.

Angiogenesis and lymphangiogenesis are key processes during embryogenesis as well as under physiological and pathological conditions. Vascular endothelial growth factor C (VEGFC), the ligand for both VEGFR2 and VEGFR3, is a central lymphangiogenic regulator that also drives angiogenesis. Here, we report that members of the highly conserved BACH (BTB and CNC homology) family of transcription factors regulate VEGFC expression, through direct binding to its promoter. Accordingly, down-regulation of bach2a hinders blood vessel formation and impairs lymphatic sprouting in a Vegfc-dependent manner during zebrafish embryonic development. In contrast, BACH1 overexpression enhances intratumoral blood vessel density and peritumoral lymphatic vessel diameter in ovarian and lung mouse tumor models. The effects on the vascular compartment correlate spatially and temporally with BACH1 transcriptional regulation of VEGFC expression. Altogether, our results uncover a novel role for the BACH/VEGFC signaling axis in lymphatic formation during embryogenesis and cancer, providing a novel potential target for therapeutic interventions.