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Near infrared autofluorescence (NIRAF) detection has previously demonstrated significant potential for real-time parathyroid gland identification. However, the performance of a NIRAF detection device - PTeye® - remains to be evaluated relative to a surgeon's own ability to identify parathyroid glands. Patients eligible for thyroidectomy and/or parathyroidectomy were enrolled under 6 endocrine surgeons at 3 high-volume institutions. Participating surgeons were categorized based on years of experience. All surgeons were blinded to output of PTeye® when identifying tissues. The surgeon's performance for parathyroid discrimination was then compared with PTeye®. Histology served as gold standard for excised specimens, while expert surgeon's opinion was used to validate in-situ tissues. PTeye® achieved 92.7% accuracy across 167 patients recruited. Junior surgeons (<5 years of experience) were found to have lower confidence in parathyroid identification and higher tissue misclassification rate per specimen when compared to PTeye® and senior surgeons (>10 years of experience). NIRAF detection with PTeye® can be a valuable intraoperative adjunct technology to aid in parathyroid identification for surgeons. •Identifying parathyroid glands (PGs) during neck operations can be challenging.•This study compared the surgeons' ability in identifying PGs to a device PTeye®.•PTeye® achieved 92.7% accuracy across 167 patients recruited.•Junior surgeons had higher error rate in identifying PGs than seniors and PTeye®.•PTeye® can be a useful adjunct tool to intraoperatively identify PGs in real-time.

► Prevalence data on ∼110,000 rotavirus strains identified from 100 countries worldwide during a 12-year period preceding introduction of rotavirus vaccines were collected and presented in this systematic review ► The paper summarizes (i) baseline strain prevalence data for the pre-vaccine era, (ii) analyzes spatiotemporal trends in distribution of circulating strains, and (iii) provides a weighted model to describe a more reliable estimate on the medical importance of individual rotavirus strains. Recently, two rotavirus vaccines have been recommended for routine immunization of infants worldwide. These vaccines proved efficacious during clinical trials and field use in both developing and developed countries, and appear to provide good protection against a range of rotavirus genotypes, including some that are not included in the vaccines. However, since conclusive data that the vaccines will protect against a wide variety of rotavirus strains are still lacking and since vaccines may exert some selection pressure, a detailed picture of global strain prevalence from the pre-rotavirus vaccine era is important to evaluate any potential changes in circulating strains observed after widespread introduction of rotavirus vaccines. Thus, we systematically reviewed rotavirus genotyping studies spanning a 12-year period from 1996 to 2007. In total, ∼110,000 strains were genotyped from 100 reporting countries. Five genotypes (G1–G4, and G9) accounted for 88% of all strains, although extensive geographic and temporal differences were observed. For example, the prevalence of G1 strains declined from 2000 onward, while G3 strains re-emerged, and G9 and G12 strains emerged during the same period. When crude strain prevalence data were weighted by region based on the region's contribution to global rotavirus mortality, the importance of genotypes G1 and G9 strains that were more prevalent in regions with low mortality was reduced and conversely the importance of G8 strains that were more prevalent in African settings with greater contribution to global rotavirus mortality was increased. This study provides the most comprehensive, up-to-date information on rotavirus strain surveillance in the pre-rotavirus vaccine era and will provide useful background to examine the impact of rotavirus vaccine introduction on future strain prevalence.

Motivated by the 2006 report of a Work Group appointed by the Environmental Protection Agency (EPA), this paper examines the present state of meta-analysis in environmental economics and offers recommendations for its future use. To this end we summarize and assess 140 meta-analyses from 125 published and unpublished studies, covering 17 topical categories in environmental and resource economics. First, we provide several generic meta-analysis models as reference points and discuss major estimation issues. Five econometric issues are identified as part of a complete analysis: (1) sample selection criteria; (2) basic data summary; (3) primary data heterogeneity; (4) heteroskedasticity; and (5) non-independence of multiple observations from primary studies. Second, a tabular summary is presented for the 140 meta-analyses with respect to estimation methods. Third, a narrative summary is presented for 19 meta-analyses, including the three value-of-statistical-life studies examined by the EPA Work Group and one analysis from each of 16 other categories. Fourth, we offer a set of “best practice” guidelines for future meta-analyses in this and other areas of economics. Last, the paper comments on the use of meta-analytic methods for benefit transfers of environmental values.

Lupines (Lupinus species; Fabaceae) are an ancient crop with great potential to be developed further for high-protein feed and food, cover crops, and phytoremediation. Being legumes, they are capable of symbiotically fixing atmospheric nitrogen. However, Lupinus species appear to be nonmycorrhizal or weakly mycorrhizal at most; instead some produce cluster roots, which release vast amounts of phosphate-mobilizing carboxylates (inorganic anions). Other lupines produce cluster-like roots, which function in a similar manner, and some release large amounts of carboxylates without specialized roots. These traits associated with nutrient acquisition make lupines ideally suited for either impoverished soils or soils with large amounts of phosphorus that is poorly available for most plants, e.g., acidic or alkaline soils. Here we explore how common the nonmycorrhizal phosphorus-acquisition strategy based on exudation of carboxylates is in the genus Lupinus, concluding it is very likely more widespread than generally acknowledged. This trait may partly account for the role of lupines as pioneers or invasive species, but also makes them suitable crop plants while we reach “peak phosphorus”.

Over the past decade several studies have reported that the gut microbiomes of mammals with similar dietary niches exhibit similar compositional and functional traits. However, these studies rely heavily on samples from captive individuals and often confound host phylogeny, gut morphology, and diet. To more explicitly test the influence of host dietary niche on the mammalian gut microbiome we use 16S rRNA gene amplicon sequencing and shotgun metagenomics to compare the gut microbiota of 18 species of wild non-human primates classified as either folivores or closely related non-folivores, evenly distributed throughout the primate order and representing a range of gut morphological specializations. While folivory results in some convergent microbial traits, collectively we show that the influence of host phylogeny on both gut microbial composition and function is much stronger than that of host dietary niche. This pattern does not result from differences in host geographic location or actual dietary intake at the time of sampling, but instead appears to result from differences in host physiology. These findings indicate that mammalian gut microbiome plasticity in response to dietary shifts over both the lifespan of an individual host and the evolutionary history of a given host species is constrained by host physiological evolution. Therefore, the gut microbiome cannot be considered separately from host physiology when describing host nutritional strategies and the emergence of host dietary niches.

In recent years, much of the emphasis for transformation of introductory STEM courses has focused on “active learning”, and while this approach has been shown to produce more equitable outcomes for students, the construct of “active learning” is somewhat ill-defined and is often used as a “catch-all” that can encompass a wide range of pedagogical techniques. Here we present an alternative approach for how to think about the transformation of STEM courses that focuses instead on what students should know and what they can do with that knowledge. This approach, known as three-dimensional learning (3DL), emerged from the National Academy’s “A Framework for K-12 Science Education”, which describes a vision for science education that centers the role of constructing productive causal accounts for phenomena. Over the past 10 years, we have collected data from introductory biology, chemistry, and physics courses to assess the impact of such a transformation on higher education courses. Here we report on an analysis of video data of class sessions that allows us to characterize these sessions as active, 3D, neither, or both 3D and active. We find that 3D classes are likely to also involve student engagement (i.e. be active), but the reverse is not necessarily true. That is, focusing on transformations involving 3DL also tends to increase student engagement, whereas focusing solely on student engagement might result in courses where students are engaged in activities that do not involve meaningful engagement with core ideas of the discipline.

The importance of improving STEM education is of perennial interest, and to this end, the education community needs ways to characterize transformation efforts. Three-dimensional learning (3DL) is one such approach to transformation, in which core ideas of the discipline, scientific practices, and crosscutting concepts are combined to support student development of disciplinary expertise. We have previously reported on an approach to the characterization of assessments, the Three-Dimensional Learning Assessment Protocol (3D-LAP), that can be used to identify whether assessments have the potential to engage students in 3DL. Here we present the development of a companion, the Three-Dimensional Learning Observation Protocol (3D-LOP), an observation protocol that can reliably distinguish between instruction that has potential for engagement with 3DL and instruction that does not. The 3D-LOP goes beyond other observation protocols, because it is intended not only to characterize the pedagogical approaches being used in the instructional environment, but also to identify whether students are being asked to engage with scientific practices, core ideas, and crosscutting concepts. We demonstrate herein that the 3D-LOP can be used reliably to code for the presence of 3DL; further, we present data that show the utility of the 3D-LOP in differentiating between instruction that has the potential to promote 3DL from instruction that does not. Our team plans to continue using this protocol to evaluate outcomes of instructional transformation projects. We also propose that the 3D-LOP can be used to support practitioners in developing curricular materials and selecting instructional strategies to promote engagement in three-dimensional instruction.

Carbon dioxide (CO2) emissions from combustion sources are uncertain in many places across the globe. Satellites have the ability to detect and quantify emissions from large CO2 point sources, including coal-fired power plants. In this study, we routinely made observations with the PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite imaging spectrometer and the Orbiting Carbon Observatory-3 (OCO-3) instrument aboard the International Space Station at over 30 coal-fired power plants between 2021 and 2022. CO2 plumes were detected in 50 % of the acquired PRISMA scenes, which is consistent with the combined influence of viewing parameters on detection (solar illumination and surface reflectance) and unknown factors (e.g., daily operational status). We compare satellite-derived emission rates to in situ stack emission observations and find average agreement to within 27 % for PRISMA and 30 % for OCO-3, although more observations are needed to robustly characterize the error. We highlight two examples of fusing PRISMA with OCO-2 and OCO-3 observations in South Africa and India. For India, we acquired PRISMA and OCO-3 observations on the same day and used the high-spatial-resolution capability of PRISMA (30 m spatial/pixel resolution) to partition relative contributions of two distinct emitting power plants to the net emission. Although an encouraging start, 2 years of observations from these satellites did not produce sufficient observations to estimate annual average emission rates within low (<15 %) uncertainties. However, as the constellation of CO2-observing satellites is poised to significantly improve in the coming decade, this study offers an approach to leverage multiple observation platforms to better quantify and characterize uncertainty for large anthropogenic emission sources.

Zika virus (ZIKV), an emerging flavivirus, has recently spread explosively through the Western hemisphere. In addition to symptoms including fever, rash, arthralgia, and conjunctivitis, ZIKV infection of pregnant women can cause microcephaly and other developmental abnormalities in the fetus. We report herein the results of ZIKV infection of adult rhesus macaques. Following subcutaneous infection, animals developed transient plasma viremia and viruria from 1-7 days post infection (dpi) that was accompanied by the development of a rash, fever and conjunctivitis. Animals produced a robust adaptive immune response to ZIKV, although systemic cytokine response was minimal. At 7 dpi, virus was detected in peripheral nervous tissue, multiple lymphoid tissues, joints, and the uterus of the necropsied animals. Notably, viral RNA persisted in neuronal, lymphoid and joint/muscle tissues and the male and female reproductive tissues through 28 to 35 dpi. The tropism and persistence of ZIKV in the peripheral nerves and reproductive tract may provide a mechanism of subsequent neuropathogenesis and sexual transmission.

Background Cervical cancer cases are increasing in sub-Saharan Africa, particularly in Kenya, exacerbated by inadequate histopathology resources, posing a significant barrier to timely diagnosis and treatment. There has been little research on the availability and evolution of histopathology resources for diagnosing cervical cancer over the years. This retrospective study evaluated this evolution at Moi Teaching and Referral Hospital in Kenya between 2018 and 2022. Methods We used a mixed-methods approach. An in-depth interview was conducted with one of MTRH’s pathology laboratory staff to assess the equipment, personnel, and quality control trends between 2018 and 2022. A thematic analysis was conducted in NVivo. We also retrospectively conducted a comprehensive inventory review of laboratory resources from 2018 to 2022 via purposive sampling. Microsoft Excel and Stata version 17 were utilized for descriptive statistical analysis. Turnaround time (TAT) was assessed against the UK’s National Health Service Cervical Screening Program guidelines. Results The number of histopathology laboratory personnel at MTRH increased from 2018 to 2022, during which the facility included two pathologists, one records person, and one office administrator. Cervical cancer biopsy samples processed by the histopathology lab increased from 225 in 2018 to 674 in 2022. However, the histopathology personnel-to-population ratio decreased from 1.5 pathologists and 2.7 histo-technicians per 100,000 in 2018 to 1.4 pathologists and 1.8 histo-technicians per 100,000 in 2022. Despite this decrease, lab equipment, automatic tissue processors and embedding machines were added, and an average 14-day turnaround time was maintained for cervical cancer pathology reports. Conclusions Our study highlights a growing burden of cervical cancer with biopsy samples processed by the MTRH histopathology laboratory, increasing from 225 in 2018 to 674 in 2022. Despite challenges such as a declining staff-to-patient ratio and limited resources, the lab maintained a commendable 14-day turnaround time, supporting timely cervical cancer diagnoses. These findings emphasize the need for continued investment in pathology resources and personnel to enhance diagnostic capacity and address the rising incidence of cervical cancer in Kenya and similar low-resource settings. The decline in the personnel-to-patient ratio underscores challenges in diagnosis, emphasizing the need to address workforce and infrastructure gaps to improve patient care within similar low-resource settings.