The salivary glands are a crucial site of replication for human cytomegalovirus (HCMV) and its murine counterpart, murine cytomegalovirus (MCMV). Studies of MCMV often involve the use of BALB/c strain mice, but most in vitro assays are carried out in the NIH 3T3 cell line, which is derived from Swiss Albino mice. This report describes a BALB/c-derived mouse salivary gland cell line immortalized using the SV40 large T antigen. Cells stained positive for PDGFR1 and negative for E-cadherin and PECAM-1, indicating mesenchymal origin. This cell line, which has been named murine salivary gland mesenchymal (mSGM), shows promise as a tool for ex vivo immunological assays due to its MHC haplotype match with the BALB/c mouse strain. In addition, plaque assays using mSGM rather than NIH 3T3 cells are significantly more sensitive for detecting low concentrations of MCMV particles. Finally, it is demonstrated that mSGM cells express all 3 BALB/c MHC class I isotypes and are susceptible to T cell-mediated ex vivo cytotoxicity assays, leading to many possible uses in immunological studies of MCMV.

Electrocatalytic synthesis under mild conditions has become increasingly important as one of the practical alternatives for industrial applications, especially for the green ammonia (NH3) industry. A properly engineered electrocatalyst plays a vital role in the realization of superior catalytic performance. Among various types of promising nanomaterials, metal-organic frameworks (MOFs) are competitive candidates for developing efficient electrocatalytic NH3 synthesis from simple nitrogen-containing molecules or ions, such as N2 and NO3-. In this review, recent advances in the development of electrocatalysts derived from MOFs for the electrosynthesis of NH3 are collected, categorized, and discussed, including their application in the N2 reduction reaction (NRR) and the NO3- reduction reaction (NO3RR). Firstly, the fundamental principles are illustrated, such as plausible mechanisms of NH3 generation from N2 and NO3-, the apparatus of corresponding electrocatalysis, parameters for evaluation of reaction efficiency, and detection methods of yielding NH3. Then, the electrocatalysts for NRR processes are discussed in detail, including pristine MOFs, MOF-hybrids, MOF-derived N-doped porous carbons, single atomic catalysts from pyrolysis of MOFs, and other MOF-related materials. Subsequently, MOF-related NO3RR processes are also listed and discussed. Finally, the existing challenges and prospects for the rational design and fabrication of electrocatalysts from MOFs for electrochemical NH3 synthesis are presented, such as the evolution of investigation methods with artificial intelligence, innovation in synthetic methods of MOF-related catalysts, advancement of characterization techniques, and extended electrocatalytic reactions.

Many species of sharks and some tunas are threatened by overexploitation, yet the degree of overlap between industrial fisheries and pelagic fishes remains poorly understood. Using satellite tracks from 933 industrial fishing vessels and predictive habitat models from 876 electronic tags deployed on seven shark and tuna species, we developed fishing effort maps across the northeast Pacific Ocean and assessed overlap with core habitats of pelagic fishes. Up to 35% of species core habitats overlapped with fishing effort. We identified overlap hotspots along the North American shelf, the equatorial Pacific, and the subtropical gyre. Results indicate where species require international conservation efforts and effective management within national waters. Only five national fleets (Mexico, Taiwan, China, Japan, and the United States) account for >90% of overlap with core habitats of our focal sharks and tunas on the high seas. These results inform global negotiations to achieve sustainability on the high seas.

INTRODUCTION: Human cytomegalovirus (HCMV) is a global health threat due to its ubiquity and lifelong persistence in infected people. During latency, host CD8+ T cell responses to HCMV continue to increase in a phenomenon known as memory inflation. We used murine CMV (MCMV) as a model for HCMV to characterize the memory inflation response to wild-type MCMV (KP) and a latency-defective mutant (ΔM33stop), which lacks M33, an MCMV chemokine receptor homolog. M33 is essential for normal reactivation from latency and this was leveraged to determine whether reactivation in vivo contributes to T cell memory inflation. METHODS: Mice were infected with wild-type or mutant MCMV and T cell responses were analyzed by flow cytometry at acute and latent time points. Ex vivo reactivation and cytotoxicity assays were carried out to further investigate immunity and virus replication. Quantitative reverse-transcriptase polymerase chain reaction (q-RTPCR) was used to examine gene expression during reactivation. MHC expression on infected cells was analyzed by flow cytometry. Finally, T cells were depleted from latently-infected B cell-deficient mice to examine the in vivo difference in reactivation between wild-type and ΔM33stop. RESULTS: We found that ΔM33stop triggers memory inflation specific for peptides derived from the immediate-early protein IE1 but not the early protein m164, in contrast to wild-type MCMV. During ex vivo reactivation, gene expression in DM33stop-infected lung tissues was delayed compared to wild-type virus. Normal gene expression was partially rescued by substitution of the HCMV US28 open reading frame in place of the M33 gene. In vivo depletion of T cells in immunoglobulin heavy chain-knockout mice resulted in reactivation of wild-type MCMV, but not ΔM33stop, confirming the role of M33 during reactivation from latency. Further, we found that M33 induces isotype-specific downregulation of MHC class I on the cell surface suggesting previously unappreciated roles in immune evasion. DISCUSSION: Our results indicate that M33 is more polyfunctional than previously appreciated. In addition to its role in reactivation, which had been previously described, we found that M33 alters viral gene expression, host T cell memory inflation, and MHC class I expression. US28 was able to partially complement most functions of M33, suggesting that its role in HCMV infection may be similarly pleotropic.

Illegal, unreported, and unregulated (IUU) fishing incurs an annual cost of up to US$25 billion in economic losses, results in substantial losses of aquatic life, and has been linked to human rights violations. Vessel tracking data from the automatic identification system (AIS) are powerful tools for combating IUU, yet AIS transponders can be disabled, reducing its efficacy as a surveillance tool. We present a global dataset of AIS disabling in commercial fisheries, which obscures up to 6% (>4.9 M hours) of vessel activity. Disabling hot spots were located near the exclusive economic zones (EEZs) of Argentina and West African nations and in the Northwest Pacific, all regions of IUU concern. Disabling was highest near transshipment hot spots and near EEZ boundaries, particularly contested ones. We also found links between disabling and location hiding from competitors and pirates. These inferences on where and why activities are obscured provide valuable information to improve fisheries management.

Deep learning shows promise for automating detection and classification of wildlife from digital aerial imagery to support cost-efficient remote sensing solutions for wildlife population monitoring. To support in-flight orthorectification and machine learning processing to detect and classify wildlife from imagery in near real-time, we evaluated deep learning methods that address hardware limitations and the need for processing efficiencies to support the envisioned in-flight workflow. We developed an annotated dataset for a suite of marine birds from high-resolution digital aerial imagery collected over open water environments to train the models. The proposed 3-stage workflow for automated, in-flight data processing includes: 1) image filtering based on the probability of any bird occurrence, 2) bird instance detection, and 3) bird instance classification. For image filtering, we compared the performance of a binary classifier with Mask Region-based Convolutional Neural Network (Mask R-CNN) as a means of sub-setting large volumes of imagery based on the probability of at least one bird occurrence in an image. On both the validation and test datasets, the binary classifier achieved higher performance than Mask R-CNN for predicting bird occurrence at the image-level. We recommend the binary classifier over Mask R-CNN for workflow first-stage filtering. For bird instance detection, we leveraged Mask R-CNN as our detection framework and proposed an iterative refinement method to bootstrap our predicted detections from loose ground-truth annotations. We also discuss future work to address the taxonomic classification phase of the envisioned workflow.

Perovskite-related materials show very promising properties in many fields. Pb-free perovskites are particularly interesting, because of the toxicity of Pb. In this study, hybrid double perovskite MA₂KBiCl₆ (MA = methylammonium cation) was found to have interesting variable temperature behaviours. Both variable temperature single crystal X-ray diffraction, synchrotron powder diffraction, and Raman spectroscopy were conducted to reveal a rhombohedral to cubic phase transition at around 330 K and an order to disorder transition for inorganic cage below 210 K.