Fort Ross Conservancy

Rapid detection of active wildfires from satellite imagery is critical for emergency response and resource allocation. Traditional operational systems rely on thermal anomaly algorithms applied to sensors such as VIIRS and MODIS, which excel at global

In November 2022, teplizumab became the first drug approved to delay the course of any autoimmune disease and to change the course of type 1 diabetes (T1D) since the discovery of insulin. The path to its approval took more than 30 years with both successes and failures along the way that would have normally led to its abandonment in other circumstances. Development of the drug was based on studies in preclinical models and parallels efforts in transplantation. From a series of innovative adaptations in response to issues related to adverse events and immunogenicity, humanized Fc receptors (FcR) nonbinding antibodies were developed with improved clinical outcomes and safety as well as new mechanisms. Importantly, as a result of these developments, teplizumab has been able to achieve efficacy over extended periods of time without global immune suppression. The approval of teplizumab represents a significant first step toward achieving escape from T1D and, in the future, reversal of the disease.

Sequencing of the 16S ribosomal RNA (rRNA) gene is widely used to survey microbial communities. Specialized 16S rRNA databases have been developed to support this approach including Greengenes, RDP and SILVA. Most taxonomy annotations in these databases are predictions from sequence rather than authoritative assignments based on studies of type strains or isolates. In this work, I investigated the taxonomy annotations and guide trees provided by these databases. Using a blinded test, I estimated that the annotation error rate of the RDP database is ∼10%. The branching orders of the Greengenes and SILVA guide trees were found to disagree at comparable rates with each other and with taxonomy annotations according to the training set (authoritative reference) provided by RDP, indicating that the trees have comparable quality. Pervasive conflicts between tree branching order and type strain taxonomies strongly suggest that the guide trees are unreliable guides to phylogeny. I found 249,490 identical sequences with conflicting annotations in SILVA v128 and Greengenes v13.5 at ranks up to phylum (7,804 conflicts), indicating that the annotation error rate in these databases is ∼17%.

Abstract Sequencing of the 16S ribosomal RNA (rRNA) gene and the fungal Internal Transcribed Spacer (ITS) region is widely used to survey microbial communities. Specialized ribosomal sequence databases have been developed to support this approach including Greengenes, SILVA and RDP. Most taxonomy annotations in these databases are predictions from sequence rather than authoritative assignments based on studies of type strains or isolates. Here, I investigate the error rates of taxonomy annotations in these databases. I found 253,485 sequences with conflicting annotations in SILVA v128 and Greengenes v13.5 at ranks up to phylum (9,644 conflicts), indicating that the annotation error rate in these databases is ~15%. I found that 34% of non-singleton genera have overlapping subtrees in the Greengenes tree from 2001 according to the RDP taxonomy, most of which are probably due to branching order errors in the Greengenes tree, which is therefore an unreliable guide to phylogeny. Using a blinded test, I estimated that the annotation error rate of the RDP database is ~10%.

Within the quantum Darwinist framework introduced by W. H. Zurek ({\em Nat. Phys.}, 5:181-188, 2009), observers obtain pointer-state information about quantum systems by interacting with a local sample of the surrounding environment, e.g. a local sample of the ambient photon field. Because the environment encodes such pointer state information uniformly and hence redundantly throughout its entire volume, the information is equally available to all observers regardless of their location. This framework is applied to the observation of stellar center-of-mass positions, which are assumed to be encoded by the ambient photon field in a way that is uniformly accessible to all possible observers. Assuming Landauer's Principle, constructing such environmental encodings requires $(ln2) kT$ per encoded bit. For the observed 10$^{24}$ stars and a uniform binary encoding of center-of-mass positions into voxels with a linear dimension of 5 km, the free energy required at the current CMB temperature T = 2.7 K is $\sim$ 2.5 $\cdot$ 10$^{-27}$ kg $\cdot$ m$^{-3}$, strikingly close to the observed value of $\Omega_{\Lambda} \rho_{c}$. Decreasing the voxel size to $(l_{P})^{3}$ results in a free energy requirement 10$^{117}$ times larger.