PanIN and CAF transitions in pancreatic carcinogenesis revealed with spatial data integration.

This study introduces a new imaging, spatial transcriptomics (ST), and single-cell RNA-sequencing integration pipeline to characterize neoplastic cell state transitions during tumorigenesis. We applied a semi-supervised analysis pipeline to examine premalignant pancreatic intraepithelial neoplasias (PanINs) that can develop into pancreatic ductal adenocarcinoma (PDAC). Their strict diagnosis on formalin-fixed and paraffin-embedded (FFPE) samples limited the single-cell characterization of human PanINs within their microenvironment.

A probabilistic view of protein stability, conformational specificity, and design.

Various approaches have used neural networks as probabilistic models for the design of protein sequences. These "inverse folding" models employ different objective functions, which come with trade-offs that have not been assessed in detail before. This study introduces probabilistic definitions of protein stability and conformational specificity and demonstrates the relationship between these chemical properties and the [Formula: see text] Boltzmann probability objective.

A robust platform for integrative spatial multi-omics analysis to map immune responses to SARS-CoV-2 infection in lung tissues.

The SARS-CoV-2 (COVID-19) virus has caused a devastating global pandemic of respiratory illness. To understand viral pathogenesis, methods are available for studying dissociated cells in blood, nasal samples, bronchoalveolar lavage fluid and similar, but a robust platform for deep tissue characterization of molecular and cellular responses to virus infection in the lungs is still lacking. We developed an innovative spatial multi-omics platform to investigate COVID-19-infected lung tissues.

MILCDock: Machine Learning Enhanced Consensus Docking for Virtual Screening in Drug Discovery.

Molecular docking tools are regularly used to computationally identify new molecules in virtual screening for drug discovery. However, docking tools suffer from inaccurate scoring functions with widely varying performance on different proteins. To enable more accurate ranking of active over inactive ligands in virtual screening, we created a machine learning consensus docking tool, MILCDock, that uses predictions from five traditional molecular docking tools to predict the probability a ligand binds to a protein.

Training undergraduate research assistants with an outcome-oriented and skill-based mentoring strategy.

Effective mentoring of undergraduate students is a growing requirement for the promotion of faculty at many universities. It is often challenging for young investigators to define a successful mentoring strategy, partially due to the absence of a broadly accepted definition of what mentoring should entail. To overcome this, an outcome-oriented mentoring framework was developed and used with more than 25 students over three years.

Evaluation of Deep Neural Network ProSPr for Accurate Protein Distance Predictions on CASP14 Targets.

The field of protein structure prediction has recently been revolutionized through the introduction of deep learning. The current state-of-the-art tool AlphaFold2 can predict highly accurate structures; however, it has a prohibitively long inference time for applications that require the folding of hundreds of sequences. The prediction of protein structure annotations, such as amino acid distances, can be achieved at a higher speed with existing tools, such as the ProSPr network.

Pharmaceutical-Grade Rigosertib Is a Microtubule-Destabilizing Agent.

We recently used CRISPRi/a-based chemical-genetic screens and cell biological, biochemical, and structural assays to determine that rigosertib, an anti-cancer agent in phase III clinical trials, kills cancer cells by destabilizing microtubules. Reddy and co-workers (Baker et al., 2020, this issue of Molecular Cell) suggest that a contaminating degradation product in commercial formulations of rigosertib is responsible for the microtubule-destabilizing activity.

Considerations for Incision and Flap Design With Implant Therapy in the Esthetic Zone.

The planning and design of any incision in the esthetic zone should be carried out based on biologic principles and with careful consideration of the desired esthetic outcome. Different incision and flap designs have been identified for implant and implant-related surgeries in the esthetic zone. Those include; flapless, vestibular incision, papilla sparing, envelope, triangular, and trapezoidal.

Combined CRISPRi/a-Based Chemical Genetic Screens Reveal that Rigosertib Is a Microtubule-Destabilizing Agent.

Chemical libraries paired with phenotypic screens can now readily identify compounds with therapeutic potential. A central limitation to exploiting these compounds, however, has been in identifying their relevant cellular targets. Here, we present a two-tiered CRISPR-mediated chemical-genetic strategy for target identification: combined genome-wide knockdown and overexpression screening as well as focused, comparative chemical-genetic profiling.

Novel Approach to Managing Malsequenced and Malpositioned Immediately Placed Implants in the Esthetic Zone.

Esthetic implant therapy can be challenging in the anterior maxilla, and meticulous treatment is often required to deliver optimal esthetics. Close collaboration between surgical and prosthetic team members using the novel approach of prosthetic crown lengthening helped camouflage a shallow implant platform location, providing the proper gingival frame for esthetic restorations. This case report presents an interdisciplinary approach that included ridge augmentation, second-stage crown lengthening, and prosthetic soft tissue manipulation to address an implant placed too shallow in the alveolus of an extraction socket.

Modified Lip Repositioning with Esthetic Crown Lengthening: A Combined Approach to Treating Excessive Gingival Display.

Lip repositioning surgery to address excessive gingival display induced by different etiologies has received major attention recently. Several techniques and variations have been reported, including myotomy or repositioning of the levator labii superioris muscle, Le Fort impaction, maxillary gingivectomies, botulinum toxin injections, and lip stabilization. This study reports a case of excessive gingival display treated by a modified combined approach.

Detecting selection in immunoglobulin sequences.

The ability to detect selection by analyzing mutation patterns in experimentally derived immunoglobulin (Ig) sequences is a critical part of many studies. Such techniques are useful not only for understanding the response to pathogens, but also to determine the role of antigen-driven selection in autoimmunity, B cell cancers and the diversification of pre-immune repertoires in certain species. Despite its importance, quantifying selection in experimentally derived sequences is fraught with difficulties.

Reduced expression of gamma interferon in serum and marked lymphoid depletion induced by Porphyromonas gingivalis increase murine morbidity and mortality due to cytomegalovirus infection.

Porphyromonas gingivalis, a gram-negative anaerobe, is a major etiological agent of severe forms of periodontal disease. Although periodontal disease is considered a localized disease, accumulating evidence indicates that it may lead to a predisposition to a decline in immunocompetence. Human cytomegalovirus (CMV) commonly infects all human populations without producing significant clinical symptoms.