bluuebunny/crossref_metadata_2025 huggingface dataset:
“Assessing the Quality of Reporting on Quality Improvement Initiatives in Breast Reconstruction – A Systematic Review”
Authors: Daniel Pereira Diego , Cormier Nicholas S. , Market Marisa R. , Frank Simon G.
Published: December 2022

Background:

There has been a recent increase in the number and complexity of quality improvement studies in breast reconstruction. To assist with the development of thorough quality improvement reporting practices, with the goal of improving the transferability of these initiatives, we conducted a systematic review of studies describing the implementation of quality improvement initiatives in breast reconstruction. We used the SQUIRE 2.0 guideline to appraise the quality of reporting of these initiatives.

Methods:

English language articles published in EMBASE, MEDLINE, CINAHL, and the Cochrane databases were searched. Quantitative studies evaluating the implementation of QI initiatives in breast reconstruction were included. The primary endpoint of interest in this review was the distribution of studies per SQUIRE 2.0 criteria scores in proportions. Abstracts and full-text screening, and data extraction were completed independently and in duplicate by the review team.

Results:

We screened 1107 studies, of which 53 full texts were assessed and 35 met inclusion criteria. In our assessment, only 3 studies (9%) met all 18 SQUIRE 2.0 criteria. SQUIRE 2.0 criteria that were met most frequently were abstract, problem description, rationale and analysis. The lowest SQUIRE 2.0 scores appeared in the interpretation criteria.

Conclusion:

Significant opportunity exists to improve quality improvement reporting in breast reconstruction, especially in the realm of costs, strategic trade-offs, ethical considerations, project sustainability and potential for spread to other contexts. Improvements in these areas will help to further advance the transferability of QI initiatives in breast reconstruction.
Prototype matching: children’s preference for forming scientific concepts
Authors: Wang Zhong , Zhang Yi , Jiang Yi
Published: December 2022

Inspired by a sample lesson, this paper studies and discusses children’s preferences in learning scientific concepts. In a “Dissolution” lesson, one of the students took the demonstration experiment of “carmine dissolves in Water” demonstrated by the teacher as the prototype to judge whether a new phenomenon belongs to dissolution, instead of analyzing and judging the phenomenon by using the dissolution definition. Therefore, we propose a conjecture that “prototype matching” may be a more preferred way for children to learn concepts than thinking through inquiry experiment, analysis, deduction, etc. To this end, we conducted a targeted test on 160 fifth grade students (all of whom had learned this lesson) from a primary school in Beijing, and used goodness of fit test to statistically analyze the results. The results showed that: ➀ the Chi square of the general result is 73.865, P<0.001, indicating that children did have obvious prototype preference; ➁ We “tampered” some of the prototypes, that is, they looked like the prototypes that the teacher had told students, but they were actually wrong. However, the results showed that children still preferred these so-called “prototypes” (chi square is 21.823, P<0.001). Conclusion: ➀ Children have an obvious preference for “prototype matching” in scientific concept learning, which is not only obviously deviated from the current general understanding of science education that emphasizes inquiry construction, but also points out that there may be a priority relationship among various ways of concept organization (such as definition theory, prototype theory, schema theory, etc.). ➁ Children’s preference for prototypes seems to be unthinking, and they will not identify the authenticity of prototypes, which is particularly noteworthy in front-line teaching.
Euglenozoan kleptoplasty illuminates the early evolution of photoendosymbiosis
Authors: Karnkowska Anna , Yubuki Naoji , Maruyama Moe , Yamaguchi Aika , Kashiyama Yuichiro , Suzaki Toshinobu , Keeling Patrick J , Hampl Vladimir , Leander Brian S
Published: December 2022

Kleptoplasts are distinct among photosynthetic organelles in eukaryotes (i.e, plastids) because they are routinely sequestered from prey algal cells and function only temporarily in the new host cell. Therefore, the hosts of kleptoplasts benefit from photosynthesis without constitutive photoendosymbiosis. Here, we report that the euglenozoanRapaza viridishas only kleptoplasts derived from a specific strain of green alga,Tetraselmissp., but no canonical plastids like those found in its sister group, the Euglenophyceae.R. viridisshowed a dynamic change in the accumulation of cytosolic polysaccharides in response to light– dark cycles, and13C isotopic labeling of ambient bicarbonate demonstrated that these polysaccharides originatein situvia photosynthesis; these data indicate that the kleptoplasts ofR. viridisare functionally active. We also identified 247 sequences encoding putative plastid-targeting proteins and 35 sequences of presumed kleptoplast transporters in the transcriptome ofR. viridis. These genes originated in a wide range of algae other thanTetraselmissp., the source of the kleptoplasts, suggesting a long history of repeated horizontal gene transfer events from different algal prey cells. Many of the kleptoplast proteins, as well as the protein-targeting system, inR. viridiswere shared with members of the Euglenophyceae, providing evidence that the early stages in the endosymbiotic origin of euglenophyte plastids also involved kleptoplasty.
Maternal obesity driven changes in collagen linearity of breast extracellular matrix induces invasive mammary epithelial cell phenotype
Authors: Amens Jensen N. , Bahçecioglu Gökhan , Dwyer Kiera , Yue Xiaoshan S. , Stack M. Sharon , Hilliard Tyvette S. , Zorlutuna Pinar
Published: December 2022

Obesity has been linked with numerous health issues as well as an increased risk of breast cancer. Although effects of direct obesity in patient outcomes is widely studied, effects of exposure to obesity-related systemic influencesin uterohas been overlooked. In this study, we investigated the effect of multigenerational obesity on epithelial cell migration and invasion using decellularized breast tissues explanted from normal female mouse pups from a diet induced multigenerational obesity mouse model. We first studied the effect of multigenerational diet on the mechanical properties, adipocyte size, and collagen structure of these mouse breast tissues, and then, examined the migration and invasion behavior of normal (KTB-21) and cancerous (MDA-MB-231) human mammary epithelial cells on the decellularized matrices from each diet group. Breast tissues of mice whose dams had been fed with high-fat diet exhibited larger adipocytes and thicker and curvier collagen fibers, but only slightly elevated elastic modulus and inflammatory cytokine levels. MDA-MB-231 cancer cell motility and invasion were significantly greater on the decellularized matrices from mice whose dams were fed with high-fat diet. A similar trend was observed with normal KTB-21 cells. Our results showed that the collagen curvature was the dominating factor on this enhanced motility and stretching the matrices to equalize the collagen fiber linearity of the matrices ameliorated the observed increase in cell migration and invasion in the mice that were exposed to a high-fat diet. Previous studies indicated an increase in serum leptin concentration for those children born to an obese mother. We generated extracellular matrices using primary fibroblasts exposed to various concentrations of leptin. This produced curvier ECM and increased breast cancer cell motility for cells seeded on the decellularized ECM generated with increasing leptin concentration. Our study shows that exposure to obesityin uterois influential in determining the extracellular matrix structure, and that the resultant changes in collagen curvature is a critical factor in regulating the migration and invasion of breast cancer cells.
Positive effects of projected climate change on post-disturbance forest regrowth rates in northeastern North American boreal forests
Authors: Danneyrolles Victor , Boucher Yan , Fournier Richard , Valeria Osvaldo
Published: December 2022

Forest anthropogenic and natural stand-replacing disturbances are increasing worldwide due to global change. Many uncertainties regarding the regeneration and growth of these young forests remain within the context of changing climate. In this study, we investigate the effects of climate, tree species composition, and other landscape-scale environmental variables upon boreal forest regrowth following clearcut logging in eastern Canada. Our main objective was to predict the effects of future climate changes upon post-logging forest height regrowth at a subcontinental scale using high spatial resolution remote sensing data. We modeled forest canopy height (estimated from airborne laser scanning [LiDAR] data over 20-m resolution virtual plots) as a function of time elapsed since the last clearcut along with climatic (i.e., temperature and moisture), tree species composition, and other environmental variables (e.g., topography and soil hydrology). Once trained and validated with ∼240,000 plots, the model that was developed in this study was used to predict potential post-logging canopy height regrowth at 20-m resolution across a 240,000 km2 area following scenarios depicting a range of projected changes in temperature and moisture across the region for 2041-2070. Our results predict an overall beneficial, but limited effect of projected climate changes upon forest regrowth rates in our study area. Stimulatory effects of projected climate change were more pronounced for conifer forests, with growth rates increasing between +5% and +50% over the study area, while mixed and broadleaved forests recorded changes that mostly ranged from -5% to +35%. Predicted increased regrowth rates were mainly associated with increased temperature, while changes in climate moisture had a minor effect. We conclude that such gains in regrowth rates may partially compensate for projected substantial increases in fire activity and other natural disturbances that are expected with climate change in these boreal forests.
Unclearing Microscopy
Authors: M’Saad Ons , Shribak Michael , Bewersdorf Joerg
Published: December 2022

The spatial resolution and contrast sensitivity of the human eye is limited, restricting our ability to directly see subcellular structures. We report a new principle for unaided eye cellular visualization in a method we call Unclearing Microscopy. By expanding cells and tissue >8,000 volumetrically and opaquing their bulk with light-scattering molecules of sufficient density, cell microstructure can now be discerned with a contrast visible to the unaided eye. We further inspect uncleared samples with transmitted light microscopy modalities and prove that 3D ultrastructural features, previously accessible only with super-resolution fluorescence or electron microscopy methods, can now be visualized with simple magnification optics alone.
Prediction and Curation of Missing Biomedical Identifier Mappings with Biomappings
Authors: Hoyt Charles Tapley , Hoyt Amelia L. , Gyori Benjamin M.
Published: December 2022

Motivation

Biomedical identifier resources (ontologies, taxonomies, controlled vocabularies) commonly overlap in scope and contain equivalent entries under different identifiers. Maintaining mappings for these relationships is crucial for interoperability and the integration of data and knowledge. However, there are substantial gaps in available mappings motivating their semi-automated curation.

Results

Biomappings implements a curation cycle workflow for missing mappings which combines automated prediction with human-in-the-loop curation. It supports multiple prediction approaches and provides a web-based user interface for reviewing predicted mappings for correctness, combined with automated consistency checking. Predicted and curated mappings are made available in public, version-controlled resource files on GitHub. Biomappings currently makes available 8,560 curated mappings and 41,178 predicted ones, providing previously missing mappings between widely used resources covering small molecules, cell lines, diseases and other concepts. We demonstrate the value of Biomappings on case studies involving predicting and curating missing mappings among cancer cell lines as well as small molecules tested in clinical trials. We also present how previously missing mappings curated using Biomappings were contributed back to multiple widely used community ontologies.

Availability

The data and code are available under the CC0 and MIT licenses athttps://github.com/biopragmatics/biomappings.

Contact

benjamin_gyori@hms.harvard.edu
Probing Conformational Landscapes and Mechanisms of Allosteric Communication in the Functional States of the ABL Kinase Domain Using Multiscale Simulations and Network-Based Mutational Profiling of Allosteric Residue Potentials
Authors: Krishnan Keerthi , Tian Hao , Tao Peng , Verkhivker Gennady M.
Published: December 2022

In the current study, multiscale simulation approaches and dynamic network methods are employed to examine the dynamic and energetic details of conformational landscapes and allosteric interactions in the ABL kinase domain that determine the kinase functions. Using a plethora of synergistic computational approaches, we elucidate how conformational transitions between the active and inactive ABL states can employ allosteric regulatory switches to modulate the intramolecular communication networks between the ATP site, the substrate binding region, and the allosteric binding pocket. A perturbation-based network approach that implements mutational profiling of allosteric residue propensities and communications in the ABL states is proposed. Consistent with the biophysical experiments, the results reveal functionally significant shifts of the allosteric interaction networks in which preferential communication paths between the ATP binding site and substrate regions in the active ABL state become suppressed in the closed inactive ABL form, which in turn features favorable allosteric couplings between the ATP site and the allosteric binding pocket. By integrating the results of atomistic simulations with dimensionality reduction methods and Markov state models we analyze the mechanistic role of the macrostates and characterize kinetic transitions between the ABL conformational states. Using network-based mutational scanning of allosteric residue propensities, this study provides a comprehensive computational analysis of the long-range communications in the ABL kinase domain and identifies conserved regulatory hotspots that modulate kinase activity and allosteric cross-talk between the allosteric pocket, ATP binding site and substrate binding regions.
Machine learning assisted ligand binding energy prediction forin silicogenerated glycosyl hydrolase enzyme combinatorial mutant library
Authors: Guranovic Igor , Kumar Mohit , Bandi Chandra K. , Chundawat Shishir P. S.
Published: December 2022

Molecular docking is a computational method used to predict the preferred binding orientation of one molecule to another when bound to each other to form an energetically stable complex. This approach has been widely used for early-stage small-molecule drug design as well as identifying suitable protein-based macromolecule residues for mutagenesis. Estimating binding free energy, based on docking interactions of protein to its ligand based on an appropriate scoring function is often critical for protein mutagenesis studies to improve the activity or alter the specificity of targeted enzymes. However, calculating docking free energy for a large number of protein mutants is computationally challenging and time-consuming. Here, we showcase an end-to-end computational workflow for predicting the binding energy of pNP-Xylose substrate docked within the substrate binding site for a large library of combinatorial mutants of an alpha-L-fucosidase (TmAfc, PDB ID-2ZWY) belonging toThermotoga maritimaglycosyl hydrolase (GH) family 29. Briefly,in silicocombinatorial mutagenesis was performed for the top conserved residues inTmAfc as determined by running multiple sequence alignment against all GH29 family enzyme sequences downloaded from an in-house developed Carbohydrate-Active enZyme (CAZy) database retriever program. The binding energy was calculated through Autodock Vina with pNP-Xylose ligand docking with energy minimizedTmAfc mutants, and the data was then used to train a neural network model which was also validated for model predictions using data from Autodock Vina. The current workflow can be adopted for any family of CAZymes to rapidly identify the effect of different mutations within the active site on substrate binding free energy to identify suitable targets for mutagenesis. We anticipate that this workflow could also serve as the starting point for performing more sophisticated and computationally intensive binding free energy calculations to identify targets for mutagenesis and hence optimize use of wet lab resources.
Evaluation of sex and age effects of fiber damage before permeabilization on mitochondrial respiration
Authors: Campbell Matthew D. , Marcinek David J.
Published: December 2022

The use of permeabilized muscle fibers (PMF) has emerged as a gold standard for assessing skeletal muscle mitochondrial function. PMF provide an intermediate approach between in vivo strategies and isolated mitochondria that allows the mitochondria to be maintained in close to their native morphology in the myofiber while allowing greater control of substrate and inhibitor concentrations. However, like mitochondrial isolation, the primary drawback to PMF is disruption of the cellular environment during the muscle biopsy and preparation. Despite all the benefits of permeabilized muscle fibers in evaluating mitochondrial respiration and dynamics one of the major drawbacks is increased variability introduced during a muscle biopsy as well as intrinsic variation that exists due to sex and age. This study was designed to evaluate how age, sex, and biopsy preparations affect mitochondrial respiration in extensor digitorum longus, soleus, and gastrocnemius muscle of mice. Here we detail a modified approach to skeletal muscle biopsy of the gastrocnemius muscle of mice focused on maintenance of intact fibers that results in greater overall respiration compared to cut fibers. The improved respiration of intact fibers is sex specific as are some of the changes in mitochondrial respiration with age. This study shows the need for standard practices when measuring mitochondrial respiration in permeabilized muscle and provides a protocol to control for variation introduced during a typical mouse muscle biopsy.
Dynamic Data Independent Acquisition Mass Spectrometry with Real-Time Retrospective Alignment
Authors: Heil Lilian R , Remes Philip M , Canterbury Jesse D , Yip Ping , Barshop William D , Wu Christine C , MacCoss Michael J
Published: December 2022

We report a data independent acquisition (DIA) strategy that dynamically adjusts the tandem mass spectrometry (MS/MS) windows during the chromatographic separation. The method focuses MS/MS acquisition on the most relevant mass range at each point in time – improving the quantitative sensitivity by increasing the time spent on each DIA window. We demonstrate an improved lower limit of quantification, on average, without sacrificing the number of peptides detected.
miR-29 is an important driver of aging-related phenotypes
Authors: Swahari Vijay , Nakamura Ayumi , Hollville Emilie , Hung Yu-Han , Kanke Matt , Kurtz C. Lisa , Caravia Xurde M. , He Shenghui , Krishnamurthy Janakiraman , Kapoor Sahil , Prasad Varun , Flowers Cornelius , Beck Matt , Baran-Gale Jeanette , Sharpless Norman , López-Otín Carlos , Sethupathy Praveen , Deshmukh Mohanish
Published: December 2022

Aging is a consequence of complex molecular changes, but the roles of individual microRNAs (miRNAs) in aging remain unclear. One of the few miRNAs that are upregulated during both normal and premature aging is miR-29. We confirmed this finding in our study in both mouse and monkey models. Follow-up analysis of the transcriptomic changes during normal aging revealed that miR-29 is among the top miRNAs predicted to drive the aging-related gene expression changes. We also showed that partial loss of miR-29 extends the lifespan ofZmpste24-/-mice, an established model of progeria, which indicates that miR-29 is functionally important in this accelerated aging model. To examine whether miR-29 upregulation alone is sufficient to promote aging-related phenotypesin vivo, we generated mice in which miR-29 can be conditionally overexpressed (miR-29TG). We found that miR-29 overexpression in mice is sufficient to drive aging-related phenotypes including alopecia, kyphosis, osteoporosis, senescence, and leads to early lethality. Transcriptomic analysis of both young miR-29TG and old WT mice revealed shared downregulation of genes enriched in extracellular matrix and fatty acid metabolism, and shared upregulation of genes in pathways linked to inflammation. Together, these results highlight the functional importance of miR-29 in controlling a gene expression program that drives agingrelated phenotypes.
Circulation of Fluconazole-ResistantC. albicans, C. aurisandC. parapsilosisBloodstream Isolates Carrying Y132F, K143R or T220L Erg11p Substitutions in Colombia
Authors: Ceballos-Garzon Andres , Peñuela Ana , Valderrama-Beltrán Sandra , Vargas-Casanova Yerly , Ariza Beatriz , Parra-Giraldo Claudia M.
Published: December 2022

AlthoughCandidaspp., is a common cause of bloodstream infections and is often associated with high mortality rates, its resistance to antifungal drugs, and the molecular mechanisms involved have been poorly studied in Colombia. Here, 123 bloodstream isolates ofCandidaspp. were collected. MALDI-TOF MS identification and fluconazole (FLC) susceptibility patterns were assessed on all isolates. Subsequently, sequencing ofERG11, TAC1orMRR1, and efflux pumps were performed for resistant isolates. Out of 123 clinical strains,C. albicansaccounted for 37.4%, followed byC. tropicalis26.8%,C. parapsilosis19.5%,C. auris8.1%,C. glabrata4.1%,C. krusei2.4% andC. lusitaniae1.6%. Resistance to FLC reached 18%. Erg11 amino acid substitutions associated with FLC-resistance (Y132F, K143R or T220L) were found in 58% of 19 FLC-resistant isolates. Furthermore, novel mutations were found in all genes studied. Regarding efflux pumps, 42% of 19 FLC-resistantCandidaspp strains showed significant efflux activity. Finally, six of the 19 FLC-resistant isolates neither harbored resistance-associated mutations nor showed efflux pump activity. AlthoughC. albicansremain the most predominant species, non-C. albicansspecies comprise a high proportion (62.6%). Among FLC-resistant species,C. auris(70%) andC. parapsilosis(25%) displayed the highest percentages of resistance. In 68% of FLC-resistant isolates, a mechanism that could explain their phenotype was found (e.g. mutations, flux pump activity or both). We provide evidence that endemic isolates harbor amino acid substitutions related with resistance to one of the most used molecules in the hospital setting, with Y132F being the most frequently detected one.
Identifying patients requiring treatment for depression in the postpartum period from common electronic medical record data available antepartum using machine learning
Authors: Wakefield Colin , Frasch Martin G.
Published: December 2022

Objective

Depression requiring treatment in the postpartum period (PPD) significantly impacts maternal and neonatal health. While preventive management of depression in pregnancy has been shown to decrease the negative effects, current methods for identifying at-risk patients are insufficient. Given the complexity of the diagnosis and interplay of clinical/demographic factors, we tested if machine learning (ML) techniques can accurately identify patients at risk of PPD.

Study Design

This is a retrospective cohort study of the NIH Nulliparous Pregnancy Outcomes Study (nuMoM2b) which enrolled 10,038 nulliparous people. The primary outcome was PPD. We constructed and optimized four ML models using distributed random forest modeling based on the nuMoM2b dataset. Model 1 utilized only readily obtainable sociodemographic data. Model 2 added maternal pre-pregnancy mental health data. Model 3 utilized recursive feature elimination to construct a parsimonious model. Model 4 further titrated the input data to exclude pre-pregnancy mental health variables.

Results

Of 8454 births, 338 (4%) were complicated by PPD. Model 3 was the highest performing, demonstrating the area under the receiver operating characteristics curve (AUC) of 0.91(±0.02). Models 1-3 identified the 9 variables most predictive of depression hierarchically ranging from BMI (highest), prior depression, age, income, medications, education, past medical history, race, and prior anxiety (lowest). In model 4, the AUC remained at 0.80(±0.04).

Conclusions

Counterintuitively, the presence of pre-pregnancy mental health conditions is not the most predictive factor of PPD. Furthermore, PPD can be predicted with high accuracy for individual patients using antepartum information commonly found in the EMR.
Sexual dimorphism of the synovial transcriptome underpins greater PTOA disease severity in male mice following joint injury
Authors: Bergman Rachel F. , Lammlin Lindsey , Junginger Lucas , Farrell Easton , Goldman Sam , Darcy Rose , Rasner Cody , Obeidat Alia M. , Malfait Anne-Marie , Miller Rachel E. , Maerz Tristan
Published: December 2022

Objective

To elucidate sex differences in synovitis, mechanical sensitization, structural damage, bone remodeling, and the synovial transcriptome in the anterior cruciate ligament rupture (ACLR) mouse model of post-traumatic osteoarthritis (PTOA).

Methods

Male and female 12-week-old C57Bl/6 mice were randomized to noninvasive ACLR or sham (n=9/sex/group/timepoint). Knee hyperalgesia, mechanical allodynia, and intra-articular MMP activity (via intravital imaging) were measured longitudinally. Trabecular and subchondral bone remodeling and osteophyte formation were assessed by μCT. Histological scoring of PTOA and synovitis and anti-MMP13 immunostaining was performed. NaV1.8-Cre;tdTomato mice were used to document localization and sprouting of nociceptors. Bulk RNAseq of synovium in sham, 7d, and 28d post-ACLR, and contralateral joints (n=6) assessed injury-induced and sex-dependent synovial gene expression.

Results

Male mice exhibited worse joint damage at 7d and 28d and worse synovitis at 28d, accompanied by greater MMP activity, knee hyperalgesia, and mechanical allodynia. Females had catabolic responses in trabecular and subchondral bone after injury, whereas males exhibited greater osteophyte formation and sclerotic remodeling of trabecular and subchondral bone. NaV1.8+ nociceptor sprouting in subchondral bone and medial synovium was induced by injury and comparable between sexes. RNAseq of synovium demonstrated that both sexes had similar injury-induced gene expression at 7d, but only female mice exhibited synovial inflammatory resolution by 28d, whereas males had persistent pro-inflammatory, pro-fibrotic, pro-neurogenic, and pro-angiogenic gene expression.

Conclusion

Worse overall joint pathology and pain behavior in male mice was associated with persistent activation of synovial inflammatory, fibrotic, and neuroangiogenic processes, implicating persistent synovitis in driving sex differences in murine PTOA.
Modeling Mechanical Feedback Mechanisms in a Multiscale Sliding Filament Model of Lymphatic Muscle Pumping
Authors: Xie Peter Y. , Morris Christopher J. , Bertram Christopher , Zaweija David , Moore James E.
Published: December 2022

The lymphatic system maintains bodily fluid balance by returning interstitial fluid to the venous system. Flow can occur through a combination of extrinsic pumping, due to forces from surrounding tissues, and intrinsic pumping involving contractions of muscle in the lymphatic vessel walls. Lymph transport is important not only for fluid homeostasis, but also for immune function, as lymph is a carrier for immune cells. Lymphatic muscle cells exhibit cardiac-like phasic contractions to generate flow and smooth-muscle-like tonic contractions to regulate flow. Lymphatic vessels therefore act as both active pumps and conduits. Lymphatic vessels are sensitive to mechanical stimuli, including flow-induced shear stresses and pressure-induced vessel stretch. These forces modulate biochemical pathways, leading to changes in intracellular calcium and interaction with regulatory and contractile proteins. In a multiscale computational model of phasic and tonic contractions in lymphatic muscle coupled to a lumped-parameter model of lymphatic pumping, we tested different models of the mechanical feedback mechanisms exhibited by lymphatics in experiments. Models were validated using flow and pressure experiments not used in the models’ construction. The final model shows that with flow-induced shear stress modulation, there is a small change in flow rate but an increase in muscle efficiency. A better understanding of the mechanobiology of lymphatic contractions can help guide future lymphatic vessel experiments, providing a basis for developing better treatments for lymphatic dysfunction.
Antifungal tolerance and resistance emerge at distinct drug concentrations and rely upon different aneuploid chromosomes
Authors: Yang Feng , Scopel Eduardo FC , Li Hao , Sun Liu-liu , Kawar Nora , Cao Yong-bing , Jiang Yuan-Ying , Berman Judith
Published: December 2022

Antifungal drug tolerance is a response distinct from resistance, in which cells grow slowly above the minimum inhibitory drug concentration (MIC). Here we found that the majority (69.2%) of 133Candida albicansclinical isolates, including standard lab strain SC5314, exhibitedtemperature-enhancedtolerance at 37°C and 39°C, and were not tolerant at 30°C. Other isolates were eitheralwaystolerant (23.3%) ornevertolerant (7.5%) at these three temperatures, suggesting that tolerance requires different physiological processes in different isolates. At supra-MIC fluconazole concentrations (8-128 μg/ml), tolerant colonies emerged rapidly at a frequency of ~10−3. In liquid passages over a broader range of fluconazole concentrations (0.25-128 μg/ml), tolerance emerged rapidly (within one passage) at supra-MIC concentrations. By contrast, resistance appeared at sub-MIC concentrations after 5 or more passages. Of 155 adaptors that evolved higher tolerance, all carried one of several recurrent aneuploid chromosomes, often including chromosome R, alone or in combination with other chromosomes. Furthermore, loss of these recurrent aneuploidies was associated with a loss of acquired tolerance, indicating that specific aneuploidies confer fluconazole tolerance. Thus, genetic background and physiology, and the degree of drug stress (above or below the MIC) influence the evolutionary trajectories and dynamics with which antifungal drug resistance or tolerance emerges.

Importance

Antifungal drug tolerance differs from drug resistance: tolerant cells grow slowly in drug, while resistant cells usually grow well, due to mutations in a few known genes. More than half ofCandida albicansclinical isolates have higher tolerance at body temperature than they do at the lower temperatures used for most lab experiments. This implies that different isolates achieve drug tolerance via several cellular processes. When we evolved different strains at a range of high drug concentrations above inhibitory levels, tolerance emerged rapidly and at high frequency (one in 1000 cells) while resistance only appeared later at very low drug concentrations. An extra copy of all or part of chromosome R was associated with tolerance, while point mutations or different aneuploidies were seen with resistance. Thus, genetic background and physiology, temperature, and drug concentration all influence how drug tolerance or resistance evolves.
Predicting Immune Escape with Pretrained Protein Language Model Embeddings
Authors: Swanson Kyle , Chang Howard , Zou James
Published: December 2022

Assessing the severity of new pathogenic variants requires an understanding of which mutations enable escape of the human immune response. Even single point mutations to an antigen can cause immune escape and infection by disrupting antibody binding. Recent work has modeled the effect of single point mutations on proteins by leveraging the information contained in large-scale, pretrained protein language models (PLMs). PLMs are often applied in a zero-shot setting, where the effect of each mutation is predicted based on the output of the language model with no additional training. However, this approach cannot appropriately model immune escape, which involves the interaction of two proteins—antibody and antigen— instead of one protein and requires making different predictions for the same antigenic mutation in response to different antibodies. Here, we explore several methods for predicting immune escape by building models on top of embeddings from PLMs. We evaluate our methods on a SARS-CoV-2 deep mutational scanning dataset and show that our embedding-based methods significantly outperform zero-shot methods, which have almost no predictive power. We also highlight insights gained into how best to use embeddings from PLMs to predict escape. Despite these promising results, simple statistical and machine learning baseline models that do not use pretraining perform comparably, showing that computationally expensive pretraining approaches may not be beneficial for escape prediction. Furthermore, all models perform relatively poorly, indicating that future work is necessary to improve escape prediction with or without pretrained embeddings1.
Phylogeographic and morphological analysis ofBotrylloides nigerHerdman, 1886 from the northeastern Mediterranean Sea
Authors: Temiz Berivan , Öztürk Esra , Blanchoud Simon , Karahan Arzu
Published: December 2022

Botrylloides nigeris an invasive marine filter-feeding invertebrate that is believed to originate from the West Atlantic region. This species of colonial tunicate has been observed on several locations along the coasts of Israel and around the Suez Canal but it has not yet been reported on the coasts of the northeastern Mediterranean Sea (NEMS), suggesting an ongoing Lessepsian migration. However, the extent of this invasion might be concealed by reports of other potentially misidentified species ofBotrylloides, given that the strong morphological similarities within this genus renders taxonomical identification particularly challenging. In this study, we performed a phylogeographic and morphological analysis ofB. nigerin the NEMS. We collected 241 samples from 8 sampling stations covering 824 km of coastlines of NEMS. We reported 14 different morphotypes, of which the orange-brown, orange and brown-striped morphs were the most abundant. Using the mitochondrial cytochrome C oxidase I (COI), one of the four most commonly used DNA barcoding marker, we identified 4 haplotypes with the Konacık (H4) and the Mezitli (H3) ones being the most diverged. The COI haplotypes clustered with the referenceB. nigersequences from GenBank and separated from sisterBotrylloidesspecies with high confidence. We confirmed our identification using the three additional barcoding markers (Histone 3, 18S rRNA and 28S rRNA), which all matched with over 99% similarity to the reference sequences. In addition, we monitored the Kızkalesi station for a year and applied temporal analysis to the colonies collected. The colonies regressed during winter while resettled and expanded during summer. We performed gene flow analysis on our spatial data that identified a possible population subdivision at the sampling site of Side, which might be caused by a local freshwater input. Overall, we here present the first report on the presence ofBotrylloides nigerin the NEMS, we show that this species is commonly present throughout this region and with a particularly high morphological as well as genomic diversity.
Non-invasive in-blood glucose sensing
Authors: Uluç Nasire , Glasl Sarah , Jüstel Dominik , Pleitez Miguel A. , Ntziachristos Vasilis
Published: December 2022

Non-invasive glucose monitoring (NIGM) is increasingly considered as an alternative to finger pricking for blood glucose assessment and management of diabetes in insulin-dependent patients, due to the pain, risk of infection, and inadequacy of finger pricking for frequent measurements. Nevertheless, current NIGM techniques do not measure glucose in blood, but rely on indirect bulk measurement of glucose in the interstitial fluid, where glucose is less concentrated, diluted in a generally unknown volume, and appears in a delayed fashion relative to blood glucose, impairing NIGM accuracy. We introduce a new biosensor, termedDepth-gated mid-InfraRedOptoacousticSensor (DIROS), which offers for the first time non-invasive glucose detection directly in blood, while simultaneously rejecting contributions from the metabolically inactivestratum corneumand other superficial skin layers. This unique ability is achieved by time-gating mid-infrared optoacoustic signals to enable glucose readings from depth-selective localization in the microvasculature of the skin. In measurements of micein vivo, DIROS revealed marked accuracy improvement over conventional bulk-tissue glucose measurements. We showcase how skin rejection and signal localization are essential for improving the NIGM accuracy, and discuss key results and how DIROS offers a holistic approach to address limitations of current NIGM methods, with high translation potential.
Finemap-MiXeR: A variational Bayesian approach for genetic finemapping
Authors: Akdeniz Bayram Cevdet , Frei Oleksandr , Shadrin Alexey , Vetrov Dmitry , Kropotov Dmitry , Hovig Eivind , Andreassen Ole A. , Dale Anders M.
Published: December 2022

Discoveries from genome-wide association studies often contain large clusters of highly correlated genetic variants, which makes them hard to interpret. In such cases, finemapping the underlying causal variants become important. Here we present a new method, the Finemap-MiXeR, based on a variational Bayesian approach for finemapping genomic data, i.e., determining the causal single nucleotide polymorphisms (SNPs) associated with a trait at a given locus after controlling for correlation among genetic variants due to linkage disequilibrium. Our approach is based on the optimization of Evidence Lower Bound of the likelihood function obtained from the MiXeR model. The optimization is done using Adaptive Moment Estimation Algorithm, allowing to obtain posterior probability of each SNP to be a causal variant. We tested Finemap-MiXeR in a range of different scenarios, using both synthetic and real data from the UK Biobank, using standing height phenotype as an example. In comparison to the existing finemapping methods FINEMAP and SuSiE methods, we observed that Finemap-MiXeR in most cases has better accuracy. Furthermore, it is computationally efficient, and unlike other methods the complexity is not increasing as the number of causal SNPs or the heritability increases. We show that our finemapping algorithm identifies a small number of genetic variants per locus which are informative for predicting the phenotype in an independent sample.
MC1R reduces scarring and rescues stalled healing in a preclinical chronic wound model
Authors: Nawilaijaroen Yonlada , Rocliffe Holly , Austin-Williams Shani , Krilis Georgios , Pellicoro Antonella , Zhou Kanheng , Ji Yubo , Bain Connor A , Kilpatrick Alastair M , Chen Yuhang , Biswas Asok , Crichton Michael , Huang Zhihong , Forbes Stuart J , Caporali Andrea , Cash Jenna L
Published: December 2022

Cutaneous healing results in scarring with significant functional and psychological sequelae, while chronic non-healing wounds represent repair failure often with devastating consequences, including amputation and death. Due to a lack of effective therapies, novel interventions addressing scarring and chronic wounds are urgently needed. Here, we demonstrate that harnessing melanocortin 1 receptor with a selective agonist (MC1R-Ag) confers multifaceted benefits to wound repair. MC1R-Ag accelerates wound closure and re-epithelialization while improving wound bed perfusion and lymphatic drainage by promoting angiogenesis and lymphangiogenesis. Concomitant reductions in oxidative stress, inflammation and scarring were also observed. To evaluate the therapeutic potential of targeting MC1R in pathological healing, we established a novel murine model that recapitulates the hallmarks of human non-healing wounds. This model combines advanced age and locally elevated oxidative stress. Remarkably, topical application of MC1R-Ag restored repair, whereas disrupting MC1R signalling exacerbated the chronic wound phenotype. Our study highlights MC1R agonism as a promising therapeutic approach for scarring and non-healing wound pathologies, and our chronic wound model as a valuable tool for elucidating ulcer development mechanisms.
Sexual conflict mitigation via sex-specific trait architecture
Authors: Kralj-Fišer Simona , Kuntner Matjaž , Debes Paul Vincent
Published: December 2022

Sexual dimorphism — the sex-specific trait expression — may emerge when selection favours different optima for the same trait between sexes, i.e., under antagonistic selection. Intra-locus sexual conflict exists when the sexually dimorphic trait under antagonistic selection is based on genes shared between sexes. A common assumption for sexual-size dimorphism (SSD) is that its presence indicates resolved sexual conflict, but how current sex-specific evolution proceeds under sexual dimorphism remains enigmatic. We investigated whether a sex-specific architecture of adult body size explains sexual conflict resolution under extreme SSD in the African hermit spider,Nephilingis cruentata, where adult female body size greatly exceeds that of males. Specifically, we estimated the sex-specific importance of genetic and maternal effects on adult body size among individuals that we laboratory-reared for up to eight generations. Quantitative genetic model estimates indicated that size variation in females is to a larger extent explained by direct genetic effects than by maternal effects, but in males to a larger extent by maternal than by genetic effects. We conclude that this sex-specific body-size architecture enables body-size evolution to proceed much more independently than under a common architecture to both sexes, thereby mitigating sexual conflict under SSD.
A deep learning approach for improving two-photon vascular imaging speeds
Authors: Zhou Annie , Mihelic Samuel A. , Engelmann Shaun A. , Tomar Alankrit , Dunn Andrew K. , Narasimhan Vagheesh M.
Published: December 2022

A potential method for tracking neurovascular disease progression over time in preclinical models is multiphoton fluorescence microscopy (MPM), which can image cerebral vasculature with capillary-level resolution. However, obtaining high-quality, three-dimensional images with a traditional point scanning MPM is time-consuming and limits sample sizes for chronic studies. Here, we present a convolutional neural network-based algorithm for fast upscaling of low-resolution or sparsely sampled images and combine it with a segmentation-less vectorization process for 3D reconstruction and statistical analysis of vascular network structure. In doing so, we also demonstrate that the use of semi-synthetic training data can replace the expensive and arduous process of acquiring low- and high-resolution training pairs without compromising vectorization outcomes, and thus open the possibility of utilizing such approaches for other MPM tasks where collecting training data is challenging. We applied our approach to large field of view images and show that our method generalizes across imaging depths, disease states and other differences in neurovasculature. Our pre-trained models and lightweight architecture can be used to reduce MPM imaging time by up to fourfold without any changes in underlying hardware, thereby enabling deployability across a range of settings.
TMvisDB: resource for transmembrane protein annotation and 3D visualization
Authors: Marquet Céline , Grekova Anastasia , Houri Leen , Bernhofer Michael , Jimenez-Soto Luisa F. , Karl Tim , Heinzinger Michael , Dallago Christian , Rost Burkhard
Published: December 2022

Since the rise of cellular organisms, transmembrane proteins (TMPs) have been crucial to a variety of cellular processes due to their central role as gates and gatekeepers. Despite their importance, experimental high-resolution structures for TMPs remain underrepresented due to technical limitations. With structure prediction methods coming of age, predictions might fill some of the need. However, identifying the membrane regions and topology in three-dimensional structure files requires additionalin silicoprediction. Here, we introduce TMvisDB to sieve through millions of predicted structures for TMPs. This resource enables both, to browse through 46 million predicted TMPs and to visualize those along with their topological annotations. The database was created by joining AlphaFold DB structure predictions and transmembrane topology predictions from the protein language model based method TMbed. We show the utility of TMvisDB for individual proteins through two single use cases, namely the B-lymphocyte antigen CD20 (Homo sapiens) and the cellulose synthase (Novosphingobium sp. P6W). To demonstrate the value for large scale analyses, we focus on all TMPs predicted for the human proteome. TMvisDB is freely available attmvis.predictprotein.org.
Flexible hidden Markov models for behaviour-dependent habitat selection
Authors: Klappstein NJ , Thomas L , Michelot T
Published: December 2022

There is strong incentive to model behaviour-dependent habitat selection, as this can help delineate critical habitats for important life processes and reduce bias in model parameters. For this purpose, a two-stage modelling approach is often taken: (i) classify behaviours with a hidden Markov model (HMM), and (ii) fit a step selection function (SSF) to each subset of data. However, this approach does not properly account for the uncertainty in behavioural classification, nor does it allow states to depend on habitat selection. An alternative approach is to estimate both state switching and habitat selection in a single, integrated model called an HMM-SSF. We build on this recent methodological work to make the HMM-SSF approach more efficient and general. We focus on writing the model as an HMM where the observation process is defined by an SSF, such that well-known inferential methods for HMMs can be used directly for parameter estimation and state classification. We extend the model to include covariates on the HMM transition probabilities, allowing for inferences into the temporal and individual-specific drivers of state switching. We demonstrate the method through an illustrative example of African zebra (Equus quagga), including state estimation, and simulations to estimate a utilisation distribution. In the zebra analysis, we identified two behavioural states, with clearly distinct patterns of movement and habitat selection (“encamped” and “exploratory”). In particular, although the zebra tended to prefer areas higher in grassland across both behavioural states, this selection was much stronger in the fast, directed exploratory state. We also found a clear diel cycle in behaviour, which indicated that zebras were more likely to be exploring in the morning and encamped in the evening. This method can be used to analyse behaviour-specific habitat selection in a wide range of species and systems. A large suite of statistical extensions and tools developed for HMMs and SSFs can be applied directly to this integrated model, making it a very versatile framework to jointly learn about animal behaviour, habitat selection, and space use.