bluuebunny/crossref_metadata_2025 huggingface dataset:
Symmetry of Nipple Position After Bilateral Nipple-Sparing Mastectomy and Implant-Based Reconstruction
Authors: Mercury Oblaise , Nores Gabriella Garcia , Carlson Grant W.
Published: June 2022

Purpose

Asymmetry of nipple position is common in the female population. There are scant data on the impact of bilateral nipple-sparing mastectomy (NSM) and immediate implant-based reconstruction on nipple asymmetry.

Methods

A retrospective review was performed of an institutional review board approved prospective database of NSM and immediate implant-based reconstruction was performed. BCCT.core software was used to examine preoperative and postoperative nipple asymmetry. It directly calculates the quantitative differences in nipple position between the breasts expressed as breast retraction assessment (BRA). Nipple to sternal notch (N-SN) asymmetry was calculated from the collected data.

Results

Sixty-eight patients undergoing bilateral NSM and implant reconstruction were reviewed. Reconstructive methods were tissue expander (TE) 39 (57.4%) and direct to implant (DTI) (prepectoral 13, submuscular 16) 29 (42.6%). The TE group had greater body mass index (BMI) (23.5 vs 22.1, P = 0.02), mastectomy weight (390.7 vs 243.8, P = 0.001) and higher preoperative N-SN asymmetry (TE 0.89 vs DTI 0.59, P = 0.02). Ten patients received radiation (TE group 4, DTI group 6). The TE group had larger implant size (479.1 vs 375.0, P = 0.0001). Overall, TE reconstruction resulted in an increase in nipple asymmetry (mean BRA: preoperative, 1.50 vs postoperative, 1.65), which was not significant. Direct to implant reconstruction increased nipple asymmetry: mean N-SN asymmetry preoperative 0.59 versus postoperative 0.97 (P = 0.04) and mean BRA scores 1.40 and 1.82 (P = 0.06). Both implant locations in the DTI group resulted in an increase in postoperative asymmetry but was significant for the prepectoral group: mean BRA preoperative 1.19 versus postoperative 1.85, P = 0.02 and mean N-SN asymmetry preoperative 0.48 vs postoperative 0.94, P = 0.04. Radiation impacted the final mean BRA score: radiation 2.24 versus no radiation 1.63 (P = 0.05).

Conclusions

Patients who underwent TE reconstruction had significantly larger breasts and greater preoperative N-SN asymmetry than the DTI group. Despite this, the TE group resulted in mild increase in nipple asymmetry. Both implant locations in DTI reconstruction resulted in increased postoperative asymmetry but was significant for the prepectoral group. Radiation therapy has a significant impact of nipple asymmetry.
The Impact of Preoperative Breast Volume on Development of Mastectomy Skin Flap Necrosis in Immediate Breast Reconstruction
Authors: Andersen Emily S. , Weintraub Collin , Reuter Muñoz Katherine D. , Wolfe Luke G. , Shah Priti , Chandora Agni , Powers Jeremy M. , McGuire Kandace P. , Luppens Daniel P.
Published: June 2022

Background

Mastectomy skin flap necrosis (MSFN) can significantly impact outcome after immediate breast reconstruction. Several techniques exist to predict MSFN, but these may require additional testing and information, and they are often not available before surgery. We aim to identify whether breast volume, as calculated from preoperative mammography, can be used as a preoperative predictor of MSFN.

Methods

A retrospective chart review from 2010 to 2020 resulted in 378 patients who underwent immediate implant-based breast reconstruction. Complete imaging data were available for 278 patients and 441 reconstructed breasts. Demographic, perioperative, and outcomes data were collected. Measurements from preoperative diagnostic mammograms were used to calculate breast volume. Univariate and multivariate analyses were used to evaluate the association of variables available preoperatively, including breast volume from mammogram and MSFN. Secondary analyses were performed for need for reoperation and loss of reconstruction.

Results

On univariate analysis of MSFN development, demographic variables found to be significantly associated with MSFN included body mass index (P = 0.04), diabetes (P = 0.03), and breast volume calculated from routine mammography (P ≤ 0.0001). Average preoperative breast volume via mammography without and with MSFN was 970.6 mL (95% confidence interval [CI], 908.9–1032.3) and 1298.3 mL (95% CI, 1140.0–1456.5) (P < 0.0001), respectively. Statistically significant intraoperative variables for MSFN development included prolonged operative time (P = 0.005), greater initial tissue expander fill volumes (P ≤ 0.001), and prepectoral implant location (P = 0.02). Higher initial tissue expander fill volumes in implant-based reconstructions were associated with increased rates of MSFN, 264.1 mL (95% CI, 247.2–281.0) without MSFN and 349.9 mL (95% CI, 302.0–397.8) in the group with MSFN, respectively (P < 0.001). On multivariate analysis, preoperative imaging volume (P = 0.02) was found to be significant, whereas body mass index and diabetes lost significance (P = 0.40) in association with MSFN.

Conclusions

The results of this study establish an association between larger breast volume on preoperative imaging and development of MSFN. This may be useful as a tool for more appropriate patient selection and guidance in the setting of immediate breast reconstruction.
Teachers
Authors: Lineaweaver William C.
Published: June 2022

Examples of influential teachings are drawn from the 6 decades of a single surgeon’s education.
The Safety of Fat Grafting: An Institutional Retrospective Review
Authors: Fang Hua Amanda , Soto Edgar , Pigg Ricky , Smith Metta , Boyd Carter J. , Ananthasekar Shivani , Fix R. Jobe , Kilic Ali , Denney Brad , Patcha Prasanth , Myers René P. , de la Torre Jorge I. , Collawn Sherry
Published: June 2022

Background

Autologous fat grafting is a popular technique for volume replacement in the breast and face. The efficacy, safety, and complication rate of this technique at the division of plastic surgery at the University of Alabama at Birmingham will be described in this review.

Methods

An institutional review board–approved retrospective review of patients undergoing fat grafting procedures from January 2015 to July 2018 was performed. Records were reviewed for fat graft recipient site, donor site, amount grafted, and complications. Continuous variables were compared using either a t test or one-way analysis of variance test. Categorical data were compared using χ2 test. A P value of 0.05 or less was considered statistically significant for all comparisons.

Results

A total of 396 patients who underwent fat grafting procedures of the face and body from January 2015 through July 2018 met inclusion criteria. Average amount of fat grafted for all grafts was 124.4 +/− 6.74 grams. Two hundred fifty of the grafts (62.7%) involved the bilateral breasts with an average of 140.6 +/− 93.97 g used, 70 per side. Of the 396 patients, 110 (27.8%) experienced complications. Forty three of the complications (10.9%) were considered to be major, which included hematomas/seromas, fat necrosis, dermatitis/cellulitis, and infection. No statistical differences were seen among recipient site complication rate. Types of minor complications were statistically significant per recipient sites with bilateral breasts more likely to experience asymmetry than the other recipient sites (20% for bilateral breasts vs 16% overall, P < 0.05). Fifty nine of the 110 patients (53.6%) had the complications reported to be resolved.

Conclusions

Fat grafting is a reliable method for volumization of the breasts and face. Minor complications were not infrequent in this case series; however, no life-threatening complications were observed. Continued work needs to be done to use fat grafting beyond traditional measures.
Usefulness of Interposition Arteriovenous Bundle Grafts in Free Flap Surgery
Authors: Kim Jisu , Lee Kyeong-Tae
Published: June 2022

Background

The paucity of reliable recipient vessels adjacent to defects poses a great challenge in free flap reconstruction. Although the use of interposition vein grafts to cover the vascular gap is common, its potential association with higher risks of flap compromise is often reported. Interposition arteriovenous bundle grafts have been introduced as an alternative. This study aimed to evaluate the outcomes of free tissue transfer using interposition arteriovenous bundle grafts and to conduct a systematic review of studies that reported the use of the technique.

Methods

Patients who underwent free tissue transfer using the interposition arteriovenous bundle graft technique were assessed for flap perfusion-related complications. A systematic review of literature was performed using pooled analysis to calculate the rate of perfusion-related complications.

Results

Overall, 14 cases of free flap reconstruction used the interposition arteriovenous bundle graft technique to cover vascular gaps in diverse regions. The most common donor vessel of this graft was the descending branch of the lateral circumflex femoral vessels (mean length, 6.9 cm). All flaps survived except for 1 case of partial flap loss, showing a flap compromise rate of 7.1%. A systematic review identified 13 studies that represented 78 cases using this technique. In the pooled analysis, including the current series, the overall flap survival rate was 95.7%, reporting 4 of 92 cases of flap compromise.

Conclusions

The interposition arteriovenous bundle graft technique may help overcome the challenges of pedicle shortage or lack of adjacent recipient vessels in free flap reconstruction.
Synchronous Telemedicine Model in Urogynecology: Are Patients Willing to Continue Telemedicine in the Post–COVID-19 Pandemic Era?
Authors: Kim Youngwu , Ortega Marcus V. , Acker Rachael , Valentine Kathrene D. , Ayati Elnaz , Von Bargen Emily
Published: June 2022

Importance

Following the recent expansion of telemedicine during the COVID-19 pandemic, this remote model of care in female pelvic medicine and reconstructive surgery will likely remain and continue to evolve.

Objective

This study was conducted to assess patients’ perceptions of and willingness to participate in a synchronous telemedicine visit beyond the COVID-19 pandemic for women with pelvic floor disorders.

Study Design

We conducted a cross-sectional study of women who completed a synchronous telemedicine visit from March 16 through May 22, 2020, at a urogynecology practice in an academic medical center. An electronic survey was distributed to women after all telemedicine visits. Demographic data, visit type, and survey responses were analyzed.

Results

Two hundred two women received the survey, and 135 women completed it (response rate of 66.8%). The mean age of the respondents was 62.9 ± 16.4 years, and the 3 most common visit diagnoses were overactive bladder (43.7%), stress urinary incontinence (22.2%), and pelvic organ prolapse (21.4%). Most survey participants (88.9%) found that the quality of their telemedicine visits was better than expected, and 89.6% reported that they would like to continue telemedicine care. Our survey showed that 19.4% of women reported difficulty with technology.

Conclusions

We found that most women presenting for synchronous telemedicine urogynecology care had a positive visit experience and would continue to use telemedicine for their care. Further developmental work needs to be done on improving the ease of technology as well as availability of telemedicine in the care of women affected by pelvic floor disorders.
Rheology of particulate suspensions with non-Newtonian fluids in capillaries
Authors: Xia Bin , Krueger Paul S.
Published: June 2022

Particulate suspensions occur in situations from blood flow to slurries in drilling applications. Existing investigations of these suspensions generally concentrate on the impact of particle volume fraction for suspensions in Newtonian fluids under free-flow conditions. Recently, particulate-polymer composites have been used in additive manufacturing (AM). Here, the polymer becomes a shear-thinning non-Newtonian fluid during extrusion, creating a particulate suspension. Motivated by the challenges in AM of particulate composites, this study investigates the rheology of suspensions of micrometre-sized particles in shear-thinning silicone while extruded through AM-scaled nozzles (millimetre-scale diameters). The suspensions were observed to follow a power-law behaviour and their rheology was investigated through the measured flow consistency (

K

) and behaviour (

n

) indices. The impact of the particle volume fraction (

ϕ

) and the ratio (

ω

) of the capillary inside diameter to the particle diameter on both indices were measured.

n

was found to be only impacted by the suspension fluid type and

ϕ

.

K

was found to be constant at large

ω

, but decreased and then increased to infinity with

ω

decreasing. Based on its behaviour,

K

was categorized into two conditions and analysed separately with semi-empirical models. The impact of particle size distribution was also investigated.
Avoiding critical thresholds through effective monitoring
Authors: Stier Adrian C. , Essington Timothy E. , Samhouri Jameal F. , Siple Margaret C. , Halpern Benjamin S. , White Crow , Lynham John M. , Salomon Anne K. , Levin Phillip S.
Published: June 2022

A major challenge in sustainability science is identifying targets that maximize ecosystem benefits to humanity while minimizing the risk of crossing critical system thresholds. One critical threshold is the biomass at which populations become so depleted that their population growth rates become negative—depensation. Here, we evaluate how the value of monitoring information increases as a natural resource spends more time near the critical threshold. This benefit emerges because higher monitoring precision promotes higher yield and a greater capacity to recover from overharvest. We show that precautionary buffers that trigger increased monitoring precision as resource levels decline may offer a way to minimize monitoring costs and maximize profits. In a world of finite resources, improving our understanding of the trade-off between precision in estimates of population status and the costs of mismanagement will benefit stakeholders that shoulder the burden of these economic and social costs.
Rhodococcus oxybenzonivorans sp. nov., a benzophenone-3-degrading bacterium, isolated from stream sediment
Authors: Baek Ju Hye , Baek Woonhee , Jeong Sang Eun , Lee Sung Chul , Jin Hyun Mi , Jeon Che Ok
Published: June 2022

A Gram-stain-positive, facultative aerobic, oxidase-negative, catalase-positive, non-sporulating, and non-motile bacterium, which degraded benzophenone-3, was isolated from stream sediment collected in the Republic of Korea and designated as strain S2-17T. Cells of this strain were rod-shaped during the early growth phase but became coccoid after the late exponential growth phase. Bacterial growth was observed at 15–37 °C (optimum, 25–30 °C) and pH 6.0–9.5 (optimum, pH 7.5–8.5) and in the presence of 0–9.0 % (w/v) NaCl (optimum, 0–1.0 %). Menaquinone-8 (H2) was the sole isoprenoid quinone, and C16 : 0, C17 : 1 ω8c, summed feature 3 (comprising C16 : 1 ω7c/C16 : 1 ω6c) and C18 : 1 ω9cwere the major fatty acids. The cell wall of strain S2-17Tcontainedmeso-diaminopimelic acid, and arabinose, galactose and mycolic acid were found in whole-cell hydrolysates, suggesting a chemotype IV cell wall. The G+C content of the genome was 65.6 mol%. Phylogenetic analyses revealed that strain S2-17Tformed a phyletic lineage within the genusRhodococcusand was most closely related toRhodococcus jostiiDSM 44719T(99.2 % 16S rRNA gene sequence similarity). Average nucleotide identity and digital DNA–DNA hybridization values between strain S2-17TandR. jostiiDSM 44719Twere 82.6 and 26.5 %, respectively, indicating differences between the species. Based on its phenotypic, chemotaxonomic and molecular features, strain S2-17Trepresents a novel species of the genusRhodococcus, for which the nameRhodococcus oxybenzonivoranssp. nov. is proposed. The type strain is S2-17T(=KACC 19281T=JCM 32046T).
Pharmacological determination of the fractional block of Nav channels required to impair neuronal excitability and ex vivo seizures
Authors: Thouta Samrat , Waldbrook Matthew G. , Lin Sophia , Mahadevan Arjun , Mezeyova Jannette , Soriano Maegan , Goodchild Samuel J. , Parrish R. Ryley
Published: June 2022

Voltage-gated sodium channels (Nav) are essential for the initiation and propagation of action potentials in neurons. Of the different channel subtypes, Nav1.1, Nav1.2 and Nav1.6 are prominently expressed in the adult central nervous system (CNS). All three of these sodium channel subtypes are sensitive to block by the neurotoxin tetrodotoxin (TTX), with TTX being almost equipotent on all three subtypes. In the present study we have used TTX to determine the fractional block of Nav channels required to impair action potential firing in pyramidal neurons and reduce network seizure-like activity.

Using automated patch-clamp electrophysiology, we first determined the IC50s of TTX on mouse Nav1.1, Nav1.2 and Nav1.6 channels expressed in HEK cells, demonstrating this to be consistent with previously published data on human Nav channels. We then compared this data to the potency of block of Nav current measured in pyramidal neurons from neocortical brain slices. Interestingly, we found that it requires nearly 10-fold greater concentration of TTX over the IC50 to induce significant block of action potentials using a current-step protocol. In contrast, concentrations near the IC50 resulted in a significant reduction in AP firing and increase in rheobase using a ramp protocol. Surprisingly, a 20% reduction in action potential generation observed with 3 nM TTX resulted in significant block of seizure-like activity in the 0 Mg2+ model of epilepsy. Additionally, we found that approximately 50% block in pyramidal cell intrinsic excitability is sufficient to completely block all seizure-like events. These data serve as a critical starting point in understanding how fractional block of Nav channels affect intrinsic neuronal excitability and seizure-like activity. It further suggests that seizures can be controlled without significantly compromising intrinsic neuronal activity and determines the required fold over IC50 for novel and clinically relevant Nav channel blockers to produce efficacy and limit side effects.
Virtual Liver Needle Biopsy from Reconstructed Three-Dimensional Histopathological Images: Quantification of Sampling Error
Authors: Li Qiang , Wang Fusheng , Chen Yaobing , Chen Hao , Wu Shengdi , Farris Alton B. , Jiang Yi , Kong Jun
Published: June 2022

Introduction

Prevalently considered as the “gold-standard” for diagnosis of hepatic fibrosis and cirrhosis, the clinical liver needle biopsy is known to be subject to inadequate sampling and a high mis-sampling rate. However, quantifying such sampling bias has been difficult as generating a large number of needle biopsies from the same living patient is practically infeasible. We construct a three-dimension (3D) virtual liver tissue volume by spatially registered high resolution Whole Slide Images (WSIs) of serial liver tissue sections with a novel dynamic registration method. We further develop a Virtual Needle Biopsy Sampling (VNBS) method that mimics the needle biopsy sampling process. We apply the VNBS method to the reconstructed digital liver volume at different tissue locations and angles. Additionally, we quantify Collagen Proportionate Area (CPA) in all resulting virtual needle biopsies in 2D and 3D.

Results

The staging score of the center 2D longitudinal image plane from each 3D biopsy is used as the biopsy staging score, and the highest staging score of all sampled needle biopsies is the diagnostic staging score. The Mean Absolute Difference (MAD) in reference to the Scheuer and Ishak diagnostic staging scores are 0.22 and 1.00, respectively. The absolute Scheuer staging score difference in 22.22% of sampled biopsies is 1. By the Ishak staging method, 55.56% and 22.22% of sampled biopsies present score difference 1 and 2, respectively. There are 4 (Scheuer) and 6 (Ishak) out of 18 3D virtual needle biopsies with intra-needle variations. Additionally, we find a positive correlation between CPA and fibrosis stages by Scheuer but not Ishak method. Overall, CPA measures suffer large intra- and inter-needle variations.

Conclusions

The developed virtual liver needle biopsy sampling pipeline provides a computational avenue for investigating needle biopsy sampling bias with 3D virtual tissue volumes. This method can be applied to other tissue-based disease diagnoses where the needle biopsy sampling bias substantially affects the diagnostic results.
Metagenomics of Parkinson’s disease implicates the gut microbiome in multiple disease mechanisms
Authors: Wallen Zachary D , Demirkan Ayse , Twa Guy , Cohen Gwendolyn , Dean Marissa N , Standaert David G , Sampson Timothy , Payami Haydeh
Published: June 2022

Parkinson’s disease (PD) may start in the gut and spread to the brain. To investigate the role of gut microbiome, we enrolled 490 PD and 234 control individuals, conducted deep shotgun sequencing of fecal DNA, followed by metagenome-wide association studies requiring significance by two methods (ANCOM-BC and MaAsLin2) to declare disease association. Thirty-percent of species and pathways tested had altered abundances in PD, depicting a widespread dysbiosis. Network analysis showed PD-associated species form polymicrobial clusters that grow or shrink together, and some compete. Metagenomic profile of PD indicates a disease permissive microbiome, evidenced by overabundance of pathogens and immunogenic components, dysregulated neuroactive signaling, preponderance of molecules that induce alpha-synuclein pathology, and over-production of toxicants; with the reduction in anti-inflammatory and neuroprotective factors limiting the capacity to recover. These data provide a broad foundation with a wealth of concrete testable hypotheses to discern the role of the gut microbiome in PD.
Human iPSC-CMs and in-silico technologies define mechanisms and accelerate targeted pharmacogenetics in hypertrophic cardiomyopathy
Authors: Margara Francesca , Psaras Yiangos , Wang Zhinuo Jenny , Schmid Manuel , Doste Ruben , Garfinkel Amanda , Repetti Giuliana G. , Seidman Jonathan , Seidman Christine , Rodriguez Blanca , Toepfer Christopher N. , Bueno-Orovio Alfonso
Published: June 2022

Cardiomyopathies have unresolved genotype-phenotype relationships and lack disease-specific treatments. Here we identify genotype-specific pathomechanisms and therapeutic targets combining experimental hiPSC-CM modelling and human-based cardiac electromechanical in-silico modelling and simulation bridging from specific mutations to clinical biomarkers. We select hypertrophic cardiomyopathy as a challenge for this approach and study genetic variations that mutate proteins of the thick (MYH7R403Q/+) and thin filaments (TNNT2R92Q/+,TNNI3R21C/+) of the cardiac sarcomere. We show that destabilisation of myosin super relaxation drives disease inMYH7R403Q/+with secondary effects on thin filament activation, which are corrected by Mavacamten. Thin filament variantsTNNT2R92Q/+andTNNI3R21C/+share calcium regulation-related pathomechanisms, for which Mavacamten provides incomplete salvage. We define the ideal characteristics of a novel thin filament-targeting compound and show its efficacy in-silico. We demonstrate that hybrid human-based hiPSC-CM and in-silico studies accelerate pathomechanism discovery and classification testing, improving clinical interpretation of genetic variants, and directing rational therapeutic targeting and design.
An Internal Model of Sensorimotor Context in Freely Swimming Electric Fish
Authors: Wallach Avner , Sawtell Nathaniel B.
Published: June 2022

Nervous systems are hypothesized to learn and store internal models that predict the sensory consequences of motor actions. However, little is known about the neural mechanisms for generating accurate predictions under real-world conditions in which the sensory consequences of action depend on environmental context. Using novel methods for underwater neural recording in freely swimming electric fish, we demonstrate that complex movement-related input to the active electrosensory system is effectively cancelled, despite being highly-dependent on the nearby environment. Computational modeling and closed-loop electrophysiological experiments indicate that the cerebellum-like circuitry of the electrosensory lobe generates context-specific predictions of self-generated input by combining motor signals with electrosensory feedback. These results provide mechanistic insight into sophisticated internal models supporting natural behavior in freely moving animals.

One-Sentence Summary

Underwater recordings in electric fish reveal neural mechanisms for predicting the sensory consequences of behavior under natural conditions in freely moving animals.
Whole-brain dynamical modeling for classification of Parkinson’s disease
Authors: Jung Kyesam , Florin Esther , Patil Kaustubh R. , Caspers Julian , Rubbert Christian , Eickhoff Simon B. , Popovych Oleksandr V.
Published: June 2022

Simulated whole-brain connectomes demonstrate an enhanced inter-individual variability depending on data processing and modeling approach. By considering the human brain connectome as an individualized attribute, we investigate how empirical and simulated whole-brain connectome-derived features can be utilized to classify patients with Parkinson’s disease against healthy controls in light of varying data processing and model validation. To this end, we applied simulated blood oxygenation level-dependent signals derived by a whole-brain dynamical model simulating electrical signals of neuronal populations to reveal differences between patients and controls. In addition to the widely used model validation via fitting the dynamical model to empirical neuroimaging data, we invented a model validation against behavioral data, such as subject classes, which we refer to as behavioral model fitting and show that it can be beneficial for Parkinsonian patient classification. Furthermore, the results of machine-learning reported in this study also demonstrated that performance of the patient classification can be improved when the empirical data are complemented by the simulation results. We also showed that temporal filtering of blood oxygenation level-dependent signals influences the prediction results, where the filtering in the low-frequency band is advisable for Parkinsonian patient classification. In addition, composing the feature space of empirical and simulated data from multiple brain parcellation schemes provided complementary features that improve prediction performance. Based on our findings, we suggest including the simulation results with empirical data is effective for inter-individual research and its clinical application.
Enhancing associative learning in rats with a computationally designed training protocol
Authors: Zhang Xu O. , Zhang Yili , Cho Claire E. , Engelke Douglas S. , Smolen Paul , Byrne John H , Do-Monte Fabricio H.
Published: June 2022

Background

Learning requires the activation of protein kinases with distinct temporal dynamics. InAplysia,nonassociative learning can be enhanced by a computationally designed learning protocol with intertrial intervals (ITIs) that maximize the interaction between fast-activated protein kinase A (PKA) and slow-activated extracellular signal-regulated kinase (ERK). Whether a similar strategy can enhance associative learning in mammals is unknown.

Methods

We simulated 1,000 training protocols with varying ITIs to predict an optimal protocol based on empirical data for PKA and ERK dynamics in rat hippocampus. Adult male rats received the optimal protocol or control protocols in auditory fear conditioning and fear extinction experiments. Immunohistochemistry was performed to evaluate phosphorylated cAMP responsive element binding (pCREB) protein levels in brain regions implicated in fear acquisition.

Results

Rats exposed to the optimal conditioning protocol with irregular ITIs exhibited impaired extinction memory acquisition within the session using a standard footshock intensity, and stronger fear memory retrieval and spontaneous recovery with a weaker footshock intensity, compared to rats that received massed or spaced conditioning protocols with fixed ITIs. Rats exposed to the optimal extinction protocol displayed improved extinction of contextual fear memory and reduced spontaneous recovery compared to rats that received standard extinction protocols. Moreover, the optimal conditioning protocol increased pCREB levels in the dentate gyrus (DG) of the dorsal hippocampus, suggesting enhanced induction of long-term potentiation.

Conclusion

These findings demonstrate that a computational model-driven behavioral intervention can enhance associative learning in mammals, and may provide insight into strategies to improve cognition in humans.
An integrative web-based software tool for multi-dimensional pathology whole-slide image analytics
Authors: Shen Alice , Wang Fusheng , Paul Saptarshi , Bhuvanapalli Divya , Alayof Jacob , Farris Alton B. , Teodoro George , Brat Daniel J. , Kong Jun
Published: June 2022

In the era of precision medicine, human tumor atlas oriented studies have been significantly facilitated by high-resolution, multi-modal tissue based microscopic pathology image analytics. To better support such tissue-based investigations, we develop Digital Pathology Laboratory (DPLab), a publicly available web-based platform, to assist biomedical research groups, non-technical end users, and clinicians for pathology Whole-Slide Image (WSI) visualization, annotation, analysis, and sharing via web browsers. A major advance of this work is the easy-to-follow methods to reconstruct three-dimension (3D) tissue image volumes by registering two-dimension (2D) whole-slide pathology images of serial tissue sections stained by hematoxylin and eosin (H&E), and immunohistochemistry (IHC). The integration of these serial slides stained by different methods provides cellular phenotype and pathophysiologic states in the context of a 3D tissue micro-environment. DPLab is hosted on a publicly accessible server and connected to a backend computational cluster for intensive image analysis computations, with results visualized, downloaded, and shared via a web interface. Equipped with an analysis toolbox of numerous image processing algorithms, DPLab supports continued integration of community-contributed algorithms and presents an effective solution to improve the accessibility and dissemination of image analysis algorithms by research communities. It represents the first step in making next generation tissue investigation tools widely available to the research community, enabling and facilitating discovery of clinically relevant disease mechanisms in a digital 3D tissue space.
Characterization of TGFβ-induced tendon-like structure in scaffold-free three-dimensional tendon cell culture
Authors: Koo Bon-hyeock , Lee Yeon-Ju , Park Na Rae , Heo Su-Jin , Hudson David M. , Fernandes Aysel A. , Friday Chet S. , Hast Michael W. , Corr David T. , Keene Douglas R. , Tufa Sara F. , Dyment Nathaniel A. , Joeng Kyu Sang
Published: June 2022

Tendons transmit mechanical forces between muscle and bone. Their biomechanical function requires high tensile strength provided by highly organized collagen fibers. Tenocytes mainly drive tendon growth via extracellular matrix (ECM) production and organization. The biological mechanisms regulating tenocyte differentiation and morphological maturation have not been well-established, partly due to the lack of reliablein vitrosystems that produce highly aligned collagenous tissues. In this study, we developed a scaffold-free, three-dimensional (3D) tendon culture system using mouse tendon cells and a differentially adherent growth channel. TGFβ treatment promoted tendon-like structure in the peripheral layer of the constructs with decreased cell density, decreased cell proliferation, increased thickness, and more elongated cells within highly aligned extracellular matrix. The constructs were used to understand the function of TGFβ signaling in tenogenic differentiation, collagen fibrillogenesis, and biomechanical properties. This scaffold-free 3D constructs system can serve as a reliablein vitrosystem to study underlying biological mechanisms that regulate cellular and matrix maturation in tendon development and growth.
Multi-objective Bayesian Optimization with Heuristic Objectives for Biomedical and Molecular Data Analysis Workflows
Authors: Selega Alina , Campbell Kieran R.
Published: June 2022

Many practical applications require optimization of multiple, computationally expensive, and possibly competing objectives that are well-suited for multi-objective Bayesian optimization (MOBO) procedures. However, for many types of biomedical data, measures of data analysis workflow success are often heuristic and therefore it is not known a priori which objectives are useful. Thus, MOBO methods that return the full Pareto front may be suboptimal in these cases. Here we propose a novel MOBO method that adaptively updates the scalarization function using properties of the posterior of a multi-output Gaussian process surrogate function. This approach selects useful objectives based on a flexible set of desirable criteria, allowing the functional form of each objective to guide optimization. We demonstrate the qualitative behaviour of our method on toy data and perform proof-of-concept analyses of single-cell RNA sequencing and highly multiplexed imaging datasets.
omicsGAT: Graph Attention Network for Cancer Subtype Analyses
Authors: Baul Sudipto , Ahmed Khandakar Tanvir , Filipek Joseph , Zhang Wei
Published: June 2022

Motivation

The use of high-throughput omics technologies is becoming increasingly popular in all facets of biomedical science. The mRNA sequencing (RNA-seq) method reports quantitative measures of more than tens of thousands of biological features. It provides a more comprehensive molecular perspective of studied cancer mechanisms compared to traditional approaches. Graph-based learning models have been proposed to learn important hidden representations from gene expression data and network structure to improve cancer outcome prediction, patient stratification, and cell clustering. However, these graph-based methods cannot rank the importance of the different neighbors for a particular sample in the downstream cancer subtype analyses. In this study, we introduce omicsGAT, a graph attention network (GAT) model to integrate graph-based learning with an attention mechanism for RNA-seq data analysis. The multi-head attention mechanism in omicsGAT can more effectively secure information of a particular sample by assigning different attention coefficients to its neighbors.

Results

Comprehensive experiments on The Cancer Genome Atlas (TCGA) breast cancer and bladder cancer bulk RNA-seq data, and primary diffuse gliomas single-cell RNA-seq data validate that (1) the proposed model can effectively integrate neighborhood information of a sample and learn an embedding vector to improve disease phenotype prediction, cancer patient stratification, and cell clustering of the sample. (2) The attention matrix generated from the multi-head attention coefficients provides more useful information compared to the sample correlation-based adjacency matrix. From the results, we can conclude that some neighbors play a more important role than others in cancer subtype analyses of a particular sample based on the attention coefficient.

Availability and implementation

Source code is available at: https://github.com/CompbioLabUCF/omicsGAT

Supplementary information

Supplementary data are available at BioRxiv online.
Inter-brain coupling analysis reveals learning-related attention of primary school students
Authors: Chen Jingjing , Xu Bing , Zhang Dan
Published: June 2022

Learning-related attention is one of the most important factors influencing learning. While technologies have enabled the automatic detection of students’ attention levels, previous studies mainly focused on colleges or high schools, lacking further validations in primary school students. More importantly, the detected attention might fail to be learning-related if students did not attend learning tasks (e.g., the attention level of a student who reads comics secretly during classroom learning). This phenomenon poses challenges to the practical application of automatic attention detection, especially in the primary school stage, which is crucial for students to set up learning attitudes/strategies. Inspired by the emerging inter-person perspective in neuroscience, we proposed an inter-brain attention coupling method to detect learning-related attention as an extension to the existing single-person-based method. To test this method, wearable electroencephalogram (EEG) devices were used to monitor students’ attention levels in a class of primary school students during classroom learning. We found that one’s inter-brain attention coupling, defined as the degree to which an individual student’s attention dynamics match the attention dynamics averaged across classmates, was positively correlated with academic performance: higher performances are associated with higher coupling to the class-average attention dynamics. Moreover, the attention detection framework based on the inter-person perspective outperforms as an indicator of academic performance compared with the widely-used attention level within an individual. The results provide practical insights by extending the applications of detected attention levels from an inter-person perspective and demonstrating its feasibility in monitoring learning-related attention among primary school students.
Modelling the metabolic consequences of antimicrobial exposure
Authors: Alonso-Vásquez Tania , Riccardi Christopher , Passeri Iacopo , Fondi Marco
Published: June 2022

Besides genetic mutations, the metabolic state of bacterial cells represents another driving factor in the emergence of antimicrobial resistance and in the actual efficacy of treatments. In this direction, studying how bacteria reprogram their metabolism when facing antimicrobial exposure is crucial to enhance our ability to limit the development and spread of antibiotic resistance. Here we have studied the metabolic consequences of antimicrobial exposure in bacteria using an integrated approach that exploits transcriptomics and computational modelling. Specifically, we asked whether common metabolic strategies emerge during the exposure to antimicrobials, regardless of the kind of antimicrobial used or, on the contrary, antimicrobial-specific pathways exist. To this purpose, we have used an heterogeneous dataset from six published studies on Escherichia coli exposed to different concentrations/types of compounds. We show that experimental condition, not antimicrobial exposure, is the factor that influences the most the resulting metabolic networks. However, despite condition-dependent metabolic signatures being evident, specific changes in flux distributions by antimicrobial exposed cells could be identified. In particular, purine and pyrimidine biosynthesis, and cofactor and prosthetic group biosynthesis were commonly affected by all considered antimicrobials. This suggests the presence of general metabolic strategies to face the stress posed by antimicrobial exposure and that, in turn, may represent an untapped resource for the fight against microbial infections. Finally, our analysis predicted an overall metabolic rewiring following bacteriostatic vs. bactericidal drug exposure that is in line with the current knowledge about the effects of these two classes of compounds on microbial metabolic phenotypes.

IMPORTANCE

A mechanistic understanding of microbial metabolic reprogramming during antimicrobial exposure is key to facilitate the discovery of new resistance mechanisms and to identify novel areas of intervention to face microbial infections. This study shows how the integration of transcriptomic data and genome-scale metabolic modelling can be used to address this critical issue, and to trace general metabolic strategies exploited by bacteria to face the stress posed by antimicrobial drugs.
Detecting sources of immune activation and viral rebound in HIV infection
Authors: Wietgrefe Stephen W. , Duan Lijie , Anderson Jodi , Marqués Guillermo , Sanders Mark , Cummins Nathan W. , Badley Andrew D. , Dobrowolski Curtis , Karn Jonathan , Pagliuzza Amélie , Chomont Nicolas , Sannier Gérémy , Dubé Mathieu , Kaufmann Daniel E. , Zuck Paul , Wu Guoxin , Howell Bonnie J , Reilly Cavan , Herschhorn Alon , Schacker Timothy W. , Haase Ashley T.
Published: June 2022

Antiretroviral therapy (ART) generally suppresses HIV replication to undetectable levels in peripheral blood, but immune activation associated with increased morbidity and mortality is sustained during ART, and infection rebounds when treatment is interrupted. To identify drivers of immune activation and potential sources of viral rebound, we modified RNAscope in situ hybridization to visualize HIV-virus producing cells as a standard to compare the following assays of potential sources of immune activation and virus rebound following treatment interruption: 1) EDITS (envelope detection by induced transcription-based sequencing) assay; 2) HIV-Flow; and 3) Flow-FISH assays that can scan tissues and cell suspensions to detect rare cells expressing env mRNA, gag mRNA/Gag protein and p24 respectively; and 4) an ultrasensitive immunoassay that detects p24 in cell/tissue lysates at subfemtomolar levels. We show that the sensitivity of these assays is sufficient to detect a rare HIV-producing/env mRNA+/p24+ cell in a million uninfected cells. These high-throughput technologies thus provide contemporary tools to detect and characterize rare cells producing virus and viral antigens as potential sources of immune activation and viral rebound.

Importance

Anti-retroviral therapy (ART) has greatly improved the quality and length of life for people living with HIV, but immune activation does not normalize during ART, and persistent immune activation has been linked to increased morbidity and mortality. We report a comparison of assays of two potential sources of immune activation during ART: rare cells producing HIV virus or the virus’ major viral protein, p24, benchmarked on a cell model of active and latent infections and a method to visualize HIV-producing cells. We show that assays of HIV Envelope mRNA (EDITS assay) and gag mRNA and p24 (Flow-FISH, HIV-Flow and ultrasensitive p24 immunoassay) detect HIV-producing cells and p24 at sensitivities of one infected cell in a million uninfected cells, thus providing validated tools to explore sources of immune activation during ART in the lymphoid and other tissue reservoirs.
TMS-Evoked Responses Are Driven by Recurrent Large-Scale Network Dynamics
Authors: Momi Davide , Wang Zheng , Griffiths John David
Published: June 2022

Abstract

A major question in systems and cognitive neuroscience is to what extent neurostimulation responses are driven by recurrent activity. This question finds sharp relief in the case of TMS-EEG evoked potentials (TEPs). TEPs are spatiotemporal waveform patterns with characteristic inflections at ∼50ms, ∼100ms, and ∼150-200ms following a single TMS pulse that disperse from, and later reconverge to, the primary stimulated regions. What parts of the TEP are due to recurrent activity? And what light might this shed on more general principles of brain organization? We studied this using source-localized TMS-EEG analyses and whole-brain connectome-based computational modelling. Results indicated that recurrent network feedback begins to drive TEP responses from ∼100ms post-stimulation, with earlier TEP components being attributable to local reverberatory activity within the stimulated region. Subject-specific estimation of neurophysiological parameters additionally indicated an important role for inhibitory GABAergic neural populations in scaling cortical excitability levels, as reflected in TEP waveform characteristics.
Modeling and Inference Methods for Switching Regime-Dependent Dynamical Systems with Multiscale Neural Observations
Authors: Song Christian Y , Hsieh Han-Lin , Pesaran Bijan , Shanechi Maryam M
Published: June 2022

Realizing neurotechnologies that enable long-term neural recordings across multiple spatial-temporal scales during naturalistic behaviors requires new modeling and inference methods that can simultaneously address two challenges. First, the methods should aggregate information across all activity scales from multiple recording sources such as spiking and field potentials. Second, the methods should detect changes in the regimes of behavior and/or neural dynamics during naturalistic scenarios and long-term recordings. Prior regime detection methods are developed for a single scale of activity rather than multiscale activity, and prior multiscale methods have not considered regime switching and are for stationary cases. Here, we address both challenges by developing a Switching Multiscale Dynamical System model and the associated filtering and smoothing methods. This model describes the encoding of an unobserved brain state in multiscale spike-field activity. It also allows for regime-switching dynamics using an unobserved regime state that dictates the dynamical and encoding parameters at every time-step. We also design the associated switching multiscale inference methods that estimate both the unobserved regime and brain states from simultaneous spike-field activity. We validate the methods in both extensive numerical simulations and prefrontal spike-field data recorded in a monkey performing saccades for fluid rewards. We show that these methods can successfully combine the spiking and field potential observations to simultaneously track the regime and brain states accurately. Doing so, these methods lead to better state estimation compared with single-scale switching methods or stationary multiscale methods. These modeling and inference methods effectively incorporate both regime-detection and multiscale observations. As such, they could facilitate investigation of latent switching neural population dynamics and improve future brain-machine interfaces by enabling inference in naturalistic scenarios where regime-dependent multiscale activity and behavior arise.
Threshold-crossing time statistics for gene expression in growing cells
Authors: Nieto César , Ghusinga Khem Raj , Vargas-García César , Singh Abhyudai
Published: June 2022

Many intracellular events are triggered by attaining critical concentrations of their corresponding regulatory proteins. How cells ensure precision in the timing of the protein accumulation is a fundamental problem, and contrasting predictions of different models can help us understand the mechanisms involved in such processes. Here, we formulate the timing of protein threshold-crossing as a first passage time (FPT) problem focusing on how the mean FPT and its fluctuations depend on the threshold protein concentration. First, we model the protein-crossing dynamics from the perspective of three classical models of gene expression that do not explicitly accounts for cell growth but consider the dilution as equivalent to degradation: (birth-death process, discrete birth with continuous deterministic degradation, andFokker-Planck approximation). We compare the resulting FPT statistics with a fourth model proposed by us (growing cell) that comprises size-dependent expression in an exponentially growing cell. When proteins accumulate in growing cells, their concentration reaches a steady value. We observe that if dilution by cell growth is modeled as degradation, cells can reach concentrations higher than this steady-state level at a finite time. In the growing cell model, on the other hand, the FPT moments diverge if the threshold is higher than the steady-state level. This effect can be interpreted as a transition between noisy dynamics when cells are small to an almost deterministic behavior when cells grow enough. We finally study the mean FPT that optimizes the timing precision. The growing cell model predicts a higher optimal FPT and less variability than the classical models.