bluuebunny/crossref_metadata_2025 huggingface dataset:
Machine Learning Techniques in Predicting BRAF Mutation Status in Cutaneous Melanoma From Clinical and Histopathologic Features
Authors: Figueroa-Silva Olalla , Pastur Romay Lucas A. , Viruez Roca Raúl D. , Rojas María D. Sánchez-Aguilar Y. , Suárez-Peñaranda José M.
Published: October 2022

Melanoma is the cutaneous neoplasm responsible for more patient deaths in all countries. BRAF mutations are the most common driver mutation and with the development of molecular targeted therapy, the precise knowledge of BRAF status has become increasingly important. Evaluation of BRAF mutation status has routinely been performed by polymerase chain reaction, a time consuming and expensive technique. Immunohistochemistry has been suggested as a cheaper alternative, but it has not gained general acceptance. A retrospective observational study in a cohort of 106 patients with invasive melanoma was conducted in order to develop and evaluate a machine learning approach to predict BRAF status using clinical and histologic variables. We compared the performance of different common machine learning algorithms and use SHapley Additive exPlanations (SHAP) to explain individual predictions and extract medical insights to define a heuristic model to estimate BRAF mutation probability. The Extreme Gradient Boosting algorithms obtained the best performance. Interpretability of models shows that the most important variables to estimate BRAF mutation probability are: age, Breslow thickness, and Breslow density. Based in this interpretation and medical knowledge, a simplify heuristic model is proposed to predict BRAF status using only 7 variables and obtain a performance of 0.878 of area under the curve. We propose a heuristic model that could be used by clinicians to obtain a good estimator of BRAF mutation probability.
An Evaluation of an Enhanced Model of Integrating Family Planning Into HIV Treatment Services in Zambia, April 2018–June 2019
Authors: Medley Amy , Tsiouris Fatima , Pals Sherri , Senyana Brenda , Hanene Susan , Kayeye Shadrick , Casquete Rocio Rodriguez , Lasry Arielle , Braaten Mollie , Aholou Tiffiany , Kasonde Prisca , Chisenga Tina , Mweebo Keith , Harris Tiffany G.
Published: October 2022

Background:

We designed and implemented an enhanced model of integrating family planning (FP) into existing HIV treatment services at 6 health facilities in Lusaka, Zambia.

Methods:

The enhanced model included improving FP documentation within HIV monitoring systems, training HIV providers in FP services, offering contraceptives within the HIV clinic, and facilitated referral to community-based distributors. Independent samples of women living with HIV (WLHIV) aged ≥16 years were interviewed before and after intervention and their clinical data abstracted from medical charts. Logistic regression models were used to assess differences in key outcomes between the 2 periods.

Results:

A total of 629 WLHIV were interviewed preintervention and 684 postintervention. Current FP use increased from 35% to 49% comparing the pre- and postintervention periods (P = 0.0025). Increased use was seen for injectables (15% vs. 25%, P < 0.0001) and implants (5% vs. 8%, P > 0.05) but not for pills (10% vs. 8%, P < 0.05) or intrauterine devices (1% vs. 1%, P > 0.05). Dual method use (contraceptive + barrier method) increased from 8% to 18% (P = 0.0003), whereas unmet need for FP decreased from 59% to 46% (P = 0.0003). Receipt of safer conception counseling increased from 27% to 39% (P < 0.0001). The estimated total intervention cost was $83,293 (2018 USD).

Conclusions:

Our model of FP/HIV integration significantly increased the number of WLHIV reporting current FP and dual method use, a met need for FP, and safer conception counseling. These results support continued efforts to integrate FP and HIV services to improve women's access to sexual and reproductive health services.
Machine Learning Model to Predict Diagnosis of Mild Cognitive Impairment by Using Radiomic and Amyloid Brain PET
Authors: Ciarmiello Andrea , Giovannini Elisabetta , Pastorino Sara , Ferrando Ornella , Foppiano Franca , Mannironi Antonio , Tartaglione Antonio , Giovacchini Giampiero ,   The Alzheimer’s Disease Neuroimaging Initiative
Published: October 2022

Purpose

The study aimed to develop a deep learning model for predicting amnestic mild cognitive impairment (aMCI) diagnosis using radiomic features and amyloid brain PET.

Patients and Methods

Subjects (n = 328) from the Alzheimer’s Disease Neuroimaging Initiative database and the EudraCT 2015-001184-39 trial (159 males, 169 females), with a mean age of 72 ± 7.4 years, underwent PET/CT with18F-florbetaben. The study cohort consisted of normal controls (n = 149) and subjects with aMCI (n = 179). Thirteen gray-level run-length matrix radiomic features and amyloid loads were extracted from 27 cortical brain areas. The least absolute shrinkage and selection operator regression was used to select features with the highest predictive value. A feed-forward neural multilayer network was trained, validated, and tested on 70%, 15%, and 15% of the sample, respectively. Accuracy, precision, F1-score, and area under the curve were used to assess model performance. SUV performance in predicting the diagnosis of aMCI was also assessed and compared with that obtained from the machine learning model.

Results

The machine learning model achieved an area under the receiver operating characteristic curve of 90% (95% confidence interval, 89.4–90.4) on the test set, with 80% and 78% for accuracy and F1-score, respectively. The deep learning model outperformed SUV performance (area under the curve, 71%; 95% confidence interval, 69.7–71.4; 57% accuracy, 48% F1-score).

Conclusions

Using radiomic and amyloid PET load, the machine learning model identified MCI subjects with 84% specificity at 81% sensitivity. These findings show that a deep learning algorithm based on radiomic data and amyloid load obtained from brain PET images improves the prediction of MCI diagnosis compared with SUV alone.
Comprehensive Treatment of Lower Eyelid Plasty Based on Intraoral Fixation and Redistribution of Lower Eyelid Fat
Authors: Ding Kun , Wei Ranran , Zhang Shan , Dong Yanhui , Chang Huanchao , Liang Xiaoqin
Published: October 2022

Background:

Eye bags especially give an impression of aging and mental exhaustion. At present, the surgical methods of bags mainly include conjunctival approach and lower eyelid skin approach. With the continuous upgrading of the concept of facial esthetics, the lower eyelid pouch surgery for middle-aged and elderly patients pays more attention to reducing surgical trauma, improving tear trough deformity along with the effacement of lid‑cheek junction.

Objective:

This paper discusses the clinical effect of the lower lid blepharoplasty involved orbital septum fat repositioning based on oral fixation via conjunctival approach combined with relaxation skin resection in the treatment of eye bags in elderly patient.

Methods:

Fifty elderly patients underwent blepharoplasty between January of 2021 and June of 2021 at our hospital. The lower eyelid orbital septum fat was released along with the prezygomatic space and the premaxillary space were stripped through the conjunctival approach. The released cellulite was redistributed in the prezygomatic space/premaxillary space and fixed in the oral vestibular with 5–0 Polysorb through the middle facial tunnel. Finally, the appropriate skin was finally removed.

Results:

After operation, 48 patients were satisfied with the operation results, with tight lower eyelid skin and natural lid‑cheek junction. One patient with conjunctival infection was cured after 7 days of antibiotic eye drops. One patient felt foreign body when chewing, and the symptoms disappeared naturally after 5 days without treatment.

Conclusion:

For middle-aged and elderly patients with bags, the surgical method in this study not only has good postoperative effect, but also has small damage to the lower eyelid orbicularis muscle. The appearance is natural and the lower eyelid skin is tight. The effacement of lid‑cheek junction and recreating a smooth transition of lower lid cheek interface, which can correct lacrimal groove deformity. The patients have high acceptance and satisfaction, which can be widely used in clinical practice.
Analysis of Native Kidney Function Recovery With Renal Scintigraphy Following Simultaneous Liver-Kidney Transplantation
Authors: Werneburg Glenn T. , Hettel Daniel R. , Mahajan Paresh , Goldfarb David A. , Fatica Richard A. , Eltemamy Mohamed , Menon K.V. Narayanan , Lindenmeyer Christina C. , Krishnamurthi Venkatesh , Wee Alvin
Published: October 2022

Background.

Patients undergoing simultaneous liver-kidney transplantation (SLK) have impaired native kidney function. The relative contribution of allograft versus native function after SLK is unknown. We sought to characterize the return of native kidney function following SLK.

Methods.

Following SLK, patients underwent technetium-99 m-mercaptoacetyltriglycine renal scintigraphy following serum creatinine nadir. Kidney contributions to estimated glomerular filtration rate (eGFR) were determined. Patients with native kidney function at serum creatinine nadir contributing eGFR ≥30 versus <30 mL/min/1.73 m2 were compared, and multiple linear regression analysis for native eGFR improvement was performed.

Results.

Thirty-one patients were included in this analysis. Average native kidney contribution to overall kidney function following SLK was 51.1% corresponding to native kidney eGFR of 44.5 mL/min/1.73 m2 and native kidney function eGFR improvement of 30.3 mL/min/1.73 m2 (P < 0.001). Twenty-six of 31 patients had native kidney contribution of eGFR ≥30 mL/min/1.73 m2. Hepatorenal syndrome as the sole primary etiology of kidney dysfunction was 100% specific for native kidney eGFR >30 mL/min/1.73 m2 and predicted native eGFR improvement (P = 0.03).

Conclusions.

Substantial improvement in native kidney function follows SLK, and hepatorenal syndrome as the sole primary etiology of kidney dysfunction is predictive of improvement. Whether such patients are suitable for liver transplant followed by surveillance with option for subsequent kidney transplants requires investigation.
Molecular genetics of paediatric brain tumours and opportunities for precision medicine – a focus on infant tumours
Authors: Rosenberg Tom , Bandopadhayay Pratiti
Published: October 2022

Purpose of review

The last few decades have seen an explosion in our understanding of the molecular drivers of childhood brain tumours. These insights have opened the possibility for precision medicine approaches for some tumour types. However, a different spectrum of tumours is more likely to occur in infants and young children, who face additional therapeutic challenges. This review focuses on recent advances in molecular genetics of common infant brain tumours and their implication for diagnosis, prognostication and utilization of precision oncology approaches.

Recent findings

Infant tumours have different biology and outcomes than similar tumours in older children and adults. For low-grade gliomas, targeted MAPK inhibition is well tolerated and likely efficacious. In high-grade gliomas, common tyrosine kinase alterations offer compelling targets for inhibition that are currently being evaluated. Paediatric-specific sequencing and methylation analysis offer insights into the driving biology of infant medulloblastoma, atypical teratoid rhabdoid tumours, embryonal tumours with multilayered rosettes, ependymoma and choroid plexus tumours, with molecular subgrouping shedding insights into distinct driving biology and clinical outcomes.

Infant brain tumours are rare and heterogenous, with overall poor outcomes. Advances in molecular genetics have been incorporated into their diagnostic criteria and allow for accurate subgrouping and improved prognostication. The utilization of targeted agents appears beneficial for many low-grade gliomas and a subset of high-grade gliomas, but further research is urgently needed to improve outcomes for other tumour entities.
The role of biofilm matrix composition in controlling colony expansion and morphology
Authors: Charlton Samuel G. V. , Kurz Dorothee L. , Geisel Steffen , Jimenez-Martinez Joaquin , Secchi Eleonora
Published: October 2022

Biofilms are biological viscoelastic gels composed of bacterial cells embedded in a self-secreted polymeric extracellular matrix (ECM). In environmental settings, such as in the rhizosphere and phyllosphere, biofilm colonization occurs at the solid–air interface. The biofilms’ ability to colonize and expand over these surfaces depends on the formation of osmotic gradients and ECM viscoelastic properties. In this work, we study the influence of biofilm ECM components on its viscoelasticity and expansion, using the model organism
Bacillus subtilis
and deletion mutants of its three major ECM components, TasA, EPS and BslA. Using a multi-scale approach, we quantified macro-scale viscoelasticity and expansion dynamics. Furthermore, we used a microsphere assay to visualize the micro-scale expansion patterns. We find that the viscoelastic phase angle

Φ

is likely the best viscoelastic parameter correlating to biofilm expansion dynamics. Moreover, we quantify the sensitivity of the biofilm to changes in substrate water potential as a function of ECM composition. Finally, we find that the deletion of ECM components significantly increases the coherence of micro-scale colony expansion patterns. These results demonstrate the influence of ECM viscoelasticity and substrate water potential on the expansion of biofilm colonies on wet surfaces at the air–solid interface, commonly found in natural environments.
Measuring the linear viscoelastic regime of MCF-7 cells with a monolayer rheometer in the presence of microtubule-active anti-cancer drugs at high concentrations
Authors: Lee Suhyang , Bashir Khawaja Muhammad Imran , Jung Dong Hee , Basu Santanu Kumar , Seo Gayeon , Cho Man-Gi , Wierschem Andreas
Published: October 2022

The rheological properties of cells have vital functional implications. Depending, for instance, on the life cycle, cells show large cell-to-cell variations making it cumbersome to quantify average viscoelastic properties of cells by single-cell techniques. Microfluidic devices, typically working in the nonlinear viscoelastic range, allow fast analysis of single-cell deformation. Averaging over a large number of cells can also be achieved by studying them in a monolayer between rheometer discs. This technique allows applying well-established rheological standard procedures to cell rheology. It offers further advantages like studying cells in the linear viscoelastic range while quantifying cell vitality. Here, we study the applicability of the technique to rather adverse conditions, like for microtubule-active anti-cancer drugs and for a cell line with large size variation. We found a strong impact of the gap width and of normal forces on the moduli and obtained high vitality levels during the rheological study. To enable studying the impact of microtubule-active drugs on vital cells at concentrations several orders of magnitude beyond the half maximal effective concentration for cytotoxicity, we arrested the cell cycle with hydroxyurea. Irrespective of the high concentrations, we observed no clear impact of the microtubule-active drugs.
Specific Ethogram of the Mexican four-eyed octopus:Octopus maya
Authors: González-Navarrete D.A. , Vergara-Ovalle F. , García-Andaluz P. , Ayala-Guerrero F. , Rosas C. , Vázquez-León P. , Paz-Trejo D.B. , Sánchez-Castillo H.
Published: October 2022

Historically, behavior studies have focused mainly on animals of two phyla in particular: Craniata and Arthropoda, however, behavioral research on alternative phyla like mollusks has been increasing because of the potential for research that these models present. When we talk about mollusk behavior, cephalopods are the first group that stands out, however, research on Mexico’s endemic species likeOctopus maya, is still lacking. This octopus could help to reach a standardized model in neuroscience, because adapts well to laboratory conditions and has been successfully cultured through several generations. These characteristics provide a great advantage as a research model since they could reduce the number of variables that affect behavioral studies, something hard to control with a captured-wild octopus. Hence, in order to work properly with species like this, in research environments, it’s fundamental to know first the behaviors that this species can perform there. Therefore, the objective of this study was to elaborate an ethogram that describes the behavioral repertoire thatO. mayadisplays in laboratory conditions. Thirteen individuals ofO. maya(6-20g) were used and maintained in tanks with a closed circulation seawater system and illuminated with a red light of 30 lx in a 12:12 LD cycle. Nine of these individuals were used for anad libitumsampling of behaviors to name, define, categorize and operationally describe them. The last four individuals were used to establish day/night activity patterns, (length and frequency of behaviors throughout the day). The obtained results showed thatO. mayahas a wide behavioral repertoire with at least twenty-three behaviors, which were included in six different behavioral categories. The obtained results showed thatO. mayahas a wide behavioral repertoire with at least twenty-three behaviors, which were organized in six different behavioral categories. Also, this species showed differentiated activity patterns between day and night, with peaks of activity, distribution, and frequencies of activity behaviors mainly during the light hours. These results showed thatO. mayahas behaviors comparable with other octopus species and support the proposal for its use as a viable research model. Knowing the behavioral repertoire ofO. mayaallows for better control in future behavioral studies using this model, provides the main tools to evaluate the organism’s health and status, and supports its use for research in neuroscience and cognition.
The metabolite α-ketobutyrate increases health and life spans by activating AMPK
Authors: Chen Chieh , Lomenick Brett , Chai Min , Huang Wilson , Chu Jessie , Vergnes Laurent , Johnson Reid O’Brien , Vashisht Ajay A. , Chin Randall M. , Dix Melissa M. , Simon Gabriel , Fu Xudong , Link Jenny C. , Hwang Heejun , Yin Xiang , de Barros Stéphanie C. , Braas Daniel , Diane Kim Nahn Hee , Wang Yibin , Dubinett Steven M. , Teitell Michael A. , Fiehn Oliver , Jiang Meisheng , Cravatt Benjamin F. , Wohlschlegel James A. , Loo Joseph A. , Reue Karen , Huang Jing
Published: October 2022

Aging is a complex process that is directly related to human health and disease. The extraordinary finding that aging is malleable, as shown in model organisms whose life and health spans are extended by specific gene mutations or dietary or pharmacological perturbations1–3, has offered enormous hope for our understanding and treatment of aging and related diseases. Although many molecules have been identified that can extend the lifespan of model organisms, few have been shown to alleviate age-related symptoms or illness in mammals4. Here we show that supplementation with the endogenous metabolite α-ketobutyrate (α-KB) increases the lifespan of adultC. elegans. Using Gelfree DARTS-PROTOMAP, we identified microtubule-actin cross-linking factor (MACF1) that was protected against proteolysis in the presence of α-KB. MACF1 belongs to the spectraplakin family of giant, evolutionarily conserved proteins with versatile functions5, but their link to longevity regulation has not been explored. α-KB’s longevity effect inC. elegansis abrogated by loss-of-function mutation invab-10, encoding the worm ortholog of mammalian MACF16. Like α-KB treatment,vab-10knockdown activates AMP-activated protein kinase (AMPK), and AMPK is required for α-KB effects on longevity. The findings suggest a model in which α-KB increases longevity by activating AMPK via VAB-10/MACF1 modulation. α-KB also delays aging in mammals, increasing the lifespan of aged male mice and the healthspan of both male and female animals. Targeting of broadly expressed scaffolding proteins in connection to cellular energy homeostasis seems to be a clever way that nature has devised for metabolite signals to impinge upon multiple organ and tissue systems, which may have utility for controlling aging and related diseases.
Improving newborn health with family-centered, early postnatal care: a quasi-experimental study
Authors: Murthy Seema , Yan Shirley Du , Alam Shahed , Kumar Amit , Rangarajan Arjun , Sawant Meenal , Sulaiman Huma , Yadav Bhanu Pratap , Pathani Tanmay Singh , Kumar H.G. Anand , Kak Sareen , A M Vinayaka , Kaur Baljit , N Rajkumar , Mishra Archana , Elliott Edith , Delaney Megan Marx , Semrau Katherine E.A.
Published: October 2022

Despite the recent decline, neonatal mortality rates (NMR) remain high in India. Family members are often responsible for the postpartum care of newborns and mothers. Yet, low health literacy and varied beliefs can lead to poor neonatal health outcomes. Postpartum education for family caregivers can improve the adoption of evidence-based newborn care and health outcomes. The Care Companion Program (CCP) is a hospital-based, pre-discharge health training session where nurses teach key healthy behaviors and help mothers and family members learn skills and practice in the hospital. Here, we assessed the impact of CCP on NMR. We conducted a quasi-experimental study to assess the effect of the CCP sessions on mortality outcomes among families seeking care in 28 public tertiary facilities, across 4 Indian states. Neonatal mortality outcomes were reported post-discharge, collected via phone surveys at four weeks of age of baby, between October 2018 to February 2020. Risk ratios (RR), adjusting for hospital-level clustering, were calculated by comparing mortality rates before and after CCP implementation. A total of 46,428 families participated in the pre-intervention group and 87,305 in the post-intervention group; 76% of families participated in the phone survey. The crude NMR was 33.64 deaths per 1000 live births (RR=0.82, 95% CI: 0.76, 0.87). After accounting for hospital-clustering, the NMR was 41.3 (adjusted RR=0.81, 95% CI: 0.71, 0.93). There may be a substantial benefit to family-centered education in the early postnatal period to reduce neonatal mortality.
Age-stratified infection fatality rate of COVID-19 in the non-elderly informed from pre-vaccination national seroprevalence studies
Authors: Pezzullo Angelo Maria , Axfors Cathrine , Contopoulos-Ioannidis Despina G. , Apostolatos Alexandre , Ioannidis John P.A.
Published: October 2022

The infection fatality rate (IFR) of COVID-19 among non-elderly people in the absence of vaccination or prior infection is important to estimate accurately, since 94% of the global population is younger than 70 years and 86% is younger than 60 years. In systematic searches in SeroTracker and PubMed (protocol:https://osf.io/xvupr), we identified 40 eligible national seroprevalence studies covering 38 countries with pre-vaccination seroprevalence data. For 29 countries (24 high-income, 5 others), publicly available age-stratified COVID-19 death data and age-stratified seroprevalence information were available and were included in the primary analysis. The IFRs had a median of 0.035% (interquartile range (IQR) 0.013 - 0.056%) for the 0-59 years old population, and 0.095% (IQR 0.036 - 0.125%,) for the 0-69 years old. The median IFR was 0.0003% at 0-19 years, 0.003% at 20-29 years, 0.011% at 30-39 years, 0.035% at 40-49 years, 0.129% at 50-59 years, and 0.501% at 60-69 years. Including data from another 9 countries with imputed age distribution of COVID-19 deaths yielded median IFR of 0.025-0.032% for 0-59 years and 0.063-0.082% for 0-69 years. Meta-regression analyses also suggested global IFR of 0.03% and 0.07%, respectively in these age groups. The current analysis suggests a much lower pre-vaccination IFR in non-elderly populations than previously suggested. Large differences did exist between countries and may reflect differences in comorbidities and other factors. These estimates provide a baseline from which to fathom further IFR declines with the widespread use of vaccination, prior infections, and evolution of new variants.

Highlights

*Across 31 systematically identified national seroprevalence studies in the pre-vaccination era, the median infection fatality rate of COVID-19 was estimated to be 0.035% for people aged 0-59 years people and 0.095% for those aged 0-69 years.

*The median IFR was 0.0003% at 0-19 years, 0.003% at 20-29 years, 0.011% at 30-39 years, 0.035% at 40-49 years, 0.129% at 50-59 years, and 0.501% at 60-69 years.

*At a global level, pre-vaccination IFR may have been as low as 0.03% and 0.07% for 0-59 and 0-69 year old people, respectively.

*These IFR estimates in non-elderly populations are lower than previous calculations had suggested.
Primary care provider preferences on dementia training and care navigation services: A qualitative study
Authors: Perales-Puchalt Jaime , Strube Kelsey , Townley Ryan , Niedens Michelle , Arreaza Hector , Zaudke Jana , Burns Jeffrey M
Published: October 2022

Background

Dementia has no cure but interventions can stabilize the progression of cognitive, functional, and behavioral symptoms. Primary care providers (PCPs) are vital for the early detection, and long-term management of these diseases, given their gatekeeping role in the healthcare system. However, PCPs rarely implement evidence-based dementia care due to barriers such as limited dementia knowledge and time. Training PCPs and linking them to dementia care navigators may address these barriers.

Objective

We explored the preferences of PCPs about dementia care training programs and dementia care navigation services.

Methods

We conducted qualitative interviews with 24 PCPs recruited nationally via snowball sampling. We conducted all interviews via videocall and organized the transcripts for qualitative review to identify codes and themes, using a pragmatic approach, a qualitative description methodology, and thematic analysis methods.

Results

PCP preferences varied regarding the topic, duration, materials, modality, and incentives of the dementia training. With regards to dementia care navigation services, preferences varied with respect to whether they benefited the PCP or the patient, and which were the optimal qualities of a dementia care navigator.

Conclusions

Dementia training and care navigation services would benefit from embedding cultural proficiency within their content, materials, and navigation abilities. EMR-based decision-support tools would facilitate PCPs’ implementation of evidence-based dementia care.
Physics-based Deep Learning for Imaging Neuronal Activity via Two-photon and Light Field Microscopy
Authors: Verinaz-Jadan Herman , Howe Carmel L. , Song Pingfan , Lesept Flavie , Kittler Josef , Foust Amanda J. , Dragotti Pier Luigi
Published: October 2022

Light Field Microscopy (LFM) is an imaging technique that offers the opportunity to study fast dynamics in biological systems due to its rapid 3D imaging rate. In particular, it is attractive to analyze neuronal activity in the brain. Unlike scanning-based imaging methods, LFM simultaneously encodes the spatial and angular information of light in a single snapshot. However, LFM is limited by a trade-off between spatial and angular resolution and is affected by scattering at deep layers in the brain tissue. In contrast, two-photon (2P) microscopy is a point-scanning 3D imaging technique that achieves higher spatial resolution, deeper tissue penetration, and reduced scattering effects. However, point-scanning acquisition limits the imaging speed in 2P microscopy and cannot be used to simultaneously monitor the activity of a large population of neurons. This work introduces a physics-driven deep neural network to image neuronal activity in scattering volume tissues using LFM. The architecture of the network is obtained by unfolding the ISTA algorithm and is based on the observation that the neurons in the tissue are sparse. The deep-network architecture is also based on a novel imaging system modeling that uses a linear convolutional neural network and fits the physics of the acquisition process. To achieve the high-quality reconstruction of neuronal activity in 3D brain tissues from temporal sequences of light field (LF) images, we train the network in a semi-supervised manner using generative adversarial networks (GANs). We use the TdTomato indicator to obtain static structural information of the tissue with the microscope operating in 2P scanning modality, representing the target reconstruction quality. We also use additional functional data in LF modality with GCaMP indicators to train the network. Our approach is tested under adverse conditions: limited training data, background noise, and scattering samples. We experimentally show that our method performs better than model-based reconstruction strategies and typical artificial neural networks for imaging neuronal activity in mammalian brain tissue, considering reconstruction quality, generalization to functional imaging, and reconstruction speed.
Complex Intracellular Mechanisms of TBK1 Kinase Activation Revealed by a Specific Small Molecule Inhibitor
Authors: Ye Junqiang , Dephoure Noah , Maniatis Tom
Published: October 2022

TANK-binding kinase 1 (TBK1), a dimeric serine/threonine protein kinase, plays a critical role in multiple signaling pathways including innate immunity, autophagy and cell death. TBK1 is activated by the phosphorylation of an essential serine residue 172 (S172) within the activation loop of the kinase domain, and this phosphorylation can occur by trans-autophosphorylation: one TBK1 dimer phosphorylates a second dimer at S172. Here we show that phosphorylation of TBK1 S172 in cultured human cells in response to multiple inducers is reduced, but not abolished by the highly specific and potent TBK1 small molecule inhibitor GSK8612. Thus, upstream kinase(s) must phosphorylate TBK1 in response to inducers in cultured cells. We show that distinct upstream kinases are recruited for the activation of TBK1 in response to different inducers. We also identify extensive crosstalk among TBK1, IKKβ and IKKε kinases in the cellular response to various inducers. In addition, we show that dsDNA and dsRNA trigger dynamic intracellular translocation of TBK1, leading to its localization and activation on the Golgi apparatus or mitochondria, respectively. GSK8612 does not block the intracellular localization of TBK1. We conclude that TBK1 is activated by both upstream kinase phosphorylation and by trans-autophosphorylation, and the signal-dependent spatial engagement of TBK1 with other signaling molecules is a fundamental mechanism for its specific activation by multiple inducers.
A workflow reproducibility scale for automatic validation of biological interpretation results
Authors: Suetake Hirotaka , Fukusato Tsukasa , Igarashi Takeo , Ohta Tazro
Published: October 2022

Background

Reproducibility of data analysis workflow is a key issue in the field of bioinformatics. Recent computing technologies, such as virtualization, have made it possible to reproduce workflow execution with ease. However, the reproducibility of results is not well discussed; that is, there is no standard way to verify whether the biological interpretation of reproduced results are the same. Therefore, it still remains a challenge to automatically evaluate the reproducibility of results.

Results

We propose a new metric, a reproducibility scale of workflow execution results, to evaluate the reproducibility of results. This metric is based on the idea of evaluating the reproducibility of results using biological feature values (e.g., number of reads, mapping rate, and variant frequency) representing their biological interpretation. We also implemented a prototype system that automatically evaluates the reproducibility of results using the proposed metric. To demonstrate our approach, we conducted an experiment using workflows used by researchers in real research projects and the use cases that are frequently encountered in the field of bioinformatics.

Conclusions

Our approach enables automatic evaluation of the reproducibility of results using a fine-grained scale. By introducing our approach, it is possible to evolve from a binary view of whether the results are superficially identical or not to a more graduated view. We believe that our approach will contribute to more informed discussion on reproducibility in bioinformatics.
3D model of mouse embryonic pancreas and endocrine compartment using stem cell-derived mesoderm and pancreatic progenitors
Authors: Edri Shlomit , Rosenthal Vardit , Ginsburg Or , Frisch Abigail Newman , Pierreux Christophe E. , Sharon Nadav , Levenberg Shulamit
Published: October 2022

The developing mouse pancreas is surrounded by mesoderm compartments providing signals that induce pancreas formation. Most pancreatic organoid protocols lack this mesoderm niche and only partially capture the pancreatic cell repertoire. This work aimed to generate pancreatic aggregates by differentiating mouse embryonic stem cells (mESCs) into mesoderm progenitors (MPS) and pancreas progenitors (PPs), without using extracellular matrix substitutes. First, mESCs were differentiated into epiblast stem cells (EpiSCs) to enhance the PP differentiation rate. Next, PPs and MPs aggregated together giving rise to various pancreatic cell types, including endocrine, acinar, and ductal cells, and to endothelial cells. Single-cell RNA sequencing analysis revealed a larger endocrine population within the PP+MP aggregates, as compared to PPs alone or PPs in Matrigel aggregates. The PP+MP aggregate gene expression signatures and its endocrine population percentage closely resembled those of the endocrine population found in the mouse embryonic pancreas, which holds promise for studying pancreas development.
Electrophysiological population dynamics reveal context dependencies during decision making in human frontal cortex
Authors: Shih Wan-Yu , Yu Hsiang-Yu , Lee Cheng-Chia , Chou Chien-Chen , Chen Chien , Glimcher Paul W. , Wu Shih-Wei
Published: October 2022

During economic choice, evidence from monkeys and humans suggest that activity in the orbitofrontal cortex (OFC) encodes the subjective values of options under consideration. Monkey data further suggests that value representations in the OFC are context dependent, representing subjective value in a way influenced by the decision makers’ recent experience. Using stereo electroencephalography (sEEG) in human subjects, we investigated the neural representations of both past and present subjective values in the OFC, insula, cingulate and parietal cortices, amygdala, hippocampus and striatum. Patients with epilepsy (n=20) reported their willingness to pay—a measure of subjective value—for snack food items in a Becker-DeGroot-Marschack (BDM) auction task. We found that the high frequency power (gamma and high-gamma bands) in the OFC positively correlated with the current subjective value but negatively correlated with the subjective value of the good offered on the last trial – a kind of temporal context dependency not yet observed in humans. These representations were observed at both the group level (across electrode contacts and subjects) and at the level of individual contacts. Noticeably, the majority of significant contacts represented either the present or past subjective value, but not both. A dynamic dimensionality-reduction analysis of OFC population trajectories suggested that the past trial begin to influence activity early in the current trial after the current offer was revealed, and that these two properties—current and past subjective values—dominate the electrophysiological signals. Together, these findings indicate that information about the value of the past and present rewards are simultaneously represented in the human OFC, and offer insights into the algorithmic structure of context-dependent computation during human economic choice.
Maternal age, obesity and hyperglycaemia are associated with a delay in preimplantation development in a mouse model of type 2 diabetes
Authors: Lilao-Garzón Joaquín , Brito-Casillas Yeray , Quesada-Canales Oscar , Wägner Ana M , Muñoz-Descalzo Silvia
Published: October 2022

Aims/hypothesis

Delayed maternal age, obesity and diabetes are associated with reduced fertility. We investigated how age and obesity/metabolic syndrome impact fertility and hypothesized that its decrease is due to defects in preimplantation embryo development.

Methods

Three groups of female C57Bl6 mice (12 weeks, 9 months and 1 year old) were fed either a high fat diet for 8 weeks, to induce obesity and the metabolic syndrome, or a control chow diet. Body weight and composition, glucose tolerance and insulin resistance were assessed. Fecundity was evaluated by mating and pregnancy rates, as well as number of embryos. Embryo quality was assessed morphologically, and cell fate composition was analysed in preimplantation embryos by state-of-the-art single cell quantitative confocal image analysis.

Results

The high fat diet was associated with increased adiposity, glucose intolerance and insulin resistance, especially in the older mice. Fecundity was affected by age, more than by the diet. Both age and high fat diet were associated with reduced cell fate allocation, indicating a delay in preimplantation embryo development, and with increased expression of GATA3, an inhibitor of placentation.

Conclusion/Interpretation

These results support that age and the metabolic syndrome reduce fertility through mechanisms which are present at conception very early in pregnancy.

What is already known about this subject?

Lifestyle changes in modern societies have led to an increase in obesity and type 2 diabetes, and women tend to become pregnant later than ever. These factors have a negative influence on female fecundity.

In mice, diet induced obesity is associated with poor quality oocytes that affect overall embryonic development.

What is the key question?

Do age and high fat diet influence cell fate differentiation during preimplantation embryo development?

What are the new findings?

Body composition and glucose metabolism are altered due to high fat diet even when weight is not affected in young animals.

Although there are no differences in mating and fertilization rates, embryo quality is lower with high fat diet.

Cells not fully committed to a cell fate (epiblast or primitive endoderm) are increased in embryos from mature dams or fed a high fat diet, indicating a delay in preimplantation embryo development.

How might this impact on clinical practice in the foreseeable future?

Our findings show a delay in early embryo development associated to obesity and maternal age. This delay could be responsible for the low fertility observed in women with type 2 diabetes and obesity.
Quantitative dose-response analysis untangles host bottlenecks to enteric infection
Authors: Campbell Ian W. , Hullahalli Karthik , Turner Jerrold R. , Waldor Matthew K.
Published: October 2022

Host bottlenecks prevent many infections before the onset of disease by eliminating invading pathogens. Monitoring the diversity of a barcoded population of the diarrhea causing bacteriumCitrobacter rodentiumduring colonization of its natural host, mice, allowed us to determine the number of cells that found the infection by establishing a replicative niche. The size of the pathogen’s founding population scaled with dose and was controlled by a severe yet slow-acting bottleneck. Reducing stomach acid or changing host genotype modestly relaxed the bottleneck without breaking the fractional relationship between dose and founders. In contrast, disrupting the microbiota caused the founding population to no longer scale with the size of the inoculum and allowed the pathogen to infect at almost any dose, indicating that the microbiota creates the dominant bottleneck. Further, in the absence of competition with the microbiota, the diversity of the pathogen population slowly contracted as the population was overtaken by bacteria that lost the critical virulence island, the locus of enterocyte effacement (LEE). Collectively, our findings reveal that the mechanisms of protection by colonization bottlenecks are reflected in and can be generally defined by the impact of dose on the pathogen’s founding population.
Single Cell Transcriptomics Reveals the Hidden Microbiomes of Human Tissues
Authors: Mahmoudabadi Gita , Crasta Sheela ,   Tabula Sapiens Consortium, Quake Stephen R.
Published: October 2022

The human microbiome has been studied extensively across those sites in the body that are readily accessible to sampling. Internal organs and tissues, however, have remained largely unexplored and, in the absence of infectious disease, are widely assumed to be free of microorganisms. Using single-cell transcriptomic data from the Tabula Sapiens spanning 11 human organ donors, 19 tissue types, 400,000+ annotated cells, 100+ cell types, and ∼70 billion sequences, we created an atlas of the human tissue microbiome with cell type resolution across three domains of life which we refer to as the Tabula Sapiens Microbiome. Together with data from 8 additional donors derived from a different set of experimental techniques for validation, we identified sequences from numerous bacterial, viral and fungal species in human tissues. We mapped the likely microbial flow routes in the body from external-facing microbiomes and natural environments to internal tissues and tumors, demonstrating the existence of several unexpected routes. In the case of tumor microbiomes, we find a considerable number of bacterial genera found in tumors are detectable across tumor-free tissues, suggesting that tumor microbiomes are in part sourced from adjacent normal tissues, even those from distant sites. Finally, by increasing the resolution of sampling from tissues to cell types, we quantified the microbial load and diversity across different human cell types to reveal a network of host cell type and microbe associations. For example, we identified traces of both latent and active Epstein Barr Virus infections in various cell types such as splenic plasma cells. Broad exploration of the human tissue microbiomes may provide insights which ultimately are of clinical importance.
Post-pubertal developmental trajectories of laryngeal shape and size in humans
Authors: Riede Tobias , Stein Amy , Baab Karen L. , Hoxworth Joseph M.
Published: October 2022

Laryngeal morphotypes have been hypothesized related to both phonation and to laryngeal pathologies. Morphotypes have not been validated or demonstrated quantitatively and sources of shape and size variation are incompletely understood but could be critical for the explanation of behavioral changes (e.g., changes of physical properties of a voice) and for therapeutic approaches to the larynx. Therefore results are likely to have implications for surgeons and speech language pathologists. A stratified human sample was interrogated for phenotypic variation of the vocal organ. First, computed tomography image stacks were used to generate three-dimensional reconstructions of the thyroid cartilage. Then cartilage shapes were quantified using multivariate statistical analysis of high dimensional shape data from margins and surfaces of the thyroid cartilage. The effects of sex, age, body mass index (BMI) and body height on size and shape differences were analyzed. We found that sex, age, BMI and the age-sex interaction showed significant effects on the mixed sex sample. Among males, only age showed a strong effect. The thyroid cartilage increased in overall size, and the angulation between left and right lamina decreased in older males. Age, BMI and the age-height interaction were statistically significant factors within females. The angulation between left and right lamina increased in older females and was smaller in females with greater BMI. A cluster analysis confirmed the strong age effect on larynx shape in males and a complex interaction between the age, BMI and height variables in the female sample. The investigation demonstrated that age and BMI, two risk factors in a range of clinical conditions, are associated with shape and size variation of the human larynx. The effects influence shape differently in female and male larynges. The male-female shape dichotomy is partly size-dependent but predominantly size-independent.
Background prostate tissue is quantitatively abnormal on MRI in patients with clinically significant prostate cancer
Authors: Conlin Christopher C , Karunamuni Roshan , Hussain Troy S , Zhong Allison Y , Kallis Karoline , Do Deondre D , Lui Asona J , Mani Garnier , Ollison Courtney , Domingo Mariluz Rojo , Shabaik Ahmed , Kane Christopher J , Bagrodia Aditya , McKay Rana R , Kuperman Joshua M , Rakow-Penner Rebecca , Hahn Michael E , Dale Anders M , Seibert Tyler M
Published: October 2022

Background

T2-weighted MRI is standard for detecting clinically significant prostate cancer (csPCa) by identifying visible lesions that stand out from the background prostate.

Purpose

To determine whether patients with csPCa have abnormalT2-weighted signal in non-lesion, background prostate tissue (BP).

Methods

This retrospective study included two patient cohorts who underwent 3T MRI examination for suspected csPCa. Median (urine-normalized)T2-weighted signal was computed for BP and compared between patients with and without csPCa. csPCa discrimination performance ofT2-weighted BP signal was evaluated using area under receiver operating characteristic curves (AUC).T2andS0(a proxy for proton density) were computed and compared between patients with and without csPCa.T2was also recomputed using larger buffers around csPCa lesions. csPCa discrimination performance was compared between two predictors: Restriction Spectrum Imaging (RSI)C1and RSIC1normalized by global prostate medianT2-weighted signal.

Results

Cohort 1: 46 patients (age: 64±10 years). Cohort 2: 151 patients (65±8 years). Urine-normalizedT2-weighted signal was systematically lower in BP of subjects with csPCa (p≤0.034) and indicated the presence of cancer (cohort 1: AUC=0.80; cohort 2: AUC=0.68). BPT2was significantly lower in csPCa patients (p≤0.011), whileS0was not (p≥0.30). BPT2measurements were stable to within 5% with buffers from 0 to 30 mm around visible lesions. csPCa discrimination improved with incorporation of BPT2-weighted signal (cohort 1: AUC=0.72 for RSIC1alone, versus 0.81 with BPT2-weighted signal; cohort 2: AUC=0.63 versus 0.76).

Conclusion

LowerT2-weighted signal in BP suggests the presence of csPCa.
Potential protective link between type I diabetes and Parkinson’s disease risk and progression
Authors: Senkevich Konstantin , Alipour Paria , Chernyavskaya Ekaterina , Yu Eric , Noyce Alastair J , Gan-Or Ziv
Published: October 2022

Background

Epidemiological studies suggested an association between Parkinson’s disease (PD) and type 2 diabetes, but less is known about type 1 diabetes (T1D) and PD.

Objectives

To explore the association between T1D and PD.

Methods

We used Mendelian randomization, linkage disequilibrium score regression and transcriptome wide association analysis (TWAS) to examine the association between PD and T1D.

Results

Mendelian randomization showed a potentially protective role of T1D for PD risk (inverse-variance weighted (IVW); OR (95% CI) 0.97 (0.94-0.99); p=0.039), as well as motor (IVW; 0.94 (0.88-0.99); p=0.044) and cognitive progression (IVW; 1.50 (1.08-2.09); p=0.015). We further found negative genetic correlation between T1D and PD (rg=-0.17, p=0.016), and identified nine genes in cross-tissue TWAS that were associated with both traits.

Conclusions

Our results suggest a potential genetic link between T1D and PD risk and progression. Larger comprehensive epidemiological and genetic studies are required to validate our findings.