bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of excess deaths and laboratory-confirmed COVID-19 deaths during a large Omicron epidemic in 2022 in Hong Kong
Authors: Xin Hualei , Law Alexandra H. T. , Cheung Justin K. , Lin Yun , Wu Peng , Li Zhongjie , Cowling Benjamin J. , Yang Weizhong , Wong Jessica Y.
Published: July 2024

Background

Using a local elimination strategy, Hong Kong was able to minimize COVID-19 mortality in 2020 and 2021, but a large epidemic caused by the Omicron variant occurred in 2022. We aimed to estimate the overall, age-, sex-, epidemic period- and cause-specific excess mortality in 2022 in Hong Kong and compared excess mortality to laboratory-confirmed COVID-19 mortality.

Methods

Negative binomial regression analysis was used to model time series of weekly all-cause and cause-specific deaths from 2010 to 2021 to predict the weekly number of deaths in 2022 against counterfactual baselines projected from the trends in the absence of a pandemic. The estimated excess deaths were compared with laboratory-confirmed COVID-19 deaths overall and by age and epidemic period.

Results

We estimated that there were 13,500 (95% CI: 13,400-13,600) excess deaths in 2022, which was slightly higher than the 12,228 deaths recorded with laboratory-confirmed COVID-19, with the majority of the excess deaths and laboratory-confirmed deaths occurring among older adults. The increased number of excess deaths over laboratory-confirmed COVID-19 deaths was most substantial from February to April 2022 (a difference of 847 deaths), when the largest Omicron wave peaked. Most of the excess deaths (78%) were from respiratory causes, while 10% were from cardiovascular causes. A slight reduction in malignant neoplasm mortality was identified among older adults in 2022.

Conclusions

A substantial increase in population mortality was identified in 2022 in Hong Kong, slightly larger than the laboratory-confirmed COVID-19 deaths. Apart from the possibility of underdiagnosis, excess deaths might also be attributed to the overload of healthcare resources during the pandemic. Deaths from COVID-19 may have displaced some deaths that would otherwise have occurred due to other causes although we did not find evidence of substantial mortality displacement.
Non-linear genetic regulation of the blood plasma proteome
Authors: Sigurdsson Arnor I. , Gräf Justus F. , Yang Zhiyu , Ravn Kirstine , Meisner Jonas , Thielemann Roman , Webel Henry , Smit Roelof A. J. , Niu Lili , Mann Matthias ,   FinnGen, Vilhjalmsson Bjarni , Neale Benjamin M. , Ganna Andrea , Hansen Torben , Loos Ruth J. F. , Rasmussen Simon
Published: July 2024

Although thousands of genetic variants are linked to human traits and diseases, the underlying mechanisms influencing these traits remain largely unexplored. One important aspect is to understand how proteins are regulated by the genome by identifying protein quantitative trait loci (pQTLs). Beyond this, there is a need to understand the role of complex genetics effects such as dominance and epistasis that regulate plasma proteins and protein biomarkers. Therefore, we developed EIR-auto-GP, a deep learning-based approach, to identify such effects. Our results complement the additive genetic regulation identified in previous pQTLs screens by adding a nuanced view of the complex genetic regulation of plasma proteins. Applying this method to the UK Biobank proteomics cohort of 48,594 individuals, we identified 138 proteins that were regulated by non-linear effects, including non-linear covariates (123) as well as genetic dominance and epistasis (15). We uncovered a novel epistatic interaction between theABOandFUT3loci, and demonstrated dominance effects of theABOlocus on plasma levels of pathogen recognition receptors CD209 and CLEC4M. Furthermore, we replicated these findings and the methodology across Olink and mass spectrometry-based cohorts and concluded that large sample sizes are needed to discover more complex genetic effects. Our approach presents a systematic, large-scale attempt to identify complex effects of plasma protein levels and can be applied to study other tissues or molecular QTLs.
Single-gene transcripts for subclinical TB: an individual participant data meta-analysis
Authors: Greenan-Barrett James , Mendelsohn Simon C. , Scriba Thomas J. , Noursadeghi Mahdad , Gupta Rishi K.
Published: July 2024

Background

Translation of blood RNA signatures may be accelerated by identifying more parsimonious biomarkers. We tested the hypothesis that single-gene transcripts provide comparable accuracy for detection of subclinical TB to multi-gene signatures and benchmarked their clinical utility to interferon-y release assays (IGRAs).

Methods

We identified datasets where participants underwent RNA sampling and at least 12 months of follow-up for progression to TB. We performed a one-stage individual participant data meta-analysis to compare multi-gene signatures against single-gene transcripts to detect subclinical TB, defined as asymptomatic prevalent or incident TB (diagnosed ≥21 days from enrolment, irrespective of symptoms) over a 12-month interval. We performed decision curve analysis to evaluate the net benefit of using RNA biomarkers and IGRA, alone or in combination, compared to treating all or no individuals with preventative treatment.

Results

We evaluated 80 single-genes and eight multi-gene signatures in a pooled analysis of four RNAseq and three qPCR datasets, comprising 6544 total samples and including 283 samples from 214 individuals with subclinical TB. Five single-gene transcripts were equivalent to the best-performing multi-gene signature over 12 months, with areas under the receiver operating characteristic curves ranging from 0.75-0.77, but none met the WHO minimum target product profile (TPP) for a TB progression test. IGRA demonstrated much lower specificity in higher burden settings, while sensitivity and specificity of RNA biomarkers were consistent across settings. In higher burden settings, RNA biomarkers had greater net benefit than IGRA, which offered little clinical utility over treating all with preventative therapy. In low burden settings, IGRA approximated the TPP and offered greater clinical utility than RNA biomarkers, but combining both tests provided the highest net benefit for services aiming to treat <50 people to prevent a single case.

Interpretation

Single-gene transcripts are equivalent to multi-gene signatures for detection of subclinical TB, with consistent performance across settings. Single transcripts demonstrate potential clinical utility to stratify treatment, particularly when used in combination with IGRA in low burden settings.
Study Protocol: Development and Retrospective Validation of an Artificial Intelligence System for Diagnostic Assessment of Prostate Biopsies
Authors: Mulliqi Nita , Blilie Anders , Ji Xiaoyi , Szolnoky Kelvin , Olsson Henrik , Titus Matteo , Gonzalez Geraldine Martinez , Boman Sol Erika , Valkonen Masi , Gudlaugsson Einar , Kjosavik Svein R. , Asenjo José , Gambacorta Marcello , Libretti Paolo , Braun Marcin , Kordek Radzislaw , Łowicki Roman , Hotakainen Kristina , Väre Päivi , Pedersen Bodil Ginnerup , Sørensen Karina Dalsgaard , Ulhøi Benedicte Parm , Rantalainen Mattias , Ruusuvuori Pekka , Delahunt Brett , Samaratunga Hemamali , Tsuzuki Toyonori , Janssen Emilius A.M. , Egevad Lars , Kartasalo Kimmo , Eklund Martin
Published: July 2024

Histopathological evaluation of prostate biopsies using the Gleason scoring system is critical for prostate cancer diagnosis and treatment selection. However, grading variability among pathologists can lead to inconsistent assessments, risking inappropriate treatment. Similar challenges complicate the assessment of other prognostic features like cribriform cancer morphology and perineural invasion. Many pathology departments are also facing an increasingly unsustainable workload due to rising prostate cancer incidence and a decreasing pathologist workforce coinciding with increasing requirements for more complex assessments and reporting.

Digital pathology and artificial intelligence (AI) algorithms for analysing whole slide images (WSI) show promise in improving the accuracy and efficiency of histopathological assessments. Studies have demonstrated AI’s capability to diagnose and grade prostate cancer comparably to expert pathologists. However, external validations on diverse data sets have been limited and often show reduced performance. Historically, there have been no well-established guidelines for AI study designs and validation methods. Diagnostic assessments of AI systems often lack pre-registered protocols and rigorous external cohort sampling, essential for reliable evidence of their safety and accuracy.

This study protocol covers the retrospective validation of an AI system for prostate biopsy assessment. The primary objective of the study is to develop a high-performing and robust AI model for diagnosis and Gleason scoring of prostate cancer in core needle biopsies, and at scale evaluate whether it can generalise to fully external data from independent patients, pathology laboratories, and digitalisation platforms. The secondary objectives cover AI performance in estimating cancer extent and in detecting cribriform prostate cancer and perineural invasion. This protocol outlines the steps for data collection, predefined partitioning of data cohorts for AI model training and validation, model development, and predetermined statistical analyses, ensuring systematic development and comprehensive validation of the system. The protocol adheres to TRIPOD+AI, PIECES, CLAIM, and other relevant best practices.
Publication trend, impact and performance in mental health during and post COVID-19 pandemic
Authors: Bahar Nurhidayah , Nor Rashid Fadilla ‘Atyka , Ahmad Nor Diana
Published: July 2024

This study presents a bibliometric analysis of publications on mental health during and post-COVID-19 pandemic in Malaysia. The dataset comprises 167 documents retrieved from the Scopus database covering the period from 2020 to 2022. Using the open-source tool Bibliometrix for science mapping analysis, we examined various aspects of these publications, including document type, number of articles, total citations, most relevant sources, source impact, most relevant authors, affiliations, globally cited documents, and a word cloud. Our findings reveal a significant and continuous growth in mental health-related publications since the onset of the pandemic in 2020, highlighting an intensified focus on this critical area. This surge in research emphasizes the heightened importance of understanding and addressing mental health issues exacerbated by the pandemic. By providing a comprehensive summary of the bibliometric data, this study enhances our understanding of publication trends and the evolving landscape of mental health research, offering valuable insights for researchers, policymakers, and practitioners aiming to respond to mental health challenges in the post-pandemic era.
The reliability and validity of a non-wearable indoor positioning system to assess mobility in older adults: A cross-sectional study
Authors: Rodrigues Isabel B. , Hewston Patricia , Adachi Jonathan , Borhan Sayem , Ioannidis George , Kouroukis Alexa , Leckie Carolyn , Lee Andrea , Rabinovich Alexander , Siva Parthipan , Swance Rachel , Tariq Suleman , Thabane Lehana , Papaioannou Alexandra
Published: July 2024

Background

Chirp is a privacy-preserving radar sensor developed to continuously monitor older adults’ safety and mobility without the need for cameras or wearable devices. Our study purpose was to evaluate the inter-sensor reliability, intrasession test-retest reliability, and concurrent validity of Chirp in a clinical setting.

Methods

We recruited 35 community-dwelling older adults (mean age 75.5 (standard deviation: 6.6) years, 86% female). All participants lived alone in an urban city in southwestern Ontario and had access to a smart device with wireless internet. Data were collected with a 4-meter ProtoKinetics Zeno™ Walkway (pressure sensors) with the Chirp sensor (radar positioning) at the end of the walkway. Participants walked during normal and adaptive locomotion experimental conditions (walking-while-talking, obstacle, narrow walking, fast walking). Each of the experimental conditions was conducted twice in a randomized order, with fast walking trials performed last. For intra-session reliability testing, we conducted two blocks of walks within a participant session separated by approximately 30 minutes. Intraclass Correlation Coefficient(A,1)(ICC(A,1)) was used to assess the reliability and validity. Linear regression, adjusted for gender, was used to investigate the association between Chirp and cognition and health-related quality of life scores.

Results

The Chirp inter-sensor reliability ICC(A,1)=0.999[95% Confidence Interval [CI]: 0.997 to 0.999] and intrasession test-retest reliability [ICC(A,1)=0.921, 95% CI: 0.725 to 0.969] were excellent across all experimental conditions. Chirp concurrent validity compared to the ProtoKinetics Zeno™ Walkway was excellent across experimental conditions [ICC(A,1)= 0.993, 95% CI: 0.985 to 0.997]. We found a weak association between Chirp and cognition scores using the Montreal Cognitive Assessment across experimental conditions (estimated β-value= 7.79, 95% CI: 2.79 to 12.80) and no association between the Chirp and health-related quality of life using the 12-item Short Form Survey across experimental conditions (estimated β-value=6.12, 95% CI: -7.12 to 19.36).

Conclusion

Our results demonstrate that Chirp is a reliable and valid measure to assess gait parameters in clinics among older adults.
Breaking free from references: a consensus-based approach for community profiling with long amplicon nanopore data
Authors: Stock Willem , Rousseau Coralie , Dierickx Glen , D’hondt Sofie , Martínez Luz Amadei , Dittami Simon M , van der Loos Luna , Clerck Olivier De
Published: July 2024

Third-generation sequencing platforms, such as Oxford Nanopore Technology (ONT), have made it possible to characterise communities through the sequencing of long amplicons. Whilst this theoretically allows for an increased taxonomic resolution compared to short-read sequencing platforms such as Illumina, the high error rate remains problematic to accurately identify the community members present within a sample. Here we present and validate CONCOMPRA, a tool that allows the detection of closely related strains within a community by drafting and mapping to consensus sequences. We show that CONCOMPRA outperforms several other tools for profiling bacterial communities using full-length 16S rRNA gene sequencing. Since CONCOMPRA does not rely on a sequence database for profiling communities, it is applicable to systems and amplicons for which a reference framework is poorly developed. Our validation test shows that the amplification of long PCR products is likely to produce chimeric byproducts that inflate alpha diversity and skew community structure, stressing the importance of chimera detection. CONCOMPRA is available on GitHub (https://github.com/willem-stock/CONCOMPRA).

Key points

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We introduce a reference free tool for (long) amplicon Oxford Nanopore sequencing data

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We show that it is capable of outperforming achieving a higher accuracy than preexisting tools

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Chimera detection and removal is an essential step in the processing of long amplicon Oxford Nanopore sequencing data
OQA : A question-answering dataset on orthodontic literature
Authors: Rousseau Maxime , Zouaq Amal , Huynh Nelly
Published: July 2024

Background

The near-exponential increase in the number of publications in orthodontics poses a challenge for efficient literature appraisal and evidence-based practice. Language models (LM) have the potential, through their question-answering fine-tuning, to assist clinicians and researchers in critical appraisal of scientific information and thus to improve decision-making.

Methods

This paper introduces OrthodonticQA (OQA), the first question-answering dataset in the field of dentistry which is made publicly available under a permissive license. A framework is proposed which includes utilization of PICO information and templates for question formulation, demonstrating their broader applicability across various specialties within dentistry and healthcare. A selection of transformer LMs were trained on OQA to set performance baselines.

Results

The best model achieved a mean F1 score of 77.61 (SD 0.26) and a score of 100/114 (87.72%) on human evaluation. Furthermore, when exploring performance according to grouped subtopics within the field of orthodontics, it was found that for all LMs the performance can vary considerably across topics.

Conclusion

Our findings highlight the importance of subtopic evaluation and superior performance of paired domain specific model and tokenizer.
Large Language Models forecast Patient Health Trajectories enabling Digital Twins
Authors: Makarov Nikita , Bordukova Maria , Rodriguez-Esteban Raul , Schmich Fabian , Menden Michael P.
Published: July 2024

Background

Generative artificial intelligence (AI) accelerates the development of digital twins, which enable virtual representations of real patients to explore, predict and simulate patient health trajectories, ultimately aiding treatment selection and clinical trial design. Recent advances in forecasting utilizing generative AI, in particular large language models (LLMs), highlights untapped potential to overcome real-world data (RWD) challenges such as missingness, noise and limited sample sizes, thus empowering the next generation of AI algorithms in healthcare.

Methods

We developed the Digital Twin - Generative Pretrained Transformer (DT-GPT) model, which utilizes biomedical LLMs using rich electronic health record (EHR) data. Our method eliminates the need for data imputation and normalization, enables forecasting of clinical variables, and preliminary explainability through a human-interpretable interface. We benchmarked DT-GPT on RWD including long-term US nationwide non-small cell lung cancer (NSCLC) and short-term Intensive Care Unit (ICU) datasets.

Findings

DT-GPT surpassed state-of-the-art machine learning methods in patient trajectory forecasting on mean absolute error (MAE) for both the long-term (3.4% MAE improvement) and the short-term (1.3% MAE improvement) dataset. Additionally, DT-GPT was capable of preserving cross-correlations of clinical variables (average R2of 0.98), handling data missingness and noise. Finally, we discovered the ability of DT-GPT to provide insights into a forecast’s rationale and to perform zero-shot forecasting on variables not used during fine-tuning, outperforming even fully trained task-specific machine learning models on 13 clinical variables.

Interpretation

DT-GPT demonstrates that LLMs can serve as a robust medical forecasting platform, empowering digital twins which virtually replicate patient characteristics beyond their training data. We envision that LLM-based digital twins will enable a variety of use cases, including clinical trial simulations, treatment selection and adverse event mitigation.
Investigating associations between physical multimorbidity clusters and subsequent depression: cluster and survival analysis of UK Biobank data
Authors: DeLong Lauren Nicole , Fleetwood Kelly , Prigge Regina , Galdi Paola , Guthrie Bruce , Fleuriot Jacques D.
Published: July 2024

Background

Multimorbidity, the co-occurrence of two or more conditions within an individual, is a growing challenge for health and care delivery as well as for research. Combinations of physical and mental health conditions are highlighted as particularly important. The aim of this study was to investigate associations between physical multimorbidity and subsequent depression.

Methods and Findings

We performed a clustering analysis upon physical morbidity data for UK Biobank participants aged 37-73 years at baseline data collection between 2006-2010. Of 502,353 participants, 142,005 had linked general practice data with at least one physical condition at baseline. Following stratification by sex (77,785 women; 64,220 men), we used four clustering methods (agglomerative hierarchical clustering, latent class analysis,k-medoids andk-modes) and selected the best-performing method based on clustering metrics. We used Fisher’s Exact test to determine significant over-/under-representation of conditions within each cluster. Amongst people with no prior depression, we used survival analysis to estimate associations between cluster-membership and time to subsequent depression diagnosis.

Thek-modes models consistently performed best, and the over-/under-represented conditions in the resultant clusters reflected known associations. For example, clusters containing an overrepresentation of cardiometabolic conditions were amongst the largest clusters in the whole cohort (15.5% of participants, 19.7% of women, 24.2% of men). Cluster associations with depression varied from hazard ratio (HR) 1.29 (95% confidence interval (CI) 0.85-1.98) to HR 2.67 (95% CI 2.24-3.17), but almost all clusters showed a higher association with depression than those without physical conditions.

Conclusions

We found that certain groups of physical multimorbidity may be associated with a higher risk of subsequent depression. However, our findings invite further investigation into other factors, like social ones, which may link physical multimorbidity with depression.
The Prevalence and Factors Associated with Utilisation of Malaria Preventive Measures among Long Distance Travellers at Maunyamo Harbour in Mongu, Western Province of Zambia. A Cross-Sectional Study
Authors: Chingumbe Inambao , Mooka Larry Lubinda , Nawa Mukumbuta
Published: July 2024

Introduction

Malaria is a significant public health concern in Zambia. Travelling is associated with exposure to different strains of malaria parasites whilst the use of preventive measures is not well documented among Zambia travellers. The Barotse flood plains in the upper Zambezi region with its swampy areas play a significant role in malaria transmission in the Western Province of Zambia. This study assessed the prevalence and factors associated with the utilisation of malaria preventive measures among long-distance travellers at Maunyamo harbour in Mongu district of Western Province.

Methods

This was a cross-sectional study design which targeted long-distance travellers from the Barotse flood plains who come to Mongu the capital and central business hub of Western Province. A sample size of 171 participants was selected using simple random sampling. Data was collected through a structured questionnaire with closed questions. Data was summarised using descriptive statistics such as frequency, percentages, and cross-tabulations with comparisons using Chi-Square or Fisher’s Exact test. Further, associations between the outcome variable and dependent variables were tested using univariate and multivariable logistic regression. A P-value of 0.05 was significant.

Results

A total of 171 respondents were included in the study, males 50.9% (87/171) and females 49.1% (84/171) were equally represented. A majority 74% (126/171) of participants were aware of malaria preventive measures, however, few actually used the conventional preventive measures such as mosquito repellents (43%), ITNs (19%), IRS (12%), and mosquito coils (5%) while a sizable number used unconventional means such as cutting and burning shrubs (18%). Factors associated with the use of conventional preventive measures included awareness of mosquito repellents as a preventive measure aOR 1.97 (P value < 0.001), whilst the younger age group of 21 – 25 years aOR 0.21 (P value 0.022) were significantly associated with less use of preventive measures compared to those aged 26 years and older. Factors such as sex, education levels and duration in business were not statistically significant.

Conclusion

Awareness of malaria preventive measures among long-distance travellers was relatively high but utilisation was much lower indicating a mismatch between knowledge and utilisation. Awareness of specific preventive measures such as mosquito repellents was associated with a higher utilisation rate whilst the younger age group was associated with lower utilisation. Socioeconomic factors like sex, education and duration were not statistically significant.
Validation of the Hospital Anxiety and Depression Scale in Patients with Decompensated Cirrhosis
Authors: Zeng Chengbo , Donlan John , Indriolo Teresa , Li Lucinda , Zhu Enya , Zhou Joyce C. , Armstrong Malia E. , Pintro Kedie , Horick Nora , Chung Raymond T. , EI-Jawahri Areej , Edelen Maria O. , Ufere Nneka N.
Published: July 2024

Background

The Hospital Anxiety and Depression Scale (HADS) demonstrates strong psychometric properties in many populations of patients with serious illness. However, its psychometric performance among patients with decompensated cirrhosis (DC) has not been examined. We investigated the reliability, validity, and responsiveness of the HADS for patients with DC.

Methods

This observational study utilized data from patients with DC at enrollment and week 6 follow-up. Two hundred eighteen outpatients with DC were recruited from a liver transplant center, with 145 completing week 6 assessment. We evaluated psychological distress using HADS and Patient Health Questionnaire 9 (PHQ-9). Patients’ health-related quality of life (HRQOL) was assessed using the Short-Form Liver Disease Quality of Life questionnaire. We examined reliability, floor/ceiling effects, structural validity, and known-groups validity for anxiety (HADS-Anxiety) and depression (HADS-Depression) subscales. We assessed the convergent validity with the PHQ-9. We predicted the change in HRQOL using the change in depression and anxiety. We also evaluated the internal responsiveness to changes in HRQOL for both HADS-Anxiety and HADS-Depression from baseline to week 6.

Results

The HADS-Anxiety and HADS-Depression subscales showed strong internal consistency (Cronbach’s alpha>0.8), adequate floor/ceiling effects (<15%), and excellent convergent validity with PHQ-9 (r>0.7). Both domains significantly predicted the changes in HRQOL longitudinally. Both HADS-Anxiety (1.8 [95% confidence interval [CI]: 0.5, 3.2]) and HADS-Depression (2.2 [95%CI: 1, 3.4]) showed responsiveness in patients with decreased HRQOL.

Conclusions

The HADS is a reliable, valid, responsive tool for assessing anxiety and depression among patients with DC.
Machine learning is more accurate and biased than risk scoring tools in the prediction of postoperative atrial fibrillation after cardiac surgery
Authors: Ho Joyce C , Joshi Shalmali , Valverde Eduardo , Wood Kathryn , Grubb Kendra , Leal Miguel , Hertzberg Vicki Stover
Published: July 2024

Incidence of postoperative atrial fibrillation (POAF) after cardiac surgery remains high and is associated with adverse patient outcomes. Risk scoring tools have been developed to predict POAF, yet discrimination performance remains moderate. Machine learning (ML) models can achieve better performance but may exhibit performance heterogeneity across race and sex subpopulations. We evaluate 8 risk scoring tools and 6 ML models on a heterogeneous cohort derived from electronic health records. Our results suggest that ML models achieve higher discrimination yet are less fair, especially with respect to race. Our findings highlight the need for building accurate and fair ML models to facilitate consistent and equitable assessment of POAF risk.
MENSA, a Media Enriched with Newly Synthesized Antibodies, to Identify SARS-CoV-2 Persistence and Latent Viral Reactivation in Long-COVID
Authors: Haddad Natalie S. , Morrison-Porter Andrea , Quehl Hannah , Capric Violeta , Lamothe Pedro A. , Anam Fabliha , Runnstrom Martin C. , Truong Alex D. , Dixit Adviteeya N. , Woodruff Matthew C. , Chen Anting , Park Jiwon , Nguyen Doan C. , Hentenaar Ian , Kim Caroline Y. , Kyu Shuya , Stewart Brandon , Wagman Elizabeth , Geoffroy Hannah , Sanz Daniel , Cashman Kevin S. , Ramonell Richard P. , Cabrera-Mora Monica , Alter David N. , Roback John D. , Horwath Michael C. , O’Keefe James B. , Dretler Alexandra W. , Gripaldo Ria , Yeligar Samantha M. , Natoli Ted , Betin Viktoria , Patel Rahulkumar , Vela Kennedy , Hernandez Mindy Rodriguez , Usman Sabeena , Varghese John , Jalal Anum , Lee Saeyun , Le Sang N. , Toby Amoss R. , Daiss John L. , Sanz Ignacio , Lee F. Eun-Hyung
Published: July 2024

Post-acute sequelae of SARS-CoV-2 (SARS2) infection (PASC) is a heterogeneous condition, but the main viral drivers are unknown. Here, we use MENSA, Media Enriched with Newly Synthesized Antibodies, secreted exclusively from circulating human plasmablasts, to provide an immune snapshot that defines the underlying viral triggers. We provide proof-of-concept testing that the MENSA technology can capture the new host immune response to accurately diagnose acute primary and breakthrough infections when known SARS2 virus or proteins are present. It is also positive after vaccination when spike proteins elicit an acute immune response. Applying the same principles for long-COVID patients, MENSA is positive for SARS2 in 40% of PASC vs none of the COVID recovered (CR) patients without any sequelae demonstrating ongoing SARS2 viral inflammation only in PASC. Additionally, in PASC patients, MENSAs are also positive for Epstein-Barr Virus (EBV) in 37%, Human Cytomegalovirus (CMV) in 23%, and herpes simplex virus 2 (HSV2) in 15% compared to 17%, 4%, and 4% in CR controls respectively. Combined, a total of 60% of PASC patients have a positive MENSA for SARS2, EBV, CMV, and/or HSV2. MENSA offers a unique antibody snapshot to reveal the underlying viral drivers in long-COVID thus demonstrating the persistence of SARS2 and reactivation of viral herpes in 60% of PASC patients.

Graphical abstract
Trends in Violence Against Women in Morocco: An Analysis of National Surveys from 2009 to 2020
Authors: Wafqui Fatima-Ezzahraa , Yahyane Abdelhakim , Bouaddi Oumnia , Rhajbal Zineb , Khalis Mohamed
Published: July 2024

Violence Against Women (VAW) remains a significant challenge in Morocco despite major advances in legislative framework and policy initiatives.

Objective

This study aims to investigate the trends of VAW in Morocco including its forms, contexts in which it occurs and the socio-demographic characteristics of victims over a 10-year period from 2009 to 2020.

Methods

We conducted an online search for official publicly available, open access national reports and surveys about VAW in Morocco, published in the period between 2009-2020. We identified Five official reports. We collected data on prevalence of VAW, profiles of the victims, its forms and contexts.

Results

From 2009 to 2020, the overall prevalence of VAW has consistently exceeded the 50% mark with 62.80% in 2009 vs 58.2% in 2020. Although it has seen a decrease, the highest prevalence of VAW was reported among married females belonging to younger age groups, with high levels of education 75.3% in 2009 vs 62.7% in 2019. Intimate partner violence, both marital and extra-marital was the most common context where VAW occurred across the ten-year period (55% and 47.4% in 2009 respectively vs 52,5% for marital violence in 2020 and 27.7% for extra marital violence in 2019). Marital or spousal violence ranged from 38.4% among non-single women to more than 80% among victims admitted to integrated care units in 2011, 2012, and 2013. Psychological violence stood out as the most common form of violence across the years, while violence in public spaces has seen a steady decrease over the years. Electronic or cyber violence was only studied in one survey and was estimated at 4.5%.

Conclusion

Despite legislative advancements, VAW remains a complex issue in Morocco, with significant prevalence requiring sustained efforts to address this issue comprehensively. Education and empowerment initiatives, alongside strengthening the implementation of the law and addressing barriers to reporting, are crucial for combating VAW effectively in Morocco.
Accurate diagnosis achieved via super-resolution whole slide images by pathologists and artificial intelligence
Authors: Wang Kuansong , Liu Ruijie , Chen Yushi , Wang Yin , Gao Yanhua , Qiu Yanning , Zhou Maoxu , Bai Bingqian , Zhang Mingxing , Sun Kai , Deng Hongwen , Xiao Hongmei , Yu Gang
Published: July 2024

Background

Digital pathology significantly improves diagnostic efficiency and accuracy; however, pathological tissue sections are scanned at high resolutions (HR), magnified by 40 times (40X) incurring high data volume, leading to storage bottlenecks for processing large numbers of whole slide images (WSIs) for later diagnosis in clinic and hospitals.

Method

We propose to scan at a magnification of 5 times (5X). We developed a novel multi-scale deep learning super-resolution (SR) model that can be used to accurately computes 40X SR WSIs from the 5X WSIs.

Results

The required storage size for the resultant data volume of 5X WSIs is only one sixty-fourth (less than 2%) of that of 40X WSIs. For comparison, three pathologists used 40X scanned HR and 40X computed SR WSIs from the same 480 histology glass slides spanning 47 diseases (such tumors, inflammation, hyperplasia, abscess, tumor-like lesions) across 12 organ systems. The results are nearly perfectly consistent with each other, with Kappa values (HR and SR WSIs) of 0.988±0.018, 0.924±0.059, and 0.966±0.037, respectively, for the three pathologists. There were no significant differences in diagnoses of three pathologists between the HR and corresponding SR WSIs, with Area under the Curve (AUC): 0.920±0.164 vs. 0.921±0.158 (p-value=0.653), 0.931±0.128 vs. 0.943±0.121 (p-value=0.736), and 0.946±0.088 vs. 0.941±0.098 (p-value=0.198). A previously developed highly accurate colorectal cancer artificial intelligence system (AI) diagnosed 1,821 HR and 1,821 SR WSIs, with AUC values of 0.984±0.016 vs. 0.984±0.013 (p-value=0.810), again with nearly perfect matching results.

Conclusions

The pixel numbers of 5X WSIs is only less than 2% of that of 40X WSIs. The 40X computed SR WSIs can achieve accurate diagnosis comparable to 40X scanned HR WSIs, both by pathologists and AI. This study provides a promising solution to overcome a common storage bottleneck in digital pathology.
Developmental encoding of ultrasound vocalizations in the mouse auditory cortex
Authors: Zucca Stefano , La Rosa Chiara , Fellin Tommaso , Peretto Paolo , Bovetti Serena
Published: July 2024

Mice communicate through high-frequency ultrasound vocalizations (USVs), which are crucial for social interactions such as courtship and aggression. Although USV representation has been found in adult brain areas along the auditory pathway, including the auditory cortex (ACx), no evidence is available on the neuronal representation of USVs early in life. Using in vivo two-photon calcium imaging, we analyzed ACx layer 2/3 neuronal responses to USVs, pure tones (4-90 kHz), and high-frequency modulated sweeps from postnatal day 12 (P12) to P21. We found that ACx neurons are tuned to respond to USV syllables as early as P12-P13, with an increasing number of responsive cells as the mouse age. By P14, while pure tone responses showed a frequency preference, no syllable preference was observed. Additionally, at P14, USVs, pure tones, and modulated sweeps activate clusters of largely non-overlapping responsive neurons. Finally, we show that while cell correlation decreases with increasing processing of peripheral auditory stimuli, neurons responding to the same stimulus maintain highly correlated spontaneous activity after circuits have attained mature organization, forming neuronal sub-networks sharing similar functional properties.
Spatial organization of PI3K-PI(3,4,5)P3-AKT signaling by focal adhesions
Authors: Wang Jing , An Zhengyang , Wu Zhongsheng , Zhou Wei , Sun Pengyu , Wu Piyu , Xue Rui , Dang Song , Bai Xue , Wang Wenxu , Chen Rongmei , Du Yongtao , Huang Pei , Lam Sin Man , Ai Youwei , Liu Suling , Shui Guanghou , Zhang Zhe , Liu Zheng , Huang Jianyong , Fang Xiaohong , He Kangmin
Published: July 2024

The class I PI3K-AKT signaling pathway is the master regulator of cell survival, growth, and proliferation, and among the most frequently mutated pathways in cancer. However, where and how the PI3K-AKT signaling is spatially activated and organized in mammalian cells remain poorly understood. Here, we identified focal adhesions (FAs) as the subcellular signaling hubs organizing the activation of PI3K-PI(3,4,5)P3-AKT signaling in mammalian cells. We found that class IA PI3Ks are preferentially and dynamically recruited to FAs for activation, resulting in localized production of the critical signaling lipid PI(3,4,5)P3around FAs. As the effector protein of PI(3,4,5)P3, AKT molecules are dynamically recruited around FAs for activation. Mechanistically, the spatial recruitment/activation of PI3K-PI(3,4,5)P3-AKT cascade are regulated by the activated FAK. Furthermore, combined inhibition of class I PI3K and FAK results in a more potent inhibitory effect on cancer cells. Thus, our results unveil a growth-factor independent, compartmentalized organization mechanism for PI3K-PI(3,4,5)P3-AKT signaling.
“Target-and-release” nanoparticles for effective immunotherapy of metastatic ovarian cancer
Authors: Pires Ivan S. , Covarrubias Gil , Gomerdinger Victoria F. , Backlund Coralie , Shanker Apoorv , Gordon Ezra , Wu Shengwei , Pickering Andrew J. , Melo Mariane B. , Suh Heikyung , Irvine Darrell J. , Hammond Paula T.
Published: July 2024

Immunotherapies such as checkpoint inhibitors (CPI) are effective in treating several advanced cancers, but these treatments have had limited success in metastatic ovarian cancer (OC). Here, we engineered liposomal nanoparticles (NPs) carrying a layer-by-layer (LbL) polymer coating that promotes their binding to the surface of OC cells. Covalent anchoring of the potent immunostimulatory cytokine interleukin-12 (IL-12) to phospholipid headgroups of the liposome core enabled the LbL particles to concentrate IL-12 in disseminated OC tumors following intraperitoneal administration. Shedding of the LbL coating and serum protein-mediated extraction of IL-12-conjugated lipids from the liposomal core over time enabled IL-12 to disseminate in the tumor bed following rapid NP localization in tumor nodules. Optimized IL-12 LbL-NPs promoted robust T cell accumulation in ascites and tumors in mouse models, extending survival compared to free IL-12 and remarkedly sensitizing tumors to CPI, leading to curative treatments and immune memory.
Ultra-resolution Deconvolution of Spatial Transcriptomics Unveils Spatiotemporal Cellular Dynamics in Complex Microenvironments
Authors: Xu Yin , Huang Zurui , Zhang Yawei , Wang Zhenghang , Guo Peijin , Zhang Feifan , Gong Wenxuan , Liang Guanghao , Mei Boyuan , Dong Lihui , Chang Renbao , Gong Minghui , Xia Yu , Ni Haochen , Yang Jing , Gao Yuan , Liu Zhaoqi , Shen Lin , Li Jian , Xu Meng Michelle , Han Dali
Published: July 2024

The current challenge in analyzing sequencing-based spatial transcriptomics (ST) is to precisely resolve the spatial distribution of cell subpopulations with low abundance and detect context-dependent variation in cell states within complex tissue microenvironments. Here, we introduce an ultra-resolution ST deconvolution algorithm (UCASpatial) that improves the resolution of mapping cell subpopulations to spatial locations by leveraging the contribution of genes indicative of cell identity through entropy-based weighting. Using both in silico and real ST datasets, we demonstrate that UCASpatial improves the robustness and accuracy in identifying low-abundant cell subpopulations and distinguishing transcriptionally heterogeneous cell subpopulations. Applying UCASpatial to murine wound healing, we recapitulate known spatiotemporal dynamics of multiple cell subpopulations involved in wound healing and reveal the spatial segregation of distinct macrophage subpopulations embedded within different cellular communities at the wound center. In human colorectal cancer (CRC), we link genomic alterations in individual cancer clones to multi-cellular characteristics of the tumor immune microenvironment (TIME) and reveal the co-evolution of tumor cells and TIME within the same tumor. We show that the copy number gain on chromosome 20q (chr20q-gain) in tumor cells orchestrates a T cell-excluded TIME, indicative of resistance to immunotherapy in CRC, and is associated with tumor-intrinsic endogenous retrovirus silencing and impaired type I interferon response. Our findings present UCASpatial as a versatile tool for deciphering ultra-resolution cellular landscapes in ST and exploring intercellular mechanisms in complex and dynamic microenvironments.
SOFisher: Reinforcement Learning-Guided Experiment Designs for Spatial Omics
Authors: Li Zhuo , Wu Weiran , Cui Yan , Sun Jian , Yuan Zhiyuan
Published: July 2024

Spatial omics technologies enable the precise detection of proteins and RNAs at high spatial resolution. Designing spatial omics experiments requires careful consideration of “what” targets to measure and “where” to position the field of views (FOVs). Current FOV sampling strategies often involve acquiring densely sampled FOVs and stitching them together, which is time-consuming, resource-intensive, and sometimes impossible. To optimize FOV sampling strategies, we developed SOFisher, a reinforcement learning-based framework that harnesses the knowledge gained from the sequence of previously sampled FOVs to guide the selection of the next FOV position, to improve the efficiency of capturing more regions of interest. We rigorously evaluated SOFisher’s performance using comprehensive simulations based on real spatial datasets, and our results clearly demonstrated that SOFisher consistently outperformed the conventional approach across various metrics. SOFisher’s robustness and generalizability were further validated through cross-domain generalization tests and its adaptability to varying FOV sizes. On a real Alzheimer’s Disease (AD) dataset, SOFisher successfully guided the selection of FOVs containing neurofibrillary tangles and amyloid-β plaques in both single and dual target tissue landmark scenarios. Remarkably, SOFisher-guided experiment design of spatial single-omics on limited tissue areas yielded insights into AD-related cell states, subtypes, and gene programs previously obtained through extensive spatial multi-omics experiments. SOFisher has the potential to revolutionize the experiment design of spatial biology.
Novel single-cell preservation and RNA sequencing technology unlocks field studies forPlasmodiumnatural infections
Authors: Sauve Erin , Monsieurs Pieter , Guetens Pieter , de Moraes Barros Roberto Rudge , Rosanas-Urgell Anna
Published: July 2024

Single-cell RNA sequencing (scRNA-seq) is a powerful technology used to investigate cellular heterogeneity. When applied to unicellular eukaryotes such asPlasmodiumparasites, scRNA-seq provides a single-cell resolution particularly valuable to study complex infections which are often comprised of mixed life stages and clones. Until now, the application of scRNA-seq has been mainly limited toin vitroand animal malaria models, despite known transcriptional differences as compared to circulating parasite populations. This is primarily due to the challenges of working withPlasmodiumnatural infections in endemic settings. We validated sample preparation methods and a novel single-cell RNA sequencing technology for the first time inP. knowlesiparasites which can be effectively implemented to analyze natural infections in low-resource settings. We recovered 22,345P. knowlesisingle-cell transcriptomes containing all asexual blood stages from 6in vitroculture samples, with conditions mimicking natural infections, and generated the most extensiveP. knowlesisingle-cell dataset to date. All 6 samples produced reproducible circular UMAP projections with consistent cluster localization and high gene expression correlation, regardless of the sample preparation methods used. Biomarker expression and life stage annotation using the Malaria Cell AtlasP. knowlesireference dataset further confirmed these results. In conclusion, the combination of adaptable sample preparation methods with novel preservation and scRNA-seq technology has the potential to fundamentally transform the study of natural infections. This approach unlocks the use of scRNA-seq in field studies which will lead to new insights intoPlasmodiumparasite biology.

Importance

Sequencing unicellular organisms, such as malaria parasites, at the single-cell level is important to understand the diversity present in cell populations. Until now, single-cell sequencing of malaria has been primarily limited to laboratory models. While these models are key to understanding biological processes, there are known differences between lab models and parasite populations circulating in natural human infections. This study presents sample preparation methods and a new single-cell RNA sequencing technology that enables sample collection from natural infections in low-resource settings. Using a mock natural infection, we validated this new single-cell RNA sequencing technology using marker genes with known expression patterns and a reference dataset from the Malaria Cell Atlas. We demonstrate that high-quality single-cell transcriptomes with consistent expression patterns can be recovered using various sample preparation methods, thereby unlocking single-cell sequencing for field studies and leading to additional insights into parasite biology in the future.
Organizational principles of the primate cerebral cortex at the single-cell level
Authors: Chen Renrui , Nie Pengxing , Ma Liangxiao , Wang Guang-Zhong
Published: July 2024

The primate cerebral cortex, the major organ for cognition, consists of an immense number of neurons. However, the organizational principles governing these neurons remain unclear. By accessing the single-cell spatial transcriptome of over 25 million neuron cells across the entire macaque cortex, we discovered that the distribution of neurons within cortical layers is highly non-random. Strikingly, over three-quarters of these neurons are located in distinct neuronal clusters. Within these clusters, different cell types tend to collaborate rather than function independently. Typically, excitatory neuron clusters mainly consist of excitatory-excitatory combinations, while inhibitory clusters primarily contain excitatory-inhibitory combinations. Both cluster types have roughly equal numbers of neurons in each layer. Importantly, most excitatory and inhibitory neuron clusters form spatial partnerships, indicating a balanced local neuronal network and correlating with specific functional regions. These findings suggest that different brain regions of the primate cortex may exhibit similar mechanisms at the neuronal population level.