bluuebunny/crossref_metadata_2025 huggingface dataset:
Blocking uncertain mispriming errors of PCR
Authors: Takahashi Takumi , Aoyanagi Hiroyuki , Pigolotti Simone , Toyabe Shoichi
Published: April 2024

The polymerase chain reaction (PCR) plays a central role in genetic engineering and is routinely used in various applications, from biological and medical research to the diagnosis of viral infections. PCR is an extremely sensitive method for detecting target DNA sequences, but it is substantially error-prone. In particular, the mishybridization of primers to contaminating sequences can result in false positives for virus tests. The blocker method, also called the clamping method, has been developed to suppress mishybridization errors. However, its application is limited by the requirement that the contaminating template sequence must be known in advance. Here, we demonstrate that a mixture of multiple blocker sequences effectively suppresses the amplification of contaminating sequences even in the presence of uncertainty. The blocking effect was characterized by a simple model validated by experiments. Furthermore, the modeling allowed us to minimize the errors by optimizing the blocker concentrations. The results highlighted an inherent robustness of the blocker method, in that fine-tuning of the blocker concentrations is not necessary. Our method extends the applicability of PCR and other hybridization-based techniques, including genome editing, RNA interference, and DNA nanotechnology, by improving their fidelity.

Significance

The applications of PCR are increasing day by day, and there is a need to suppress PCR errors to improve the accuracy of PCR-based techniques and broaden their applicability. The blocker method has been developed to substantially suppress mispriming. However, the method requires prior knowledge of the contaminating sequence, which limits its applicability. We successfully demonstrate that adding a combination of multiple blocker sequences can substantially suppress PCR errors, even when we have only partial information about the contaminating sequences. We also construct a biophysical model of the blocking effect, which allows us to find the optimal blocker combinations that minimize the PCR error. Since the method targets hybridization, it is readily applicable to a wide range of biotechnologies.
Antigen affinity and site of immunization dictate B cell recall responses
Authors: Termote M. , Marques R. C. , Hyllner E. , Guryleva M. V. , Henskens M. , Brutscher A. , Baken I.J.L. , Dopico X. Castro , Gasull A. Dalmau , Murrell B. , Stamatatos L. , Westerberg L. S. , Dosenovic P.
Published: April 2024

Protective antibodies against HIV-1 require unusually high levels of somatic hypermutations (SHMs) introduced in germinal centers (GCs). To achieve this, a sequential vaccination approach was proposed. Using HIV-1 antibody knock-in mice with fate-mapping genes, we examined if antigen affinity affects the outcome of the B cell recall response. Compared to high affinity boost, low affinity boost resulted in decreased numbers of memory-derived B cells in secondary GCs, but with higher average SHM, indicating an affinity threshold for memory B cells to enter secondary GCs. Upon boosting local LNs, numbers of residual GC B cells increased independent on antigen affinity, while average SHM decreased. Our results demonstrate that antigen affinity and location of the boost affect the outcome of the B cell recall response. These results can help guide the design of vaccine immunogens aiming to selectively engage specific B cell clones for further SHM diversification.
Evolving antibody response to SARS-CoV-2 antigenic shift from XBB to JN.1
Authors: Jian Fanchong , Wang Jing , Yisimayi Ayijiang , Song Weiliang , Xu Yanli , Chen Xiaosu , Niu Xiao , Yang Sijie , Yu Yuanling , Wang Peng , Sun Haiyan , Yu Lingling , Wang Jing , Wang Yao , An Ran , Wang Wenjing , Ma Miaomiao , Xiao Tianhe , Gu Qingqing , Shao Fei , Wang Youchun , Shen Zhongyang , Jin Ronghua , Cao Yunlong
Published: April 2024

The continuous evolution of SARS-CoV-2, particularly the emergence of the BA.2.86/JN.1 lineage replacing XBB lineages, necessitates re-evaluation of current vaccine compositions. Here, we provide a comprehensive analysis of the humoral immune response to XBB and JN.1 human exposures, emphasizing the need for JN.1-lineage-based boosters. We demonstrate the antigenic distinctiveness of XBB and JN.1 lineages in SARS-CoV-2-naive individuals but not in those with prior vaccinations or infections, and JN.1 infection elicits superior plasma neutralization titers against its subvariants. We highlight the strong immune evasion and receptor binding capability of KP.3, supporting its foreseeable prevalence. Extensive analysis of the BCR repertoire, isolating ∼2000 RBD-specific monoclonal antibodies (mAbs) with their targeting epitopes characterized by deep mutational scanning (DMS), underscores the systematic superiority of JN.1-elicited memory B cells (MBCs). Notably, Class 1 IGHV3-53/3-66-derived neutralizing antibodies (NAbs) contribute majorly within wildtype (WT)-reactive NAbs against JN.1. However, KP.2 and KP.3 evade a substantial subset of them, even those induced by JN.1, advocating for booster updates to KP.3 for optimized enrichment. JN.1-induced Omicron-specific antibodies also demonstrate high potency across all Omicron lineages. Escape hotspots of these NAbs have mainly been mutated in Omicron RBD, resulting in higher immune barrier to escape, considering the probable recovery of previously escaped NAbs. Additionally, the prevalence of broadly reactive IGHV3-53/3-66- encoding antibodies and MBCs, and their capability of competing with all Omicron-specific NAbs suggests their inhibitory role on the de novo activation of Omicron-specific naive B cells, potentially explaining the heavy immune imprinting in mRNA-vaccinated individuals. These findings delineate the evolving antibody response to Omicron antigenic shift from XBB to JN.1, and highlight the importance of developing JN.1 lineage, especially KP.3-based vaccine boosters, to enhance humoral immunity against current and future SARS-CoV-2 variants.
A disease similarity approach identifies short-lived Niemann-Pick type C disease mice with accelerated brain aging as a novel mouse model for Alzheimer’s disease and aging research
Authors: Gujjala Vikas Anil , Klimek Isaiah , Abyadeh Morteza , Tyshkovskiy Alexander , Oz Naci , Castro José Pedro , Gladyshev Vadim N. , Newton Jason , Kaya Alaattin
Published: April 2024

Since its first description in 1906 by Dr. Alois Alzheimer, Alzheimer’s disease (AD) has been the most common type of dementia. Initially thought to be caused by age-associated accumulation of plaques, in recent years, research has increasingly associated AD with lysosomal storage and metabolic disorders, and the explanation of its pathogenesis has shifted from amyloid and tau accumulation to oxidative stress and impaired lipid and glucose metabolism aggravated by hypoxic conditions. However, the underlying mechanisms linking those cellular processes and conditions to disease progression have yet to be defined. Here, we applied a disease similarity approach to identify unknown molecular targets of AD by using transcriptomic data from congenital diseases known to increase AD risk, namely Down Syndrome, Niemann Pick Disease Type C (NPC), and Mucopolysaccharidoses I. We uncovered common pathways, hub genes, and miRNAs acrossin vitroandin vivomodels of these diseases as potential molecular targets for neuroprotection and amelioration of AD pathology, many of which have never been associated with AD. We then investigated common molecular alterations in brain samples from an NPC disease mouse model by juxtaposing them with brain samples of both human and mouse models of AD. Detailed phenotypic and molecular analyses revealed that the NPCmutmouse model can serve as a potential short-livedin vivomodel for AD research and for understanding molecular factors affecting brain aging. This research represents the first comprehensive approach to congenital disease association with neurodegeneration and a new perspective on AD research while highlighting shortcomings and lack of correlation in diversein vitromodels. Considering the lack of an AD mouse model that recapitulates the physiological hallmarks of brain aging, the characterization of a short-lived NPC mouse model will further accelerate the research in these fields and offer a unique model for understanding the molecular mechanisms of AD from a perspective of accelerated brain aging.
Improving genomic selection in hexaploid wheat with sub-genome additive and epistatic models
Authors: Tessele Augusto , González-Diéguez David O. , Crossa Jose , Johnson Blaine E. , Morris Geoffrey P. , Fritz Allan K.
Published: April 2024

The goal of wheat breeding is the development of superior cultivars tailored to specific environments, and the identification of promising crosses is crucial for the success of breeding programs. Although genomic estimated breeding values were developed to estimate additive effects of genotypes before testing as parents, application has focused on predicting performance of candidate lines, ignoring non-additive genetic effects. However, non-additive genetic effects are hypothesized to be especially importance in allopolyploid species due to the interaction between homeologous genes. The objectives of this study were to model additive and additive-by-additive epistatic effects to better delineate the genetic architecture of grain yield in wheat and to the improve accuracy of genomewide predictions. The dataset utilized consisted of 3740 F5:6experimental lines tested in the K-State wheat breeding program across the years 2016 and 2018. Covariance matrices were calculated based on whole and sub-genome marker data and the natural and orthogonal interaction approach (NOIA) was used to estimate variance components for additive and additive-by-additive epistatic effects. Incorporating epistatic effects in additive models resulted in non-orthogonal partitioning of genetic effects but increased total genetic variance and reduced deviance information criteria. Estimation of sub-genome effects indicated that genotypes with the greatest whole genome effects often combine sub-genomes with intermediate to high effects, suggesting potential for crossing parental lines which have complementary sub-genome effects. Modeling epistasis in either whole-genome or sub-genome models led to a marginal (3%) but significant improvement in genomic prediction accuracy, which could result in significant genetic gains across multiple cycles of breeding.
InsulatedpiggyBacand FRT vectors for engineering transgenic homozygous and heterozygous eHAP cells
Authors: Minard Annabel Y , Winistorfer Stanley , Piper Robert C
Published: April 2024

Transgene expression in eHAP cells, a haploid cell line popularly used to generate gene knockouts, is difficult owing to its low transfection efficiency and propensity for silencing integrated transgenes. To simplify transgene expression, we engineered insulated integrating plasmids that sustain high levels of transgene expression in eHAP cells, and that can be used in other cell lines. These vectors are compatible with FLP-FRT andpiggyBacintegration, they flank a gene-of interest bilaterally with tandem cHS4 core insulators, and co-express nuclear-localized blue fluorescent protein for identification of high expressing cells. We further demonstrate that transgenic haploid eHAP cells can be fused to form transgenic heterozygous diploid cells. This method creates diploid cells carrying the transgenic material of the haploid progenitors and could also be used to create heterozygous cells of defined genotypes. These tools expand the repertoire of experiments that can be performed in eHAP cells and other cultured cells.
Modeling Normal and Imbalanced Neural Avalanches: A Computational Approach to Understanding Criticality in the Brain and Its Potential Role in Schizophrenia
Authors: Mongomery Richard Murdoch
Published: April 2024

Neural avalanches, characterized by bursts of activity followed by periods of quiescence, have been observed in the brain and are thought to reflect the critical dynamics necessary for optimal information processing. Deviations from normal avalanche behavior have been hypothesized to underlie various neurological disorders, particularly schizophrenia. Schizophrenia is a complex psychiatric disorder associated with altered perception, cognition, and behavior, and recent theories suggest that disruptions in the brain’s critical dynamics may contribute to its pathophysiology. In this study, we present a computational model to investigate the properties of normal and imbalanced neural avalanches, with a focus on understanding the potential role of criticality in schizophrenia. We generate avalanche sizes using the Pareto distribution with a power law exponent of -3/2, which is consistent with experimental observations. The model incorporates increasing avalanche sizes over time to simulate the growth of neural activity. We introduce imbalance by adding lateness or earliness to the avalanche sizes, mimicking the potential disruptions in critical dynamics that may occur in schizophrenia. The mean and standard deviation of avalanche sizes are calculated to characterize the normal and imbalanced behavior. The results are visualized using line plots, with shaded areas representing the standard deviation range. Our model provides a framework for understanding the differences between normal and imbalanced neural avalanches, offering insights into the potential mechanisms underlying the altered critical dynamics in schizophrenia. By exploring the relationship between neural avalanches and schizophrenia, this study contributes to the ongoing efforts to elucidate the neurobiological basis of this disorder and may inform future research on potential diagnostic markers and therapeutic interventions targeting the brain’s critical dynamics.
A scalable CRISPR-Cas9 gene editing system facilitates CRISPR screens in the malaria parasitePlasmodium berghei
Authors: Jonsdottir Thorey K. , Paoletta Martina S. , Ishizaki Takahiro , Hernandez Sophia , Ivanova Maria , Herrera Curbelo Alicia , Saiki Paulina A. , Selinger Martin , Das Debojyoti , Henriksson Johan , Bushell Ellen S.C.
Published: April 2024

ManyPlasmodiumgenes remain uncharacterised due to low genetic tractability. Previous large scale knockout screens have only been able to target about half of the genome in the more genetically tractable rodent malaria parasitePlasmodium berghei. To overcome this limitation, we have developed a scalable CRISPR system called PbHiT, which uses a single cloning step to generate targeting vectors with 100 bp homology arms physically linked to a guide RNA (gRNA) that effectively integrate into the target locus. We show that PbHiT coupled with gRNA sequencing robustly recapitulates known knockout mutant phenotypes in pooled transfections. Furthermore, we provide vector designs and sequences to target the entireP. bergheigenome and scale-up vector production using a pooled ligation approach. This work presents for the first time a tool for high-throughput CRISPR screens inPlasmodiumfor studying the parasite’s biology at scale.
PREVALENCE OF HUMAN AND ANIMAL AFRICAN TRYPANOSOMIASIS IN NIGERIA: A SCOPING REVIEW
Authors: Odebunmi Elizabeth O. , Ibeachu Chukwuemeka , Chukwudi Chinwe U.
Published: April 2024

Background

African trypanosomiasis continues to pose a substantial threat to both human and animal health in sub-Saharan Africa. This study examined the prevalence of African trypanosomiasis within human and animal populations in Nigeria, the trypanosome species involved, the spread of animal reservoirs, and the variability in diagnostic methodologies employed.

Methodology/principal findings

A scoping review was performed, following the methodological framework outlined in PRISMA-ScR checklist. Eligible studies were explored for disease prevalence, causative parasites, reservoir hosts, and diagnostic techniques used. A total of 16 eligible studies published between 1993 and 2021 were retrieved. 13 studies reported the prevalence of African trypanosomiasis in animals, and 3 for humans. Varying prevalence rates were recorded depending on the host population and diagnostic methods employed. The overall prevalence of Animal African Trypanosomiasis (AAT) and Human African Trypanosomiasis (HAT) was 27.3% (4,404/16,117) and 3.6% (72/1,974) respectively. The highest incidence of HAT was detected using the Card Agglutination Test for Trypanosomiasis (CATT), whereas that of AAT was observed using PCR, followed by microscopy which was the most extensively employed technique in this study. The various diagnostic methods used in various studies showed a variety of sensitivities and specificities, affecting the accuracy of disease detection. Remarkably, domestic animals like cattle, pigs, and dogs were identified as potential reservoirs for the human-infective parasites (T. b. gambiense)in Nigeria.

Conclusion

This study highlights the high prevalence rate and complex epidemiology of African trypanosomiasis in humans and animals in Nigeria. These findings underscore the importance of comprehensive measures involving both veterinary and human health sectors to combat African trypanosomiasis effectively in Nigeria. Only few studies have investigated the prevalence of HAT in Nigeria. Hence, adequately coordinated epidemiological surveys are imperative to ascertain the true epidemiological status of HAT in Nigeria and inform targeted intervention policies to achieve WHO’s NTD elimination targets in 2030.
GABA/Glutamate neuron differentiation imbalance and increased AKT/mTOR signalling in CNTNAP2-/-cerebral organoids
Authors: Chalkiadaki Kleanthi , Statoulla Elpida , Zafeiri Maria , Voudouri Georgia , Amvrosiadis Theoklitos , Typou Alexandra , Theodoridou Niki , Moschovas Dimitrios , Avgeropoulos Apostolos , Samiotaki Martina , Mason John O. , Gkogkas Christos G.
Published: April 2024

We developed a human cerebral organoid model derived from induced pluripotent stem cells (iPSCs) with targeted genome editing to abolish protein expression of the Contactin Associated Protein-like 2 (CNTNAP2)autism spectrum disorder (ASD) risk gene, mimicking loss-of-function mutations seen in patients. CNTNAP2-/-cerebral organoids displayed accelerated cell cycle, ventricular zone disorganisation and increased cortical folding. Proteomic analysis revealed disruptions in Glutamatergic/GABAergic synaptic pathways and neurodevelopment, highlighting increased protein expression of corticogenesis and neurodevelopment-related genes such as Forkhead box protein G1 (FOXG1) and Paired box 6 (PAX6). Transcriptomic analysis revealed differentially expressed genes (DEG) belonging to inhibitory neuron-related gene networks. Interestingly, there was a weak correlation between the transcriptomic and proteomic data, suggesting nuanced translational control mechanisms. Along these lines we found upregulated Protein Kinase B (Akt)/mechanistic target of rapamycin (mTOR) signalling in CNTNAP2-/-organoids. Spatial transcriptomics analysis of CNTNAP2-/-ventricular-like zones demonstrated pervasive changes in gene expression, particularly in PAX6-cells, implicating upregulation of cell cycle regulation pathways, synaptic and Glutamatergic/GABAergic pathways. We noted a significant overlap of all D30 cerebral organoids ‘omics datasets with an idiopathic ASD (macrocephaly) iPSC-derived telencephalic organoids DEG dataset, where FOXG1 was upregulated. Moreover, we detected increased Glutamate decarboxylase 1 (GAD1) and decreased T-Box Brain Transcription Factor 1 (TBR1) expressing cells, suggesting altered GABAergic/Glutamatergic neuron development. These findings potentially highlight a shared mechanism in the early cortical development of various forms of ASD, further elucidate the role of CNTNAP2 in ASD pathophysiology and cortical development and pave the way for targeted therapies using cerebral organoids as preclinical models.
Longitudinal Fecal Shedding of SARS-CoV-2, Pepper Mild Mottle Virus, and Human Mitochondrial DNA in COVID-19 Patients
Authors: Liu Pengbo , Sablon Orlando III , Wang Yuke , Hilton Stephen Patrick , Khalil Lana , Ingersoll Jessica Mae , Truell Jennifer Carter , Edupuganti Sri , Alaaeddine Ghina , Naji Amal , Monarrez Eduardo , Wolfe Marlene , Rouphael Nadine K , Kraft Colleen Suzanne , Moe Christine L
Published: April 2024

Since the coronavirus disease 2019 (COVID-19) pandemic, wastewater-based epidemiology (WBE) has been widely applied in many countries and regions for monitoring COVID-19 transmission in the population through testing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater. However, the lack of dynamic level of viral shedding in the wastewater and accurate number of infections in the community creates challenges in predicting COVID-19 prevalence in the population and interpreting WBE results. In this study, we measured SARS-CoV-2, pepper mild mottle virus (PMMoV), and human mitochondrial DNA (mtDNA) in longitudinal fecal samples collected from 42 COVID-19 patients for up to 42 days after diagnosis. SARS-CoV-2 RNA was detected in 73.1% (19/26) of inpatient study participants in at least one of the collected fecal specimens during the sampling period. Most participants shed the virus within three weeks after diagnosis, but five inpatient participants still shed the virus between 20 and 60 days after diagnosis. The median concentration of SARS-CoV-2 in positive fecal samples was 1.08x105 genome copies (GC)/gram dry fecal material. PMMoV and mtDNA were detected in 99.4% (154/155) and 100% (155/155) of all fecal samples, respectively. The median concentrations of PMMoV RNA and mtDNA in fecal samples were 1.73x107 and 2.49x108 GC/dry gram, respectively. These results provide important information about the dynamics of fecal shedding of SARS-CoV-2 and two human fecal indicators in COVID-19 patients. mtDNA showed higher positive rates, higher concentrations, and less variability between and within individuals than PMMoV, suggesting that mtDNA could be a better normalization factor for WBE results than PMMoV.
Late diagnosis of Marfan syndrome is associated with unplanned aortic surgery and cardiovascular death
Authors: Claus Jason , Schoof Lauritz , Mir Thomas S. , Kammal Anna Lena , Schön Gerhard , Kutsche Kerstin , Behrendt Christian-Alexander , Kallenbach Klaus , Kölbel Tilo , Kubisch Christian , Demal Till Joscha , Petersen Johannes , Brickwedel Jens , Hübler Michael , Detter Christian , Kirchhof Paulus , Debus Eike Sebastian , Rybczynski Meike , von Kodolitsch Yskert
Published: April 2024

Background

Marfan syndrome (MFS) guidelines recommend optimal pharmacological therapy (OPT) and replacement of the ascending aorta (RAA) at 5.0cm diameters to prevent acute type A aortic dissection (ATAAD) and death. The effect of early MFS diagnosis and initiation of therapy on outcomes is not known.

Objective

To evaluate the effect of age at MFS diagnosis and therapy initiation on delayed RAA and death.

Methods

This retrospective observational cohort study with long-term follow-up included consecutive patients with MFS, pathogenicFBN1variant, and regular visits to a European Reference Network Center. We considered MFS diagnosis at age ≥21 years late, and OPT initiation at age <21 years early. Outcomes were delayed RAA with aneurysm diameter >5.0cm or ATAAD, and death from all causes. We used landmark design starting at age 21 years to determine associations with outcomes.

Results

The study group consisted of 288 patients (45.1% male), including 169 patients with late MFS diagnosis (58.7%) and 63 with early OPT (21.9%). During mean follow-up of 25±14.7 years, 78 patients had delayed RAA, with 42 operations for ATAAD and 36 for aneurysms ≥5.0cm. There were 33 deaths, including 11 deaths late after ATAAD. All deaths were cardiovascular. Late diagnosis, but not early OPT, showed univariate association with delayed RAA (P<0.001) and death (P=0.025). Multivariate Cox regression analysis confirmed late diagnosis as predictor of delayed RAA (hazard ratio (HR)=8.01; 95% confidence interval (95%CI) 2.52-25.45; P<0.001) and death (HR=4.68; 95%CI 1.17-18.80; P=0.029).

Conclusions

Late diagnosis of Marfan syndrome is associated with delayed surgery and death.
Large-scale identification of social and behavioral determinants of health from clinical notes: Comparison of Latent Semantic Indexing and Generative Pretrained Transformer (GPT) models
Authors: Roy Sujoy , Morrell Shane , Zhao Lili , Homayouni Ramin
Published: April 2024

Background

Social and behavioral determinants of health (SBDH) are associated with a variety of health and utilization outcomes, yet these factors are not routinely documented in the structured fields of electronic health records (EHR). The objective of this study was to evaluate different machine learning approaches for detection of SBDH from the unstructured clinical notes in the EHR.

Methods

Latent Semantic Indexing (LSI) was applied to 2,083,180 clinical notes corresponding to 46,146 patients in the MIMIC-III dataset. Using LSI, patients were ranked based on conceptual relevance to a set of keywords (lexicons) pertaining to 15 different SBDH categories. For Generative Pretrained Transformer (GPT) models, API requests were made with a Python script to connect to the OpenAI services in Azure, using gpt-3.5-turbo-1106 and gpt-4-1106-preview models. Prediction of SBDH categories were performed using logistic regression model that included age, gender race and SBDH ICD-9 codes with a natural cubic spline of 2 degrees of freedom for age.

Results

LSI retrieved patients according to 15 SBDH domains, with an overall average PPV≥83%. Using manually curated gold standard (GS) sets for nine SBDH categories, the macro-F1 score of LSI (0.74) was better than ICD-9 (0.71) and GPT-3.5 (0.54), but lower than GPT-4 (0.80). Due to document size limitations, only a subset of the GS cases could be processed by GPT-3.5 (55.8%) and GPT-4 (94.2%), compared to LSI (100%). Using common GS subsets for nine different SBDH categories, the macro-F1 of ICD-9 combined with either LSI (mean 0.88, 95% CI 0.82-0.93), GPT-3.5 (0.86, 0.82-0.91) or GPT-4 (0.88, 0.83-0.94) was not significantly different. After including age, gender, race and ICD-9 in a logistic regression model, the AUC for prediction of six out of the nine SBDH categories was higher for LSI compared to GPT-4.0.

Conclusions

These results demonstrate that the LSI approach performs comparable to more recent large language models, such as GPT-3.5 and GPT-4.0, when using the same set of documents. Importantly, LSI is robust, deterministic, and does not have document-size limitations or cost implications, which make it more amenable to real-world applications in health systems.
Sustained impact of 10-valent pneumococcal conjugate vaccine on invasive pneumococcal disease in Kenya, 2011-2022
Authors: Kagucia E Wangeci , Nyamwaya Brian M , Ongayo Gerald , Kaniu Mary , Sang Samuel , Lucinde Ruth , Karani Angela , Akech Donald , Odiwuor Fredrick , Mataza Christine , Tabu Collins , Mturi Neema , Ndaa Siti , Mulunda Caroline , Etyang Timothy , Aliyan Nadia , Nyaguara Amek , Voller Shirine , Bottomley Christian , Hammitt Laura , Adetifa Ifedayo , Scott J Anthony G
Published: April 2024

Background

There are only a few long-term PCV impact assessments in sub-Saharan Africa, and these have been confined to settings using a 13-valent PCV. A 10-valent PCV was introduced in Kenya in 2011 with catchup vaccination among children aged <5 years in Kilifi. We evaluated the impact of PCV10 introduction in Kilifi through 2022.

Methods

Surveillance for IPD among residents of the Kilifi Health and Demographic Surveillance System was conducted at the Kilifi County Referral Hospital. Identification of pneumococcus isolated from blood or cerebrospinal fluid and pneumococcal serotyping were conducted according to WHO recommendations. Age– and serotype-specific incidence rate ratios, adjusted for pre-defined confounders (aIRRs), were used to compare annual IPD incidence in the pre-vaccine period to that in 2017-2019 (late post-vaccine) and 2020-2022 (COVID-19).

Findings

Compared to the pre-vaccine period, the incidence of vaccine serotype (VT) IPD among children aged <5 years was significantly lower in 2017-2019 (aIRR 0.14; 95%CI 0.04-0.49) and in 2020-2022 (aIRR 0.03; 95%CI 0.00-0.25). It also declined among older children and adults. The incidence of non-VT (NVT) IPD among children aged <15 years was higher during the post-vaccine period. All serotype IPD incidence declined across all age groups. Among individuals with NVT-IPD, serotypes included in new-generation PCVs accounted for about one-third and about one-half of disease among individuals aged <5 years and ≥5 years, respectively.

Interpretation

Despite potential waning of the effects of catchup vaccination during introduction, reductions in VT-IPD incidence were sustained through 12 years of PCV10 use. All serotype IPD incidence declined across all ages despite serotype replacement among children. New-generation PCVs may enhance IPD control.
Social Impacts of Multi-City HIV Research Participation Among Sexual and Gender Expansive Individuals in Kazakhstan
Authors: Vinogradov Vitaliy , Lee Yong Gun , Zhakupova Gulnara , Mergenova Gaukhar , Davis Alissa , Paine Emily Allen , Reeder Kelsey G. , Laughney Caitlin I. , Sung Jimin , Primbetova Sholpan , Terlikbayeva Assel , Sugarman Jeremy , Wu Elwin
Published: April 2024

Background: Sexual and gender expansive (SGE) individuals in Kazakhstan are disproportionately affected by HIV yet stigma and discrimination pose ethical and practical challenges for HIV prevention research involving them. Although researchers are tasked with ensuring that risks of research participation are reasonable in relation to its benefits, participation-related risks and benefits—including negative and positive social impacts (NSIs and PSIs respectively) on personal relationships, social status, health, and other aspects of life—among SGE populations have received little attention.Methods: We examined NSIs and PSIs of participation among SGE individuals in a three-city HIV prevention study in Kazakhstan at the clinical trial's follow-up visits. We analyzed responses from 579 unique SGE participants who completed a total of 2648 follow-up visits over the 36-month study period (2019–2022).Results: Overall, NSIs were rare: 9 (2%) participants reported NSIs during the study; virtually no NSIs (mean=0.0037, SD=0.03) were reported at each follow-up visit. These few NSIs included 'trouble with friends, family, or acquaintances' and 'other'. By contrast, PSIs were extensive: 515 (89%) participants reported PSIs during the study; almost an average of five PSIs (mean=4.8, SD=3.4) were reported at each follow-up visit. The most endorsed PSIs were 'gained knowledge', 'improvement in HIV-related issues', and 'improvement in life'.Conclusions: Our findings demonstrate the potential for HIV prevention research to be associated with PSIs for SGE individuals experiencing stigmatization and discrimination. Future research should address NSIs, particularly interpersonal challenges among network members, within HIV prevention research to minimize risks and burdens of participation.
Development of a predictive algorithm for patient survival after traumatic injury using a five analyte blood panel
Authors: Fathi Parinaz , Karkanitsa Maria , Rupert Adam , Lin Aaron , Darrah Jenna , Dennis Thomas F. , Lai Jeffrey , Babu Kavita , Neavyn Mark , Kozar Rosemary , Griggs Christopher , Cunningham Kyle W. , Schulman Carl I. , Crandall Marie , Sereti Irini , Ricotta Emily , Sadtler Kaitlyn
Published: April 2024

Severe trauma can induce systemic inflammation but also immunosuppression, which makes understanding the immune response of trauma patients critical for therapeutic development and treatment approaches. By evaluating the levels of 59 proteins in the plasma of 50 healthy volunteers and 1000 trauma patients across five trauma centers in the United States, we identified 6 novel changes in immune proteins after traumatic injury and further new variations by sex, age, trauma type, comorbidities, and developed a new equation for prediction of patient survival. Blood was collected at the time of arrival at Level 1 trauma centers and patients were stratified based on trauma level, tissues injured, and injury types. Trauma patients had significantly upregulated proteins associated with immune activation (IL-23, MIP-5), immunosuppression (IL-10) and pleiotropic cytokines (IL-29, IL-6). A high ratio of IL-29 to IL-10 was identified as a new predictor of survival in less severe patients with ROC area of 0.933. Combining machine learning with statistical modeling we developed an equation (“VIPER”) that could predict survival with ROC 0.966 in less severe patients and 0.8873 for all patients from a five analyte panel (IL-6, VEGF-A, IL-21, IL-29, and IL-10). Furthermore, we also identified three increased proteins (MIF, TRAIL, IL-29) and three decreased proteins (IL-7, TPO, IL-8) that were the most important in distinguishing a trauma blood profile. Biologic sex altered phenotype with IL-8 and MIF being lower in healthy women, but higher in female trauma patients when compared to male counterparts. This work identifies new responses to injury that may influence systemic immune dysfunction, serving as targets for therapeutics and immediate clinical benefit in identifying at-risk patients.
Methamphetamine-associated Heart Failure: Clinical phenotypes and Outcomes in a Safety Net Population
Authors: Thakkar Anjali B. , Durstenfeld Matthew S. , Ma Yifei , Win Sithu , Hsue Priscilla Y.
Published: April 2024

Background

Methamphetamine use has increased dramatically over the past decade and is associated with the development of heart failure (HF). However, clinical characteristics and outcomes have not been well described. This study aimed to compare clinical characteristics and outcomes among individuals with HF who do and do not use methamphetamines in a safety-net hospital.

Method

This retrospective matched cohort study included all individuals with HF with history of methamphetamine use and age, gender-, and year-matched controls without history of methamphetamine use within a municipal health system from 2001-2019. 1,783 individuals with methamphetamine use and HF were identified; 12 were excluded due to inability to identify matched methamphetamine-negative controls. Therefore, 1,771 individuals with methamphetamine use and heart failure and 3,542 age, sex, and year-of-HF-diagnosis matched controls with heart failure without methamphetamine use were included. The primary outcome was all-cause mortality. Secondary outcomes included time to HF hospitalization, and 30-day, 90-day, and 1 year HF and all-cause readmissions.

Results

Median age of the cohort was 52.1 years and 22.6% were female. There was no significant difference in mortality between the two groups (40% vs 36.6%, HR 1.00, 95% CI 0.91, 1.10, p=1.00). A subset had an index HF hospitalization (n=1,404) during the study period including 637 (35.9%) with history of methamphetamine use and 767 (21.7%) without history of methamphetamine use (relative risk 1.66, 95%CI 1.52-1.81, p<0.0001). Among those ever hospitalized for HF, individuals with methamphetamine use had increased odds of HF and all-cause readmission at 30 days, 90 days, and 1 year.

Conclusion

Despite having higher risk of both all cause and HF readmissions, individuals with methamphetamine-associated heart failure did not have higher risk of mortality. Measures to address frequent healthcare utilization among people with methamphetamine use and HF are needed.
Diagnostic and prognostic value of ECG-predicted hypertension-mediated left ventricular hypertrophy using machine learning
Authors: Naderi Hafiz , Ramírez Julia , van Duijvenboden Stefan , Pujadas Esmeralda Ruiz , Aung Nay , Wang Lin , Chamling Bishwas , Dörr Marcus , Markus Marcello R P , Chahal C. Anwar A , Lekadir Karim , Petersen Steffen E , Munroe Patricia B
Published: April 2024

Background

Four hypertension-mediated left ventricular hypertrophy (LVH) phenotypes have been reported using cardiac magnetic resonance (CMR): normal LV, LV remodeling, eccentric and concentric LVH, with varying prognostic implications. The electrocardiogram (ECG) is routinely used to detect LVH, however its capacity to differentiate between LVH phenotypes is unknown. This study aimed to classify hypertension-mediated LVH from the ECG using machine learning (ML) and test for associations of ECG-predicted phenotypes with incident cardiovascular outcomes.

Methods

ECG biomarkers were extracted from the 12-lead ECG of 20,439 hypertensives in UK Biobank (UKB). Classification models integrating ECG and clinical variables were built using logistic regression, support vector machine (SVM) and random forest. The models were trained in 80% of the participants, and the remaining 20% formed the test set. External validation was sought in 877 hypertensives from the Study of Health in Pomerania (SHIP). In the UKB test set, we tested for associations between ECG-predicted LVH phenotypes and incident major adverse cardiovascular events (MACE) and heart failure.

Results

Among UKB participants 19,408 had normal LV, 758 LV remodeling, 181 eccentric and 92 concentric LVH. Classification performance of the three models was comparable, with SVM having a slightly superior performance (accuracy 0.79, sensitivity 0.59, specificity 0.87, AUC 0.69) and similar results observed in SHIP. There was superior prediction of eccentric LVH in both cohorts. In the UKB test set, ECG-predicted eccentric LVH was associated with heart failure (HR 3.42, CI 1.06-9.86).

Conclusions

ECG-based ML classifiers represent a potentially accessible screening strategy for the early detection of hypertension-mediated LVH phenotypes.

Graphical abstract
Molecular architecture of glideosome and nuclear F-actin inPlasmodium falciparum
Authors: Pražák Vojtech , Vasishtan Daven , Grünewald Kay , Douglas Ross G. , Ferreira Josie L.
Published: April 2024

Actin-based motility is required for the transmission of malaria sporozoites. While this has been shown biochemically, filamentous actin has remained elusive and has to date never been directly visualised inside the parasite. Using focused ion beam milling and electron cryo-tomography, we studied dynamic actin filaments in unperturbedPlasmodium falciparumcells for the first time. This allowed us to dissect the assembly, path and fate of actin filaments during parasite gliding and determine a complete 3D model of F-actin within sporozoites. We show that within the cell, actin assembles into micrometre long filaments, much longer than observed inin vitrostudies. After their assembly at the parasite’s apical end, actin filaments continue to grow as they are transported down the cell as part of the glideosome machinery, and are disassembled at the basal end in a rate-limiting step. Large pores in the IMC, constrained to the basal end, may facilitate actin exchange between the pellicular space and the cytosol for its recycling and maintenance of directional actin flow for efficient gliding. The data also reveal striking and extensive actin bundles in the nucleus. Implications of these structures for motility and transmission are discussed.
Novel Automatic Classification of Human Adult Lung Alveolar Type II Cells Infected with SARS-CoV-2 through Deep Transfer Learning Approach
Authors: Turki Turki , Al Habib Sarah , Taguchi Y-h.
Published: April 2024

SARS-CoV-2 can infect alveoli, inducing a lung injury and thereby impairing the lung function. Healthy alveolar type II (AT2) cells play a major role in lung injury repair as well as keeping alveoli space free from fluids, which is not the case for infected AT2 cells. Unlike previous studies, this novel study aims to automatically differentiate between healthy and infected AT2 cells with SARS-CoV-2 through using efficient AI-based models, which can aid in disease control and treatment. Therefore, we introduce a highly accurate deep transfer learning (DTL) approach that works as follows. First, we downloaded and processed 286 images pertaining to healthy and infected human AT2 (hAT2) cells, obtained from the electron microscopy public image archive. Second, we provided processed images to two DTL computations to induce ten DTL models. The first DTL computation employs five pre-trained models (including DenseNet201 and ResNet152V2) trained on more than million images from ImageNet database to extract features from hAT2 images. Then, flattening and providing the output feature vectors to a trained densely connected classifier with Adam optimizer. The second DTL computation works in a similar manner with a minor difference in which we freeze the first layers for feature extraction in pre-trained models while unfreezing and training the next layers. Compared to TFtDenseNet201, experimental results using five-fold cross-validation demonstrate that TFeDenseNet201 is 12.37 × faster and superior, yielding the highest average ACC of 0.993 (F1 of 0.992 and MCC of 0.986) with statistical significance (p< 2.2 × 10−16from at-test).
Heterogeneous efflux pump expression underpins phenotypic resistance to antimicrobial peptides
Authors: Lee Ka Kiu , Łapińska Urszula , Tolle Giulia , Phetsang Wanida , Verderosa Anthony D. , Invergo Brandon M. , Westley Joseph , Bebes Attila , Yuecel Raif , O’Neill Paul A. , Farbos Audrey , Jeffries Aaron R. , van Houte Stineke , Caboni Pierluigi , Blaskovich Mark A. T. , Housden Benjamin E. , Tsaneva-Atanasova Krasimira , Pagliara Stefano
Published: April 2024

Antimicrobial resistance threatens the viability of modern medical interventions. There is a dire need of developing novel approaches to counter resistance mechanisms employed by starved or slow-growing pathogens that are refractory to conventional antimicrobial therapies. Antimicrobial peptides have been advocated as potential therapeutic solutions due to low levels of genetic resistance observed in bacteria against these compounds. However, here we show that subpopulations of stationary phaseEscherichia coliandPseudomonas aeruginosasurvive tachyplesin treatment without genetic mutations. These phenotypic variants induce efflux, outer membrane vesicles secretion and membrane modifications in response to tachyplesin exposure, sequestering the peptide in their membranes where it cannot exert its antimicrobial activity. We discovered that formation of these phenotypic variants could be prevented by administering tachyplesin in combination with sertraline, a clinically used antidepressant, suggesting a novel approach for combatting antimicrobial-refractory stationary phase bacteria.
Single-molecule visualization of sequence-specific RNA binding by a designer PPR protein
Authors: Marzano Nicholas , Johnston Brady , Paudel Bishnu P. , Schmidberger Jason , Jergic Slobodan , Böcking Till , Agostino Mark , Small Ian , van Oijen Antoine M. , Bond Charles S.
Published: April 2024

Pentatricopeptide repeat (PPR) proteins are a large family of modular RNA-binding proteins that recognize specific ssRNA target sequences. There is significant interest in developing ‘designer’ PPRs for use in diagnostics or as tools to detect and localize target RNA sequences. However, it is unclear how PPRs search for target sequences within complex transcriptomes and current models to predict PPR binding sites struggle to reconcile the effects that RNA mismatches and secondary structure have on PPR binding. To address this, we determined the structure of a designer PPR (dPPR10) bound to its target sequence and used two- and three-colour single-molecule FRET to interrogate the mechanism of ssRNA binding to individual PPR proteins in real time. We demonstrate that longer RNA sequences were significantly slower to bind (or could not bind at all) and that this is, in part, due to their propensity to form stable secondary structures that sequester the target sequence from dPPR10. Importantly, dPPR10 does not associate with non-target flanking sequences, binding specifically to its target sequence within longer ssRNA species. This data provides evidence that PPRs have limited to no capacity to ‘scan’ RNA transcripts for target sequences and instead rely on diffusion for cognate searching. The kinetic constraints imposed by random three-dimensional diffusion may explain the long-standing conundrum of why PPR proteins are abundant in organelles, but almost unknown outside them (i.e. in the cytosol and nucleus). These findings will inform improved prediction of PPR binding sites for the development of designer PPRs.

Pentatricopeptide repeat proteins (PPR) are a large family of modular RNA-binding proteins, whereby each module can be ‘designed’ to bind to a specific ssRNA nucleobase and thus any RNA sequence of interest. As such, there is substantial interest in developing ‘designer’ PPRs for a range of biotechnology applications, including diagnostics orin vivolocalisation of RNA species; however, the mechanistic details regarding how PPRs search for and bind to target sequences is unclear. As such, we combined structure-based and single- molecule approaches and determined that PPRs bind only to their target sequences (i.e., they do not associate with non-target RNA sequences) and do not ‘scan’ longer RNA oligonucleotides for the target sequence. Instead, target searching appears kinetically-constrained by random three-dimensional diffusion, providing an explanation as to why PPRs are found almost exclusively in organelle compartments that typically have smaller transcriptomes. Collectively, this work identifies several key considerations for future ‘designer’ PPR developments.
Dose-Efficient Cryo-Electron Microscopy for Thick Samples using Tilt-Corrected Scanning Transmission Electron Microscopy, Demonstrated on Cells and Single Particles
Authors: Yu Yue , Spoth Katherine A. , Colletta Michael , Nguyen Kayla X. , Zeltmann Steven E. , Zhang Xiyue S. , Paraan Mohammadreza , Kopylov Mykhailo , Dubbeldam Charlie , Serwas Daniel , Siems Hannah , Muller David A. , Kourkoutis Lena F.
Published: April 2024

Cryo-EM is a powerful tool in structural biology, providing insights through techniques like single-particle analysis (SPA) and cryogenic electron tomography (cryo-ET). In thick specimens, challenges arise as an exponentially larger fraction of the transmitted electrons lose energy from inelastic scattering and can no longer be properly focused as a result of chromatic aberrations in the post-specimen optics. Rather than filtering out the inelastic scattering at the price of reducing potential signal, as is done in energy-filtered transmission electron microscopy (EFTEM), we show how a dose-efficient and unfiltered image can be rapidly obtained using tilt-corrected bright-field scanning-TEM (tcBF-STEM) data collected on a pixelated detector. Enhanced contrast and a 3-5x improvement in collection efficiency are observed for 2D images of intact bacterial cells and large organelles using tcBF-STEM compared to EFTEM for thicknesses beyond 500 nm. As a proof of concept for the technique’s performance in structural determination, we present an SPA map at subnanometer resolution for a highly symmetric virus-like particle (VLP) with 789 particles. These findings suggest applications for tcBF-STEM in cryo-EM of thicker cellular volumes where current approaches struggle.