bluuebunny/crossref_metadata_2025 huggingface dataset:
Trauma patients with type O blood exhibit unique multiomics signature with decreased lectin pathway of complement levels
Authors: Stocker Benjamin W. , LaCroix Ian S. , Erickson Christopher , Gallagher Lauren T. , Ramser Benjamin J. , Thielen Otto , Hallas William , Mitra Sanchayita , Moore Ernest E. , Hansen Kirk , D'Alessandro Angelo , Silliman Christopher C. , Cohen Mitchell J.
Published: May 2024

BACKGROUND

Patients with type O blood may have an increased risk of hemorrhagic complications because of lower baseline levels of von Willebrand factor and factor VIII, but the transition to a mortality difference in trauma is less clear. We hypothesized that type O trauma patients will have differential proteomic and metabolomic signatures in response to trauma beyond von Willebrand factor and factor VIII alone.

METHODS

Patients meeting the highest level of trauma activation criteria were prospectively enrolled. Blood samples were collected upon arrival to the emergency department. Proteomic and metabolomic (multiomics) analyses of these samples were performed using liquid chromatography–mass spectrometry. Demographic, clinical, and multiomics data were compared between patients with type O blood versus all other patients.

RESULTS

There were 288 patients with multiomics data; 146 (51%) had type O blood. Demographics, injury patterns, and initial vital signs and laboratory measurements were not different between groups. Type O patients had increased lengths of stay (7 vs. 6 days, p = 0.041) and a trend toward decreased mortality secondary to traumatic brain injury compared with other causes (traumatic brain injury, 44.4% vs. 87.5%; p = 0.055). Type O patients had decreased levels of mannose-binding lectin and mannose-binding lectin–associated serine proteases 1 and 2, which are required for the initiation of the lectin pathway of complement activation. Type O patients also had metabolite differences signifying energy metabolism and mitochondrial dysfunction.

CONCLUSION

Blood type O patients have a unique multiomics signature, including decreased levels of proteins required to activate the lectin complement pathway. This may lead to overall decreased levels of complement activation and decreased systemic inflammation in the acute phase, possibly leading to a survival advantage, especially in traumatic brain injury. However, this may later impair healing. Future work will need to confirm these associations, and animal studies are needed to test therapeutic targets.

LEVEL OF EVIDENCE

Prognostic and Epidemiological; Level IV.
Training for a mass casualty incident: Conception, development, and implementation of a crew-resource management course for forward surgical teams
Authors: de Lesquen Henri , Paris Raphael , Lacheze Solenn , de la Villeon Bruno , Menini William , Lamblin Antoine , Vacher Anthony , Balandraud Paul , Pasquier Pierre , Avaro Jean-Philippe
Published: May 2024

BACKGROUND

Since 2021, the predeployment training of French FSTs has included a simulation-based curriculum consisting of organizational and human factors. The purpose of this article is to describe the development of a crew-resource management (CRM) training course dedicated for the forward surgical teams (FSTs) of the French Military Health Service.

METHODS

The approach was based on three steps: (1) establishment of a conceptual framework of FSTs deployment; (2) development of an aircrew-like CRM training combining lectures, laboratory exercises, and situational training exercises to consider four fundamental “nontechnical” (cognitive and social) skills for effective and safe combat casualty care: (a) leadership, (b) decision-making, (c) coordination, and (d) situational awareness; (3) Implementation of teamwork evaluation tools.

RESULTS

A multidisciplinary team designed a conceptual framework for FST preparedness, 24 French FSTs completed a high-quality training that takes into account both technical and nontechnical skills to maintain quality of combat care during mass-casualty incidents, FSTs' CRM skills were assessed using an audio/video recording of a simulated mass-casualty incident.
Association of timing and agent for venous thromboembolism prophylaxis in patients with severe traumatic brain injury on venous thromboembolism events, mortality, neurosurgical intervention, and discharge disposition
Authors: Johnson Patrick L. , Dualeh Shukri H. A. , Ward Ayobami L. , Jean Raymond A. , Aubry Staci T. , Chapman Alistair J. , Curtiss William J. , Joseph Jacob R. , Scott John W. , Hemmila Mark R.
Published: May 2024

BACKGROUND

Trauma patients are at increased risk for venous thromboembolism events (VTEs). The decision of when to initiate VTE chemoprophylaxis (VTEP) and with what agent remains controversial in patients with severe traumatic brain injury (TBI).

METHODS

This comparative effectiveness study evaluated the impact of timing and agent for VTEP on outcomes for patients with severe TBI (Abbreviated Injury Scale head score of 3, 4, or 5). Data were collected at 35 Level 1 and 2 trauma centers from January 1, 2017, to June 1, 2022. Patients were placed into analysis cohorts: no VTEP, low-molecular-weight heparin (LMWH) ≤48 hours, LMWH >48 hours, heparin ≤48 hours, and heparin >48 hours. Propensity score matching accounting for patient factors and injury characteristics was used with logistic regression modeling to evaluate in-hospital mortality, VTEs, and discharge disposition. Neurosurgical intervention after initiation of VTEP was used to evaluate extension of intracranial hemorrhage.

RESULTS

Of 12,879 patients, 32% had no VTEP, 36% had LMWH, and 32% had heparin. Overall mortality was 8.3% and lowest among patients receiving LMWH ≤48 hours (4.1%). Venous thromboembolism event rates were lower with use of LMWH (1.6% vs. 4.5%; odds ratio, 2.98; 95% confidence interval, 1.40–6.34; p = 0.005) without increasing mortality or neurosurgical interventions. Venous thromboembolism event rates were lower with early prophylaxis (2.0% vs. 3.5%; odds ratio, 1.76; 95% confidence interval, 1.15–2.71; p = 0.01) without increasing mortality (p = 1.0). Early VTEP was associated with more nonfatal intracranial operations (p < 0.001). However, patients undergoing neurosurgical intervention after VTEP initiation had no difference in rates of mortality, withdrawal of care, or unfavorable discharge disposition (p = 0.7, p = 0.1, p = 0.5).

CONCLUSION

In patients with severe TBI, LMWH usage was associated with lower VTE incidence without increasing mortality or neurosurgical interventions. Initiation of VTEP ≤48 hours decreased VTE incidence and increased nonfatal neurosurgical interventions without affecting mortality. Low-molecular-weight heparin is the preferred VTEP agent for severe TBI, and initiation ≤48 hours should be considered in relation to these risks and benefits.

LEVEL OF EVIDENCE

Therapeutic/Care Management; Level III.
A Contemporary Analysis of Mental Well-being Among Living Donor Kidney Applicants
Authors: Levea Swee-Ling , Prasadh Jai G. , Wang Benjamin K. , Salcedo-Betancourt Juan D. , Matevish Lauren , Sanchez Vivaldi Jorge , Lieber Sarah R. , Shah Jigesh A. , Hwang Christine S. , Wojciechowski David , Vagefi Parsia A. , Patel Madhukar S.
Published: May 2024

Background.

Living donation is paramount for expanding the donor pool. The aim of this study was to assess changes over time in self-reported mental health of living donor kidney applicants in efforts to inform patient-centered discussions with potential donors.

Methods.

Kidney donor applications from 2017 through 2021 were compiled. Data included age, gender, race, ethnicity, applicant–recipient relationship, medical history, and medications. Trends over time were analyzed and post hoc analyses were performed.

Results.

During the study period, 2479 applicants to the living donor kidney program were evaluated; 73% of applicants were female individuals. More than half of applicants were not related to their intended recipient; this fraction increased from 46% in 2017 to 58% in 2021 (P < 0.01). A similar decline in family relations was not present among Black and Latino applicants. Of all applicants, 18% reported depression and 18% reported anxiety; 20% reported taking antidepressants or anxiolytics. Depression and anxiety increased 170% (P < 0.001) and 136% (P < 0.001) from 2018 to 2019, respectively; antidepressant and anxiolytic use rose 138% (P < 0.001) between 2018 and 2020.

Conclusions.

The profile of living donor applicants has changed in recent years, with approximately 1 in 5 requiring antidepressants or anxiolytics. Predonation counseling and postdonation monitoring are imperative to decrease adverse psychological outcomes for living donors.
Using neural ordinary differential equations to predict complex ecological dynamics from population density data
Authors: Arroyo-Esquivel Jorge , Klausmeier Christopher A. , Litchman Elena
Published: May 2024

Simple models have been used to describe ecological processes for over a century. However, the complexity of ecological systems makes simple models subject to modelling bias due to simplifying assumptions or unaccounted factors, limiting their predictive power. Neural ordinary differential equations (NODEs) have surged as a machine-learning algorithm that preserves the dynamic nature of the data (Chen
et al.
2018
Adv. Neural Inf. Process. Syst.
). Although preserving the dynamics in the data is an advantage, the question of how NODEs perform as a forecasting tool of ecological communities is unanswered. Here, we explore this question using simulated time series of competing species in a time-varying environment. We find that NODEs provide more precise forecasts than autoregressive integrated moving average (ARIMA) models. We also find that untuned NODEs have a similar forecasting accuracy to untuned long-short term memory neural networks and both are outperformed in accuracy and precision by empirical dynamical modelling . However, we also find NODEs generally outperform all other methods when evaluating with the interval score, which evaluates precision and accuracy in terms of prediction intervals rather than pointwise accuracy. We also discuss ways to improve the forecasting performance of NODEs. The power of a forecasting tool such as NODEs is that it can provide insights into population dynamics and should thus broaden the approaches to studying time series of ecological communities.
Extreme neck elongation evolved despite strong developmental constraints in bizarre Triassic reptiles—implications for neck modularity in archosaurs
Authors: Rytel Adam , Böhmer Christine , Spiekman Stephan N. F. , Tałanda Mateusz
Published: May 2024

The Triassic radiation of vertebrates saw the emergence of the modern vertebrate groups, as well as numerous extinct animals exhibiting conspicuous, unique anatomical characteristics. Among these, members of Tanystropheidae (Reptilia: Archosauromorpha) displayed cervical vertebral elongation to an extent unparalleled in any other vertebrate. Tanystropheids were exceptionally ecologically diverse and had a wide spatial and temporal distribution. This may have been related to their neck anatomy, yet its evolution and functional properties remain poorly understood. We used geometric morphometrics to capture the intraspecific variation between the vertebrae comprising the cervical column among early archosauromorphs, to trace the evolutionary history of neck elongation in these animals. Our results show that the cervical series of these reptiles can be divided into modules corresponding to those of extant animals. Tanystropheids achieved neck elongation through somite elongation and a shift between cervical and thoracic regions, without presacral vertebrae count increase—contrary to crown archosaurs. This suggests a peculiar developmental constraint that strongly affected the evolution of tanystropheids. The data obtained just at the base of the archosauromorph phylogenetic tree are crucial for further studies on the modularity of vertebral columns of not only Triassic reptile groups but extant and other extinct animals as well.
Video-Language Models as Flexible Social and Physical Reasoners
Authors: Fleury Daniel
Published: May 2024

From an early age, humans are challenged with evaluating rich environments full of socially and physically grounded concepts. For example, we might be spectating a rapidly unfolding tennis match, anticipating ball trajectories based on players’ body cues and goals. In another scenario, we may engage with long storylines, juggling the mental states of characters with varying knowledge of an unfolding conflict. The complexity of this learning problem is notable as it can be multimodal, integrate information at varying timescales, and implicitly co-attend to social and physical scene properties for downstream reasoning. Large language-vision models like GPT4-V, LLaMA-3, which use vision-language embeddings, show skills in commonsense psychology and physics, though they only process single images. Models like CLIP and VisualBERT encode visual information in high-level cortical areas but do not inherently capture video-level representations. This paper introduces a novel video-language architecture that incorporates pooled video embeddings into LLMs by first extracting spatiotemporal embeddings and mapping them to the model’s decoder through a learnable linear layer. We enhance the model by training it with video-caption pairs from the ADEPT and AGENT datasets, aimed at quantifying “surprisal” in physical and psychological contexts. Finally, we design separate voxel wise encoding models for videos involving physics and psychology using the hidden states and logits from the LLMs last layer and pre-projected CLIP embeddings. We find that hidden state activations can remarkably explain high variance (R^2 up to ∼70%) across dorsal physics regions and highly distributed, ventral social vision areas. Notably, for models trained to only encode physically surprising stimuli, the hidden states andpre-projected CLIP embeddings explain nearly identical regions of variance across the inferior-parietal lobule. However, when the encoding model is trained to encode only socially surprising events, hidden states explain far more distributed ventral and dorsal activations over pre-projected CLIP embeddings.
AAnet resolves a continuum of spatially-localized cell states to unveil tumor complexity
Authors: Venkat Aarthi , Youlten Scott E. , Juan Beatriz P. San , Purcell Carley , Amodio Matthew , Burkhardt Daniel B. , Benz Andrew , Holst Jeff , McCool Cerys , Mollbrink Annelie , Lundeberg Joakim , van Dijk David , Goldstein Leonard D. , Kummerfeld Sarah , Krishnaswamy Smita , Chaffer Christine L.
Published: May 2024

Identifying functionally important cell states and structure within a heterogeneous tumor remains a significant biological and computational challenge. Moreover, current clustering or trajectory-based computational models are ill-equipped to address the notion that cancer cells reside along a phenotypic continuum. To address this, we present Archetypal Analysis network (AAnet), a neural network that learns key archetypal cell states within a phenotypic continuum of cell states in single-cell data. Applied to single-cell RNA sequencing data from pre-clinical models and a cohort of 34 clinical breast cancers, AAnet identifies archetypes that resolve distinct biological cell states and processes, including cell proliferation, hypoxia, metabolism and immune interactions. Notably, archetypes identified in primary tumors are recapitulated in matched liver, lung and lymph node metastases, demonstrating that a significant component of intratumoral heterogeneity is driven by cell intrinsic properties. Using spatial transcriptomics as orthogonal validation, AAnet-derived archetypes show discrete spatial organization within tumors, supporting their distinct archetypal biology. We further reveal that ligand:receptor cross-talk between cancer and adjacent stromal cells contributes to intra-archetypal biological mimicry. Finally, we use AAnet archetype identifiers to validate GLUT3 as a critical mediator of a hypoxic cell archetype harboring a cancer stem cell population, which we validate in human triple-negative breast cancer specimens. AAnet is a powerful tool to reveal functional cell states within complex samples from multimodal single-cell data.
Opto-chemogenetic inhibition of L-type CaV1 channels in neurons through a membrane-assisted molecular linkage
Authors: Geng Jinli , Yang Yaxiong , Li Boying , Yu Zhen , Qiu Shuang , Zhang Wen , Gao Shixin , Liu Nan , Liu Yi , Wang Bo , Fan Yubo , Xing Chengfen , Liu Xiaodong
Published: May 2024

Acute, specific, and robust inhibition of L-type Ca2+(CaV1) channels has been sought after for both research and therapeutic applications. Compared to other available CaV1 antagonists, genetically-encoded modulators, such as CMI (C-terminus mediated inhibition) peptides encoded by CaV1 DCT (distal C-terminus), hold great potentials due to its affirmative mechanisms of action on both gating and signaling. Here, we find that membrane-anchoring with a Ras tag could essentially help form a type of intramolecular-equivalent linkage, by which the tag anchored-peptide appears to dimerize with another protein or peptide on the membrane, supported by the evidence from patch-clamp electrophysiology and FRET imaging. We then design and implement the constitutive and inducible CMI modules, with appropriate dynamic ranges targeting the short and long variants of CaV1.3, both naturally occurring in neurons. Upon optical (infrared-responsive nanoparticles) and/or chemical (rapamycin) induction of FRB/FKBP binding, DCT peptides with no CMI in the cytosol acutely translocate onto the membrane via FRB-Ras, where the physical linkage requirement could be fulfilled. The peptides robustly produce acute and potent inhibitions on both recombinant CaV1.3 channels and neuronal CaV1 activities, and thus the Ca2+influx-neuritogenesis coupling. Validated through opto-chemogenetic induction, this prototype demonstrates channel modulation via membrane-assisted molecular linkage, promising broad applicability to diverse membrane proteins.
Cross-domain information fusion for enhanced cell population delineation in single-cell spatial-omics data
Authors: Zhu Bokai , Gao Sheng , Chen Shuxiao , Yeung Jason , Bai Yunhao , Huang Amy Y. , Yeo Yao Yu , Liao Guanrui , Mao Shulin , Jiang Sizun , Rodig Scott J. , Shalek Alex K. , Nolan Garry P. , Jiang Sizun , Ma Zongming
Published: May 2024

Cell population delineation and identification is an essential step in single-cell and spatial-omics studies. Spatial-omics technologies can simultaneously measure information from three complementary domains related to this task: expression levels of a panel of molecular biomarkers at single-cell resolution, relative positions of cells, and images of tissue sections, but existing computational methods for performing this task on single-cell spatial-omics datasets often relinquish information from one or more domains. The additional reliance on the availability of “atlas” training or reference datasets limits cell type discovery to well-defined but limited cell population labels, thus posing major challenges for using these methods in practice. Successful integration of all three domains presents an opportunity for uncovering cell populations that are functionally stratified by their spatial contexts at cellular and tissue levels: the key motivation for employing spatial-omics technologies in the first place.

In this work, we introduceCell Spatio- andNeighborhood-informedAnnotation andPatterning (CellSNAP), a self-supervised computational method that learns a representation vector for each cell in tissue samples measured by spatial-omics technologies at the single-cell or finer resolution. The learned representation vector fuses information about the corresponding cell across all three aforementioned domains. By applying CellSNAP to datasets spanning both spatial proteomic and spatial transcriptomic modalities, and across different tissue types and disease settings, we show that CellSNAP markedly enhancesde novodiscovery of biologically relevant cell populations at fine granularity, beyond current approaches, by fully integrating cells’ molecular profiles with cellular neighborhood and tissue image information.
Circulating PD-1hiCXCR5- and CXCR5+ CD4 T cells are elevated in patients with newly diagnosed Giant Cell Arteritis and predict relapse
Authors: Monjo Irene , Nieto-Carvalhal Beatriz , Uyaguari Mariela , García-Carazo Sara , Balsa Alejandro , de Miguel Eugenio , Miranda-Carús María-Eugenia
Published: May 2024

BACKGROUND

Giant cell arteritis (GCA) is a large/medium-vessel granulomatous vasculitis, and the PD-1/PD-L1 coinhibitory pathway seems to be implicated in its pathogenesis. CD4 T cells expressing high PD-1 levels, CD4+CXCR5-PD-1hiperipheral helper (Tph) and CD4+CXCR5+PD-1hifollicular helper T cells (Tfh), are key mediators of autoimmunity. Their frequencies are elevated in the peripheral blood of subjects with several autoimmune conditions but have not been investigated in GCA. Our objective was to study the frequency of circulating Tph (cTph) and Tfh (cTfh) in patients with newly diagnosed GCA (nGCA).

METHODS

Prospective, non-interventional study on consecutive patients referred to our ultrasound GCA fast-track clinic over a period of 24 months. Peripheral blood was drawn immediately upon initial diagnosis. For each patient, an age and gender-matched healthy control (HC) was included. PBMCs isolated by Ficoll-Hypaque were examined by cytometry. Patients were subsequently treated with standard therapy according to the updated 2018 EULAR recommendations.

RESULTS

65 nGCA patients were included. As compared with HC, nGCA patients presented at baseline with an increased frequency of cTph and cTfh cells. Among the 46 patients who could be followed up for 12 months, 19 experienced a relapse. The baseline frequency of cTph and cTfh cells had been significantly lower in patients who relapsed as compared with those who did not. A cTph cell frequency <0.56 predicted relapse with a sensitivity of 90% and specificity of 93%.

CONCLUSION

nGCA patients demonstrate increased baseline cTph and cTfh cell frequencies. Lower baseline proportions of cTph and cTfh cells associate with relapse.
Development of a humanized anti-FABP4 monoclonal antibody for treatment of breast cancer
Authors: Hao Jiaqing , Jin Rong , Yi Yanmei , Jiang Xingshan , Yu Jianyu , Xu Zhen , Schnicker Nicholas J. , Chimenti Michael S. , Sugg Sonia L. , Li Bing
Published: May 2024

Background

Breast cancer, lung cancer, and colorectal cancer are the primary contributors to newly diagnosed cases among women, with breast cancer representing the second highest proportion of the total. The treatment protocols vary depends on different stages of breast cancer, and numerous clinical trials are ongoing based on the data derived from laboratory. Our studies demonstrate that circulating adipose fatty acid binding protein (A-FABP, or FABP4) links obesity-induced dysregulated lipid metabolism and breast cancer risk, thus offering a new target for breast cancer treatment.

Methods

We immunized FABP4 knockout mice with recombinant human FABP4 and screened hybridoma clones with specific binding to FABP4. The potential effects of antibodies on breast cancer cellsin vitrowere evaluated using migration, invasion, and limit dilution assays. Tumor progressionin vivowas evaluated in various types of tumorigenesis models including C57BL/6 mice, Balb/c mice, and SCID mice. The phenotype and function of immune cells in tumor microenvironment were characterized with multi-color flow cytometry. Tumor stemness was detected by ALDH assays. To characterize antigen-antibody binding capacity, we determined the dissociation constant of S-V9 against FABP4 via surface plasmon resonance. Further analyses in tumor tissue were performed using 10X Genomics Visium spatial single cell technology.

Results

Herein, we report the generation of humanized monoclonal antibodies blocking FABP4 activity for breast cancer treatment in mouse models. One clone, named 12G2, which significantly reduced circulating levels of FABP4 and inhibited mammary tumor growth, was selected for further characterization. After confirming the therapeutic efficacy of the chimeric 12G2 monoclonal antibody consisting of mouse variable regions and human IgG1 constant regions, 16 humanized 12G2 monoclonal antibody variants were generated by grafting its complementary determining regions to selected human germline sequences. Humanized V9 monoclonal antibody showed consistent results in inhibiting mammary tumor growth and metastasis by affecting tumor cell mitochondrial metabolism.

Conclusions

Our current evidence suggest that targeting FABP4 with humanized monoclonal antibodies represents a novel strategy for the treatment of breast cancer and possibly other obesity- associated diseases.
Estradiol induces global changes in miRNA expression in endometrial cancer cells and upregulates oncogenic miR-182
Authors: Klicka Klaudia , Grzywa Tomasz M. , Wejman Jarosław , Ostrowska Joanna , Włodarski Paweł K.
Published: May 2024

Endometrial cancer (EC) occurs mainly in perimenopausal age. Risk factors are associated with unopposed estrogen stimulation of the endometrium. There are two main types of EC, EC1 and EC2. The pathogenesis of EC1 is estrogen-dependent. MiRNAs are small RNAs that regulate gene expression posttranscriptionally. They are induced by estrogens in different hormone-dependent neoplasias including breast cancer. However, little is known regarding their role in EC. Thus, this study aims to assess the role of the miRNA-estrogen axis in endometrial cancer cells. Estrogen-dependent endometrial cancer cell line Ishikawa was used in the study. Cells were incubated with estradiol, followed by RNA isolation. We used the microarray method to identify estradiol-induced miRNAs in EC cells. Then, we analyzed tissues derived from 45 patients (18 EC1, 12 EC2, and 15 healthy endometrium (HE)) that were cut using the Laser Capture Microdissection method. The expression of selected miRNAs and their targets was assessed using the RT-qPCR method. Ishikawa cells were transfected with miRNA mimic, miRNA inhibitor (anti-miRNA), and their scrambled controls. We identified 66 estrogen-upregulated miRNAs in endometrial cancer cells. Out of them, miR-182 was upregulated in EC1 compared to HE. We found that miR-182 is an oncomiR in EC since its increased expression promoted the proliferation of EC cells and decreased expression of miR-182 was associated with the inhibition of cancer cell proliferation. Moreover, miR-182 inhibition upregulated SMAD4 expression. Our study allowed us to better understand the role of estrogen in the pathogenesis of EC.
The 40 Hz flickering light restores synaptic plasticity and mitochondrial phenotype in experimental model of Alzheimer’s disease
Authors: Barzegar behrooz Amir , Aghanoori Mohamad-Reza , Khodagholi Fariba , Nazari Maryam , Latifi hamid , vosoghian Fatemeh , Anjomani Mojdeh , Lotfi Jaber , Ahmadiani Abolhassan , Eliassi Afsaneh , Nabavizadeh Fatemeh , Ghavami Saeid , soleimani Elham , Fahanik-babaei Javad
Published: May 2024

Alzheimer’s disease (AD) is the most prevalent form of dementia and a public health priority. The causes of AD are not completely understood. Pathogenetic factors including mitochondrial dysfunction, oxidative stress, reduced energy status, and compromised ion channels contribute to the onset and progression of the disease. Flickering light therapy in experimental and clinical AD has shown promising outcomes. However, the mechanisms behind the effect of flickering light at the molecular and cellular level has not yet been fully investigated. In this study, we established streptozotocin (STZ)-induced AD models by intracerebroventricular (ICV) injection of STZ in Wistar rats and monitored their memory decline. Sham and AD rats were either exposed or not exposed to 40 Hz flickering light for 7 consecutive days after 7 days of STZ injection. Memory and cognition-related behavioral analysis, pathological, electrophysiological, and biochemical assessment of the brain tissue, and mitochondrial function assays were conducted after the treatment. Cognitive and memory impairment, examined by Morris water maze (MWM), novel object recognition (NOR), and passive avoidance (PA) test, was observed in the STZ-induced AD rats and light treatment improved these behaviors. STZ injection led to significant accumulation of reactive oxygen species (ROS) and amyloid beta (Aβ), decreased serotonin and dopamine levels, and mitochondrial respiration. The 40 Hz flickering light reversed all these parameters in the light treatment group. The synaptic plasticity of STZ-induced AD rats was severely affected, but flickering light prevented the loss of synaptic plasticity and activity in the light-treated AD rats. Additionally, flickering 40 Hz white light elevated the levels of mitochondrial metabolites and the current and possible opening of the mitochondrial calcium-sensitive potassium (mitoBKCa) channel which were significantly downregulated in AD rat neurons. The 40 Hz flickering light restored mitochondrial function and synaptic plasticity of neurons in AD rats and improved the cognition of animals; therefore, it can be a promising strategy to reduce AD progression.
Automated and closed clinical-grade manufacturing protocol produces potent NK cells against neuroblastoma cells and AML blasts
Authors: Jahan Farhana , Penna Leena , Luostarinen Annu , Veltman Laurens , Hongisto Heidi , Lähteenmäki Kaarina , Müller Sabine , Ylä-Herttuala Seppo , Korhonen Matti , Vettenranta Kim , Laitinen Anita , Salmenniemi Urpu , Kerkelä Erja
Published: May 2024

Natural killer (NK) cells have great potential as allogeneic immune cell therapy due to their natural ability to recognize and kill tumor cells, and due to their apparent safety. This study describes the development of an immunotherapy option tailored for high-risk acute myeloid leukemia (AML) in adults and neuroblastoma in children. A GMP-compliant manufacturing protocol for the local production of functionally potent NK cells is detailed in the study, including a comprehensive description of the quality control strategy and considerations for product batch specifications in early clinical development. The protocol is based on the closed, automated CliniMACS Prodigy® platform (Miltenyi Biotec) and a modified Natural Killer Cell Transduction (NKCT) process without transduction and expansion. NK cells are isolated from leukapheresis through CD3 depletion and CD56 enrichment, followed by a 12-hour activation with cytokines (500 IU/ml IL-2, 140 IU/ml IL-15).

Three CliniMACS Prodigy® NKCT processes were executed, demonstrating the feasibility and consistency of the modified NKCT process. A three-step process without expansion, however, compromised the NK cell yield. T cells were depleted effectively, indicating excellent safety of the product for allogeneic use. Phenotypic and functional characterization of the NK cells before and after cytokine activation revealed a notable increase in the expression of activation markers, particularly CD69, consistent with enhanced functionality. Intriguingly, even following a brief 12-hour activation period, the NK cells exhibited increased killing efficacy against CD33+ AML blasts isolated from patients and against SH-SY5Y neuroblastoma (NBL) target cellsin vitro, suggesting a potential therapeutic benefit for AML and NBL patients.
Alterations in Causal Functional Brain Networks in Alzheimer’s Disease: A resting-state fMRI study
Authors: Biswas Rahul , Sripada SuryaNarayana
Published: May 2024

Background

Alterations in functional connectivity (FC) of the brain is known to predate the onset of clinical symptoms of Alzheimer’s disease (AD) by several decades. Identifying the altered functional brain networks in AD can help in its prognosis and diagnosis.

Objective

FC analysis is predominantly correlational. However, correlation does not necessarily imply causation. This study aims to infer causal functional connectivity (CFC) from functional magnetic resonance imaging (fMRI) data and obtain the sub-networks of CFC that are altered in AD compared to cognitively normal (CN) subjects.

Methods

We used the recently developed Time-aware PC algorithm to infer CFC between brain regions. The CFC outcome was compared with correlation-based functional connectivity obtained by sparse partial correlation. Then, Network-based Statistics (NBS) was used to obtain CFC sub-networks that altered in AD subjects compared to healthy controls while correcting for multiple comparisons at 5% level of significance.

Results

Our findings identified causal brain networks involving the inferior frontal gyrus, superior temporal gyrus (temporal pole), middle temporal gyrus (temporal pole), and different lobes of the cerebellum to be significantly reduced in strength in AD compared to CN group (p-value = 0.0299; NBS corrected). In the sample dataset that has been analysed, no brain networks were found to exhibit significant increase in strength in AD compared to CN group at 5% level of significance with NBS correction.

Conclusions

Our findings provide insights into disruptions in causal brain networks in AD. The corresponding brain regions are in agreement with published medical literature on brain regions impacted by AD. Our work establishes a methodology for finding causal brain networks that are affected by AD using TPC algorithm to compute subject-specific CFC and then using NBS for finding CFC subnetworks that alter between AD and CN groups. Larger datasets are expected to identify further subnetworks affected by AD.
Development and external validation of an ultrasound image-based deep learning model to estimate gestational age in the second and third trimesters of pregnancy using data from Garbh-Ini cohort: a prospective cohort study in North Indian population
Authors: Mishra Divyanshu , Chandramohan Varun , Sharma Nikhil , Gosain Mudita , Wadhwa Nitya , Natchu Uma Chandra Mouli ,   GARBH-Ini study group, Khurana Ashok , Noble J. Alison , Thiruvengadam Ramachandran , Desiraju Bapu Koundinya , Bhatnagar Shinjini
Published: May 2024

Accurate estimation of gestational age (GA) is essential to plan appropriate antenatal care. Current GA estimation models rely on fetal biometry measurements, which are susceptible to ethnic and pathological variations in fetal growth, especially in the second and third trimesters of pregnancy. In this study, we challenge the current paradigm of estimating GA using fetal biometry, by using ultrasound (US) images and deep learning models which can automatically learn image features associated with GA. We developed deep learning models for GA estimation using US images taken at 18-32 weeks of pregnancy from 2207 participants of Garbh-Ini - a hospital-based prospective cohort of pregnant women in North India. Further, we designed a novel conformal prediction (CP) algorithm to detect and reject images when there is a data distribution shift, preventing erroneous predictions. Our best model, GArbh-Ini Ultrasound image-based Gestational age Estimator (GAUGE), which was trained on US images of the fetal head (9647 images from 2207 participants), had a mean absolute error (MAE) of 2.8 days when evaluated on an internal test dataset (N = 204). GAUGE is 44% and 35% more accurate than the widely used Hadlock and INTERGROWTH-21st biometry-based GA models, respectively on the internal test dataset. For an external test dataset (N = 311), collected retrospectively from The Ultrasound Lab, New Delhi, the same model achieved a MAE of 5.9 days. In addition, we show that GAUGE relies on the finer details in the image instead of the fetal biometry and that this leads to a similar performance across small for gestational age (SGA) and appropriate for gestational age (AGA) groups. The ability of GAUGE to consider image features beyond derived biometry suggests that GAUGE offers a better choice for populations with a high prevalence of fetal growth restriction.
Dimension Reduction using Local Principal Components for Regression-based Multi-SNP Analysis in 1000 Genomes and the Canadian Longitudinal Study on Aging (CLSA)
Authors: Yavartanoo Fatemeh , Brossard Myriam , Bull Shelley B. , Paterson Andrew D. , Yoo Yun Joo
Published: May 2024

For genetic association analysis based on multiple SNP regression of genotypes obtained by dense DNA sequencing or array data imputation, multi-collinearity can be a severe issue causing failure to fit the regression model. In this study, we proposed a method of Dimension Reduction using Local Principal Components (DRLPC) which aims to resolve multi-collinearity by removing SNPs under the assumption that the remaining SNPs can capture the effect of a removed SNP due to high linear dependency. This approach to dimension reduction is expected to improve the power of regression-based statistical tests. We apply DRLPC to chromosome 22 SNPs of two data sets, the 1000 Genomes Project (phase 3) and Canadian Longitudinal Study on Aging (CLSA), and calculated Variance Inflation Factors (VIF) in various SNP-sets before and after implementing DRLPC as a metric of collinearity. Notably, DRLPC addresses multi-collinearity by excluding variables with a VIF exceeding a predetermined threshold (VIF=20), thereby improving applicability for subsequent regression analyses. The number of variables in a final set for regression analysis is reduced to around 20% on average for larger-sized genes, whereas for smaller ones, the proportion is around 48%; suggesting that DRLPC is more effective for larger genes. We also compare the power of several multi-SNP statistics constructed for gene-specific analysis to evaluate power gains achieved by DRLPC. In simulation studies based on 100 genes with ≤500 SNPs per gene, DRLPC effectively increased the power of the multiple regression Wald test from 60% to around 80%.
Advancing apple genetics research:Malus coronariaandMalus ioensisgenomes and a gene family-based pangenome of native North American apples
Authors: Svara Anze , Sun Honghe , Fei Zhangjun , Khan Awais
Published: May 2024

WildMalusspecies flourished in North America long before Europeans introduced domesticated apples.Malus coronariaandM. ioensisare native to the mid-western and eastern USA, whileM. angustifoliaandM. fuscagrow in the southeast and west, respectively. They offer disease resistance, climate and soil adaptability, and horticultural traits for apple breeding. However, their utilization remains limited due to insufficient genomic resources and specific genetics. We report high-quality phased chromosome-scale assemblies ofM. coronariaandM. ioensis, generated using long-read and conformation capture sequencing. Phylogenetic and synteny analysis indicated high relatedness between these two genomes and previously-published genome ofM. angustifolia, and lower relatedness withM. fusca. Gene family-based pangenome of North AmericanMalusidentified 60,211 orthogroups containing 340,087 genes. Genes involved in basic cellular and metabolic processes, growth, and development were core to the existence of these species, whereas genes involved in secondary metabolism, stress response, and interactions with other organisms were accessory and are likely associated with adaptation to specific environments. Structural variation hotspots were mostly overlapping with high gene density. This study offers novel native North AmericanMalusgenome resources that can be used to identify genes for apple breeding and understand their evolution and adaptation.
Frontal theta power prospectively associated with response inhibition
Authors: van Rooij Daan , van Bijnen Sam , Schutte Iris , van der Stoep Nathan , Kenemans J. Leon
Published: May 2024

A proactive mechanism has been postulated to promote successful inhibition (Kenemans, 2015). Specifically, this mechanism is thought to operate before any action demanding or countermanding event has occurred. In the current study, we investigated whether EEG theta power could reflect this mechanism, in a sample of healthy individuals performing a stop-signal paradigm. By comparing frontal theta power preceding failed versus successful stop trials, we tested whether frontal theta is predictive of inhibition success. We hypothesized that proactive cognitive control manifests in frontal theta power preceding a countermanding go-stop event. Our results demonstrate that frontal theta is indeed higher preceding successful as compared to preceding failed stopping events. We also show that frontal theta power preceding stopping events is associated with Stop-Signal Reaction Times (SSRT), with a higher theta being indicative of shorter SSRTs. This association was not present for go-RT. This study may be the first to reveal a relationship between lower frontal theta power and subsequent stopping failure, suggesting theta’s role in proactive response inhibition.
Adjuvanted subunit intranasal vaccine prevents SARS-CoV-2 onward transmission in hamsters
Authors: Sui Yongjun , Kar Swagata , Chawla Bhavna , Hoang Tanya , Yu YuanKai , Wallace Shannon M. , Andersen Hanne , Berzofsky Jay A.
Published: May 2024

Most COVID-19 vaccine trials have focused on recipient protection, not protection of their contacts, a critical need. As a subunit intranasal COVID-19 vaccine reduced nasopharyngeal virus more than did an intramuscular (IM) vaccine, we hypothesized that this vaccine might reduce onward transmission to others. We vaccinated hamsters with either the IM-administrated Moderna mRNA vaccine twice or one dose of mRNA IM followed by adjuvanted subunit intranasal vaccine. 24 hours after SARS-CoV-2 challenge, these animals were housed with naïve recipients in a contactless chamber that allows airborne transmission. Onward airborne transmission was profoundly blocked: the donor and recipients of the intranasal vaccine-boosted group had lower oral and lung viral loads (VL), which correlated with mucosal ACE2 inhibition activity. These data strongly support the use of the intranasal vaccine as a boost to protect not only the vaccinated person, but also people exposed to the vaccinated person, a key public health goal.

Author summary

Natural transmission of SARS-CoV-2 is primarily airborne, through the respiratory mucosal route. However, current licensed COVID-19 vaccines are all intramuscular and induce more systemic than mucosal immunity. Here, we did a head-to-head comparison of COVID-19 booster vaccines on SARS-CoV-2 onward transmission. We found that compared to boosting with a Moderna mRNA systemic vaccine, a nanoparticle intranasal COVID-19 vaccine much more effectively prevents onward airborne transmission to naïve recipient hamsters. The protection was correlated with local mucosal antibody. Thus, a mucosal nanoparticle vaccine should be considered for preventing onward airborne transmission, a key public health necessity that has not been adequately studied.
Modulation of aperiodic EEG activity provides sensitive index of cognitive state changes during working memory task
Authors: Frelih Tisa , Matkovič Andraž , Mlinarič Tjaša , Bon Jurij , Repovš Grega
Published: May 2024

To better understand cognitive processes, it is essential to examine the interplay between periodic (oscillatory) and aperiodic electrophysiological brain activity. In this study, we aim to clarify how the periodic and aperiodic electrophysiological components respectively reflect the cognitive processes involved in working memory. Fiftyseven participants performed an n-back task while their brain activity was recorded using EEG. The analysis of both components of the EEG spectrum during task performance indicate that both periodic and aperiodic activities exhibit distinct taskrelated spatiotemporal dynamics that are closely related to cognitive demands. The results indicate that the substantial changes traditionally attributed to theta oscillations in working memory tasks are, in fact, due to shifts in the spectral slope of aperiodic activity. This suggests that the modulation of aperiodic activity associated with cognitive control processes may provide a more sensitive index of cognitive state changes than previously recognised. To validate our findings, we also used these analysis methods in another working memory task, which showed similar patterns of periodic and aperiodic activity. Our findings challenge the conventional understanding of theta oscillations in cognitive processing and question the routine practice of EEG baseline correction in time-frequency analysis, which may obscure significant modulations in continuous working memory tasks. Consequently, the inclusion of aperiodic activity as a fundamental component of EEG analysis is critical to the accurate representation of the neural basis of cognition.
AFFIPred: AlphaFold2 Structure-based Functional Impact Prediction of Missense Variations
Authors: Pir Mustafa Samet , Timucin Emel
Published: May 2024

Structural information holds immense potential for pathogenicity prediction of missense variations, albeit structure-based pathogenicity classifiers are limited compared to their sequence-based counterparts due to the well-known gap between sequence and structure data. Leveraging the highly accurate protein structure prediction method, AlphaFold2 (AF2), we introduce AFFIPred, an ensemble machine learning classifier that combines established sequence and AF2-based structural characteristics to predict disease-causing missense variant pathogenicity. Based on the assessments on unseen datasets, AFFIPred reached a comparable level of performance with the state-of-the-art predictors such as AlphaMissense and Rhapsody. We also showed that the recruitment of AF2 structures that are full-length and represent the unbound states ensures more precise SASA calculations compared to the recruitment of experimental structures. Second, in line with the the completeness of the AF2 structures, their use provide a more comprehensive view of the structural characteristics of the missense variation datasets by capturing all variants. AFFIPred maintains high-level accuracy without the well-known limitations of structure-based pathogenicity classifiers, paving the way for the development of more sophisticated structure-based methods without PDB dependence. AFFIPred has predicted over 210 million variations of the human proteome, which are accessible athttps://affipred.timucinlab.com/.
Nerve injury converts Schwann cells in a persisting repair state in human neuroma tissue
Authors: Deininger Stefanie , Schumacher Jakob , Blechschmidt Anna , Song Jialei , Klugmann Claudia , Antoniadis Gregor , Pedro Maria , Knöll Bernd , Meyer zu Reckendorf Sofia
Published: May 2024

Peripheral nerve injury (PNI) induces neuroma formation at the severed nerve stump resulting in impaired nerve regeneration and functional recovery in patients. So far, molecular mechanisms and cell types present in the neuroma impeding on regeneration have only sparsely been analyzed. Herein we compare resected human neuroma tissue with intact donor nerves from the same patient. Neuroma from several post-injury timepoints (1-13 months) were included, thereby allowing for temporal correlation with molecular and cellular processes. We observed reduced axonal area and percentage of myelin producing Schwann cells (SCs) compared to intact nerves. However, total SOX10 positive SC numbers were comparable. Notably, markers for SCs in a repair mode including c-JUN and SHH (sonic hedgehog) and SC proliferation (pH3) were upregulated in neuroma, suggesting presence of SCs in repair rather than differentiated status. In agreement, in neuroma, pro-regenerative markers such as phosphorylated i.e. activated CREB (pCREB), ATF3, GAP43 and SCG10 were upregulated. Neuroma tissue was infiltrated by several types of macrophages. Finally, when taken in culture, neuroma SCs were indistinguishable from controls SCs with regard to proliferation and morphology. However, cultured neuroma SCs retained a different molecular signature from control SCs including increased inflammation and reduced gene expression for differentiation markers such as myelin genes.

In summary, human neuroma tissue consists of SCs with a repair status and is infiltrated strongly by several types of macrophages.