bluuebunny/crossref_metadata_2025 huggingface dataset:
The distribution of volatile elements during rocky planet formation
Authors: Suer Terry-Ann , Jackson Colin , Grewal Damanveer S. , Dalou Celia , Lichtenberg Tim
Published: November 2023

Core segregation and atmosphere formation are two of the major processes that redistribute the volatile elements—hydrogen (H), carbon (C), nitrogen (N), and sulfur (S)—in and around rocky planets during their formation. The volatile elements by definition accumulate in gaseous reservoirs and form atmospheres. However, under conditions of early planet formation, these elements can also behave as siderophiles (i.e., iron-loving) and become concentrated in core-forming metals. Current models of core formation suggest that metal-silicate reactions occurred over a wide pressure, temperature, and compositional space to ultimately impose the chemistries of the cores and silicate portions of rocky planets. Additionally, the solubilities of volatile elements in magmas determine their transfer between the planetary interiors and atmospheres, which has recently come into sharper focus in the context of highly irradiated, potentially molten exoplanets. Recently, there has been a significant push to experimentally investigate the metal-silicate and magma-gas exchange coefficients for volatile elements over a wide range of conditions relevant to rocky planet formation. Qualitatively, results from the metal-silicate partitioning studies suggest that cores of rocky planets could be major reservoirs of the volatile elements though significant amounts will remain in mantles. Results from solubility studies imply that under oxidizing conditions, most H and S are sequestered in the magma ocean, while most N is outgassed to the atmosphere, and C is nearly equally distributed between the atmosphere and the interior. Under reducing conditions, nearly all N dissolves in the magma ocean, the atmosphere becomes the dominant C reservoir, while H becomes more equally distributed between the interior and the atmosphere, and S remains dominantly in the interior. These chemical trends bear numerous implications for the chemical differentiation of rocky planets and the formation and longevity of secondary atmospheres in the early Solar System and exoplanetary systems. Further experimental and modeling efforts are required to understand the potential of chemical and physical disequilibria during core formation and magma ocean crystallization and to constrain the distributions of volatile elements in the interiors and atmospheres of rocky planets through their formation and long-term geologic evolution.
A clinical prediction model based on interpretable machine learning algorithms for prolonged hospital stay in acute ischemic stroke patients: a real-world study
Authors: Wang Kai , Jiang Qianmei , Gao Murong , Wei Xiu’e , Xu Chan , Yin Chengliang , Liu Haiyan , Gu Renjun , Wang Haosheng , Li Wenle , Rong Liangqun
Published: November 2023

Objective

Acute ischemic stroke (AIS) brings an increasingly heavier economic burden nowadays. Prolonged length of stay (LOS) is a vital factor in healthcare expenditures. The aim of this study was to predict prolonged LOS in AIS patients based on an interpretable machine learning algorithm.

Methods

We enrolled AIS patients in our hospital from August 2017 to July 2019, and divided them into the “prolonged LOS” group and the “no prolonged LOS” group. Prolonged LOS was defined as hospitalization for more than 7 days. The least absolute shrinkage and selection operator (LASSO) regression was applied to reduce the dimensionality of the data. We compared the predictive capacity of extended LOS in eight different machine learning algorithms. SHapley Additive exPlanations (SHAP) values were used to interpret the outcome, and the most optimal model was assessed by discrimination, calibration, and clinical utility.

Results

Prolonged LOS developed in 149 (22.0%) of the 677 eligible patients. In eight machine learning algorithms, prolonged LOS was best predicted by the Gaussian naive Bayes (GNB) model, which had a striking area under the curve (AUC) of 0.878 ± 0.007 in the training set and 0.857 ± 0.039 in the validation set. The variables sorted by the gap values showed that the strongest predictors were pneumonia, dysphagia, thrombectomy, and stroke severity. High net benefits were observed at 0%–76% threshold probabilities, while good agreement was found between the observed and predicted probabilities.

Conclusions

The model using the GNB algorithm proved excellent for predicting prolonged LOS in AIS patients. This simple model of prolonged hospitalization could help adjust policies and better utilize resources.
Development and validation of a nomogram for predicting ongoing pregnancy in single vitrified-warmed blastocyst embryo transfer cycles
Authors: Park Jae Kyun , Park Ji Eun , Bang Soyoung , Jeon Haeng Jun , Kim Ji Won , Lee Woo Sik
Published: November 2023

Introduction

The global adoption of the “freeze-all strategy” has led to a continuous increase in utilization of single vitrified-warmed blastocyst embryo transfer (SVBT) owing to its clinical effectiveness. Accurate prediction of clinical pregnancy is crucial from a patient-centered perspective. However, this remains challenging, with inherent limitations due to the absence of precise and user-friendly prediction tools. Thus, this study primarily aimed to develop and assess a nomogram based on quantitative clinical data to optimize the efficacy of personalized prognosis assessment.

Materials and methods

We conducted a retrospective cohort analysis of ongoing pregnancy data from 658 patients with infertility who underwent SVBT at our center between October 17, 2017, and December 18, 2021. Patients were randomly assigned to the training (n=461) or validation (n=197) cohort for nomogram development and testing, respectively. A nomogram was constructed using the results of the multivariable logistic regression (MLR), which included clinical covariates that were assessed for their association with ongoing pregnancy.

Results

The MLR identified eight significant variables that independently predicted ongoing pregnancy outcomes in the study population. These predictors encompassed maternal physiology, including maternal age at oocyte retrieval and serum anti-Müllerian hormone levels; uterine factors, such as adenomyosis; and various embryo assessment parameters, including the number of fertilized embryos, blastocyst morphology, blastulation day, blastocyst re-expansion speed, and presence of embryo string. The area under the receiver operating characteristic curve in our prediction model was 0.675 (95% confidence interval [CI], 0.622–0.729) and 0.656 (95% CI, 0.573–0.739) in the training and validation cohorts, respectively, indicating good discrimination performance in both cohorts.

Conclusions

Our individualized nomogram is a practical and user-friendly tool that can provide accurate and useful SVBT information for patients and clinicians. By offering this model to patients, clinical stakeholders can alleviate uncertainty and confusion about fertility treatment options and enhance patients’ confidence in making informed decisions.
Metabolic and senescence characteristics associated with the immune microenvironment in ovarian cancer
Authors: Xiong Jian , Fu Yiyuan , Huang Jiezheng , Wang Yibin , Jin Xiaolong , Wan Xiaoyan , Huang Liu , Huang Zheng
Published: November 2023

Ovarian cancer is a highly malignant gynecological cancer influenced by the immune microenvironment, metabolic reprogramming, and cellular senescence. This review provides a comprehensive overview of these characteristics. Metabolic reprogramming affects immune cell function and tumor growth signals. Cellular senescence in immune and tumor cells impacts anti-tumor responses and therapy resistance. Targeting immune cell metabolism and inducing tumor cell senescence offer potential therapeutic strategies. However, challenges remain in identifying specific targets and biomarkers. Understanding the interplay of these characteristics can lead to innovative therapeutic approaches. Further research is needed to elucidate mechanisms, validate strategies, and improve patient outcomes in ovarian cancer.
Dissecting causal associations of type 2 diabetes with 111 types of ocular conditions: a Mendelian randomization study
Authors: Chen Rumeng , Xu Shuling , Ding Yining , Li Leyang , Huang Chunxia , Bao Meihua , Li Sen , Wang Qiuhong
Published: November 2023

Background

Despite the well-established findings of a higher incidence of retina-related eye diseases in patients with diabetes, there is less investigation into the causal relationship between diabetes and non-retinal eye conditions, such as age-related cataracts and glaucoma.

Methods

We performed Mendelian randomization (MR) analysis to examine the causal relationship between type 2 diabetes mellitus (T2DM) and 111 ocular diseases. We employed a set of 184 single nucleotide polymorphisms (SNPs) that reached genome-wide significance as instrumental variables (IVs). The primary analysis utilized the inverse variance-weighted (IVW) method, with MR-Egger and weighted median (WM) methods serving as supplementary analyses.

Results

The results revealed suggestive positive causal relationships between T2DM and various ocular conditions, including “Senile cataract” (OR= 1.07; 95% CI: 1.03, 1.11; P=7.77×10-4), “Glaucoma” (OR= 1.08; 95% CI: 1.02, 1.13; P=4.81×10-3), and “Disorders of optic nerve and visual pathways” (OR= 1.10; 95% CI: 0.99, 1.23; P=7.01×10-2).

Conclusion

Our evidence supports a causal relationship between T2DM and specific ocular disorders. This provides a basis for further research on the importance of T2DM management and prevention strategies in maintaining ocular health.
Energy management considering multiple power markets and microgrid storage
Authors: Yan Mengxuan , Li Zhanlian , Lai Chun Sing , Zhao Zhuoli , Zobaa Ahmed F. , Lai Loi Lei , Shi Zebing
Published: November 2023

The operational cost of a microgrid is significantly influenced by the response of storage systems and the complexities of the power market’s tariff structures. This paper addresses the challenges arising from the coexistence of new market entries and traditional tariffs, which contribute to a complex market environment. To tackle this issue, the paper establishes a microgrid market environment encompassing four types of tariffs. By modeling the response of electric storage and cold storage in a microgrid, the study formulates a non-linear mixed-integer optimization problem. Numerical studies are then conducted to verify the model and analyze market performance. The results reveal a trade-off in behavior among different market entries when optimizing the total cost of microgrid operation. These findings shed light on the complexities and trade-offs involved in microgrid operational cost optimization within a diverse market environment, offering valuable insights for market participants.
A short-term hybrid wind speed prediction model based on decomposition and improved optimization algorithm
Authors: Wang Lu , Liao Yilan
Published: November 2023

Introduction: In the field of wind power generation, short-term wind speed prediction plays an increasingly important role as the foundation for effective utilization of wind energy. However, accurately predicting wind speed is highly challenging due to its complexity and randomness in practical applications. Currently, single algorithms exhibit poor accuracy in short-term wind speed prediction, leading to the widespread adoption of hybrid wind speed prediction models based on deep learning techniques. To comprehensively enhance the predictive performance of short-term wind speed models, this study proposes a hybrid model, VMDAttention LSTM-ASSA, which consists of three stages: decomposition of the original wind speed sequence, prediction of each mode component, and weight optimization.

Methods: To comprehensively enhance the predictive performance of short-term wind speed models, this study proposes a hybrid model, VMDAttention LSTM-ASSA, which consists of three stages: decomposition of the original wind speed sequence, prediction of each mode component, and weight optimization. Firstly, the model incorporates an attention mechanism into the LSTM model to extract important temporal slices from each mode component, effectively improving the slice prediction accuracy. Secondly, two different search operators are introduced to enhance the original Salp Swarm Algorithm, addressing the issue of getting trapped in local optima and achieving globally optimal short-term wind speed predictions.

Result: Through comparative experiments using multiple-site short-term wind speed datasets, this study demonstrates that the proposed VMD-AtLSTM-ASSA model outperforms other hybrid prediction models (VMD-RNN, VMD-BPNN, VMD-GRU, VMD-LSTM) with a maximum reduction of 80.33% in MAPE values. The experimental results validate the high accuracy and stability of the VMD-AtLSTM-ASSA model.

Discussion: Short-term wind speed prediction is of paramount importance for the effective utilization of wind power generation, and our research provides strong support for enhancing the efficiency and reliability of wind power generation systems. Future research directions may include further improvements in model performance and extension into other meteorological and environmental application domains.
A bi-layer wind-CCUS-battery expansion stochastic planning framework considering a source-load bilateral carbon incentive mechanism based on the carbon emission flow theory
Authors: Deng Xu , Nan Junpei , Feng Jieran , Gong Xianfu , Zhou Hao , Tang Wenhu
Published: November 2023

The rapid development of low-carbon energy technologies and energy storage technologies has provided an important and feasible path to decarbonizing the power system. In this context, there is an increasing number of studies on renewable energy, carbon capture, utilization and storage (CCUS) and energy storage expansion planning. However, most of the existing studies attribute the carbon responsibilities to the source side and a small number to the load side. Expansion planning studies that consider the overall carbon emissions of the system to be shared between the source and the load side are still relatively few. Therefore, it is necessary for the source and the load side to share the responsibility for the total system carbon emissions. To fill this research gap, this paper proposes a source-load bilateral carbon incentive mechanism for wind-CCUS-battery power systems based on the carbon emission flow theory. Besides, a bi-layer wind-CCUS-battery expansion stochastic planning framework considering wind and load uncertainties is constructed. The first layer takes the minimum expectation of power generation costs, fixed investment costs of wind turbines and CCUS units and carbon incentive costs as the objective function from a source-side perspective. The second layer takes the minimum battery investment cost and the expectation of electricity purchasing costs and load-side carbon incentive costs as the objective function from a load-side perspective. Finally, the proposed model is tested on the IEEE 24 bus power system for validity and advantage. The results show that the current high investment cost is not favorable to CCUS construction. At this time, the bilateral carbon incentive mechanism is more conducive to promoting system carbon reduction than the unilateral carbon incentive mechanism. In the future, as the cost of CCUS decreases, the source-side carbon incentive mechanism is more conducive to system carbon reduction than the bilateral carbon incentive mechanism. Due to the consideration of the stochastic uncertainty of wind turbines and loads, the research in this paper is closer to the reality, which can provide a reference for the future carbon emission reduction path of the power system, especially for the quantitative analysis of carbon emission reduction of CCUS, which is an important guiding significance for the promotion of the engineering practice of CCUS.
Grid interface control of wind–solar generator in Hail region of Saudi Arabia using FOPI controller
Authors: Younsi Sami , Kahouli Omar , Alsaif Haitham , Ali Naim Ben , Chaabane Mohamed
Published: November 2023

This study investigates the performance of a wind–solar generator (WSG) in the Hail region of Kingdom of Saudi Arabia (KSA) with a fractional order PI controller (FOPI) applied to the grid connection line. The proposed hybrid generator consists of a wind turbine with a PMSM machine and a PV panel connected to a secondary distribution grid by a DC link, three-phase inverter, and an RL filter. The line currents injected into the grid and/or loads are controlled by calculating the output reference voltage of an inverter and by the reference active and reactive requested powers. For this purpose, control loops around the RL filter were developed with fractional-order proportional-integral (FOPI) controllers, and a comparison with classic PI controllers was made. The system was simulated using the MATLAB/Simulink software. The results showed that the generator satisfied the power demand under the climatic conditions of the Hail region. They also demonstrated the good performance of the proposed controllers, which had good tracking accuracy and robustness to variations in wind speed and power demanded by loads in a very short time. The FOPI controller exhibited faster dynamic response and less overshoot than the classic PI controller.
The green divide and heat exposure: urban transformation projects in istanbul
Authors: Yazar Mahir , Daloglu Cetinkaya Irem , Iban Muzaffer Can , Bilgilioglu Suleyman Sefa
Published: November 2023

Extreme heat events are happening more frequently and with greater severity, causing significant negative consequences, especially for vulnerable urban populations around the globe. Heat stress is even more common in cities with dense and irregular planning and lacking urban blue-green infrastructures. This study investigates the greening and cooling effects of five selected urban transformation projects and their surrounding areas (within a 10-min walking distance) in Istanbul from 2013 to 2021, with a focus on environmental justice and climate adaptation planning perspectives. By employing temporal analysis of Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) values derived from Landsat data sets to detect changes in these five selected urban transformation projects in the megacity of Türkiye, Istanbul, this study finds that the distribution of green infrastructures (e.g., tree canopy) is only limited to project sites of long-running and state-supported urban transformation projects in Istanbul. Consequently, the unequal distribution of green infrastructures creates cooling effects only for the locals residing in the new residential projects. However, the surrounding areas have less urban green infrastructure and are exposed more to the urban heat over time. Urban development policies and planning highly contribute to increasing the climate vulnerabilities among those who do not benefit from the recently developed residential units in Istanbul. Such a trend can affect adaptive capacity of vulnerable communities and redress environmental injustices in urban planning in the megacity of Istanbul.
Computational profiling and prognostic modeling based on lysosome-related genes in colorectal cancer
Authors: Zhang Linjie , Yang Jingbang , Deng Yizhang , Deng Wuguo , Li Liren
Published: November 2023

Background: Despite significant advances over the past decade, patients diagnosed with advanced colorectal cancer (CRC) continue to face unfavorable prognoses. Recent studies have underscored the pivotal role of lysosomes in tumor development and progression. This led us to postulate and develop a novel lysosomal-centric model for predicting CRC risk and therapeutic response.

Methods: CRC tissue samples were sourced from the TCGA database, while lysosome-associated genes were collated from the GSEA database. Differentially expressed lysosome-related genes (DE-LRGs) were discerned by contrasting tumor samples with normal tissue. Based on the expression profile of DE-LRGs, patients were stratified into two distinct clusters. Survival disparities between the clusters were delineated using Kaplan-Meier estimators. For tumor microenvironment assessment, we employed ESTIMATE and ssGSEA. Functional pathway enrichment was ascertained using both GSVA and GSEA. Subsequent uni- and multi-variate Cox regression analyses pinpointed risk-associated DE-LRGs. Leveraging these genes, we constructed a novel risk prediction model and derived risk scores. The model’s prognostic capability was externally validated using dataset GSE39084. The mutational landscape across risk categories was evaluated using the Maftools algorithm. The potential efficacy of targeted and immunotherapeutic interventions for each patient cohort was gauged using pRRophetic, CYT, and IMvigor210.

Results: We identified 46 DE-LRGs. Tumor Immune MicroEnvironment (TIME) assessment revealed that cluster 2 patients exhibited elevated ESTIMATE, Immunocore, and stromal scores, yet diminished tumor purity relative to cluster 1. Notable differences in immune cell infiltration patterns were observed between clusters, and distinct pathway enrichments were evident. Cluster 2 manifested a pronounced expression of immune checkpoint-related genes. Four DE-LRGs (ATP6V0A4, GLA, IDUA, and SLC11A1) were deemed critical for risk association, leading to the formulation of our novel risk model. The model exhibited commendable predictive accuracy, which was corroborated in an external validation cohort. A palpable survival advantage was observed in high-TMB, low-risk subgroups. Moreover, the low-risk cohort displayed heightened sensitivity to both targeted and immunotherapeutic agents.

Conclusion: Our findings underscore the potential of lysosome-associated genes as robust prognostic and therapeutic response markers in CRC patients.
Expanding the phenotype and metabolic basis of ATP6AP2-congenital disorder of glycosylation in a Chinese patient with a novel variant c.185G>A (p.Gly62Glu)
Authors: Fang Yuan , Wang Yi-Zhen , Chen Lian , Xie Xin-Bao
Published: November 2023

Background: A rare X-linked hereditary condition known as ATP6AP2-congenital disorder of glycosylation (ATP6AP2-CDG) is caused by pathogenic variants in ATP6AP2, resulting in autophagic misregulation with reduced siganling of mammalian target of rapamycin (mTOR) that clinically presents with aberrant protein glycosylation, hepatosteatosis, immunodeficiency, cutis laxa, and psychomotor dysfunction. To date, only two missense mutations have been reported in three patients from two unrelated families.

Methods: In order to extend the profiles of phenotype and genotype associated with ATP6AP2-CDG, we assessed the clinical history, whole exome sequencing (WES), and liver histology as well as immunohistochemistry in a Chinese patient, and performed quantitative real-time polymerase chain reaction (qRT-PCR), Western blotting and untargeted metabolomics in genetic exogenously constructed cells.

Results: The 11-month-old Chinese boy presented with recurrent jaundice, cutis laxa, cirrhosis, growth retardation, coagulopathy, anemia, and cardiomegaly, and underwent liver transplantation. A novel mutation, c.185G>A (p.Gly62Glu), was identified in exon 3 of ATP6AP2. The expression of ATP6AP2 was observed to remain unchanged in the liver sample of the patient as well as in HEK293T cells harboring the p.Gly62Glu. This missense mutation was found to dysregulate autophagy and mTOR signaling. Moreover, metabolomics analysis revealed that the exogenously introduced Gly62Glu mutant resulted in the downregulation of numerous metabolites involved in lipid metabolism pathway.

Conclusion: This study may enable a more detailed exploration of its precise pathogenesis and potential therapeutic interventions.
Integrated antibody and cellular immunity monitoring are required for assessment of the long term protection that will be essential for effective next generation vaccine development
Authors: Paramithiotis Eustache , Varaklis Christophe , Pillet Stephane , Shafiani Shahin , Lancelotta Mary Pat , Steinhubl Steve , Sugden Scott , Clutter Matt , Montamat-Sicotte Damien , Chermak Todd , Crawford Stephanie Y. , Lambert Bruce L. , Mattison John , Murphy Robert L.
Published: November 2023

The COVID pandemic exposed the critical role T cells play in initial immunity, the establishment and maintenance of long term protection, and of durable responsiveness against novel viral variants. A growing body of evidence indicates that adding measures of cellular immunity will fill an important knowledge gap in vaccine clinical trials, likely leading to improvements in the effectiveness of the next generation vaccines against current and emerging variants. In depth cellular immune monitoring in Phase II trials, particularly for high risk populations such as the elderly or immune compromised, should result in better understanding of the dynamics and requirements for establishing effective long term protection. Such analyses can result in cellular immunity correlates that can then be deployed in Phase III studies using appropriate, scalable technologies. Measures of cellular immunity are less established than antibodies as correlates of clinical immunity, and some misconceptions persist about cellular immune monitoring usefulness, cost, complexity, feasibility, and scalability. We outline the currently available cellular immunity assays, review their readiness for use in clinical trials, their logistical requirements, and the type of information each assay generates. The objective is to provide a reliable source of information that could be leveraged to develop a rational approach for comprehensive immune monitoring during vaccine development.
Adoptive transfer of allergen-expressing B cells prevents IgE-mediated allergy
Authors: Prickler Lisa , Baranyi Ulrike , Mengrelis Konstantinos , Weijler Anna Marianne , Kainz Verena , Kratzer Bernhard , Steiner Romy , Mucha Jasmin , Rudoph Elisa , Pilat Nina , Bohle Barbara , Strobl Herbert , Pickl Winfried Franz , Valenta Rudolf , Linhart Birgit , Wekerle Thomas
Published: November 2023

Introduction

Prophylactic strategies to prevent the development of allergies by establishing tolerance remain an unmet medical need. We previously reported that the transfer of autologous hematopoietic stem cells (HSC) expressing the major timothy grass pollen allergen, Phl p 5, on their cell surface induced allergen-specific tolerance in mice. In this study, we investigated the ability of allergen-expressing immune cells (dendritic cells, CD4+ T cells, CD8+ T cells, and CD19+ B cells) to induce allergen-specific tolerance in naive mice and identified CD19+ B cells as promising candidates for allergen-specific cell therapy.

Methods

For this purpose, CD19+ B cells were isolated from Phl p 5-transgenic BALB/c mice and transferred to naive BALB/c mice, pre-treated with a short course of rapamycin and an anti-CD40L antibody. Subsequently, the mice were subcutaneously sensitized three times at 4-week intervals to Phl p 5 and Bet v 1 as an unrelated control allergen. Allergen-expressing cells were followed in the blood to monitor molecular chimerism, and sera were analyzed for Phl p 5- and Bet v 1-specific IgE and IgG1 levels by RBL assay and ELISA, respectively. In vivo allergen-induced lung inflammation was measured by whole-body plethysmography, and mast cell degranulation was determined by skin testing.

Results

The transfer of purified Phl p 5-expressing CD19+ B cells to naive BALB/c mice induced B cell chimerism for up to three months and prevented the development of Phl p 5-specific IgE and IgG1 antibody responses for a follow-up period of 26 weeks. Since Bet v 1 but not Phl p 5-specific antibodies were detected, the induction of tolerance was specific for Phl p 5. Whole-body plethysmography revealed preserved lung function in CD19+ B cell-treated mice in contrast to sensitized mice, and there was no Phl p 5-induced mast cell degranulation in treated mice.

Discussion

Thus, we demonstrated that the transfer of Phl p 5-expressing CD19+ B cells induces allergen-specific tolerance in a mouse model of grass pollen allergy. This approach could be further translated into a prophylactic regimen for the prevention of IgE-mediated allergy in humans.
Distinct effector functions mediated by Fc regions of bovine IgG subclasses and their interaction with Fc gamma receptors
Authors: Noble Alistair , Paudyal Basudev , Schwartz John C. , Mwangi William , Munir Danish , Tchilian Elma , Hammond John A. , Graham Simon P.
Published: November 2023

Cattle possess three IgG subclasses. However, the key immune functions, including complement and NK cell activation, and enhancement of phagocytosis, are not fully described for bovine IgG1, 2 and 3. We produced chimeric monoclonal antibodies (mAbs) consisting of a defined variable region linked to the constant regions of bovine IgG1, 2 and 3, and expressed His-tagged soluble recombinant bovine Fc gamma receptors (FcγRs) IA (CD64), IIA (CD32A), III (CD16) and Fcγ2R. Functional assays using bovinized mAbs were developed. IgG1 and IgG3, but not IgG2, activated complement-dependent cytotoxicity. Only IgG1 could activate cattle NK cells to mobilize CD107a after antigen crosslinking, a surrogate assay for antibody-dependent cell cytotoxicity. Both IgG1 and IgG2 could trigger monocyte-derived macrophages to phagocytose fluorescently labelled antigen-expressing target cells. IgG3 induced only weak antibody-dependent cellular phagocytosis (ADCP). By contrast, monocytes only exhibited strong ADCP when triggered by IgG2. IgG1 bound most strongly to recombinant FcγRs IA, IIA and III, with weaker binding by IgG3 and none by IgG2, which bound exclusively to Fcγ2R. Immune complexes containing IgG1, 2 and 3 bound differentially to leukocyte subsets, with IgG2 binding strongly to neutrophils and monocytes and all subclasses binding platelets. Differential expression of the FcγRs on leukocyte subsets was demonstrated by surface staining and/or RT-qPCR of sorted cells, e.g., Fcγ2R mRNA was expressed in monocytes/macrophages, neutrophils, and platelets, potentially explaining their strong interactions with IgG2, and FcγRIII was expressed on NK cells, presumably mediating IgG1-dependent NK cell activation. These data reveal differences in bovine IgG subclass functionality, which do not correspond to those described in humans, mice or pigs, which is relevant to the study of these IgG subclasses in vaccine and therapeutic antibody development.
Prevalence and genetic diversity of rotavirus in Bangladesh during pre-vaccination period, 1973-2023: a meta-analysis
Authors: Sharif Nadim , Sharif Nazmul , Khan Afsana , Azpíroz Irma Domínguez , Diaz Raquel Martínez , Díez Isabel De la Torre , Parvez Anowar Khasru , Dey Shuvra Kanti
Published: November 2023

Introduction

Rotavirus infection is a major cause of mortality among children under 5 years in Bangladesh. There is lack of integrated studies on rotavirus prevalence and genetic diversity during 1973 to 2023 in Bangladesh.

Methods

This meta-analysis was conducted to determine the prevalence, genotypic diversity and seasonal distribution of rotavirus during pre-vaccination period in Bangladesh. This study included published articles on rotavirus A, rotavirus B and rotavirus C. We used Medline, Scopus and Google Scholar for published articles. Selected literatures were published between 1973 to 2023.

Results

This study detected 12431 research articles published on rotavirus. Based on the inclusion criteria, 29 of 75 (30.2%) studies were selected. Molecular epidemiological data was taken from 29 articles, prevalence data from 29 articles, and clinical symptoms from 19 articles. The pooled prevalence of rotavirus was 30.1% (95% CI: 22%-45%, p = 0.005). Rotavirus G1 (27.1%, 2228 of 8219) was the most prevalent followed by G2 (21.09%, 1733 of 8219), G4 (11.58%, 952 of 8219), G9 (9.37%, 770 of 8219), G12 (8.48%, 697 of 8219), and G3 (2.79%, 229 of 8219), respectively. Genotype P[8] (40.6%, 2548 of 6274) was the most prevalent followed by P[4] (12.4%, 777 of 6274) and P[6] (6.4%, 400 of 6274), respectively. Rotavirus G1P[8] (19%) was the most frequent followed by G2P [4] (9.4%), G12P[8] (7.2%), and G9P[8], respectively. Rotavirus infection had higher odds of occurrence during December and February (aOR: 2.86, 95% CI: 2.43-3.6, p = 0.001).

Discussion

This is the first meta-analysis including all the studies on prevalence, molecular epidemiology, and genetic diversity of rotavirus from 1973 to 2023, pre-vaccination period in Bangladesh. This study will provide overall scenario of rotavirus genetic diversity and seasonality during pre-vaccination period and aids in policy making for rotavirus vaccination program in Bangladesh. This work will add valuable knowledge for vaccination against rotavirus and compare the data after starting vaccination in Bangladesh.
Response to therapy in Richter syndrome: a systematic review with meta-analysis of early clinical trials
Authors: Sousa-Pimenta Mário , Martins Ângelo , Mariz José Mário , Berraondo Pedro
Published: November 2023

Introduction and aims

Richter syndrome (RS) represents the clonal evolution of chronic lymphocytic leukemia with histological transformation into a high-grade B cell lymphoma (diffuse large B cell lymphoma - DLBCL) or Hodgkin lymphoma. Considering that RS is an uncommon condition with poor prognosis, few high-quality evidence is available. To overcome this unmet need, this meta-analysis aimed to pool efficacy of early clinical trials in Richter syndrome (DLBCL subtype).

Methods

MEDLINE, Scopus and Web of Science were searched up to May of 2023 to identify clinical trials decoying efficacy. The pooled complete response, objective response and intension-to-treat failure rates were calculated by pharmacological categories (classical chemotherapy, immunochemotherapy, immunotherapy, Bruton-tyrosine kinase inhibitors, targeted approaches, cell-based therapies and combinatorial regimens) using the Der-Simonian and Laird random-effects model. The Freeman-Tukey double arcsine method was used to estimate variance and confidence intervals. Heterogeneity was assessed using the I2 method.

Results

Overall, from 1242 studies identified, 30 were included, pooling data from 509 patients. The higher efficacy rates when, cell-based therapies were excluded, were achieved by immunochemotherapeutic regimens followed by combinatorial regimens, with complete response rates of 21.54% (IC95%14.93-28.87) and 23.77% (IC95% 8.70-42.19), respectively. Bispecific antibodies (alone or coupled with a chemotherapy debulking strategy) overtook Bruton tyrosine kinase inhibitors response rates. The latter, although achieving objective response rates above average, presented scarce complete response rates. Checkpoint inhibitors alone usually do not lead to complete responses, but their effectiveness may improve when combined with other agents, unveiling the importance of immune microenvironmental modulation.

Conclusion

This is the first meta-analysis of early clinical trials assessing the impact of different therapeutics in RS. By analyzing the pooled efficacy estimates, our work suggests the role of a tailor-made bridging therapy for young patients with RS eligible for allogeneic hematopoietic stem cell transplantation (alloSCT), formally the only curative strategy.
The emerging role and therapeutic implications of bacterial and parasitic deubiquitinating enzymes
Authors: Wehrmann Markus , Vilchez David
Published: November 2023

Deubiquitinating enzymes (DUBs) are emerging as key factors for the infection of human cells by pathogens such as bacteria and parasites. In this review, we discuss the most recent studies on the role of deubiquitinase activity in exploiting and manipulating ubiquitin (Ub)-dependent host processes during infection. The studies discussed here highlight the importance of DUB host-pathogen research and underscore the therapeutic potential of inhibiting pathogen-specific DUB activity to prevent infectious diseases.
Fc-mediated functions and the treatment of severe respiratory viral infections with passive immunotherapy – a balancing act
Authors: Vanderven Hillary A. , Kent Stephen J.
Published: November 2023

Passive immunotherapies have been used to treat severe respiratory infections for over a century, with convalescent blood products from recovered individuals given to patients with influenza-related pneumonia as long ago as the Spanish flu pandemic. However, passive immunotherapy with convalescent plasma or hyperimmune intravenous immunoglobulin (hIVIG) has not provided unequivocal evidence of a clinical benefit for severe respiratory infections including influenza and COVID-19. Efficacy trials, primarily conducted in late-stage disease, have demonstrated inconsistent efficacy and clinical benefit for hIVIG treatment of severe respiratory infections. To date, most serological analyses of convalescent plasma and hIVIG trial samples have focused on the measurement of neutralizing antibody titres. There is, however, increasing evidence that baseline antibody levels and extra-neutralizing antibody functions influence the outcome of passive immunotherapy in humans. In this perspective, findings from convalescent plasma and hIVIG trials for severe influenza, COVID-19 and respiratory syncytial virus (RSV) will be described. Clinical trial results will be discussed in the context of the potential beneficial and deleterious roles of antibodies with Fc-mediated effector functions, with a focus on natural killer cells and antibody-dependent cellular cytotoxicity. Overall, we postulate that treating respiratory viral infections with hIVIG represents a delicate balance between protection and immunopathology.
Revolutionizing cancer immunotherapy in solid tumor: CAR engineering and single-cell sequencing insights
Authors: Pu Zuhui , Wang Tony Bowei , Mou Lisha
Published: November 2023

The global increase in cancer incidence presents significant economic and societal challenges. While chimeric antigen receptor-modified T cell (CAR-T) therapy has demonstrated remarkable success in hematologic malignancies and has earned FDA approval, its translation to solid tumors encounters faces significant obstacles, primarily centered around identifying reliable tumor-associated antigens and navigating the complexities of the tumor microenvironment. Recent developments in single-cell RNA sequencing (scRNA-seq) have greatly enhanced our understanding of tumors by offering high-resolution, unbiased analysis of cellular heterogeneity and molecular patterns. These technologies have revolutionized our comprehension of tumor immunology and have led to notable progress in cancer immunotherapy. This mini-review explores the progress of chimeric antigen receptor (CAR) cell therapy in solid tumor treatment and the application of scRNA-seq at various stages following the administration of CAR cell products into the body. The advantages of scRNA-seq are poised to further advance the investigation of the biological characteristics of CAR cells in vivo, tumor immune evasion, the impact of different cellular components on clinical efficacy, the development of clinically relevant biomarkers, and the creation of new targeted drugs and combination therapy approaches. The integration of scRNA-seq with CAR therapy represents a promising avenue for future innovations in cancer immunotherapy. This synergy holds the potential to enhance the precision and efficacy of CAR cell therapies while expanding their applications to a broader range of malignancies.
Seasonal iron fluxes and iron cycling in sandy bioirrigated sediments
Authors: Swenson Perger Darci A. , Dwyer Ian P. , Aller Robert C. , Volkenborn Nils , Heilbrun Christina , Wehrmann Laura M.
Published: November 2023

Permeable sediments, which represent more than 50% of the continental shelves, have been largely neglected as a potential source of Fe in current global estimates of benthic dissolved iron (Fed) fluxes. There are open questions regarding the effects of a range of factors on Fed fluxes from these deposits, including seasonal dynamics and the role of bioirrigation. To address these gaps, we performed laboratory-based sediment incubation experiments with muddy sands during summer (21 °C) and winter (7 °C). We used bioirrigation mimics to inject overlying water into the permeable sediment with patterns resembling the bioirrigation activity of the prolific bioturbating polychaete, Clymenella torquata. Newly developed in-line Fe accumulators were used to estimate Fe fluxes with a recirculating set-up. We found high Fed fluxes from sandy sediments, especially in benthic chambers with simulated bioirrigation. In the winter fluxes reached >200 µmol Fed m-2 d-1 at the onset of irrigation and then decreased over the course of a 13-day experiment while in the summer fluxes from irrigated sediments reached >100 µmol Fed m-2 d-1 and remained high throughout a 7-day experiment. Despite different geochemical expressions of Fe-S cycling and resulting porewater Fed concentrations in winter and summer, large Fed fluxes were sustained during both seasons. Solid-phase and porewater concentration profiles showed that maximum concentrations of key constituents, including total solid-phase reactive Fe, and porewater Fed and ammonium, were located closer to the sediment water interface (SWI) in irrigated cores than in non-irrigated cores due to the upward advective transport of dissolved porewater constituents. This upward transport also facilitated Fed fluxes out of the sediments, especially during times of active pumping. Our study demonstrates the potential for large Fed fluxes from sandy sediments in both summer and winter, despite relatively low standing stocks of labile organic matter and porewater Fed. The primary driver of these high fluxes was advective porewater transport, in our study induced by the activity of infaunal organisms. These results suggest that permeable sediments, which dominate shelf regions, must be explicitly considered in global estimates of benthic Fed fluxes, and cannot be simply extrapolated from estimates based on muddy sediments.
Surgical treatment of primary hepatic neuroendocrine tumor diagnosed by Al18F-NOTA-Octreotide PET/CT: a case report
Authors: Zhang Zhongyan , Li Hehe
Published: November 2023

Neuroendocrine tumors (NETs) are a heterogeneous group of tumors originating from peptide-producing neurons and neuroendocrine cells. The liver is the most common site of metastasis for NETs, while primary hepatic neuroendocrine tumors (PHNETs) are exceedingly rare. While somatostatin receptor scintigraphy (SRS) has demonstrated superior efficacy compared to [18F]FDG PET imaging in the diagnosis of neuroendocrine tumors, [18F]AlF-NOTA-Octreotide ([18F]AlF-OC) PET/CT also exhibits specific advantages over SRS. This article presents a case study of a patient with a liver mass who underwent sequential [18F]FDG and [18F]AlF-OC PET/CT scans, ruling out hepatocellular carcinoma and confirming the diagnosis of PHNETs. Subsequently, the patient underwent surgical treatment. From another perspective, [18F]AlF-OC exhibits distinct advantages. The postoperative pathology revealed a PHNETs, which further emphasizes its clinical rarity.
Development and validation of a machine learning model integrated with the clinical workflow for early detection of sepsis
Authors: Mahyoub Mohammed A. , Yadav Ravi R. , Dougherty Kacie , Shukla Ajit
Published: November 2023

Background

Sepsis is a life-threatening condition caused by a dysregulated response to infection, affecting millions of people worldwide. Early diagnosis and treatment are critical for managing sepsis and reducing morbidity and mortality rates.

Materials and methods

A systematic design approach was employed to build a model that predicts sepsis, incorporating clinical feedback to identify relevant data elements. XGBoost was utilized for prediction, and interpretability was achieved through the application of Shapley values. The model was successfully deployed within a widely used Electronic Medical Record (EMR) system.

Results

The developed model demonstrated robust performance pre-operations, with a sensitivity of 92%, specificity of 93%, and a false positive rate of 7%. Following deployment, the model maintained comparable performance, with a sensitivity of 91% and specificity of 94%. Notably, the post-deployment false positive rate of 6% represents a substantial reduction compared to the currently deployed commercial model in the same health system, which exhibits a false positive rate of 30%.

Discussion

These findings underscore the effectiveness and potential value of the developed model in improving timely sepsis detection and reducing unnecessary alerts in clinical practice. Further investigations should focus on its long-term generalizability and impact on patient outcomes.
Flow cytometry and cell sorting
Authors: Telford William G.
Published: November 2023

While flow cytometry is a critical single cell analytical technique in biomedical science, the technology of flow cytometry associated cell sorting is equally important. Physical separation of cells analyzed by flow cytometry was recognized as an important goal even in the field’s beginning, and many of the earliest cytometers were also cell sorters. Isolation of cells based on flow cytometric analysis has formed the foundation of immune cell differentiation and development and continues to grow importance as techniques for genomic and proteomic analysis expand. This brief review will describe both the historical development and current state of cell sorting. The multiple mechanisms for cell sorters will be covered, and critical aspects of cell sorting will be discussed. Newer technologies for cell sorting including microfluidic technologies will also be considered.
The application of artificial intelligence in diabetic retinopathy screening: a Saudi Arabian perspective
Authors: Barakat Abdulaziz A. , Mobarak Omar , Javaid Haroon Ahmed , Awad Mhd Rasheed , Hamweyah Karam , Ouban Abderrahman , Al-Hazzaa Selwa A. F.
Published: November 2023

Introduction

Diabetic retinopathy (DR) is the leading cause of preventable blindness in Saudi Arabia. With a prevalence of up to 40% of patients with diabetes, DR constitutes a significant public health burden on the country. Saudi Arabia has not yet established a national screening program for DR. Mounting evidence shows that Artificial intelligence (AI)-based DR screening programs are slowly becoming superior to traditional screening, with the COVID-19 pandemic accelerating research into this topic as well as changing the outlook of the public toward it. The main objective of this study is to evaluate the perception and acceptance of AI in DR screening among eye care professionals in Saudi Arabia.

Methods

A cross-sectional study using a self-administered online-based questionnaire was distributed by email through the registry of the Saudi Commission For Health Specialties (SCFHS). 309 ophthalmologists and physicians involved in diabetic eye care in Saudi Arabia participated in the study. Data analysis was done by SPSS, and a value of p < 0.05 was considered significant for statistical purposes.

Results

54% of participants rated their level of AI knowledge as above average and 63% believed that AI and telemedicine are interchangeable. 66% believed that AI would decrease the workforce of physicians. 79% expected clinical efficiency to increase with AI. Around 50% of participants expected AI to be implemented in the next 5 years.

Discussion

Most participants reported good knowledge about AI. Physicians with more clinical experience and those who used e-health apps in clinical practice regarded their AI knowledge as higher than their peers. Perceived knowledge was strongly related to acceptance of the benefits of AI-based DR screening. In general, there was a positive attitude toward AI-based DR screening. However, concerns related to the labor market and data confidentiality were evident. There should be further education and awareness about the topic.