bluuebunny/crossref_metadata_2025 huggingface dataset:
Phage-encoded depolymerases as a strategy for combating multidrug-resistant Acinetobacter baumannii
Authors: Islam Md Minarul , Mahbub Nasir Uddin , Shin Woo Shik , Oh Man Hwan
Published: October 2024

Acinetobacter baumannii, a predominant nosocomial pathogen, represents a grave threat to public health due to its multiple antimicrobial resistance. Managing patients afflicted with severe infections caused by multiple drug-resistant A. baumannii is particularly challenging, given the associated high mortality rates and unfavorable prognoses. The diminishing efficacy of antibiotics against this superbug underscores the urgent necessity for novel treatments or strategies to address this formidable issue. Bacteriophage-derived polysaccharide depolymerase enzymes present a potential approach to combating this pathogen. These enzymes target and degrade the bacterial cell’s exopolysaccharide, capsular polysaccharide, and lipopolysaccharide, thereby disrupting biofilm formation and impairing the bacteria’s defense mechanisms. Nonetheless, the narrow host range of phage depolymerases limits their therapeutic efficacy. Despite the benefits of these enzymes, phage-resistant strains have been identified, highlighting the complexity of phage-host interactions and the need for further investigation. While preliminary findings are encouraging, current investigations are limited, and clinical trials are imperative to advance this treatment approach for broader clinical applications. This review explores the potential of phage-derived depolymerase enzymes against A. baumannii infections.
Virome analysis provides new insights into the pathogenesis mechanism and treatment of SLE disease
Authors: Wu Yifan , Zhang Zhiyuan , Wang Xinglian , Liu Xun , Qiu Ye , Ge Xingyi , Miao Zhichao , Meng Xiangxian , Peng Yousong
Published: October 2024

Introduction

This study aimed to investigate the virome diversity of the SLE disease and the association between viral infections and the disease.

Methods

SLE-related RNA-Seq data were retrieved from public databases. A rigorous computational workflow was employed to identify the human viruses. Differential expression analysis and functional enrichment analysis were conducted in R.

Results

We identified ten human virus species from 826 RNA-Seq samples of human blood, comprising 688 SLE patients and 138 healthy controls. Eight of the ten virus species exhibited higher positive rates in SLE patients compared to healthy controls, with Human betaherpesvirus 5 (HHV5) having the highest positive rate (4.1%) and being exclusively detected in SLE samples. The virus abundances were low and comparable in both SLE patients and healthy controls. Analysis of the antiviral interferon-stimulated genes (ISGs) in samples showed higher ISG expression levels in HHV4 and HHV5-positive samples compared to virus-negative samples. Several genes that were up-regulated in SLE patients were further up-regulated after HHV5 infection, and they were mainly enriched in immune response-related biological processes. Additionally, the expression levels of several marker genes of SLE severity were compared between HHV5-positive and virus-negative SLE patients, suggesting that HHV5 infection may be associated with aggravated SLE disease.

Discussion

We found that SLE patients are more susceptible to viral infections than healthy individuals. Viral infections, such as HHV5, may be associated with aggravated SLE disease. This study deepens our understanding of the association between viruses and SLE and provides new insights into prevention and control of the disease.
MultiSentimentArcs: a novel method to measure coherence in multimodal sentiment analysis for long-form narratives in film
Authors: Chun Jon
Published: October 2024

Affective artificial intelligence and multimodal sentiment analysis play critical roles in designing safe and effective human-computer interactions and are in diverse applications ranging from social chatbots to eldercare robots. However emotionally intelligent artificial intelligence can also manipulate, persuade, and otherwise compromise human autonomy. We face a constant stream of ever more capable models that can better understand nuanced, complex, and interrelated sentiments across different modalities including text, vision, and speech. This paper introduces MultiSentimentArcs, combination of an open and extensible multimodal sentiment analysis framework, a challenging movie dataset, and a novel benchmark. This enables the quantitative and qualitative identification, comparison, and prioritization of conflicting sentiments commonly arising from different models and modalities. Diachronic multimodal sentiment analysis is especially challenging in film narratives where actors, directors, cinematographers and editors use dialog, characters, and other elements in contradiction with each other to accentuate dramatic tension. MultiSentimentArcs uses local open-source software models to democratize artificial intelligence. We demonstrate how a simple 2-step pipeline of specialized open-source software with a large multimodal model followed by a large language model can approximate video sentiment analysis of a commercial state-of-the-art Claude 3 Opus. To the best of our knowledge, MultiSentimentArcs is the first fully open-source diachronic multimodal sentiment analysis framework, dataset, and benchmark to enable automatic or human-in-the-loop exploration, analysis, and critique of multimodal sentiment analysis on long-form narratives. We demonstrate two novel coherence metrics and a methodology to identify, quantify, and explain real-world sentiment models and modalities. MultiSentimentArcs integrates artificial intelligence with traditional narrative studies and related fields like film, linguistic and cultural studies. It also contributes to eXplainable artificial intelligence and artificial intelligence safety by enhancing artificial intelligence transparency in surfacing emotional persuasion, manipulation, and deception techniques. Finally, it can filter noisy emotional input and prioritize information rich channels to build more performant real-world human computer interface applications in fields like e-learning and medicine. This research contributes to the field of Digital Humanities by giving non-artificial intelligence experts access to directly engage in analysis and critique of research around affective artificial intelligence and human-AI alignment. Code and non-copyrighted data will be available at https://github.com/jon-chun/multisentimentarcs.
A spatial analysis of border “security” and jaguars in the U.S.-Mexico borderlands
Authors: Hausermann Heidi , Hutchinson Eliot , Walder-Hoge Zoey
Published: October 2024

In March 1996, a jaguar (Panthera onca) named Border King was seen in Arizona’s Peloncillo Mountains, followed by a sighting of a second male, Macho B, in September. The cats had crossed the U.S.-Mexico border and quickly came to symbolize a conservation success story in complicated geopolitical terrain. Two decades later, the Trump Administration’s increased militarization of the borderlands prompted concerns about the deleterious impacts of border wall expansion for jaguar movement and survival. This study examines the expansion of border barriers, and potential impact on jaguar habitat. Using geospatial technologies and public data, we measure border barrier expansion between 2005 and 2021. We found that of the suitable jaguar habitat that touched the border in the study area (155 km), 86% (or 133 km) had been cut off by border barrier by 2021. We distinguish “wall” from other barriers, including vehicle barriers, using aerial imagery. Our results show although barriers built from 2006 to 2015 were triple the length of those built under Trump, the majority consisted of vehicle barriers, which animals may be able to cross. Trump era construction shifted vehicle barriers to restrictive walls limiting animal movement. We argue examining the type of barrier is crucial in understanding the potential for border “security” disruption to jaguar movement and futures in the borderlands.
Cardiovascular disease risk in patients with elevated LDL-C levels: FH vs. non-FH
Authors: Huang Haomin , Li Lamei , Yang Anni , Chen Tao , Shi Ganwei , Li Feng , Wang Luya , Cai Gaojun
Published: October 2024

Introduction

Coronary artery disease (CAD) remains the primary cause of death worldwide, and familial hypercholesterolemia (FH) is a common disease that leads to CAD. This study aimed to explore the difference in CAD risk between FH and non-FH patients with high low-density lipoprotein cholesterol (LDL-C) levels.

Methods

Individuals (≥18 years) who underwent coronary angiography (CAG) from June 2016 to September 2020 were consecutively enrolled. Participants with LDL-C levels ≥4.0 mmol/L were ultimately included in this study. For all participants, next-generation sequencing was performed with expanded gene panels including 11 genes (LDLR, APOB, PCSK9, LDLRAP1, ABCG5, ABCG8, LIPA, LPA, APOBR, LRPAP1, and STAP1).

Results

A total of 223 individuals were included in this study. According to the CAG findings, 199 CAD patients and 24 non-CAD patients were included. The proportions of FH genes, regardless of whether 3 major genes or all 11 genes were sequenced, were not significantly different between the CAD and non-CAD groups (P > 0.05). In addition, all CAD patients were divided into a triple vessel disease (TVD) group and a non-TVD group. The TVD group had a greater proportion of patients with mutations in 3 FH major genes (P < 0.05). In addition, TC, LDL-C and modified LDL-C (MLDL-C) levels were higher and the estimated glomerular filtration rate (eGFR) was lower in the TVD group than in the non-TVD group (all P < 0.05). However, multivariate logistic regression analyses revealed that only the eGFR was an independent risk factor for TVD (OR 0.99; 95% CI: 0.98–1.00, P < 0.05). To eliminate the impact of the eGFR, subgroup analysis was conducted, and the results indicated that among CAD patients in the high-eGFR group, having FH mutations in 3 major genes was an independent risk factor for TVD (OR 3.00; 95% CI: 1.16–7.79, P < 0.05). In total, 104 FH-related mutations were detected in this study.

Conclusions

FH mutation did not increase the rate of CAD in individuals with an MLDL-C level ≥4.0 mmol/L. However, among CAD patients (MLDL-C level ≥4.0 mmol/L) with almost normal renal function (≥87.4 ml/min/1.73 m2), the probability of enduring TVD in those with FH mutations in 3 major genes was 3.00 times greater than that in those without FH mutations.
Simultaneous determination of the combined and free concentrations of atorvastatin and its major metabolite in vitro and in vivo based on ultraﬁltration coupled with UPLC-MS/MS method: an application in a protein binding rate and metabolism ability study in uremic hemodialysis patients
Authors: Cao Ming-Chen , Huang Xin , Tang Bo-Hao , Shi Hai-Yan , Zheng Yi , Zhao Wei
Published: October 2024

Introduction

A rapid, accurate, and specific ultrafiltration with ultra-performance liquid chromatographic-tandem mass spectrometry method was validated for the simultaneous determination of the protein binding rate of atorvastatin in uremic patients. Methods: The plasma samples were centrifuged at 6,000 r/min for 15 min at 37°C and the ultrafiltrate was collected. An ACQUITY UPLC® BEH C18 Column with gradient elution of water (0.1% formic acid) and acetonitrile was used for separation at a flow rate of 0.4 ml/min.

Results

The calibration curves of two analytes in the serum showed excellent linearity over the concentration ranges of 0.05-20.00 ng/ml for atorvastatin, and 0.05-20.00 ng/ml for orthohydroxy atorvastatin, respectively. This method was validated according to standard US food and drug administration and European medicines agency guidelines in terms of selectivity, linearity, detection limits, matrix effects, accuracy, precision, recovery, and stability. This assay can be easily implemented in clinical practice to determine the free and combined concentrations of atorvastatin in the plasma of uremic patients. The final result showed that the average plasma protein binding rate in uremic patients was 86.58 ± 2.04%, relative standard deviation (RSD) (%) = 1.98, while the plasma protein binding rate in patients with normal renal function was 97.62 ± 1.96%, RSD (%) = 2.04. There was a significant difference in the protein binding rate in different types of plasma (P < 0.05), and the protein binding rate decreased with increasing creatinine until it stabilized at nearly 80%. The mean metabolite/prototype ratio of atorvastatin in patients with normal renal function and in patients with uremia was 1.085 and 0.974, respectively.

Discussion

The metabolic process of atorvastatin may be inhibited in uremic hemodialysis patients, but the total concentration of atorvastatin did not change significantly; due to the decrease of protein binding rate increase the drug distribution of atorvastatin in the liver or muscle tissue, which may increase the risk of certain adverse reactions. We recommend that clinicians use free drug concentration monitoring to adjust the dose of atorvastatin to ensure patient safety for uremic hemodialysis patients.
Youth, money, and behavior: the impact of financial literacy programs
Authors: Mancone Stefania , Tosti Beatrice , Corrado Stefano , Spica Giuseppe , Zanon Alessandra , Diotaiuti Pierluigi
Published: October 2024

This narrative review critically examines the scope and impact of financial literacy programs targeted at children and adolescents. By synthesizing findings from diverse studies, the review identifies key components of effective financial education, including the integration of experiential learning, the role of digital tools, and the importance of parental involvement. Challenges such as ensuring curriculum relevance in a rapidly evolving financial landscape and addressing the varied learning needs of young populations are discussed. Recommendations for future research include the necessity for longitudinal studies to assess the long-term effects of early financial education and exploration into the digitalization of financial literacy. This review aims to contribute to the development of more inclusive, adaptive, and impactful financial literacy education strategies, underscoring the critical role of comprehensive financial education in preparing young individuals for financial autonomy and resilience.
Exploring the influence of green growth and energy sources on “carbon-dioxide emissions”: implications for climate change mitigation
Authors: Akther Sharmin , Sultanuzzaman Md Reza , Zhang Yanrong , Almutlaq Fahad , Huq Md Enamul
Published: October 2024

Climate change is a global concern driven by greenhouse gas emissions. Bangladesh, being densely populated and a significant carbon emitter, must urgently reduce its “carbon-dioxide emissions”. The primary objectives of this research are to meticulously examine the impact of green growth, non-renewable energy, renewable energy, and technological innovations on carbon dioxide emissions in Bangladesh from 1990 to 2020, with the goal of informing policies for effective and sustainable climate change mitigation in Bangladesh. The analysis using advanced econometric methods, including autoregressive distributed lag, fully modified ordinary least squares, and canonical cointegration regression, reveals that green growth and technological innovations have adverse long-term but positive short-term effects on carbon emissions in Bangladesh. Additionally, it is noteworthy that both non-renewable and renewable energy sources significantly contribute to long-term and short-term carbon emissions. The study confirms the Environmental Kuznets Curve, showing a “∩” shaped relationship between green development and carbon emissions. Policymakers should prioritize green growth, incentivize technological innovation, promote sustainable economic practices, and implement comprehensive energy transition strategies. The insights from this study inform policy formulation to address the complex relationships between green growth, energy sources, and carbon-dioxide emissions for sustainable climate change mitigation in Bangladesh. Bangladesh’s efforts contribute to global emission reduction and foster a resilient future.
Incidentally cured psoriasis in a patient with refractory/relapsed diffuse large B-cell lymphoma receiving CD19 CAR-T cell therapy: a case report
Authors: Wang Song-yun , An Wan-hua , Wang Ze-song , Wang Wan-li , Zhang Bin , Xu Kai-lin , Guo Shu-li , Gao Ming , Li Bo , Huang Lei , Tian Huan-huan , Guo Wen-yi , Wang Hui-rui
Published: October 2024

Chimeric antigen receptor T (CAR-T) cell therapy is a new treatment for cancers, but reports on curing immune-related skin diseases are limited. We report a case of successful CAR-T-cell therapy in a patient with refractory/relapsed diffuse large B-cell lymphoma (R/R DLBCL) who was incidentally cured of chronic generalized plaque psoriasis. The patient, a 65-year-old male who had a known history of psoriasis for 45 years, did not receive immunotherapy for psoriasis during this period. Imaging, molecular biology and immunology diagnostics confirmed DLBCL. After several weeks of standard-dose R-CHOP chemotherapy, the patient achieved partial remission, but according to CT, the patient relapsed, and there was no significant improvement in her psoriasis symptoms. Subsequently, the patient was enrolled in the CD19 CAR-T-cell therapy group. Four weeks after CAR-T-cell infusion, the patient’s abdominal pain disappeared, and there was a significant improvement in overall skin lesions. One year later, follow-up results indicated complete remission of R/R DLBCL (confirmed by PET-CT), with only minimal residual psoriatic skin lesions limited to the patient’s neck. The results of using CAR-T-cell therapy to achieve an incidental cure for psoriasis highlight the potential for exploring cell-based therapies for complex autoinflammatory skin diseases.
Two applications of the Consensus Solutions process with collaborative modeling for management of a contentious oyster fishery
Authors: North Elizabeth W. , Wilberg Michael J. , Blair Jeff , Wainger Lisa , Cornwell Jeffrey C. , Jones Robert , Hayes Chris , Gawde Rasika , Hood Raleigh Robert , Goelz Taylor , Hartley Troy , Mace Marvin M. , Diriker Memo , Fowler Niquinn , Polkinghorn Brian
Published: October 2024

Worldwide, enhancement of oyster populations is undertaken to achieve a variety of goals including support of food production, local economies, water quality, coastal habitat, biodiversity, and cultural heritage. Although numerous strategies for improving oyster stocks exist, enhancement efforts can be thwarted by long-standing conflict among community groups about which strategies to implement, where efforts should be focused, and how much funding should be allocated to each strategy. The objective of this paper is to compare two engagement approaches that resulted in recommendations for multi-benefit enhancements to oyster populations and the oyster industry in Maryland, U.S.A., using the Consensus Solutions process with collaborative simulation modeling. These recommendations were put forward by the OysterFutures Workgroup in 2018 and the Maryland Oyster Advisory Commission (OAC) in 2021. Notable similarities between the efforts were the basic principles of the Consensus Solutions process: neutral facilitation, a 75% agreement threshold, the presence of management agency leadership at the meetings, a scientific support team that created a management scenario model in collaboration with community group representatives, numerous opportunities for representatives to listen to each other, and a structured consensus building process for idea generation, rating, and approval of management options. To ensure meaningful representation by the most affected user groups, the goal for membership composition was 60% from industry and 40% from advocacy, agency, and academic groups in both processes. Important differences between the processes included the impetus for the process (a research program versus a legislatively-mandated process), the size of the groups, the structure of the meetings, and the clear and pervasive impact of the COVID-19 pandemic on the ability of OAC members to interact. Despite differences and challenges, both groups were able to agree on a package of recommendations, indicating that consensus-based processes with collaborative modeling offer viable paths toward coordinated cross-sector natural resource decisions with scientific basis and community support. In addition, collaborative modeling resulted in ‘myth busting’ findings that allowed participants to reassess and realign their thinking about how the coupled human-oyster system would respond to management changes.
Shifts in sulphur-cycling bacteria in the rhizobiome support the adaptation of Caulerpa prolifera to elevated sulphide levels
Authors: Barilo Anastasiia , Engelen Aschwin , Wilken Susanne , Bouwmeester Harro , Muyzer Gerard
Published: October 2024

Caulerpa is a genus of green macroalgae that lives in tropical and subtropical coastal waters. It is an intriguing organism because, despite having plant-like structures, it is one giant cell – which, next to multiple nuclei, chloroplasts, and mitochondria, also contains endo- and epiphytic bacteria. The role of these bacteria is unknown, but they might impact the growth and development of the host, adaptation to environmental parameters, and, hence, the ecological success of these algae. We hypothesised that increased sulphide concentrations would trigger a significant shift in the microbial community composition associated with C. prolifera rhizoids, favouring sulphide-oxidizing bacteria. To test this hypothesis, we conducted a mesocosm experiment incubating C. prolifera in sediments with different sulphide concentrations and analysed the algal photosynthesis, growth, and microbiome composition. While photosynthesis was not affected, the Caulerpa weight-based growth rate decreased linearly with increasing sulphide concentration. To analyse the microbiome, we extracted DNA and RNA from the fronds, rhizoids, and the accompanying sediments and performed 16S amplicon sequencing. The microbiome of the fronds was unaffected in both the DNA and RNA samples. However, an increase in sulphide concentration coincided with a decrease in the relative abundance of sulphate-reducing bacteria associated with Caulerpa rhizoids, particularly from the family Desulfocapsaceae. In the RNA samples, potential sulphide oxidisers of the rhizoid-associated members of the Beggiatoaceae were detected. Our results suggest that the rhizobiome of Caulerpa plays a significant role in its adaptation to sulphide-rich environments, offering new insights into the complex interactions within marine holobionts.
Flow-based parameterization for DAG and feature discovery in scientific multimodal data
Authors: Walker Elise , Actor Jonas A. , Martinez Carianne , Trask Nathaniel
Published: October 2024

Representation learning algorithms are often used to extract essential features from high-dimensional datasets. These algorithms commonly assume that such features are independent. However, multimodal datasets containing complementary information often have causally related features. Consequently, there is a need to discover features purporting conditional independencies. Bayesian networks (BNs) are probabilistic graphical models that use directed acyclic graphs (DAGs) to encode the conditional independencies of a joint distribution. To discover features and their conditional independence structure, we develop pimaDAG, a variational autoencoder framework that learns features from multimodal datasets, possibly with known physics constraints, and a BN describing the feature distribution. Our algorithm introduces a new DAG parameterization, which we use to learn a BN simultaneously with a latent space of a variational autoencoder in an end-to-end differentiable framework via a single, tractable evidence lower bound loss function. We place a Gaussian mixture prior on the latent space and identify each of the Gaussians with an outcome of the DAG nodes; this identification enables feature discovery with conditional independence relationships obeying the Markov factorization property. Tested against a synthetic and a scientific dataset, our results demonstrate the capability of learning a BN on simultaneously discovered key features in a fully unsupervised setting.
Development of a deep learning model for automated detection of calcium pyrophosphate deposition in hand radiographs
Authors: Hügle Thomas , Rosoux Elisabeth , Fahrni Guillaume , Markham Deborah , Manigold Tobias , Becce Fabio
Published: October 2024

Background

Calcium pyrophosphate deposition (CPPD) disease is a leading cause of arthritis, which can mimic or strongly interfere with other rheumatic diseases such as gout, osteoarthritis (OA) or rheumatoid arthritis (RA). In the recently established ACR/EULAR CPPD classification criteria, calcification and OA features of the wrist and hand joints are substantial features.

Objectives

To develop and test a deep-learning algorithm for automatically and reliably detecting CPPD features in hand radiographs, focusing on calcification of the triangular fibrocartilage complex (TFCC) and metacarpophalangeal (MCP)-2 and -3 joints, in separate or combined models.

Methods

Two radiologists independently labeled a dataset of 926 hand radiographs, yielding 319 CPPD positive and 607 CPPD negative cases across the three sites of interest after adjudicating discrepant cases. CPPD presence was then predicted using a convolutional neural network. We tested seven CPPD models, each with a different combination of sites out of TFCC, MCP-2 and MCP-3. The model performance was assessed using the area under the receiver operating characteristic (AUROC) and area under the precision-recall (AUPR) curves, with heatmaps (Grad-CAM) aiding in case discrimination.

Results

All models trialed gave good class separation, with the combined TFCC, MCP-2 and MCP-3 model showing the most robust performance with a mean AUROC of 0.86, mean AUPR of 0.77, sensitivity of 0.77, specificity of 0.80, and precision of 0.67. The TFCC-alone model had a slightly lower mean AUROC of 0.85 with a mean AUPR of 0.73. The MCP-2-alone and MCP-3-alone models exhibited mean AUROCs of 0.78–0.87, but lower mean AUPRs of 0.29–0.47. Heatmap analysis revealed activation in the regions of interest for positive cases (true and false positives), but unexpected highlights were encountered possibly due to correlated features in different hand regions.

Conclusion

A combined deep-learning model detecting CPPD at the TFCC and MCP-2/3 joints in hand radiographs provides the highest diagnostic performance. The algorithm could be used to screen larger OA or RA databases or electronic medical records for CPPD cases. Future work includes dataset expansion and validation with external datasets.
Case report: Lichenoid esophagitis revealing an HIV infection
Authors: Marschner Jasmin , Schmitt-Graeff Annette , Kreisel Wolfgang , Decker Annegrit , Schauer Franziska
Published: October 2024

Esophageal lichen planus is an underrecognized manifestation of lichen planus. It is typically diagnosed based on characteristic endoscopic findings, such as hyperkeratosis, trachealization, denudation and/or stenosis, along with the presence of a lichenoid infiltrate in histopathological examination. In cases where no other manifestation of lichen planus are found and direct immunofluorescence for fibrinogen along the basement membrane is negative, the term “lichenoid esophagitis” should be preferred. This distinction is critical, as it prompts a thorough evaluation for underlying diseases, including autoimmune conditions and viral infections. We report a case of a 69-year-old male with stenosing esophagitis resembling esophageal lichen planus on endoscopic evaluation. The condition was refractory to multiple dilation procedures and high-dose proton pump inhibitor therapy. Histopathological analysis revealed a dense lymphocytic infiltrate extending into the epithelial layer, while direct immunofluorescence microscopy for fibrinogen was negative. There were no other signs of lichen planus on the skin or mucous membranes. The patient’s medical history included recurrent transient ischemic attack (non-cardiac), penile cancer and recurrent mucosal candidiasis. Laboratory findings revealed Epstein–Barr virus viremia and IgG hypergammaglobulinemia, raising suspicion of immunodeficiency. Further testing confirmed an active HIV infection, classified as category C3, and antiretroviral therapy was initiated. Following the initiation of antiretroviral therapy, the patient experienced rapid clinical and histopathological improvement of the lichenoid esophageal inflammation, although the esophageal stenosis persisted. Subsequent follow-up endoscopies confirmed resolution of the inflammatory component, underscoring the positive impact of addressing the underlying HIV infection on the esophagus. This case report highlights the importance of recognizing lichenoid esophagitis as a potential diagnosis in cases of unexplained chronic esophagitis, especially when standard treatments are ineffective. The presence of lichenoid inflammation without other manifestations of lichen planus should trigger an investigation into underlying conditions.
Culturomics- and metagenomics-based insights into the soil microbiome preservation and application for sustainable agriculture
Authors: Clagnan Elisa , Costanzo Manuela , Visca Andrea , Di Gregorio Luciana , Tabacchioni Silvia , Colantoni Eleonora , Sevi Filippo , Sbarra Federico , Bindo Arianna , Nolfi Lorenzo , Magarelli Rosaria Alessandra , Trupo Mario , Ambrico Alfredo , Bevivino Annamaria
Published: October 2024

Soil health is crucial for global food production in the context of an ever-growing global population. Microbiomes, a combination of microorganisms and their activities, play a pivotal role by biodegrading contaminants, maintaining soil structure, controlling nutrients’ cycles, and regulating the plant responses to biotic and abiotic stresses. Microbiome-based solutions along the soil-plant continuum, and their scaling up from laboratory experiments to field applications, hold promise for enhancing agricultural sustainability by harnessing the power of microbial consortia. Synthetic microbial communities, i.e., selected microbial consortia, are designed to perform specific functions. In contrast, natural communities leverage indigenous microbial populations that are adapted to local soil conditions, promoting ecosystem resilience, and reducing reliance on external inputs. The identification of microbial indicators requires a holistic approach. It is fundamental for current understanding the soil health status and for providing a comprehensive assessment of sustainable land management practices and conservation efforts. Recent advancements in molecular technologies, such as high-throughput sequencing, revealed the incredible diversity of soil microbiomes. On one hand, metagenomic sequencing allows the characterization of the entire genetic composition of soil microbiomes, and the examination of their functional potential and ecological roles; on the other hand, culturomics-based approaches and metabolic fingerprinting offer complementary information by providing snapshots of microbial diversity and metabolic activities both in and ex-situ. Long-term storage and cryopreservation of mixed culture and whole microbiome are crucial to maintain the originality of the sample in microbiome biobanking and for the development and application of microbiome-based innovation. This review aims to elucidate the available approaches to characterize diversity, function, and resilience of soil microbial communities and to develop microbiome-based solutions that can pave the way for harnessing nature’s untapped resources to cultivate crops in healthy soils, to enhance plant resilience to abiotic and biotic stresses, and to shape thriving ecosystems unlocking the potential of soil microbiomes is key to sustainable agriculture. Improving management practices by incorporating beneficial microbial consortia, and promoting resilience to climate change by facilitating adaptive strategies with respect to environmental conditions are the global challenges of the future to address the issues of climate change, land degradation and food security.
Navigating collateral sensitivity: insights into the mechanisms and applications of antibiotic resistance trade-offs
Authors: Mahmud Hafij Al , Wakeman Catherine A.
Published: October 2024

The swift rise of antibiotic resistance, coupled with limited new antibiotic discovery, presents a significant hurdle to global public health, demanding innovative therapeutic solutions. Recently, collateral sensitivity (CS), the phenomenon in which resistance to one antibiotic increases vulnerability to another, has come to light as a potential path forward in this attempt. Targeting either unidirectional or reciprocal CS holds promise for constraining the emergence of drug resistance and notably enhancing treatment outcomes. Typically, the alteration of bacterial physiology, such as bacterial membrane potential, expression of efflux pumps, cell wall structures, and endogenous enzymatic actions, are involved in evolved collateral sensitivity. In this review, we present a thorough overview of CS in antibiotic therapy, including its definition, importance, and underlying mechanisms. We describe how CS can be exploited to prevent the emergence of resistance and enhance the results of treatment, but we also discuss the challenges and restrictions that come with implementing this practice. Our review underscores the importance of continued exploration of CS mechanisms in the broad spectrum and clinical validation of therapeutic approaches, offering insights into its role as a valuable tool in combating antibiotic resistance.
The function of nicotinamide phosphoribosyl transferase (NAMPT) and its role in diseases
Authors: Peng Aihong , Li Junqin , Xing Jianxiao , Yao Yuanjun , Niu Xuping , Zhang Kaiming
Published: October 2024

Nicotinamide phosphoribosyl transferase (NAMPT) is a rate-limiting enzyme in the mammalian nicotinamide adenine dinucleotide (NAD) salvage pathway, and plays a vital role in the regulation of cell metabolic activity, reprogramming, aging and apoptosis. NAMPT synthesizes nicotinamide mononucleotide (NMN) through enzymatic action, which is a key protein involved in host defense mechanism and plays an important role in metabolic homeostasis and cell survival. NAMPT is involved in NAD metabolism and maintains intracellular NAD levels. Sirtuins (SIRTs) are a family of nicotinamide adenine dinucleotide (NAD)-dependent histone deacetylases (HDACs), the members are capable of sensing cellular NAD+ levels. NAMPT-NAD and SIRT constitute a powerful anti-stress defense system. In this paper, the structure, biological function and correlation with diseases of NAMPT are introduced, aiming to provide new ideas for the targeted therapy of related diseases.
BrainNet: an automated approach for brain stress prediction utilizing electrodermal activity signal with XLNet model
Authors: Xuanzhi Liao , Hakeem Abeer , Mohaisen Linda , Umer Muhammad , Khan Muhammad Attique , Alsenan Shrooq , Alsubai Shtwai , Innab Nisreen
Published: October 2024

Brain stress monitoring has emerged as a critical research area for understanding and managing stress and neurological health issues. This burgeoning field aims to provide accurate information and prediction about individuals' stress levels by analyzing behavioral data and physiological signals. To address this emerging problem, this research study proposes an innovative approach that uses an attention mechanism-based XLNet model (called BrainNet) for continuous stress monitoring and stress level prediction. The proposed model analyzes streams of brain data, including behavioral and physiological signal patterns using Swell and WESAD datasets. Testing on the Swell multi-class dataset, the model achieves an impressive accuracy of 95.76%. Furthermore, when evaluated on the WESAD dataset, it demonstrates even higher accuracy, reaching 98.32%. When applied to the binary classification of stress and no stress using the Swell dataset, the model achieves an outstanding accuracy of 97.19%. Comparative analysis with other previously published research studies underscores the superior performance of the proposed approach. In addition, cross-validation confirms the significance, efficacy, and robustness of the model in brain stress level prediction and aligns with the goals of smart diagnostics for understanding neurological behaviors.
Efficacy and safety of thrombectomy with or without intravenous thrombolysis in the treatment of acute basilar artery occlusion ischemic stroke: an updated systematic review and meta-analysis
Authors: Tian Shuyi , Zou Mengqing , Li Dan , Zhou Hang , Wang Chenghan , Liu Qianshuo , Gao Lianbo
Published: October 2024

Background

Mechanical thrombectomy (MT) is a well-established treatment for acute basilar artery occlusion (BAO)-induced posterior circulation ischemic stroke.

Objective

The objective of the study was to compare the outcomes of endovascular therapy (EVT) with and without bridging intravenous thrombolysis (IVT) in patients with acute BAO, using an updated meta-analysis.

Methods

A systematic literature search was conducted to identify studies that compared the efficacy and safety of EVT with and without IVT in the treatment of acute BAO ischemic stroke. The extracted data included sample size, patient age, National Institutes of Health Stroke Scale (NIHSS) scores, 90-day modified Rankin Scale (mRS) scores of 0–2 and 0–3, mortality rates, symptomatic intracranial hemorrhage (sICH), and occurrence of subarachnoid hemorrhage (SAH).

Results

Five studies that included a total of 1,578 patients (594 IVT + EVT vs. 984 EVT), met the inclusion criteria and were analyzed. The meta-analysis demonstrated that bridging IVT was associated with a higher likelihood of achieving a 90-day mRS score of 0–2 (41% vs. 34%; OR = 1.35, 95% CI 1.09–1.68, p = 0.006). Furthermore, the mortality rate was significantly lower in the IVT + EVT group than in the direct EVT group (25% vs. 30%; OR = 0.70, 95% CI 0.55–0.89, p = 0.003), with low heterogeneity observed (I2 = 0.0%, p = 0.78). However, there were no significant differences between the groups regarding the rates of sICH (5% vs. 6%; OR = 0.85, 95% CI: 0.52–1.39, p = 0.53), SAH (3% vs. 3%; OR = 0.93, 95% CI: 0.39–2.22, p = 0.87), perforation (2% vs. 3%; OR = 0.71, 95% CI 0.26–1.95, p = 0.51), and dissection (3% vs. 2%; OR = 0.97, 95% CI: 0.13–7.14, p = 0.98).

Conclusion

Bridging IVT in conjunction with EVT was associated with better functional outcomes and reduced mortality rates in patients with acute ischemic stroke (AIS) due to BAO compared to EVT alone, without an increased risk of sICH, SAH, perforation, and dissection. In addition, the benefit of bridging IVT to EVT appeared to be more pronounced in European patients than in Asian patients compared to EVT alone. However, the conclusions of this study are not definitive and require validation through large-scale randomized controlled trials (RCTs) to draw more robust conclusions.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42024531363.
Premorbid frailty, stress hyperglycemia ratio, and functional outcome in patients with acute ischemic stroke
Authors: Zedde Marialuisa , Lattanzi Simona , Pilotto Andrea , Janitschke Daniel , Stögbauer Jakob , Merzou Fatma , Pascarella Rosario , Padovani Alessandro , Morotti Andrea , Lochner Piergiorgio
Published: October 2024

Background

Frailty, defined as multidimensional prognostic index (MPI), has been recently identified as strong predictor of disability and mortality in the elderly with acute ischemic stroke (AIS). The stress hyperglycemia ratio (SHR) is a recently introduced biomarker significantly associated with poor outcome in AIS.

Objectives

This study aimed to investigate in what extent frailty, measured by MPI, and SHR affects the 3-months outcome of patients > 65 years-old with AIS.

Methods

Consecutive patients with AIS >65 years-old who underwent intravenous thrombolysis (IVT) from 2015 to 2019 were enrolled in a German and an Italian Stroke Unit. The SHR was calculated by dividing the fasting plasma glucose at admission with glycated hemoglobin. Demographics and clinical premorbid data, stroke-related variables, including baseline and post-treatment NIHSS score were included in a logistic regression model. The 3-months functional outcome was evaluated by using modified Rankin scale (mRS); good outcome was defined as mRS 0–2, poor as mRS ≥ 3.

Results

One hundred and fifty-five AIS patients were enrolled in the study. Median MPI was 0.19 [0.13–0.31]; 118 (76.1%) patients were classified as “robust” and 37 (23.9%) as “frail.” In regression analysis, age, NIHSS, and MPI demonstrated as the most significant predictor of 3-months good outcome in the whole cohort. In robust patients, SHR values were significantly associated with the outcome.

Conclusions

MPI is associated with the 3-months outcome in our cohort, in particular with good outcome. Conversely, SHR seems to be associated with a 3-months poor outcome in “robust” patients but not in frail patients.
Evaluation of EMG patterns in children during assisted walking in the exoskeleton
Authors: Villani Margherita , Avaltroni Priscilla , Scordo Giulia , Rubeca Damiana , Kreynin Peter , Bereziy Ekaterina , Berger Denise , Cappellini Germana , Sylos-Labini Francesca , Lacquaniti Francesco , Ivanenko Yury
Published: October 2024

While exoskeleton technology is becoming more and more common for gait rehabilitation in children with neurological disorders, evaluation of gait performance still faces challenges and concerns. The reasoning behind evaluating the spinal locomotor output is that, while exoskeleton's guidance forces create the desired walking kinematics, they also affect sensorimotor interactions, which may lead to an abnormal spatiotemporal integration of activity in particular spinal segments and the risk of abnormalities in gait recovery. Therefore, traditional indicators based on kinematic or kinetic characteristics for optimizing exoskeleton controllers for gait rehabilitation may be supplemented by performance measures associated with the neural control mechanisms. The purpose of this study on a sample of children was to determine the basic features of lower limb muscle activity and to implement a method for assessing the neuromechanics of spinal locomotor output during exoskeleton-assisted gait. To this end, we assessed the effects of a robotic exoskeleton (ExoAtlet Bambini) on gait performance, by recording electromyographic activity of leg muscles and analyzing the corresponding spinal motor pool output. A slower walking setting (about 0.2 m/s) was chosen on the exoskeleton. The results showed that, even with slower walking, the level of muscle activation was roughly comparable during exoskeleton-assisted gait and normal walking. This suggests that, despite full assistance for leg movements, the child's locomotor controllers can interpret step-related afferent information promoting essential activity in leg muscles. This is most likely explained by the active nature of stepping in the exoskeleton (the child was not fully relaxed, experienced full foot loading and needed to maintain the upper trunk posture). In terms of the general muscle activity patterns, we identified notable variations for the proximal leg muscles, coactivation of the lumbar and sacral motor pools, and weak propulsion from the distal extensors at push-off. These changes led to the lack of characteristic lumbosacral oscillations of the center of motoneuron activity, normally associated with the pendulum mechanism of bipedal walking. This work shows promise as a useful technique for analyzing exoskeleton performance to help children develop their natural gait pattern and to guide system optimization in the future for inclusion into clinical care.
Six months of different exercise type in sedentary primary schoolchildren: impact on physical fitness and saliva microbiota composition
Authors: Mancini Annamaria , Vitucci Daniela , Lasorsa Vito Alessandro , Lupo Corrado , Brustio Paolo Riccardo , Capasso Mario , Orrù Stefania , Rainoldi Alberto , Schena Federico , Buono Pasqualina
Published: October 2024

Introduction

Lifestyle influences microbiota composition. We previously reported a healthier microbiota composition in saliva from active schoolchildren compared to sedentary. In the present study, we evaluated the effects of 6 months of different exercise types on physical fitness and saliva microbiota composition in 8-11-years-old sedentary schoolchildren.

Methods

Sixty-four sedentary children from five primary schools in Turin, Italy, were divided into three groups: one continued normal curricular activity while two underwent different exercise protocols for 6 months. The Structured Exercise (Sa) group did 2 h per week of muscle activation, strength and coordination exercises supervised by a kinesiologist. The Daily Mile (Dm) group did 1 h per week of Sa plus 15 min of walking/running outdoors four times a week, supervised by a class teacher; control group (Ct) did 2 h a week of curricular exercise supervised by a class teacher. Physical fitness was evaluated before and after the intervention. Saliva samples were collected post-intervention in all participants and analyzed using PCR amplification of 16S rRNA bacterial genes. The Amplicon Sequence Variants were filtered, decontaminated, and phylogenetically classified using DADA2 software. Differential abundance analysis of microbiome taxa and pathway data was conducted using the LEfSe algorithm and PICRUSt.

Results

The Sa group showed better performances in lower limb power and sprint performance while both the Sa and Dm groups improved in endurance and balance at the end of the intervention; only balance resulted slightly improved in the Ct group. Among the genera differently enriched in saliva after the training intervention, we found that the Prevotella, the Dubosiella and the Family XIII AD3011 group were the most abundant in the Sa group; differently, the Neisseria and the Abiotrophia in Ct group. Four species showed significant the Prevotella melaninogenica and the Prevotella nanceiensis were more abundant in the Sa, conversely, Gemella sanguinis was enriched in Dm and Abiotrophia defectiva in Ct saliva group.

Conclusion

We demonstrated that Sa and Dm, not curricular exercise, improve the physical fitness components in sedentary schoolchildren correlated to health and promote an enrichment in saliva microbiota species associated to a healthier profile.