bluuebunny/crossref_metadata_2025 huggingface dataset:
The German Quality Network Sepsis: Evaluation of a Quality Collaborative on Decreasing Sepsis-Related Mortality in a Controlled Interrupted Time Series Analysis
Authors: Schwarzkopf Daniel , Rüddel Hendrik , Brinkmann Alexander , Fleischmann-Struzek Carolin , Friedrich Marcus E. , Glas Michael , Gogoll Christian , Gründling Matthias , Meybohm Patrick , Pletz Mathias W. , Schreiber Torsten , Thomas-Rüddel Daniel O. , Reinhart Konrad
Published: April 2022

Background

Sepsis is one of the leading causes of preventable deaths in hospitals. This study presents the evaluation of a quality collaborative, which aimed to decrease sepsis-related hospital mortality.

Methods

The German Quality Network Sepsis (GQNS) offers quality reporting based on claims data, peer reviews, and support for establishing continuous quality management and staff education. This study evaluates the effects of participating in the GQNS during the intervention period (April 2016–June 2018) in comparison to a retrospective baseline (January 2014–March 2016). The primary outcome was all-cause risk-adjusted hospital mortality among cases with sepsis. Sepsis was identified by International Classification of Diseases (ICD) codes in claims data. A controlled time series analysis was conducted to analyze changes from the baseline to the intervention period comparing GQNS hospitals with the population of all German hospitals assessed via the national diagnosis-related groups (DRGs)-statistics. Tests were conducted using piecewise hierarchical models. Implementation processes and barriers were assessed by surveys of local leaders of quality improvement teams.

Results

Seventy-four hospitals participated, of which 17 were university hospitals and 18 were tertiary care facilities. Observed mortality was 43.5% during baseline period and 42.7% during intervention period. Interrupted time-series analyses did not show effects on course or level of risk-adjusted mortality of cases with sepsis compared to the national DRG-statistics after the beginning of the intervention period (p = 0.632 and p = 0.512, respectively). There was no significant mortality decrease in the subgroups of patients with septic shock or ventilation >24 h or predefined subgroups of hospitals. A standardized survey among 49 local quality improvement leaders in autumn of 2018 revealed that most hospitals did not succeed in implementing a continuous quality management program or relevant measures to improve early recognition and treatment of sepsis. Barriers perceived most commonly were lack of time (77.6%), staff shortage (59.2%), and lack of participation of relevant departments (38.8%).

Conclusion

As long as hospital-wide sepsis quality improvement efforts will not become a high priority for the hospital leadership by assuring adequate resources and involvement of all pertinent stakeholders, voluntary initiatives to improve the quality of sepsis care will remain prone to failure.
Quantification of Organic Carbon Sequestered by Biogenic Iron Sulfide Minerals in Long-Term Anoxic Laboratory Incubations
Authors: Nabeh Nader , Brokaw Cheyenne , Picard Aude
Published: April 2022

Organic carbon sequestration in sedimentary environments controls oxygen and carbon dioxide concentrations in the atmosphere. While minerals play an important role in the preservation of organic carbon, there is a lack of understanding about the formation and stability of organo-mineral interactions in anoxic environments, especially those involving authigenic iron sulfide minerals. In this study, we quantified organic carbon and nitrogen sequestered in biogenic iron sulfide minerals co-precipitated with sulfate-reducing bacteria (SRB) in freshwater and marine conditions in long-term laboratory experiments. The amounts of C and N associated with biogenic iron sulfide minerals increased with increasing cell biomass concentrations available in the media. C and N levels stabilized over the first 2 months of incubation and remained stable for up to 1 year. Crystalline mackinawite (FeS) formed in all experimental conditions and transformed to greigite only in some experimental conditions. We did not find evidence that this mineral transformation affected C and N levels, neither could we identify the factors that controlled greigite formation. Pyrite did not form in our experimental conditions. While C concentrations in minerals correlated with concentrations of reduced sulfate in both the freshwater and marine media, removal of OC by iron sulfide minerals was more efficient in freshwater than marine conditions. Removal of OC by iron sulfide minerals was also more efficient when cells were present (SRB biomass) in comparison with abiotic incubations with organic mixtures (e.g., tryptone, yeast extract, and casamino acids). Our study highlights the potential for biogenic iron sulfide minerals to quantitatively contribute to organic carbon preservation in anoxic environments.
Nutrient Gradients Mediate Complex Colony-Level Antibiotic Responses in Structured Microbial Populations
Authors: Stevanovic Mirjana , Boukéké-Lesplulier Thomas , Hupe Lukas , Hasty Jeff , Bittihn Philip , Schultz Daniel
Published: April 2022

Antibiotic treatments often fail to eliminate bacterial populations due to heterogeneity in how individual cells respond to the drug. In structured bacterial populations such as biofilms, bacterial metabolism and environmental transport processes lead to an emergent phenotypic structure and self-generated nutrient gradients toward the interior of the colony, which can affect cell growth, gene expression and susceptibility to the drug. Even in single cells, survival depends on a dynamic interplay between the drug’s action and the expression of resistance genes. How expression of resistance is coordinated across populations in the presence of such spatiotemporal environmental coupling remains elusive. Using a custom microfluidic device, we observe the response of spatially extended microcolonies of tetracycline-resistant E. coli to precisely defined dynamic drug regimens. We find an intricate interplay between drug-induced changes in cell growth and growth-dependent expression of resistance genes, resulting in the redistribution of metabolites and the reorganization of growth patterns. This dynamic environmental feedback affects the regulation of drug resistance differently across the colony, generating dynamic phenotypic structures that maintain colony growth during exposure to high drug concentrations and increase population-level resistance to subsequent exposures. A mathematical model linking metabolism and the regulation of gene expression is able to capture the main features of spatiotemporal colony dynamics. Uncovering the fundamental principles that govern collective mechanisms of antibiotic resistance in spatially extended populations will allow the design of optimal drug regimens to counteract them.
The Host CYP1A1-Microbiota Metabolic Axis Promotes Gut Barrier Disruption in Methicillin-Resistant Staphylococcus aureus-Induced Abdominal Sepsis
Authors: Ma Xiaoyuan , Jin Huaijian , Chu Xiang , Dai Weihong , Tang Wanqi , Zhu Junyu , Wang Fangjie , Yang Xue , Li Wei , Liu Guodong , Yang Xia , Liang Huaping
Published: April 2022

Background

Host-microbiota crosstalk has been implicated in multiple host metabolic pathway axes that regulate intestinal barrier function. Although constitutive cytochrome P4501A1 (CYP1A1) expression perturbs the microbiome-derived autoregulatory loop following enteric infection, little is known about the role of host CYP1A1 in modulating gut microbiome-mediated signaling during methicillin-resistant Staphylococcus aureus (MRSA)-induced abdominal sepsis and its effects on intestinal barrier integrity.

Methods

Abdominal sepsis was induced by the intraperitoneal injection of MRSA in mice. The effect of CYP1A1 deficiency on gut barrier integrity was investigated using RNA sequencing, microbiome analyses, and targeted metabolomics. The microbiota-produced metabolites were validated in patients with sepsis and persistent MRSA infection.

Results

Mice lacking CYP1A1 exhibited an altered gut microbiome, a reduced metabolic shift from lysine to cadaverine in the caecal contents and antimicrobial molecule production (Retnlb, Gbp7, and Gbp3), and they were protected against gut barrier disruption when subjected to MRSA challenge. These beneficial effects were validated in aryl hydrocarbon receptor (AHR) knockout (KO) mice by cohousing with CYP1A1 KO mice and abrogated after supplementation with cadaverine or Enterococcus faecalis, the primary microbiota genus for cadaverine synthesis. Antibiotic-driven gut dysbacteriosis impaired the survival benefit and disrupted the intestinal barrier integrity in CYP1A1 KO mice after MRSA infection. Furthermore, increased cadaverine levels in feces and serum were detected in critically ill patients with gut leakiness during persistent MRSA infection, whereas cadaverine was not detected in healthy controls. Additionally, microbiota-derived cadaverine induced enterocyte junction disruption by activating the histamine H4 receptor/nuclear factor-κB/myosin light-chain kinase signaling pathway.

Conclusion

This study revealed the unexpected function of host CYP1A1 in microbiota-mediated cadaverine metabolism, with crucial consequences for dysbacteriosis following MRSA-induced abdominal sepsis, indicating that inhibiting CYP1A1 or blocking cadaverine-histamine H4 receptor signaling could be a potential therapeutic target against abdominal sepsis.

Clinical Trial Registration

[http://www.chictr.org.cn/index.aspx], identifier [ChiCTR1800018646].
Level of Detection (LOD50) of Campylobacter Is Strongly Dependent on Strain, Enrichment Broth, and Food Matrix
Authors: Hazeleger Wilma C. , Jacobs-Reitsma Wilma F. , Den Besten Heidy M. W.
Published: April 2022

The detection of thermotolerant Campylobacter in food may be difficult due to the growth of extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae during enrichment, resulting in false-negative samples. Therefore, the ISO protocol (ISO 10272-1:2017) suggests that, next to Bolton broth (BB), Preston broth (PB) is used as an enrichment broth to inhibit competitive flora in samples with suspected high levels of background microorganisms, such as ESBL-producing bacteria. However, the application of the strains used for validation of this ISO was not clearly characterized. This study examined the LOD50 (level of detection, the concentration where the probability of detection is 50%) of the validation strains (three C. jejuni and two C. coli strains) in BB and PB using different food matrices, namely, raw milk, chicken skin, frozen minced meat, and frozen spinach. The LOD50 was calculated by inoculating multiple portions with at least two inoculum levels. For each reproduction, eight test portions were used for each inoculum level and the test portion size was 10 g (chicken skin, frozen minced meat, and frozen spinach) or 10 mL (raw milk). Furthermore, the effect of artificially inoculated ESBL-producing E. coli on the LOD50 was examined to mimic the presence of ESBL-producing background microorganisms in the food matrices, namely, raw milk and chicken skin. In BB, the LOD50 of all strains tested in raw milk, chicken skin, and frozen spinach was rather low (0.4–37 CFU/test portion), while the LOD50 in frozen minced meat was higher and much more variable (1–1,500 CFU/test portion), depending on the strain. Generally, enrichment in PB resulted in higher LOD50 than in BB, especially for C. coli. Co-inoculation with ESBL-producing E. coli increased the LOD50 in BB, while PB successfully inhibited the growth of this competitive microorganism. In conclusion, food matrix and enrichment broth may have a large influence on the LOD50 of different Campylobacter strains. Therefore, it is not possible to give an unequivocal advice on when to use which enrichment broth, and this advocates the use of both methods in case of doubt. Furthermore, this study indicates specific strains that would be a good choice to use for Campylobacter method verification as described in ISO 16140-3:2021.
Metabolomic Profiling of Plasma Reveals Differential Disease Severity Markers in COVID-19 Patients
Authors: Oliveira Lucas Barbosa , Mwangi Victor Irungu , Sartim Marco Aurélio , Delafiori Jeany , Sales Geovana Manzan , de Oliveira Arthur Noin , Busanello Estela Natacha Brandt , Val Fernando Fonseca de Almeida e , Xavier Mariana Simão , Costa Fabio Trindade , Baía-da-Silva Djane Clarys , Sampaio Vanderson de Souza , de Lacerda Marcus Vinicius Guimarães , Monteiro Wuelton Marcelo , Catharino Rodrigo Ramos , de Melo Gisely Cardoso
Published: April 2022

The severity, disabilities, and lethality caused by the coronavirus 2019 (COVID-19) disease have dumbfounded the entire world on an unprecedented scale. The multifactorial aspect of the infection has generated interest in understanding the clinical history of COVID-19, particularly the classification of severity and early prediction on prognosis. Metabolomics is a powerful tool for identifying metabolite signatures when profiling parasitic, metabolic, and microbial diseases. This study undertook a metabolomic approach to identify potential metabolic signatures to discriminate severe COVID-19 from non-severe COVID-19. The secondary aim was to determine whether the clinical and laboratory data from the severe and non-severe COVID-19 patients were compatible with the metabolomic findings. Metabolomic analysis of samples revealed that 43 metabolites from 9 classes indicated COVID-19 severity: 29 metabolites for non-severe and 14 metabolites for severe disease. The metabolites from porphyrin and purine pathways were significantly elevated in the severe disease group, suggesting that they could be potential prognostic biomarkers. Elevated levels of the cholesteryl ester CE (18:3) in non-severe patients matched the significantly different blood cholesterol components (total cholesterol and HDL, both p < 0.001) that were detected. Pathway analysis identified 8 metabolomic pathways associated with the 43 discriminating metabolites. Metabolomic pathway analysis revealed that COVID-19 affected glycerophospholipid and porphyrin metabolism but significantly affected the glycerophospholipid and linoleic acid metabolism pathways (p = 0.025 and p = 0.035, respectively). Our results indicate that these metabolomics-based markers could have prognostic and diagnostic potential when managing and understanding the evolution of COVID-19.
Carbohydrate Metabolism in Bacteria: Alternative Specificities in ADP-Glucose Pyrophosphorylases Open Novel Metabolic Scenarios and Biotechnological Tools
Authors: Bhayani Jaina , Iglesias Maria Josefina , Minen Romina I. , Cereijo Antonela E. , Ballicora Miguel A. , Iglesias Alberto A. , Asencion Diez Matias D.
Published: April 2022

We explored the ability of ADP-glucose pyrophosphorylase (ADP-Glc PPase) from different bacteria to use glucosamine (GlcN) metabolites as a substrate or allosteric effectors. The enzyme from the actinobacteria Kocuria rhizophila exhibited marked and distinctive sensitivity to allosteric activation by GlcN-6P when producing ADP-Glc from glucose-1-phosphate (Glc-1P) and ATP. This behavior is also seen in the enzyme from Rhodococcus spp., the only one known so far to portray this activation. GlcN-6P had a more modest effect on the enzyme from other Actinobacteria (Streptomyces coelicolor), Firmicutes (Ruminococcus albus), and Proteobacteria (Agrobacterium tumefaciens) groups. In addition, we studied the catalytic capacity of ADP-Glc PPases from the different sources using GlcN-1P as a substrate when assayed in the presence of their respective allosteric activators. In all cases, the catalytic efficiency of Glc-1P was 1–2 orders of magnitude higher than GlcN-1P, except for the unregulated heterotetrameric protein (GlgC/GgD) from Geobacillus stearothermophilus. The Glc-1P substrate preference is explained using a model of ADP-Glc PPase from A. tumefaciens based on the crystallographic structure of the enzyme from potato tuber. The substrate-binding domain localizes near the N-terminal of an α-helix, which has a partial positive charge, thus favoring the interaction with a hydroxyl rather than a charged primary amine group. Results support the scenario where the ability of ADP-Glc PPases to use GlcN-1P as an alternative occurred during evolution despite the enzyme being selected to use Glc-1P and ATP for α-glucans synthesis. As an associated consequence in such a process, certain bacteria could have improved their ability to metabolize GlcN. The work also provides insights in designing molecular tools for producing oligo and polysaccharides with amino moieties.
Residues 140–142, 199–200, 222–223, and 262 in the Surface Glycoprotein of Subgroup A Avian Leukosis Virus Are the Key Sites Determining Tva Receptor Binding Affinity and Infectivity
Authors: Li Jinqun , Chen Jian , Dong Xinyi , Liang Canxin , Guo Yanyan , Chen Xiang , Huang Mengyu , Liao Ming , Cao Weisheng
Published: April 2022

Subgroup A avian leukosis virus (ALV-A) invades cells through gp85-encoded surface glycoprotein (SU) via specifically recognizing the cellular receptor Tva. To identify the key residues of ALV-A SU that determine the Tva binding affinity and infectivity in DF-1 cells, a strategy of substituting corresponding residues of SU between ALV-A RSA and ALV-E ev-1 (using Tvb as the receptor) was adopted. A series of chimeric soluble gp85 proteins were expressed for co-immunoprecipitation (co-IP) analysis and blocking analysis of viral entry, and various recombinant viruses based on replication-competent avian retrovirus vectors containing Bryan polymerase (RCASBP) were constructed for transfection into DF-1 cells and measurement of the percentage of GFP-positive cells. The results revealed that the substitution of residues V138, W140, Y141, L142, S145, and L154 of host range region 1 (hr1), residues V199, G200, Q202, R222, and R223 of host range region 2 (hr2), and residue G262 of variable region 3 (vr3) reduced the viral infectivity and Tva binding affinity, which was similar to the effects of the −139S, −151N, −155PWVNPF, −201NFD, Δ214–215, and −266S mutations. Our study indicated that hr1 and hr2 contain the principal receptor interaction determinants, with new identified-vr3 also playing a key role in the receptor binding affinity of ALV-A.
Immune Checkpoint Molecules Expressed on CD4+ T Cell Subsets in Chronic Asymptomatic Hepatitis B Virus Carriers With Hepatitis B e Antigen-Negative
Authors: Cui Dawei , Jiang Daixi , Yan Cuilin , Liu Xia , Lv Yan , Xie Jue , Chen Yu
Published: April 2022

Background

Chronic hepatitis B virus (HBV) infection remains a major public health problem worldwide. Immune checkpoint molecules expressed on CD4+ T cells play critical roles in chronic HBV infection. However, their roles in chronic asymptomatic HBV carriers (ASCs) with hepatitis B e antigen (HBeAg)-negative remain unclear. In this study, we explored the role of immune checkpoint molecules expressed on CD4+ T cell subsets in chronic ASCs with HBeAg-negative.

Methods

Human peripheral blood mononuclear cells (PBMCs) from the ASCs with HBeAg-negative and healthy controls (HC) were isolated, and immune checkpoint molecules expressed on CD4+ T cell subsets and serum cytokines were detected by flow cytometry. Moreover, the mRNA expressions of immune checkpoint molecules were analyzed by a real-time quantitative PCR assay.

Results

In comparison with HC, CD4+ T cells highly expressed LAG-3, TIM-3, and PD-1 in PBMCs from chronic ASCs with HBeAg-negative. Interestingly, the expressions of TIM-3 and PD-1 on circulating follicular helper T (Tfh) cells in ASCs were significantly high. Moreover, high expressions of LAG-3, TIM-3, and PD-1 were different among Treg, Th1, Th2, and Th17 cells. In addition, the expressions of TIM-3 and CTLA-4 mRNA in PBMCs from ASCs were significantly elevated. However, the frequency of CTLA-4+CD4+ T cell subsets in PBMCs from ASCs was not different from HC. The levels of six cytokines in serum from ASCs were not clearly different from HC.

Conclusion

Immune checkpoint molecules highly expressed on CD4+ T cell subsets indicated an important role in chronic ASCs with HBeAg-negative, which provided potential therapeutic targets in the pathogenesis of chronic HBV infection.
Comparative Antigenicity and Pathogenicity of Two Distinct Genotypes of Highly Pathogenic Avian Influenza Viruses (H5N8) From Wild Birds in China, 2020–2021
Authors: Jiang Wenming , Liu Shuo , Yin Xin , Li Zhixin , Lan Zouran , Xire Luosong , Wang Zhongbing , Xie Yinqian , Peng Cheng , Li Jinping , Hou Guangyu , Yu Xiaohui , Sun Rongzhao , Liu Hualei
Published: April 2022

To date, there have been three epidemic waves of H5N8 avian influenza worldwide. The current third epidemic wave began in October 2020 and has expanded to at least 46 countries. Active and passive surveillance were conducted to monitor H5N8 viruses from wild birds in China. Genetic analysis of 10 H5N8 viruses isolated from wild birds identified two different genotypes. Animal challenge experiments indicated that the H5N8 isolates are highly pathogenic in chickens, mildly pathogenic in ducks, while pathogenicity varied in BALB/c mice. Moreover, there were significant differences in antigenicity as compared to Re-11 vaccine strain and vaccinated chickens were not completely protected against challenge with the high dose of H5N8 virus. With the use of the new matched vaccine and increased poultry immune density, surveillance should be intensified to monitor the emergence of mutant strains and potential worldwide spread via wild birds.
Gestational Dating by Urine Metabolic Profile at High Resolution Weekly Sampling Timepoints: Discovery and Validation
Authors: Sylvester Karl G. , Hao Shiying , Li Zhen , Han Zhi , Tian Lu , Ladella Subhashini , Wong Ronald J. , Shaw Gary M. , Stevenson David K. , Cohen Harvey J. , Whitin John C. , McElhinney Doff B. , Ling Xuefeng B.
Published: April 2022

Background: Pregnancy triggers longitudinal metabolic alterations in women to allow precisely-programmed fetal growth. Comprehensive characterization of such a “metabolic clock” of pregnancy may provide a molecular reference in relation to studies of adverse pregnancy outcomes. However, a high-resolution temporal profile of metabolites along a healthy pregnancy remains to be defined.

Methods: Two independent, normal pregnancy cohorts with high-density weekly urine sampling (discovery: 478 samples from 19 subjects at California; validation: 171 samples from 10 subjects at Alabama) were studied. Urine samples were profiled by liquid chromatography-mass spectrometry (LC-MS) for untargeted metabolomics, which was applied for gestational age dating and prediction of time to delivery.

Results: 5,473 urinary metabolic features were identified. Partial least-squares discriminant analysis on features with robust signals (n = 1,716) revealed that the samples were distributed on the basis of the first two principal components according to their gestational age. Pathways of bile secretion, steroid hormone biosynthesis, pantohenate, and CoA biosynthesis, benzoate degradation, and phenylpropanoid biosynthesis were significantly regulated, which was collectively applied to discover and validate a predictive model that accurately captures the chronology of pregnancy. With six urine metabolites (acetylcholine, estriol-3-glucuronide, dehydroepiandrosterone sulfate, α-lactose, hydroxyexanoy-carnitine, and l-carnitine), models were constructed based on gradient-boosting decision trees to date gestational age in high accordance with ultrasound results, and to accurately predict time to delivery.

Conclusion: Our study characterizes the weekly baseline profile of the human pregnancy metabolome, which provides a high-resolution molecular reference for future studies of adverse pregnancy outcomes.
Statistical Analysis of Multisensory and Text-Derived Representations on Concept Learning
Authors: Wang Yuwei , Zeng Yi
Published: April 2022

When learning concepts, cognitive psychology research has revealed that there are two types of concept representations in the human brain: language-derived codes and sensory-derived codes. For the objective of human-like artificial intelligence, we expect to provide multisensory and text-derived representations for concepts in AI systems. Psychologists and computer scientists have published lots of datasets for the two kinds of representations, but as far as we know, no systematic work exits to analyze them together. We do a statistical study on them in this work. We want to know if multisensory vectors and text-derived vectors reflect conceptual understanding and if they are complementary in terms of cognition. Four experiments are presented in this work, all focused on multisensory representations labeled by psychologists and text-derived representations generated by computer scientists for concept learning, and the results demonstrate that (1) for the same concept, both forms of representations can properly reflect the concept, but (2) the representational similarity analysis findings reveal that the two types of representations are significantly different, (3) as the concreteness of the concept grows larger, the multisensory representation of the concept becomes closer to human beings than the text-derived representation, and (4) we verified that combining the two improves the concept representation.
Contributions of Magnetoencephalography to Understanding Mechanisms of Generalized Epilepsies: Blurring the Boundary Between Focal and Generalized Epilepsies?
Authors: Aung Thandar , Tenney Jeffrey R. , Bagić Anto I.
Published: April 2022

According to the latest operational 2017 ILAE classification of epileptic seizures, the generalized epileptic seizure is still conceptualized as “originating at some point within and rapidly engaging, bilaterally distributed networks.” In contrast, the focal epileptic seizure is defined as “originating within networks limited to one hemisphere.” Hence, one of the main concepts of “generalized” and “focal” epilepsy comes from EEG descriptions before the era of source localization, and a presumed simultaneous bilateral onset and bi-synchrony of epileptiform discharges remains a hallmark for generalized seizures. Current literature on the pathophysiology of generalized epilepsy supports the concept of a cortical epileptogenic focus triggering rapidly generalized epileptic discharges involving intact corticothalamic and corticocortical networks, known as the cortical focus theory. Likewise, focal epilepsy with rich connectivity can give rise to generalized spike and wave discharges resulting from widespread bilateral synchronization. Therefore, making this key distinction between generalized and focal epilepsy may be challenging in some cases, and for the first time, a combined generalized and focal epilepsy is categorized in the 2017 ILAE classification. Nevertheless, treatment options, such as the choice of antiseizure medications or surgical treatment, are the reason behind the importance of accurate epilepsy classification. Over the past several decades, plentiful scientific research on the pathophysiology of generalized epilepsy has been conducted using non–invasive neuroimaging and postprocessing of the electromagnetic neural signal by measuring the spatiotemporal and interhemispheric latency of bi-synchronous or generalized epileptiform discharges as well as network analysis to identify diagnostic and prognostic biomarkers for accurate diagnosis of the two major types of epilepsy. Among all the advanced techniques, magnetoencephalography (MEG) and multiple other methods provide excellent temporal and spatial resolution, inherently suited to analyzing and visualizing the propagation of generalized EEG activities. This article aims to provide a comprehensive literature review of recent innovations in MEG methodology using source localization and network analysis techniques that contributed to the literature of idiopathic generalized epilepsy in terms of pathophysiology and clinical prognosis, thus further blurring the boundary between focal and generalized epilepsy.
EEG Evidence Reveals Zolpidem-Related Alterations and Prognostic Value in Disorders of Consciousness
Authors: Hao Zexuan , Xia Xiaoyu , Bai Yang , Wang Yong , Dou Weibei
Published: April 2022

Effective treatment and accurate long-term prognostication of patients with disorders of consciousness (DOC) remain pivotal clinical issues and challenges in neuroscience. Previous studies have shown that zolpidem produces paradoxical recovery and induces similar change patterns in specific electrophysiological features in some DOC (∼6%). However, whether these specific features are neural markers of responders, and how neural features evolve over time remain unclear. Here, we capitalized on static and dynamic EEG analysis techniques to fully uncover zolpidem-induced alterations in eight patients with DOC and constructed machine-learning models to predict long-term outcomes at the single-subject level. We observed consistent patterns of change across all patients in several static features (e.g., decreased relative theta power and weakened alpha-band functional connectivity) after zolpidem administration, albeit none zolpidem responders. Based on the current evidence, previously published electrophysiological features are not neural markers for zolpidem responders. Moreover, we found that the temporal dynamics of the brain slowed down after zolpidem intake. Brain states before and after zolpidem administration could be completely characterized by the EEG features. Furthermore, long-term outcomes were accurately predicted using connectivity features. Our findings suggest that EEG neural signatures have huge potential to assess consciousness states and predict fine-grained outcomes. In summary, our results extend the understanding of the effects of zolpidem on the brain and open avenues for the application prospect of zolpidem and EEG in patients with DOC.
A2 Milk and BCM-7 Peptide as Emerging Parameters of Milk Quality
Authors: Giribaldi Marzia , Lamberti Cristina , Cirrincione Simona , Giuffrida Maria Gabriella , Cavallarin Laura
Published: April 2022

Beta-casein makes up about 30% of the total protein contained in milk and can be present in cows' milk in two distinct forms (A1 or A2) or as a combination of the two. The only difference between these two variants of β-casein (β-CN) is a single amino acid substitution. This results in a different behavior of the protein upon enzymatic cleavage, following human consumption or due to microbial action. In most of the commercially available milk containing A1 or A1/A2 β-CN variants, the β-casomorphin-7 peptide (BCM-7) is released upon digestion and during cheese manufacturing/ripening, while this does not happen with A2 milk. BCM-7 is a known μ-opioid receptor agonist that may influence the gastro-intestinal physiology directly and may also exert effects elsewhere in the body, such as on the cardiovascular, neurological and endocrine systems. The present article is aimed at a revision of prior review papers on the topic, with a focus on the impact of ingestion of A1 β-CN milk and A2 β-CN milk on any health-related outcomes and on the impact of A1 or A2 β-CN variant on technological properties of cows' milk. When systematic reviews were considered, it was possible to conclude that A2 β-CN exerts beneficial effects at the gastrointestinal level compared with A1 β-CN, but that there is no evidence of A1 β-CN having negative effects on human health. Physicochemical differences among cows' milk containing either β-CN A2 or β-CN A1 and their effects on technological properties are discussed.
Gallnut Tannic Acid Exerts Anti-stress Effects on Stress-Induced Inflammatory Response, Dysbiotic Gut Microbiota, and Alterations of Serum Metabolic Profile in Beagle Dogs
Authors: Yang Kang , Jian Shiyan , Wen Chaoyu , Guo Dan , Liao Pinfeng , Wen Jiawei , Kuang Tao , Han Sufang , Liu Qingshen , Deng Baichuan
Published: April 2022

Stress exposure is a potential threat to humans who live or work in extreme environments, often leading to oxidative stress, inflammatory response, intestinal dysbiosis, and metabolic disorders. Gallnut tannic acid (TA), a naturally occurring polyphenolic compound, has become a compelling source due to its favorable anti-diarrheal, anti-oxidative, anti-inflammatory, and anti-microbial activities. Thus, this study aimed to evaluate the anti-stress effects of gallnut TA on the stress-induced inflammatory response, dysbiotic gut microbiota, and alterations of serum metabolic profile using beagle models. A total of 13 beagle dogs were randomly divided into the stress (ST) and ST + TA groups. Dietary supplementation with TA at 2.5 g/kg was individually fed to each dog in the ST + TA group for 14 consecutive days. On day 7, all dogs were transported for 3 h from a stressful environment (days 1–7) to a livable site (days 8–14). In our results, TA relieved environmental stress-induced diarrheal symptoms in dogs and were shown to protect from myocardial injury and help improve immunity by serum biochemistry and hematology analysis. Also, TA inhibited the secretion of serum hormones [cortisol (COR), glucocorticoid (GC), and adrenocorticotropic hormone (ACTH)] and the expression of heat shock protein (HSP) 70 to protect dogs from stress-induced injury, thereby relieving oxidative stress and inflammatory response. Fecal 16S rRNA gene sequencing revealed that TA stimulated the growth of beneficial bacteria (Allobaculum, Dubosiella, Coriobacteriaceae_UCG-002, and Faecalibaculum) and suppressed the growth of pathogenic bacteria (Escherichia-Shigella and Streptococcus), thereby increasing fecal butyrate levels. Serum metabolomics further showed that phytosphingosine, indoleacetic acid, arachidonic acid, and biotin, related to the metabolism of sphingolipid, tryptophan, arachidonic acid, and biotin, respectively, could serve as potential biomarkers of stress exposure. Furthermore, Spearman’s correlation analysis showed strong relationships between the four potential serum biomarkers and differential bacteria. Overall, gallnut TA may be a potential prebiotic for the prevention and treatment of stress-induced metabolic disorders by targeting intestinal microbiota.
Food-Level Analysis to Identify Dietary Choices With the Highest Nutritional Quality and Lowest Greenhouse Gas Emissions and Price
Authors: Aceves-Martins Magaly , Bates Ruth L. , Craig Leone C. A. , Chalmers Neil , Horgan Graham , Boskamp Bram , de Roos Baukje
Published: April 2022

Introduction

Food systems are challenged to provide healthy, sustainable and affordable foods. From a consumer perspective, identifying healthy, sustainable and affordable choices based on individual food products rather than diets could promote better shopping choices.

Objective

To identify foods and drinks with the highest nutritional quality and lowest greenhouse gas emissions (GHGE) and price. We also assessed how a combination of these indicators (e.g., nutritional quality, GHGE and price) for food categories aligned with current United Kingdom dietary recommendations.

Materials and Methods

We performed a secondary analysis of the National Diet and Nutrition Survey (NDNS) nutrient databank year 11 (2018/2019). Spearman correlation coefficients were used to assess the strength of relationships between nutritional quality, environmental impact and/or prices per 100 kcal. In addition, we developed an optimized nutritional quality, GHGE and price score for each food or drink item based on the overall medians for each of these indicators.

Results

Median nutritional value was highest for fruit and vegetables, whilst median GHGE and price was lower for starchy carbohydrates, fats and items of which consumption should be limited. The relative proportions of foods considered the most nutritious and with a low GHGE and price in each of the food categories, on a per 100 kcal basis, were comparable to the proportions in the Eatwell Guide, except for the proportion of fruits and vegetables being smaller and the proportion of potatoes, bread, rice, pasta, and other starchy carbohydrates being larger in our analysis.

Conclusion

Public health efforts should consider the impact of dietary choices not only in terms of nutritional quality but also in terms of environmental and economic impact. Our food-based analysis shows a large variation in nutritional quality, GHGE and price within and across food categories, which provides consumers with opportunities for “food swaps” that are more nutritious and have lower GHGE and price.
The Importance of Heating Unit Operations in the Food Industry to Obtain Safe and High-Quality Products
Authors: Tadini Carmen C. , Gut Jorge A. W.
Published: April 2022

Civilization has begun around 3,500 BCE in Mesopotamia and the realization by people that they could manipulate food to preserve it, through sun drying, fermentation, freezing in the snow, or cooking by fire, was an important factor for the nomadic humans to start settling. Food by nature is subject to spoilage and the application of any kind of preservation method enables storage and weighted consumption. Throughout human history, many techniques have been developed and improved such as heat treatment, drying, freezing, extraction, mixing and the use of preservatives, among others. In the food industry of the modern world, each technique is implemented through sequential steps, known as unit operations. This opinion paper presents an overview of the main heating unit operations used in the food industry, highlighting their benefits to converting raw materials into palatable products with high quality and safe for consumption. Examples are presented to illustrate how several food products available in the market were submitted only to physical transformations based on scientific knowledge. However, there is a range of intensity in physical processing and the applied energy level depends on the nature of the food, target microorganism, storage conditions, type of packaging, and desired shelf-life. The importance of food safety is stressed since processed foods have been criticized for confusion between nutritious values and processing steps. There are still many challenges to the food industry to design the process in optimal conditions for food quality and with less environmental impacts and novel thermal and non-thermal technologies have been studied and implemented.
Development and Validation of a Nomogram Based on Geriatric Nutritional Risk Index to Predict Surgical Site Infection Among Gynecologic Oncology Patients
Authors: Chen Zhihui , Zhong Mingchen , Xu Ziqin , Ye Qing , Xie Wenwen , Gao Shengchun , Chen Le , Qiu Lidan , Jiang Jiaru , Wu Hongmei , Li Xiuyang , Wang Haihong
Published: April 2022

Background

The geriatric nutritional risk index (GNRI) is a commonly used method to assess nutritional risk for predicting potential surgical site infections (SSI) in cancer patients. This study aims to create and verify a simple nomogram and a dynamic web-based calculator for predicting the risk of SSI among gynecologic oncology patients.

Methods

A retrospective evaluation was conducted on patients who were admitted into a tertiary hospital in China with confirmed diagnosis of gynecologic cancer between 01 August 2017 and 30 November 2021. A two-piecewise linear regression model with a smoothing function was used to investigate the non-linear association between GNRI and SSI to determine the ideal cut-off point. Three models were developed on the basis of different variables to predict SSI in gynecologic oncology patients. Through a nomogram the concordance index (C-index), the Akaike information criterion (AIC), and the integrated discrimination index (IDI) were used to determine the final model. Finally, the performance of the nomogram was validated using the 1,000-bootstrap resamples method and analyzed using C-index, GiViTI calibration belts, and decision curve. Also, a user-friendly dynamic web-based calculator was developed.

Results

A total of 1,221 patients were included in the analysis. A non-linear association could be observed between GNRI and SSI risk with a GNRI cut-off value of 101.7. After adding GNRI to Model 2 (which comprised Morse Fall Scale score, preoperative length of stay, operation time, and estimated blood loss), the AIC value decreased, the C-index value increased and IDI increased significantly. The nomogram C-index in the development cohort and internal validation cohort demonstrates a moderate-high degree of discrimination. The GiViTI calibrated belt showed a good agreement between the observed and predicted probabilities of SSI. The decision curve validates the clinical feasibility of the nomogram with a threshold value between 0 and 49%.

Conclusion

The GNRI cut-off value of 101.7 allowed for appropriate stratification of patients into distinct SSI risk groups. This study found that including GNRI in the above nomogram (Model 2) would enhance its potential to predict SSI in gynecologic oncology patients.
Gut Microbiota and Serum Metabolite Potential Interactions in Growing Layer Hens Exposed to High-Ambient Temperature
Authors: Zhou Changming , Gao Xiaona , Cao Xianhong , Tian Guanming , Huang Cheng , Guo Lianying , Zhao Yulan , Hu Guoliang , Liu Ping , Guo Xiaoquan
Published: April 2022

Emerging evidence has revealed the dysbiosis of gut microbiota contributes to development of metabolic diseases in animals. However, the potential interaction between gut microbiota and host metabolism in growing hens under metabolic disorder induced by chronic heat exposure (CHE) remains inconclusive. The aim of our study was to examine the potential association among the cecal microbiota community, physiological indicators, and serum metabolite profiles in CHE hens. One hundred and eighty Hy-Line Brown hens were randomly allocated into three groups: thermoneutral control (TN), heat stress (HS), and pair-fed (PF). The experiment lasted for 5 weeks, with the first 2 weeks serving as the adaptation period. Results showed that the expression level of heat shock protein 70 (HSP70) in both serum and cecal tissues was significantly increased in the HS group. Serum parameters analysis also revealed that CHE caused physiological function damage and metabolic disorders. These results suggest the experiment was successful, inducing chronic heat stress. 16S rRNA sequencing analysis showed that the CHE can clearly induce dysbiosis of the gut microbial community reflected in the increment of the F/B ratio. Besides, serum untargeted metabolomics revealed the relative concentrations of 40 metabolites were significantly altered in the HS group compared with the TN group. Pathway analysis showed that these metabolites were mainly involving the increased proteolysis rather than lipolysis, and this tendency could be a specific metabolic adaptation of the poultry. The pair-feed experiment showed that the above changes induced by CHE were partly independent from the reduction of feed intake. Mantel correlation analysis between gut microorganisms and physiological indicators showed that the phylum Firmicutes and Euryarchaeota have a potential interaction with a serum lipid parameter. Random forest analysis showed that both genus Faecalibacterium and Methanobrevibacter were important predictors of the CHE-induced lipid metabolism disorder. Taken together, our findings may contribute to a better understanding of the metabolic mechanisms underlying the energy metabolism imbalance caused by the CHE and provide novel insights into the host-microbes interactions and its effects on the metabolic adaptation of hens under chronic heat exposure.
Radiomics Study for Differentiating Focal Hepatic Lesions Based on Unenhanced CT Images
Authors: Zhao Xitong , Liang Pan , Yong Liuliang , Jia Yan , Gao Jianbo
Published: April 2022

Objectives

To investigate the feasibility of computer-aided discriminative diagnosis among hepatocellular carcinoma (HCC), hepatic metastasis, hepatic hemangioma, hepatic cysts, hepatic adenoma, and hepatic focal nodular hyperplasia, based on radiomics analysis of unenhanced CT images.

Methods

452 patients with 77 with HCC, 104 with hepatic metastases, 126 with hepatic hemangioma, 99 with hepatic cysts, 24 with FNH, 22 with HA, who underwent CT examination from 2016 to 2018, were included. Radcloud Platform was used to extract radiomics features from manual delineation on unenhanced CT images. Most relevant radiomic features were selected from 1409 via LASSO (least absolute shrinkage and selection operator). The whole dataset was divided into training and testing set with the ratio of 8:2 using computer-generated random numbers. Support Vector Machine (SVM) was used to establish the classifier.

Results

The computer-aided diagnosis model was established based on radiomic features of unenhanced CT images. 27 optimal discriminative features were selected to distinguish the six different histopathological types of all lesions. The classifiers had good diagnostic performance, with the area under curve (AUC) values greater than 0.900 in training and validation groups. The overall accuracy of the training and testing set about differentiating the six different histopathological types of all lesions was 0.88 and 0.76 respectively. 34 optimal discriminative were selected to distinguish the benign and malignant tumors. The overall accuracy in the training and testing set was 0.89and 0.84 respectively.

Conclusions

The computer-aided discriminative diagnosis model based on unenhanced CT images has good clinical potential in distinguishing focal hepatic lesions with noninvasive radiomic features.
Multi-Region Radiomic Analysis Based on Multi-Sequence MRI Can Preoperatively Predict Microvascular Invasion in Hepatocellular Carcinoma
Authors: Gao Lanmei , Xiong Meilian , Chen Xiaojie , Han Zewen , Yan Chuan , Ye Rongping , Zhou Lili , Li Yueming
Published: April 2022

Objectives

Microvascular invasion (MVI) affects the postoperative prognosis in hepatocellular carcinoma (HCC) patients; however, there remains a lack of reliable and effective tools for preoperative prediction of MVI. Radiomics has shown great potential in providing valuable information for tumor pathophysiology. We constructed and validated radiomics models with and without clinico-radiological factors to predict MVI.

Methods

One hundred and fifteen patients with pathologically confirmed HCC (training set: n = 80; validation set: n = 35) who underwent preoperative MRI were retrospectively recruited. Radiomics models based on multi-sequence MRI across various regions (including intratumoral and/or peritumoral areas) were built using four classification algorithms. A clinico-radiological model was constructed individually and combined with a radiomics model to generate a fusion model by multivariable logistic regression.

Results

Among the radiomics models, the model based on T2WI and arterial phase (T2WI-AP model) in the volume of the liver–HCC interface (VOIinterface) exhibited the best predictive power, with AUCs of 0.866 in the training group and 0.855 in the validation group. The clinico-radiological model exhibited good efficacy (AUC: 0.819 and 0.717, respectively). The fusion model showed excellent predictive ability (AUC: 0.915 and 0.868, respectively), outperforming both the clinico-radiological and the T2WI-AP models in the training and validation sets.

Conclusion

The fusion model of multi-region radiomics achieves an enhanced prediction of the individualized risk estimation of MVI in HCC patients. This may be a beneficial tool for clinicians to improve decision-making in personalized medicine.