bluuebunny/crossref_metadata_2025 huggingface dataset:
Socio-technical systems and trust transfer in live streaming e-commerce: analyzing stickiness and purchase intentions with SEM-fsQCA
Authors: Chang Yu-Hsin , Silalahi Andri Dayarana K. , Eunike Ixora Javanisa , Riantama Dalianus
Published: February 2024

Live streaming has gained substantial significance in the e-commerce realm, attracting the attention of scholars due to its profound impact on the consumer decision-making journey. However, previous studies have not sufficiently investigated into the complex of marketing strategies through trust transfer mechanisms and socio-technical aspects, considering the dynamic nature of the live streaming e-commerce environment. Grounded on the socio-technical system theory, this research develops a research framework that centers on the exploration of interactivity, entertainment, and visualization as catalysts for trust transfer in live streaming. Trust transfer is conceptualized as advancing from cognitive trust to affective trust. Cognitive trust is proposed as a mediating factor bridging socio-technical system constructs to affective trust, ultimately shaping stickiness behavior and purchase intention in the live streaming context. To test the hypotheses, this study collected data from 682 participants in Indonesia and employed a hybrid analysis approach, combining SEM and fsQCA. The SEM results confirm that socio-technical system constructs significantly predict cognitive trust but do not directly impact affective trust. Instead, cognitive trust plays a full mediating role in transforming trust rooted in emotional bonds within the live streaming environment. Furthermore, both cognitive and affective trust exhibit a significant influence on the formation of stickiness behavior and the driving of purchase intention in the domain of live streaming e-commerce. The findings from fsQCA validate diverse configurations that shape stickiness behaviors and purchase intention, enriching marketing and communication strategies within the live streaming context. Additionally, the fsQCA configurations suggest varying conditions for high and low desired outcomes in stickiness and purchase intention, offering a comprehensive understanding of consumer behavior in live streaming e-commerce. This research makes substantial contributions to both theoretical understanding and marketing practice by providing an extensive discussion of configuration combinations that offer enhanced insights into the study's findings.
Prenatal diagnosis and clinical management of cardiac rhabdomyoma: a single-center study
Authors: Peng Longzhuang , Cai Youchun , Wu Jianhang , Ling Wen , Wu Qiumei , Guo Shan , Huang Biying , Jiang Caihong , Weng Zongjie
Published: February 2024

Objective

The study aims to assess the ultrasonic features of fetal cardiac rhabdomyoma (CR), track the perinatal outcome and postnatal disease progression, investigate the clinical utility of ultrasound, MRI and tuberous sclerosis complex (TSC) gene analysis in CR evaluation, and offer evidence for determing of fetal CR prognosis.

Methods

We conducted a retrospective analysis of prenatal ultrasound-diagnosed fetal CR cases in our hospital from June 2011 to June 2022, tracked the perinatal outcomes, regularly followed live infants to analyze cardiac lesion changes and disease progression, and compared the sensitivities of ultrasound, MRI and their combination in the detecting of intracranial sclerosing nodules.

Results

Our study included 54 fetuses with CR: 32 pregnancies were terminated, 22 were delivered, 35 were diagnosed with TSC, 13 had simple CR without TSC, and in 6 cases, remained unclear whether TSC accompanied the CR due to insufficient evidence. 45 fetuses (83.3%) had multiple lesions, while 9 fetuses (16.7%) presented with a single lesion. Twelve cases had intracardiac complications, all associated with multiple lesions, and these cases exhibited larger maximum tumor diameters than the non-complicated group. Multiple intracardiac lesions were more prevalent in the TSC group than in the simple CR group. However, there was no significant difference in maximum tumor diameter between the two groups. Among 30 fetuses who underwent fetal brain MRI, 23 were eventually diagnosed with TSC, with 11 fetuses showing intracranial sclerosis nodules by ultrasound and 15 by MRI, and the diagnostic consistency was moderate (k = 0.60). Twenty-two fetuses were born and followed up for 6–36 months. CR lesions diminished or disappeared in 18 infants (81.8%), while they remained unchanged in 4 infants (18.2%). Ten out of 12 (83.3%) surviving children diagnosed with TSC developed epilepsy, and 7 (58.3%) had neurodevelopmental dysfunction.

Conclusions

The majority of CR cases involve multiple lesions, which are a primary risk factor for TSC. Through prenatal ultrasound examination is crucial for assessing fetal CR prognosis. Although ultrasound combined with MRI can detect intracranial sclerosis nodules in TSC fetuses, its sensitivity is limited. TSC gene sequencing is an essential diagnostic method. Simple CR cases without TSC generally have a favorable prognosis.
Spatial variability of shear wave velocity: implications for the liquefaction response of a case study from the 2010 Maule Mw 8.8 Earthquake, Chile
Authors: Núñez-Jara S. , Montalva G. , Pilz M. , Miller M. , Saldaña H. , Olivar-Castaño A. , Araya R.
Published: February 2024

Assessing the potential and extent of earthquake-induced liquefaction is paramount for seismic hazard assessment, for the large ground deformations it causes can result in severe damage to infrastructure and pose a threat to human lives, as evidenced by many contemporary and historical case studies in various tectonic settings. In that regard, numerical modeling of case studies, using state-of-the-art soil constitutive models and numerical frameworks, has proven to be a tailored methodology for liquefaction assessment. Indeed, these simulations allow for the dynamic response of liquefiable soils in terms of effective stresses, large strains, and ground displacements to be captured in a consistent manner with experimental and in-situ observations. Additionally, the impact of soil properties spatial variability in liquefaction response can be assessed, because the system response to waves propagating are naturally incorporated within the model. Considering that, we highlight that the effect of shear-wave velocity Vs spatial variability has not been thoroughly assessed. In a case study in Metropolitan Concepción, Chile, our research addresses the influence of Vs spatial variability on the dynamic response to liquefaction. At the study site, the 2010 Maule Mw 8.8 megathrust Earthquake triggered liquefaction-induced damage in the form of ground cracking, soil ejecta, and building settlements. Using simulated 2D Vs profiles generated from real 1D profiles retrieved with ambient noise methods, along with a PressureDependentMultiYield03 sand constitutive model, we studied the effect of Vs spatial variability on pore pressure generation, vertical settlements, and shear and volumetric strains by performing effective stress site response analyses. Our findings indicate that increased Vs variability reduces the median settlements and strains for soil units that exhibit liquefaction-like responses. On the other hand, no significant changes in the dynamic response are observed in soil units that exhibit non-liquefaction behavior, implying that the triggering of liquefaction is not influenced by spatial variability in Vs. We infer that when liquefaction-like behavior is triggered, an increase of the damping at the shallowest part of the soil domain might be the explanation for the decrease in the amplitude of the strains and settlements as the degree of Vs variability increases.
Charcoal analysis for temperature reconstruction with infrared spectroscopy
Authors: Minatre Kerri L. , Arienzo Monica M. , Moosmüller Hans , Maezumi S. Yoshi
Published: February 2024

The duration and maximum combustion temperature of vegetation fires are important fire properties with implications for ecology, hydrology, hazard potential, and many other processes. Directly measuring maximum combustion temperature during vegetation fires is difficult. However, chemical transformations associated with temperature are reflected in the chemical properties of charcoals (a by-product of fire). Therefore, charcoal could be used indirectly to determine the maximum combustion temperature of vegetation fires with application to palaeoecological charcoal records. To evaluate the reliability of charcoal chemistry as an indicator of maximum combustion temperature, we studied the chemical properties of charcoal formed through two laboratory methods at measured temperatures. Using a muffle furnace, we generated charcoal from the woody material of ten different tree and shrub species at seven distinct peak temperatures (from 200°C to 800°C in 100°C increments). Additionally, we simulated more natural combustion conditions by burning woody material and leaves of four tree species in a combustion facility instrumented with thermocouples, including thermocouples inside and outside of tree branches. Charcoal samples generated in these controlled settings were analyzed using Fourier Transform Infrared (FTIR) spectroscopy to characterize their chemical properties. The Modern Analogue Technique (MAT) was employed on FTIR spectra of muffle furnace charcoal to assess the accuracy of inferring maximum pyrolysis temperature. The MAT model temperature matching accuracy improved from 46% for all analogues to 81% when including ±100°C. Furthermore, we used MAT to compare charcoal created in the combustion facility with muffle furnace charcoal. Our findings indicate that the spectra of charcoals generated in a combustion facility can be accurately matched with muffle furnace-created charcoals of similar temperatures using MAT, and the accuracy improved when comparing the maximum pyrolysis temperature from muffle furnace charcoal with the maximum inner temperature of the combustion facility charcoal. This suggests that charcoal produced in a muffle furnace may be representative of the inner maximum temperatures for vegetation fire-produced charcoals.
Thermal field reconstruction and compressive sensing using proper orthogonal decomposition
Authors: Matulis John , Bindra Hitesh
Published: February 2024

Model order reduction allows critical information about sensor placement and experiment design to be distilled from raw fluid mechanics simulation data. In many cases, sensed information in conjunction with reduced order models can also be used to regenerate full field variables. In this paper, a proper orthogonal decomposition (POD) inferencing method is extended to the modeling and compressive sensing of temperature, a scalar field variable. The method is applied to a simulated, critically stable, incompressible flow over a heated cylinder (Re = 1000) with Prandtl number varying between 0.001 and 50. The model is trained on pressure and temperature data from simulations. Field reconstructions are then generated using data from selected sensors and the POD model. Finally, the reconstruction error is evaluated across all Prandtl numbers for different numbers of retained modes and sensors. The predicted trend of increasing reconstruction accuracy with decreasing Prandtl number is confirmed and a Prandtl number/sensor count error matrix is presented.
Development and preliminary verification of a 1D–3D coupled flow and heat transfer model of OTSG
Authors: Lu Xianghui , Wang Xin , Zheng Xiong , Chen Xiting , Meng Shuqi , Ruan Tianming , Chen Jun , Mao Yulong , Hu Yisong , Shang Chaohao
Published: February 2024

Introduction: A simulation model was developed by coupling a one-dimensional (1D) system code and 3D CFD software, to analyze the three-dimensional (3D) flow and heat transfer characteristics of the once-through steam generator (OTSG).

Methods: The shell side of the OTSG was simulated by FLUENT, and the tube side was simulated by the system code LOCUST. Through spatial mapping, the 1D and 3D simulations were coupled along the outer wall of the OTSG's helically coiled tubes.

Results and Discussion: This coupling method enabled the acquisition of high-resolution flow and heat transfer characteristics of the OTSG, and the error of heat flux calculation result by the coupled model is within 15%. Through coupling simulation analysis of the prototype OTSG, it was found that the inlet and outlet temperature difference reached as high as 150°C. The unevenness of the radial temperature distribution increased along the flow direction, and the wake swing effect caused by the sweeping flow of the tube bundle at the exit position was evident. The results of this study provide reference and a coupled simulation method for the engineering design and thermal-hydraulic characteristics analysis of OTSG.
Environmental financing: does digital economy matter?
Authors: Akberdina Victoria , Lavrikova Yulia , Vlasov Maxim
Published: February 2024

Sustainable development and ecological restoration are a common goal pursued by countries around the world to mitigate the collision between economic growth and the environment. Digital economy has been rather instrumental in settling this type of conflict. The study is intended to identify the relationship between digital financing and environmental financing by assessing the specificities of their temporal and industry-specific dynamics, as well as to determine the side effects that the digital economy has in terms of current environmental investments and costs. The special attention is paid to the effect of the digital economy on both total environmental financing and its components, namely, environmental investment and current environmental protection costs. The authors come up with two indicators to evaluate the impact of the digital economy, these are digital financing (direct impact) and digital capital (indirect impact). To calculate these indicators, the authors’ own method is developed. The impact of the digital economy on environmental financing was tested using the least squares method with clustering of annual standard deviation and individual fixed effects. The research data were retrieved from the Federal State Statistics Service (Rosstat) of the Russian Federation for 2012–2022. Our findings show that digital financing exerts a significant positive effect on environmental financing, which indicates that two dynamic processes in the economy—digital transformation and introduction of advanced environmental digital technologies—are synchronized. The authors prove that digital investments stimulate a comparable increase in environmental investment due to the effects created by digital technologies penetrating into environmental protection technologies. We demonstrate that the level of digitalization of the population, companies and the state assessed through the digital capital index has a positive effect on environmental financing. The results of the study are of use in the sphere of public policy.
B cell repertoire sequencing of HIV-1 pediatric elite-neutralizers identifies multiple broadly neutralizing antibody clonotypes
Authors: Kumar Sanjeev , Bajpai Prashant , Joyce Collin , Kabra Sushil Kumar , Lodha Rakesh , Burton Dennis R. , Briney Bryan , Luthra Kalpana
Published: February 2024

Introduction

A limited subset of HIV-1 infected adult individuals typically after at least 2-3 years of chronic infection, develop broadly neutralizing antibodies (bnAbs), suggesting that highly conserved neutralizing epitopes on the HIV-1 envelope glycoprotein are difficult for B cell receptors to effectively target, during natural infection. Recent studies have shown the evolution of bnAbs in HIV-1 infected infants.

Methods

We used bulk BCR sequencing (BCR-seq) to profile the B cell receptors from longitudinal samples (3 time points) collected from a rare pair of antiretroviralnaïve, HIV-1 infected pediatric monozygotic twins (AIIMS_329 and AIIMS_330) who displayed elite plasma neutralizing activity against HIV-1.

Results

BCR-seq of both twins revealed convergent antibody characteristics including V-gene use, CDRH3 lengths and somatic hypermutation (SHM). Further, antibody clonotypes with genetic features similar to highly potent bnAbs isolated from adults showed ongoing development in donor AIIMS_330 but not in AIIMS_329, corroborating our earlier findings based on plasma bnAbs responses. An increase in SHM was observed in sequences of the IgA isotype from AIIMS_330.

Discussion

This study suggests that children living with chronic HIV-1 can develop clonotypes of HIV-1 bnAbs against multiple envelope epitopes similar to those isolated from adults, highlighting that such B cells could be steered to elicit bnAbs responses through vaccines aimed to induce bnAbs against HIV-1 in a broad range of people including children.
Advances in understanding of dendritic cell in the pathogenesis of acute kidney injury
Authors: Lv Dongfang , Jiang Huihui , Yang Xianzhen , Li Yi , Niu Weipin , Zhang Denglu
Published: February 2024

Acute kidney injury (AKI) is characterized by a rapid decline in renal function and is associated with a high morbidity and mortality rate. At present, the underlying mechanisms of AKI remain incompletely understood. Immune disorder is a prominent feature of AKI, and dendritic cells (DCs) play a pivotal role in orchestrating both innate and adaptive immune responses, including the induction of protective proinflammatory and tolerogenic immune reactions. Emerging evidence suggests that DCs play a critical role in the initiation and development of AKI. This paper aimed to conduct a comprehensive review and analysis of the role of DCs in the progression of AKI and elucidate the underlying molecular mechanism. The ultimate objective was to offer valuable insights and guidance for the treatment of AKI.
The subdued post-boost spike-directed secondary IgG antibody response in Ugandan recipients of the Pfizer-BioNTech BNT162b2 vaccine has implications for local vaccination policies
Authors: Ankunda Violet , Katende Joseph Ssebwana , Oluka Gerald Kevin , Sembera Jackson , Baine Claire , Odoch Geoffrey , Ejou Peter , Kato Laban ,   The COVID-19 Immunoprofiling Team, Kaleebu Pontiano , Serwanga Jennifer
Published: February 2024

Introduction

This study aimed to delineate longitudinal antibody responses to the Pfizer-BioNTech BNT162b2 COVID-19 vaccine within the Ugandan subset of the Sub-Saharan African (SSA) demographic, filling a significant gap in global datasets.

Methods

We enrolled 48 participants and collected 320 specimens over 12 months after the primary vaccination dose. A validated enzyme-linked immunosorbent assay (ELISA) was used to quantify SARS-CoV-2-specific IgG, IgM, and IgA antibody concentrations (ng/ml) and optical densities (ODs). Statistical analyses included box plots, diverging bar graphs, and the Wilcoxon test with Bonferroni correction.

Results

We noted a robust S-IgG response within 14 days of the primary vaccine dose, which was consistent with global data. There was no significant surge in S-IgG levels after the booster dose, contrasting trends in other global populations. The S-IgM response was transient and predominantly below established thresholds for this population, which reflects its typical early emergence and rapid decline. S-IgA levels rose after the initial dose then decreased after six months, aligning with the temporal patterns of mucosal immunity. Eleven breakthrough infections were noted, and all were asymptomatic, regardless of the participants’ initial S-IgG serostatus, which suggests a protective effect from vaccination.

Discussion

The Pfizer-BioNTech BNT162b2 COVID-19 vaccine elicited strong S-IgG responses in the SSA demographic. The antibody dynamics distinctly differed from global data highlighting the significance of region-specific research and the necessity for customised vaccination strategies.
The effect of dose-interval on antibody response to mRNA COVID-19 vaccines: a prospective cohort study
Authors: Almeida Nisha D. , Schiller Ian , Ke Danbing , Sakr Elsa , Plesa Maria , Vanamala Sandeep , Moneger Anne-Laure , Bazan Maria , Lucchesi Chiara , Wozniak Natalia , Fritz Jorg H. , Piccirillo Ciriaco A. , Pelchat Martin , Arnold Corey , Galipeau Yannick , McCluskie Pauline S. , Langlois Marc-Andre , Dasgupta Kaberi , Mazer Bruce D.
Published: February 2024

Background

Vaccination against COVID-19 is highly effective in preventing severe disease and hospitalization, but primary COVID mRNA vaccination schedules often differed from those recommended by the manufacturers due to supply chain issues. We investigated the impact of delaying the second dose on antibody responses to COVID mRNA-vaccines in a prospective cohort of health-care workers in Quebec.

Methods

We recruited participants from the McGill University Health Centre who provided serum or participant-collected dried blood samples (DBS) at 28-days, 3 months, and 6 months post-second dose and at 28-days after a third dose. IgG antibodies to SARS-CoV2 spike (S), the receptor-binding domain (RBD), nucleocapsid (N) and neutralizing antibodies to the ancestral strain were assessed by enzyme-linked immunosorbent assay (ELISA). We examined associations between long (≤89 days) versus short (<89 days) between-dose intervals and antibody response through multivariable mixed-effects models adjusted for age, sex, prior covid infection status, time since vaccine dose, and assay batch.

Findings

The cohort included 328 participants who received up to three vaccine doses (>80% Pfizer-BioNTech). Weighted averages of the serum (n=744) and DBS (n=216) cohort results from the multivariable models showed that IgG anti-S was 31% higher (95% CI: 12% to 53%) and IgG anti-RBD was 37% higher (95% CI: 14% to 65%) in the long vs. short interval participants, across all time points.

Interpretation

Our study indicates that extending the covid primary series between-dose interval beyond 89 days (approximately 3 months) provides stronger antibody responses than intervals less than 89 days. Our demonstration of a more robust antibody response with a longer between dose interval is reassuring as logistical and supply challenges are navigated in low-resource settings.
Development of a non-programmable sperm cryopreservation technique in dwarf surfclams Mulinia lateralis–a potential model species for bivalve research
Authors: Xu Zhen , Yang Zujing , Bao Lisui , Li Xiaoxu , Huang Xiaoting , Liu Yibing
Published: February 2024

Sperm cryopreservation technique has been published in many farmed bivalve species. One of the key factors preventing its application in aquaculture and/or cryobanking is the knowledge gap on the performance of resultant progeny at late developmental stages and subsequent generations. An effective strategy to overcome these challenges is to use a model species with a short generation interval, such as the dwarf surfclam Mulinia lateralis (three months). This study evaluated the parameters key to the development of a non-programmable sperm cryopreservation technique in this species, with a D-stage larval rate similar to control being achieved when the sperm were cryopreserved under the conditions (cryoprotectant agent: 8% dimethyl sulfoxide; equilibration period: 10 min; rack height: 4 cm; thawing temperature: 60°C and sperm to egg ratio: 1100:1) optimized. This technique is the most common method applied in bivalve and the results from this study were all within the ranges published for other bivalve species, indicating this species would be an ideal bivalve model species for addressing cryopreservation evaluation issues that need a long extended time to collect data and/or challenging field experiments.
Molecular dynamics simulation on the mechanical properties of Zr-Cu metallic nanoglasses with heterogeneous chemical compositions
Authors: Li Tian , Li Nana , Kuang Bo , Zheng Guangping
Published: February 2024

The mechanical properties of metallic nanoglasses (NGs) strongly depend on the average size of glassy grains (Davg). Nevertheless, current knowledge on the effects of sizes of glassy grains is incomplete for the mechanical properties of NGs. Herein, ZrxCu100-x (25 ≤ x ≤ 75) nanoglasses containing glassy grains with different chemical compositions, i.e., the heterogeneous NGs (HNGs), are investigated by molecular dynamics simulation, and the relation between ultimate tensile strength (UTS) and Davg is determined. Specifically, the UTS decreases with decreasing Davg in Zr-Cu HNGs when Davg < 10 nm, mainly resulting from the increased volume fraction of glass-glass interfaces, while UTS would follow the Hall–Petch like relation for Zr-Cu HNGs when Davg > 10 nm, which is closely related to glassy grains with compositions dominated by Zr atoms. This study provides a deep insight into the mechanical property dependence on grain size in the HNGs, which could be a novel strategy in resolving the issue of strength-ductility tradeoff in NGs.
Essential oils: a systematic review on revolutionizing health, nutrition, and omics for optimal well-being
Authors: Pezantes-Orellana Camila , German Bermúdez Fátima , Matías De la Cruz Carmen , Montalvo José Luis , Orellana-Manzano Andrea
Published: February 2024

Purpose

Essential oils from various plants have diverse therapeutic properties and are researched extensively. They have applications in medicine, aromatherapy, microbiology, agriculture, livestock, and the food industry, benefiting the population.

Methods

This systematic review followed the PRISMA verification protocol. The study focused on the anti-inflammatory effects, nutraceutical properties, antioxidant and antibacterial activity of essential oils in lemon, orange, cumin, cinnamon, coriander, rosemary, thyme, and parsley. We also looked at their presence in the diet, their effect, their mechanism of action on health, and the most important active compounds. The search was conducted in the PubMed database for the last 12 years of publications, including in vitro, in vivo, and online cell model tests.

Results

Essential oils have been shown to have multiple health benefits, primarily due to their antimicrobial and anti-inflammatory effects. The mechanism of action of cinnamon oil alters bacterial membranes, modifies lipid profiles, and inhibits cell division, giving a potential benefit in protection against colitis. On the other hand, a significant improvement was observed in the diastolic pressure of patients with metabolic syndrome when supplementing them with cumin essential oil. The antimicrobial properties of coriander essential oil, especially its application in seafood like tilapia, demonstrate efficacy in improving health and resistance to bacterial infections. Cumin essential oil treats inflammation. Parsley essential oil is an antioxidant. Orange peel oil is antibacterial, antifungal, antiparasitic, and pro-oxidative. Lemon essential oil affects mouse intestinal microbiota. Thyme essential oil protects the colon against damage and DNA methylation. Carnosic acid in rosemary oil can reduce prostate cancer cell viability by modifying the endoplasmic reticulum function.

Conclusion and discussion

Essential oils have many therapeutic and antiparasitic properties. They are beneficial to human health in many ways. However, to understand their potential benefits, more research is needed regarding essential oils such as coriander, parsley, rosemary, cumin, and thyme. These research gaps are relevant since they restrict understanding of the possible benefits of these crucial oils for health-related contexts.
Development and evaluation of a mechanical ventilator-sharing system
Authors: Achanta Satyanarayana , Gentile Michael A. , Euliano Neil R.
Published: February 2024

Background

During the COVID-19 pandemic surge in the hospitalization of critically ill patients and the global demand for mechanical ventilators, alternative strategies for device sharing were explored. We developed and assessed the performance of a system for shared ventilation that uses clinically available components to individualize tidal volumes under a variety of clinically relevant conditions. The feasibility of remote monitoring of ventilators was also assessed.

Methods

By using existing resources and off-the-shelf components, a ventilator-sharing system (VSS) that ventilates 2 patients simultaneously with a single device, and a ventilator monitoring system (VMS) that remotely monitors pulmonary mechanics were developed. The feasibility and effectiveness of VSS and VMS were evaluated in benchtop testing using 2 test lungs on a single ventilator, and then performance was assessed in translational swine models of normal and impaired lung function.

Results

In benchtop testing, VSS and VMS delivered the set individualized parameters with minimal % errors in test lungs under pressure- and volume-regulated ventilation modes, suggesting the highest precision and accuracy. In animal studies, the VSS and VMS successfully delivered the individualized mechanical ventilation parameters within clinically acceptable limits. Further, we found no statistically significant difference between the target and measured values.

Conclusion

The VSS adequately ventilated 2 test lungs or animals with variable lung conditions. The VMS accurately displayed mechanical ventilation settings, parameters, and alarms. Both of these systems could be rapidly assembled for scaling up to ventilate several critically ill patients in a pandemic or mass casualty disaster situations by leveraging off-the-shelf and custom 3D printed components.
Toxicity evaluation of processing Evodiae fructus based on intestinal microbiota
Authors: Liang Xuejuan , Liu Jing , Di Jiaxin , Xiao Nenqun , Peng Yanmei , Tian Qixue , Chen Linglong
Published: February 2024

Background

With the development of healthcare services, drug efficacy, and safety have become the focus of drug use, and processing alters drug toxicity and efficacy, exploring the effects of processing on Evodiae fructus (EF) can guide the clinical use of drugs.

Methods

Fifty male Kunming mice were randomly divided into the control group (CCN), raw small-flowered EF group (CRSEF), raw medium-flowered EF group (CRMEF), processing small-flowered EF group (CPSEF), and processing medium-flowered EF group (CPMEF). The CRSEF, CRMEF, CPSEF, and CPMEF groups were gavaged with aqueous extracts of raw small-flowered EF dry paste (RSEF), medium-flowered EF dry paste (RMEF), processing small-flowered EF dry paste (PSEF) and processing medium-flowered EF dry paste (PMEF), respectively, for 21 days at 5 times the pharmacopeial dosage. Upon concluding the experiment, histopathological sections of liver and kidney tissues were examined. Additionally, levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), serum creatinine (SCr), and blood urea nitrogen (BUN) were determined. DNA from the intestinal contents of the mice was extracted, and 16S rRNA full-length high-throughput sequencing was performed.

Results

After fed EF 21 days, mice exhibited a decreasing trend in body weight. Comparative analysis with the CCN group revealed an upward trend in SCr, BUN, AST, and ALT levels in both CRSEF and CRMEF groups. The CRMEF group displayed notably elevated BUN and AST levels, with an observed increasing trend in Scr and ALT. Kidney sections unveiled cellular edema and considerable inflammatory cell infiltrates, whereas significant liver damage was not evident. Compared with CRSEF, Bun levels were significantly lower while AST levels were significantly higher in the CPMEF group. Additionally, the intestinal microbiota diversity and the relative abundance of Psychrobacter decreased significantly, and the relative abundance of Staphylococcus, Jeotgalicoccus, and Salinicoccus increased significantly in the CPMEF group. AST, ALT, and SCr were positively correlated with Staphylococcus, Jeotgalicoccus, and Salinicoccus.

Conclusion

In conclusion, PMEF significantly increased harmful bacteria (Staphylococcus, Jeotgalicoccus, and Salinicoccu) and decreased beneficial bacteria. SEF with 5 times the clinical dose showed nephrotoxicity and SEF nephrotoxicity decreased after processing, but EF hepatotoxicity was not significant, which may be due to insufficient dose concentration and time.
Transboundary determinants of avian zoonotic infectious diseases: challenges for strengthening research capacity and connecting surveillance networks
Authors: Fair Jeanne M. , Al-Hmoud Nisreen , Alrwashdeh Mu’men , Bartlow Andrew W. , Balkhamishvili Sopio , Daraselia Ivane , Elshoff Annie , Fakhouri Lara , Javakhishvili Zura , Khoury Fares , Muzyka Denys , Ninua Levan , Tsao Jean , Urushadze Lela , Owen Jennifer
Published: February 2024

As the climate changes, global systems have become increasingly unstable and unpredictable. This is particularly true for many disease systems, including subtypes of highly pathogenic avian influenzas (HPAIs) that are circulating the world. Ecological patterns once thought stable are changing, bringing new populations and organisms into contact with one another. Wild birds continue to be hosts and reservoirs for numerous zoonotic pathogens, and strains of HPAI and other pathogens have been introduced into new regions via migrating birds and transboundary trade of wild birds. With these expanding environmental changes, it is even more crucial that regions or counties that previously did not have surveillance programs develop the appropriate skills to sample wild birds and add to the understanding of pathogens in migratory and breeding birds through research. For example, little is known about wild bird infectious diseases and migration along the Mediterranean and Black Sea Flyway (MBSF), which connects Europe, Asia, and Africa. Focusing on avian influenza and the microbiome in migratory wild birds along the MBSF, this project seeks to understand the determinants of transboundary disease propagation and coinfection in regions that are connected by this flyway. Through the creation of a threat reduction network for avian diseases (Avian Zoonotic Disease Network, AZDN) in three countries along the MBSF (Georgia, Ukraine, and Jordan), this project is strengthening capacities for disease diagnostics; microbiomes; ecoimmunology; field biosafety; proper wildlife capture and handling; experimental design; statistical analysis; and vector sampling and biology. Here, we cover what is required to build a wild bird infectious disease research and surveillance program, which includes learning skills in proper bird capture and handling; biosafety and biosecurity; permits; next generation sequencing; leading-edge bioinformatics and statistical analyses; and vector and environmental sampling. Creating connected networks for avian influenzas and other pathogen surveillance will increase coordination and strengthen biosurveillance globally in wild birds.
Initial experience with radiomics of carotid perivascular adipose tissue in identifying symptomatic plaque
Authors: Nie Ji-Yan , Chen Wen-Xi , Zhu Zhi , Zhang Ming-Yu , Zheng Yu-Jin , Wu Qing-De
Published: February 2024

Background

Carotid atherosclerotic ischemic stroke threatens human health and life. The aim of this study is to establish a radiomics model of perivascular adipose tissue (PVAT) around carotid plaque for evaluation of the association between Peri-carotid Adipose Tissue structural changes with stroke and transient ischemic attack.

Methods

A total of 203 patients underwent head and neck computed tomography angiography examination in our hospital. All patients were divided into a symptomatic group (71 cases) and an asymptomatic group (132 cases) according to whether they had acute/subacute stroke or transient ischemic attack. The radiomic signature (RS) of carotid plaque PVAT was extracted, and the minimum redundancy maximum correlation, recursive feature elimination, and linear discriminant analysis algorithms were used for feature screening and dimensionality reduction.

Results

It was found that the RS model achieved the best diagnostic performance in the Bagging Decision Tree algorithm, and the training set (AUC, 0.837; 95%CI: 0.775, 0.899), testing set (AUC, 0.834; 95%CI: 0.685, 0.982). Compared with the traditional feature model, the RS model significantly improved the diagnostic efficacy for identifying symptomatic plaques in the testing set (AUC: 0.834 vs. 0.593; Z = 2.114, p = 0.0345).

Conclusion

The RS model of PVAT of carotid plaque can be used as an objective indicator to evaluate the risk of plaque and provide a basis for risk stratification of carotid atherosclerotic disease.
Ethical considerations for integrating multimodal computer perception and neurotechnology
Authors: Hurley Meghan E. , Sonig Anika , Herrington John , Storch Eric A. , Lázaro-Muñoz Gabriel , Blumenthal-Barby Jennifer , Kostick-Quenet Kristin
Published: February 2024

Background

Artificial intelligence (AI)-based computer perception technologies (e.g., digital phenotyping and affective computing) promise to transform clinical approaches to personalized care in psychiatry and beyond by offering more objective measures of emotional states and behavior, enabling precision treatment, diagnosis, and symptom monitoring. At the same time, passive and continuous nature by which they often collect data from patients in non-clinical settings raises ethical issues related to privacy and self-determination. Little is known about how such concerns may be exacerbated by the integration of neural data, as parallel advances in computer perception, AI, and neurotechnology enable new insights into subjective states. Here, we present findings from a multi-site NCATS-funded study of ethical considerations for translating computer perception into clinical care and contextualize them within the neuroethics and neurorights literatures.

Methods

We conducted qualitative interviews with patients (n = 20), caregivers (n = 20), clinicians (n = 12), developers (n = 12), and clinician developers (n = 2) regarding their perspective toward using PC in clinical care. Transcripts were analyzed in MAXQDA using Thematic Content Analysis.

Results

Stakeholder groups voiced concerns related to (1) perceived invasiveness of passive and continuous data collection in private settings; (2) data protection and security and the potential for negative downstream/future impacts on patients of unintended disclosure; and (3) ethical issues related to patients’ limited versus hyper awareness of passive and continuous data collection and monitoring. Clinicians and developers highlighted that these concerns may be exacerbated by the integration of neural data with other computer perception data.

Discussion

Our findings suggest that the integration of neurotechnologies with existing computer perception technologies raises novel concerns around dignity-related and other harms (e.g., stigma, discrimination) that stem from data security threats and the growing potential for reidentification of sensitive data. Further, our findings suggest that patients’ awareness and preoccupation with feeling monitored via computer sensors ranges from hypo- to hyper-awareness, with either extreme accompanied by ethical concerns (consent vs. anxiety and preoccupation). These results highlight the need for systematic research into how best to implement these technologies into clinical care in ways that reduce disruption, maximize patient benefits, and mitigate long-term risks associated with the passive collection of sensitive emotional, behavioral and neural data.
Spectroscopic analysis of Pu-bearing compounds in double-walled cells
Authors: Villa-Aleman Eliel , Darvin Jason R. , Dick Don D. , Maxwell Michael C. , Swindle Ashlee R. , Foley Bryan J.
Published: February 2024

Spectroscopic analysis of radiological materials has been historically limited to radiological labs with older or less advanced scientific instrumentation. The development of double-walled cells (DWCs) at the Savannah River National Laboratory (SRNL) has enabled Pu-bearing compounds to be removed from radiological laboratories and studied in our radiologically clean spectroscopy laboratory with state-of-the-art instrumentation. In this manuscript, we discuss the contributions of DWCs that have allowed the application of Raman spectroscopy, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), diffuse reflectance spectroscopy (DRS) in the shortwave infrared, and gamma spectroscopy at SRNL. Significant advances have been made in the understanding of the thermal decomposition of Pu(III) and Pu(IV) oxalates, alpha-induced damage to the PuO2 crystal lattice, and the effect of calcination temperatures on the quality of PuO2. These techniques have enabled methods to conduct PuO2 age dating since last calcination and estimate the calcination temperature with Raman spectroscopy and DRS. Additional spectroscopic information measured with DRIFTS has enabled the observation of the evolution of carbon species with calcination temperature, while gamma spectroscopy provides information on age dating since last purification.
Genetic prediction of the causal relationship between schizophrenia and tumors: a Mendelian randomized study
Authors: Zhou Xintong , Liu Qi , Liu Shihan , Wang Liquan , Sun Zhongli , Sun Changgang , Cui Xiangning
Published: February 2024

Background

Patients with schizophrenia are at a higher risk of developing cancer. However, the causal relationship between schizophrenia and different tumor types remains unclear.

Methods

Using a two-sample, two-way Mendelian randomization method, we used publicly available genome-wide association analysis (GWAS) aggregate data to study the causal relationship between schizophrenia and different cancer risk factors. These tumors included lung adenocarcinoma, lung squamous cell carcinoma, small-cell lung cancer, gastric cancer, alcohol-related hepatocellular cancer, tumors involving the lungs, breast, thyroid gland, pancreas, prostate, ovaries and cervix, endometrium, colon and colorectum, and bladder. We used the inverse variance weighting (IVW) method to determine the causal relationship between schizophrenia and different tumor risk factors. In addition, we conducted a sensitivity test to evaluate the effectiveness of the causality.

Results

After adjusting for heterogeneity, evidence of a causal relationship between schizophrenia and lung cancer risk was observed (odds ratio [OR]=1.001, 95% confidence interval [CI], 1.000–1.001; P=0.0155). In the sensitivity analysis, the causal effect of schizophrenia on the risk of lung cancer was consistent in both direction and degree. However, no evidence of causality or reverse causality between schizophrenia and other tumors was found.

Conclusion

This study elucidated a causal relationship between the genetic predictors of schizophrenia and the risk of lung cancer, thereby providing a basis for the prevention, pathogenesis, and treatment of schizophrenia in patients with lung cancer.
The potential of aryl hydrocarbon receptor as receptors for metabolic changes in tumors
Authors: Wang Zhiying , Zhang Yuanqi , Liao Zhihong , Huang Mingzhang , Shui Xiaorong
Published: February 2024

Cancer cells can alter their metabolism to meet energy and molecular requirements due to unfavorable environments with oxygen and nutritional deficiencies. Therefore, metabolic reprogramming is common in a tumor microenvironment (TME). Aryl hydrocarbon receptor (AhR) is a ligand-activated nuclear transcription factor, which can be activated by many exogenous and endogenous ligands. Multiple AhR ligands can be produced by both TME and tumor cells. By attaching to various ligands, AhR regulates cancer metabolic reprogramming by dysregulating various metabolic pathways, including glycolysis, lipid metabolism, and nucleotide metabolism. These regulated pathways greatly contribute to cancer cell growth, metastasis, and evading cancer therapies; however, the underlying mechanisms remain unclear. Herein, we review the relationship between TME and metabolism and describe the important role of AhR in cancer regulation. We also focus on recent findings to discuss the idea that AhR acts as a receptor for metabolic changes in tumors, which may provide new perspectives on the direction of AhR research in tumor metabolic reprogramming and future therapeutic interventions.
Exploring the diagnostic value of CLR and CPR in differentiating Kawasaki disease from other infectious diseases based on clinical predictive modeling
Authors: Liao Jin-Wen , Guo Xin , Li Xu-Xia , Xian Jia-Ming , Chen Cheng , Xu Ming-Guo
Published: February 2024

Background

Kawasaki disease (KD) is an important cause of acquired heart disease in children and adolescents worldwide. KD and infectious diseases can be easily confused when the clinical presentation is inadequate or atypical, leading to misdiagnosis or underdiagnosis of KD. In turn, misdiagnosis or underdiagnosis of KD can lead to delayed use of intravenous immunoglobulin (IVIG), increasing the risk of drug resistance and coronary artery lesions (CAL).

Objectives

The purpose of this study was to develop a predictive model for identifying KD and infectious diseases in children in the hope of helping pediatricians develop timely and accurate treatment plans.

Methods

The data Patients diagnosed with KD from January 2018 to July 2022 in Shenzhen Longgang District Maternity & Child Healthcare Hospital, and children diagnosed with infectious diseases in the same period will be included in this study as controls. We collected demographic information, clinical presentation, and laboratory data on KD before receiving IVIG treatment. All statistical analyses were performed using R-4.2.1 (https://www.rproject.org/). Logistic regression and Least Absolute Shrinkage with Selection Operator (LASSO) regression analyses were used to build predictive models. Calibration curves and C-index were used to validate the accuracy of the prediction models.

Results

A total of 1,377 children were enrolled in this study, 187 patients with KD were included in the KD group and 1,190 children with infectious diseases were included in the infected group. We identified 15 variables as independent risk factors for KD by LASSO analysis. Then by logistic regression we identified 7 variables for the construction of nomogram including white blood cell (WBC), Monocyte (MO), erythrocyte sedimentation rate (ESR), alanine transaminase (ALT), albumin (ALB), C-reactive protein to procalcitonin ratio (CPR) and C-reactive protein to lymphocyte ratio (CLR). The calibration curve and C-index of 0.969 (95% confidence interval: 0.960–0.978) validated the model accuracy.

Conclusion

Our predictive model can be used to discriminate KD from infectious diseases. Using this predictive model, it may be possible to provide an early determination of the use of IVIG and the application of antibiotics as soon as possible.