bluuebunny/crossref_metadata_2025 huggingface dataset:
Targeting pediatric cancers via T-cell recognition of the monomorphic MHC class I-related protein MR1
Authors: Cornel Annelisa M. , van der Sman Loutje , van Dinter Jip T , Arrabito Marta , Dunnebach Ester , van Hoesel Marliek , Kluiver Thomas A , Lopes Ana P , Dautzenberg Noël M M , Dekker Linde , van Rijn Jorik M , van den Beemt Denise A M H , Buhl Juliane L , du Chatinier Aimee , Barneh Farnaz , Lu Yuyan , Lo Nigro Luca , Krippner-Heidenreich Anja , Sebestyén Zsolt , Kuball Jurgen , Hulleman Esther , Drost Jarno , van Heesch Sebastiaan , Heidenreich Olaf T , Peng Weng Chuan , Nierkens Stefan
Published: March 2024

Human leukocyte antigen (HLA) restriction of conventional T-cell targeting introduces complexity in generating T-cell therapy strategies for patients with cancer with diverse HLA-backgrounds. A subpopulation of atypical, major histocompatibility complex-I related protein 1 (MR1)-restricted T-cells, distinctive from mucosal-associated invariant T-cells (MAITs), was recently identified recognizing currently unidentified MR1-presented cancer-specific metabolites. It is hypothesized that the MC.7.G5 MR1T-clone has potential as a pan-cancer, pan-population T-cell immunotherapy approach. These cells are irresponsive to healthy tissue while conferring T-cell receptor(TCR) dependent, HLA-independent cytotoxicity to a wide range of adult cancers. Studies so far are limited to adult malignancies. Here, we investigated the potential of MR1-targeting cellular therapy strategies in pediatric cancer. Bulk RNA sequencing data of primary pediatric tumors were analyzed to assessMR1expression.In vitropediatric tumor models were subsequently screened to evaluate their susceptibility to engineered MC.7.G5 TCR-expressing T-cells. Targeting capacity was correlated with qPCR-basedMR1mRNA and protein overexpression. RNA expression ofMR1in primary pediatric tumors varied widely within and between tumor entities. Notably, embryonal tumors exhibited significantly lowerMR1expression than other pediatric tumors. In line with this, most screened embryonal tumors displayed resistance to MR1T-targetingin vitro. MR1T susceptibility was observed particularly in pediatric leukemia and diffuse midline glioma models. This study demonstrates potential of MC.7.G5 MR1T-cell immunotherapy in pediatric leukemias and diffuse midline glioma, while activity against embryonal tumors was limited. The dismal prognosis associated with relapsed/refractory leukemias and high-grade brain tumors highlights the promise to improve survival rates of children with these cancers.
Baricitinib for refractory Takayasu arteritis: a prospective cohort study in a tertiary referral centre
Authors: Zhou Ziyue , Fang Chenglong , Wang Li , Li Jing , Yang Yunjiao , Zhang Li , Jin Shangyi , Zeng Xiaofeng , Tian Xinping
Published: March 2024

Objective

To investigate the treatment efficacy and safety of baricitinib in patients with refractory Takayasu arteritis (TAK).

Methods

We performed a prospective cohort study in which baricitinib 4 mg daily was prescribed to patients with refractory TAK, combined with oral glucocorticoids (GCs).

Results

10 patients with refractory TAK were enrolled with a median age of 28 (IQR=22–37) years, median disease duration of 50 (IQR=24–65) months. The median dose of GCs was 10 (IQR=8.1–22.5) mg prednisone or equivalence dosage at baseline. At 6 months of baricitinib treatment, 6/10 (60%) patients had an overall treatment response. During an average follow-up of 15.3 (range 4–31) months, 4/10 (40%) patients maintained overall treatment response. 8/10 (80%) patients tapered or maintained the same dose of GCs with no change of the combined classical synthetic disease-modifying antirheumatic drugs. Two patients discontinued GCs at 18 and 24 months and were in continuous remission till the end of the study. One patient withdrew baricitinib due to liver dysfunction.

Conclusion

Baricitinib 4 mg daily is effective for refractory TAK and is well tolerated.
Treatment approach for coexisting chest wall fractures and unstable thoracolumbar spine fractures in polytrauma patients requiring prone spine surgery
Authors: Alqazzaz Aymen , Naseer Zan , Beyer Carl A , Cannon Jeremy W , Khalsa Amrit
Published: March 2024

Concomitant chest wall fractures (sternal and/or rib fractures) with unstable thoracolumbar fractures that require surgical fixation are rare but highly morbid injuries that mandate a multidisciplinary approach to treatment. There is limited evidence in the literature regarding optimal timing and order of surgical fixation of these patients with multiple injuries. Here, we present our experience with two patients at a single institution that demonstrates the challenges that present with this patient population. We advocate for earlier fixation of the chest wall fractures in the appropriately indicated patients, prior to prone positioning for spinal fixation.
Optimal time interval of information update using by exit-choice system to improve pedestrian evacuation efficiency
Authors: Zhu Kong-Jin , Zhu Jun , Cai Shao-Bo , Ling Xiang , Wu Chao-Yun , Hao Qing-Yi , Guo Ning
Published: March 2024

In the case of emergency evacuation of large places, the rapid evacuation of pedestrians has always been a matter of great concern. However, research on pre-movement behavior and decision-making fatigue behavior of pedestrians in emergency evacuation situations is limited. In order to study how to improve evacuation efficiency under the introduction of exit-choice system, this paper uses the cellular automata model to simulate different exit arrangements and exit numbers at different time intervals of information update by the system. It is found that there is an optimal time interval of information update when three exits of a room have different widths, and the evacuation time significantly reduces compared to real-time update. The potential mechanism of the optimal time interval of information update is that the evacuees can be reasonably allocated to each exit, so that the passage capacity of each exit can be maximized, and the evacuation time is significantly reduced. Sensitivity analysis shows that the change of exit location has an important influence on the evacuation time. The different pre-movement times of pedestrians have a certain degree of influence on the evacuation time of real-time update. The different distance parameters and flow parameters had a significant impact on the evacuation time in the real-time update case.
Characterization & Implementation of ISFET Array Chip Using 0.18μm CMOS Technology for Integrated Sensor Application
Authors: Agarwal Neeraj , Agarwal Neeru
Published: March 2024

We implemented an ion-sensitive field effect transistor (ISFET) array chip comprising n-ISFET and p-ISFET for sensor application using 0.18[Formula: see text][Formula: see text]m CMOS technology. N-channel metal-oxide semiconductor (NMOS) and P-channel metal-oxide semiconductor (PMOS) ISFETs are fabricated in regular dimensions ([Formula: see text]8[Formula: see text][Formula: see text]m) compatible with the standard CMOS process. We implemented n-ISFET cells and p-ISFET cells of different dimensions for characterization and to observe the possible effect of scalability. Each cell also has two identical NMOS and PMOS ISFETs of standard dimension, unlike very large dimensions ([Formula: see text]200[Formula: see text][Formula: see text]m). We are using metals 1–6 and via together on the gate area to make it an extended or floating gate for the electrochemical sensing of ISFET. These metals are electrically floating with an intermediate dielectric. These different-size floating gate ISFETs provide different sensing areas, and the passivation Si3N4 layer is used for pH sensing without any extra post-processing measures. We observe the ISFET sensitivity and performance with the 0.18[Formula: see text][Formula: see text]m technology submicron effect. The measured results propose ISFET as a promising sensor device for portable applications. The ISFET chip dimension is 1179[Formula: see text][Formula: see text]m × 1185[Formula: see text][Formula: see text]m.
Evaluation of the Signal and Noise of Readout Electronics for Radiation Detector by Using MATLAB Simulation Program
Authors: Assaf Jamal , Ahmad Zuheir , Skeiker Kamal
Published: March 2024

Within the frame of this work, a user-friendly MATLAB program for the simulation of signals and electronic noise at the nuclear radiation readout system was developed. Signal and noise in terms of equivalent noise charge (ENC) have been evaluated. Five noise sources were considered in order to have high simulation accuracy. The role and influence of different parameters of the readout circuits on the output signal and noise were predicted and illustrated. Moreover, the effect of all elementary parameters of each noise source on the ENC was taken into consideration. Since the energy resolution is affected by the electronic noise expressed by ENC, the obtained simulation results help to select the most feasible concept and parameters for a real system having a minimal noise effect. Using the program, several examples of the effect of those parameters on different ENC contributions related to the noise sources have been analyzed and discussed in detail. A comparison between the simulated results and experimental data was conducted.
Robotic Process Automation Efficiency for Mobile App Testing: An Empirical Investigation
Authors: Wang Yuqiong , Zhao Yuxiao , Wang Xiang , Tang Weidong , Zhang Jinhui , Wang Shaolei , Wang Peng , Hu Jian
Published: March 2024

In today’s rapidly evolving software environment, the graphical user interface (GUI) plays a crucial role in providing intuitive, user-friendly interaction. However, traditional intrusive GUI testing methods often face challenges such as interrupting user workflows, requiring significant manual effort and insufficient test scenario coverage. Non-intrusive testing methods, such as Robotic Process Automation (RPA), offer a solution to validate GUI functionality without modifying the application’s code or affecting the user experience. RPA systems automate repetitive tasks by simulating user interactions, becoming valuable tools in GUI testing. However, challenges like limited computational resources, time constraints, or restricted exploration capabilities may limit the efficiency of individual RPA agents, thus restricting coverage and effectiveness.

To address this issue, this study explores the performance of a single RPA agent versus an RPA cluster under different testing conditions, using three popular testing methods: Monkey, Stoat and Q-testing. Experimental results indicate that an RPA cluster outperforms a single RPA in GUI coverage and error detection, making a significant contribution to the field of non-intrusive GUI exploration testing. The findings of this study provide directions for future research to ensure the delivery of high-quality mobile applications.
TRAFMEL: Multimodal Entity Linking Based on Transformer Reranking and Multimodal Co-Attention Fusion
Authors: Zhang Xiaoming , Meng Kaikai , Wang Huiyong
Published: March 2024

Multimodal entity linking aims to link mentions to target entities in the multimodal knowledge graph. The current multimodal entity linking mainly focuses on the global fusion of text and image, seldom fully exploring the correlation between modalities. In order to improve the fusion effect of multimodal feature, we propose a multimodal entity linking model based on a Multimodal Co-Attention Fusion strategy. This strategy is designed to enable text and image to guide each other for extracting features, thus making full exploration of the correlation between modalities to improve the fine-grained feature fusion effect. Furthermore, we also design a candidate entity generation strategy based on Transformer, which combines multiple candidate entity sets and adjusts the candidate entity ranking to obtain high-quality candidate entity sets. We perform experiments on domain datasets and public datasets, and the experimental results demonstrate that our model has a good performance in candidate entity generation and multimodal feature fusion, outperforming the state-of-the-art baseline models.
Asymptotic analysis of thin structures with point-dependent energy growth
Authors: Eleuteri Michela , Prinari Francesca , Zappale Elvira
Published: March 2024

In this paper, 3D–2D-dimensional reduction for hyperelastic thin films modeled through energies with point-dependent growth, assuming that the sample is clamped on the lateral boundary, is performed in the framework of [Formula: see text]-convergence. Integral representation results, with a more regular Lagrangian related to the original energy density, are provided for the lower dimensional limiting energy, in different contexts.
Glow & Lovely: Purpose-driven Brand
Authors: Singh Jagandeep , Sambyal Rachita
Published: March 2024

The rebranding of Fair & Lovely (F&L), one of Hindustan Unilever Limited’s (HUL) flagship brands, to Glow & Lovely (G&L) in 2020 had hogged the limelight. HUL termed the rebranding as an important evolutionary step that moved away from the “regressive idea of beauty” and banished an undesirable social stereotype. Stakeholders had divergent opinions with the rebranding effort being termed from “path-breaking” to “too little”. Likewise, there was a divided house on the future sales of the repositioned brand. However, G&L, akin to its predecessor, maintained traction in the marketplace. The case provides an opportunity to understand the concepts of brand positioning and brand repositioning. It highlights how a corporate citizen can engage in responsible advertising and break an undesirable social stereotype. Attributes associated with fairness were identified to capture the extent of brand repositioning. Attributes associated with fairness were identified to capture the extent of brand repositioning. The primary data collected on such attributes was analysed with the help of Multi-Dimensional Scaling using alternating least-squares (ALSCAL) method. Discriminant analysis was used to understand which attributes differentiated various brands of fairness creams.
EFFICIENT EVALUATION OF DOUBLE-BARRIER OPTIONS
Authors: BOYARCHENKO SVETLANA , LEVENDORSKIĬ SERGEI
Published: March 2024

In the paper, we develop a very fast and accurate method for pricing double barrier options with continuous monitoring in wide classes of Lévy models; the calculations are in the dual space, and the Wiener–Hopf factorization is used. For wide regions in the parameter space, the precision of the order of [Formula: see text] is achievable in seconds, and of the order of [Formula: see text]–[Formula: see text] — in fractions of a second. The Wiener–Hopf factors and repeated integrals in the pricing formulas are calculated using sinh-deformations of the lines of integration, the corresponding changes of variables and the simplified trapezoid rule. If the Bromwich integral is calculated using the Gaver–Wynn Rho acceleration instead of the sinh-acceleration, the CPU time is typically smaller but the precision is of the order of [Formula: see text]–[Formula: see text], at best. Explicit pricing algorithms and numerical examples are for no-touch options, digitals (equivalently, for the joint distribution function of a Lévy process and its supremum and infimum processes), and call options. Several graphs are produced to explain fundamental difficulties for accurate pricing of barrier options using time discretization and interpolation-based calculations in the state space.
Albert’s twisted field construction using division algebras with a multiplicative norm
Authors: Pumplün S.
Published: March 2024

We generalize Albert’s twisted field construction, applying it to unital division algebras with a multiplicative norm. We give conditions for the resulting algebras to be division algebras. Four- and eight-dimensional real unital and non-unital division algebras with large derivation algebras are constructed out of Hamilton’s quaternion and Cayley’s octonion algebra.
AMPLITUDE EQUATIONS AND ORDER PARAMETERS OF HUMAN SARS-COV-2 INFECTIONS AND IMMUNE REACTIONS: A MODEL-BASED APPROACH
Authors: FRANK T. D.
Published: March 2024

Several recent modeling studies have attempted to understand the human immune reaction to SARS-CoV-2 infections. Such a model-based understanding provides a sound basis for fighting COVID-19 on the level of individual patients. However, in this context, a worked-out nonlinear physics analysis providing insights into underlying amplitude equations and potential COVID-19 order parameters has not been conducted so far. In order to conduct such an analysis, a three-variable virus dynamics model is considered that can account for the human immune reaction to SARS-CoV-2 infections. The model amplitudes equations are derived and the relevant order parameter is determined. In line with theoretical reasoning, it is demonstrated that the order parameter and its amplitude determine the initial stage of SARS-CoV-2 infections, in general, and the initial dynamics of immune reactions, in particular. Explicitly, this finding is demonstrated for data from four COVID-19 patients. For those patients it is also demonstrated that the remnant of the order parameter determines the final disease decline phase. In this context, a time-resolved eigenvalue analysis is conducted that reveals that the transition from the initial stage to the decline stage which is associated with a switch of the leading eigenvalue from a positive to a negative value. It is argued that the immune reaction essentially contributes to this switch. From a medical-physics point of view, this observation suggests that the immune reaction of COVID-19 patients can stabilize the virus-free fixed point of affected sites.
MoRF_ESM: Prediction of MoRFs in disordered proteins based on a deep transformer protein language model
Authors: Fang Chun , He Jiasheng , Yamana Hayato
Published: March 2024

Molecular recognition features (MoRFs) are particular functional segments of disordered proteins, which play crucial roles in regulating the phase transition of membrane-less organelles and frequently serve as central sites in cellular interaction networks. As the association between disordered proteins and severe diseases continues to be discovered, identifying MoRFs has gained growing significance. Due to the limited number of experimentally validated MoRFs, the performance of existing MoRF’s prediction algorithms is not good enough and still needs to be improved. In this research, we present a model named MoRF_ESM, which utilizes deep-learning protein representations to predict MoRFs in disordered proteins. This approach employs a pretrained ESM-2 protein language model to generate embedding representations of residues in the form of attention map matrices. These representations are combined with a self-learned TextCNN model for feature extraction and prediction. In addition, an averaging step was incorporated at the end of the MoRF_ESM model to refine the output and generate final prediction results. In comparison to other impressive methods on benchmark datasets, the MoRF_ESM approach demonstrates state-of-the-art performance, achieving [Formula: see text] higher AUC than other methods when tested on TEST1 and achieving [Formula: see text] higher AUC than other methods when tested on TEST2. These results imply that the combination of ESM-2 and TextCNN can effectively extract deep evolutionary features related to protein structure and function, along with capturing shallow pattern features located in protein sequences, and is well qualified for the prediction task of MoRFs. Given that ESM-2 is a highly versatile protein language model, the methodology proposed in this study can be readily applied to other tasks involving the classification of protein sequences.
Dynamic Analysis of an FGM Beam Undergoing Large Overall Motion in Temperature Field
Authors: Du Chaofan , Cao Tingkui , Yu Chuanbin , Zhang Zhichao , Zhang Dingguo
Published: March 2024

The dynamic analysis of a functionally gradient material (FGM) beam undergoing large overall motion based on meshless methods is studied in the variable temperature field environment. Considering the high-order terms of nonlinear coupling deformation which were often ignored in previous studies, the high-order rigid–flexible coupled (HOC) dynamic model of a rotating FGM beam with a lumped mass in a temperature field is established by employing Lagrange’s equations of the second kind. Compared with the first-order approximate coupled (FOAC) dynamic model, the HOC dynamic model is more accurate and has a wider scope of application. The validity of the point interpolation (PIM) method and radial point interpolation method (RPIM) in this paper is verified by comparison with simulation results of the assumed mode method (AMM) and the finite element method (FEM). On this basis, the factors affecting the dynamic characteristics of the FGM beam such as the form of temperature field, the functionally gradient index, and the location of added lumped mass are discussed. In this paper, the meshless method with higher computational efficiency and the HOC dynamic model with more accurate results are adopted. This study will provide guidance and reference for dealing with problems in engineering, machinery, aerospace, and other fields in complex environment.
A comparative study on the maximum mass and radius of anisotropic compact stars from Heintzmann geometry and the TOV approach
Authors: Das B. , Goswami K. B. , Chattopadhyay P. K.
Published: March 2024

In this paper, a class of anisotropic compact stars is analyzed in Heintzmann geometry. The Einstein field equations (EFEs) have been solved to obtain the stellar model in presence of pressure anisotropy. We have considered the [Formula: see text] metric component as proposed by Heintzmann, and by solving the EFEs, the [Formula: see text] metric component is evaluated in the presence of pressure anisotropy. It is noted that for an isotropic star ([Formula: see text]), the maximum mass lies within the range 1.87–3.04[Formula: see text] for radii ranging between 8–13 km. For anisotropic compact stars, the maximum mass increases with [Formula: see text] and lies within the range 1.99–3.23 [Formula: see text] for anisotropy parameter [Formula: see text]. The physical viability of the model is examined by applying our model to study the properties of a few known compact objects. All the stability conditions are fulfilled in the proposed model. It is also interesting to note that the maximum mass calculated from our model from geometrical consideration and solving the TOV equation is approximately equal, and the radii predicted from the present model comply with the estimated radius from observations of recently observed pulsars and lighter compact objects of GW events such as GW 190814 and GW 170817.
Agility in Engineering Change Management: Navigating Complexities of Emergent Changes in PLM
Authors: Riascos Roberto , Ostrosi Egon , Stjepandić Josip , Sagot Jean-Claude
Published: March 2024

This paper addresses the needs of the Product Emergence Process (PEP) to adopt agile methodologies, specifically those managed in a Product Lifecycle Management (PLM) system. Agile methodologies are expected to provide solutions to reduced lead time, changing product requirements, rising product complexity and turbulent market conditions. Engineering Change Management (ECM) is the process that drives and oversees the process that ensures products meet expected targets and is particularly impacted with the adoption of an agile approach. Furthermore, commercial PLM systems primarily cater to a waterfall approach. The objective of this paper is to propose a conceptual solution that enables the execution of the ECM process in a PLM system while empowering the companies to manage the challenges of product development in a more agile manner. For a feasible integration of agile and PLM tools we propose DIONE (DIscovery, OpportuNity, Exploit). DIONE maps agile methods (specifically those of Scrum) to PLM artifacts of the ECM, and allows for ongoing changes, with continuous assessments during execution cycles. A practical implementation of DIONE in PLM is proposed. The paper also explores the challenges identified for implementing such a framework and the benefits of hybrid development approaches. The key findings emphasize the need for well-thought implementation of agile methodologies in ECM, the need for automation of impact analysis and leveraging engineering knowledge to support the ECM. The paper also explores organizational challenges identified for implementing agile in the PEP. In conclusion, this research highlights the importance of adopting an agile approach to manage effectively the complexity of emerging change requests in ECM. It encourages further research in automation, knowledge gathering and management, and the need to be innovative in the ways the ECM can be implemented.
A Game-Theoretical Self-Adaptation Framework for Securing Software-Intensive Systems
Authors: Li Nianyu , Zhang Mingyue , Li Jialong , Adepu Sridhar , Kang Eunsuk , Jin Zhi
Published: March 2024

Security attacks present unique challenges to the design of self-adaptation mechanism for software-intensive systems due to the adversarial nature of the environment. Game-theoretical approaches have been explored in security to model malicious behaviors and design reliable defense for the system in a mathematically grounded manner. However, modeling the system as a single player, as done in prior works, is insufficient for the system under partial compromise and for the design of fine-grained defensive policies where the rest of the system with autonomy can cooperate to mitigate the impact of attacks. To address such issues, we propose a new self-adaptation framework incorporating Bayesian game theory and model the defender (i.e., the system) at the granularity of components. Under security attacks, the architecture model of the system is automatically translated, by the proposed translation process with designed algorithms, into a multi-player Bayesian game. This representation allows each component to be modeled as an independent player, while security attacks are encoded as variant types for the components. By solving for pure equilibrium (i.e., adaptation response), the system’s optimal defensive strategy is dynamically computed, enhancing system resilience against security attacks by maximizing system utility. We validate the effectiveness of our framework through two sets of experiments using generic benchmark tasks tailored for the security domain. Additionally, we exemplify the practical application of our approach through a real-world implementation in the Secure Water Treatment System to demonstrate the applicability and potency in mitigating security risks.
Numerical Simulation and Sensitivity Analysis Using RSM on Natural Convective Heat Exchanger Containing Hybrid Nanofluids
Authors: Islam Saiful , Siddiki Md. Noor-A-Alam , Islam Md. Shahinur
Published: March 2024

This work presents a numerical analysis for exploring heat transfer phenomena in an enclosed cavity using magnetohydrodynamics natural convection. Because of the numerous real-world applications of nanofluids and hybrid nanofluids in industrial and thermal engineering developments, hybrid nanofluids are used as fluid mediums in the fluid field. A hexagonal-shaped heat exchanger is taken with two circular surfaces along the middle part. The upright circular surface acts as a homogeneous heat source, while the lower circular surface functions as a heat sink. The remaining portions of the adjacent walls are thermally insulated. The copper (Cu) and titanium dioxide (TiO2) nanoparticles are suspended into water to make a hybrid nanofluid. For solving the corresponding governing equations, the weighted-residual finite element method is applied. To explain the major outcomes, isotherms, streamlines, and many others 2D and 3D contour plots are involved graphically with a physical explanation for different magnitudes of significant parameters: Rayleigh number 103≤Ra≤106, Hartmann number 0≤Ha≤100, and nanoparticle volume fraction 0≤ϕ≤0.06. The novelty of this work is to apply response surface methodology on the natural convective hybrid nanofluid model, to visualize 2D and 3D effects, and to study the sensitivity of independent parameters on response function. Due to the outstanding thermal properties of the hybrid nanofluid, the addition of Cu and TiO2 nanoparticles into H2O develops the heat transfer rate to 35.85% rather than base fluid. Moreover, a larger magnitude of Ra and the accumulation of mixture nanoparticles result in the thermal actuation of a hybrid nanofluid. With greater magnetic impact, an opposite response is exhibited.
Evaluation of the Effect of Lactobacillus acidophilus ATCC 4356 Bacteriocin against Staphylococcus aureus
Authors: Fagheei Aghmiyuni Zeinab , Saderi Horieh , Owlia Parviz , Saidi Navid
Published: March 2024

Background. Lactobacillus acidophilus is lactic acid bacteria that produce bacteriocins. Bacteriocins are antimicrobial peptides or proteins that exhibit activity against closely related bacteria. The aim of this study was to determine the effect of L. acidophilus ATCC 4356 bacteriocin against Staphylococcus aureus. Material and Methods. We used four different phenotypic methods for antimicrobial activities against two standard strains: methicillin-resistant S. aureus (MRSA) ATCC 33591 and methicillin-susceptible S. aureus (MSSA) ATCC 25923. The methods were (1) agar well diffusion, (2) overlay soft agar, (3) paper disk, and (4) modification of punch hole. The ammonium sulfate method was used to concentrate crude bacteriocin, and ultrafiltration and dialysis tubes were used to remove ammonium sulfate from the bacteriocins. Each method was repeated in triplicate. Result. L. acidophilus ATCC 4356 showed antimicrobial activity against both MRSA and MSSA standard strains only by the overlay soft agar method and not by the agar well diffusion, punch hole modification, and paper disk methods. No antimicrobial effects were observed in crude bacteriocins concentrated. Conclusion. The growth inhibition of S. aureus in overlay soft agar method may be due to the production of bacteriocin-like substances. The overlay soft agar method is a qualitative test, so there is a need for further study to optimize the conditions for the production of bacteriocin-like substances in the culture supernatant and precise comparison between the inhibitory activity and pheromone secretion of different strains.
A Network Analysis of Gender Differences in PTSD Symptoms among Chinese Adults during COVID‐19 Pandemic
Authors: Yang Fan , Liu Xiaohan , Zhang Bo , Fu Mingqi , Huang Ning , Zhen Cheng , Guo Jing
Published: March 2024

Background. The COVID‐19 pandemic is by far the most significant public health crisis in the 21st century, arousing many psychological concerns like post‐traumatic stress disorder (PTSD). Aims. This study is aimed at revealing gender differences and similarities in PTSD symptoms among Chinese adults during COVID‐19 pandemic. Methods. Data used in this study were from an online cross‐sectional study conducted in February 2020 via a web‐based platform. We analyzed data from 558 Chinese adults (334 men and 224 women) with PCL‐5 scores over the PTSD criteria. A network analysis was performed to explore the structure of PTSD symptoms for subgroups of men and women. Results. The results showed intrusive thoughts and emotional cue reactivity, together with negative beliefs and negative trauma‐related emotions, presented strong positive connections in both men and women. A negative connection between intrusive thoughts and self‐destructive/reckless behavior existed among women but not men. Regarding centrality symptoms, women and men had flashbacks and self‐destructive/reckless behavior in common, but with differential orders. The most central symptom of PTSD was self‐destructive/reckless behavior for women and difficulty concentrating for men. Conclusion. We urge that self‐destructive/reckless behaviors and flashbacks, as potential core symptoms of COVID‐19‐related PTSD, be given more attention in future pandemic‐related psychiatric intervention programs.
The Association between Serum Level of Vitamin D and Inflammatory Biomarkers in Hospitalized Adult Patients: A Cross-Sectional Study Based on Real-World Data
Authors: Zhang Xiaomin , Chen Zhiqi , Xiang Yi , Zhou Yiquan , Tang Molian , Cai Jun , Xu Xinyi , Cui Hongyuan , Feng Yi , Xu Renying
Published: March 2024

Objective. The association between vitamin D status and inflammation remains unclear in hospitalized patients. Materials and Methods. We performed the current study based on real-world data from two teaching hospitals. Serum level of vitamin D (assessed by 25-hydroxyvitamin D) was evaluated within 2 days after admission. All the patients were further classified into three groups: deficiency (<12 ng/mL), insufficiency (12–20 ng/mL), and adequate (≥20 ng/mL). White blood cell (WBC) count, serum level of C-reactive protein (CRP), and procalcitonin were also measured and used to evaluate inflammation. Other potential covariates were abstracted from medical records. Charlson comorbidity index (CCI) was calculated to assess the severity of disease. Results. A total number of 35,528 hospitalized adult patients (21,171 men and 14,357 women) were included. The average age and BMI were 57.5 ± 16.2 years and 23.4 ± 3.7 kg/m2, respectively, while medium vitamin D level was 16.1 ng/mL (interquartile range: 11.4 ng/mL, 21.6 ng/mL) and median CCI was one point (interquartile range: 0 point, two points). The prevalence of deficiency and insufficiency was 28.0% and 40.5%. Multivariate linear regression model showed that serum level of vitamin D was significantly associated with WBC and CRP but not associated with procalcitonin. Each standard deviation (≈7.4 ng/mL) increase in vitamin D was associated with a decrease in WBC by 0.13 × 109/mL (95% CI: 0.2 × 109/mL, 0.06 × 109/mL) and 0.62 mg/L (95% CI: 0.88 mg/L, 0.37 mg/L) for CRP. Subgroup analysis and sensitivity analysis (excluding those whose eGFR <60 ml/min/1.73 m2, those whose daily calorie intake <1,000 kcal, and those who were recruited from Xin Hua hospital) generated similar results. Conclusions. The deficiency and insufficiency of vitamin D in the hospitalized adult patients was very common. However, the results should be interpreted with caution for limited representation of the whole inpatients. Low level of vitamin D was associated with inflammatory biomarkers, which provide the evidences to early intervention for lower the risk of infection.
A Dual-Hierarchy Synchronization Method for Signal Preambles with High Detection Rates for Satellite-Based ADS-B Receivers with Different Sensitivities
Authors: Jian Xinhui , Zhang Xuejun , Ma Jianxiang , Zhang Weidong
Published: March 2024

Existing methods are unable to achieve high detection rates and low false alarm rates of satellite-based Automatic Dependent Surveillance-Broadcast (ADS-B) signal preambles at extremely low signal-to-noise ratios (SNRs) using limited on-star resources. In this paper, a dual-hierarchy synchronization method is proposed, including a first-level coarse synchronization and a second-level fine synchronization. The coarse synchronization process involves three steps: (1) detection of unknown signals, (2) soft decision, and (3) adaptive interval output. The first step introduces the threshold (TMSED) of the minimum signal energy to be detected to guarantee a high detection rate. In the soft decision step, a value (SV) designed to improve the robustness of the system curbs false detection caused by noise interference. In the last step, the coarse synchronization interval radius (r) is mapped out according to the SNR to reduce resource consumption. The fine synchronization process is based on the coarse synchronization output, and the correlation peak is calculated to complete the synchronization of the signal preambles. The results show that the proposed method achieves a high detection rate of 96% at an extremely low SNR using a low sampling frequency of 10 MHz. Furthermore, the adjustment of TMSED allows this method to be applied to ADS-B receivers with different sensitivities. The comprehensive performance of this method to achieve high detection rates and acceptable false alarm rates at extremely low SNRs with limited on-star resources is verified by final simulations to be superior to other methods.
Characterization of Langra Mango Peel Powder and Assessment of Its Prebiotic and Antioxidant Potential
Authors: Jakha K. Hinokali , Goyal Chhaya , Dhyani Priya , Rai Dinesh Chandra , Saharan Baljeet Singh , Dhull Sanju Bala , Duhan Joginder Singh
Published: March 2024

The possibility of developing waste by-products of food processing into functional food additives along with probiotics is an interesting avenue to research. This study investigated the nutritional and functional attributes of dried mango peel powder (MPP) of Langra cultivar and its putative potential to act as a prebiotic in the presence of two probiotic strains Lacticaseibacillus rhamnosus NCDC347 and Limosilactobacillus fermentum NCDC143 @ 2.5 & 5% after 24 to 48 h fermentation. Proximate analysis revealed that the MPP contains 6.45 % moisture, 6.34 % protein, 3.88 % fat, 2.50 % ash, 32.86 % crude dietary fiber, and 47.97 % of total carbohydrate content. MP displayed substantial antioxidant potential with 54.6% DPPH inhibitory activity, 15.67  mg GAE/g TPC, 8.88 mg QuE/g TFC, OHC of 1.47  g oil/g, and a WHC of 4.7  g water/g. MPP could selectively stimulate the growth of two probiotic strains over enteric bacteria. It was revealed that a combination of MPP @5% with L. fermentum NCDC143 after 24 h fermentation had the best in vitro prebiotic activity score of 3.35  and 3.53  against Escherichia coli ATCC 25922 and Enterococcus faecalis NCDC114, respectively. The prebiotic activity score of MPP was better than commercial prebiotic malto-dextrin for all combinations of probiotic and enteric strains tested. The percentage DPPH inhibition activity of MPP increased during fermentation with L. fermentum NCDC143, highlighting its role as a source of antioxidants. These findings contribute to the formulation of synbiotic products that are able to maintain selected healthy microbiota in the human gut.
Optimization of Wall Materials for Astaxanthin Powder Production from Shrimp Shell Extract Using Simplex Lattice Mixture Design
Authors: Sharayei P. , Azarpazhooh E. , Einafshar S. , Zomorodi Sh. , Zare F. , Ramaswamy Hosahalli S.
Published: March 2024

Shrimp shell waste is an attractive source of value-added bioactive-rich by-products. Shrimp shell extract containing astaxanthin was recovered by solvent extraction method (petroleum ether/acetone/water with a ratio of 15 : 75 : 10) and ultrasound process (amplitude 20% for 15 min at 35°C). The extract was then encapsulated by freeze-drying using wall materials such as maltodextrin (with the dextrose equivalent (DE) of 7 (MD7) and 20 (MD20)) and modified starch (Hi-Cap 100) incorporated at different ratios. Simplex lattice with augmented axial points in the mixture design was applied for the optimization of wall material. The optimal wall materials were 29.4% (MD7), 34.0% (Hi-Cap 100), and 36.6% (MD20), with encapsulation yield (Y) of 94.6%, encapsulation efficiency (EE) of 91.8%, astaxanthin content (Ast) of 46.1 μg/g DW, and DPPH scavenging capacity of 64.0%, respectively. The optimized microcapsules had spongy morphology and brittle and flaky mass. The degradation kinetics of bioactive astaxanthin in UV light was evaluated and found to follow first-order reaction kinetics. The microcapsules obtained under optimal wall composition exhibited the highest UV light stability with half-life values of 76.8 h, demonstrating a high stability.
Lifetime Exposure to Cigarette Smoke, B-Cell Tumor Immune Infiltration, and Immunoglobulin Abundance in Ovarian Tumors
Authors: Hathaway Cassandra A. , Townsend Mary K. , Wang Tianyi , Vinci Christine , Jake-Schoffman Danielle E. , Hecht Jonathan L. , Saeed-Vafa Daryoush , Moran Segura Carlos , Nguyen Jonathan V. , Conejo-Garcia Jose R. , Fridley Brooke L. , Tworoger Shelley S.
Published: March 2024

Background:

Cigarette smoke exposure has been linked to systemic immune dysfunction, including for B-cell and immunoglobulin (Ig) production, and poor outcomes in patients with ovarian cancer. No study has evaluated the impact of smoke exposure across the life-course on B-cell infiltration and Ig abundance in ovarian tumors.

Methods:

We measured markers of B and plasma cells and Ig isotypes using multiplex immunofluorescence on 395 ovarian cancer tumors in the Nurses’ Health Study (NHS)/NHSII. We conducted beta-binomial analyses evaluating odds ratios (OR) and 95% confidence intervals (CI) for positivity of immune markers by cigarette exposure among cases and Cox proportional hazards models to evaluate hazard ratios (HR) and 95% CI for developing tumors with low (<median) or high (≥median) immune cell/Ig percentage.

Results:

There were no associations between smoke exposure and B-cell or IgM infiltration in ovarian tumors. Among cases, we observed higher odds of IgA+ among ever smokers (OR, 1.54; 95% CI, 1.14–2.07) and ever smokers with no parental smoke exposure (OR, 2.03; 95% CI, 1.18–3.49) versus never smokers. Women with parental cigarette smoke exposure versus not had higher risk of developing ovarian cancer with low IgG+ (HR, 1.51; 95% CI, 1.10–2.09), whereas ever versus never smokers had a lower risk (HR, 0.74; 95% CI, 0.56–0.99).

Conclusions:

Ever smoking was associated with increased odds of IgA in ovarian tumors.

Impact:

IgA has been associated with improved ovarian cancer outcomes, suggesting that although smoking is associated with poor outcomes in patients with ovarian cancer, it may lead to improved tumor immunogenicity.
Upfront Neck Dissection for Treatment Selection and Improvement in Quality of Life as a Novel Treatment Paradigm for Deintensification in HPV+ OPSCC
Authors: Swiecicki Paul L. , Bellile Emily , Dragovic Aleksandar F. , McHugh Jonathan , Udager Aaron , Mierzwa Michelle Lynn , Shah Jennifer , Heft-Neal Molly , Rosko Andrew , Malloy Kelly M. , Casper Keith , Chinn Steven Bennett , Shuman Andrew G. , Stucken Chaz , Chepeha Douglas B. , Wolf Gregory T. , Bradford Carol Rossier , Eisbruch Avraham , Prince Mark E. , Worden Francis P. , Spector Matthew E.
Published: March 2024

Purpose:

Locoregionally advanced HPV+ oropharyngeal squamous cell carcinoma (OPSCC) has excellent cure rates, although current treatment regimens are accompanied by acute and long-term toxicities. We designed a phase II deescalation trial for patients with HPV+ OPSCC to evaluate the feasibility of an upfront neck dissection to individualize definitive treatment selection to improve the quality of life without compromising survival.

Patients and Methods:

Patients with T1–3, N0–2 HPV+ OPSCC underwent an upfront neck dissection with primary tumor biopsy. Arm A included patients with a single lymph node less than six centimeters, with no extracapsular spread (ECS) and no primary site adverse features underwent transoral surgery. Arm B included patients who had two or more positive lymph nodes with no ECS, or those with primary site adverse features were treated with radiation alone. Arm C included patients who had ECS in any lymph node and were treated with chemoradiation. The primary endpoint was quality of life at 1 year compared with a matched historical control.

Results:

Thirty-four patients were enrolled and underwent selective neck dissection. On the basis of pathologic characteristics, 14 patients were assigned to arm A, 10 patients to arm B, and 9 to arm C. A significant improvement was observed in Head and Neck Quality of Life (HNQOL) compared with historical controls (−2.6 vs. −11.9, P = 0.034). With a median follow-up of 37 months, the 3-year overall survival was 100% and estimated 3-year estimated progression-free survival was 96% [95% confidence interval (CI), 76%–99%].

Conclusions:

A neck dissection–driven treatment paradigm warrants further research as a deintensification strategy.
Abstract 1043: Identification of the novel immune synapse-localized proteome for immuno-oncology using Microscoop-induced targeted photo-biotinylation
Authors: Chong Weng-Man , Li Cecile , Huang Chun-Kai , Cheung Chantal Hoi Yin , Chang Hsiao-Jen , Chung Chia-Wen , Liao Jung-Chi
Published: March 2024

Although tens of immune synapse (IS) protein species are known, there remain many unknown IS-localized protein species. Understanding the proteome of the IS between a target cell and a lymphocyte is crucial for advancing immuno-oncology. The low abundance of ISs and the lack of a definitive enrichment marker have limited efficient proteomic profiling. Here, we used Microscoop™, an innovative system that integrates microscopy, machine learning, and targeted photo-biotinylation to enable precise and spatially specific enrichment of IS proteins, thereby facilitating proteomic discovery of the IS. We utilized Raji B cells as antigen-presenting cells (APCs) and induced IS formation with Jurkat T cells. The system first employed immunofluorescence imaging of CD3, a common IS marker in Jurkat T cells, and used a convolutional neural network-based deep learning algorithm to train the recognition of ISs from CMTPX-stained Raji B cells. Our automated system then successfully achieved spatially-targeted biotin-tagging of proteins at ISs through thousands of fields of view of imaging, deep learning-driven pattern generation, and photochemical labeling. Subsequent streptavidin pull-down and mass spectrometry analysis enabled the identification of IS-specific proteins. Remarkably, our spatial proteomic approach led to the isolation and identification of hundreds of different species at the IS interface, including proteins associated with key components of T-cell receptor (TCR) signaling pathways such as the TCR/CD3 complex, Src and Tec family tyrosine kinases, and pivotal NF-kB signaling proteins. Beyond these, we also identified a significant enrichment of proteins not previously associated with the IS. Our study not only illuminates previously unknown aspects of immune regulation at the IS interface, but also shedded light on proteins potentially important for immuno-oncology. These insights have significant implications for cancer research, particularly in understanding and manipulating immune responses for therapeutic purposes.

Citation Format: Weng-Man Chong, Cecile Li, Chun-Kai Huang, Chantal Hoi Yin Cheung, Hsiao-Jen Chang, Chia-Wen Chung, Jung-Chi Liao. Identification of the novel immune synapse-localized proteome for immuno-oncology using Microscoop-induced targeted photo-biotinylation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1043.