bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bismuth-gold nanohybrid conjugated with a HEX-bound oligonucleotide; a novel nano photosensitizer to combat antimicrobial resistance
Authors: Nomani Atiyeh , Nosrati Hamed , Faraji Naser , Charmi Jalil , Javani Siamak 
Published: July 2024

Abstract

Antimicrobial resistance (AMR) leads to a decrease in the adequacy of antimicrobial agents and an increase in the rate of adverse effects and mortality. The main objective of this project is to investigate the synergistic effect of BiAu@NCLin-T1 and its substructures as an antimicrobial photodynamic therapy (aPDT) agent to combat microbial resistance. In addition, the effect of photothermal therapy (PTT) on some of the designed nanostructures at a temperature of 40°C was also tested. The antimicrobial test was carried out using the growth curve method against E. coli and S. aureus as Gram-negative and positive model bacteria. Computational methods were used to investigate the stability and entropy of oligonucleotide sequence structures. Various analyses were performed to identify the nanostructures, including Ultraviolet-visible (UV-vis) spectroscopy, Fourier-transform infrared spectroscopy (FTIR), dynamic light scattering (DLS), transmission electron microscopy (TEM), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray analysis (EDS) and fluorescence analysis. The BiAu@NCLin-T1 appeared the significant aPDT impact against the gram-negative E.coli strain at two distinctive oligonucleotide concentrations (1, and 1.5 µM). Based on the results, the outlined nanostructures can act as a photosensitizer (PS), a photothermal treatment agent (PTT), and an antimicrobial agent to combat resistant bacteria.
Club cell secretory protein 16 up-regulates cell proliferation, inhibits inflammation and pyroptosis against particular matter 2.5 -induced epithelium damage in asthmatic mice
Authors: Lin Jinle , Chen Xiaowen , Chen Yuehua , Zeng Xiaobing , Yao Jie , Miao Yuyang , Wang Fang , Luo Shaohua , Jiang Lei , Hu Wenxue , Liu Xiaolong , Zhang Jing , Zhang Wenwu , Dou Qingli , Li Zhongpeng , Zhou Siping , Wu Jian 
Published: July 2024

Abstract

Introduction
: Club cell secretory protein (CC16) is reported to have multiple protective functions in airway diseases, including anti-inflammatory, immunomodulatory and antioxidant. This study aims to determine whether CC16 can repair lung injury caused by particular matter 2.5(PM2.5) exposure in asthmatic mice.
Methods
In the ovalbumin (OVA)-induced asthma murine study, 6-week-old male C57BL/6J mice were primary exposed to PM2.5 for 24 hours and following treated with CC16, Artery blood gas, lung function,histopathology and immunohistochemical staining were detected. The BEAS-2B cell line was primary exposed to PM2.5 for 24 hours and then treated with CC16 subsequently, fluorescence and electron microscopy, protein and RNA of inflammation and pyroptosis, and RNA Sequencing were detected.
Results
In the OVA-induced asthmatic mice after exposure of PM2.5 treatment with CC16 ameliorated PM2.5-induced lung tissue damage, respiratory acidosis and restore the increased airway resistance after PM2.5-exposed group, accompanied with the inhibition in the protein of inflammation and pyroptosis.Moreover, CC16 increased cell proliferation, ameliorated pyroptotic cell death induced by PM2.5 and inhibited the expression on the protein and RNA of inflammation and pyroptosis. Transcriptome analysis revealed that CC16 down-regulate genes associated with inflammatory adhesion, while up-regulating proliferation genes,like E-Twenty-Six-1.
Conclusions
CC16 could repair airway epithelium PM2.5-induced damage in asthma mice by up-regulating cell proliferation,inhibiting pyroptosis and imflammation, which it will been used as a novel therapeutic agent to alleviate the health risks of PM2.5 exposure in future.
Quantum-Classical Synergy: Enhancing De Novo Genome Assembly with Hybridized QUBO Optimization
Authors: Mukherjee Anshit , Mallik Biswadip Basu 
Published: July 2024

Abstract

The difficult computational task of de novo genome assembly is to piece together the original DNA sequence from a collection of overlapping pieces. The issue can be expressed as an NP-hard quadratic unconstrained binary optimization (QUBO) problem. To solve QUBO problems more effectively than conventional techniques, quantum computing presents a viable alternative. This is because quantum annealers and gate-based quantum algorithms may take advantage of quantum effects like superposition and entanglement. But there are drawbacks to quantum computing as well, such scalability, noise, and decoherence. In this work, we present a hybrid quantum-classical optimization algorithm that solves the QUBO problem of de novo genome assembly by utilizing the advantages of both paradigms. To find near-optimal solutions in the presence of defects and noise, our technique combines a classical local search heuristic with a quantum approximate optimization algorithm (QAOA). We assess our algorithm's performance against current quantum and conventional approaches using both artificial and actual data sets. We demonstrate that our algorithm can outperform the state-of-the-art methods in terms of accuracy and computing cost, and it has the potential to solve intricate and large-scale genome assembly challenges.
City-level drug policies in Portugal: the COVID-19 pandemic as an analyser of harm reduction intervention responsiveness in Porto and Lisbon
Authors: Pires Cristiana Vale , Curado Adriana , Fuertes Ricardo , Carvalho Maria Carmo , Valente Helena 
Published: July 2024

Abstract

Background
The COVID-19 pandemic health crisis and its potential implications for people who use drugs (PWUD) created permissive conditions toward social innovation and experimentation. Still, it also exposed gaps in harm reduction approaches. The local level situations informed the harm reduction responsiveness, so it was not applied uniformly in different regions. This paper intends to contribute to the analysis of harm reduction responsiveness during the COVID-19 outbreak by comparing the adaptations and implementation of harm reduction and municipal services to support street-involved PWUD in two Portuguese cities – Porto and Lisbon. This study aims to shed light on the city-level implementation of drug policies in Portugal.
Methods
This study is based on a comparative qualitative analysis based on the experiences of PWUD and HR professionals regarding the implementation of harm reduction responses during the COVID-19 pandemic in Porto and Lisbon. The study is based
on interviews with street-involved (SI) PWUD (n=22, 12 in Porto and 10 in Lisbon) and online focus groups with harm reduction professionals (N=12, 6 in Porto and 6 in Lisbon).
Results
Harm reduction teams in Porto and Lisbon implemented contingency plans and proactive adaptations to respond to the pandemic-related emerging needs. However, the study revealed contrasting experiences in the city-level support to harm reduction and responsiveness to the impacts of COVID-19 among SI PWUD in Porto and Lisbon. There were relevant differences in the support they received from the City Council and the city-level responses implemented to support street-involved (SI) PWUD. While the approach in Porto was described as restrictive and zero-tolerance towards drug use, in Lisbon, the responses were harm reduction-focused. The harm reduction-focused approach implemented in Lisbon revealed better results regarding the harm reduction responsiveness to the pandemic health crisis and adherence of SI PWUD to services, mostly because of their inclusive approaches.
Conclusion
The pandemic constraints and adaptations must be contextualized in an overall process of disinvestment in harm reduction in Portugal. Moreover, beyond the Portuguese drug policy model, city-level drug policies are crucial in the design and implementation of local drug policies.
Structural, optoelectronic, thermoelectric, and thermodynamic properties of novel copper-based halide double perovskites Cs 2 CuXCl 6 (X = Sb, As, Bi): First principles insights
Authors: Azze Siham El , Ziati Meryem , Baz Morad El , Faqir Mustapha , Ez-Zahraouy Hamid 
Published: July 2024

Abstract

In the present investigation, a complete physical study of electronic structure, optical, thermoelectric and thermodynamic properties have been done on a set of three lead-free double halide perovskite materials, Cs2CuXCl6; using the first principle calculation on the basis of Density Functional Theory and the theory of Boltzmann transport applied in the WIEN2K simulator program. When substituting the X with As, Sb and Bi cation in the double perovskite structure Cs2CuXCl6, interesting electronic and optical properties have been shown, namely low indirect band gap of 0.78, 1.21 and 1.51 eV for Cs2CuAsCl6, Cs2CuSbCl6 and Cs2CuBiCl6 respectively, as well as high absorption in the UV-Visible region. Among the three studied compounds, Cs2CuAsCl6 exhibits an excellent structural stability regarding its high bulk modulus and maximum tolerance factor. It is noticeable from the thermoelectric study that Seebeck coefficient decreases with increasing temperature, while the figure of merit is proportional with temperature enhancement, such a behavior makes of the investigated materials promising candidates for visible-light solar cell device applications, especially that our theoretical results match perfectly with previous works [1].
Cesarean hysterectomy in pregnancies complicated with placenta previa accreta: A retrospective hospital-based study
Authors: Zhan Yongchi , Lu Enfan , Xu Tingting , Huang Guiqiong , Deng Chunyan , Chen Tiantian , Ren Yuxin , Wu Xia , Yu Haiyan , Wang Xiaodong 
Published: July 2024

Abstract

Background
Placenta previa accreta (PPA) is a severe obstetric condition that can cause massive postpartum hemorrhage and transfusion. Cesarean hysterectomy is necessary in some severe cases of PPA to stop the life-threatening bleeding, but cesarean hysterectomy can be associated with significant surgical blood loss and major complications. The current study is conducted to investigate the potential risk factors of excessive blood loss during cesarean hysterectomy in women with PPA.
Methods
This is a retrospective study including singleton pregnancies after 28 weeks of gestation in women with placenta previa and pathologically confirmed placenta accreta spectrum who received hysterectomy during cesarean sections. A total of 199 women from January 2012 to August 2023 were included in this study and were divided into Group 1 (estimated surgical blood loss (EBL) ≤ 3500 mL, n=103) and Group 2 (EBL > 3500 mL, n=96). The primary outcome was defined as an EBL over 3500 mL. Baseline characteristics and surgical outcomes were compared between the two groups. A multivariate logistic regression model was applied to find potential risk factors of the primary outcome.
Results
Massive surgical blood loss was prevalent in our study group, with a median EBL of 3500 mL. The multivariate logistic analysis showed that emergency surgery (OR 2.18, 95% CI 1.08-4.41, p = 0.029), cervical invasion of the placenta (OR 2.70, 95% CI 1.43-5.10, p = 0.002), and intraoperative bladder injury (OR 5.18, 95% CI 2.02-13.28, p = 0.001) were all associated with the primary outcome. Bilateral internal iliac arteries balloon occlusion (OR 0.57, 95% CI 0.34-0.97) and abdominal aortic balloon occlusion (OR 0.33, 95% CI 0.19-0.56) were negatively associated with the primary outcome.
Conclusions
Emergency surgery, cervical invasion of the placenta, and intraoperative bladder injury were potential risk factors for additional EBL during cesarean hysterectomy in women with PPA. Future prospective studies are needed to confirm the effect of intra-arterial balloon occlusion in cesarean hysterectomy of PPA.
Identification of shared gene signatures for diagnosing Systemic lupus erythematosus with osteonecrosis of the femoral head through bioinformatics analysis and machine learning
Authors: Lu Fei-Long , Zhang Wen-Bin , Ma Yu-Lin , Song Hao , Hu Yi-Mei 
Published: July 2024

Abstract

Background: Osteonecrosis of the femoral head (ONFH) is a severe complication of systemic lupus erythematosus (SLE). Although there is a characteristic disease spectrum between SLE and ONFH, the exact pathogenesis remains unclear. Furthermore, the lack of early diagnostic criteria complicates the diagnosis of SLE-ONFH. This study aimed to identify key diagnostic candidate genes in patients with SLE and ONFH.
Methods: SLE and ONFH datasets were obtained from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) and module genes were identified using Limma and Weighted Gene Co-expression Network Analysis (WGCNA), followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. A protein‒protein interaction (PPI) network was constructed, and machine learning algorithms—extreme gradient boosting (XGB), support vector machine (SVM), random forest (RF), and generalized linear models (GLMs)—were applied to identify candidate hub genes for diagnosing SLE combined with ONFH. Receiver operating characteristic (ROC) curves and nomograms were generated.
Results: The SLE dataset included 493 DEGs and 1,171 module genes. The ONFH dataset included 384 DEGs and 525 module genes. By intersecting the DEGs and module genes, a total of 74 genes were obtained, which were mainly enriched in the "chemokine signaling pathway" and "cytokine‒cytokine receptor interaction pathway." By constructing the PPI network, 22 node genes were identified. Using machine learning, the five candidate hub genes with the highest scores were selected for nomogram construction and diagnostic value evaluation. The nomogram and all five candidate key genes demonstrated high diagnostic value.
Conclusion: The results of this study indicate that ELANE, LTF, ALAS2, MX1, and CA1 are the selected candidate key genes. The construction of a nomogram provides a new direction for the clinical prediction of SLE combined with ONFH.
Bidirectional Relationships between Phonological Processing and Basic Number Knowledge in Kindergarten Children: A Longitudinal Study
Authors: Chen Xin , Ma Chi , Yang Xiujie 
Published: July 2024

Abstract

An ongoing debate on the association of phonological processing and number knowledge concerns the extent to which they influence each other when children were at young ages. The current study aims at establishing the direction of the developmental relationship between these two kinds of abilities at an early age. Eighty-two Chinese kindergarten children were followed from 5 to 6 years old with a one-year interval. We investigated three phonological processing skills (phonological awareness, phonological memory, and rapid automatized naming) and two kinds of basic number knowledge (number identification and number comparison) at time 1 and time 2. Cross-lagged panel analyses revealed that the association between phonological awareness and number comparison was bidirectional. Specifically, early phonological awareness at time 1 could predict later number identification, and early number comparison at time 1 was a significant predictor of later phonological memory. In contrast, rapid automatized naming had no such predictive relations with other variables. The present findings are among the first to provide evidence that basic number knowledge could predict later phonological processing in kindergarten children.
Genetics, age, and diet influence gut bacterial communities and performance of black soldier fly larvae (Hermetia illucens)
Authors: Silvaraju Shaktheeshwari , Zhang Qi-hui , Kittelmann Sandra , Puniamoorthy Nalini 
Published: July 2024

Abstract

Background
The gut microbiota of black soldier fly larvae (BSFL, Hermetia illucens) play a crucial role in recycling various organic waste streams. This capability is linked to the presence of a potential common core microbiota in BSFL. However, subjective thresholds for defining core taxa and the difficulty of separating genetic and environmental influences have prevented a clear consensus in the literature. We analysed the gut bacterial communities of two genetically distinct BSF lines (wild type (WT) and lab-adapted line (LD)) raised on ten different diets based on common agricultural by-products and food waste in Southeast Asia.
Results
High-throughput 16S rRNA gene sequencing revealed that gut bacterial communities were significantly influenced by genetics (p = 0.001), diet (plant/meat-based; p = 0.001), larval age (p = 0.001), and their interactions (p = 0.002). This led us to investigate both common core taxa and lineage-specific core taxa. At a strict > 97% prevalence threshold, four core taxa were identified: Providencia_A_732258, an unclassified genus within the family Enterococcaceae, Morganella, and Enterococcus_H_360604. A relaxed threshold (> 80% prevalence) extended the core to include other potential common core taxa such as Klebsiella, Proteus, and Scrofimicrobium. Our data suggest that Proteus, Scrofimicrobium, Corynebacterium, Vagococcus_B, Lysinibacillus_304693 (all LD), and Paenibacillus_J_366884 (WT) are lineage-specific core members rather than a common core (> 90% prevalence in either LD or WT, with prevalence significantly different between lines (p ≤ 0.05)). Positive correlations were observed between several core genera and larval performance in LD, typical of a highly optimized lab-adapted line. Interestingly, only members of the genus Providencia appeared to play a crucial role in most aspects of larval performance in both genetic lineages.
Conclusion
Our study demonstrates that the gut microbiota of black soldier fly larvae is influenced by genetic factors, diet composition, larval age, and their interactions. We identified a distinct lineage-specific core microbiota, emphasizing genetic background's role. Future studies should apply a standardized high prevalence threshold of at least > 90% unless there is a valid reason for relaxation or sample exclusion. The consistent association of Providencia spp. with larval performance across both genetic lines highlights their crucial role in the BSFL gut ecosystem.
Combined analysis of entosis and disulfidptosis to predict the prognosis and tumor microenvironment (TME) landscape of hepatocellular carcinoma
Authors: hu shuai , Huang Kai , Zhang Guangquan , He Yongfei , Xu Junming , Zhai Hang , Wang Jicai , Hong Shengjie , Wu Fenfang , Shi Xianjie 
Published: July 2024

Abstract

Background
Hepatocellular carcinoma (HCC) is a common malignant digestive tract tumor worldwide. Disulfidptosis and entosis are two special cell death mechanisms. The purpose of this study was to investigate the prognostic and clinical applicability of these two cell death-related genes in HCC.
Methods
The R package "Deseq2" was used to conduct differential expression analysis, 22 disulfidptosis-related genes and 25 entosis-related genes were screened out to 15 differential genes, and 8 key genes were subsequently screened out by single-factor Cox regression analysis using the R package “survival”. Finally, LASSO regression analysis was performed with the R package “glment” to screen 2 prognostic genes. A prognostic prediction model was constructed based on this scoring system. Then, immunoinfiltration analysis was performed with the R packages “IBOR” and “estimate”. Drug sensitivity analysis was performed with the R package “OncoPredict” to screen for liver cancer-sensitive drugs.
Results
A hepatocellular carcinoma prognosis prediction model based on the KIF2C and SLC7A11 scoring system was constructed with good predictive ability, and the KIF2C and SLC7A11 scoring systems were applied to screen immunotherapy targets and sensitive drugs related to HCC.
Semantic Segmentation in Autonomous Driving using Multi-scale Feature Fusion and Graph Network
Authors: Li Yajing , Zhang Yong , Zhang Yuqing , Piao Xinglin , Pei Huimin , Hu Yongli 
Published: July 2024

Abstract

Semantic segmentation in urban scenes is an important task in computer vision. However, there are many challenges in urban road scenes, such as category imbalance and complex backgrounds. These problems lead to unclear edge segmentation and fuzzy categorization of occluded objects in existing semantic segmentation methods in urban scenes, which limits the accuracy and robustness in practical applications. In this paper, we propose a model that recursively enhances edge feature representation combined with local spatial context. We address the problem of unclear edge segmentation by introducing Multi-scale Central Difference Convolution (MS-CDC) to fuse multi-scale edge features. The FeedBack Connection (FBC) module based on feature pyramid fuses the multi-scale features while recursively augmenting the original network to make the occluded objects more robust. Meanwhile, we design a Local Feature Extraction (LFE) module to capture pixel-wise relationships by constructing local pixel graph and center pixel graph. It can learn local contextual information to extract finer pixel features. Experimental results on the Cityscapes and Mapillary Vista dataset validate the effectiveness of our proposed model. Our model can achieve new results by 80.67 \(%\) and 45.5$%$ mIoU on the Cityscapes and Mapillary Vista val set. We open-source our code at \href{https://github.com/sanmanaa/segmentation-autodriving-graph-centralconv}{https://github.com/sanmanaa/segmentation-autodriving-graph-centralconv}
Epigenetic Modulation by PRC2: Implications for Immune Regulation and Prognostic Outcomes in Breast Cancer
Authors: Zhang Yi , Wang Tongbo , Chen Xiaoqi , Song Jiarui , Yang Man , Jiang Hongnan , Kong Xiangyi , Wang Yipeng , Gao Jidong 
Published: July 2024

Abstract

Purpose
Overexpression of polycomb repressive complex 2 (PRC2) is commonly expressed in various malignancies, often correlating with unfavorable prognoses and indicating its potential as a therapeutic target.This study aimed to elucidate the comprehensive role of PRC2, especially in the context of breast cancer (BRCA), examining its association with the cell cycle and its implications within the tumor immune microenvironment.
Methods
Utilizing a comprehensive approach, we evaluated the levels of the primary components of PRC2, composed of EZH2, SUZ12, and EED. By employing Gene Set Enrichment Analysis (GSEA), we integrated these expression profiles. We introduced a cumulative representation known as the PRC2 complex score to assess the collective impact of these proteins in BRCA.
Results
Analysis revealed a pronounced increase in PRC2 expression in BRCA tissues compared to their normal counterparts. Intriguingly, this heightened expression was not uniform across all BRCA subtypes, hinting at subtype-specific or regulatory patterns for PRC2. Additionally, a pivotal role for the PRC2 complex in cell cycle advancement was observed, suggesting its involvement in promoting cell proliferation. A noteworthy association was also discerned between the PRC2 complex and immune cell dynamics, highlighting its potential in shaping the immunological landscape within BRCA.
Conclusion
Our findings underscore the potential of the PRC2 complex as a pivotal biomarker in the progression of BRCA. The intricate role it plays in the tumor immune microenvironment, particularly its influence on Th2 cell regulation, opens new avenues for targeted therapeutic strategies.