bluuebunny/crossref_metadata_2025_split huggingface dataset:
ZBiotics ameliorates T2DM-induced histopathological damage in liver, kidney and adipose tissues by modulating the NOD-like receptor signaling in Wistar rats
Authors: Esawie Mohammed , Matboli Marwa , Bushra Mariam Sameh , Hasanin Amany H. , Habib Eman Kamal , Mohamed Reham Hussein , Ali Hebatalla Said 
Published: February 2025

Abstract
Probiotics serve as promising candidates in type 2 diabetes mellitus (T2DM) therapy. Not only they presumably reduce the T2DM prevalence, but also keep down its complications. In the present study, we explored the beneficial impact of ZBiotics, an engineered probiotic, on T2DM Wistar rats. In silico analysis was performed to construct a genetic-epigenetic network linked to STING-NOD pathway and autophagy signaling. Then, 30 Wistar rats were divided into 5 groups (each n = 6); normal group, diabetic model, B. subtilis, and ZBiotics treated rats at high and low doses. Experimental procedures were carried out including biochemical and histopathologic analyses. Samples were extracted from rats’ blood, liver, kidney and adipose tissues. At the molecular aspect, the molecular players, chosen by the in silico analysis, were assessed using 2–ΔΔCt to estimate their relative quantification. With immunohistochemistry, TNF-alpha and LC3B were assessed as reflectors for inflammation and autophagy respectively. ZBiotics was reported to ameliorate the T2DM-induced histological damage. Besides, it downregulated TNF-alpha and upregulated LC3B expression levels. At the biochemical aspect, ZBiotics corrected LDL-c and improved serum creatinine and CK-MB levels. Inflammation relevant genes have been downregulated regarding CHUK, NFKB1 and miR-611. Therefore, ZBiotics is speculated to operate by modulating the genetic-epigenetic network linked to inflammatory cGAS-STING and autophagy signaling. ZBiotics is recommended for clinical trials as a separate candidate or as an adjuvant to the conventional T2DM therapy.
Exploring the intricacies of plant growth promoting rhizobacteria interactions: an omics review
Authors: Mmotla Kamogelo , Sibanyoni Nompumelelo R. , Allie Farhahna , Sitole Lungile , Mafuna Thendo , Mashabela Manamele D. , Mhlongo Msizi I. 
Published: February 2025

Abstract

Background
Plant growth-promoting rhizobacteria (PGPR) are beneficial microorganisms that inhabit the rhizosphere. PGPR play a role in stimulating plant growth and development and enhancing plant resistance and tolerance to biotic and abiotic stresses. To effectively fulfil their roles, PGPR engage in intricate interactions with one another, a phenomenon that occurs within the rhizosphere.
Mainbody.
This collaborative synergy among PGPR species within the rhizosphere is essential for them to perform their functions optimally. Nonetheless, the precise mechanisms and dynamics of PGPR-PGPR interactions, particularly at the transcriptomic level, remain the subject of ongoing research. Scientists are actively exploring and studying how these microorganisms interact and coordinate their activities within the rhizosphere, shedding light on the molecular processes underpinning their cooperative efforts. In this review, we undertake a thorough examination centred on the communication systems that regulate interactions among PGPR in the rhizosphere. Our examination delves into the mechanisms by which this communication triggers alterations at both the transcriptomic and metabolomic levels. Additionally, we assess the cutting-edge omics technologies currently available to study these intricate processes.

Conclusion
Understanding the modes of communication and molecular mechanisms underlying these interactions is crucial for harnessing their full potential, particularly in sustainable agriculture. By exploring transcriptomic and metabolomic alterations driven by these interactions, as well as the integration of advanced omics technologies, researchers can uncover new insights into decoding these complex processes, paving the way for innovative strategies to enhance sustainable agriculture.
Targeting AI-2 quorum sensing: harnessing natural products against Streptococcus suis biofilm infection
Authors: Gao Shuji , Yuan Shuo , Quan Yingying , Jin Wenjie , Shen Yamin , Li Rishun , Liu Baobao , Wang Yuxin , Yi Li , Wang Shaohui , Hou Xiaogai , Wang Yang 
Published: February 2025

Abstract
The biofilm acts as a protective layer for Streptococcus suis (S. suis), contributing to the development of drug resistance and chronic infections. Autoinducer 2 (AI-2) quorum sensing represents the primary regulatory pathway governing biofilm formation in S. suis. Consequently, targeting AI-2 quorum sensing to inhibit biofilm formation represents a promising strategy for preventing and managing drug resistance and chronic infections caused by S. suis. This study established a small natural product library by integrating commercial drug molecules with Chinese herbal medicine molecules. Consequently, two natural products, salvianolic acid A (SAA) and rhapontin (RH), which target S. suis AI-2 via quorum sensing, were identified. SAA and RH inhibit AI-2 synthesis through noncompetitive and competitive binding to S-ribosylhomocysteinase (LuxS). By inhibiting S. suis AI-2 quorum sensing, these compounds modulate the expression of adhesion genes and the synthesis of extracellular polysaccharides (EPS), reducing the adhesion ability of S. suis and ultimately inhibiting biofilm formation. Using LC‒MS/MS, we further analysed the impact of SAA and RH on the metabolic activity of S. suis, revealing the potential medicinal value of these compounds. Finally, the efficacy of SAA and RH against S. suis infection was validated in Galleria mellonella larvae, confirming their significant anti-infection effects.
Regulatory signatures involved in the cell cycle pathway contribute to egg production heterosis in chicken
Authors: Yuan Jingwei , Wang Yuanmei , Sun Yanyan , Li Yunlei , Ni Aixin , Li Qin , Yang Hanhan , Xu Xinying , Zong Yunhe , Ma Hui , Chen Jilan 
Published: February 2025

Abstract

Background
Crossbreeding is widely promoted as an efficient strategy to improve the productivity in agriculture. The molecular mechanism underlying heterosis for egg production is always intriguing in chicken. The transcriptional dynamic changes play a crucial role in the formation of heterosis, but little is known for the egg production traits.

Results
In present study, we measured the continuous manifestation of heterosis ranging from 2.67% to 10.24% for egg number in the crossbreds generated by reciprocal crossing White Leghorn and Beijing You chicken. The high-quality transcriptomes of ovary for purebreds (WW and YY) and crossbreds (WY and YW) in 5 laying stages were sequenced and integrated to identify regulatory networks relevant to the heterosis. We found highly conserved transcriptional features among 4 genetic groups. By using weighted gene co-expression network analysis (WGCNA), we obtained multiple gene co-expression modules that were significantly correlated with egg number for each group. The common KEGG pathways including apelin signaling pathway, cell cycle, ribosome, spliceosome and oxidative phosphorylation, were screened for the 2 crossbreds. Then, we identified consensus co-expression modules (CMs) that showed divergent expression pattern among crossbred (WY or YW) and purebreds (WW and YY). The hub genes of CMs were again overrepresented in the cell cycle pathway, and the crossbreds exhibited temporally complementary dominance of hub genes in the 5 laying stages. These results suggested that the crossbreds inherited from both parents to maintain the ovary function by cell cycle-related genes, contributing to the persistent heterosis for egg production. Furthermore, the dominant genes including MAD2L1, CHEK2 and E2F1 were demonstrated to function in ovarian follicle development and maturation and could be the candidate genes for egg production heterosis.

Conclusion
Our study characterized the dynamic profile of genome-wide gene expression in ovary and highlighted the role of dominant expression of cell cycle pathway genes in heterosis. These findings provided new insights for the molecular mechanism of egg production heterosis, which would facilitate the rational choice of suitable parents for producing crossbred chickens with higher egg production.
De-biasing microbiome sequencing data: bacterial morphology-based correction of extraction bias and correlates of chimera formation
Authors: Rauer Luise , De Tomassi Amedeo , Müller Christian L. , Hülpüsch Claudia , Traidl-Hoffmann Claudia , Reiger Matthias , Neumann Avidan U. 
Published: February 2025

Abstract

Introduction
Microbiome amplicon sequencing data are distorted by multiple protocol-dependent biases from bacterial DNA extraction, contamination, sequence errors, and chimeras, hindering clinical microbiome applications. In particular, extraction bias is a major confounder in sequencing-based microbiome analyses, with no correction method available to date. Here, we suggest using mock community controls to computationally correct extraction bias based on bacterial morphological properties.

Methods
We compared dilution series of 3 cell mock communities with an even or staggered composition. DNA of these mock, and additional skin microbiome samples, was extracted with 8 different extraction protocols (2 buffers, 2 extraction kits, 2 lysis conditions). Extracted DNA was sequenced (V1–V3 16S rRNA gene) together with corresponding DNA mocks.

Results
Microbiome composition was significantly different between extraction kits and lysis conditions, but not between buffers. Independent of the extraction protocol, chimera formation increased with higher input cell numbers. Contaminants originated mostly from buffers, and considerable cross-contamination was observed in low-input samples. Comparing the microbiome composition of the cell mocks to corresponding DNA mocks revealed taxon-specific protocol-dependent extraction bias. Strikingly, this extraction bias per species was predictable by bacterial cell morphology. Morphology-based computational correction of extraction bias significantly improved resulting microbial compositions when applied to different mock samples, even with different taxa. Equivalent correction of the skin samples showed a substantial impact on microbiome compositions.

Conclusions
Our results indicate that higher DNA density increases chimera formation during PCR amplification. Furthermore, we show that computational correction of extraction bias based on bacterial cell morphology would be feasible using appropriate positive controls, thus constituting an important step toward overcoming protocol biases in microbiome analysis.
Machine learning for predicting severe dengue in Puerto Rico
Authors: Madewell Zachary J. , Rodriguez Dania M. , Thayer Maile B. , Rivera-Amill Vanessa , Paz-Bailey Gabriela , Adams Laura E. , Wong Joshua M. 
Published: February 2025

Abstract

Background
Distinguishing between non-severe and severe dengue is crucial for timely intervention and reducing morbidity and mortality. World Health Organization (WHO)-recommended warning signs offer a practical approach for clinicians but have limited sensitivity and specificity. This study aims to evaluate machine learning (ML) model performance compared to WHO-recommended warning signs in predicting severe dengue among laboratory-confirmed cases in Puerto Rico.

Methods
We analyzed data from Puerto Rico’s Sentinel Enhanced Dengue Surveillance System (May 2012–August 2024), using 40 clinical, demographic, and laboratory variables. Nine ML models, including Decision Trees, K-Nearest Neighbors, Naïve Bayes, Support Vector Machines, Artificial Neural Networks, AdaBoost, CatBoost, LightGBM, and XGBoost, were trained using fivefold cross-validation and evaluated with area under the receiver operating characteristic curve (AUC-ROC), sensitivity, and specificity. A subanalysis excluded hemoconcentration and leukopenia to assess performance in resource-limited settings. An AUC-ROC value of 0.5 indicates no discriminative power, while values closer to 1.0 reflect better performance.

Results
Among the 1708 laboratory-confirmed dengue cases, 24.3% were classified as severe. Gradient boosting algorithms achieved the highest predictive performance, with an AUC-ROC of 97.1% (95% CI: 96.0–98.3%) for CatBoost using the full 40-variable feature set. Feature importance analysis identified hemoconcentration (≥ 20% increase during illness or ≥ 20% above baseline for age and sex), leukopenia (white blood cell count < 4000/mm3), and timing of presentation at 4–6 days post-symptom onset as key predictors. When excluding hemoconcentration and leukopenia, the CatBoost AUC-ROC was 96.7% (95% CI: 95.5–98.0%), demonstrating minimal reduction in performance. Individual warning signs like abdominal pain and restlessness had sensitivities of 79.0% and 64.6%, but lower specificities of 48.4% and 59.1%, respectively. Combining ≥ 3 warning signs improved specificity (80.9%) while maintaining moderate sensitivity (78.6%), resulting in an AUC-ROC of 74.0%.

Conclusions
ML models, especially gradient boosting algorithms, outperformed traditional warning signs in predicting severe dengue. Integrating these models into clinical decision-support tools could help clinicians better identify high-risk patients, guiding timely interventions like hospitalization, closer monitoring, or the administration of intravenous fluids. The subanalysis excluding hemoconcentration confirmed the models’ applicability in resource-limited settings, where access to laboratory data may be limited.

Graphical Abstract
Repeated positron emission tomography tracing neutrophil elastase in a porcine intensive-care sepsis model
Authors: Wilske Frida , Eriksson Olof , Amini Rose-Marie , Estrada Sergio , Janols Helena , Khalil Amina , Larsson Anders , Lipcsey Miklós , Mangsbo Sara , Sigfridsson Jonathan , Sjölin Jan , Skorup Paul , Wall Anders , Wilson Viola , Castegren Markus , Antoni Gunnar 
Published: February 2025

Abstract

Background
Neutrophil granulocytes are important parts of the defence against bacterial infections. Their action is a two-edged sword, the mediators killing the intruding bacteria are at the same time causing tissue damage. Neutrophil activation is part of the dysregulated immune response to infection defining sepsis and neutrophil elastase is one of the powerful proteases causing both effects and damage. Inhibition of neutrophil elastase has been tried in sepsis and ARDS, so far with inconclusive results.

Methods
We used positron emission tomography (PET) combined with computed tomography (CT) and the selective and specific neutrophil elastase inhibitor PET-tracer [11C]GW457427 ([11C]NES), in an intensive care unit porcine Escherichia coli sepsis model with the primary aim to visualise the biodistribution of neutrophil elastase in the initial acute phase of the septic reaction. Repeated PET–CT investigations were performed before and after induction of sepsis.

Results
At baseline [11C]NES uptake was found in the bone marrow, spleen and liver. The uptake in the bone marrow was markedly increased two hours into the sepsis, whereas in spleen and liver the uptake was not as markedly changed compared to baseline. At 4 h after the sepsis induction [11C]NES in the bone marrow decreased while the uptake increased in the spleen, liver and lungs.

Conclusion
The neutrophil elastase PET-tracer [11C]NES is a novel and unique instrument to study the acute innate neutrophil immune response in sepsis and associated vital organ failure. We here present images and quantitative data of the neutrophil elastase distribution the first hours of acute experimental sepsis. Surprisingly, a pronounced increase of neutrophil elastase was found in the bone marrow 2 h into the sepsis reaction followed at 4 h by increase in the liver, spleen and lungs and a concomitant reduction of the tracer uptake in bone marrow.
How can Blood Flow Restriction Exercise be Utilised for the Management of Persistent Pain Following Complex Injuries in Military Personnel? A Narrative Review
Authors: Gray Luke , Ladlow Peter , Coppack Russell J , Cassidy Robyn P , Kelly Lynn , Lewis Sarah , Caplan Nick , Barker-Davies Robert , Bennett Alexander N , Hughes Luke 
Published: February 2025

Abstract

Background
Persistent pain is a complicated phenomenon associated with a wide array of complex pathologies and conditions (e.g., complex regional pain syndrome, non-freezing cold injury), leading to extensive disability and reduced physical function. Conventional resistance training is commonly contraindicated in load compromised and/or persistent pain populations, compromising rehabilitation progression and potentially leading to extensive pharmacological intervention, invasive procedures, and reduced occupational status. The management of persistent pain and utility of adjunct therapies has become a clinical and research priority within numerous healthcare settings, including defence medical services.

Main Body
Blood flow restriction (BFR) exercise has demonstrated beneficial morphological and physiological adaptions in load-compromised populations, as well as being able to elicit acute hypoalgesia. The aims of this narrative review are to: (1) explore the use of BFR exercise to elicit hypoalgesia; (2) briefly review the mechanisms of BFR-induced hypoalgesia; (3) discuss potential implications and applications of BFR during the rehabilitation of complex conditions where persistent pain is the primary limiting factor to progress, within defence rehabilitation healthcare settings. The review found BFR application is a feasible intervention across numerous load-compromised clinical populations (e.g., post-surgical, post-traumatic osteoarthritis), and there is mechanistic rationale for use in persistent pain pathologies. Utilisation may also be pleiotropic in nature by ameliorating pathological changes while also modulating pain response. Numerous application methods (e.g., with aerobic exercise, passive application, or resistance training) allow practitioners to cater for specific limitations (e.g., passive, or contralateral application with kinesiophobia) in clinical populations. Additionally, the low-mechanical load nature of BFR exercise may allow for high-frequency use within residential military rehabilitation, providing a platform for conventional resistance training thereafter.

Conclusion
Future research needs to examine the differences in pain modulation between persistent pain and pain-free populations with BFR application, supporting the investigation of mechanisms for BFR-induced hypoalgesia, the dose-response relationship between BFR-exercise and pain modulation, and the efficacy and effectiveness of BFR application in complex musculoskeletal and persistent pain populations.
Diversity and abundance of butterflies in urban areas of Bankura district, Bankura, West Bengal, India
Authors: Patra Avisek , Patra Anirban , Mandal Biplab , Ghosh Anupam 
Published: February 2025

Abstract

Objective
During the present study, the biodiversity profile of butterflies was assessed on the Bankura Christian College campus, a large area with a huge amount of trees, bushes, rain forest, and undisturbed areas within the urban areas of Bankura district of West Bengal, India.

Methodology
Present study was carried out in Bankura Christian College campus, a relatively undisturbed area in Bankura town, of West Bengal, India. The findings presented here were based on seasonal diversity of Butterflies in the college campus. The species dominance of Butterflies was numerically measured on the basis of density, relative density, abundance, relative abundance, frequency, and relative frequency. To analyze the result, single factor ANOVA was performed in between five different seasons. Seasonal variation was analysed using individual rarefaction analysis. The Jaccard similarity index was also used to conduct hierarchical classical clustering.

Result
A total of 47 genera and 59 species of butterflies that belongs to five families were recorded. The findings of the present study indicated a high abundance of the butterflies that belongs to Nymphalidae family comprising 13 Genera and 22 species.

Conclusion
In the Monsoon season, the highest number of butterflies were recorded in comparison to other seasons. Different types of ecological indices were also calculated from observed species diversity of butterflies. Individual rarefaction analysis revealed that the probability of finding the greatest specimen was in monsoon season. Hierarchical cluster analysis among seasons based on the Jaccard Similarity index using Paired group (UPGMA) shows higher similarity of butterflies in between monsoon and Fall season.
Combined Analyses of Circulating Tumor DNA and Immunoscore in Patients With Stage III Colon Cancer: A Post Hoc Analysis of the PRODIGE-GERCOR IDEA-France/HORG-IDEA-Greece Trials
Authors: Taieb Julien , Souglakos John , Boukovinas Ioannis , Falcoz Antoine , Pages Franck , Messaritakis Ippokratis , Bennouna Jaafar , Artru Pascal , Louvet Christophe , Lepere Celine , Emile Jean Francois , Bouche Olivier , Mazard Thibault , Vernerey Dewi , Vogiatzoglou Konstantinos , Tzardi Maria , Sharma Shruti , Liu Minetta C. , Sethi Himanshu , André Thierry , Galon Jérome , Laurent-Puig Pierre 
Published: February 2025

PURPOSE
Immunoscore (IS) and circulating tumor DNA (ctDNA) are two emerging technologies in improving prognostication and tailoring adjuvant treatments in patients resected from a stage III colon cancer (CC). Here, we analyzed the prognostic value of the two biomarkers in patients who participated in the randomized phase III IDEA-France and HORG trials.

METHODS
Plasma samples were collected after surgery and before adjuvant chemotherapy. ctDNA analysis was performed using a clinically validated, personalized, tumor-informed 16-plex protein chain reaction assay. Multivariable analyses for time to recurrence (TTR; patients without recurrence or death due to CC) and overall survival (OS) were performed using ctDNA and IS results, along with other parameters including treatment duration and disease risk group.

RESULTS

Of the 554 patients with available ctDNA results, 445 were ctDNA-negative (80.3%) and 109 were ctDNA-positive (19.7%); baseline characteristics showed more T4/N2 and venous embolism/lymphatic invasion/perineural invasion+ in ctDNA-positive patients. With a median follow-up of 6.7 years, the 2-year TTR rate was 43.5% (95% CI, 34.1 to 52.6) for ctDNA-positive patients and 88.1% (95% CI, 84.7 to 90.8) for ctDNA-negative patients (
P
< .0001). ctDNA was confirmed as an independent prognostic marker for both TTR (adjusted hazard ratio [adjHR], 5.21 [95% CI, 3.59 to 7.58];
P
< .001) and OS (adjHR, 4.84 [95% CI, 3.40 to 6.89];
P
< .001). ctDNA remained the most significant prognostic factor irrespective of disease stage, treatment duration, and IS results. IS was not prognostic in ctDNA-positive patients but remained a significant prognostic tool for ctDNA-negative patients.

CONCLUSION
In this combined analysis of two adjuvant trials dedicated to patients with stage III CC after surgery, ctDNA was detectable in 19.7% of the patients and was confirmed as a major independent prognostic biomarker. IS seems to bring additional prognostic information in the 80.3% of patients who are ctDNA-negative.