bluuebunny/crossref_metadata_2025 huggingface dataset:
A systematic screening assay identifies efficient small guide RNAs for CRISPR activation
Authors: Arvidsson Elin , Lobo Diana Duarte , Sabarese Ermelinda , Duarte Fabio , Nobre Rui Jorge , Quintino Luis , Lundberg Cecilia
Published: January 2025

CRISPR-mediated gene activation (CRISPRa) encompasses a growing field of biotechnological approaches with exciting implications for gene therapy. However, there is a lack of experimental validation tools for selecting efficient sgRNAs for downstream applications. Here, we present a screening assay capable of identifying efficient single- and double sgRNAs through fluorescence quantification in vitro. In addition, we provide a tailored Golden Gate cloning workflow for streamlined incorporation of selected sgRNA candidates into lentiviral (LVs) or adeno-associated viral vectors (AAVs). The overall workflow was validated using therapeutically relevant genes for neurodegenerative diseases, including Tfeb, Adam17, and Sirt1. The most efficient sgRNAs also demonstrated activation of endogenous gene expression at mRNA level. Correlation analysis of gene activation relative to sgRNA binding site distance to transcription start-site or nearby transcription factor binding sites failed to detect common characteristics influencing gene activation in the selected promoter regions. This data demonstrates the potential of the screening assay to identify functionally efficient sgRNA candidates across multiple genes along with streamlined cloning of viral vectors and may assist in accelerating future developments of CRISPRa-focused applications.
The Batten disease gene Cln3 is required for the activation of intestinal stem cell during regeneration via JAK/STAT signaling in Drosophila
Authors: Yu Zihua , Yan Jinhua , Liu Zhiming , Wang Haiyan , Luo Guanzheng , Chen Haiyang
Published: January 2025

CLN3 mutation causes Juvenile neuronal ceroid lipofuscinosis (JNCL, also known as Batten disease), an early onset neurodegenerative disorder. Patients who suffer from Batten disease often die at an early age. However, the mechanisms underlying how CLN3 loss develops Batten disease remain largely unclear. Here, using Drosophila midgut system, we demonstrate that Drosophila Cln3 has no effect on midgut homeostasis maintaince, including cellular component, intestinal stem cells (ISCs) proliferation and differentiation, but is necessary for ISC activation upon tissue damage. Cell type-specific Gal4 screening reveals that the failure of ISC activation during regeneration caused by Cln3 loss is ISC-autonomous. Through genetic analyses, we elucidate that JAK/STAT signaling in ISCs is not activated with Cln3 depletion upon tissue damage, and functions downstream of Cln3. Our study provides a potential mechanism underlying the development of CLN3-mediated Batten disease at cellular level.
Dual role of pyroptosis in liver diseases: mechanisms, implications, and therapeutic perspectives
Authors: Yang Siyuan , Zou Yunyi , Zhong Chunhua , Zhou Zuoqiong , Peng Xiyang , Tang Changfa
Published: January 2025

Pyroptosis, a form of programmed cell death induced by inflammasome with a mechanism distinct from that of apoptosis, occurs via one of the three pathway types: classical, non-classical, and granzyme A/B-dependent pyroptosis pathways. Pyroptosis is implicated in various diseases, notably exhibiting a dual role in liver diseases. It facilitates the clearance of damaged hepatocytes, preventing secondary injury, and triggers immune responses to eliminate pathogens and damaged cells. Conversely, excessive pyroptosis intensifies inflammatory responses, exacerbates hepatocyte damage and promotes the activation and proliferation of hepatic stellate cells, accelerating liver fibrosis. Furthermore, by sustaining an inflammatory state, impacts the survival and proliferation of cancer cells. This review comprehensively summarizes the dual role of pyroptosis in liver diseases and its therapeutic strategies, offering new theoretical foundations and practical guidance for preventing and treating of liver diseases.
Microbial-based natural products as potential inhibitors targeting DNA gyrase B of Mycobacterium tuberculosis: an in silico study
Authors: Elsaman Tilal , Mohamed Magdi Awadalla , Mohamed Malik Suliman , Eltayib Eyman Mohamed , Abdalla Abualgasim Elgaili
Published: January 2025

Introduction

Since the emergence of Mycobacterium tuberculosis (MBT) strains resistant to most currently used anti-tubercular drugs, there has been an urgent need to develop efficient drugs capable of modulating new therapeutic targets. Mycobacterial DNA gyrase is an enzyme that plays a crucial role in the replication and transcription of DNA in MBT. Consequently, targeting this enzyme is of particular interest in developing new drugs for the treatment of drug-resistant tuberculosis, including multidrug-resistant tuberculosis (MDR-TB) and extensively drug-resistant tuberculosis (XDR-TB).

Methods

In the present study, multiple computational tools were adopted to screen a microbial-based natural products database (NPAtlas) for potential inhibitors of the ATPase activity of MBT DNA gyrase.

Results and discussion

Twelve hits were initially identified as the top candidates based on their docking scores (ranging from −9.491 to −10.77 kcal/mol) and binding free energies (−60.37 to −73.21 kcal/mol). Following this, computational filters, including ADME-T profiling and pharmacophore modeling, were applied to further refine the selection. As a result, three compounds 1-Hydroxy-D-788-7, Erythrin, and Pyrindolol K2 emerged as the most promising, exhibiting favorable drug-like properties. Notably, 1-Hydroxy-D-788-7, an anthracycline derivative, demonstrated superior binding affinity in molecular dynamics simulations. The RMSD values, ranging from 1.7 to 2.5 Å, alongside RMSF analysis and a detailed evaluation of the established interaction forces, revealed that 1-Hydroxy-D-788-7 was the strongest binder to Mycobacterial DNA Gyrase B. The stable binding and favorable interaction profile highlighted 1-Hydroxy-D-788-7 as a top hit. These comprehensive computational findings strongly support the potential of 1-Hydroxy-D-788-7 as an effective anti-TB lead compound, warranting further experimental validation to confirm its therapeutic efficacy.
Multi-step pre-treatment of rice husk for fractionation of components including silica
Authors: Ishida Shinnosuke , Kudo Shinji , Asano Shusaku , Hayashi Jun-ichiro
Published: January 2025

Introduction

Rice husk, a widely available agricultural by-product lignocellulosic biomass, is a promising and sustainable feedstock for organic and inorganic chemicals due to the rich silica content. However, its current application is largely limited, with most being incinerated as waste. This study introduces a novel multi-step pre-treatment process to fractionate these components efficiently, enabling their comprehensive valorization.

Methods

The process begins with hydrothermal treatment, selectively extracting hemicellulose while preserving the structural integrity of other components. This is followed by an organosolv treatment using ethanol/water mixture, optimized to dissolve and extract organosolv lignin effectively. Subsequently, alkaline aqueous solution treatment under nitrogen atmosphere facilitates the recovery of silica as sodium silicate, a valuable industrial precursor. To ensure high-purity cellulose recovery, the final step employs alkaline hydrothermal processing under oxygen, achieving effective lignin depolymerization and removal.

Results and discussion

Each step was carefully optimized, considering parameters such as temperature, solvent composition, and reaction time, to enhance selectivity and yield. Notably, this method reduces environmental negative impact by avoiding the use of acids while utilizing renewable solvents. The sequential application of these treatments resulted in separation exceeding 97% for hemicellulose, lignin, and silica, leaving high-purity cellulose with the loss of 22.8 wt%. Hemicellulose, organosolv lignin, and silica in the removed fractions were 66.5, 78.1, and 77.5 wt% at the first, second, and third treatments, respectively.
Numerical research on the impact of horizontal freezing on existing underground structures in shield reception
Authors: Hong Zequn , Fu Shuoren , Wu Yuanhao , Zhang Yong , Lu Lu
Published: January 2025

The freezing construction of the end of the new shield tunnel has a mechanical impact on the surrounding structures. Few studies exist on the reasonable range of soil reinforcement near the shield tunnel and the influence of frost heave on the existing structure during the freezing process. To explore the influence of horizontal freezing of a proposed tunnel on existing underground structures, a three-dimensional numerical model of ‘thermal-mechanical’ coupling was established based on the horizontal freezing reinforcement project applied in a shield receiving end, and the temperature field distribution characteristics of different freezing stages were obtained. After confirming that the frozen wall had reached the design thickness based on the temperature field, the mechanical effects of frost heave on the existing structures were investigated, including the side tunnel, the upper subway tunnel, and the end diaphragm wall. The results showed that the frost heave pressure was mainly distributed in the structure near the freezing zone, while the structure far away from the freezing zone was relatively less affected by frost heave. By defining the strong and weak influence sections, we introduced the influence coefficient η to quantify the frost heave effect on the side tunnel. Under the condition that the thickness of the frozen wall was constant, the strong influence range of the side tunnel reached 1.4 times the freezing length of the proposed tunnel at a distance of 3.6 times the frozen wall thickness. The farther the clearance between the side tunnel and the proposed tunnel was, the smaller the influence coefficient η was, and the shorter the strong influence section was. The frost-heaving effect generated by freezing at the shield tunnel receiving end was more pronounced along the diameter of the freezing pipes, while axial release strength was comparatively weaker. This research can provide a reference for evaluating the influence of freezing construction on adjacent underground structures.
Role of plasma metabolome in mediating the effect of plasma lipidome on NAFLD: a Mendelian randomization study
Authors: Zheng Zhuyuan , Yang Shaojie , Dai Wanlin , Sun Yang , Wang Jingnan , Zhang Xiaolin , Zheng Yiming , Kong Jing
Published: January 2025

Background

This study explored the causal connection among the plasma lipidome, nonalcoholic fatty liver disease (NAFLD), and potential metabolome mediators through Mendelian randomization (MR).

Methods

We obtained summary statistics for 179 plasma lipidome traits (N = 7,174), 1,400 plasma metabolome traits (N = 8,299), and one NAFLD trait from publicly available genome-wide association studies. A two-sample MR analysis was conducted to infer causality. Additionally, multiple sensitivity analyses were conducted to assess the heterogeneity, horizontal pleiotropy, and robustness of the MR findings. MetaboAnalyst 6.0 was used for the pathway analysis of the identified lipids and metabolites. Furthermore, we used mediation analysis to assess whether the effect of plasma lipidome on NAFLD was mediated by plasma metabolome.

Results

The MR analysis predicted a genetically determined causal relationship between plasma lipidomes and NAFLD. No compelling proof was found that genetically predicted NAFLD influenced the risk of the five plasma lipidomes mentioned earlier. Based on established causal relationships between lipids and metabolites, we identified that eight metabolic pathways are closely associated with NAFLD. Our mediation analysis revealed six mediation relationships, indicating the causal pathway from plasma lipids to NAFLD mediated by five specific metabolites. No potential pleiotropy was found in the sensitivity analysis.

Conclusions

In summary, our study identified causal relationships between plasma lipidomes, plasma metabolomes, and NAFLD. Certainly, the impact of plasma lipidomes on NAFLD is not limited to plasma metabolomes, indicating a need to further investigate into other possible mediators. These identified factors may become new biomarkers of the NAFLD contributing to its prevention, diagnosis, and treatment.
Effects of practical models of low-volume high-intensity interval training on glycemic control and insulin resistance in adults: a systematic review and meta-analysis of randomized controlled studies
Authors: Lu Yining , Baker Julien S. , Ying Shanshan , Lu Yichen
Published: January 2025

Objectives

The aim of this systematic review and meta-analysis was to investigate the effects of practical models of low-volume high-intensity interval training protocols (LV-HIIT) on glucose control and insulin resistance compared with moderate-intensity continuous training (MICT) protocols and no-exercise controls (CON).

Methods

Four databases (PubMed, Web of Science, Scopus, and Cochrane Library) were searched for randomized controlled studies conducted using LV-HIIT interventions (HIIT/SIT protocols involving ≤ 15 min of intense training, within a session lasting ≤ 30 min; < 30 s all-out sprint for SIT additionally). The inclusion criteria required glucose and insulin resistance markers to be evaluated pre- and post-intervention among adults who were not trained athletes.

Results

As a result, twenty studies were included, and meta-analyses were conducted using sixteen studies employing HIIT protocols. Compared with CON, LV-HIIT with reduced intensity and extended interval duration significantly improved fasting glucose (FPG) (mean difference (MD) in mg/dL=-16.63; 95% confidence interval (CI): -25.30 to -7.96; p<0.001) and HbA1c (MD=-0.70; 95% CI: -1.10 to -0.29; p<0.001). Greater improvements were found in participants who were overweight/obese or having type 2 diabetes (T2D). FPG decreased with every additional second of interval duration (β;=-0.10; 95% CI: -0.19 to -0.00; p=0.046). FPI (β;=-0.65; 95% CI: -1.27 to -0.02; p=0.042) and HOMA-IR (β;=-0.22; 95% CI: -0.36 to -0.09; p=0.001) decreased with every additional minute of interval duration per session. HOMA-IR also decreased with every additional minute of weekly interval duration (β;=-0.06; 95%CI: -0.08 to -0.04; p<0.001). Compared with MICT, LV-HIIT was more effective in improving insulin sensitivity (SMD=-0.40; 95%CI: -0.70 to -0.09; p=0.01), but there were no differences in FPG, FPI, HbA1c or HOMA-IR (p>0.05). The effect of LV-HIIT on FPI was larger compared with MICT among individuals who lost weight.

Conclusion

Conclusively, a practical model of LV-HIIT with reduced intensity and extended interval was effective in improving glucose control and its effects were similar to MICT. Greater improvements were found in individuals with overweight/obesity or T2D in protocols with longer intervals or accumulated interval duration per session/week. More large-scale, randomized controlled studies with similar intervention protocols in a wide range of population are warranted to confirm these important results.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42024516594.
Uncovering the drivers, impacts, and urgent solutions to soil erosion in the Ethiopian Highlands: a global perspective on local challenges
Authors: Teku Degfie , Derbib Tarekegn
Published: January 2025

Soil erosion in the Ethiopian Highlands is a critical environmental challenge, driven by both natural and anthropogenic factors such as deforestation, overgrazing, unsustainable agricultural practices, and climatic variability. Addressing this issue is essential for safeguarding the region’s agricultural productivity, biodiversity, and socio-economic stability. This review aims to synthesize and evaluate existing research on the extent, impacts, and mitigation strategies of soil erosion across the Ethiopian Highlands, with a focus on informing sustainable land management practices and policy interventions. The review draws on findings from 129 peer-reviewed studies and reports, providing a comprehensive national-scale assessment of soil erosion. The selected literature encompasses empirical field studies, remote sensing analyses, and policy evaluations. The reviewed literature highlights severe soil degradation, with erosion rates in some areas exceeding 200 tonnes per hectare annually, resulting in the loss of over 1.5 billion tonnes of topsoil each year. This degradation reduces agricultural productivity by 5%–10% annually and causes economic losses exceeding $1 billion, approximately 2% of Ethiopia’s GDP. The impacts of soil erosion extend to water quality, biodiversity, and rural livelihoods. Mitigation strategies such as terracing, stone bunds, and agroforestry have demonstrated potential to reduce soil loss by up to 60%, stabilize slopes, and enhance soil organic matter. This review underscores the urgency of integrated and scalable approaches to combat soil erosion, combining sustainable land management practices, supportive policy frameworks, and active community engagement.
Uncertainty in soil gas permeability measurements
Authors: Feng Lingxia , Hu Junguo , Jiang Junjie
Published: January 2025

Introduction

Soil gas permeability is critical to the study of soil pore structure, soil gas transport, and crop growth.

Methods

In this paper, a pressure decay method is proposed to calculate soil gas permeability based on the law of conservation of mass, which is measured and compared with the steady-state method in a variety of soils, including compacted soils and soils with different moisture contents. The applicability of the two methods and the effects of compaction and water content on soil gas permeability were explored.

Results

The experimental results show that in low-permeability soils, there is a bias in the measured values of the steady-state method. In contrast, the results calculated based on the pressure decay method are more accurate. Increasing the water content of the soil or compacting the soil results in a 20%–88% or 63%–93% decrease in soil gas permeability, respectively, with the degree of decrease correlating with the viscosity of the medium.

Discussion

The findings show that calculating soil gas permeability based on the pressure decay method helps compensate for the inaccuracy of the steady-state method in measuring results in low-permeability soils. This leads to a better evaluation of soil aeration conditions, which, in turn, serves environmental, agricultural, and ecological research.
Carbon reduction effects of government digital attention
Authors: Hu Rong , Song Kaiyi
Published: January 2025

In the digital economy era, increasing government’s adoption and attention to digital technology is not only conducive to accelerating the improvement of governance capacity, but also an important measure to achieve green economic development. This paper uses text analysis to measure the government digital attention at the city level, and then uses panel data econometric models to estimate the impact of government digital attention on carbon emissions reduction. The findings reveal that government digital attention can significantly reduce carbon dioxide emissions by improving the government’s low-carbon governance, strengthening the public’s low-carbon attention, and encouraging the enterprises’ low-carbon transformation. Further, government digital attention mainly reduces carbon dioxide from direct energy consumption, transportation and electricity product. The carbon reduction effect of government digital attention is also affected by degree of marketization, and the high degree of marketization helps to reinforce the effect. Moreover, there is spatial heterogeneity in the effect, it is more significant in the eastern region. Our conclusions are then of important implications for promoting China’s carbon dioxide reduction and achieving high-quality sustainable development.
Carbon finance for forest resilience in California
Authors: Elias Micah , Yackulic Ethan , Duffy Katharyn , Saksa Phil , Sanchez Daniel L. , Pevzner Nicholas , Plumb Spencer , Dyszynski Jillian , Bracer Carina
Published: January 2025

Restoring a resilient forest structure in California’s American River watershed in the Sierra Nevada mountains can generate up to $6,100 per acre in carbon revenue from increased forest carbon and market-ready biomass utilization pathways, potentially fully funding forest management. Employing a dynamic performance benchmark (DPB) framework, this study models the impacts of restoring resilience to high-risk forests via forest thinning followed by prescribed fire. These practices show an initial carbon cost, but ultimately reduce carbon emissions from wildfire and increase carbon storage compared to a no-treatment counterfactual scenario by 35 tCO2e per acre on average, with market-ready biomass utilization pathways adding another 6–23 tCO2e average benefit per acre. Treatments enhance carbon stability by shifting carbon storage from dense, overcrowded small trees to more dispersed, fire-resilient large trees and reduces fire severity (flame length) by 78% five years post-treatment. Compared to pretreatment levels, treatment decreases the number of trees on the landscape by 74% while increasing carbon storage by 6% at the end of the 25-year simulation. To reduce investor risk into nature-based solutions focused on increasing carbon stability in fire adapted forests and generate carbon revenue from fuel treatments, accurate predictive tools are needed. To maximize certainty of carbon benefits, landscape level treatments, DPBs, and ex-post carbon crediting will be critical. This study shows that carbon revenue from traditional markets or novel carbon contribution programs can help close the funding gap for forest restoration in California while underscoring the need for innovative conservation finance mechanisms to support ecosystem resilience and climate mitigation goals.
A new name for an old problem—Colletotrichum cigarro is the cause of St John’s wilt of Hypericum perforatum
Authors: Kreth Lana-Sophie , Damm Ulrike , Götz Monika
Published: January 2025

A major problem for St John’s wort (Hypericum perforatum) is St John’s wilt, which can lead to reduced crop yields and even complete crop losses. In the past, the pathogen was referred to as Colletotrichum gloeosporioides or occasionally as Colletotrichum cf. gloeosporioides based on morphology. Although a strain from this host had been re-identified as C. cigarro in taxonomic studies, there is uncertainty about the identity of the St John’s wilt pathogen, which is generally still addressed as C. gloeosporioides in applied science. In a multi-locus [internal transcribed spacer (ITS), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), actin (ACT), and glutamine synthetase (GS)] analysis of the C. gloeosporioides species complex, all isolates obtained from newly collected symptomatic H. perforatum stems and seeds from Germany and Switzerland were identified as C. cigarro. Although they belonged to the same haplotype, the morphology of the isolates was very variable. Pathogenicity tests demonstrated that only C. cigarro strains from H. perforatum cause symptoms on H. perforatum, whereas other Colletotrichum species tested only caused latent infection of H. perforatum.
Identification and preliminary validation of biomarkers associated with mitochondrial and programmed cell death in pre-eclampsia
Authors: Lin Rong , Weng XiaoYing , Lin Liang , Hu XuYang , Liu ZhiYan , Zheng Jing , Shen FenFang , Li Rui
Published: January 2025

Background

The involvement of mitochondrial and programmed cell death (mtPCD)–related genes in the pathogenesis of pre-eclampsia (PE) remains inadequately characterized.

Methods

This study explores the role of mtPCD genes in PE through bioinformatics and experimental approaches. Differentially expressed mtPCD genes were identified as potential biomarkers from the GSE10588 and GSE98224 datasets and subsequently validated. Hub genes were determined using support vector machine, least absolute shrinkage and selection operator, and Boruta based on consistent expression profiles. Their performance was assessed through nomogram and artificial neural network models. Biomarkers were subjected to localization, functional annotation, regulatory network analysis, and drug prediction. Clinical validation was conducted via real-time quantitative polymerase chain reaction (RT-qPCR), immunofluorescence, and Western blot.

Results

Four genes [solute carrier family 25 member 5 (SLC25A5), acyl-CoA synthetase family member 2 (ACSF2), mitochondrial fission factor (MFF), and phorbol-12-myristate-13-acetate–induced protein 1 (PMAIP1)] were identified as biomarkers distinguishing PE from normal controls. Functional analysis indicated their involvement in various biological pathways. Immune analysis revealed associations between biomarkers and immune cell activity. A regulatory network was informed by biomarker expression and database predictions, in which KCNQ1OT1 modulates ACSF2 expression via hsa-miR-200b-3p. Drug predictions, including clodronic acid, were also proposed. Immunofluorescence, RT-qPCR, and Western blot confirmed reduced expression of SLC25A5, MFF, and PMAIP1 in PE, whereas ACSF2 was significantly upregulated.

Conclusion

These four mtPCD-related biomarkers may play a pivotal role in PE pathogenesis, offering new perspectives on the disease’s diagnostic and mechanistic pathways.
Single-cell RNA sequencing and AlphaFold 3 insights into cytokine signaling and its role in uveal melanoma
Authors: Sun Hongyan , Li Cunzi , Pu Zuhui , Lu Ying , Wu Zijing , Zhou Lan , Lin Hongzhan , Wang Yumo , Zi Tao , Mou Lisha , Yang Ming-ming
Published: January 2025

Background

Uveal melanoma (UVM) is a form of eye cancer with a poor prognosis, particularly in metastatic patients. This study aimed to elucidate the cellular heterogeneity within UVM and identify prognostic biomarkers.

Methods

We performed single-cell RNA sequencing (scRNA-seq) on primary and metastatic UVM samples. A UVM-specific gene signature was constructed using LASSO regression and validated via ROC curve analysis in the TCGA-UVM and GSE84976 cohorts. AlphaFold 3 was used to predict the 3D structures of key proteins. T-cell populations were analyzed using pseudotime trajectory mapping and interaction network visualization. CRISPR-Cas9 screening analysis was conducted to identify hub genes and cytokine pathways that may serve as therapeutic targets. Additionally, we constructed the Dictionary of Immune Responses to Cytokines at single-cell resolution to evaluate cytokine signatures.

Results

ScRNA-seq revealed five major cell types within UVMs and subdivided them into seven distinct subtypes. Cytokine signaling analysis revealed differential expression of cytokine signaling in immune-related genes (CSIRGs) across these subtypes in primary and metastatic tumors. The UVM-specific gene signature demonstrated high predictive accuracy in ROC curve analysis and was associated with overall survival in Kaplan–Meier survival analyses. Additionally, AlphaFold 3 predicted the 3D structures of key proteins with high confidence. T-cell population analysis revealed complex developmental pathways and interaction networks in UVM. Myeloid-derived suppressor cells (MDSCs) were found to be increased in metastatic UVM, correlating with the enrichment of GM-CSF. CRISPR-Cas9 screening analysis identified hub genes and cytokine pathways with low gene effect scores across cell lines, indicating their potential importance in UVM.

Conclusion

This study identified critical cellular subtypes and prognostic biomarkers in UVM, shedding light on targeted therapies. The insights into cytokine signaling and T-cell dynamics within the UVM microenvironment provide a foundation for developing personalized therapeutic strategies to improve patient outcomes.
Efficacy and safety of PD-1 inhibitors as second-line treatment for advanced squamous esophageal cancer: a systematic review and network meta-analysis with a focus on PD-L1 expression levels
Authors: Yang Fei , Dan Min , Shi Jindan , Fan Ling , Zhang Haoluo , Jian Tiantian , Lei Kelu , Wang Yue , Xin Juan , Yu Zhigang , Chen Wei
Published: January 2025

Background

PD-1 inhibitors have shown promising efficacy in enhancing OS and AEs as second-line therapies for patients with advanced esophageal squamous cell carcinoma (ESCC). However, there remains no clear consensus on which PD-1 inhibitor provides the best balance between efficacy and safety. To address this key issue in the second-line treatment of ESCC, we conducted a network meta-analysis (NMA) with a focus on OS benefits, particularly in patients with different levels of PD-L1 expression.

Methods

A systematic search of relevant literature was conducted in Web of Science, Embase, PubMed, and Cochrane Library, covering publications from the inception of these database to June 2024. The evaluated endpoints included OS, progression-free survival (PFS), objective response rate (ORR), AEs, and Grade ≥ 3 adverse events (Grade ≥ 3 AEs). A systematic review and Bayesian network meta-analysis were performed to assess the efficacy and safety of various immunotherapy regimens in patients with advanced ESCC. To ensure transparency, novelty, and reliability, this study was prospectively registered in the systematic review registry (CRD42024540581).

Results

Five randomized controlled trials (RCTs), encompassing 2,078 patients and six treatment regimens, were included in this study. Among advanced ESCC patients not selected based on PD-L1 expression, Sintilimab demonstrated the greatest OS benefit (HR = 0.70, 95% CI: 0.50-0.98). Camrelizumab showed the most favorable improvement in PFS compared to chemotherapy (HR = 0.64, 95% CI: 0.47-0.87) and also achieved the best ORR benefit (OR = 3.72, 95% CI: 1.98-6.99). In terms of safety, Nivolumab (OR = 0.10, 95% CI: 0.05-0.19) and Tislelizumab (OR = 0.18, 95% CI: 0.10-0.33) exhibited significant safety advantages over chemotherapy concerning AEs. Moreover, Nivolumab (OR = 0.13, 95% CI: 0.08-0.20) was associated with a markedly lower risk of Grade ≥ 3 AEs compared to chemotherapy. Subgroup analysis based on PD-L1 expression revealed that Tislelizumab (HR = 0.53, 95% CI: 0.37-0.76) offered the greatest OS benefit for patients with PD-L1 ≥ 10%, while Camrelizumab (HR = 0.71, 95% CI: 0.57-0.89) was the most likely regimen to provide an OS advantage for patients with PD-L1 < 10%.

Conclusion

Compared to chemotherapy, PD-1 inhibitors may provide improved survival outcomes for patients with advanced ESCC. Among patients not selected based on PD-L1 expression, Sintilimab is most likely to deliver the best survival benefit. For patients with PD-L1 expression ≥ 10%, Tislelizumab is expected to offer the greatest efficacy, while Camrelizumab appears to be the most effective for those with PD-L1 < 10%.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024540581.
Regulation of viral replication by host restriction factors
Authors: Lin Ying , Zhu Yun , Jing Ling , Lei Xiaobo , Xie Zhengde
Published: January 2025

Viral infectious diseases, caused by numerous viruses including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A virus (IAV), enterovirus (EV), human immunodeficiency virus (HIV), hepatitis B virus (HBV), and human papillomavirus (HPV), pose a continuous threat to global health. As obligate parasites, viruses rely on host cells to replicate, and host cells have developed numerous defense mechanisms to counteract viral infection. Host restriction factors (HRFs) are critical components of the early antiviral response. These cellular proteins inhibit viral replication and spread by impeding essential steps in the viral life cycle, such as viral entry, genome transcription and replication, protein translation, viral particle assembly, and release. This review summarizes the current understanding of how host restriction factors inhibit viral replication, with a primary focus on their diverse antiviral mechanisms against a range of viruses, including SARS-CoV-2, influenza A virus, enteroviruses, human immunodeficiency virus, hepatitis B virus, and human papillomavirus. In addition, we highlight the crucial role of these factors in shaping the host-virus interactions and discuss their potential as targets for antiviral drug development.
Identification and validation of immune and diagnostic biomarkers for interstitial cystitis/painful bladder syndrome by integrating bioinformatics and machine-learning
Authors: Zhou Tao , Zhu Can , Zhang Wei , Wu Qiongfang , Deng Mingqiang , Jiang Zhiwei , Peng Longfei , Geng Hao , Tuo Zhouting , Zou Ci
Published: January 2025

Background

The etiology of interstitial cystitis/painful bladder syndrome (IC/BPS) remains elusive, presenting significant challenges in both diagnosis and treatment. To address these challenges, we employed a comprehensive approach aimed at identifying diagnostic biomarkers that could facilitate the assessment of immune status in individuals with IC/BPS.

Methods

Transcriptome data from IC/BPS patients were sourced from the Gene Expression Omnibus (GEO) database. We identified differentially expressed genes (DEGs) crucial for gene set enrichment analysis. Key genes within the module were revealed using weighted gene co-expression network analysis (WGCNA). Hub genes in IC/BPS patients were identified through the application of three distinct machine-learning algorithms. Additionally, the inflammatory status and immune landscape of IC/BPS patients were evaluated using the ssGSEA algorithm. The expression and biological functions of key genes in IC/BPS were further validated through in vitro experiments.

Results

A total of 87 DEGs were identified, comprising 43 up-regulated and 44 down-regulated genes. The integration of predictions from the three machine-learning algorithms highlighted three pivotal genes: PLAC8 (AUC: 0.887), S100A8 (AUC: 0.818), and PPBP (AUC: 0.871). Analysis of IC/BPS tissue samples confirmed elevated PLAC8 expression and the presence of immune cell markers in the validation cohorts. Moreover, PLAC8 overexpression was found to promote the proliferation of urothelial cells without affecting their migratory ability by inhibiting the Akt/mTOR/PI3K signaling pathway.

Conclusions

Our study identifies potential diagnostic candidate genes and reveals the complex immune landscape associated with IC/BPS. Among them, PLAC8 is a promising diagnostic biomarker that modulates the immune response in patients with IC/BPS, which provides new insights into the future diagnosis of IC/BPS.
Recent trends in research on the role of cholesterol in leukemia: a bibliometric and visualization study
Authors: Lv Huijuan , Lu Ke , Wang Ximing , Zhang Yanfang , Zhuang Mengqi , Li Jing , Su Keli , Gao Wen
Published: January 2025

Background

Cholesterol metabolism significantly impacts leukemia pathophysiology, affecting tumor cell survival, proliferation, and treatment resistance. This study employs bibliometric analysis and visualization techniques to investigate research trends regarding cholesterol in leukemia and identify key hotspots.

Methods

A systematic search of the Web of Science Core Collection was performed for literature published from 1980 to 2024 using the keywords “cholesterol” and “leukemia,” yielding 1,220 articles. Bibliometric tools like VOSviewer and CiteSpace were utilized for visualizing citation networks and thematic clusters.

Results

The analysis comprised 1,220 publications produced by 6,771 researchers across 1,756 institutions in 68 countries, published in 576 journals with 5,903 unique keywords. Publication output demonstrated a significant rise from 1980 to 2024, peaking in 2022. The United States led in total publications (381) and citations (40,462), followed by China (137 articles) and Japan (102). Notably, U.S. publications had lower average citations than those from Germany and Brazil. Key institutions included the University of São Paulo, Medical College of Wisconsin, and National Cancer Institute, with prominent authors such as Maranhao Raul C. and Girotti Albert W. The journal Cancer Research was the most prolific, while Blood had the highest citation frequency. Major research areas encompassed molecular biology, immunology, and medicine, focusing on the cholesterol-leukemia link. Keyword co-occurrence and co-citation analyses reveal increasing interest in topics like STAT3, multidrug resistance, and treatment interactions. These insights suggest crucial areas for further research.

Discussion

Our findings emphasize cholesterol’s significance in leukemia, indicating its potential as a therapeutic target. Further exploration at the intersection of cholesterol metabolism and leukemia requires multidisciplinary collaboration.

Conclusion

This bibliometric study delineates the evolving research landscape on cholesterol’s role in leukemia, pinpointing emerging trends and future research directions to inform effective therapeutic strategies.
Combination chemotherapy with sintilimab for treatment of a male patient with primary pulmonary choriocarcinoma: a case report and literature review
Authors: Liang Xiaojing , Xu Guoqing , Zhang Jisong , Xu Li , Dong Liangliang , Wang Xiaoyue , Han Weidong , Chen Enguo
Published: January 2025

Primary pulmonary choriocarcinoma (PPC) is an extremely rare malignant cancer in men with no clinical guidelines for the treatment. Cytotoxic chemotherapy has a limited effect on the prognosis of PPC. Recently, immune checkpoint inhibitors (ICIs) have shown promising treatment effectiveness. A literature review revealed that a combination of chemotherapy and ICIs could prolong the survival time of PPC patients. Herein, we report a 67-year-old man with a cough, expectoration, and blood in the sputum, presenting with a mass in the lower lobe of the right lung. The hematoxylin and eosin staining and immunohistochemical profile of the primary lesion showed features of choriocarcinoma, accompanied by elevations in serum human chorionic gonadotropin (HCG) levels. Programmed death-ligand 1 (PD-L1) expression was positive (70%) in the 22C3 assay. He received a combination of cisplatin, etoposide, paclitaxel, and sintilimab. Four months after the treatment began, chest computed tomography (CT) showed significant mass reduction. Therefore, ICIs may be a promising therapy option for patients with PPC.
Immunometabolism of Tregs: mechanisms, adaptability, and therapeutic implications in diseases
Authors: Lu Yuming , Wang Yifan , Ruan Tiantian , Wang Yihan , Ju Linling , Zhou Mengya , Liu Luyin , Yao Dengfu , Yao Min
Published: January 2025

Immunometabolism is an emerging field that explores the intricate interplay between immune cells and metabolism. Regulatory T cells (Tregs), which maintain immune homeostasis in immunometabolism, play crucial regulatory roles. The activation, differentiation, and function of Tregs are influenced by various metabolic pathways, such as the Mammalian targets of rapamycin (mTOR) pathway and glycolysis. Correspondingly, activated Tregs can reciprocally impact these metabolic pathways. Tregs also possess robust adaptive capabilities, thus enabling them to adapt to various microenvironments, including the tumor microenvironment (TME). The complex mechanisms of Tregs in metabolic diseases are intriguing, particularly in conditions like MASLD, where Tregs are significantly upregulated and contribute to fibrosis, while in diabetes, systemic lupus erythematosus (SLE), and rheumatoid arthritis (RA), they show downregulation and reduced anti-inflammatory capacity. These phenomena suggest that the differentiation and function of Tregs are influenced by the metabolic environment, and imbalances in either can lead to the development of metabolic diseases. Thus, moderate differentiation and inhibitory capacity of Tregs are critical for maintaining immune system balance. Given the unique immunoregulatory abilities of Tregs, the development of targeted therapeutic drugs may position them as novel targets in immunotherapy. This could contribute to restoring immune system balance, resolving metabolic dysregulation, and fostering innovation and progress in immunotherapy.
LFN-YOLO: precision underwater small object detection via a lightweight reparameterized approach
Authors: Liu Mingxin , Wu Yujie , Li Ruixin , Lin Cong
Published: January 2025

Underwater object detection plays a significant role in fisheries resource assessment and ecological environment protection. However, traditional underwater object detection methods struggle to achieve accurate detection in complex underwater environments with limited computational resources. This paper proposes a lightweight underwater object detection network called LightFusionNet-YOLO (LFN-YOLO). First, we introduce the reparameterization technique RepGhost to reduce the number of parameters while enhancing training and inference efficiency. This approach effectively minimizes precision loss even with a lightweight backbone network. Then, we replaced the standard depthwise convolution in the feature extraction network with SPD-Conv, which includes an additional pooling layer to mitigate detail loss. This modification effectively enhances the detection performance for small objects. Furthermore, We employed the Generalized Feature Pyramid Network (GFPN) for feature fusion in the network's neck, enhancing the network's adaptability to features of varying scales. Finally, we design a new detection head, CLLAHead, which reduces computational costs and strengthens the robustness of the model through cross-layer local attention. At the same time, the DFL loss function is introduced to reduce regression and classification errors. Experiments conducted on public datasets, including URPC, Brackish, and TrashCan, showed that the mAP@0.5 reached 74.1%, 97.5%, and 66.2%, respectively, with parameter sizes and computational complexities of 2.7M and 7.2 GFLOPs, and the model size is only 5.9 Mb. Compared to mainstream vision models, our model demonstrates superior performance. Additionally, deployment on the NVIDIA Jetson AGX Orin edge computing device confirms its high real-time performance and suitability for underwater applications, further showcasing the exceptional capabilities of LFN-YOLO.
Evaluating ChatGPT’s diagnostic potential for pathology images
Authors: Ding Liya , Fan Lei , Shen Miao , Wang Yawen , Sheng Kaiqin , Zou Zijuan , An Huimin , Jiang Zhinong
Published: January 2025

Background

Chat Generative Pretrained Transformer (ChatGPT) is a type of large language model (LLM) developed by OpenAI, known for its extensive knowledge base and interactive capabilities. These attributes make it a valuable tool in the medical field, particularly for tasks such as answering medical questions, drafting clinical notes, and optimizing the generation of radiology reports. However, keeping accuracy in medical contexts is the biggest challenge to employing GPT-4 in a clinical setting. This study aims to investigate the accuracy of GPT-4, which can process both text and image inputs, in generating diagnoses from pathological images.

Methods

This study analyzed 44 histopathological images from 16 organs and 100 colorectal biopsy photomicrographs. The initial evaluation was conducted using the standard GPT-4 model in January 2024, with a subsequent re-evaluation performed in July 2024. The diagnostic accuracy of GPT-4 was assessed by comparing its outputs to a reference standard using statistical measures. Additionally, four pathologists independently reviewed the same images to compare their diagnoses with the model’s outputs. Both scanned and photographed images were tested to evaluate GPT-4’s generalization ability across different image types.

Results

GPT-4 achieved an overall accuracy of 0.64 in identifying tumor imaging and tissue origins. For colon polyp classification, accuracy varied from 0.57 to 0.75 in different subtypes. The model achieved 0.88 accuracy in distinguishing low-grade from high-grade dysplasia and 0.75 in distinguishing high-grade dysplasia from adenocarcinoma, with a high sensitivity in detecting adenocarcinoma. Consistency between initial and follow-up evaluations showed slight to moderate agreement, with Kappa values ranging from 0.204 to 0.375.

Conclusion

GPT-4 demonstrates the ability to diagnose pathological images, showing improved performance over earlier versions. Its diagnostic accuracy in cancer is comparable to that of pathology residents. These findings suggest that GPT-4 holds promise as a supportive tool in pathology diagnostics, offering the potential to assist pathologists in routine diagnostic workflows.
Navigating the potential and pitfalls of large language models in patient-centered medication guidance and self-decision support
Authors: Aydin Serhat , Karabacak Mert , Vlachos Victoria , Margetis Konstantinos
Published: January 2025

Large Language Models (LLMs) are transforming patient education in medication management by providing accessible information to support healthcare decision-making. Building on our recent scoping review of LLMs in patient education, this perspective examines their specific role in medication guidance. These artificial intelligence (AI)-driven tools can generate comprehensive responses about drug interactions, side effects, and emergency care protocols, potentially enhancing patient autonomy in medication decisions. However, significant challenges exist, including the risk of misinformation and the complexity of providing accurate drug information without access to individual patient data. Safety concerns are particularly acute when patients rely solely on AI-generated advice for self-medication decisions. This perspective analyzes current capabilities, examines critical limitations, and raises questions regarding the possible integration of LLMs in medication guidance. We emphasize the need for regulatory oversight to ensure these tools serve as supplements to, rather than replacements for, professional healthcare guidance.
Insights into the gut microbiota characteristics between the organic and traditional feeding chickens based on amplicon and metagenomic sequencing
Authors: Zhang Wenzhou , Jian Xiaoru , Ding Siqi , Chang Jiamin , Ji Shouping , Chi Yulang
Published: January 2025

Intestinal microorganisms play a crucial role in chicken health and production performance, especially in the research of traditional and organic feeding methods. The intestinal contents of organic and feed chickens were analyzed by 16S rRNA gene and metagenome technology. The results showed that the microbial diversity of organic chickens was significantly higher than that of the feed chickens, especially the key microorganisms, such as Enterococcus, were more abundant in organic chickens. The functional analysis of metagenome revealed the significant difference in the metabolic function of intestinal microorganisms between them. The present study provides new insights into the gut microbiota characteristics of the organic and feed chicken based on amplicon and metagenomic sequencing. Our results are helpful to fully illustrate the effects of different feeding methods on intestinal microorganisms in chickens and can offer a more scientific basis for chicken production management.