bluuebunny/crossref_metadata_2025 huggingface dataset:
Diversity and functional traits based indigenous rhizosphere associated phosphate solubilizing bacteria for sustainable production of rice
Authors: Rasul Maria , Yahya Mahreen , Suleman Muhammad , Hakim Sughra , Mirza Babur S. , Mirza Muhammad Sajjad , Reitz Thomas , Tarkka Mika Tapio , Yasmin Sumera
Published: December 2024

Introduction

Rice, particularly Basmati rice, holds significant global importance as a staple food. The indiscriminate use of phosphate-based fertilizers during rice production has led to high residual levels of these chemicals in soil, impacting soil health and fertility. This study aimed to address this challenge by investigating the potential of phosphate solubilizing bacteria (PSB) in improving soil fertility and boosting the growth of Basmati rice.

Methods

Using amplicon-based 16S rDNA sequencing, bacterial isolation and cultivation, conducting greenhouse and field experiments, and PSB localization, we optimized the search for PSB inoculants to enhance Basmati rice growth.

Results and discussion

Rice rhizosphere prokaryote communities showed significant differences in microbial diversity and composition between between basmati and non-basmati rice cultivated areas. Dominant bacterial phyla included Proteobacteria, Acidobacteria, Actinobacteria, and Firmicutes, with Actinobacteria and Proteobacteria playing a crucial role in nutrient recycling. Isolation and optimization of PSB strains, including Acinetobacter sp. MR5 and Pseudomonas sp. R7, were carried out and soil microcosm studies confirmed their efficacy in increasing soil available phosphorus concentration. Response surface methodology revealed the relative importance of factors such as pH, inoculum density and incubation temperature in maximising phosphate solubilization. Microplot experiments demonstrated the effectiveness of optimized PSB inoculants in promoting Basmati rice growth, with significant increases in plant height, tiller number, biomass, and grain yield compared to uninoculated controls. A consortium of PSB proved superior to single-strain inoculants, even with reduced chemical fertilizer application. Field trials at several rice growing sites confirmed the positive impact of the PSB consortium on grain yield, soil phosphorus availability, and plant phosphorus uptake. The competence and persistence of the inoculated strains in the rhizosphere was confirmed by FISH and BOX Polymerase Chain Reaction (BOX-PCR). This work highlights the potential of PSB-based biofertilizers to improve soil fertility, promote sustainable rice production and reduce the negative environmental impacts of chemical fertilizers. Future research would focus on scaling up these findings for widespread adoption in agriculture and exploring their applicability to other crops and agroecosystems.
Predicting microbe-disease associations via graph neural network and contrastive learning
Authors: Jiang Cong , Feng Junxuan , Shan Bingshen , Chen Qiyue , Yang Jian , Wang Gang , Peng Xiaogang , Li Xiaozheng
Published: December 2024

In the contemporary field of life sciences, researchers have gradually recognized the critical role of microbes in maintaining human health. However, traditional biological experimental methods for validating the association between microbes and diseases are both time-consuming and costly. Therefore, developing effective computational methods to predict potential associations between microbes and diseases is an important and urgent task. In this study, we propose a novel computational framework, called GCATCMDA, for forecasting potential associations between microbes and diseases. Firstly, we construct Gaussian kernel similarity networks for microbes and diseases using known microbe-disease association data. Then, we design a feature encoder that combines graph convolutional network and graph attention mechanism to learn the node features of networks, and propose a feature dual-fusion module to effectively integrate node features from each layer's output. Next, we apply the feature encoder separately to the microbe similarity network, disease similarity network, and microbe-disease association network, and enhance the consistency of features for the same nodes across different association networks through contrastive learning. Finally, we pass the microbe and disease features into an inner product decoder to obtain the association scores between them. Experimental results demonstrate that the GCATCMDA model achieves superior predictive performance compared to previous methods. Furthermore, case studies confirm that GCATCMDA is an effective tool for predicting microbe-disease associations in real situations.
Rapid, sensitive, and visual detection of mandarin fish ranavirus and infectious spleen and kidney necrosis virus using an RPA-CRISPR/Cas12a system
Authors: Lu Zhoutao , Liang Mincong , Li Chuanrui , Xu Yichun , Weng Shaoping , He Jianguo , Guo Changjun
Published: December 2024

Iridoviruses are large cytoplasmic icosahedral viruses that contain dsDNA. Among them, mandarin fish ranavirus (MRV) and infectious spleen and kidney necrosis virus (ISKNV) are particularly notable due to their high contagiousness and pathogenicity. These viruses pose a significant threat to fish aquaculture, resulting in substantial annual economic losses for the fish farming industry. Therefore, the development of novel, rapid virus detection technologies is essential for the prevention and control of ISKNV and MRV diseases. In this study, we developed a rapid, sensitive, and visual detection method for MRV and ISKNV using the recombinase polymerase amplification (RPA)−CRISPR/Cas12a system. This method can detect as low as 1 copy/μL of MRV and 0.1 copy/μL of ISKNV, demonstrating excellent specificity and reproducibility. The detection can be performed at a constant temperature of 37–39°C, eliminating the need for complex equipment. A 30-min RPA amplification followed by a 15-min CRISPR/Cas reaction is sufficient for detecting most samples. For low-concentration samples, extending the CRISPR/Cas reaction time to 60 min improves result visibility. The designed RPA reaction system is capable of performing reverse transcription of RNA, allowing for the detection of mRNA transcribed from the MCP gene of MRV and ISKNV in the sample. Furthermore, two probes were identified that can be observed without the need for excitation light. In conclusion, a field-suitable detection method for ISKNV and MRV has been established, providing a powerful tool for the prompt diagnosis of these aquatic pathogens and aiding in the prevention and control of ISKNV and MRV diseases.
Great diverse rhizobial community nodulating Astragalus mongholicus in the northeastern region of China
Authors: Gao Mengzhe , Yuan Xiaoxia , Ji Zhaojun , Yang Bingjie , Li Hua , Zhang Bo
Published: December 2024

Introduction

Astragalus mongholicus Bunge is an important medicinal legume species widely cultivated in northeastern China (NEC) and northwestern China (NWC) and can establish a symbiotic relationship with nitrogen-fixing rhizobial strains. However, there are limited reports comparing the genetic diversity, differentiation, and gene flow of rhizobial strains associated with this plant in different geographic regions.

Methods

We used multilocus sequence analysis (MLSA) to investigate the phylogeny and genetic diversity of rhizobia and to estimate their intra- and inter-regional gene flow and genetic differentiation based on the analysis of concatenated core genes (recA, atpD, and glnII) and the critical symbiotic gene nodC.

Results

We isolated eight known and three novel genospecies representing four genera, among which Rhizobium yanglingense was the most predominant microsymbiont. Phylogenetic analysis revealed a highly diverse rhizobial community nodulating Astragalus mongholicus in NEC, consisting of the four genera Rhizobium, Bradyrhizobium, Sinorhizobium, and Mesorhizobium. This community differed markedly from the rhizobial community found in NWC. Various rhizobial genospecies with different symbiotic gene nodC sequences were capable of nodulating A. mongholicus in NEC. Therefore, A. mongholicus exhibits promiscuity in its association with symbionts in the natural environment, showing no strong preference for either the species-defining core genes or the symbiotic genes of rhizobia. We also found that the Glyco_tranf_GTA_type superfamily (Glycosyltransferase family A) is the most highly conserved and essential domain in the NodC protein, which is encoded by the symbiotic nodC gene, across nodulating rhizobia. In addition, we found independent genetic differentiation among rhizobial communities geographically, and the frequency of gene flow among microsymbionts between NEC and NWC was low. We speculate that the formation of the highly diverse rhizobial community in NEC resulted from the independent evolution of each ancestral lineage. This diversity likely arose from intraregional genetic differentiation driven by mutations rather than recombination.

Conclusion

Ecogeographical isolation between NEC and NWC restricted inter-regional genetic drift and gene flow. Therefore, intraregional genetic differentiation is the major evolutionary force underlying the genetic diversity of rhizobia.
A bifunctional endolytic alginate lyase with two different lyase catalytic domains from Vibrio sp. H204
Authors: Peng Chune , Wang Qingbin , Xu Wei , Wang Xinkun , Zheng Qianqian , Liang Xiaohui , Dong Xiaodan , Li Fuchuan , Peng Lizeng
Published: December 2024

Alginate lyases can fully degrade alginate into various size-defined unsaturated oligosaccharide products by β-elimination. Here, we identified the bifunctional endolytic alginate lyase Aly35 from the marine bacterium Vibrio sp. Strain H204. The enzyme Aly35 is classified into the polysaccharide lyase 7 superfamily and contains two alginate lyase catalytic domains. The relationship and function of the two lyase domains are not well known. Thus, the full-length recombinant enzyme and its truncated proteins Aly35-CD1 (catalytic domain 1), Aly35-CD2 (catalytic domain 2 domain) were constructed. The three enzymes showed similar biochemical characteristics and exhibited temperature and pH stability. Further research showed that Aly35 and Aly35-CD2 can efficiently degrade alginate, polymannuronate (PM) and polyguluronate (PG) into a series of unsaturated oligosaccharides, while Aly35-CD1 exhibits greater PM-degrading activity than that of Aly35-CD2 but can not degraded PG efficiently. The results suggest that the domain (Trp295-His582) is critical for PG-degrading activity, the domain has (Leu53-Lys286) higher PM-degrading activity, both catalytic domains together confer increased alginate (including M-blocks and G blocks)-degrading activity. The enzyme Aly35 and its truncations Aly35-CD1 and Aly35-CD2 will be useful tools for structural analyses and for preparing bioactive oligosaccharides, especially Aly35-CD1 can be used to prepare G unit–rich oligosaccharides from alginate.
Characteristics and direct causes of death in severely ill patients admitted to a neurology department
Authors: Lee Da Heui , Jeong Seok Young , Shin Byoung-Soo , Kang Hyun Goo
Published: December 2024

Introduction

The study aimed to analyze the characteristics of patients admitted to the neurology department of a tertiary hospital who subsequently died, focusing on those with high disease severity.

Materials and methods

We conducted a retrospective cohort study of patients who died among those admitted to the neurology department of a regional tertiary hospital from 2013 to 2021. Clinical, radiological, and laboratory results of the included patients were collected, and their primary diagnoses, duration from time of admission to death, and direct causes of death were analyzed. Furthermore, the patients were categorized into subgroups based on sex (male and female), primary diagnosis (ischemic and non-ischemic stroke), and cancer diagnosis for comparative analysis.

Results

Of 187 deaths, the primary diagnoses were ischemic stroke (131 cases), seizures (19 cases), encephalitis and encephalopathy (18 cases), and other conditions (19 cases). The direct causes of death included ischemic stroke in 68 patients, sepsis in 33, cerebral hemorrhage in 19, pneumonia in 15, acute kidney injury in nine, status epilepticus in seven, and other causes in 36. Pneumonia, cerebral hemorrhage, acute kidney injury, and status epilepticus were the more prevalent direct causes of death in men, whereas ischemic stroke and sepsis were more prevalent in women. Additionally, sepsis, pneumonia, acute kidney injury, and status epilepticus, as direct causes of death, were significantly higher among patients with a primary diagnosis of non-ischemic stroke than among those with a primary diagnosis of ischemic stroke. Furthermore, there were differences in some pre-existing diseases and laboratory findings when comparing between the cancer group and the non-cancer group.

Discussion

Ischemic stroke was the primary diagnosis and direct cause of death in a high proportion of patients. Other noteworthy direct causes of death were cerebral hemorrhage and infections such as sepsis and pneumonia. Based on these findings, the characteristics and prognoses of patients admitted to neurology departments can be predicted and used for management.
Design of upper limb muscle strength assessment system based on surface electromyography signals and joint motion
Authors: Wang Siqi , Lai Wei , Zhang Yipeng , Yao Junyu , Gou Xingyue , Ye Hui , Yi Jun , Cao Dong
Published: December 2024

Purpose

This study aims to develop a assessment system for evaluating shoulder joint muscle strength in patients with varying degrees of upper limb injuries post-stroke, using surface electromyographic (sEMG) signals and joint motion data.

Methods

The assessment system includes modules for acquiring muscle electromyography (EMG) signals and joint motion data. The EMG signals from the anterior, middle, and posterior deltoid muscles were collected, filtered, and denoised to extract time-domain features. Concurrently, shoulder joint motion data were captured using the MPU6050 sensor and processed for feature extraction. The extracted features from the sEMG and joint motion data were analyzed using three algorithms: Random Forest (RF), Backpropagation Neural Network (BPNN), and Support Vector Machines (SVM), to predict muscle strength through regression models. Model performance was evaluated using Root Mean Squared Error (RMSE), R-Square (R2), Mean Absolute Error (MAE), and Mean Bias Error (MBE), to identify the most accurate regression prediction algorithm.

Results

The system effectively collected and analyzed the sEMG from the deltoid muscles and shoulder joint motion data. Among the models tested, the Support Vector Regression (SVR) model achieved the highest accuracy with an R2 of 0.8059, RMSE of 0.2873, MAE of 0.2155, and MBE of 0.0071. The Random Forest model achieved an R2 of 0.7997, RMSE of 0.3039, MAE of 0.2405, and MBE of 0.0090. The BPNN model achieved an R2 of 0.7542, RMSE of 0.3173, MAE of 0.2306, and MBE of 0.0783.

Conclusion

The SVR model demonstrated superior accuracy in predicting muscle strength. The RF model, with its feature importance capabilities, provides valuable insights that can assist therapists in the muscle strength assessment process.
Deep learning-based multiclass segmentation in aneurysmal subarachnoid hemorrhage
Authors: Kiewitz Julia , Aydin Orhun Utku , Hilbert Adam , Gultom Marie , Nouri Anouar , Khalil Ahmed A. , Vajkoczy Peter , Tanioka Satoru , Ishida Fujimaro , Dengler Nora F. , Frey Dietmar
Published: December 2024

Introduction

Radiological scores used to assess the extent of subarachnoid hemorrhage are limited by intrarater and interrater variability and do not utilize all available information from the imaging. Image segmentation enables precise identification and delineation of objects or regions of interest and offers the potential for automatization of score assessments using precise volumetric information. Our study aims to develop a deep learning model that enables automated multiclass segmentation of structures and pathologies relevant for aneurysmal subarachnoid hemorrhage outcome prediction.

Methods

A set of 73 non-contrast CT scans of patients with aneurysmal subarachnoid hemorrhage were included. Six target classes were manually segmented to create a multiclass segmentation ground truth: subarachnoid, intraventricular, intracerebral and subdural hemorrhage, aneurysms and ventricles. We used the 2d and 3d configurations of the nnU-Net deep learning biomedical image segmentation framework. Additionally, we performed an interrater reliability analysis in our internal test set (n = 20) and an external validation on a set of primary intracerebral hemorrhage patients (n = 104). Segmentation performance was evaluated using the Dice coefficient, volumetric similarity and sensitivity.

Results

The nnU-Net-based segmentation model demonstrated performance closely matching the interrater reliability between two senior raters for the subarachnoid hemorrhage, ventricles, intracerebral hemorrhage classes and overall hemorrhage segmentation. For the hemorrhage segmentation a median Dice coefficient of 0.664 was achieved by the 3d model (0.673 = 2d model). In the external test set a median Dice coefficient of 0.831 for the hemorrhage segmentation was achieved.

Conclusion

Deep learning enables automated multiclass segmentation of aneurysmal subarachnoid hemorrhage-related pathologies and achieves performance approaching that of a human rater. This enables automatized volumetries of pathologies identified on admission CTs in patients with subarachnoid hemorrhage potentially leading to imaging biomarkers for improved outcome prediction.
Comprehensive list of preventative migraine headache medications without significant drug–drug interactions
Authors: Dave Jay , Hakkinen Ian , Zhang Pengfei
Published: December 2024

Background/objective

Preventive medications are crucial in migraine prevention. In cases of refractory migraine headaches, multiple medications may be required. We seek to identify a comprehensive list of preventive migraine headache medications that can be used as two, three, and four drug combinations without drug–drug interactions.

Methods

We compiled a list of prevention medications from Szperka et al.’s “Migraine Care in the Era of COVID-19” as well as American Headache Society’s 2018 and 2021 “Consensus Statements on Integrating New Migraine Treatments into Clinical Practice.” We obtained all possible two to four combinations of prevention medications through this list. We then filtered out all combinations containing at least one interaction based on DrugBank database and also identified least to most interacting medications.

Results

A total of 26 unique prevention medications are identified. This results in a total of 325 combinations of two preventives, 2,600 combinations of three preventives, and 14,950 combinations of four preventives. There are a total of 124, 146, and 0 non-interacting two, three, and four preventive combinations, respectively. All except 16 combinations of pick-twos can be placed within a pick-three combinations. The resulting distinct non-interacting medications can be represented by a condensed list of 162 unique combinations of medications. CGRP antagonists, Botulinum toxin A, melatonin, and candesartan are least interacting.

Conclusion

This list of migraine preventive medications without drug–drug interactions is a useful tool for clinicians seeking to manage refractory headaches more effectively by implementing an evidence-based polypharmacy.
Effects of transcranial direct current stimulation on modulating executive functions in healthy populations: a systematic review and meta-analysis
Authors: You Guopeng , Pan Xinliang , Li Jun , Zhao Shaocong
Published: December 2024

Background

Conventional research has asserted that cognitive function, particularly, response inhibition, is closely related to the inferior frontal cortex (IFC), dorsolateral prefrontal cortex (DLPFC), or orbital frontal cortex (OFC), which belong to the prefrontal cortex (PFC). Different targets of anodal or cathodal transcranial direct current stimulation (a-tDCS or c-tDCS) would affect the experimental results, but the stimulation of the same brain target would produce inconsistent findings.

Purpose

This study aimed to investigate the effects of a-tDCS and c-tDCS applied over the PFC for healthy populations on reactive and proactive control process compared with sham or no tDCS conditions, as assessed using the Stop-signal task (SST) and Go/NoGo (GNG) task performance.

Methods

This systematic review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Search was conducted on Web of Science, Google Scholar, PubMed, Elsevier, Scopus, and Science Direct until March 2024. Studies that assessed the inhibitory control in SST or/and GNG tasks were included to achieve a homogenous sample.

Results

Fourteen studies were included for meta-analyses, which were performed for two outcome measures, namely, stop-signal reaction time (SSRT) and commission error (CE) rate. A-tDCS and c-tDCS over the PFC had significant ergogenic effects on SST performance (mean difference = −17.03, 95% CI [−24.62, −9.43], p < 0.0001; mean difference = −15.19, 95% CI [−19.82, −10.55], p < 0.00001), and that of a-tDCS had a positive effect on GNG task performance (mean difference = −1.42, 95% CI [−2.71, −0.14], p = 0.03).

Conclusion

This review confirmed the engagement of PFC tDCS in reactive and proactive inhibitory processes. Future research should increase sample size and implement personalized stimulus protocols.
Mapping the structure of biomarkers in autism spectrum disorder: a review of the most influential studies
Authors: Jin Fang , Wang Zhidan
Published: December 2024

Background

Autism spectrum disorder is a distinctive developmental condition which is caused by an interaction between genetic vulnerability and environmental factors. Biomarkers play a crucial role in understanding disease characteristics for diagnosis, prognosis, and treatment. This study employs bibliometric analysis to identify and review the 100 top-cited articles’ characteristics, current research hotspots and future directions of autism biomarkers.

Methods

A comprehensive search of autism biomarkers studies was retrieved from the Web of Science Core Collection database with a combined keyword search strategy. A comprehensive analysis of the top 100 articles was conducted with CiteSpace, VOSviewer, and Excel, including citations, countries, authors, and keywords.

Results

The top 100 cited studies were published between 1988 and 2021, with the United States led in productivity. Core biomarkers such as genetics, children, oxidative stress, and mitochondrial dysfunction are well-established. Potential trends for future research may include brain studies, metabolomics, and associations with other psychiatric disorders.

Conclusion

This pioneering bibliometric analysis provides a comprehensive compilation of the 100 most-cited studies on autism, which not only offers a valuable resource for doctors, and researchers but shedding insights into current shortcomings and future endeavors. Future research should prioritize the application of emerging technologies for biomarkers, longitudinal study of biomarkers, and specificity of autism biomarkers to advance the precision of ASD diagnosis and treatment.
Enzymatically hydrolyzed diet improves growth performance and intestinal microbiome in growing pigs
Authors: Gong Tianye , Ji Mengting , Yang Yuting , Liu Jingchao , Gong Yuxuan , Liu Sijun , Zhao Yan , Cao Guoqing , Guo Xiaohong , Yang Yang , Li Bugao
Published: December 2024

Background

The use of enzymes within pig feed can reduce the challenges associated with antibiotic-free animal feeding. However, this enzymatic effect is often limited by the internal and external gut environment. This study aimed to improve diet quality and assess the impact of an enzymatically hydrolyzed diet (EHD) on growth performance, meat quality, and intestinal health in growing pigs.

Methods

The EHD was prepared by treating a liquid basal diet with a compound enzyme preparation (5 non-starch polysaccharides (NSP) enzymes: cellulase, pectinase, xylanase, β- glucanase, α-galactosidase; 3 exogenous digestive enzymes: amylase, lipase, protease; lysozyme, and glucose oxidase) in a 1:2.5 ratio with water and heated at 40°C for 1 h. Thirty-six growing pigs (average body weight 25 ± 0.5 kg; age 75 ± 3 days) from the Duroc × Landrace × Yorkshire crossbreed were randomly divided into three dietary groups: solid basal diet (S-CON), liquid basal diet (L-CON), and EHD.

Results

Enzymatic pre-treatment reduced the anti-nutritional factors (ANFs) in the diets (p < 0.01). Additionally, the gluconic acid in the EHD might reduce the pH of diets and inhibit pathogenic bacteria growth. Pigs fed the EHD had higher average daily gains (p < 0.01) and lower feed-to-gain ratios (p < 0.01). Muscle samples revealed higher meat redness and reductions in drip loss, shear force, cooking loss, and meat yellowness (p < 0.01). Moreover, the EHD increased intestinal concentrations of amylase and cellulase (p < 0.01). In terms of gut health, pigs on the EHD diet presented more aligned small intestinal villi, with improved villus height and villus crypt ratio (p < 0.01). There was also up-regulation of the abundance of the tight junction proteins Occludin and ZO-1 and down-regulation of the mRNA expression of TNF-α and IL-6 in the colon (p < 0.05). Additionally, the abundance of beneficial intestinal flora, particularly Firmicutes and Lactobacillus, increased significantly. Lactobacillus and Prevotella were positively correlated with increased short-chain fatty acids.

Conclusion

Overall, the EHD substantially improved growth performance and intestinal health in pigs, providing a potential reference for improving the effectiveness of enzymatic pretreatment in animal diets.
Relevance of diet in schizophrenia: a review focusing on prenatal nutritional deficiency, obesity, oxidative stress and inflammation
Authors: Rarinca Viorica , Vasile Amalia , Visternicu Malina , Burlui Vasile , Halitchi Gabriela , Ciobica Alin , Singeap Ana-Maria , Dobrin Romeo , Burlui Ecaterina , Maftei Lucian , Trifan Anca
Published: December 2024

Background/Objectives

Schizophrenia is a complex mental disorder influenced by genetic and environmental factors, including dietary habits. Oxidative stress and inflammation play a crucial role in the pathophysiology of schizophrenia. Emerging research suggests that diet may affect schizophrenia through different biological mechanisms beyond oxidative stress and inflammation. In particular, epigenetic changes may alter the expression of genes related to neurodevelopment and neurotransmitter systems, while neuroplasticity plays a crucial role in brain adaptation and resilience to psychiatric disorders.

Methods

The literature search included the main available databases (Science Direct, PubMed and Google Scholar), considering the English language, and our screening was performed based on several words such as “schizophrenia”, “diet”, “nutrients”, “obesity”, “oxidative stress”, “inflammation”, “antioxidants” and “prenatal nutritional deficiency”. The review focused specifically on studies examining the relevance of diet in schizophrenia, as well as prenatal nutritional deficiency, obesity, oxidative stress, and inflammation associated with this disorder.

Results

Following a review of the literature, it was found that nutritional deficiencies, including lack of omega-3 fatty acids, vitamins D, and B, during the prenatal and postnatal periods can have a negative impact on neurodevelopment and increase the risk of schizophrenia. Patients with schizophrenia have imbalances in antioxidant enzymes, such as glutathione peroxidase (GPx), superoxide dismutase (SOD), catalase (CAT), and reduced levels of antioxidants (vitamin E, vitamin C). These biochemical changes lead to an increase in markers of oxidative stress, including malondialdehyde (MDA). In addition, cytokine-mediated inflammation, microglial activation, and intestinal dysbiosis are associated with the onset of schizophrenia and the severity of schizophrenia symptoms. Currently, there is no universally accepted dietary regimen for control. However, various diets and nutritional methods are being researched and applied to alleviate the symptoms of schizophrenia and improve the overall health of patients, including the Mediterranean diet, the ketogenic diet, the gluten-free diet, and the DASH (Dietary Approaches to Stop Hypertension) diet.

Conclusion

A healthy diet, rich in anti-inflammatory nutrients and antioxidants, may help manage schizophrenia by reducing oxidative stress, preventing complications, and improving quality of life. Omega-3 fatty acids, vitamin D, and B vitamins are particularly important for brain development and function. In this review, we aim to analyze the literature on the influence of diet on schizophrenia, focusing on the role of prenatal nutritional deficiencies, obesity, oxidative stress, and inflammation.
Predicting epidermal growth factor receptor mutation status of lung adenocarcinoma based on PET/CT images using deep learning
Authors: Huang Lele , Kong Weifang , Luo Yongjun , Xie Hongjun , Liu Jiangyan , Zhang Xin , Zhang Guojin
Published: December 2024

Background

The aim of this study is to develop deep learning models based on 18F-fluorodeoxyglucose positron emission tomography/computed tomographic (18F-FDG PET/CT) images for predicting individual epidermal growth factor receptor (EGFR) mutation status in lung adenocarcinoma (LUAD).

Methods

We enrolled 430 patients with non–small-cell lung cancer from two institutions in this study. The advanced Inception V3 model to predict EGFR mutations based on PET/CT images and developed CT, PET, and PET + CT models was used. Additionally, each patient’s clinical characteristics (age, sex, and smoking history) and 18 CT features were recorded and analyzed. Univariate and multivariate regression analyses identified the independent risk factors for EGFR mutations, and a clinical model was established. The performance using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, recall, and F1-value was evaluated. The DeLong test was used to compare the predictive performance across various models.

Results

Among these four models, deep learning models based on CT and PET + CT exhibit the same predictive performance, followed by PET and the clinical model. The AUC values for CT, PET, PET + CT, and clinical models in the training set are 0.933 (95% CI, 0.922–0.943), 0.895 (95% CI, 0.882–0.907), 0.931 (95% CI, 0.921–0.942), and 0.740 (95% CI, 0.685–0.796), respectively; whereas those in the testing set are:0.921 (95% CI, 0.904–0.938), 0.876 (95% CI, 0.855–0.897), 0.921 (95% CI, 0.904–0.937), and 0.721 (95% CI, 0.629–0.814), respectively. The DeLong test results confirm that all deep learning models are superior to clinical one.

Conclusion

The PET/CT images based on trained CNNs effectively predict EGFR and non-EGFR mutations in LUAD. The deep learning predictive models could guide treatment options.
Anesthetic spindles serve as EEG markers of the depth variations in anesthesia induced by multifarious general anesthetics in mouse experiments
Authors: You Ying , Liu Hui , Yang Zhanfei , Chen Yuxuan , Yang Fei , Yu Tian , Zhang Yu
Published: December 2024

Background

Mice play a crucial role in studying the mechanisms of general anesthesia. However, identifying reliable EEG markers for different depths of anesthesia induced by multifarious agents remains a significant challenge. Spindle activity, typically observed during NREM sleep, reflects synchronized thalamocortical activity and is characterized by a frequency range of 7–15 Hz and a duration of 0.5–3 s. Similar patterns, referred to as “anesthetic spindles,” are also observed in the EEG during general anesthesia. However, the variability of anesthetic spindles across different anesthetic agents and depths is not yet fully understood.

Method

Mice were anesthetized with dexmedetomidine, propofol, ketamine, etomidate, isoflurane, or sevoflurane, and cortical EEG recordings were obtained. EEG signals were bandpass filtered between 0.1 and 60 Hz and analyzed using a custom MATLAB script for spindle detection. Anesthesia depth was assessed based on Guedel’s modified stages of anesthesia and the presence of burst suppression in the EEG.

Results

Compared to sleep spindles, anesthetic spindles induced by the different agents exhibited higher amplitudes and longer durations. Isoflurane- and sevoflurane-induced spindles varied with the depth of anesthesia. Spindles associated with etomidate were prominent during induction and light anesthesia, whereas those induced by sevoflurane and isoflurane were more dominant during deep anesthesia and emergence. Post-anesthesia, spindles persisted but ceased more quickly following inhalational anesthesia.

Conclusion

Anesthesia spindle waves reflect distinct changes in anesthesia depth and persist following emergence, serving as objective EEG markers for assessing both anesthesia depth and the recovery process.
Drug-induced retinal vein occlusion: a disproportionality analysis from the FDA adverse event reporting system (2004–2023)
Authors: Chen Xiao-Dong , Xiao Kun-Hong , Zhou Chao-Bing
Published: December 2024

Introduction

Retinal vein occlusion (RVO) often causes irreversible visual impairment, making early prevention crucial. This study aims to identify associations between different medications and RVO and provide information for clinical practice.

Method

This study included reports of RVO from the FDA Adverse Event Reporting System (FAERS) database from the first quarter (Q1) of 2004 to the fourth quarter (Q4) of 2023. The reported drugs were analyzed for adverse drug reaction (ADR) signals using four disproportionality algorithms. Kaplan-Meier curves and median time to onset were used to evaluate the drugs.

Results

From 2004 to 2023, the FAERS database recorded 6,151 reports associated with RVO. Disproportionality analyses identified 25 drugs significantly associated with RVO. Mirabegron showed the highest risk signal, followed by Raloxifene, Tadalafil, Fingolimod, and Bimatoprost. These high-risk drugs are distributed across different therapeutic areas, including urogenital system and sex hormones, ophthalmic drugs, nervous system drugs, musculoskeletal system drugs, anti-tumor and immune-modulating drugs, and anti-parasitic drugs. Specific drug targets such as adrenergic receptor agonists, hormone regulators, and PDE5 inhibitors were identified as high risk. Ophthalmic drugs exhibited the longest median time to adverse ocular reactions at 532.01 days, followed by anti-parasitic drugs, nervous system drugs, urogenital system and sex hormone drugs, anti-tumor and immune-modulating drugs, and musculoskeletal system drugs.

Conclusion

This study provides an overview of drug-induced RVO, identifying potential culprit drugs and their distribution characteristics. These findings enhance understanding of medication safety and help optimize clinical practice.
Alhagi maurorum extract in combination with lytic phage cocktails: a promising therapeutic approach against biofilms of multi-drug resistant P. mirabilis
Authors: Mirzaei Arezoo , Esfahani Bahram Nasr , Ghanadian Mustafa , Wagemans Jeroen , Lavigne Rob , Moghim Sharareh
Published: December 2024

Antimicrobial resistance (AMR) poses a significant global threat to public health systems, rendering antibiotics ineffective in treating infectious diseases. Combined use of bio compounds, including bacteriophages and plant extracts, is an attractive approach to controlling antibiotic resistance. In this study, the combination of phage cocktail (Isf-Pm1 and Isf-Pm2) and Alhagi maurorum crude extract (AME) was investigated in controlling biofilm-forming multi-drug resistant P. mirabilis isolates, in vitro and a phantom bladder model. The combination of AME and phage cocktails demonstrated no significant disparity in its ability to inhibit quorum sensing (QS) when compared to the individual control of AME alone. Following treatment with the combination of phage cocktail and AME at a 125 μg/mL concentration, the MDR P. mirabilis biofilm biomass was notably reduced by 73% compared to the control (P< 0.0001). The anti-biofilm effect was confirmed by Scanning Electron Microscopy (SEM). Moreover, in a bladder phantom model, there was a considerable decrease in encrustation levels compared to the control. The combined treatment resulted in a 1.85 logarithmic reduction in bacterial adhesion to Vero cells compared to the control. The real-time PCR results indicated significant downregulation of QS- and adhesion-related gens. The phage therapy, combined with AME, holds promising potential in reducing biofilm formation.
Comparative analysis of mineralocorticoid receptor antagonists and renin-angiotensin system inhibitors/angiotensin receptor neprilysin inhibitor in heart failure with mildly reduced ejection fraction
Authors: Lee Chia-Chen , Te-Wei Kuan David , Chang Kai-Chun , Chen Zheng-Wei , Cheng Jen-Fang , Lin Ting-Tse , Lin Lian-Yu , Wu Cho-Kai
Published: December 2024

Introduction

To clarify the efficacy of mineralocorticoid receptor antagonists (MRA) and renin-angiotensin system inhibitors/angiotensin receptor neprilysin inhibitors (RASI/ARNI) in heart failure with mildly reduced ejection fraction (HFmrEF).

Methods

This study assessed the association between these medications and outcomes in HFmrEF using data from the National Taiwan University Hospital-integrated Medical Database. The primary outcome was cardiovascular mortality/heart failure hospitalization (HHF). Inverse probability of treatment weighting balanced baseline patient characteristics. The exposure of primary interest was use of MRA and use of RASI/ARNI, while the non-user group was also likely to receive other heart failure medication treatment.

Results

Among 2,584 HFmrEF patients, 17% received MRA and 43% received RASI/ARNI. Predictors of MRA use included older age, slightly higher ejection fraction, and lower NT-proBNP level. RASI/ARNI use was predicted by higher BMI, lower NT-proBNP level, normal uric acid and potassium levels. MRA use was not associated with a lower risk of cardiovascular death [hazard ratio = 0.89, 95% confidence interval (CI): 0.78–1.02] or HHF (hazard ratio = 1.01, 95% CI: 0.94–1.09). Conversely, RASI//ARNI use was linked to a lower risk of cardiovascular death (hazard ratio = 0.82, 95% CI: 0.71–0.94) but not HHF (hazard ratio = 0.995, 95% CI: 0.924–1.07). Landmark analysis showed no significant difference in outcomes for follow-up durations exceeding 2 years.

Conclusion

MRA had a neutral effect on cardiovascular death and HHF, while RASI/ARNI was associated with a lower risk of cardiovascular death. RASI/ARNI may be more beneficial than MRA for HFmrEF patients. Regular re-evaluation is essential to adjust heart failure treatment.
Design of one-dimensional phononic crystals comprising robust Fano edge modes as a highly sensitive sensor for alcohols
Authors: Fathy Hamza Makhlouf , El-Sherbeeny Ahmed M. , Al Zoubi Wail , Hajjiah Ali , Elsayed Hussein A. , Semeda Ramadan , Ismail Fathy Moataz , Abukhadra Mostafa R. , Mehaney Ahmed
Published: December 2024

This work introduces various designs of phononic crystals (PnCs), referred to as topological phononic crystals (TPnCs), as novel, stable, and high-performance sensing tools. Meanwhile, we introduce the concept of the topological edge state to address the discrepancies between theoretical predictions and experimental results of PnC sensors. Consequently, the design of a PnC sensor structure that maintains high stability amidst fluctuations in layer manufacturing and deformations during construction represents the mainstay of our study. Notably, the numerical findings demonstrate the stability of the proposed sensor in the presence of various geometric changes. In addition, we assess the effectiveness of several periodic PnC designs in sensing the physical properties of fluids, specifically alcohols like butanol. Accordingly, temperature sensing of butanol is conducted over a wide range (170°C–270°C) by monitoring the displacement of Fano resonance modes. In this regard, the proposed PnC structure demonstrates an impressive sensitivity of 119.23 kHz/°C. Furthermore, our design achieves a high-quality factor and figure of merit of 378.23 and 1.085, respectively, across the temperature range of 170°C–230°C. These outcomes are promising for the development of ultrasensitive thermal sensors. Ultimately, our research provides valuable insights into the creation of highly sensitive and stable temperature sensors suitable for a range of industrial applications.
Analysis of genetic instability induced by radon exposure in iron mine processing workers in Shandong Province, Northern China
Authors: Fang Lianying , Wu Fangfang , Sun Hao , Li Weiguo , Hou Dianjun , Ma Ya
Published: December 2024

Background

Radon, a colorless and odorless radioactive gas, poses serious health risks. It is the second leading cause of lung cancer and notably increases lung cancer risk in smokers. Although previous epidemiological studies have mainly examined lung cancer rates in miners, the effects of radon on genomic stability and its molecular mechanisms are not well understood.

Methods

This study evaluated chromosomal aberrations (CA) and cytokinesis-block micronucleus (CBMN) in miners’ lymphocytes, investigating the relationship between cytogenetic damage and variables such as exposure duration and age. Additionally, gene expression profiles were compared between radon-exposed miners and a control group to identify genes involved in DNA damage repair.

Results

We observed a significant increase in CA and CBMN among underground miners. Gene expression analysis showed 14 genes were upregulated and four downregulated in the exposed group compared to controls.

Conclusion

These findings indicate a strong link between high radon exposure and genomic instability in miners. Improved monitoring of work environments and stronger protective measures are critical to safeguarding miners’ health.
Gender-specific perception of job stressors and resources: a structural equation model-based secondary analysis
Authors: Heub Angelina , Schaller Andrea , Lange Martin
Published: December 2024

Objective

Stress is an extensive issue in modern society, affecting men and women differently. A better understanding of these patterns is required within the work context. Therefore, this study aimed to identify gender differences in the effects of stressors (quantitative demands, qualitative demands, working time) and resources (job control, quality of leadership, co-worker support) on subjective perceived stress across occupational groups.

Methods

This study was conducted as a secondary data analysis based on the ‘German Study on Mental Health at Work’ data. The national representative cross-sectional sample included 4,118 employees. The data were analyzed using structural equation modeling.

Results

Correlations between quantitative demands, working time, co-worker support, quality of leadership, job control, and subjective perceived stress were first confirmed for a total sample of employees. Gender differences in these interactions were then analyzed using multi-group equation modeling and a gender-stratified sample. Men and women showed an increase in subjective perceived stress for high quantitative demands. This increase was more prominent for men. Women further showed an increase in subjective perceived stress in response to long working time. High co-worker support, quality of leadership, and job control had stress-reducing effects but did not result in significant gender differences. No association was found between qualitative demands and subjective perceived stress.

Conclusion

The results underline that not all working conditions significantly impact stress for both genders and gender differences exist only within the stressors. Hence, gendered strategies may only be required in some constellations. However, specific contexts require integrating gendered approaches in research and operational practice.
Engaging rural communities in Bangladesh to tackle antimicrobial resistance through the Community Dialogue Approach: a process evaluation protocol for COSTAR project in Cumilla, Bangladesh
Authors: Saify Md Badruddin , Jones Nichola , Fieroze Fariza , Mitchell Jessica , Hicks Joseph Paul , Huque Samina , Saha Sajib , Latham Sophia , Hawkings Helen , Huque Rumana , King Rebecca
Published: December 2024

Introduction

Antimicrobial resistance (AMR) is a global problem and is especially threatening for low-and-middle income countries like Bangladesh. The COSTAR (Community-led Solutions to Antimicrobial Resistance) project includes a Randomised Control Trial (RCT) which aims to evaluate the effectiveness of the Community Dialog Approach (CDA) to improve levels of correct and appropriate knowledge and reported practice about antibiotics, antibiotic use, and antibiotic resistance (ABR) from a One Health perspective, among adult community members in 5 selected sub-districts of Cumilla. The CDA is a community engagement approach involving community members in active discussions also known as Community Dialogs (CD), run by local facilitators. The dialogs promote collective action to produce sustainable social change. The trial’s process evaluation will evaluate fidelity, dose, adaptation, reach, mechanisms of impact and the process of knowledge diffusion using the MRC framework for the evaluation of complex interventions.

Methods and analysis

The process evaluation will be implemented in the catchment areas of 25 selected community clinics (CCs) in the intervention group. The key actors involved in the process evaluation are participants from master trainers and trainers training; community dialog facilitators; supervisors; community dialog participants and non-participants; and local and national level government stakeholders. Qualitative and quantitative data will be collected through Focus Group Discussion (FGDs); Case Studies; Key Informant Interview (KIIs); CD observations; monitoring forms; quarterly feedback from facilitators and supervisors, and pre-and-post-test questionnaires administered during the training of facilitators. All qualitative data will be coded using a priori coding framework in NVIVO 14. Quantitative data will be analysed using descriptive statistics.

Ethics and dissemination

Ethical approval was obtained from the Bangladesh Medical Research Council (BMRC): BMRC/NREC/2019–2022/427 and from the University of Leeds Faculty of Medicine and Health ethics board: MREC 20–034. All results will be disseminated through a one pager summary; infographics; peer-reviewed journal articles and national and international conferences.

Clinical trial registration

https://www.isrctn.com/ISRCTN93756764, identifier ISRCTN93756764.