bluuebunny/crossref_metadata_2025 huggingface dataset:
Predictive value of hyponatremia for short-term mortality in supratentorial spontaneous intracerebral hemorrhage: a single center study
Authors: Qian Ao , Zheng Longyi , He Zeyuan , Zhou Jing , Tang Shuang , Xing Wenli
Published: January 2024

Background

Hyponatremia is a common electrolyte disturbance in patients with neurological disease; however, its predictive role for outcome in patients with supratentorial spontaneous intracerebral hemorrhage (sICH) is controversial. This study aims to explore the association between hyponatremia within 7 days after bleeding and 90-day mortality in patients with supratentorial sICH.

Methods

A retrospective analysis was conducted at our institution. Patients with sICH meeting the inclusion criteria were enrolled in this study. Multivariate regression analyses were performed to determine the predictive value of hyponatremia (serum sodium <135 mmol/L) for 90-day mortality and functional outcome. Subgroup analysis was performed based on the degree and duration of hyponatremia and therapeutic strategies. The Spearman correlation test was performed to explore the relationship between hyponatremia severity and duration with variables in a multivariate regression model. Kaplan–Meier curve was depicted to reveal the relationship between hyponatremia and mortality. The receiver operating characteristic (ROC) curve was plotted to show the diagnostic effect of the minimum concentration of serum sodium (sodiummin) on 90-day mortality.

Results

A total of 960 patients were enrolled, 19.6% (188) of whom were patients with hyponatremia and 26.0% (250) had 90-day mortality. The incidence of hyponatremia was roughly 2.5 times in non-survivors compared with survivors (34.8% vs. 14.2%). Multivariate regression analysis revealed that hyponatremia was the independent predictor of 90-day mortality (OR 2.763, 95%CI 1.836–4.157) and adverse outcome (OR 3.579, 95%CI 2.332–6.780). Subgroup analysis indicated an increased trend in mortality risk with both duration (more or less than 48 h) and severity of hyponatremia (mild, moderate, and severe) and confirmed the predictive value of hyponatremia for mortality in patients undergoing surgical intervention (external ventricular drainage, craniotomy, and decompressive craniectomy; all p < 0.05). The Spearman correlation test indicated no moderate or strong relationship between hyponatremia severity and duration with other variables in the multivariate model (all |rs| < 0.4). The ROC curve suggested the moderate diagnostic performance of sodiummin for mortality in both general patients and subgroups of therapeutic method patients (AUC from 0.6475 to 0.7384).

Conclusion

Hyponatremia occurring in the first 7 days after bleeding is an independent predictor of 90-day morality and adverse outcome. Rigorous electrolyte scrutiny in patients treated surgically is required.
A generalizable deep voxel-guided morphometry algorithm for the detection of subtle lesion dynamics in multiple sclerosis
Authors: Raj Anish , Gass Achim , Eisele Philipp , Dabringhaus Andreas , Kraemer Matthias , Zöllner Frank G.
Published: January 2024

Introduction

Multiple sclerosis (MS) is a chronic neurological disorder characterized by the progressive loss of myelin and axonal structures in the central nervous system. Accurate detection and monitoring of MS-related changes in brain structures are crucial for disease management and treatment evaluation. We propose a deep learning algorithm for creating Voxel-Guided Morphometry (VGM) maps from longitudinal MRI brain volumes for analyzing MS disease activity. Our approach focuses on developing a generalizable model that can effectively be applied to unseen datasets.

Methods

Longitudinal MS patient high-resolution 3D T1-weighted follow-up imaging from three different MRI systems were analyzed. We employed a 3D residual U-Net architecture with attention mechanisms. The U-Net serves as the backbone, enabling spatial feature extraction from MRI volumes. Attention mechanisms are integrated to enhance the model's ability to capture relevant information and highlight salient regions. Furthermore, we incorporate image normalization by histogram matching and resampling techniques to improve the networks' ability to generalize to unseen datasets from different MRI systems across imaging centers. This ensures robust performance across diverse data sources.

Results

Numerous experiments were conducted using a dataset of 71 longitudinal MRI brain volumes of MS patients. Our approach demonstrated a significant improvement of 4.3% in mean absolute error (MAE) against the state-of-the-art (SOTA) method. Furthermore, the algorithm's generalizability was evaluated on two unseen datasets (n = 116) with an average improvement of 4.2% in MAE over the SOTA approach.

Discussion

Results confirm that the proposed approach is fast and robust and has the potential for broader clinical applicability.
Research progress of CTC, ctDNA, and EVs in cancer liquid biopsy
Authors: Wang Xiaoling , Wang Lijuan , Lin Haihong , Zhu Yifan , Huang Defa , Lai Mi , Xi Xuxiang , Huang Junyun , Zhang Wenjuan , Zhong Tianyu
Published: January 2024

Circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and extracellular vehicles (EVs) have received significant attention in recent times as emerging biomarkers and subjects of transformational studies. The three main branches of liquid biopsy have evolved from the three primary tumor liquid biopsy detection targets—CTC, ctDNA, and EVs—each with distinct benefits. CTCs are derived from circulating cancer cells from the original tumor or metastases and may display global features of the tumor. ctDNA has been extensively analyzed and has been used to aid in the diagnosis, treatment, and prognosis of neoplastic diseases. EVs contain tumor-derived material such as DNA, RNA, proteins, lipids, sugar structures, and metabolites. The three provide different detection contents but have strong complementarity to a certain extent. Even though they have already been employed in several clinical trials, the clinical utility of three biomarkers is still being studied, with promising initial findings. This review thoroughly overviews established and emerging technologies for the isolation, characterization, and content detection of CTC, ctDNA, and EVs. Also discussed were the most recent developments in the study of potential liquid biopsy biomarkers for cancer diagnosis, therapeutic monitoring, and prognosis prediction. These included CTC, ctDNA, and EVs. Finally, the potential and challenges of employing liquid biopsy based on CTC, ctDNA, and EVs for precision medicine were evaluated.
Effects of p53 and ATRX inhibition on telomeric recombination in aging fibroblasts
Authors: Udroiu Ion , Marinaccio Jessica , Sgura Antonella
Published: January 2024

In order to avoid replicative senescence, tumor cells must acquire a telomere maintenance mechanism. Beside telomerase activation, a minority of tumors employs a recombinational mechanism called Alternative Lengthening of Telomeres (ALT). Several studies have investigated the potential ALT stimulation by inactivation of ATRX in tumor cells, obtaining contrasting results. Differently, since ALT can be viewed as a mechanism to overcome telomere shortening-mediated replicative senescence, we have investigated the effects of the inhibition of ATRX and p53 in aging primary fibroblasts. We observed that senescence leads to a phenotype that seems permissive for ALT activity, i.e. high levels of ALT-associated PML bodies (APB), telomeric damage and telomeric cohesion. On the other hand, RAD51 is highly repressed and thus telomeric recombination, upon which the ALT machinery relies, is almost absent. Silencing of ATRX greatly increases telomeric recombination in young cells, but is not able to overcome senescence-induced repression of homologous recombination. Conversely, inhibition of both p53 and ATRX leads to a phenotype reminiscent of some aspects of ALT activity, with a further increase of APB, a decrease of telomere shortening (and increased proliferation) and, above all, an increase of telomeric recombination.
Identification of a novel RPGR mutation associated with retinitis pigmentosa and primary ciliary dyskinesia in a Slovak family: a case report
Authors: Kolkova Zuzana , Durdik Peter , Holubekova Veronika , Durdikova Anna , Jesenak Milos , Banovcin Peter
Published: January 2024

Background

The mutations in the RPGR (retinitis pigmentosa GTPase regulator) gene are the most common cause of X-linked retinitis pigmentosa (XLRP), a rare genetic disorder affecting the photoreceptor cells in the retina. Several reported cases identified this gene as a genetic link between retinitis pigmentosa (RP) and primary ciliary dyskinesia (PCD), characterised by impaired ciliary function predominantly in the respiratory tract. Since different mutations in the same gene can result in various clinical manifestations, it is important to describe a correlation between the gene variant and the observed phenotype.

Methods

Two young brothers from a non-consanguineous Slovak family with diagnosed retinal dystrophy and recurrent respiratory infections were examined. Suspected PCD was diagnosed based on a PICADAR questionnaire, nasal nitric oxide analysis, transmission electron microscopy, high-speed video microscopy analysis, and genetic testing.

Results

We identified a novel frameshift RPGR mutation NM_001034853: c.309_310insA, p.Glu104Argfs*12, resulting in a complex X-linked phenotype combining PCD and RP. In our patients, this mutation was associated with normal ultrastructure of respiratory cilia, reduced ciliary epithelium, more aciliary respiratory epithelium, shorter cilia, and uncoordinated beating with a frequency at a lower limit of normal beating, explaining the clinical manifestation of PCD in our patients.

Conclusion

The identified novel pathogenic mutation in the RPGR gene expands the spectrum of genetic variants associated with the X-linked PCD phenotype overlapping with RP, highlighting the diversity of mutations contributing to the disorder. The described genotype–phenotype correlation can be useful in clinical practice to recognise a broader spectrum of PCD phenotypes as well as for future research focused on the genetic basis of PCD, gene interactions, the pathways implicated in PCD pathogenesis, and the role of RPGR protein for the proper functioning of cilia in various tissues throughout the body.
Characterization of active peptides derived from three leeches and comparison of their anti-thrombotic mechanisms using the tail vein thrombosis model in mice and metabonomics
Authors: Dong Weichao , Li Huajian , Li Yanan , Wang Yuqing , Dai Long , Wang Shaoping
Published: January 2024

Background and aims: The increasing incidence of cardiovascular diseases has created an urgent need for safe and effective anti-thrombotic agents. Leech, as a traditional Chinese medicine, has the effect of promoting blood circulation and removing blood stasis, but its real material basis and mechanism of action for the treatment of diseases such as blood stasis and thrombosis have not been reported.

Methods: In this study, Whitmania Pigra Whitman (WPW), Hirudo nipponica Whitman (HNW) and Whitmania acranutata Whitman (WAW) were hydrolyzed by biomimetic enzymatic hydrolysis to obtain the active peptides of WPW (APP), the active peptides of HNW (APH) and the active peptides of WAW (APA), respectively. Then their structures were characterized by sykam amino acid analyzer, fourier transform infrared spectrometer (FT-IR), circular dichroism (CD) spectrometer and LC-MS. Next, the anti-thrombotic activities of APP, APH and APA were determined by carrageenan-induced tail vein thrombosis model in mice, and the anti-thrombotic mechanisms of high-dose APP group (HAPP), high-dose APH group (HAPH) and high-dose APA group (HAPA) were explored based on UHPLC-Q-Exactive Orbitrap mass spectrometry.

Results: The results showed that the amino acid composition of APP, APH and APA was consistent, and the proportion of each amino acid was few different. The results of FT-IR and CD showed that there were no significant differences in the proportion of secondary structures (such as β-sheet and random coil) and infrared absorption peaks between APP, APH and APA. Mass spectrometry data showed that there were 43 common peptides in APP, APH and APA, indicating that the three have common material basis. APP, APH and APA could significantly inhibit platelet aggregation, reduce black-tail length, whole blood viscosity (WBV), plasma viscosity (PV), and Fibrinogen (FIB), and prolong coagulation time, including activated partial thrombin time (APTT), prothrombin time (PT) and thrombin time (TT). In addition, 24 metabolites were identified as potential biomarkers associated with thrombosis development. Among these, 19, 23, and 20 metabolites were significantly normalized after administration of HAPP, HAPH, and HAPA in the mice, respectively. Furthermore, the intervention mechanism of HAPP, HAPH and HAPA on tail vein thrombosis mainly involved in linoleic acid metabolism, primary bile acid biosynthesis and ether lipid metabolism.

Conclusion: Our findings suggest that APP, APH and APA can exert their anti-blood stasis and anti-thrombotic activities by interfering with disordered metabolic pathways in vivo, and there is no significant difference in their efficacies.
Antitumor efficacy of silver nanoparticles reduced with β-D-glucose as neoadjuvant therapy to prevent tumor relapse in a mouse model of breast cancer
Authors: Franco Molina Moisés Armides , Reding Hernández David , García Coronado Paola Leonor , Kawas Jorge R. , Zárate Triviño Diana G. , Hernández Martínez Sara Paola , Castro Valenzuela Beatriz Elena , Rodríguez Padilla Cristina
Published: January 2024

Introduction: Neoadjuvant therapy constitutes a valuable modality for diminishing tumor volume prior to surgical resection. Nonetheless, its application encounters limitations in the context of recurrent tumors, which manifest resistance to conventional treatments. Silver nanoparticles (AgNPs) have emerged as a promising alternative for cancer treatment owing to their cytotoxic effects.

Methods: Cellular viability was assessed by Alamar blue assay in 4T1 breast cancer cell line. Silver biodistribution was detected by an inductively coupled plasma optical emission spectrometer in an in vivo mice model. For neoadjuvant evaluation, mice were randomized and treated intratumoral with AgNPs-G or intraperitoneally with doxorubicin (DOX) as a control. Recurrence was determined after 170 days by counting lung metastatic nodules (dyed with Bouin solution) with histological confirmation by H&E. Masson’s stain, Ki67 immunohistochemistry, and a TUNEL assay were performed in lungs from treated mice.

Results: AgNPs-G reduced 4T1 cell viability and in an ex vivo assay the AgNPs-G decreased the tumor cell viability. After intravenous administration of AgNPs-G were detected in different organs. After intratumor administration, AgNPs-G are retained. The AgNPs-G treatment significantly reduced tumor volume before its surgical resection. AgNPs-G reduced the development of lung metastatic nodules and the expression of Ki67. TUNEL assay indicated that AgNPs-G didn’t induce apoptosis.

Conclusions: We concluded that intratumor administration of AgNPs-G reduced tumor volume before surgical resection, alongside a reduction in lung metastatic nodules, and Ki67 expression. These findings provide valuable insights into the AgNPs-G potential for intratumor and neoadjuvant cancer therapies. However, further research is needed to explore their full potential and optimize their use in clinical settings.
Development and application of consensus in silico models for advancing high-throughput toxicological predictions
Authors: Collins Sean P. , Mailloux Brandon , Kulkarni Sunil , Gagné Matthew , Long Alexandra S. , Barton-Maclaren Tara S.
Published: January 2024

Computational toxicology models have been successfully implemented to prioritize and screen chemicals. There are numerous in silico (quantitative) structure–activity relationship ([Q]SAR) models for the prediction of a range of human-relevant toxicological endpoints, but for a given endpoint and chemical, not all predictions are identical due to differences in their training sets, algorithms, and methodology. This poses an issue for high-throughput screening of a large chemical inventory as it necessitates several models to cover diverse chemistries but will then generate data conflicts. To address this challenge, we developed a consensus modeling strategy to combine predictions obtained from different existing in silico (Q)SAR models into a single predictive value while also expanding chemical space coverage. This study developed consensus models for nine toxicological endpoints relating to estrogen receptor (ER) and androgen receptor (AR) interactions (i.e., binding, agonism, and antagonism) and genotoxicity (i.e., bacterial mutation, in vitro chromosomal aberration, and in vivo micronucleus). Consensus models were created by combining different (Q)SAR models using various weighting schemes. As a multi-objective optimization problem, there is no single best consensus model, and therefore, Pareto fronts were determined for each endpoint to identify the consensus models that optimize the multiple-criterion decisions simultaneously. Accordingly, this work presents sets of solutions for each endpoint that contain the optimal combination, regardless of the trade-off, with the results demonstrating that the consensus models improved both the predictive power and chemical space coverage. These solutions were further analyzed to find trends between the best consensus models and their components. Here, we demonstrate the development of a flexible and adaptable approach for in silico consensus modeling and its application across nine toxicological endpoints related to ER activity, AR activity, and genotoxicity. These consensus models are developed to be integrated into a larger multi-tier NAM-based framework to prioritize chemicals for further investigation and support the transition to a non-animal approach to risk assessment in Canada.
Prediction of initial objective response to drug-eluting beads transcatheter arterial chemoembolization for hepatocellular carcinoma using CT radiomics-based machine learning model
Authors: Zhang Xueying , He Zijun , Zhang Yucong , Kong Jian
Published: January 2024

Objective: A prognostic model utilizing CT radiomics, radiological, and clinical features was developed and validated in this study to predict an objective response to initial transcatheter arterial chemoembolization with drug-eluting beads (DEB-TACE) for hepatocellular carcinoma (HCC).

Methods: Between January 2017 and December 2022, the baseline clinical characteristics and preoperative and postoperative follow-up imaging data of 108 HCC patients who underwent the first time treatment of DEB-TACE were analyzed retrospectively. The training group (n = 86) and the validation group (n = 22) were randomly assigned in an 8:2 ratio. By logistic regression in machine learning, radiomics, and clinical-radiological models were constructed separately. Finally, the integrated model construction involved the integration of both radiomics and clinical-radiological signatures. The study compared the integrated model with radiomics and clinical-radiological models using calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA).

Results: The objective response rate observed in a group of 108 HCC patients who received initial DEB-TACE treatment was found to be 51.9%. Among the three models, the integrated model exhibited superior predictive accuracy in both the training and validation groups. The training group resulted in an area under the curve (AUC) of 0.860, along with sensitivity and specificity values of 0.650 and 0.913, respectively. Based on the findings from the validation group, the AUC was estimated to be 0.927. Additionally, it was found that values of sensitivity and specificity were 0.875 and 0.833, respectively. In the validation group, the AUC of the integrated model showed a significant improvement when contrasted to the clinical-radiological model (p = 0.042). Nevertheless, no significant distinction was observed in the AUC when comparing the integrated model with the radiomics model (p = 0.734). The DCA suggested that the integrated model demonstrates advantageous clinical utility.

Conclusion: The integrated model, which combines the CT radiomics signature and the clinical-radiological signature, exhibited higher predictive efficacy than either the radiomics or clinical-radiological models alone. This suggests that during the prediction of the objective responsiveness of HCC patients to the first DEB-TACE treatment, the integrated model yields superior outcomes.
Pharmacological and mechanistic aspects of quercetin in osteoporosis
Authors: Deng Ting-Ting , Ding Wen-Yu , Lu Xi-Xue , Zhang Qing-Hao , Du Jin-Xin , Wang Li-Juan , Yang Mei-Na , Yin Ying , Liu Fan-Jie
Published: January 2024

Osteoporosis (OP) is a bone disease associated with increasing age. Currently, the most common medications used to treat OP are anabolic agents, anti-resorptive agents, and medications with other mechanisms of action. However, many of these medications have unfavorable adverse effects or are not intended for long-term use, potentially exerting a severe negative impact on a patient’s life and career and placing a heavy burden on families and society. There is an urgent need to find new drugs that can replace these and have fewer adverse effects. Quercetin (Que) is a common flavonol in nature. Numerous studies have examined the therapeutic applications of Que. However, a comprehensive review of the anti-osteoporotic effects of Que has not yet been conducted. This review aimed to describe the recent studies on the anti-osteoporotic effects of Que, including its biological, pharmacological, pharmacokinetic, and toxicological properties. The outcomes demonstrated that Que could enhance OP by increasing osteoblast differentiation and activity and reducing osteoclast differentiation and activity via the pathways of Wnt/β-catenin, BMP/SMAD/RUNX2, OPG/RANKL/RANK, ERK/JNK, oxidative stress, apoptosis, and transcription factors. Thus, Que is a promising novel drug for the treatment of OP.
Steric blocking upside down: a different way of thinking about the competition between myosin and tropomyosin
Authors: Chalovich Joseph M.
Published: January 2024

At low free Ca2+, the actin binding proteins tropomyosin, troponin I, troponin T and troponin C inhibit contraction in striated muscles. Ca2+ activation alters the position of tropomyosin on actin to uncover binding sites for high affinity forms of myosin (i.e., myosin-ADP). Inhibition of contraction is commonly thought to result from steric blocking of myosin binding to actin by tropomyosin. However, myosin-ADP binding to actin is energetically more favorable than localization of tropomyosin in the blocking position. Tropomyosin is an effective inhibitor of binding only at low levels of myosin-ADP. At low free Ca2+, troponin-tropomyosin also inhibits the rate of a step associated with Pi release to about 1% of the maximum rate. This results in accumulation of myosin with bound ATP and ADP-Pi. Such myosin binds weakly to actin. Ca2+ activation increases the rate of Pi release, but not to the maximum value, and increases the population of myosin-ADP. The high affinity binding of myosin-ADP to actin can displace tropomyosin into the fully active position in relation to the amount of myosin-ADP bound. It seems likely that an important outcome of the steric clash between myosin-ADP and tropomyosin is the dual activation by Ca2+ and myosin-ADP. The C-terminal region of troponin T (TnT) contributes to the incomplete activation by Ca2+ alone. Because this region of TnT is highly conserved, the ability of myosin-ADP to move tropomyosin may be more important than any restriction that tropomyosin may place on myosin binding.
Variations in the plasticity of functional traits indicate the differential impacts of abiotic and biotic factors on the structure and growth of trees in tropical dry forest fragments
Authors: Chaturvedi Ravi Kant , Pandey Santosh Kumar , Tripathi Anshuman , Goparaju Laxmi , Raghubanshi Akhilesh Singh , Singh J. S.
Published: January 2024

Abiotic and biotic factors have considerable impact on the plasticity of plant functional traits, which influences forest structure and productivity; however, their inter-relationships have not been quantified for fragmented tropical dry forest (TDF) ecosystems. We asked the following questions: (1) what are the variations in the plasticity of functional traits due to soil moisture availability in TDF fragments? (2) what are the roles of soil nutrients and forest disturbances in influencing variations in the plasticity of functional traits in the TDF fragments? and (3) how do the variations in the plasticity of functional traits influence the structure and productivity of TDF fragments? Based on linear mixed-effects results, we observed significant variations among tree species for soil moisture content (SMC) under the canopy and selected functional traits across forest fragments. We categorized tree species across fragments by principal component analysis (PCA) and hierarchical clustering on principal components (HCPC) analyses into three functional types,viz., low wood density high deciduous (LWHD), high wood density medium deciduous (HWMD), and high wood density low deciduous (HWLD). Assemblage of functional traits suggested that the LWHD functional type exhibits a drought-avoiding strategy, whereas HWMD and HWLD adopt a drought-tolerant strategy. Our study showed that the variations in functional trait plasticity and the structural attributes of trees in the three functional types exhibit contrasting affinity with SMC, soil nutrients, and disturbances, although the LWHD functional type was comparatively more influenced by soil resources and disturbances compared to HWMD and HWLD along the declining SMC and edge distance gradients. Plasticity in functional traits for the LWHD functional type exhibited greater variations in traits associated with the conservation of water and resources, whereas for HWMD and HWLD, the traits exhibiting greater plasticity were linked with higher productivity and water transport. The cumulative influence of SMC, disturbances, and functional trait variations was also visible in the relative abundance of functional types in large and small sized fragments. Our analysis further revealed the critical differences in the responses of functional trait plasticity of the coexisting tree species in TDF, which suggests that important deciduous endemic species with drought-avoiding strategies might be prone to strategic exclusion under expected rises in anthropogenic disturbances, habitat fragmentation, and resource limitations.
DIC-Transformer: interpretation of plant disease classification results using image caption generation technology
Authors: Zeng Qingtian , Sun Jian , Wang Shansong
Published: January 2024

Disease image classification systems play a crucial role in identifying disease categories in the field of agricultural diseases. However, current plant disease image classification methods can only predict the disease category and do not offer explanations for the characteristics of the predicted disease images. Due to the current situation, this paper employed image description generation technology to produce distinct descriptions for different plant disease categories. A two-stage model called DIC-Transformer, which encompasses three tasks (detection, interpretation, and classification), was proposed. In the first stage, Faster R-CNN was utilized to detect the diseased area and generate the feature vector of the diseased image, with the Swin Transformer as the backbone. In the second stage, the model utilized the Transformer to generate image captions. It then generated the image feature vector, which is weighted by text features, to improve the performance of image classification in the subsequent classification decoder. Additionally, a dataset containing text and visualizations for agricultural diseases (ADCG-18) was compiled. The dataset contains images of 18 diseases and descriptive information about their characteristics. Then, using the ADCG-18, the DIC-Transformer was compared to 11 existing classical caption generation methods and 10 image classification models. The evaluation indicators for captions include Bleu1–4, CiderD, and Rouge. The values of BLEU-1, CIDEr-D, and ROUGE were 0.756, 450.51, and 0.721. The results of DIC-Transformer were 0.01, 29.55, and 0.014 higher than those of the highest-performing comparison model, Fc. The classification evaluation metrics include accuracy, recall, and F1 score, with accuracy at 0.854, recall at 0.854, and F1 score at 0.853. The results of DIC-Transformer were 0.024, 0.078, and 0.075 higher than those of the highest-performing comparison model, MobileNetV2. The results indicate that the DIC-Transformer outperforms other comparison models in classification and caption generation.
Effects of ethephon on heartwood formation and related physiological indices of Dalbergia odorifera T. Chen
Authors: Zhu Yuan-Jing , Li Jia-Wen , Meng Hui , He Wen-Jie , Yang Yun , Wei Jian-He
Published: January 2024

Introduction

Dalbergia odorifera T. Chen, known as fragrant rosewood, is a rare and endangered tree species. Studies have shown that plant growth regulators can effectively promote heartwood formation. This study aimed to investigate the effects of ethephon (ETH) on heartwood formation and the influence of ethephon and hydrogen peroxide (H2O2) on the physiological characteristics in D. odorifera.

Methods

D. odorifera branches underwent treatment with 2.5% plant growth regulators, including ETH, jasmonic acid (JA), salicylic acid (SA), abscisic acid (ABA), H2O2, and inhibitors such as ascorbic acid (AsA) to inhibit H2O2 synthesis, and (S) -trans 2-amino-4 - (2-aminoethoxy) -3-butene (AVG) to inhibit ethylene synthesis. After a 14-day period, we conducted an analysis to evaluate the impact of these plant growth regulators on elongation distance, vessel occlusion percentage, and trans-nerol content. Additionally, the effects of ETH and H2O2 on endogenous plant hormones, H2O2 content, soluble protein content, and enzyme activity were investigated within 0-48 h of treatment.

Results

After treatment with ETH for 14 days, the extension distance of the heartwood material was 15 cm, while the trans-nerolol content was 15 times that of the ABA group. ETH and H2O2 promoted endogenous ethylene synthesis; Ethylene content peaked at 6 and 18 h. The peak ethylene content in the ETH group was 68.07%, 12.89%, and 20.87% higher than the initial value of the H2O2 group and ddH2O group, respectively, and 29.64% higher than that in the AVG group. The soluble protein content and activity of related enzymes were significantly increased following ETH treatment.

Discussion

ETH exhibited the most impact on heartwood formation while not hindering tree growth. This treatment effectively triggered the production of endogenous ethylene in plants and enhanced the activity of essential enzymes involved in heartwood formation. These findings serve as a valuable reference for future investigations into heartwood formation.
Sucrose synthase gene SUS3 could enhance cold tolerance in tomato
Authors: Li Shouming , Wang Ying , Liu Yuanyuan , Liu Changhao , Xu Wei , Lu Yongen , Ye Zhibiao
Published: January 2024

Tomatoes are susceptible to damage from cold temperatures in all stages of growth. Therefore, it is important to identify genetic resources and genes that can enhance tomato’s ability to tolerate cold. In this study, a population of 223 tomato accessions was used to identify the sensitivity or tolerance of plants to cold stress. Transcriptome analysis of these accessions revealed that SUS3, a member of the sucrose synthase gene family, was induced by cold stress. We further investigated the role of SUS3 in cold stress by overexpression (OE) and RNA interference (RNAi). Compared with the wild type, SUS3-OE lines accumulated less MDA and electrolyte leakage and more proline and soluble sugar, maintained higher activities of SOD and CAT, reduced superoxide radicals, and suffered less membrane damage under cold. Thus, our findings indicate that SUS3 plays a crucial role in the response to cold stress. This study indicates that SUS3 may serve as a direct target for genetic engineering and improvement projects, which aim to augment the cold tolerance of tomato crops.
Cotton-Net: efficient and accurate rapid detection of impurity content in machine-picked seed cotton using near-infrared spectroscopy
Authors: Li Qingxu , Zhou Wanhuai , Zhang Xuedong , Li Hao , Li Mingjie , Liang Houjun
Published: January 2024

Widespread adoption of machine-picked cotton in China, the impurity content of seed cotton has increased significantly. This impurity content holds direct implications for the valuation of seed cotton and exerts a consequential influence on the ensuing quality of processed lint and textiles. Presently, the primary approach for assessing impurity content in seed cotton primarily depends on semi-automated testing instruments, exhibiting suboptimal detection efficiency and not well-suited for the impurity detection requirements during the purchase of seed cotton. To address this challenge, this study introduces a seed cotton near-infrared spectral (NIRS) data acquisition system, facilitating the rapid collection of seed cotton spectral data. Three pretreatment algorithms, namely SG (Savitzky-Golay convolutional smoothing), SNV (Standard Normal Variate Transformation), and Normalization, were applied to preprocess the seed cotton spectral data. Cotton-Net, a one-dimensional convolutional neural network aligned with the distinctive characteristics of the seed cotton spectral data, was developed in order to improve the prediction accuracy of seed cotton impurity content. Ablation experiments were performed, utilizing SELU, ReLU, and Sigmoid functions as activation functions. The experimental outcomes revealed that after normalization, employing SELU as the activation function led to the optimal performance of Cotton-Net, displaying a correlation coefficient of 0.9063 and an RMSE (Root Mean Square Error) of 0.0546. In the context of machine learning modeling, the LSSVM model, developed after Normalization and Random Frog algorithm processing, demonstrated superior performance, achieving a correlation coefficient of 0.8662 and an RMSE of 0.0622. In comparison, the correlation coefficient of Cotton-Net increased by 4.01%. This approach holds significant potential to underpin the subsequent development of rapid detection instruments targeting seed cotton impurities.
The self and conscious experience
Authors: Marchetti Giorgio
Published: January 2024

The primary determinant of the self (S) is the conscious experience (CE) we have of it. Therefore, it does not come as a surprise that empirical research on S mainly resorts to the CE (or lack of CE) that subjects have of their S. What comes as a surprise is that empirical research on S does not tackle the problem of how CE contributes to building S. Empirical research investigates how S either biases the cognitive processing of stimuli or is altered through a wide range of means (meditation, hypnosis, etc.). In either case, even for different reasons, considerations of how CE contributes to building S are left unspecified in empirical research. This article analyzes these reasons and proposes a theoretical model of how CE contributes to building S. According to the proposed model, the phenomenal aspect of consciousness is produced by the modulation—engendered by attentional activity—of the energy level of the neural substrate (that is, the organ of attention) that underpins attentional activity. The phenomenal aspect of consciousness supplies the agent with a sense of S and informs the agent on how its S is affected by the agent’s own operations. The phenomenal aspect of consciousness performs its functions through its five main dimensions: qualitative, quantitative, hedonic, temporal, and spatial. Each dimension of the phenomenal aspect of consciousness can be explained by a specific aspect of the modulation of the energy level of the organ of attention. Among other advantages, the model explains the various forms of S as outcomes resulting from the operations of a single mechanism and provides a unifying framework for empirical research on the neural underpinnings of S.
Qualitative study on domestic social robot adoption and associated security concerns among older adults in Slovenia
Authors: Žvanut Boštjan , Mihelič Anže
Published: January 2024

Introduction

Despite the increasing use of domestic social robots by older adults, there remains a significant knowledge gap regarding attitudes, concerns, and potential adoption behavior in this population. This study aims to categorize older adults into distinct technology adoption groups based on their attitudes toward domestic social robots and their behavior in using the existing technology.

Methods

An exploratory qualitative research design was used, involving semi-structured interviews with 24 retired Slovenian older adults aged 65 years or older, conducted between 26 June and 14 September 2023.

Results

Four distinct groups of older adults were identified: (1) Cautious Optimists, (2) Skeptical Traditionalists, (3) Positive Optimists, and (4) Technophiles based on eight characteristics.

Discussion

These groups can be aligned with the categories of the Diffusion of Innovation Theory. Privacy and security concerns, influenced by varying levels of familiarity with the technology, pose barriers to adoption. Perceived utility and ease of use vary considerably between groups, highlighting the importance of taking into account the different older adults. The role of social influence in the adoption process is complex, with some groups being more receptive to external opinions, while others exhibit more autonomous decision-making.
The health status, social support, and subjective well-being of older individuals: evidence from the Chinese General Social Survey
Authors: Zhang Yuchen , Sun Longyu
Published: January 2024

Objectives

This study aims to investigate the impact of health status and social support on the subjective well-being of older individuals.

Methods

Using data from the China General Social Survey 2017, this research analyzed 5,187 Chinese citizens aged 60 years and older. The predicted effect of each variable on subjective well-being was evaluated through hierarchical regression analysis. The direct and indirect effects of social support and health status on subjective well-being are examined based on a structural equation model.

Results

The mental health and social support positively impact subjective well-being. Mental health mediates the effect of physical health on subjective well-being, and social support mediates the relationship between physical and mental health and subjective well-being.

Conclusion

The findings provide strong evidence for the interrelationship mechanisms among the factors influencing subjective well-being. Consequently, improving mental health services and social support systems is advantageous for enhancing the well-being of Chinese seniors.
Quantum retrodiction in Gaussian systems and applications in optomechanics
Authors: Lammers Jonas , Hammerer Klemens
Published: January 2024

What knowledge can be obtained from the record of a continuous measurement about the quantum state of the measured system at the beginning of the measurement? The task of quantum state retrodiction, the inverse of the more common state prediction, is rigorously addressed in quantum measurement theory through retrodictive positive operator-valued measures (POVMs). This introduction to this general framework presents its practical formulation for retrodicting Gaussian quantum states using continuous-time homodyne measurements and applies it to optomechanical systems. We identify and characterize achievable retrodictive POVMs in common optomechanical operating modes with resonant or off-resonant driving fields and specific choices of local oscillator frequencies in homodyne detection. In particular, we demonstrate the possibility of a near-ideal measurement of the quadrature of the mechanical oscillator, giving direct access to the position or momentum distribution of the oscillator at a given time. This forms the basis for complete quantum state tomography, albeit in a destructive manner.
Differences between 48 and 72-hour intervals on match load and subsequent recovery: a report from the Brazilian under-20 national football team
Authors: Wilke Carolina Franco , Coimbra Cândido Celso , Drummond Filipe R. , Drummond Lucas Rios , Campos Helton Oliveira , Kanope Tane , Ramos Guilherme Passos
Published: January 2024

Purpose

To compare the external and internal load and subsequent recovery of football players after international tournament matches separated by 48 h vs. 72 h.

Methods

A total of 14 male football players from the Brazilian National Team, competing in the 2019 South American Under-20 Championship, participated in the study. Match load was quantified using GPS variables and perceived exertion ratings (1). Additionally, before and 13–15 h after each match, players answered questions about the number of hours and quality of sleep, recovery status, and muscle soreness (0–10) and provided a blood sample for creatine kinase and reactive C-protein analysis. Values of all variables were compared between matches played with 48-h intervals (matches 1–4) and 72-h intervals (matches 5–8).

Results

No significant differences in performance or perceptual parameters were observed between matches (p = 0.136–0.953). However, CK was higher in matches 1–4 compared to matches 5 and 6; and ΔPCR was higher in matches 2 and 3 compared to matches 5 and 6, and in match 4 compared to matches 5 and 8.

Conclusions

After matches with a 48-h rest interval, players showed increased markers of inflammation and muscle damage compared to matches with a 72-h rest interval.
European Society for Organ Transplantation (ESOT) Consensus Statement on Outcome Measures in Liver Transplantation According to Value-Based Health Care
Authors: Carbone Marco , Neuberger James , Rowe Ian , Polak Wojciech G. , Forsberg Anna , Fondevila Constantino , Mantovani Lorenzo , Nardi Alessandra , Colli Agostino , Rockell Karen , Schick Liz , Cristoferi Laura , Oniscu Gabriel C. , Strazzabosco Mario , Cillo Umberto
Published: January 2024

Liver transplantation is a highly complex, life-saving, treatment for many patients with advanced liver disease. Liver transplantation requires multidisciplinary teams, system-wide adaptations and significant investment, as well as being an expensive treatment. Several metrics have been proposed to monitor processes and outcomes, however these lack patient focus and do not capture all aspects of the process. Most of the reported outcomes do not capture those outcomes that matter to the patients. Adopting the principles of Value-Based Health Care (VBHC), may provide an opportunity to develop those metrics that matter to patients. In this article, we present a Consensus Statement on Outcome Measures in Liver Transplantation following the principles of VBHC, developed by a dedicated panel of experts under the auspices of the European Society of Organ Transplantation (ESOT) Guidelines’ Taskforce. The overarching goal is to provide a framework to facilitate the development of outcome measures as an initial step to apply the VMC paradigm to liver transplantation.
New Trends in Civic Activism
in Central and Eastern Europe
Authors: Pietrzyk-Reeves Dorota
Published: January 2024

Transitions, democratization and recent democratic backsliding in CEE provide
a rich context for examining the meaning and shifting of civic activism and how people
participate and organize in civil society today. This article offers a fresh and comparative
analysis based on empirical data on the question of what motivates formal and informal
activism, and the potentially transformative role of civil society that has recently faced
such challenges as democratic backsliding, shrinking public space and polarization. It
looks specifically at the responses of Polish and Hungarian activists and advocacy CSOs
to these new challenges. Their strategies bring an important lesson on how civil society
actors can adapt, continue their mission, or even turn challenges into opportunities.
These new trends indicate that civic space in CEE is shifting which is further influenced
by the reactions to new forms of social, economic and political crises. It is argued that
this shift and the new trends in civic activism require not only fresh empirical data, but
also a revision of normative and methodological approaches that have so far been used
in civil society and social movement research.
Civil Society in the Crosshairs
Authors: Kákai László , Glied Viktor
Published: January 2024

As a result of permanent crises, changing political circumstances, rise of populism and overwhelming socio-cultural conflicts, recently liberal democracy is on the decline. This process strongly affects the civil sector, which in the 21st century is still considered one of the main defenders of democracy and human rights. Civil sector also performs a couple of functions that help them try to monitor the state (watchdog function), protect citizens, minorities, human rights, environment, animals etc. and provide a normative behavioural attitude. Nowadays in many countries the activities of civil organizations are restricted, displaced or terminated. Focusing on those countries where democratic backsliding process can be clearly observed, this study examines the background and forms of the process by which civils turned from partners to “enemies” in the last decade.
Doping Knowledge as an Indicator to Measure the Development Level of Civil Society
Authors: Balcerek-Kosiarz Marta , Balcerek Tomasz
Published: January 2024

The aim of the paper is to present the model of Polish civil society development in sport, which is based on three phases: the first one consists in creating rules by international organizations; in the second one public authorities introduce legal regulations based on previously developed organizational standards; in turn, the third phase relies on checking to what extent these rules and regulations have been internalized by their addresses. The indicator for measuring the level of development of civil society in sport was the knowledge of the legal concept of doping among members of Polish national teams.
Analysis of Energy and Thermal Performance of High-Altitude Airship under Variable Attitude
Authors: Zhang Bangchu , Fu Hao , Zhu Weiyu , Yang Kuijian , Xu Yuanming
Published: January 2024

The thermal problem of high-altitude airships has an essential impact on position control and energy system performance. Adjusting the airship’s attitude angle causes differences in thermal performance during position alterations. This paper studies an airship’s energy and thermal performance under variable attitudes. We establish an airship solar radiation and thermal model to analyze power output under different thermal conditions. The thermal performance of airships at varying pitch angles is investigated using computational fluid dynamic (CFD) software (Fluent V6.3.26). To determine the optimal distribution of pitch angles under various conditions, we have developed an optimization model that considers both the presence and absence of thermal influence. We have also assessed the impact of airship geometric parameters on the optimal pitch angle, considering the diversity of airship shapes. Our results demonstrate that pitch angle alterations significantly influence airships’ temperature and flow field distribution. But the degree of necessity of considering the thermal effect in calculating the optimal pitch angle distribution varies depending on the date and latitude, with the most vital need observed during low-latitude summer and the weakest during high-latitude winter. The findings of this research have significant reference value in selecting operation strategies and the control of operating performance for high-altitude airships.