Miracle-dz/UniFAR-FTUs huggingface dataset:
Prognostic and clinicopathological effect of the prognostic nutritional index (PNI) in patients with cervical cancer: a meta-analysis

Abstract Background Numerous studies have explored whether the prognostic nutritional index (PNI) can predict the prognosis of cervical cancer (CC); however, their findings remain controversial. This meta-analysis focused on evaluating the relationship between the PNI and the prognosis of patients with CC. Methods Relevant articles were collected from specific databases up to March 16, 2023. The relationship between the PNI and survival outcomes in patients with CC was estimated using combined hazard ratios (HRs) and associated 95% confidence intervals (CIs). The association of the PNI with clinicopathological features in patients with CC was assessed by combining odds ratios (ORs) and associated 95% CIs. Results Nine articles with 2508 cases were included in the meta-analysis. According to our pooled findings, a decreased PNI showed a significant association with worse overall survival (OS) (HR = 2.98, 95% CI = 2.22–3.99, p < .001) as well as progression-free survival (PFS) (HR = 2.43, 95% CI = 1.92–3.07, p < .001) in patients with CC. The subgroup analysis indicated that the results were reliable. Moreover, the decreased PNI showed a significant association with the presence of lymph node metastasis (LN metastasis, OR = 1.53, 95% CI = 1.04–82.24, p = .030) and maximum tumor size >4 cm (OR = 1.73, 95% CI = 1.21–2.46, p = .002). However, the PNI was not significantly associated with histology, differentiation, or FIGO stage. Conclusion In this study, a low PNI predicted dismal OS and PFS in patients with CC, who also tend to suffer from LN metastasis and larger tumor size. PNI is a promising biomarker for predicting the prognosis of patients with CC in clinical practice.
The diagnostic value of machine learning for the classification of malignant bone tumor: a systematic evaluation and meta-analysis

Background Malignant bone tumors are a type of cancer with varying malignancy and prognosis. Accurate diagnosis and classification are crucial for treatment and prognosis assessment. Machine learning has been introduced for early differential diagnosis of malignant bone tumors, but its performance is controversial. This systematic review and meta-analysis aims to explore the diagnostic value of machine learning for malignant bone tumors. Methods PubMed, Embase, Cochrane Library, and Web of Science were searched for literature on machine learning in the differential diagnosis of malignant bone tumors up to October 31, 2022. The risk of bias assessment was conducted using QUADAS-2. A bivariate mixed-effects model was used for meta-analysis, with subgroup analyses by machine learning methods and modeling approaches. Results The inclusion comprised 31 publications with 382,371 patients, including 141,315 with malignant bone tumors. Meta-analysis results showed machine learning sensitivity and specificity of 0.87 [95% CI: 0.81,0.91] and 0.91 [95% CI: 0.86,0.94] in the training set, and 0.83 [95% CI: 0.74,0.89] and 0.87 [95% CI: 0.79,0.92] in the validation set. Subgroup analysis revealed MRI-based radiomics was the most common approach, with sensitivity and specificity of 0.85 [95% CI: 0.74,0.91] and 0.87 [95% CI: 0.81,0.91] in the training set, and 0.79 [95% CI: 0.70,0.86] and 0.79 [95% CI: 0.70,0.86] in the validation set. Convolutional neural networks were the most common model type, with sensitivity and specificity of 0.86 [95% CI: 0.72,0.94] and 0.92 [95% CI: 0.82,0.97] in the training set, and 0.87 [95% CI: 0.51,0.98] and 0.87 [95% CI: 0.69,0.96] in the validation set. Conclusion Machine learning is mainly applied in radiomics for diagnosing malignant bone tumors, showing desirable diagnostic performance. Machine learning can be an early adjunctive diagnostic method but requires further research and validation to determine its practical efficiency and clinical application prospects. Systematic review registration https://www.crd. york.ac. uk/prospero/, identifier CRD42023387057.
Simulation of Initial Streamer Discharge in Mineral Transformer Oil Considering Multiple Ionized Molecular Clusters

A simulation model of needle-plate electrode discharge in mineral transformer oil is established on COMSOL finite element simulation software. In order to investigate the influence of multi/single ionized molecular clusters on streamer discharge in oil, numerical calculations were conducted for the charged particles in the discharge model, considering different ionized molecular clusters, voltage peaks, and voltage rise times. The electric field distribution along the $z$ -axis and branching direction, as well as the distribution characteristics of the charged particles, were analyzed. The simulation results indicate that under different ionized molecular cluster conditions, streamer branching forms near the needle electrode. When considering multiple ionized molecular clusters, the morphology of the streamer is determined by the low ionization potential molecular clusters, while high ionization potential molecular clusters affect the electric field strength inside the streamer channel. The development of the streamer exhibits a staged propagation, which is more significant when considering only high ionization potential molecular clusters. Higher voltage peak will cause the streamer to propagate farther and form secondary streamer more easily. Faster voltage rise times facilitate the formation and propagation of the streamer, and the thickness of the streamer head is positively correlated with the voltage rise time. This study contributes further understanding of the mechanisms behind streamer discharge in liquid dielectrics, with mineral transformer oil serving as a representative medium.
Using High-Throughput Phenotyping Analysis to Decipher the Phenotypic Components and Genetic Architecture of Maize Seedling Salt Tolerance

Soil salinization is a worldwide problem that limits agricultural production. It is important to understand the salt stress tolerance ability of maize seedlings and explore the underlying related genetic resources. In this study, we used a high-throughput phenotyping platform with a 3D laser sensor (Planteye F500) to identify the digital biomass, plant height and normalized vegetation index under normal and saline conditions at multiple time points. The result revealed that a three-leaf period (T3) was identified as the key period for the phenotypic variation in maize seedlings under salt stress. Moreover, we mapped the salt-stress-related SNPs and identified candidate genes in the natural population via a genome-wide association study. A total of 44 candidate genes were annotated, including 26 candidate genes under normal conditions and 18 candidate genes under salt-stressed conditions. This study demonstrates the feasibility of using a high-throughput phenotyping platform to accurately, continuously quantify morphological traits of maize seedlings in different growing environments. And the phenotype and genetic information of this study provided a theoretical basis for the breeding of salt-resistant maize varieties and the study of salt-resistant genes.
Mantle plume activity and melting conditions： Evidence from olivines in picritic-komatiitic rocks from the Emeishan Large Igneous Province, southwestern China

ical compositions are used to identify primitive picrite basalts from the early part of flood basalt successions in the western part of the Emeishan large igneous province (ELIP), southwestern China. The Fo contents of olivine phenocrysts of komatiites with MgO ~21.79 wt% range from 85.2% to 91.4%. The composition of unerupted parental melts is calculated from the compositions of the most Fo-rich olivine phenocrysts. These melts had ~22 wt% MgO, and originated in mantle with a potential temperature of ~1600 ̊C and at about 4.2 GPa pressure, supporting the conclusion that the generation of ELIP can be attributed to melting of a plume head beginning at ~138 km depth.
Genetic characteristics, antimicrobial susceptibility, and virulence genes distribution of Campylobacter isolated from local dual-purpose chickens in central China

Food-borne antibiotic-resistant Campylobacter poses a serious threat to public health. To understand the prevalence and genetic characteristics of Campylobacter in Chinese local dual-purpose (meat and eggs) chickens, the genomes of 30 Campylobacter isolates, including 13 C. jejuni and 17 C. coli from Jianghan-chickens in central China, were sequenced and tested for antibiotic susceptibility. The results showed that CC-354 and CC-828 were the dominant clonal complexes of C. jejuni and C. coli, respectively, and a phylogenetic analysis showed that three unclassified multilocus sequence types of C. coli were more closely genetically related to C. jejuni than to other C. coli in this study. Of the six antibiotics tested, the highest resistance rates were to ciprofloxacin and tetracycline (100%), followed by lincomycin (63.3%), erythromycin (30.0%), amikacin (26.7%), and cefotaxime (20.0%). The antibiotic resistance rate of C. coli was higher than that of C. jejuni. The GyrA T86I mutation and 15 acquired resistance genes were detected with whole-genome sequencing (WGS). Among those, the GyrA T86I mutation and tet(O) were most prevalent (both 96.7%), followed by the blaOXA-type gene (90.0%), ant(6)-Ia (26.7%), aac(6’)-aph(3’’) (23.3%), erm(B) (13.3%), and other genes (3.3%). The ciprofloxacin and tetracycline resistance phenotypes correlated strongly with the GyrA T86I mutation and tet(O)/tet(L), respectively, but for other antibiotics, the correlation between genes and resistance phenotypes were weak, indicating that there may be resistance mechanisms other than the resistance genes detected in this study. Virulence gene analysis showed that several genes related to adhesion, colonization, and invasion (including cadF, porA, ciaB, and jlpA) and cytolethal distending toxin (cdtABC) were only present in C. jejuni. Overall, this study extends our knowledge of the epidemiology and antibiotic resistance of Campylobacter in local Chinese dual-purpose chickens.
Multiple craniotomies for the resection of symptomatic multifocal intracranial metastatic cardiac myxoma: A case report

Background: Myxomas, rare benign mesenchymal lesions, are the most common cardiac tumors. Patients may rarely develop hematogenous metastasis to the brain, which can present as new-onset neurological deficits that correlate with multifocal hemorrhagic lesions on imaging. Limited guidelines presently exist for the treatment of such lesions. This report outlines a unique case involving three craniotomies and failed radiation therapy in the treatment of metastatic cardiac myxoma. Case Description: A 63-year-old woman presented with a right middle cerebral artery embolic stroke secondary to a left atrial myxoma and multifocal hemorrhagic lesions consistent with intracranial metastasis. She had a right frontal craniotomy for tumor resection, followed by stereotactic radiosurgery, though this did not arrest disease progression. She later had a left occipital craniotomy for a symptomatic lesion. More than two years after her initial presentation, she returned with acute-onset symptoms correlating to growth in a left frontal lesion requiring another resection. Following this third craniotomy, imaging has not revealed the progression of metastatic intracranial disease. She is pursuing further treatment through primary cardiac tumor resection. Conclusion: Although rare, hematogenous seeding with subsequent formation of hemorrhagic metastasis is a possible complication of atrial myxoma. While surgical resection, radiation therapy, and chemotherapy have historically been used, no standard of care currently exists. This case demonstrates repeat tumor resection as effective for managing symptomatic intracranial metastatic myxoma in a patient with poor response to radiation therapy and multiple recurrences, with follow-up showing improvement in neurological symptoms and mass effect and absence of recurrence on imaging.
Effect of Health Literacy Intervention on Glycemic Control and Renal Function Among Thai Older Adults at Risk of Type 2 Diabetes Mellitus

Purpose Diabetes patients with low health literacy often have poor health and clinical outcomes. The study aimed to assess the effectiveness of a health literacy intervention on glycemic control and renal function among Thai older adults at risk of type 2 diabetes mellitus (T2DM). Methods A quasi-experimental study was carried out in rural areas of Phayao Province in northern Thailand. The participants were older adults with T2DM who recorded blood glucose levels ranging from 140 to 180 mg/dL and who were not receiving prescribed medication. The intervention lasted 12 weeks, and data were collected at three points: baseline, post-intervention, and at 3 months’ follow-up. The study outcomes included the measurement of fasting blood sugar (FBS), hemoglobin A1C (HbA1c), and glomerular filtration rate (eGFR) levels after the intervention. A linear mixed model and generalized estimating equations model were used to assess the intervention effect for continuous and binary outcomes, respectively. Results From baseline to post-intervention, FBS and HbA1c decreased more in the intervention group than in the control group by 8.2 mg/dL (p < 0.001) and 0.1% (p = 0.029), respectively, whereas eGFR increased by 8.0 mL/min/1.73m2 (p < 0.001). The absolute effect of the intervention at follow-up was −9.8 units for FBS, −0.4 units for HbA1c, and 14.0 units for eGFR. Abnormal HbA1c level (≥6.5%) of the intervention group was reported as 70.3% at baseline, 31.3% at post-intervention, and 9.4% at follow-up. Compared to baseline levels, the T2DM patients who received the intervention were 0.31 times less likely to have abnormal HbA1c levels than the control subjects at follow-up (p = 0.003) who received no intervention. Conclusion Our findings suggest that this intervention may potentially improve diabetes self-management and prevention behaviors, thereby reducing the diabetes burden in rural communities in northern Thailand.
Effect of Combined Levothyroxine (L-T4) and 3-Iodothyronamine (T1AM) Supplementation on Memory and Adult Hippocampal Neurogenesis in a Mouse Model of Hypothyroidism

Mood alterations, anxiety, and cognitive impairments associated with adult-onset hypothyroidism often persist despite replacement treatment. In rodent models of hypothyroidism, replacement does not bring 3-iodothyronamine (T1AM) brain levels back to normal. T1AM is a thyroid hormone derivative with cognitive effects. Using a pharmacological hypothyroid mouse model, we investigated whether augmenting levothyroxine (L-T4) with T1AM improves behavioural correlates of depression, anxiety, and memory and has an effect on hippocampal neurogenesis. Hypothyroid mice showed impaired performance in the novel object recognition test as compared to euthyroid mice (discrimination index (DI): 0.02 ± 0.09 vs. 0.29 ± 0.06; t = 2.515, p = 0.02). L-T4 and L-T4+T1AM rescued memory (DI: 0.27 ± 0.08 and 0.34 ± 0.08, respectively), while T1AM had no effect (DI: −0.01 ± 0.10). Hypothyroidism reduced the number of neuroprogenitors in hippocampal neurogenic niches by 20%. L-T4 rescued the number of neuroprogenitors (mean diff = 106.9 ± 21.40, t = 4.99, pcorr = 0.003), while L-T4+T1AM produced a 30.61% rebound relative to euthyroid state (mean diff = 141.6 ± 31.91, t = 4.44, pcorr = 0.004). We performed qPCR analysis of 88 genes involved in neurotrophic signalling pathways and found an effect of treatment on the expression of Ngf, Kdr, Kit, L1cam, Ntf3, Mapk3, and Neurog2. Our data confirm that L-T4 is necessary and sufficient for recovering memory and hippocampal neurogenesis deficits associated with hypothyroidism, while we found no evidence to support the role of non-canonical TH signalling.
Хімія харчових продуктів і матеріалів / Chemistry of food products and materials

The extensive use of nuclear technologies is fraught with risks of the adverse effect of ionising radiation on the human body. So, new and effective means of preventing radiation damage should be searched for. We have searched through scientific editions and databases for information on radioprotective effects of edible and aromatic plants, radiation nephropathy, and plant-derived substances that can prevent it. Methods that allow analysing, systematising, comparing, and summarising data have been applied. The paper gives an overview of the experimental findings obtained by domestic and foreign scientists from their phytochemical and clinical studies of the radioprotective effects of bioactive substances contained in edible and aromatic plants. It has been found that polyphenolic compounds in plants, due to their antioxidant properties, can neutralise free radicals (thus inhibiting radiation-induced chain reactions of oxidation in cells), scavenge and neutralise lipoperoxyl radicals, and chelate metal ions (which are important as free radical reaction initiators). Besides, these compounds are antimutagenic. Radiotherapy can cause various radiation-induced kidney disorders, including radiation nephropathy. Nowadays, scientists are actively searching for promising plant-derived substances that could prevent and alleviate radiation nephropathy. It is an obvious renoprotective strategy to administer radioprotective agents containing polyphenolic compounds preventively, prior to radiation treatment. It has been shown how promising it is to continue phytochemical, pharmacodynamic, and toxicological research into the properties of polyphenolic compounds in edible and aromatic plants, as this research aims at using them as a basis in creating new effective remedies to prevent and treat radiation damage.
The Tornado : its structure, dynamics, prediction, and hazards

In undergoing this life, many people always try to do and get the best. New knowledge, experience, lesson, and everything that can improve the life will be done. However, many people sometimes feel confused to get those things. Feeling the limited of experience and sources to be better is one of the lacks to own. However, there is a very simple thing that can be done. This is what your teacher always manoeuvres you to do this one. Yeah, reading is the answer. Reading a book as this the tornado its structure dynamics prediction and hazards and other references can enrich your life quality. How can it be?
The Rise in Women’s Labor-Force Participation in Mexico—Supply vs. Demand Factors

This study estimates the relative importance of alternative supply and demand mechanisms in explaining the rise of female labor-force participation (FLFP) over the last 55 years in Mexico. The growth of FLFP in Mexico between 1960 and 2015 followed an S-shaped, with a considerable acceleration during the 1990s. Using descriptive decomposition methods and a shift-share design, the study shows that, put together, supply and demand factors can account for most of the rise of FLFP over the entire period, led by increases in women’s education, declining fertility, and shifts in the occupational structure of the workforce. However, there is unexplained variation in the 1990s, when FLFP spiked.
Knowledge-based urban development in China

This Jhesis starts with a conceptual exploration of broad disciplines related to the emerging field of Knowledge-Based Urban Development (KBUD) , upon which it developed understanding of the holistic meaning of KBUD. It argues that the need for knowledge for KBUD should include all types of knowledge the wisdom and that KBUD, in particular knowledge city, is to enhance urban social, economic, cultural, and environmental sustainability in a balanced manner. The fundamental of knowledge city lies on its justice and inclusion, which is developed equally for all. Building upon the theoretical arguments it made, this research developed an analytical framework for analysing knowledge city. By applying the framework to both international KBUD initiatives and the Chinese case studies, it found that although there seems to be a general trend that suggests that the cities in developed countries have comparative advantages in transforming into knowledge city, the state of development is by no means the determining condition for a city to develop towards KBUD. Rather, the making of knowledge city relies on the ability to engage people of the whole community to establish an efficient institutional mechanism and develop an appropriate policy framework, which encourages and facilitates the creation of a cohesive knowledge environment, especially upgrading the city's knowledge base and fostering a cohering knowledge culture, to mobilise and apply all types of knowledge to serve and rule urban development behaviour so that it corresponds fully to the needs of enhancing the city's social, economic, cultural, and environmental sustainability. The empirical evidence from the Chinese case studies also suggests that the very recent change of China's development ideology, which calls for the development of a "harmonious society" following the "scientific development concept" approach, is meaningful, from the KBUD perspective, only if they are conducive to making connection with and adopted for coordinating localised knowledge creation, transmission and utilisation, which are regulated for the great collective interests, in other words, for people of the whole community, for social equity and inclusion. This thesis ends with offering some recommendations both for China's urban development policy and directions of future research.
Inertial sensors for gait monitoring and design of adaptive controllers for exoskeletons after stroke: a feasibility study

Introduction: Tuning the control parameters is one of the main challenges in robotic gait therapy. Control strategies that vary the control parameters based on the user’s performance are still scarce and do not exploit the potential of using spatiotemporal metrics. The goal of this study was to validate the feasibility of using shank-worn Inertial Measurement Units (IMUs) for clinical gait analysis after stroke and evaluate their preliminary applicability in designing an automatic and adaptive controller for a knee exoskeleton (ABLE-KS). Methods: First, we estimated the temporal (i.e., stride time, stance, and swing duration) and spatial (i.e., stride length, maximum vertical displacement, foot clearance, and circumduction) metrics in six post-stroke participants while walking on a treadmill and overground and compared these estimates with data from an optical motion tracking system. Next, we analyzed the relationships between the IMU-estimated metrics and an exoskeleton control parameter related to the peak knee flexion torque. Finally, we trained two machine learning algorithms, i.e., linear regression and neural network, to model the relationship between the exoskeleton torque and maximum vertical displacement, which was the metric that showed the strongest correlations with the data from the optical system [r = 0.84; ICC(A,1) = 0.73; ICC(C,1) = 0.81] and peak knee flexion torque (r = 0.957). Results: Offline validation of both neural network and linear regression models showed good predictions (R2 = 0.70–0.80; MAE = 0.48–0.58 Nm) of the peak torque based on the maximum vertical displacement metric for the participants with better gait function, i.e., gait speed > 0.7 m/s. For the participants with worse gait function, both models failed to provide good predictions (R2 = 0.00–0.19; MAE = 1.15–1.29 Nm) of the peak torque despite having a moderate-to-strong correlation between the spatiotemporal metric and control parameter. Discussion: Our preliminary results indicate that the stride-by-stride estimations of shank-worn IMUs show potential to design automatic and adaptive exoskeleton control strategies for people with moderate impairments in gait function due to stroke.