Efficacy and safety of robotic Cyberknife radiotherapy in uveal melanoma: a systematic review and meta-analysis.

Objectives: This systematic review is aimed to evaluate the efficacy and safety of robotic Cyberknife radiotherapy (CKRT) in the treatment of uveal melanoma (UM).

Methods: Clinical studies published in English that assessed the efficacy and safety of robotic CKRT in UM were systematically searched in PubMed, Web of Science, Cochrane and Embase from inception to July 2023. Studies reporting extraocular tumours or other radiosurgery approaches were excluded.

Response of overlying masonry structure induced by double track EPBM cutting through cemented soil composite pile foundation field measurements and numerical analysis.

This article uses the engineering background of the Zhengzhou Metro Line 5 with a cement-soil group pile composite foundation. It simplifies the composite foundation using the area-weighted composite modulus method and establishes a finite element model of a double-line EPBM passing beneath the cement-soil group pile composite foundation building. The calculation results were compared and validated against monitoring data.

Small molecules that targeting p53 Y220C protein: mechanisms, structures, and clinical advances in anti-tumor therapy.

The p53 protein is regarded as the "Guardian of the Genome," but its mutation is tumor progression and present in more than half of malignant tumors. The pro-metastatic property of mutant p53 makes a strong argument for targeting mutant p53 with new therapeutic strategies. However, mutant p53 was considered as a challenging target for drug discovery due to the lack of small molecular binding pockets.

Unraveling diabetic kidney disease: insights from single-cell RNA sequencing.

The incidence of diabetic kidney disease (DKD) is rising annually. Diabetes leads to structural damage and dysfunction in the kidneys, clinically manifesting as progressive proteinuria and declining renal function, ultimately resulting in end-stage renal disease (ESRD). Recent findings have identified a subset of DKD known as normoalbuminuric diabetic kidney disease (NADKD), characterized by normal urine albumin levels but reduced renal function.

Cadmium translocation combined with metabolomics analysis revealed potential mechanisms of MT@MSN-CS and GSH@MSN-CS in reducing cadmium accumulation in rice (Oryza sativa L.) grains.

Applying nano-delivery systems for phytohormones via foliar application has proven effective in reducing grain cadmium (Cd) levels in crops. However, the mechanisms underlying this reduction remain inadequately understood. This study integrated the determination of leaf photosynthetic parameters, Cd translocation analysis, and metabolomics to elucidate the effects of reduced glutathione (GSH) and melatonin (MT), delivered with or without chitosan-encapsulated mesoporous silica nanoparticles (MSN-CS), on grain Cd levels in rice.

Modified Green-Ampt model for infiltration analysis in loess area and its parameter determination and verification.

Water infiltration into soil is important in geotechnical engineering. The classical Green-Ampt (GA) infiltration model is widely used in soil infiltration due to its physical significance, but it ignores the actual unsaturated layer in the infiltration process and has some deficiencies. Thus, the present study established a modified GA infiltration model (MLGA model) using Darcy's infiltration law and continuity equation to fully consider the variation characteristics of the soil water profile in the infiltration process.

Integrated RNA sequencing analysis and machine learning identifies a metabolism-related prognostic signature in clear cell renal cell carcinoma.

The connection between metabolic reprogramming and tumor progression has been demonstrated in an increasing number of researches. However, further research is required to identify how metabolic reprogramming affects interpatient heterogeneity and prognosis in clear cell renal cell carcinoma (ccRCC). In this work, single-cell RNA sequencing (scRNA-seq) based deconvolution was utilized to create a malignant cell hierarchy with metabolic differences and to investigate the relationship between metabolic biomarkers and prognosis.

A Native LH1-RC-HiPIP Supercomplex from an Extremophilic Phototroph.

Halorhodospira (Hlr.) halophila strain BN9622 is an extremely halophilic and alkaliphilic purple phototrophic bacterium and has been widely used as a model for exploring the osmoadaptive and photosynthetic strategies employed by phototrophic extreme halophiles that enable them to thrive in hypersaline environments. Here we present the cryo-EM structures of (1) a unique native Hlr.

The association between sarcopenic obesity, sarcopenia and functional dependence, malnutrition, and mortality: the phenomenon of obesity paradox in sarcopenic obesity.

The aim of this study is to investigate the association between four phenotypes of sarcopenia/obesity in older individuals and functional disability, malnutrition, and all-cause mortality. This study is a cross-sectional study, survival is 3 years. A total of 487 Chinese older adults were included with 283 (58.

Design and experimental study of tillage depth control system for electric rotary tiller based on LADRC.

This paper proposes an adaptive real-time tillage depth control system for electric rotary tillers, based on Linear Active Disturbance Rejection Control (LADRC), to improve tillage depth accuracy in tea garden intercropping with soybeans. The tillage depth control system comprises a body posture sensor, a control unit, and a hybrid stepper motor, integrating sensor data to drive the motor and achieve precise depth control. Real-time displacement sensor signals are compared with target values, enabling closed-loop control of the rotary tiller.

Chinese herbal medicine recognition network based on knowledge distillation and cross-attention.

In order to reduce the number of parameters in the Chinese herbal medicine recognition model while maintaining accuracy, this paper takes 20 classes of Chinese herbs as the research object and proposes a recognition network based on knowledge distillation and cross-attention - ShuffleCANet (ShuffleNet and Cross-Attention). Firstly, transfer learning was used for experiments on 20 classic networks, and DenseNet and RegNet were selected as dual teacher models. Then, considering the parameter count and recognition accuracy, ShuffleNet was determined as the student model, and a new cross-attention mechanism was proposed.

Study on the preparation and design of chenille/polyester integrated yarns and its acoustic properties.

With the rapid development of industrialization and urbanization, the impact of noise on people's health has become an increasingly serious issue, but it is still a challenge for the reducing the noise due to its complex property. Textiles with many loose porous structures have gained much significant attentions, thus chenille yarns with plush fibers on the surface, and polyester monofilament were chosen to fabricate the integrated knitting yarns, and their fundamental and mechanical properties were fully evaluated. The results showed that the diameter and braiding angle of the blended yarns decreased with the increase of pitch, resulting in a linear correlation of R > 0.

Identification of biomarkers for knee osteoarthritis through clinical data and machine learning models.

Knee osteoarthritis (KOA) represents a progressive degenerative disorder characterized by the gradual erosion of articular cartilage. This study aimed to develop and validate biomarker-based predictive models for KOA diagnosis using machine learning techniques. Clinical data from 2594 samples were obtained and stratified into training and validation datasets in a 7:3 ratio.

Investigating lung cancer microenvironment from cell segmentation of pathological image and its application in prognostic stratification.

Lung cancer, particularly adenocarcinoma, ranks high in morbidity and mortality rates worldwide, with a relatively low five-year survival rate. To achieve precise prognostic assessment and clinical intervention for patients, thereby enhancing their survival prospects, there is an urgent need for more accurate stratification schemes. Currently, the TNM staging system is predominantly used in clinical practice for prognostic evaluation, but its accuracy is constrained by the reliance on physician experience.

Comparison of the safety and efficacy of dual antiplatelet therapy versus tenecteplase in patients with minor nondisabling acute ischemic stroke.

To evaluate the safety and efficacy of dual antiplatelet therapy (DAPT) versus tenecteplase in minor non-disabling acute ischemic stroke. This retrospective observational study utilized data from our stroke database. All consecutive patients with minor non-disabling acute ischemic stroke treated with either DAPT or tenecteplase between January 2020 and June 2023 were included in the analysis.

Research on vehicle scheduling for forest fires in the northern Greater Khingan Mountains.

In the face of forest fire emergencies, fast and efficient dispatching of rescue vehicles is an important means of mitigating the damage caused by forest fires, and is an effective method of avoiding secondary damage caused by forest fires, minimizing the damage caused by forest fires to the ecosystem, and mitigating the losses caused by economic development. this paper takes the actual problem as the starting point, constructs a reasonable mathematical model of the problem, for the special characteristics of the emergency rescue vehicle scheduling problem of forest fires, taking into account the actual road conditions in the northern pristine forest area, through the analysis of the cost of paths between the forest area and the highway, to obtain the least obstructed rescue paths, to narrow the gap between the theoretical model and the problem of the actual. Improvement of ordinary genetic algorithm, design of double population strategy selection operation, the introduction of chaotic search initialization population, to improve the algorithm's solution efficiency and accuracy, through the northern pristine forest area of Daxing'anling real forest fire cases and generation of large-scale random fire point simulation experimental test to verify the effectiveness of the algorithm, to ensure that the effectiveness and reasonableness of the solution to the problem of forest fire emergency rescue vehicle scheduling program.

Evaluation of five questionnaires for obstructive sleep apnea screening in the elderly.

Obstructive sleep apnea (OSA) often leads to complications in the elderly. This study compares the usefulness of five screening tools for OSA in elderly patients. Data from elderly patients diagnosed with OSA, collected from the Sleep Medicine Center of the First Affiliated Hospital of Guangzhou Medical University from January 2012 to June 2017, is analyzed.

Development of a mitochondrial mini-barcode and its application in metabarcoding for identification of leech in traditional Chinese medicine.

In Traditional Chinese Medicine (TCM), the medicinal leech is vital for treatments to promote blood circulation and eliminate blood stasis. However, the prevalence of counterfeit leech products in the market undermines the quality and efficacy of these remedies. Traditional DNA barcoding techniques, such as the COI barcode, have been limited in their application due to amplification challenges.

A novel voting measure for identifying influential nodes in complex networks based on local structure.

Identifying influential nodes in real networks is significant in studying and analyzing the structural as well as functional aspects of networks. VoteRank is a simple and effective algorithm to identify high-spreading nodes. The accuracy and monotonicity of the VoteRank algorithm are poor as the network topology fails to be taken into account.

Application of machine learning in depression risk prediction for connective tissue diseases.

This study retrospectively collected clinical data from 480 patients with connective tissue diseases (CTDs) at Nanjing First Hospital between August 2019 and December 2023 to develop and validate a multi-classification machine learning (ML) model for assessing depression risk. Addressing the limitations of traditional assessment tools, six ML models were constructed using univariate analysis and the LASSO algorithm, with the categorical boosting (Catboost) model emerging as the best performer, demonstrating strong predictive ability across different depression severity levels (none_F1 = 0.879, mild_F1 = 0.

The integration of optimizing train timetables with EMU route plans.

Generally, to address the resource management issues in high-speed railway operations, particularly in the context of large-scale networked high-speed train transportation organizations, a phased optimization approach is introduced. This approach divides the problem into two stages: the high-speed train timetabling and the planning of Electric Multiple Unit (EMU) route. The lack of direct integration between these stages has hindered the flexible and efficient utilization of line capacity and EMU resources based on large-scale network, limiting the potential for mutual compensation and coordination among different types of resources across different regions.

Hydropower Station diversion tunnel layered excavation deformation mechanism under high crustal stress.

Aiming at the crucial engineering challenge of the ambiguous excavation deformation mechanism of hard and brittle surrounding rock under high geos-tress conditions, with the right bank diversion tunnel at the dam site of the hydropower station as the research object, the deformation and failure characteristics of the surrounding rock and their formation mechanisms during the layered excavation of the diversion tunnel were investigated. The research findings show: (1) The main factors influencing the deformation of the diversion tunnel's surrounding rock are the high ground stress environment, the degree of fracture development in the rock mass, and the effectiveness of the support system. (2) Following the excavation of the first layer, extensive shallow damage predominates, with damaged blocks primarily exhibiting sheet-like and plate-like forms.

Small protein ERSP encoded by LINC02870 promotes triple negative breast cancer progression via IRE1α/XBP1s activation.

Clinical treatment options for triple-negative breast cancer (TNBC) are currently limited to chemotherapy because of a lack of effective therapeutic targets. Recent evidence suggests that long noncoding RNAs (lncRNAs) encode bioactive peptides or proteins, thereby playing noncanonical yet significant roles in regulating cellular processes. However, the potential of lncRNA-translated products in cancer progression remains largely unknown.

Preparation and mechanical performance of fluorite tailings geopolymer precursor under alkaline heat activation.

As one of the bulk solid wastes in the Yellow River basin in China, fluorite tailings urgently need to be utilized as resources. In this paper, NaOH and NaCO were used for alkali thermal activation of ground fluorite tailings under different temperature conditions, and the reactivity was analyzed by XRD, SEM and compressive strength after hydration, so as to evaluate the feasibility of fluorite tailings as geopolymer precursor. The results show that the fluorite tailings can exhibit certain reactivity under alkaline heat excitation, and significant amorphous glass phase can be detected.