Hexaxial external fixator versus intramedullary nail in treating segmental tibial fractures: a retrospective study.

BACKGROUND: It's difficult to treat segmental tibial fractures (STFs), which are intricate injuries associated with significant soft tissue damage. The aim of this study was to compare the clinical effect of hexaxial external fixator (HEF) and intramedullary nail (IMN) in treatment of STFs. METHODS: A total of 42 patients with STFs were finally recruited between January 2018 and June 2022. There were 25 males and 17 females with age range of 20 to 60 years. All fractures were classified as type 42C2 using the Arbeitsgemeinschaftfür Osteosythese/Orthopaedic Trauma Association (AO/OTA) classification. 22 patients were treated with HEF and 20 patients were treated with IMN. The condition of vascular and neural injuries, time of full weight bearing, bone union time and infection rate were documented and analyzed between the two groups. The mechanical medial proximal tibial angle (mMPTA), mechanical posterior proximal tibial angle (mPPTA), mechanical lateral distal tibial angle (mLDTA), mechanical anterior distal tibial angle (mADTA), hospital for special surgery (HSS) knee joint score, American Orthopaedic Foot and Ankle Society (AOFAS) ankle joint score, range of motion (ROM) of flexion of keen joint and ROM of plantar flexion and dorsal flexion of ankle joint were compared between the two groups at the last clinical visit. RESULTS: There were no vascular and neural injuries or other severe complications in both groups. All 22 patients in HEF group underwent closed reduction but 3 patients in IMN group were treated by open reduction. The time of full weight bearing was (11.3 ± 3.2) days in HEF group and (67.8 ± 5.8) days in IMN group(P < 0.05), with bone union time for (6.9 ± 0.8) months and (7.7 ± 1.4) months, respectively(P < 0.05). There was no deep infection in both groups. In the HEF group and IMN group, mMPTA was (86.9 ± 1.5)° and (89.7 ± 1.8)°(P < 0.05), mPPTA was (80.8 ± 1.9)° and (78.6 ± 2.0)°(P < 0.05), mLDTA was (88.5 ± 1.7)° and (90.3 ± 1.7)°(P < 0.05), while mADTA was (80.8 ± 1.5)° and (78.4 ± 1.3)°(P < 0.05). No significant differences were found between the two groups at the last clinical visit concerning HSS knee joint score and AOFAS ankle joint score, ROM of flexion of keen joint and ROM of plantar flexion of ankle joint (P > 0.05). The ROM of dorsal flexion of ankle joint in IMN group was (30.4 ± 3.5)°, better than (21.6 ± 2.8)° in HEF group (P < 0.05). CONCLUSION: In terms of final clinical outcomes, the use of either HEF or IMN for STFs can achieve good therapeutic effects. While HEF is superior to IMN in terms of completely closed reduction, early full weight bearing, early bone union and alignment. Nevertheless, HEF has a greater impact on the ROM of dorsal flexion of the ankle joint, and much more care and adjustment are needed for the patients than IMN.

DiffFSRE: Diffusion-Enhanced Prototypical Network for Few-Shot Relation Extraction.

Supervised learning methods excel in traditional relation extraction tasks. However, the quality and scale of the training data heavily influence their performance. Few-shot relation extraction is gradually becoming a research hotspot whose objective is to learn and extract semantic relationships between entities with only a limited number of annotated samples. In recent years, numerous studies have employed prototypical networks for few-shot relation extraction. However, these methods often suffer from overfitting of the relation classes, making it challenging to generalize effectively to new relationships. Therefore, this paper seeks to utilize a diffusion model for data augmentation to address the overfitting issue of prototypical networks. We propose a diffusion model-enhanced prototypical network framework. Specifically, we design and train a controllable conditional relation generation diffusion model on the relation extraction dataset, which can generate the corresponding instance representation according to the relation description. Building upon the trained diffusion model, we further present a pseudo-sample-enhanced prototypical network, which is able to provide more accurate representations for prototype classes, thereby alleviating overfitting and better generalizing to unseen relation classes. Additionally, we introduce a pseudo-sample-aware attention mechanism to enhance the model's adaptability to pseudo-sample data through a cross-entropy loss, further improving the model's performance. A series of experiments are conducted to prove our method's effectiveness. The results indicate that our proposed approach significantly outperforms existing methods, particularly in low-resource one-shot environments. Further ablation analyses underscore the necessity of each module in the model. As far as we know, this is the first research to employ a diffusion model for enhancing the prototypical network through data augmentation in few-shot relation extraction.

Enhanced Heterogeneous Graph Attention Network with a Novel Multilabel Focal Loss for Document-Level Relation Extraction.

Recent years have seen a rise in interest in document-level relation extraction, which is defined as extracting all relations between entities in multiple sentences of a document. Typically, there are multiple mentions corresponding to a single entity in this context. Previous research predominantly employed a holistic representation for each entity to predict relations, but this approach often overlooks valuable information contained in fine-grained entity mentions. We contend that relation prediction and inference should be grounded in specific entity mentions rather than abstract entity concepts. To address this, our paper proposes a two-stage mention-level framework based on an enhanced heterogeneous graph attention network for document-level relation extraction. Our framework employs two different strategies to model intra-sentential and inter-sentential relations between fine-grained entity mentions, yielding local mention representations for intra-sentential relation prediction and global mention representations for inter-sentential relation prediction. For inter-sentential relation prediction and inference, we propose an enhanced heterogeneous graph attention network to better model the long-distance semantic relationships and design an entity-coreference path-based inference strategy to conduct relation inference. Moreover, we introduce a novel cross-entropy-based multilabel focal loss function to address the class imbalance problem and multilabel prediction simultaneously. Comprehensive experiments have been conducted to verify the effectiveness of our framework. Experimental results show that our approach significantly outperforms the existing methods.

Universal Lower Bound on Topological Entanglement Entropy.

Entanglement entropies of two-dimensional gapped ground states are expected to satisfy an area law, with a constant correction term known as the topological entanglement entropy (TEE). In many models, the TEE takes a universal value that characterizes the underlying topological phase. However, the TEE is not truly universal: it can differ even for two states related by constant-depth circuits, which are necessarily in the same phase. The difference between the TEE and the value predicted by the anyon theory is often called the "spurious" topological entanglement entropy. We show that this spurious contribution is always non-negative, thus the value predicted by the anyon theory provides a universal lower bound. This observation also leads to a definition of TEE that is invariant under constant-depth quantum circuits.

Selective Inhibition of Organic Cation Transporter 1 by Benzoylpaeoniflorin Attenuates Hepatic Lipid Accumulation through AMPK Activation.

Organic cation transporter 1 (OCT1) is a liver-specific transporter and plays an essential role in drug disposition and hepatic lipid metabolism. Therefore, inhibition of OCT1 may not only lead to drug-drug interactions but also represent a potential therapy for fatty liver diseases. In this study, we systematically investigated the inhibitory effect of 200 natural products on OCT1-mediated uptake of 4,4-dimethylaminostyryl-N-methylpyridinium (ASP+) and identified 10 potent OCT1 inhibitors. The selectivity of these inhibitors over OCT2 was evaluated using both in vitro uptake assays and in silico molecular docking analyses. Importantly, benzoylpaeoniflorin was identified as the most potent OCT1 inhibitor with the highest selectivity over OCT2. Additionally, benzoylpaeoniflorin prevented lipid accumulation in hepatocytes, with concomitant activation of AMPK and down-regulation of lipogenic genes, such as acetyl-CoA carboxylase (ACC) and fatty acid synthase (FASN). To conclude, our findings are of significant value in understanding OCT1-based natural product-drug interactions and provide a natural source of OCT1 inhibitors which may hold promise for treating fatty liver diseases.

Grading of clear cell renal cell carcinoma using diffusion MRI with a fractional order calculus model.

BACKGROUND: The fractional order calculus (FROC) model has been developed to describe restrained motion of water molecules as well as microstructural heterogeneity, providing a novel tool for non-invasive tumor grading. PURPOSE: To evaluate the role of the FROC model in characterizing clear cell renal cell carcinoma (ccRCC) grades. MATERIAL AND METHODS: A total of 59 patients diagnosed with ccRCC were included in this prospective study. The diffusion metrics derived from the mono-exponential model (apparent diffusion coefficient [ADC]), intra-voxel incoherent motion [IVIM] model [D, D*, f], and FROC model [Dfroc, ß, µ]) were calculated and compared between low- and high-grade ccRCCs. Binary logistic regression analysis was performed to establish the diagnostic models. Receiver operating characteristic (ROC) analysis and DeLong test were performed to evaluate and compare the diagnostic performance of metrics in grading ccRCC. RESULTS: All the metrics except D* and f exhibited statistical differences between low- and high-grade ccRCCs. ROC analysis showed individual FROC parameters, µ, Dfroc, and ß, outperformed ADC and IVIM parameters in grading ccRCC. For single parameter, µ demonstrated the highest AUC value, sensitivity, and diagnostic accuracy in discriminating the two ccRCC groups while ß exhibited the optimal specificity. Importantly, the combination of Dfroc, µ, and ß could further improve the diagnostic performance. CONCLUSION: The FROC parameters were superior to ADC and IVIM parameters in grading ccRCC, indicating the great potential of the FROC model in distinguishing low- and high-grade ccRCCs.

Environmental risk of tailings pond leachate pollution: Traceable strategy for leakage channel and influence range of leachate.

Identifying the leakage channel and the influencing range is essential for controlling the environmental risks of leachate from the tailings pond. The investigation of leachate pollution in tailings pond has the defect of focusing only on the scope of tailings pond in recent studies. This study innovatively built a comprehensive investigation and accurate verification system for leachate leakage of tailings pond integrated with the aeromagnetic survey, ground penetrating radar, hydrochemistry and isotope coupling methods. Geophysical exploration found that among the four fault zones, and the F1 was the channel for leachate to recharge the groundwater 2.53 km away from the tailings pond. The fissures inside the tailings pond were connected with the natural fissures outside, forming a leachate migration channel. The hydrochemistry and isotope characteristics showed that the groundwater far away from the tailings pond were polluted by arsenic containing leachate, which verified the geophysical exploration results. The significant correlation between arsenic and SO2-4 concentration indicated that arsenic in leachate originated from the oxidation release of sulfide minerals (i.e., arsenopyrite). This study sheds light on the comprehensive investigation of leachate leakage in the tailings pond. This development method also provides guidance for environmental risk identification of other contaminated sites.

VOC emission caps constrained by air quality targets based on response surface model: A case study in the Pearl River Delta Region, China.

Because of the recent growth in ground-level ozone and increased emission of volatile organic compounds (VOCs), VOC emission control has become a major concern in China. In response, emission caps to control VOC have been stipulated in recent policies, but few of them were constrained by the co-control target of PM2.5 and ozone, and discussed the factor that influence the emission cap formulation. Herein, we proposed a framework for quantification of VOC emission caps constrained by targets for PM2.5 and ozone via a new response surface modeling (RSM) technique, achieving 50% computational cost savings of the quantification. In the Pearl River Delta (PRD) region, the VOC emission caps constrained by air quality targets varied greatly with the NOx emission reduction level. If control measures in the surrounding areas of the PRD region were not considered, there could be two feasible strategies for VOC emission caps to meet air quality targets (160 µg/m3 for the maximum 8-hr-average 90th-percentile (MDA8-90%) ozone and 25 µg/m3 for the annual average of PM2.5): a moderate VOC emission cap with <20% NOx emission reductions or a notable VOC emission cap with >60% NOx emission reductions. If the ozone concentration target were reduced to 155 µg/m3, deep NOx emission reductions is the only feasible ozone control measure in PRD. Optimization of seasonal VOC emission caps based on the Monte Carlo simulation could allow us to gain higher ozone benefits or greater VOC emission reductions. If VOC emissions were further reduced in autumn, MDA8-90% ozone could be lowered by 0.3-1.5 µg/m3, equaling the ozone benefits of 10% VOC emission reduction measures. The method for VOC emission cap quantification and optimization proposed in this study could provide scientific guidance for coordinated control of regional PM2.5 and O3 pollution in China.

Plasma IL-6 and TNF-α levels correlate significantly with grading changes in localized prostate cancer.

PURPOSE: To study the effect of inflammatory markers in blood such as interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) on the Gleason score (GS) changes in patients with prostate cancer (PCa) after radical prostatectomy (RP), we conducted this study. PATIENTS AND METHODS: From November 2012 to September 2021, a total of 237 patients underwent RP at our institution. Blood samples from all patients were collected within 1 week before surgery. Preoperative clinical characteristics include age, serum IL-6 and TNF-α, neutrophil-to-lymphocyte ratio, C-reactive protein, the platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, systemic immune-inflammation index, the prostate imaging reporting and data system (PI-RADS) score, prostate-specific antigen, and biopsy GS were assessed. Univariate and multivariate logistic regression analyzes were used to determine the risk factors of GS changes after RP. The efficiency of this prediction model was identified with the area under the curve of the receiver operating characteristic curve. RESULTS: Seventy-three patients (30.8%) had GS upgraded in the overall cohort, and 55 patients (23.2%) had GS downgraded. In comparing PCa patients with and without GS upgraded, multivariate logistic regression analysis showed that serum TNF-α (odds ratio [OR]: 2.518, p = 0.019) and IL-6 (OR: 0.478, p = 0.023) were independent factors predicting the occurrence of GS upgrade. We also compared the characteristics of patients with GS upgraded and GS downgraded; multivariate logistic regression analysis also demonstrated significant differences in serum IL-6 and TNF-α between these two groups (all p < 0.05). In addition, we found that low prostate volume and biopsy GS ≥ 7 were significantly associated with higher PI-RADS sores in multivariate analysis. CONCLUSION: The high expression of serum TNF-α level is positively correlated with GS upgraded in PCa patients. High expression of serum IL-6 level is negatively correlated with GS upgraded in PCa patients and positively related with GS downgraded.

Chiral Central Charge from a Single Bulk Wave Function.

A (2+1)-dimensional gapped quantum many-body system can have a topologically protected energy current at its edge. The magnitude of this current is determined entirely by the temperature and the chiral central charge, a quantity associated with the effective field theory of the edge. We derive a formula for the chiral central charge that, akin to the topological entanglement entropy, is completely determined by the many-body ground state wave function in the bulk. According to our formula, nonzero chiral central charge gives rise to a topological obstruction that prevents the ground state wave function from being real valued in any local product basis.

Modular Commutators in Conformal Field Theory.

The modular commutator is a recently discovered entanglement quantity that quantifies the chirality of the underlying many-body quantum state. In this Letter, we derive a universal expression for the modular commutator in conformal field theories in 1+1 dimensions and discuss its salient features. We show that the modular commutator depends only on the chiral central charge and the conformal cross ratio. We test this formula for a gapped (2+1)-dimensional system with a chiral edge, i.e., the quantum Hall state, and observe excellent agreement with numerical simulations. Furthermore, we propose a geometric dual for the modular commutator in certain preferred states of the AdS/CFT correspondence. For these states, we argue that the modular commutator can be obtained from a set of crossing angles between intersecting Ryu-Takayanagi surfaces.

Early potential evaluation of lead compounds from a DNA-encoded library by the determination of their thermodynamics through a chromatographic method based on immobilized ß2-adrenoceptor.

Early potential evaluation of lead compounds is critical to decrease downstream lead-optimization cycle times and clinical attrition rates for drug development. This increasingly necessitates the methodologies for accurately evaluating the potential compounds. This work immobilized ß2-adrenoceptor (ß2-AR) onto microspheres through Halo-tag mediated reaction. Characterizing the resulting microspheres by elemental and functional analysis, we utilized the immobilized receptor to determine the thermodynamics of terbutaline, tulobuterol, clorprenaline, salbutamol, and methoxyphenamine. The association constants correlated to their capacity factors on the column containing the immobilized ß2-AR, thus providing a possibility for early potential evaluation of lead compounds from complex matrices like a DNA-encoded library. By this model, the lead compound (XC267) was predicted to have an association constant higher than terbutaline, salbutamol, and methoxyphenamine, but lower than tulobuterol and clorprenaline. The binding interaction between XC267 and ß2-AR is a spontaneous endothermic process with an association constant of (6.62 ± 0.13) × 104 M-1 at 37 °C. The change of Gibbs free energy(ΔGθ), enthalpy change (ΔHθ), and entropy change (ΔSθ) was -28.49 kJ/mol, -10.58 kJ/mol, and 57.79 J/moL·K at 37 °C. By the semi-empirical rule of Ross, the driving force of the interaction between XC267 and ß2-AR was electrostatic interaction. Such binding force was also achieved by molecular docking. These results suggested that XC267 is a candidate to treat asthma by specific binding to ß2-AR. We reasoned that receptor chromatography is able to the early potential evaluation of lead compounds from complex matrices.

Investigation on the interaction between myricetin and dihydromyricetin with trypsin, α-chymotrypsin, lysozyme by spectroscopy and molecular docking methods.

The interaction between myricetin and dihydromyricetin with trypsin, α-chymotrypsin and lysozyme was investigated using multispectral and molecular docking methods. The results of fluorescence quenching revealed that myricetin and dihydromyricetin could quench the intrinsic fluorescence of three different proteinases through a static quenching procedure. The binding constant and number of binding sites at different temperatures were measured. The thermodynamic parameters obtained at different temperatures showed van der Waals interactions and hydrogen bonds played the main roles in the interaction of myricetin with trypsin and lysozyme, hydrophobic force was dominant both in myricetin with α-chymotrypsin interaction and dihydromyricetin with trypsin and lysozyme interaction, as for the electrostatic forces, it was mainly the driving force in dihydromyricetin binding to α-chymotrypsin. There was non-radiative energy transfer between three proteinases and myricetin or dihydromyricetin with high probability. The microenvironment of trypsin, α-chymotrypsin and lysozyme is changed. The docking studies revealed that myricetin and dihydromyricetin entered the hydrophobic cavity of three proteinases and formed hydrogen bonds. The binding affinity of myricetin or dihydromyricetin is different with the trypsin, α-chymotrypsin and lysozyme due to the different molecular structure.

Behavior Variations and Their Implications for Popularity Promotions: From Elites to Mass on Weibo.

The boom in social media with regard to producing and consuming information simultaneously implies the crucial role of online user influence in determining content popularity. In particular, understanding behavior variations between the influential elites and the mass grassroots is an important issue in communication. However, how their behavior varies across user categories and content domains and how these differences influence content popularity are rarely addressed. From a novel view of seven content domains, a detailed picture of the behavior variations among five user groups, from the views of both the elites and mass, is drawn on Weibo, one of the most popular Twitter-like services in China. Interestingly, elites post more diverse content with video links, while the mass possess retweeters of higher loyalty. According to these variations, user-oriented actions for enhancing content popularity are discussed and testified. The most surprising finding is that the diverse content does not always bring more retweets, and the mass and elites should promote content popularity by increasing their retweeter counts and loyalty, respectively. For the first time, our results demonstrate the possibility of highly individualized strategies of popularity promotions in social media, instead of a universal principle.

microRNA-320b suppresses HNF4G and IGF2BP2 expression to inhibit angiogenesis and tumor growth of lung cancer.

We examined the effect of microRNA-320b (miR-320b) on tumor growth and angiogenesis in lung cancer and also determined its downstream molecular mechanisms. Lung cancer tissues and adjacent non-cancerous tissues were collected from 66 patients with lung cancer. miR-320b expression was experimentally determined to be expressed at low level in cancer tissues. The results of gain-of-function experiments suggested that miR-320b overexpression suppressed cancer cell invasion, tube formation, tumor volume and angiogenesis in xenografted nude mice. Hepatocyte nuclear factor 4 gamma (HNF4G) was identified as a target of miR-320b based on in silico analysis. Dual-luciferase reporter gene assays further identified the binding relationship between HNF4G and miR-320b. Lung cancer tissues exhibited increased expression of HNF4G and insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2). Meanwhile, HNF4G knockdown suppressed IGF2BP2 expression, thereby repressing cancer cell invasion and tube formation. Furthermore, IGF2BP2 modified m6A to increase the expression of thymidine kinase 1 (TK1), thus promoting angiogenesis. In nude mice, restoration of TK1 reversed the suppressive effect of miR-320b overexpression on tumor growth rate and CD31 expression. In conclusion, miR-320b suppresses lung cancer growth and angiogenesis by inhibiting HNF4G, IGF2BP2 and TK1.

The prognostic value and potential subtypes of immune activity scores in three major urological cancers.

Immune-based rather than cancer-based classification systems are becoming an important additional component for prognostic prediction. Herein, we investigate the status of tumor-immune interaction and prognostic value of immune activity scores in bladder urothelial carcinoma (BLCA), kidney renal clear cell carcinoma (KIRC), and prostate adenocarcinoma (PRAD) from The Cancer Genome Atlas dataset and tracking the tumor immunophenotype platform. Traditional clinicopathological parameters still are effective predictors for prognosis. Comparison of 23-set, seven-step immune activity scores, and its distribution between favorable and adverse outcome groups within each cancer type and among cancer types show that each cancer has a distinct tumor-immune pattern. Adjusted overall immune activity scores based on the binary logistic regression analysis show a great discrimination ability in the progression-free survival (p = .0056 in BLCA, p < .0001 in KIRC, and p < .0001 in PRAD). K-mean cluster method and principal component analysis were performed to explore the cancer subtype. The results reveal that certain immune activity scores pattern such as high nature killer (NK) cell, T cell, macrophage, T helper type 1 (Th1) cell, and dendritic cell recruiting scores in BLCA, low NK cell, CD8 T cell, macrophage, T cell, Th1 cell recruiting scores in KIRC have a favorable clinical outcome comparing to other subtypes. Also, It is remarkable that a relatively small subtype of patients has a poor clinical prognosis in PRAD and this subtype features high CD4 T cell, macrophage, T cell, and regulatory T cell recruiting scores.

Schottky barrier heights in two-dimensional field-effect transistors: from theory to experiment.

Over the past decade, two-dimensional semiconductors (2DSCs) have aroused wide interest due to their extraordinary electronic, magnetic, optical, mechanical, and thermal properties, which hold potential in electronic, optoelectronic, thermoelectric applications, and so forth. The field-effect transistor (FET), a semiconductor gated with at least three terminals, is pervasively exploited as the device geometry for these applications. For lack of effective and stable substitutional doping techniques, direct metal contact is often used in 2DSC FETs to inject carriers. A Schottky barrier (SB) generally exists in the metal-2DSC junction, which significantly affects and even dominates the performance of most 2DSC FETs. Therefore, low SB or Ohmic contact is highly preferred for approaching the intrinsic characteristics of the 2DSC channel. In this review, we systematically introduce the recent progress made in theoretical prediction of the SB height (SBH) in the 2DSC FETs and the efforts made both in theory and experiments to achieve low SB contacts. From the comparison between the theoretical and experimentally observed SBHs, the emerging first-principles quantum transport simulation turns out to be the most powerful theoretical tool to calculate the SBH of a 2DSC FET. Finally, we conclude this review from the viewpoints of state-of-the-art electrode designs for 2DSC FETs.

Online stereo vision measurement based on correction of sensor structural parameters.

Vibration can easily affect the structure of long baseline binocular vision sensors, resulting in changes in the external parameters of the binocular calibration model and the failure of measurement method. This paper presents an online stereo vision measurement based on correction of sensor structural parameters. The flexible structure model based on calibration model and iterative gradient descent nonlinear optimization model based on 3D redundant information are established. The optimal estimation of external parameters and object position measurement are realized according to multi-information constraints. Experiments show that this method can effectively solve the measurement failure caused by vibration in stereo vision measurement.

Domain Wall Topological Entanglement Entropy.

We study the ground-state entanglement of gapped domain walls between topologically ordered systems in two spatial dimensions. We derive a universal correction to the ground-state entanglement entropy, which is equal to the logarithm of the total quantum dimension of a set of superselection sectors localized on the domain wall. This expression is derived from the recently proposed entanglement bootstrap method.

Characteristics and prognostic value of potential dependency genes in clear cell renal cell carcinoma based on a large-scale CRISPR-Cas9 and RNAi screening database DepMap.

BACKGROUND: Large-scale loss-of-function screening database such as Cancer Dependency Map (Depmap) provide abundant resources. Investigation of these potential dependency genes from human cancer cell lines in the real-world patients cohort would evaluate their prognostic value thus facilitate their clinical application and guide drug development. METHODS: A few genes were selected from top clear cell renal cell carcinoma (ccRCC) lineage preferential dependency candidates from Depmap. Their characteristic including expression levels both in normal and tumor tissues and correlations with methylation or copy number, genetic alterations, functional enrichment, immune-associated interactions, prognostic value were evaluated in KIRC cohort from TCGA, GTEx, and multiple other open databases and platforms. RESULTS: 16 genes were collected from 106 ccRCC preferential candidates and further analyzed including B4GALT4, BCL2L1, CDH2, COPG1, CRB3, FERMT2, GET4, GPX4, HNF1B, ITGAV, MDM2, NFE2L2, PAX8, RUVBL1, TFRC, and TNFSF10. The normalized gene effect scores of these genes varied from different ccRCC cell lines and principal component analysis (PCA) showed their tissue specificity expression profiles. Genetic alteration rates of them were low to moderate (0.7%-13%) in KIRC cohort. CDH2, MDM2, TNFSF10 showed a statistically significant higher level in tumors than normal tissues while PAX8 and FERMT2 were significantly downregulated. Moderate positive or negative correlations were observed in several genes between their expression and relative gene copy number or methylation levels, respectively. Based on the multivariable COX regression model adjusted by critical clinical variables revealed the expression of GET4 (p=0.002, HR=1.023 95%CI 1.009-1.038) and CRB3 (p<0.001, HR=0.969 95%CI 0.960-0.980) were independent predictive factors for overall survival in KIRC cohort. CONCLUSIONS: A dependency gene validated in cell lines didn't directly represent its role in corresponding patients with same histological type and their prognostic value might be determined by multiple factors including dependency driven types, genetic alteration rates and expression levels. GET4 and CRB3 were the independent prognostic factors for ccRCC patients. CRB3 seemed like a potential broad tumor suppressor gene while GET4 might be a ccRCC preferential dependency gene with a ligandable structure.