A Novel Prognostic Predictor of Immune Micro-environment and Therapeutic Response in Kidney Renal Clear Cell Carcinoma based on Necroptosis-related Gene Signature

Background: Necroptosis, a cell death of caspase-independence, plays a pivotal role in cancer biological regulation. Although necroptosis is closely associated with oncogenesis, cancer metastasis, and immunity, there remains a lack of studies determining the role of necroptosis-related genes (NRGs) in the highly immunogenic cancer type, kidney renal clear cell carcinoma (KIRC). Methods: The information of clinicopathology and transcriptome was extracted from TCGA database. Following the division into the train and test cohorts, a three-NRGs (TLR3, FASLG, ZBP1) risk model was identified in train cohort by LASSO regression. The overall survival (OS) comparison was conducted between different risk groups through Kaplan-Meier analysis, which was further validated in test cohort. The Cox proportional hazards regression model was introduced to assess its impact of clinicopathological factors and risk score on survival. ESTIMATE and CIBERSORT algorithms were introduced to evaluate immune microenvironment, while enrichment analysis was conducted to explore the biological significance. Correlation analysis was applied for the correlation assessment between checkpoint gene expression and risk score, between gene expression and therapeutic response. Gene expressions from TCGA were verified by GEO datasets and immunohistochemistry (IHC) analysis. Results: This NRGs-related signature predicted poorer OS in high-risk group, which was also verified in test cohort. Risk score could also independently predict survival outcome of KIRC. Significant changes were also found in immune microenvironment and checkpoint gene expressions between different risk groups, with immune functional enrichment in high-risk group. Interestingly, therapeutic response was correlated with the expressions of NRGs. The expressions of NRGs from TCGA were consistent with those from GEO datasets and IHC analysis. Conclusion: The NRGs-related signature functions as a novel prognostic predictor of immune microenvironment and therapeutic response in KIRC

Density structures of the upper mantle in the East African Rift System: implications for the evolution of intracontinental rifting

The East African Rift System (EARS) provides an ideal natural laboratory for studying the mechanisms of tectonic plate breakup and continental drift, as well as a unique perspective for exploring the maturation process of continental rifting and its drivers. This study combines high-resolution satellite gravity data and seismic tomography model with an integrated geophysical approach to reveal the density structures in the upper mantle of the EARS. The results show that the northeastern to central Congo and Zimbabwe Craton exhibit significant high-density anomalies extending up to 250 km, which is indicative of a thicker and more intact lithosphere. In contrast, the Uganda, Tanzania, eastern and southern Congo, and Kaapvaal Craton show shallow high-density anomalies underlain by low-density anomalies that are clearly derived from the deeper mantle, indicating a thining of the lithosphere with some degree of possible melting at the base. The various rift segments of the EARS exhibit different rift morphologies. The Main Ethiopian Rift and the Kenya Rift of the Eastern Rift Branch show strong low-density anomalies, indicating intense melting, which is much stronger than that observed in the Western Rift Branch. However, the two rifts may have originated from the same mantle uplift in which the low-density anomalies of the Eastern and Western Rift Branches connected in the deep upper mantle. The lower portion of the Malawi Rift exhibits weaker low-denstiy anomalies, which can be observed to the south of the Malawi Rift, extending further south as a continuation of the EARS. Combining the results of previous kinetics simulations and our density perturbation results, it can be inferred that the Eastern Rift Branch is mainly affected by active rifting, while the Western Rift Branch is affected by both active and passive rifting

Variations in the reproductive strategies of three populations of Phrynocephalus helioscopus in China

Background Egg size and clutch size are key life history traits. During the breeding period, it is possible for females to increase their reproductive output either by increasing the number of eggs if the optimal egg size (OES) is maintained, or by increasing the allocation of energy to each egg. However, the strategies adopted are often influenced by animals’ morphology and environment. Methods Here, we examined variation in female morphological and reproductive traits, tested for trade-offs between egg size and clutch size, and evaluated the relationship between egg size and female morphology in three populations of Phrynocephalus helioscopus. Results Female body size, egg size, and clutch size were larger in the Yi Ning (YN) and Fu Yun (FY) populations than in the Bei Tun (BT) population (the FY and YN populations laid more, and rounder eggs). Egg size was independent of female body size in two populations (BT and FY), even though both populations had an egg-size/clutch size trade-off. In the YN population, egg size and clutch size were independent, but egg size was correlated with female body size, consistent with the hypothesis of morphological constraint. Conclusions Our study found geographical variation in body size and reproductive strategies of P. helioscopus. Egg size was correlated with morphology in the larger-bodied females of the YN population, but not in the smaller-bodied females of the BT population, illustrating that constraints on female body size and egg size are not consistent between populations

Electrical contact properties between Yb and few-layer WS2_2

Charge injection mechanism from contact electrodes into two-dimensional (2D) dichalcogenides is an essential topic for exploiting electronics based on 2D channels, but remains not well understood. Here, low-work-function metal ytterbium (Yb) was employed as contacts for tungsten disulfide (WS$_2$) to understand the realistic injection mechanism. The contact properties in WS$_2$ with variable temperature (T) and channel thickness (tch) were synergetically characterized. It is found that the Yb/WS$_2$ interfaces exhibit a strong pinning effect between energy levels and a low contact resistance (R_\rm{C}) value down to $5\,k\Omega\cdot\mu$m. Cryogenic electrical measurements reveal that R_\rm{C} exhibits weakly positive dependence on T till 77 K, as well as a weakly negative correlation with tch. In contrast to the non-negligible R_\rm{C} values extracted, an unexpectedly low effective thermal injection barrier of 36 meV is estimated, indicating the presence of significant tunneling injection in subthreshold regime and the inapplicability of the pure thermionic emission model to estimate the height of injection barrier

Naringenin prevents TGF-β1 secretion from breast cancer and suppresses pulmonary metastasis by inhibiting PKC activation

Presenting the incidence of pulmonary metastasis (mice with metastasis/total mice). Tumor-bearing mice treated with naringenin or 1D11 were imaged on day 24 using bags to avoid the bioluminescence from primary tumor. The mice with pulmonary metastases were numbered based on the bioluminescence signal. (TIF 26 kb

Fibre-Optic Photoacoustic Beacon and 2D Sparse Sensor Array for 3D Tracking of Needles

Accurate knowledge of the needle tip location during percutaneous procedures such as liver and breast biopsies, cancer treatment, drug delivery, and fetal blood transfusion would reduce adverse events, misdiagnoses and failed procedures. We have developed a novel trackable ultrasonic needle and 3D tracking system for such percutaneous medical needle procedures. The location of the needle tip is annotated onto the anatomical ultrasound images being used to guide the procedure, with the quantitative distance of the needle tip from the ultrasound imaging plane also visualised. The device works by transmitting pulses of ultrasound from our proprietary low-cost fibre-optic trackable needle which are detected by a sparse sensor array located on the patient’s skin. This novel solution allows truly simultaneous 3D tracking and imaging with any ultrasound or other imaging system, in contrast to existing ultrasonic solutions which either provide only 2D tracking or must reduce the imaging frame rate to avoid interference. Tracking accuracy was assessed in water to depths of 14 cm and up to 3 cm from the ultrasound imaging plane: the spatial-average bias between tracked and true positions was 0.37mm and the spatial-average repeatability was 1.2 mm

A Hybrid Deep Feature-Based Deformable Image Registration Method for Pathology Images

Pathologists need to combine information from differently stained pathology slices for accurate diagnosis. Deformable image registration is a necessary technique for fusing multi-modal pathology slices. This paper proposes a hybrid deep feature-based deformable image registration framework for stained pathology samples. We first extract dense feature points via the detector-based and detector-free deep learning feature networks and perform points matching. Then, to further reduce false matches, an outlier detection method combining the isolation forest statistical model and the local affine correction model is proposed. Finally, the interpolation method generates the deformable vector field for pathology image registration based on the above matching points. We evaluate our method on the dataset of the Non-rigid Histology Image Registration (ANHIR) challenge, which is co-organized with the IEEE ISBI 2019 conference. Our technique outperforms the traditional approaches by 17% with the Average-Average registration target error (rTRE) reaching 0.0034. The proposed method achieved state-of-the-art performance and ranked 1st in evaluating the test dataset. The proposed hybrid deep feature-based registration method can potentially become a reliable method for pathology image registration.Comment: 22 pages, 12 figures. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

The rapid development of large language models has revolutionized code intelligence in software development. However, the predominance of closed-source models has restricted extensive research and development. To address this, we introduce the DeepSeek-Coder series, a range of open-source code models with sizes from 1.3B to 33B, trained from scratch on 2 trillion tokens. These models are pre-trained on a high-quality project-level code corpus and employ a fill-in-the-blank task with a 16K window to enhance code generation and infilling. Our extensive evaluations demonstrate that DeepSeek-Coder not only achieves state-of-the-art performance among open-source code models across multiple benchmarks but also surpasses existing closed-source models like Codex and GPT-3.5. Furthermore, DeepSeek-Coder models are under a permissive license that allows for both research and unrestricted commercial use