Whole exome sequencing and system biology analysis support the "two-hit" mechanism in the onset of Ameloblastoma

Ameloblastoma is the most frequent odontogenic tumor. Various evidence has highlighted the role of somatic mutations, including recurrent mutation BRAF V600E, in the tumorigenesis of Ameloblastoma, but the intact genetic pathology remains unknown. We sequenced the whole exome of both tumor tissue and healthy bone tissue from four mandibular ameloblastoma patients. The identified somatic mutations were integrated into Weighted Gene Co-expression Network Analysis on publicly available expression data of odontoblast, ameloblast, and Ameloblastoma. We identified a total of 70 rare and severe somatic mutations. We found BRAF V600E on all four patients, supporting previous discovery. HSAP4 was also hit by two missense mutations on two different patients. By applying Weighted Gene Co-expression Network Analysis on expression data of odontoblast, ameloblast, and Ameloblastoma, we found a proliferation-associated gene module that was significantly disrupted in tumor tissues. Each patient carried at least two rare, severe somatic mutations affecting genes within this module, including HSPA4, GNAS, CLTC, NES, and KMT2D. All these mutations had a ratio of variant-support reads lower than BRAF V600E, indicating that they occurred later than BRAF V600E. We suggest that a severe somatic mutation on the gene network of cell proliferation other than BRAF V600E, namely second hit, may contribute to the tumorigenesis of Ameloblastoma

Comparative Studies on Microbial Community Structure and Production Performance of Jiang-Flavor Daqu in Different Areas of Maotai Town

The microbial community structure and diversity of Jiang-flavor Daqu (TS, WS, WM, MH and DJ) from different areas of Maotai town were analyzed by using the third-generation nanopore sequencing platform, and its physicochemical indexes and characteristic flavor substances were measured. The results showed that there were some similarities and differences between Daqu in different areas of Maotai town. In terms of microbial community structure, Bacillus, Saccharopolyspora, Weissella, Staphylococcus and Streptomyces were the common dominant bacterial genera in the five Daqu samples. Among them, Bacillus was the absolute dominant bacteria in MH and DJ. Aspergillus and Penicillium were the common dominant fungal genera, and the proportions of Lichtheimia and Saccharomycopsis in TS, WM and MH were significantly higher than those in DJ and WS. Compared with TS and WM, network correlation analysis showed that MH, DJ and WS had stronger interactions among dominant bacteria. In addition, redundancy analysis (RDA) showed that Weissella was positively correlated with esterification power, liquefaction power, saccharification power, acetic acid, ethyl acetate, ethyl lactate and n-pentanol. Lichtheimia was positively correlated with liquefaction power, saccharification power, acetic acid, isovaleric acid, 2,3-butanediol, phenylacetaldehyde and dibutyl phthalate. Saccharomycopsis was positively correlated with esterification power and ethyl acetate. Bacillus was positively correlated with 2,3,5,6-tetramethylpyrazine, propionic acid, isovaleric acid, dibutyl phthalate, 2,3-butanediol and phenacetaldehyde

PolyMPCNet: Towards ReLU-free Neural Architecture Search in Two-party Computation Based Private Inference

The rapid growth and deployment of deep learning (DL) has witnessed emerging privacy and security concerns. To mitigate these issues, secure multi-party computation (MPC) has been discussed, to enable the privacy-preserving DL computation. In practice, they often come at very high computation and communication overhead, and potentially prohibit their popularity in large scale systems. Two orthogonal research trends have attracted enormous interests in addressing the energy efficiency in secure deep learning, i.e., overhead reduction of MPC comparison protocol, and hardware acceleration. However, they either achieve a low reduction ratio and suffer from high latency due to limited computation and communication saving, or are power-hungry as existing works mainly focus on general computing platforms such as CPUs and GPUs. In this work, as the first attempt, we develop a systematic framework, PolyMPCNet, of joint overhead reduction of MPC comparison protocol and hardware acceleration, by integrating hardware latency of the cryptographic building block into the DNN loss function to achieve high energy efficiency, accuracy, and security guarantee. Instead of heuristically checking the model sensitivity after a DNN is well-trained (through deleting or dropping some non-polynomial operators), our key design principle is to em enforce exactly what is assumed in the DNN design -- training a DNN that is both hardware efficient and secure, while escaping the local minima and saddle points and maintaining high accuracy. More specifically, we propose a straight through polynomial activation initialization method for cryptographic hardware friendly trainable polynomial activation function to replace the expensive 2P-ReLU operator. We develop a cryptographic hardware scheduler and the corresponding performance model for Field Programmable Gate Arrays (FPGA) platform

AutoReP: Automatic ReLU Replacement for Fast Private Network Inference

The growth of the Machine-Learning-As-A-Service (MLaaS) market has highlighted clients' data privacy and security issues. Private inference (PI) techniques using cryptographic primitives offer a solution but often have high computation and communication costs, particularly with non-linear operators like ReLU. Many attempts to reduce ReLU operations exist, but they may need heuristic threshold selection or cause substantial accuracy loss. This work introduces AutoReP, a gradient-based approach to lessen non-linear operators and alleviate these issues. It automates the selection of ReLU and polynomial functions to speed up PI applications and introduces distribution-aware polynomial approximation (DaPa) to maintain model expressivity while accurately approximating ReLUs. Our experimental results demonstrate significant accuracy improvements of 6.12% (94.31%, 12.9K ReLU budget, CIFAR-10), 8.39% (74.92%, 12.9K ReLU budget, CIFAR-100), and 9.45% (63.69%, 55K ReLU budget, Tiny-ImageNet) over current state-of-the-art methods, e.g., SNL. Morever, AutoReP is applied to EfficientNet-B2 on ImageNet dataset, and achieved 75.55% accuracy with 176.1 times ReLU budget reduction.Comment: ICCV 2023 accepeted publicatio

Mechanical overloading induces GPX4-regulated chondrocyte ferroptosis in osteoarthritis via Piezo1 channel facilitated calcium influx

Introductions: Excessive mechanical stress is closely associated with cell death in various conditions. Exposure of chondrocytes to excessive mechanical loading leads to a catabolic response as well as exaggerated cell death. Ferroptosis is a recently identified form of cell death during cell aging and degeneration. However, it's potential association with mechanical stress remains to be illustrated. Objectives: To identify whether excessive mechanical stress can cause ferroptosis. To explore the role of mechanical overloading in chondrocyte ferroptosis. Methods: Chondrocytes were collected from loading and unloading zones of cartilage in patients with osteoarthritis (OA), and the ferroptosis phenotype was analyzed through transmission electron microscope and microarray. Moreover, the relationship between ferroptosis and OA was analyzed by GPX4-conditional knockout (Col2a1-CreERT: GPX4flox/flox) mice OA model and chondrocytes cultured with high strain mechanical stress. Furthermore, the role of Piezo1 ion channel in chondrocyte ferroptosis and OA development was explored by using its inhibitor (GsMTx4) and agonist (Yoda1). Additionally, chondrocyte was cultured in calcium-free medium with mechanical stress, and ferroptosis phenotype was tested. Results: Human cartilage and mouse chondrocyte experiments revealed that mechanical overloading can induce GPX4-associated ferroptosis. Conditional knockout of GPX4 in cartilage aggravated experimental OA process, while additional treatment with ferroptosis suppressor protein (FSP-1) and coenzyme Q10 (CoQ10) abated OA development in GPX4-CKO mice. In mouse OA model and chondrocyte experiments, inhibition of Piezo1 channel activity increased GPX4 expression, attenuated ferroptosis phenotype and reduced the severity of osteoarthritis. Additionally, high strain mechanical stress induced ferroptosis damage in chondrocyte was largely abolished by blocking calcium influx through calcium-free medium. Conclusions: Our findings show that mechanical overloading induces ferroptosis through Piezo1 activation and subsequent calcium influx in chondrocytes, which might provide a potential target for OA treatment

Stabilization of Bio-Oss® particulates using photocurable hydrogel to enhance bone regeneration by regulating macrophage polarization

Bone substitutes are widely used in maxillofacial and oral surgeries. However, in clinical practice, bone substitutes with various forms, including separated particulates, powders, and blocks, have exhibited poor handling properties and space maintenance characteristics, resulting in long surgery procedures and unstable volume of the newly formed bone. Movable separated particulates with high stiffness have induced local inflammatory responses that hinder bone regeneration. The present study aimed to develop a new method to enhance the stability and operability of bone substitutes commonly used in dentistry by premixing with photocurable hydrogel GelMA. The GelMA-encapsulated particulate had a strong capacity to aggregate separated particulates and firmly attach to the host bone defect after photocuring compared to particulates alone. Additionally, macrophages at the surface of the GelMA-stabilized particulates tended to present a more M2-like phenotype than those at the surface of Bio-Oss®, leading to more MMR+ multinucleated giant cell formation and the induction of blood vessel invasion and new bone formation. In conclusion, this hydrogel-coated bone substitute strategy facilitates bone regeneration with increased operability, a stable volume of osteogenic space, and a favorable osteogenic microenvironment, indicating its potential value in the field of maxillofacial and oral surgeries when bone substitutes are needed

Macrophage polarization states in atherosclerosis

Atherosclerosis, a chronic inflammatory condition primarily affecting large and medium arteries, is the main cause of cardiovascular diseases. Macrophages are key mediators of inflammatory responses. They are involved in all stages of atherosclerosis development and progression, from plaque formation to transition into vulnerable plaques, and are considered important therapeutic targets. Increasing evidence suggests that the modulation of macrophage polarization can effectively control the progression of atherosclerosis. Herein, we explore the role of macrophage polarization in the progression of atherosclerosis and summarize emerging therapies for the regulation of macrophage polarization. Thus, the aim is to inspire new avenues of research in disease mechanisms and clinical prevention and treatment of atherosclerosis

Anomalous stopping of laser-accelerated intense proton beam in dense ionized matter

Ultrahigh-intensity lasers (10$^{18}$-10$^{22}$W/cm$^{2}$) have opened up new perspectives in many fields of research and application [1-5]. By irradiating a thin foil, an ultrahigh accelerating field (10$^{12}$ V/m) can be formed and multi-MeV ions with unprecedentedly high intensity (10$^{10}$A/cm$^2$) in short time scale ($\sim$ps) are produced [6-14]. Such beams provide new options in radiography [15], high-yield neutron sources [16], high-energy-density-matter generation [17], and ion fast ignition [18,19]. An accurate understanding of the nonlinear behavior of beam transport in matter is crucial for all these applications. We report here the first experimental evidence of anomalous stopping of a laser-generated high-current proton beam in well-characterized dense ionized matter. The observed stopping power is one order of magnitude higher than single-particle slowing-down theory predictions. We attribute this phenomenon to collective effects where the intense beam drives an decelerating electric field approaching 1GV/m in the dense ionized matter. This finding will have considerable impact on the future path to inertial fusion energy.Comment: 8 pages, 4 figure

Energy loss enhancement of very intense proton beams in dense matter due to the beam-density effect

Thoroughly understanding the transport and energy loss of intense ion beams in dense matter is essential for high-energy-density physics and inertial confinement fusion. Here, we report a stopping power experiment with a high-intensity laser-driven proton beam in cold, dense matter. The measured energy loss is one order of magnitude higher than the expectation of individual particle stopping models. We attribute this finding to the proximity of beam ions to each other, which is usually insignificant for relatively-low-current beams from classical accelerators. The ionization of the cold target by the intense ion beam is important for the stopping power calculation and has been considered using proper ionization cross section data. Final theoretical values agree well with the experimental results. Additionally, we extend the stopping power calculation for intense ion beams to plasma scenario based on Ohm's law. Both the proximity- and the Ohmic effect can enhance the energy loss of intense beams in dense matter, which are also summarized as the beam-density effect. This finding is useful for the stopping power estimation of intense beams and significant to fast ignition fusion driven by intense ion beams