SPNE: sample-perturbed network entropy for revealing critical states of complex biological systems.

Complex biological systems do not always develop smoothly but occasionally undergo a sharp transition; i.e. there exists a critical transition or tipping point at which a drastic qualitative shift occurs. Hunting for such a critical transition is important to prevent or delay the occurrence of catastrophic consequences, such as disease deterioration. However, the identification of the critical state for complex biological systems is still a challenging problem when using high-dimensional small sample data, especially where only a certain sample is available, which often leads to the failure of most traditional statistical approaches. In this study, a novel quantitative method, sample-perturbed network entropy (SPNE), is developed based on the sample-perturbed directed network to reveal the critical state of complex biological systems at the single-sample level. Specifically, the SPNE approach effectively quantifies the perturbation effect caused by a specific sample on the directed network in terms of network entropy and thus captures the criticality of biological systems. This model-free method was applied to both bulk and single-cell expression data. Our approach was validated by successfully detecting the early warning signals of the critical states for six real datasets, including four tumor datasets from The Cancer Genome Atlas (TCGA) and two single-cell datasets of cell differentiation. In addition, the functional analyses of signaling biomarkers demonstrated the effectiveness of the analytical and computational results.

Identifying the critical states and dynamic network biomarkers of cancers based on network entropy.

BACKGROUND: There are sudden deterioration phenomena during the progression of many complex diseases, including most cancers; that is, the biological system may go through a critical transition from one stable state (the normal state) to another (the disease state). It is of great importance to predict this critical transition or the so-called pre-disease state so that patients can receive appropriate and timely medical care. In practice, however, this critical transition is usually difficult to identify due to the high nonlinearity and complexity of biological systems. METHODS: In this study, we employed a model-free computational method, local network entropy (LNE), to identify the critical transition/pre-disease states of complex diseases. From a network perspective, this method effectively explores the key associations among biomolecules and captures their dynamic abnormalities. RESULTS: Based on LNE, the pre-disease states of ten cancers were successfully detected. Two types of new prognostic biomarkers, optimistic LNE (O-LNE) and pessimistic LNE (P-LNE) biomarkers, were identified, enabling identification of the pre-disease state and evaluation of prognosis. In addition, LNE helps to find "dark genes" with nondifferential gene expression but differential LNE values. CONCLUSIONS: The proposed method effectively identified the critical transition states of complex diseases at the single-sample level. Our study not only identified the critical transition states of ten cancers but also provides two types of new prognostic biomarkers, O-LNE and P-LNE biomarkers, for further practical application. The method in this study therefore has great potential in personalized disease diagnosis.

miR-193a as a potential mediator of WT-1/synaptopodin in the renoprotective effect of Losartan on diabetic kidney.

Diabetic nephropathy (DN) is the most common complication of diabetic patients, and has become a global healthcare problem. In this study, we used diabetic mice to evaluate the effect of Losartan on DN, in which the experimental animals were divided into three groups: non-diabetic mice (db/m group), untreated-diabetic mice (db/db group), and Losartan-treated diabetic mice (db/db-losartan). Next, immunohistochemistry and immunofluorescence were used to detect Wilms tumor protein 1 (WT-1) and synaptopodin expression, respectively. Protein levels of WT-1, synaptopodin, claudin1, and Pax-2 were assessed by Western blotting and real-time PCR. The miR-193a mRNA levels were quantitated by real-time PCR. The results showed that albuminuria was increased in diabetic mice compared with control animals and was significantly ameliorated by treatment with Losartan. In addition, Losartan significantly upregulated the immunopositive cell numbers of WT-1, the expression of WT-1 and synaptopodin in renal tissue. By contrast, expression of claudin1 and Pax-2 in renal tissue were decreased in db/db-losartan group. Besides, expression of miR-193a was decreased significantly in db/db-losartan group compared with the untreated diabetic group. Thus, Losartan has renoprotective effects on the control of tissue damage possibly by inhibiting the expression of miR-193a, thereby promoting the repair of podocyte injury in mice with DN.

Intracellular marriage of bicarbonate and Mn ions as "immune ion reactors" to regulate redox homeostasis and enhanced antitumor immune responses.

BACKGROUND: Different from Fe ions in Fenton reaction, Mn ions can function both as catalyst for chemodynamic therapy and immune adjuvant for antitumor immune responses. In Mn-mediated Fenton-like reaction, bicarbonate ([Formula: see text]), as the most important component to amplify therapeutic effects, must be present, however, intracellular [Formula: see text] is strictly limited because of the tight control by live cells. RESULTS: Herein, Stimuli-responsive manganese carbonate-indocyanine green complexes (MnCO3-ICG) were designed for intracellular marriage of bicarbonate and Mn ions as "immune ion reactors" to regulate intracellular redox homeostasis and antitumor immune responses. Under the tumor acidic environment, the biodegradable complex can release "ion reactors" of Mn2+ and [Formula: see text], and ICG in the cytoplasm. The suddenly increased [Formula: see text] in situ inside the cells regulate intracellular pH, and accelerate the generation of hydroxyl radicals for the oxidative stress damage of tumors cells because [Formula: see text] play a critical role to catalyze Mn-mediated Fenton-like reaction. Investigations in vitro and in vivo prove that the both CDT and phototherapy combined with Mn2+-enhanced immunotherapy effectively suppress tumor growth and realize complete tumor elimination. CONCLUSIONS: The combination therapy strategy with the help of novel immune adjuvants would produce an enhanced immune response, and be used for the treatment of deep tumors in situ.

The preventive and therapeutic effects of AAV1-KLF4-shRNA in cigarette smoke-induced pulmonary hypertension.

We found previously that KLF4 expression was up-regulated in cultured rat and human pulmonary artery smooth muscle cells (PASMCs) exposed to cigarette smoke (CS) extract and in pulmonary artery from rats with pulmonary hypertension induced by CS. Here, we aim to investigate whether CS-induced pulmonary hypertension (PH) is prevented and ameliorated by targeted pulmonary vascular gene knockdown of KLF4 via adeno-associated virus 1 (AAV1)-KLF4-shRNA in vivo in rat model. The preventive and therapeutic effects were observed according to the different time-point of AAV1-KLF4-shRNA intratracheal administration. We tested haemodynamic measurements of systemic and pulmonary circulations and observed the degree of pulmonary vascular remodelling. In the preventive experiment, KLF4 expression and some pulmonary circulation hemodynamic measurements such as right ventricular systolic pressure (RVSP), mean right ventricular pressure (mRVP), peak RV pressure rate of rise (dP/dt max) and right ventricle (RV) contractility index were increased significantly in the CS-induced PH model. While in the prevention group (AAV1-KLF4-shRNA group), RVSP, mRVP, dP/dt max and RV contractility index which are associated with systolic function of right ventricle decreased and the degree of pulmonary vascular remodelling relieved. In the therapeutic experiment, we observed a similar trend. Our findings emphasize the feasibility of sustained pulmonary vascular KLF4 gene knockdown using intratracheal delivery of AAV1 in an animal model of cigarette smoke-induced PH and determined gene transfer of KLF4-shRNA could prevent and ameliorate the progression of PH.

Xbp1s-Ddit3 promotes MCT-induced pulmonary hypertension.

Pulmonary hypertension (PH) is a life-threatening disease characterized by vascular remodeling. Exploring new therapy target is urgent. The purpose of the present study is to investigate whether and how spliced x-box binding protein 1 (xbp1s), a key component of endoplasmic reticulum stress (ERS), contributes to the pathogenesis of PH. Forty male SD rats were randomly assigned to four groups: Control, Monocrotaline (MCT), MCT+AAV-CTL (control), and MCT+AAV-xbp1s. The xbp1s protein levels were found to be elevated in lung tissues of the MCT group. Intratracheal injection of adeno-associated virus serotype 1 carrying xbp1s shRNA (AAV-xbp1s) to knock down the expression of xbp1s effectively ameliorated the MCT-induced elevation of right ventricular systolic pressure (RVSP), total pulmonary resistance (TPR), right ventricular hypertrophy and medial wall thickness of muscularized distal pulmonary arterioles. The abnormally increased positive staining rates of proliferating cell nuclear antigen (PCNA) and Ki67 and decreased positive staining rates of terminal deoxynucleotidyl transferase (TdT)-mediated dUTP nick end labeling (TUNEL) in pulmonary arterioles were also reversed in the MCT+AAV-xbp1s group. For mechanistic exploration, bioinformatics prediction of the protein network was performed on the STRING database, and further verification was performed by qRT-PCR, Western blots and co-immunoprecipitation (Co-IP). DNA damage-inducible transcript 3 (Ddit3) was identified as a downstream protein that interacted with xbp1s. Overexpression of Ddit3 restored the decreased proliferation, migration and cell viability caused by silencing of xbp1s. The protein level of Ddit3 was also highly consistent with xbp1s in the animal model. Taken together, our study demonstrated that xbp1s-Ddit3 may be a potential target to interfere with vascular remodeling in PH.

Epidemiological survey to determine the prevalence of cholecystolithiasis in Uyghur, Kazakh, and Han Ethnic Groups in the Xinjiang Uyghur Autonomous Region of China: cross-sectional studies.

BACKGROUND: This study was performed to understand the prevalence of and possible risk factors for cholecystolithiasis in Uyghur, Kazakh, Han, and other ethnic groups in the Xinjiang Uyghur autonomous region of China. METHODS: Subjects were enrolled using typical case sampling and multistage stratified random sampling. We collected epidemiological data regarding cholecystolithiasis using a standard questionnaire of risk factors for gallbladder disease in Xinjiang. The subjects completed the questionnaire and underwent an abdominal ultrasound examination of the liver and gallbladder. RESULTS: This study included 5454 Xinjiang residents aged ≥ 18 years. The prevalence of cholecystolithiasis was 15% (11.3% in men and 17.1% in women), and the sex difference was statistically significant (male-to-female odds ratio [OR] 1.867; p < 0.001). The cholecystolithiasis prevalence was also significantly different among the Han, Uyghur, Kazakh, and other ethnic groups (13.1%, 20.8%, 11.5%, and 16.8%, respectively; p < 0.001). The prevalence of cholecystolithiasis in northern Xinjiang was 13.5% and that in southern Xinjiang was 17.5%; this difference was also statistically significant (OR 1.599; p < 0.001). Across all ethnic groups, the cholecystolithiasis prevalence significantly increased with age (all p < 0.01) and body mass index (BMI) (all p < 0.01). A multivariate logistic regression analysis indicated that cholecystolithiasis prevalence was associated with sex, age, BMI, smoking, diabetes, fatty liver disease, and geographical differences between northern and southern Xinjiang. CONCLUSIONS: The prevalence of cholecystolithiasis was significantly higher in the Uyghur ethnic group than in the Han, Kazakh, and other ethnic groups; in women than in men; in southern Xinjiang than in northern Xinjiang; in patients with fatty liver disease; and increased with age and BMI. Our findings could provide a theoretical basis for the formulation of control measures for cholecystolithiasis.

[Rapid identification of Cordyceps and its products using DNA barcoding method].

Cordyceps is one of the most valuable traditional Chinese medicines. There are various counterfeits in markets because of high price and limited output. In this study,116 Cordyceps,146 hosts and 29 related products were collected and detected by using normal DNA barcoding technology and specific PCR method. The results indicated that Cordyceps and its adulterants could be distinguished from each other through DNA barcoding technology based on ITS and COⅠsequences. Two pairs specific primers ITSSF1/ITSSR1 and ITSSF2/ITSSR2 were developed to amplify 297 bp and 136 bp ITS regions of Cordyceps sinensis,respectively. It could be used to identify C. sinensis specifically and rapidly. Furthermore,specific primers ITSSF1/ITSSR1 and ITSSF2/ITSSR2 combined with ITS and COⅠsequences could differentiate powder Cordyceps from fermentation mycelia and could identify related products. Therefore,the method developed from this study could be applied to identify the powder of Cordyceps from fermentation mycelia and related products efficiently.

[Rapid identification of Gekko gecko by loop-mediated isothermal amplification based on 12S rRNA sequence].

Gekko gecko (Tokay Gecko) is a valuable traditional Chinese medicine. In this study, the loop-mediated isothermal amplification (LAMP) technique was introduced for visual rapid identification of G. gecko from adulterants. A total of sixty-five 12S rRNA sequences of fourteen species of G. gecko and its adulterants were obtained. The results showed that G. gecko could be identified from its adulterants through BLAST analysis based on 12S rRNA regions. The 12S rRNA sequences of ten batches of G. gecko were conserved. There were only two haplotypes and three variation sites in the available regions for primers design. Six specific LAMP primers were successfully designed online based on 12S rRNA sequences. The visual rapid detection of G. gecko could be achieved with the optimized conditions (64 °C for 1 h and 80 °C for 5 min). And the required minimal template concentration was 5 µg·L⁻¹ while conventional PCR with 0.5 mg·L⁻¹. Consequently, the LAMP method established from this study was rapid, specific, highly sensitive, and simple. It could be applied to detect G. gecko from its adulterants efficiently.

[Statues and research strategy of molecular breeding in Artemisia annua].

Malaria is one of the three most deadly diseases in the world. Artemisinin is the first line and effective drug for treating malaria, and only can be extracted from Artemisia annua. Therefore, it is of great significance to cultivate new varieties of A. annua with high artemisinin content. Based on the germplasm bank and the whole genome, transcriptome and genetic map, the authors can explore high-quality genes, stress-resistant genes and genetic markers which have been used for rapid breeding of superior varieties of A. annua. So these methods of molecular breeding will become the main breeding direction of A. annua in the future. The breeding times of new varieties of A. annua can be shortened with molecular breeding technology. Based on the genetic background and the current situation of molecular breeding of A. annua, the strategy and technical route of molecular breeding were discussed and worked out in this paper, which provided a guidance and scientific reference for molecular breeding of A. annua in the future.

[Mechanism of high temperature promoting artemisinin biosynthesis in Artemisia annua].

Artemisia annua also known as Qinghao, is a kind of traditional Chinese medicine. Its active ingredient is artemisinin, a sesquiterpene lactone compound with a peroxy bridging group structure. A. annua is an effective antimalarial drug. Artemisinin, a secondary metabolite in A. annua, can be induced by many physical and chemical factors, such as salinity, moisture, light, and plant hormones. Temperature, as an important growth factor, also has a great influence on the synthesis of artemisinin. This article aims to study the effect of high temperature on inducing artemisinin biosynthesis in A. annua. The A. annua seedlings were placed at 25, 40 °C, and the samples were taken after 0, 3, 12 and 36 h. The content of artemisinin in each sample was determined by liquid chromatography-mass spectrometry. Total RNA was extracted from the samples, and then transcriptome sequencing and real-time fluorescence quantitative PCR were used to quantitatively analyze the expression of the key enzyme genes in artemisinin synthesis pathway and competition pathway. The results showed that artemisinin content was increased by 20%, 42% and 68% after 3, 12, 36 h of treatment at 40 °C. The expression levels of FDS, ALDH1, CYP71AV1 and ADS were up-regulated by 4.3, 3.3, 2.5, 1.9 times, and the expression levels of SQS and BPS were down-regulated by 37% and 90% respectively. In summary, high temperature can promote the biosynthesis of artemisinin by promoting the expression of synthetase genes in artemisinin synthesis pathway and inhibiting the expression of synthetase genes in artemisinin-competition pathway.

Sound Source Localization Using Non-Conformal Surface Sound Field Transformation Based on Spherical Harmonic Wave Decomposition.

Spherical microphone arrays have been paid increasing attention for their ability to locate a sound source with arbitrary incident angle in three-dimensional space. Low-frequency sound sources are usually located by using spherical near-field acoustic holography. The reconstruction surface and holography surface are conformal surfaces in the conventional sound field transformation based on generalized Fourier transform. When the sound source is on the cylindrical surface, it is difficult to locate by using spherical surface conformal transform. The non-conformal sound field transformation by making a transfer matrix based on spherical harmonic wave decomposition is proposed in this paper, which can achieve the transformation of a spherical surface into a cylindrical surface by using spherical array data. The theoretical expressions of the proposed method are deduced, and the performance of the method is simulated. Moreover, the experiment of sound source localization by using a spherical array with randomly and uniformly distributed elements is carried out. Results show that the non-conformal surface sound field transformation from a spherical surface to a cylindrical surface is realized by using the proposed method. The localization deviation is around 0.01 m, and the resolution is around 0.3 m. The application of the spherical array is extended, and the localization ability of the spherical array is improved.

Effects of Chinese herbs in children with Henoch-Schonlein purpura nephritis: a randomized controlled trial.

OBJECTIVE: To research the curative effect of Chinese herbs for clearing away heat, promoting diuresis, nourishing the kidney, and consolidating essence in children with Henoch-Schonlein purpura nephritis (HSPN) with internal accumulation of damp-toxin using randomized controlled observations on large samples. To seek the mechanism of the therapy and its scope of indications. METHODS: Overall, 186 children with HSPN were randomly divided into two groups: treatment group (n = 126) treated with Chinese herbs for clearing heat and promoting diuresis and a control group (n = 60) treated with Western Medicine. The treatment was carried out for three courses of 4 weeks each. We recorded changes in patient urine routines, 24 h urinary protein, blood-coagulating series, immunoglobulin and T-cell subgroups, and improvements in main symptoms. We evaluated the alleviation of clinical symptoms and the improvement of proteinuria, hematuria, and other laboratory test results. Finally, we analyzed the patient population suitable for this therapy according to the relationship between the grouping of patient body weight and curative effect. RESULTS: Damp-heat syndrome improved in the treatment group, with a significant difference in total effective rate after a 4-week treatment (chi2 = 13.5220, P = 0.0002) and in curative rate after a 12-week treatment (chi2 = 6.3410, P = 0.0118), compared to those in the control group. The curative effect in the treatment group was greater than that in the control group but there was no statistical difference between the two groups. The curative effect after a 4-week treatment of patients in the treatment group weighing 30 kg or less based on Traditional Chinese Medicine (TCM) signs and urinary protein was significantly greater than that in the control group. However, there was no statistical difference in the curative effect on urinary red cells and various indexes after a 12-week treatment between the two groups. CONCLUSION: Therapy for clearing away heat, promoting diuresis, nourishing the kidney, and consolidating essence using TCM is effective in children with HSPN from internal accumulation of damp-toxin. The therapy is especially suitable for patients weighing 30 kg or less. The curative effect may be related to the improvement of immune function and blood-coagulation.

Learning to Restore Compressed Point Cloud Attribute: A Fully Data-Driven Approach and A Rules-Unrolling-Based Optimization.

The emergence of holographic media drives the standardization of Geometry-based Point Cloud Compression (G-PCC) to sustain networked service provisioning. However, G-PCC inevitably introduces visually annoying artifacts, degrading the quality of experience (QoE). This work focuses on restoring G-PCC compressed point cloud attributes, e.g., RGB colors, to which fully data-driven and rules-unrolling-based post-processing filters are studied. At first, as compressed attributes exhibit nested blockiness, we develop a learning-based sample adaptive offset (NeuralSAO), which leverages a neural model using multiscale feature aggregation and embedding to characterize local correlations for quantization error compensation. Later, given statistically Gaussian distributed quantization noise, we suggest the utilization of a bilateral filter with Gaussian kernels to weigh neighbors by jointly considering their geometric and photometric contributions for restoration. Since local signals often present varying distributions, we propose estimating the smoothing parameters of the bilateral filter using an ultra-lightweight neural model. Such a bilateral filter with learnable parameters is called NeuralBF. The proposed NeuralSAO demonstrates the state-of-art restoration quality improvement, e.g., >20% BD-BR (Bjøntegaard delta rate) reduction over G-PCC on solid points clouds. However, NeuralSAO is computationally intensive and may suffer from poor generalization. On the other hand, although NeuralBF only achieves half of the gains of NeuralSAO, it is lightweight and exhibits impressive generalization across various samples. This comparative study between the data-driven large-scale NeuralSAO and the rules-unrolling-based small-scale NeuralBF helps to understand the capacity (i.e., performance, complexity, generalization) of underlying filters in terms of the quality restoration for compressed point cloud attribute.

A Versatile Point Cloud Compressor Using Universal Multiscale Conditional Coding - Part II: Attribute.

A universal multiscale conditional coding framework, Unicorn, is proposed to code the geometry and attribute of any given point cloud. Attribute compression is discussed in Part II of this paper, while geometry compression is given in Part I of this paper. We first construct the multiscale sparse tensors of each voxelized point cloud attribute frame. Since attribute components exhibit very different intrinsic characteristics from the geometry element, e.g., 8-bit RGB color versus 1-bit occupancy, we process the attribute residual between lower-scale reconstruction and current-scale data. Similarly, we leverage spatially lower-scale priors in the current frame and (previously processed) temporal reference frame to improve the probability estimation of attribute intensity through conditional residual prediction in lossless mode or enhance the attribute reconstruction through progressive residual refinement in lossy mode for better performance. The proposed Unicorn is a versatile, learning-based solution capable of compressing a great variety of static and dynamic point clouds in both lossy and lossless modes. Following the same evaluation criteria, Unicorn significantly outperforms standard-compliant approaches like MPEG G-PCC, V-PCC, and other learning-based solutions, yielding state-of-the-art compression efficiency with affordable encoding/decoding runtime.

A Versatile Point Cloud Compressor Using Universal Multiscale Conditional Coding - Part I: Geometry.

A universal multiscale conditional coding framework, Unicorn, is proposed to compress the geometry and attribute of any given point cloud. Geometry compression is addressed in Part I of this paper, while attribute compression is discussed in Part II. We construct the multiscale sparse tensors of each voxelized point cloud frame and properly leverage lower-scale priors in the current and (previously processed) temporal reference frames to improve the conditional probability approximation or content-aware predictive reconstruction of geometry occupancy in compression. Unicorn is a versatile, learning-based solution capable of compressing static and dynamic point clouds with diverse source characteristics in both lossy and lossless modes. Following the same evaluation criteria, Unicorn significantly outperforms standard-compliant approaches like MPEG G-PCC, V-PCC, and other learning-based solutions, yielding state-of-the-art compression efficiency while presenting affordable complexity for practical implementations.

Fluorinated BPA derivatives enhanced 10B delivery in tumors.

Boron neutron capture therapy (BNCT) is an emerging approach for treating malignant tumors with binary targeting. However, its clinical application has been hampered by insufficient 10B accumulation in tumors and low 10B concentration ratios of tumor-to-blood (T/B) and tumor-to-normal tissue (T/N). Herein, we developed fluorinated BPA derivatives with different fluorine groups as boron delivery agents for enabling sufficient 10B accumulation in tumors and enhancing T/B and T/N ratios. Our findings demonstrated that fluorinated BPA derivatives had good biological safety. Furthermore, fluorinated BPA derivatives showed improved 10B accumulation in tumors and enhanced T/B and T/N ratios compared to the clinical boron drug fructose-BPA (f-BPA). In particular, in B16-F10 tumor-bearing mice, fluorinated BPA derivatives met the requirements for clinical BNCT even at half of the clinical dose. Thus, fluorinated BPA derivatives are potentially effective boron delivery agents for clinical BNCT in melanoma.

Revealing underlying regulatory mechanisms of LINC00313 in Osimertinib-resistant LUAD cells by ceRNA network analysis.

BACKGROUND: Osimertinib, a third-generation epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI), is the preferred treatment for EGFR-mutated lung cancer. However, acquired resistance inevitably develops. While non-coding RNAs have been implicated in lung cancer through various functions, the molecular mechanisms responsible for osimertinib resistance remain incompletely elucidated. METHODS: RNA-sequencing technology was employed to determine differentially expressed lncRNAs (DE-lncRNAs) and mRNAs (DE-mRNAs) between H1975 and H1975OR cell lines. Starbase 2.0 was utilized to predict DE-lncRNA and DE-mRNA interactions, constructing ceRNA networks. Subsequently, functional and pathway enrichment analysis were performed on target DE-mRNAs to identify pathways associated with osimertinib resistance. Key target DE-mRNAs were then selected as potential risk signatures for lung adenocarcinoma (LUAD) prognostic modeling using multivariate Cox regression analyses. The Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) and immunohistochemistry staining were used for result validation. RESULTS: Functional analysis revealed that the identified DE-mRNAs primarily enriched in EGFR-TKI resistance pathways, especially in the PI3K/Akt signaling pathway, where their concerted actions may lead to osimertinib resistance. Specifically, upregulation of LINC00313 enhanced COL1A1 expression by acting as a miR-218-5p sponge, triggering an upstream response that activates the PI3K/Akt pathway, potentially contributing to osimertinib resistance. Furthermore, the expressions of LINC00313 and COL1A1 were validated by qRT-PCR, and the activation of the PI3K/Akt pathway was confirmed by immunohistochemistry staining. CONCLUSIONS: Our results suggest that the LINC00313/miR-218-5p/COL1A1 axis potentially contributes to osimertinib resistance through the PI3K/Akt signaling pathway, providing novel insights into the molecular mechanisms underlying acquired osimertinib resistance in LUAD. Additionally, our study may aid in the identification of potential therapeutic targets for overcoming resistance to osimertinib.

GRNet: Geometry Restoration for G-PCC Compressed Point Clouds Using Auxiliary Density Signaling.

The lossy Geometry-based Point Cloud Compression (G-PCC) inevitably impairs the geometry information of point clouds, which deteriorates the quality of experience (QoE) in reconstruction and/or misleads decisions in tasks such as classification. To tackle it, this work proposes GRNet for the geometry restoration of G-PCC compressed large-scale point clouds. By analyzing the content characteristics of original and G-PCC compressed point clouds, we attribute the G-PCC distortion to two key factors: point vanishing and point displacement. Visible impairments on a point cloud are usually dominated by an individual factor or superimposed by both factors, which are determined by the density of the original point cloud. To this end, we employ two different models for coordinate reconstruction, termed Coordinate Expansion and Coordinate Refinement, to attack the point vanishing and displacement, respectively. In addition, 4-byte auxiliary density information is signaled in the bitstream to assist the selection of Coordinate Expansion, Coordinate Refinement, or their combination. Before being fed into the coordinate reconstruction module, the G-PCC compressed point cloud is first processed by a Feature Analysis Module for multiscale information fusion, in which kNN-based Transformer is leveraged at each scale to adaptively characterize neighborhood geometric dynamics for effective restoration. Following the common test conditions recommended in the MPEG standardization committee, GRNet significantly improves the G-PCC anchor and remarkably outperforms state-of-the-art methods on a great variety of point clouds (e.g., solid, dense, and sparse samples) both quantitatively and qualitatively. Meanwhile, GRNet runs fairly fast and uses a smaller-size model when compared with existing learning-based approaches, making it attractive to industry practitioners.