CDK6 as a Biomarker for Immunotherapy, Drug Sensitivity, and Prognosis in Bladder Cancer: Bioinformatics and Immunohistochemical Analysis.

Background: CDK6 is linked to tumor progression and metastasis, although its molecular mechanism and prognostic value are unclear in bladder cancer. Materials and methods: In our study, raw data were obtained from public databases and Single-center retrospective case series. We conducted a bioinformatics analysis and immunohistochemistry to explore the biological landscape of CDK6 in tumors, with a particular focus on bladder cancer. We examined its expression characteristics and prognostic value and performed functional annotation analysis using gene function enrichment. We also assessed the association between bladder cancer molecular subtypes and mutation spectra and analyzed the landscape of the tumor immune microenvironment to predict treatment response sensitivity. Results: Our study found that CDK6 was a potential prognostic marker for bladder cancer. We discovered that bladder cancer patients with high CDK6 expression do not respond well to immunotherapy and have a poor prognosis. CDK6 regulates tumor immune status, metabolism, and cell cycle-related signaling pathways, thereby influencing tumor biological behavior. Furthermore, CDK6 mediated the suppression of the immune microenvironment to weaken anti-tumor immune responses. Finally, a comprehensive characterization of CDK6 was applied in the prognostic prediction of bladder cancer, suggesting that targeting CDK6 represents a potential therapeutic option. Conclusions: These results indicated that CDK6 is an independent biomarker for predicting prognosis and immunotherapy efficacy of bladder cancer. A deeper understanding of its specific molecular mechanisms may provide new treatment strategies.

Gut microbiota-mediated C-sulfonate metabolism impairs the bioavailability and anti-cholestatic efficacy of andrographolide.

Cholestatic liver injury results from the accumulation of toxic bile acids in the liver, presenting a therapeutic challenge with no effective treatment available to date. Andrographolide (AP) has exhibited potential as a treatment for cholestatic liver disease. However, its limited oral bioavailability poses a significant obstacle to harnessing its potent therapeutic properties and restricts its clinical utility. This limitation is potentially attributed to the involvement of gut microbiota in AP metabolism. In our study, employing pseudo-germ-free, germ-free and strain colonization animal models, along with 16S rRNA and shotgun metagenomic sequencing analysis, we elucidate the pivotal role played by gut microbiota in the C-sulfonate metabolism of AP, a process profoundly affecting its bioavailability and anti-cholestatic efficacy. Subsequent investigations pinpoint a specific enzyme, adenosine-5'-phosphosulfate (APS) reductase, predominantly produced by Desulfovibrio piger, which catalyzes the reduction of SO42- to HSO3-. HSO3- subsequently interacts with AP, targeting its C=C unsaturated double bond, resulting in the formation of the C-sulfonate metabolite, 14-deoxy-12(R)-sulfo andrographolide (APM). Inhibition of APS reductase leads to a notable enhancement in AP bioavailability and anti-cholestatic efficacy. Furthermore, employing RNA sequencing analysis and farnesoid X receptor (FXR) knockout mice, our findings suggest that AP may exert its anti-cholestatic effects by activating the FXR pathway to promote bile acid efflux. In summary, our study unveils the significant involvement of gut microbiota in the C-sulfonate metabolism of AP and highlights the potential benefits of inhibiting APS reductase to enhance its therapeutic effects. These discoveries provide valuable insights into enhancing the clinical applicability of AP as a promising treatment for cholestatic liver injury.

Identification and validation of reference genes for RT-qPCR analysis in Iris domestica under Cd stress.

Iris domestica is a widely used ornamental garden and important medicinal plant. Our previous studies have shown that it exhibits significant uptake and translocation capacity under Cd stress compared to other Iris species. Gene expression is studied using RT-qPCR; however, there are no reference genes have been found for I. domestica under Cd stress. In this investigation, thirteen possible reference genes from previous studies and our transcriptome were screened using RT-qPCR in the leaves and roots of Cd-stressed plants. The findings revealed that UBC9 and ACT were the best reference genes for roots with and without Cd stress, whereas YLS8 and ACT7 were the best reference genes for leaves. Among the different tissues without Cd stress, UBC9 and UBC28 exhibited the best results, whereas PP2C06 and UBC9 exhibited the best results under Cd stress. The most stable reference genes in the leaves and roots were UBC9 and UBC28, respectively, under and without Cd stress, and GADPH was the most unstable. Finally, three metal ion response genes, NRAMP2, YSL9 and CYP81Q32 were detected using RT-qPCR and compared with the transcriptome data to further confirm the reliability of the chosen genes. This study identified suitable reference genes for I. domestica under Cd-stress conditions.

Separation and purification of nylon 54 salts from fermentation broth by an integrated process involving microfiltration, ultrafiltration, and ion exchange.

Nylon 54 is a novel, biodegradable polyamide with excellent thermal resistance and water absorption properties. It can be polymerized using bio-based cadaverine and succinic acid as monomers. Traditional separation methods isolate individual monomers from the fermentation broth through acidification or alkalization, resulting in significant amounts of waste salts; however, synchronous separation of dibasic acids and diamines has not been reported. This study investigated an integrated process for the separation and extraction of nylon 54 salts from a co-fermentation broth without acidification or alkalization. We meticulously optimized the operational parameters of the integrated process to achieve maximum separation efficiency. Following microfiltration, ultrafiltration, and decolorization, the bacterial eliminating rate was ≥99.83%, and the protein concentration was ≤40 mg/L. The absorbance of the decolorized solution was ≤0.021 at 430 nm, and the recovery rate of nylon 54 salt reached 97%. Then, the pretreated solution was passed through sequential chromatographic columns, which effectively removed organic acid by-products (such as acetic acid and lactic acid), SO4 2-, and NH4 + from the fermentation broth, resulting in a cadaverine yield of 98.01% and a succinic acid yield of 89.35%. Finally, by concentrating and crystallizing the eluent, the simulated fermentation broth yielded nylon 54 salt with a purity of 99.16% and a recovery rate of 58%, and the real fermentation broth yielded nylon 54 salt with a purity of 98.10% and a recovery rate of 56.21%. This integrated process offers a sustainable and environmentally friendly pathway for the complete biosynthesis of nylon 54 salt and has the potential to be extended to the preparation of other nylon salts.

Alzheimer's disease protective allele of Clusterin modulates neuronal excitability through lipid-droplet-mediated neuron-glia communication.

Genome-wide association studies (GWAS) of Alzheimer's disease (AD) have identified a plethora of risk loci. However, the disease variants/genes and the underlying mechanisms remain largely unknown. For a strong AD-associated locus near Clusterin (CLU), we tied an AD protective allele to a role of neuronal CLU in promoting neuron excitability through lipid-mediated neuron-glia communication. We identified a putative causal SNP of CLU that impacts neuron-specific chromatin accessibility to transcription-factor(s), with the AD protective allele upregulating neuronal CLU and promoting neuron excitability. Transcriptomic analysis and functional studies in induced pluripotent stem cell (iPSC)-derived neurons co-cultured with mouse astrocytes show that neuronal CLU facilitates neuron-to-glia lipid transfer and astrocytic lipid droplet formation coupled with reactive oxygen species (ROS) accumulation. These changes cause astrocytes to uptake less glutamate thereby altering neuron excitability. Our study provides insights into how CLU confers resilience to AD through neuron-glia interactions.

Atf3-mediated metabolic reprogramming in hepatic macrophage orchestrates metabolic dysfunction-associated steatohepatitis.

Metabolic dysfunction-associated steatohepatitis (MASH) is regulated by complex interplay between the macrophages and surrounding cells in the liver. Here, we show that Atf3 regulates glucose-fatty acid cycle in macrophages attenuates hepatocyte steatosis, and fibrogenesis in hepatic stellate cells (HSCs). Overexpression of Atf3 in macrophages protects against the development of MASH in Western diet-fed mice, whereas Atf3 ablation has the opposite effect. Mechanistically, Atf3 improves the reduction of fatty acid oxidation induced by glucose via forkhead box O1 (FoxO1) and Cd36. Atf3 inhibits FoxO1 activity via blocking Hdac1-mediated FoxO1 deacetylation at K242, K245, and K262 and increases Zdhhc4/5-mediated CD36 palmitoylation at C3, C7, C464, and C466; furthermore, macrophage Atf3 decreases hepatocytes lipogenesis and HSCs activation via retinol binding protein 4 (Rbp4). Anti-Rbp4 can prevent MASH progression that is induced by Atf3 deficiency in macrophages. This study identifies Atf3 as a regulator of glucose-fatty acid cycle. Targeting macrophage Atf3 or Rbp4 may be a plausible therapeutic strategy for MASH.

Fracture behavior of additively manufactured corrax maraging stainless steel.

Additively manufactured a low carbon Fe-Cr-Ni-Al Corrax stainless steel has ultra-high strength, but the mechanism at work when the steel cracks is still unclear. In this study, Corrax stainless steel was tensile tested to fracture and cracks in the vicinity of the fracture surface were analyzed by scanning electron microscope and electron-backscattered diffraction. The results show that the cracks propagated at angles of 45-60° to the tensile axis. Some cracks were transgranular, and high-angle grain boundaries had little effect on crack propagation. Crack propagation was inhibited in regions with lower Taylor factors. Kernel average misorientation value analysis established that the crack propagation process is accompanied by significant plastic deformation. The influence of particles and unfused pores on crack propagation is also discussed.

Lignin-Based Carbon Fiber/Epoxy Resin Biocomposites with Excellent Fire Resistance and Mechanical Properties.

Carbon fiber (CF)-reinforced epoxy resin (EP) composites are lightweight materials with excellent comprehensive performance. However, the flammability of EP and the poor interfacial bonding between CF and EP are two key disadvantages that limit their further applications. Here, a kind of water-soluble lignin-based CF sizing agent (ELBEDK) is prepared through hydrophilic modification of enzymatic lignin, which can significantly enhance the interfacial interaction between CF and EP. Additionally, a highly efficient intumescent flame retardant (LMA) is prepared. The EP, enzymatic lignin, LMA and CF sized ELBEDK are compounded to obtain the fire-safety CF reinforced composites (SCF/FEP/L). The flame retardancy of SCF/FEP/L with 7% LMA (SCF/FEP7) reached V-0 rating. Moreover, SCF/FEP/L with 7% LMA and 15% lignin (SCF/FEP7/L15) present an limiting oxygen index (LOI)of 30.2% and V-0 of UL-94. Specifically, the total smoke production and the heat release rate are 47.8% and 46.81% lower than that of SCF/EP, respectively, indicating the improved smoke suppression and flame retardancy. The IFSS and flexural strength of SCF/FEP7/L15 are improved to be 59.4 MPa and 511.1 MPa, respectively. This study presents a simple approach to fabricate low-cost high performance lignin-based flame retardant CF/EP biocomposites with wide application potential.

Alzheimer's disease risk allele of PICALM causes detrimental lipid droplets in microglia.

Despite genome-wide association studies of late-onset Alzheimer's disease (LOAD) having identified many genetic risk loci1-6, the underlying disease mechanisms remain largely unknown. Determining causal disease variants and their LOAD-relevant cellular phenotypes has been a challenge. Leveraging our approach for identifying functional GWAS risk variants showing allele-specific open chromatin (ASoC)7, we systematically identified putative causal LOAD risk variants in human induced pluripotent stem cells (iPSC)-derived neurons, astrocytes, and microglia (MG) and linked PICALM risk allele to a previously unappreciated MG-specific role of PICALM in lipid droplet (LD) accumulation. ASoC mapping uncovered functional risk variants for 26 LOAD risk loci, mostly MG-specific. At the MG-specific PICALM locus, the LOAD risk allele of rs10792832 reduced transcription factor (PU.1) binding and PICALM expression, impairing the uptake of amyloid beta (Aß) and myelin debris. Interestingly, MG with PICALM risk allele showed transcriptional enrichment of pathways for cholesterol synthesis and LD formation. Genetic and pharmacological perturbations of MG further established a causal link between the reduced PICALM expression, LD accumulation, and phagocytosis deficits. Our work elucidates the selective LOAD vulnerability in microglia for the PICALM locus through detrimental LD accumulation, providing a neurobiological basis that can be exploited for developing novel clinical interventions.

Functionalized lignin nanoparticles assembled with MXene reinforced polypropylene with favorable UV-aging resistance, electromagnetic shielding effects and superior fire-safety.

Deterioration in mechanical performances and aging resistance due to the introduction of flame retardants is a major obstacle for bio-based fire-safety polypropylene (PP). Herein, we reported a kind of functionalized lignin nanoparticles assembled with MXene (MX@LNP), and applied it to construct the flame-retardant PP composites (PP-MA) with superior fire safety, excellent mechanical performance, electromagnetic shielding effects and aging resistance. Specifically, the PP-MA doped with only 18 wt% flame-retardant additives (PP-MA18) achieved the UL-94 V-0 rating. In comparison to pure PP, PP-MA18 presented a greatly decreased peak of heat release rate (pHRR), total heat rate (THR), and peak smoke production rate (pSPR) by 79.7 %, 69.0 % and 75.8 %, respectively, and satisfactory decrease in total flammable and toxic volatiles evolved. The formed fine solid microstructure of carbon residuals effectively promoted the compactness of char layers. More importantly, the nano-effect and the strong interface interaction between the complexed MX@LNP and PP enhanced the tensile strength (45.78 MPa) and elongation at break (725.95 %) of PP-MA. Additionally, the significant ultraviolet absorption and electromagnetic wave dissipation performance of MXene and lignin enabled excellent aging resistance and electromagnetic shielding effects of PP-MA compared with PP. This achieved MX@LNP afforded a novel approach for developing flame retardant materials with excellent application performance.

3D Visual Discomfort Assessment With a Weakly Supervised Graph Convolution Neural Network Based on Inaccurately Labeled EEG.

Visual discomfort significantly limits the broader application of stereoscopic display technology. Hence, the accurate assessment of stereoscopic visual discomfort is a crucial topic in this field. Electroencephalography (EEG) data, which can reflect changes in brain activity, have received increasing attention in objective assessment research. However, inaccurately labeled data, resulting from the presence of individual differences, restrict the effectiveness of the widely used supervised learning methods in visual discomfort assessment tasks. Simultaneously, visual discomfort assessment methods should pay greater attention to the information provided by the visual cortical areas of the brain. To tackle these challenges, we need to consider two key aspects: maximizing the utilization of inaccurately labeled data for enhanced learning and integrating information from the brain's visual cortex for feature representation purposes. Therefore, we propose the weakly supervised graph convolution neural network for visual discomfort (WSGCN-VD). In the classification part, a center correction loss serves as a weakly supervised loss, employing a progressive selection strategy to identify accurately labeled data while constraining the involvement of inaccurately labeled data that are influenced by individual differences during the model learning process. In the feature extraction part, a feature graph module pays particular attention to the construction of spatial connections among the channels in the visual regions of the brain and combines them with high-dimensional temporal features to obtain visually dependent spatio-temporal representations. Through extensive experiments conducted in various scenarios, we demonstrate the effectiveness of our proposed model. Further analysis reveals that the proposed model mitigates the impact of inaccurately labeled data on the accuracy of assessment.

Recombinant therapeutic proteins degradation and overcoming strategies in CHO cells.

Mammalian cell lines are frequently used as the preferred host cells for producing recombinant therapeutic proteins (RTPs) having post-translational modified modification similar to those observed in proteins produced by human cells. Nowadays, most RTPs approved for marketing are produced in Chinese hamster ovary (CHO) cells. Recombinant therapeutic antibodies are among the most important and promising RTPs for biomedical applications. One of the issues that occurs during development of RTPs is their degradation, which caused by a variety of factors and reducing quality of RTPs. RTP degradation is especially concerning as they could result in reduced biological functions (antibody-dependent cellular cytotoxicity and complement-dependent cytotoxicity) and generate potentially immunogenic species. Therefore, the mechanisms underlying RTP degradation and strategies for avoiding degradation have regained an interest from academia and industry. In this review, we outline recent progress in this field, with a focus on factors that cause degradation during RTP production and the development of strategies for overcoming RTP degradation. KEY POINTS: • The recombinant therapeutic protein degradation in CHO cell systems is reviewed. • Enzymatic factors and non-enzymatic methods influence recombinant therapeutic protein degradation. • Reducing the degradation can improve the quality of recombinant therapeutic proteins.

Novel Techniques and Models for Studying the Role of the Gut Microbiota in Drug Metabolism.

The gut microbiota, known as the second human genome, plays a vital role in modulating drug metabolism, significantly impacting therapeutic outcomes and adverse effects. Emerging research has elucidated that the microbiota mediates a range of modifications of drugs, leading to their activation, inactivation, or even toxication. In diverse individuals, variations in the gut microbiota can result in differences in microbe-drug interactions, underscoring the importance of personalized approaches in pharmacotherapy. However, previous studies on drug metabolism in the gut microbiota have been hampered by technical limitations. Nowadays, advances in biotechnological tools, such as microbially derived metabolism screening and microbial gene editing, have provided a deeper insight into the mechanism of drug metabolism by gut microbiota, moving us toward personalized therapeutic interventions. Given this situation, our review summarizes recent advances in the study of gut-microbiota-mediated drug metabolism and showcases techniques and models developed to navigate the challenges posed by the microbial involvement in drug action. Therefore, we not only aim at understanding the complex interaction between the gut microbiota and drugs and outline the development of research techniques and models, but we also summarize the specific applications of new techniques and models in researching gut-microbiota-mediated drug metabolism, with the expectation of providing new insights on how to study drug metabolism by gut microbiota.

Brain Lipids and Lipid Droplet Dysregulation in Alzheimer's Disease and Neuropsychiatric Disorders.

Background: Lipids are essential components of the structure and for the function of brain cells. The intricate balance of lipids, including phospholipids, glycolipids, cholesterol, cholesterol ester, and triglycerides, is crucial for maintaining normal brain function. The roles of lipids and lipid droplets and their relevance to neurodegenerative and neuropsychiatric disorders (NPDs) remain largely unknown. Summary: Here, we reviewed the basic role of lipid components as well as a specific lipid organelle, lipid droplets, in brain function, highlighting the potential impact of altered lipid metabolism in the pathogenesis of Alzheimer's disease (AD) and NDPs. Key Messages: Brain lipid dysregulation plays a pivotal role in the pathogenesis and progression of neurodegenerative and NPDs including AD and schizophrenia. Understanding the cell type-specific mechanisms of lipid dysregulation in these diseases is crucial for identifying better diagnostic biomarkers and for developing therapeutic strategies aiming at restoring lipid homeostasis.

Improved brain community structure detection by two-step weighted modularity maximization.

The human brain can be regarded as a complex network with interacting connections between brain regions. Complex brain network analyses have been widely applied to functional magnetic resonance imaging (fMRI) data and have revealed the existence of community structures in brain networks. The identification of communities may provide insight into understanding the topological functions of brain networks. Among various community detection methods, the modularity maximization (MM) method has the advantages of model conciseness, fast convergence and strong adaptability to large-scale networks and has been extended from single-layer networks to multilayer networks to investigate the community structure changes of brain networks. However, the problems of MM, suffering from instability and failing to detect hierarchical community structure in networks, largely limit the application of MM in the community detection of brain networks. In this study, we proposed the weighted modularity maximization (WMM) method by using the weight matrix to weight the adjacency matrix and improve the performance of MM. Moreover, we further proposed the two-step WMM method to detect the hierarchical community structures of networks by utilizing node attributes. The results of the synthetic networks without node attributes demonstrated that WMM showed better partition accuracy than both MM and robust MM and better stability than MM. The two-step WMM method showed better accuracy of community partitioning than WMM for synthetic networks with node attributes. Moreover, the results of resting state fMRI (rs-fMRI) data showed that two-step WMM had the advantage of detecting the hierarchical communities over WMM and was more insensitive to the density of the rs-fMRI networks than WMM.

Association Analysis of Transcriptome and Targeted Metabolites Identifies Key Genes Involved in Iris germanica Anthocyanin Biosynthesis.

The anthocyanin biosynthetic pathway is the main pathway regulating floral coloration in Iris germanica, a well-known ornamental plant. We investigated the transcriptome profiles and targeted metabolites to elucidate the relationship between genes and metabolites in anthocyanin biosynthesis in the bitone flower cultivar 'Clarence', which has a deep blue outer perianth and nearly white inner perianth. In this study, delphinidin-, pelargonidin-, and cyanidin-based anthocyanins were detected in the flowers. The content of delphinidin-based anthocyanins increased with the development of the flower. At full bloom (stage 3), delphinidin-based anthocyanins accounted for most of the total anthocyanin metabolites, whereas the content of pelargonidin- and cyanidin-based anthocyanins was relatively low. Based on functional annotations, a number of novel genes in the anthocyanin pathway were identified, which included early biosynthetic genes IgCHS, IgCHI, and IgF3H and late biosynthetic genes Ig F3'5'H, IgANS, and IgDFR. The expression of key structural genes encoding enzymes, such as IgF3H, Ig F3'5'H, IgANS, and IgDFR, was significantly upregulated in the outer perianth compared to the inner perianth. In addition, most structural genes exhibited their highest expression at the half-color stage rather than at the full-bloom stage, which indicates that these genes function ahead of anthocyanins synthesis. Moreover, transcription factors (TFs) of plant R2R3-myeloblastosis (R2R3-MYB) related to the regulation of anthocyanin biosynthesis were identified. Among 56 R2R3-MYB genes, 2 members belonged to subgroup 4, with them regulating the expression of late biosynthetic genes in the anthocyanin biosynthetic pathway, and 4 members belonged to subgroup 7, with them regulating the expression of early biosynthetic genes in the anthocyanin biosynthetic pathway. Quantitative real-time PCR (qRT-PCR) analysis was used to validate the data of RNA sequencing (RNA-Seq). The relative expression profiles of most candidate genes were consistent with the FPKM of RNA-seq. This study identified the key structural genes encoding enzymes and TFs that affect anthocyanin biosynthesis, which provides a basis and reference for the regulation of plant anthocyanin biosynthesis in I. germanica.

The relationship between self-control and mental health problems among Chinese university students.

Background: Mental health issues are often associated with poor self-control. Therefore, effective interventions against mental health problems should include self-control training. However, it is unclear whether the effect of self-control varies across different types of mental health problems. Methods: A cross-sectional survey was conducted using the convenience sampling method at five universities in Chongqing, China, where 1,409 students reported their demographic information, level of self-control, and symptoms of irritability, depression, and anxiety. Descriptive statistical methods and a network analysis approach were employed to explore the relationship between self-control and symptoms of irritability, depression, and anxiety among 1,409 students. The bridging links between self-control and the three mental health problems were analyzed. Results: The findings revealed a negative correlation between self-control and symptoms of irritability, depression, and anxiety among university students. Impulse control was found to be the bridge between self-control and irritability or anxiety symptoms, while resistance to temptation was the bridge between self-control and depressive symptoms. Conclusion: These results demonstrate the different relationship between self-control with irritability, anxiety, and depressive symptoms. The findings of this study may shed light on future mental health interventions for university students during potential public health emergencies, such as prior knowledge of the main types of psychological problems among university students, which may allow for the development of precise self-control intervention strategies, such as targeting impulsivity or resistance to temptation.

Hepatocytic lipocalin-2 controls HDL metabolism and atherosclerosis via Nedd4-1-SR-BI axis in mice.

High-density lipoprotein (HDL) metabolism is regulated by complex interplay between the scavenger receptor group B type 1 (SR-BI) and multiple signaling molecules in the liver. Here, we show that lipocalin-2 (Lcn2) is a key regulator of hepatic SR-BI, HDL metabolism, and atherosclerosis. Overexpression of human Lcn2 in hepatocytes attenuates the development of atherosclerosis via SR-BI in western-diet-fed Ldlr-/- mice, whereas hepatocyte-specific ablation of Lcn2 has the opposite effect. Mechanistically, hepatocyte Lcn2 improves HDL metabolism and alleviates atherogenesis by blocking Nedd4-1-mediated SR-BI ubiquitination at K500 and K508. The Lcn2-improved HDL metabolism is abolished in mice with hepatocyte-specific Nedd4-1 or SR-BI deletion and in SR-BI (K500A/K508A) mutation mice. This study identifies a regulatory axis from Lcn2 to HDL via blocking Nedd4-1-mediated SR-BI ubiquitination and demonstrates that hepatocyte Lcn2 may be a promising target to improve HDL metabolism to treat atherosclerotic cardiovascular diseases.

The expression and clinical value of LRP11, FUBP1 and TET1 in cervical cancer.

Cervical cancer is the second leading cause of cancer death among women worldwide. Identification of effective genes along with biological markers as targeting agents is very necessary for the diagnosis and treatment of this disease. Bioinformatics techniques along with genetic and molecular investigations have provided the possibility of studying different levels of information such as the genome, transcriptome, proteome, and metabolize with high depth and accuracy. The collection of these data provides comprehensive and valuable information about the investigated phenotypes, including complex diseases such as cancer. In this study, we examined three genes LRP11, FUBP1, and TET1 related to cervical cancer. The results of this study showed that the level of expression of these genes is high in lymph nodes and the thyroid and is less in the pancreas and liver. Also, the expression level of the FUBP1 gene is higher than that of LRP11, and the expression level of the LRP11 gene is higher than that of TET1. Regarding the structure and proteomics of the studied genes, it can be seen that due to the presence of more domains in the LRP11 and FUBP1 genes, these genes probably independently participate in various functions and have a wider range of activity than the TET1 gene. Also, the analysis of the stability of the examined genes showed that the stability of the FUBP1 gene is relatively higher than that of the TET1 gene, and this gene is also more stable than the LRP11 gene. Considering that these genes are effective key genes for the early detection of cervical cancer, it is hoped that they will be used as markers in the diagnosis and treatment of cervical cancer.

Probing the Effect of Photovoltaic Material on Voc in Ternary Polymer Solar Cells with Non-Fullerene Acceptors by Machine Learning.

The power conversion efficiency (PCE) of ternary polymer solar cells (PSCs) with non-fullerene has a phenomenal increase in recent years. However, improving the open circuit voltage (Voc) of ternary PSCs with non-fullerene still remains a challenge. Therefore, in this work, machine learning (ML) algorithms are employed, including eXtreme gradient boosting, K-nearest neighbor and random forest, to quantitatively analyze the impact mechanism of Voc in ternary PSCs with the double acceptors from the two aspects of photovoltaic materials. In one aspect of photovoltaic materials, the doping concentration has the greatest impact on Voc in ternary PSCs. Furthermore, the addition of the third component affects the energy offset between the donor and acceptor for increasing Voc in ternary PSCs. More importantly, to obtain the maximum Voc in ternary PSCs with the double acceptors, the HOMO and LUMO energy levels of the third component should be around (-5.7 ± 0.1) eV and (-3.6 ± 0.1) eV, respectively. In the other aspect of molecular descriptors and molecular fingerprints in the third component of ternary PSCs with the double acceptors, the hydrogen bond strength and aromatic ring structure of the third component have high impact on the Voc of ternary PSCs. In partial dependence plot, it is clear that when the number of methyl groups is four and the number of carbonyl groups is two in the third component of acceptor, the Voc of ternary PSCs with the double acceptors can be maximized. All of these findings provide valuable insights into the development of materials with high Voc in ternary PSCs for saving time and cost.