Structural basis for human Cav1.2 inhibition by multiple drugs and the neurotoxin calciseptine.

Cav1.2 channels play crucial roles in various neuronal and physiological processes. Here, we present cryo-EM structures of human Cav1.2, both in its apo form and in complex with several drugs, as well as the peptide neurotoxin calciseptine. Most structures, apo or bound to calciseptine, amlodipine, or a combination of amiodarone and sofosbuvir, exhibit a consistent inactivated conformation with a sealed gate, three up voltage-sensing domains (VSDs), and a down VSDII. Calciseptine sits on the shoulder of the pore domain, away from the permeation path. In contrast, when pinaverium bromide, an antispasmodic drug, is inserted into a cavity reminiscent of the IFM-binding site in Nav channels, a series of structural changes occur, including upward movement of VSDII coupled with dilation of the selectivity filter and its surrounding segments in repeat III. Meanwhile, S4-5III merges with S5III to become a single helix, resulting in a widened but still non-conductive intracellular gate.

Acetylation of PHF5A Modulates Stress Responses and Colorectal Carcinogenesis through Alternative Splicing-Mediated Upregulation of KDM3A.

Alternative pre-mRNA-splicing-induced post-transcriptional gene expression regulation is one of the pathways for tumors maintaining proliferation rates accompanying the malignant phenotype under stress. Here, we uncover a list of hyperacetylated proteins in the context of acutely reduced Acetyl-CoA levels under nutrient starvation. PHF5A, a component of U2 snRNPs, can be acetylated at lysine 29 in response to multiple cellular stresses, which is dependent on p300. PHF5A acetylation strengthens the interaction among U2 snRNPs and affects global pre-mRNA splicing pattern and extensive gene expression. PHF5A hyperacetylation-induced alternative splicing stabilizes KDM3A mRNA and promotes its protein expression. Pathologically, PHF5A K29 hyperacetylation and KDM3A upregulation axis are correlated with poor prognosis of colon cancer. Our findings uncover a mechanism of an anti-stress pathway through which acetylation on PHF5A promotes the cancer cells' capacity for stress resistance and consequently contributes to colon carcinogenesis.

LAMTOR1 ablation impedes cGAS degradation caused by chemotherapy and promotes antitumor immunity.

Chemotherapy resistance remains a significant obstacle that limits the long-term efficacy of cancer therapy, necessitating further investigations into the underlying mechanisms. Here, we find that DNA fragments induced by chemotherapeutic agents trigger the degradation of cGAS, a potent double-strand DNA (dsDNA) sensor, by lysosomes. Mechanically, the lysosome-localized protein LAMTOR1 is up-regulated, and the interaction between LAMTOR1 and cGAS is enhanced upon exposure to DNA fragments, boosting the accumulation and digestion of cGAS in lysosomes through the receptor protein p62. LAMTOR1 deficiency increases cGAS abundance and promotes activation of the cGAS-STING pathway, leading to subsequent production of type I interferons induced by cytosolic DNA stimulation. Loss of LAMTOR1 synergizes with immunotherapy and chemotherapy to inhibit tumor growth and prolong the survival time of tumor-bearing mice by promoting the infiltration of effective T lymphocytes. Thus, our study reveals a regulation of cGAS abundance and provides a potential strategy to overcome chemotherapy resistance by targeting LAMTOR1.

Structural basis of SecA-mediated protein translocation.

Secretory proteins are cotranslationally or posttranslationally translocated across lipid membranes via a protein-conducting channel named SecY in prokaryotes and Sec61 in eukaryotes. The vast majority of secretory proteins in bacteria are driven through the channel posttranslationally by SecA, a highly conserved ATPase. How a polypeptide chain is moved by SecA through the SecY channel is poorly understood. Here, we report electron cryomicroscopy structures of the active SecA-SecY translocon with a polypeptide substrate. The substrate is captured in different translocation states when clamped by SecA with different nucleotides. Upon binding of an ATP analog, SecA undergoes global conformational changes to push the polypeptide substrate toward the channel in a way similar to how the RecA-like helicases translocate their nucleic acid substrates. The movements of the polypeptide substrates in the SecA-SecY translocon share a similar structural basis to those in the ribosome-SecY complex during cotranslational translocation.

TIPE2 protein restrains invariant NKT activation and protects against immune-mediated hepatitis in mice.

BACKGROUND AND AIMS: Concanavalin A (ConA) administration induces a rapid and severe liver injury in mice, and invariant natural killer T (iNKT) cells are recognized to be the key effector cells in this process. However, the underlying regulatory mechanisms are not well defined. APPROACH AND RESULTS: We found that iNKT cells constitutively expressed TIPE2 (Tumor necrosis factor-α-induced protein 8-like 2, or TNFAIPL2). Genetic TIPE2 ablation strongly sensitized mice to ConA-induced hepatitis, accompanied with hyperactivation of iNKT cells. Moreover, Tipe2-/- mice were also more susceptible to α-galactosylceramide (αGalCer)-induced liver injury, with elevated serum ALT level and enhanced proinflammatory cytokine production. CD1d signaling blockade or iNKT cell elimination through antibodies reduced the effect of TIPE2 deficiency on liver injury. Mechanistic studies revealed that TIPE2 in iNKT cells functioned as a negative regulator, limiting iNKT cell activity and cytokine production through PIP3- AKT/mTOR pathway. TIPE2-mediated protection from liver injury was further validated by the administration of adeno-associated viruses expressing TIPE2, which effectively ameliorated ConA-induced hepatic injury. However, TIPE2 was dispensable in two other liver injury models, including D-GalN/LPS and APAP-induced hepatitis. CONCLUSION: Our findings reveal a new role of TIPE2 in the attenuation of iNKT cell-mediated hepatic injury. We propose that TIPE2 serves as an important regulator of immune homeostasis in the liver, and might be exploited for the therapeutic treatment of autoimmune liver diseases.

SIRT2 negatively regulates the cGAS-STING pathway by deacetylating G3BP1.

SIRT2, a cytoplasmic member of the Sirtuin family, has important roles in immunity and inflammation. However, its function in regulating the response to DNA virus infection remains elusive. Here, we find that SIRT2 is a unique regulator among the Sirtuin family that negatively modulates the cGAS-STING-signaling pathway. SIRT2 is down-regulated after Herpes simplex virus-1 (HSV-1) infection, and SIRT2 deficiency markedly elevates the expression levels of type I interferon (IFN). SIRT2 inhibits the DNA binding ability and droplet formation of cGAS by interacting with and deacetylating G3BP1 at K257, K276, and K376, leading to the disassembly of the cGAS-G3BP1 complex, which is critical for cGAS activation. Administration of AGK2, a selective SIRT2 inhibitor, protects mice from HSV-1 infection and increases the expression of IFN and IFN-stimulated genes. Our study shows that SIRT2 negatively regulates cGAS activation through G3BP1 deacetylation, suggesting a potential antiviral strategy by modulating SIRT2 activity.

fMRI spectral signatures of sleep.

Sleep can be distinguished from wake by changes in brain electrical activity, typically assessed using electroencephalography (EEG). The hallmark of nonrapid-eye-movement (NREM) sleep is the shift from high-frequency, low-amplitude wake EEG to low-frequency, high-amplitude sleep EEG dominated by spindles and slow waves. Here we identified signatures of sleep in brain hemodynamic activity, using simultaneous functional MRI (fMRI) and EEG. We found that, at the transition from wake to sleep, fMRI blood oxygen level-dependent (BOLD) activity evolved from a mixed-frequency pattern to one dominated by two distinct oscillations: a low-frequency (<0.1 Hz) oscillation prominent in light sleep and correlated with the occurrence of spindles, and a high-frequency oscillation (>0.1 Hz) prominent in deep sleep and correlated with the occurrence of slow waves. The two oscillations were both detectable across the brain but exhibited distinct spatiotemporal patterns. During the falling-asleep process, the low-frequency oscillation first appeared in the thalamus, then the posterior cortex, and lastly the frontal cortex, while the high-frequency oscillation first appeared in the midbrain, then the frontal cortex, and lastly the posterior cortex. During the waking-up process, both oscillations disappeared first from the thalamus, then the frontal cortex, and lastly the posterior cortex. The BOLD oscillations provide local signatures of spindle and slow wave activity. They may be employed to monitor the regional occurrence of sleep or wakefulness, track which regions are the first to fall asleep or wake up at the wake-sleep transitions, and investigate local homeostatic sleep processes.

Comparative genomic analysis of pathogenic factors of Listeria spp. using whole-genome sequencing.

Listeria monocytogenes is an important foodborne pathogen known for causing listeriosis. To gain insights into the pathogenicity, genetic characterization, and evolution of various Listeria species, in vitro cell adhesion and invasion ability assays and whole-genome sequencing were performed using four Listeria strains isolated from livestock and poultry slaughterhouses. The four Listeria strains exhibited adhesion and invasion abilities in Caco-2 and RAW264.7 cells. Pathogenic Liv1-1 and Lm2-20 had higher adhesion ability, but non-pathogenic Lin4-99 was more invasive than Lm2-20 (p < 0.05). Genetic characterization revealed the presence of a single chromosome without plasmid across four strains with similar whole-genome sizes and G + C% content. Analysis of key pathogenic genes underscored the presence of multiple virulence genes among the four Listeria strains. In contrast, non-pathogenic Listeria lacked LIPI-1, LIPI-2, and LIPI-3 genes, which could possibly be the cause of their non-pathogenicity despite their in vitro cell adhesion and invasion abilities. Thus, genetic determinants of Listeria do not necessarily predict cell adhesion and/or invasive ability in vitro. This study presents a comprehensive comparative genome-wide analysis of four Listeria strains, offering invaluable insights into the pathogenesis of the Listeria genus.

PLM-T3SE: Accurate Prediction of Type III Secretion Effectors Using Protein Language Model Embeddings.

The Type III secretion effectors (T3SEs) are bacterial proteins synthesized by Gram-negative pathogens and delivered into host cells via the Type III secretion system (T3SS). These effectors usually play a pivotal role in the interactions between bacteria and hosts. Hence, the precise identification of T3SEs aids researchers in exploring the pathogenic mechanisms of bacterial infections. Since the diversity and complexity of T3SE sequences often make traditional experimental methods time-consuming, it is imperative to explore more efficient and convenient computational approaches for T3SE prediction. Inspired by the promising potential exhibited by pre-trained language models in protein recognition tasks, we proposed a method called PLM-T3SE that utilizes protein language models (PLMs) for effective recognition of T3SEs. First, we utilized PLM embeddings and evolutionary features from the position-specific scoring matrix (PSSM) profiles to transform protein sequences into fixed-length vectors for model training. Second, we employed the extreme gradient boosting (XGBoost) algorithm to rank these features based on their importance. Finally, a MLP neural network model was used to predict T3SEs based on the selected optimal feature set. Experimental results from the cross-validation and independent test demonstrated that our model exhibited superior performance compared to the existing models. Specifically, our model achieved an accuracy of 98.1%, which is 1.8%-42.4% higher than the state-of-the-art predictors based on the same independent data set test. These findings highlight the superiority of the PLM-T3SE and the remarkable characterization ability of PLM embeddings for T3SE prediction.

LncRNA XIST/miR-455-3p/HOXC4 axis promotes breast cancer development by activating TGF-ß/SMAD signaling pathway.

Breast cancer is the second primary cause of cancer death among women. Long non-coding RNA (lncRNA) X-inactive specific transcript (XIST) is a central regulator for X chromosome inactivation, and its abnormal expression is a primary feature of breast cancer. So far, the mechanism of XIST in breast cancer has not been fully elucidated. We attempted to illustrate the mechanism of XIST in breast cancer. The expressions of XIST, microRNA-455-3p (miR-455-3p) in breast cancer were measured using quantitative real-time PCR. The expressions of homeobox C4 (HOXC4) were assessed with immunohistochemical and Western blot. Also, the functions of XIST in breast cancer were assessed by Cell Counting Kit-8 analysis, colony formation assay, flow cytometry, Western blot, Transwell, and cell scratch assays. Meanwhile, the mechanism of XIST in breast cancer was validated using database analysis and dual-luciferase reporter assay. Furthermore, the function of XIST in breast cancer in vivo was estimated by tumor xenograft model, immunohistochemical assay, and hematoxylin-eosin staining. XIST and HOXC4 expressions were increased, but miR-455-3p expressions were decreased in breast cancer tissues and cells. Knocking down XIST restrained breast cancer cell proliferation, invasion, migration, epithelial-mesenchymal transformation (EMT), and induced cell cycle arrest at G0/G1. Meanwhile, XIST interacted with miR-455-3p, while miR-455-3p interacted with HOXC4. XIST knockdown repressed breast cancer cell proliferation, invasion, and EMT, while miR-455-3p inhibitor or HOXC4 overexpression abolished those impacts. HOXC4 overexpression also blocked the impacts of miR-455-3p mimic on breast cancer cell malignant behavior. In vivo experimental data further indicated that XIST knockdown repressed breast cancer cell tumorigenic ability, and decreased HOXC4 and p-SMAD3 (TGF-ß/SMAD-related protein) expressions.XIST/miR-455-3p/HOXC4 facilitated breast cancer development by activating the TGF-ß/SMAD pathway.

A Highly Specific and Versatile Biochip for Ultra-Sensitive Quantification of Denatured Collagen in Assessing Collagen Quality.

Collagen, a widely used biomaterial, is susceptible to denaturation during production from native tissues, posing serious challenges for its applications in tissue engineering. Accurate quantification of denatured collagen (DC) is essential for evaluating the quality of collagen-based biomaterials, yet quantitative methods for assessing collagen denaturation are lacking. Here, we for the first time present a highly specific biochip for sensitive quantification of denatured collagen levels (Ldc), addressing this critical need in collagen quality analysis. The denatured collagen-specific chip (DCSC) features an intrinsically nontrimerizing peptide probe, F-GOP-14, targeting denatured collagen and a fully denatured collagen-coated capture surface. The DCSC demonstrates exceptional sensitivity and accuracy in quantifying DC concentration (Cdc) and total collagen concentration (Ctc), enabling precise calculation of Ldc. Importantly, DCSC is versatile, detecting Ldc across various denaturing scenarios, including UV radiation, thermal environments, and decellularization. This denatured collagen-specific biochip offers a robust method for accurately analyzing Ldc, with significant potential for enhancing collagen quality assessment in biomaterial development and production.

An Unconventional Immunosensor for Biomolecule Detection via Nonspecific Gold Nanoparticle-Antibody Interactions.

Immunogold, that is, gold nanoparticles (AuNPs) conjugated with biomolecules such as antibodies and peptides, have been widely used to construct sandwiched immunosensors for biodetection. Two main challenges in these immunoassays are difficulties in finding and validating a suitable antibody, and the nonspecific interaction between the substrate and immunogold, which lowers the detection sensitivity and even causes false results. To avoid these issues, we took advantage of the nonspecific interaction between AuNPs and capture antibodies and proposed a new sensing mechanism. That is, after the capture of analyte targets by the capture antibodies on the substrate, AuNPs of certain chemical functionality would preferably bind to the free capture antibodies. Consequently, the amount of deposited AuNPs will inversely depend on the concentration of the analytes. As a proof-of-concept, we designed a mass-based sensor where anti-IgG antibodies were coated on a quartz crystal microbalance substrate. After IgG was introduced, tannic acid-capped AuNPs were applied to bind with the free anti-IgG antibody molecules. A frequency change (Δf) of the quartz substrate was induced by the increased mass loading. To further amplify the loading mass, an Ag enhancer solution was added, and Ag growth was catalyzed by the bound AuNPs. The Δf response showed a concentration-dependent decrease when increasing IgG concentration with a detection limit of 2.6 ng/mL. This method relies on the nonspecific interaction between AuNPs and anti-IgG antibodies to realize sensitive detection of IgG and eliminates the use of detection antibodies. The concept is an alternative to many existing immunoassay technologies.

High-Performance Bifunctional Electrocatalysts for Flexible and Rechargeable Zn-Air Batteries: Recent Advances.

Flexible rechargeable Zn-air batteries (FZABs) exhibit high energy density, ultra-thin, lightweight, green, and safe features, and are considered as one of the ideal power sources for flexible wearable electronics. However, the slow and high overpotential oxygen reaction at the air cathode has become one of the key factors restricting the development of FZABs. The improvement of activity and stability of bifunctional catalysts has become a top priority. At the same time, FZABs should maintain the battery performance under different bending and twisting conditions, and the design of the overall structure of FZABs is also important. Based on the understanding of the three typical configurations and working principles of FZABs, this work highlights two common strategies for applying bifunctional catalysts to FZABs: 1) powder-based flexible air cathode and 2) flexible self-supported air cathode. It summarizes the recent advances in bifunctional oxygen electrocatalysts and explores the various types of catalyst structures as well as the related mechanistic understanding. Based on the latest catalyst research advances, this paper introduces and discusses various structure modulation strategies and expects to guide the synthesis and preparation of efficient bifunctional catalysts. Finally, the current status and challenges of bifunctional catalyst research in FZABs are summarized.

Constrution of Quinazoline-Linked Covalent Organic Frameworks via a Multicomponent Reaction for Photocatalysis.

Quinazoline (Qz)-linked covalent organic frameworks (COFs) have been constructed via a three-component reaction of ortho-acylanilines, benzaldehydes and NH4OAc. The structure of Qz-COFs has been confirmed by solid-state nuclear magnetic resonance spectroscopy, Fourier transform infrared and powder X-ray diffraction patterns. The Qz-COFs possess high chemical stability, showing good endurance to strong acid, strong base, oxidant, reductant and other conditions. Particularly, Qz-COF-3 can catalyze the aerobic photooxidation of toluene and other compounds containing C(sp3)-H bonds.

PreDBP-PLMs: Prediction of DNA-binding proteins based on pre-trained protein language models and convolutional neural networks.

The recognition of DNA-binding proteins (DBPs) is the crucial step to understanding their roles in various biological processes such as genetic regulation, gene expression, cell cycle control, DNA repair, and replication within cells. However, conventional experimental methods for identifying DBPs are usually time-consuming and expensive. Therefore, there is an urgent need to develop rapid and efficient computational methods for the prediction of DBPs. In this study, we proposed a novel predictor named PreDBP-PLMs to further improve the identification accuracy of DBPs by fusing the pre-trained protein language model (PLM) ProtT5 embedding with evolutionary features as input to the classic convolutional neural network (CNN) model. Firstly, the ProtT5 embedding was combined with different evolutionary features derived from the position-specific scoring matrix (PSSM) to represent protein sequences. Then, the optimal feature combination was selected and input to the CNN classifier for the prediction of DBPs. Finally, the 5-fold cross-validation (CV), the leave-one-out CV (LOOCV), and the independent set test were adopted to examine the performance of PreDBP-PLMs on the benchmark datasets. Compared to the existing state-of-the-art predictors, PreDBP-PLMs exhibits an accuracy improvement of 0.5 % and 5.2 % on the PDB186 and PDB2272 datasets, respectively. It demonstrated that the proposed method could serve as a useful tool for the recognition of DBPs.

Rotameric heterogeneity of conserved tryptophan is responsible for reduced photochemical quantum yield in cyanobacteriochrome slr1393g3.

The red/green cyanobacteriochrome (CBCR) slr1393g3 exhibits a quantum yield of only 8% for its forward photoconversion significantly lower than other species from the same CBCR subfamily. The cause for this reduced photoconversion is not yet clear, although in the related NpR6012g4 dark-state structural heterogeneity of a paramount Trp residue has been proposed to cause the formation of nonproductive subpopulation. However, there is no such information on the equivalent residue in slr1393g3, W496. Here we use solid-state NMR to explore all possible sidechain rotamers of this Trp residue and their local interactions at the atomic level. The indole nitrogen (Nε1) is used as an NMR probe, achieved by site-specific 15N-indole labeling of a quadruply Trp-deleted variant and trehalose vitrification technique. The data reveal a set of seven indole rotamers of W496 with four distinct environments for the Nε1-H group. Only a minority population of 20% is found to retain the π-stacking and hydrogen-bonding interactions with the chromophore in the dark state that has been assigned to account for complete forward photoconversion. Our results demonstrate the direct role of W496 in modulating the forward quantum yield of slr1393g3 via rearrangement of its sidechain rotameric conformations.

Association Between Sarcopenia, Clinical Outcomes, and Survival in Patients with Extensive-Stage Small Cell Lung Cancer Treated with First-Line Immunochemotherapy: A Prospective Cohort Study.

OBJECTIVE: To investigate the association between sarcopenia, short-term efficacy, and long-term survival in patients with extensive small-cell lung cancer (SCLC) treated with standard first-line immunochemotherapy. METHODS: A total of 63 patients initially diagnosed with extensive-stage small cell lung cancer were enrolled in the prospective study from December 1, 2020 to December 31, 2022. The clinical characteristics, body composition, blood test results, and image data were obtained before treatment. Patients were divided into sarcopenia and non-sarcopenia groups according to the diagnostic criteria of the Asian Sarcopenia Working Group 2019. The primary outcome was overall survival (OS) and comprehensive survival analyses were performed. Secondary outcomes included short-term efficacy and adverse events associated with first-line immunochemotherapy. RESULTS: The median age of the 63 patients enrolled in our study was 63.0 years (40-80 years). The incidence of sarcopenia was 19.0% (12/63) in patients with extensive SCLC. Compared with non-sarcopenia patients, extensive-stage SCLC patients with sarcopenia were significantly older (69.0 vs. 62.0, P = 0.017), and had lower body mass index (BMI) (20.29 vs. 24.27, P < 0.001), hand grip strength (HGS) (20.42 vs. 30.75, P < 0.001), and albumin (35.9 vs. 41.40, P < 0.001). The objective response rate after two cycles of standard first-line immunochemotherapy in the sarcopenia group was lower than in the non-sarcopenia group (30.0 vs. 78.9%, P = 0.012). There was no significant difference in chemotherapy-related hematological toxicity between the two groups. During a median follow-up of 15 months (3-33 months), patients with extensive SCLC had a median OS of 24 months, with 1-year survival of 75% and 2-year survival of 52%, respectively. Compared to non-sarcopenia patients, the median OS in the sarcopenia group was significantly shorter (9 vs. 24 months, P = 0.0014). Multivariate Cox analysis showed that sarcopenia was an independent risk factor for OS in patients with extensive SCLC (HR = 4.993, 95%CI = 1.106-22.538, P = 0.037). CONCLUSIONS: Patients with Extensive SCLC and sarcopenia had worse clinical outcomes and shorter OS. Sarcopenia is a prognostic factor affecting first-line treatment efficacy and long-term survival of patients with SCLC in the era of immunotherapy.

Knowledge-guided data mining on the standardized architecture of NRPS: Subtypes, novel motifs, and sequence entanglements.

Non-ribosomal peptide synthetase (NRPS) is a diverse family of biosynthetic enzymes for the assembly of bioactive peptides. Despite advances in microbial sequencing, the lack of a consistent standard for annotating NRPS domains and modules has made data-driven discoveries challenging. To address this, we introduced a standardized architecture for NRPS, by using known conserved motifs to partition typical domains. This motif-and-intermotif standardization allowed for systematic evaluations of sequence properties from a large number of NRPS pathways, resulting in the most comprehensive cross-kingdom C domain subtype classifications to date, as well as the discovery and experimental validation of novel conserved motifs with functional significance. Furthermore, our coevolution analysis revealed important barriers associated with re-engineering NRPSs and uncovered the entanglement between phylogeny and substrate specificity in NRPS sequences. Our findings provide a comprehensive and statistically insightful analysis of NRPS sequences, opening avenues for future data-driven discoveries.

Exploring the Alternative Conformation of a Known Protein Structure Based on Contact Map Prediction.

The rapid development of deep learning-based methods has considerably advanced the field of protein structure prediction. The accuracy of predicting the 3D structures of simple proteins is comparable to that of experimentally determined structures, providing broad possibilities for structure-based biological studies. Another critical question is whether and how multistate structures can be predicted from a given protein sequence. In this study, analysis of tens of two-state proteins demonstrated that deep learning-based contact map predictions contain structural information on both states, which suggests that it is probably appropriate to change the target of deep learning-based protein structure prediction from one specific structure to multiple likely structures. Furthermore, by combining deep learning- and physics-based computational methods, we developed a protocol for exploring alternative conformations from a known structure of a given protein, by which we successfully approached the holo-state conformations of multiple representative proteins from their apo-state structures.

Numerical investigation on the convergence of self-consistent Schrödinger-Poisson equations in semiconductor device transport simulation.

Semiconductor devices at the nanoscale with low-dimensional materials as channels exhibit quantum transport characteristics, thereby their electrical simulation relies on the self-consistent solution of the Schrödinger-Poisson equations. While the non-equilibrium Green's function (NEGF) method is widely used for solving this quantum many-body problem, its high computational cost and convergence challenges with the Poisson equation significantly limit its applicability. In this study, we investigate the stability of the NEGF method coupled with various forms of the Poisson equation, encompassing linear, analytical nonlinear, and numerical nonlinear forms Our focus lies on simulating carbon nanotube field-effect transistors (CNTFETs) under two distinct doping scenarios: electrostatic doping and ion implantation doping. The numerical experiments reveal that nonlinear formulas outperform linear counterpart. The numerical one demonstrates superior stability, particularly evident under high bias and ion implantation doping conditions. Additionally, we investigate different approaches for presolving potential, leveraging solutions from the Laplace equation and a piecewise guessing method tailored to each doping mode. These methods effectively reduce the number of iterations required for convergence.