Advancements and challenges in stem cell transplantation for regenerative medicine.

Stem cell transplantation has emerged as a promising avenue in regenerative medicine, potentially facilitating tissue repair in degenerative diseases and injuries. This review comprehensively examines recent developments and challenges in stem cell transplantation. It explores the identification and isolation of various stem cell types, including embryonic, induced pluripotent, and adult stem cells derived from multiple sources. Additionally, the review highlights the tissue-specific applications of these stem cells, focusing on bone and cartilage regeneration, treatment of neurological disorders, and management of hematological conditions. Future advancements and effective resolution of current challenges will be crucial in fully realizing the potential of stem cell transplantation in regenerative medicine. With responsible and ethical practices, the field can potentially transform disease and injury treatment, ultimately improving the quality of life for countless individuals.

Knowledge, Attitude, and Practice Toward Varicocele in Patients with Varicoceles: A Cross-Sectional Study in Chinese Patients.

Objective: To explore patients' knowledge, attitude, and practice (KAP) toward varicocele in China and the relationship between treatment selection and KAP. Methods: This cross-sectional study enrolled varicocele patients at the Third Affiliated Hospital of Soochow University (September to October 2023). Structural equation modeling (SEM) was used to explore the relationship between clinical factors and KAP. A score >mean score for each dimension was defined as adequate knowledge, positive attitude, and proactive practice. The patients were grouped according to varicocelectomy vs no surgery. Univariable and multivariable logistic regression analyses were used to identify the factors independently associated with KAP. A structural equation modeling (SEM) analysis was performed to examine how the KAP dimensions influenced each other. Results: Among 502 patients, 44.02%, 35.86%, and 20.12% were ≤30, 31-40, and >40 years old, respectively. Those who underwent varicocelectomy (n=407) had significantly higher knowledge (20 (15-22) vs 0 (0-6), P<0.001), attitude (26 (24-26) vs 14 (10-18), P<0.001), and practice (20 (17-24) vs 8 (6-16), P<0.001) than those who did not. A higher proportion of patients with varicocelectomy were <40 years old, more educated, had higher income, and were unmarried compared with those without surgery (all P<0.001). High school or higher education level and varicocelectomy (irrespective of type) were independently associated with adequate knowledge (all P<0.001). Knowledge, college/bachelor's degree education, and varicocelectomy type (irrespective of type) were associated with positive attitudes (all P<0.05). In the SEM, knowledge directly influenced attitude, knowledge directly influenced practice, and attitude directly influenced practice (all P<0.001). Having knowledge of the subject may direct varicocele patients to varicocelectomy. Conclusion: Chinese patients who underwent varicocelectomy exhibit appropriate KAP regarding varicocele, while non-surgery patients have poorer KAP. These results suggest that patients who did not undergo surgery should nevertheless be properly informed about their disease.

Forming Single-Cell-Derived Colon Cancer Organoid Arrays on a Microfluidic Chip for High Throughput Tumor Heterogeneity Analysis.

Single-cell-derived tumor organoids (STOs) possess a distinct genetic background, making them valuable tools for demonstrating tumor heterogeneity. In order to fulfill the high throughput demands of STO assays, we have developed a microfluidic chip containing 30 000 microwells, which is dedicated to a single cell culture approach for selective expansion and differential induction of cancer stem cells. The microwells are coated with a hydrophilic copolymer to eliminate cell adhesion, and the cell culture is supported by poly(ethylene glycol) (PEG) to establish a nonadhesive culture environment. By utilizing an input cell density of 7 × 103·mL-1, it is possible to construct a 4000 single cell culture system through stochastic cell occupation. We demonstrate that the addition of 15% PEG10000 in the cell culture medium effectively prevents cell loss while facilitating tumor stem cell expansion. As were demonstrated by HCT116, HT29, and SW480 colon cancer cells, the microfluidic approach achieved a STO formation rate of ∼20%, resulting in over 800 STOs generated from a single culture. Comprehensive analysis through histomorphology, immunohistochemistry, drug response evaluation, assessment of cell invasion, and biomarker detection reveals the heterogeneity among individual STOs. Specifically, the smaller STOs exhibited higher invasion and drug resistance capabilities compared with the larger ones. The developed microfluidic approach effectively facilitates STO formation and offers promising prospects for investigating tumor heterogeneity, as well as conducting personalized therapy-focused drug screening.

Nacre-like surface nanolaminates enhance fatigue resistance of pure titanium.

Fatigue failure is invariably the most crucial failure mode for metallic structural components. Most microstructural strategies for enhancing fatigue resistance are effective in suppressing either crack initiation or propagation, but often do not work for both synergistically. Here, we demonstrate that this challenge can be overcome by architecting a gradient structure featuring a surface layer of nacre-like nanolaminates followed by multi-variant twinned structure in pure titanium. The polarized accommodation of highly regulated grain boundaries in the nanolaminated layer to cyclic loading enhances the structural stability against lamellar thickening and microstructure softening, thereby delaying surface roughening and thus crack nucleation. The decohesion of the nanolaminated grains along horizonal high-angle grain boundaries gives rise to an extraordinarily high frequency (≈1.7 × 103 times per mm) of fatigue crack deflection, effectively reducing fatigue crack propagation rate (by 2 orders of magnitude lower than the homogeneous coarse-grained counterpart). These intriguing features of the surface nanolaminates, along with the various toughening mechanisms activated in the subsurface twinned structure, result in a fatigue resistance that significantly exceeds those of the homogeneous and gradient structures with equiaxed grains. Our work on architecting the surface nanolaminates in gradient structure provides a scalable and sustainable strategy for designing more fatigue-resistant alloys.

Prediction of clinical prognosis and drug sensitivity in hepatocellular carcinoma through the combination of multiple cell death pathways.

Hepatocellular carcinoma (HCC) is the sixth most common malignant tumor, highlighting a significant need for reliable predictive models to assess clinical prognosis, disease progression, and drug sensitivity. Recent studies have highlighted the critical role of various programmed cell death pathways, including apoptosis, necroptosis, pyroptosis, ferroptosis, cuproptosis, entotic cell death, NETotic cell death, parthanatos, lysosome-dependent cell death, autophagy-dependent cell death, alkaliptosis, oxeiptosis, and disulfidptosis, in tumor development. Therefore, by investigating these pathways, we aimed to develop a predictive model for HCC prognosis and drug sensitivity. We analyzed transcriptome, single-cell transcriptome, genomic, and clinical information using data from the TCGA-LIHC, GSE14520, GSE45436, and GSE166635 datasets. Machine learning algorithms were used to establish a cell death index (CDI) with seven gene signatures, which was validated across three independent datasets, showing that high CDI correlates with poorer prognosis. Unsupervised clustering revealed three molecular subtypes of HCC with distinct biological processes. Furthermore, a nomogram integrating CDI and clinical information demonstrated good predictive performance. CDI was associated with immune checkpoint genes and tumor microenvironment components using single-cell transcriptome analysis. Drug sensitivity analysis indicated that patients with high CDI may be resistant to oxaliplatin and cisplatin but sensitive to axitinib and sorafenib. In summary, our model offers a precise prediction of clinical outcomes and drug sensitivity for patients with HCC, providing valuable insights for personalized treatment strategies.

Three-dimensional adaptive dynamic surface guidance law for missile with terminal angle and field-of-view constraints.

In this paper, an adaptive dynamic surface (DSC) guidance law for missile is designed to intercept the maneuvering target with field-of-view (FOV) and terminal angle constraints in three-dimensional(3D) space, and the missile autopilot dynamics is considered. Firstly, the time-varying transformation function related to line of sight (LOS) is used to replace the FOV constraints, transforming the process-constrained control problem into the output-constrained control problem. Meanwhile, the 3D coupled relative kinematics model considering missile autopilot dynamics and maneuvering target acceleration is established. Secondly, a novel time-varying asymmetric barrier Lyapunov function (TABLF) with dead-zone characteristics is introduced to the adaptive dynamic surface guidance law design process to improve the robustness of parameter debugging. Thirdly, with the help of a nonlinear adaptive filter, the 'explosion of complexity' problem can be avoided effectively, which is caused by analytic computation of virtual signal derivatives. Furthermore, aiming at the problem of autopilot dynamic errors, target acceleration disturbances, and unmeasurable parameters in the model, a novel adaptive law is used to evaluate online. Then, the stability of the closed-loop system is rigorously proven using Lyapunov criteria. Ultimately, Numerical simulations with various constraints and comparison studies have been considered to show the feasibility and effectiveness of the proposed missile guidance law.

TCFormer: Visual Recognition via Token Clustering Transformer.

Transformers are widely used in computer vision areas and have achieved remarkable success. Most state-of-the-art approaches split images into regular grids and represent each grid region with a vision token. However, fixed token distribution disregards the semantic meaning of different image regions, resulting in sub-optimal performance. To address this issue, we propose the Token Clustering Transformer (TCFormer), which generates dynamic vision tokens based on semantic meaning. Our dynamic tokens possess two crucial characteristics: (1) Representing image regions with similar semantic meanings using the same vision token, even if those regions are not adjacent, and (2) concentrating on regions with valuable details and represent them using fine tokens. Through extensive experimentation across various applications, including image classification, human pose estimation, semantic segmentation, and object detection, we demonstrate the effectiveness of our TCFormer. The code and models for this work are available at https://github.com/zengwang430521/TCFormer.

Associations between urinary rare Earth elements with renal function: Findings from a cross-sectional study in Guangxi, China.

BACKGROUND: With increased applications of rare earth elements (REEs) across various industries, evaluating the relationship between REEs exposure and potential health effects has become a public concern. In vivo experiments have established that REEs impact renal function. However, relevant epidemiological evidence on this relationship remains scarce. The objective of this study is to examine the impact of exposure to REEs on renal function. METHODS: In this cross-sectional study, 1052 participants were recruited from Guangxi, China. We measured urinary concentrations of 12 REEs using an inductively coupled plasma-mass spectrometer (ICP-MS). Multiple linear regression models were developed to explore the relationship between a single REEs exposure and the estimated glomerular filtration rate (eGFR), a marker of renal function. Weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) were used to examine the combined effects of REE co-exposure on eGFR. RESULTS: In the multiple linear regression analysis, increasing the concentrations of lanthanum (La, ß: 8.22, 95% CI: 5.67-10.77), cerium (Ce, ß:6.61, 95% CI: 3.80-9.43), praseodymium (Pr, ß: 8.46, 95% CI: 5.85-11.07), neodymium (Nd, ß:8.75, 95% CI: 6.10-11.41), and dysprosium (Dy, ß:7.38, 95% CI: 4.85-9.91) significantly increased the eGFR. In the WQS regression model, the WQS index was significantly associated with eGFR (ß: 4.03, 95% CI: 2.46-5.60), with Pr having the strongest correlation with eGFR. Similar results were obtained in the BKMR model. Additionally, interactions between Pr and La, and Pr and Nd were observed. CONCLUSIONS: Co-exposure to REEs is positively associated with elevated eGFR. Pr is likely to have the most significant influence on increased eGFRs and this might be exacerbated when interacting with La and Nd. Mixed exposure to low doses of REEs had a protective effect on renal function, which can provide some evidence for the exposure threshold of REEs in the environment. TRIAL REGISTRATION: The study has been approved by the Guangxi Medical University Medical Ethics Committee (#20170206-1), and all participants provided written informed consent.

Associations of prenatal exposure to PM2.5 and its components with offsprings' neurodevelopmental and behavioral problems: A prospective cohort study from China.

Prenatal exposure to fine particulate matter (PM2.5) has been linked with increased neurodevelopmental disorders. However, the most detrimental component of PM2.5 and the most vulnerable exposure time windows remain undetermined, especially in areas with high PM2.5 levels. In a prospective cohort study involving 4494 mother-child dyads, we examined the associations of prenatal exposure to PM2.5 and its four main components with children's neurodevelopmental and behavioral problems (NBPs), separately in three pregnancy trimesters. Poisson regression and generalized additive models were used to depict the linear and nonlinear associations, respectively. Weighted quantile sum and Bayesian kernel machine regression models were applied to examine the effects of exposure to both mixed and individual components. Results showed that exposure to PM2.5 and its components throughout the three trimesters increased the risk of children's NBPs (Risk ratio for PM2.5: 1.16, 95 % confidence interval 1.14-1.18 per µg/m3 in the first trimester; 1.15, 1.12-1.17 in the second trimester; 1.06, 1.04-1.08 in the third trimester), with associations gradually diminishing as pregnancy progressed (P values for trends < 0.05). Among the four main components of PM2.5, exposure to SO42- posed the highest risks on children's NBPs, while organic matter contributed the largest proportion to the overall impacts of PM2.5 exposure. These results underscore the significance of mitigating PM2.5 exposure in pregnant women to reduce the risk of neurodevelopmental disorders in offspring. Our findings would inform risk assessment of PM2.5 exposure and facilitate the development of precision preventive strategies targeting specific components of PM2.5 in similar areas with high levels of exposure.

Ag/MXene as Saturable Absorber for Tm:Ho Co-Doped Q-Switched Fiber Laser.

Q-switched fiber lasers have become reliable light sources for generating high-energy pulses, which can be passively modulated by saturable absorbers with excellent nonlinear optical properties. The composite combining Ag and MXene exhibits a broadband nonlinear response and high modulation depth, making it a promising candidate for saturable absorbers in pulsed lasers. Herein, we demonstrate a Q-switched Tm:Ho co-doped fiber laser centered at 2 µm, where the Ag/MXene composite serves as a saturable absorber to generate pulses. The typical spectrum, pulse train, and radio frequency spectrum of Q-switched pulses were observed, in which the 60 dB signal-to-noise ratio was higher than that of 2 µm Q-switched fiber lasers based on other materials, demonstrating the stability of the output pulses. Additionally, the long-term stability of the laser was evaluated over 2 h, where the well-maintained central wavelength and output power also indicated the robustness of the Q-switched laser. Furthermore, the influence of the pump power on the parameters of Q-switched pulses was also investigated, which is conducive to control the output characteristics of lasers. Specifically, the pulse width of the Q-switched pulse decreased, while the repetition rate, output power, and single pulse energy all increased with the increase in pump power. These experimental results demonstrate the ability of Ag/MXene as a saturable absorber and show its potential for generating high-performance pulses in ultrafast lasers.

Generation of pure transverse spin and nontrivial polarization structures of beams by dielectric metasurface.

Transverse spin, a spin component with unique characteristics, provides a new dimension for plenty of applications, such as optical trapping, imaging, and communication. Here, we analyze the pure transverse spin in the Bessel beam, which is solely present in the azimuthal direction. Based on a single layer dielectric metasurface, we efficiently generate Bessel beams with pure transverse spin in a compact optical system. As designed, the transverse spin is flexibly tunable by converting the polarization of the incident light. Furthermore, in the scattered Bessel beam, the local electromagnetic field oscillates around the transverse axis, which is perpendicular to the beam propagation. At certain positions, the local polarization ellipse degenerates into a perfect circle, resulting in a ring-periodic distribution of circularly polarized points (C points) in the beam. This suggests that the local polarization demonstrates a nontrivial periodic structure. This work deepens our understanding of spin-related physics and opens a new avenue for the study and application of transverse spins in ultracompact, flat, multifunctional nanophotonic platforms.

Health Care Professionals' and Parents' Perspectives on the Use of AI for Pain Monitoring in the Neonatal Intensive Care Unit: Multisite Qualitative Study.

BACKGROUND: The use of artificial intelligence (AI) for pain assessment has the potential to address historical challenges in infant pain assessment. There is a dearth of information on the perceived benefits and barriers to the implementation of AI for neonatal pain monitoring in the neonatal intensive care unit (NICU) from the perspective of health care professionals (HCPs) and parents. This qualitative analysis provides novel data obtained from 2 large tertiary care hospitals in Canada and the United Kingdom. OBJECTIVE: The aim of the study is to explore the perspectives of HCPs and parents regarding the use of AI for pain assessment in the NICU. METHODS: In total, 20 HCPs and 20 parents of preterm infants were recruited and consented to participate from February 2020 to October 2022 in interviews asking about AI use for pain assessment in the NICU, potential benefits of the technology, and potential barriers to use. RESULTS: The 40 participants included 20 HCPs (17 women and 3 men) with an average of 19.4 (SD 10.69) years of experience in the NICU and 20 parents (mean age 34.4, SD 5.42 years) of preterm infants who were on average 43 (SD 30.34) days old. Six themes from the perspective of HCPs were identified: regular use of technology in the NICU, concerns with regard to AI integration, the potential to improve patient care, requirements for implementation, AI as a tool for pain assessment, and ethical considerations. Seven parent themes included the potential for improved care, increased parental distress, support for parents regarding AI, the impact on parent engagement, the importance of human care, requirements for integration, and the desire for choice in its use. A consistent theme was the importance of AI as a tool to inform clinical decision-making and not replace it. CONCLUSIONS: HCPs and parents expressed generally positive sentiments about the potential use of AI for pain assessment in the NICU, with HCPs highlighting important ethical considerations. This study identifies critical methodological and ethical perspectives from key stakeholders that should be noted by any team considering the creation and implementation of AI for pain monitoring in the NICU.

Oxford Nanopore Technologies (ONT) Full-length Transcriptomics Shows Electroacupuncture ameliorates Lipid Metabolic Disorder through Suppressing Hepatic Pdia3/Perk/Qrich1 Expression in Rats.

BACKGROUND: The incidence of dyslipidemia increases after menopause. Electroacupuncture (EA) has been recommended for menopause-related disease. However, the positive effect on lipid metabolism disorders is still unclear. OBJECTIVES: To investigate the underlying mechanism of EA treatment on lipid metabolism disorders through ONT full-length transcriptome sequencing Methods: Adult female SD rats were randomly divided into Ctrl, sham operation+high-fat feed(Sham+HFD), Ovariectomized+high-fat feed (OVX+HFD), Ovariectomized+high-fat feed + Atorvastatin (OVX+HFD+ATO) and OVX+HFD+EA groups. Periovarian adipose tissue around the bilateral ovaries of rats in the Sham+HFD group was resected. Rats in the OVX+HFD, OVX+HFD+ATO and OVX+HFD+EA groups were subjected to bilateral oophorectomy to prepare the ovariectomized rat model. Treatment was applied to rats in the OVX+HFD+EA group. ST36, PC6, SP6, BL18 and ST40 were the selected acupoints. Daily food intake and body weights of rats were recorded. The samples were collected 30 days after treatment. The serum levels of total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein (HDL-C) were detected to assess the improvement of lipid metabolism disorders. HE and oil red O staining were used to stain the liver tissues. Total RNA was extracted from liver tissues, and its transcriptional changes were determined by high-throughput sequencing. Additionally, RTÁqPCR and immunofluorescence staining were used to verify the crucial signal pathway screened by the ONT fullÁlength transcriptome sequencing. RESULTS: EA treatment resulted in a lowered weight of perirenal fat and liver and a significant improvement in the color of the liver. In addition, EA could improve the lipid profile and hepatic steatosis in OVX+HFD rats. According to fullÁlength transcriptome sequencing, 2292 genes showed differential expression in the OVX+HFD group; of these, 1121 were upregulated and 1171 down-regulated. 609 DEGs were found in the OVX+HFD+EA group compared to the OVX+HFD group; 235 up-regulated and 374 down-regulated. We also found that 77 genes are significantly upregulated after EA intervention through Venn map analysis (including Agtr1a, Pdia3, etc.), which may be the targeted genes for EA treatment of lipid metabolism disorders. Finally, we verified the expression of Pdia3, Perk and Qrich1 levels in liver tissues. HFD feeding could increase the expression of Pdia3 and its downstream signal pathways molecular Perk and Qrich1. But these effects were reversed by EA treatment, the results demonstrated that the expression of pdia3, Perk, as well as Qrich1 of OVX+HFD rats had a decreasing trend after EA treatment. CONCLUSIONS: EA could ameliorate lipid metabolic disorder in OVX+HFD rats. The Pdia3/Perk/Qrich1 signal pathway may play crucial roles in the improvement of lipid metabolism disorder of OVX+HFD rats after EA treatment.

Accuracy of 12 Intraocular Lens Power Formulas After Corneal Myopic Refractive Surgery.

PURPOSE: To assess the predictive accuracy of new-generation online intraocular lens (IOL) power formulas in eyes with previous myopic laser refractive surgery (LRS) and to evaluate the influence of corneal asphericity on the predictive accuracy. METHODS: The authors retrospectively evaluated 52 patients (78 eyes) with a history of laser in situ keratomileusis (LASIK) or photorefractive keratectomy (PRK) who subsequently underwent cataract surgery. Refractive prediction errors were calculated for 12 no-history new online formulas: 8 formulas with post-LRS versions (Barrett True-K, EVO 2.0, Hoffer QST, and Pearl DGS) using keratometry and posterior/total keratometry measured by IOLMaster 700 and 4 formulas without post-LRS versions (Cooke K6 and Kane) using keratometry and total keratometry. The refractive prediction error, mean absolute error (MAE), and percentages of eyes with prediction errors of ±0.25, ±0.50, ±0.75, ±1.00, and ±1.50 diopters (D) were compared. RESULTS: The MAEs of the 12 formulas were significantly different (F = 83.66, P < .001). The MAEs ranged from 0.62 to 0.94 D and from 1.07 to 1.84 D in the formulas with and without post-LRS versions, respectively. The EVO formula produced the lowest MAE (0.60) and MedAE (0.47), followed by the Barrett True-K (0.69 and 0.50, respectively). Each percentage of eyes with refractive prediction error was also significantly different among the 12 formulas (P < .001). CONCLUSIONS: The EVO and Barrett True-K formulas demonstrate comparable performance to the other existing formulas in eyes with a history of myopic LASIK/PRK. Surgeons should use these formulas with post-LRS versions and input keratometric values whenever possible. [J Refract Surg. 2024;40(6):e354-e361.].

Developmental and nuclear proteomic signatures characterize the temporal regulation of fibroin synthesis during the last molting-feeding transition of silkworm.

Silkworm fibroins are natural proteinaceous macromolecules and provide core mechanical properties to silk fibers. The synthesis process of fibroins is posterior silk gland (PSG)-exclusive and appears active at the feeding stage and inactive at the molting stage. However, the molecular mechanisms controlling it remain elusive. Here, the silk gland's physiological and nuclear proteomic features were used to characterize changes in its structure and development from molting to feeding stages. The temporal expression profile and immunofluorescence analyses revealed a synchronous transcriptional on-off mode of fibroin genes. Next, the comparative nuclear proteome of the PSG during the last molting-feeding transition identified 798 differentially abundant proteins (DAPs), including 42 transcription factors and 15 epigenetic factors. Protein-protein interaction network analysis showed a "CTCF-FOX-HOX-SOX" association with activated expressions at the molting stage, suggesting a relatively complex and multifactorial regulation of the PSG at the molting stage. In addition, FAIRE-seq verification indicated "closed" and "open" conformations of fibroin gene promoters at the molting and feeding stages, respectively. Such proteome combined with chromatin accessibility analysis revealed the detailed signature of protein factors involved in the temporal regulation of fibroin synthesis and provided insights into silk gland development as well as silk production in silkworms.

Effect of Overheating on the Tensile Properties of Nickel-Based Superalloy GH4720Li.

Aero-engines can be exposed to One Engine Inoperative (OEI) conditions during service, and the resulting overheating effect may significantly impact their structural integrity and flight safety. This paper focuses on the influence of overheating on the microstructural evolution and tensile properties of the GH4720Li alloy, a nickel-based polycrystalline superalloy commonly used in turbine disks. Based on the typical OEI operating conditions of a real aero-engine, a series of non-isothermal high-temperature tensile tests involving an OEI stage of 800 °C were conducted. The effects of OEI-induced overheating on the microstructure and tensile properties of the GH4720Li alloy were investigated. The results showed that, after OEI treatment, the primary γ' phase in this alloy was partially dissolved. The GH4720Li superalloy also exhibited numerous microcracks at the grain boundaries, resulting in complex effects on its tensile properties. The alloy's yield strength and ultimate tensile strength were slightly decreased, whereas its ductility decreased considerably. The OEI-induced embrittlement phenomenon was mainly caused by the non-uniform distribution of the tertiary γ' phase within grains. The formation of microcracks nucleated at the interfaces between the primary γ' precipitates and γ matrix phase was another key factor.

Weak Augmentation Guided Relational Self-Supervised Learning.

Self-supervised Learning (SSL) including the mainstream contrastive learning has achieved great success in learning visual representations without data annotations. However, most methods mainly focus on the instance level information (ie, the different augmented images of the same instance should have the same feature or cluster into the same class), but there is a lack of attention on the relationships between different instances. In this paper, we introduce a novel SSL paradigm, which we term as relational self-supervised learning (ReSSL) framework that learns representations by modeling the relationship between different instances. Specifically, our proposed method employs sharpened distribution of pairwise similarities among different instances as relation metric, which is thus utilized to match the feature embeddings of different augmentations. To boost the performance, we argue that weak augmentations matter to represent a more reliable relation, and leverage momentum strategy for practical efficiency. The designed asymmetric predictor head and an InfoNCE warm-up strategy enhance the robustness to hyper-parameters and benefit the resulting performance. Experimental results show that our proposed ReSSL substantially outperforms the state-of-the-art methods across different network architectures, including various lightweight networks (eg, EfficientNet and MobileNet).

The role and future prospects of artificial intelligence algorithms in peptide drug development.

Peptide medications have been more well-known in recent years due to their many benefits, including low side effects, high biological activity, specificity, effectiveness, and so on. Over 100 peptide medications have been introduced to the market to treat a variety of illnesses. Most of these peptide medications are developed on the basis of endogenous peptides or natural peptides, which frequently required expensive, time-consuming, and extensive tests to confirm. As artificial intelligence advances quickly, it is now possible to build machine learning or deep learning models that screen a large number of candidate sequences for therapeutic peptides. Therapeutic peptides, such as those with antibacterial or anticancer properties, have been developed by the application of artificial intelligence algorithms.The process of finding and developing peptide drugs is outlined in this review, along with a few related cases that were helped by AI and conventional methods. These resources will open up new avenues for peptide drug development and discovery, helping to meet the pressing needs of clinical patients for disease treatment. Although peptide drugs are a new class of biopharmaceuticals that distinguish them from chemical and small molecule drugs, their clinical purpose and value cannot be ignored. However, the traditional peptide drug research and development has a long development cycle and high investment, and the creation of peptide medications will be substantially hastened by the AI-assisted (AI+) mode, offering a new boost for combating diseases.

A two-step quadrature-based variational calculation of ro-vibrational levels and wavefunctions of CO2 using a bisector-x molecule-fixed frame.

In this paper, we propose a new two-step strategy for computing ro-vibrational energy levels and wavefunctions of a triatomic molecule and apply it to CO2. A two-step method [J. Tennyson and B. T. Sutcliffe, Mol. Phys., 1986, 58, 1067] uses a basis whose functions are products of K-dependent "vibrational" functions and symmetric top functions. K is the quantum number for the molecule-fixed z component of the angular momentum. For a linear molecule, a two-step method is efficient because the Hamiltonian used to compute the basis functions includes the largest coupling term. The most important distinguishing feature of the two-step method we propose is that it uses an associated Legendre basis and quadrature rather than a K-dependent discrete variable representation. This reduces the cost of the calculation and simplifies the method. We have computed ro-vibrational energy levels with J up to 100 for CO2, on an accurate available potential energy surface which is known as the AMES-2 PES and present a subset of those levels. We have converged most levels up to 20 000 cm-1 to 0.0001 cm-1.