Comparative analysis of short-term efficacy between robot-assisted retrograde drilling and arthroscopic microfracture for osteochondral lesions of the talus.

Objective: To investigate the short-term clinical efficacy of robot-assisted retrograde drilling and arthroscopic microfracture for osteochondral lesions of the talus (OCLT). Methods: This study was divided into two groups: experimental group: robot-assisted retrograde drilling group; control group: arthroscopic microfracture group. A total of 6 OCLT patients who were treated with robot navigation-assisted retrograde drilling and 10 OCLT patients who were treated with arthroscopic microfracture between October 2020 and October 2021 were retrospectively analyzed. There were 11 males and five females, with a mean age of 36 years. The patients were followed up for 6-12 months to compare the changes in the OCLT lesion area by magnetic resonance imaging (MRI), visual analogue scale/score (VAS) and American Orthopedic Foot and Ankle Society score (AOFAS) before and after surgery. Results: All 16 patients were followed up for an average of 8 months, and no complications such as joint infection, nerve injury, or active bleeding occurred during the follow-up period. Only one patient suffered discomfort involving transient postoperative pain in the operative area, but did not experience long-term numbness or chronic pain. Postoperative MRI revealed that none of the patients had severe signs of osteonecrosis, osteolysis or cystic changes of the talus, with lesion areas smaller than those before surgery. The difference was statistically significant (P < 0.01). The patients in the experimental group showed a more significant improvement in the last 3 months than in the first 3 months of the follow-up period. At the last follow-up, the VAS score was 3 points in the experimental group and 2.2 points in the control group, and the AOFAS score was 88.6 points in the experimental group and 88 points in the control group, all of which were significantly higher than those before operation, and the differences were statistically significant, but there was no statistically significant difference between the groups. Conclusion: Both robot navigation-assisted retrograde drilling and arthroscopic microfracture for bone marrow stimulation (BMS) to treat OCLT in all patients obtained satisfactory effects in the short term. In addition, the follow-up revealed that with excellent efficacy and few complications, robot navigation-assisted retrograde drilling was safe and minimally invasive, and greatly reduced operative time. Consequently, robot navigation-assisted retrograde drilling for BMS was a safe and effective procedure for the treatment of OCLT.

Highly-Polarized Solar-Blind Ultraviolet Organic Photodetectors.

Developing high-performance polarization-sensitive ultraviolet photodetectors is crucial for their application in military remote sensing, detection, bio-inspired navigation, and machine vision. However, the significant absorption in the visible light range severely limits the application of polarization-sensitive ultraviolet photodetectors, such as high-quality anti-interference imaging. Here, based on a wide-bandgap organic semiconductor single crystal (trans-1,2-bis(5-phenyldithieno[2,3-b:3',2'-d]thiophen-2-yl)ethene, BPTTE), high-performance polarization-sensitive solar-blind ultraviolet photodetectors with a dichroic ratio close to 4.26 are demonstrated. The strong anisotropy of 2D grown BPTTE single crystals in molecular vibration and optical absorption is characterized by various techniques. Under voltage modulation, stable and efficient detection of polarized light is demonstrated, attributed to the intrinsic anisotropy of transition dipole moment in the bc crystal plane, rather than other factors. Finally, high-contrast polarimetric imaging and anti-interference imaging are successfully demonstrated based on BPTTE single crystal photodetectors, highlighting the potential of organic semiconductors for polarization-sensitive solar-blind ultraviolet photodetectors.

Characterization of metallothionein genes from Broussonetia papyrifera: metal binding and heavy metal tolerance mechanisms.

BACKGROUND: Broussonetia papyrifera is an economically significant tree with high utilization value, yet its cultivation is often constrained by soil contamination with heavy metals (HMs). Effective scientific cultivation management, which enhances the yield and quality of B. papyrifera, necessitates an understanding of its regulatory mechanisms in response to HM stress. RESULTS: Twelve Metallothionein (MT) genes were identified in B. papyrifera. Their open reading frames ranged from 186 to 372 bp, encoding proteins of 61 to 123 amino acids with molecular weights between 15,473.77 and 29,546.96 Da, and theoretical isoelectric points from 5.24 to 5.32. Phylogenetic analysis classified these BpMTs into three subclasses: MT1, MT2, and MT3, with MT2 containing seven members and MT3 only one. The expression of most BpMT genes was inducible by Cd, Mn, Cu, Zn, and abscisic acid (ABA) treatments, particularly BpMT2e, BpMT2d, BpMT2c, and BpMT1c, which showed significant responses and warrant further study. Yeast cells expressing these BpMT genes exhibited enhanced tolerance to Cd, Mn, Cu, and Zn stresses compared to control cells. Yeasts harboring BpMT1c, BpMT2e, and BpMT2d demonstrated higher accumulation of Cd, Cu, Mn, and Zn, suggesting a chelation and binding capacity of BpMTs towards HMs. Site-directed mutagenesis of cysteine (Cys) residues indicated that mutations in the C domain of type 1 BpMT led to increased sensitivity to HMs and reduced HM accumulation in yeast cells; While in type 2 BpMTs, the contribution of N and C domain to HMs' chelation possibly corelated to the quantity of Cys residues. CONCLUSION: The BpMT genes are crucial in responding to diverse HM stresses and are involved in ABA signaling. The Cys-rich domains of BpMTs are pivotal for HM tolerance and chelation. This study offers new insights into the structure-function relationships and metal-binding capabilities of type-1 and - 2 plant MTs, enhancing our understanding of their roles in plant adaptation to HM stresses.

FeSA­Ir/Metallene Nanozymes Induce Sequential Ferroptosis­Pyroptosis for Multi­Immunogenic Responses Against Lung Metastasis.

For cancer metastasis inhibition, the combining of nanozymes with immune checkpoint blockade (ICB) therapy remains the major challenge in controllable reactive oxygen species (ROS) generation for creating effective immunogenicity. Herein, new nanozymes with light-controlled ROS production in terms of quantity and variety are developed by conjugating supramolecular-wrapped Fe single atom on iridium metallene with lattice-strained nanoislands (FeSA-Ir@PF NSs). The Fenton-like catalysis of FeSA-Ir@PF NSs effectively produced •OH radicals in dark, which induced ferroptosis and apoptosis of cancer cells. While under second near-infrared (NIR-II) light irradiation, FeSA-Ir@PF NSs showed ultrahigh photothermal conversion efficiency (𝜂, 75.29%), cooperative robust •OH generation, photocatalytic O2 and 1O2 generation, and caused significant pyroptosis of cancer cells. The controllable ROS generation, sequential cancer cells ferroptosis and pyroptosis, led 99.1% primary tumor inhibition and multi-immunogenic responses in vivo. Most importantly, the inhibition of cancer lung metastasis is completely achieved by FeSA-Ir@PF NSs with immune checkpoint inhibitors, as demonstrated in different mice lung metastasis models, including circulating tumor cells (CTCs) model. This work provided new inspiration for developing nanozymes for cancer treatments and metastasis inhibition.

The prediction of Recombination Hotspot Based on Automated Machine Learning.

Meiotic recombination plays a pivotal role in genetic evolution. Genetic variation induced by recombination is a crucial factor in generating biodiversity and a driving force for evolution. At present, the development of recombination hotspot prediction methods has encountered challenges related to insufficient feature extraction and limited generalization capabilities. This paper focused on the research of recombination hotspot prediction methods. We explored deep learning-based recombination hotspot prediction and scrutinized the shortcomings of prevalent models in addressing the challenge of recombination hotspot prediction. To addressing these deficiencies, an automated machine learning approach was utilized to construct recombination hotspot prediction model. The model combined sequence information with physicochemical properties by employing TF-IDF-Kmer and DNA composition components to acquire more effective feature data. Experimental results validate the effectiveness of the feature extraction method and automated machine learning technology used in this study. The final model was validated on three distinct datasets and yielded accuracy rates of 97.14%, 79.71%, and 98.73%, surpassing the current leading models by 2%, 2.56%, and 4%, respectively. In addition, we incorporated tools such as SHAP and AutoGluon to analyze the interpretability of black-box models, delved into the impact of individual features on the results, and investigated the reasons behind misclassification of samples. Finally, a website of recombination hotspot prediction was established to facilitate easy access to necessary information and tools for researchers. The research outcomes of this paper underscore the enormous potential of automated machine learning methods in gene sequence prediction.

Fitness cost of tet(A) type I variant-mediated tigecycline resistance in Klebsiella pneumoniae.

OBJECTIVE: The aim of the present study is to explore the impact of the tet(A) type I variant (tetA-v1) on its fitness effect in Klebsiella pneumoniae. METHODS: Clinical K. pneumoniae strains were utilized as parental strains to generate strains carrying only the plasmid vector (pBBR1MCS-5) or the tetA-v1 recombinant plasmid (ptetA-v1). Antimicrobial susceptibility testing was conducted to estimate the contribution of tetA-v1 to drug resistance. Plasmid stability was evaluated by serial passage over 10 consecutive days in the absence of tigecycline. Biological fitness was examined through growth curve analysis, in vitro competition assays and a neutropenic mouse thigh infection model. RESULTS: A 2-4-fold increase in tigecycline MIC was observed following the acquisition of tetA-v1. Without tigecycline treatment, the stability of ptetA-v1 plasmids has been decreasing since day 1. The ptetA-v1 plasmid in Kp89, Kp91, and Kp93 exhibited a decrease of about 20% compared to the pBBR1MCS-5 plasmid. The acquisition of the tetA-v1 gene could inhibit the growth ability of K. pneumoniae strains both in vitro and in vivo. tetA-v1 gene imposed a fitness cost in K. pneumoniae, particularly in the CRKP strain Kp51, with a W value of approximately 0.56. CONCLUSION: The presence of tetA-v1 is associated with a significant fitness cost in K. pneumoniae in the absence of tigecycline, both in vitro and in vivo.

CT-Based AI model for predicting therapeutic outcomes in ureteral stones after single extracorporeal shock wave lithotripsy through a cohort study.

OBJECTIVES: Exploring the efficacy of an artificial intelligence (AI) model derived from the analysis of CT images to precisely forecast the therapeutic outcomes of singular-session extracorporeal shock wave lithotripsy (ESWL) in the management of ureteral stones. METHODS: A total of 317 patients diagnosed clinically with ureteral stones were included in this investigation. Unenhanced CT was administered to the participants within the initial fortnight preceding the inaugural ESWL. The internal cohort consisted of 250 individuals from a local healthcare facility, whereas the external cohort comprised 67 participants from another local medical institution. The proposed framework comprises three main components: an automated semantic segmentation model developed using 3D U-Net, a feature extractor that integrates radiomics and autoencoder techniques, and an ESWL efficacy prediction model trained with various machine learning algorithms. All participants underwent thorough postoperative follow-up examinations four weeks hence. The efficacy of ESWL was defined by the absence of stones or residual fragments measuring ≤2 mm in KUB X-ray assessments. Model stability and generalizability were judiciously validated through a fivefold cross-validation approach and a multi-center external test strategy. Moreover, Shapley Additive Explanations (SHAP) values for individual features were computed to elucidate the nuanced contributions of each feature to the model's decision-making process. RESULTS: The semantic segmentation model we constructed exhibited an average Dice coefficient of 0.88 ± 0.08 on the external testing set. ESWL classifiers built using Support Vector Machine (SVM), Random Forest (RF), XGBoost (XB), and CatBoost (CB) achieved AUROC values of 0.78, 0.84, 0.85, and 0.90, respectively, on the internal validation set. For the external testing set, SVM, RF, XB, and CB predicted ESWL with AUROC values of 0.68, 0.79, 0.80, and 0.83, respectively, with the last one being the optimal algorithm. The radiomics features and auto-encoder features made significant contributions to the decision-making process of the classification model. CONCLUSIONS: This investigation unmistakably underscores the remarkable predictive prowess exhibited by a scrupulously crafted AI model using CT images to precisely anticipate the therapeutic results of a singular session of extracorporeal shock wave lithotripsy for ureteral stones.

Iterative Design of Near-Infrared Fluorescent Probes for Early Diagnosis of Alzheimer's Disease by Targeting Aß Oligomers.

Amyloid-ß oligomers (AßOs), crucial toxic proteins in early Alzheimer's disease (AD), precede the formation of Aß plaques and cognitive impairment. In this context, we present our iterative process for developing novel near-infrared fluorescent (NIRF) probes specifically targeting AßOs, aimed at early AD diagnosis. An initial screening identified compound 18 as being highly selective for AßOs. Subsequent analysis revealed that compound 20 improved serum stability while retaining affinity for AßOs. The most promising iteration, compound 37, demonstrated exceptional qualities: a high affinity for AßOs, emission in the near-infrared region, and good biocompatibility. Significantly, ex vivo double staining indicated that compound 37 detected AßOs in AD mouse brain and in vivo imaging experiments showed that compound 37 could differentiate between 4-month-old AD mice and age-matched wild-type mice. Therefore, compound 37 has emerged as a valuable NIRF probe for early detection of AD and a useful tool in exploring AD's pathological mechanisms.

A fresh-cut papaya freshness prediction model based on partial least squares regression and support vector machine regression.

This study investigated the physicochemical and flavor quality changes in fresh-cut papaya that was stored at 4 °C. Multivariate statistical analysis was used to evaluate the freshness of fresh-cut papaya. Aerobic plate counts were selected as a predictor of freshness of fresh-cut papaya, and a prediction model for freshness was established using partial least squares regression (PLSR), and support vector machine regression (SVMR) algorithms. Freshness of fresh-cut papaya could be well distinguished based on physicochemical and flavor quality analyses. The aerobic plate counts, as a predictor of freshness of fresh-cut papaya, significantly correlated with storage time. The SVMR model had a higher prediction accuracy than the PLSR model. Combining flavor quality with multivariate statistical analysis can be effectively used for evaluating the freshness of fresh-cut papaya.

Targeting Non-Alcoholic Fatty Liver Disease with Hawthorn Ethanol Extract (HEE): A Comprehensive Examination of Hepatic Lipid Reduction and Gut Microbiota Modulation.

Recent studies have highlighted the lipid-lowering ability of hawthorn ethanol extract (HEE) and the role played by gut flora in the efficacy of HEE. Our study sought to explore the effects of HEE on non-alcoholic fatty liver disease (NAFLD) in normal flora and pseudo germ-free mice. The results showed that HEE effectively diminished hepatic lipid accumulation, ameliorated liver function, reduced inflammatory cytokine levels and blood lipid profiles, and regulated blood glucose levels. HEE facilitated triglyceride breakdown, suppressed fatty acid synthesis, and enhanced intestinal health by modulating the diversity of the gut microbiota and the production of short-chain fatty acids in the gut. In addition, HEE apparently helps to increase the presence of beneficial genera of bacteria, thereby influencing the composition of the gut microbiota, and the absence of gut flora affects the efficacy of HEE. These findings reveal the potential of hawthorn for the prevention and treatment of NAFLD and provide new perspectives on the study of functional plants to improve liver health.

Improved random forest classification model combined with C5.0 algorithm for vegetation feature analysis in non-agricultural environments.

In response to the challenges posed by the high computational complexity and suboptimal classification performance of traditional random forest algorithms when dealing with high-dimensional and noisy non-agricultural vegetation satellite data, this paper proposes an enhanced random forest algorithm based on the C5.0 algorithm. The paper focuses on the Liaohe Plain, selecting two distinct non-agricultural landscape patterns in Shenbei New District and Changtu County as research objects. High-resolution satellite data from GF-2 serves as the experimental dataset. This paper introduces an ensemble feature method based on the bagging concept to improve the original random forest classification model. This method enhances the likelihood of selecting features beneficial to classifying positive class samples, avoiding excessive removal of useful features from negative samples. This approach ensures feature importance and model diversity. The C5.0 algorithm is then employed for feature selection, and the enhanced vegetation index (EVI) is utilized for vegetation coverage estimation. Results indicate that employing a multi-scale parameter selection tool, combined with limited field-measured data, facilitates the identification and classification of plant species in forest landscapes. The C5.0 algorithm effectively selects classification features, minimizing information redundancy. The established object-oriented random forest classification model achieves an impressive accuracy of 94.02% on the aerial imagery for forest classification dataset, with EVI-based vegetation coverage estimation demonstrating high accuracy. In experiments on the same test set, the proposed algorithm attains an average accuracy of 90.20%, outperforming common model algorithms such as bidirectional encoder representation from transformer, FastText, and convolutional neural network, which achieve average accuracies ranging from 84.41 to 88.33% in identifying non-agricultural artificial habitat vegetation features. The proposed algorithm exhibits a competitive edge compared to other algorithms. These research findings contribute scientific evidence for protecting agricultural ecosystems and restoring agricultural ecosystem biodiversity.

Glucagon-like peptide-1 receptor agonists: new strategies and therapeutic targets to treat atherosclerotic cardiovascular disease.

Atherosclerotic cardiovascular disease (ASCVD) is a leading cause of cardiovascular mortality and is increasingly prevalent in our population. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) can safely and effectively lower glucose levels while concurrently managing the full spectrum of ASCVD risk factors and improving patients' long-term prognosis. Several cardiovascular outcome trials (CVOTs) have been carried out to further investigate the cardiovascular benefits of GLP-1RAs. Analyzing data from CVOTs can provide insights into the pathophysiologic mechanisms by which GLP-1RAs are linked to ASCVD and define the use of GLP-1RAs in clinical practice. Here, we discussed various mechanisms hypothesized in previous animal and preclinical human studies, including blockade of the production of adhesion molecules and inflammatory factors, induction of endothelial cells' synthesis of nitric oxide, protection of mitochondrial function and restriction of oxidative stress, suppression of NOD-like receptor thermal protein domain associated protein three inflammasome, reduction of foam cell formation and macrophage inflammation, and amelioration of vascular smooth muscle cell dysfunction, to help explain the cardiovascular benefits of GLP-1RAs in CVOTs. This paper provides an overview of the clinical research, molecular processes, and possible therapeutic applications of GLP-1RAs in ASCVD, while also addressing current limitations in the literature and suggesting future research directions.

Genome Analysis of Plasmodium falciparum: A Preliminary Observation - Sierra Leone, 2022-2023.

What is already known about this topic?: Sierra Leone, with a gross domestic product (GDP) per capita below $300 and significant poverty, ranks among the world's least developed countries (LDCs). Despite its modest population of 8.6 million, the nation reports approximately 2.6 million malaria cases annually. Previously, there has been no reporting on the malaria genome data from this country. What is added by this report?: In this study, we present the first reported whole-genome sequence analysis of 19 high parasite-density Plasmodium falciparum isolates from Sierra Leone, providing insights into the genomic epidemiology of this high-prevalence area. We found a high degree of relatedness among infections and substantial genetic diversity, consistent with the gradual reduction in overall case numbers. Moreover, our whole-genome analysis revealed that, beyond drug-resistance genes, gene families related to blood cell invasion, immune evasion, and others are undergoing directional selection. This suggests that the population in Sierra Leone has developed a relatively strong acquired immunity. What are the implications for public health practice?: The genomic data not only facilitate the creation of single nucleotide polymorphism barcodes for case tracking but also enable the analysis of evolving transmission dynamics and selection pressures. Additionally, the samples from Sierra Leone exhibited higher selective pressures on resistance genes compared to those from Asia, a trend not commonly observed in other African samples. This suggests that less stringent healthcare systems and inconsistent treatment strategies can subject parasites to increased drug pressure, thereby accelerating the development of resistant strains.

SIRT5 exacerbates eosinophilic chronic rhinosinusitis through promoting polarization of M2 macrophage.

BACKGROUND: Previous study implied that local M2 polarization of macrophage promoted mucosal edema and exacerbates Th2 type inflammation in chronic rhinosinusitis with nasal polyps (CRSwNP). However, the specific pathogenic role of M2 macrophages and the intrinsic regulators in the development of CRS remains elusive. OBJECTIVE: We thought to investigate the regulatory role of SIRT5 in the polarization of M2 macrophages and its potential contribution to the development of CRSwNP. METHODS: RT-qPCR and Western blot analyses were performed to examine the expression levels of SIRT5 and markers of M2 macrophages in sinonasal mucosa samples obtained from both CRS and control groups. Wild-type and Sirt5 knockout mice were used to establish nasal polyp model with Th2 inflammation and investigate the effects of SIRT5 in macrophages on disease development. Furthermore, in vitro experiments were conducted to elucidate the regulatory role of SIRT5 in polarization of M2 macrophages. RESULTS: Clinical investigations showed that SIRT5 was highly expressed and positively correlated with M2 macrophages markers in eosinophilic polyps. The expression of SIRT5 in M2 macrophages was found to contribute to the development of the disease, which was impaired in Sirt5 deficiency mice. Mechanistically, SIRT5 was shown to enhance the alternative polarization of macrophages through promoting glutaminolysis. CONCLUSIONS: SIRT5 plays a crucial role in promoting the development of CRSwNP by supporting the alternative polarization of macrophage and thus provides a potential target for CRSwNP interventions.

IRE1α determines ferroptosis sensitivity through regulation of glutathione synthesis.

Cellular sensitivity to ferroptosis is primarily regulated by mechanisms mediating lipid hydroperoxide detoxification. We show that inositol-requiring enzyme 1 (IRE1α), an endoplasmic reticulum (ER) resident protein critical for the unfolded protein response (UPR), also determines cellular sensitivity to ferroptosis. Cancer and normal cells depleted of IRE1α gain resistance to ferroptosis, while enhanced IRE1α expression promotes sensitivity to ferroptosis. Mechanistically, IRE1α's endoribonuclease activity cleaves and down-regulates the mRNA of key glutathione biosynthesis regulators glutamate-cysteine ligase catalytic subunit (GCLC) and solute carrier family 7 member 11 (SLC7A11). This activity of IRE1α is independent of its role in regulating the UPR and is evolutionarily conserved. Genetic deficiency and pharmacological inhibition of IRE1α have similar effects in inhibiting ferroptosis and reducing renal ischemia-reperfusion injury in mice. Our findings reveal a previously unidentified role of IRE1α to regulate ferroptosis and suggests inhibition of IRE1α as a promising therapeutic strategy to mitigate ferroptosis-associated pathological conditions.

Crystalline nanosheets of three-dimensional supramolecular frameworks with uniform thickness and high stability.

Fabricating three dimensional (3D) supramolecular frameworks (SMFs) into stable crystalline nanosheets remains a great challenge due to the homogeneous and weak inter-building block interactions along 3D directions. Herein, crystalline nanosheets of a 3D SMF with a uniform thickness of 4.8 ± 0.1 nm immobilized with Pt nanocrystals on the surface (Q[8]/Pt NSs) were fabricated via the solid-liquid reaction between cucurbit[8]uril/H2PtCl6 single crystals and hydrazine hydrate with the help of gas and heat yielded during the reaction process. A series of experiments and theoretical calculations reveal the ultrahigh stability of Q[8]/Pt NSs due to the high density hydrogen bonding interaction among neighboring Q[8] molecules. This in turn endows Q[8]/Pt NSs with excellent photocatalytic and continuous thermocatalytic CO oxidation performance, representing the thus-far reported best Pt nano-material-based catalysts.

Real-time diagnosis of intracerebral hemorrhage by generating dual-energy CT from single-energy CT.

Real-time diagnosis of intracerebral hemorrhage after thrombectomy is crucial for follow-up treatment. However, this is difficult to achieve with standard single-energy CT (SECT) due to similar CT values of blood and contrast agents under a single energy spectrum. In contrast, dual-energy CT (DECT) scanners employ two different energy spectra, which allows for real-time differentiation between hemorrhage and contrast extravasation based on energy-related attenuation characteristics. Unfortunately, DECT scanners are not as widely used as SECT scanners due to their high costs. To address this dilemma, in this paper, we generate pseudo DECT images from a SECT image for real-time diagnosis of hemorrhage. More specifically, we propose a SECT-to-DECT Transformer-based Generative Adversarial Network (SDTGAN), which is a 3D transformer-based multi-task learning framework equipped with a shared attention mechanism. In this way, SDTGAN can be guided to focus more on high-density areas (crucial for hemorrhage diagnosis) during the generation. Meanwhile, the introduced multi-task learning strategy and the shared attention mechanism also enable SDTGAN to model dependencies between interconnected generation tasks, improving generation performance while significantly reducing model parameters and computational complexity. In the experiments, we approximate real SECT images using mixed 120kV images from DECT data to address the issue of not being able to obtain the true paired DECT and SECT data. Extensive experiments demonstrate that SDTGAN can generate DECT images better than state-of-the-art methods. The code of our implementation is available at https://github.com/jiang-cw/SDTGAN.

Genetic Diversity and Natural Selection of Plasmodium vivax Merozoite Surface Protein 8 in Global Populations.

Plasmodium vivax Merozoite Surface Protein 8 (PvMSP8) is a promising candidate target for the development of multi-component vaccines. Therefore, determining the genetic variation pattern of Pvmsp8 is essential in providing a reference for the rational design of the P. vivax malaria vaccines. This study delves into the genetic characteristics of the Pvmsp8 gene, specifically focusing on samples from the China-Myanmar border (CMB) region, and contrasts these findings with broader global patterns. The study uncovers that Pvmsp8 exhibits a notable level of conservation across different populations, with limited polymorphisms and relatively low nucleotide diversity (0.00023-0.00120). This conservation contrasts starkly with the high polymorphisms found in other P. vivax antigens such as Pvmsp1. A total of 25 haplotypes and 14 amino acid mutation sites were identified in the global populations, and all mutation sites were confined to non-functional regions. The study also notes that most CMB Pvmsp8 haplotypes are shared among Burmese, Cambodian, Thai, and Vietnamese populations, indicating less geographical variance, but differ notably from those found in Pacific island regions or the Panama. The findings underscore the importance of considering regional genetic diversity in P. vivax when developing targeted malaria vaccines. Non departure from neutral evolution were found by Tajima's D test, however, statistically significant differences were observed between the kn/ks rates. The study's findings are crucial in understanding the evolution and population structure of the Pvmsp8 gene, particularly during regional malaria elimination efforts. The highly conserved nature of Pvmsp8, combined with the lack of mutations in its functional domain, presents it as a promising candidate for developing a broad and effective P. vivax vaccine. This research thus lays a foundation for the rational development of multivalent malaria vaccines targeting this genetically stable antigen.