Results of a Pilot External Quality Assessment Scheme for Genetic Testing of Newborns with Spinal Muscular Atrophy.

BACKGROUND: This study aims to evaluate the ability of laboratories to perform spinal muscular atrophy (SMA) genetic testing in newborns based on dried blood spot (DBS) samples, and to provide reference data and advance preparation for establishing the pilot external quality assessment (EQA) scheme for SMA genetic testing of newborns in China. METHODS: The pilot EQA scheme contents and evaluation principles of this project were designed by National Center for Clinical Laboratories (NCCL), National Health Commission. Two surveys were carried out in 2022, and 5 batches of blood spots were submitted to the participating laboratory each time. All participating laboratories conducted testing upon receiving samples, and test results were submitted to NCCL within the specified date. RESULTS: The return rates were 75.0% (21/28) and 95.2% (20/21) in the first and second surveys, respectively. The total return rate of the two examinations was 83.7% (41/49). Nineteen laboratories (19/21, 90.5%) had a full score passing on the first survey, while in the second survey twenty laboratories (20/20, 100%) scored full. CONCLUSIONS: This pilot EQA survey provides a preliminary understanding of the capability of SMA genetic testing for newborns across laboratories in China. A few laboratories had technical or operational problems in testing. It is, therefore, of importance to strengthen laboratory management and to improve testing capacity for the establishment of a national EQA scheme for newborn SMA genetic testing.

Transition role of entangled data in quantum machine learning.

Entanglement serves as the resource to empower quantum computing. Recent progress has highlighted its positive impact on learning quantum dynamics, wherein the integration of entanglement into quantum operations or measurements of quantum machine learning (QML) models leads to substantial reductions in training data size, surpassing a specified prediction error threshold. However, an analytical understanding of how the entanglement degree in data affects model performance remains elusive. In this study, we address this knowledge gap by establishing a quantum no-free-lunch (NFL) theorem for learning quantum dynamics using entangled data. Contrary to previous findings, we prove that the impact of entangled data on prediction error exhibits a dual effect, depending on the number of permitted measurements. With a sufficient number of measurements, increasing the entanglement of training data consistently reduces the prediction error or decreases the required size of the training data to achieve the same prediction error. Conversely, when few measurements are allowed, employing highly entangled data could lead to an increased prediction error. The achieved results provide critical guidance for designing advanced QML protocols, especially for those tailored for execution on early-stage quantum computers with limited access to quantum resources.

Utilizing 5' UTR Engineering Enables Fine-Tuning of Multiple Genes within Operons to Balance Metabolic Flux in Bacillus subtilis.

The application of synthetic biology tools to modulate gene expression to increase yield has been thoroughly demonstrated as an effective and convenient approach in industrial production. In this study, we employed a high-throughput screening strategy to identify a 5' UTR sequence from the genome of B. subtilis 168. This sequence resulted in a 5.8-fold increase in the expression level of EGFP. By utilizing the 5' UTR sequence to overexpress individual genes within the rib operon, it was determined that the genes ribD and ribAB serve as rate-limiting enzymes in the riboflavin synthesis pathway. Constructing a 5' UTR library to regulate EGFP expression resulted in a variation range in gene expression levels exceeding 100-fold. Employing the same 5' UTR library to regulate the expression of EGFP and mCherry within the operon led to a change in the expression ratio of these two genes by over 10,000-fold. So, employing a 5' UTR library to modulate the expression of the rib operon gene and construct a synthetic rib operon resulted in a 2.09-fold increase in riboflavin production. These results indicate that the 5' UTR sequence identified and characterized in this study can serve as a versatile synthetic biology toolkit for achieving complex metabolic network reconstruction. This toolkit can facilitate the fine-tuning of gene expression to produce target products.

Facilitated Unidirectional Electron Transmission by Ru Nano Particulars Distribution on MXene Mo2C@g-C3N4 Heterostructures for Enhanced Photocatalytic H2 Evolution.

Precious metals exhibit promising potential for the hydrogen evolution reaction (HER), but their limited abundance restricts widespread utilization. Loading precious metal nanoparticles (NPs) on 2D/2D heterojunctions has garnered considerable interest since it saves precious metal consumption and facilitates unidirectional electron transmission from semiconductors to active sites. In this study, Ru NPs loaded on MXenes Mo2C by an in-site simple strategy and then formed 2D/2D heterojunctions with 2D g-C3N4 (CN) via electrostatic self-assembly were used to enhance photocatalytic H2 evolution. Evident from energy band structure analyses such as UV-vis and TRPL, trace amounts of Ru NPs as active sites significantly improve the efficiency of the hydrogen evolution reaction. More interestingly, MXene Mo2C, as substrates for supporting Ru NPs, enriches photoexcited electrons from CN, thereby enhancing the unidirectional electron transmission. As a result, the combination of Ru-Mo2C and CN constructs a composite heterojunction (Ru-Mo2C@CN) that shows an improved H2 production rate at 1776.4 µmol∙g-1∙h-1 (AQE 3.58% at 400 nm), which is facilitated by the unidirectional photogenerated electron transmission from the valence band on CN to the active sites on Ru (CN→Mo2C→Ru). The study offers fresh perspectives on accelerated unidirectional photogenerated electron transmission and saved precious metal usage in photocatalytic systems.

Result of a Pilot External Quality Assessment Scheme for Clinical Diagnosis of Inherited Metabolic Disorders in China.

BACKGROUND: We aimed to evaluate the diagnostic capabilities of Chinese laboratories for inherited metabolic disorders (IMDs) using gas chromatography-mass spectrometry (GC-MS) on urine samples. Meanwhile, based on the result of the pilot external quality assessment (EQA) scheme, we hope to establish a standardized and reliable procedure for future EQA practice. METHODS: We recruited laboratories that participated in the EQA of quantitative analysis of urinary organic acids with GC-MS before joining the surveys. In each survey, a set of five real urine samples was distributed to each participant. The participants should analyze the sample by GC-MS and report the "analytical result", "the most likely diagnosis", and "recommendation for further tests" to the NCCL before the deadline. RESULTS: A total of 21 laboratories participated in the scheme. The pass rates were 94.4% in 2020 and 89.5% in 2021. For all eight IMDs tested, the analytical proficiency rates ranged from 84.7% - 100%, and the interpretational performance rate ranged from 88.2% - 97.0%. The performance on hyperphenylalaninemia (HPA), 3-methylcrotonyl-CoA carboxylase deficiency (MCCD), and ethylmalonic encephalopathy (EE) samples were not satisfactory. CONCLUSIONS: In general, the participants of this pilot EQA scheme are equipped with the basic capability for qualitative organic acid analysis and interpretation of the results. Limited by the small size of laboratories and samples involved, this activity could not fully reflect the state of clinical practice of Chinese laboratories. NCCL will improve the EQA scheme and implement more EQA activities in the future.

Analysis of Imprecision for Internal Quality Control of Newborn Screening by Tandem Mass Spectrometry in China, 2015 - 2021.

BACKGROUND: This study aimed to assess the performance of the newborn screening laboratories in China through retrospective analysis of the coefficient of variation (CV) of the internal quality control (IQC) data in the national tandem mass spectrometry screening for inherited metabolic disorders in newborns. METHODS: From 2015 to 2021, the IQC data of amino acid and acylcarnitine test were collected twice each year. CVmonthly in-control was calculated by excluding outliers for the current month and its discrete distribution and changes in trend were comprehensively evaluated for both normal and high concentration levels. The proportion of laboratories meeting both 1/3 and 1/4 quality criteria of the total error allowable (TEa), based on the CVmonthly in-control for each testing item, was calculated. RESULTS: The analysis of CVmonthly in-control for the two concentration levels for the amino acids and acylcarnitine parameters showed that CVmonthly in-control for the normal concentration levels were more discrete before 2018, while CVmonthly in-control for the high concentration levels were less discrete than the normal concentration levels, but there were relatively more outliers. More than 80% of laboratories were able to meet the 1/3 TEa standard for each test at the high concentration level, while the pass rate for the 1/4 TEa standard was significantly lower than 80% (except for C2). CONCLUSIONS: According to the current status of testing in China, it is recommended to use 1/3TEa as the imprecision level standard; for laboratories with relatively high precision, the 1/4TEa standard can be used.

Predicting Natural Evolution in the RBD Region of the Spike Glycoprotein of SARS-CoV-2 by Machine Learning.

Machine learning (ML) is a key focus in predicting protein mutations and aiding directed evolution. Research on potential virus variants is crucial for vaccine development. In this study, the machine learning software PyPEF was employed to conduct mutation analysis within the receptor-binding domain (RBD) of the Spike glycoprotein of SARS-CoV-2. Over 48,960,000 variants were predicted. Eight prospective variants that could surface in the future underwent modeling and molecular dynamics simulations. The study forecasts that the latest variant, ISOY2P5O1, may potentially emerge around 17 November 2023, with an approximate window of uncertainty of ±22 days. The ISOY8P5O2 variant displayed an increased binding capacity in the dry assay, with a total predicted binding energy of -110.306 kcal/mol. This represents an 8.25% enhancement in total binding energy compared to the original SARS-CoV-2 strain discovered in Wuhan (-101.892 kcal/mol). Reverse research confirmed the structural significance of mutation sites using ML models, particularly in the context of protein folding. The study validated regression methods (SVR, RF, and PLS) with different data structures. This study investigates the effectiveness of the "ML-Guided Design Correctly Predicts Combinatorial Effects Strategy" compared to the "ML-Guided Design Correctly Predicts Natural Evolution Prediction Strategy". To enhance machine learning, we created a timestamping algorithm and two auxiliary programs using advanced techniques to rapidly process extensive data, surpassing batch sequencing capabilities. This study not only advances machine learning in guiding protein evolution but also holds potential for forecasting future viruses and vaccine development.

Modulating the pore and electronic structure for targeted recovery of platinum: Accelerated kinetic and reinforced coordination.

Adsorption for recovery of low-concentration platinum (Pt) from the complex composition of acidic digestates was challenging because of slow kinetic and poor affinity. It was expected to be overcome by the improvement of pore size distribution and adsorption site activity. Herein, a series of Prussian blue etchings (PBE) with porosity-rich and activity-high cyano (CN) was synthesized to recover low-concentration Pt. The N2 isotherm results showed that the pore structure evolved from mesoporous to microporous. The Fourier transform infrared spectroscopy (FT-IR), X-ray photoelectron spectroscopy (XPS), and density functional theory (DFT) calculations results revealed that the modulation of electronic structure converted FeII to FeIII in [FeII(CN)6]4-. The coexistence of micro- and meso-pore structures provided channels to accelerate adsorption and ensured PtII enrichment. The regulation of Fe valence state activated CN, which reinforced the strength of coordination interaction between Pt and Fe-CN- at N-atom. The adsorption rate and maximum capacity of PBE1 were 4.4 and 2.5 times higher than those of PB, respectively, due to the dual efficacy of accelerated kinetic and reinforced coordination. This study systematically analyzes the pivotal role of pore and electronic structure modulation in adsorption kinetic and affinity, which provides a novel strategy for PtII targeted recovery.

Rapid separation of the low concentration Pd from Pd-Pt coexisting systems: Cyano-group's monomer-specific affinity.

Rapid separation of low concentration palladium (Pd) from Pd-Platinum (Pt) coexisting systems remains a formidable challenge, primarily due to the undifferentiated substitution of ligands in Pd/Pt complexes by adsorption sites. The development of an adsorbent featuring monomer-specific affinity adsorption sites for Pd/Pt could mitigate this drawback. Herein, Manganese hexacyanoferrate (MnHCF) possessing the sensitivity and specificity to Pd ions (Pd(II)) was synthesized via the facile co-precipitation method. MnHCF could rapidly and selectively capture 90.30 % of Pd(II) from a 10 ppm Pd-Pt coexisting system within just 5 min. Spectroscopic analyses and density functional theory (DFT) calculations indicated that cyano-group (CN) in MnHCF exhibited the monomer-specific affinity for targeted capturing Pd via the direct and strong coordination interaction (Fe-CN-PdCl2), which was co-determined by the electron-losing of C (0.06 e) and N (0.07 e) atom. At the same time, CN could neither react directly with the fully coordinated [PtCl6]2- species nor substitute the Cl- ligand, both of which contributed to the non-adsorption of Pt, thus triggering the Pd-Pt separation. This study provides a promising candidate adsorbent for practical applications in platinum group metals recovery by the design of adsorption sites with monomer-specific affinity.

A Time-Consistency Curriculum for Learning from Instance-Dependent Noisy Labels.

Many machine learning algorithms are known to be fragile on simple instance-independent noisy labels. However, noisy labels in real-world data are more devastating since they are produced by more complicated mechanisms in an instance-dependent manner. In this paper, we target this practical challenge of Instance-Dependent Noisy Labels by jointly training (1) a model reversely engineering the noise generating mechanism, which produces an instance-dependent mapping between the clean label posterior and the observed noisy label; and (2) a robust classifier that produces clean label posteriors. Compared to previous methods, the former model is novel and enables end-to-end learning of the latter directly from noisy labels. An extensive empirical study indicates that the time-consistency of data is critical to the success of training both models and motivates us to develop a curriculum selecting training data based on their dynamics on the two models' outputs over the course of training. We show that the curriculum-selected data provide both clean labels and high-quality input-output pairs for training the two models. Therefore, it leads to promising and robust classification performance even in notably challenging settings of instance-dependent noisy labels where many SoTA methods could easily fail. Extensive experimental comparisons and ablation studies further demonstrate the advantages and significance of the time-consistency curriculum in learning from instance-dependent noisy labels on multiple benchmark datasets.

Clinical outcomes and spinal growth after posterior hemivertebra resection and short segment fusion in children.

To evaluate the corrective effect of posterior hemivertebra resection and short-segment fusion surgery on pediatric patients and to assess the impact of short-segment fixation surgery on vertebral development during follow-up, a retrospective analysis was performed on 28 pediatric patients who underwent posterior hemivertebra resection surgery. The corrective effect was evaluated by comparing indicators such as segmental scoliosis Cobb angle, upper and lower compensatory curves and trunk balance at different time points. Meanwhile, the vertebral and spinal canal diameters of instrumented vertebrae and adjacent noninstrumented vertebrae were measured and compared to assess vertebral and spinal canal development. The correction rate of segmental scoliosis was 72.2%. The estimated mean vertebral volume of the instrumented vertebra was slightly lower than that of the unfused segment at the final follow-up, but the difference was not statistically significant. The growth rate of the spinal canal during follow-up was much smaller than that of the vertebral body. In summary, internal fixation at a young age shows no significant inhibitory effects on spinal development within the fusion segment. Posterior hemivertebra resection and short-segment fusion surgery are safe and effective.

Osteosarcoma neutrophil extracellular trap network-associated gene recurrence and metastasis model.

Osteosarcoma (OS) is the most common malignancy in children and adolescents and has a high probability of recurrence and metastasis. A growing number of studies have shown that neutrophil extracellular traps (NETs) are strongly associated with cancer metastasis, but in osteosarcoma, genes associated with NETs that promote osteosarcoma recurrence and metastasis remain to be explored. We systematically investigated the gene expression patterns of NETs in OS samples from the GEO database. NETs molecular typing was evaluated based on NETs expression profiles, and the association between NETs molecular subtypes and immune microenvironment and metastatic features were explored. Ultimately, we constructed a signature model and column line graph associated with metastasis prediction and screened possible potential drugs for metastatic osteosarcoma. We established two different molecular subtypes of NETs, which showed significant differences in metastatic status, metastasis time, tumor immune microenvironment, and biological effects. We also constructed a NETs-related gene metastasis signature(NRGMS) to assess the expression pattern of NETs in patients to predict metastatic recurrence in osteosarcoma patients. We screened for TOMM40 and FH associated with metastatic recurrence in osteosarcoma patients. Overall, this study constructs a predictive model for osteosarcoma metastasis of NETs-related genes, which is expected to provide new insights into the metastasis of osteosarcoma.

Ameliorative Role of Mitochondrial Therapy in Cognitive Function of Vascular Dementia Mice.

BACKGROUND: Mitochondrial dysfunction plays a vital role in the progression of vascular dementia (VaD). We hypothesized that transfer of exogenous mitochondria might be a beneficial strategy for VaD treatment. OBJECTIVE: The study was aimed to investigate the role of mitochondrial therapy in cognitive function of VaD. METHODS: The activity and integrity of isolated mitochondria were detected using MitoTracker and Janus Green B staining assays. After VaD mice were intravenously injected with exogenous mitochondria, Morris water maze and passive avoidance tests were used to detect cognitive function of VaD mice. Haematoxylin and eosin, Nissl, TUNEL, and Golgi staining assays were utilized to measure neuronal and synaptic injury in the hippocampus of VaD mice. Detection kits were performed to detect mitochondrial membrane potential (ΔΨ), SOD activity and the levels of ATP, ROS, and MDA in the brains of VaD mice. RESULTS: The results showed that isolated mitochondria were intact and active. Mitochondrial therapy could ameliorate cognitive performance of VaD mice. Additionally, mitochondrial administration could attenuate hippocampal neuronal and synaptic injury, improve mitochondrial ΔΨ, ATP level and SOD activity, and reduce ROS and MDA levels in the brains of VaD mice. CONCLUSIONS: The study reports profitable effect of mitochondrial therapy against cognitive impairment of VaD, making mitochondrial treatment become a promising therapeutic strategy for VaD.

Corrigendum: Meta-analysis of the association between toll-like receptor gene polymorphisms and hepatitis C virus infection.

[This corrects the article DOI: 10.3389/fmicb.2023.1254805.].

Traditional Chinese exercises on pain and disability in middle-aged and elderly patients with lumbar disc herniation: a systematic review and meta-analysis of randomized controlled trials.

Background: Traditional Chinese exercises (TCEs) have played a significant role in treating various diseases. However, there is limited research assessing the efficacy of TCEs in treating Lumbar disc herniation (LDH). This study aimed to systematically evaluate the effects of four commonly used TCEs (Baduanjin, Yijinjing, Taichi, and Wuqinxi) on pain and disability in elderly patients with LDH. Objectives: To assess the quality of relevant randomized controlled trials (RCTs) to provide evidence support for the treatment of LDH. Methods: RCTs were identified through eight databases. Meta-analysis and trial sequence analysis (TSA) were conducted using RevMan 5.4, Stata 17.0, and TSA 0.9. Results: A total of 22 RCTs, involving 1931 patients, were included in the analysis. TCEs exhibited a superior effectiveness in treating LDH compared to the control group. However, the TSA analysis suggested the possibility of false positives, indicating the need for more high-quality RCT evidence. Nevertheless, TCEs showed reliable results in significantly improving the VAS score and JOA score of LDH patients. Conclusion: Current evidence indicates that the four TCEs have advantages in treating LDH in middle-aged and elderly individuals. However, considering the limitations of this study, we need to exercise caution in drawing conclusions, and further research is required to validate these findings. Systematic Review Registration: http://www.crd.york.ac.uk/PROSPERO, identifier [CRD42023431633].

MetaCC allows scalable and integrative analyses of both long-read and short-read metagenomic Hi-C data.

Metagenomic Hi-C (metaHi-C) can identify contig-to-contig relationships with respect to their proximity within the same physical cell. Shotgun libraries in metaHi-C experiments can be constructed by next-generation sequencing (short-read metaHi-C) or more recent third-generation sequencing (long-read metaHi-C). However, all existing metaHi-C analysis methods are developed and benchmarked on short-read metaHi-C datasets and there exists much room for improvement in terms of more scalable and stable analyses, especially for long-read metaHi-C data. Here we report MetaCC, an efficient and integrative framework for analyzing both short-read and long-read metaHi-C datasets. MetaCC outperforms existing methods on normalization and binning. In particular, the MetaCC normalization module, named NormCC, is more than 3000 times faster than the current state-of-the-art method HiCzin on a complex wastewater dataset. When applied to one sheep gut long-read metaHi-C dataset, MetaCC binning module can retrieve 709 high-quality genomes with the largest species diversity using one single sample, including an expansion of five uncultured members from the order Erysipelotrichales, and is the only binner that can recover the genome of one important species Bacteroides vulgatus. Further plasmid analyses reveal that MetaCC binning is able to capture multi-copy plasmids.

Hyperprogression after anti-programmed death-1 therapy in a patient with urothelial bladder carcinoma: A case report.

BACKGROUND: Immune checkpoint inhibitors, including programmed death-ligand 1 (PD-L1) and programmed death-1 (PD-1) have recently been approved to treat locally advanced and metastatic urothelial carcinoma (UC). However, some patients experience rapid tumor progression rather than any clinical benefit from anti-PD-L1/PD-1 therapy. CASE SUMMARY: A 73-year-old woman with bladder UC showed the progression of multiple metastases after surgery and chemotherapy for over 12 mo. The patient could not tolerate further chemotherapy. Next-generation sequencing was performed, and the results indicated that the tumor mutational burden was 6.4 mutations/Mb. The patient received the anti-PD-L1 agent toripalimab combined with albumin-bound paclitaxel. Compared with the baseline staging before immunotherapy, the patient had a treatment failure time of < 2 mo, an increase in tumor burden of > 50%, and a > 2-fold increase in progression, indicating hyperprogression. CONCLUSION: Selecting patients most likely to respond to treatment with immunotherapeutic agents remains challenging. For older patients with advanced UC who have already exhausted multi-line chemotherapy options, immunotherapy should be used prudently if no effective biomarker is available. Further studies are required to clarify the causes and mechanisms of hyperprogression.

Meta-analysis of the association between toll-like receptor gene polymorphisms and hepatitis C virus infection.

Objective: The objective of this study is to investigate the association between toll-like receptor (TLR) 3/7 gene polymorphisms and the infection by hepatitis C virus (HCV). Methods: PubMed, Embase, Web of Science, Scopus, CNKI, Wanfang Data, and SinoMed were searched to identify studies focusing on the association between the TLR3 rs3775290 or the TLR7 rs179008 single nucleotide polymorphisms (SNPs) and the HCV infection. All the related articles were collected from the inception of each database to 15 January 2023. Our meta-analysis was conducted using the allelic model, the dominant model, and the recessive model. Outcomes were presented by odds ratio (ORs) and 95% confidence interval (95%CI). The heterogeneity across studies was assessed by the I2 test. A subgroup analysis was performed to explore the source of heterogeneity. Funnel plots were drawn to assess the risk of publication bias. Review Manager 5.4 was used for statistical analysis. Results: Ten articles were finally included, among which six studies were analyzed for rs3775290 and five studies were analyzed for rs179008. Studies relating to rs3775290 included 801 patients and 1,045 controls, whereas studies relating to rs179008 included 924 patients and 784 controls. The results of the meta-analysis showed that there is no significant association between rs3775290 gene polymorphism and HCV infection (T vs. C: OR = 1.12, 95%CI 0.97-1.30; TT+CT vs. CC: OR = 1.20, 95%CI 0.73-1.96; TT vs. CT+CC: OR = 1.13, 95%CI 0.68-1.89). The recessive model showed that rs179008-T allele homozygotes had an 89% increased risk of infection by HCV compared with rs179008-A allele carriers (TT vs. AT+AA: OR = 1.89, 95%CI 1.13-3.16). The results of the subgroup analysis demonstrated that the characteristics of the control population may serve as an important source of heterogeneity. In the African populations, individuals with homozygous rs179008-T alleles had a higher risk of infection by HCV than rs179008-A allele carriers (OR = 2.14, 95%CI 1.18-3.87). We did not find that this difference existed in the European populations (OR = 1.24, 95%CI 0.43-3.56). Conclusion: There is no significant association between rs3775290 single nucleotide polymorphism and the infection by HCV. Individuals with homozygous rs179008-T alleles have a higher risk of an infection by HCV than rs179008-A allele carriers, which is statistically significant in the African populations.

Problem-Dependent Power of Quantum Neural Networks on Multiclass Classification.

Quantum neural networks (QNNs) have become an important tool for understanding the physical world, but their advantages and limitations are not fully understood. Some QNNs with specific encoding methods can be efficiently simulated by classical surrogates, while others with quantum memory may perform better than classical classifiers. Here we systematically investigate the problem-dependent power of quantum neural classifiers (QCs) on multiclass classification tasks. Through the analysis of expected risk, a measure that weighs the training loss and the generalization error of a classifier jointly, we identify two key findings: first, the training loss dominates the power rather than the generalization ability; second, QCs undergo a U-shaped risk curve, in contrast to the double-descent risk curve of deep neural classifiers. We also reveal the intrinsic connection between optimal QCs and the Helstrom bound and the equiangular tight frame. Using these findings, we propose a method that exploits loss dynamics of QCs to estimate the optimal hyperparameter settings yielding the minimal risk. Numerical results demonstrate the effectiveness of our approach to explain the superiority of QCs over multilayer Perceptron on parity datasets and their limitations over convolutional neural networks on image datasets. Our work sheds light on the problem-dependent power of QNNs and offers a practical tool for evaluating their potential merit.

Association between malnutrition and surgical site wound infection among spinal surgery patients: A meta-analysis.

A surgical site infection (SSI) is one of the most common complications of spinal surgery. Malnutrition has also been linked to SSI after other surgical procedures. However, whether malnutrition is a risk factor for SSI after spinal surgery remains controversial. Therefore, we performed a meta-analysis to comprehensively evaluate the relationship between malnutrition and SSI. Relevant studies of the correlation between malnutrition and SSI were retrieved from the Cochrane Library, EMBASE, PubMed, Web of Science, China National Knowledge Infrastructure and Wanfang Data from database inception to 21 May 2023. Two reviewers independently assessed the included studies, and a meta-analysis was performed using STATA 17.0 software. A total of 24 articles with 179 388 patients were included: 3919 and 175 469 cases comprised the SSI and control groups, respectively. The meta-analysis results showed that malnutrition significantly increased the SSI incidence (odds ratio, 1.811; 95% confidence interval, 1.512-2.111; p < 0.001). These results suggest that patients with malnutrition are at higher risk for SSI after surgery. However, because of significant differences in sample sizes among studies, and because some studies had limitations to their methodological quality, further validation of these results by additional high-quality studies with larger sample sizes is necessary.