Frequency-dependent selection of neoantigens fosters tumor immune escape and predicts immunotherapy response.

Cancer is an evolutionary process shaped by selective pressure from the microenvironments. However, recent studies reveal that certain tumors undergo neutral evolution where there is no detectable fitness difference amongst the cells following malignant transformation. Here, through computational modeling, we demonstrate that negative frequency-dependent selection (or NFDS), where the immune response against cancer cells depends on the clonality of neoantigens, can lead to an immunogenic landscape that is highly similar to neutral evolution. Crucially, NFDS promotes high antigenic heterogeneity and early immune evasion in hypermutable tumors, leading to poor responses to immune checkpoint blockade (ICB) therapy. Our model also reveals that NFDS is characterized by a negative association between average clonality and total burden of neoantigens. Indeed, this unique feature of NFDS is common in the whole-exome sequencing (WES) datasets (357 tumor samples from 275 patients) from four melanoma cohorts with ICB therapy and a non-small cell lung cancer (NSCLC) WES dataset (327 tumor samples from 100 patients). Altogether, our study provides quantitative evidence supporting the theory of NFDS in cancer, explaining the high prevalence of neutral-looking tumors. These findings also highlight the critical role of frequency-dependent selection in devising more efficient and predictive immunotherapies.

Multichannel Nanogenerator-Driven Collaborative Metabolic Fingerprint Diagnostic Strategy for Early Screening and Risk Evaluation of Nonalcoholic Fatty Liver Disease.

Nonalcoholic fatty liver disease (NAFLD), along with its progressive forms nonalcoholic steatohepatitis (NASH) and NASH fibrosis, has emerged as a global health crisis. However, the absence of robust screening and risk evaluation tools contributes to the underdiagnosis of NAFLD. Herein, we reported a multichannel nanogenerator-assisted laser desorption/ionization mass spectrometry (LDI-MS) platform for early screening and risk evaluation of NAFLD. Specifically, titanium oxide nanosheets (TiNS) and covalent-organic framework nanosheets (COFNS) were employed as nanogenerators with excellent optical properties and exhibited efficient desorption/ionization during the LDI-MS process. Only ∼0.025 µL of serum without pretreatments and separation, serum metabolic fingerprints (SMFs) can be extracted within seconds. Notably, integrated SMFs from TiNS and COFNS significantly improved diagnostic performance and achieved the area under the curve (AUC) values of 1.000 with 100% sensitivity and 100% specificity for the validation sets of global diagnosis, early diagnosis, high-risk NASH, and NASH fibrosis evaluation. Additionally, four biomarker panels were identified, and their diagnostic AUC values were more than 0.944. Ultimately, key metabolic pathways indicating the change from simple NAFLD to high-risk NASH and NASH fibrosis were uncovered. This work provided a noninvasive and high-throughput screening and risk evaluation strategy for NAFLD healthcare management, thus contributing to the precise treatment of the NALFD.

Highly precise thickness measurement of multilayer films based on the cross-correlation algorithm using a widely tunable MG-Y laser.

Inspired by the demodulation algorithm of Fabry-Perot composite sensors in the field of fiber-optic sensing, this paper proposes a method based on a widely tunable modulated grating Y-branch (MG-Y) laser combined with the cross-correlation algorithm to achieve a highly precise measurement of the optical thickness of each layer of a multilayer optical sample. A sample consisting of a double glass stack was selected, and the interference spectrum of the stacked sample was acquired using a widely tunable MG-Y laser. A fast Fourier transform (FFT) algorithm combined with a finite impulse response (FIR) bandpass filter was utilized to separate the different frequency components of the multilayer optical sample. The normalized spectra of each layer were reconstructed using the Hilbert transform. Subsequently, a cross-correlation algorithm was employed to process the normalized spectrum and determine the optical thickness of each layer with high precision. The samples were measured at predetermined locations, with 150 consecutive measurements performed to assess the repetition of the thickness. The standard deviation of these measurements was found to be lower than 1.5 nm. The results show that the cross-correlation algorithm is advantageous in the optical thickness measurement of multilayer films.

Non-O1, Non-O139 Vibrio cholerae Bacteremia in an Autoimmune Pancreatitis Patient.

Over 200 different serogroups of Vibrio cholerae based on O-polysaccharide specificity have been described worldwide, including the two most important serogroups, O1 and O139. Non-O1/non-O139 V. cholerae serogroups generally do not produce the cholera-causing toxin but do sporadically cause gastroenteritis and extra-intestinal infections. Recently, however, bloodstream infections caused by non-O1/non-O139 V. cholerae are being increasingly reported, and these infections are associated with high mortality in immunocompromised hosts. We describe a case of non-O1/non-O139 V. cholerae bacteremia in a patient with autoimmune pancreatitis and stenosis of the intra- and extrahepatic bile ducts. The clinical manifestations of bacteremia were fever and mild digestive symptoms. The blood cultures showed V. cholerae, which was identified as a non-O1, non-O139 serogroup by slide agglutination tests and PCR. The bloodstream infection of the patient was likely caused by the consumption of contaminated seafood at a banquet. The patient recovered after the administration of a third-generation cephalosporin. Non-O1/non-O139 V. cholerae infection presents with or without gastrointestinal manifestations; close attention should be paid to the possibility of disseminated non-O1/non-O139 V. cholerae infection in high-risk patients.

The causal relationship between sarcopenia-related traits and ischemic stroke: Insights from univariable and multivariable Mendelian randomization analyses.

AIMS: The causal relationship between sarcopenia-related traits and ischemic stroke (IS) remains poorly understood. This study aimed to explore the causal impact of sarcopenia-related traits on IS and to identify key mediators of this association. METHODS: We conducted univariable, multivariable two-sample, and two-step Mendelian randomization (MR) analyses using genome-wide association study (GWAS) data. This included data for appendicular lean mass (ALM), hand grip strength (HGS), and usual walking pace (UWP) from the UK Biobank, and IS data from the MEGASTROKE consortium. Additionally, 21 candidate mediators were analyzed based on their respective GWAS data sets. RESULTS: Each 1-SD increase in genetically proxied ALM was associated with a 7.5% reduction in the risk of IS (95% CI: 0.879-0.974), and this correlation remained after controlling for levels of physical activity and adiposity-related indices. Two-step MR identified that six mediators partially mediated the protective effect of higher ALM on IS, with the most significant being coronary heart disease (CHD, mediating proportion: 39.94%), followed by systolic blood pressure (36.51%), hypertension (23.87%), diastolic blood pressure (15.39%), type-2 diabetes mellitus (T2DM, 12.71%), and low-density lipoprotein cholesterol (7.97%). CONCLUSION: Our study revealed a causal protective effect of higher ALM on IS, independent of physical activity and adiposity-related indices. Moreover, we found that higher ALM could reduce susceptibility to IS partially by lowering the risk of vascular risk factors, including CHD, hypertension, T2DM, and hyperlipidemia. In brief, we elucidated another modifiable factor for IS and implied that maintaining sufficient muscle mass may reduce the risk of such disease.

Impact of body composition, grip strength, and physical performance on clinical outcomes for locally advanced gastric cancer during neoadjuvant chemotherapy: A prospective cohort study.

OBJECTIVE: Neoadjuvant chemotherapy (NC) is critical in treating locally advanced gastric cancer (LAGC). However, the effect of body composition, grip strength, and physical performance during neoadjuvant chemotherapy remains uncertain. This study aimed to investigate the impact of these factors on perioperative clinical outcomes in LAGC patients undergoing NC. METHODS: A total of 162 consecutive patients receiving NC at two centers were prospectively registered between June 2022 and September 2023. The data on body composition parameters, grip strength, and physical performance during NC were collected, compared, and analyzed. The primary outcome was the tumor response after completion of NC. RESULTS: Overall, we included 92 LAGC patients. No significant changes were observed in body composition, grip strength, and physical performance after NC. The change in skeletal muscle index and grip strength were both significantly lower in the patients with poor tumor response. According to the Youden index, the cutoff values of △SMI and △grip strength were -2.0 and -2.8, respectively. Based on these two parameters, the area under the curve to predict tumor response was 0.817 (P < 0.001). Furthermore, visceral fat index (VFI) loss >6.9 and 5-time chair stand test increase >2.4 independently predicted postoperative complication (OR: 3.82, 95% CI: 1.138-12.815, P = 0.030; OR: 5.01, 95% CI: 1.086-23.131, P = 0.039, respectively). CONCLUSIONS: For LAGC patients receiving NC, changes in SMI, VFI, grip strength, and physical status can predict perioperative clinical outcomes. These patients should be given special nutritional intervention.

Biclustering analysis on tree-shaped time-series single cell gene expression data of Caenorhabditis elegans.

BACKGROUND: In recent years, gene clustering analysis has become a widely used tool for studying gene functions, efficiently categorizing genes with similar expression patterns to aid in identifying gene functions. Caenorhabditis elegans is commonly used in embryonic research due to its consistent cell lineage from fertilized egg to adulthood. Biologists use 4D confocal imaging to observe gene expression dynamics at the single-cell level. However, on one hand, the observed tree-shaped time-series datasets have characteristics such as non-pairwise data points between different individuals. On the other hand, the influence of cell type heterogeneity should also be considered during clustering, aiming to obtain more biologically significant clustering results. RESULTS: A biclustering model is proposed for tree-shaped single-cell gene expression data of Caenorhabditis elegans. Detailedly, a tree-shaped piecewise polynomial function is first employed to fit non-pairwise gene expression time series data. Then, four factors are considered in the objective function, including Pearson correlation coefficients capturing gene correlations, p-values from the Kolmogorov-Smirnov test measuring the similarity between cells, as well as gene expression size and bicluster overlapping size. After that, Genetic Algorithm is utilized to optimize the function. CONCLUSION: The results on the small-scale dataset analysis validate the feasibility and effectiveness of our model and are superior to existing classical biclustering models. Besides, gene enrichment analysis is employed to assess the results on the complete real dataset analysis, confirming that the discovered biclustering results hold significant biological relevance.

The possible causal relationship between COVID-19 and imaging markers of cerebral small vessel disease: a Mendelian randomization study.

OBJECTIVES: Observational studies have suggested that SARS-CoV-2 infection may increase the burden of cerebral small vessel disease (CSVD). This study aims to explore the causal correlation between COVID-19 and the imaging markers of CSVD using Mendelian randomization (MR) methods. METHODS: Summary-level genome-wide association study (GWAS) statistics for COVID-19 susceptibility, hospitalization, and severity were utilized as proxies for exposure. Large-scale meta-analysis GWAS data on three neuroimaging markers of white matter hyperintensity, lacunar stroke, and brain microbleeds, were employed as outcomes. Our primary MR analysis employed the inverse variance weighted (IVW) approach, supplemented by MR-Egger, weighted median, and MR-PRESSO methods. We also conducted multivariable MR analysis to address confounding bias and validate the robustness of the established causal estimates. Comprehensive sensitivity analyses included Cochran's Q test, Egger-intercept analysis, MR-PRESSO, and leave-one-out analysis. RESULTS: The MR analysis revealed a significant causal correlation between the severity of COVID-19 and an increased risk of lacunar stroke, as demonstrated by the IVW method (ORivw = 1.08, 95% CI: 1.03-1.16, pivw = 0.005, FDR = 0.047). Nevertheless, no causal correlations were observed between COVID-19 susceptibility or hospitalization and any CSVD imaging markers. The robustness and stability of these findings were further confirmed by multivariable MR analysis and comprehensive sensitivity analyses. DISCUSSION: This study provides compelling evidence of a potential causal effect of severe COVID-19 on the incidence of lacunar stroke, which may bring fresh insights into the understanding of the comorbidity between COVID-19 and CSVD.

Effects of different treatments for type 2 diabetes mellitus on mortality of coronavirus disease from 2019 to 2021 in China: a multi-institutional retrospective study.

The coronavirus disease (COVID-19) pandemic has continued for 5 years. Sporadic cases continue to occur in different locations. Type 2 diabetes mellitus (T2DM) is associated with a high risk of a poor prognosis in patients with COVID-19. Successful control of blood glucose levels can effectively decrease the risks of severe infections and mortality. However, the effects of different treatments were reported differently and even adversely. This retrospective study included 4,922 patients who have been diagnosed as COVID-19 and T2DM from 138 Hubei hospitals. The clinical characteristics and outcomes were compared and calculated their risk for death using multivariate Cox regression and Kaplan-Meier curves. After adjustment of age, sex, comorbidities, and in-hospital medications, metformin and alpha-glucosidase inhibitor (AGI) use performed lower all-cause mortality (adjusted hazard ratio [HR], 0.41; 95% confidence interval [CI]: 0.24-0.71; p = 0.001 for metformin; 0.53, 0.35-0.80, p = 0.002 for AGIs), while insulin use was associated with increased all-cause mortality (adjusted HR, 2.07, 95% CI, 1.61-2.67, p < 0.001). After propensity score-matched (PSM) analysis, adjusted HRs for insulin, metformin, and AGIs associated with all-cause mortality were 1.32 (95% CI, 1.03-1.81; p = 0.012), 0.48 (95% CI, 0.23-0.83, p = 0.014), and 0.59 (95% CI, 0.35-0.98, p = 0.05). Therefore, metformin and AGIs might be more suitable for patients with COVID-19 and T2DM while insulin might be used with caution.

Opening and Constructing Stable Lithium-ion Channels within Polymer Electrolytes.

Lithium-ion batteries play an integral role in various aspects of daily life, yet there is a pressing need to enhance their safety and cycling stability. In this study, we have successfully developed a highly secure and flexible solid-state polymer electrolyte (SPE) through the in situ polymerization of allyl acetoacetate (AAA) monomers. This SPE constructed an efficient Li+ transport channel inside and effectively improved the solid-solid interface contact of solid-state batteries to reduce interfacial impedance. Furthermore, it exhibited excellent thermal stability, an ionic conductivity of 3.82×10-4 S cm-1 at room temperature (RT), and a Li+ transport number (tLi+) of 0.66. The numerous oxygen vacancies on layered inorganic SiO2 created an excellent environment for TFSI- immobilization. Free Li+ migrated rapidly at the C=O equivalence site with the poly(allyl acetoacetate) (PAAA) matrix. Consequently, when cycled at 0.5C and RT, it displayed an initial discharge specific capacity of 140.6 mAh g-1 with a discharge specific capacity retention rate of 70 % even after 500 cycles. Similarly, when cycled at a higher rate of 5C, it demonstrated an initial discharge specific capacity of 132.3 mAh g-1 while maintaining excellent cycling stability.

Enhancing vitamin D3 bioaccessibility: Unveiling hydrophobic interactions in soybean protein isolate and vitamin D3 binding via an infant in vitro digestion model.

In the domain of infant nutrition, optimizing the absorption of crucial nutrients such as vitamin D3 (VD3) is paramount. This study harnessed dynamic-high-pressure microfluidization (DHPM) on soybean protein isolate (SPI) to engineer SPI-VD3 nanoparticles for fortifying yogurt. Characterized by notable binding affinity (Ka = 0.166 × 105 L·mol-1) at 80 MPa and significant surface hydrophobicity (H0 = 3494), these nanoparticles demonstrated promising attributes through molecular simulations. During simulated infant digestion, the 80 MPa DHPM-treated nanoparticles showcased an impressive 74.4% VD3 bioaccessibility, delineating the pivotal roles of hydrophobicity, bioaccessibility, and micellization dynamics. Noteworthy was their traversal through the gastrointestinal tract, illuminating bile salts' crucial function in facilitating VD3 re-encapsulation, thereby mitigating crystallization and augmenting absorption. Moreover, DHPM treatment imparted enhancements in nanoparticle integrity and hydrophobic properties, consequently amplifying VD3 bioavailability. This investigation underscores the potential of SPI-VD3 nanoparticles in bolstering VD3 absorption, thereby furnishing invaluable insights for tailored infant nutrition formulations.

DFT investigation of the DDQ-catalytic mechanism for constructing C-O bonds.

In this study, we investigated the photo-catalytic mechanisms for the construction of C-O bonds from arenes (benzene, 2',6'-dimethyl-[1,1'-biphenyl]-2-carboxylic acid, or 2,4-dichloro-1-fluorobenzene), catalyzed by 2,3-dichloro-5,6-dicyano-p-benzoquinone (DDQ). All the structures for the Gibbs free surfaces were calculated at the M06-2X-D3/ma-def2-SVP level in the SMD solvent model. Also, TDDFT calculations of DDQ were performed at the PBE1PBE-D3/ma-def2-SVP level in the SMD solvent model. The computational results indicated that DDQ, serving as a photo-catalyst, would be excited under visible light of 450 nm, aligning well with experimental observations as reflected in the UV-vis spectrum. Gibbs free energy surface analyses of the three reactions suggested that the path involving 3DDQ* activating the reactant (-COOH, H2O, or CH3OH) is favorable. Additionally, the role of O2 was investigated, revealing that it could facilitate the recycling of DDQ by lowering the energy barrier for the conversion of the DDQH˙ radical (not DDQH2) into DDQ. The use of ρhole and ρele can reveal the photo-catalytic reaction and charge transfer processes, while localized orbital locator isosurfaces and electron spin density isosurface graphs were employed to analyze structures and elucidate the single electron distribution. These computational results offer valuable insights into the studied interactions and related processes, shedding light on the mechanisms governing C-O bond formation from arenes catalyzed by DDQ.

A substitutional quantum defect in WS2 discovered by high-throughput computational screening and fabricated by site-selective STM manipulation.

Point defects in two-dimensional materials are of key interest for quantum information science. However, the parameter space of possible defects is immense, making the identification of high-performance quantum defects very challenging. Here, we perform high-throughput (HT) first-principles computational screening to search for promising quantum defects within WS2, which present localized levels in the band gap that can lead to bright optical transitions in the visible or telecom regime. Our computed database spans more than 700 charged defects formed through substitution on the tungsten or sulfur site. We found that sulfur substitutions enable the most promising quantum defects. We computationally identify the neutral cobalt substitution to sulfur (Co S 0 ) and fabricate it with scanning tunneling microscopy (STM). The Co S 0 electronic structure measured by STM agrees with first principles and showcases an attractive quantum defect. Our work shows how HT computational screening and nanoscale synthesis routes can be combined to design promising quantum defects.

Improving crop health by synthetic microbial communities: Progress and prospects.

Crop health directly affects yields and food security. At present, agrochemicals such as fertilizers and pesticides are mainly used in agricultural production to promote crop health. However, long-term excessive utilization of agrochemicals will damage the ecological environment of farmlands and increase the safety risk of agricultural products. It is urgent to explore efficient and environment-friendly agricultural products. Rhizosphere microbiome are considered as the second genome of plants, which are closely related to crop health. Understanding the key functional microbes, microbe-microbe interactions, and plant-microbe interactions are fundamental for exploring the potential of beneficial microbes in promoting crop health. However, due to the heterogeneity and complexity of the natural environment, stimulating the function of indigenous microorganisms remains uncertain. Synthetic microbial community (SynCom) is an artificial combination of two or more different strain isolates of microorganisms, with different taxonomic, genetic, or functional characteristic. Because of the advantages of maintaining species diversity and community stability, SynCom has been widely applied in the fields of human health, environmental governance and industrial production, and may also have great potential in promoting crop health. We summarized the concept and research status of SynCom, expounded the principles and methods of constructing SynCom, and analyzed the research on the promotion of crop health by exploring the mechanism of plant-microbe interactions, promoting plant growth and development, and improving stress resistance. Finally, we envisaged the future prospects to guide the using SynCom to improve crop health.

Spatiotemporal drivers of urban water pollution: Assessment of 102 cities across the Yangtze River Basin.

Effective management of large basins necessitates pinpointing the spatial and temporal drivers of primary index exceedances and urban risk factors, offering crucial insights for basin administrators. Yet, comprehensive examinations of multiple pollutants within the Yangtze River Basin remain scarce. Here we introduce a pollution inventory for urban clusters surrounding the Yangtze River Basin, analyzing water quality data from 102 cities during 2018-2019. We assessed the exceedance rates for six pivotal indicators: dissolved oxygen (DO), ammonia nitrogen (NH3-N), chemical oxygen demand (COD), biochemical oxygen demand (BOD), total phosphorus (TP), and the permanganate index (CODMn) for each city. Employing random forest regression and SHapley Additive exPlanations (SHAP) analyses, we identified the spatiotemporal factors influencing these key indicators. Our results highlight agricultural activities as the primary contributors to the exceedance of all six indicators, thus pinpointing them as the leading pollution source in the basin. Additionally, forest coverage, livestock farming, chemical and pharmaceutical sectors, along with meteorological elements like precipitation and temperature, significantly impacted various indicators' exceedances. Furthermore, we delineate five core urban risk components through principal component analysis, which are (1) anthropogenic and industrial activities, (2) agricultural practices and forest extent, (3) climatic variables, (4) livestock rearing, and (5) principal polluting sectors. The cities were subsequently evaluated and categorized based on these risk components, incorporating policy interventions and administrative performance within each region. The comprehensive analysis advocates for a customized strategy in addressing the discerned risk factors, especially for cities presenting elevated risk levels.

Efficacy and Safety of Long-Term Dual Antiplatelet Therapy: A Systematic Review and Meta-Analysis.

BACKGROUND: Dual antiplatelet therapy (DAPT) with aspirin and a P2Y12 inhibitor is a standard therapy in patients with ischemic vascular diseases (IVD) including coronary artery, cerebrovascular and peripheral arterial diseases, although the optimal duration of this treatment is still debated. Previous meta-analyses reported conflicting results about the effects of long-term and short-term as well as non-DAPT use in various clinical settings. Herein, we conducted a comprehensive meta-analysis to assess the efficacy and safety of different durations of DAPT. METHODS: We reviewed relevant articles and references from database, which were published prior to April 2023. Data from prospective studies were processed using RevMan5.0 software, provided by Cochrane Collaboration and transformed using relevant formulas. The inclusion criteria involved randomization to long-term versus short-term or no DAPT; the endpoints included at least one of total or cardiovascular (CV) mortalities, IVD recurrence, and bleeding. RESULTS: A total of 34 randomized studies involving 141 455 patients were finally included. In comparison with no or short-term DAPT, long-term DAPT reduced MI and stroke, but did not reduce the total and CV mortalities. Meanwhile, bleeding events were increased, even though intracranial and fatal bleedings were not affected. Besides, the reduction of MI and stroke recurrence showed no statistical significance between long-term and short-term DAPT groups. CONCLUSION: Long-term DAPT may not reduce the mortality of IVD besides increasing bleeding events, although reduced the incidences of MI and stroke early recurrence to a certain extent and did not increase the risk of fatal intracranial bleeding.

General Synthesis of meso-1,4-Dialdehydes and Their Application in Ir-Catalyzed Asymmetric Tishchenko Reactions.

A practical synthesis of meso-1,4-dialdehydes based on the oxidative cleavage of cyclobutanediol derivatives using polymer-supported periodate was developed. The meso-1,4-dialdehydes were obtained in up to >99% yield and subsequently employed in Ir-catalyzed asymmetric Tishchenko reactions to give the corresponding chiral lactones, which are versatile synthetic intermediates, in good yield with moderate enantiomeric excess. The catalytically active species was identified by means of cold-spray ionization mass spectrometry and 1H NMR spectroscopy.

Metabolomic insights into the effects of seasonal shifts on the dynamic variation of non-volatile compounds of abalone (Haliotis discus hannai).

Abalone (Haliotis spp.) is a shellfish known for its exceptional nutritional value and significant economic worth. This study investigated the dynamic characteristics of non-volatile compounds over a year, including metabolites, lipids, nucleotides, and free amino acids (FAAs), which determined the nutritional quality and flavor of abalone. 174 metabolites and 371 lipids were identified and characterized, while 20 FAAs and 11 nucleotides were quantitatively assessed. These non-volatile compounds of abalone were fluctuated with months variation, which was consistent with the fluctuations of environmental factors, especially seawater temperature. Compared with seasonal variation, gender had less influence on these non-volatiles. June and July proved to be the optimal harvesting periods for abalone, with the levels of overall metabolites, lipids, FAAs, and nucleotides in abalone exhibiting a higher value in June and July over a year. Intriguingly, taurine covered 60% of the total FAAs and abalone could be used as dietary taurine supplementation.

[Treatment of open fracture bone defect of distal femur with antibiotic cement column and bone graft].

OBJECTIVE: To investigate the efficacy of antibiotic cement column combined with iliac bone graft in the treatment of open fracture with bone defect of distal femur. METHODS: From October 2014 to March 2021, 16 patients of open fracture bone defect of distal femur were treated with antibiotic bone cement column and iliac bone graft, including 12 males and 4 females. The age ranged from 28 to 68 years old. There were 11 cases of traffic accident injury, 5 cases of falling injury, 3 cases as Gustilo type Ⅰ, 5 cases as type Ⅱ and 8 cases as type ⅢA. AO classification was used:9 cases of C2 type and 7 cases of C3 type. The time from injury to final bone grafting ranged from 4 to 119 days. The length of bone defect ranged from 2 to10 cm. Fractures healing time, complications and knee function Merchan score were recorded. RESULTS: All the 16 patients were followed up from 9 to 29 months. The incisions of 16 patients healed in one stage without postoperative infection, plate fracture, limb shortening and valgus and varus deformity. The healing time randed from 4 to 10 months . Knee joint function according to the Merchant scoring standard, showed that 8 cases were excellent, 4 cases were good, 3 cases were fair, and 1 case was poor. CONCLUSION: The use of antibiotic bone cement column combined with iliac bone graft in the treatment of open and complex bone defects of distal femur is an effective surgical method to prevent infection, assist fracture reduction, increase fixation strength and significantly reduce the amount of bone grafting.

Prediction of mass spectrometry ionization efficiency based on COSMO-RS and machine learning algorithms.

Non-targeted analysis of high-resolution mass spectrometry (MS) can identify thousands of compounds, which also gives a huge challenge to their quantification. The aim of this study is to investigate the impact of mass spectrometry ionization efficiency on various compounds in food at different solvent ratios and to develop a predictive model for mass spectrometry ionization efficiency to enable non-targeted quantitative prediction of unknown compounds. This study covered 70 compounds in 14 different mobile phase ratio environments in positive ion mode to analyze the rules of the matrix effect. With the organic phase ratio from low to high, most compounds changed by 1.0 log units in log IE. The addition of formic acid enhanced the signal but also promoted the matrix effect, which often occurred in compounds with strong ionization capacity. It was speculated that the matrix effect was mainly in the form of competitive charge and charged droplet' gasification sites during MS detection. Subsequently, we present a log IE prediction method built using the COSMO-RS software and the artificial neural network (ANN) algorithm to address this difficulty and overcome the shortcomings of previous models, which always ignore the matrix effect. This model was developed following the principles of QSAR modeling recommended by the Organization for Economic Cooperation and Development (OECD). Furthermore, we validated this approach by predicting the log IE of 70 compounds, including those not involved in the log IE model development. The results presented demonstrate that the method we put forward has an excellent prediction accuracy for log IE (R2pred = 0.880), which means that it has the potential to predict the log IE of new compounds without authentic standards.