Precise healing of oral and maxillofacial wounds: tissue engineering strategies and their associated mechanisms.

Precise healing of wounds in the oral and maxillofacial regions is usually achieved by targeting the entire healing process. The rich blood circulation in the oral and maxillofacial regions promotes the rapid healing of wounds through the action of various growth factors. Correspondingly, their tissue engineering can aid in preventing wound infections, accelerate angiogenesis, and enhance the proliferation and migration of tissue cells during wound healing. Recent years, have witnessed an increase in the number of researchers focusing on tissue engineering, particularly for precise wound healing. In this context, hydrogels, which possess a soft viscoelastic nature and demonstrate exceptional biocompatibility and biodegradability, have emerged as the current research hotspot. Additionally, nanofibers, films, and foam sponges have been explored as some of the most viable materials for wound healing, with noted advantages and drawbacks. Accordingly, future research is highly likely to explore the application of these materials harboring enhanced mechanical properties, reduced susceptibility to external mechanical disturbances, and commendable water absorption and non-expansion attributes, for superior wound healing.

Low-Temperature Oxidation of Methane on Rutile TiO2(110): Identifying the Role of Surface Oxygen Species.

Understanding the microkinetic mechanism underlying photocatalytic oxidative methane (CH4) conversion is of significant importance for the successful design of efficient catalysts. Herein, CH4 photooxidation has been systematically investigated on oxidized rutile(R)-TiO2(110) at 60 K. Under 355 nm irradiation, the C-H bond activation of CH4 is accomplished by the hole-trapped dangling OTi- center rather than the hole-trapped Ob- center via the Eley-Rideal reaction pathway, producing movable CH3• radicals. Subsequently, movable CH3• radicals encounter an O/OH species to form CH3O/CH3OH species, which could further dissociate into CH2O under irradiation. However, the majority of the CH3• radical intermediate is ejected into a vacuum, which may induce radical-mediated reactions under ambient conditions. The result not only advances our knowledge about inert C-H bond activation but also provides a deep insight into the mechanism of photocatalytic CH4 conversion, which will be helpful for the successful design of efficient catalysts.

Miniature mass spectrometer-based point-of-care assay for quantification of metformin and sitagliptin in human blood and urine.

Metformin (MET) and sitagliptin (STG) are widely used as the first-line and long-term oral hypoglycemic agents for managing type 2 diabetes mellitus (T2DM). However, the current lack of convenient and rapid measurement methods poses a challenge for individualized management. This study developed a point-of-care (POC) assay method utilizing a miniature mass spectrometer, enabling rapid and accurate quantification of MET and STG concentrations in human blood and urine. By combining the miniature mass spectrometer with paper spray ionization, this method simplifies the process into three to four steps, requires minimal amounts of bodily fluids (50 µL of blood and 2 µL of urine), and is able to obtain quantification results within approximately 2 min. Stable isotope-labeled internal standards were employed to enhance the accuracy and stability of measurement. The MS/MS responses exhibited good linear relationship with concentration, with relative standard deviations (RSDs) below 25%. It has the potential to provide immediate treatment feedback and decision support for patients and healthcare professionals in clinical practice.

A comparison study of dynamic [18F]Alfatide II imaging and [11C]MET in orthotopic rat models of glioblastoma.

PURPOSE: To investigate and compare the dynamic positron emission tomography (PET) imaging with [18F]Alfatide II Imaging and [11C]Methionine ([11C]MET) in orthotopic rat models of glioblastoma multiforme (GBM), and to assess the utility of [18F]Alfatide II in detecting and evaluating neoangiogenesis in GBM. METHODS: [18F]Alfatide II and [11C]MET were injected into the orthotopic GBM rat models (n = 20, C6 glioma cells), followed by dynamic PET/MR scans 21 days after surgery of tumor implantation. On the PET image with both radiotracers, the MRI-based volume-of-interest (VOI) was manually delineated encompassing glioblastoma. Time-activity curves were expressed as tumor-to-normal brain ratio (TNR) parameters and PET pharmacokinetic modeling (PKM) performed using 2-tissue-compartment models (2TCM). Immunofluorescent staining (IFS), western blotting and blocking experiment of tumor tissue were performed for the validation. RESULTS: Compared to 11C-MET, [18F]Alfatide II presented a persistent accumulation in the tumor, albeit with a slightly lower SUVmean of 0.79 ± 0.25, and a reduced uptake in the contralateral normal brain tissue, respectively. This resulted in a markedly higher tumor-to-normal brain ratio (TNR) of 18.22 ± 1.91. The time-activity curve (TACs) showed a significant increase in radioactive uptake in tumor tissue, followed by a plateau phase up to 60 min for [18F]Alfatide II (time to peak:255 s) and 40 min for [11C]MET (time to peak:135 s) post injection. PKM confirmed significantly higher K1 (0.23/0.07) and K3 (0.26/0.09) in the tumor region compared to the normal brain with [18F]Alfatide II. Compared to [11C]MET imaging, PKM confirmed both significantly higher K1/K2 (1.24 ± 0.79/1.05 ± 0.39) and K3/K4 (11.93 ± 4.28/3.89 ± 1.29) in the tumor region with [18F]Alfatide II. IFS confirmed significant expression of integrin and tumor vascularization in tumor region. CONCLUSION: [18F]Alfatide II demonstrates potential in imaging tumor-associated neovascularization in the context of glioblastoma multiforme (GBM), suggesting its utility as a tool for further exploration in neovascular characterization.

How Much Storage Precision Can Be Lost: Guidance for Near-Lossless Compression of Untargeted Metabolomics Mass Spectrometry Data.

Several lossy compressors have achieved superior compression rates for mass spectrometry (MS) data at the cost of storage precision. Currently, the impacts of precision losses on MS data processing have not been thoroughly evaluated, which is critical for the future development of lossy compressors. We first evaluated different storage precision (32 bit and 64 bit) in lossless mzML files. We then applied 10 truncation transformations to generate precision-lossy files: five relative errors for intensities and five absolute errors for m/z values. MZmine3 and XCMS were used for feature detection and GNPS for compound annotation. Lastly, we compared Precision, Recall, F1 - score, and file sizes between lossy files and lossless files under different conditions. Overall, we revealed that the discrepancy between 32 and 64 bit precision was under 1%. We proposed an absolute m/z error of 10-4 and a relative intensity error of 2 × 10-2, adhering to a 5% error threshold (F1 - scores above 95%). For a stricter 1% error threshold (F1 - scores above 99%), an absolute m/z error of 2 × 10-5 and a relative intensity error of 2 × 10-3 were advised. This guidance aims to help researchers improve lossy compression algorithms and minimize the negative effects of precision losses on downstream data processing.

Ion entropy and accurate entropy-based FDR estimation in metabolomics.

Accurate metabolite annotation and false discovery rate (FDR) control remain challenging in large-scale metabolomics. Recent progress leveraging proteomics experiences and interdisciplinary inspirations has provided valuable insights. While target-decoy strategies have been introduced, generating reliable decoy libraries is difficult due to metabolite complexity. Moreover, continuous bioinformatics innovation is imperative to improve the utilization of expanding spectral resources while reducing false annotations. Here, we introduce the concept of ion entropy for metabolomics and propose two entropy-based decoy generation approaches. Assessment of public databases validates ion entropy as an effective metric to quantify ion information in massive metabolomics datasets. Our entropy-based decoy strategies outperform current representative methods in metabolomics and achieve superior FDR estimation accuracy. Analysis of 46 public datasets provides instructive recommendations for practical application.

Deciphering the molecular and functional basis of TMexCD1: the plasmid-encoded efflux pump of resistance-nodulation-division superfamily.

Horizontal gene transfer has been demonstrated to be an important driver for the emergency of multidrug-resistant pathogens. Recently, a transferable gene cluster tmexCD1-toprJ1 of the resistance-nodulation-division (RND) superfamily was identified in the plasmids of animal-derived Klebsiella pneumoniae strains, with a higher efflux capacity for various drugs than the Escherichia coli AcrAB-TolC homolog system. In this study, we focused on the differences in the inner membrane pump of these two systems and identified some key residues that contribute to the robust efflux activity of the TMexCD1 system. With the aid of homologous modeling and molecular docking, eight residues from the proximal binding pocket (PBP) and nine from the distal binding pocket (DBP) were selected and subjected to site-directed mutagenesis. Several of them, such as S134, I139, D181, and A290, were shown to be important for substrate binding in the DBP region, and all residues in PBP and DBP showed certain substrate preferences. Apart from the conservative switch loop (L613-623TMexD1) previously identified in the E. coli AcrB (EcAcrB), a relatively unconservative loop (L665-675TMexD1) at the bottom of PBP was proposed as a critical element for the robust activity of TMexD1, due to variations at sites E669, G670, N673, and S674 compared to EcAcrAB, and the significantly altered efflux activity due to their mutations. The conservation and flexibility of these key factors can contribute to the evolution of the RND efflux pumps and thus serve as potential targets for developing inhibitors to block the widespread of the TMexCD1 system.

Identification and validation of serum metabolite biomarkers for endometrial cancer diagnosis.

Endometrial cancer (EC) stands as the most prevalent gynecological tumor in women worldwide. Notably, differentiation diagnosis of abnormity detected by ultrasound findings (e.g., thickened endometrium or mass in the uterine cavity) is essential and remains challenging in clinical practice. Herein, we identified a metabolic biomarker panel for differentiation diagnosis of EC using machine learning of high-performance serum metabolic fingerprints (SMFs) and validated the biological function. We first recorded the high-performance SMFs of 191 EC and 204 Non-EC subjects via particle-enhanced laser desorption/ionization mass spectrometry (PELDI-MS). Then, we achieved an area-under-the-curve (AUC) of 0.957-0.968 for EC diagnosis through machine learning of high-performance SMFs, outperforming the clinical biomarker of cancer antigen 125 (CA-125, AUC of 0.610-0.684, p < 0.05). Finally, we identified a metabolic biomarker panel of glutamine, glucose, and cholesterol linoleate with an AUC of 0.901-0.902 and validated the biological function in vitro. Therefore, our work would facilitate the development of novel diagnostic biomarkers for EC in clinics.

Spatiotemporal Controllable Sono-Nanovaccines Driven by Free-Field Based Whole-Body Ultrasound for Personalized Cancer Therapy.

Therapeutic cancer vaccines fail to produce satisfactory outcomes against solid tumors since vaccine-induced anti-tumor immunity is significantly hampered by immunosuppression. Generating an in situ cancer vaccine targeting immunological cold tumor microenvironment (TME) appears attractive. Here, a type of free-field based whole-body ultrasound (US)-driven nanovaccines are constructed, named G5-CHC-R, by conjugating the sonosensitizer, Chenghai chlorin (CHC) and the immunomodulator, resiquimod (R848) on top of a super small-sized dendrimeric nanoscaffold. Once entering tumors, R848 can be cleaved from a hypoxia-sensitive linker, thus modifying the TME via converting macrophage phenotypes. The animals bearing orthotopic pancreatic cancer with intestinal metastasis and breast cancer with lung metastasis are treated with G5-CHC-R under a free-field based whole-body US system. Benefit from the deep penetration capacity and highly spatiotemporal selectiveness, G5-CHC-R triggered by US represented a superior alternative for noninvasive irradiation of deep-seated tumors and magnification of local immune responses via driving mass release of tumor antigens and "cold-warm-hot" three-state transformation of TME. In addition to irradiating primary tumors, a robust adaptive anti-tumor immunity is potentiated, leading to successful induction of systemic tumor suppression. The sono-nanovaccines with good biocompatibility posed wide applicability to a broad spectrum of tumors, revealing immeasurable potential for translational research in oncology.

Targeting blood brain barrier-Remote ischemic conditioning alleviates cognitive impairment in female APP/PS1 rats.

AIMS: Alzheimer's disease (AD) is a significant global health concern, and it is crucial that we find effective methods to prevent or slow down AD progression. Recent studies have highlighted the essential role of blood vessels in clearing Aß, a protein that contributes to AD. Scientists are exploring blood biomarkers as a potential tool for future AD diagnosis. One promising method that may help prevent AD is remote ischemic conditioning (RIC). RIC involves using sub-lethal ischemic-reperfusion cycles on limbs. However, a comprehensive understanding of how RIC can prevent AD and its long-term effectiveness is still lacking. Further research is essential to fully comprehend the potential benefits of RIC in preventing AD. METHODS: Female wild-type (WT) and APP/PS1 transgenic rats, aged 12 months, underwent ovariectomy and were subsequently assigned to WT, APP/PS1, and APP/PS1 + RIC groups. RIC was conducted five times a week for 4 weeks. The rats' depressive and cognitive behaviors were evaluated using force swimming, open-field tests, novel objective recognition, elevated plus maze, and Barnes maze tests. Evaluation of the neurovascular unit (NVU), synapses, vasculature, astrocytes, and microglia was conducted using immunofluorescence staining (IF), Western blot (WB), and transmission electron microscopy (TEM). Additionally, the cerebro-vasculature was examined using micro-CT, and cerebral blood flow (CBF) was measured using Speckle Doppler. Blood-brain barrier (BBB) permeability was determined by measuring the Evans blue leakage. Finally, Aß levels in the rat frontal cortex were measured using WB, ELISA, or IF staining. RESULTS: RIC enhanced memory-related protein expression and rescued depressive-like behavior and cognitive decline in APP/PS1 transgenic rats. Additionally, the intervention protected NVU in the rat frontal cortex, as evidenced by (1) increased expression of TJ (tight junction) proteins, pericyte marker PDGFRß, and glucose transporter 1 (GLUT1), as well as decreased VCAM1; (2) mitigation of ultrastructure impairment in neuron, cerebral vascular, and astrocyte; (3) upregulation of A2 astrocyte phenotype markers and downregulation of A1 phenotype markers, indicating a shift toward a healthier phenotype. Correspondingly, RIC intervention alleviated neuroinflammation, as evidenced by the decreased Iba1 level, a microglia marker. Meanwhile, RIC intervention elevated CBF in frontal cortex of the rats. Notably, RIC intervention effectively suppressed Aß toxicity, as demonstrated by the enhancement of α-secretase and attenuation of ß-secretase (BACE1) and γ- secretase and Aß1-42 and Aß1-40 levels as well. CONCLUSION: Chronic RIC intervention exerts vascular and neuroprotective roles, suggesting that RIC could be a promising therapeutic strategy targeting the BBB and NVU during AD development.

Remote Ischemia Postconditioning Mitigates Hippocampal Neuron Impairment by Modulating Cav1.2-CaMKIIα-Aromatase Signaling After Global Cerebral Ischemia in Ovariectomized Rats.

Brain-derived estrogen (BDE2) is gaining attention as an endogenous neurotransmitter. Recent research has revealed that selectively removing the aromatase gene, the pivotal enzyme responsible for BDE2 synthesis, in forebrain neurons or astrocytes can lead to synaptic loss and cognitive impairment. It is worth noting that remote ischemia post-conditioning (RIP), a non-invasive technique, has been shown to activate natural protective mechanisms against severe ischemic events. The aim of our study was to investigate whether RIP triggers aromatase-BDE2 signaling, shedding light on its neuroprotective mechanisms after global cerebral ischemia (GCI) in ovariectomized rats. Our findings are as follows: (1) RIP was effective in mitigating ischemic damage in hippocampal CA1 neurons and improved cognitive function after GCI. This was partially due to increased Aro-BDE2 signaling in CA1 neurons. (2) RIP intervention efficiently enhanced pro-survival kinase pathways, such as AKT, ERK1/2, CREB, and suppressed CaMKIIα signaling in CA1 astrocytes induced by GCI. Remarkably, inhibiting CaMKIIα activity led to elevated Aro-BDE2 levels and replicated the benefits of RIP. (3) We also identified the positive mediation of Cav1.2, an LVGCC calcium channel, on CaMKIIα-Aro/BDE2 pathway response to RIP intervention. (4) Significantly, either RIP or CaMKIIα inhibition was found to alleviate reactive astrogliosis, which was accompanied by increased pro-survival A2-astrocyte protein S100A10 and decreased pro-death A1-astrocyte marker C3 levels. In summary, our study provides compelling evidence that Aro-BDE2 signaling is a critical target for the reparative effects of RIP following ischemic insult. This effect may be mediated through the CaV1.2-CaMKIIα signaling pathway, in collaboration with astrocyte-neuron interactions, thereby maintaining calcium homeostasis in the neuronal microenvironment and reducing neuronal damage after ischemia.

MRMPro: a web-based tool to improve the speed of manual calibration for multiple reaction monitoring data analysis by mass spectrometry.

BACKGROUND: As a gold-standard quantitative technique based on mass spectrometry, multiple reaction monitoring (MRM) has been widely used in proteomics and metabolomics. In the analysis of MRM data, as no peak picking algorithm can achieve perfect accuracy, manual inspection is necessary to correct the errors. In large cohort analysis scenarios, the time required for manual inspection is often considerable. Apart from the commercial software that comes with mass spectrometers, the open-source and free software Skyline is the most popular software for quantitative omics. However, this software is not optimized for manual inspection of hundreds of samples, the interactive experience also needs to be improved. RESULTS: Here we introduce MRMPro, a web-based MRM data analysis platform for efficient manual inspection. MRMPro supports data analysis of MRM and schedule MRM data acquired by mass spectrometers of mainstream vendors. With the goal of improving the speed of manual inspection, we implemented a collaborative review system based on cloud architecture, allowing multiple users to review through browsers. To reduce bandwidth usage and improve data retrieval speed, we proposed a MRM data compression algorithm, which reduced data volume by more than 60% and 80% respectively compared to vendor and mzML format. To improve the efficiency of manual inspection, we proposed a retention time drift estimation algorithm based on similarity of chromatograms. The estimated retention time drifts were then used for peak alignment and automatic EIC grouping. Compared with Skyline, MRMPro has higher quantification accuracy and better manual inspection support. CONCLUSIONS: In this study, we proposed MRMPro to improve the usability of manual calibration for MRM data analysis. MRMPro is free for non-commercial use. Researchers can access MRMPro through http://mrmpro.csibio.com/ . All major mass spectrometry formats (wiff, raw, mzML, etc.) can be analyzed on the platform. The final identification results can be exported to a common.xlsx format for subsequent analysis.

Early Diagnosis and Prognosis Prediction of Pancreatic Cancer Using Engineered Hybrid Core-Shells in Laser Desorption/Ionization Mass Spectrometry.

Effective detection of bio-molecules relies on the precise design and preparation of materials, particularly in laser desorption/ionization mass spectrometry (LDI-MS). Despite significant advancements in substrate materials, the performance of single-structured substrates remains suboptimal for LDI-MS analysis of complex systems. Herein, designer Au@SiO2@ZrO2 core-shell substrates are developed for LDI-MS-based early diagnosis and prognosis of pancreatic cancer (PC). Through controlling Au core size and ZrO2 shell crystallization, signal amplification of metabolites up to 3 orders is not only achieved, but also the synergistic mechanism of the LDI process is revealed. The optimized Au@SiO2@ZrO2 enables a direct record of serum metabolic fingerprints (SMFs) by LDI-MS. Subsequently, SMFs are employed to distinguish early PC (stage I/II) from controls, with an accuracy of 92%. Moreover, a prognostic prediction scoring system is established with enhanced efficacy in predicting PC survival compared to CA19-9 (p < 0.05). This work contributes to material-based cancer diagnosis and prognosis.

Diagnosis of Esophageal Squamous Cell Carcinoma by High-Performance Serum Metabolic Fingerprints: A Retrospective Study.

Esophageal squamous cell carcinoma (ESCC) is a highly prevalent and aggressive malignancy, and timely diagnosis of ESCC contributes to an increased cancer survival rate. However, current detection methods for ESCC mainly rely on endoscopic examination, limited by a relatively low participation rate. Herein, ferric-particle-enhanced laser desorption/ionization mass spectrometry (FPELDI MS) is utilized to record the serum metabolic fingerprints (SMFs) from a retrospective cohort (523 non-ESCC participants and 462 ESCC patients) to build diagnostic models toward ESCC. The PFELDI MS achieved high speed (≈30 s per sample), desirable reproducibility (coefficients of variation < 15%), and high throughput (985 samples with ≈124 200 data points for each spectrum). Desirable diagnostic performance with area-under-the-curves (AUCs) of 0.925-0.966 is obtained through machine learning of SMFs. Further, a metabolic biomarker panel is constructed, exhibiting superior diagnostic sensitivity (72.2-79.4%, p < 0.05) as compared with clinical protein biomarker tests (4.3-22.9%). Notably, the biomarker panel afforded an AUC of 0.844 (95% confidence interval [CI]: 0.806-0.880) toward early ESCC diagnosis. This work highlighted the potential of metabolic analysis for accurate screening and early detection of ESCC and offered insights into the metabolic characterization of diseases including but not limited to ESCC.

Extraction of pectins from renewable grapefruit (Citrus paradisi) peels using deep eutectic solvents and analysis of their structural and physicochemical properties.

This study presents an innovative attempt to extract high-quality pectins from grapefruit (Citrus paradisi) peels by using deep eutectic solvents (DESs) as extraction agents. The maximum yield of betaine-citric acid (BC)-extracted pectin (BC-P) reached 36.47 % under the optimum process conditions: an L/S ratio of 25 mL/g, a pH of 2.0, and a temperature of 85 °C for 120 min. The yield of BC-P was significantly higher than HCl-extracted pectin (HCl-P, 8.76 %) under a pH of 2.0. In addition, the structural, physicochemical, and emulsifying properties of the purified pectins (BC-P and HCl-P) and commercial pectin (CP) were comparatively analyzed. Results showed that BC-P exhibited higher RG-I value, more arabinan side-chains, bigger Mw and Mn value than HCl-P. Moreover, the viscosity, G' and G'' of BC-P were significantly higher than those of HCl-P and CP. More importantly, BC-P demonstrated better emulsifying activity and stability compared to HCl-P and CP. When the concentration of BC-P was increased to 1.50 %, a stable emulsion containing a 50 % soybean oil fraction could be obtained. Our results confirmed that DESs can be considered as high-effective agents for pectin extraction. Pectins extracted from grapefruit peels can be as a promising natural emulsifiers that can be used in the food industry.

Injectiondesign: web service of plate design with optimized stratified block randomization for modern GC/LC-MS-based sample preparation.

BACKGROUND: Plate design is a necessary and time-consuming operation for GC/LC-MS-based sample preparation. The implementation of the inter-batch balancing algorithm and the intra-batch randomization algorithm can have a significant impact on the final results. For researchers without programming skills, a stable and efficient online service for plate design is necessary. RESULTS: Here we describe InjectionDesign, a free online plate design service focused on GC/LC-MS-based multi-omics experiment design. It offers the ability to separate the position design from the sequence design, making the output more compatible with the requirements of a modern mass spectrometer-based laboratory. In addition, it has implemented an optimized block randomization algorithm, which can be better applied to sample stratification with block randomization for an unbalanced distribution. It is easy to use, with built-in support for common instrument models and quick export to a worksheet. CONCLUSIONS: InjectionDesign is an open-source project based on Java. Researchers can get the source code for the project from Github: https://github.com/CSi-Studio/InjectionDesign . A free web service is also provided: http://www.injection.design .

G-Aligner: a graph-based feature alignment method for untargeted LC-MS-based metabolomics.

BACKGROUND: Liquid chromatography-mass spectrometry is widely used in untargeted metabolomics for composition profiling. In multi-run analysis scenarios, features of each run are aligned into consensus features by feature alignment algorithms to observe the intensity variations across runs. However, most of the existing feature alignment methods focus more on accurate retention time correction, while underestimating the importance of feature matching. None of the existing methods can comprehensively consider feature correspondences among all runs and achieve optimal matching. RESULTS: To comprehensively analyze feature correspondences among runs, we propose G-Aligner, a graph-based feature alignment method for untargeted LC-MS data. In the feature matching stage, G-Aligner treats features and potential correspondences as nodes and edges in a multipartite graph, considers the multi-run feature matching problem an unbalanced multidimensional assignment problem, and provides three combinatorial optimization algorithms to find optimal matching solutions. In comparison with the feature alignment methods in OpenMS, MZmine2 and XCMS on three public metabolomics benchmark datasets, G-Aligner achieved the best feature alignment performance on all the three datasets with up to 9.8% and 26.6% increase in accurately aligned features and analytes, and helped all comparison software obtain more accurate results on their self-extracted features by integrating G-Aligner to their analysis workflow. G-Aligner is open-source and freely available at https://github.com/CSi-Studio/G-Aligner under a permissive license. Benchmark datasets, manual annotation results, evaluation methods and results are available at https://doi.org/10.5281/zenodo.8313034 CONCLUSIONS: In this study, we proposed G-Aligner to improve feature matching accuracy for untargeted metabolomics LC-MS data. G-Aligner comprehensively considered potential feature correspondences between all runs, converting the feature matching problem as a multidimensional assignment problem (MAP). In evaluations on three public metabolomics benchmark datasets, G-Aligner achieved the highest alignment accuracy on manual annotated and popular software extracted features, proving the effectiveness and robustness of the algorithm.

Column storage enables edge computation of biological big data on 5G networks.

With the continuous improvement of biological detection technology, the scale of biological data is also increasing, which overloads the central-computing server. The use of edge computing in 5G networks can provide higher processing performance for large biological data analysis, reduce bandwidth consumption and improve data security. Appropriate data compression and reading strategy becomes the key technology to implement edge computing. We introduce the column storage strategy into mass spectrum data so that part of the analysis scenario can be completed by edge computing. Data produced by mass spectrometry is a typical biological big data based. A blood sample analysed by mass spectrometry can produce a 10 gigabytes digital file. By introducing the column storage strategy and combining the related prior knowledge of mass spectrometry, the structure of the mass spectrum data is reorganized, and the result file is effectively compressed. Data can be processed immediately near the scientific instrument, reducing the bandwidth requirements and the pressure of the central server. Here, we present Aird-Slice, a mass spectrum data format using the column storage strategy. Aird-Slice reduces volume by 48% compared to vendor files and speeds up the critical computational step of ion chromatography extraction by an average of 116 times over the test dataset. Aird-Slice provides the ability to analyze biological data using an edge computing architecture on 5G networks.

Case report: Short-term efficacy and changes in 18F-FDG-PET with acute multi-target stimulation in spinocerebellar ataxia type 3 (SCA3/MJD).

Objective: Spinocerebellar ataxia type 3 (SCA3), also known as Machado-Joseph disease (MJD), is a rare neurodegenerative disease for which there is no specific treatment. Very few cases have been treated with single-target deep brain stimulation (DBS), and the results were not satisfactory. We applied multi-target DBS to an SCA3/MJD patient and performed positron emission computed tomography (PET) before and after DBS to explore the short-term clinical therapeutic effect. Materials and methods: A 26-year-old right-hand-dominant female with a family history of SCA3/MJD suffered from cerebellar ataxia and dystonia. Genetic testing indicated an expanded CAG trinucleotide repeat in the ATXN3 gene and a diagnosis of SCA3/MJD. Conservative treatment had no obvious effect; therefore, leads were implanted in the bilateral dentate nucleus (DN) and the globus pallidus internus (GPi) and connected to an external stimulation device. The treatment effect was evaluated in a double-blind, randomized protocol in five phases (over a total of 15 days): no stimulation, GPi, DN, or sham stimulation, and combined GPi and DN stimulation. 18F-fluoro-2-deoxy-d-glucose and dopamine transporter PET, Scale for the Assessment and Rating of Ataxia, Fahn-Tolosa-Marin Clinical Rating Scale for Tremor (FTM), Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS), and SF-36 quality of life scores were compared before and after DBS. Results: The Total Scale for the Assessment and Rating of Ataxia scores improved by ~42% (from 24 to 14). The BFMDRS movement scores improved by ~30% (from 40.5 to 28.5). The BFMDRS disability scores improved by ~12.5% (from 16 to 14). Daily living activities were not noticeably improved. Compared with the findings in pre-DBS imaging, 18F-fluoro-2-deoxy-d-glucose uptake increased in the cerebellum, while according to dopamine transporter imaging, there were no significant differences in the bilateral caudate nucleus and putamen. Conclusion: Multi-target acute stimulation (DN DBS and GPi DBS) in SCA3/MJD can mildly improve cerebellar ataxia and dystonia and increase cerebellar metabolism.

One-year direct and indirect costs of ischaemic stroke in China.

BACKGROUND: This is the first real-world study to estimate the direct costs and indirect costs of first-ever ischaemic stroke with 1-year follow-up in China, based on a nationally representative sample. METHODS: Patients were chosen from 20 geographically diverse sites from the nationally representative database China National Stroke Registry-III (CNSR-III). The inclusion criteria were surviving patients who were hospitalised with first-ever ischaemic stroke from February 2017 to February 2018 (the index event); aged 18-80 during the index event; no history of other stroke types. The primary endpoints were direct medical costs, direct non-medical costs, indirect costs and total cost (ie, the sum of all cost components). Patient characteristics and clinical data were extracted from CNSR-III. Stroke-related in-hospital direct medical costs were collected from hospital electronic medical records. The patient survey collected data related to out-of-hospital direct medical costs, direct non-medical costs and indirect costs. The secondary objective was to explore clinical factors associated with cost outcomes through univariate analysis and multiple regression. RESULTS: The study enrolled 520 patients. The total cost was 57 567.48 CNY, with 26 612.67 CNY direct medical costs, 2 787.56 CNY direct non-medical costs and 28 167.25 CNY indirect costs. Univariate analysis showed that longer lengths of stay during the index event, higher National Institutes of Health Stroke Scale (NIHSS) and modified Rankin Scale scores were associated with higher costs in all categories. Conversely, EuroQol 5 Dimension utility scores were associated with decreased costs except direct non-medical costs. Multiple regressions showed that higher admission NIHSS scores were independently associated with higher direct medical costs, indirect costs and total cost. Higher 3-month utilities were associated with lower total cost. CONCLUSION: This real-world study showed substantial 1-year economic burden following first-ever ischaemic stroke in China, and that indirect costs are a non-negligible driver of costs.