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The harvest moisture content (MC) of maize (Zea mays L.) is an important factor affecting industrial processing and harvest quality. However, higher MC levels may escalate drying expenses during production. While augmented plant density has shown potential to enhance maize yield, limited information exists regarding its impact on plant density and MC interaction. This study amassed four year of field trial data from four primary maize ecological areas in China (Longitude: 89°E to 125°E, Latitude: 35°N to 44°N) to examine the relationship between plant density and MC of maize. Our analysis revealed that increasing plant density exerted an effect on the MC of maize. This effect stemmed from a combination of uncertain grain development and premature plant senescence due to overcrowding. We categorized the relationship between plant density and MC into six types: NC-Type (No-changing), I-Type (ever-increasing), L-Type (ever-lessening), V-Type (like the valley), P-Type (like the peak), and W-Type (like a wave). On average, a variation approximately 0.053 % in MC was observed when the plant population changed by 1000 plants/ha. Moreover, different maize varieties contributed to a more substantial variation in MC. Despite the negligible impact of MC variation caused by plant density on grain quality, subsequent harvest management, and industrial production of maize, there was a significant enhancement in maize yield with increased plant density. Thus, increasing plant density presents an opportunity to boost maize output without compromising quality or grain moisture levels.

Abstract Objective Osteonecrosis of the femoral head (ONFH) is a severe disease that primarily affects the middle-aged population, imposing a significant economic and social burden. Recent research has linked the progression of non-traumatic osteonecrosis of the femoral head (NONFH) to the composition of the gut microbiota. Steroids and alcohol are considered major contributing factors. However, the relationship between NONFH caused by two etiologies and the microbiota remains unclear. In this study, we examined the gut microbiota and fecal metabolic phenotypes of two groups of patients, and analyzed potential differences in the pathogenic mechanisms from both the microbial and metabolic perspectives. Methods Utilizing fecal samples from 68 NONFH patients (32 steroid-induced, 36 alcohol-induced), high-throughput 16 S rDNA sequencing and liquid chromatography with tandem mass spectrometry (LC-MS/MS) metabolomics analyses were conducted. Univariate and multivariate analyses were applied to the omics data, employing linear discriminant analysis effect size to identify potential biomarkers. Additionally, functional annotation of differential metabolites and associated pathways was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Subsequently, Spearman correlation analysis was employed to assess the potential correlations between differential gut microbiota and metabolites. Results High-throughput 16 S rDNA sequencing revealed significant gut microbial differences. At the genus level, the alcohol group had higher Lactobacillus and Roseburia, while the steroid group had more Megasphaera and Akkermansia. LC-MS/MS metabolomic analysis indicates significant differences in fecal metabolites between steroid- and alcohol-induced ONFH patients. Alcohol-induced ONFH (AONFH) showed elevated levels of L-Lysine and Oxoglutaric acid, while steroid-induced ONFH(SONFH) had increased Gluconic acid and Phosphoric acid. KEGG annotation revealed 10 pathways with metabolite differences between AONFH and SONFH patients. Correlation analysis revealed the association between differential gut flora and differential metabolites. Conclusions Our results suggest that hormones and alcohol can induce changes in the gut microbiota, leading to alterations in fecal metabolites. These changes, driven by different pathways, contribute to the progression of the disease. The study opens new research directions for understanding the pathogenic mechanisms of hormone- or alcohol-induced NONFH, suggesting that differentiated preventive and therapeutic approaches may be needed for NONFH caused by different triggers.

Homidia cingula Börner, 1906, the type species of the genus Homidia Börner, 1906, is widespread from India to Southeast Asia, but its detailed morphological characteristics have not yet been described. We examined the morphology of specimens of H. cingula from Indonesia and southwestern China and confirmed their conspecific status by comparing their DNA barcoding sequences. We also compared the morphology of H. cingula with other two closely related species, confirming the valid species status of H. subcingula Denis, 1948. Our study provides new taxonomic and molecular data for the genus Homidia.

Abstract Background In the United States, the National Alzheimer’s Coordinating Center (NACC) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI) are two major data sharing resources for Alzheimer’s Disease (AD) research. NACC and ADNI strive to make their data more FAIR (findable, interoperable, accessible and reusable) for the broader research community. However, there is limited work harmonizing and supporting cross-cohort interoperability of the two resources. Method In this paper, we leverage an ontology-based approach to harmonize data elements in the two resources and develop a web-based query system to search patient cohorts across the two resources. We first mapped data elements across NACC and ADNI, and performed value harmonization for the mapped data elements with inconsistent permissible values. Then we built an Alzheimer’s Disease Data Element Ontology (ADEO) to model the mapped data elements in NACC and ADNI. We further developed a prototype cross-cohort query system to search patient cohorts across NACC and ADNI. Results After manual review, we found 172 mappings between NACC and ADNI. These 172 mappings were further used to construct common concepts in ADEO. Our data element mapping and harmonization resulted in five files storing common concepts, variables in NACC and ADNI, mappings between variables and common concepts, permissible values of categorical type data elements, and coding inconsistency harmonization, respectively. Our cross-cohort query system consists of three core architectural elements: a web-based interface, an advanced query engine, and a backend MongoDB database. Conclusions In this work, ADEO has been specifically designed to facilitate data harmonization and cross-cohort query of NACC and ADNI data resources. Although our prototype cross-cohort query system was developed for exploring NACC and ADNI, its backend and frontend framework has been designed and implemented to be generally applicable to other domains for querying patient cohorts from multiple heterogeneous data sources.

Fast neutron absorption spectroscopy is widely used in the study of nuclear structure and element analysis. However, due to the traditional neutron source pulse duration being of the order of nanoseconds, it is difficult to obtain a high-resolution absorption spectrum. Thus, we present a method of ultrahigh energy-resolution absorption spectroscopy via a high repetition rate, picosecond duration pulsed neutron source driven by a terawatt laser. The technology of single neutron count is used, which results in easily distinguishing the width of approximately 20 keV at 2 MeV and an asymmetric shape of the neutron absorption peak. The absorption spectroscopy based on a laser neutron source has one order of magnitude higher energy-resolution power than the state-of-the-art traditional neutron sources, which could be of benefit for precisely measuring nuclear structure data.

Objective Leucocyte esterase (LE) strip test is the most rapid, convenient, and cheap method to diagnose chronic periprosthesis joint infection (PJI). However, the determination of LE strip mainly relies on colorimetric method with strong subjectivity, which leads to low diagnostic accuracy. Therefore, we try to convert LE strip images into digital data through the RGB photometric system to achieve objective diagnosis. This method will greatly improve the accuracy of LE strip detection and diagnosis of PJI. Methods From January 2021 to September 2021, 46 patients with suspected PJI after total hip and knee arthroplasty underwent diagnostic joint puncture. After effective joint fluid samples were harvested, they were divided into original fluid and centrifuged fluid for LE strip detection. Real‐time images of LE strip were taken at 90 s, 3 min, 5 min, 10 min, and 15 min after sampling, and their brightness (Y) was obtained after they were input into an RGB photometric system. Grouping was based on centrifugation, infection, and time points, and then the differences in brightness among groups were compared. The correlation between LE strip image brightness and WBC count was evaluated. Student t‐test was used for the parametric data and chi‐square test for qualitative data. Simple linear regression was utilized to analyze the correlation between brightness and WBC count in each group. Results Included were 19 cases of PJI and 27 Non‐PJI subjects diagnosed against ICM2018 diagnostic criteria. The brightness was lower in the PJI group than in Non‐PJI group (p

Objective Imaging measurements allow assessment of the mechanical alignment before and after total knee arthroplasty (TKA). The changes in radiographic parameters in each period of time within 1 year after TKA has been poorly understood. The purpose of this study was to examine the timing and causes of imaging changes in lower extremity force lines after total knee arthroplasty with mechanical alignment. Methods A total of 93 mechanically‐aligned TKA were radiographically examined before, 3 days, 3 months, and 1 year after surgery. Radiographic parameters included hip‐knee angle (HKA), lateral distal femoral angle (LDFA), medial proximal tibial angle (MPTA), knee joint line orientation (KJLO), ankle joint line orientation (AJLO), the knee joint line relative to ankle joint line angle (KJLTA) and midpoints of the ankle distance (MAD). Paired t‐test were used to analyze the changes of these imaging parameters, By establishing a simple tibial model, the time points of changes in the imaging parameters after TKA was determined, with an attempt to understand the post‐TKA changes in these imaging parameters. Results Statistically significant differences were found between the preoperative data and the data measured 3 days after surgery in HKA, LDFA, MPTA, MAD, KJLTA, AJLO (P 0.05). Significant differences were revealed between the data measured 3 months and those collected 1 year after surgery in LDFA, MPTA, AJLO, KJLTA (P 0.05). The tibial model was made to look into the changes in postoperative imaging parameters. ΔMAD and postoperative AJLO were calculated to verify the model and hypothesis. Conclusions Postoperative changes in radiographic parameters and tibial models showed that the lower extremities were in an unnatural state within 1 year after TKA. The changes in the lower extremities force line were the results of the gradual adaptation of the lower extremities to TKA and the lateral swing of the extremities (3°) after surgery. Imaging data 1 year after surgery should be taken into account in the explanation of post‐TKA changes in lower limb force lines.

Abstract Background and Aim Ropeginterferon alfa‐2b is a novel mono‐pegylated, extra‐long‐acting interferon. It is administered infrequently and showed good tolerability and clinical activity for the chronic hepatitis B or C treatment in our previous Phase 2 clinical trials. This study aims to validate the potency and safety of this novel agent in a Phase 3 chronic viral hepatitis setting. Methods Patients with chronic hepatitis C genotype 2 were randomized to receive subcutaneous injections of ropeginterferon alfa‐2b biweekly or the conventional pegylated interferon alfa‐2b weekly for 24 weeks, combined with ribavirin. The primary endpoint was to assess the safety and antiviral potency of ropeginterferon alfa‐2b by the non‐inferiority in sustained virologic response at 12 weeks after treatment. Results A total of 222 patients were enrolled. Ropeginterferon alfa‐2b group showed a favorable safety profile. Side effects that were generally associated with prior interferon therapies, including neutropenia, asthenia, fatigue, alopecia, dizziness, decreased appetite, nausea, flu‐like symptoms including myalgia, pyrexia, and headache, and administration site reactions, were notably less in the ropeginterferon alfa‐2b group. The cumulative incidence of adverse events of special interest was also notably higher in the control group. The primary endpoint was met and ropeginterferon alfa‐2b showed a better SVR12 rate of 79.8% than 71.9% of the control group. Conclusion Ropeginterferon alfa‐2b is efficacious and has a favorable safety profile as compared with the conventional pegylated interferon alfa‐2b. This study together with previous Phase 2 data validated ropeginterferon alfa‐2b to be a new treatment option for chronic hepatitis C genotype 2.

Abstract Objective Minimal invasive approach has been increasingly used in total knee arthroplasty (TKA) and more is expected of early rehabilitation in terms of pain release and recovery of knee function. The approach type is one of the major factors that determines the early rehabilitation after TKA. The purpose of this study is to determine whether mini‐subvastus approach (MSVA) is superior to the traditional medial parapatellar approach (MPA) in TKA. Methods From 2018 to 2019, a randomized double‐blinded prospective study was conducted on 58 patients who underwent simultaneous bilateral TKA. The subjects included eight men and 50 women, with an average age of 65 years. One side was randomized using MSVA and the other side using MPA. Visual analog scale (VAS), operative duration, recovery time to straight leg raising (SLR), range of motion (ROM), HSS score, release rate of lateral retinaculum, satisfaction rate were recorded and compared. Paired‐samples T test were used for quantitative data and chi‐square test for qualitative data. Results There was no statistical difference in the ratio of left and right sides, preoperative ROM, VAS, HSS score, muscular strength of lower limbs, KL grade, operative order, and operative duration between the two groups. The average ROM (118.91 ± 8.21 vs. 107.60 ± 7.99, t = 14.320, p = 0.0000) and HSS score (72.03 ± 4.55 vs. 61.22 ± 4.36, t = 13.095, p = 0.0000) on POD 3, VAS in rest and motion on POD 1 and 3, the recovery time to SLR (1.17 ± 0.38 vs. 3.09 ± 0.76, t = 19.902, p = 0.0000), and the satisfaction rate on POD 1 (96.55% vs. 74.14%, χ2 = 9.9251, p = 0.0016) were superior in the MSVA group over MPA group. ROM in rest and motion and HSS score on POD 30 had no difference. The release rate of lateral retinaculum was less in the MSVA group than in the MPA group. The mean value of HKA, FFC, and FTC and the proportion of outliers did not differ significantly between the two groups. Conclusions Compared with MPA, MSVA can make ROM of knee and SLR recover earlier, reduce postoperative pain after TKA, improve the early postoperative satisfaction and reduce the lateral release rate. MSVA can be used as a favorable measure in the concept of enhanced recovery after surgery (ERAS).

Aphidoletes aphidimyza is a predator that is an important biological agent used to control agricultural and forestry aphids. Although many studies have investigated its biological and ecological characteristics, few molecular studies have been reported. The current study was performed to identify suitable reference genes to facilitate future gene expression and function analyses via quantitative reverse transcription PCR. Eight reference genes glyceraldehyde-3-phosphate dehydrogenase (GAPDH), RPS13, RPL8, RPS3, α-Tub, β-actin, RPL32, and elongation factor 1 alpha (EF1-α) were selected. Their expression levels were determined under four different experimental conditions (developmental stages, adult tissues, sugar treatment, and starvation treatment) using qRT-PCR technology. The stability was evaluated with five methods (Ct value, geNorm, NormFinder, BestKeeper, and RefFinder). The results showed that GAPDH, RPL32, and EF1-α were ranked as the best reference gene combinations for measuring gene expression levels among different developing stages and in various starvation treatments. RPL8 and RPS3 were recommended to normalize the gene expression levels among different adult tissues. RPL32, β-actin, and EF1-α were recommended sugar-feeding conditions. To validate the utility of the selected reference pair, RPL8, and RPS3, we estimated the tissue-biased expression level of a chemosensory protein gene (AaphCSP1). As expected, AaphCSP1 is highly expressed in the antennae and lowly expressed in the abdomen. These findings will lay the foundation for future research on the molecular physiology and biochemistry of A. aphidimyza.

Abstract Background Over the last decade, computational sciences have contributed immensely to characterization of phenotypes of airway diseases, but it is difficult to compare derived phenotypes across studies, perhaps as a result of the different decisions that fed into these phenotyping exercises. We aim to perform a systematic review of studies using computational approaches to phenotype obstructive airway diseases in children and adults. Methods and analysis We will search PubMed, Embase, Scopus, Web of Science, and Google Scholar for papers published between 2010 and 2020. Conferences proceedings, reference list of included papers, and experts will form additional sources of literature. We will include observational epidemiological studies that used a computational approach to derive phenotypes of chronic airway diseases, whether in a general population or in a clinical setting. Two reviewers will independently screen the retrieved studies for eligibility, extract relevant data, and perform quality appraisal of included studies. A third reviewer will arbitrate any disagreements in these processes. Quality appraisal of the studies will be undertaken using the Effective Public Health Practice Project quality assessment tool. We will use summary tables to describe the included studies. We will narratively synthesize the generated evidence, providing critical assessment of the populations, variables, and computational approaches used in deriving the phenotypes across studies Conclusion As progress continues to be made in the area of computational phenotyping of chronic obstructive airway diseases, this systematic review, the first on this topic, will provide the state of the art on the field and highlight important perspectives for future works. Ethics and dissemination No ethical approval is needed for this work is based only on the published literature and does not involve collection of any primary or human data. Registration and reporting Systematic review registration PROSPERO CRD42020164898

The incidence and mortality of cancer are gradually increasing. The highly invasive and metastasis of tumor cells increase the difficulty of diagnosis and treatment, so people pay more and more attention to the diagnosis and treatment of cancer. Conventional treatment methods, including surgery, radiotherapy and chemotherapy, are difficult to eliminate tumor cells completely. And the emergence of nanotechnology has boosted the efficiency of tumor diagnosis and therapy. Herein, the research progress of nanotechnology used for tumor diagnosis and treatment is reviewed, and the emerging detection technology and the application of nanodrugs in clinic are summarized and prospected. The first part refers to the application of different nanomaterials for imaging in vivo and detection in vitro, which includes magnetic resonance imaging, fluorescence imaging, photoacoustic imaging and biomarker detection. The distinctive physical and chemical advantages of nanomaterials can improve the detection sensitivity and accuracy to achieve tumor detection in early stage. The second part is about the nanodrug used in clinic for tumor treatment. Nanomaterials have been widely used as drug carriers, including the albumin paclitaxel, liposome drugs, mRNA-LNP, protein nanocages, micelles, membrane nanocomplexes, microspheres et al., which could improve the drug accumulate in tumor tissue through enhanced permeability and retention effect to kill tumor cells with high efficiency. But there are still some challenges to revolutionize traditional tumor diagnosis and anti-drug resistance based on nanotechnology.

PurposeEndothelial dysfunction, which was associated with chronic hypothyroidism, was an early event in atherosclerosis. Whether short-term hypothyroidism following thyroxine withdrawal during radioiodine (RAI) therapy was associated with endothelial dysfunction in patients with differentiated thyroid cancer (DTC) was unclear. Aim of the study was to assess whether short-term hypothyroidism could impair endothelial function and the accompanied metabolic changes in the whole process of RAI therapy.MethodsWe recruited fifty-one patients who underwent total thyroidectomy surgery and would accept RAI therapy for DTC. We analyzed thyroid function, endothelial function and serum lipids levels of the patients at three time points: the day before thyroxine withdrawal(P1), the day before 131I administration(P2) and 4-6 weeks after RAI therapy(P3). A high-resolution ultrasound named flow-mediated dilation (FMD) was used to measure endothelial function of the patients.ResultsWe analyzed the changes of FMD, thyroid function and lipids at three time points. FMD(P2) decreased significantly compared to FMD(P1) (P1vsP2, 8.05 ± 1.55vs 7.26 ± 1.50, p

Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential to manipulate cell types in controlled ways and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data-generating centers, data archives, and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization. Emphasis of the BICCN is on the whole mouse brain with demonstration of prototype feasibility for human and nonhuman primate (NHP) brains. Here, we provide a guide to the cellular and spatial approaches employed by the BICCN, and to accessing and using these data and extensive resources, including the BRAIN Cell Data Center (BCDC), which serves to manage and integrate data across the ecosystem. We illustrate the power of the BICCN data ecosystem through vignettes highlighting several BICCN analysis and visualization tools. Finally, we present emerging standards that have been developed or adopted toward Findable, Accessible, Interoperable, and Reusable (FAIR) neuroscience. The combined BICCN ecosystem provides a comprehensive resource for the exploration and analysis of cell types in the brain. Characterizing cellular diversity is necessary to understand the function of different cell types in the brain. This Consensus View provides a guide to the cellular and spatial approaches used in cell type surveys by the BRAIN Initiative Cell Census Network (BICCN), as well as information on accessing and using the BICCN data and its extensive resources.

Abstract Background The purpose of this study was to compare the serum inflammatory indicators and radiographic results of conventional manual total knee arthroplasty (CM-TKA) with those of MAKO-robotic assisted total knee arthroplasty (MA-TKA). Methods We retrospectively analysed 65 patients with knee osteoarthritis who underwent unilateral TKA from December 2020 to November 2021 in our department, which included 34 patients who underwent MA-TKA and 31 patients who underwent CM-TKA. The tourniquet time and estimated blood loss (EBL) were compared between the two groups. Knee function was evaluated using range of motion (ROM), functional score and pain score. Leukocytes, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), interleukin-6 (IL-6), creatine kinase (CK), and neutrophil-to-lymphocyte ratio (NLR) were recorded at 3 time points (preoperative, and on the first and third postoperative days). The hip-knee-ankle angle (HKA) and the femoral and tibial component angles in the coronal and sagittal planes were used for postoperative radiographic evaluation. Results The postoperative MA-TKA group had less EBL (496.9 ± 257.8 vs. 773.0 ± 301.3 ml, p 0.05). IL-6 levels were significantly lower in the MA-TKA group on the 1st postoperative day (11.4 (5.2, 21.0) vs. 24.6 (86.3, 170.8), p = 0.031). This difference in inflammatory indices became more pronounced at 72 hours after the operation because CRP, ESR, IL-6, and CK values were significantly lower in the MA-TKA group on the 3rd postoperative day (72 h) (p 0.05). Conclusions In Chinese patients with OA, there was a milder systemic inflammatory response in the early postoperative period after MA-TKA compared to that of CM-TKA, as well as better radiographic outcomes. However, the tourniquet time was prolonged, and no advantages were observed in terms of functional score or pain score in the short-term follow-up.

Abstract Detection and imaging of α‐L‐fucosidase (AFU) is of great value to understand its roles in hepatocellular carcinoma (HCC) and tumor early diagnosis, but ideal assays are still lacking. Herein, a near‐infrared (NIR) fluorescent biosensor (α‐Fuc‐DCM) was elaborately designed and synthesized for rapid and ratiometric detection of AFU activity in cells and HCC tumor mouse models. In the presence of AFU, this biosensor shows an enhancement in NIR emission in a ratiometric manner, which significantly improves the detection accuracy with the limit of detection as low as 4.8 mU/mL. Taking advantage of these merits, the activity of AFU in lysosomes could be visualized using ratiometric and NIR dual modality in living cells. Furthermore, its remarkable application for monitoring of endogenous AFU activity in HCC tumor‐bearing mouse model is also demonstrated with bright fluorescence signal, which indicated that the biosensor could clearly monitor the liver tumor in the early stage. Importantly, the α‐Fuc‐DCM probe can be utilized to detect the AFU in serum from HCC patients. This strategy offers a promising biosensor system for early diagnosis of HCC and studying the roles of AFU in cancers.

Cymbidium, which includes approximately 80 species, is one of the most ornamental and cultivated orchid genera. However, a lack of markers and sparse sampling have posed great challenges to resolving the phylogenetic relationships within the genus. In the present study, we reconstructed the phylogenetic relationships by utilizing one nuclear DNA (nrITS) and seven plastid genes (rbcL, trnS, trnG, matK, trnL, psbA, and atpI) from 70 species (varieties) in Cymbidium. We also examined the occurrence of phylogenetic conflict between nuclear (nrITS) and plastid loci and investigated how phylogenetic conflict bears on taxonomic classification within the genus. We found that phylogenetic conflict and low support values may be explained by hybridization and a lack of informative characteristics. Our results do not support previous classification of the subgenera and sections within Cymbidium. Discordance between gene trees and network analysis indicate that reticulate evolution occurred in the genus Cymbidium. Overall, our study indicates that Cymbidium has undergone a complex evolution.

Gastrin plays important role in stimulating the initiation and development of many gastrointestinal diseases through interacting with the cholecystokinin 2 receptor (CCK2R). The smallest bioactive unit of gastrin activating CCK2R is the C-terminal tetrapeptide capped with an indispensable amide end. Understanding the mechanism of this smallest bioactive unit interacting with CCK2R on a molecular basis could provide significant insights for designing CCK2R antagonists, which can be used to treat gastrin-related diseases. To this end, we performed extensive Gaussian accelerated molecular dynamics simulations to investigate the interaction between gastrin C-terminal pentapeptide capped with/without amide end and CCK2R. The amide cap influences the binding modes of the pentapeptide with CCK2R by weakening the electrostatic attractions between the C-terminus of the pentapeptide and basic residues near the extracellular domain in CCK2R. The C-terminus with the amide cap penetrates into the transmembrane domain of CCK2R while floating at the extracellular domain without the amide cap. Different binding modes induced different conformational dynamics of CCK2R. Residue pairs in CCK2R had stronger correlated motions when binding with the amidated pentapeptide. Key residues and interactions important for CCK2R binding with the amidated pentagastrin were also identified. Our results provide molecular insights into the determinants of the bioactive unit of gastrin activating CCK2R, which would be of great help for the design of CCK2R antagonists.

Sudden unexpected death of epilepsy (SUDEP) is a catastrophic and fatal complication of epilepsy and is the primary cause of mortality in those who have uncontrolled seizures. While several multifactorial processes have been implicated including cardiac, respiratory, autonomic dysfunction leading to arrhythmia, hypoxia, and cessation of cerebral and brainstem function, the mechanisms underlying SUDEP are not completely understood. Postictal generalized electroencephalogram (EEG) suppression (PGES) is a potential risk marker for SUDEP, as studies have shown that prolonged PGES was significantly associated with a higher risk of SUDEP. Automated PGES detection techniques have been developed to efficiently obtain PGES durations for SUDEP risk assessment. However, real-world data recorded in epilepsy monitoring units (EMUs) may contain high-amplitude signals due to physiological artifacts, such as breathing, muscle, and movement artifacts, making it difficult to determine the end of PGES. In this paper, we present a hybrid approach that combines the benefits of unsupervised and supervised learning for PGES detection using multi-channel EEG recordings. A K-means clustering model is leveraged to group EEG recordings with similar artifact features. We introduce a new learning strategy for training a set of random forest (RF) models based on clustering results to improve PGES detection performance. Our approach achieved a 5-second tolerance-based detection accuracy of 64.92%, a 10-second tolerance-based detection accuracy of 79.85%, and an average predicted time distance of 8.26 seconds with 286 EEG recordings using leave-one-out (LOO) cross-validation. The results demonstrated that our hybrid approach provided better performance compared to other existing approaches.

Nitrogen fertilizer application is an important measure to obtain high and stable corn yield, and the moisture content of corn grains is an important factor affecting the quality of mechanical grain harvesting. In this study, four different nitrogen fertilizer treatments from 0 to 450 kg ha–1 pure nitrogen were set for a planting density of 12.0×104 plants ha–1 in 2017 and 2018, and 18 different nitrogen fertilizer treatments from 0 to 765 kg ha–1 pure nitrogen were set for planting densities of 7.5×104 and 12.0×104 plants ha–1 in 2019, to investigate the effect of nitrogen application rate on the moisture content of corn grains. Under each treatment, the growth of corn, leaf area index (LAI) of green leaves, grain moisture content, and grain dehydration rate were measured. The results showed that, as nitrogen application increased from 0 to 765 kg ha–1, the silking stage was delayed by about 1 day, the maturity stage was delayed by about 1–2 days, and the number of physiologically mature green leaves and LAI increased. At and after physiological maturity, the extreme difference in grain moisture content between different nitrogen application rates was 1.9–4.0%. As the amount of nitrogen application increased, the corn grain dehydration rate after physiological maturity decreased, but it did not reach statistical significance between nitrogen application rate and grain dehydration rate. No significant correlation was observed between LAI at physiological maturity and grain dehydration rate after physiological maturity. In short, nitrogen application affected the grain moisture content of corn at and after physiological maturity, however, the difference in grain moisture content among different nitrogen application rates was small. These results suggest that the effect of nitrogen application on the moisture content of corn grains should not be considered in agricultural production.

Abstract Background Liver injuries have been reported in patients with coronavirus disease 2019 (COVID-19). This study aimed to investigate the clinical role played by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Methods In this multicentre, retrospective study, the parameters of liver function tests in COVID-19 inpatients were compared between various time-points in reference to SARS-CoV-2 shedding, and 3 to 7 days before the first detection of viral shedding was regarded as the reference baseline. Results In total, 70 COVID-19 inpatients were enrolled. Twenty-two (31.4%) patients had a self-medication history after illness. At baseline, 10 (14.3%), 7 (10%), 9 (12.9%), 2 (2.9%), 15 (21.4%), and 4 (5.7%) patients already had abnormal alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), albumin, and total bilirubin (TBIL) values, respectively. ALT and AST abnormal rates and levels did not show any significant dynamic changes during the full period of viral shedding (all p > 0.05). The GGT abnormal rate (p = 0.008) and level (p = 0.033) significantly increased on day 10 of viral shedding. Meanwhile, no simultaneous significant increases in abnormal ALP rates and levels were observed. TBIL abnormal rates and levels significantly increased on days 1 and 5 of viral shedding (all p

Rapid and accurate sensing of β-galactosidase (β-gal) activity is particularly critical for the early detection of many diseases and has become a topic of interest in recent years. However, most traditional probes for β-gal sensing often suffer from the disadvantages of narrow dynamic range, low reaction efficiency and are only employed with either colorimetric or fluorescence sensing. Furthermore, β-galactosidase sensing based assay for efficient detection and antibiotic resistance analysis of Escherichia coli (E.coli) is not available. Here, an enzyme-induced probe assay was reported for dual sensitive fluorescence and colorimetric measurement of β-gal activity, and was further employed for detection of Escherichia coli and their antibiotic resistance analysis. The DCM-βgal probe was virtually non-emissive in aqueous solution, while it could be activated by β-gal to produce bright emission. Under optimized conditions, DCM-βgal displayed high sensitivity, selectivity and rapid response to β-gal with a low detection limit of 1.5 × 10−3 U ml−1. Importantly, this assay was successfully applied to sensitive detection of E. coli cells with a fast detection process within 5 h and a low detection concentration of 1 × 103 CFU ml−1. Furthermore, the enzyme-activatable assay was also successfully applied for high throughput E. coli antibiotic resistance analysis. The DCM-βgal strategy is applied for the first time on the detection of E. coli cells and their antibiotic resistance analysis. It is provided with the advantages of high selectively, a simple operation, low cost and rapid detection. The detection platform can also be extended to analyze the level of β-gal in other types of cells or biological samples. Overall, the simple, effective and dual-readout assay holds promise for efficient sensing of β-gal activity and provides a potential tool for E. coli detection and their antibiotic resistance analysis.

Epilepsy affects ~2–3 million individuals in the United States, a third of whom have uncontrolled seizures. Sudden unexpected death in epilepsy (SUDEP) is a catastrophic and fatal complication of poorly controlled epilepsy and is the primary cause of mortality in such patients. Despite its huge public health impact, with a ~1/1,000 incidence rate in persons with epilepsy, it is an uncommon enough phenomenon to require multi-center efforts for well-powered studies. We developed the Multimodal SUDEP Data Resource (MSDR), a comprehensive system for sharing multimodal epilepsy data in the NIH funded Center for SUDEP Research. The MSDR aims at accelerating research to address critical questions about personalized risk assessment of SUDEP. We used a metadata-guided approach, with a set of common epilepsy-specific terms enforcing uniform semantic interpretation of data elements across three main components: (1) multi-site annotated datasets; (2) user interfaces for capturing, managing, and accessing data; and (3) computational approaches for the analysis of multimodal clinical data. We incorporated the process for managing dataset-specific data use agreements, evidence of Institutional Review Board review, and the corresponding access control in the MSDR web portal. The metadata-guided approach facilitates structural and semantic interoperability, ultimately leading to enhanced data reusability and scientific rigor. MSDR prospectively integrated and curated epilepsy patient data from seven institutions, and it currently contains data on 2,739 subjects and 10,685 multimodal clinical data files with different data formats. In total, 55 users registered in the current MSDR data repository, and 6 projects have been funded to apply MSDR in epilepsy research, including three R01 projects and three R21 projects.

Objective To introduce posteromedial corner release with the knee in the figure‐of‐four position versus the conventional position for varus knee arthroplasty. Methods This is a retrospective study. From March 2015 to September 2019, a series of 123 patients (139 knees) with varus knee were randomly and blindly allocated to experimental group (60 patients; 68 knees) and control group (57 patients; 65 knees). Patients in experimental group underwent posteromedial corner release with the knee in the figure‐of‐four position; and patients in control group with the knee in the conventional position. If soft tissue balance was not completely achieved or the medial gap was still tight, an additional loosening technique were used to achieve symmetric medial and lateral space in both groups. Time for soft tissue balancing was defined as the time from the start of the spacer test to the end of the balance test. Length of release was defined as the distance from the osteotomy surface of the tibial plateau to the farthest structures released. The rating system of Hospital for Special Surgery (HSS) knee score was used to evaluate the clinical results. Quantitative variables were described as mean and standard deviation, and compared by one‐way analysis of variance. Results The mean age of experimental group and control group was 70.2 ± 8.7 years and 68.7 ± 6.2 years, respectively (P > 0.05). Preoperatively, the mean HSS score of the groups was 38.2 ± 11.3 and 39.1 ± 10.7, respectively (P > 0.05). The mean varus knee angle was 19.7° ± 9.3° and 19.3° ± 10.7°, respectively (P > 0.05). The mean time for soft tissue balancing was 8.4 ± 3.3 min and 11.3 ± 6.9 min in experimental and control group, respectively (P 0.05). No complications were found during the follow‐up time, and the clinical symptoms were observed to be significantly improved in the patients. Conclusion The posteromedial corner can be released more extensively and thoroughly when the knee is placed in the figure‐of‐four position during varus knee arthroplasty.

Abstract Background Paphiopedilum is the largest genus of slipper orchids. Previous studies showed that the phylogenetic relationships of this genus are not well resolved, and sparse taxon sampling documented inverted repeat (IR) expansion and small single copy (SSC) contraction of the chloroplast genomes of Paphiopedilum. Results Here, we sequenced, assembled, and annotated 77 plastomes of Paphiopedilum species (size range of 152,130 – 164,092 bp). The phylogeny based on the plastome resolved the relationships of the genus except for the phylogenetic position of two unstable species. We used phylogenetic and comparative genomic approaches to elucidate the plastome evolution of Paphiopedilum. The plastomes of Paphiopedilum have a conserved genome structure and gene content except in the SSC region. The large single copy/inverted repeat (LSC/IR) boundaries are relatively stable, while the boundaries of the inverted repeat and small single copy region (IR/SSC) varied among species. Corresponding to the IR/SSC boundary shifts, the chloroplast genomes of the genus experienced IR expansion and SSC contraction. The IR region incorporated one to six genes of the SSC region. Unexpectedly, great variation in the size, gene order, and gene content of the SSC regions was found, especially in the subg. Parvisepalum. Furthermore, Paphiopedilum provides evidence for the ongoing degradation of the ndh genes in the photoautotrophic plants. The estimated substitution rates of the protein coding genes show accelerated rates of evolution in clpP, psbH, and psbZ. Genes transferred to the IR region due to the boundary shift also have higher substitution rates. Conclusions We found IR expansion and SSC contraction in the chloroplast genomes of Paphiopedilum with dense sampling, and the genus shows variation in the size, gene order, and gene content of the SSC region. This genus provides an ideal system to investigate the dynamics of plastome evolution.

J-aggregation has been proved to be an efficient strategy for the development of fluorescent imaging agents in the NIR-II spectral region but the design of appropriate J-aggregates is challenging. Here, the authors demonstrate J-aggregation of a BODIPY dye with NIR-II emission and demonstrate lymph node imaging for fluorescence guided surgery.

Abstract Background Knee osteoarthritis associated with extra-articular deformity (EAD) can confront the arthroplasty surgeons with challenges of bone resection and soft tissue balancing. The aim of this study was to describe a single-stage procedure associating corrective osteotomy with total knee arthroplasty (TKA), and to determine the outcome at mid- to long-term follow-up. Methods A total of seven patients (seven knees) with knee osteoarthritis and supracondylar deformity were included in this study. Six patients were female, and one was male, with the median age of 62 years (range, 37-76 years). All patients were treated with single-stage TKA and femoral osteotomy. Osteotomy was fixed with long cemented stem. Hospital of Special Surgery (HSS) scores, collateral ligament laxity, and range of motion (ROM) were clinically evaluated preoperatively and at each follow-up. Radiographic parameters including the mechanical axis deviation (MAD), mechanical lateral distal femoral angle (mLDFA), mechanical proximal tibial angle (mMPTA), and joint line congruence angle (JLCA) were also measured. The occurrence of perioperative complications was recorded. Results The median follow-up time was 91 months (range, 38-104 months). At the last follow-up, all components were stable and no patients required revision. Nonunion of the osteotomy occurred in one patient. In all patients, the lower limb mechanical alignment improved greatly. The mean angle of MAD was restored from 10.49±6.05 cm preoperatively to 1.11±4.97 cm postoperatively. The 90° mLDFA was almost acquired in all cases, with the postoperative value of 90.79±2.40°. After operation, the mMPTA improved from 84.18±6.13° to 91.33±3.13°. The JLCA changed from 2.94±1.61° to −0.71±3.50°. The median HSS score improved from 45 (range, 34-56) preoperatively to 90 (range, 82-97) postoperatively, with the outcome of all patients rated good to excellent. The median ROM improved from 70° (range 0–110°) preoperatively to 105° (range 90–125°) postoperatively. No instability of knee joint was observed. Complications included an intraoperative split fracture of distal femur and one case of wound exudation resulting from fat liquefaction. Conclusions For knee osteoarthritis with femoral supracondylar deformity, single-stage TKA and corrective osteotomy was feasible but technically demanding. The use of long cemented stem for osteotomy fixation can provide reliable rotational control of the bone segments.

Background: The incidence and mortality of sepsis are increasing year by year, and there is still a lack of specific biomarkers to predict its prognosis. Prognostic value of vascular endothelial growth factor (VEGF) in predicting the severity and mortality of sepsis has been gradually discovered.Methods: Literature was searched through Embase, PubMed, Web of Science, China National Knowledge Infrastructure(CNKI) and Cochrane Library databases in March 2022. Observational studies, evaluating the impact of VEGF in sepsis outcomes (mortality and severity) are included in this meta-analysis. Risk of bias was assessed with the Newcastle-Ottawa Scale (NOS). Sensitivity and publication bias analyses were also assessed. Meta-regression analysis were performed to identify the potential sources of heterogeneity.Result: A total of 1,574 articles were retrieved from the systematic literature search. We included 20 studies for qualitative and quantitative analysis. Deceased and critically ill patients had higher baseline VEGF levels than survivors and non-severe patients. The pooled sensitivity and specificity for VEGF predicts sepsis mortality were 0.79and 0.76, respectively. the area under the SROC curve was 0.83.Conclusion: High VEGF are associated with poor clinical outcomes for patients diagnosed with sepsis. This study was recorded on PROSPERO, under the registration ID: CRD42022323079.

The patient was a 25-year-old man presented with cutaneous dirt-adherent disease with a past medical history of schizophrenia. Both the patient and his mother had Darier’s disease, genetic screening revealed that the patient carried a heterozygous frameshift mutation in ATP2A2 gene, which was inherited from his mother. Cutis verticis gyrata was also found in the patient.

Abstract Background Convolutional neural network (CNN) has achieved state-of-art performance in many electroencephalogram (EEG) related studies. However, the application of CNN in prediction of risk factors for sudden unexpected death in epilepsy (SUDEP) remains as an underexplored area. It is unclear how the trade-off between computation cost and prediction power varies with changes in the complexity and depth of neural nets. Methods The purpose of this study was to explore the feasibility of using a lightweight CNN to predict SUDEP. A total of 170 patients were included in the analyses. The CNN model was trained using clips with 10-s signals sampled from the original EEG. We implemented Hann function to smooth the raw EEG signal and evaluated its effect by choosing different strength of denoising filter. In addition, we experimented two variations of the proposed model: (1) converting EEG input into an “RGB” format to address EEG channels underlying spatial correlation and (2) incorporating residual network (ResNet) into the bottle neck position of the proposed structure of baseline CNN. Results The proposed baseline CNN model with lightweight architecture achieved the best AUC of 0.72. A moderate noise removal step facilitated the training of CNN model by ensuring stability of performance. We did not observe further improvement in model’s accuracy by increasing the strength of denoising filter. Conclusion Post-seizure slow activity in EEG is a potential marker for SUDEP, our proposed lightweight architecture of CNN achieved satisfying trade-off between efficiently identifying such biomarker and computational cost. It also has a flexible interface to be integrated with different variations in structure leaving room for further improvement of the model’s performance in automating EEG signal annotation.

Abstract Background Sudden Unexpected Death in Epilepsy (SUDEP) has increased in awareness considerably over the last two decades and is acknowledged as a serious problem in epilepsy. However, the scientific community remains unclear on the reason or possible bio markers that can discern potentially fatal seizures from other non-fatal seizures. The duration of postictal generalized EEG suppression (PGES) is a promising candidate to aid in identifying SUDEP risk. The length of time a patient experiences PGES after a seizure may be used to infer the risk a patient may have of SUDEP later in life. However, the problem becomes identifying the duration, or marking the end, of PGES (Tomson et al. in Lancet Neurol 7(11):1021–1031, 2008; Nashef in Epilepsia 38:6–8, 1997). Methods This work addresses the problem of marking the end to PGES in EEG data, extracted from patients during a clinically supervised seizure. This work proposes a sensitivity analysis on EEG window size/delay, feature extraction and classifiers along with associated hyperparameters. The resulting sensitivity analysis includes the Gradient Boosted Decision Trees and Random Forest classifiers trained on 10 extracted features rooted in fundamental EEG behavior using an EEG specific feature extraction process (pyEEG) and 5 different window sizes or delays (Bao et al. in Comput Intell Neurosci 2011:1687–5265, 2011). Results The machine learning architecture described above scored a maximum AUC score of 76.02% with the Random Forest classifier trained on all extracted features. The highest performing features included SVD Entropy, Petrosan Fractal Dimension and Power Spectral Intensity. Conclusion The methods described are effective in automatically marking the end to PGES. Future work should include integration of these methods into the clinical setting and using the results to be able to predict a patient’s SUDEP risk.

Abstract Background The Kentucky Cancer Registry (KCR) is a central cancer registry for the state of Kentucky that receives data about incident cancer cases from all healthcare facilities in the state within 6 months of diagnosis. Similar to all other U.S. and Canadian cancer registries, KCR uses a data dictionary provided by the North American Association of Central Cancer Registries (NAACCR) for standardized data entry. The NAACCR data dictionary is not an ontological system. Mapping between the NAACCR data dictionary and the National Cancer Institute (NCI) Thesaurus (NCIt) will facilitate the enrichment, dissemination and utilization of cancer registry data. We introduce a web-based system, called Interactive Mapping Interface (IMI), for creating mappings from data dictionaries to ontologies, in particular from NAACCR to NCIt. Method IMI has been designed as a general approach with three components: (1) ontology library; (2) mapping interface; and (3) recommendation engine. The ontology library provides a list of ontologies as targets for building mappings. The mapping interface consists of six modules: project management, mapping dashboard, access control, logs and comments, hierarchical visualization, and result review and export. The built-in recommendation engine automatically identifies a list of candidate concepts to facilitate the mapping process. Results We report the architecture design and interface features of IMI. To validate our approach, we implemented an IMI prototype and pilot-tested features using the IMI interface to map a sample set of NAACCR data elements to NCIt concepts. 47 out of 301 NAACCR data elements have been mapped to NCIt concepts. Five branches of hierarchical tree have been identified from these mapped concepts for visual inspection. Conclusions IMI provides an interactive, web-based interface for building mappings from data dictionaries to ontologies. Although our pilot-testing scope is limited, our results demonstrate feasibility using IMI for semantic enrichment of cancer registry data by mapping NAACCR data elements to NCIt concepts.

Abstract Applying machine learning to healthcare sheds light on evidence-based decision making and has shown promises to improve healthcare by combining clinical knowledge and biomedical data. However, medicine and data science are not synchronized. Oftentimes, researchers with a strong data science background do not understand the clinical challenges, while on the other hand, physicians do not know the capacity and limitation of state-of-the-art machine learning methods. The difficulty boils down to the lack of a common interface between two highly intelligent communities due to the privacy concerns and the disciplinary gap. The School of Biomedical Informatics (SBMI) at UTHealth is a pilot in connecting both worlds to promote interdisciplinary research. Recently, the Center for Secure Artificial Intelligence For hEalthcare (SAFE) at SBMI is organizing a series of machine learning healthcare hackathons for real-world clinical challenges. We hosted our first Hackathon themed centered around Sudden Unexpected Death in Epilepsy and finding ways to recognize the warning signs. This community effort demonstrated that interdisciplinary discussion and productive competition has significantly increased the accuracy of warning sign detection compared to the previous work, and ultimately showing a potential of this hackathon as a platform to connect the two communities of data science and medicine.

Abstract Background To explore the kinetic changes in virology, specific antibody response and imaging during the clinical course of COVID-19. Methods This observational study enrolled 20 patients with COVID-19, who were hospitalized between January 20–April 6, 2020, in the two COVID-19 designated hospitals of Zhoushan, Zhejiang and Rushan, Shandong, China, The laboratory findings, imaging, serum response to viral infection, and viral RNA level in the throat and stool samples were assessed from onset to recovery phase in patients with COVID-19. Results SARS-COV-2 RNA was positive as early as day four. It remained positive until day 55 post-onset in the sputum-throat swabs and became negative in most cases (55%) within 14 days after onset. Lymphocytopenia occurred in 40% (8/20) of patients during the peak infection period and returned to normal at week five. The most severe inflammation in the lungs appeared in week 2 or 3 after onset, and this was completely absorbed between week 6 and 8 in 85.7% of patients. All patients had detectable antibodies to the receptor binding domain (RBD), and 95% of these patients had IgG to viral N proteins. The antibody titer peaked at week four. Anti-S IgM was positive in 7 of 20 patients after week three. Conclusions All COVID-19 patients in this study were self-limiting and recovered well though it may take as long as 6–8 weeks. Our findings on the kinetic changes in imaging, serum response to viral infection and viral RNA level may help understand pathogenesis and define clinical course of COVID-19.

The accurate evaluation of maize stalk lodging resistance in different growth periods enables timely management of lodging risks and ensures stable and high maize yields. Here, we established five different sowing dates to create different conditions for maize growth. We evaluated the effects of the different growth conditions on lodging resistance by determining stalk morphology, moisture content, mechanical strength and dry matter, and the relationship between stalk breaking force and these indicators during the silking stage (R1), milk stage (R3), physiological maturity stage (R6), and 20 days after R6. Plant height at R1 positively affected stalk breaking force. At R3, the coefficient of ear height and the dry weight per unit length of basal internodes were key indicators of stalk lodging resistance. At R6, the key indicators were the coefficient of the center of gravity height and plant fresh weight. After R6, the key indicator was the coefficient of the center of gravity height. The crushing strength of the fourth internode correlated significantly and positively with the stalk breaking force from R1 to R6, which indicates that crushing strength is a reliable indicator of stalk mechanical strength. These results suggest that high stalk strength and low ear height benefit lodging resistance prior to R6. During and after R6, the coefficient of the center of gravity height and the mechanical strength of basal internodes can be used to evaluate plant lodging resistance and the appropriate time for harvesting in fields with a high lodging risk.

Abstract Periprosthetic joint infection (PJI) represents one of the most challenging complications after total joint arthroplasty (TJA). Despite the availability of a variety of diagnostic techniques, the diagnosis of PJI remains a challenge due to the lack of well-established diagnostic criteria. The leucocyte esterase (LE) strips test has been proved to be a valuable diagnostic tool for PJI, and its weight in PJI diagnostic criteria has gradually increased. Characterized by its convenience, speed and immediacy, leucocyte esterase strips test has a prospect of broad application in PJI diagnosis. Admittedly, the leucocyte esterase strips test has some limitations, such as imprecision and liability to interference. Thanks to the application of new technologies, such as machine reading, quantitative detection and artificial intelligence, the LE strips test is expected to overcome the limitations and improve its accuracy.

Abstract Background The acetabular distraction technique demonstrates encouraging radiographic and clinical outcomes in treating chronic pelvic discontinuity. The aim of this study is to describe a modified distraction technique and to show our results. Methods This study identified 12 cases of chronic pelvic discontinuity undergoing primary or revision total hip arthroplasty (THA) with the technique of reverse reaming distraction between July 2015 and November 2018. All 12 patients had a minimum follow-up of 12 months. Radiographs were reviewed to inspect for component loosening. Clinical assessment included the Harris hip score (HHS) and an ambulatory scoring system. Results At the time of final follow-up, no patient was revised. One patient had up to 1 cm migration of the cup in a horizontal or vertical direction and more than 20° change in the abduction angle but was asymptomatic. In the remaining 11 patients, no migration of the component was detected. Both the HHS and ambulatory score showed improvement in all patients. There were no perioperative complications. No postoperative dislocation occurred. Conclusions Reverse reaming distraction is a feasible technique in treatment of chronic pelvic discontinuity, with encouraging results at early term. However, ongoing follow-up is required to determine the long-term prognosis in patients receiving this technique.

Orchids constitute approximately 10% of flowering plant species. However, only about 10 orchid genomes have been published. Metabolites are the main way through which orchids respond to their environment. Dendrobium nobile, belonging to Dendrobium, the second largest genus in Orchidaceae, has high ornamental, medicinal, and ecological value. D. nobile is the source of many popular horticultural varieties. Among the Dendrobium species, D. nobile has the highest amount of dendrobine, which is regarded as one of the criteria for evaluating medicinal quality. Due to lack of data and analysis at the genomic level, the biosynthesis pathways of dendrobine and other related medicinal ingredients in D. nobile are unknown. In this paper, we report a chromosome-scale reference genome of D. nobile to facilitate the investigation of its genomic characteristics for comparison with other Dendrobium species. The assembled genome size of D. nobile was 1.19 Gb. Of the sequences, 99.45% were anchored to 19 chromosomes. Furthermore, we identified differences in gene number and gene expression patterns compared with two other Dendrobium species by integrating whole-genome sequencing and transcriptomic analysis [e.g., genes in the polysaccharide biosynthesis pathway and upstream of the alkaloid (dendrobine) biosynthesis pathway]. Differences in the TPS and CYP450 gene families were also found among orchid species. All the above differences might contribute to the species-specific medicinal ingredient biosynthesis pathways. The metabolic pathway-related analysis will provide further insight into orchid responses to the environment. Additionally, the reference genome will provide important insights for further molecular elucidation of the medicinal active ingredients of Dendrobium and enhance the understanding of orchid evolution.

BackgroundMyasthenia gravis (MG) is an autoimmune, neuromuscular condition and patients with MG are vulnerable due to immunosuppressant use and disease manifestations of dyspnea and dysphagia during the coronavirus disease 2019 (COVID-19) pandemic.MethodsWe conducted a retrospective cohort study using the Optum® de-identified COVID-19 Electronic Health Record (EHR) dataset. Primary outcomes, such as hospitalization, ventilator use, intensive care unit (ICU) admission, and death in COVID-19 patients with MG, were compared with those of COVID-19 patients without MG: the subgroups of non-MG included those with rheumatoid arthritis (RA), systemic lupus (SLE), and multiple sclerosis (MS). We further analyzed factors affecting mortality, such as age, race/ethnicity, comorbidities, and MG treatments.ResultsAmong 421,086 individuals with COVID-19, there were 377 patients with MG, 7,362 patients with RA, 1,323 patients with SLE, 1,518 patients with MS, and 410,506 patients without MG. Patients with MG were older and had more comorbidities compared with non-MG patients and had the highest rates of hospitalization (38.5%), ICU admission (12.7%), ventilator use (3.7%), and mortality (10.6%) compared with all other groups. After adjusting for risk factors, patients with MG had increased risks for hospitalization and ICU compared with patients with non-MG and with RA but had risks similar to patients with SLE and with MS. The adjusted risk for ventilator use was similar across all groups, but the risk for mortality in patients with MG was lower compared with the SLE and MS groups. Among patients with MG, age over 75 years and dysphagia were predictors for increased COVID-19 mortality, but the recent MG treatment was not associated with COVID-19 mortality.ConclusionsCOVID-19 patients with MG are more likely to be admitted to the hospital and require ICU care. Older age and patients with dysphagia had an increased risk of mortality.

Summary: Accurate and rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is significant for early tracing, isolation, and treatment of infected individuals, which will efficiently prevent large-scale transmission of coronavirus disease 2019 (COVID-19). Here, two kinds of test strips for receptor binding domain (RBD) and N antigens of SARS-CoV-2 are established with high sensitivity and specificity, in which AIE luminogens (AIEgens) are utilized as reporters. Because of the high brightness and resistance to quenching in aqueous solution, the limit of detection can be as low as 6.9 ng/mL for RBD protein and 7.2 ng/mL for N protein. As an antigen collector, an N95 mask equipped with a test strip with an excellent enrichment effect would efficiently simplify the sampling procedures. Compared with a test strip based on Au nanoparticles or fluorescein isothiocyanate (FITC), the AIEgen-based test strip shows high anti-interference capacity in complex biosamples. Therefore, an AIEgen-based test strip assay could be built as a promising platform for emergency use during the pandemic.

PurposePatients with cancer often have compromised immune system which can lead to worse COVID-19 outcomes. The purpose of this study is to assess the association between COVID-19 outcomes and existing cancer-specific characteristics.Patients and methodsPatients aged 18 or older with laboratory-confirmed COVID-19 between June 1, 2020, and December 31, 2020, were identified (n = 314 004) from the Optum® de-identified COVID-19 Electronic Health Record (EHR) derived from more than 700 hospitals and 7000 clinics in the United States. To allow sufficient observational time, patients with less than one year of medical history in the EHR dataset before their COVID-19 tests were excluded (n = 42 365). Assessed COVID-19 outcomes including all-cause 30-day mortality, hospitalization, ICU admission, and ventilator use, which were compared using relative risks (RRs) according to cancer status and treatments.ResultsAmong 271 639 patients with COVID-19, 18 460 had at least one cancer diagnosis: 8034 with a history of cancer and 10 426 with newly diagnosed cancer within one year of COVID-19 infection. Patients with a cancer diagnosis were older and more likely to be male, white, Medicare beneficiaries, and have higher prevalences of chronic conditions. Cancer patients had higher risks for 30-day mortality (RR 1.07, 95% CI 1.01-1.14, P = 0.028) and hospitalization (RR 1.04, 95% CI 1.01-1.07, P = 0.006) but without significant differences in ICU admission and ventilator use compared to non-cancer patients. Recent cancer diagnoses were associated with higher risks for worse COVID-19 outcomes (RR for mortality 1.17, 95% CI 1.08-1.25, PConclusions and relevanceIndividuals with cancer had higher risks for 30-day mortality and hospitalization after SARS-CoV-2 infection compared to patients without cancer. More specifically, patients with a cancer diagnosis within 1 year and those receiving active treatment were more vulnerable to worse COVID-19 outcomes.

Objective. Antithyroglobulin antibodies (TgAbs) could be used as a surrogate tumor marker of TgAb-positive-differentiated thyroid carcinoma. This study aims to determine whether the change in TgAb levels over time could be used as a predictor of responses to therapy in pediatric papillary thyroid carcinoma (PTC) patients. Methods. We retrospectively analyzed the records of 48 pediatric PTC patients with TgAb levels ≥50 IU/ml 6 months after initial 131I treatment. Suppressed thyroglobulin (Tg) levels 6 months after initial 131I treatment were used to divide the patients into positive Tg (P-Tg, Tg ≥ 0.2 ng/ml) and negative Tg (N-Tg, Tg

BackgroundThe National Cancer Institute Informatics Technology for Cancer Research (ITCR) program provides a series of funding mechanisms to create an ecosystem of open-source software (OSS) that serves the needs of cancer research. As the ITCR ecosystem substantially grows, it faces the challenge of the long-term sustainability of the software being developed by ITCR grantees. To address this challenge, the ITCR sustainability and industry partnership working group (SIP-WG) was convened in 2019. ObjectiveThe charter of the SIP-WG is to investigate options to enhance the long-term sustainability of the OSS being developed by ITCR, in part by developing a collection of business model archetypes that can serve as sustainability plans for ITCR OSS development initiatives. The working group assembled models from the ITCR program, from other studies, and from the engagement of its extensive network of relationships with other organizations (eg, Chan Zuckerberg Initiative, Open Source Initiative, and Software Sustainability Institute) in support of this objective. MethodsThis paper reviews the existing sustainability models and describes 10 OSS use cases disseminated by the SIP-WG and others, including 3D Slicer, Bioconductor, Cytoscape, Globus, i2b2 (Informatics for Integrating Biology and the Bedside) and tranSMART, Insight Toolkit, Linux, Observational Health Data Sciences and Informatics tools, R, and REDCap (Research Electronic Data Capture), in 10 sustainability aspects: governance, documentation, code quality, support, ecosystem collaboration, security, legal, finance, marketing, and dependency hygiene. ResultsInformation available to the public reveals that all 10 OSS have effective governance, comprehensive documentation, high code quality, reliable dependency hygiene, strong user and developer support, and active marketing. These OSS include a variety of licensing models (eg, general public license version 2, general public license version 3, Berkeley Software Distribution, and Apache 3) and financial models (eg, federal research funding, industry and membership support, and commercial support). However, detailed information on ecosystem collaboration and security is not publicly provided by most OSS. ConclusionsWe recommend 6 essential attributes for research software: alignment with unmet scientific needs, a dedicated development team, a vibrant user community, a feasible licensing model, a sustainable financial model, and effective product management. We also stress important actions to be considered in future ITCR activities that involve the discussion of the sustainability and licensing models for ITCR OSS, the establishment of a central library, the allocation of consulting resources to code quality control, ecosystem collaboration, security, and dependency hygiene.

Background Several studies have reported changes in the volume and type of acute ischemic stroke (AIS) hospitalizations during the early stage of the COVID‐19 pandemic. However, population‐based assessments, which include lower volume centers and more comprehensive geographic areas, are limited. Here, we evaluate an entire state‐level experience during the first peak COVID pandemic and compare against a 1‐year prior historical period. Methods We conducted a retrospective population‐based study using the Texas Inpatient Public Use Data File, capturing all discharges from hospitals in the State of Texas, except federal hospitals. AIS admission volumes, patient characteristics, proportions of large vessel occlusion (LVO), admission rates to comprehensive stroke centers, use of intravenous tissue plasminogen activator and endovascular treatment, and patient outcomes were compared between April 1, 2019 and June 30, 2019 (historical control period) and April 1, 2020 and June 30, 2020 (pandemic period). Results A total of 9277 hospitalized AIS cases were identified during the pandemic period, a decrease of 12% (10 524) compared with the control period. Cases without LVO dropped by 15%, whereas LVO cases dropped by only 5%. There were no significant differences in age or race and ethnicity of patients. While admission rates to comprehensive stroke centers (39.6% versus 39.4%, P=0.81) and endovascular treatment use in LVO (17.0% versus 16.3%, P=0.45) were not different between the 2 periods, the use of intravenous tissue plasminogen activator (15.0% versus 13.6%, relative risk [RR], 0.90; 95% CI, 0.84–0.97; P=0.004) decreased. The percentage of patients who died or were discharged to hospice increased from 7.2% to 8.25% (RR, 1.17; 95% CI. 1.06–1.29; P=0.001). Conclusions This study from a statewide population‐level analysis confirms smaller hospital‐based cohorts observing decreasing numbers of milder AIS admissions, and lower use of thrombolysis. Although LVO admissions and endovascular treatment use were largely unchanged, these findings suggest missed treatment opportunities for patients with AIS in the pandemic.

BackgroundThere remains uncertainty about the impact of menopausal hormone therapy (MHT) on women's health. A systematic, comprehensive assessment of the effects on multiple outcomes is lacking. We conducted an umbrella review to comprehensively summarize evidence on the benefits and harms of MHT across diverse health outcomes.Methods and findingsWe searched MEDLINE, EMBASE, and 10 other databases from inception to November 26, 2017, updated on December 17, 2020, to identify systematic reviews or meta-analyses of randomized controlled trials (RCTs) and observational studies investigating effects of MHT, including estrogen-alone therapy (ET) and estrogen plus progestin therapy (EPT), in perimenopausal or postmenopausal women in all countries and settings. All health outcomes in previous systematic reviews were included, including menopausal symptoms, surrogate endpoints, biomarkers, various morbidity outcomes, and mortality. Two investigators independently extracted data and assessed methodological quality of systematic reviews using the updated 16-item AMSTAR 2 instrument. Random-effects robust variance estimation was used to combine effect estimates, and 95% prediction intervals (PIs) were calculated whenever possible. We used the term MHT to encompass ET and EPT, and results are presented for MHT for each outcome, unless otherwise indicated. Sixty systematic reviews were included, involving 102 meta-analyses of RCTs and 38 of observational studies, with 102 unique outcomes. The overall quality of included systematic reviews was moderate to poor. In meta-analyses of RCTs, MHT was beneficial for vasomotor symptoms (frequency: 9 trials, 1,104 women, risk ratio [RR] 0.43, 95% CI 0.33 to 0.57, p < 0.001; severity: 7 trials, 503 women, RR 0.29, 95% CI 0.17 to 0.50, p = 0.002) and all fracture (30 trials, 43,188 women, RR 0.72, 95% CI 0.62 to 0.84, p = 0.002, 95% PI 0.58 to 0.87), as well as vaginal atrophy (intravaginal ET), sexual function, vertebral and nonvertebral fracture, diabetes mellitus, cardiovascular mortality (ET), and colorectal cancer (EPT), but harmful for stroke (17 trials, 37,272 women, RR 1.17, 95% CI 1.05 to 1.29, p = 0.027) and venous thromboembolism (23 trials, 42,292 women, RR 1.60, 95% CI 0.99 to 2.58, p = 0.052, 95% PI 1.03 to 2.99), as well as cardiovascular disease incidence and recurrence, cerebrovascular disease, nonfatal stroke, deep vein thrombosis, gallbladder disease requiring surgery, and lung cancer mortality (EPT). In meta-analyses of observational studies, MHT was associated with decreased risks of cataract, glioma, and esophageal, gastric, and colorectal cancer, but increased risks of pulmonary embolism, cholelithiasis, asthma, meningioma, and thyroid, breast, and ovarian cancer. ET and EPT had opposite effects for endometrial cancer, endometrial hyperplasia, and Alzheimer disease. The major limitations include the inability to address the varying effects of MHT by type, dose, formulation, duration of use, route of administration, and age of initiation and to take into account the quality of individual studies included in the systematic reviews. The study protocol is publicly available on PROSPERO (CRD42017083412).ConclusionsMHT has a complex balance of benefits and harms on multiple health outcomes. Some effects differ qualitatively between ET and EPT. The quality of available evidence is only moderate to poor.

P. wenshanica S.C.Chen & Z.H.Tsi and P. subcalceata Gagnep. have long been recognized as synonyms of P. leveilleana Schltr. In the present study, detailed morphological comparisons suggest that specimens referred to as P. wenshanica and P. subcalceata differ significantly in both vegetative and floral characters from those of P. leveilleana. Here we resurrect P. wenshanica and P. subcalceata as independent species. Key diagnostic characters essential for delineating identities of these species are presented.

Abstract Background Follow-up after artificial joint replacement greatly helps achieve surgical outcomes. Mobile internet technology and mobile terminal equipment may increase the effectiveness of artificial joint replacement. However, only a few studies have evaluated the effectiveness of this technology. We aimed to analyze the reasons and outcomes of patients who used the instant messaging platform after undergoing artificial joint replacement. Methods Among the 548 cases of arthroplasty (250 hips, 298 knees) performed between December 2015 and June 2018 in the Department of Joint Surgery of our institution; 358 (164 hip joints, 194 knee joints) participated in instant messaging platform consultation, whereas the remaining 190 (86 hip joints, 104 knee joints) participated in traditional telephone consultation, as a control group. Follow-up time was from December 2015 to August 2018 (follow-up period was 2–32 months). Data on age, sex, type of surgery, date of surgery, date of discharge, and length of hospital stay were collected from electronic medical records. Results We analyzed the consultation contents of 358 patients who participated in instant messaging platform consultation. Counseling was mainly related to pain (13.6%), appointment review (12.4%), activity problems (10.5%), and incision problems (8.9%). Most problems were resolved through online guidance, with 8.4% of patients requiring only outpatient treatment and 2.5% of patients requiring rehospitalization. A total of 190 patients were followed up through traditional telephone consultation; 6.8% of patients required outpatient department treatment and 7.4% were eventually re-admitted. Conclusion The instant messaging platform consultation service effectively informs patients of potential postoperative problems and helps resolve them. It allows early detection and management of postoperative adverse events, including problems related to medication, wound, and activity, thereby effectively reducing readmission rate.

Background: Coronavirus disease 2019 (COVID-19) has been associated with coagulopathy, and D-dimer levels have been used to predict disease severity. However, the role of D-dimer in predicting mortality in COVID-19 patients with acute ischemic stroke (AIS) remains incompletely characterized.Methods: We conducted a retrospective cohort study using the Optum® de-identified COVID-19 Electronic Health Record dataset. Patients were included if they were 18 or older, had been hospitalized within 7 days of confirmed COVID-19 positivity from March 1, 2020 to November 30, 2020. We determined the optimal threshold of D-dimer to predict in-hospital mortality and compared risks of in-hospital mortality between patients with D-dimer levels below and above the cutoff. Risk ratios (RRs) were estimated adjusting for baseline characteristics and clinical variables.Results: Among 15,250 patients hospitalized with COVID-19 positivity, 285 presented with AIS at admission (2%). Patients with AIS were older [70 (60–79) vs. 64 (52–75), p < 0.001] and had greater D-dimer levels at admission [1.42 (0.76–3.96) vs. 0.94 (0.55–1.81) μg/ml FEU, p < 0.001]. Peak D-dimer level was a good predictor of in-hospital mortality among all patients [c-statistic 0.774 (95% CI 0.764–0.784)] and among patients with AIS [c-statistic 0.751 (95% CI 0.691–0.810)]. Among AIS patients, the optimum cutoff was identified at 5.15 μg/ml FEU with 73% sensitivity and 69% specificity. Elevated peak D-dimer level above this cut-off was associated with almost 3 times increased mortality [adjusted RR 2.89 (95% CI 1.87–4.47), p < 0.001].Conclusions: COVID-19 patients with AIS present with greater D-dimer levels. Thresholds for outcomes prognostication should be higher in this population.

ObjectiveThis study aimed to assess the morphology of the femoral medullary canal in subjects with developmental dysplasia of the hip (DDH) with the intent of improving the design of femoral stems in total hip arthroplasty.MethodsComputed tomography images of 56 DDH hips, which were classified into Crowe I to Crowe IV, and 30 normal hips were collected and used to reconstruct three-dimensional morphology of the femoral medullary cavity. Images of twenty-one cross sections were taken from 20 mm above the apex of the lesser trochanter to the isthmus. The morphology of femoral cavity was evaluated on each cross section for the longest canal diameter, the femoral medullary torsion angle (FMTA), and the femoral medullary roundness index (FMRI).ResultsThe Crowe IV group displayed the narrowest medullary canal in the region superior to the end of the lesser trochanter, but then gradually aligned with the medullary diameter of the other groups down to the isthmus. The FMTA along the femoral cavity increased with the severity of DDH, but the rate of variation of FMTA along the femoral canal was consistent in the DDH groups. The DDH hips generally showed a larger FMRI than the normal hips, indicating more elliptical shapes.ConclusionA femoral stem with a cone shape in the proximal femur and a cylindrical shape for the remainder down to the isthmus may benefit the subjects with severe DDH. This design could protect bone, recover excessive femoral anteversion and facilitate the implantation in the narrow medullary canal.