[Research progress on the application of specially lense related to myopia prevention and control]

In order to decelerate the growth of myopia in children and adolescents and reduce the risks of associated eye complications, extensive research has been conducted on preventive measures, including optical, behavioral, and pharmaceutical interventions. Spectacle lenses, due to their safety, convenience, and high patient compliance, stand out as the most common method for correcting refractive errors compared to other interventions. As far as we know, various forms of spectacle lenses are currently used in clinical practice, including bifocal lenses, progressive multifocal lenses, peripheral defocus lenses, defocus incorporated multiple segments (DIMS) lenses, highly aspherical lenslets, diffusion optics technology lenses, and violet light transmission (VL) glasses. However, a systematic and comprehensive overview of myopia-controlling spectacle lenses is still lacking. Therefore, this article summarizes the latest research progress on the myopia prevention and control technology of spectacle lenses at home and abroad, providing theoretical support for the myopia prevention and control effect of different spectacle lens technologies, promoting the application of related technologies in clinical work, and offering new ideas for myopia prevention and control.

An investigation into the relationship between community engagement and maternal mental health in Calgary, Alberta using the All Our Families cohort

INTRODUCTION

Existing literature shows that increased community engagement is associated with decreased depressive symptoms. To our knowledge, no existing studies have investigated the relationship between community engagement and adverse mental health among mothers in a Canadian context, nor has this relationship been studied over time. The current study aims to address these gaps by modelling the association between community engagement and anxiety and depression longitudinally using a cohort of prenatal and postnatal mothers living in Calgary, Alberta.

METHODS

We used data from the All our Families (AOF) study, a prospective cohort study of expectant and new mothers in Calgary, Alberta from 2008 to 2017 across seven timepoints. We used three-level latent growth curves to model the relationship between individual-level community engagement and maternal depression and anxiety scores, while adjusting for both individual and neighborhood-level characteristics.

RESULTS

The study sample consisted of 2129 mothers across 174 neighborhoods in Calgary. Adjusted latent growth curve models demonstrated that community engagement was associated with lower depression (b = - 0.28, 95% CI - 0.33, - 0.23) and anxiety (b = - 0.07, 95% CI - 0.12, - 0.02) scores among mothers over time.

DISCUSSION

Adjusted results show that community engagement has a protective effect against depression and anxiety amongst mothers. The results of this study are in line with existing evidence suggesting that social cohesion, civic participation, and community engagement are protective against adverse mental health outcomes.

Surgical treatment of nasopharyngeal cancer - a consensus recommendation from two Chinese associations

BACKGROUND

Surgical treatment is playing an increasingly important role in the management of nasopharyngeal carcinoma (NPC). This consensus focuses on the indications for optimal surgery, and surgical methods in the whole process of treatment for NPC to provide a useful reference to assist these difficult clinical decisions.

METHODOLOGY

A thorough review of available literature on NPC and surgery was conducted by the Association for the prevention and treatment of nasopharyngeal carcinoma in China, international exchange and promotion Association for medicine and healthcare, and the Committee on nasopharyngeal cancer of Guangdong provincial anticancer association. A set of questions and a preliminary draft guideline was circulated to a panel of 1096 experienced specialists on this disease for voting on controversial areas and comments. A refined second proposal, based on a summary of the initial voting and different opinions expressed, was recirculated to the experts in two authoritative medical science and technology academic groups in the prevention and treatment of NPC in China for review and reconsideration.

RESULTS

The initial round of questions showed variations in clinical practice even among similar specialists, reflecting the lack of high-quality supporting data and resulting difficulties in formulating clinical decisions. Through exchange of comments and iterative revisions, recommendations with high-to-moderate agreement were formulated on general treatment strategies and details of surgery, including indications and surgical approaches.

CONCLUSION

By standardizing the surgical indications and practice, we hope not only to improve the surgical outcomes, but also to highlight the key directions of future clinical research in the surgical management of NPC.

A Generalized Deep Learning Method for Synthetic CT Generation

PURPOSE/OBJECTIVE(S)

The application of deep learning to generate synthetic CT (sCT) has been widely studied in radiotherapy. Existing methods generally involve data from two different image modalities, such as CBCT-CT or MRI-CT, the quality of sCT is adversely affected by source image quality. We propose a unique method of synthesizing MRI and CBCT into sCT based on single-modal CT for training, and call it SmGAN.

MATERIALS/METHODS

We used planning CT of a group of 35 head and neck cases to as training data. We then applied two different spatial transformations to the planning CT image to produce the transformed CT1 and CT2. And We used a random style enhancement technique (Shuffle Remap) to modify the image distribution of CT1 which we termed CT1+E. CT1+E was used to simulate the patient's "image of the day" while CT2 to simulate the "planning image". After feeding both CT1+E and CT2 into the generator, we obtained the sCT predicted by the generator. The generator was trained using the Mean Absolute Error (MAE) loss between sCT and CT1. In the actual clinical process, we use the patient's CBCT or MRI instead of CT1+E and the patient's planning CT instead of CT2 as the input of the generator. After processing, we get an sCT that can maintain the spatial position of the image taken on the day, while presenting features similar to the planning CT. The evaluation data we have includes 10 pairs of MRI-Def_CT and 10 pairs of CBCT-Def_CT Head and Neck patients. Def_CT is obtained from the planning CT based on the spatial position deformation of MRI and CBCT. To evaluate the accuracy of sCT based on MRI and CBCT with Def CT, we use a range of metrics, including Hounsfield Unit (HU) difference, peak signal-to-noise ratio (PSNR), structural similarity (SSIM) and gamma pass rate. All results will be benchmarks against the advanced method RegGAN for comparison.

RESULTS

Compared to RegGAN, the results of SmGAN were significantly better. The mean absolute errors within the body were (44.7±216.2 HU vs. 36.7±131.4 HU) and (64.9±123.7 HU vs. 58.2±152.8 HU) for the CBCT-SCT and MRI-SCT, respectively (Table 1). In addition, experimental results show that SmGAN also outperforms RegGAN in dose calculation accuracy. For example, under the 10% threshold, SmGAN's gamma pass rate of 1mm and 1% is 0.926±0.02, compared with gamma rate of 0.896±0.02 for RegGAN.

CONCLUSION

We proposed a generalized deep learning model for synthetic CT generation, based on CBCT or MRI images. The proposed algorithm achieved high accuracy of dosimetric metrics, as well as excellent IMRT QA verification results. Compared to other existing synthetic CT generation methods, the proposed SmGAN required a single-modal image for training, which is considered as a major breakthrough in the industry, and is expected to have wide spread of clinical applications.

Autonomic modulation, spontaneous baroreflex sensitivity and fatigue in young men after COVID-19

Impaired autonomic modulation and baroreflex sensitivity (BRS) have been reported during and after COVID-19. Both impairments are associated with negative cardiovascular outcomes. If these impairments were to exist undetected in young men after COVID-19, they could lead to negative cardiovascular outcomes. Fatigue is associated with autonomic dysfunction during and after COVID-19. It is unclear if fatigue can be used as an indicator of impaired autonomic modulation and BRS after COVID-19. This study aims to compare parasympathetic modulation, sympathetic modulation, and BRS between young men who had COVID-19 versus controls and to determine if fatigue is associated with impaired autonomic modulation and BRS. Parasympathetic modulation as the high-frequency power of R-R intervals (lnHFR-R), sympathetic modulation as the low-frequency power of systolic blood pressure variability (LFSBP), and BRS as the -index were measured by power spectral density analysis. These variables were compared between 20 young men who had COVID-19 and 24 controls. Independent t-tests and Mann-Whitney U tests indicated no significant difference between the COVID-19 and the control group in: lnHFR-R, P=0.20; LFSBP, P=0.11, and -index, P=0.20. Fatigue was not associated with impaired autonomic modulation or BRS. There is no difference in autonomic modulations or BRS between young men who had COVID-19 compared to controls. Fatigue did not seem to be associated with impaired autonomic modulation or impaired BRS in young men after COVID-19. Findings suggest that young men might not be at increased cardiovascular risk from COVID-19-related dysautonomia and impaired BRS.

[Safety and efficacy of the early administration of levosimendan in patients with acute non-ST-segment elevation myocardial infarction and elevated NT-proBNP levels: An Early Management Strategy of Acute Heart Failure (EMS-AHF)]

Objectives: To investigated the safety and efficacy of treating patients with acute non-ST-segment elevation myocardial infarction (NSTEMI) and elevated levels of N-terminal pro-hormone B-type natriuretic peptide (NT-proBNP) with levosimendan within 24 hours of first medical contact (FMC). Methods: This multicenter, open-label, block-randomized controlled trial (NCT03189901) investigated the safety and efficacy of levosimendan as an early management strategy of acute heart failure (EMS-AHF) for patients with NSTEMI and high NT-proBNP levels. This study included 255 patients with NSTEMI and elevated NT-proBNP levels, including 142 males and 113 females with a median age of 65 (58-70) years, and were admitted in the emergency or outpatient departments at 14 medical centers in China between October 2017 and October 2021. The patients were randomly divided into a levosimendan group (n=129) and a control group (n=126). The primary outcome measure was NT-proBNP levels on day 3 of treatment and changes in the NT-proBNP levels from baseline on day 5 after randomization. The secondary outcome measures included the proportion of patients with more than 30% reduction in NT-proBNP levels from baseline, major adverse cardiovascular events (MACE) during hospitalization and at 6 months after hospitalization, safety during the treatment, and health economics indices. The measurement data parameters between groups were compared using the t-test or the non-parametric test. The count data parameters were compared between groups using the χ² test. Results: On day 3, the NT-proBNP levels in the levosimendan group were lower than the control group but were statistically insignificant [866 (455, 1 960) vs. 1 118 (459, 2 417) ng/L, Z=-1.25,P=0.21]. However, on day 5, changes in the NT-proBNP levels from baseline in the levosimendan group were significantly higher than the control group [67.6% (33.8%,82.5%)vs.54.8% (7.3%,77.9%), Z=-2.14, P=0.03]. There were no significant differences in the proportion of patients with more than 30% reduction in the NT-proBNP levels on day 5 between the levosimendan and the control groups [77.5% (100/129) vs. 69.0% (87/126), χ²=2.34, P=0.13]. Furthermore, incidences of MACE did not show any significant differences between the two groups during hospitalization [4.7% (6/129) vs. 7.1% (9/126), χ²=0.72, P=0.40] and at 6 months [14.7% (19/129) vs. 12.7% (16/126), χ²=0.22, P=0.64]. Four cardiac deaths were reported in the control group during hospitalization [0 (0/129) vs. 3.2% (4/126), P=0.06]. However, 6-month survival rates were comparable between the two groups (log-rank test, P=0.18). Moreover, adverse events or serious adverse events such as shock, ventricular fibrillation, and ventricular tachycardia were not reported in both the groups during levosimendan treatment (days 0-1). The total cost of hospitalization [34 591.00(15 527.46,59 324.80) vs. 37 144.65(16 066.90,63 919.00)yuan, Z=-0.26, P=0.80] and the total length of hospitalization [9 (8, 12) vs. 10 (7, 13) days, Z=0.72, P=0.72] were lower for patients in the levosimendan group compared to those in the control group, but did not show statistically significant differences. Conclusions: Early administration of levosimendan reduced NT-proBNP levels in NSTEMI patients with elevated NT-proBNP and did not increase the total cost and length of hospitalization, but did not significantly improve MACE during hospitalization or at 6 months.

A method for generating synthetic longitudinal health data

Getting access to administrative health data for research purposes is a difficult and time-consuming process due to increasingly demanding privacy regulations. An alternative method for sharing administrative health data would be to share synthetic datasets where the records do not correspond to real individuals, but the patterns and relationships seen in the data are reproduced. This paper assesses the feasibility of generating synthetic administrative health data using a recurrent deep learning model. Our data comes from 120,000 individuals from Alberta Health's administrative health database. We assess how similar our synthetic data is to the real data using utility assessments that assess the structure and general patterns in the data as well as by recreating a specific analysis in the real data commonly applied to this type of administrative health data. We also assess the privacy risks associated with the use of this synthetic dataset. Generic utility assessments that used Hellinger distance to quantify the difference in distributions between real and synthetic datasets for event types (0.027), attributes (mean 0.0417), Markov transition matrices (order 1 mean absolute difference: 0.0896, sd: 0.159; order 2: mean Hellinger distance 0.2195, sd: 0.2724), the Hellinger distance between the joint distributions was 0.352, and the similarity of random cohorts generated from real and synthetic data had a mean Hellinger distance of 0.3 and mean Euclidean distance of 0.064, indicating small differences between the distributions in the real data and the synthetic data. By applying a realistic analysis to both real and synthetic datasets, Cox regression hazard ratios achieved a mean confidence interval overlap of 68% for adjusted hazard ratios among 5 key outcomes of interest, indicating synthetic data produces similar analytic results to real data. The privacy assessment concluded that the attribution disclosure risk associated with this synthetic dataset was substantially less than the typical 0.09 acceptable risk threshold. Based on these metrics our results show that our synthetic data is suitably similar to the real data and could be shared for research purposes thereby alleviating concerns associated with the sharing of real data in some circumstances.

[Research progress on the role of adipose-derived stem cell exosomes in skin scar formation]

The adipose-derived stem cell exosomes are subcellular structures of adipose stem cells. They are nano-sized membrane vesicles that can transport various cell components and act on target cells by paracrine, and they play an important role in the exchanges of substance and information between cells. Scar healing is the commonest way of healing after skin tissue injury. Pathological scar can not only cause movement dysfunction, but also lead to deformity, which affects the appearance of patients and brings life and mental pressure to the patients. In recent years, many researches have shown that the adipose-derived stem cell exosomes contain a variety of bioactive molecules, which play an important role in reducing scar formation and scar-free wound healing, by affecting the proliferation and migration of fibroblasts and the composition of extracellular matrix. This article reviewed the recent literature on the roles and mechanisms of adipose-derived stem cell exosomes in scar formation, and prospected the future application and development of adipose-derived stem cell exosomes in scar treatment.

Sex-specific metabolic risk factors and their trajectories towards the non-alcoholic fatty liver disease incidence

PURPOSE

Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver disease. This study examined sex-specific associations between NAFLD and metabolic factors and investigated the trajectory of risk factors.

METHODS

We retrospectively investigated 16,140 individuals from Beijing Health Management Cohort. Univariate and multivariate time-dependent Cox regression analyses were performed to identify independent risk factors for new-onset NAFLD. The trajectory of risk factors was investigated using the latent growth curve model and growth mixture model.

RESULTS

Over a median follow-up of 3.15 years, 2,450 (15.18%) participants developed NAFLD. The risk factors for NAFLD in men were increased body mass index (BMI); waist circumference (WC); triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), haemoglobin (Hb), and serum uric acid (SUA) levels; and platelet (PLT) count and decreased serum creatinine-to-body weight (sCr/bw) and high-density lipoprotein cholesterol (HDL-C) levels. In women, the risk factors were increased BMI, WC, and fasting plasma glucose (FPG), TG, LDL-C, SUA, white blood cell (WBC), and PLT and decreased sCr/bw and HDL-C levels. In addition, BMI, LDL-C, sCr/bw and PLT changing trajectories were associated with NAFLD in men; BMI, WC, TG, LDL-C, SUA and sCr/bw trends was associated with NAFLD risk in women.

CONCLUSIONS

Development of NAFLD is associated with BMI, LDL-C, sCr/bw and PLT changing trajectories in men; BMI, WC, TG, LDL-C, SUA and sCr/bw trends are associated an increased risk of NAFLD in women. Deterioration of metabolic risk factors status can be a predictor of NAFLD many years before its occurrence.

[A retrospective controlled study on the treatment effect of distraction osteogenesis and maxillomandibular advancement for severe obstructive sleep apnea hypopnea syndrome patients]

Objective: To compare the treatment effect of distraction osteogenesis (DO) and maxillomandibular advancement (MMA) for severe obstructive sleep apnea hypopnea syndrome (OSAHS) patients and to guide clinical decisions about treatment of OSAHS. Methods: Thirty-seven OSAHS patients which accepted maxillomandibular advancement (MMA) or distraction osteogenesis (DO) in Stomatological Hospital of the Department of Maxillofacial Trauma and Orthognathic Surgery, School of Stomatology, The Forth Military Medical University from June 2017 to June 2019 were collected. Their preoperative and postoperative data of cephalometry, polysomnography (PSG), Pittsburgh sleep quality index (PSQI) and Epworth sleepiness scale (ESS) scores were collected and analyzed. With propensity score matching method, the treatment effect of MMA and DO was analyzed and compared. Results: According to the statistics of MMA group, only AHI was correlated with operative successful rate and cure rate. With the increase of AHI, the treatment effect of MMA on OSAHS patients gradually decreased. The cut-off point of AHI as a predictor of MMA treatment failure was 78.2 n/h. All the matched cases were severe OSAHS patients. Statistical analysis showed that the mandibular elongation of DO patients[(24.00±4.39) mm] was significantly more than that of MMA group [(11.20±1.37) mm] (t=-6.11, P<0.001), the improvement of PSG index [including lowest oxygen saturation (LSpO₂), longest apnea (LA) and longest hypopnea (LH)] in DO group [LSpO₂=(93.40±1.82)%; LA=(18.28±8.32) s; LH=(61.84±32.94) s] was significantly higher than that in the MMA group [LSpO₂=(86.00±4.06)%, LA=(64.08±21.78) s, LH=(172.40±30.70) s](t=-3.72, P=0.005; t=4.39, P=0.003; t=5.49, P=0.004). The PSQI and the ESS scores of DO group (PSQI=4.20±0.83; ESS=3.40±1.52) were also significantly better than that of MMA group (PSQI=8.80±2.39, ESS=9.40±2.88)(t=4.07, P=0.001; t=4.12, P=0.002). Conclusions: For severe OSAHS patients, the objective and subjective indicators of DO treatment group showed a better therapeutic effect than that of MMA.

[Prognosis of adenoid cystic carcinoma of head and neck and risk factors for lung metastasis]

Objective: To analyze the prognosis and risk factors of lung metastasis of patients with adenoid cystic carcinoma(ACC) of head and neck. Methods: A retrospective study was conducted. The data of 157 patients with ACC of head and neck treated in Beijing Tongren Hospital, Capital Medical University from January 2014 to October 2020 were collected, including 72 males and 85 females, with onset age between 14 and 72 years old. According to whether lung metastasis occurred, the patients were divided into lung metastasis group (88 cases) and non-pulmonary metastasis group (69 cases). Kaplan-Meier method was used to calculate the overall survival rate and progression-free survival rate using SPSS 26.0 software. Log-rank test was used to evaluate statistically relevant clinicopathological factors. Cox proportional risk model was used in multivariate analysis for the factors affecting the lung metastasis-free survival using R Studio 1.2.5042. Results: The 3-year and 5-year overall survival rates were 91.5% and 85.2%, respectively. The 3-year and 5-year progression-free survival rates were 57.7% and 34.3%, respectively. Univariate analysis showed that primary site, histological grade, high-grade transformation, Ki-67, T stage, and lymph node status were the risk factors for lung metastasis (χ²=11.78, 10.41, 4.06, 4.71, 5.37, 16.20, respectively, all P<0.05). Multivariate analysis showed independent risk factors for lung metastasis, including submandibular gland and sublingual gland (HR=3.53, 95%CI: 1.19-10.46, P<0.05), T3-4 stage (HR=3.09, 95%CI: 1.54-6.23, P<0.05), and Grade Ⅱ-Ⅲ grade (HR=2.47, 95%CI: 1.26-4.86,P<0.05). Conclusion: Distant metastasis, mainly pulmonary metastasis, affects the long-term prognosis of patients with ACC significantly. Primary site, T stage and histopathological grade can be used as the predictors for the risk of lung metastasis.

Measuring re-identification risk using a synthetic estimator to enable data sharing

Background

One common way to share health data for secondary analysis while meeting increasingly strict privacy regulations is to de-identify it. To demonstrate that the risk of re-identification is acceptably low, re-identification risk metrics are used. There is a dearth of good risk estimators modeling the attack scenario where an adversary selects a record from the microdata sample and attempts to match it with individuals in the population.

Objectives

Develop an accurate risk estimator for the sample-to-population attack.

Methods

A type of estimator based on creating a synthetic variant of a population dataset was developed to estimate the re-identification risk for an adversary performing a sample-to-population attack. The accuracy of the estimator was evaluated through a simulation on four different datasets in terms of estimation error. Two estimators were considered, a Gaussian copula and a d-vine copula. They were compared against three other estimators proposed in the literature.

Results

Taking the average of the two copula estimates consistently had a median error below 0.05 across all sampling fractions and true risk values. This was significantly more accurate than existing methods. A sensitivity analysis of the estimator accuracy based on variation in input parameter accuracy provides further application guidance. The estimator was then used to assess re-identification risk and de-identify a large Ontario COVID-19 behavioral survey dataset.

Conclusions

The average of two copula estimators consistently provides the most accurate re-identification risk estimate and can serve as a good basis for managing privacy risks when data are de-identified and shared.

Low-Rank Plus Sparse Decomposition of fMRI Data With Application to Alzheimer's Disease

Studying functional brain connectivity plays an important role in understanding how human brain functions and neuropsychological diseases such as autism, attention-deficit hyperactivity disorder, and Alzheimer's disease (AD). Functional magnetic resonance imaging (fMRI) is one of the most popularly used tool to construct functional brain connectivity. However, the presence of noises and outliers in fMRI blood oxygen level dependent (BOLD) signals might lead to unreliable and unstable results in the construction of connectivity matrix. In this paper, we propose a pipeline that enables us to estimate robust and stable connectivity matrix, which increases the detectability of group differences. In particular, a low-rank plus sparse (L + S) matrix decomposition technique is adopted to decompose the original signals, where the low-rank matrix L recovers the essential common features from regions of interest, and the sparse matrix S catches the sparse individual variability and potential outliers. On the basis of decomposed signals, we construct connectivity matrix using the proposed novel concentration inequality-based sparse estimator. In order to facilitate the comparisons, we also consider correlation, partial correlation, and graphical Lasso-based methods. Hypothesis testing is then conducted to detect group differences. The proposed pipeline is applied to rs-fMRI data in Alzheimer's disease neuroimaging initiative to detect AD-related biomarkers, and we show that the proposed pipeline provides accurate yet more stable results than using the original BOLD signals.

Balancing Gender Bias in Job Advertisements With Text-Level Bias Mitigation

Despite progress toward gender equality in the labor market over the past few decades, gender segregation in labor force composition and labor market outcomes persists. Evidence has shown that job advertisements may express gender preferences, which may selectively attract potential job candidates to apply for a given post and thus reinforce gendered labor force composition and outcomes. Removing gender-explicit words from job advertisements does not fully solve the problem as certain implicit traits are more closely associated with men, such as ambitiousness, while others are more closely associated with women, such as considerateness. However, it is not always possible to find neutral alternatives for these traits, making it hard to search for candidates with desired characteristics without entailing gender discrimination. Existing algorithms mainly focus on the detection of the presence of gender biases in job advertisements without providing a solution to how the text should be (re)worded. To address this problem, we propose an algorithm that evaluates gender bias in the input text and provides guidance on how the text should be debiased by offering alternative wording that is closely related to the original input. Our proposed method promises broad application in the human resources process, ranging from the development of job advertisements to algorithm-assisted screening of job applications.

Associations between Longitudinal Gestational Weight Gain and Scalar Infant Birth Weight: A Bayesian Joint Modeling Approach

Despite the importance of maternal gestational weight gain, it is not yet conclusively understood how weight gain during different stages of pregnancy influences health outcomes for either mother or child. We partially attribute this to differences in and the validity of statistical methods for the analysis of longitudinal and scalar outcome data. In this paper, we propose a Bayesian joint regression model that estimates and uses trajectory parameters as predictors of a scalar response. Our model remedies notable issues with traditional linear regression approaches found in the clinical literature. In particular, our methodology accommodates nonprospective designs by correcting for bias in self-reported prestudy measures; truly accommodates sparse longitudinal observations and short-term variation without data aggregation or precomputation; and is more robust to the choice of model changepoints. We demonstrate these advantages through a real-world application to the Alberta Pregnancy Outcomes and Nutrition (APrON) dataset and a comparison to a linear regression approach from the clinical literature. Our methods extend naturally to other maternal and infant outcomes as well as to areas of research that employ similarly structured data.

Comparison of Prognostic Scoring Systems to Predict Durable Pain Relief After Microvascular Decompression for Trigeminal Neuralgia

BACKGROUND

Microvascular decompression (MVD) is an effective treatment for trigeminal neuralgia, but pain recurs in a substantial minority of patients. Two recently published scoring systems by Hardaway et al. and Panczykowski et al. use simple preoperative clinical and imaging features to predict durable pain relief following MVD, but their predictive performance has not been independently validated. This study aimed to compare predictive performance of the Hardaway et al. score (HS) and Panczykowski et al. score (PS) for 1-year, 3-year, and long-term pain-free outcomes after MVD for trigeminal neuralgia.

METHODS

HS and PS were computed for a retrospective, single-institution cohort of 68 patients with trigeminal neuralgia who underwent MVD. Primary outcome was pain recurrence after MVD. Predictive performance of HSs and PSs was evaluated with area under the curve sensitivity analysis and regression models for survival analyses at 1 year, 3 years, and last follow-up.

RESULTS

Area under the curve for predicting pain-free outcome was higher for PS versus HS at 1 year (0.873 vs. 0.775) and 3 years (0.793 vs. 0.704). Cox proportional hazard models showed that PS better predicted long-term pain-free outcomes compared with HS (P < 0.05). One-year pain-free outcome was best predicted by pain type; longer-term outcomes were better predicted by presence and degree of neurovascular compression on preoperative imaging.

CONCLUSIONS

PS is superior to HS in predicting pain-free outcomes after MVD, which may aid in patient selection and counseling. Overall, more significant neurovascular compression of the trigeminal nerve root, and to a lesser extent classical paroxysmal pain, are good predictors of durable pain relief after MVD.

Predictive variables for peripheral neuropathy in treated HIV type 1 infection revealed by machine learning

OBJECTIVE

Peripheral neuropathies (PNPs) in HIV-infected patients are highly debilitating because of neuropathic pain and physical disabilities. We defined prevalence and associated predictive variables for PNP subtypes in a cohort of persons living with HIV.

DESIGN

Adult persons living with HIV in clinical care were recruited to a longitudinal study examining neurological complications.

METHODS

Each patient was assessed for symptoms and signs of PNP with demographic, laboratory, and clinical variables. Univariate, multiple logistic regression and machine learning analyses were performed by comparing patients with and without PNP.

RESULTS

Three patient groups were identified: PNP (n = 111) that included HIV-associated distal sensory polyneuropathy (n = 90) or mononeuropathy (n = 21), and non-neuropathy (n = 408). Univariate analyses showed multiple variables differed significantly between the non-neuropathy and PNP groups including age, estimated HIV type 1 (HIV-1) duration, education, employment, neuropathic pain, peak viral load, polypharmacy, diabetes, cardiovascular disorders, AIDS, and prior neurotoxic nucleoside antiretroviral drug exposure. Classification algorithms distinguished those with PNP, all with area under the receiver operating characteristic curve values of more than 0.80. Random forest models showed greater accuracy and area under the receiver operating characteristic curve values compared with the multiple logistic regression analysis. Relative importance plots showed that the foremost predictive variables of PNP were HIV-1 duration, peak plasma viral load, age, and low CD4+ T-cell levels.

CONCLUSION

PNP in HIV-1 infection remains common affecting 21.4% of patients in care. Machine-learning models uncovered variables related to PNP that were undetected by conventional analyses, emphasizing the importance of statistical algorithmic approaches to understanding complex neurological syndromes.

Estimation for the bivariate quantile varying coefficient model with application to diffusion tensor imaging data analysis

Despite interest in the joint modeling of multiple functional responses such as diffusion properties in neuroimaging, robust statistical methods appropriate for this task are lacking. To address this need, we propose a varying coefficient quantile regression model able to handle bivariate functional responses. Our work supports innovative insights into biomedical data by modeling the joint distribution of functional variables over their domains and across clinical covariates. We propose an estimation procedure based on the alternating direction method of multipliers and propagation separation algorithms to estimate varying coefficients using a B-spline basis and an $L_2$ smoothness penalty that encourages interpretability. A simulation study and an application to a real-world neurodevelopmental data set demonstrates the performance of our model and the insights provided by modeling functional fractional anisotropy and mean diffusivity jointly and their association with gestational age and sex.

Discovery of Highly Potent and Selective IRAK1 Degraders to Probe Scaffolding Functions of IRAK1 in ABC DLBCL

MyD88 gene mutation has been identified as one of the most prevalent driver mutations in the activated B-cell-like diffuse large B-cell lymphoma (ABC DLBCL). The published literature suggests that interleukin-1 receptor-associated kinase 1 (IRAK1) is an essential gene for ABC DLBCL harboring MyD88 mutation. Importantly, the scaffolding function of IRAK1, rather than its kinase activity, is required for tumor cell survival. Herein, we present our design, synthesis, and biological evaluation of a novel series of potent and selective IRAK1 degraders. One of the most potent compounds, Degrader-3 (JNJ-1013), effectively degraded cellular IRAK1 protein with a DC₅₀ of 3 nM in HBL-1 cells. Furthermore, JNJ-1013 potently inhibited IRAK1 downstream signaling pathways and demonstrated strong anti-proliferative effects in ABC DLBCL cells with MyD88 mutation. This work suggests that IRAK1 degraders have the potential for treating cancers that are dependent on the IRAK1 scaffolding function.

MicroRNA-198 inhibits metastasis of thyroid cancer by targeting H3F3A

OBJECTIVE

This study was designed to investigate the role of microRNA-198 in thyroid cancer (TCa) progression.

PATIENTS AND METHODS

Quantitative real-time polymerase chain reaction (qRT-PCR) was carried out to examine microRNA-198 and H3F3A levels in tumor tissue specimens and paracancerous ones collected from 50 patients with TCa, and the interplay between microRNA-198 or H3F3A and some clinical indicators or prognosis of TCa patients was analyzed as well. MicroRNA-198 and H3F3A overexpression models were constructed using lentivirus in TCa cell lines TPC-1 and BHP2-7, and the impacts of microRNA-198 on TCa cell functions were evaluated by using cell counting kit-8 (CCK-8), plate clone formation, and transwell assays. Finally, recovery investigations were conducted to explore the underlying mechanisms as well as the interaction between microRNA-198 and H3F3A.

RESULTS

QRT-PCR indicated that in tumor tissues of TCa patients, microRNA-198 showed a remarkably lower expression than in adjacent normal tissue samples. Compared with patients with high expression of microRNA-198, those with microRNA-198 low expression had more advanced tumor stage, larger tumor size, higher lymph node metastasis rate, and lower overall survival rate. Meanwhile, the results of research on H3F3A were just opposite to the above observations on microRNA-198. In in vitro cell experiments, overexpression of microRNA-198 significantly weakened the proliferation and migration ability of thyroid tumor cells. Besides, Luciferase reporter gene experiment revealed that H3F3A was a specific target gene for microRNA-198. Moreover, qRT-PCR indicated that H3F3A and microRNA-198 were negatively correlated in thyroid carcinoma tissues. In addition, compared with NC group, overexpression of H3F3A markedly enhanced the migration and proliferative capacity of TCa cells. Lastly, recovery experiment revealed a mutual regulation between microRNA-198 and H3F3A, the two of which may together participate in the malignant progression of TCa.

CONCLUSIONS

MicroRNA-198 is remarkably reduced in TCa and inhibits malignant progression of TCa by regulating H3F3A. Meanwhile, microRNA-198 is remarkably associated with pathological stage, tumor size, lymph node metastasis, and poor prognosis of TCa.

Tailoring 3D Carbon Foam using CNTs and MnO2 to Fabricate Stable Lithium/Dissolved Lithium Polysulfide Batteries

The lithium-sulfur (Li-S) battery is an ideal electrochemical energy storage system owing to the high theoretical energy density and acceptable cost of finance and the environment. However, some disadvantages, including low electrical conductivity, poor sulfur utilization, and rapid capacity fading, obstruct its practical application. In this work, 3D carbon foam from a melamine resin is synthesized via high-temperature calcination. Carbon nanotubes (CNTs) and MnO₂ are utilized to tailor the properties of the 3D cathode collector in the liquid Li₂S₆-containing Li-S battery without additional conductive agents, binders, and aluminum foil. Herein, the decorated MnO₂ on the carbon fiber foam prolongs the lifespan of the Li-S battery, and adding CNTs is beneficial to enhance the capacity and cyclic performance of the Li-S battery under high sulfur loading. The Li-S battery with a sulfur loading of 3 mg cm^-2 possesses a reversible capacity of 437.9 mA h g^-1 after 400 cycles at 0.1 C. The capacity could be maintained at 568 mA h g^-1 at 0.1 C after 80 cycles when the sulfur loading increases to 6 mg cm^-2.

High-Dimensional Spatial Quantile Function-on-Scalar Regression

This article develops a novel spatial quantile function-on-scalar regression model, which studies the conditional spatial distribution of a high-dimensional functional response given scalar predictors. With the strength of both quantile regression and copula modeling, we are able to explicitly characterize the conditional distribution of the functional or image response on the whole spatial domain. Our method provides a comprehensive understanding of the effect of scalar covariates on functional responses across different quantile levels and also gives a practical way to generate new images for given covariate values. Theoretically, we establish the minimax rates of convergence for estimating coefficient functions under both fixed and random designs. We further develop an efficient primal-dual algorithm to handle high-dimensional image data. Simulations and real data analysis are conducted to examine the finite-sample performance.

Stable Anatomy Detection in Multimodal Imaging Through Sparse Group Regularization: A Comparative Study of Iron Accumulation in the Aging Brain

Multimodal neuroimaging provides a rich source of data for identifying brain regions associated with disease progression and aging. However, present studies still typically analyze modalities separately or aggregate voxel-wise measurements and analyses to the structural level, thus reducing statistical power. As a central example, previous works have used two quantitative MRI parameters-R2* and quantitative susceptibility (QS)-to study changes in iron associated with aging in healthy and multiple sclerosis subjects, but failed to simultaneously account for both. In this article, we propose a unified framework that combines information from multiple imaging modalities and regularizes estimates for increased interpretability, generalizability, and stability. Our work focuses on joint region detection problems where overlap between effect supports across modalities is encouraged but not strictly enforced. To achieve this, we combine L ₁ (lasso), total variation (TV), and L ₂ group lasso penalties. While the TV penalty encourages geometric regularization by controlling estimate variability and support boundary geometry, the group lasso penalty accounts for similarities in the support between imaging modalities. We address the computational difficulty in this regularization scheme with an alternating direction method of multipliers (ADMM) optimizer. In a neuroimaging application, we compare our method against independent sparse and joint sparse models using a dataset of R2* and QS maps derived from MRI scans of 113 healthy controls: our method produces clinically-interpretable regions where specific iron changes are associated with healthy aging. Together with results across multiple simulation studies, we conclude that our approach identifies regions that are more strongly associated with the variable of interest (e.g., age), more accurate, and more stable with respect to training data variability. This work makes progress toward a stable and interpretable multimodal imaging analysis framework for studying disease-related changes in brain structure and can be extended for classification and disease prediction tasks.

[Expert consensus on the treatment of oral and maxillofacial space infections]

Oral and maxillofacial space infections (OMSI) are common diseases of the facial region involving fascial spaces. Recently, OMSI shows trends of multi drug-resistance, severe symptoms, and increased mortality. OMSI treatment principles need to be updated to improve the cure rate. Based on the clinical experiences of Chinese experts and with the incorporation of international counterparts' expertise, the principles of preoperative checklist, interpretation of examination results, empirical medication principles, surgical treatment principles, postoperative drainage principles, prevention strategies of wisdom teeth pericoronitis-related OMSI, blood glucose management, physiotherapy principles, Ludwig's angina treatment and perioperative care were systematically summarized and an expert consensus on the diagnosis and treatment of OMSI was reached. The consensus aims to provide criteria for the diagnosis and treatment of OMSI in China so as to improve the level of OMSI treatment.

Evaluation of the diagnostic performance of the creatinine-based Chronic Kidney Disease Epidemiology Collaboration equation in people with diabetes: A systematic review

AIMS

GFR estimated with the creatinine-based Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI_Cr ) equation is used to screen for diabetic kidney disease and assess its severity. We systematically reviewed the process and outcome of evaluating CKD-EPI_Cr in estimating point GFR or GFR decline over time in adults with type 1 or type 2 diabetes.

METHODS

In this systematic review, MEDLINE, Embase and Cochrane Central Register of Controlled Trials were searched up to August 2019. Observational studies comparing CKD-EPI_Cr with measured GFR (mGFR) in adults with diabetes were included. Studies on people with kidney transplant, non-diabetes related kidney disease, pregnancy, potential kidney donors, and those with critical or other systematic illnesses were excluded. Two independent reviewers extracted data from published papers and disagreements were resolved by consensus. Risk-of-bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. (PROSPERO registration number: CRD42018108776).

RESULTS

From the 2820 records identified, 29 studies (14 704 participants) were included. All studies were at risk of bias. Bias (eight different forms) ranged from -26 to 35 ml min^-1  1.73 m^-2 ; precision (five different forms) ranged between 9 and 63 ml min^-1  1.73 m^-2 ; accuracy (five different forms) ranged between 16% and 96%; the correlation coefficient between CKD-EPI_Cr and mGFR (four different forms) ranged between 0.38 and 0.86; and the reduced major axis regression slope ranged between 0.8 and 1.8.

CONCLUSIONS

Qualitative synthesis of data suggested CKD-EPI_Cr was inaccurate in estimating point GFR or GFR decline over time. Furthermore, a lack of consistency in the methods and processes of evaluating the diagnostic performance of CKD-EPI_Cr limits reliable quantitative assessment. The equation needs to be improved in adults with diabetes.

[Correlation between thyroid function and glucolipid metabolism in type 1 diabetic adults]

To assess the correlation between thyroid function and glucolipid metabolism in type 1 diabetic adults. A retrospective analysis was conducted in 230 type 1 diabetic adults who were hospitalized in the Department of Endocrinology of Shandong Provincial Hospital Affiliated to Shandong University from January 2008 to January 2020. It showed that thyroid stimulating hormone(TSH) was significantly positively correlated with total cholesterol (TC) (r=0.239), triglycerides (TG) (r=0.166) and low-density lipoprotein cholesterol (LDL-C) (r=0.249), respectively (all P<0.05). Free triiodothyronine (FT₃) was significantly negatively correlated with fasting plasma glucose (FPG) (r=-0.272), glycated hemoglobin (HbA1c) (r=-0.240), TC (r=-0.197) and LDL-C (r=-0.220), respectively (all P<0.05). Free thyroxine (FT₄) was negatively correlated with TC (r=-0.171) and LDL-C (r=-0.170), respectively (all P<0.05). TC was an independent predictor of TSH, FT₃ and FT₄, FT₃ and FT₄ were independent predictors of HbA1c. TSH was an independent predictor of TC, TG and LDL-C. Thyroid function is closely related to glucolipid metabolism in type 1 diabetic adults.

[Occurrence and related factors of preterm birth in Guangxi Zhuang Autonomous Region during 2017-2019]

Objective: To investigate the incidence of preterm birth in Guangxi Zhuang Autonomous Region and explore the related factors and their combined effects. Methods: The study subjects were women giving birth to live babies at the monitoring points of critical maternal hospital monitoring system in Guangxi Zhuang Autonomous Region from January 1, 2017 to December 31, 2019. The data of general characteristics (age and marital status), pregnancies (parity, number of previous cesarean delivery, the number of prenatal check and number of fetuses in this pregnancy) and disease conditions (placenta previa, placental abruption, hypertension, diabetes, anemia, and heart disease) were collected, and the incidence of preterm birth were calculated according to the definition of preterm birth set by WHO and China, respectively. Logistic regression model was used to explore the factors associated with premature birth and their combined effects. Results: According to definitions of WHO and China, the cumulative incidence of preterm birth in Guangxi from 2017 to 2019 was 7.45% (16 819/225 727) and 7.34% (16 559/225 727), respectively. Advanced age [≤34 years old as reference, OR (95%CI) of 35-39 and ≥40 years old were 1.36 (1.30-1.42) and 1.61 (1.50-1.74), respectively], unmarried (including divorced or widowed) [OR (95%CI): 1.28 (1.17-1.40)], primiparae [OR (95%CI): 1.34 (1.29-1.40)], previous cesarean section [no previous cesarean section as reference, OR (95%CI) of 1 and ≥2 times of previous cesarean section were 1.30 (1.24-1.36) and 1.85 (1.65-2.08), respectively], antenatal examination<8 [OR (95%CI): 2.72 (2.62-2.81)], multiple pregnancies [OR (95%CI): 15.00 (14.01-16.06)], placenta previa [OR (95%CI): 6.90 (6.35-7.50)], placental abruption [OR (95%CI): 8.18 (7.36-9.10)], gestational hypertension [OR (95%CI): 2.29 (2.17-2.42)], gestational diabetes mellitus [OR (95%CI): 1.43 (1.37-1.49)], anemia [OR (95%CI): 1.10 (1.07-1.14)], and heart diseases [OR (95%CI): 2.98(2.43-3.65)] were all positively correlated with preterm birth. The risk of preterm birth in pregnant women exposed to 1, 2, 3, 4, 5, 6 and ≥7 preterm birth related factors was 1.51, 2.29, 4.49, 9.69, 20.87, 46.88 and 192.11 times that of non-exposed women, respectively (all P values<0.001). Conclusion: Preterm birth is associated with maternal general characteristics, pregnancy and disease status, and the combined effect of preterm birth related factors significantly increases the risk of preterm birth.

[Clinical study of yiqi huoxue recipe in the treatment of liver fibrosis of chronic viral hepatitis]

Objective: To clarify the clinical efficacy of Yiqi Huoxue recipe in the treatment of liver fibrosis of chronic viral hepatitis. Methods: An open, positive-drug, parallel-controlled study method was applied. A total of 207 cases of liver fibrosis with chronic hepatitis B and C diagnosed with liver biopsy and transient elastography were selected. According to the principle of syndrome differentiation in traditional Chinese medicine, self-made Yiqi Huoxue recipe (n = 127) and Fuzheng Huayu capsule (n = 80) were used for the treatment course of 24-48 weeks. Change score of TCM symptom, liver biochemistry, liver stiffness measurement (LSM), and noninvasive liver fibrosis index [aspartate transaminase to platelet ratio index (APRI), and fibrosis-4 score (FIB-4)] were compared between the two groups to evaluate the therapeutic effect of Yiqi Huoxue recipe on liver fibrosis. Results: Yiqi Huoxue recipe group and Fuzheng Huayu capsule group baseline LSM, APRI and FIB-4 was compared, and there was no statistically significant difference between them (P > 0.05). Yiqi Huoxue recipe and Fuzheng Huayu capsule received patients had improved symptom scores to a certain extent. Hepatic facies, discomfort over liver area, and soreness and weakness of waist and knees (P < 0.05) was significantly improved in Yiqi Huoxue recipe than Fuzheng Huayu capsule. Liver biochemical indicators (ALT, AST, GGT, ALP) had gradually relapsed with the extension of treatment duration and the normalization rate between the two groups after 24 to 48 weeks had reached 100% vs. 100%, 100% vs. 93.8%, 96.8% vs. 92.3% and 87.5% vs. 81.8%. After 12 weeks of treatment, APRI values ​​of both groups had significantly reduced, and after 48 weeks of treatment, LSM values of both groups had significantly improved. Moreover, Yiqi Huoxue recipe FIB-4 score was significantly improved after 48 weeks of treatment, and the difference was statistically significant compared to Fuzheng Huayu capsule group (P < 0.05). After treatment, LSM, APRI, and FIB-4 total effectiveness in the two groups were 80.0% vs. 63.6%, P = 0.046; 68.4% vs. 52.0%, P = 0.052; 68.4% vs. 62.0%, P = 0.437, respectively. LSM total effectiveness was significantly higher in Yiqi Huoxue recipe treated group than Fuzheng Huayu capsule group. Conclusion: Traditional Chinese medicine Yiqi Huoxue decoction can be used as an optimal treatment for liver fibrosis of chronic viral hepatitis.

Sparse Multicategory Generalized Distance Weighted Discrimination in Ultra-High Dimensions

Distance weighted discrimination (DWD) is an appealing classification method that is capable of overcoming data piling problems in high-dimensional settings. Especially when various sparsity structures are assumed in these settings, variable selection in multicategory classification poses great challenges. In this paper, we propose a multicategory generalized DWD (MgDWD) method that maintains intrinsic variable group structures during selection using a sparse group lasso penalty. Theoretically, we derive minimizer uniqueness for the penalized MgDWD loss function and consistency properties for the proposed classifier. We further develop an efficient algorithm based on the proximal operator to solve the optimization problem. The performance of MgDWD is evaluated using finite sample simulations and miRNA data from an HIV study.

iTRAQ-based quantitative proteomics analysis reveals inhibitory mechanismsof the antimicrobial peptide MDAP-2 against Salmonella gallinarum

MDAP-2 is a new AMP with high inhibitory activity on Salmonella gallinarum, which may be developed as an antimicrobial agent in the agricultural industry and food preservation. To investigate the underlying the action mechanism of MDAP-2 on Salmonella gallinarum, impacts of MDAP-2 on the growth curve and bacterial morphology of Salmonella gallinarum were studied. iTRAQ-based proteomics analysis was also performed on proteins extracted from treated and untreated Salmonella gallinarum cells. The differentially expressed proteins were then analyzed using the KEGG and GO databases. Finally, the function of some differentially expressed proteins was verified. The results showed that 150 proteins (41 up-regulated and 109 down-regulated) were found differentially expressed (fold > 1.8, p⟨0.05). The results indi- cate that MDAP-2 kills Salmonella gallinarum mainly through two mechanisms: (i) direct inhibi- tion of cell wall/ membrane/ envelope biogenesis, energy production/ conversion, carbohydrate transport/ metabolism, and DNA transcription/ translation through regulation of special protein levels; (ii) indirect effects on the same pathway through the accumulation of Reactive oxygen species (O2 ▪-, H2O2 and OH▪-).

Assessing IRAK4 Functions in ABC DLBCL by IRAK4 Kinase Inhibition and Protein Degradation

The interleukin-1 receptor-activated kinase 4 (IRAK4) belongs to the IRAK family of serine/threonine kinases and plays a central role in the innate immune response. However, the function of IRAK4 in tumor growth and progression remains elusive. Here we sought to determine the enzymatic and scaffolding functions of IRAK4 in activated B-cell-like diffuse large B cell lymphoma (ABC DLBCL). We chose a highly selective IRAK4 kinase inhibitor to probe the biological effects of kinase inhibition and developed a series of IRAK4 degraders to evaluate the effects of protein degradation in ABC DLBCL cells. Interestingly, the results demonstrated that neither IRAK4 kinase inhibition nor protein degradation led to cell death or growth inhibition, suggesting a redundant role for IRAK4 in ABC DLBCL cell survival. IRAK4 degraders characterized in this study provide useful tools for understanding IRAK4 protein scaffolding function, which was previously unachievable using pharmacological perturbation.