Assessment of the antimicrobial and immunomodulatory activity of QS-CATH, a promising therapeutic agent isolated from the Chinese spiny frogs (Quasipaa spinosa).

Cathelicidins are important antimicrobial peptides in various vertebrate species where they are crucial parts of the innate immune system. The current understanding of amphibian cathelicidins is limited, particularly with regard to their immunomodulatory effects. To address this knowledge gap, we produced the cDNA sequence of the cathelicidin gene from a skin transcriptome of the Chinese spiny frog Quasipaa spinosa. The amino acid sequence of the Quasipaa spinosa cathelicidin (QS-CATH) was predicted to consist of a signal peptide, a cathelin domain, and a mature peptide. Comparative analysis of the QS-CATH amino acid sequence with that of other amphibian cathelicidins revealed high variability in the functional mature peptide among amphibians, whereas the cathelin domain was conserved. The QS-CATH gene was expressed in several tissues, with the highest level of expression in the spleen. Upregulation of QS-CATH after Aeromonas hydrophila infection occurred in the kidney, gut, spleen, skin, and liver. Chemically synthesized QS-CATH exhibited pronounced antibacterial activity against Shigella flexneri, Staphylococcus warneri, Escherichia coli, Salmonella enterica, and Listeria monocytogenes. Furthermore, QS-CATH disrupted the cell membrane integrity of S. flexneri, as evidenced by a lactate dehydrogenase release assay, and it hydrolyzed the genomic DNA of S. flexneri. Additionally, QS-CATH elicited chemotaxis and modulated the expression of inflammatory cytokine genes in RAW264.7 mouse leukemic monocyte/macrophage cells. These findings confirm the antimicrobial effects of amphibian cathelicidin and its ability to influence immune cell function. This will expedite the potential utilization of amphibian antimicrobial peptides as therapeutic agents.

Multimodal Action Quality Assessment.

Action quality assessment (AQA) is to assess how well an action is performed. Previous works perform modelling by only the use of visual information, ignoring audio information. We argue that although AQA is highly dependent on visual information, the audio is useful complementary information for improving the score regression accuracy, especially for sports with background music, such as figure skating and rhythmic gymnastics. To leverage multimodal information for AQA, i.e., RGB, optical flow and audio information, we propose a Progressive Adaptive Multimodal Fusion Network (PAMFN) that separately models modality-specific information and mixed-modality information. Our model consists of with three modality-specific branches that independently explore modality-specific information and a mixed-modality branch that progressively aggregates the modality-specific information from the modality-specific branches. To build the bridge between modality-specific branches and the mixed-modality branch, three novel modules are proposed. First, a Modality-specific Feature Decoder module is designed to selectively transfer modality-specific information to the mixed-modality branch. Second, when exploring the interaction between modality-specific information, we argue that using an invariant multimodal fusion policy may lead to suboptimal results, so as to take the potential diversity in different parts of an action into consideration. Therefore, an Adaptive Fusion Module is proposed to learn adaptive multimodal fusion policies in different parts of an action. This module consists of several FusionNets for exploring different multimodal fusion strategies and a PolicyNet for deciding which FusionNets are enabled. Third, a module called Cross-modal Feature Decoder is designed to transfer cross-modal features generated by Adaptive Fusion Module to the mixed-modality branch. Our extensive experiments validate the efficacy of the proposed method, and our method achieves state-of-the-art performance on two public datasets. Code is available at https://github.com/qinghuannn/PAMFN.

Impacts of Poverty and Lifestyles on Mortality: A Cohort Study in Predominantly Low-Income Americans.

INTRODUCTION: Low socioeconomic status has been linked to increased mortality. However, the impacts of poverty, alone or combined with health behaviors, on mortality and life expectancy have not been adequately investigated. METHODS: Data from the Southern Community Cohort Study was used, including nearly 86,000 participants recruited during 2002-2009 across 12 US southeastern states. Analysis was conducted from February 2022 to January 2023. RESULTS: During a median follow-up of 12.1 years, 19,749 deaths were identified. A strong dose-response relationship was found between household incomes and mortality, with a 3.3-fold (95%CI=3.1-3.6) increased all-cause mortality observed for individuals in the lowest income group (<$15,000/year) compared with those in the highest group (≥$50,000/year). Within each income group, mortality monotonically increased with declining healthy lifestyle score. Risk was significantly lower among those in the lowest income but healthiest lifestyle group, compared to those with the highest income but unhealthiest lifestyle (HR=0.82, 95%CI=0.69-0.97). Poor White participants appeared to experience higher all-cause mortality than poor Black participants. Life expectancy was more than 10.0 years shorter for those in the lowest income group compared with those in the highest income group. CONCLUSIONS: Poverty is strongly associated with increased risk of death, but the risks could be modestly abated by a healthier lifestyle. These findings call for a comprehensive strategy for enhancing a healthy lifestyle and improving income equality to reduce death risks, particularly among those experiencing health disparities due to poverty.

Race- and Gender-Specific Associations between Neighborhood-Level Socioeconomic Status and Body Mass Index: Evidence from the Southern Community Cohort Study.

Obesity and a low socioeconomic status (SES), measured at the neighborhood level, are more common among Americans of Black race and with a low individual-level SES. We examined the association between the neighborhood SES and body mass index (BMI) using data from 80,970 participants in the Southern Community Cohort Study, a cohort that oversamples Black and low-SES participants. BMI (kg/m2) was examined both continuously and categorically using cut points defined by the CDC. Neighborhood SES was measured using a neighborhood deprivation index composed of census-tract variables in the domains of education, employment, occupation, housing, and poverty. Generally, the participants in lower-SES neighborhoods were more likely to have a higher BMI and to be considered obese. We found effect modification by race and sex, where the neighborhood-BMI association was most apparent in White female participants in all the quintiles of the neighborhood SES (ORQ2 = 1.55, 95%CI = 1.34, 1.78; ORQ3 = 1.71, 95%CI = 1.48, 1.98; ORQ4 = 1.76, 95%CI = 1.52, 2.03; ORQ5 = 1.64, 95%SE = 1.39, 1.93). Conversely, the neighborhood-BMI association was mostly null in Black male participants (ORQ2 = 0.91, 95%CI = 0.72, 1.15; ORQ3 = 1.05, 95%CI = 0.84, 1.31; ßQ4 = 1.00, 95%CI = 0.81, 1.23; ORQ5 = 0.76, 95%CI = 0.63, 0.93). Within all the subgroups, the associations were attenuated or null in participants residing in the lowest-SES neighborhoods. These findings suggest that the associations between the neighborhood SES and BMI vary, and that other factors aside from the neighborhood SES may better predict the BMI in Black and low-SES groups.

Assessment of biomechanical properties of the new two-hole miniplate internal fixation for bony mallet finger treatment by finite element analysis.

Surgery is highly recommended for a bony mallet finger when the fracture fragment involves greater than one-third of the articular surface. K-wire based and plated-based internal fixation are widely used for mallet fracture. However, the outcomes of different surgical treatment options make the treatment of the bony mallet finger controversial due to frequent complications. The two-hole miniplate is a new and promising plate-based internal fixation treatment for the bony mallet finger with low complication rates in recent years. The aim of this study was to evaluate the biomechanical parameters (von Mises stress, strain and deformation) of the two-hole miniplate fixation compared to the traditional K-wire-based fixation using finite element analysis (FEA). Further, the biomechanical parameters of each part of the two-hole miniplate internal fixation were also analyzed. The results indicated that the two-hole miniplate model had the minimum von Mises stress value and the displacement of fracture fragment was less than 30 µm. The two-hole miniplate had an apparent compression effect on the avulsion fracture and inhibited the fracture displacement. This study would provide further guidance for clinical application in using the two-hole miniplate internal fixation.

Enhancing the Performance of Pathological Voice Quality Assessment System Through the Attention-Mechanism Based Neural Network.

OBJECTIVE: Doctors, nowadays, primarily use auditory-perceptual evaluation, such as the grade, roughness, breathiness, asthenia, and strain scale, to evaluate voice quality and determine the treatment. However, the results predicted by individual physicians often differ, because of subjective perceptions, and diagnosis time interval, if the patient's symptoms are hard to judge. Therefore, an accurate computerized pathological voice quality assessment system will improve the quality of assessment. METHOD: This study proposes a self_attention-based system, with a deep learning technology, named self_attention-based bidirectional long-short term memory (SA BiLSTM). Different pitches [low, normal, high], and vowels [/a/, /i/, /u/], were added into the proposed model, to make it learn how professional doctors evaluate the grade, roughness, breathiness, asthenia, and strain scale, in a high dimension view. RESULTS: The experimental results showed that the proposed system provided higher performance than the baseline system. More specifically, the macro average of the F1 score, presented as decimal, was used to compare the accuracy of classification. The (G, R, and B) of the proposed system were (0.768±0.011, 0.820±0.009, and 0.815±0.009), which is higher than the baseline systems: deep neural network (0.395±0.010, 0.312±0.019, 0.321±0.014) and convolution neural network (0.421±0.052, 0.306±0.043, 0.3250±0.032) respectively. CONCLUSIONS: The proposed system, with SA BiLSTM, pitches, and vowels, provides a more accurate way to evaluate the voice. This will be helpful for clinical voice evaluations and will improve patients' benefits from voice therapy.

Assessment of self-reported financial toxicity among patients with nasopharyngeal carcinoma undergoing radiotherapy: A cross-sectional study in western China.

Objective : Using the Comprehensive Score for Financial Toxicity (COST) tool to measure financial toxicity (FT) among nasopharyngeal cancer (NPC) patients in western China and investigate the association between FT and psychological distress. Methods: We conducted a cross-sectional study of survivors with NPC in a tertiary oncology hospital in China. FT was assessed using the COST (Chinese version), a validated instrument widely used both at home and abroad. The NCCN Distress Thermometer (DT) was used to measure psychological distress. A multivariate logistic regression model was built to determine factors associated with FT, and the Pearson correlation was used to assess the correlation between COST and DT scores. Results: Of 210 patients included in this study, the mean FT score was 16.3 (median: 22.5, SD: 9.7), and the prevalence of FT was 66.2% (mild FT: 37.1%, moderate FT: 50.5%, severe FT: 2.4%). Suggested by the logistic regression model, 5 variables were associated with increased FT: unemployed, no commercial insurance, receiving lower annual income, advanced cancer, and receiving targeted therapy. The Pearson correlation showed a significantly moderate correlation between financial toxicity and psychological distress (r= -0.587, P < 0.001). Conclusion: Patients with nasopharyngeal carcinoma (NPC) in western China demonstrated higher self-reported financial toxicity (FT) associated with factors including unemployed, no commercial insurance, receiving lower annual income, advanced cancer, and receiving targeted therapy. These predictors will help clinicians identify potential patients with FT in advance and conduct effective psychological interventions.

Contribution of insurance status to the association between marital status and cancer-specific survival: a mediation analysis.

OBJECTIVES: To evaluate the extent to which marriage influences cancer-specific survival (CSS) by influencing the insurance status among patients with common solid cancers and the feasibility of reducing the survival gap caused by marriage by increasing private insurance coverage for unmarried patients. SETTING: A retrospective cohort study with patients retrieved from the Surveillance, Epidemiology and End Results programme. PARTICIPANTS: Patients with nine common solid cancers diagnosed between 2007 and 2016 were included. Patients were excluded if their marital status, insurance status, socioeconomical status, stage or cause of death was unavailable, if survival time was less than 1 month, or if they were younger than 18 years at the time of diagnosis. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was CSS, which was compared between married and unmarried individuals. Mediation analyses were conducted to determine the contribution of insurance status to the association between marriage and CSS. RESULTS: Married patients had better CSS than those unmarried (time ratio 1.778; 95% CI 1.758 to 1.797). Private health insurance was a key factor mediating the association between marital status and CSS (proportion mediated (PM), 17%; 95% CI 17% to 17.1%). The PM ranges from 10.7% in prostate cancer to 20% in kidney cancer. The contribution of private insurance to the association between marital status and CSS was greater among women than among men (PM 18.5% vs 16.7%). The mediating effect of private insurance was the greatest for the comparison between married and separated individuals (PM 25.6%; 95% CI 25.3% to 25.8%) and smallest for the comparison between married and widowed individuals (PM 11.0%; 95% CI 10.9% to 11.1%). CONCLUSIONS: 17% of the marital disparities in CSS are mediated by private insurance coverage. Increasing private insurance coverage for unmarried patients may reduce the survival gap related to marital status and sex. However, it is unclear whether better publicly funded insurance would have the same effect.

Racial/Ethnic Disparities in Mortality Related to Access to Care for Major Cancers in the United States.

Importance: The reasons underlying racial/ethnic mortality disparities for cancer patients remain poorly understood, especially regarding the role of access to care. Participants: Over five million patients with a primary diagnosis of lung, breast, prostate, colon/rectum, pancreas, ovary, or liver cancer during 2004-2014, were identified from the National Cancer Database. Cox proportional hazards models were applied to estimate hazard ratios (HR) and 95% confidence intervals (CI) for total mortality associated with race/ethnicity, and access to care related factors (i.e., socioeconomic status [SES], insurance, treating facility, and residential type) for each cancer. Results: Racial/ethnic disparities in total mortality were observed across seven cancers. Compared with non-Hispanic (NH)-white patients, NH-black patients with breast (HR = 1.27, 95% CI: 1.26 to 1.29), ovarian (HR = 1.20, 95% CI: 1.17 to 1.23), prostate (HR = 1.31, 95% CI: 1.30 to 1.33), colorectal (HR = 1.11, 95% CI: 1.10 to 1.12) or pancreatic (HR = 1.03, 95% CI: 1.02 to 1.05) cancers had significantly elevated mortality, while Asians (13-31%) and Hispanics (13-19%) had lower mortality for all cancers. Racial/ethnic disparities were observed across all strata of access to care related factors and modified by those factors. NH-black and NH-white disparities were most evident among patients with high SES or those with private insurance, while Hispanic/Asian versus NH-white disparities were more evident among patients with low SES or those with no/poor insurance. Conclusions and Relevance: Racial/ethnic mortality disparities for major cancers exist across all patient groups with different access to care levels. The influence of SES or insurance on mortality disparity follows different patterns for racial/ethnic minorities versus NH-whites. Impact: Our study highlights the need for racial/ethnic-specific strategies to reduce the mortality disparities for major cancers.

Intelligent Fall-Risk Assessment Based on Gait Stability and Symmetry Among Older Adults Using Tri-Axial Accelerometry.

This study aimed to use the k-nearest neighbor (kNN) algorithm, which combines gait stability and symmetry derived from a normalized cross-correlation (NCC) analysis of acceleration signals from the bilateral ankles of older adults, to assess fall risk. Fifteen non-fallers and 12 recurrent fallers without clinically significant musculoskeletal and neurological diseases participated in the study. Sex, body mass index, previous falls, and the results of the 10 m walking test (10 MWT) were recorded. The acceleration of the five gait cycles from the midsection of each 10 MWT was used to calculate the unilateral NCC coefficients for gait stability and bilateral NCC coefficients for gait symmetry, and then kNN was applied for classifying non-fallers and recurrent fallers. The duration of the 10 MWT was longer among recurrent fallers than it was among non-fallers (p < 0.05). Since the gait signals were acquired from tri-axial accelerometry, the kNN F1 scores with the x-axis components were 92% for non-fallers and 89% for recurrent fallers, and the root sum of squares (RSS) of the signals was 95% for non-fallers and 94% for recurrent fallers. The kNN classification on gait stability and symmetry revealed good accuracy in terms of distinguishing non-fallers and recurrent fallers. Specifically, it was concluded that the RSS-based NCC coefficients can serve as effective gait features to assess the risk of falls.

Association of Healthy Lifestyles With Risk of Alzheimer Disease and Related Dementias in Low-Income Black and White Americans.

BACKGROUND AND OBJECTIVES: Although the importance of healthy lifestyles for preventing Alzheimer disease and related dementias (ADRD) has been recognized, epidemiologic evidence remains limited for non-White or low-income individuals who bear disproportionate burdens of ADRD. This population-based cohort study aims to investigate associations of lifestyle factors, individually and together, with the risk of ADRD among socioeconomically disadvantaged Americans. METHODS: In the Southern Community Cohort Study, comprising two-thirds self-reported Black and primarily low-income Americans, we identified incident ADRD using claims data among participants enrolled in Medicare for at least 12 consecutive months after age 65 years. Five lifestyle factors-tobacco smoking, alcohol consumption, leisure-time physical activity (LTPA), sleep hours, and diet quality-were each scored 0 (unhealthy), 1 (intermediate), or 2 (healthy) based on the health guidelines. A composite lifestyle score was created by summing all scores. Cox regression was used to estimate hazard ratios (HRs, 95% CIs) for incident ADRD, treating death as a competing risk. RESULTS: We identified 1,694 patients with newly diagnosed ADRD among 17,209 participants during a median follow-up of 4.0 years in claims data; the mean age at ADRD diagnosis was 74.0 years. Healthy lifestyles were individually associated with an 11%-25% reduced risk of ADRD: multivariable-adjusted HR (95% CI) was 0.87 (0.76-0.99) for never vs current smoking, 0.81 (0.72-0.92) for low-to-moderate vs no alcohol consumption, 0.89 (0.77-1.03) for ≥150 minutes of moderate or ≥75 minutes of vigorous LTPA each week vs none, 0.75 (0.64-0.87) for 7-9 hours vs >9 hours of sleep, and 0.85 (0.75-0.96) for the highest vs lowest tertiles of the Healthy Eating Index. The composite lifestyle score showed a dose-response association with up to 36% reduced risk of ADRD: multivariable-adjusted HRs (95% CIs) across quartiles were 1 (ref), 0.88 (0.77-0.99), 0.79 (0.70-0.90), and 0.64 (0.55-0.74); p trend <0.001. The beneficial associations were observed regardless of participants' sociodemographics (e.g., race, education, and income) and health conditions (e.g., history of cardiometabolic diseases and depression). DISCUSSION: Our findings support significant benefits of healthy lifestyles for ADRD prevention among socioeconomically disadvantaged Americans, suggesting that promoting healthy lifestyles and reducing barriers to lifestyle changes are crucial to tackling the growing burden and disparities posed by ADRD.

Sociocultural Factors, Access to Healthcare, and Lifestyle: Multifactorial Indicators in Association with Colorectal Cancer Risk.

Black Americans of low socioeconomic status (SES) have higher colorectal cancer incidence than other groups in the United States. However, much of the research that identifies colorectal cancer risk factors is conducted in cohorts of high SES and non-Hispanic White participants. Adult participants of the Southern Community Cohort Study (N = 75,182) were followed for a median of 12.25 years where 742 incident colorectal cancers were identified. The majority of the cohort are non-Hispanic White or Black and have low household income. Cox models were used to estimate HRs for colorectal cancer incidence associated with sociocultural factors, access to and use of healthcare, and healthy lifestyle scores to represent healthy eating, alcohol intake, smoking, and physical activity. The association between Black race and colorectal cancer was consistent and not diminished by accounting for SES, access to healthcare, or healthy lifestyle [HR = 1.34; 95% confidence interval (CI),1.10-1.63]. Colorectal cancer screening was a strong, risk reduction factor for colorectal cancer (HR = 0.65; 95% CI, 0.55-0.78), and among colorectal cancer-screened, Black race was not associated with risk. Participants with high school education were at lower colorectal cancer risk (HR = 0.81; 95% CI, 0.67-0.98). Income and neighborhood-level SES were not strongly associated with colorectal cancer risk. Whereas individual health behaviors were not associated with risk, participants that reported adhering to ≥3 health behaviors had a 19% (95% CI, 1-34) decreased colorectal cancer risk compared with participants that reported ≤1 behaviors. The association was consistent in fully-adjusted models, although HRs were no longer significant. Colorectal cancer screening, education, and a lifestyle that includes healthy behaviors lowers colorectal cancer risk. Racial disparities in colorectal cancer risk may be diminished by colorectal cancer screening. PREVENTION RELEVANCE: Colorectal cancer risk may be reduced through screening, higher educational attainment and performing more health behaviors. Importantly, our data show that colorectal cancer screening is an important colorectal cancer prevention strategy to eliminate the racial disparity in colorectal cancer risk. See related Spotlight, p. 561.

Adaptive Action Assessment.

Action assessment, the process of evaluating how well an action is performed, is an important task in human action analysis. Action assessment has experienced considerable development based on visual cues; however, existing methods neglect to adaptively learn different architectures for varied types of actions and are therefore limited in achieving high-performance assessment for each type of action. In fact, every type of action has specific evaluation criteria, and human experts are trained for years to correctly evaluate a single type of action. Therefore, it is difficult for a single assessment architecture to achieve high performance for all types of actions. However, manually designing an assessment architecture for each specific type of action is very difficult and impracticable. This work addresses this problem by adaptively designing different assessment architectures for different types of actions, and the proposed approach is therefore called the adaptive action assessment. In order to facilitate our adaptive action assessment by exploiting the specific joint interactions for each type of action, a set of graph-based joint relations is learned for each type of action by means of trainable joint relation graphs built according to the human skeleton structure, and the learned joint relation graphs can visually interpret the assessment process. In addition, we introduce using a normalized mean squared error loss (N-MSE loss) and a Pearson loss that perform automatic score normalization to operate adaptive assessment training. The experiments on four benchmarks for action assessment demonstrate the effectiveness and feasibility of the proposed method. We also demonstrate the visual interpretability of our model by visualizing the details of the assessment process.

Factors influencing women's entrepreneurial success: A multi-analytical approach.

Women entrepreneurs are significant contributors to the economic development of any country and their role becomes more vital in improving the economic condition of developing countries. This highlights the important role of women-owned small and medium enterprises (SMEs) and their entrepreneurial success. Therefore, the current study extends the entrepreneurship literature by examining the effects of factors like personality traits (PT), motivation and commitment (MC), availability of financial resources (AFR), and government support (GS) on entrepreneurial success (ES) of women-owned SMEs. Using a purposive sampling technique data from 255 women-owned SMEs were collected. A multi-analytical approach was employed to analyze the data. The Structural equation modeling (SEM) results indicated that PT, MC, AFR, and GS have a direct effect of ES whereas MC also mediated the link between PT and ES, and the results reveal that in presence of MC the effects of PT on ES become more significant. SEM results revealed that PT and AFR are the most important factors related to entrepreneurial success. On the contrary, ANN analysis revealed that "motivation and commitment" is the most influencing factor. These findings can guide business practitioners and policymakers in the envisioned strategy formulation to encourage women entrepreneurs who can contribute to their country's sustainable economic growth.

HMM-Based Fuzzy Control for Nonlinear Markov Jump Singularly Perturbed Systems With General Transition and Mode Detection Information.

In this article, the hidden Markov model (HMM)-based fuzzy control problem is addressed for slow sampling model nonlinear Markov jump singularly perturbed systems (SPSs), in which the general transition and mode detection information issue is considered. The general information issue is formulated as the one with not only the transition probabilities (TPs) and the mode detection probabilities (MDPs) being partly known but also with the certain estimation errors existing in the known elements of them. This formulation covers the cases with both the TPs and the MDPs being fully known, or one of them being fully known but another being partly known, or both them being partly known but without the certain estimation errors, which were considered in some previous literature. By utilizing the HMM with general information, some strictly stochastic dissipativity analysis criteria are derived for the slow sampling model nonlinear Markov jump SPSs. In addition, a unified HMM-based fuzzy controller design methodology is established for slow sampling model nonlinear Markov jump SPSs such that a fuzzy controller can be designed depending on whether the fast dynamics of the systems are available or not. A numerical example and a tunnel diode circuit are finally used to illustrate the validity of the obtained results.

Liquid biopsy posttreatment surveillance in endemic nasopharyngeal carcinoma: a cost-effective strategy to integrate circulating cell-free Epstein-Barr virus DNA.

BACKGROUND: The optimal posttreatment surveillance strategy for nasopharyngeal carcinoma (NPC) remains unclear. Circulating cell-free Epstein-Barr virus (cfEBV) DNA has been recognized as a promising biomarker to facilitate early detection of NPC recurrence. Therefore, we aim to determine whether integrating circulating cfEBV DNA into NPC follow-up is cost-effective. METHODS: For each stage of asymptomatic nonmetastatic NPC patients after complete remission to primary NPC treatment, we developed a Markov model to compare the cost-effectiveness of the following surveillance strategies: routine follow-up strategy, i.e., (1) routine clinical physical examination; routine imaging strategies, including (2) routine magnetic resonance imaging plus computed tomography plus bone scintigraphy (MRI + CT + BS); and (3) routine 18F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT); cfEBV DNA-guided imaging strategies, including (4) cfEBV DNA-guided MRI + CT + BS and (5) cfEBV DNA-guided PET/CT. Clinical probabilities, utilities, and costs were derived from published studies or databases. Sensitivity analyses were performed. RESULTS: For all disease stages, cfEBV DNA-guided imaging strategies demonstrated similar survival benefits but were considerably more economical than routine imaging strategies. They only required approximately one quarter of the number of imaging studies compared with routine imaging strategies to detect one recurrence. Specifically, cfEBV DNA-guided MRI + CT + BS was most cost-effective for stage II (incremental cost-effectiveness ratio [ICER] $57,308/quality-adjusted life-year [QALY]) and stage III ($46,860/QALY) patients, while cfEBV DNA-guided PET/CT was most cost-effective for stage IV patients ($62,269/QALY). However, routine follow-up was adequate for stage I patients due to their low recurrence risk. CONCLUSIONS: The cfEBV DNA-guided imaging strategies are effective and cost-effective follow-up methods in NPC. These liquid biopsy-based strategies offer evidence-based, stage-specific surveillance modalities for clinicians and reduce disease burden for patients.

Using Risk Stratification to Optimize Mammography Screening in Chinese Women.

Background: The cost-effectiveness of mammography screening among Chinese women remains contentious. Here, we characterized breast cancer (BC) epidemiology in Hong Kong and evaluated the cost-effectiveness of personalized risk-based screening. Methods: We used the Hong Kong Breast Cancer Study (a case-control study with 3501 cases and 3610 controls) and Hong Kong Cancer Registry to develop a risk stratification model based on well-documented risk factors. We used the Shanghai Breast Cancer Study to validate the model. We considered risk-based programs with different screening age ranges and risk thresholds under which women were eligible to join if their remaining BC risk at the starting age exceeded the threshold. Results: The lifetime risk (15-99 years) of BC ranged from 1.8% to 26.6% with a mean of 6.8%. Biennial screening was most cost-effective when the starting age was 44 years, and screening from age 44 to 69 years would reduce breast cancer mortality by 25.4% (95% credible interval [CrI] = 20.5%-29.4%) for all risk strata. If the risk threshold for this screening program was 8.4% (the average remaining BC risk among US women at their recommended starting age of 50 years), the coverage was 25.8%, and the incremental cost-effectiveness ratio (ICER) was US$18 151 (95% CrI = $10 408-$27 663) per quality-of-life-year (QALY) compared with no screening. The ICER of universal screening was $34 953 (95% CrI = $22 820-$50 268) and $48 303 (95% CrI = $32 210-$68 000) per QALY compared with no screening and risk-based screening with 8.4% threshold, respectively. Conclusion: Organized BC screening in Chinese women should commence as risk-based programs. Outcome data (e.g., QALY loss because of false-positive mammograms) should be systemically collected for optimizing the risk threshold.

Improving fragment-based ab initio protein structure assembly using low-accuracy contact-map predictions.

Sequence-based contact prediction has shown considerable promise in assisting non-homologous structure modeling, but it often requires many homologous sequences and a sufficient number of correct contacts to achieve correct folds. Here, we developed a method, C-QUARK, that integrates multiple deep-learning and coevolution-based contact-maps to guide the replica-exchange Monte Carlo fragment assembly simulations. The method was tested on 247 non-redundant proteins, where C-QUARK could fold 75% of the cases with TM-scores (template-modeling scores) ≥0.5, which was 2.6 times more than that achieved by QUARK. For the 59 cases that had either low contact accuracy or few homologous sequences, C-QUARK correctly folded 6 times more proteins than other contact-based folding methods. C-QUARK was also tested on 64 free-modeling targets from the 13th CASP (critical assessment of protein structure prediction) experiment and had an average GDT_TS (global distance test) score that was 5% higher than the best CASP predictors. These data demonstrate, in a robust manner, the progress in modeling non-homologous protein structures using low-accuracy and sparse contact-map predictions.

Cross-phytogroup assessment of foliar epiphytic mycobiomes.

The foliar surface forms one of the largest aboveground habitats on Earth and maintains plant-fungus relationships that greatly affect ecosystem functioning. Despite many studies with particular plant species, the foliar epiphytic mycobiome has not been studied across a large number of plant species from different taxa. Using high-throughput sequencing, we assessed epiphytic mycobiomes on leaf surfaces of 592 plant species in a botanical garden. Plants of angiosperms, gymnosperms, and pteridophytes were involved. Plant taxonomy, leaf side, growing environment, and evolutionary relationships were considered. We found that pteridophytes showed the higher fungal species diversity, stronger mutualistic fungal interactions, and a greater percentage of putative pathogens than gymnosperms and angiosperms. Plant taxonomic group, leaf side, and growing environment were significantly associated with the foliar epiphytic mycobiome, but the similarity of the mycobiomes among plants was not directly related to the distance of the host evolutionary tree. Our results provide a general understanding of the foliar fungal mycobiomes from pteridophytes to angiosperms. These findings will facilitate our understanding of foliar fungal epiphytes and their roles in plant communities and ecosystems.

Deep Learning-Guided Fiberoptic Raman Spectroscopy Enables Real-Time In Vivo Diagnosis and Assessment of Nasopharyngeal Carcinoma and Post-treatment Efficacy during Endoscopy.

In this work, we develop a deep learning-guided fiberoptic Raman diagnostic platform to assess its ability of real-time in vivo nasopharyngeal carcinoma (NPC) diagnosis and post-treatment follow-up of NPC patients. The robust Raman diagnostic platform is established using innovative multi-layer Raman-specified convolutional neural networks (RS-CNN) together with simultaneous fingerprint and high-wavenumber spectra acquired within sub-seconds using a fiberoptic Raman endoscopy system. We have acquired a total of 15,354 FP/HW in vivo Raman spectra (control: 1761; NPC: 4147; and post-treatment (PT): 9446) from 888 tissue sites of 418 subjects (healthy control: 85; NPC: 82; and PT: 251) during endoscopic examination. The optimized RS-CNN model provides an overall diagnostic accuracy of 82.09% (sensitivity of 92.18% and specificity of 73.99%) for identifying NPC from control and post-treatment patients, which is superior to the best diagnosis performance (accuracy of 73.57%; sensitivity of 89.74%; and specificity of 58.10%) using partial-least-squares linear-discriminate-analysis, proving the robustness and high spectral information sensitiveness of the RS-CNN model developed. We further investigate the saliency map of the best RS-CNN models using the correctly predicted Raman spectra. The specific Raman signatures that are related to the cancer-associated biomolecular variations (e.g., collagens, lipids, and nucleic acids) are uncovered in the map, validating the diagnostic capability of RS-CNN models to correlate with biomolecular signatures. Deep learning-based Raman spectroscopy is a powerful diagnostic tool for rapid screening and surveillance of NPC patients and can also be deployed for longitudinal follow-up monitoring of post-treatment NPC patients to detect early cancer recurrences in the head and neck.