Deciphering disulfidptosis: Uncovering a lncRNA-based signature for prognostic assessment, personalized immunotherapy, and therapeutic agent selection in lung adenocarcinoma patients.

BACKGROUND: Disulfidptosis, a recently identified type of regulated cell death, plays critical roles in various biological processes of cancer; however, whether they can impact the prognosis of lung adenocarcinoma (LUAD) remains to be fully elucidated. We aimed to adopt this concept to develop and validate a lncRNA signature for LUAD prognostic prediction. METHODS: For this study, the TCGA-LUAD dataset was used as the training cohort, and multiple datasets from the GEO database were pooled as the validation cohort. Disulfidptosis regulated genes were obtained from published studies, and various statistical methods, including Kaplan-Meier (KM), Cox, and LASSO, were used to train our gene signature DISULncSig. We utilized KM analysis, COX analysis, receiver operating characteristic analysis, time-dependent AUC analysis, principal component analysis, nomogram predictor analysis, and functional assays in our validation process. We also compared DISULncSig with previous studies. We performed analyses to evaluate DISULncSig's immunotherapeutic ability, focusing on eight immune algorithms, TMB, and TIDE. Additionally, we investigated potential drugs that could be effective in treating patients with high-risk scores. Additionally qRT-PCR examined the expression patterns of DISULncSig lncRNAs, and the ability of DISULncSig in pan-cancer was also assessed. RESULTS: DISULncSig containing twelve lncRNAs was trained and showed strong predictive ability in the validation cohort. Compared with previous similar studies, DISULncSig had more prognostic ability advantages. DISULncSig was closely related to the immune status of LUAD, and its tight relationship with checkpoints KIR2DL3, IL10, IL2, CD40LG, SELP, BTLA, and CD28 may be the key to its potential immunotherapeutic ability. For the high DISULncSig score population, we found ten drug candidates, among which epothilone-b may have the most potential. The pan-cancer analysis found that DISULncSig was a risk factor in multiple cancers. Additionally, we discovered that some of the DISULncSig lncRNAs could play crucial roles in specific cancer types. CONCLUSION: The current study established a powerful prognostic DISULncSig signature for LUAD that was also valid for most pan-cancers. This signature could serve as a potential target for immunotherapy and might help the more efficient application of drugs to specific populations.

A new statistical approach for China road freight transport at a subnational level.

Currently, there is a large deviation between official road freight data and real road freight performance at a subnational level in China. In order to deal with this deviation, the new concept of local freight tonnage and ton-kilometers is presented in this paper based on the territoriality principle, where either the origin or the destination of goods transported is local. Also, the statistic procedures and estimation models of the local freight tonnage and ton-kilometers are proposed based on five accessible basic datasets. Finally, an empirical study in Sichuan province of China is conducted. The statistical results show that there is a large amount of local freight transported by local non-commercial trucks and non-local trucks, which is ignored in the existing road freight statistics. Especially, the higher the level of local economic development, the greater the deviation between the official road freight data and the real road freight performance at a subnational level.

Assessment of a Real-world Learning Curve for the Endoscopic Resection of Gastric Gastrointestinal Stromal Tumors.

BACKGROUND: Endoscopic resection (ER) is a proven treatment for gastric gastrointestinal stromal tumors (gGISTs). We aimed to assess the learning curve (LC) associated with ER for gGISTs and identify determinants. METHODS: We conducted an analysis of 289 patients who underwent the ER of gGISTs by an experienced endoscopist. To characterize the LC, we employed cumulative sum analysis of the duration of surgery. The participants were divided into an early phase (cases 1-50) and a later phase (case 51-289), which were compared. Furthermore, we identified risk factors for the conversion from endoscopic to laparoscopic resection (LR). RESULTS: The durations of surgery and hospitalization were shorter, and there were fewer complications and fasting days in the later phase. The conversion rates to LR were 6.0% and 2.5% in the early and later phases, respectively. The tumor diameter (≥3.0 cm) and invasion beyond the muscularis propria were significant risk factors for conversion to LR (odds ratio 17.92, 95% confidence interval 2.66-120.87; and 58.03, 6.40-525.84; respectively). CONCLUSIONS: The LC for ER of gGISTs lasts for approximately 50 cases. In addition, tumors ≥3.0 cm in diameter and those that invade beyond the muscularis propria are more likely to require conversion to LR.

B1 inhomogeneity-corrected T1 mapping and quantitative magnetization transfer imaging via simultaneously estimating Bloch-Siegert shift and magnetization transfer effects.

PURPOSE: To introduce a method of inducing Bloch-Siegert shift and magnetization Transfer Simultaneously (BTS) and demonstrate its utilization for measuring binary spin-bath model parameters free pool spin-lattice relaxation ( T 1 F $$ {T}_1^{\mathrm{F}} $$ ), macromolecular fraction ( f $$ f $$ ), magnetization exchange rate ( k F $$ {k}_{\mathrm{F}} $$ ) and local transmit field ( B 1 + $$ {B}_1^{+} $$ ). THEORY AND METHODS: Bloch-Siegert shift and magnetization transfer is simultaneously induced through the application of off-resonance irradiation in between excitation and acquisition of an RF-spoiled gradient-echo scheme. Applying the binary spin-bath model, an analytical signal equation is derived and verified through Bloch simulations. Monte Carlo simulations were performed to analyze the method's performance. The estimation of the binary spin-bath parameters with B 1 + $$ {B}_1^{+} $$ compensation was further investigated through experiments, both ex vivo and in vivo. RESULTS: Comparing BTS with existing methods, simulations showed that existing methods can significantly bias T 1 $$ {T}_1 $$ estimation when not accounting for transmit B 1 $$ {B}_1 $$ heterogeneity and MT effects that are present. Phantom experiments further showed that the degree of this bias increases with increasing macromolecular proton fraction. Multi-parameter fit results from an in vivo brain study generated values in agreement with previous literature. Based on these studies, we confirmed that BTS is a robust method for estimating the binary spin-bath parameters in macromolecule-rich environments, even in the presence of B 1 + $$ {B}_1^{+} $$ inhomogeneity. CONCLUSION: A method of estimating Bloch-Siegert shift and magnetization transfer effect has been developed and validated. Both simulations and experiments confirmed that BTS can estimate spin-bath parameters ( T 1 F $$ {T}_1^{\mathrm{F}} $$ , f $$ f $$ , k F $$ {k}_{\mathrm{F}} $$ ) that are free from B 1 + $$ {B}_1^{+} $$ bias.

Pricing decisions of risk averse logistic companies with carbon cap and trade under Stackelberg game.

With the implementation of the double carbon plan, this paper considers the delivery fees of two risk averse logistics companies under carbon cap and trade mechanism. We establish logistics company Stackelberg (MS) model and retailer Stackelberg (RS) model under mean variance (MV) framework, respectively. We obtain the optimal delivery fees and retail prices. We find out that the higher degree of risk aversion can lead to a lower delivery fee. We also show that a higher carbon trading price or a higher cross price sensitivity will increase delivery fees. Moreover, we indicate that the performances of logistics companies under MS scenario are higher than that RS scenario. In addition, we suggest that under the carbon cap and trade rules, in order to obtain higher profits, logistics companies should use fuel vehicle for transportation under certain conditions, and use electric vehicle in other cases.

National and provincial burden of varicella disease and cost-effectiveness of childhood varicella vaccination in China from 2019 to 2049: a modelling analysis.

Background: In China, varicella is the third most frequently reported vaccine-preventable infectious disease after tuberculosis and influenza, and imposes a heavy burden on families and society. To inform future immunization policy, we investigated disease burden of varicella in China and explored cost-effectiveness of different varicella vaccination strategies at national and provincial levels. Methods: A dynamic transmission model was developed to assess disease burden of varicella and the impact of varicella vaccination in China. A cost-effectiveness analysis of three alternative vaccination strategies in China's National Immunization Program (NIP) compared with no vaccination was conducted. Scenario analyses and sensitivity analyses were performed to check the robustness of the results. Findings: It was estimated that 3.35 million new varicella cases occurred in 2019, more than three times of 982 thousand cases officially reported from National Notifiable Infectious Disease Surveillance System (NNIDSS). The under-reported rate was approximately 71%. The economic analysis revealed that from the societal perspective, the incremental cost-effectiveness ratio (ICER) for one dose of varicella vaccination in NIP was US$ 2357 per QALY at the national level and it was cost-effective in 22 of 31 provinces. The ICER for one dose varicella vaccination plus a mass catch-up for unvaccinated children aged 2-11 years old would be US$ -5260 per QALY, cost-saving at the national level. The one dose plus mass catch-up NIP strategy was also cost-saving in 24 of the 31 provinces. Interpretation: Varicella incident cases were substantially under-reported in China. Varicella vaccination in the NIP could significantly contribute to reducing the burden of varicella disease. From the societal perspective, including varicella vaccination into China's NIP was highly cost-effective at the national level and in most provinces. Funding: Bill & Melinda Gates Foundation.

Association between multimorbidity patterns and healthcare costs among middle-aged and older adults in China.

BACKGROUND: This study investigated multimorbidity patterns among middle-aged and older Chinese people and whether healthcare costs varied among different multimorbidity patterns. METHODS: Data were from the 2011-2018 waves of the China Health and Retirement Longitudinal Study (CHARLS). We included 20,855 unique observations with information coming from their last wave of interviews and aged at least 45 years or older. Latent class analysis (LCA) was performed to classify individuals with common multimorbidity clusters based on 14 self-reported chronic diseases. Healthcare costs were from participants' self-reports and categorized into outpatient, inpatient, and self-treatment. Two-part regression was performed to analyze the association of multimorbidity patterns with healthcare costs. RESULTS: Five multimorbidity clusters were identified: minimal disease, arthritis, cardiovascular disease (CVD), lung/asthma, and multisystem morbidity. The multisystem morbidity group had the highest use in all three types of healthcare and the highest self-treatment cost. Compared with the minimal disease group, the other four groups did not show significant differences in outpatient costs. Relative to the minimal disease group, the lung/asthma group reported lower inpatient costs. CONCLUSION: Healthcare use and costs varied across multimorbidity patterns among middle-aged and older Chinese people. Implementing an integrated care plan for multimorbidity is suggested to improve the cost-effectiveness of healthcare provision and reduce the financial burden of the healthcare system. Reimbursement policy design should also take multimorbidity patterns into account.

Continual Learning for Blind Image Quality Assessment.

The explosive growth of image data facilitates the fast development of image processing and computer vision methods for emerging visual applications, meanwhile introducing novel distortions to processed images. This poses a grand challenge to existing blind image quality assessment (BIQA) models, which are weak at adapting to subpopulation shift. Recent work suggests training BIQA methods on the combination of all available human-rated IQA datasets. However, this type of approach is not scalable to a large number of datasets and is cumbersome to incorporate a newly created dataset as well. In this paper, we formulate continual learning for BIQA, where a model learns continually from a stream of IQA datasets, building on what was learned from previously seen data. We first identify five desiderata in the continual setting with three criteria to quantify the prediction accuracy, plasticity, and stability, respectively. We then propose a simple yet effective continual learning method for BIQA. Specifically, based on a shared backbone network, we add a prediction head for a new dataset and enforce a regularizer to allow all prediction heads to evolve with new data while being resistant to catastrophic forgetting of old data. We compute the overall quality score by a weighted summation of predictions from all heads. Extensive experiments demonstrate the promise of the proposed continual learning method in comparison to standard training techniques for BIQA, with and without experience replay. We made the code publicly available at https://github.com/zwx8981/BIQA_CL.

High-order robust control and Stackelberg game-based optimization for uncertain fuzzy PMSM system with inequality constraints.

There exist the uncertainties and the inequality constraints in permanent magnet synchronous motor (PMSM) system. In order to meet the safety control requirements in industrial applications, the state transformation is used to meet the inequality constraints for limiting the outputs within desired bounds. Then, fuzzy set theory, which is different from fuzzy logic, is used to describe uncertainty, and the fuzzy PMSM dynamical model is established. Based on that, a robust control with high-order term is proposed to compensate for the time-varying uncertainty. Furthermore, for improving the system performance and decreasing the control cost, the Stackelberg game is introduced into the optimization scheme design, in which the leader plays a more important role than follower. These characteristic corresponds to the influence of the two tunable control parameters on the system. Thus, the optimal parameters are obtained by the rules of Stackelberg game. Finally, experimental results show the effectiveness of the above theories.

The Evaluation Indexes Suitable for Nonhuman Primates can be Extracted from Clinical Consciousness Disorder Assessment Scales: A Hypothesis.

BACKGROUND: Currently, case studies or clinical trials in different patient populations remain the main resource underlying the understanding of disorder of consciousness (DoC). This provides a low efficacy for the derivation of data and the implementation of associated controlled experimental designs. Preclinical models provide precise controls, reduced variability, rich data output and limited ethical complexity. Nonhuman primates are suitable model animals for disorders of consciousness due to their brain structure being very similar to that of humans. Behavioral tests remain the primary standard for assessing the consciousness status of humans. However, there is currently no behavioral assessment scale available for evaluation of the state of consciousness disorder in nonhuman primates. This presents a significant challenge for the establishment of different models of consciousness disorder. Therefore, there is considerable motivation to focus on the development of a proper tool for assessment of the state of consciousness associated with nonhuman primate models that are based on clinically common consciousness assessment scales. METHODS: It is assumed that the Delphi and level analysis methods based on clinical consciousness disorder assessment scales may provide an effective way to select and include assessment indexes for levels of consciousness in nonhuman primates. RESULTS: 8 first-level indicators with 41 second-level indexes were selected preliminary as a pool of evaluation entries of state of consciousness of nonhuman primates. CONCLUSIONS: It may be practicable to extract appropriate indicators for non-human primates from the clinical consciousness disorder assessment scales. Besides, a combination of Delphi method, behavioral analysis, electroencephalography, neuroimaging (such as positron emission tomography-computed tomography) and functional magnetic resonance imaging is necessary to test the reliability and validity of the novel scale reported here.

Asynchronous Intermittent Regulation of Human Arm Movement with Markovian Jumping Parameters.

In this paper, the regulation stability problem of the human arm continuous movement is investigated based on Markovian jumping parameters. In particular, the intermittent control mechanism is adopted in the arm movement regulation procedure to model the human intermittent motor control strategy. Furthermore, by taking into account the Markovian jumping parameters with different modes, the asynchronous regulation issue is proposed to model mode mismatch between the motor control and arm movement. On the basis of model transformation, sufficient stability conditions are established during the arm movements, and the desired regulation gain can be obtained by the convex optimization method. In the end, an illustrative example is presented to show the applicability and effectiveness of our developed model and optimized regulation approach.

The IFRS adoption, accounting quality, and banking performance: An evaluation of susceptibilities and financial stability in developing economies.

International Financial Reporting Standards (IFRS) 's adoption increased attention to International Accounting Standard Regulations worldwide. It has opened the door for empirical analysis having different perceptions of mandatory IFRS adoption. This paper's main objective is to examine the impact of accounting quality and IFRS adoption on Pakistan's banking sector efficiency. We have employed the Malmquist productivity index, Roychowdhury's Earnings Management, and modified learner index to conduct the empirical analysis. The results mean how much banking sector efficiency is affected by accounting quality and IFRS adoption. The results demonstrate that the banking sector efficiency significantly increases through accounting quality and IFRS. Furthermore, it can be seen that the foreign banks' efficiency in Pakistan is less than other banks compared to public or private banks. Additionally, more earnings timeliness has been noted in large banks than medium and small banks in Pakistan. Preferably, the practice of quality accounting relies on disclosed information through financial statements. In contrast, the organizations may evade the losses once the information quality is precise and appropriate. The study provides valuable information to managers and other stakeholders.

Evaluation of Traumatic Subdural Hematoma Volume by Using Image Segmentation Assessment Based on Deep Learning.

Rapid and accurate evaluations of hematoma volume can guide the treatment of traumatic subdural hematoma. We aim to explore the consistency between the measurement results of traumatic subdural hematoma (TSDH) using a deep learn-based image segmentation algorithm. A retrospective study was conducted on 90 CT images of patients diagnosed with TSDH in our hospital from January 2019 to January 2022. All image data were measured by manual segmentation, convolutional neural networks (CNN) algorithm segmentation, and ABC/2 volume formula. With manual segmentation as the "golden standard," a consistency test was carried out with CNN algorithm segmentation and ABC/2 volume formula, respectively. The percentage error of CNN algorithm segmentation is less than ABC/2 volume formula. There is no significant difference between CNN algorithm segmentation and manual segmentation (P > 0.05). The area under curve of the ABC/2 volume formula, manual segmentation, and CNN algorithm segmentation is 0.811 (95% CI: 0.717~0.905), 0.840 (95% CI: 0.753~0.928), and 0.832 (95% CI: 0.742~0.922), respectively. From our results, the algorithm based on CNN has a good efficiency in segmentation and accurate calculation of TSDH hematoma volume.

Finite-Time Asynchronous Event-Triggered Formation of UAVs with Semi-Markov-Type Topologies.

In this paper, the finite-time formation problem of UAVs is investigated with consideration of semi-Markov-type switching topologies. More precisely, finite-time passivity performance is adopted to overcome the dynamical effect of disturbances. Furthermore, an asynchronous event-triggered communication scheme is proposed for more efficient information exchanges. The mode-dependent formation controllers are designed in terms of the Lyapunov-Krasovskii method, such that the configuration formation can be accomplished. Finally, simulation results are given to demonstrate the validity of the proposed formation approach.

Finite-frequency control for nonlinear semi-Markov jump systems with piecewise transition probabilities.

Considering the frequency effect of external disturbances, this paper concerns the finite-frequency control problem for nonlinear semi-Markov jump systems (SMJSs) with piecewise transition probabilities (TPs) via the Takagi-Sugeno (T-S) fuzzy modeling approach. More precisely, the piecewise TPs are assumed to switch stochastically within limits, which implies that the corresponding distributions of sojourn time (ST) also vary randomly. Furthermore, another upper semi-Markov chain is utilized to characterize TPs variation in a finite set. With the aid of Finsler's lemma and Parseval's theorem, sufficient criteria for the controlled SMJS are constructed to meet the desired disturbance attenuation performance in the frequency domain. Then, the mode-dependent controllers are developed to use the TP information more efficiently. In particular, a novel matrix method is proposed to decouple the mode-dependent variables and controller gains by selecting slack matrices. Eventually, a numerical example is transmitted to demonstrate the validity and merits of established results.

Research on the Relationship between Chinese Elderly Health Status, Social Security, and Depression.

(1) Background: To explore the relationship between health status, social security status, and the occurrence of depression in older adults and provide a basis for mental health care services for the elderly population; (2) Methods: This study used the 2018 China Health and Senior Care Tracking Survey (CHARLS) data to select 8383 older people aged over 60 years old as the research subjects. The two-category Logistic model was used to analyze the research problem; (3) Results: Older adults with depressive tendencies accounted for 34.1% of the total older adults. The incidence of depression among female older adults reached 41.51%. The risk of depression in the elderly population was 40.3% lower in males than in females (OR = 0.597, 95% CI: 0.539−0.662). Self-rated health status, physical disability, and receipt of pensions affected the incidence of depression in older adults (all p < 0.05); (4) Conclusions: Focus on and intervene in the mental status of elderly females and disabled elderly people. Provide mental and economic support and mental health care services to the elderly at the family and social levels. Promote the healthy development of the mental health of the elderly and promote active aging.

Assessment of effect on water quality by hybrid constructed floating treatment wetlands in the low flow urban rivers.

In this study, the effect of hybrid constructed floating treatment wetlands (FTWs) in a low-flow urban river was evaluated, and the influence radius on dissolved oxygen (DO), ammonia nitrogen (NH4+-N), and total phosphorus (TP) under different flow conditions was quantified. It was found that DO considerably increased and NH4+-N and TP decreased at the outlet after treatment with hybrid constructed FTW. The NH4+-N removal rate continued to increase to 72.03%, whereas that for TP decreased to 63.16% with fluctuation. The cloud picture of the influence radius showed that when DO ≤ 3 mg/L, Rflow ≈ 5 m, Rstill ≈ 3 m, and when DO > 3 mg/L, Rflow = Rstill ≈ 8 m. For NH4+-N under flow conditions, Rflow ≈ 8 m, whereas under still conditions when NH4+-N ≤ 7 mg/L, Rstill ≈ 5 m, and when NH4+-N > 7 mg/L, the concentration changes were not considerable. When TP ≤ 0.4 mg/L, Rflow ≈ 5 m, and when TP > 0.4 mg/L, Rflow ≈ 8 m; while under still conditions, when TP ≤ 0.8 mg/L, Rstill ≈ 5 m, and when TP > 0.8 mg/L, the concentration changes were not remarkable. Various water quality parameters and water flow affected the radius of influence of FTW on DO, NH4+-N, and TP at the spatial level. For the same water quality parameter, the influence radius in the flow state was larger than that in the still state (Rflow ≥ RStill). This study evaluated treatment efficiency of the hybrid constructed FTW in urban rivers and provided guidance and support for FTW deployment in future.

Distributed nonsynchronous event-triggered state estimation of genetic regulatory networks with hidden Markovian jumping parameters.

In this paper, the distributed state estimation problem of genetic regulatory networks (GRNs) with hidden Markovian jumping parameters (HMJPs) is explored. Furthermore, in order to improve the communication efficiency among state estimation sensors, the event-triggered strategy is employed in the distributed framework for sensor networks. Particularly, by considering the fact that the true modes are always unaccessible, a novel nonsynchronous state estimation (NSE) strategy is utilized based on observed hidden mode information. By means of Lyapunov-Krasovski method, sufficient stochastic state estimation analysis and synthesis results are established, such that the concentrations of mRNA and protein in GRNs can be both well estimated by convex optimization. Finally, an illustrative example with relevant simulations results is provided to validate the applicability and effectiveness of the developed state estimation approach.

The Lifetime Cost Estimation of Human Papillomavirus-related Diseases in China: A Modeling Study.

OBJECTIVES: To estimate the lifetime treatment costs of patients with human papillomavirus (HPV) infection-related diseases in China and to provide cost estimates for the economic evaluation of HPV intervention strategies. METHODS: We extracted real-world hospital data from 2012 to 2019 and screened for subjects who met the criteria of clinical diagnosis of HPV-related diseases to obtain country-specific inputs into a Markov decision model. The model simulated lifetime treatment costs for HPV from the perspective of a national payer. A 5% discount rate was applied. Costs were converted and inflated to 2020 US dollars (USD). RESULTS: Using 2021 as the base year, the lifetime costs per patient for carcinoma in situ, local metastasis, and distant metastasis cervical cancer are $24,208 (95%CI: 18,793-30,897), $19,562 (95%CI: 14,456-25,567), and $17,599 (95%CI: 10,604-25,807), respectively. For carcinoma in situ, local metastasis, and distant metastasis vaginal cancer, the lifetime costs are $17,593 (95%CI: 14,962-23,596), $17,120 (95%CI: 13,215-22,417), and $22,411 (95%CI: 12,172-22,249), respectively. The base-case lifetime cost per patient for different stages of vulvar cancer/penile cancer/anal cancer/oral cancer/oropharyngeal cancer/laryngeal cancer falls within $17,120-$58,236. CONCLUSIONS: Using real-world data, we calculated lifetime treatment costs of HPV-related cancer in China and found that the lifetime cost for patients exceeded $17,000 for various stages of disease. The national burden of HPV-related disease could be significantly reduced by eliminating HPV infection.