Thalassaemia in China.

Because of successful thalassaemia prevention programmes in resource-rich countries and it's huge population China now has the greatest number of new cases of thalassaemia globally as well as more people with thalassaemia than any other country. 30 million Chinese have thalassaemia-associated mutations and about 300,000 have thalassaemia major or intermedia requiring medical intervention. Over the past 2 decades there has been tremendous economic growth in China including per capita spending on health care. There is now nation-wide availability and partial or full insurance for prenatal genetic testing, RBC-transfusions, iron-chelating drugs and haematopoietic cell transplants. Prenatal screening and educational programmes have reduced the incidence of new cases. However, substantial challenges remain. For example, regional differences in access to medical care and unequal economic development require innovations to reduce the medical, financial and psychological burdens of Chinese with thalassaemia and their families. In this review we discuss success in preventing and treating thalassaemia in China highlighting remaining challenges. Our discussion has important implications for resource-poor geospaces challenged with preventing and treating thalassaemia.

Immune checkpoint inhibitor-related adverse events in lung cancer: Real-world incidence and management practices of 1905 patients in China.

BACKGROUND: Immune checkpoint inhibitors (ICIs) are the standard treatment for advanced lung cancer, but immune-related adverse events (irAEs) remain poorly understood, especially in a real-world setting. METHODS: A multicenter observational study was conducted. Medical records of lung cancer patients treated with ICIs at 26 hospitals from January 1, 2015, to February 28, 2021, were retrieved. Types of ICIs included antiprogrammed cell death 1 or antiprogrammed cell death ligand 1 (PD-L1) monotherapy, anticytotoxic T-lymphocyte antigen-4 monotherapy, or combination therapy. RESULTS: In total, 1905 patients with advanced lung cancer were evaluated. The median age was 63 (range 28-87) years, and the male/female ratio was 3.1:1 (1442/463). The primary histological subtype was adenocarcinoma (915). A total of 26.9% (512/1905) of the patients developed 671 irAEs, and 5.8% (110/1905) developed 120 grade 3-5 irAEs. Median duration from ICI initiation to irAEs onset was 56 (range 0-1160) days. The most common irAEs were thyroid dysfunction (7.2%, 138/1905), pneumonitis (6.5%, 124/1905), and dermatological toxicities (6.0%, 115/1905). A total of 162 irAEs were treated with steroids and 11 irAEs led to death. Patients with positive PD-L1 expression (≥1%) and who received first-line ICI treatment developed more irAEs. Patients who developed irAEs had a better disease control rate (DCR, 71.3% [365/512] vs. 56.0% [780/1145]; p < 0.001). CONCLUSIONS: The incidence rate of irAEs was 26.9% in a real-world setting. IrAEs might be related to a better DCR, but clinicians should be more aware of irAE recognition and management in clinical practice.

Survey of health literacy level and related influencing factors in military college students in Chongqing, China: A cross-sectional analysis.

Health literacy (HL) has become an important public health issue and is receiving growing attention. However, the HL levels of military college students in China have never been analyzed. This study aimed to investigate the HL and related associate factors in military college students in Chongqing, China. Data was obtained with the "Chinese Citizen Health Literacy Questionnaire (2012 edition)" from 3183 military college students aged 16-28 years at Chongqing in December 2015. A total score of ≥80 points determined adequate HL, and HL level was defined as the proportion of students who had adequate HL out of the total number of participants. Multiple logistic regression analysis with a stepwise forward likelihood ratio (LR) method was used to determine the effects of sociodemographic characteristics, health-related behaviors, and family-related factors on HL level. The mean score of HL was 68.56, and the HL level of military college students was 21.05%; the overall knowledge rate was 71.33%. The independent factors that were associated with HL level were years in college, educational system, time playing online games, annual household income and father's education level. Senior (odds ratio [OR] = 1.229, 95% confidence interval [CI] 1.018∼1.484), undergraduate (OR = 1.509, 95% CI 1.151∼1.978), time played games more than 5 hours each week (OR = 0.638, 95% CI 0.486∼0.837), annual household incomes more than 50,000 yuan (OR = 1.231, 95% CI 1.027∼1.476) and father's education level (high school: OR = 2.327, 95% CI 1.186∼4.565; university: OR = 2.450, 95% CI 1.244∼4.825), were independently associated with higher HL level. HL levels of military college students in Chongqing need to be improved across the board. Our data suggests that special emphasis should be placed on students in junior and those in the specialist educational system. School departments may also benefit from incorporating health literacy into their curricula and helping students manage the time they spend playing online games.

Relationships of multimorbidity and income with hospital admissions in 3 health care systems.

Associations of multimorbidity and income with hospital admission were investigated in population samples from 3 widely differing health care systems: Scotland (n = 36,921), China (n = 162,464), and Hong Kong (n = 29,187). Multimorbidity increased odds of admissions in all 3 settings. In Scotland, poorer people were more likely to be admitted (adjusted odds ratio [aOR] = 1.62; 95% CI, 1.41-1.86 for the lowest income group vs the highest), whereas China showed the opposite (aOR = 0.58; 95% CI, 0.56-0.60). In Hong Kong, poorer people were more likely to be admitted to public hospitals (aOR = 1.68; 95% CI, 1.36-2.07), but less likely to be admitted to private ones (aOR = 0.18; 95% CI, 0.13-0.25). Strategies to improve equitable health care should consider the impact of socioeconomic deprivation on the use of health care resources, particularly among populations with prevalent multimorbidity.

Is extreme learning machine feasible? A theoretical assessment (part I).

An extreme learning machine (ELM) is a feedforward neural network (FNN) like learning system whose connections with output neurons are adjustable, while the connections with and within hidden neurons are randomly fixed. Numerous applications have demonstrated the feasibility and high efficiency of ELM-like systems. It has, however, been open if this is true for any general applications. In this two-part paper, we conduct a comprehensive feasibility analysis of ELM. In Part I, we provide an answer to the question by theoretically justifying the following: 1) for some suitable activation functions, such as polynomials, Nadaraya-Watson and sigmoid functions, the ELM-like systems can attain the theoretical generalization bound of the FNNs with all connections adjusted, i.e., they do not degrade the generalization capability of the FNNs even when the connections with and within hidden neurons are randomly fixed; 2) the number of hidden neurons needed for an ELM-like system to achieve the theoretical bound can be estimated; and 3) whenever the activation function is taken as polynomial, the deduced hidden layer output matrix is of full column-rank, therefore the generalized inverse technique can be efficiently applied to yield the solution of an ELM-like system, and, furthermore, for the nonpolynomial case, the Tikhonov regularization can be applied to guarantee the weak regularity while not sacrificing the generalization capability. In Part II, however, we reveal a different aspect of the feasibility of ELM: there also exists some activation functions, which makes the corresponding ELM degrade the generalization capability. The obtained results underlie the feasibility and efficiency of ELM-like systems, and yield various generalizations and improvements of the systems as well.

Is extreme learning machine feasible? A theoretical assessment (part II).

An extreme learning machine (ELM) can be regarded as a two-stage feed-forward neural network (FNN) learning system that randomly assigns the connections with and within hidden neurons in the first stage and tunes the connections with output neurons in the second stage. Therefore, ELM training is essentially a linear learning problem, which significantly reduces the computational burden. Numerous applications show that such a computation burden reduction does not degrade the generalization capability. It has, however, been open that whether this is true in theory. The aim of this paper is to study the theoretical feasibility of ELM by analyzing the pros and cons of ELM. In the previous part of this topic, we pointed out that via appropriately selected activation functions, ELM does not degrade the generalization capability in the sense of expectation. In this paper, we launch the study in a different direction and show that the randomness of ELM also leads to certain negative consequences. On one hand, we find that the randomness causes an additional uncertainty problem of ELM, both in approximation and learning. On the other hand, we theoretically justify that there also exist activation functions such that the corresponding ELM degrades the generalization capability. In particular, we prove that the generalization capability of ELM with Gaussian kernel is essentially worse than that of FNN with Gaussian kernel. To facilitate the use of ELM, we also provide a remedy to such a degradation. We find that the well-developed coefficient regularization technique can essentially improve the generalization capability. The obtained results reveal the essential characteristic of ELM in a certain sense and give theoretical guidance concerning how to use ELM.

Epidemiology of multimorbidity in China and implications for the healthcare system: cross-sectional survey among 162,464 community household residents in southern China.

BACKGROUND: China, like other countries, is facing a growing burden of chronic disease but the prevalence of multimorbidity and implications for the healthcare system have been little researched. We examined the epidemiology of multimorbidity in southern China in a large representative sample. The effects of multimorbidity and other factors on usual source of healthcare were also examined. METHODS: We conducted a large cross-sectional survey among approximately 5% (N = 162,464) of the resident population in three prefectures in Guangdong province, southern China in 2011. A multistage, stratified random sampling was adopted. The study population had many similar characteristics to the national census population. Interviewer-administered questionnaires were used to collect self-report data on demographics, socio-economics, lifestyles, healthcare use, and health characteristics from paper-based medical reports. RESULTS: More than one in ten of the total study population (11.1%, 95% confidence interval (CI) 10.6 to 11.6) had two or more chronic conditions from a selection of 40 morbidities. The prevalence of multimorbidity increased with age (adjusted odds ratio (aOR) = 1.36, 95% CI 1.35 to 1.38 per five years). Female gender (aOR = 1.70, 95% CI 1.64 to 1.76), low education (aOR = 1.26, 95% CI 1.23 to 1.29), lack of medical insurance (aOR = 1.79, 95% CI 1.71 to 1.89), and unhealthy lifestyle behaviours were independent predictors of multimorbidity. Multimorbidity was associated with the regular use of secondary outpatient care in preference to primary care. CONCLUSIONS: Multimorbidity is now common in China. The reported preferential use of secondary care over primary care by patients with multimorbidity has many major implications. There is an urgent need to further develop a strong and equitable primary care system.

Adaptive synchronization for neutral-type neural networks with stochastic perturbation and Markovian switching parameters.

In this paper, the problem of adaptive synchronization is investigated for stochastic neural networks of neutral-type with Markovian switching parameters. Using the M-matrix approach and the stochastic analysis method, some sufficient conditions are obtained to ensure three kinds of adaptive synchronization for the stochastic neutral-type neural networks. These three kinds of adaptive synchronization include the almost sure asymptotical synchronization, exponential synchronization in p th moment and almost sure exponential synchronization. Some numerical examples are provided to illustrate the effectiveness and potential of the proposed design techniques.

Assessment of iron overload in very young children with limited thalassemia care resources in South China.

Southern China has one of the world's largest population of patients needing transfusions. Transfusion and chelation are not uniformly available and no magnetic resonance imaging (MRI) assessment data exists to date. A total of 153 young ß-thalassemia major (ß-TM) patients were assessed using a validated 1.5T scanner in Hong Kong, People's Republic of China (PRC). Their median age was 13 (range 7 to 30), and most patients were young (22.0% age <10, 73.0% age <15, 88.0% age <18). Erratic health care made estimation of total transfusion and chelation exposure impossible. Despite their early age, 24.0% had severe cardiac hemosiderosis [T2*<10 milliseconds (ms)], at ages as early as 8 years old. Median heart iron was 1.68 mg/g dry weight (range 0.19-7.66) and increased with age (p = 0.017), while liver iron was 22.2 mg/g dry weight (range 3.15 to 39.2). Serum ferritin levels were poor predictors of heart and liver, or pancreatic R* and pituitary R* values. Magnetic resonance imaging scans are needed to screen very young ß-TM patients with immediate risk of premature cardiac death in developing nations and triage them to more intensive treatment. This is particularly important in countries with a large number of patients and limited resources. Our data suggests that in developing countries, there is no lower limit for thalassemia MRI scanning programs.

Predicting secretory proteins of malaria parasite by incorporating sequence evolution information into pseudo amino acid composition via grey system model.

The malaria disease has become a cause of poverty and a major hindrance to economic development. The culprit of the disease is the parasite, which secretes an array of proteins within the host erythrocyte to facilitate its own survival. Accordingly, the secretory proteins of malaria parasite have become a logical target for drug design against malaria. Unfortunately, with the increasing resistance to the drugs thus developed, the situation has become more complicated. To cope with the drug resistance problem, one strategy is to timely identify the secreted proteins by malaria parasite, which can serve as potential drug targets. However, it is both expensive and time-consuming to identify the secretory proteins of malaria parasite by experiments alone. To expedite the process for developing effective drugs against malaria, a computational predictor called "iSMP-Grey" was developed that can be used to identify the secretory proteins of malaria parasite based on the protein sequence information alone. During the prediction process a protein sample was formulated with a 60D (dimensional) feature vector formed by incorporating the sequence evolution information into the general form of PseAAC (pseudo amino acid composition) via a grey system model, which is particularly useful for solving complicated problems that are lack of sufficient information or need to process uncertain information. It was observed by the jackknife test that iSMP-Grey achieved an overall success rate of 94.8%, remarkably higher than those by the existing predictors in this area. As a user-friendly web-server, iSMP-Grey is freely accessible to the public at http://www.jci-bioinfo.cn/iSMP-Grey. Moreover, for the convenience of most experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results without the need to follow the complicated mathematical equations involved in this paper.

Synchronization of stochastic delayed neural networks with markovian switching and its application.

In this paper, the problem of adaptive synchronization for a class of stochastic neural networks (SNNs) which involve both mixed delays and Markovian jumping parameters is investigated. The mixed delays comprise the time-varying delays and distributed delays, both of which are mode-dependent. The stochastic perturbations are described in terms of Browian motion. By the adaptive feedback technique, several sufficient criteria have been proposed to ensure the synchronization of SNNs in mean square. Moreover, the proposed adaptive feedback scheme is applied to the secure communication. Finally, the corresponding simulation results are given to demonstrate the usefulness of the main results obtained.

Real-time human identification using a pyroelectric infrared detector array and hidden Markov models.

This paper proposes a real-time human identification system using a pyroelectric infrared (PIR) detector array and hidden Markov models (HMMs). A PIR detector array with masked Fresnel lens arrays is used to generate digital sequential data that can represent a human motion feature. HMMs are trained to statistically model the motion features of individuals through an expectation-maximization (EM) learning process. Human subjects are recognized by evaluating a set of new feature data against the trained HMMs using the maximum-likelihood (ML) criterion. We have developed a prototype system to verify the proposed method. Sensor modules with different numbers of detectors and different sampling masks were tested to maximize the identification capability of the sensor system.

[Primary assessment of treatment effect of thymosin alpha1 on chemotherapy-induced neurotoxicity].

BACKGROUND & OBJECTIVE: Clinical trails showed that thymosin alpha1 offers protection from toxicities (nausea, vomiting, fatigue) of chemotherapy. This study was designed to investigate the protection of thymosin alpha1 to nervous system. METHODS: Twenty-two patients with advanced lung cancer, or advanced breast cancer were treated with vinorelbine (25 mg/m(2), d(1), d(8)) combined with cisplatin (80 mg/m(2), d(1)), or gemcitabine (1.25 g/m(2), d(1), d(8)) combined with cisplatin (80 mg/m(2), d(1)),or paclitaxel (80 mg/m(2), d(1), d(8), d(15)) combined with carboplatin (AUC=6 d(1)),or paclitaxel (80 mg/m(2), d(1), d(8), d(15)) combined with epirubicin (80 mg/m(2), d(1)). They all experienced grade 2 to 4 of neurotoxicities according to common toxicity criteria of National Cancer Institute after chemotherapy. The same chemotherapy regimens were combined with thymosin alpha1 (1.6 mg/d for 4 days before chemotherapy, and 1.6 mg twice weekly for 1-3 weeks after chemotherapy began) in the next cycle. Clinical neurologic evaluation was performed at baseline every week. RESULTS: In 10 patients (45.4%), neurotoxicities reduced from grade 2-4 before chemotherapy to less than grade 2 after chemotherapy. CONCLUSION: Thymosin alpha1 may prevent patients from chemotherapy-induced neurotoxicities.

An assessment of World Health Organization criteria for severe acute respiratory syndrome in patients with cancer.

BACKGROUND: The differential diagnosis of severe acute respiratory syndrome (SARS) in patients with cancer can be challenging. Although diagnostic criteria for SARS have been issued by the World Health Organization (WHO), simple adoption of the established criteria may lead to overdiagnosis in patients with cancer or to an increase in the risk of spreading SARS within cancer hospitals. METHODS: The authors report their experience with the exclusion and quarantine of patients with cancer during the peak of the SARS epidemic in Beijing, China. The patients included 4 males and 7 females with a median age of 66 years (range, 39-73 years). RESULTS: All 11 patients met the WHO diagnostic criteria for probable SARS. Among those 11 patients with probable SARS, only 1 had confirmed SARS; for the other 10 patients, the possibility of SARS infection was ruled out. CONCLUSIONS: Special attention must be paid to patients with cancer who have symptoms similar to those seen in SARS. Although the WHO diagnostic criteria for SARS should be widely accepted, they are not definite or practical in certain populations.