The correlation of osteoporosis to clinical features: a study of 4382 Female Cases of a Hospital Cohort with musculoskeletal symptoms in Southwest China

<p>Abstract</p> <p>Background</p> <p>By analyzing the clinical features and risk factors in female patients with musculoskeletal symptoms of Southwest China, this report presents the initial analysis of characteristics in this region and compared with international evaluative criteria.</p> <p>Methods</p> <p>Diagnosis of osteoporosis (OP) was made in female hospital patients age ≥ 18 years admitted from January 1998 to December 2008 according to WHO definition. Case data were analyzed by symptoms, age, disease course and risk factors to reveal correlation with diagnosis of OP. Logistic regression was used to identify the risks of osteoporosis.</p> <p>Results</p> <p>A total of 4382 patients were included in the analysis of the baseline characteristics, among which 1455 in the OP group and 2927 in the non-OP group. The morbidity of OP <b/>is significantly increased in females' ≥ 50 years. Both groups had symptoms related to pain and numbness; no significant difference was found in reported upper and lower back pain, or leg pain between two groups (<it>p </it>> 0.05). Neck, shoulder and arm pain, leg and arm numbness were more common in the non-osteoporosis group (p < 0.05, OR < 1, and upper limit of 95% CI of OR < 1). Hypertension, diabetes, hyperostosis were major risk factors for the patients with OP. The most common lifestyle-related risk factors for osteoporosis were smoking, body mass index, lack of physical activity and menopause.</p> <p>Conclusions</p> <p>The present study offers the first reference data of the relationship between epidemiologic distribution of osteoporosis and associated factors in adults Chinese women. These findings provide a theoretical basis for its prevention and treatment in developing country.</p

Advances in Processing, Mining, and Learning Complex Data: From Foundations to Real-World Applications

Processing, mining, and learning complex data refer to an advanced study area of data mining and knowledge discovery concerning the development and analysis of approaches for discovering patterns and learning models from data with a complex structure (e.g., multirelational data, XML data, text data, image data, time series, sequences, graphs, streaming data, and trees) [1–5]. These kinds of data are commonly encountered in many social, economic, scientific, and engineering applications. Complex data pose new challenges for current research in data mining and knowledge discovery as they require new methods for processing, mining, and learning them. Traditional data analysis methods often require the data to be represented as vectors [6]. However, many data objects in real-world applications, such as chemical compounds in biopharmacy, brain regions in brain health data, users in business networks, and time-series information in medical data, contain rich structure information (e.g., relationships between data and temporal structures). Such a simple feature-vector representation inherently loses the structure information of the objects. In reality, objects may have complicated characteristics, depending on how the objects are assessed and characterized. Meanwhile, the data may come from heterogeneous domains [7], such as traditional tabular-based data, sequential patterns, graphs, time-series information, and semistructured data. Novel data analytics methods are desired to discover meaningful knowledge in advanced applications from data objects with complex characteristics. This special issue contributes to the fundamental research in processing, mining, and learning complex data, focusing on the analysis of complex data sources

Advances in Processing, Mining, and Learning Complex Data: From Foundations to Real-World Applications

Processing, mining, and learning complex data refer to an advanced study area of data mining and knowledge discovery concerning the development and analysis of approaches for discovering patterns and learning models from data with a complex structure (e.g., multirelational data, XML data, text data, image data, time series, sequences, graphs, streaming data, and trees) [1–5]. These kinds of data are commonly encountered in many social, economic, scientific, and engineering applications. Complex data pose new challenges for current research in data mining and knowledge discovery as they require new methods for processing, mining, and learning them. Traditional data analysis methods often require the data to be represented as vectors [6]. However, many data objects in real-world applications, such as chemical compounds in biopharmacy, brain regions in brain health data, users in business networks, and time-series information in medical data, contain rich structure information (e.g., relationships between data and temporal structures). Such a simple feature-vector representation inherently loses the structure information of the objects. In reality, objects may have complicated characteristics, depending on how the objects are assessed and characterized. Meanwhile, the data may come from heterogeneous domains [7], such as traditional tabular-based data, sequential patterns, graphs, time-series information, and semistructured data. Novel data analytics methods are desired to discover meaningful knowledge in advanced applications from data objects with complex characteristics. This special issue contributes to the fundamental research in processing, mining, and learning complex data, focusing on the analysis of complex data sources

UbiPhysio: Support Daily Functioning, Fitness, and Rehabilitation with Action Understanding and Feedback in Natural Language

We introduce UbiPhysio, a milestone framework that delivers fine-grained action description and feedback in natural language to support people's daily functioning, fitness, and rehabilitation activities. This expert-like capability assists users in properly executing actions and maintaining engagement in remote fitness and rehabilitation programs. Specifically, the proposed UbiPhysio framework comprises a fine-grained action descriptor and a knowledge retrieval-enhanced feedback module. The action descriptor translates action data, represented by a set of biomechanical movement features we designed based on clinical priors, into textual descriptions of action types and potential movement patterns. Building on physiotherapeutic domain knowledge, the feedback module provides clear and engaging expert feedback. We evaluated UbiPhysio's performance through extensive experiments with data from 104 diverse participants, collected in a home-like setting during 25 types of everyday activities and exercises. We assessed the quality of the language output under different tuning strategies using standard benchmarks. We conducted a user study to gather insights from clinical experts and potential users on our framework. Our initial tests show promise for deploying UbiPhysio in real-life settings without specialized devices.Comment: 27 pages, 14 figures, 5 table

Pain-Related Factors and Their Impact on Quality of Life in Chinese Patients With Amyotrophic Lateral Sclerosis

ObjectivesPain is considered a common symptom in amyotrophic lateral sclerosis (ALS). However, the results of studies on pain in ALS are limited and inconsistent. The aim of our study was to comprehensively evaluate the potential factors of pain and effects on quality of life (QoL) in patients with ALS from China.Participants and MethodsPatients were eligible if they fulfilled the criteria of probable and definitive ALS according to the revised El Escorial criteria. Pain was assessed by the Brief Pain Inventory (BPI). Disease severity, sleep quality, fatigue, anxiety, depression, and quality of life (QoL) were evaluated in ALS patients by the ALS Functional Rating Scale-revised (ALSFRS-R) and ALS severity scale (ALSSS), Pittsburgh Sleep Quality Index (PSQI), Fatigue Severity Scale (FSS), Hamilton Anxiety Rating Scale (HARS), Hamilton Depression Rating Scale (HDRS) and McGill Quality of Life Questionnaire (MQOL). Then, the clinical characteristics of ALS patients with pain were compared with those without pain. Last, associated factors of pain, as well as impact on QoL in Chinese ALS patients, were assessed.ResultsA total of 86 ALS patients were included. ALS patients with pain tended to have higher FSS scores and poorer QoL. The FSS score and ALSSS [lower extremity (LE) + upper extremity (UE)] were associated with pain in ALS patients. The ALS Functional Rating Scale-revised (ALSFRS-R), Pain Severity Index (PSI), HARS and HDRS scores were significantly associated with both the physical and psychological domains of QoL.ConclusionOur study was the first to comprehensively evaluate factors associated with pain in Chinese ALS patients, finding that fatigue can be a risk factor for pain and ALSSS (LE + UE) score was related with pain intensity. Additionally, we identified the adverse effects of ALSSS (LE + UE), HARS and HDRS scores on QoL in Chinese ALS patients

Structure determination of DNA methylation lesions N1-meA and N3-meC in duplex DNA using a cross-linked protein–DNA system

N1-meA and N3-meC are cytotoxic DNA base methylation lesions that can accumulate in the genomes of various organisms in the presence of SN2 type methylating agents. We report here the structural characterization of these base lesions in duplex DNA using a cross-linked protein–DNA crystallization system. The crystal structure of N1-meA:T pair shows an unambiguous Hoogsteen base pair with a syn conformation adopted by N1-meA, which exhibits significant changes in the opening, roll and twist angles as compared to the normal A:T base pair. Unlike N1-meA, N3-meC does not establish any interaction with the opposite G, but remains partially intrahelical. Also, structurally characterized is the N6-meA base modification that forms a normal base pair with the opposite T in duplex DNA. Structural characterization of these base methylation modifications provides molecular level information on how they affect the overall structure of duplex DNA. In addition, the base pairs containing N1-meA or N3-meC do not share any specific characteristic properties except that both lesions create thermodynamically unstable regions in a duplex DNA, a property that may be explored by the repair proteins to locate these lesions

Cortical Gyrification and Sulcal Spans in Early Stage Alzheimer's Disease

Alzheimer's disease (AD) is characterized by an insidious onset of progressive cerebral atrophy and cognitive decline. Previous research suggests that cortical folding and sulcal width are associated with cognitive function in elderly individuals, and the aim of the present study was to investigate these morphological measures in patients with AD. The sample contained 161 participants, comprising 80 normal controls, 57 patients with very mild AD, and 24 patients with mild AD. From 3D T1-weighted brain scans, automated methods were used to calculate an index of global cortex gyrification and the width of five individual sulci: superior frontal, intra-parietal, superior temporal, central, and Sylvian fissure. We found that global cortex gyrification decreased with increasing severity of AD, and that the width of all individual sulci investigated other than the intra-parietal sulcus was greater in patients with mild AD than in controls. We also found that cognitive functioning, as assessed by Mini-Mental State Examination (MMSE) scores, decreased as global cortex gyrification decreased. MMSE scores also decreased in association with a widening of all individual sulci investigated other than the intra-parietal sulcus. The results suggest that abnormalities of global cortex gyrification and regional sulcal span are characteristic of patients with even very mild AD, and could thus facilitate the early diagnosis of this condition

The Effect of Kinesiology Taping on the Hemiplegic Shoulder Pain: A Randomized Controlled Trial

Objective. The purpose of the study was to explore the effect of kinesiology taping on hemiplegic shoulder pain (HSP) in terms of pain intensity, magnitude of subluxation, muscle activity, and active range of motion (AROM). Design. Double-blind, placebo-controlled clinical trial. Setting. the Rehabilitation Center of the West China Hospital. Participants. Nineteen individuals suffering from HSP were recruited in this study. Intervention. Patients were randomly assigned into the taping group or control group. The taping group received therapeutic kinesiology taping and conventional treatment, while the control group received placebo taping (applied without tension) and conventional treatment. Main Outcome Measures. The shoulder pain intensity (numerical pain rating scale), magnitude of subluxation, muscle activity (measured by surface electromyography (sEMG)), and shoulder active range of movement (AROM) were assessed at the baseline, on the first day (immediately after taping) and 4 weeks after treatment (without taping). Results. All patients completed the trials. There were no significant differences between groups at the baseline. The taping group showed immediate improvement on the first day after taping in terms of pain intensity, magnitude of subluxation, and muscle activity (p0.05). After 4 weeks of treatment, the taping group showed significant changes in pain intensity, magnitude of subluxation, muscle activity, and AROM (p<0.05). And significant differences in pain intensity and muscle activity could be seen between the two groups (p<0.05). Conclusion. The results indicate that the kinesiology taping is effective in reducing the shoulder pain and subluxation and increasing muscle activity and AROM for patients with HSP after stroke

Survival in desert: Extreme water adaptations and bioinspired structural designs

Summary: Deserts are the driest places in the world, desert creatures have evolved special adaptations to survive in this extreme water shortage environment. The collection and transport of condensed water have been of particular interest regarding the potential transfer of the underlying mechanisms to technical applications. In this review, the mechanisms of water capture and transport were first summarized. Secondly, an introduction of four typical desert creatures including cactus, desert beetles, lizards, and snakes which have special adaptations to manage water was elaborated. Thirdly, the recent progress of biomimetic water-collecting structures including cactus, desert beetles, and lizards inspired designs and the influence of overflow on water collection was demonstrated. Finally, the conclusions were drawn, and future issues were pointed out. The present study will further promote research on bioinspired water management strategies