Global One Health index for zoonoses: A performance assessment in 160 countries and territories.

The One Health (OH) approach is used to control/prevent zoonotic events. However, there is a lack of tools for systematically assessing OH practices. Here, we applied the Global OH Index (GOHI) to evaluate the global OH performance for zoonoses (GOHI-Zoonoses). The fuzzy analytic hierarchy process algorithm and fuzzy comparison matrix were used to calculate the weights and scores of five key indicators, 16 subindicators, and 31 datasets for 160 countries and territories worldwide. The distribution of GOHI-Zoonoses scores varies significantly across countries and regions, reflecting the strengths and weaknesses in controlling or responding to zoonotic threats. Correlation analyses revealed that the GOHI-Zoonoses score was associated with economic, sociodemographic, environmental, climatic, and zoological factors. Additionally, the Human Development Index had a positive effect on the score. This study provides an evidence-based reference and guidance for global, regional, and country-level efforts to optimize the health of people, animals, and the environment.

A survey of recent methods for addressing AI fairness and bias in biomedicine.

Objectives: Artificial intelligence (AI) systems have the potential to revolutionize clinical practices, including improving diagnostic accuracy and surgical decision-making, while also reducing costs and manpower. However, it is important to recognize that these systems may perpetuate social inequities or demonstrate biases, such as those based on race or gender. Such biases can occur before, during, or after the development of AI models, making it critical to understand and address potential biases to enable the accurate and reliable application of AI models in clinical settings. To mitigate bias concerns during model development, we surveyed recent publications on different debiasing methods in the fields of biomedical natural language processing (NLP) or computer vision (CV). Then we discussed the methods, such as data perturbation and adversarial learning, that have been applied in the biomedical domain to address bias. Methods: We performed our literature search on PubMed, ACM digital library, and IEEE Xplore of relevant articles published between January 2018 and December 2023 using multiple combinations of keywords. We then filtered the result of 10,041 articles automatically with loose constraints, and manually inspected the abstracts of the remaining 890 articles to identify the 55 articles included in this review. Additional articles in the references are also included in this review. We discuss each method and compare its strengths and weaknesses. Finally, we review other potential methods from the general domain that could be applied to biomedicine to address bias and improve fairness. Results: The bias of AIs in biomedicine can originate from multiple sources such as insufficient data, sampling bias and the use of health-irrelevant features or race-adjusted algorithms. Existing debiasing methods that focus on algorithms can be categorized into distributional or algorithmic. Distributional methods include data augmentation, data perturbation, data reweighting methods, and federated learning. Algorithmic approaches include unsupervised representation learning, adversarial learning, disentangled representation learning, loss-based methods and causality-based methods.

Scientometric analysis of electrocatalysis in wastewater treatment: today and tomorrow.

Electrocatalytic methods are valuable tools for addressing water pollution and scarcity, offering effective pollutant removal and resource recovery. To investigate the current status and future trends of electrocatalysis in wastewater treatment, a detailed analysis of 9417 papers and 4061 patents was conducted using scientometric methods. China emerged as the leading contributor to publications, and collaborations between China and the USA have emerged as the most frequent partnerships. Primary article co-citation clusters focused on oxygen evolution reaction and electrochemical oxidation, transitioning towards advanced oxidation processes ("persulfate activation"), and electrocatalytic reduction processes ("nitrate reduction"). Bifunctional catalysts, theoretical calculations, electrocatalytic combination technologies, and emerging contaminants were identified as current research hotspots. Patent analysis revealed seven types of electrochemical technologies, which were compared using SWOT analysis, highlighting electrochemical oxidation as prominent. The technological evolution presented the pathway of electro-Fenton to combined electrocatalytic technologies with biochemical processes, and finally to coupling with electrocoagulation. Standardized evaluation systems, waste resource utilization, and energy conservation were important directions of innovation in electrocatalytic technologies. Overall, this study provided a reference for researchers to understand the framework of electrocatalysis in wastewater treatment and also shed light on potential avenues for further innovation in the field.

Weak correlations among leaf thermal metrics, economic traits and damages under natural heatwaves.

The frequency and intensity of heatwaves are increasing around the world, causing severe damages to plants, but whether leaf thermal metrics is in line with leaf economic spectrum is still controversial. Here, we measured leaf damage ratio, leaf thermal metrics (tolerance and sensitivity) and economic traits of 131 woody species across five cities along the Yangtze River after a two-month natural extreme temperature event. We found that leaf thermal sensitivity but not thermal tolerance was correlated with leaf damage ratio, and the relationships between leaf thermal metrics and economic traits were weak, indicating that leaf thermal adaptation may be independent from leaf carbon construction. This study suggests a potential indicator for predicting plant survival under heatwaves, urging future research to explore more physiological traits to comprehensively understand plant heat responses and adaptations.

Prehabilitation programs - a systematic review of the economic evidence.

Introduction: Prehabilitation, which involves improving a patient's physical and psychological condition before surgery, has shown potential benefits but has yet to be extensively studied from an economic perspective. To address this gap, a systematic review was conducted to summarize existing economic evaluations of prehabilitation interventions. Methods: The PRISMA Protocols 2015 checklist was followed. Over 16,000 manuscripts were reviewed, and 99 reports on preoperative interventions and screening tests were identified, of which 12 studies were included in this analysis. The costs are expressed in Pounds (GBP, £) and adjusted for inflation to December 2022. Results: The studies were conducted in Western countries, focusing on specific surgical subspecialties. While the interventions and study designs varied, most studies demonstrated cost savings in the intervention group compared to the control group. Additionally, all cost-effectiveness analysis studies favored the intervention group. However, the review also identified several limitations. Many studies had a moderate or high risk of bias, and critical information such as time horizons and discount rates were often missing. Important components like heterogeneity, distributional effects, and uncertainty were frequently lacking as well. The misclassification of economic evaluation types highlighted a lack of knowledge among physicians in prehabilitation research. Conclusion: This review reveals a lack of robust evidence regarding the economics of prehabilitation programs for surgical patients. This suggests a need for further research with rigorous methods and accurate definitions.

Sarcopenia Transitions and Influencing Factors Among Chinese Older Adults With Multistate Markov Model.

Background and Objectives: Little is known about the sarcopenia transition process across different stages among Chinese community-dwelling older adults. We aimed to explore dynamic transitions of sarcopenia and its influencing factors in Chinese older adults. Research Design and Methods: Data were derived from the China Health and Retirement Longitudinal Study. A total of 2856 older adults with complete data in the 2011, 2013, and 2015 waves were included in our study. Participants were categorized into 3 states: no sarcopenia, possible sarcopenia, and sarcopenia according to the Asian Working Group for Sarcopenia 2019 (AWGS 2019) criteria. Continuous-time multistate Markov model was performed to estimate the 1-year transition probabilities and the associated factors of sarcopenia transitions. The association strength was expressed as hazard ratio and 95% confidence interval. Results: The progression and reversion rates between no sarcopenia and sarcopenia state were 6.01 and 9.20 per 100 person-years, respectively. The 1-year progression probability to possible sarcopenia was higher compared with the likelihood of moving to the sarcopenia state (0.127 vs 0.034). The reversion probability to no sarcopenia was also higher among those with possible sarcopenia (0.281 vs 0.157). Older age, rural living, worse cognition status, higher chronic disease numbers, and lower nutrition status measured by body mass index accelerated the sarcopenia progression. Cognition status and body mass index level were related to higher chances of reverting. Discussion and Implications: Possible sarcopenia might be a critical time window to promote sarcopenia reversion. Timely interventions aimed at delaying the progression and facilitating sarcopenia recovery should focus on improving cognitive function and nutrition levels.

Mechanism of Yiqi Huoxue Huatan recipe in the treatment of coronary atherosclerotic disease through network pharmacology and experiments.

In recent years, with population aging and economic development, morbidity and mortality of atherosclerotic cardiovascular disease associated with atherosclerosis (AS) have gradually increased. In this study, a combination of network pharmacology and experimental verification was used to systematically explore the action mechanism of Yiqi Huoxue Huatan Recipe (YHHR) in the treatment of coronary atherosclerotic heart disease (CAD). We searched and screened the active ingredients of Coptis chinensis, Astragalus membranaceus, Salvia miltiorrhiza, and Hirudo. We also searched multiple databases for related target genes corresponding to the compounds and CAD. STRING was used to construct the protein-protein interaction (PPI) network of genes. Metascape was used to perform gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis for common targets to analyze the main pathways, and finally, the molecular docking and main possible pathways were verified by experimental studies. Firstly, a total of 1480 predicted target points were obtained through the Swiss Target Prediction database. After screening, merging, and deleting duplicate values, a total of 768 targets were obtained. Secondly, "Coronary atherosclerotic heart disease" was searched in databases such as the OMIM, GeneCards, and TTD. 1844 disease-related targets were obtained. Among PPI network diagram of YHHR-CAD, SRC had the highest degree value, followed by AKT1, TP53, hsp90aa1 and mapk3. The KEGG pathway bubble diagram was drawn using Chiplot, the Signal pathways such as NF kappa B signaling pathway, Lipid and AS, and Apelin signaling pathway are closely related to the occurrence of CAD. The PCR and Western blot methods were used to detect the expression of NF-κB p65. When compared with that in the model group, the expression of NF-κB p65mRNA decreased in the low-concentration YHHR group, with P < .05, while the expression of NF-κB p65mRNA decreased significantly in the high-concentration YHHR group, with P < .01. On the other hand, when compared with that in the model group, the expression of NF-κB p65 decreased in the low-concentration YHHR group, but was not statistically significant, while the expression of NF-κB p65 was significant in the high-concentration YHHR group, and has statistical significance with P < .05. YHHR has been shown to resist inflammation and AS through the SRC/NF-κB signaling pathway.

Multilayered insights: a machine learning approach for personalized prognostic assessment in hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) is a complex malignancy, and precise prognosis assessment is vital for personalized treatment decisions. Objective: This study aimed to develop a multi-level prognostic risk model for HCC, offering individualized prognosis assessment and treatment guidance. Methods: By utilizing data from The Cancer Genome Atlas (TCGA) and the Surveillance, Epidemiology, and End Results (SEER) database, we performed differential gene expression analysis to identify genes associated with survival in HCC patients. The HCC Differential Gene Prognostic Model (HCC-DGPM) was developed through multivariate Cox regression. Clinical indicators were incorporated into the HCC-DGPM using Cox regression, leading to the creation of the HCC Multilevel Prognostic Model (HCC-MLPM). Immune function was evaluated using single-sample Gene Set Enrichment Analysis (ssGSEA), and immune cell infiltration was assessed. Patient responsiveness to immunotherapy was evaluated using the Immunophenoscore (IPS). Clinical drug responsiveness was investigated using drug-related information from the TCGA database. Cox regression, Kaplan-Meier analysis, and trend association tests were conducted. Results: Seven differentially expressed genes from the TCGA database were used to construct the HCC-DGPM. Additionally, four clinical indicators associated with survival were identified from the SEER database for model adjustment. The adjusted HCC-MLPM showed significantly improved discriminative capacity (AUC=0.819 vs. 0.724). External validation involving 153 HCC patients from the International Cancer Genome Consortium (ICGC) database verified the performance of the HCC-MLPM (AUC=0.776). Significantly, the HCC-MLPM exhibited predictive capacity for patient response to immunotherapy and clinical drug efficacy (P < 0.05). Conclusion: This study offers comprehensive insights into HCC prognosis and develops predictive models to enhance patient outcomes. The evaluation of immune function, immune cell infiltration, and clinical drug responsiveness enhances our comprehension and management of HCC.

Assessment of performance for a key indicator of One Health: evidence based on One Health index for zoonoses in Sub-Saharan Africa.

BACKGROUND: Zoonoses are public health threats that cause severe damage worldwide. Zoonoses constitute a key indicator of One Health (OH) and the OH approach is being applied for zoonosis control programmes of zoonotic diseases. In a very recent study, we developed an evaluation system for OH performance through the global OH index (GOHI). This study applied the GOHI to evaluate OH performance for zoonoses in sub-Saharan Africa. METHODS: The framework for the OH index on zoonoses (OHIZ) was constructed including five indicators, 15 subindicators and 28 datasets. Publicly available data were referenced to generate the OHIZ database which included both qualitative and quantitative indicators for all sub-Sahara African countries (n = 48). The GOHI algorithm was used to estimate scores for OHIZ. Indicator weights were calculated by adopting the fuzzy analytical hierarchy process. RESULTS: Overall, five indicators associated with weights were generated as follows: source of infection (23.70%), route of transmission (25.31%), targeted population (19.09%), capacity building (16.77%), and outcomes/case studies (15.13%). Following the indicators, a total of 37 sub-Sahara African countries aligned with OHIZ validation, while 11 territories were excluded for unfit or missing data. The OHIZ average score of sub-Saharan Africa was estimated at 53.67/100. The highest score was 71.99 from South Africa, while the lowest score was 40.51 from Benin. It is also worth mentioning that Sub-Sahara African countries had high performance in many subindicators associated with zoonoses, e.g., surveillance and response, vector and reservoir interventions, and natural protected areas, which suggests that this region had a certain capacity in control and prevention or responses to zoonotic events. CONCLUSIONS: This study reveals that it is possible to perform OH evaluation for zoonoses in sub-Saharan Africa by OHIZ. Findings from this study provide preliminary research information in advancing knowledge of the evidenced risks to strengthen strategies for effective control of zoonoses and to support the prevention of zoonotic events.

A cost-effective tsCUT&Tag method for profiling transcription factor binding landscape.

Knowledge of the transcription factor binding landscape (TFBL) is necessary to analyze gene regulatory networks for important agronomic traits. However, a low-cost and high-throughput in vivo chromatin profiling method is still lacking in plants. Here, we developed a transient and simplified cleavage under targets and tagmentation (tsCUT&Tag) that combines transient expression of transcription factor proteins in protoplasts with a simplified CUT&Tag without nucleus extraction. Our tsCUT&Tag method provided higher data quality and signal resolution with lower sequencing depth compared with traditional ChIP-seq. Furthermore, we developed a strategy combining tsCUT&Tag with machine learning, which has great potential for profiling the TFBL across plant development.

Global spatio-temporal change assessment in interregional water stress footprint in China by a high resolution MRIO model.

Developing effective strategies to alleviate increasing water stress in China requires an understanding of how consumption and production drive water stress footprints (WSF) at a high resolution and multiple spatial and temporal scales. However, current Chinese multi-regional input-output (CMRIO) models have limited resolution. Here, we build a high-resolution international MRIO model covering 31 Chinese provinces, 163 sectors, to address this issue, and then analyze the impact of changes in China's interprovincial and international trade patterns on the WSF from 2012 to 2017. We find that China's water stress embodied in inter-provincial trade has increased year after year, to 5606 km3 H2O-eq in 2017, exceeding 50 % of the total domestic footprint. Domestic water stress transfer is most apparent in the outsourcing of water stress from eastern coastal regions to Central and Western regions, with the top interregional supply chain paths mainly associated with the demand of processed rice and tobacco products. China has transformed into a net exporter of water stress in 2017, with water stress exports to developing countries accounting for 54 % of total exports, up from 51 % in 2012. With deepening globalization, trade between China and developing countries has boosted bilateral economic development, while also exacerbating water stress in China. In addition to agricultural cultivation, industrial products such as plastics and steel exported to meet international industries further contribute to water stress in Northern China. Further identify hotspots of water stress consumption is needed to prioritize actions to relieve regional water stress in a more effective manner, and our study can provide key information.

Towards a global One Health index: a potential assessment tool for One Health performance.

BACKGROUND: A One Health approach has been increasingly mainstreamed by the international community, as it provides for holistic thinking in recognizing the close links and inter-dependence of the health of humans, animals and the environment. However, the dearth of real-world evidence has hampered application of a One Health approach in shaping policies and practice. This study proposes the development of a potential evaluation tool for One Health performance, in order to contribute to the scientific measurement of One Health approach and the identification of gaps where One Health capacity building is most urgently needed. METHODS: We describe five steps towards a global One Health index (GOHI), including (i) framework formulation; (ii) indicator selection; (iii) database building; (iv) weight determination; and (v) GOHI scores calculation. A cell-like framework for GOHI is proposed, which comprises an external drivers index (EDI), an intrinsic drivers index (IDI) and a core drivers index (CDI). We construct the indicator scheme for GOHI based on this framework after multiple rounds of panel discussions with our expert advisory committee. A fuzzy analytical hierarchy process is adopted to determine the weights for each of the indicators. RESULTS: The weighted indicator scheme of GOHI comprises three first-level indicators, 13 second-level indicators, and 57 third-level indicators. According to the pilot analysis based on the data from more than 200 countries/territories the GOHI scores overall are far from ideal (the highest score of 65.0 out of a maximum score of 100), and we found considerable variations among different countries/territories (31.8-65.0). The results from the pilot analysis are consistent with the results from a literature review, which suggests that a GOHI as a potential tool for the assessment of One Health performance might be feasible. CONCLUSIONS: GOHI-subject to rigorous validation-would represent the world's first evaluation tool that constructs the conceptual framework from a holistic perspective of One Health. Future application of GOHI might promote a common understanding of a strong One Health approach and provide reference for promoting effective measures to strengthen One Health capacity building. With further adaptations under various scenarios, GOHI, along with its technical protocols and databases, will be updated regularly to address current technical limitations, and capture new knowledge.

Investigation of microplastics in sludge from five wastewater treatment plants in Nanjing, China.

Municipal wastewater treatment plants (WWTPs) have been regarded as the main receptors of microplastics in industrial and domestic wastewater. The excess sludge they generate is an important carrier for the microplastics to enter the environment. In China, relevant regional studies are still in an initial phase. In this work, microplastics in the sewage sludges at different sampling points of five WWTPs in Nanjing City (an important city in the Yangtze River basin) were investigated, including their abundance, morphology and chemical composition. Furthermore, the influence factors such as population density, economic development level, wastewater source and treatment process were also discussed. The analysis results through optical microscope and FT-IR showed that the detected microplastics were divided into fragments, films, fibers and granules. Their chemical component reached up to 19 species, including small amounts of petroleum resins which was scarcely detected in other studies. Wastewater source was the primary factor influencing the microplastic abundance and size in sludge. And the microplastic shape and chemical components were closely related to the industrial type. Furthermore, because the removal effect on the microplastics with different morphologies were varied with the treatment process, the preliminary suggestions on the technology for particular wastewater were proposed. This study provides partial regional data and analysis for the microplastics contained in the sludge of WWTPs, expecting to provide a certain theoretical support for the operations management of WWTPs and standardized sludge treatment.

A cost-effective barcode system for maize genetic discrimination based on bi-allelic InDel markers.

BACKGROUND: Maize is one of the most important cereal crop all over the world with a complex genome of about 2.3 gigabase, and exhibits tremendous phenotypic and molecular diversity among different germplasms. Along with the phenotype identification, molecular markers have been accepted extensively as an alternative tool to discriminate different genotypes. RESULTS: By using previous re-sequencing data of 205 lines, bi-allelic insertions and deletions (InDels) all over maize genome were screened, and a barcode system was constructed consisting of 37 bi-allelic insertion-deletion markers with high polymorphism information content (PIC) values, large discriminative size among varieties. The barcode system was measured and determined, different maize hybrids and inbreds were clearly discriminated efficiently with these markers, and hybrids responding parents were accurately determined. Compared with microarray data of more than 200 maize lines, the barcode system can discriminate maize varieties with 1.57% of different loci as a threshold. The barcode system can be used in standardized easy and quick operation with very low cost and minimum equipment requirements. CONCLUSION: A barcode system was constructed for genetic discrimination of maize lines, including 37 InDel markers with high PIC values and user-friendly. The barcode system was measured and determined for efficient identification of maize lines.

Estimation of marginal abatement costs of CO2 in Chinese provinces under 2020 carbon emission rights allocation: 2005-2020.

The calculation of marginal abatement costs of CO2 plays a vital role in meeting China's 2020 emission reduction targets by providing reference for determining carbon tax and carbon trading pricing. However, most existing researches only used one method to discuss regional and industrial marginal abatement costs, and almost no studies predicted future marginal abatement costs from the perspective of CO2 emission efficiency. To make up for the gaps, this paper first estimates marginal abatement costs of CO2 in three major industries of 30 provinces in China from 2005 to 2015 based on three assumptions. Second, based on the principle of fairness and efficiency, China's 2020 emission reduction targets are decomposed by province. Based on the ZSG-C-DDF model, the marginal abatement costs of CO2 in all provinces in China in 2020 are estimated and compared with the marginal abatement costs of 2005 to 2015. The results show that (1) from 2005 to 2015, marginal abatement costs of CO2 in all provinces show a fluctuating upward trend; (2) compared with the marginal abatement costs of primary industry or tertiary industry, most provinces have lower marginal abatement costs for secondary industry; and (3) the average marginal abatement costs of CO2 for China in 2020 are 2766.882 Yuan/tonne for the 40% carbon intensity reduction target and 3334.836 Yuan/tonne for the 45% target, showing that the higher the emission reduction target, the higher the marginal abatement costs of CO2. (4) Overall, the average marginal abatement costs of CO2 in China by 2020 are higher than those in 2005-2015. The empirical analysis in this paper can provide multiple references for environmental policy makers.

Engineering Halomonas spp. as A Low-Cost Production Host for Production of Bio-surfactant Protein PhaP.

Halomonas spp. have been studied as a low cost production host for producing bulk materials such as polyhydroxyalkanoates (PHA) bioplastics, since they are able to grow at high pH and high NaCl concentration under unsterile and continuous conditions without microbial contamination. In this paper, Halomonas strain TD is used as a host to produce a protein named PHA phasin or PhaP which has a potential to be developed into a bio-surfactant. Four Halomonas TD expression strains are constructed based on a strong T7-family expression system. Of these, the strain with phaC deletion and chromosomal expression system resulted in the highest production of PhaP in soluble form, reaching 19% of total cellular soluble proteins and with a yield of 1.86 g/L in an open fed-batch fermentation process. A simple "heat lysis and salt precipitation" method is applied to allow rapid PhaP purification from a mixture of cellular proteins with a PhaP recovery rate of 63%. It clearly demonstrated that Halomonas TD could be used for high yield expression of a bio-surfactant protein PhaP for industrial application in an economical way.

[Assessment of Ecosystem Health of Baogang Tailings Groundwater Based on Microbiome Index of Biotic Integrity (M-IBI)].

Index of Biological Integrity (IBI) is a scientific tool used to evaluate health of aquatic ecosystems. IBI associates anthropogenic influences with biological activity in the water body, and is formulated using data developed from biosurveys. Compared with other biotic assemblage indicators of water quality, little attention has been paid to the application of microbial community in ecosystem health assessment for groundwater bodies so far. An approach based on microbiome index of biotic integrity was developed to assess groundwater ecosystem health in this study. The method based on Illumina high-throughput DNA sequencing was applied to achieve the information of microbial community. The key environmental factors were selected based on CCA analysis and the optimized values were calculated for defining the taxonomic genera sensitive and resistant to these factors. The resulting candidate biotic factors were used to construct microbiome index of biotic integrity (M-IBI) evaluating system. The results showed among the studied sample sites from groundwater of Baogang rare earth tailings, 33.3% of samples were at "Great" level, 16.7% at "Good" level, most of samples (41.7%) at "moderate" level and 8.3% at "Bad" level. The ecosystem healthy status of the sample sites near the tailings was affected by human disturbances, while the samples far away the tailings were at healthy level. The results of the groundwater ecosystem healthy assessment based on M-IBI system had a good match with the groundwater quality standard based on chemical properties. It indicated that M-IBI could be a potential index to evaluate the health of groundwater ecosystem.

Monitoring epidemic alert levels by analyzing Internet search volume.

The prevention of infectious diseases is a global health priority area. The early detection of possible epidemics is the first and important defense line against infectious diseases. However, conventional surveillance systems, e.g., the Centers for Disease Control and Prevention (CDC), rely on clinical data. The CDC publishes the surveillance results weeks after epidemic outbreaks. To improve the early detection of epidemic outbreaks, we designed a syndromic surveillance system to predict the epidemic trends based on disease-related Google search volume. Specifically, we first represented the epidemic trend with multiple alert levels to reduce the noise level. Then, we predicted the epidemic alert levels using a continuous density HMM, which incorporated the intrinsic characteristic of the disease transmission for alert level estimation. Respective models are built to monitor both national and regional epidemic alert levels of the U.S. The proposed system can provide real-time surveillance results, which are weeks before the CDC's reports. This paper focusses on monitoring the infectious disease in the U.S., however, we believe similar approach may be used to monitor epidemics for the developing countries as well.

Sonographic assessment of hypopharyngeal carcinoma: preliminary study.

OBJECTIVES: This study investigated the ability of sonography for diagnosis of hypopharyngeal carcinoma. METHODS: Between November 2008 and January 2010, 34 consecutive patients with hypopharyngeal carcinoma (34 tumors) were examined by sonography. The visualization capability of sonography was evaluated by grading criteria of "excellent," "good," "moderate," and "poor" in comparison with computed tomography (CT). Localization of the primary tumor foci and intrahypopharyngeal and extrahypopharyngeal invasion were initially assessed by sonography and confirmed with surgical and pathologic findings. Laryngeal movement was observed on real-time sonography and compared with endoscopic findings. RESULTS: On sonography, 29 of the 34 lesions (85.3%) were graded excellent, similar to the shapes and dimensions of the tumors on CT. Localization was correctly undertaken in 26 of the 28 foci resected (92.9%), with excellent agreement between sonography and surgical and pathologic findings (κ = 0.823; P < .001). In evaluating intrahypopharyngeal and extrahypopharyngeal invasion with sonography, the sensitivity and specificity were 90.9% and 82.4%, respectively, for intrahypopharyngeal intersubsite spreading, 50.0% and 96.2% for diagnosis of thyroid cartilage destruction, both 100% for evaluation of cervical esophagus, neck soft tissue, and thyroid gland involvement, and 76.9% and 100% for assessment of hemilarynx fixation. CONCLUSIONS: Sonography has a similar role in visualization of hypopharyngeal carcinoma as CT and is satisfactory in localization of the primary focus and assessment of tumor extension inside and outside the hypopharynx.

[Assessment of energy expenditure and body composition in cancer patients].

OBJECTIVE: To demonstrate the changes of resting energy expenditure (REE), substrate metabolism and body composition in cancer patients. METHODS: From September 2004 to March 2008, REE, carbohydrate oxidation (CO) and fat oxidation (FO) in 936 cancer patients and 840 control subjects were measured by indirect calorimetry. Bioelectrical impedance appliance was applied to assess intracellular fluid, extracellular fluid, fat mass (FM) and fat free mass (FFM) in the two groups. RESULTS: No difference in REE was found between the cancer patients and non-cancer patients [(1452.2 +/- 196.4) kcal/d vs. (1429.5 +/- 182.6) kcal/d, P = 0.136]. But REE/FFM and REE/pREE were elevated in cancer patients than in controls (all P < 0.05). Of the cancer patients, 48.6% were hypermetabolic, 42.9% normal and 8.5% hypometabolic, while those were 22.5%, 58.5% and 19.0% in controls. Cancer patients had higher FO [(77.8 +/- 11.3) g/min vs. (67.1 +/- 12.1) g/min, P = 0.000], lower CO and npRQ [(68.7 +/- 10.5) g/min vs. (88.8 +/- 12.1) g/min, P = 0.000; 0.782 +/- 0.012 vs. 0.810 +/- 0.014, P = 0.000]. Cancer patients exhibited lower FM and FFM [(14.9 +/- 4.5) kg vs. (18.4 +/- 5.2) kg, P = 0.000; (44.4 +/- 7.2) kg vs. (46.1 +/- 8.1) kg, P = 0.008]. CONCLUSIONS: Elevated REE is common in cancer patients. Substrate metabolism of the cancer patients features in increased FO, decreased CO and npRQ, which is correlated with the elevated REE. FM and FFM loses in proportion in cancer patients.