1.Shaoyaotang Regulates miRNA-155-mediated SOCS1/JAK1/STAT1 Signaling Pathway to Affect Macrophage Polarization
Qi CHENG ; Bo ZOU ; Youwei XIAO ; Yiqian YU ; Ruoru HUANG ; Yan GONG ; Jiachun XIONG ; Jun XIONG ; Dichang LAI ; Dongsheng WU ; Hui CAO
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(13):43-52
ObjectiveTo investigate the mechanism by which Shaoyaotang regulates the miRNA-155-mediated suppressor of cytokine signaling 1 (SOCS1)/Janus kinase 1 (JAK1)/signal transducer and activator of transcription 1 (STAT1) signaling pathway and thereby affects macrophage polarization. MethodsThe cell-counting kit-8 (CCK-8) assay was used to detect the effect of drug-containing serum of Shaoyaotang at different concentrations on the viability of RAW 264.7 cells. A cell model of inflammation was established by stimulating RAW264.7 cells with lipopolysaccharide (LPS) at a concentration of 10 mg·L-1 The modeled cells were assigned by the random number table method into seven groups: LPS-induced M1 polarization (model), M1+miRNA-155 mimics, M1+miRNA-155 inhibitor, M1+Shaoyaotang-containing serum, M1+miRNA-155 mimics+Shaoyaotang-containing serum, M1+miRNA-155 inhibitor+Shaoyaotang-containing serum, and M1+blank serum. Enzyme-linked immunosorbent assay was employed to measure the levels of inflammatory factors [tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and interleukin-1β (IL-1β)]. Immunofluorescence assay was used to detect the expression of macrophage polarization markers [inducible nitric oxide synthase (iNOS) and macrophage mannose receptor 1 (CD206)]. Real-time PCR was employed to measure the expression of miRNA-155 in cells. Western blot was performed to determine the protein levels of SOCS1, STAT1, and JAK1. ResultsCompared with the LPS-induced M1 polarization (model) group, the M1+miRNA-155 mimics group showed up-regulated expression of miRNA-155, JAK1, STAT1, TNF-α, IL-6, IL-1β, and iNOS (P<0.05) and down-regulated expression of CD206 (P<0.05). In both the M1+miRNA-155 inhibitor group and the M1+Shaoyaotang-containing serum group, the expression levels of miRNA-155, JAK1, STAT1, TNF-α, IL-6, IL-1β, and iNOS were down-regulated (P<0.05), while those of SOCS1 and CD206 were up-regulated (P<0.05). Compared with the M1+miRNA-155 mimics group, the M1+miRNA-155 mimics+Shaoyaotang-containing serum group showed down-regulated expression of miRNA-155, JAK1, STAT1, TNF-α, IL-6, IL-1β, and iNOS (P<0.05) and up-regulated expression of SOCS1 and CD206 (P<0.05). Compared with the M1+miRNA-155 inhibitor group, the M1+miRNA-155 inhibitor+Shaoyaotang-containing serum group showed down-regulated expression of miRNA-155, JAK1, STAT1, TNF-α, IL-6, IL-1β, and iNOS (P<0.05) and up-regulated expression of SOCS1 and CD206 (P<0.05). ConclusionShaoyaotang regulates macrophage polarization by modulating miRNA-155 expression and interfering with the SOCS1/JAK1/STAT1 signaling pathway. The findings provide new experimental evidence for the treatment of ulcerative colitis with Shaoyaotang.
2.Exploration of New Susceptible Genes associated with Non-Alcoholic Fatty Liver Disease among Children with Obesity Using Whole Exome Sequencing.
Xiong Feng PAN ; Cai Lian WEI ; Jia You LUO ; Jun Xia YAN ; Xiang XIAO ; Jie WANG ; Yan ZHONG ; Mi Yang LUO
Biomedical and Environmental Sciences 2025;38(6):727-739
OBJECTIVE:
This study aimed to evaluate the association between susceptibility genes and non-alcoholic fatty liver disease (NAFLD) in children with obesity.
METHODS:
We conducted a two-step case-control study. Ninety-three participants were subjected to whole-exome sequencing (exploratory set). Differential genes identified in the small sample were validated in 1,022 participants using multiplex polymerase chain reaction and high-throughput sequencing (validation set).
RESULTS:
In the exploratory set, 14 genes from the NAFLD-associated pathways were identified. In the validation set, after adjusting for sex, age, and body mass index, ECI2 rs2326408 (dominant model: OR = 1.33, 95% CI: 1.02-1.72; additive model: OR = 1.22, 95% CI: 1.01-1.47), C6orf201 rs659305 (dominant model: OR = 1.30, 95% CI: 1.01-1.69; additive model: OR = 1.21, 95% CI: 1.00-1.45), CALML5 rs10904516 (pre-ad dominant model: OR = 1.36, 95% CI: 1.01-1.83; adjusted dominant model: OR = 1.40, 95% CI: 1.03-1.91; and pre-ad additive model: OR = 1.26, 95% CI: 1.04-1.66) polymorphisms were significantly associated with NAFLD in children with obesity ( P < 0.05). Interaction analysis revealed that the gene-gene interaction model of CALML5 rs10904516, COX11 rs17209882, and SCD5 rs3733228 was optional ( P < 0.05), demonstrating a negative interaction between the three genes.
CONCLUSION
In the Chinese population, the CALML5 rs10904516, C6orf201 rs659305, and ECI2 rs2326408 variants could be genetic markers for NAFLD susceptibility.
Humans
;
Non-alcoholic Fatty Liver Disease/genetics*
;
Child
;
Male
;
Female
;
Genetic Predisposition to Disease
;
Case-Control Studies
;
Exome Sequencing
;
Adolescent
;
Polymorphism, Single Nucleotide
;
Obesity/complications*
;
Pediatric Obesity/complications*
;
China
3.(Meta)transcriptomic Insights into the Role of Ticks in Poxvirus Evolution and Transmission: A Multicontinental Analysis.
Yu Xi WANG ; Jing Jing HU ; Jing Jing HOU ; Xiao Jie YUAN ; Wei Jie CHEN ; Yan Jiao LI ; Qi le GAO ; Yue PAN ; Shui Ping LU ; Qi CHEN ; Si Ru HU ; Zhong Jun SHAO ; Cheng Long XIONG
Biomedical and Environmental Sciences 2025;38(9):1058-1070
OBJECTIVE:
Poxviruses are zoonotic pathogens that infect humans, mammals, vertebrates, and arthropods. However, the specific role of ticks in transmission and evolution of these viruses remains unclear.
METHODS:
Transcriptomic and metatranscriptomic raw data from 329 sampling pools of seven tick species across five continents were mined to assess the diversity and abundance of poxviruses. Chordopoxviral sequences were assembled and subjected to phylogenetic analysis to trace the origins of the unblasted fragments within these sequences.
RESULTS:
Fifty-eight poxvirus species, representing two subfamilies and 20 genera, were identified, with 212 poxviral sequences assembled. A substantial proportion of AT-rich fragments were detected in the assembled poxviral genomes. These genomic sequences contained fragments originating from rodents, archaea, and arthropods.
CONCLUSION
Our findings indicate that ticks play a significant role in the transmission and evolution of poxviruses. These viruses demonstrate the capacity to modulate virulence and adaptability through horizontal gene transfer, gene recombination, and gene mutations, thereby promoting co-existence and co-evolution with their hosts. This study advances understanding of the ecological dynamics of poxvirus transmission and evolution and highlights the potential role of ticks as vectors and vessels in these processes.
Animals
;
Poxviridae/physiology*
;
Ticks/virology*
;
Phylogeny
;
Transcriptome
;
Evolution, Molecular
;
Poxviridae Infections/virology*
;
Genome, Viral
4.Epidemiology and management patterns of chronic thromboembolic pulmonary hypertension in China.
Wanmu XIE ; Yongpei YU ; Qiang HUANG ; Xiaoyan YAN ; Yuanhua YANG ; Changming XIONG ; Zhihong LIU ; Jun WAN ; Sugang GONG ; Lan WANG ; Cheng HONG ; Chenghong LI ; Jean-François RICHARD ; Yanhua WU ; Jun ZOU ; Chen YAO ; Zhenguo ZHAI
Chinese Medical Journal 2025;138(8):1000-1002
5.Analysis of influencing factors of blood transfusion in children with traumatic brain injury and construc-tion of prediction model:A multi-center retrospective study
Wei LIU ; Jun HOU ; Longquan TANG ; Peng ZHOU ; Yan ZHONG ; Qinyan LUO ; Xiaoyu KUANG ; Hua LIU ; Ziqing XIONG ; Wei XIONG ; Chenggao WU ; Aiping LE
The Journal of Practical Medicine 2025;41(4):553-560
Objective To develop a predictive model for guiding blood transfusion decisions in pediatric patients with traumatic brain injury(TBI)by identifying and analyzing key factors that influence blood transfusion requirements.Methods A retrospective analysis was conducted on the clinical data of 1,535 pediatric patients with TBI admitted to four medical institutions from January 1,2015,to December 31,2022.Patients were divided into two groups:those who received red blood cell transfusions during hospitalization and those who did not.Comparative analyses were performed on demographic,clinical,and laboratory data between these two groups.Logistic regression analysis was used to identify risk factors associated with in-hospital blood transfusion,and a predictive model was developed using a nomogram.The performance of this model was evaluated using a receiver operating characteristic(ROC)curve.Results Significant differences were observed between the blood transfusion and non-blood transfusion groups in terms of baseline demographics,clinical indicators,and laboratory test results(all P<0.05).Patients in the blood transfusion group exhibited significantly higher in-hospital mortality,compli-cation rates,use of mechanical ventilation,ICU admission rates,and length of stay compared to those in the non-blood transfusion group(all P<0.05).Multivariate logistic regression analysis identified heart rate,presence of other fractures,treatment methods,hemoglobin(Hb),platelet count(Plt),activated partial thromboplastin time(APTT),and D-dimer levels as independent risk factors for blood transfusion in TBI patients.The area under the ROC curve for the blood transfusion prediction model,based on these independent risk factors,was 0.95(95%CI:0.94~0.97),indicating excellent predictive accuracy.Calibration and decision curves further validated the robust-ness and reliability of the model's predictive capacity.Conclusions Heart rate,presence of other fractures,treatment methods,Hb,Plt count,APTT,and D-dimer levels serve as independent risk factors for blood transfusion in TBI patients.The prediction model developed based on these factors demonstrates excellent predictive performance,thereby guiding clinicians in making informed blood transfusion decisions and enhancing the success rate of patient outcomes.
6.Guideline for Adult Weight Management in China
Weiqing WANG ; Qin WAN ; Jianhua MA ; Guang WANG ; Yufan WANG ; Guixia WANG ; Yongquan SHI ; Tingjun YE ; Xiaoguang SHI ; Jian KUANG ; Bo FENG ; Xiuyan FENG ; Guang NING ; Yiming MU ; Hongyu KUANG ; Xiaoping XING ; Chunli PIAO ; Xingbo CHENG ; Zhifeng CHENG ; Yufang BI ; Yan BI ; Wenshan LYU ; Dalong ZHU ; Cuiyan ZHU ; Wei ZHU ; Fei HUA ; Fei XIANG ; Shuang YAN ; Zilin SUN ; Yadong SUN ; Liqin SUN ; Luying SUN ; Li YAN ; Yanbing LI ; Hong LI ; Shu LI ; Ling LI ; Yiming LI ; Chenzhong LI ; Hua YANG ; Jinkui YANG ; Ling YANG ; Ying YANG ; Tao YANG ; Xiao YANG ; Xinhua XIAO ; Dan WU ; Jinsong KUANG ; Lanjie HE ; Wei GU ; Jie SHEN ; Yongfeng SONG ; Qiao ZHANG ; Hong ZHANG ; Yuwei ZHANG ; Junqing ZHANG ; Xianfeng ZHANG ; Miao ZHANG ; Yifei ZHANG ; Yingli LU ; Hong CHEN ; Li CHEN ; Bing CHEN ; Shihong CHEN ; Guiyan CHEN ; Haibing CHEN ; Lei CHEN ; Yanyan CHEN ; Genben CHEN ; Yikun ZHOU ; Xianghai ZHOU ; Qiang ZHOU ; Jiaqiang ZHOU ; Hongting ZHENG ; Zhongyan SHAN ; Jiajun ZHAO ; Dong ZHAO ; Ji HU ; Jiang HU ; Xinguo HOU ; Bimin SHI ; Tianpei HONG ; Mingxia YUAN ; Weibo XIA ; Xuejiang GU ; Yong XU ; Shuguang PANG ; Tianshu GAO ; Zuhua GAO ; Xiaohui GUO ; Hongyi CAO ; Mingfeng CAO ; Xiaopei CAO ; Jing MA ; Bin LU ; Zhen LIANG ; Jun LIANG ; Min LONG ; Yongde PENG ; Jin LU ; Hongyun LU ; Yan LU ; Chunping ZENG ; Binhong WEN ; Xueyong LOU ; Qingbo GUAN ; Lin LIAO ; Xin LIAO ; Ping XIONG ; Yaoming XUE
Chinese Journal of Endocrinology and Metabolism 2025;41(11):891-907
Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.
7.Prevalence and molecular characterization of Shiga toxin-producing Esch-erichia coli in domestic goats in the Chengkou District of Chongqing
Jing-jing PENG ; Bin HU ; Xi YANG ; Yi LI ; Hai HUANG ; Wen-shuang LIU ; Yu MENG ; Li-jun WANG ; Yan-wen XIONG ; Yi YUAN ; Pei-bin HOU
Chinese Journal of Zoonoses 2025;41(5):529-536
This study investigated the infection status,drug resistance,and molecular characteristics of Shiga toxin-producing Escherichia coli(STEC)in domestic goats in Chengkou county,Chongqing.In August 2023,283 fecal samples were collected from households in Chengkou county.After enrichment with EC broth and inoculation onto selective media,samples that tested positive for stx1/stx2 were selected for further isolation.The positive strains were investigated with antimicrobial susceptibility testing and whole genome sequencing.According to the whole genomic sequences,the stx subtypes,serotypes,multi-locus sequence types,virulence genes,drug resistance genes,and phylogenetic relationships of the STEC strains were analyzed.Forty-six strains of STEC were isolated from 283 goat fecal samples,thus resulting in a detection rate of 16.25%.The 46 STEC strains were categorized into 12 O∶H serotypes,among which O76∶H19 and O8∶H7 predominated,each represented by 9 strains.Five STEC strains were identified as serotype O157∶H7.The 46 STEC strains were categorized into 11 sequence types(STs),among which ST675 and ST196 predominated,each represented by nine strains,accounting for a 19.57%proportion.The strains were categorized into 7 stx subtypes,among which stx1c(26/46,56.52%),followed by stx2k(9/46,19.57%)predominated.All nine Stx2k-STEC strains were identified as serotype O8∶H7 and sequence type ST196.In antimicrobial susceptibility testing,2 STEC strains were resistant to ampicillin,one strain was resistant to ampicillin/sulbactam,one strain was resistant to cefazolin,and one strain was resistant to cefoxitin.Nine Stx2k-STEC strains were found to carry the beta-lactam resistance gene blaEC-18.Antimicrobial sensitivity tests revealed that the nine Stx2k-STEC strains were sensitive to all 15 tested antibiotics.Moreover,phylogenetic analysis indicated that the 9 Stx2k-STEC strains were remarkably similar but showed high genetic diversity with respect to that of the Stx2k-STEC strains isolated from other regions in China.Goatsare an important animal reservoir for STEC in theChengkou district of Chongqing,and novel sequence type Stx2k-STEC strains distinct from those found in other regions of China were identified in this region.
8.Prevalence and molecular characterization of Shiga toxin-producing Esch-erichia coli in domestic goats in the Chengkou District of Chongqing
Jing-jing PENG ; Bin HU ; Xi YANG ; Yi LI ; Hai HUANG ; Wen-shuang LIU ; Yu MENG ; Li-jun WANG ; Yan-wen XIONG ; Yi YUAN ; Pei-bin HOU
Chinese Journal of Zoonoses 2025;41(5):529-536
This study investigated the infection status,drug resistance,and molecular characteristics of Shiga toxin-producing Escherichia coli(STEC)in domestic goats in Chengkou county,Chongqing.In August 2023,283 fecal samples were collected from households in Chengkou county.After enrichment with EC broth and inoculation onto selective media,samples that tested positive for stx1/stx2 were selected for further isolation.The positive strains were investigated with antimicrobial susceptibility testing and whole genome sequencing.According to the whole genomic sequences,the stx subtypes,serotypes,multi-locus sequence types,virulence genes,drug resistance genes,and phylogenetic relationships of the STEC strains were analyzed.Forty-six strains of STEC were isolated from 283 goat fecal samples,thus resulting in a detection rate of 16.25%.The 46 STEC strains were categorized into 12 O∶H serotypes,among which O76∶H19 and O8∶H7 predominated,each represented by 9 strains.Five STEC strains were identified as serotype O157∶H7.The 46 STEC strains were categorized into 11 sequence types(STs),among which ST675 and ST196 predominated,each represented by nine strains,accounting for a 19.57%proportion.The strains were categorized into 7 stx subtypes,among which stx1c(26/46,56.52%),followed by stx2k(9/46,19.57%)predominated.All nine Stx2k-STEC strains were identified as serotype O8∶H7 and sequence type ST196.In antimicrobial susceptibility testing,2 STEC strains were resistant to ampicillin,one strain was resistant to ampicillin/sulbactam,one strain was resistant to cefazolin,and one strain was resistant to cefoxitin.Nine Stx2k-STEC strains were found to carry the beta-lactam resistance gene blaEC-18.Antimicrobial sensitivity tests revealed that the nine Stx2k-STEC strains were sensitive to all 15 tested antibiotics.Moreover,phylogenetic analysis indicated that the 9 Stx2k-STEC strains were remarkably similar but showed high genetic diversity with respect to that of the Stx2k-STEC strains isolated from other regions in China.Goatsare an important animal reservoir for STEC in theChengkou district of Chongqing,and novel sequence type Stx2k-STEC strains distinct from those found in other regions of China were identified in this region.
9.Analysis of influencing factors of blood transfusion in children with traumatic brain injury and construc-tion of prediction model:A multi-center retrospective study
Wei LIU ; Jun HOU ; Longquan TANG ; Peng ZHOU ; Yan ZHONG ; Qinyan LUO ; Xiaoyu KUANG ; Hua LIU ; Ziqing XIONG ; Wei XIONG ; Chenggao WU ; Aiping LE
The Journal of Practical Medicine 2025;41(4):553-560
Objective To develop a predictive model for guiding blood transfusion decisions in pediatric patients with traumatic brain injury(TBI)by identifying and analyzing key factors that influence blood transfusion requirements.Methods A retrospective analysis was conducted on the clinical data of 1,535 pediatric patients with TBI admitted to four medical institutions from January 1,2015,to December 31,2022.Patients were divided into two groups:those who received red blood cell transfusions during hospitalization and those who did not.Comparative analyses were performed on demographic,clinical,and laboratory data between these two groups.Logistic regression analysis was used to identify risk factors associated with in-hospital blood transfusion,and a predictive model was developed using a nomogram.The performance of this model was evaluated using a receiver operating characteristic(ROC)curve.Results Significant differences were observed between the blood transfusion and non-blood transfusion groups in terms of baseline demographics,clinical indicators,and laboratory test results(all P<0.05).Patients in the blood transfusion group exhibited significantly higher in-hospital mortality,compli-cation rates,use of mechanical ventilation,ICU admission rates,and length of stay compared to those in the non-blood transfusion group(all P<0.05).Multivariate logistic regression analysis identified heart rate,presence of other fractures,treatment methods,hemoglobin(Hb),platelet count(Plt),activated partial thromboplastin time(APTT),and D-dimer levels as independent risk factors for blood transfusion in TBI patients.The area under the ROC curve for the blood transfusion prediction model,based on these independent risk factors,was 0.95(95%CI:0.94~0.97),indicating excellent predictive accuracy.Calibration and decision curves further validated the robust-ness and reliability of the model's predictive capacity.Conclusions Heart rate,presence of other fractures,treatment methods,Hb,Plt count,APTT,and D-dimer levels serve as independent risk factors for blood transfusion in TBI patients.The prediction model developed based on these factors demonstrates excellent predictive performance,thereby guiding clinicians in making informed blood transfusion decisions and enhancing the success rate of patient outcomes.
10.Guideline for Adult Weight Management in China
Weiqing WANG ; Qin WAN ; Jianhua MA ; Guang WANG ; Yufan WANG ; Guixia WANG ; Yongquan SHI ; Tingjun YE ; Xiaoguang SHI ; Jian KUANG ; Bo FENG ; Xiuyan FENG ; Guang NING ; Yiming MU ; Hongyu KUANG ; Xiaoping XING ; Chunli PIAO ; Xingbo CHENG ; Zhifeng CHENG ; Yufang BI ; Yan BI ; Wenshan LYU ; Dalong ZHU ; Cuiyan ZHU ; Wei ZHU ; Fei HUA ; Fei XIANG ; Shuang YAN ; Zilin SUN ; Yadong SUN ; Liqin SUN ; Luying SUN ; Li YAN ; Yanbing LI ; Hong LI ; Shu LI ; Ling LI ; Yiming LI ; Chenzhong LI ; Hua YANG ; Jinkui YANG ; Ling YANG ; Ying YANG ; Tao YANG ; Xiao YANG ; Xinhua XIAO ; Dan WU ; Jinsong KUANG ; Lanjie HE ; Wei GU ; Jie SHEN ; Yongfeng SONG ; Qiao ZHANG ; Hong ZHANG ; Yuwei ZHANG ; Junqing ZHANG ; Xianfeng ZHANG ; Miao ZHANG ; Yifei ZHANG ; Yingli LU ; Hong CHEN ; Li CHEN ; Bing CHEN ; Shihong CHEN ; Guiyan CHEN ; Haibing CHEN ; Lei CHEN ; Yanyan CHEN ; Genben CHEN ; Yikun ZHOU ; Xianghai ZHOU ; Qiang ZHOU ; Jiaqiang ZHOU ; Hongting ZHENG ; Zhongyan SHAN ; Jiajun ZHAO ; Dong ZHAO ; Ji HU ; Jiang HU ; Xinguo HOU ; Bimin SHI ; Tianpei HONG ; Mingxia YUAN ; Weibo XIA ; Xuejiang GU ; Yong XU ; Shuguang PANG ; Tianshu GAO ; Zuhua GAO ; Xiaohui GUO ; Hongyi CAO ; Mingfeng CAO ; Xiaopei CAO ; Jing MA ; Bin LU ; Zhen LIANG ; Jun LIANG ; Min LONG ; Yongde PENG ; Jin LU ; Hongyun LU ; Yan LU ; Chunping ZENG ; Binhong WEN ; Xueyong LOU ; Qingbo GUAN ; Lin LIAO ; Xin LIAO ; Ping XIONG ; Yaoming XUE
Chinese Journal of Endocrinology and Metabolism 2025;41(11):891-907
Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

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