1.Identification of blood-entering components of Anshen Dropping Pills based on UPLC-Q-TOF-MS/MS combined with network pharmacology and evaluation of their anti-insomnia effects and mechanisms.
Xia-Xia REN ; Jin-Na YANG ; Xue-Jun LUO ; Hui-Ping LI ; Miao QIAO ; Wen-Jia WANG ; Yi HE ; Shui-Ping ZHOU ; Yun-Hui HU ; Rui-Ming LI
China Journal of Chinese Materia Medica 2025;50(7):1928-1937
This study identified blood-entering components of Anshen Dropping Pills and explored their anti-insomnia effects and mechanisms. The main blood-entering components of Anshen Dropping Pills were detected and identified by UPLC-Q-TOF-MS/MS. The rationality of the formula was assessed by using enrichment analysis based on the relationship between drugs and symptoms, and core targets of its active components were selected as the the potential anti-insomnia targets of Anshen Dropping Pills through network pharmacology analysis. Furthermore, protein-protein interaction(PPI) network, Gene Ontology(GO) enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis were performed on the core targets. An active component-core target network for Anshen Dropping Pills was constructed. Finally, the effects of low-, medium-, and high-dose groups of Anshen Dropping Pills on sleep episodes, sleep duration, and sleep latency in mice were measured by supraliminal and subliminal pentobarbital sodium experiments. Moreover, total scores of the Pittsburgh sleep quality index(PSQI) scale was used to evaluate the changes before and after the treatment with Anshen Dropping Pills in a clinical study. The enrichment analysis based on the relationship between drugs and symptoms verified the rationality of the Anshen Dropping Pills formula, and nine blood-entering components of Anshen Dropping Pills were identified by UPLC-Q-TOF-MS/MS. The network proximity revealed a significant correlation between eight components and insomnia, including magnoflorine, liquiritin, spinosin, quercitrin, jujuboside A, ginsenoside Rb_3, glycyrrhizic acid, and glycyrrhetinic acid. Network pharmacology analysis indicated that the major anti-insomnia pathways of Anshen Dropping Pills involved substance and energy metabolism, neuroprotection, immune system regulation, and endocrine regulation. Seven core genes related to insomnia were identified: APOE, ALB, BDNF, PPARG, INS, TP53, and TNF. In summary, Anshen Dropping Pills could increase sleep episodes, prolong sleep duration, and reduce sleep latency in mice. Clinical study results demonstrated that Anshen Dropping Pills could decrease total scores of PSQI scale. This study reveals the pharmacodynamic basis and potential multi-component, multi-target, and multi-pathway effects of Anshen Dropping Pills, suggesting that its anti-insomnia mechanisms may be associated with the regulation of insomnia-related signaling pathways. These findings offer a theoretical foundation for the clinical application of Anshen Dropping Pills.
Animals
;
Drugs, Chinese Herbal/administration & dosage*
;
Tandem Mass Spectrometry/methods*
;
Sleep Initiation and Maintenance Disorders/metabolism*
;
Mice
;
Network Pharmacology
;
Male
;
Chromatography, High Pressure Liquid
;
Humans
;
Protein Interaction Maps/drug effects*
;
Sleep/drug effects*
;
Female
;
Adult
2.Identification and expression analysis of seed dehydration tolerance and PLD gene family in Panax medicinal plants.
Chao-Lin LI ; Min HUANG ; Na GE ; Qing-Yan WANG ; Jin-Shan JIA ; Ting LUO ; Jin-Yan ZHANG ; Ping ZHOU ; Jun-Wen CHEN
China Journal of Chinese Materia Medica 2025;50(12):3307-3321
Panax species are mostly valuable medicinal plants. While some species' seeds are sensitive to dehydration, the dehydration tolerance of seeds from other Panax species remains unclear. The phospholipase D(PLD) gene plays an important role in plant responses to dehydration stress. However, the characteristics of the PLD gene family and their mechanisms of response to dehydration stress in seeds of Panax species with different dehydration tolerances are not well understood. This study used seeds from eight Panax species to measure the germination rates and PLD activity after dehydration and to analyze the correlation between dehydration tolerance and seed traits. Bioinformatics analysis was also conducted to characterize the PnPLD and PvPLD gene families and to evaluate their expression patterns under dehydration stress. The dehydration tolerance of Panax seeds was ranked from high to low as follows: P. ginseng, P. zingiberensis, P. quinquefolius, P. vietnamensis var. fuscidiscus, P. japonicus var. angustifolius, P. japonicus, P. notoginseng, and P. stipuleanatus. A significant negative correlation was found between dehydration tolerance and seed shape(three-dimensional variance), with flatter seeds exhibiting stronger dehydration tolerance(r=-0.792). Eighteen and nineteen PLD members were identified in P. notoginseng and P. vietnamensis var. fuscidiscus, respectively. These members were classified into five isoforms: α, β, γ, δ, and ζ. The gene structures, subcellular localization, physicochemical properties, and other characteristics of PnPLD and PvPLD were similar. Both promoters contained regulatory elements associated with plant growth and development, hormone responses, and both abiotic and biotic stress. During dehydration, the PLD enzyme activity in P. notoginseng seeds gradually increased as the water content decreased, whereas in P. vietnamensis var. fuscidiscus, PLD activity first decreased and then increased. The expression of PLDα and PLDδ in P. notoginseng seeds initially increased and then decreased, whereas in P. vietnamensis var. fuscidiscus, the expression of PLDα and PLDδ consistently decreased. In conclusion, the dehydration tolerance of Panax seeds showed a significant negative correlation with seed shape. The dehydration tolerance in P. vietnamensis var. fuscidiscus and dehydration sensitivity of P. notoginseng seeds may be related to differences in PLD enzyme activity and the expression of PLDα and PLDδ genes. This study provided the first systematic comparison of dehydration tolerance in Panax seeds and analyzed the causes of tolerance differences and the optimal water content for long-term storage at ultra-low temperatures, thus providing a theoretical basis for the short-term and ultra-low temperature long-term storage of medicinal plant seeds with varying dehydration tolerances.
Seeds/metabolism*
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Panax/physiology*
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Plant Proteins/metabolism*
;
Gene Expression Regulation, Plant
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Phospholipase D/metabolism*
;
Plants, Medicinal/enzymology*
;
Germination
;
Multigene Family
;
Water/metabolism*
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Dehydration
;
Phylogeny
3.Evidence evaluation of 12 commonly-used Chinese patent medicines in treatment of osteoporosis based on Eff-iEC and GRADE.
Guang-Cheng WEI ; Zhi-Long ZHANG ; Xin-Wen ZHANG ; Ye LUO ; Jin-Jie SHI ; Rui MA ; Jie-Yang DU ; Ke ZHU ; Jiu-Cheng PENG ; Yu-Long YA ; Wei CAO
China Journal of Chinese Materia Medica 2025;50(15):4372-4385
This study applied the grading of recommendations assessment, development and evaluation(GRADE) system and the integrated evidence chain-based effectiveness evaluation of traditional Chinese medicine(Eff-iEC) to evaluate the evidence for 12 commonly used Chinese patent medicines for the treatment of osteoporosis, which are frequently recommended in guidelines or expert consensuses. The results showed that Xianling Gubao Capsules/Tablets were rated as C(low-level evidence) according to the GRADE system, and as BA~+B~+(intermediate evidence) according to the Eff-iEC system. Jintiange Capsules were rated as C(low-level evidence) by the GRADE system, and as AA~+B(high-level evidence) by the Eff-iEC system. Gushukang Granules/Capsules were rated as C(low-level evidence) by GRADE system, and as BA~+B~+(intermediate evidence) by Eff-iEC system. Zuogui Pills were rated as C(low-level evidence) by GRADE system, and as AA~(++)B~+(high-level evidence) by Eff-iEC system. Qianggu Capsules were rated as D(extremely low-level evidence) by GRADE system, and as AA~+B~+(high-level evidence) by Eff-iEC system. Zhuanggu Zhitong Capsules were rated as D(extremely low-level evidence) by GRADE system, and as BA~+B(intermediate evidence) by Eff-iEC system. Jingui Shenqi Pills were rated as D(extremely low-level evidence) by GRADE system, and as AA~+B(high-level evidence) by Eff-iEC system. Quanduzhong Capsules were rated as D(extremely low-level evidence) by GRADE system, and as AD~+B~+(low-level evidence) by Eff-iEC system. Epimedium Total Flavones Capsules were rated as D(extremely low-level evidence) by GRADE system, and as AAB~+(high-level evidence) by Eff-iEC system. Yougui Pills were rated as D(extremely low-level evidence) by GRADE system, and as AA~(++)B~(+ )(high-level evidence) by Eff-iEC system. Qigu Capsules were rated as D(extremely low-level evidence) by GRADE system, and as BB~+B(intermediate evidence) by Eff-iEC system. Liuwei Dihuang Pills were rated as C(low-level evidence) by GRADE system, and as AA~(++)B~+(high-level evidence) by Eff-iEC system. Overall, the Eff-iEC system provides a more comprehensive assessment of the effectiveness evidence for traditional Chinese medicine(TCM) than the GRADE system. However, it still has certain limitations that hinder its wider promotion and application. In terms of clinical evidence evaluation, both the Eff-iEC and GRADE systems reflect that the current clinical research quality on Chinese patent medicines for the treatment of osteoporosis is generally low. High-quality clinical trials are still needed in the future to further validate clinical efficacy.
Drugs, Chinese Herbal/therapeutic use*
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Osteoporosis/drug therapy*
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Humans
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Nonprescription Drugs/therapeutic use*
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Evidence-Based Medicine
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Medicine, Chinese Traditional
4.Biomedical Data in China: Policy, Accumulation, Platform Construction, and Applications.
Jing-Chen ZHANG ; Jing-Wen SUN ; Xiao-Meng LIU ; Jin-Yan LIU ; Wei LUO ; Sheng-Fa ZHANG ; Wei ZHOU
Chinese Medical Sciences Journal 2025;40(1):9-17
Biomedical data is surging due to technological innovations and integration of multidisciplinary data, posing challenges to data management. This article summarizes the policies, data collection efforts, platform construction, and applications of biomedical data in China, aiming to identify key issues and needs, enhance the capacity-building of platform construction, unleash the value of data, and leverage the advantages of China's vast amount of data.
China
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Humans
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Biomedical Research
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Data Management
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Data Collection
5.Analysis of risk factors, pathogenic bacteria characteristics, and drug resistance of postoperative surgical site infection in adults with limb fractures.
Yan-Jun WANG ; Zi-Hou ZHAO ; Shuai-Kun LU ; Guo-Liang WANG ; Shan-Jin MA ; Lin-Hu WANG ; Hao GAO ; Jun REN ; Zhong-Wei AN ; Cong-Xiao FU ; Yong ZHANG ; Wen LUO ; Yun-Fei ZHANG
Chinese Journal of Traumatology 2025;28(4):241-251
PURPOSE:
We carried out the study aiming to explore and analyze the risk factors, the distribution of pathogenic bacteria, and their antibiotic-resistance characteristics influencing the occurrence of surgical site infection (SSI), to provide valuable assistance for reducing the incidence of SSI after traumatic fracture surgery.
METHODS:
A retrospective case-control study enrolling 3978 participants from January 2015 to December 2019 receiving surgical treatment for traumatic fractures was conducted at Tangdu Hospital of Air Force Medical University. Baseline data, demographic characteristics, lifestyles, variables related to surgical treatment, and pathogen culture were harvested and analyzed. Univariate analyses and multivariate logistic regression analyses were used to reveal the independent risk factors of SSI. A bacterial distribution histogram and drug-sensitive heat map were drawn to describe the pathogenic characteristics.
RESULTS:
Included 3978 patients 138 of them developed SSI with an incidence rate of 3.47% postoperatively. By logistic regression analysis, we found that variables such as gender (males) (odds ratio (OR) = 2.012, 95% confidence interval (CI): 1.235 - 3.278, p = 0.005), diabetes mellitus (OR = 5.848, 95% CI: 3.513 - 9.736, p < 0.001), hypoproteinemia (OR = 3.400, 95% CI: 1.280 - 9.031, p = 0.014), underlying disease (OR = 5.398, 95% CI: 2.343 - 12.438, p < 0.001), hormonotherapy (OR = 11.718, 95% CI: 6.269 - 21.903, p < 0.001), open fracture (OR = 29.377, 95% CI: 9.944 - 86.784, p < 0.001), and intraoperative transfusion (OR = 2.664, 95% CI: 1.572 - 4.515, p < 0.001) were independent risk factors for SSI, while, aged over 59 years (OR = 0.132, 95% CI: 0.059 - 0.296, p < 0.001), prophylactic antibiotics use (OR = 0.082, 95% CI: 0.042 - 0.164, p < 0.001) and vacuum sealing drainage use (OR = 0.036, 95% CI: 0.010 - 0.129, p < 0.001) were protective factors. Pathogens results showed that 301 strains of 38 species of bacteria were harvested, among which 178 (59.1%) strains were Gram-positive bacteria, and 123 (40.9%) strains were Gram-negative bacteria. Staphylococcus aureus (108, 60.7%) and Enterobacter cloacae (38, 30.9%) accounted for the largest proportion. The susceptibility of Gram-positive bacteria to Vancomycin and Linezolid was almost 100%. The susceptibility of Gram-negative bacteria to Imipenem, Amikacin, and Meropenem exceeded 73%.
CONCLUSION
Orthopedic surgeons need to develop appropriate surgical plans based on the risk factors and protective factors associated with postoperative SSI to reduce its occurrence. Meanwhile, it is recommended to strengthen blood glucose control in the early stage of admission and for surgeons to be cautious and scientific when choosing antibiotic therapy in clinical practice.
Humans
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Surgical Wound Infection/epidemiology*
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Male
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Female
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Risk Factors
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Retrospective Studies
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Middle Aged
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Adult
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Case-Control Studies
;
Fractures, Bone/surgery*
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Aged
;
Drug Resistance, Bacterial
;
Logistic Models
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Anti-Bacterial Agents/therapeutic use*
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Incidence
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Bacteria/drug effects*
6.Complications among patients undergoing orthopedic surgery after infection with the SARS-CoV-2 Omicron strain and a preliminary nomogram for predicting patient outcomes.
Liang ZHANG ; Wen-Long GOU ; Ke-Yu LUO ; Jun ZHU ; Yi-Bo GAN ; Xiang YIN ; Jun-Gang PU ; Huai-Jian JIN ; Xian-Qing ZHANG ; Wan-Fei WU ; Zi-Ming WANG ; Yao-Yao LIU ; Yang LI ; Peng LIU
Chinese Journal of Traumatology 2025;28(6):445-453
PURPOSE:
The rate of complications among patients undergoing surgery has increased due to infection with SARS-CoV-2 and other variants of concern. However, Omicron has shown decreased pathogenicity, raising questions about the risk of postoperative complications among patients who are infected with this variant. This study aimed to investigate complications and related factors among patients with recent Omicron infection prior to undergoing orthopedic surgery.
METHODS:
A historical control study was conducted. Data were collected from all patients who underwent surgery during 2 distinct periods: (1) between Dec 12, 2022 and Jan 31, 2023 (COVID-19 positive group), (2) between Dec 12, 2021 and Jan 31, 2022 (COVID-19 negative control group). The patients were at least 18 years old. Patients who received conservative treatment after admission or had high-risk diseases or special circumstances (use of anticoagulants before surgery) were excluded from the study. The study outcomes were the total complication rate and related factors. Binary logistic regression analysis was used to identify related factors, and odds ratio (OR) and 95% confidence interval (CI) were calculated to assess the impact of COVID-19 infection on complications.
RESULTS:
In the analysis, a total of 847 patients who underwent surgery were included, with 275 of these patients testing positive for COVID-19 and 572 testing negative. The COVID-19-positive group had a significantly higher rate of total complications (11.27%) than the control group (4.90%, p < 0.001). After adjusting for relevant factors, the OR was 3.08 (95% CI: 1.45-6.53). Patients who were diagnosed with COVID-19 at 3-4 weeks (OR = 0.20 (95% CI: 0.06-0.59), p = 0.005), 5-6 weeks (OR = 0.16 (95% CI: 0.04-0.59), p = 0.010), or ≥7 weeks (OR = 0.26 (95% CI: 0.06-1.02), p = 0.069) prior to surgery had a lower risk of complications than those who were diagnosed at 0-2 weeks prior to surgery. Seven factors (age, indications for surgery, time of operation, time of COVID-19 diagnosis prior to surgery, C-reactive protein levels, alanine transaminase levels, and aspartate aminotransferase levels) were found to be associated with complications; thus, these factors were used to create a nomogram.
CONCLUSION
Omicron continues to be a significant factor in the incidence of postoperative complications among patients undergoing orthopedic surgery. By identifying the factors associated with these complications, we can determine the optimal surgical timing, provide more accurate prognostic information, and offer appropriate consultation for orthopedic surgery patients who have been infected with Omicron.
Humans
;
COVID-19/complications*
;
Male
;
Female
;
Middle Aged
;
Postoperative Complications/epidemiology*
;
SARS-CoV-2
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Orthopedic Procedures/adverse effects*
;
Aged
;
Nomograms
;
Adult
;
Retrospective Studies
;
Risk Factors
7.Berg Balance Scale score is a valuable predictor of all-cause mortality among acute decompensated heart failure patients.
Yu-Xuan FAN ; Jing-Jing CHENG ; Zhi-Qing FAN ; Jing-Jin LIU ; Wen-Juan XIU ; Meng-Yi ZHAN ; Lin LUO ; Guang-He LI ; Le-Min WANG ; Yu-Qin SHEN
Journal of Geriatric Cardiology 2025;22(6):555-562
OBJECTIVE:
To investigate possible associations between physical function assessment scales, such as Short Physical Performance Battery (SPPB) and Berg Balance Scale (BBS), with all-cause mortality in acute decompensated heart failure (ADHF) patients.
METHODS:
A total of 108 ADHF patients were analyzed from October 2020 to October 2022, and followed up to May 2023. The association between baseline clinical characteristics and all-cause mortality was analyzed by univariate Cox regression analysis, while for SPPB and BBS, univariate Cox regression analysis was followed by receiver operating characteristic curves, in which the area under the curve represented their predictive accuracy for all-cause mortality. Incremental predictive values for both physical function assessments were measured by calculating net reclassification index and integrated discrimination improvement scores. Optimal cut-off value for BBS was then identified using restricted cubic spline plots, and survival differences below and above that cut-off were compared using Kaplan-Meier survival curves and the log-rank test. The clinical utility of BBS was measured using decision curve analysis.
RESULTS:
For baseline characteristics, age, female, blood urea nitrogen, as well as statins, angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, or angiotensin receptor-neprilysin inhibitors, were predictive for all-cause mortality for ADHF patients. With respect to SPPB and BBS, higher scores were associated with lower all-cause mortality rates for both assessments; similar area under the curves were measured for both (0.774 for SPPB and 0.776 for BBS). Furthermore, BBS ≤ 36.5 was associated with significantly higher mortality, which was still applicable even adjusting for confounding factors; BBS was also found to have great clinical utility under decision curve analysis.
CONCLUSIONS
BBS or SPPB could be used as tools to assess physical function in ageing ADHF patients, as well as prognosticate on all-cause mortality. Moreover, prioritizing the improvement of balance capabilities of ADHF patients in cardiac rehabilitation regimens could aid in lowering mortality risk.
8.Morphological classification and molecular identification of Hyalomma asiaticum in parts of Xindi Township,Xinjiang
Xiao-Qing ZAN ; Qiao-Yun REN ; Jin LUO ; Yan-Long WANG ; Pei-Wen DIAO ; Li-Yan CHE ; Jian-Xun LUO ; Hong YIN ; Gui-Quan GUAN ; Guang-Yuan LIU ; Hong-Xi ZHAO
Chinese Journal of Zoonoses 2024;40(4):289-294
The purpose of this study was to identify the tick species native to Xindi Township,Yumin County,Xinjiang,China.Preliminary morphological identification of parasitic ticks collected from animals in the area was conducted with an ultra-depth of field three-dimensional VHX 600 digital stereo microscope.Total DNA of the ticks was extracted,amplified by PCR based on the COI and ITS2 gene loci,and the posi-tive PCR products were sequenced.The sequence were a-ligned with reference sequences from the NCBI database were aligned with the Basic Local Alignment Search Tool.A genet-ic phylogenetic tree was generated with the neighbor-joining method of MEGA 7.0 software to determine the evolutionary biological characteristics of ticks.Morphological identification showed that the ticks collected from Xindi Township of Yu-min County were consistent with the characteristics of Hya-lomma asiaticum.An evolutionary tree based on the COI and ITS2 gene sequences showed that the ticks collected in this study were clustered with known H.asiaticum sequences.The PCR products of COI and ITS2 were sequenced and compared,which confirmed that the collected tick species were H.asiaticum,in agreement with the morphological and molecular biological results.These findings help to clarify the distribution of ticks in Xindi Township of Xinjiang,and provide basic data for the analysis of tick genetic and evolutionary characteristics,as reference for surveillance and control of ticks in the Xinjiang Uygur Autonomous Region.
9.Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients (version 2024)
Yao LU ; Yang LI ; Leiying ZHANG ; Hao TANG ; Huidan JING ; Yaoli WANG ; Xiangzhi JIA ; Li BA ; Maohong BIAN ; Dan CAI ; Hui CAI ; Xiaohong CAI ; Zhanshan ZHA ; Bingyu CHEN ; Daqing CHEN ; Feng CHEN ; Guoan CHEN ; Haiming CHEN ; Jing CHEN ; Min CHEN ; Qing CHEN ; Shu CHEN ; Xi CHEN ; Jinfeng CHENG ; Xiaoling CHU ; Hongwang CUI ; Xin CUI ; Zhen DA ; Ying DAI ; Surong DENG ; Weiqun DONG ; Weimin FAN ; Ke FENG ; Danhui FU ; Yongshui FU ; Qi FU ; Xuemei FU ; Jia GAN ; Xinyu GAN ; Wei GAO ; Huaizheng GONG ; Rong GUI ; Geng GUO ; Ning HAN ; Yiwen HAO ; Wubing HE ; Qiang HONG ; Ruiqin HOU ; Wei HOU ; Jie HU ; Peiyang HU ; Xi HU ; Xiaoyu HU ; Guangbin HUANG ; Jie HUANG ; Xiangyan HUANG ; Yuanshuai HUANG ; Shouyong HUN ; Xuebing JIANG ; Ping JIN ; Dong LAI ; Aiping LE ; Hongmei LI ; Bijuan LI ; Cuiying LI ; Daihong LI ; Haihong LI ; He LI ; Hui LI ; Jianping LI ; Ning LI ; Xiying LI ; Xiangmin LI ; Xiaofei LI ; Xiaojuan LI ; Zhiqiang LI ; Zhongjun LI ; Zunyan LI ; Huaqin LIANG ; Xiaohua LIANG ; Dongfa LIAO ; Qun LIAO ; Yan LIAO ; Jiajin LIN ; Chunxia LIU ; Fenghua LIU ; Peixian LIU ; Tiemei LIU ; Xiaoxin LIU ; Zhiwei LIU ; Zhongdi LIU ; Hua LU ; Jianfeng LUAN ; Jianjun LUO ; Qun LUO ; Dingfeng LYU ; Qi LYU ; Xianping LYU ; Aijun MA ; Liqiang MA ; Shuxuan MA ; Xainjun MA ; Xiaogang MA ; Xiaoli MA ; Guoqing MAO ; Shijie MU ; Shaolin NIE ; Shujuan OUYANG ; Xilin OUYANG ; Chunqiu PAN ; Jian PAN ; Xiaohua PAN ; Lei PENG ; Tao PENG ; Baohua QIAN ; Shu QIAO ; Li QIN ; Ying REN ; Zhaoqi REN ; Ruiming RONG ; Changshan SU ; Mingwei SUN ; Wenwu SUN ; Zhenwei SUN ; Haiping TANG ; Xiaofeng TANG ; Changjiu TANG ; Cuihua TAO ; Zhibin TIAN ; Juan WANG ; Baoyan WANG ; Chunyan WANG ; Gefei WANG ; Haiyan WANG ; Hongjie WANG ; Peng WANG ; Pengli WANG ; Qiushi WANG ; Xiaoning WANG ; Xinhua WANG ; Xuefeng WANG ; Yong WANG ; Yongjun WANG ; Yuanjie WANG ; Zhihua WANG ; Shaojun WEI ; Yaming WEI ; Jianbo WEN ; Jun WEN ; Jiang WU ; Jufeng WU ; Aijun XIA ; Fei XIA ; Rong XIA ; Jue XIE ; Yanchao XING ; Yan XIONG ; Feng XU ; Yongzhu XU ; Yongan XU ; Yonghe YAN ; Beizhan YAN ; Jiang YANG ; Jiangcun YANG ; Jun YANG ; Xinwen YANG ; Yongyi YANG ; Chunyan YAO ; Mingliang YE ; Changlin YIN ; Ming YIN ; Wen YIN ; Lianling YU ; Shuhong YU ; Zebo YU ; Yigang YU ; Anyong YU ; Hong YUAN ; Yi YUAN ; Chan ZHANG ; Jinjun ZHANG ; Jun ZHANG ; Kai ZHANG ; Leibing ZHANG ; Quan ZHANG ; Rongjiang ZHANG ; Sanming ZHANG ; Shengji ZHANG ; Shuo ZHANG ; Wei ZHANG ; Weidong ZHANG ; Xi ZHANG ; Xingwen ZHANG ; Guixi ZHANG ; Xiaojun ZHANG ; Guoqing ZHAO ; Jianpeng ZHAO ; Shuming ZHAO ; Beibei ZHENG ; Shangen ZHENG ; Huayou ZHOU ; Jicheng ZHOU ; Lihong ZHOU ; Mou ZHOU ; Xiaoyu ZHOU ; Xuelian ZHOU ; Yuan ZHOU ; Zheng ZHOU ; Zuhuang ZHOU ; Haiyan ZHU ; Peiyuan ZHU ; Changju ZHU ; Lili ZHU ; Zhengguo WANG ; Jianxin JIANG ; Deqing WANG ; Jiongcai LAN ; Quanli WANG ; Yang YU ; Lianyang ZHANG ; Aiqing WEN
Chinese Journal of Trauma 2024;40(10):865-881
Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.
10.Transformer attention mechanism based three-dimensional dose prediction for lung cancer intensity-modulated radiotherapy
Yangting CHEN ; Xin YANG ; Fu JIN ; Bin FENG ; Wen LUO
Chinese Journal of Radiation Oncology 2024;33(6):532-539
Objective:To develop a deep learning architecture based on 3D Transformers to predict dose distribution within intensity modulated radiation therapy (IMRT) plans for lung cancer.Methods:Clinical data of 174 lung cancer patients treated with IMRT in Chongqing University Cancer Hospital between January 2020 and December 2022 were retrospectively analyzed. All patients were divided into the training ( n=116), validation ( n=29), and test ( n=29) sets. We employed the Swin Unet Transformer (Swin Unetr) model to predict the three-dimensional dose distribution. The model was trained using computed tomography (CT) images, planning target volume (PTV) images, organs at risk (OAR) images, beam configuration information images, and distance images. We used various evaluation metrics such as mean absolute errors (MAE), Dice similarity coefficients (DSC), and dose volume histogram (DVH) dosimetric parameters to assess the performance of Swin Unetr and compared it with three mainstream deep learning models: CGAN, ResSEUnet, and ResUnet. Results:The MAE of the dose distribution prediction by Swin Unetr was recorded at 0.0143±0.0055. Conversely, the values of CGAN, ResSEUnet, and ResUnet were 0.0162±0.0055, 0.0167±0.0063, and 0.0164±0.0057, respectively. Furthermore, Swin Unetr achieved the highest DSC values (>0.85) across all isodose volumes. Regarding DVH dosimetric parameters, excluding D 2% of PTV and D mean of the heart, Swin Unetr exhibited no statistically significant differences in the remaining DVH dosimetric parameters (all P>0.05), demonstrating the best evaluation results in 66.67% of the overall dosimetric parameters and 75% of the PTV dosimetric parameters. Conclusions:Swin Unetr achieves the best score in multiple dosimetric evaluation indicators, and the highest DSC across all isodose volumes. Swin Unetr has significantly improved the accuracy of three-dimensional dose prediction during IMRT for lung cancer.

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