目的:探讨基于CT三维重组技术的R.E.N.A.L.评分系统在腹腔镜肾部分切除术中的临床应用价值。方法:搜集我院2020年6月至2024年1月经手术治疗的79例肾肿瘤患者的临床及术前影像资料,根据术前肾脏CT三维重组结果,分析血管变异与肾脏热缺血...目的:探讨基于CT三维重组技术的R.E.N.A.L.评分系统在腹腔镜肾部分切除术中的临床应用价值。方法:搜集我院2020年6月至2024年1月经手术治疗的79例肾肿瘤患者的临床及术前影像资料,根据术前肾脏CT三维重组结果,分析血管变异与肾脏热缺血时间、手术总时间、术中出血量及术后并发症之间的关系,并进行R.E.N.A.L.评分。采用Logistic回归筛选出肾热缺血时间大于20 min的独立危险因素。结果:有无血管变异在肾脏热缺血时间、手术总时间、术中出血量及术后并发症之间无明显差异(P > 0.05)。R.E.N.A.L.总评分是肾热缺血时间大于20 min的独立危险因素(P P Objective: To explore the clinical application value of R.E.N.A.L. scoring system based on CT three-dimensional reconstruction technology in laparoscopic partial nephrectomy. Methods: The clinical and preoperative imaging data of 79 patients with renal tumors who underwent surgical treatment in our hospital from June 2020 to January 2024 were collected. According to the results of preoperative renal CT three-dimensional reconstruction, the relationship between vascular variation and renal warm ischemia time, total operation time, intraoperative bleeding and postoperative complications was analyzed, and R.E.N.A.L. score was performed. Logistic regression was used to screen out independent risk factors for renal warm ischemia time greater than 20 min. Results: There was no significant difference in renal warm ischemia time, total operation time, intraoperative blood loss and postoperative complications between the presence or absence of vascular variation (P > 0.05). The total R.E.N.A.L. score was an independent risk factor for renal warm ischemia time greater than 20 min (P P < 0.05). Conclusion: CT three-dimensional reconstruction can clearly understand the anatomical location of the kidney, tumor and blood vessels before surgery, thereby reducing the occurrence of perioperative complications.展开更多
Objective:Despite the combination of Scutellaria barbata D.Don and Scleromitrion diffusum(Willd.)R.J.Wang(SB-SD)being a recognized Chinese medicinal herbal pair that is commonly used in the treatment of ovarian cancer...Objective:Despite the combination of Scutellaria barbata D.Don and Scleromitrion diffusum(Willd.)R.J.Wang(SB-SD)being a recognized Chinese medicinal herbal pair that is commonly used in the treatment of ovarian cancer,there is a poor understanding of their pharmacological mechanisms.This study examines the antitumor properties and potential mechanisms of SB-SD on human ovarian cancer A2780 cells through a multi-omics approach,establishing a pharmacological basis for clinical utilization.Methods:A range of mass ratios and reagents were used in the hot reflux extraction of SB-SD.The inhibitory effect of the SB-SD extracts on A2780 cell proliferation was assessed using the cell-counting kit 8assay.A zebrafish tumor implantation model was used to evaluate the effects of SB-SD extracts on tumor growth and metastasis in vivo.Transcriptomics and proteomics were used to investigate alterations in biological pathways in A2780 cells after treatment with different concentrations of SB-SD extract.Cell cycle,cell apoptosis,intracellular free iron concentration,intracellular reactive oxygen species(ROS)concentration,malondialdehyde(MDA),and mitochondrial membrane potential were measured.Real-time quantitative reverse transcription polymerase chain reaction and Western blotting were utilized to investigate the effects of heme catabolism and ferritinophagy on ferroptosis induced by SB-SD extract in A2780 cells.Results:The 70%ethanol extract of SB-SD(a mass ratio of 4:1)inhibited A2780 cell proliferation significantly with a half maximal inhibitory concentration of 660μg/m L in a concentration-and timedependent manner.Moreover,it effectively suppressed tumor growth and metastasis in a zebrafish tumor implantation model.SB-SD extract induced the accumulation of free iron,ROS,MDA,and mitochondrial damage in A2780 cells.The mechanisms might involve the upregulated expression of ferritinophagyrelated genes microtubule-associated protein 1 light chain 3,autophagy-related gene 5,and nuclear receptor coactivator 4.Conclusion:SB-SD extract effectively inhibited the development of ovarian cancer both in vitro and in vivo.Its mechanism of action involved inducing ferroptosis by facilitating heme catabolism and ferritinophagy.This herbal pair holds promise as a potential therapeutic option for ovarian cancer treatment and may be utilized in combination with routine treatment to improve the treatment outcomes of ovarian cancer patients.展开更多
Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the i...Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the interfaces of verbal and emotional communications. The progress of AI is significant on the verbal level but modest in terms of the recognition of facial emotions even if this functionality is one of the oldest in humans and is omnipresent in our daily lives. Dysfunction in the ability for facial emotional expressions is present in many brain pathologies encountered by psychiatrists, neurologists, psychotherapists, mental health professionals including social workers. It cannot be objectively verified and measured due to a lack of reliable tools that are valid and consistently sensitive. Indeed, the articles in the scientific literature dealing with Visual-Facial-Emotions-Recognition (ViFaEmRe), suffer from the absence of 1) consensual and rational tools for continuous quantified measurement, 2) operational concepts. We have invented a software that can use computer-morphing attempting to respond to these two obstacles. It is identified as the Method of Analysis and Research of the Integration of Emotions (M.A.R.I.E.). Our primary goal is to use M.A.R.I.E. to understand the physiology of ViFaEmRe in normal healthy subjects by standardizing the measurements. Then, it will allow us to focus on subjects manifesting abnormalities in this ability. Our second goal is to make our contribution to the progress of AI hoping to add the dimension of recognition of facial emotional expressions. Objective: To study: 1) categorical vs dimensional aspects of recognition of ViFaEmRe, 2) universality vs idiosyncrasy, 3) immediate vs ambivalent Emotional-Decision-Making, 4) the Emotional-Fingerprint of a face and 5) creation of population references data. Methods: With M.A.R.I.E. enable a rational quantified measurement of Emotional-Visual-Acuity (EVA) of 1) a) an individual observer, b) in a population aged 20 to 70 years old, 2) measure the range and intensity of expressed emotions by 3 Face-Tests, 3) quantify the performance of a sample of 204 observers with hyper normal measures of cognition, “thymia,” (ibid. defined elsewhere) and low levels of anxiety 4) analysis of the 6 primary emotions. Results: We have individualized the following continuous parameters: 1) “Emotional-Visual-Acuity”, 2) “Visual-Emotional-Feeling”, 3) “Emotional-Quotient”, 4) “Emotional-Deci-sion-Making”, 5) “Emotional-Decision-Making Graph” or “Individual-Gun-Trigger”6) “Emotional-Fingerprint” or “Key-graph”, 7) “Emotional-Finger-print-Graph”, 8) detecting “misunderstanding” and 9) detecting “error”. This allowed us a taxonomy with coding of the face-emotion pair. Each face has specific measurements and graphics. The EVA improves from ages of 20 to 55 years, then decreases. It does not depend on the sex of the observer, nor the face studied. In addition, 1% of people endowed with normal intelligence do not recognize emotions. The categorical dimension is a variable for everyone. The range and intensity of ViFaEmRe is idiosyncratic and not universally uniform. The recognition of emotions is purely categorical for a single individual. It is dimensional for a population sample. Conclusions: Firstly, M.A.R.I.E. has made possible to bring out new concepts and new continuous measurements variables. The comparison between healthy and abnormal individuals makes it possible to take into consideration the significance of this line of study. From now on, these new functional parameters will allow us to identify and name “emotional” disorders or illnesses which can give additional dimension to behavioral disorders in all pathologies that affect the brain. Secondly, the ViFaEmRe is idiosyncratic, categorical, and a function of the identity of the observer and of the observed face. These findings stack up against Artificial Intelligence, which cannot have a globalist or regionalist algorithm that can be programmed into a robot, nor can AI compete with human abilities and judgment in this domain. *Here “Emotional disorders” refers to disorders of emotional expressions and recognition.展开更多
Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the i...Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the interfaces of verbal and emotional communications. The progress of AI is significant on the verbal level but modest in terms of the recognition of facial emotions even if this functionality is one of the oldest in humans and is omnipresent in our daily lives. Dysfunction in the ability for facial emotional expressions is present in many brain pathologies encountered by psychiatrists, neurologists, psychotherapists, mental health professionals including social workers. It cannot be objectively verified and measured due to a lack of reliable tools that are valid and consistently sensitive. Indeed, the articles in the scientific literature dealing with Visual-Facial-Emotions-Recognition (ViFaEmRe), suffer from the absence of 1) consensual and rational tools for continuous quantified measurement, 2) operational concepts. We have invented a software that can use computer-morphing attempting to respond to these two obstacles. It is identified as the Method of Analysis and Research of the Integration of Emotions (M.A.R.I.E.). Our primary goal is to use M.A.R.I.E. to understand the physiology of ViFaEmRe in normal healthy subjects by standardizing the measurements. Then, it will allow us to focus on subjects manifesting abnormalities in this ability. Our second goal is to make our contribution to the progress of AI hoping to add the dimension of recognition of facial emotional expressions. Objective: To study: 1) categorical vs dimensional aspects of recognition of ViFaEmRe, 2) universality vs idiosyncrasy, 3) immediate vs ambivalent Emotional-Decision-Making, 4) the Emotional-Fingerprint of a face and 5) creation of population references data. Methods: M.A.R.I.E. enables the rational, quantified measurement of Emotional Visual Acuity (EVA) in an individual observer and a population aged 20 to 70 years. Meanwhile, it can measure the range and intensity of expressed emotions through three Face- Tests, quantify the performance of a sample of 204 observers with hypernormal measures of cognition, “thymia” (defined elsewhere), and low levels of anxiety, and perform analysis of the six primary emotions. Results: We have individualized the following continuous parameters: 1) “Emotional-Visual- Acuity”, 2) “Visual-Emotional-Feeling”, 3) “Emotional-Quotient”, 4) “Emotional-Decision-Making”, 5) “Emotional-Decision-Making Graph” or “Individual-Gun-Trigger”, 6) “Emotional-Fingerprint” or “Key-graph”, 7) “Emotional-Fingerprint-Graph”, 8) detecting “misunderstanding” and 9) detecting “error”. This allowed us a taxonomy with coding of the face-emotion pair. Each face has specific measurements and graphics. The EVA improves from ages of 20 to 55 years, then decreases. It does not depend on the sex of the observer, nor the face studied. In addition, 1% of people endowed with normal intelligence do not recognize emotions. The categorical dimension is a variable for everyone. The range and intensity of ViFaEmRe is idiosyncratic and not universally uniform. The recognition of emotions is purely categorical for a single individual. It is dimensional for a population sample. Conclusions: Firstly, M.A.R.I.E. has made possible to bring out new concepts and new continuous measurements variables. The comparison between healthy and abnormal individuals makes it possible to take into consideration the significance of this line of study. From now on, these new functional parameters will allow us to identify and name “emotional” disorders or illnesses which can give additional dimension to behavioral disorders in all pathologies that affect the brain. Secondly, the ViFaEmRe is idiosyncratic, categorical, and a function of the identity of the observer and of the observed face. These findings stack up against Artificial Intelligence, which cannot have a globalist or regionalist algorithm that can be programmed into a robot, nor can AI compete with human abilities and judgment in this domain. *Here “Emotional disorders” refers to disorders of emotional expressions and recognition.展开更多
文摘目的:探讨基于CT三维重组技术的R.E.N.A.L.评分系统在腹腔镜肾部分切除术中的临床应用价值。方法:搜集我院2020年6月至2024年1月经手术治疗的79例肾肿瘤患者的临床及术前影像资料,根据术前肾脏CT三维重组结果,分析血管变异与肾脏热缺血时间、手术总时间、术中出血量及术后并发症之间的关系,并进行R.E.N.A.L.评分。采用Logistic回归筛选出肾热缺血时间大于20 min的独立危险因素。结果:有无血管变异在肾脏热缺血时间、手术总时间、术中出血量及术后并发症之间无明显差异(P > 0.05)。R.E.N.A.L.总评分是肾热缺血时间大于20 min的独立危险因素(P P Objective: To explore the clinical application value of R.E.N.A.L. scoring system based on CT three-dimensional reconstruction technology in laparoscopic partial nephrectomy. Methods: The clinical and preoperative imaging data of 79 patients with renal tumors who underwent surgical treatment in our hospital from June 2020 to January 2024 were collected. According to the results of preoperative renal CT three-dimensional reconstruction, the relationship between vascular variation and renal warm ischemia time, total operation time, intraoperative bleeding and postoperative complications was analyzed, and R.E.N.A.L. score was performed. Logistic regression was used to screen out independent risk factors for renal warm ischemia time greater than 20 min. Results: There was no significant difference in renal warm ischemia time, total operation time, intraoperative blood loss and postoperative complications between the presence or absence of vascular variation (P > 0.05). The total R.E.N.A.L. score was an independent risk factor for renal warm ischemia time greater than 20 min (P P < 0.05). Conclusion: CT three-dimensional reconstruction can clearly understand the anatomical location of the kidney, tumor and blood vessels before surgery, thereby reducing the occurrence of perioperative complications.
基金supported by the National Natural Science Foundation of China(No.81873195)the Applied Basic Research Program of Liaoning Province(No.2023JH2/101300103)+1 种基金the Liaoning Revitalization Talents Program(No.XLYC1907113)the Dalian Medical University Foundation for Teaching Reform Project of Undergraduate Innovative Talents Training(No.111807010303)。
文摘Objective:Despite the combination of Scutellaria barbata D.Don and Scleromitrion diffusum(Willd.)R.J.Wang(SB-SD)being a recognized Chinese medicinal herbal pair that is commonly used in the treatment of ovarian cancer,there is a poor understanding of their pharmacological mechanisms.This study examines the antitumor properties and potential mechanisms of SB-SD on human ovarian cancer A2780 cells through a multi-omics approach,establishing a pharmacological basis for clinical utilization.Methods:A range of mass ratios and reagents were used in the hot reflux extraction of SB-SD.The inhibitory effect of the SB-SD extracts on A2780 cell proliferation was assessed using the cell-counting kit 8assay.A zebrafish tumor implantation model was used to evaluate the effects of SB-SD extracts on tumor growth and metastasis in vivo.Transcriptomics and proteomics were used to investigate alterations in biological pathways in A2780 cells after treatment with different concentrations of SB-SD extract.Cell cycle,cell apoptosis,intracellular free iron concentration,intracellular reactive oxygen species(ROS)concentration,malondialdehyde(MDA),and mitochondrial membrane potential were measured.Real-time quantitative reverse transcription polymerase chain reaction and Western blotting were utilized to investigate the effects of heme catabolism and ferritinophagy on ferroptosis induced by SB-SD extract in A2780 cells.Results:The 70%ethanol extract of SB-SD(a mass ratio of 4:1)inhibited A2780 cell proliferation significantly with a half maximal inhibitory concentration of 660μg/m L in a concentration-and timedependent manner.Moreover,it effectively suppressed tumor growth and metastasis in a zebrafish tumor implantation model.SB-SD extract induced the accumulation of free iron,ROS,MDA,and mitochondrial damage in A2780 cells.The mechanisms might involve the upregulated expression of ferritinophagyrelated genes microtubule-associated protein 1 light chain 3,autophagy-related gene 5,and nuclear receptor coactivator 4.Conclusion:SB-SD extract effectively inhibited the development of ovarian cancer both in vitro and in vivo.Its mechanism of action involved inducing ferroptosis by facilitating heme catabolism and ferritinophagy.This herbal pair holds promise as a potential therapeutic option for ovarian cancer treatment and may be utilized in combination with routine treatment to improve the treatment outcomes of ovarian cancer patients.
文摘Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the interfaces of verbal and emotional communications. The progress of AI is significant on the verbal level but modest in terms of the recognition of facial emotions even if this functionality is one of the oldest in humans and is omnipresent in our daily lives. Dysfunction in the ability for facial emotional expressions is present in many brain pathologies encountered by psychiatrists, neurologists, psychotherapists, mental health professionals including social workers. It cannot be objectively verified and measured due to a lack of reliable tools that are valid and consistently sensitive. Indeed, the articles in the scientific literature dealing with Visual-Facial-Emotions-Recognition (ViFaEmRe), suffer from the absence of 1) consensual and rational tools for continuous quantified measurement, 2) operational concepts. We have invented a software that can use computer-morphing attempting to respond to these two obstacles. It is identified as the Method of Analysis and Research of the Integration of Emotions (M.A.R.I.E.). Our primary goal is to use M.A.R.I.E. to understand the physiology of ViFaEmRe in normal healthy subjects by standardizing the measurements. Then, it will allow us to focus on subjects manifesting abnormalities in this ability. Our second goal is to make our contribution to the progress of AI hoping to add the dimension of recognition of facial emotional expressions. Objective: To study: 1) categorical vs dimensional aspects of recognition of ViFaEmRe, 2) universality vs idiosyncrasy, 3) immediate vs ambivalent Emotional-Decision-Making, 4) the Emotional-Fingerprint of a face and 5) creation of population references data. Methods: With M.A.R.I.E. enable a rational quantified measurement of Emotional-Visual-Acuity (EVA) of 1) a) an individual observer, b) in a population aged 20 to 70 years old, 2) measure the range and intensity of expressed emotions by 3 Face-Tests, 3) quantify the performance of a sample of 204 observers with hyper normal measures of cognition, “thymia,” (ibid. defined elsewhere) and low levels of anxiety 4) analysis of the 6 primary emotions. Results: We have individualized the following continuous parameters: 1) “Emotional-Visual-Acuity”, 2) “Visual-Emotional-Feeling”, 3) “Emotional-Quotient”, 4) “Emotional-Deci-sion-Making”, 5) “Emotional-Decision-Making Graph” or “Individual-Gun-Trigger”6) “Emotional-Fingerprint” or “Key-graph”, 7) “Emotional-Finger-print-Graph”, 8) detecting “misunderstanding” and 9) detecting “error”. This allowed us a taxonomy with coding of the face-emotion pair. Each face has specific measurements and graphics. The EVA improves from ages of 20 to 55 years, then decreases. It does not depend on the sex of the observer, nor the face studied. In addition, 1% of people endowed with normal intelligence do not recognize emotions. The categorical dimension is a variable for everyone. The range and intensity of ViFaEmRe is idiosyncratic and not universally uniform. The recognition of emotions is purely categorical for a single individual. It is dimensional for a population sample. Conclusions: Firstly, M.A.R.I.E. has made possible to bring out new concepts and new continuous measurements variables. The comparison between healthy and abnormal individuals makes it possible to take into consideration the significance of this line of study. From now on, these new functional parameters will allow us to identify and name “emotional” disorders or illnesses which can give additional dimension to behavioral disorders in all pathologies that affect the brain. Secondly, the ViFaEmRe is idiosyncratic, categorical, and a function of the identity of the observer and of the observed face. These findings stack up against Artificial Intelligence, which cannot have a globalist or regionalist algorithm that can be programmed into a robot, nor can AI compete with human abilities and judgment in this domain. *Here “Emotional disorders” refers to disorders of emotional expressions and recognition.
文摘Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the interfaces of verbal and emotional communications. The progress of AI is significant on the verbal level but modest in terms of the recognition of facial emotions even if this functionality is one of the oldest in humans and is omnipresent in our daily lives. Dysfunction in the ability for facial emotional expressions is present in many brain pathologies encountered by psychiatrists, neurologists, psychotherapists, mental health professionals including social workers. It cannot be objectively verified and measured due to a lack of reliable tools that are valid and consistently sensitive. Indeed, the articles in the scientific literature dealing with Visual-Facial-Emotions-Recognition (ViFaEmRe), suffer from the absence of 1) consensual and rational tools for continuous quantified measurement, 2) operational concepts. We have invented a software that can use computer-morphing attempting to respond to these two obstacles. It is identified as the Method of Analysis and Research of the Integration of Emotions (M.A.R.I.E.). Our primary goal is to use M.A.R.I.E. to understand the physiology of ViFaEmRe in normal healthy subjects by standardizing the measurements. Then, it will allow us to focus on subjects manifesting abnormalities in this ability. Our second goal is to make our contribution to the progress of AI hoping to add the dimension of recognition of facial emotional expressions. Objective: To study: 1) categorical vs dimensional aspects of recognition of ViFaEmRe, 2) universality vs idiosyncrasy, 3) immediate vs ambivalent Emotional-Decision-Making, 4) the Emotional-Fingerprint of a face and 5) creation of population references data. Methods: M.A.R.I.E. enables the rational, quantified measurement of Emotional Visual Acuity (EVA) in an individual observer and a population aged 20 to 70 years. Meanwhile, it can measure the range and intensity of expressed emotions through three Face- Tests, quantify the performance of a sample of 204 observers with hypernormal measures of cognition, “thymia” (defined elsewhere), and low levels of anxiety, and perform analysis of the six primary emotions. Results: We have individualized the following continuous parameters: 1) “Emotional-Visual- Acuity”, 2) “Visual-Emotional-Feeling”, 3) “Emotional-Quotient”, 4) “Emotional-Decision-Making”, 5) “Emotional-Decision-Making Graph” or “Individual-Gun-Trigger”, 6) “Emotional-Fingerprint” or “Key-graph”, 7) “Emotional-Fingerprint-Graph”, 8) detecting “misunderstanding” and 9) detecting “error”. This allowed us a taxonomy with coding of the face-emotion pair. Each face has specific measurements and graphics. The EVA improves from ages of 20 to 55 years, then decreases. It does not depend on the sex of the observer, nor the face studied. In addition, 1% of people endowed with normal intelligence do not recognize emotions. The categorical dimension is a variable for everyone. The range and intensity of ViFaEmRe is idiosyncratic and not universally uniform. The recognition of emotions is purely categorical for a single individual. It is dimensional for a population sample. Conclusions: Firstly, M.A.R.I.E. has made possible to bring out new concepts and new continuous measurements variables. The comparison between healthy and abnormal individuals makes it possible to take into consideration the significance of this line of study. From now on, these new functional parameters will allow us to identify and name “emotional” disorders or illnesses which can give additional dimension to behavioral disorders in all pathologies that affect the brain. Secondly, the ViFaEmRe is idiosyncratic, categorical, and a function of the identity of the observer and of the observed face. These findings stack up against Artificial Intelligence, which cannot have a globalist or regionalist algorithm that can be programmed into a robot, nor can AI compete with human abilities and judgment in this domain. *Here “Emotional disorders” refers to disorders of emotional expressions and recognition.
