Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

It remains unclear whether heart transplantation is still feasible on patients who develop neurological complications before surgery and underwent successful neurological treatment.This article reported the diagnosis and treatment process of a heart failure patient complicating with acute ischemic stroke,who underwent successful heart transplantation after thrombectomy for acute ischemic stroke,aiming to provide clinical evidence and decision-making plan on diagnosis and treatment options for this group of patients with severe neurological complications.

As a microbial therapy method, fecal microbiota transplantation (FMT) has attracted the attention of researchers in recent years. As one of the most direct and effective methods to improve gut microbiota, FMT achieves therapeutic benefits by transplanting functional gut microbiota from healthy human feces into the intestines of patients to reconstruct new gut microbiota. FMT has been proven to be an effective treatment for gastrointestinal diseases such as Clostridium difficile infection, irritable bowel syndrome, and inflammatory bowel disease. In addition, the clinical and basic research of FMT outside the gastrointestinal system is also emerging. It is worth noting that there is bidirectional communication between the gut microbial community and the central nervous system (CNS) through the gut-brain axis. Some gut bacteria can synthesize and release neurotransmitters such as glutamate, gamma-aminobutyric acid (GABA) and dopamine. Imbalanced gut microbiota may interfere with the normal levels of these neurotransmitters, thereby affecting brain function. Gut microbiota can also produce metabolites that may cross the blood-brain barrier and affect CNS function. FMT may affect the occurrence and development of CNS and its related diseases by reshaping the gut microbiota of patients through a variety of pathways such as nerves, immunity, and metabolites. This article introduces the development of FMT and the research status of FMT in China, and reviews the basic and clinical research of FMT in neurodegenerative diseases (Alzheimer’s disease, Parkinson’s disease), neurotraumatic diseases (spinal cord injury, traumatic brain injury) and stroke from the characteristics of three types of nervous system diseases, the characteristics of intestinal flora, and the therapeutic effect and mechanism of fecal microbiota transplantation, summarize the common mechanism of fecal microbiota transplantation in the treatment of CNS diseases and the therapeutic targets. We found that the common mechanisms of FMT in the treatment of nervous system diseases may include the following 3 categories through summary and analysis. (1) Gut microbiota metabolites, such as SCFAs, TMAO and LPS. (2) Inflammatory factors and immune inflammatory pathways such as TLR-MyD88 and NF-κB. (3) Neurotransmitter 5-HT. In the process of reviewing the studies, we found the following problems. (1) In basic researches on the relationship between FMT and CNS diseases, there are relatively few studies involving the autonomic nervous system pathway. (2) Clinical trial studies have shown that FMT improves the severity of patients’ symptoms and may be a promising treatment for a variety of neurological diseases. (3) The improvement of clinical efficacy is closely related to the choice of donor, especially emphasizing that FMT from healthy and young donors may be the key to the improvement of neurological diseases. However, there are common challenges in current research on FMT, such as the scientific and rigorous design of FMT clinical trials, including whether antibiotics are used before transplantation or different antibiotics are used, as well as different FMT processes, different donors, different functional analysis methods of gut microbiota, and the duration of FMT effect. Besides, the safety of FMT should be better elucidated, especially weighing the relationship between the therapeutic benefits and potential risks of FMT carefully. It is worth mentioning that the clinical development of FMT even exceeds its basic research. Science and TIME rated FMT as one of the top 10 breakthroughs in the field of biomedicine in 2013. FMT therapy has great potential in the treatment of nervous system diseases, is expected to open up a new situation in the medical field, and may become an innovative weapon in the medical field.

Objective To investigate the improvement effect and mechanism of marmesin on cognitive impairment in Alzheimer's disease(AD)mice.Methods Fifty mice were randomly divided into five groups:blank group,model group,low-and high-dose marmesin groups and donepezil(positive drug)group,with 10 mice in each group.After 21 days of continuous administration,except for the blank group,the mice in other groups were given intraperitoneal injection of scopolamine to establish the AD model.Network pharmacology was used to construct the protein-protein interaction(PPI)network of common targets of marmesin in the treatment of AD,and gene ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis were performed to provide further research direction.The cognitive function of AD model mice was evaluated by Morris water maze,open field test and new object recognition test.Nissl staining was used to observe the damage of hippocampal neurons.The levels of acetylcholine(Ach),acetylcholine transferase(ChAT),acetylcholinesterase(AChE),reactive oxygen species(ROS),malondialdehyde(MDA)and catalase(CAT)in hippocampus of mice were detected by kit.The protein expression levels of interleukin 6(IL-6),interleukin 1β(IL-1 β),tumor necrosis factor α(TNF-α),nuclear factor E2-related factor 2(NRF2),silent information regulator homologous protein 3(SIRT3),Kelch-like ECH-associated protein 1(KEAP1),quinone oxidoreductase 1(NQO1)and heme oxygenase 1(HO-1)in hippocampus were detected by Western Blot.Results Compared with the model group,the latency of Morris water maze test was significantly shortened in the high-dose marmesin group,the time of entering the target area in the open field new object test and the movement distance in the central area of the open field were prolonged,the number of neurons in the hippocampal CA1 and CA3 regions was significantly increased,the levels of ChAT and Ach in the hippocampus were significantly increased,AChE level was significantly decreased,CAT level was significantly increased,ROS and MDA levels were significantly decreased,TNF-α expression level was decreased,SIRT3 and HO-1 expression levels were increased,and KE AP1 protein expression level was decreased,the differences being statistically significant(P＜0.05 or P＜0.01 or P＜0.001).Conclusion Marmesin can effectively improve the learning and memory impairment of AD mice,and its mechanism may be related to the activation of NRF2/SIRT3 signaling pathway,thereby alleviating oxidative stress level and neuroinflammation,and repairing cholinergic neuron function.

Objective:To assess the capability of seven reference medical laboratories to detect BCR::ABL1 p210 transcription levels and to compare the results among those laboratories.Methods:The interlaboratory comparison was carried out in two stages. The samples were prepared by the reference laboratory. The quantitative values of BCR::ABL1 p210 of the comparison samples covered 0.001%-0.01%, 0.01%-0.1%, 0.1%-1%, 1%-10% and>10% in each stage. Real-time quantitative PCR (RT-PCR) and dPCR (digital PCR) were used to examine the samples. The conversion factor (CF) was calculated and validated for each laboratory.Results:In the RT-PCR comparison, one laboratory was failed to detect BCR::ABL1 p210 in fourteen samples at the first stage. The results of the other six laboratories were qualified with the bias <±1.2 folds (-0.133-0.338) and 95% limits of agreement within ±5 folds (upper limit 0.147-0.785, lower limit -0.770--0.109), and the corresponding CF values were calculated and validated. In the dPCR comparison, one laboratory did not report results at the second stage. The results of the other six laboratories were qualified with the bias <±1.2 folds (-0.026-0.267) and 95% limits of agreement within±5 folds (upper limit 0.084-0.991, lower limit -0.669--0.135), and the corresponding CF values were calculated and validated. The samples with BCR::ABL1 p210 quantitative values of 0.01%-0.1%, 0.1%-1%, 1%-10% and >10% could be detected by both RT-PCR and qPCR. When the quantitative value of BCR::ABL1 p210 was 0.001%-0.01%, the detection rate of dPCR was higher than that of RT-PCR (85.56% vs. 68.00%).Conclusions:A good consistency is present among various laboratories. The quantitative value of BCR::ABL1 p210 is comparable among laboratories as shown by the CF value conversion. For quantitative detection of BCR::ABL1 p210 deep molecular reaction, dPCR has a higher positive detection rate and more advantages than RT-PCR. To ensure the accuracy and reproducibility of the BCR::ABL1 p210 test, it is imperative for every laboratory to enhance their daily quality control practices.

Purpose::To identify the risk factors for training-related lower extremity muscle injuries in young males by a non-invasive method of body composition analysis.Methods::A total of 282 healthy young male volunteers aged 18 -20 years participated in this cohort study. Injury location, degree, and injury rate were adjusted by a questionnaire based on the overuse injury assessment methods used in epidemiological studies of sports injuries. The occurrence of training injuries is monitored and diagnosed by physicians and treated accordingly. The body composition was measured using the BodyStat QuadScan 4000 multifrequency Bio-impedance system at 5, 50, 100 and 200 kHz to obtain 4 impedance values. The Shapiro-Wilk test was used to check whether the data conformed to a normal distribution. Data of normal distribution were shown as mean ± SD and analyzed by t-test, while those of non-normal distribution were shown as median (Q 1, Q 3) and analyzed by Wilcoxon rank sum test. The receiver operator characteristic curve and logistic regression analysis were performed to investigate risk factors for developing training-related lower extremity injuries and accuracy. Results::Among the 282 subjects, 78 (27.7%) developed training injuries. Lower extremity training injuries revealed the highest incidence, accounting for 23.4% (66 cases). These patients showed higher percentages of lean body mass ( p = 0.001), total body water (TBW, p=0.006), extracellular water ( p=0.020) and intracellular water ( p=0.010) as well as a larger ratio of basal metabolic rate/total weight ( p=0.006), compared with those without lower extremity muscle injuries. On the contrary, the percentage of body fat ( p=0.001) and body fat mass index ( p=0.002) were lower. Logistic regression analysis showed that TBW percentage > 65.35% ( p=0.050, odds ratio =3.114) and 3rd space water > 0.95% ( p=0.045, odds ratio =2.342) were independent risk factors for lower extremity muscle injuries. Conclusion::TBW percentage and 3rd space water measured with bio-impedance method are potential risk factors for predicting the incidence of lower extremity muscle injuries in young males following training.