ObjectiveTo investigate the effect and mechanism of Yijingtang （YJT） in treating diminished ovarian reserve （DOR） in rats by regulating the Toll-like receptor 4 （TLR4）/myeloid differentiation factor 88 （MyD88）/nuclear factor-κB （NF-κB） signaling pathway. MethodsFifty female SD rats with normal estrous cycles were randomly allocated into blank， model， low- and high-dose （12.579 and 25.158 g·kg^-1， respectively） YJT， and dehydroepiandrosterone （7.487 5 mg·kg^-1） groups， with 10 rats in each group. The rats in other groups except the blank group were administrated with the tripterygium glycosides tablet suspension （5 mg·kg^-1） by gavage for 14 days for the modeling of DOR. The rats in the drug treatment groups were administrated with corresponding drugs by gavage from day 15 for 30 consecutive days， and those in the blank and model groups received equal volumes of distilled water. The vaginal exfoliated cell smears were observed to assess the changes in the estrous cycle. The wet weight of bilateral ovaries was weighed for calculation of the ovarian index. Hematoxylin-eosin staining was performed to observe the histopathological changes in the ovaries and the proportions of follicles at various levels were calculated. The serum levels of sex hormones ［follicle-stimulating hormone （FSH）， luteinizing hormone （LH）， estradiol （E₂）， and anti-Müllerian hormone （AMH）］ and inflammatory factors ［tumor necrosis factor-alpha （TNF-α）， interleukin-1beta （IL-1β）， and interleukin-10 （IL-10）］ were determined by enzyme-linked immunosorbent assay. Real-time quantitative polymerase chain reaction（Real-time PCR） was conducted to determine the mRNA levels of TLR4， MyD88， NF-κB profilin α （IκBα）， NF-κB and inflammatory factors in the ovarian tissue. Western blot was employed to measure the protein levels of factors related to the TLR4/MyD88/NF-κB signaling pathway in the ovarian tissue. Immunofluorescence （IF） was used to detect the nuclear translocation of NF-κB p65 in the ovarian tissue. ResultsCompared with the blank group， the model group showed disturbed estrous cycles， increased inflammatory infiltration in the ovarian tissue， decreases in ovarian index and proportion of presinusoidal follicles， and an increase in the proportion of atretic follicles （P<0.05， P<0.01）. In addition， the model group showed elevated serum levels of FSH， LH， TNF-α， and IL-1β， up-regulated mRNA levels of TLR4， MyD88， IκBα， NF-κB， TNF-α， and IL-1β and protein levels of TLR4， MyD88， p-IκBα， and p-NF-κB p65 （P<0.01）， lowered serum levels of AMH， E₂， and IL-10， down-regulated mRNA level of IL-10 （P<0.01）， and massive nuclear translocation of NF-κB p65 in the ovarian tissue. Compared with the model group， dehydroepiandrosterone and low and high doses of YJT restored the disturbed estrous cycle， reduced inflammatory infiltration in the ovarian tissue， increased the ovarian index （P<0.01）， and changed the follicular composition ratio （P<0.01）. Furthermore， the drugs lowered the serum levels of FSH， LH， TNF-α， and IL-1β， down-regulated the mRNA levels of TLR4， MyD88， IκBα， NF-κB， TNF-α， and IL-1β and the protein levels of TLR4， MyD88， p-IκBα， and p-NF-κB p65 （P<0.05， P<0.01）， raised the serum levels of AMH， E₂， and IL-10， up-regulated the mRNA level of IL-10 （P<0.05， P<0.01）， and reduced the nuclear translocation of NF-κB p65 in the ovarian tissue. ConclusionYJT may inhibit the release and expression of inflammatory factors by regulating the TLR4/MyD88/NF-κB signaling pathway to attenuate the inflammatory responses in the ovarian tissue， thereby improving the ovarian function in DOR rats.

ObjectiveTo investigate the effect and mechanism of Yijingtang （YJT） in treating diminished ovarian reserve （DOR） in rats by regulating the Toll-like receptor 4 （TLR4）/myeloid differentiation factor 88 （MyD88）/nuclear factor-κB （NF-κB） signaling pathway. MethodsFifty female SD rats with normal estrous cycles were randomly allocated into blank， model， low- and high-dose （12.579 and 25.158 g·kg^-1， respectively） YJT， and dehydroepiandrosterone （7.487 5 mg·kg^-1） groups， with 10 rats in each group. The rats in other groups except the blank group were administrated with the tripterygium glycosides tablet suspension （5 mg·kg^-1） by gavage for 14 days for the modeling of DOR. The rats in the drug treatment groups were administrated with corresponding drugs by gavage from day 15 for 30 consecutive days， and those in the blank and model groups received equal volumes of distilled water. The vaginal exfoliated cell smears were observed to assess the changes in the estrous cycle. The wet weight of bilateral ovaries was weighed for calculation of the ovarian index. Hematoxylin-eosin staining was performed to observe the histopathological changes in the ovaries and the proportions of follicles at various levels were calculated. The serum levels of sex hormones ［follicle-stimulating hormone （FSH）， luteinizing hormone （LH）， estradiol （E₂）， and anti-Müllerian hormone （AMH）］ and inflammatory factors ［tumor necrosis factor-alpha （TNF-α）， interleukin-1beta （IL-1β）， and interleukin-10 （IL-10）］ were determined by enzyme-linked immunosorbent assay. Real-time quantitative polymerase chain reaction（Real-time PCR） was conducted to determine the mRNA levels of TLR4， MyD88， NF-κB profilin α （IκBα）， NF-κB and inflammatory factors in the ovarian tissue. Western blot was employed to measure the protein levels of factors related to the TLR4/MyD88/NF-κB signaling pathway in the ovarian tissue. Immunofluorescence （IF） was used to detect the nuclear translocation of NF-κB p65 in the ovarian tissue. ResultsCompared with the blank group， the model group showed disturbed estrous cycles， increased inflammatory infiltration in the ovarian tissue， decreases in ovarian index and proportion of presinusoidal follicles， and an increase in the proportion of atretic follicles （P<0.05， P<0.01）. In addition， the model group showed elevated serum levels of FSH， LH， TNF-α， and IL-1β， up-regulated mRNA levels of TLR4， MyD88， IκBα， NF-κB， TNF-α， and IL-1β and protein levels of TLR4， MyD88， p-IκBα， and p-NF-κB p65 （P<0.01）， lowered serum levels of AMH， E₂， and IL-10， down-regulated mRNA level of IL-10 （P<0.01）， and massive nuclear translocation of NF-κB p65 in the ovarian tissue. Compared with the model group， dehydroepiandrosterone and low and high doses of YJT restored the disturbed estrous cycle， reduced inflammatory infiltration in the ovarian tissue， increased the ovarian index （P<0.01）， and changed the follicular composition ratio （P<0.01）. Furthermore， the drugs lowered the serum levels of FSH， LH， TNF-α， and IL-1β， down-regulated the mRNA levels of TLR4， MyD88， IκBα， NF-κB， TNF-α， and IL-1β and the protein levels of TLR4， MyD88， p-IκBα， and p-NF-κB p65 （P<0.05， P<0.01）， raised the serum levels of AMH， E₂， and IL-10， up-regulated the mRNA level of IL-10 （P<0.05， P<0.01）， and reduced the nuclear translocation of NF-κB p65 in the ovarian tissue. ConclusionYJT may inhibit the release and expression of inflammatory factors by regulating the TLR4/MyD88/NF-κB signaling pathway to attenuate the inflammatory responses in the ovarian tissue， thereby improving the ovarian function in DOR rats.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Objective: To evaluate the clinical effect of blood transfusion treatment in elderly critically ill patients under different blood transfusion initiation thresholds. Methods: A total of 144 elderly critically ill patients aged >70 years who underwent red blood cell transfusion in the elderly intensive care unit (ICU) of our hospital from January 2021 to January 2023 were included. According to different blood transfusion initiation thresholds, the patients were divided into restrictive blood transfusion group (n=77, Hb<70 g/L before blood transfusion) and liberal blood transfusion group (n=67, Hb 70-100 g/L before blood transfusion). Acute physiology and chronic health evaluation Ⅱ (APACHE Ⅱ) score, estimated mortality and general data collection were performed when the two groups of patients entered the ICU. Blood transfusion details of these patients in the ICU were collected and documented, including pre-transfusion Hb levels, volume and number of red blood cell transfusion, and post- transfusion Hb levels. Propensity score matching (PSM) was used to match the baseline data of the two groups of patients, and the clinical outcomes were compared and analyzed after matching. Results: After PSM matching, 52 pairs of patients were successfully matched. The matched restrictive and liberal transfusion groups showed comparable characterists, including age, APACHE Ⅱ score, the number of cases with APACHE Ⅱ score >20, estimated mortality, incidence of comorbidities and primary diseases (P>0.05). The number of red blood cell transfusions and transfusion volume (U) in the ICU of the two groups were 7.77±4.73 vs 12.19±10.41, 11.64±7.65 vs 19.14±16.14 (all P<0.05), and the Hb levels (g/L) before and after red blood cell transfusion in the ICU was 59.92±5.98 vs 77.44±8.60,77.88±17.21 vs 87.56±15.23 (all P<0.05). In terms of clinical outcomes, there was no significant difference between the two groups (all P>0.05): ICU length of stay (d) 39.56±36.80 vs 40.10±49.29, three-week mortality rate (%) 21.2 vs 21.2, in-hospital mortality rate (%) 46.2 vs 53.9, mortality rate in subgroup with APACHE Ⅱ score ≤ 20 (%) 11.5 vs 1.9, the incidence of severe infection (%) 78.8 vs 73.1, the incidence of heart failure (%) 57.7 vs 44.2, and the incidence of pulmonary edema (%) 26.9 vs 19.2. Conclusion: Elderly ICU patients can tolerate lower blood transfusion thresholds. Therefore, the restrictive transfusion strategy can reduce the total amount of blood transfusion, save valuable blood resources, and achieve the same blood transfusion effect as the liberal transfusion strategy.