OBJECTIVE To comprehensively analyze the effectiveness， safety and economic value of carfilzomib in the treatment of multiple myeloma （MM）， and provide evidence-based guidance for clinical rational drug use. METHODS A systematic search was performed in PubMed， Embase， the Cochrane Library， Web of Science， CNKI， Wanfang， VIP， and relevant health technology assessment （HTA） websites， from database inception to December 31， 2024. Two researchers independently screened studies based on predefined inclusion and exclusion criteria， extracted data， and assessed study quality. Descriptive statistical analyses were conducted. RESULTS A total of 21 studies were included， comprising 7 systematic reviews/meta-analyses， 5 clinical trials， 5 pharmacoeconomic studies， and 4 HTA reports. Effectiveness analysis indicated that， compared with control groups， carfilzomib significantly improved overall response rate and clinical benefit rate （ P ＜0.05）， prolonged progression-free survival， and enhanced patient’s quality of life （ P ＜0.05）， while its impact on overall survival remains to be further confirmed. Safety analysis showed there was no significant difference in the risk of peripheral neuropathy between carfilzomib and controls， while the risks of cardiotoxicity and hypertension were significantly increased （ P ＜0.05）. Economic analysis suggested that carfilzomib regimens demonstrated certain cost-effectiveness in second-line treatment in the U.S. and some European countries. However， its economic value was influenced by drug price， dosing regimen， and regional differences， and it may lack a cost advantage in some countries or in third-line treatment. CONCLUSIONS Carfilzomib shows definite efficacy and generally acceptable safety in the treatment of MM， but cardiotoxicity and hypertension risks require careful monitoring. Given its high treatment cost， pharmacoeconomic studies in the Chinese population are urgently needed.

Objective: To analyze the intervention effects of moderate to vigorous classroom physical exercise on psychological sub health among Uyghur junior high school students, providing reference for mental health promotion and intervention in the ethnic group. Methods: From April to July 2022, 647 eighth grade Uighur junior high school students from two middle schools in the Kashgar Prefecture, Xinjiang, were selected using a random cluster digital sampling method. They were randomly assigned to a control group ( n =326) and an intervention group ( n =321). While adhering to the regular curriculum, the intervention group additionally received 12 week, 36 session (every Monday, Wednesday, and Friday afternoon) moderate to vigorous classroom physical exercise intervention (45 minutes per session, including warm up, main exercises, and cool down activities). Self administered psychological sub health was completed through Brief Instrument on Psychological Health of Youths before and after intervention, and the data were analyzed using covariance analysis. Results: Before intervention, there were no statistically significant differences between the control and intervention groups in the total scores for psychological sub health or in the scores for the three dimensions including emotional problems, conduct problems, and social adaptation difficulties ( t =0.76, 0.40, 0.01, 0.94 , all P >0.05). After intervention, the scores of the intervention group s junior high school students on the emotional problems, conduct problems, and social adaptation difficulties dimensions decreased by 0.50, 0.28, and 0.18, respectively, compared with the control group, and all differences were statistically significant ( t =3.35, 3.36, 2.07, all P <0.05). The main effect of the psychological sub health category was statistically significant ( F =60.66, P <0.01, partial η 2=0.09). Compared with the control group, the psychological sub health scores of junior high school students in the intervention group decreased by 0.96 ( t =3.42, P < 0.05 ). Conclusion The 12 week moderate to vigorous classroom physical exercise intervention has a positive effect on the psychological sub health of Uyghur junior high school students.

Objective To understand mosquito density, species composition, and seasonal variations around the Beijing Capital International Airport(BCIA)and provide scientific evidence for mosquito-borne disease prevention and control. Methods Meteorological data were collected from 2016 to 2022, and mosquito density was monitored at seven surveillance sites around the BCIA from May to October each year using CO2-baited mosquito traps to analyze the relationship between mosquito density and meteorological factors. Results In total,68 518 female mosquitoes were captured, with a mosquito density of 10.20 per light · hour. The dominant species was Culex pipiens pallens(73.90%), followed by Aedes albopictus(9.71%)and Ae. vexans(9.29%);the mosquito density was highest in 2016(14.8 per light·hour)and lowest in 2022(4.46 per light·hour). Significant statistical differences were observed in mosquito density among different species(F=18.118, P<0.05). The density of Cx. pipiens pallens and other mosquito species showed a mutually exclusive trend; the peak of mosquito density varied based on years and habitats, with significant statistical differences in mosquito density among different habitats(F=8.504, P<0.05). The highest mosquito density was observed near the Wenyu River(21.50 per light·hour), whereas the lowest was recorded at the BCIA construction site(2.44 per light· hour). The monthly average temperature(r=0.595), monthly average highest temperature(r=0.575), and monthly average lowest temperature(r=0.624)showed moderate positive correlations, whereas the monthly average air pressure(r=-0.484)showed a moderate negative correlation. The monthly average minimum temperature was included in the regression model(F=25.575, P<0.000), and the equation Y=1.029X4-8.181 was used. The monthly average air pressure 2 months prior(b=-2.418, β=-1.619, P<0.05)and the monthly average relative humidity(b=-0.739, β=-1.201, P<0.05)significantly negatively predicted the mosquito density. Notably, the regression equation used was y=2526.170+(-2.418)X9+(-0.739)X13. The exposure-response analysis revealed that the density of mosquitoes was not linearly related to the average monthly air pressure, rainfall, and duration of sunshine. Conclusions The dominant mosquito species around the BCIA was Cx. pipiens pallens, Ae. albopictus, and Ae. vexans. During the control of Cx. pipiens pallens, the impact on other mosquito species must also be considered. Environmental management, breeding sites, and scientific use of pesticides should be prioritized based on the activity periods of mosquitoes. Further studies on mosquitoes and meteorological factors should be conducted to provide references and novel avenues for mosquito control.

Histone deacetylase 3 (HDAC3) is an epigenetic modification enzyme that plays a crucial role in the development and progression of diabetes and its complications. Studies have reported that increased HDAC3 activity is associated with pancreatic β-cell dysfunction in type 1 diabetes, while in type 2 diabetes, HDAC3 affects insulin resistance and signaling by regulating the metabolism of the liver, adipose tissue, and muscle. Additionally, HDAC3 plays a key role in diabetic complications such as cardiomyopathy, retinopathy, and nephropathy. Selective inhibition of HDAC3 has the potential to improve insulin sensitivity, reduce chronic inflammation, and enhance pancreatic cell function, offering a promising new therapeutic strategy for diabetes and its complications.

ObjectiveTo investigate the influence of histone deacetylase 3 (HDAC3) on the occurrence, development of psoriasis-like inflammation in mice, and the relative immune mechanisms. MethodsHealthy C57BL/6 mice aged 6-8 weeks were selected and randomly divided into 3 groups: control group (Control), psoriasis model group (IMQ), and HDAC3 inhibitor RGFP966-treated psoriasis model group (IMQ+RGFP966). One day prior to the experiment, the back hair of the mice was shaved. After a one-day stabilization period, the mice in Control group was treated with an equal amount of vaseline, while the mice in IMQ group was treated with imiquimod (62.5 mg/d) applied topically on the back to establish a psoriasis-like inflammation model. The mice in IMQ+RGFP966 group received intervention with a high dose of the HDAC3-selective inhibitor RGFP966 (30 mg/kg) based on the psoriasis-like model. All groups were treated continuously for 5 d, during which psoriasis-like inflammation symptoms (scaling, erythema, skin thickness), body weight, and mental status were observed and recorded, with photographs taken for documentation. After euthanasia, hematoxylin-eosin (HE) staining was used to assess the effect of RGFP966 on the skin tissue structure of the mice, and skin thickness was measured. The mRNA and protein expression levels of HDAC3 in skin tissues were detected using reverse transcription real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot (WB), respectively. Flow cytometry was employed to analyze neutrophils in peripheral blood and lymph nodes, CD4⁺ T lymphocytes, CD8⁺ T lymphocytes in peripheral blood, and IL-17A secretion by peripheral blood CD4⁺ T lymphocytes. Additionally, spleen CD4⁺ T lymphocyte expression of HDAC3, CCR6, CCR8, and IL-17A secretion levels were analyzed. Immunohistochemistry was used to detect the localization and expression levels of HDAC3, IL-17A, and IL-10 in skin tissues. ResultsCompared with the Control group, the IMQ group exhibited significant psoriasis-like inflammation, characterized by erythema, scaling, and skin wrinkling. Compared with the IMQ group, RGFP966 exacerbated psoriasis-like inflammatory symptoms, leading to increased hyperkeratosis. The psoriasis area and severity index (PASI) skin symptom scores were higher in the IMQ group than those in the Control group, and the scores were further elevated in the IMQ+RGFP966 group compared to the IMQ group. Skin thickness measurements showed a trend of IMQ+RGFP966>IMQ>Control. The numbers of neutrophils in the blood and lymph nodes increased sequentially in the Control, IMQ, and IMQ+RGFP966 groups, with a similar trend observed for CD4⁺ and CD8⁺ T lymphocytes in the blood. In skin tissues, compared with the Control group, the mRNA and protein levels of HDAC3 decreased in the IMQ group, but RGFP966 did not further reduce these expressions. HDAC3 was primarily located in the nucleus. Compared with the Control group, the nuclear HDAC3 content decreased in the skin tissues of the IMQ group, and RGFP966 further reduced nuclear HDAC3. Compared with the Control and IMQ groups, RGFP966 treatment decreased HDAC3 expression in splenic CD4⁺ and CD8⁺ T cells. RGFP966 treatment increased the expression of CCR6 and CCR8 in splenic CD4⁺ T cells and enhanced IL-17A secretion by peripheral blood and splenic CD4⁺ T lymphocytes. Additionally, compared with the IMQ group, RGFP966 reduced IL-10 protein levels and upregulated IL-17A expression in skin tissues. ConclusionRGFP966 exacerbates psoriatic-like inflammatory responses by inhibiting HDAC3, increasing the secretion of the cytokine IL-17A, and upregulating the expression of chemokines CCR8 and CCR6.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

As human deep space exploration enters a practical phase, ensuring astronaut health and safety has become a critical determinant of mission success. The cerebrovascular system, essential for maintaining brain function, is highly sensitive to environmental changes. Cerebrovascular diseases represent one of the characteristic adverse effects of deep space conditions such as microgravity and high-energy radiation, and have emerged as a frontier challenge in space medicine. Based on experiences from manned space missions, major research challenges persist, particularly the lack of experimental data specific to the lunar environment and the unclear threshold for low-dose radiation-induced injury. Elucidating the mechanisms and multifactorial interactions by which deep space environments impact cerebrovascular structure and function, and summarizing the key risk factors, pathological processes, and recent advances in monitoring and early-warning technologies for cerebrovascular diseases in lunar astronauts, and of crucial importance. A comprehensive understanding of the interplay between deep space environmental stressors and cerebrovascular injury, as well as the development of personalized prevention and intervention strategies, will provide both theoretical and practical foundations for safeguarding cerebrovascular health in future Chinese deep space missions, while promoting progress in related biomedical research, technological innovation, and international collaboration.
Humans ; Astronauts ; Cerebrovascular Disorders/etiology* ; Space Flight ; Weightlessness/adverse effects* ; Risk Factors ; Moon

Objective: To analyze the phylogenetic characteristics of VP1 gene of Coxsackievirus A10 (CVA10) isolates from 2004 to 2023, and to understand the genetic evolution and epidemic trends of CVA10, so as to provide references for the prevention and control of hand, foot, and mouth disease. Methods: The full-length sequences of the VP1 region of CVA10 isolates were retrieved from the BV-BRC database before December 15, 2024. Gene typing, sequence analysis, evolutionary analysis, and amino acid mutation site analysis were conducted using bioinformatics software. Results: A total of 1 253 CVA10 isolates VP1 region nucleotide full-length sequences from 2004 to 2023 were included, with 9 strains from 2004 to 2008, 338 strains from 2009 to 2012, and 906 strains from 2013 to 2023. China had the highest number of CVA10 isolates, with 1 143 strains accounting for 91.22%, and the predominant genotype was C3. Compared to the prototype strain, the nucleotide sequence homology of the VP1 region of CVA10 isolates ranged from 74.94% to 77.63%, while the amino acid sequence homology ranged from 88.59% to 93.62%. The third codon position preferred cytosine and thymine. The top three most abundant amino acids were threonine, alanine, and valine. The average relative synonymous codon usage of 30 amino acid codon groups was greater than 1. The average amino acid substitution entropy value was 0.04, with four amino acid mutation-prone sites identified, and the mutation-prone rate was 1.35%. Conclusions From 2004 to 2023, the majority of CVA10 isolates were primarily sourced from China, with genotype C3 being the predominant circulating strain in China. The nucleotide homology between the CVA10 isolates and the prototype strain was relatively low, and mutation-prone sites were identified, indicating that enhanced monitoring of viral variation is necessary.

Objective To investigate the protective effects of paeonol(PAE)on autophagy in human neuroblastoma cells(SH-SY5Y)induced by overexpression of α-synuclein(α-Syn),and to explore its related mechanism.Methods SH-SY5Y cells served as control group,while those induced with A53T-α-Syn mutation were used as model group.Additional groups included PAE(150 μg/ml)group,3-MA(1 mmol/L)group,and PAE(150 μg/ml)+3-MA(1 mmol/L)group.Cell viability was assessed using CCK-8 method,cell morphology was observed under an optical microscope,and protein expressions of α-Syn,LC3-Ⅱ,p62,Beclin-1,phosphorylated c-Jun N-terminal kinase(p-JNK),and p-Bcl-2 were determined by Western blotting.Results Compared with control group,model control exhibited decreased cell survival(P＜0.01),increased α-Syn expression(P＜0.001),reduced expression of autophagy-related proteins LC3-Ⅱ and Beclin-1(P＜0.01,P＜0.05),elevated autophagy substrate protein p62(P＜0.05),and decreased expression of autophagy pathway-related proteins p-JNK and Bcl-2(P＜0.05,P＜0.01).Compared with model group,PAE group showed increased cell survival(P＜0.01),decreased α-Syn and p62 protein expression(P＜0.01,P＜0.05),and increased expression of LC3-Ⅱ,Beclin-1,p-JNK and Bcl-2(P＜0.05).Compared with PAE group,3-MA+PAE group demonstrated increased α-Syn expression(P＜0.05).Conclusions PAE could attenuate the injury of SH-SY5Y cells induced by A53T-α-Syn and eliminate over-expressed α-Syn by activating autophagy pathway,which may be associated with the upregulation of JNK/Bcl-2 mediated autophagy pathway.

Objective To analyze the risk of postoperative ileus in severe ulcerative colitis(UC)patients undergoing total proctocolectomy with ileal pouch-anal anastomosis(TPC-IPAA)and develop and validate a nomogram prediction model.Methods A total of 278 severe UC patients un-dergoing TPC-IPAA from January 2018 to May 2022 were enrolled and divided into ileus group(n=73)and non-ileus group(n=205)based on the occurrence of postoperative ileus.Another 120 severe UC patients undergoing TPC-IPAA from June 2022 to April 2023 were selected as validation cohort(with a 7-to-3 ratio between the modeling cohort and the validation cohort).Factors influen-cing postoperative ileus in severe UC patients undergoing TPC-IPAA were analyzed to construct a No-mogram prediction model.The discrimination,consistency,and clinical utility of the Nomogram model were evaluated by the receiver operating characteristic(ROC)curve,calibration curve,and decision curve analysis(DC A).Results There were no significant differences in general characteristics be-tween the modeling cohort and the validation cohort(P＞0.05).Significant differences were ob-served in preoperative American Society of Anesthesiologists(ASA)classification,preoperative al-bumin level,history of abdominal surgery,surgical approach,operation duration,intraoperative blood loss,and postoperative intra-abdominal infection between the ileus group and the non-ileus-group(P＜0.05).Preoperative ASA classification,preoperative albumin level,history of abdomi-nal surgery,operation duration,intraoperative blood loss,and postoperative intra-abdominal infec-tion were independent influencing factors for postoperative ileus in severe UC patients undergoing TPC-IPAA(P＜0.05).The ROC curve showed that the area under the curve of the Nomogram model for predicting postoperative ileus in severe UC patients undergoing TPC-IPAA was 0.782(95％CI,0.723 to 0.842)in the modeling cohort and 0.785(95％CI,0.693 to 0.878)in the validation cohort,indicating good discrimination of the model.The calibration curve demonstrated good consistency of the nomogram model.The DCA curve suggested high clinical utility of the Nomogram model.Conclusion The risk of postoperative ileus in severe UC patients undergoing TPC-IPAA is influenced by preoperative ASA classification,history of abdominal surgery,preopera-tive albumin level,intraoperative blood loss,operation duration,and postoperative intra-abdominal infection.The nomogram prediction model developed based on these factors has high predictive per-formance for the risk of postoperative ileus.