Female university students' fertility intentions and their psychosocial factors.

BACKGROUND: Raising the birth rate can effectively increase the resulting labour supply and minimise the adverse impact of an ageing population on high-quality economic development since the demographic dividend is rapidly declining. The Chinese government has a "three-child" policy in place, yet the fertility rate is still falling. This study intends to investigate the present fertility intentions of female university students and assess the extent to which feminism has affected their intentions. It will next investigate the degree to which and the mechanisms by which the psychosocial factors have an impact on those intentions. METHODS: A cross-sectional survey of female university students was conducted in Nanjing, China, from February to March 2023. To assure the representativeness of the sample, a technique of stratified proportional sampling, PPS sampling, and convenience sampling was utilized. A total of 1124 valid samples were acquired from female university students in 15 comprehensive universities. The data were mined and analysed by SPSS (version 24.0) and AMOS (version 24.0) software. RESULTS: Overall female university students' fertility intentions are low at this stage, with more than half (53.55%) of them having no clear desire to have children. The level of feminist identity significantly negatively affected the Intensity of desire to have children (-0.32) and child-number desires (-0.7). Psychosocial factors had a greater degree of influence on fertility intentions. The direct effect of the level of feminist identity and the perception of fertility hindrances on childbearing desires was -0.63 and -0.50 respectively, and the direct effect of the perception of fertility supports on childbearing intentions was 0.79. CONCLUSION: The level of feminist identity is significantly and negatively related to childbearing desires. Psychosocial factors have a greater degree of influence on fertility intentions, with the level of feminist identity, the perception of fertility hindrances and the perception of fertility supports all significantly impacting fertility intentions. The findings of this study emphasise the importance of the government providing a full range of social security and employers providing better employee benefits to promote a fertility-friendly society.

The relationship between air pollutants and preterm birth and blood routine changes in typical river valley city.

OBJECTIVE: To collect maternal maternity information on preterm births in two tertiary hospitals in the urban area of Baota District, Yan'an City, from January 2018 to December 2020, to explore the long-term and short-term effects of air pollutants (PM2.5, PM10, SO2, NO2, CO and O3) and preterm births, and to explore changes in blood cell counts due to air pollutants. METHODS: Daily average mass concentration data of six air pollutants in the urban area of Yan'an City from January 1, 2017 to December 31, 2020 were collected from the monitoring station in Baota District, Yan'an City. Meteorological information was obtained from the Meteorological Bureau of Yan'an City, including temperature,relative humidity and wind speed for the time period. The mass concentration of air pollutants in each exposure window of pregnant women was assessed by the nearest monitoring station method, and conditional logistic regression was used to analyze the relationship between air pollutants and preterm births, as well as the lagged and cumulative effects of air pollutants. Multiple linear regression was used to explore the relationship between air pollutants and blood tests after stepwise linear regression was used to determine confounders for each blood test. RESULTS: The long-term effects of pollutants showed that PM2.5, PM10, SO2, NO2and CO were risk factors for preterm birth. In the two-pollutant model, PM2.5, PM10, SO2 and NO2 mixed with other pollutants were associated with preterm birth. The lagged effect showed that PM2.5, PM10, SO2, NO, and CO were associated with preterm birth; the cumulative effect showed that other air pollutants except O3 were associated with preterm birth. The correlation study between air pollutants and blood indicators showed that air pollutants were correlated with leukocytes, monocytes, basophils, erythrocytes, hs-CRPand not with CRP. CONCLUSION: Exposure to air pollutants is a risk factor for preterm birth. Exposure to air pollutants was associated with changes in leukocytes, monocytes, basophils and erythrocytes and hs-CRP.

Zigzag Hopping Site Embedded Covalent Organic Frameworks Coating for Zn Anode.

Precise design and tuning of Zn hopping/transfer sites with deeper understanding of the dendrite-formation mechanism is vital in artificial anode protective coating for aqueous Zn-ion batteries (AZIBs). Here, we probe into the role of anode-coating interfaces by designing a series of anhydride-based covalent organic frameworks (i.e., PI-DP-COF and PI-DT-COF) with specifically designed zigzag hopping sites and zincophilic anhydride groups that can serve as desired platforms to investigate the related Zn2+ hopping/transfer behaviours as well as the interfacial interaction. Combining theoretical calculations with experiments, the ABC stacking models of these COFs endow the structures with specific zigzag sites along the 1D channel that can accelerate Zn2+ transfer kinetics, lower surface-energy, homogenize ion-distribution or electric-filed. Attributed to these superiorities, thus-obtained optimal PI-DT-COF cells offer excellent cycling lifespan in both symmetric-cell (2000 cycles at 60 mA cm-2) and full-cell (1600 cycles at 2 A g-1), outperforming almost all the reported porous crystalline materials.

Investigation of ash fusion characteristics on co-combustion of coal and biomass (straw, sludge, and herb residue) based on experimental and machine learning method.

Co-combustion of coal and biomass has the potential to reduce the cost of power generation in plants. However, because of the high content of the alkali metal of biomass ash, co-combustion of these two fuels leads to unpredictable ash fusion temperature (AFT). This study conducted experiments to measure the AFT of straw, sludge, and herb residue when they were blended with coal at different ratios. Additionally, a machine learning algorithm called tuna swarm optimization (TSO) was employed to optimize the support vector regression (SVR) model to predict the softening temperature (ST) of samples. The results indicate that straw and sludge were found to be suitable for blending in small proportions, while herb residue was suitable for blending in larger proportions. In comparison to the traditional grid search optimization model, the TSO algorithm significantly enhances the prediction accuracy of both training and test sets, and improves the generalization ability of SVR.

Green analytical assay for the viability assessment of single maize seeds using double-threshold strategy for catalase activity and malondialdehyde content.

The development of nondestructive technology for the detection of seed viability is challenging. In this study, to establish a green and effective method for the viability assessment of single maize seeds, a two-stage seed viability detection method was proposed. The catalase (CAT) activity and malondialdehyde (MDA) content were selected as the most key biochemical components affecting maize seed viability, and regression prediction models were developed based on their hyperspectral information and a data fusion strategy. Qualitative discrimination models for seed viability evaluation were constructed based on the predicted response values of the selected key biochemical components. The results showed that the double components thresholds strategy achieved the highest discrimination accuracy (92.9%), providing a crucial approach for the rapid and environmentally friendly detection of seed viability.

Ambient health sensing on passive surfaces using metamaterials.

Ambient sensors can continuously and unobtrusively monitor a person's health and well-being in everyday settings. Among various sensing modalities, wireless radio-frequency sensors offer exceptional sensitivity, immunity to lighting conditions, and privacy advantages. However, existing wireless sensors are susceptible to environmental interference and unable to capture detailed information from multiple body sites. Here, we present a technique to transform passive surfaces in the environment into highly sensitive and localized health sensors using metamaterials. Leveraging textiles' ubiquity, we engineer metamaterial textiles that mediate near-field interactions between wireless signals and the body for contactless and interference-free sensing. We demonstrate that passive surfaces functionalized by these metamaterials can provide hours-long cardiopulmonary monitoring with accuracy comparable to gold standards. We also show the potential of distributed sensors and machine learning for continuous blood pressure monitoring. Our approach enables passive environmental surfaces to be harnessed for ambient sensing and digital health applications.

Exploring the association between atmospheric pollutants and preterm birth risk in a river valley city.

Objective: To investigate the association between exposure to atmospheric pollutants and preterm birth in a river valley-type city and its critical exposure windows. Methods: A retrospective cohort study was used to collect data from the medical records of preterm and full-term deliveries in two hospitals in urban areas of a typical river valley-type city from January 2018 to December 2019. A total of 7,288 cases were included in the study with general information such as pregnancy times, the number of cesarean sections, occupation, season of conception and regularity of the menstrual cycle. And confounding factors affecting preterm birth were inferred using the chi-square test. The effects of exposure to each pollutant, including particulate matter 2.5 (PM2.5), particulate matter 10 (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO) and ozone (O3), during pregnancy on preterm birth and the main exposure windows were explored by establishing a logistic regression model with pollutants introduced as continuous variables. Results: Maternal age, pregnancy times, number of births, number of cesarean sections, season of conception, complications diseases, comorbidities diseases, hypertension disorder of pregnancy and neonatal low birth weight of the newborn were significantly different between preterm and term pregnant women. Logistic regression analysis after adjusting for the above confounders showed that the risk of preterm birth increases by 0.9, 0.6, 2.4% in T2 and by 1.0, 0.9, 2.5% in T3 for each 10 µg/m3 increase in PM2.5, PM10, NO2 concentrations, respectively. The risk of preterm birth increases by 4.3% in T2 for each 10 µg/m3 increase in SO2 concentrations. The risk of preterm birth increases by 123.5% in T2 and increases by 188.5% in T3 for each 10 mg/m3 increase in CO concentrations. Conclusion: Maternal exposure to PM2.5, PM10, NO2, CO was associated with increased risk on preterm birth in mid-pregnancy (T2) and late pregnancy (T3), SO2 exposure was associated with increased risk on preterm birth in mid-pregnancy (T2).

Deciphering glutamine metabolism patterns for malignancy and tumor microenvironment in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer characterized by metabolic reprogramming. Glutamine metabolism is pivotal in metabolic reprogramming, contributing to the significant heterogeneity observed in ccRCC. Consequently, developing prognostic markers associated with glutamine metabolism could enhance personalized treatment strategies for ccRCC patients. This study obtained RNA sequencing and clinical data from 763 ccRCC cases sourced from multiple databases. Consensus clustering of 74 glutamine metabolism related genes (GMRGs)- profiles stratified the patients into three clusters, each of which exhibited distinct prognosis, tumor microenvironment, and biological characteristics. Then, six genes (SMTNL2, MIOX, TMEM27, SLC16A12, HRH2, and SAA1) were identified by machine-learning algorithms to develop a predictive signature related to glutamine metabolism, termed as GMRScore. The GMRScore showed significant differences in clinical prognosis, expression profile of immune checkpoints, abundance of immune cells, and immunotherapy response of ccRCC patients. Besides, the nomogram incorporating the GMRScore and clinical features showed strong predictive performance in prognosis of ccRCC patients. ALDH18A1, one of the GRMGs, exhibited elevated expression level in ccRCC and was related to markedly poorer prognosis in the integrated cohort, validated by proteomic profiling of 232 ccRCC samples from Fudan University Shanghai Cancer Center (FUSCC). Conducting western blotting, CCK-8, transwell, and flow cytometry assays, we found the knockdown of ALDH18A1 in ccRCC significantly promoted apoptosis and inhibited proliferation, invasion, and epithelial-mesenchymal transition (EMT) in two human ccRCC cell lines (786-O and 769-P). In conclusion, we developed a glutamine metabolism-related prognostic signature in ccRCC, which is tightly linked to the tumor immune microenvironment and immunotherapy response, potentially facilitating precision therapy for ccRCC patients. Additionally, this study revealed the key role of ALDH18A1 in promoting ccRCC progression for the first time.

Unveiling the impact of tertiary lymphoid structures on immunotherapeutic responses of clear cell renal cell carcinoma.

Tertiary lymphoid structures (TLS) are organized aggregates of immune cells that form under pathological conditions. However, the predictive value of TLS in clear cell renal cell carcinoma (ccRCC) for immunotherapies remains unclear. We comprehensively assessed the implications for prognosis and immunological responses of the TLS spatial and maturation heterogeneity in 655 ccRCC patients. A higher proportion of early-TLS was found in peritumoral TLS, while intratumoral TLS mainly comprised secondary follicle-like TLS (SFL-TLS), indicating markedly better survival. Notably, presence of TLS, especially intratumoral TLS and SFL-TLS, significantly correlated with better survival and objective reflection rate for ccRCC patients receiving anti-Programmed Cell Death Protein-1 (PD-1)/Programmed Cell Death-Ligand-1 (PD-L1) immunotherapies. In peritumoral TLS cluster, primary follicle-like TLS, the proportion of tumor-associated macrophages, and Treg infiltration in the peritumoral regions increased prominently, suggesting an immunosuppressive tumor microenvironment. Interestingly, spatial transcriptome annotation and multispectral fluorescence showed that an abundance of mature plasma cells within mature TLS has the capacity to produce IgA and IgG, which demonstrate significantly higher objective response rates and a superior prognosis for ccRCC patients subjected to immunotherapy. In conclusion, this study revealed the implications of TLS spatial and maturation heterogeneity on the immunological status and clinical responses, allowing the improvement of precise immunotherapies of ccRCC.

Metachronous multifocal carcinoma: A case report.

BACKGROUND: The incidence of multiple primary carcinomas (MPC) varies greatly, ranging from 0.73% to 11.70% in foreign countries, with duo-duplex carcinoma being the most common, trio-duplex carcinoma and above being rare, and simultaneous multigenic carcinoma being even rarer, accounting for 18.4% to 25.3% of the incidence of MPC. However, there is no report regarding patients presenting with simultaneous dual-origin carcinoma of the liver and colon and heterochronous pancreatic cancer. CASE SUMMARY: We report a special case of multifocal carcinoma, in which one patient had a medical condition of primary liver and colon cancer and pancreatic cystadenocarcinoma 2 years after surgery. Through aggressive advanced fluorescent laparoscopic techniques, standardized immunotherapy, targeting, and chemotherapy, a better prognosis and a desirable survival period were achieved for the patient. CONCLUSION: There is a need to clarify the nature of MPC through advanced surgical means to ensure better diagnosis and treatment.

Size-independent boosting of near-infrared persistent luminescence in nano-phosphors via a magnesium doping strategy.

Near-infrared (NIR)-emitting persistent luminescence nanoparticles (PLNPs) are ideal optical imaging contrast reagents characterized by autofluorescence-free optical imaging for their frontier applications in long-term bioimaging. Preparation of uniform small-sized PLNPs with excellent luminescence performance is crucial for biomedical applications, but challenging. Here, we report a facile magnesium doping strategy to achieve size-independent boost of NIR persistent luminescence in typical and most concerned ZnGa2O4:Cr3+ PLNPs. This strategy relies on the doping of Mg2+ ions that with similar size of Zn2+ ions in the host lattice matrix, and concomitant to the electron traps tailoring tuned by varying the feed ratio of Mg2+. The optimum Mg2+-doped PLNPs give a long afterglow time (signal-to-noise ratio (SNR) = 31.6 at 30 d) without changing the desirable uniform sub-10 nm size of the original nanocrystals. The appropriate increase of the depth and concentration of electron trap contribute jointly to the enhancement of lifetime (488 % longer, 20.57 s) and afterglow time for 700 nm persistent luminescence. Meanwhile, these PLNPs keep the original excellent rechargeability and promote over 60 times increase of SNR in renewable in vivo imaging. This simple strategy provides a basis for new opportunities to address the critical challenge of effective optical performance boost in small-sized PLNPs.

Machine Learning-based Framework Develops a Tumor Thrombus Coagulation Signature in Multicenter Cohorts for Renal Cancer.

Background: Renal cell carcinoma (RCC) is frequently accompanied by tumor thrombus in the venous system with an extremely dismal prognosis. The current Tumor Node Metastasis (TNM) stage and Mayo clinical classification do not appropriately identify preference-sensitive treatment. Therefore, there is an urgent need to develop a better ideal model for precision medicine. Methods: In this study, we developed a coagulation tumor thrombus signature for RCC with 10 machine-learning algorithms (101 combinations) based on a novel computational framework using multiple independent cohorts. Results: The established tumor thrombus coagulation-related risk stratification (TTCRRS) signature comprises 10 prognostic coagulation-related genes (CRGs). This signature could predict survival outcomes in public and in-house protein cohorts and showed high performance compared to 129 published signatures. Additionally, the TTCRRS signature was significantly related to some immune landscapes, immunotherapy response, and chemotherapy. Furthermore, we also screened out hub genes, transcription factors, and small compounds based on the TTCRRS signature. Meanwhile, CYP51A1 can regulate the proliferation and migration properties of RCC. Conclusions: The TTCRRS signature can complement the traditional anatomic TNM staging system and Mayo clinical stratification and provide clinicians with more therapeutic options.

Laparoscopic left hemihepatectomy guided by indocyanine green fluorescence: A cranial-dorsal approach.

BACKGROUND: Advancements in laparoscopic technology and a deeper understanding of intrahepatic anatomy have led to the establishment of more precise laparoscopic hepatectomy (LH) techniques. The indocyanine green (ICG) fluorescence navigation technique has emerged as the most effective method for identifying hepatic regions, potentially overcoming the limitations of LH. While laparoscopic left hemihepatectomy (LLH) is a standardized procedure, there is a need for innovative strategies to enhance its outcomes. AIM: To investigate a standardized cranial-dorsal strategy for LLH, focusing on important anatomical markers, surgical skills, and ICG staining methods. METHODS: Thirty-seven patients who underwent ICG fluorescence-guided LLH at Qujing Second People's Hospital between January 2019 and February 2022 were retrospectively analyzed. The cranial-dorsal approach was performed which involves dissecting the left hepatic vein cephalad, isolating the Arantius ligament , exposing the middle hepatic vein, and dissecting the parenchyma from the dorsal to the foot in order to complete the anatomical LLH. The surgical methods, as well as intra- and post-surgical data, were recorded and analyzed. Our hospital's Medical Ethics Committee approved this study (Ethical review: 2022-019-01). RESULTS: Intraoperative blood loss during LLH was 335.68 ± 99.869 mL and the rates of transfusion and conversion to laparotomy were 13.5% and 0%, respectively. The overall incidence of complications throughout the follow-up (median of 18 months; range 1-36 months) was 21.6%. No mortality or severe complications (level IV) were reported. CONCLUSION: LLH has the potential to become a novel, standardized approach that can effectively, safely, and simply expose the middle hepatic vein and meet the requirements of precision surgery.

Targeting transcription factors through an IMiD independent zinc finger domain.

Immunomodulatory imide drugs (IMiDs) degrade specific C2H2 zinc finger degrons in transcription factors, making them effective against certain cancers. SALL4, a cancer driver, contains seven C2H2 zinc fingers in four clusters, including an IMiD degron in zinc finger cluster two (ZFC2). Surprisingly, IMiDs do not inhibit growth of SALL4 expressing cancer cells. To overcome this limit, we focused on a non-IMiD degron, SALL4 zinc finger cluster four (ZFC4). By combining AlphaFold and the ZFC4-DNA crystal structure, we identified a potential ZFC4 drug pocket. Utilizing an in silico docking algorithm and cell viability assays, we screened chemical libraries and discovered SH6, which selectively targets SALL4-expressing cancer cells. Mechanistic studies revealed that SH6 degrades SALL4 protein through the CUL4A/CRBN pathway, while deletion of ZFC4 abolished this activity. Moreover, SH6 led to significant 62% tumor growth inhibition of SALL4+ xenografts in vivo and demonstrated good bioavailability in pharmacokinetic studies. In summary, these studies represent a new approach for IMiD independent drug discovery targeting C2H2 transcription factors in cancer.

Undescribed matrine-type alkaloids from Sophora alopecuroides with anti-inflammatory activity.

A phytochemical investigation on the alkaloid fractions of Sophora alopecuroides L. led to the production of 11 undescribed matrine-type alkaloids, sophaloseedlines I-S (1-11), 12 known analogs (12-23), and an unexpected artificial matrine-derived Al(III) complex (24). The corresponding structures were elucidated by the interpretation of spectroscopic analyses, quantum chemical calculation, and six instances (1-4, 18, and 24), verified by X-ray crystallography. The biological activities screening demonstrated that none of the isolates exhibited cytotoxicity against four human cancer cell lines (HepG2, A549, THP-1, and MCF-7) and respiratory syncytial virus (RSV) at 50 µM, while moderate anti-inflammatory activity with IC50 value from 15.6 to 47.8 µM was observed. The key structure-activity relationships of those matrine-type alkaloids for anti-inflammatory effects have been summarized. In addition, the most potent 7-epi-sophoramine (19) and aluminum sophaloseedline T (24) could effectively inhibit the release of pro-inflammatory factors (TNF-α, IL-6, and IL-1ß), as well as the expression of iNOS and COX-2 proteins.

Tumor microenvironment-based signatures distinguish intratumoral heterogeneity, prognosis, and immunogenomic features of clear cell renal cell carcinoma.

Background: The tumor microenvironment (TME) performs a crucial function in the tumorigenesis and response to immunotherapies of clear cell renal cell carcinoma (ccRCC). However, a lack of recognized pre-clinical TME-based risk models poses a great challenge to investigating the risk factors correlated with prognosis and treatment responses for patients with ccRCC. Methods: Stromal and immune contexture were assessed to calculate the TMErisk score of a large sample of patients with ccRCC from public and real-world cohorts using machine-learning algorithms. Next, analyses for prognostic efficacy, correlations with clinicopathological features, functional enrichment, immune cell distributions, DNA variations, immune response, and heterogeneity were performed and validated. Results: Clinical hub genes, including INAFM2, SRPX, DPYSL3, VSIG4, APLNR, FHL5, A2M, SLFN11, ADAMTS4, IFITM1, NOD2, CCR4, HLA-DQB2, and PLAUR, were identified and incorporated to develop the TMErisk signature. Patients in the TMEhigh risk group (category) exhibited a considerably grim prognosis, and the TMErisk model was shown to independently function as a risk indicator for the overall survival (OS) of ccRCC patients. Expression levels of immune checkpoint genes were substantially increased in TMEhigh risk group, while those of the human leukocyte antigen (HLA) family genes were prominently decreased. In addition, tumors in the TMEhigh group showed significantly high infiltration levels of tumor-infiltrated lymphocytes, including M2 macrophages, CD8+ T cells, B cells, and CD4+ T cells. In heterogeneity analysis, more frequent somatic mutations, including pro-tumorigenic BAP1 and PBRM1, were observed in the TMEhigh group. Importantly, 19.3% of patients receiving immunotherapies in the TMEhigh group achieved complete or partial response compared with those with immune tolerance in the TMElow group, suggesting that TMErisk prominently differentiates prognosis and responses to immunotherapy for patients with ccRCC. Conclusions: We first established the TMErisk score of ccRCC using machine-learning algorithms based on a large-scale population. The TMErisk score can be utilized as an innovative independent prognosis predictive marker with high sensitivity and accuracy. Our discovery also predicted the efficacy of immunotherapy in ccRCC patients, indicating the intimate link between tumor immune microenvironment and intratumoral heterogeneity.

The unique genomic landscape and prognostic mutational signature of Chinese clear cell renal cell carcinoma.

Background: The genomic background affects the occurrence and metastasis of cancers, including clear cell renal cell carcinoma (ccRCC). However, reports focusing on the prognostic mutational signature of Chinese ccRCC are lacking. Methods: Overall, 929 patients, including a training cohort with Chinese patients (n = 201), a testing cohort with Caucasian patients (n = 274), and a validation cohort (n = 454) were analyzed for the genomic landscape of ccRCC. Then, machine-learning algorithms were used to identify and evaluate the genomic mutational signature (GMS) in ccRCC. Analyses for prognosis, immune microenvironment, association with independent clinicopathological features, and predictive responses for immune checkpoint therapies (ICTs) were performed. Results: The DNA variation data of 929 patients with ccRCC suggested markedly differential genomic mutational frequency of the most frequent genes, such as VHL, PBRM1, BAP1, SETD2, and KDM5C between the Chinese and Caucasian populations. PBRM1 showed significant co-occurrence with VHL and SETD2. We then successfully identified a seven-gene mutational signature (GMSMut) that included mutations in FBN1, SHPRH, CELSR1, COL6A6, DST, ABCA13, and BAP1. The GMSMut significantly predicted progressive progression (P < 0.0001, HR = 2.81) and poor prognosis (P < 0.0001, HR = 3.89) in the Chinese training cohort. Moreover, ccRCC patients with the GMSMut had poor survival rates in the testing cohort (P = 0.020) and poor outcomes were predicted for those treated with ICTs in the validation cohort (P = 0.036). Interestingly, a favorable clinical response to ICTs, elevated expression of immune checkpoints, and increased abundance of tumor-infiltrated lymphocytes, specifically CD8+ T cells, Tregs, and macrophages, were observed in the GMSMut cluster. Conclusions: This study described the pro-tumorigenic GMSMut cluster that improved the prognostic accuracy in Chinese patients with ccRCC. Our discovery of the novel independent prognostic signature highlights the relationship between tumor phenotype and genomic mutational characteristics of ccRCC.