Spatiotemporal constrained RNA-protein heterogeneous network for protein complex identification.

The identification of protein complexes from protein interaction networks is crucial in the understanding of protein function, cellular processes and disease mechanisms. Existing methods commonly rely on the assumption that protein interaction networks are highly reliable, yet in reality, there is considerable noise in the data. In addition, these methods fail to account for the regulatory roles of biomolecules during the formation of protein complexes, which is crucial for understanding the generation of protein interactions. To this end, we propose a SpatioTemporal constrained RNA-protein heterogeneous network for Protein Complex Identification (STRPCI). STRPCI first constructs a multiplex heterogeneous protein information network to capture deep semantic information by extracting spatiotemporal interaction patterns. Then, it utilizes a dual-view aggregator to aggregate heterogeneous neighbor information from different layers. Finally, through contrastive learning, STRPCI collaboratively optimizes the protein embedding representations under different spatiotemporal interaction patterns. Based on the protein embedding similarity, STRPCI reweights the protein interaction network and identifies protein complexes with core-attachment strategy. By considering the spatiotemporal constraints and biomolecular regulatory factors of protein interactions, STRPCI measures the tightness of interactions, thus mitigating the impact of noisy data on complex identification. Evaluation results on four real PPI networks demonstrate the effectiveness and strong biological significance of STRPCI. The source code implementation of STRPCI is available from https://github.com/LI-jasm/STRPCI.

Document-level biomedical relation extraction via hierarchical tree graph and relation segmentation module.

MOTIVATION: Biomedical relation extraction at the document level (Bio-DocRE) involves extracting relation instances from biomedical texts that span multiple sentences, often containing various entity concepts such as genes, diseases, chemicals, variants, etc Currently, this task is usually implemented based on graphs or transformers. However, most work directly models entity features to relation prediction, ignoring the effectiveness of entity pair information as an intermediate state for relation prediction. In this article, we decouple this task into a three-stage process to capture sufficient information for improving relation prediction. RESULTS: We propose an innovative framework HTGRS for Bio-DocRE, which constructs a Hierarchical Tree Graph (HTG) to integrate key information sources in the document, achieving relation reasoning based on entity. In addition, inspired by the idea of semantic segmentation, we conceptualize the task as a table-filling problem and develop a Relation Segmentation (RS) module to enhance relation reasoning based on the entity pair. Extensive experiments on three datasets show that the proposed framework outperforms the state-of-the-art methods and achieves superior performance. AVAILABILITY AND IMPLEMENTATION: Our source code is available at https://github.com/passengeryjy/HTGRS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Serum zinc concentration and dietary zinc intake in relation to cognitive function: an analysis of the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort.

PURPOSE: There are several pathways by which zinc may be a modifiable factor to slow age-related cognitive decline. We investigated the associations between serum and dietary zinc and cognitive impairment in a longitudinal cohort. METHODS: We used data from the REasons for Geographic and Racial Differences in Stroke (REGARDS) Cohort (n = 30,239) and the REGARDS Trace Element Study (n = 2666). Baseline serum zinc concentrations (2003-2007) were measured using inductively coupled plasma mass spectrometry. Baseline dietary zinc intake was measured via the Block food frequency questionnaire. Serum zinc concentrations and dietary zinc intake were categorized into quartiles. The outcome of interest was impairment on the Six-Item Screener (SIS), a measure of global cognitive functioning administered annually. The Enhanced Cognitive Battery (ECB), a more comprehensive series of tests assessing memory and fluency, was administered every two years and considered a secondary outcome. Associations between zinc and incident impairment were assessed using multivariable logistic regression. RESULTS: Among 2065 participants with serum zinc data, 184 individuals developed impairment over 10 years of follow-up. In adjusted models, there was no significant association between serum zinc and impairment as assessed by the SIS or the ECB. Among 18,103 participants who had dietary data, 1424 experienced incident impairment on the SIS. Dietary zinc intake was not significantly associated with impairment as assessed by the SIS or the ECB in adjusted models. CONCLUSION: Findings from this U.S. cohort did not support the hypothesis that serum zinc concentration or dietary zinc intake is associated with the risk of cognitive impairment.

The association between lead exposure and dental caries ─ a systematic review.

INTRODUCTION: Dental caries has declined over the years, but it remains a major public health issue. This review aimed to investigate the association between lead and caries experience in either deciduous or permanent teeth. METHODS: A comprehensive search of PubMed, EMBASE, and Google Scholar was conducted to identify relevant studies published up until December 2022. Included were human observational studies that investigated the association between lead exposure and dental caries. The review adhered to the PRISMA guideline. RESULTS: Sixteen studies were included in this review, with nine focusing on deciduous teeth, thirteen on permanent teeth, and six examining both types of teeth. Most of the studies (5 of 6) found a positive association between blood lead (PbB) levels and caries in deciduous teeth, while the findings for permanent teeth were less conclusive, with only 3 of 10 studies finding an association. One of the two studies assessing salivary lead (PbSa) levels found a weak association for permanent teeth. All four studies that examined lead (Pb) concentration in teeth found a positive association for both deciduous and permanent teeth. CONCLUSION: Many published studies indicated a positive association between Pb exposure and caries experience in deciduous dentition. Children with elevated PbB level should be considered as having higher caries experience. Due to lack of consensus on measurement and examination technique, there remains insufficient evidence to make any definitive conclusions especially in permanent teeth, and so more studies are warranted.

Pregnancy Outcomes in Women Who Developed Elevated Blood Pressure and Stage I Hypertension after 20 Weeks Gestation.

OBJECTIVE: The American College of Obstetrics threshold for hypertension (≥140/90 mm Hg) differs from those of the American College of Cardiology (ACC) and the American Heart Association (AHA). It is unknown if ACC/AHA hypertension levels are associated with adverse pregnancy outcomes (APOs) after 20 weeks gestation. The purpose of this study is to analyze APOs in women with blood pressure (BP) in the elevated or stage 1 range after 20 weeks gestation. STUDY DESIGN: This was a secondary analysis of the nuMoM2b prospective cohort study of 10,038 nulliparous, singleton pregnancies between 2010 and 2014. BP was measured at three visits during the pregnancy using a standard protocol. Women without medical comorbidities, with normal BP by ACC/AHA guidelines (systolic BP [SBP] < 120 and diastolic BP [DBP] < 80 mm Hg) up to 22 weeks, were included. Exposure was BP between 22 and 29 weeks gestation: normal (SBP < 120 and DBP < 80 mm Hg), elevated (SBP: 120-129 and DBP < 80 mm Hg), and stage 1 (SBP: 130-139 or DBP: 80-89 mm Hg). The primary outcome was hypertensive disorder of pregnancy (HDP) at delivery. Secondary outcomes included fetal growth restriction (FGR), placental abruption, preterm delivery, and cesarean delivery. Multivariable-adjusted odds ratio (aORs) and 95% confidence intervals (CIs) were estimated using logistic regression models. RESULTS: Of 4,460 patients that met inclusion criteria, 3,832 (85.9%) had BP in the normal range, 408 (9.1%) in elevated, and 220 (4.9%) in stage 1 range between 22 and 29 weeks. The likelihood of HDP was significantly higher in women with elevated BP (aOR 1.71, 95%CI: 1.18,2.48), and stage 1 BP (aOR: 2.79, 95%CI: 1.84,4.23) compared to normal BP (p < 0.001). Stage 1 BP had twice odds of FGR (aOR: 2.33, 95%CI: 1.22,4.47) and elevated BP had three times odds of placental abruption (aOR: 3.03; 95%CI: 1.24,7.39). CONCLUSION: Elevated or stage 1 BP >20 weeks of pregnancy are associated with HDP, FGR, and placental abruption. KEY POINTS: · Elevated and stage 1 BP increases risk for HDP.. · Elevated BP increases risk for placental abruption.. · Stage 1 BP increases risk for FGR..

[Risk factors for bronchopulmonary dysplasia in twin preterm infants: a multicenter study]. / åŒèƒŽæ—©äº§å„¿æ”¯æ°”ç®¡è‚ºå‘è‚²ä¸è‰¯å±é™©å› ç´ åˆ†æžï¼šä¸€é¡¹å¤šä¸­å¿ƒç ”ç©¶.

OBJECTIVES: To investigate the risk factors for bronchopulmonary dysplasia (BPD) in twin preterm infants with a gestational age of <34 weeks, and to provide a basis for early identification of BPD in twin preterm infants in clinical practice. METHODS: A retrospective analysis was performed for the twin preterm infants with a gestational age of <34 weeks who were admitted to 22 hospitals nationwide from January 2018 to December 2020. According to their conditions, they were divided into group A (both twins had BPD), group B (only one twin had BPD), and group C (neither twin had BPD). The risk factors for BPD in twin preterm infants were analyzed. Further analysis was conducted on group B to investigate the postnatal risk factors for BPD within twins. RESULTS: A total of 904 pairs of twins with a gestational age of <34 weeks were included in this study. The multivariate logistic regression analysis showed that compared with group C, birth weight discordance of >25% between the twins was an independent risk factor for BPD in one of the twins (OR=3.370, 95%CI: 1.500-7.568, P<0.05), and high gestational age at birth was a protective factor against BPD (P<0.05). The conditional logistic regression analysis of group B showed that small-for-gestational-age (SGA) birth was an independent risk factor for BPD in individual twins (OR=5.017, 95%CI: 1.040-24.190, P<0.05). CONCLUSIONS: The development of BPD in twin preterm infants is associated with gestational age, birth weight discordance between the twins, and SGA birth.

Smoking Modifies the Association Between Radon Exposure and Incident Ischemic Stroke: The REGARDS Study.

BACKGROUND: Exposure to radon has been linked to lung cancer and other lung diseases. Although biologically plausible, research of residential radon exposure in relation to stroke risk is scarce. METHODS: Study participants were from the REGARDS (Reasons for Geographic and Racial Differences in Stroke) cohort (n=30 239), which consisted of male and female non-Hispanic Black and White adults aged 45 and older. After excluding participants with baseline stroke and transient ischemic attack, and missing information on exposure and outcome of interest, the final sample size was 26 950. The primary outcome was time to the first ischemic stroke through September 30, 2020. County-level radon measures from Lawrence Berkeley National Laboratory were linked to each participant based on their geocoded residential history. We used Cox proportional hazards regression models with a time-dependent exposure to estimate hazard ratios and 95% CIs for the association. RESULTS: After controlling for potential confounding factors including demographic, lifestyle, clinical variables, and PM2.5, radon exposure was significantly associated with incident ischemic stroke among never-smokers (hazard ratio, 1.39 [95% CI, 1.01-1.90]) but not ever-smokers. The results were generally consistent in the sensitivity analysis when using radon measures from state/Environmental Protection Agency residential radon survey. CONCLUSIONS: Findings from this study suggest that the association between residential radon exposure and incidence of ischemic stroke varies by smoking status and may be prominent in never-smokers. Further studies incorporating indoor-radon measures are needed to confirm these findings.

Photo- or Electrochemical Cyclization of Dienes with Diselenides to Access Seleno-Benzo[b]azepines.

A cascade selenylation/cyclization of dienes with diselenides has been realized under visible-light irradiation or electrolysis conditions. Employing O2 or electricity as a "green" oxidant, this protocol provides a green and efficient method for an array of biologically important seleno-benzo[b]azepine derivatives in moderate to good yields. The direct sunlight irradiation and gram-scale reaction render the approach practical and attractive.

DGCL: Distance-wise and Graph Contrastive Learning for medication recommendation.

Medicine recommendation aims to provide a combination of medicine based on the patient's electronic health record (EHR), which is an essential task in healthcare. Existing methods either base recommendations on EHRs or provide models with knowledge of drug-drug interactions (DDIs) to achieve DDI reduction. However, the former models the patient's health history but ignores undesirable DDIs, while the latter lacks mining of patient health records and gets low recommendation accuracy. Therefore, this study contributes to research on personalized medication recommendations that consider drug interaction effects and models the patient's past medical history. In this paper, the Distance-wise and Graph Contrastive Learning (DGCL) framework is proposed. Specifically, we develop a two-stage neural network module for clinical record learning. We propose the distance detection loss to model the difference between the output distribution of current cases and historical records. In the DDI recognition and control task, DGCL proposes a graph contrastive learning method to jointly train the DDI knowledge graph and the electronic record graph, thereby effectively controlling the level of DDI for recommended medications. By comparing the performance on the MIMIC-III dataset with several baselines, DGCL outperforms other models in terms of efficacy and safety.

ADPG: Biomedical entity recognition based on Automatic Dependency Parsing Graph.

Named entity recognition is a key task in text mining. In the biomedical field, entity recognition focuses on extracting key information from large-scale biomedical texts for the downstream information extraction task. Biomedical literature contains a large amount of long-dependent text, and previous studies use external syntactic parsing tools to capture word dependencies in sentences to achieve nested biomedical entity recognition. However, the addition of external parsing tools often introduces unnecessary noise to the current auxiliary task and cannot improve the performance of entity recognition in an end-to-end way. Therefore, we propose a novel automatic dependency parsing approach, namely the ADPG model, to fuse syntactic structure information in an end-to-end way to recognize biomedical entities. Specifically, the method is based on a multilayer Tree-Transformer structure to automatically extract the semantic representation and syntactic structure in long-dependent sentences, and then combines a multilayer graph attention neural network (GAT) to extract the dependency paths between words in the syntactic structure to improve the performance of biomedical entity recognition. We evaluated our ADPG model on three biomedical domain and one news domain datasets, and the experimental results demonstrate that our model achieves state-of-the-art results on these four datasets with certain generalization performance. Our model is released on GitHub: https://github.com/Yumeng-Y/ADPG.

MKCL: Medical Knowledge with Contrastive Learning model for radiology report generation.

Automatic radiology report generation has the potential to alert inexperienced radiologists to misdiagnoses or missed diagnoses and improve healthcare delivery efficiency by reducing the documentation workload of radiologists. Motivated by the continuous development of automatic image captioning, more and more deep learning methods have been proposed for automatic radiology report generation. However, the visual and textual data bias problem still face many challenges in the medical domain. Additionally, do not integrate medical knowledge, ignoring the mutual influences between medical findings, and abundant unlabeled medical images influence the accuracy of generating report. In this paper, we propose a Medical Knowledge with Contrastive Learning model (MKCL) to enhance radiology report generation. The proposed model MKCL uses IU Medical Knowledge Graph (IU-MKG) to mine the relationship among medical findings and improve the accuracy of identifying positive diseases findings from radiologic medical images. In particular, we design Knowledge Enhanced Attention (KEA), which integrates the IU-MKG and the extracted chest radiological visual features to alleviate textual data bias. Meanwhile, this paper leverages supervised contrastive learning to relieve radiographic medical images which have not been labeled, and identify abnormalities from images. Experimental results on the public dataset IU X-ray show that our proposed model MKCL outperforms other state-of-the-art report generation methods. Ablation studies also demonstrate that IU medical knowledge graph module and supervised contrastive learning module enhance the ability of the model to detect the abnormal parts and accurately describe the abnormal findings. The source code is available at: https://github.com/Eleanorhxd/MKCL.

CCL17 Blockade by CCL17mAb/GSK-J4 Ameliorates Hyperalgesia in a Rat Model of Postoperative Pain.

C-C motif chemokine ligand 17 (CCL17), an important chemokine, plays a vital role in regulating immune balance in the central nervous system. In this study, we explored the potential roles of CCL17 in a rat postoperative pain model and that of blocking CCL17 in the prevention of postoperative pain in rats. A right plantar incision in rat was used as a model of postoperative pain. A behavioral change was measured preoperatively and postoperatively using mechanical withdrawal thresholds and thermal withdrawal latency. CCL17 and its upstream Jmjd-3 mRNA levels in the spinal cord were detected using real-time PCR, CCL17 levels in the serum were measured using enzyme-linked immunosorbent assay (ELISA), and the expression of interferon regulatory factor 4 (IRF4), which interacts with Jmjd-3, was detected by immunohistochemistry staining. After that, rats were intraperitoneally injected with either anti-CCL17 monoclonal antibody (mAb) or GSK-J4 (the Jmjd3 inhibitor) to evaluate the protective effects of blocking CCL17 on postoperative pain. We found that CCL17 and Jmjd-3 were significantly increased in the spinal cords of the postoperative pain rat, consistent with changes in hyperalgesia. In addition, our results showed that the mechanical and thermal allodynia was significantly ameliorated using anti-CCL17mAb or GSK-J4. Moreover, we found that anti-CCL17mAb or GSK-J4 treatment decreased c-fos expression in response to peripheral stimulation. Finally, our preliminary exploration found that anti-CCL17mAb or GSK-J4 had a protective effect on tissue damage. These findings indicated that high expression of CCL17 played a critical role in postoperative pain induced by plantar incision and that CCL17 blockade may serve as an effective approach to managing postoperative pain.

Analysis of risk factors for parenteral nutrition-associated cholestasis in preterm infants: a multicenter observational study.

BACKGROUND: It is proposed that the development of parenteral nutrition-associated cholestasis (PNAC) was significantly associated with preterm birth, low birth weight, infection, etc.; however, the etiology and pathogenesis of PNAC are not fully understood. Most of the studies examining PNAC-associated risk factors were single-center studies with relatively small sample sizes. OBJECTIVE: To analyze the risk factors associated with PNAC in preterm infants in China. METHODS: This is a retrospective multicenter observational study. Clinical data on the effect of multiple oil-fat emulsions (soybean oil-medium chain triglycerides-olive oil-fish oil, SMOF) in preterm infants were collected from a prospective multicenter randomized controlled study. A secondary analysis was performed in which preterm infants were divided into the PNAC group and the non-PNAC group based on the PNAC status. RESULTS: A total of 465 cases very preterm infants or very low birth weight infants were included in the study in which 81 cases were assigned to the PNAC group and 384 cases were assigned to the non-PNAC group. The PNAC group had a lower mean gestational age, lower mean birth weight, longer duration of invasive and non-invasive mechanical ventilation, a longer duration oxygen support, and longer hospital stay (P < 0.001 for all). The PNAC group had higher respiratory distress syndrome, hemodynamically significant patent ductus arteriosus, necrotizing enterocolitis (NEC) with stage II or higher, surgically treated NEC, late-onset sepsis, metabolic bone disease, and extrauterine growth retardation (EUGR) compared to the non-PNAC group (P < 0.05 for all). In contrast with the non-PNAC group, the PNAC group received a higher maximum dose of amino acids and fat emulsion, more medium/long-chain fatty emulsion, less SMOF, had a longer duration of parenteral nutrition, lower rates of breastfeeding, higher incidence of feeding intolerance (FI), more accumulated days to achieve total enteral nutrition, less accumulated days of total calories up to standard 110 kcal/kg/day and slower velocity of weight growth (P < 0.05 for all). Logistic regression analysis indicated that the maximum dose of amino acids (OR, 5.352; 95% CI, 2.355 to 12.161), EUGR (OR, 2.396; 95% CI, 1.255 to 4.572), FI (OR, 2.581; 95% CI, 1.395 to 4.775), surgically treated NEC (OR, 11.300; 95% CI, 2.127 ~ 60.035), and longer total hospital stay (OR, 1.030; 95% CI, 1.014 to 1.046) were independent risk factors for the development of PNAC. SMOF (OR, 0.358; 95% CI, 0.193 to 0.663) and breastfeeding (OR, 0.297; 95% CI, 0.157 to 0.559) were protective factors for PNAC. CONCLUSIONS: PNAC can be reduced by optimizing the management of enteral and parenteral nutrition and reducing gastrointestinal comorbidities in preterm infants.

Be the mother, not the daughter: Immigrant Chinese women, postpartum care knowledge, and mothering autonomy.

Scholars have documented the transformation of modern motherhood, as mothering practices have been a target of medical knowledge that comes to define correct modes of conduct for women caring for their pregnant bodies, undergoing childbirth and childrearing. Such accounts usually set scientific knowledge and medical authority in opposition to women's autonomy. Drawing on the interviews with immigrant Chinese mothers in Canada, we offer a different account of knowledge and agency in new motherhood. These women's often-intense experiences of intergenerational care-giving associated with the practice of zuo yuezi reveal a more fluid relationship between medical authority and mothering agency. We find that the central tension during the postpartum experience lies in intergenerational and family relationships. In this context, new mothers draw on alternative sources of knowledge-and medical professionals are one such key source-to demonstrate within the family their competence to make care decisions for themselves and their babies. These women's use of medical knowledge to counter a familial and intergenerational authority complicates dominant accounts about medicalisation, demonstrating that women's relationship to medical knowledge and authority maybe be far more fluid and complex than a standard account of medicalisation and loss of women's agency would predict.

Obesogenic effect of Bisphenol P on mice via altering the metabolic pathways.

Bisphenol P (BPP), structurally similar to bisphenol A, is commonly identified in the samples of environment, food, and humans. Unfortunately, very little information is currently available on adverse effects of BPP. The obesogenic effects and underlying mechanisms of BPP on mice were investigated in this study. Compared with the control, high-resolution microcomputed tomography (micro-CT) scans displayed that the visceral fat volume of mice was significantly increased at a dose of 5 mg/kg/day after BPP exposure for 14 days, whereas the subcutaneous fat volume remained unchanged. Nontargeted metabolomic analysis revealed that BPP significantly perturbed the metabolic pathways of mouse livers, and acetyl-CoA was identified as the potential key metabolite responsible for the visceral fat induced by BPP. These findings recommend that a great deal of attention should be paid to the obesogenic properties of BPP as a result of its widely utilized and persistence in the environment.

Neonatal Hypoglycemia following Late Preterm Antenatal Corticosteroid Administration in Individuals with Diabetes in Pregnancy.

OBJECTIVE: Antenatal corticosteroid (ACS) administration is standard practice for pregnant individuals delivering in the late preterm period, though no guidelines are in place for those with diabetes. This study aims to characterize the prevalence of neonatal hypoglycemia after ACS administration in pregnant individuals with diabetes delivering in the late preterm period. STUDY DESIGN: This is a retrospective, single-center, case-control study of individuals with diabetes who delivered between 340/7 and 366/7 weeks' gestation at a large academic medical center from 2016 to 2021. A total of 169 individuals were included in the analysis; 87 received corticosteroids and 82 did not. The proportion of neonates with hypoglycemia, neonatal intensive care unit (NICU) admission, respiratory distress syndrome, and hyperbilirubinemia were compared between parents who received ACSs versus those who did not. RESULTS: The prevalence of neonatal hypoglycemia (40.2 vs. 23.2%, p = 0.027), requiring treatment (40.3 vs. 22.4%, p = 0.041), and hyperbilirubinemia (35.6 vs 18.5%, p = 0.018) was greater for neonates born to individuals with diabetes who received late preterm ACSs compared with those who did not. There was no difference in NICU admission and respiratory distress between the groups. These results remained unchanged after controlling for confounders including gestational age at delivery and birth weight. CONCLUSION: This study demonstrates that late preterm corticosteroid administration to pregnant individuals with diabetes increases the risk for neonatal hypoglycemia without changing the rates of respiratory morbidity. KEY POINTS: · Late preterm ACS in diabetic patients resulted in higher rates of neonatal hypoglycemia.. · There are no differences in rates of respiratory distress syndrome and transient tachypnea of the newborn between the ACS group and control group.. · There was no noted difference in rate of NICU admission and length of stay between the two groups..

DSSS Signal Detection Based on CNN.

With the wide application of direct sequence spread spectrum (DSSS) signals, the comprehensive performance of DSSS communication systems has been continuously improved, making the electronic reconnaissance link in communication countermeasures more difficult. Electronic reconnaissance technology, as the fundamental means of modern electronic warfare, mainly includes signal detection, recognition, and parameter estimation. At present, research on DSSS detection algorithms is mostly based on the correlation characteristics of DSSS signals, and autocorrelation algorithm is the most mature and widely used method in practical engineering. With the continuous development of deep learning, deep-learning-based methods have gradually been introduced to replace traditional algorithms in the field of signal processing. This paper proposes a spread spectrum signal detection method based on convolutional neural network (CNN). Through experimental analysis, the detection performance of the CNN model proposed in this paper on DSSS signals in various situations has been compared and analyzed with traditional autocorrelation detection methods for different signal-to-noise ratios. The experiments verified the estimation performance of the model in this paper under different signal-to-noise ratios, different spreading code lengths, different spreading code types, and different modulation methods and compared it with the autocorrelation detection algorithm. It was found that the detection performance of the model in this paper was higher than that of the autocorrelation detection method, and the overall performance was improved by 4 dB.

Period Estimation of Spread Spectrum Codes Based on ResNet.

In order to more effectively monitor and interfere with enemy signals, it is particularly important to accurately and efficiently identify the intercepted signals and estimate their parameters in the increasingly complex electromagnetic environment. Therefore, in non-cooperative situations, it is of great practical significance to study how to accurately detect direct sequence spread spectrum (DSSS) signals in real time and estimate their parameters. The traditional time-delay correlation algorithm encounters the challenges such as peak energy leakage and false peak interference. As an alternative, this paper introduces a Pseudo-Noise (PN) code period estimation method utilizing a one-dimensional (1D) convolutional neural network based on the residual network (CNN-ResNet). This method transforms the problem of spread spectrum code period estimation into a multi-classification problem of spread spectrum code length estimation. Firstly, the In-phase/Quadrature(I/Q) two-way of the received DSSS signals is directly input into the CNN-ResNet model, which will automatically learn the characteristics of the DSSS signal with different PN code lengths and then estimate the PN code length. Simulation experiments are conducted using a data set with DSSS signals ranging from -20 to 10 dB in terms of signal-to-noise ratios (SNRs). Upon training and verifying the model using BPSK modulation, it is then put to the test with QPSK-modulated signals, and the estimation performance was analyzed through metrics such as loss function, accuracy rate, recall rate, and confusion matrix. The results demonstrate that the 1D CNN-ResNet proposed in this paper is capable of effectively estimating the PN code period of the non-cooperative DSSS signal, exhibiting robust generalization abilities.

A Comparative Study of Skin Changes in Different Species of Mice in Chronic Photoaging Models.

This study aimed to design a novel mouse model of chronic photoaging. We used three different species of mice (C57BL/6J, ICR, and KM) to create a chronic photoaging model of the skin. The irradiation time was gradually increased for 40 consecutive days. The skins of the mice were removed on day 41 and subjected to staining to observe them for morphological changes. Immunohistochemistry was used to detect tumor necrosis factor-α (TNF-α) and p53 expression; superoxide dismutase (SOD) and malondialdehyde (MDA) were measured as well. Compared with C57BL/J mice, which showed hyperpigmentation, the irradiated skin of ICR and KM mice showed more obvious skin thickening and photoaging changes of the collagen and elastic fibers. KM mice had higher levels of inflammation, oxidative stress, and senescent cells. Compared with the 5-month-old KM mice, the photoaging changes of the 9-month-old KM mice were more pronounced, the SOD values were lower, and the MDA values were higher. In summary, KM mice have higher levels of abnormal elastic fibers, inflammation, cellular senescence, and oxidative stress than ICR mice, and are more suitable for studies related to chronic skin photoaging. C57BL/6J mice were found to be suitable for studies related to skin pigmentation due to photoaging.

[Comparison of the impact of different fat emulsions on clinical outcomes in preterm infants with varying duration of parenteral nutrition: a randomized controlled multicenter study]. / ä¸¤ç§è„‚è‚ªä¹³å‰‚ä¸åŒè‚ å¤–è¥å »æ—¶é—´å¯¹æ—©äº§å„¿ä¸´åºŠç»“å±€å½±å“çš„æ¯”è¾ƒï¼šä¸€é¡¹éšæœºå¯¹ç §å¤šä¸­å¿ƒç ”ç©¶.

OBJECTIVES: To compare the impact of two types of fat emulsion on clinical outcomes in preterm infants with varying duration of parenteral nutrition (PN). METHODS: Preterm infants meeting the inclusion criteria were randomly assigned to two groups: medium/long-chain triglyceride fat emulsion (referred to as MCT/LCT) group or multi-oil fat emulsion (containing soybean oil, medium-chain triglycerides, olive oil, and fish oil; referred to as SMOF) group. The infants were stratified into groups based on the duration of PN (15-21 days, 22-28 days, and ≥29 days). Clinical characteristics, nutritional status, biochemical indicators, and clinical outcomes were compared between the two groups. RESULTS: Compared with the MCT/LCT group, the SMOF group had lower peak levels of triglyceride during the hospital stay in preterm infants with PN of 15-21 days, 22-28 days, and ≥29 days, respectively (P<0.05). Logistic regression trend analysis showed that with a longer duration of PN, the risk of parenteral nutrition-associated cholestasis (PNAC) and bronchopulmonary dysplasia (BPD) significantly increased in the MCT/LCT group (P<0.05), while the risk of brain injury did not significantly change (P>0.05). In the SMOF group, the risks of PNAC and BPD did not significantly change with a longer duration of PN (P>0.05), but the risk of brain injury significantly decreased (P=0.006). CONCLUSIONS: Compared to MCT/LCT, SMOF have better lipid tolerance. With a longer duration of PN, SMOF does not increase the risks of PNAC and BPD and had a protective effect against brain injury. This suggests that in preterm infants requiring long-term PN, the use of SMOF is superior to MCT/LCT.