Ethanol changes Nestin-promoter induced neural stem cells to disturb newborn dendritic spine remodeling in the hippocampus of mice

Adolescent binge drinking leads to long-lasting disorders of the adult central nervous system,particularly aberrant hippocampal neurogenesis.In this study,we applied in vivo fluorescent tracing using NestinCreERT2::Rosa26-tdTomato mice and analyzed the endogenous neurogenesis lineage progression of neural stem cells(NSCs)and dendritic spine formation of newborn neurons in the subgranular zone of the dentate gyrus.We found abnormal orientation of tamoxifen-induced tdTomato+(tdTom^(+))NSCs in adult mice 2 months after treatment with EtOH(5.0 g/kg,i.p.)for 7 consecutive days.EtOH markedly inhibited tdTom^(+)NSCs activation and hippocampal neurogenesis in mouse dentate gyrus from adolescence to adulthood.EtOH(100 mM)also significantly inhibited the proliferation to 39.2%and differentiation of primary NSCs in vitro.Adult mice exposed to EtOH also exhibited marked inhibitions in dendritic spine growth and newborn neuron maturation in the dentate gyrus,which was partially reversed by voluntary running or inhibition of the mammalian target of rapamycinenhancer of zeste homolog 2 pathway.In vivo tracing revealed that EtOH induced abnormal orientation of tdTom+NSCs and spatial misposition defects of newborn neurons,thus causing the disturbance of hippocampal neurogenesis and dendritic spine remodeling in mice.

Improving Federated Learning through Abnormal Client Detection and Incentive

Data sharing and privacy protection are made possible by federated learning,which allows for continuous model parameter sharing between several clients and a central server.Multiple reliable and high-quality clients must participate in practical applications for the federated learning global model to be accurate,but because the clients are independent,the central server cannot fully control their behavior.The central server has no way of knowing the correctness of the model parameters provided by each client in this round,so clients may purposefully or unwittingly submit anomalous data,leading to abnormal behavior,such as becoming malicious attackers or defective clients.To reduce their negative consequences,it is crucial to quickly detect these abnormalities and incentivize them.In this paper,we propose a Federated Learning framework for Detecting and Incentivizing Abnormal Clients(FL-DIAC)to accomplish efficient and security federated learning.We build a detector that introduces an auto-encoder for anomaly detection and use it to perform anomaly identification and prevent the involvement of abnormal clients,in particular for the anomaly client detection problem.Among them,before the model parameters are input to the detector,we propose a Fourier transform-based anomaly data detectionmethod for dimensionality reduction in order to reduce the computational complexity.Additionally,we create a credit scorebased incentive structure to encourage clients to participate in training in order tomake clients actively participate.Three training models(CNN,MLP,and ResNet-18)and three datasets(MNIST,Fashion MNIST,and CIFAR-10)have been used in experiments.According to theoretical analysis and experimental findings,the FL-DIAC is superior to other federated learning schemes of the same type in terms of effectiveness.

Predictors of Abnormal Vaginal Discharge among Women of Reproductive Age in Southeast Nigeria

Background: An abnormal vaginal discharge is a common complaint among women of reproductive age, and it can indicate serious conditions like pelvic inflammatory disease and cervical cancer. This study aimed to assess the predictors of abnormal vaginal discharge in women of reproductive age group in Imo State, Southeast Nigeria. Methods: A cross-sectional study was conducted among 368 women of reproductive age group attending the clinic at Federal University Teaching Hospital Owerri, in Imo State, Nigeria. Respondents were recruited using a systematic sampling technique. Data were collected using a pre-tested interviewer-administered questionnaire. Multivariable analysis was performed to determine predictors of abnormal vaginal discharge. Statistical significance was set at p Results: The mean age of the respondents was 30 ± 4.5 years. Predictors of abnormal vaginal discharge were: age 36 - 45 years (OR: 4.5;95% C.I: 1.023 - 8.967, p = 0.041), being a student (OR: 2.4: 95% C.I: 1.496 - 7.336, p = 0.003), use of oral contraceptives (OR: 3.4;95% C.I: 1.068 - 6.932, p = 0.010), use of water cistern (OR: 4.7;C.I: 1.654 - 5.210, p = 0.028) anal hygiene practices (OR: 2.7;95% C.I: 1.142 - 4.809, p Conclusion: These findings suggest that targeted sexual and reproductive health interventions should be provided to reduce the risk of abnormal vaginal discharge in women of reproductive age group.

Morbidity and Mortality of Newborns in a Context of Limited Resources in Tombouctou, Mali

Introduction: Worldwide, 2.3 million children died in the first 20 days after birth in 2022, according to the WHO. In Mali, according to the sixth Demographic and Health Survey, the neonatal mortality rate was estimated at 33% live births in 2018. The Timbuktu region had the highest neonatal mortality rate in the country with 44%. The objective of this work was to study the causes of neonatal morbidity and mortality and related factors in the paediatrics department of Timbuktu hospital. Materials and method: This was a descriptive, cross-sectional study conducted from 1 January to 31 December 2023 in the neonatology unit of the paediatrics department of Timbuktu hospital, including all newborns admitted to hospital. Results: Our study took place over 12 months, during which 618 admissions were made to the paediatric ward, including 244 newborns, i.e. 39.48%. The majority of newborns (86.5%) were admitted in the first week of life. The mean age was 3 days, with a sex ratio of 1.1 for males. Weight under 2500 g was 54.1% for an average weight of 2372 g. The main mode of admission was transfer from the hospital maternity unit (62%). The main reasons for admission were acute foetal distress (27.9%) and prematurity (26.2%). The average age of the mothers was 24, with extremes of 15 and 49. The mothers were housewives (87.3%), uneducated and primiparous (59% and 36.5% respectively);only 40.2% had made more than 3 antenatal care visits. Newborns born by vaginal delivery accounted for 80.7% and those born by caesarean section for 19.3%. The risk of infection was present in 52.5% of cases. The three leading causes of hospitalisation were birth asphyxia (40.2%), neonatal infection (32.4%) and prematurity (25%). The mortality rate was 21.7%. The main causes of death were prematurity (39.6%), birth asphyxia (32.1%) and neonatal infection (24.5%). Conclusion: Neonatal morbidity and mortality remain a concern in Timbuktu. Despite the unfavourable security situation, morbidity and mortality indicators are close to those in some hospitals in Mali. The correct application of Essential Newborn Care and antenatal care remains a major challenge for the hospital and the Timbuktu region.

Universal newborn hearing screening program in Saudi Arabia: Current insight

Newborn hearing screening(NHS) programs are essential to identify hearing loss early in life and to improve outcomes in children. In Saudi Arabia, the national NHS program has been operational since 2016;however, few studies have evaluated its status, and none have covered all provinces across the country. This cross-sectional retrospective study provides an overview of the program's status across all provinces, focusing on screening coverage rates, referral/fail rates, and follow-up procedures. In 2021, 199,034 newborns were screened, with a coverage rate of 92.6% and an overall referral/fail rate of 1.87%. These performance measures provide a foundation for future progress and improvements. This study highlights the importance of ongoing efforts to enhance the program's effectiveness and sustainability.

Draft of an Anthropometric Reference System for Full-Term Cameroonian Newborns: Prospective Study with Analytical Aim in the Maternity Wards of Douala

Introduction: Anthropometry applied to newborns is a reliable indicator of the quality of fetal growth. The latter is influenced by genetic, racial and nutritional factors varying from one population to another, explaining why a standard cannot be applied to all populations. Research question: should the Caucasian frame of reference be dogmatically applied in our African context? Multicenter studies are therefore necessary;hence the interest of this work, the main objective of which was to describe the anthropometric profile of full-term newborns in the city of Douala. Methodology: We carried out a cross-sectional study with an analytical aim and prospective data collection in the maternity wards of the Douala General Hospital, Laquintinie Hospital, District hospitals of Deido, Nylon and Bonassama over a period of 4 months (January to April 2020). We were interested in any newborn, born alive, vaginally or by cesarean section, seen in the first 24 hours from a full-term single-fetal pregnancy whose mother had given consent. We excluded newborns whose term was unclear and those with congenital malformations or signs of embryo-foetopathy. Data collection was done using structured and pre-tested survey sheets. The study variables were obstetric and anthropometric. Statistical analyzes were carried out with CS Pro 7.3 and SPSS version 25.0 software. The Student, Chi-square and Fischer tests were used to compare the means of the variables, the percentages with a significance threshold P value Results: During the study period, 305 full-term newborns were included, divided into 172 boys and 133 girls. The average anthropometric parameters of the full-term newborn in the city of Douala were: average weight: 3305 grams, average height: 49.8 centimeters, average head circumference: 34.6 centimeters, average upper arm circumference: 11.3 centimeters, circumference average thoracic: 32.8 centimeters. The percentile distribution showed a 10th percentile at 2656 grams and a 90th percentile at 3966 grams for weight defining the limits for small-for-gestational-age neonates and macrosomes. Conclusion: The anthropometric data of the full-term newborn in the city of Douala were: an average weight of 3305.4 grams, an average height of 49.8 centimeters, an average head circumference of 34.2 centimeters, an average upper arm circumference of 11.3 centimeters, and an average thoracic circumference of 32.8 centimeters with higher valuesin male newborns.

Relationship of Retinal Nerve Fiber Layer Thickness and Retinal Vessel Calibers with Cognitive Impairment in the Asymptomatic Polyvascular Abnormalities Population

Objective Cognitive impairment(CI)in older individuals has a high morbidity rate worldwide,with poor diagnostic methods and susceptible population identification.This study aimed to investigate the relationship between different retinal metrics and CI in a particular population,emphasizing polyvascular status.Methods We collected information from the Asymptomatic Polyvascular Abnormalities Community Study on retinal vessel calibers,retinal nerve fiber layer(RNFL)thickness,and cognitive function of 3,785participants,aged 40 years or older.Logistic regression was used to analyze the relationship between retinal metrics and cognitive function.Subgroups stratified by different vascular statuses were also analyzed.Results RNFL thickness was significantly thinner in the CI group(odds ratio:0.973,95%confidence interval:0.953–0.994).In the subgroup analysis,the difference still existed in the non-intracranial arterial stenosis,non-extracranial carotid arterial stenosis,and peripheral arterial disease subgroups(P<0.05).Conclusion A thin RNFL is associated with CI,especially in people with non-large vessel stenosis.The underlying small vessel change in RNFL and CI should be investigated in the future.

Abnormal State Detection in Lithium-ion Battery Using Dynamic Frequency Memory and Correlation Attention LSTM Autoencoder

This paper addresses the challenge of identifying abnormal states in Lithium-ion Battery(LiB)time series data.As the energy sector increasingly focuses on integrating distributed energy resources,Virtual Power Plants(VPP)have become a vital new framework for energy management.LiBs are key in this context,owing to their high-efficiency energy storage capabilities essential for VPP operations.However,LiBs are prone to various abnormal states like overcharging,over-discharging,and internal short circuits,which impede power transmission efficiency.Traditional methods for detecting such abnormalities in LiB are too broad and lack precision for the dynamic and irregular nature of LiB data.In response,we introduce an innovative method:a Long Short-Term Memory(LSTM)autoencoder based on Dynamic Frequency Memory and Correlation Attention(DFMCA-LSTM-AE).This unsupervised,end-to-end approach is specifically designed for dynamically monitoring abnormal states in LiB data.The method starts with a Dynamic Frequency Fourier Transform module,which dynamically captures the frequency characteristics of time series data across three scales,incorporating a memory mechanism to reduce overgeneralization of abnormal frequencies.This is followed by integrating LSTM into both the encoder and decoder,enabling the model to effectively encode and decode the temporal relationships in the time series.Empirical tests on a real-world LiB dataset demonstrate that DFMCA-LSTM-AE outperforms existing models,achieving an average Area Under the Curve(AUC)of 90.73%and an F1 score of 83.83%.These results mark significant improvements over existing models,ranging from 2.4%–45.3%for AUC and 1.6%–28.9%for F1 score,showcasing the model’s enhanced accuracy and reliability in detecting abnormal states in LiB data.

Abnormal Traffic Detection for Internet of Things Based on an Improved Residual Network

Along with the progression of Internet of Things(IoT)technology,network terminals are becoming continuously more intelligent.IoT has been widely applied in various scenarios,including urban infrastructure,transportation,industry,personal life,and other socio-economic fields.The introduction of deep learning has brought new security challenges,like an increment in abnormal traffic,which threatens network security.Insufficient feature extraction leads to less accurate classification results.In abnormal traffic detection,the data of network traffic is high-dimensional and complex.This data not only increases the computational burden of model training but also makes information extraction more difficult.To address these issues,this paper proposes an MD-MRD-ResNeXt model for abnormal network traffic detection.To fully utilize the multi-scale information in network traffic,a Multi-scale Dilated feature extraction(MD)block is introduced.This module can effectively understand and process information at various scales and uses dilated convolution technology to significantly broaden the model’s receptive field.The proposed Max-feature-map Residual with Dual-channel pooling(MRD)block integrates the maximum feature map with the residual block.This module ensures the model focuses on key information,thereby optimizing computational efficiency and reducing unnecessary information redundancy.Experimental results show that compared to the latest methods,the proposed abnormal traffic detection model improves accuracy by about 2%.

Abnormal Action Detection Based on Parameter-Efficient Transfer Learning in Laboratory Scenarios

Laboratory safety is a critical area of broad societal concern,particularly in the detection of abnormal actions.To enhance the efficiency and accuracy of detecting such actions,this paper introduces a novel method called TubeRAPT(Tubelet Transformer based onAdapter and Prefix TrainingModule).Thismethod primarily comprises three key components:the TubeR network,an adaptive clustering attention mechanism,and a prefix training module.These components work in synergy to address the challenge of knowledge preservation in models pretrained on large datasets while maintaining training efficiency.The TubeR network serves as the backbone for spatio-temporal feature extraction,while the adaptive clustering attention mechanism refines the focus on relevant information.The prefix training module facilitates efficient fine-tuning and knowledge transfer.Experimental results demonstrate the effectiveness of TubeRAPT,achieving a 68.44%mean Average Precision(mAP)on the CLA(Crazy LabActivity)small-scale dataset,marking a significant improvement of 1.53%over the previous TubeR method.This research not only showcases the potential applications of TubeRAPT in the field of abnormal action detection but also offers innovative ideas and technical support for the future development of laboratory safety monitoring technologies.The proposed method has implications for improving safety management systems in various laboratory environments,potentially reducing accidents and enhancing overall workplace safety.

A Comparison between Late Preterm and Term Infants with Respiratory Distress Syndrome, Early-Onset Sepsis, and Neonatal Jaundice in Ecuadorian Newborns

Background: To examine the differences in prevalence of respiratory distress syndrome, early-onset sepsis and jaundice, between late preterm infants versus term infants in Ecuadorian newborns. Methods: Study design: Epidemiological, observational, and cross-sectional, with two cohorts of patients. Settings: IESS Quito Sur Hospital at Quito, Ecuador, from February to April of 2020. Participants: This study included 204 newborns, 102 preterm infants, 102 term infants. Results: There are significant differences between late preterm infants and term infants, with a p-value of 0.000 in the prevalence of early sepsis, 70.59% vs. 35.29%. In respiratory distress syndrome between late and term premature infants, significant differences were observed with a p-value of 0.000, the proportion being 55.58% vs. 24.51% respectively. The prevalence of jaundice is higher in term infants with a p value of 0.002, 72.55%, versus 51.96% in late preterm infants, and the mean value of bilirubins in mg/dL was higher in term infants 14.32 versus 12.33 in late preterm infants;this difference is statistically significant with a p value of 0.004. Admission to the NICU is more frequent in late preterm infants with a p-value of 0.000, being 42.16% for late preterm infants vs. 7.84% in term infants;the mean of the hospital days with p-value 0.005, was higher in late preterm infants 4.97 days vs. 3.55 days for term newborns. Conclusion: Due to the conditions of their immaturity, late preterm infants are 2.86 times more likely to present early sepsis than full-term newborns. It is shown that late preterm infants are 2.69 times more likely to have respiratory distress syndrome compared to term infants, therefore, late preterm infants have a longer hospital stay of 4.97 days versus 3.55 days in term infants. Jaundice and mean bilirubin levels are higher in term infants due to blood group incompatibility and insufficient breastfeeding.

Vehicle Abnormal Behavior Detection Based on Dense Block and Soft Thresholding

With the rapid advancement of social economies,intelligent transportation systems are gaining increasing atten-tion.Central to these systems is the detection of abnormal vehicle behavior,which remains a critical challenge due to the complexity of urban roadways and the variability of external conditions.Current research on detecting abnormal traffic behaviors is still nascent,with significant room for improvement in recognition accuracy.To address this,this research has developed a new model for recognizing abnormal traffic behaviors.This model employs the R3D network as its core architecture,incorporating a dense block to facilitate feature reuse.This approach not only enhances performance with fewer parameters and reduced computational demands but also allows for the acquisition of new features while simplifying the overall network structure.Additionally,this research integrates a self-attentive method that dynamically adjusts to the prevailing traffic conditions,optimizing the relevance of features for the task at hand.For temporal analysis,a Bi-LSTM layer is utilized to extract and learn from time-based data nuances.This research conducted a series of comparative experiments using the UCF-Crime dataset,achieving a notable accuracy of 89.30%on our test set.Our results demonstrate that our model not only operates with fewer parameters but also achieves superior recognition accuracy compared to previous models.

Abnormal Action Recognition with Lightweight Pose Estimation Network in Electric Power Training Scene

Electric power training is essential for ensuring the safety and reliability of the system.In this study,we introduce a novel Abnormal Action Recognition(AAR)system that utilizes a Lightweight Pose Estimation Network(LPEN)to efficiently and effectively detect abnormal fall-down and trespass incidents in electric power training scenarios.The LPEN network,comprising three stages—MobileNet,Initial Stage,and Refinement Stage—is employed to swiftly extract image features,detect human key points,and refine them for accurate analysis.Subsequently,a Pose-aware Action Analysis Module(PAAM)captures the positional coordinates of human skeletal points in each frame.Finally,an Abnormal Action Inference Module(AAIM)evaluates whether abnormal fall-down or unauthorized trespass behavior is occurring.For fall-down recognition,three criteria—falling speed,main angles of skeletal points,and the person’s bounding box—are considered.To identify unauthorized trespass,emphasis is placed on the position of the ankles.Extensive experiments validate the effectiveness and efficiency of the proposed system in ensuring the safety and reliability of electric power training.

First record of abnormal body coloration in a rockfish Sebastes koreanus(Scorpaenoidei:Sebastidae)from coastal water of China based on morphological characteristics and DNA barcoding

The first record of abnormal body coloration in Sebastes koreanus Kim and Lee,1994,from the Yellow Sea of China,was documented based on morphological characteristics and DNA barcoding.The two rockfish specimens were collected from the coastal waters of Qingdao,China,and the whole body and all fins of them were red.Of the two red-colored rockfish,there were tiny deep red spots on each fin,2 red radial stripes behind and below the eyes and 1 large deep red blotch on the opercula,while the similar stripe and spot patterns are also present in the S.koreanus specimens with normal body coloration.The countable characteristics of the two specimens are in the range of the morphometry of S.koreanus.To further clarify the species identity and taxonomic status of the two specimens,DNA barcode analysis was carried out.The genetic distance between the red-colored rockfish and S.koreanus was 0,and the minimum net genetic distances between the red-colored rockfish and other Sebastes species except for S.koreanus were 3.0%,which exceeds the threshold of species delimitation.The phylogenetic analysis showed that the DNA barcoding sequences of the two red-colored rockfish clustered with the S.koreanus sequences.The above results of DNA barcode analysis also support that the two red-colored rockfish could be identified as the species of S.koreanus.The mechanism of color variation in S.koreanus is desirable for further research and the species could be an ideal model to study the color-driven speciation of the rockfishes.

A Clinical Study to Assess the Effectiveness of Oral Combination Kit Therapy in Syndromic Management of Abnormal Vaginal Discharge (FEMINE Study) in Kinshasa, Democratic Republic of Congo

Background: Vaginal discharge is one of most common and nagging problems that women face. About 20% - 25% of women who visit gynecology department complain of vaginal discharge and leucorrhoea. An orally administered combination kit, containing 2 g secnidazole, 1 g azithromycin and 150 mg fluconazole (Azimyn FS Kit), has been successfully evaluated in clinical trials and used in several countries for management syndromic vaginal discharge due to infections. Methods: This is a longitudinal study which aimed to verify the clinical efficacy of the combined oral kit containing secnidazole, azithromycin and fluconazole (Azimyn FS Kit®) in the syndromic treatment of abnormal vaginal discharge in patients received in outpatient consultations in Kinshasa/DR Congo from March to September 2023. Results: Majority of patients had whitish vaginal discharge (51.6%) of average abundance (56.2%), accompanied by pruritus in 72.1% of cases, and dyspareunia in 23.5% of cases and hypogastralgia in 40.2% of cases. One week after treatment with the Azimyn FS® combined kit, at the greatest majority of patients (97.3%), abnormal vaginal discharge had decreased by more than 50% (84.1%). Two weeks after treatment with the Azimyn FS® combined kit, almost all patients (97.3%) no longer had abnormal vaginal discharge which had completely disappeared. Conclusion: A single dose of secnidazole, azithromycin and fluconazole in the form of an oral combi-kit (Azimyn FS Kit) has shown excellent therapeutic effectiveness in the syndromic treatment of abnormal vaginal discharge wherein patients were treated without diagnostic confirmation.

Balloon dilation of congenital perforated duodenal web in newborns: Evaluation of short and long-term results

BACKGROUND Incomplete congenital duodenal obstruction(ICDO)is caused by a congenitally perforated duodenal web(CPDW).Currently,only six cases of balloon dilatation of the PDW in newborns have been described.AIM To present our experience of balloon dilatation of a perforated duodenal memb-rane in newborns with ICDO.METHODS Five newborns who underwent balloon dilatation of the CPDW along a prein-stalled guidewire between 2021 and 2023 were included.Nineteen newborns diagnosed with ICDO who underwent laparotomy were included in the control group.RESULTS In all cases,good anatomical and clinical results were obtained.In three cases,a follow-up study was conducted after 1 year.The average time to start enteral feeding per os was significantly earlier in the study group(4.4 d)than in the laparotomic group(21.2 days;P<0.0001).The time spent by patients in the intensive care unit and hospital after balloon dilatation was also significantly shorter.We determined the selection criteria for possible and effective CPDW balloon dilatation in newborns as follows:(1)Presence of dynamic radiographic signs of the passage of a radiopaque substance beyond the zone of narrowing or radiographic signs of pneumatisation of the duodenum and small bowel distal to the web;(2)presence of endoscopic signs of CPDW;(3)successful cannulation with a guidewire performed parallel to the endoscope,with holes in the congenital duodenal web;and(4)successful positioning of the balloon performed along a freestanding guidewire on the web.CONCLUSION Strictly following selection criteria for newborns with ICDO caused by CPDW ensures that endoscopic balloon dilatation using a pre-installed guidewire is safe and effective and shows good 1-year follow-up results.

High-grade serous carcinoma of the fallopian tube in a young woman with chromosomal 4q abnormality:A case report

BACKGROUND Few studies have reported an association between an increased risk of acquiring cancers and survival in patients with 4q deletion syndrome.This study presents a rare association between chromosome 4q abnormalities and fallopian tube highgrade serous carcinoma(HGSC)in a young woman.CASE SUMMARY A 35-year-old woman presented with acute dull abdominal pain and a known chromosomal abnormality involving 4q13.3 duplication and 4q23q24 deletion.Upon arrival at the emergency room,her abdomen appeared ovoid and distended with palpable shifting dullness.Ascites were identified through abdominal ultrasound,and computed tomography revealed an omentum cake and an enlarged bilateral adnexa.Blood tests showed elevated CA-125 levels.Paracentesis was conducted,and immunohistochemistry indicated that the cancer cells favored an ovarian origin,making us suspect ovarian cancer.The patient underwent debulking surgery,which led to a diagnosis of stage IIIC HGSC of the fallopian tube.Subsequently,the patient received adjuvant chemotherapy with carboplatin and paclitaxel,resulting in stable current condition.CONCLUSION This study demonstrates a rare correlation between a chromosome 4q abnormality and HGSC.UBE2D3 may affect crucial cancer-related pathways,including P53,BRCA,cyclin D,and tyrosine kinase receptors,thereby possibly contributing to cancer development.In addition,ADH1 and DDIT4 may be potential influencers of both carcinogenic and therapeutic responses.

Diagnostic significance of serum levels of serum amyloid A,procalcitonin,and high-mobility group box 1 in identifying necrotising enterocolitis in newborns

BACKGROUND Necrotising enterocolitis(NEC)is a critical gastrointestinal emergency affecting premature and low-birth-weight neonates.Serum amyloid A(SAA),procalcitonin(PCT),and high-mobility group box 1(HMGB1)have emerged as potential biomarkers for NEC due to their roles in inflammatory response,tissue damage,and immune regulation.AIM To evaluate the diagnostic value of SAA,PCT,and HMGB1 in the context of NEC in newborns.METHODS The study retrospectively analysed the clinical data of 48 newborns diagnosed with NEC and 50 healthy newborns admitted to the hospital.Clinical,radiological,and laboratory findings,including serum SAA,PCT,and HMGB1 Levels,were collected,and specific detection methods were used.The diagnostic value of the biomarkers was evaluated through statistical analysis,which was performed using chi-square test,t-test,correlation analysis,and receiver operating characteristic(ROC)analysis.RESULTS The study demonstrated significantly elevated levels of serum SAA,PCT,and HMGB1 Levels in newborns diagnosed with NEC compared with healthy controls.The correlation analysis indicated strong positive correlations among serum SAA,PCT,and HMGB1 Levels and the presence of NEC.ROC analysis revealed promising sensitivity and specificity for serum SAA,PCT,and HMGB1 Levels as potential diagnostic markers.The combined model of the three biomarkers demonstrating an extremely high area under the curve(0.908).CONCLUSION The diagnostic value of serum SAA,PCT,and HMGB1 Levels in NEC was highlighted.These biomarkers potentially improve the early detection,risk stratification,and clinical management of critical conditions.The findings suggest that these biomarkers may aid in timely intervention and the enhancement of outcomes for neonates affected by NEC.

A core scientific problem in the treatment of central nervous system diseases:newborn neurons

It has long been asserted that failure to recover from central nervous system diseases is due to the system's intricate structure and the regenerative incapacity of adult neurons.Yet over recent decades,numerous studies have established that endogenous neurogenesis occurs in the adult central nervous system,including humans'.This has challenged the long-held scientific consensus that the number of adult neurons remains constant,and that new central nervous system neurons cannot be created or renewed.Herein,we present a comprehensive overview of the alterations and regulatory mechanisms of endogenous neurogenesis following central nervous system injury,and describe novel treatment strategies that to rget endogenous neurogenesis and newborn neurons in the treatment of central nervous system injury.Central nervous system injury frequently results in alterations of endogenous neurogenesis,encompassing the activation,proliferation,ectopic migration,diffe rentiation,and functional integration of endogenous neural stem cells.Because of the unfavorable local microenvironment,most activated neural stem cells diffe rentiate into glial cells rather than neurons.Consequently,the injury-induced endogenous neurogenesis response is inadequate for repairing impaired neural function.Scientists have attempted to enhance endogenous neurogenesis using various strategies,including using neurotrophic factors,bioactive materials,and cell reprogramming techniques.Used alone or in combination,these therapeutic strategies can promote targeted migration of neural stem cells to an injured area,ensure their survival and diffe rentiation into mature functional neurons,and facilitate their integration into the neural circuit.Thus can integration re plenish lost neurons after central nervous system injury,by improving the local microenvironment.By regulating each phase of endogenous neurogenesis,endogenous neural stem cells can be harnessed to promote effective regeneration of newborn neurons.This offers a novel approach for treating central nervous system injury.

Analysis of the Efficacy of Prenatal B-Ultrasound in Diagnosing Fetal Abnormalities

Objective:To explore the positive significance of using prenatal B-ultrasound in diagnosing fetal abnormalities.Methods:A total of 200 pregnant women who visited Shaanxi Provincial People’s Hospital between January 2023 and January 2024 were recruited as the research subjects.All pregnant women received prenatal examinations.A retrospective analysis was carried out to analyze the positive significance of prenatal B-ultrasound examination in the diagnosis of fetal abnormalities.Results:Prenatal B-ultrasound examination detected 10 cases of fetal abnormalities,with a detection rate of 5.00%.When compared with the postnatal examination results of 5.50%,the difference was insignificant(P>0.05).Moreover,comparing the fetal limb abnormalities and cardiovascular abnormalities in prenatal B-ultrasound examination and postnatal examination,one case of congenital heart disease was missed in the prenatal B-ultrasound examination,and the others were consistent with the postnatal examination results,with a coincidence rate of 90.91%,indicating a high compliance rate.Conclusion:Fetal abnormalities have a great impact on mothers,babies,and families,and it is particularly important to strengthen diagnosis during this process.Prenatal B-ultrasound examination can improve the accuracy of diagnosis of fetal abnormalities and can be promoted in clinical practice as a basis for screening fetal abnormalities.