Objective:To investigate the contributing factors to elevated blood pressure in borderline cases during medical selection for recruitment of Air Force flying cadets in order to enhance the accuracy of selection.Methods:Blood pressure was measured among 2 350 male high school graduates in the 2022 re-selection phase of medical selection of Air Force flying cadets. None of the participants had a family history of hypertension according to previous health checkups. Identified through blood pressure measurement, subjects with borderline hypertension were assigned to an intervention group (self-intervention with personalized correction plans) and a control group (self-intervention alone) using a random number table. Standardized blood pressure measurements and comprehensive medical history reviews were performed to compare pre- and post-intervention outcomes across the 2 groups, followed by an investigation into the causative mechanisms of elevated blood pressure.Results:Among the 102 cases of borderline hypertension (51 per group) identified, primary contributing factors included the white-coat phenomenon (41.2%), pre-examination physical activity (17.6%), pre-examination medications (3.9%) and poor sleep quality (35.3%). No significant differences in systolic blood pressure (SBP) or diastolic blood pressure (DBP) were observed between the 2 groups at baseline (both P>0.05). After interventions, the intervention group showed significantly lower SBP ( t=3.13, P=0.002) and DBP ( t=7.68, P<0.001) than the control group. Both groups exhibited reductions in SBP and DBP from baseline ( t=6.63, 8.97, 4.13, 2.03, P<0.001, <0.001, <0.001, =0.043). The percentage of students with normal blood pressure was 96.1% (49/51) in the intervention group and 78.4% (40/51) in the control group. Conclusions:Transient blood pressure elevation in selection settings primarily stems from the white-coat phenomenon, physical exertion, medications and sleep disturbances. Standardizing blood pressure measurement protocols and addressing transient factors can help avoid unwarranted disqualifications and ensure the accuracy of selection.

The complement component 4 binding protein alpha(C4BPA)gene is the alpha chain of complement binding protein 4.As a plasma protein involved in the complement and coagulation systems,it can influence immune responses and lipid metabolism.In order to study the polymor-phism of C4BPA gene and its correlation with milk quality traits in Chinese Holstein cows,genom-ic DNA was extracted from blood samples of 92 Chinese Holstein cows,and the target fragment of C4BPA gene was amplified by PCR,and the association analysis was performed by using direct se-quencing to obtain the SNP loci and milk quality traits.The results showed that among the four SNPs found at the third intron of the C4BPA gene,I3-11 G＞A was highly significantly correlated with milk protein and urea nitrogen(P＜0.05),I3-291 T＞G was significantly correlated with lac-tose(P＜0.05),I3-374 C＞T was highly significantly correlated with lactose and urea nitrogen(P＜0.05),and I3-375 T＞G was highly significantly correlated with lactose(P＜0.05),milk pro-tein and urea nitrogen.The chi-square test values for each point indicated that the population was in genetic equilibrium.Individuals of haplotype combination H1 H1 had the highest lactose content,and haplotype combination H1H2 can be used as the best haplotype combination in the molecular selection work of dairy cows.

Purpose To explore the feasibility and clinical value of deep learning-based image reconstruction technology in 5.0T MRI for nasopharyngeal carcinoma.Materials and Methods A prospective study was conducted on 50 newly diagnosed nasopharyngeal carcinoma patients from August to December 2024 at Sun Yat-sen University Cancer Center.5.0T MRI was performed to scan the nasopharynx region.Routine scanning protocols included transverse T2WI,transverse T1WI,transverse contrast-enhanced T1WI and coronal fat-suppressed contrast-enhanced T1WI sequences.Based on these standard scanning protocols,DeepRecon deep learning reconstruction technology with different levels(grade 1-5)was applied,generating a total of 24 sets of images.Qualitative evaluation employed a Likert scale(5-point system)for subjective scoring on lesion detection,lesion edge clarity,artifacts and overall image quality.Quantitative evaluation was performed using the signal-to-noise ratio and contrast-to-noise ratio to objectively assess the quality of the 24 image sets.Differences in qualitative and quantitative indicators between different groups were compared,while the Kappa coefficient was used to analyze the consistency of subjective evaluations by two radiologists.Results In the qualitative assessment of 24 image sets from four MRI sequences(with and without DeepRecon reconstruction),DeepRecon images(grade 2-4)significantly outperformed traditional images in all features except for artifact reduction(Z=-12.11--6.23,all P<0.001).Images reconstructed at DeepRecon grade 3 had the highest overall score and the best image quality.Furthermore,compared with traditional images,DeepRecon images(grade 2-5)demonstrated significantly improved signal-to-noise ratio for both lesions and the lateral pterygoid muscle(t=-15.67--3.44,Z=-6.09--4.63,all P<0.01).In addition,in the transverse T2WI,transverse contrast-enhanced T1WI and coronal fat-suppressed contrast-enhanced T1WI images with DeepRecon reconstruction(grade 2-5),the contrast-to-noise ratio(lesion/lateral pterygoid muscle)also showed significant improvement compared to traditional images(t=-12.71--3.19,Z=-6.08--4.47,all P<0.001).The inter-observer agreement for the overall subjective quality score between the two radiologists was good(Kappa=0.75-0.82,all P<0.01).Conclusion DeepRecon deep learning reconstruction technology significantly increases the signal-to-noise ratio and resolution of traditional magnetic resonance images of nasopharyngeal cancer,improving image clarity and bringing more possibilities for the advancement of imaging diagnosis.

Purpose To explore the feasibility and clinical value of deep learning-based image reconstruction technology in 5.0T MRI for nasopharyngeal carcinoma.Materials and Methods A prospective study was conducted on 50 newly diagnosed nasopharyngeal carcinoma patients from August to December 2024 at Sun Yat-sen University Cancer Center.5.0T MRI was performed to scan the nasopharynx region.Routine scanning protocols included transverse T2WI,transverse T1WI,transverse contrast-enhanced T1WI and coronal fat-suppressed contrast-enhanced T1WI sequences.Based on these standard scanning protocols,DeepRecon deep learning reconstruction technology with different levels(grade 1-5)was applied,generating a total of 24 sets of images.Qualitative evaluation employed a Likert scale(5-point system)for subjective scoring on lesion detection,lesion edge clarity,artifacts and overall image quality.Quantitative evaluation was performed using the signal-to-noise ratio and contrast-to-noise ratio to objectively assess the quality of the 24 image sets.Differences in qualitative and quantitative indicators between different groups were compared,while the Kappa coefficient was used to analyze the consistency of subjective evaluations by two radiologists.Results In the qualitative assessment of 24 image sets from four MRI sequences(with and without DeepRecon reconstruction),DeepRecon images(grade 2-4)significantly outperformed traditional images in all features except for artifact reduction(Z=-12.11--6.23,all P<0.001).Images reconstructed at DeepRecon grade 3 had the highest overall score and the best image quality.Furthermore,compared with traditional images,DeepRecon images(grade 2-5)demonstrated significantly improved signal-to-noise ratio for both lesions and the lateral pterygoid muscle(t=-15.67--3.44,Z=-6.09--4.63,all P<0.01).In addition,in the transverse T2WI,transverse contrast-enhanced T1WI and coronal fat-suppressed contrast-enhanced T1WI images with DeepRecon reconstruction(grade 2-5),the contrast-to-noise ratio(lesion/lateral pterygoid muscle)also showed significant improvement compared to traditional images(t=-12.71--3.19,Z=-6.08--4.47,all P<0.001).The inter-observer agreement for the overall subjective quality score between the two radiologists was good(Kappa=0.75-0.82,all P<0.01).Conclusion DeepRecon deep learning reconstruction technology significantly increases the signal-to-noise ratio and resolution of traditional magnetic resonance images of nasopharyngeal cancer,improving image clarity and bringing more possibilities for the advancement of imaging diagnosis.

The complement component 4 binding protein alpha(C4BPA)gene is the alpha chain of complement binding protein 4.As a plasma protein involved in the complement and coagulation systems,it can influence immune responses and lipid metabolism.In order to study the polymor-phism of C4BPA gene and its correlation with milk quality traits in Chinese Holstein cows,genom-ic DNA was extracted from blood samples of 92 Chinese Holstein cows,and the target fragment of C4BPA gene was amplified by PCR,and the association analysis was performed by using direct se-quencing to obtain the SNP loci and milk quality traits.The results showed that among the four SNPs found at the third intron of the C4BPA gene,I3-11 G＞A was highly significantly correlated with milk protein and urea nitrogen(P＜0.05),I3-291 T＞G was significantly correlated with lac-tose(P＜0.05),I3-374 C＞T was highly significantly correlated with lactose and urea nitrogen(P＜0.05),and I3-375 T＞G was highly significantly correlated with lactose(P＜0.05),milk pro-tein and urea nitrogen.The chi-square test values for each point indicated that the population was in genetic equilibrium.Individuals of haplotype combination H1 H1 had the highest lactose content,and haplotype combination H1H2 can be used as the best haplotype combination in the molecular selection work of dairy cows.

Objective:To investigate the contributing factors to elevated blood pressure in borderline cases during medical selection for recruitment of Air Force flying cadets in order to enhance the accuracy of selection.Methods:Blood pressure was measured among 2 350 male high school graduates in the 2022 re-selection phase of medical selection of Air Force flying cadets. None of the participants had a family history of hypertension according to previous health checkups. Identified through blood pressure measurement, subjects with borderline hypertension were assigned to an intervention group (self-intervention with personalized correction plans) and a control group (self-intervention alone) using a random number table. Standardized blood pressure measurements and comprehensive medical history reviews were performed to compare pre- and post-intervention outcomes across the 2 groups, followed by an investigation into the causative mechanisms of elevated blood pressure.Results:Among the 102 cases of borderline hypertension (51 per group) identified, primary contributing factors included the white-coat phenomenon (41.2%), pre-examination physical activity (17.6%), pre-examination medications (3.9%) and poor sleep quality (35.3%). No significant differences in systolic blood pressure (SBP) or diastolic blood pressure (DBP) were observed between the 2 groups at baseline (both P>0.05). After interventions, the intervention group showed significantly lower SBP ( t=3.13, P=0.002) and DBP ( t=7.68, P<0.001) than the control group. Both groups exhibited reductions in SBP and DBP from baseline ( t=6.63, 8.97, 4.13, 2.03, P<0.001, <0.001, <0.001, =0.043). The percentage of students with normal blood pressure was 96.1% (49/51) in the intervention group and 78.4% (40/51) in the control group. Conclusions:Transient blood pressure elevation in selection settings primarily stems from the white-coat phenomenon, physical exertion, medications and sleep disturbances. Standardizing blood pressure measurement protocols and addressing transient factors can help avoid unwarranted disqualifications and ensure the accuracy of selection.

The peroxisome proliferator-activated receptor gamma(peroxisome proliferator-activated receptor gamma,coactivator 1 beta,PPARGC1B)gene is an intranuclear receptor transcription fac-tor responsible for regulating the expression of target genes.To comprehend the characteristics and mutations of the PPARGC1B gene within the Sichuan yak population,the SNP loci of the PPARGC1B gene were identified through direct sequencing of PCR products.Additionally,the cod-ing region of the PPARGC1B gene was obtained via PCR amplification and sequencing.Bioinforma-tics analyses were conducted to predict protein-coding and mRNA secondary structure.This study identified four exon SNP mutation sites(E9-189A→C,E9-387G→A,E9-542C→T,and E9-554T→C)based on the single nucleotide polymorphism analysis of the PPARGC1B gene in Sichuan yaks.Notably,the E9-387G→A and E9-554T→C loci exhibited significant correlations with shear force and backfat thickness in Sichuan yaks.Subsequently,bioinformatics analysis of the four mutation sites revealed that the PPARGC1B protein is an acidic,unstable,non-transmembrane,and non-secretory hydrophilic protein with a coiled helix structure.It lacks a signal peptide and transmembrane region,predominantly functions in the nucleus,and features 106 phosphorylation sites,one glycosylation site,and one conserved RRM structure.The secondary structure comprises mainly α-helix and random coils.Although the protein structure of the PPARGC1B gene remained unchanged post-mutation,there were significant differences in mRNA secondary structure.These findings suggest that the polymorphic loci of the PPARGC1B gene in Sichuan yaks could serve as a theoretical basis for enhancing meat quality traits through molecular biological methods,presen-ting practical applications in breeding.

The SNP loci of ACOX1 gene in 83 China Holstein cows were detected by PCR amplifica-tion and direct sequencing,and the association between the genetic polymorphism loci of ACOX 1 gene and milk quality traits of China Holstein cows was analyzed by SPSS 25.0 software.The re-sults showed that a SNP locus I3-2 267 G→C was found in the third intron of ACOX1 gene,it was moderately polymorphic and in Hardy Weinberg equilibrium in the population.By correlation anal-ysis,it was found that the SNP locus was significantly related to the somatic cell content and cor-rected milk quantity of dairy cows.The I3-2 267 G→C locus of ACOX1 gene can be used as a mo-lecular marker of quality traits of Holstein cows in China,and provide reference for the study of quality traits of Holstein cows in China.

The gene encoding regulatory subunit 15 A of protein phosphatase 1 produces a protein that is a universally present protein phosphatase in eukaryotic cells.In this study,genomic DNAs were extracted from the blood of 89 Chinese Holstein cows and were used as templates for PCR amplification of the target fragment of the PPP1R15A gene.The product was tested and a polymor-phic site,E3-250T＞A was found.The polymorphism of this side and its correlation with milk pro-duction traits in Chinese Holstein cattle were statistically analyzed using SPSS 23.0 software.The findings revealed three genotypes at this site:AA,AT and TT.Cows possessing the AT and TT genotypes exhibited significant differences(P＜0.01)in milk fat and solid non-fat content com-pared to those with the AA genotype.While no significant differences were noted for other milk production traits,including milk yield,protein,lactose,somatic cell count,blood urea nitrogen,and corrected milk.The identification of functional SNPs in the PPP1R15A gene provides a theoretical basis for further research and identification of causal variations in the cow PPP1R15A gene.