Objective:To compare the etiological characteristics between influenza-like illness (ILI) cases in outpatient and emergency departments and those with severe acute respiratory infection (SARI) in Guangdong Province, hoping to provide scientific evidence for the treatment, prevention, and control of respiratory infectious diseases.Methods:Laboratory testing for multiple respiratory pathogens was conducted on 6 090 specimens collected from ILI and SARI cases in Guangdong Province from August to December 2023. Chi-square test was used to analyze the differences in positive rates. Results:The overall positive rate of respiratory pathogens was 49.5% (3 016/6 090). The positive rate was 54.5% (2 260/4 145) in ILI cases and 38.9% (756/1 945) in SARI cases. The overall positive rate was higher in ILI cases than in SARI cases across all genders and age groups, and in most cities of the province, with statistically significant differences ( P<0.05). No significant difference was found in the overall positive rate between different genders. However, the difference between different age groups was statistically significant( P<0.001), with the highest rate identified in children aged 5-14 years (57.2%, 957/1 673). The main pathogens detected in ILI cases were influenza virus, human rhinovirus/enterovirus, and Streptococcus pneumoniae, while in SARI cases they were Mycoplasma pneumoniae, human rhinovirus/enterovirus, and influenza virus. The positive rates of adenovirus, human parainfluenza virus, SARS-CoV-2, human coronavirus, influenza virus, and Streptococcus pneumoniae were significantly higher in ILI cases than in SARI cases, while the positive rate of Mycoplasma pneumoniae was significantly higher in SARI cases ( P<0.05). Moreover, ILI cases were characterized by a higher risk of coinfection compared with SARI cases, especially in males or those aged 25-59 years. Conclusions:There are differences in the detection rates and spectrum of respiratory pathogens between ILI and SARI cases in Guangdong Province. Case features should be considered when developing strategies for preventing and treating respiratory infections.

For rare real-world data involving off-label drug use or comorbidity-associated polypharmacy,researchers have increasingly adopted target trial emulation to investigate drug repurposing for target indications.The success of such studies hinges on rigorous trial design and strict adherence to predefined protocols and standardized pipelines.Key elements in the trial design include the precise definition of inclusion and exclusion criteria,the selection of trial and control drugs and determination of treatment allocation time,the determination of appropriate efficacy endpoints for the target indication,the identification of causal estimands,and the development of robust strategies for confounding adjustment.The execution of the trial follows a structured process:screening eligible subjects,extracting relevant drug exposure data,constructing treatment and control groups,emulating the target trial,and ultimately generating hypotheses for drug repurposing through statistical inference.Propensity score methods,including stratification,matching and weighting techniques,are critical tools for addressing confounding bias and ensuring accurate estimation of causal effects.In recent years,creative progress has been made in target trial emulation,particularly in the calculation of propensity scores.Researchers have adopted advanced machine learning techniques,to enhance variable selection and have actively explored the use of innovative methods of digital intelligence technology like classification and regression trees,support vector machines,and deep learning for the application of propensity score calculation.Target trial emulation based on real-world data has achieved remarkable advancements in drug repurposing,demonstrating broad application prospects,particularly in cardiovascular diseases,metabolic disorders,Alzheimer's disease,and cancer.

For rare real-world data involving off-label drug use or comorbidity-associated polypharmacy,researchers have increasingly adopted target trial emulation to investigate drug repurposing for target indications.The success of such studies hinges on rigorous trial design and strict adherence to predefined protocols and standardized pipelines.Key elements in the trial design include the precise definition of inclusion and exclusion criteria,the selection of trial and control drugs and determination of treatment allocation time,the determination of appropriate efficacy endpoints for the target indication,the identification of causal estimands,and the development of robust strategies for confounding adjustment.The execution of the trial follows a structured process:screening eligible subjects,extracting relevant drug exposure data,constructing treatment and control groups,emulating the target trial,and ultimately generating hypotheses for drug repurposing through statistical inference.Propensity score methods,including stratification,matching and weighting techniques,are critical tools for addressing confounding bias and ensuring accurate estimation of causal effects.In recent years,creative progress has been made in target trial emulation,particularly in the calculation of propensity scores.Researchers have adopted advanced machine learning techniques,to enhance variable selection and have actively explored the use of innovative methods of digital intelligence technology like classification and regression trees,support vector machines,and deep learning for the application of propensity score calculation.Target trial emulation based on real-world data has achieved remarkable advancements in drug repurposing,demonstrating broad application prospects,particularly in cardiovascular diseases,metabolic disorders,Alzheimer's disease,and cancer.

Objective:To compare the etiological characteristics between influenza-like illness (ILI) cases in outpatient and emergency departments and those with severe acute respiratory infection (SARI) in Guangdong Province, hoping to provide scientific evidence for the treatment, prevention, and control of respiratory infectious diseases.Methods:Laboratory testing for multiple respiratory pathogens was conducted on 6 090 specimens collected from ILI and SARI cases in Guangdong Province from August to December 2023. Chi-square test was used to analyze the differences in positive rates. Results:The overall positive rate of respiratory pathogens was 49.5% (3 016/6 090). The positive rate was 54.5% (2 260/4 145) in ILI cases and 38.9% (756/1 945) in SARI cases. The overall positive rate was higher in ILI cases than in SARI cases across all genders and age groups, and in most cities of the province, with statistically significant differences ( P<0.05). No significant difference was found in the overall positive rate between different genders. However, the difference between different age groups was statistically significant( P<0.001), with the highest rate identified in children aged 5-14 years (57.2%, 957/1 673). The main pathogens detected in ILI cases were influenza virus, human rhinovirus/enterovirus, and Streptococcus pneumoniae, while in SARI cases they were Mycoplasma pneumoniae, human rhinovirus/enterovirus, and influenza virus. The positive rates of adenovirus, human parainfluenza virus, SARS-CoV-2, human coronavirus, influenza virus, and Streptococcus pneumoniae were significantly higher in ILI cases than in SARI cases, while the positive rate of Mycoplasma pneumoniae was significantly higher in SARI cases ( P<0.05). Moreover, ILI cases were characterized by a higher risk of coinfection compared with SARI cases, especially in males or those aged 25-59 years. Conclusions:There are differences in the detection rates and spectrum of respiratory pathogens between ILI and SARI cases in Guangdong Province. Case features should be considered when developing strategies for preventing and treating respiratory infections.

Objective To translate the Inflammatory Bowel Disease Disability Visual Analogue Scale (IBD Disk) into Chinese and conduct cross-cultural adaptation, and to test its reliability and validity among patients with inflammatory bowel disease (IBD). Methods Based on the modified Brislin translation model, the IBD Disk was translated into Chinese through forward translation, back translation, group discussion, and cross-cultural adaptation. From January to December 2022, a convenience sampling method was used to select 299 IBD patients for investigation to verify the reliability and validity of the Scale. Results The Chinese version of the IBD Disk includes 10 items, with decision values of 4.79 to 15.68 (>3.00), and P value was less than 0.05, indicating high discriminatory power for each item; the total Cronbach's α coefficient of the scale was 0.88, and the test-retest reliability was 0.87, indicating a good reproducibility of the scale; confirmatory factor analysis results indicated that the scale had ideal fit; Pearson correlation analysis results indicated that the total score of the IBD Disk was significantly positively correlated with the total score of the Inflammatory Bowel Disease Disability Index Scale (IBD-DI) (r=0.81, P < 0.001), suggesting good correlation between the IBD Disk and the IBD-DI. Conclusion The Chinese version of the IBD Disk has good reliability and validity, and is suitable to be used as a disability assessment tool for IBD patients in Chinese culture.

Objective To analyze the feasibility and efficacy of a deep convolutional neural network(DCNN)model based on chest CT images to evaluate bone mineral density(BMD).Methods A total of 1 048 health check subjects'2 096 central level images of lumbar 1 and 2 vertebral bodies were used for experiments and analysis in this retrospective study.According to the results of quanti-tative computed tomography(QCT)BMD measurement,the subjects were divided into three categories:normal,osteopenia,osteopo-rosis(OP).Herein,a DCNN segmentation model was constructed based on chest CT images[training set(n=1 096),tuning set(n=200),and test set(n=800)],the segmentation performance was evaluated using the Dice similarity coefficient(DSC)to com-pare the consistency with the manually sketched region of vertebral body.Then,the DCNN classification models 1(fusion feature construction of lumbar 1 and 2 vertebral bodies)and model 2(image feature construction of lumbar 1 alone)was developed based on the training set(n=530).Model performance was compared in a test set(n=418)by the receiver operating characteristic(ROC)curve analysis.Results When the number of images in the training set(n=300)was adopted,the DSC value was 0.950 in the test set.The results showed that the sensitivity,specificity and area under the curve(AUC)of model 1 and model 2 in diagno-sing osteopenia and OP were 0.716,0.960,0.952;0.941,0.948,0.980;0.638,0.954,0.940;0.843,0.959,0.978,respectively.The AUC value of normal model 1 was higher than that of model 2(0.990 vs 0.983,P=0.033),while there was no significant difference in AUC values between osteopenia and OP(P=0.210,0.546).Conclusion A DCNN may have the potential to evaluate bone mass based on chest CT images,which is expected to become an effective tool for OP screening.

Objective To quantify the correlations between Elekta XVI cone beam CT dose and various scanning protocols,providing mathematical models to assess the protocol-dependency of imaging dose during imnage guided radiotherapy.Methods Based on standard protocols and various combinations of kVp and mA on an XVI mounted on an Elekta Versa HD accelerator,the air KERMA was measured at various positions in a standard PTW CTDI body phantom using calibrated PTW 30009 kV chamber and UNIDOS webline electrometer.Weighted CT dose index (CTDIw) was computed thereafter.SigmaPlot 10.0 was used to fit the measurements against mA and/or kVp yielding empirical functions.Results Under standard protocols,the CTDIw of Varian OBI was only 11.23％ (chest) and 9.15％ (pelvis) of Elekta XVI.Using the default and other 4 investigated kVp values,the central and peripheral KERMA were both proportional to mA,and vet the slope value a varied dramatically from 0.479 to 6.679.Major affecting factors included kVp settings,measurement locations,and dosimetric mnetrics,etc.None linear regressions were used to fit kVp against KERMA at various locations and CTDIw (R2 ＞ 0.997).The differences between all coefficients were statistically significant (P ＜ 0.05).The impact of changing both mA and kVp on the dose to phantom center can be described as mGy =(5.917-0.197 ×kVp+0.002 × kVp2-5.063 × 10-6 × kVp3) × mA.Conclusions Imaging dose of Elekta XVI is strongly dependent on scanning paraneters.The proposed mathematical models can be used as efficient and robust indicators of such dependency.

Objective To investigate the diagnostic value of dual-energy CT virtual non-contrast (VNC) technology for osteoporosis(OP). Methods Dual-energy CT images of 50 patients with lumbar traumas were collected prospectively.Patients who suffer from vertebral bodies fractures between lumbar 1 to 4, have internal metal fixations or underwent percutaneous vertebroplasty, or presented tumors or compromised bone metabolism induced by diseases or medications were excluded.The scanning range was from the upper edge of the 12th thoracic vertebral body to the lower edge of the first sacral vertebral body. The voltages of tubes A and B were 90 kV and Sn 150 kV,and the reference tubes currents were 220 mAs and 138 mAs. Image reconstruction was performed using Advanced Modeled Iterative Reconstruction (ADMIRE)with iterative strength of 3 and convolution kernel of Qr 40.The default parameters of the virtual non-contrast software were corrected by the standard recommended by the Bone Marrow software of the post-processing platform Syngo.via,and the CT value of calcium(contrast media CM),the CT value of mixed energy images(regular CT value,rCT),the calcium density(CaD)and the fat fraction(Fat)were measured. The bone mineral density (BMD) and T score of each lumbar vertebra from lumbar 1 to lumbar 4 were measured by dual energy X-ray absorptiometry(DXA).With T score less than or equal to the 2.5 standard deviation as the gold standard for the diagnosis of OP,correlations between CT measurements and vertebral BMDs were analyzed using Pearson correlation analysis and linear regression and the diagnostic values of different CT measurements for OP were compared using receiver operating characteristic curve. Results Each of the vertebral bodies was analyzed as a single unit.Fifty of them were osteoporotic and the rest 116 were non-osteoporotic.Except for Fat,the CT measurement parameters of the osteoporotic vertebral bodies were lower than those of the ones without osteoporosis, and the difference was statistically significant (P<0.01).CM,rCT and CaD were significantly correlated with BMD(r were 0.75,0.65,0.71,all P<0.01)and there was a linear relationship(F were 209.91,120.24,167.69,all P<0.01).Meanwhile,CM,rCT,CaD and T score were also significantly correlated (r were 0.74, 0.65, 0.70, all P<0.01) with a linear relationship (F were 195.04,120.29,156.37,all P<0.01).CM,rCT and CaD had relatively high concordance rates against the OP diagnosis gold standard (respectively 81.9%, 62.2% and 81.9%). CM and CaD had higher concordance rates than rCT,the difference being statistically significant(P<0.01),and by the CM less than 239.5 HU or CaD less than 10.9 mg/cm3standard, their sensitivities of diagnosing osteoporosis were respectively 86.0% and 84.0%,while the specificities,80.2% and 81.0%.After superimposing CM and CaD, the results did not improve the diagnosis efficiency of OP (pre-superposition diagnostic performance better than post-superposition (P<0.05). Conclusion The VNC technology on DECT can do both vertebral fractures diagnosis and osteoporosis assessment at the same time, thus optimizing the clinical examination process.

Objective To develop a rapid and sensitive DNA microarray for Listeria monocytogenes detection.Methods A DNA microarray was developed using gyrB,ISR,16S rRNA,23S rRNA,hlyA,iap and prfA as the target genes and tested against 18 different species of known reference for repeatability,sensitivity,and specificity to verify the effectiveness of the chip.Results After testing of samples by the LM array,results show that the 70 mer Oligos synthesized by IDT are superior to the Oligos synthesized by Sagon with respect to both probe spotting or samples detection.The comparison of 3 spotting probe concentrations of 10 μmol/L,40 μmol/L and 80 μmol/L demonstrated that the 10 pmol/L probes result in good detection signals equivalent to the 40 μmol/L and 80 μmol/L probes.The repeatability and sensitivity evaluated by sample testing on the LM array revealed that the chips developed in this study have good repeatability and the lower limit of sample detection is 0.9 ng DNA.The LM array can distinguish clearly and definitively between Listeria and non-Listeria bacteria in the sample.Conclusion The microarray is able to rapidly detect and identify Listeria monocytogenes.

Objective To investigate methods for prenatal molecular diagnosis of fetuses at high risk for X-linked adrenoleukodystrophy(X-ALD).Methods The amniotic fluid was obtained and genomic DNA was isolated from amniotic fluid cells.Maternal contamination was evaluated by paternity test.PCRRFLP,sequencing and denaturing high performance liquid chromatography(DHPLC)were used to detect the ABCD1 gene of fetal genome.Results In the pedigree 1,the PCR product(799 bp)of the fetus 1 and her father(normal control)could be digested with BcnI. No P560L mutation,which was present in the index patient,was detected in the ABCD1 gene from the genomic DNA of the fetus 1 using direct sequencing.In the pedigree 2,the PCR product(232 bp)of the fetus 2 and her father could not be digested with MaeI and no Q177X mutation,which was present in the propositus,was detected in the ABCD1 gene from the genomic DNA of the fetus 2 using direct sequencing.In the pedigree 3,the PCR product(271 bp)was digested with AciI.the pattern of the fetus 3 and the propositus being the same,and the R617C mutation was found in the ABCD1 gene from the genomic DNA of the fetus 3 using direct sequencing.In the pedigree 4,the PCR product(269 bp)was analyzed with the DHPLC,and the pattern of elution peaks of the fetus 4 and her father was similar,but different from that of the propositus.No K276E mutation was detectable in the ABCD1 gene from the genomic DNA of the fetus 4 by using direct sequencing.Judging from the sex of the fetuses,fetuses 1 and 2 were normal homozygotes,fetus 3 was an ALD hemizygote,and fetus 4 was a normal hemizygote.Conclusion A new protocol for X-ALD prenatal molecular diagnosis is proposed,which would ensure the accuracy of prenatal diagnosis.