Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Obstructive sleep apnea (OSA) is an increasingly widespread sleep-breathing disordered disease, and is an independent risk factor for many high-risk chronic diseases such as hypertension, coronary heart disease, stroke, arrhythmias and diabetes, which is potentially fatal. The key to the prevention and treatment of OSA is early diagnosis and treatment, so the assessment and diagnostic technologies of OSA have become a research hotspot. This paper reviews the research progresses of severity assessment parameters and diagnostic technologies of OSA, and discusses their future development trends. In terms of severity assessment parameters of OSA, apnea hypopnea index (AHI), as the gold standard, together with the percentage of duration of apnea hypopnea (AH%), lowest oxygen saturation (LSpO₂), heart rate variability (HRV), oxygen desaturation index (ODI) and the emerging biomarkers, constitute a multi-dimensional evaluation system. Specifically, the AHI, which measures the frequency of sleep respiratory events per hour, does not fully reflect the patients’ overall sleep quality or the extent of their daytime functional impairments. To address this limitation, the AH%, which measures the proportion of the entire sleep cycle affected by apneas and hypopneas, deepens our understanding of the impact on sleep quality. The LSpO₂ plays a critical role in highlighting the potential severe hypoxic episodes during sleep, while the HRV offers a different perspective by analyzing the fluctuations in heart rate thereby revealing the activity of the autonomic nervous system. The ODI provides a direct and objective measure of patients’ nocturnal oxygenation stability by calculating the number of desaturation events per hour, and the biomarkers offers novel insights into the diagnosis and management of OSA, and fosters the development of more precise and tailored OSA therapeutic strategies. In terms of diagnostic techniques of OSA, the standardized questionnaire and Epworth sleepiness scale (ESS) is a simple and effective method for preliminary screening of OSA, and the polysomnography (PSG) which is based on recording multiple physiological signals stands for gold standard, but it has limitations of complex operations, high costs and inconvenience. As a convenient alternative, the home sleep apnea testing (HSAT) allows patients to monitor their sleep with simplified equipment in the comfort of their own homes, and the cardiopulmonary coupling (CPC) offers a minimal version that simply analyzes the electrocardiogram (ECG) signals. As an emerging diagnostic technology of OSA, machine learning (ML) and artificial intelligence (AI) adeptly pinpoint respiratory incidents and expose delicate physiological changes, thus casting new light on the diagnostic approach to OSA. In addition, imaging examination utilizes detailed visual representations of the airway’s structure and assists in recognizing structural abnormalities that may result in obstructed airways, while sound monitoring technology records and analyzes snoring and breathing sounds to detect the condition subtly, and thus further expands our medical diagnostic toolkit. As for the future development directions, it can be predicted that interdisciplinary integrated researches, the construction of personalized diagnosis and treatment models, and the popularization of high-tech in clinical applications will become the development trends in the field of OSA evaluation and diagnosis.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Background::Histological healing is closely associated with improved long-term clinical outcomes and lowered relapses in patients with ulcerative colitis (UC). Here, we developed a novel diagnostic criterion for assessing histological healing in UC patients.Methods::We conducted a retrospective cohort study in UC patients, whose treatment was iteratively optimized to achieve mucosal healing at Shanghai Tenth People’s Hospital of Tongji University from January 2017 to May 2022. We identified an inflammatory cell enumeration index (ICEI) for assessing histological healing based on the proportions of eosinophils, CD177 + neutrophils, and CD40L + T cells in the colonic lamina propria under high power field (HPF), and the outcomes (risks of symptomatic relapses) of achieving histological remission vs. persistent histological inflammation using Kaplan-Meier curves. Intrareader reliability and inter-reader reliability were evaluated by each reader. The relationships to the changes in the Nancy index and the Geboes score were also assessed for responsiveness. The ICEI was further validated in a new cohort of UC patients from other nine university hospitals. Results::We developed an ICEI for clinical diagnosis of histological healing, i.e., Y = 1.701X 1 + 0.758X 2 + 1.347X 3 - 7.745 (X 1, X 2, and X 3 represent the proportions of CD177 + neutrophils, eosinophils, and CD40L + T cells, respectively, in the colonic lamina propria under HPF). The receiver operating characteristics curve (ROC) analysis revealed that Y <-0.391 was the cutoff value for the diagnosis of histological healing and that an area under the curve (AUC) was 0.942 (95% confidence interval [CI]: 0.905-0.979) with a sensitivity of 92.5% and a specificity of 83.6% ( P <0.001). The intraclass correlation coefficient (ICC) for the intrareader reliability was 0.855 (95% CI: 0.781-0.909), and ICEI had good inter-reader reliability of 0.832 (95% CI: 0.748-0.894). During an 18-month follow-up, patients with histological healing had a substantially better outcome compared with those with unachieved histological healing ( P <0.001) using ICEI. During a 12-month follow-up from other nine hospitals, patients with histological healing also had a lower risk of relapse than patients with unachieved histological healing. Conclusions::ICEI can be used to predict histological healing and identify patients with a risk of relapse 12 months and 18 months after clinical therapy. Therefore, ICEI provides a promising, simplified approach to monitor histological healing and to predict the prognosis of UC.Registration::Chinese Clinical Trial Registry, No. ChiCTR2300077792.

The transmission cycle of echinococcosis was established in 1853.More than 160 years have elapsed since Iceland initiated control measures to break the transmission cycle of echinococcosis in 1863.Control plans have been implemented in more than a dozen countries/territories,and lessons have been learned from failures as well as successes.In this review,we fo-cus on the failure experiences,which have also promoted successes in the control of cystic echinococcosis(caused by the para-site Echinococcus granulosus)in regions including Iceland,New Zealand,Uruguay,Wales(England),Turkana(Kenya),and Sardinia(Italy).The causes of the failures were analyzed,and the effects of health education,dog deworming,and con-trol measures for infected animal slaughter on echinococcosis control are comprehensively summarized.However,no suc-cessful experience has been reported in the control of alveolar echinococcosis(caused by the parasite Echinococcus multilocu-laris).On the basis of the biological characteristics of E.mul-tilocularis parasitization in dogs for a duration of 30 days and larvae parasitization in rodents,the fundamental measure for controlling alveolar echinococcosis is administration of monthly deworming treatments to dogs in high prevalence areas.

Investigating the species/biovars,distribution patterns,and genetic correlations of Brucella from sheep in north-west China is critical to reveal the population and epidemiological characteristics of the Brucella melitensis.In this study,con-ventional identification and AMOS-PCR were used to determine the species/biovars of Brucella isolated from 13 regions in northwest China.MLST and MLVA-16 genotyping methods were used to analyze the genetic characteristics of the strains.Con-ventional identification and AMOS-PCR detection revealed that 59 Brucella melitensis were isolated in this study,in-cluding 22 strains from Inner Mongolia,17 strains from Xin-jiang,13 strains from Gansu,and 7 strains from Qinghai,of which 58 strains were B.melitensis biovar 3,and one strain was B.melitensis biovar 1.MLST analysis indicated that 90％(53/59)of B.melitensis were of ST8 sequence type,the dominant epidemic population.The MLVA-11 survey demonstrated that 59 B.melitensis strains clustered into six MLVA-11 genotypes,and 87％of the strains were of MLVA-11 genotype 116.Therefore,the predominant strains in the northwest region were from the Eastern Mediterranean lineage.MLVA-16 divided 59 strains of B.melitensis into 40 gen-otypes,eight of which were shared genotypes.Each genotype was composed of two to seven strains from the same region,thereby indicating that the cases of each shared genotype were outbreaks from a common source of infection.All shared MLVA-16 genotypes comprised strains from the same province,thus indicating apparent regional clustering characteristics of strains in each province.In a genetic comparison between populations and isolated strains from the spleens of sheep,multiple identical MLVA-16 genotypes were found to be composed of strains from different hosts.These findings indicated a transmission path-way from sheep/goats to humans.B.melitensis biovar 3 was the main pathogen causing animal brucellosis in the northwest re-gion,and infected sheep were the main brucellosis infection source in the regional population.The ST8 strains were the domi-nant epidemic population,and the MLVA genotype of strains in each region showed clear regional clustering characteristics.

Objective:To evaluate the efficacy of acute T-cell lymphoblastic leukemia(T-ALL)in children and explore the prognostic risk factors.Methods:The clinical data of 127 newly diagnosed children with T-ALL admitted to five hospitals in Fujian province from April 2011 to December 2020 were retrospectively analyzed,and compared with children with newly diagnosed acute precursor B-cell lymphoblastic leukemia(B-ALL)in the same period.Kaplan-Meier analysis was used to evaluate the overall survival(OS)and event-free survival(EFS),and COX proportional hazard regression model was used to evaluate the prognostic factors.Among 116 children with T-ALL who received standard treatment,78 cases received the Chinese Childhood Leukemia Collaborative Group(CCLG)-ALL 2008 protocol(CCLG-ALL 2008 group),and 38 cases received the China Childhood Cancer Collaborative Group(CCCG)-ALL 2015 protocol(CCCG-ALL 2015 group).The efficacy and serious adverse event(SAE)incidence of the two groups were compared.Results:Proportion of male,age ≥ 10 years old,white blood cell count(WBC)≥ 50 × 109/L,central nervous system leukemia,minimal residual disease(MRD)≥ 1％during induction therapy,and MRD ≥ 0.01％at the end of induction in T-ALL children were significantly higher than those in B-ALL children(P＜0.05).The expected 10-year EFS and OS of T-ALL were 59.7％and 66.0％,respectively,which were significantly lower than those of B-ALL(P＜0.001).COX analysis showed that WBC ≥ 100 x 109/L at initial diagnosis and failure to achieve complete remission(CR)after induction were independent risk factors for poor prognosis.Compared with CCLG-ALL 2008 group,CCCG-ALL 2015 group had lower incidence of infection-related SAE(15.8％vs 34.6％,P=0.042),but higher EFS and OS(73.9％vs 57.2％,PEFS=0.090;86.5％vs 62.3％,PoS=0.023).Conclusions:The prognosis of children with T-ALL is worse than children with B-ALL.WBC ≥ 100 × 109/L at initial diagnosis and non-CR after induction(especially mediastinal mass has not disappeared)are the risk factors for poor prognosis.CCCG-ALL 2015 regimen may reduce infection-related SAE and improve efficacy.